Search results for: existing reinforced concrete columns

Authors: John Zanetich

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Designing an educational activity that encourages inquiry and collaboration is key to engaging students in meaningful learning. Educational Information and Communications Technology (EICT) plays an important role in facilitating cooperative and collaborative learning in the classroom. The EICT also facilitates students’ learning and development of the critical thinking skills needed to solve real world problems. Projects and activities based on constructivism encourage students to embrace complexity as well as find relevance and joy in their learning. It also enhances the students’ capacity for creative and responsible real-world problem solving. Classroom activities based on constructivism offer students an opportunity to develop the higher–order-thinking skills of defining problems and identifying solutions. Participating in a classroom project is an activity for both acquiring experiential knowledge and applying new knowledge to practical situations. It also provides an opportunity for students to integrate new knowledge into a skill set using reflection. Classroom projects can be developed around a variety of learning objects including social media, knowledge management and learning communities. The construction of meaning through project-based learning is an approach that encourages interaction and problem-solving activities. Projects require active participation, collaboration and interaction to reach the agreed upon outcomes. Projects also serve to externalize the invisible cognitive and social processes taking place in the activity itself and in the student experience. This paper describes a classroom project designed to elicit interactions by helping students to unfreeze existing knowledge, to create new learning experiences, and then refreeze the new knowledge. Since constructivists believe that students construct their own meaning through active engagement and participation as well as interactions with others. knowledge management can be used to guide the exchange of both tacit and explicit knowledge in interpersonal interactions between students and guide the construction of meaning. This paper uses an action research approach to the development of a classroom project and describes the use of technology, social media and the active use of tacit knowledge in the college classroom. In this project, a closed group Facebook page becomes the virtual classroom where interaction is captured and measured using engagement analytics. In the virtual learning community, the principles of knowledge management are used to identify the process and components of the infrastructure of the learning process. The project identifies class member interests and measures student engagement in a learning community by analyzing regular posting on the Facebook page. These posts are used to foster and encourage interactions, reflect a student’s interest and serve as reaction points from which viewers of the post convert the explicit information in the post to implicit knowledge. The data was collected over an academic year and was provided, in part, by the Google analytic reports on Facebook and self-reports of posts by members. The results support the use of active tacit knowledge activities, knowledge management and social media to enhance the student learning experience and help create the knowledge that will be used by students to construct meaning.

Keywords: constructivism, knowledge management, tacit knowledge, social media

Procedia PDF Downloads 195

Authors: Caroline Atef Shoukry Tadros

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Massive Urbanization growth threatens the sustainability of cities and the quality of city life. This raised the need for an alternate model of sustainability, so we need to plan the future cities in a smarter way with smarter mobility. Smart Mobility planning applications are solutions that use digital technologies and infrastructure advances to improve the efficiency, sustainability, and inclusiveness of urban transportation systems. They can contribute to meeting the needs of Urbanization growth by addressing the challenges of traffic congestion, pollution, accessibility, and safety in cities. Some example of a Smart Mobility planning application are Mobility-as-a-service: This is a service that integrates different transport modes, such as public transport, shared mobility, and active mobility, into a single platform that allows users to plan, book, and pay for their trips. This can reduce the reliance on private cars, optimize the use of existing infrastructure, and provide more choices and convenience for travelers. MaaS Global is a company that offers mobility-as-a-service solutions in several cities around the world. Traffic flow optimization: This is a solution that uses data analytics, artificial intelligence, and sensors to monitor and manage traffic conditions in real-time. This can reduce congestion, emissions, and travel time, as well as improve road safety and user satisfaction. Waycare is a platform that leverages data from various sources, such as connected vehicles, mobile applications, and road cameras, to provide traffic management agencies with insights and recommendations to optimize traffic flow. Logistics optimization: This is a solution that uses smart algorithms, blockchain, and IoT to improve the efficiency and transparency of the delivery of goods and services in urban areas. This can reduce the costs, emissions, and delays associated with logistics, as well as enhance the customer experience and trust. ShipChain is a blockchain-based platform that connects shippers, carriers, and customers and provides end-to-end visibility and traceability of the shipments. Autonomous vehicles: This is a solution that uses advanced sensors, software, and communication systems to enable vehicles to operate without human intervention. This can improve the safety, accessibility, and productivity of transportation, as well as reduce the need for parking space and infrastructure maintenance. Waymo is a company that develops and operates autonomous vehicles for various purposes, such as ride-hailing, delivery, and trucking. These are some of the ways that Smart Mobility planning applications can contribute to meeting the needs of the Urbanization growth. However, there are also various opportunities and challenges related to the implementation and adoption of these solutions, such as the regulatory, ethical, social, and technical aspects. Therefore, it is important to consider the specific context and needs of each city and its stakeholders when designing and deploying Smart Mobility planning applications.

Keywords: smart mobility planning, smart mobility applications, smart mobility techniques, smart mobility tools, smart transportation, smart cities, urbanization growth, future smart cities, intelligent cities, ICT information and communications technologies, IoT internet of things, sensors, lidar, digital twin, ai artificial intelligence, AR augmented reality, VR virtual reality, robotics, cps cyber physical systems, citizens design science

Procedia PDF Downloads 47

Authors: Lise Paesen, Marielle Leijten

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People diagnosed with probable Alzheimer disease suffer from an impairment of their language capacities; a gradual impairment which affects both their spoken and written communication. Our study aims at characterising the language decline in DAT patients with the use of congeneric elicited writing tasks. Within these tasks, a descriptive text has to be written based upon images with which the participants are confronted. A randomised set of images allows us to present the participants with a different task on every encounter, thus allowing us to avoid a recognition effect in this iterative study. This method is a revision from previous studies, in which participants were presented with a larger picture depicting an entire scene. In order to create the randomised set of images, existing pictures were adapted following strict criteria (e.g. frequency, AoA, colour, ...). The resulting data set contained 50 images, belonging to several categories (vehicles, animals, humans, and objects). A pre-test was constructed to validate the created picture set; most images had been used before in spoken picture naming tasks. Hence the same reaction times ought to be triggered in the typed picture naming task. Once validated, the effectiveness of the descriptive tasks was assessed. First, the participants (n=60 students, n=40 healthy elderly) performed a typing task, which provided information about the typing speed of each individual. Secondly, two descriptive writing tasks were carried out, one simple and one complex. The simple task contains 4 images (1 animal, 2 objects, 1 vehicle) and only contains elements with high frequency, a young AoA (<6 years), and fast reaction times. Slow reaction times, a later AoA (≥ 6 years) and low frequency were criteria for the complex task. This task uses 6 images (2 animals, 1 human, 2 objects and 1 vehicle). The data were collected with the keystroke logging programme Inputlog. Keystroke logging tools log and time stamp keystroke activity to reconstruct and describe text production processes. The data were analysed using a selection of writing process and product variables, such as general writing process measures, detailed pause analysis, linguistic analysis, and text length. As a covariate, the intrapersonal interkey transition times from the typing task were taken into account. The pre-test indicated that the new images lead to similar or even faster reaction times compared to the original images. All the images were therefore used in the main study. The produced texts of the description tasks were significantly longer compared to previous studies, providing sufficient text and process data for analyses. Preliminary analysis shows that the amount of words produced differed significantly between the healthy elderly and the students, as did the mean length of production bursts, even though both groups needed the same time to produce their texts. However, the elderly took significantly more time to produce the complex task than the simple task. Nevertheless, the amount of words per minute remained comparable between simple and complex. The pauses within and before words varied, even when taking personal typing abilities (obtained by the typing task) into account.

Keywords: Alzheimer's disease, experimental design, language decline, writing process

Procedia PDF Downloads 252

Authors: Dmitriy Chernov, Maria Karavassilis, Suhyoun Youn, Amna Izhar, Devasenan Devendra

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Introduction and Background: A well-structured and comprehensive departmental induction improves patient safety and job satisfaction amongst doctors. The aims of our Project were as follows: 1. Assess the perceived preparedness of junior doctors starting their rotation in Acute Medicine at Watford General Hospital. 2. Develop a supplemental Induction Guide and Pocket reference in the form of an iOS mobile application. 3. To collect feedback after implementing the mobile application following a trial period of 8 weeks with a small cohort of junior doctors. Materials and Methods: A questionnaire was distributed to all new junior trainees starting in the department of Acute Medicine to assess their experience of current induction. A mobile Induction application was developed and trialled over a period of 8 weeks, distributed in addition to the existing didactic induction session. After the trial period, the same questionnaire was distributed to assess improvement in induction experience. Analytics data were collected with users’ consent to gauge user engagement and identify areas of improvement of the application. A feedback survey about the app was also distributed. Results: A total of 32 doctors used the application during the 8-week trial period. The application was accessed 7259 times in total, with the average user spending a cumulative of 37 minutes 22 seconds on the app. The most used section was Clinical Guidelines, accessed 1490 times. The App Feedback survey revealed positive reviews: 100% of participants (n=15/15) responded that the app improved their overall induction experience compared to other placements; 93% (n=14/15) responded that the app improved overall efficiency in completing daily ward jobs compared to previous rotations; and 93% (n=14/15) responded that the app improved patient safety overall. In the Pre-App and Post-App Induction Surveys, participants reported: a 48% improvement in awareness of practical aspects of the job; a 26% improvement of awareness on locating pathways and clinical guidelines; a 40% reduction of feelings of overwhelmingness. Conclusions and recommendations: This study demonstrates the importance of technology in Medical Education and Clinical Induction. The mobile application average engagement time equates to over 20 cumulative hours of on-the-job training delivered to each user, within an 8-week period. The most used and referred to section was clinical guidelines. This shows that there is high demand for an accessible pocket guide for this type of material. This simple mobile application resulted in a significant improvement in feedback about induction in our Department of Acute Medicine, and will likely impact workplace satisfaction. Limitations of the application include: post-app surveys had a small number of participants; the app is currently only available for iPhone users; some useful sections are nested deep within the app, lacks deep search functionality across all sections; lacks real time user feedback; and requires regular review and updates. Future steps for the app include: developing a web app, with an admin dashboard to simplify uploading and editing content; a comprehensive search functionality; and a user feedback and peer ratings system.

Keywords: mobile app, doctor induction, medical education, acute medicine

Procedia PDF Downloads 63

Authors: Rajkumar Ghosh

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Water scarcity is a pressing issue in urban areas, even in smart cities where efficient resource management is a priority. This scarcity is mainly caused by factors such as lifestyle changes, excessive groundwater extraction, over-usage of water, rapid urbanization, and uncontrolled population growth. In the specific case of Gomti Nagar, Lucknow, Uttar Pradesh, India, the depletion of groundwater resources is particularly severe, leading to a water imbalance and posing a significant challenge for the region's sustainable development. The aim of this study is to address the water shortage in the Gomti Nagar region by focusing on the implementation of artificial groundwater recharge methods. Specifically, the research aims to investigate the effectiveness of rainwater collection through rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to reduce aquifer depletion and bridge the gap between groundwater recharge and extraction. The research methodology for this study involves the utilization of RTRWHs as the main method for collecting rainwater. This approach is considered effective in managing and conserving water resources in a sustainable manner. The focus is on implementing RTRWHs in residential and commercial buildings to maximize the collection of rainwater and its subsequent utilization for various purposes in the Gomti Nagar region. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage (0.04%) of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance of 24519 ML/yr in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. The findings of this study can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis. The data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. Statistical analysis and modelling techniques were employed to quantify the water imbalance and evaluate the effectiveness of RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. The study highlights the need for widespread adoption of RTRWHs in all buildings and emphasizes the importance of integrating such systems into the urban planning and development process. By doing so, smart cities like Gomti Nagar can achieve efficient water management, ensuring a better future with improved water availability for its residents.

Keywords: rooftop rainwater harvesting, rainwater, water management, aquifer

Procedia PDF Downloads 61

Authors: Naghmeh M. Bandari, Javad Dargahi, Muthukumaran Packirisamy

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Robot-assisted minimally invasive surgery (RMIS) has been widely performed around the world during the last two decades. RMIS demonstrates significant advantages over conventional surgery, e.g., improving the accuracy and dexterity of a surgeon, providing 3D vision, motion scaling, hand-eye coordination, decreasing tremor, and reducing x-ray exposure for surgeons. Despite benefits, surgeons cannot touch the surgical site and perceive tactile information. This happens due to the remote control of robots. The literature survey identified the lack of force feedback as the riskiest limitation in the existing technology. Without the perception of tool-tissue contact force, the surgeon might apply an excessive force causing tissue laceration or insufficient force causing tissue slippage. The primary use of force sensors has been to measure the tool-tissue interaction force in real-time in-situ. Design of a tactile sensor is subjected to a set of design requirements, e.g., biocompatibility, electrical-passivity, MRI-compatibility, miniaturization, ability to measure static and dynamic force. In this study, a planar optical fiber-based sensor was proposed to mount at the surgical grasper. It was developed based on the light intensity modulation principle. The deflectable part of the sensor was a beam modeled as a cantilever Euler-Bernoulli beam on rigid substrates. A semi-cylindrical indenter was attached to the bottom surface the beam at the mid-span. An optical fiber was secured at both ends on the same rigid substrates. The indenter was in contact with the fiber. External force on the sensor caused deflection in the beam and optical fiber simultaneously. The micro-bending of the optical fiber would consequently result in light power loss. The sensor was simulated and studied using finite element methods. A laser light beam with 800nm wavelength and 5mW power was used as the input to the optical fiber. The output power was measured using a photodetector. The voltage from photodetector was calibrated to the external force for a chirp input (0.1-5Hz). The range, resolution, and hysteresis of the sensor were studied under monotonic and harmonic external forces of 0-2.0N with 0 and 5Hz, respectively. The results confirmed the validity of proposed sensing principle. Also, the sensor demonstrated an acceptable linearity (R2 > 0.9). A minimum external force was observed below which no power loss was detectable. It is postulated that this phenomenon is attributed to the critical angle of the optical fiber to observe total internal reflection. The experimental results were of negligible hysteresis (R2 > 0.9) and in fair agreement with the simulations. In conclusion, the suggested planar sensor is assessed to be a cost-effective solution, feasible, and easy to use the sensor for being miniaturized and integrated at the tip of robotic graspers. Geometrical and optical factors affecting the minimum sensible force and the working range of the sensor should be studied and optimized. This design is intrinsically scalable and meets all the design requirements. Therefore, it has a significant potential of industrialization and mass production.

Keywords: force sensor, minimally invasive surgery, optical sensor, robotic surgery, tactile sensor

Procedia PDF Downloads 192

Authors: Jessica Kate Simonds

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The last successful hijacking perpetrated by Somali pirates in 2012 represented a critical turning point for the identity and brand of Indian Ocean (IO) insecurity, coined in this paper as the era of the post-piratical. This paper explores the broadening of the PMSC business model to account and contribute to the design of a new IO security environment that prioritises foreign and insurgency drone activity and Houthi rebel operations as the main threat to merchant shipping in the post-2012 era. This study is situated within a longer history of analysing maritime insecurity and also contributes a bespoke conceptual framework that understands the sea as a space that is produced and reproduced relative to existing and emerging threats to merchant shipping based on bespoke models of information sharing and intelligence acquisition. This paper also makes a prominent empirical contribution by drawing on a post-positivist methodology, data drawn from original semi-structured interviews with senior maritime insurers and active merchant seafarers that is triangulated with industry-produced guidance such as the BMP series as primary data sources. Each set is analysed through qualitative discourse and content analysis and supported by the quantitative data sets provided by the IMB Piracy Reporting center and intelligence networks. This analysis reveals that mechanisms such as the IGP&I Maritime Security Committee and intelligence divisions of PMSC’s have driven the exchanges of knowledge between land and sea and thus the reproduction of the maritime security environment through new regulations and guidance to account dones, rebels and bombs as the key challenges in the IO, beyond piracy. A contribution of this paper is the argument that experts who may not be in the highest-profile jobs are the architects of maritime insecurity based on their detailed knowledge and connections to vessels in transit. This paper shares the original insights of those who have served in critical decision making spaces to demonstrate that the development and refinement of industry produced deterrence guidance that has been accredited to the mitigation of piracy, have shaped new editions such as BMP 5 that now serve to frame a new security environment that prioritises the mitigation of risks from drones and WBEID’s from both state and insurgency risk groups. By highlighting the experiences and perspectives of key players on both land and at sea, the key finding of this paper is outlining that as pirates experienced a financial boom by profiteering from their bespoke business model during the peak of successful hijackings, the private security market encountered a similar level of financial success and guaranteed risk environment in which to prospect business. Thus, the reproduction of the Indian Ocean as a maritime security environment reflects a new found purpose for PMSC’s as part of the broader conglomerate of maritime insurers, regulators, shipowners and managers who continue to redirect the security consciousness and IO brand of insecurity.

Keywords: maritime security, private security, risk intelligence, political geography, international relations, political economy, maritime law, security studies

Procedia PDF Downloads 158

Authors: Andrea Bertocchi, Alessio Barnaba Di Fonzo, Davide Talarico, Simone Rivaroli, Jeff Konin

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The patient is a 89 years old male (180cm/85kg) retired notary former golfer with no past medical history. He describes a progressive ideomotor slowdown for 14 months. The disorder is characterized by short-term memory deficits and, for some months, also by unstable walking with a broad base with skidding and risk of falling at directional changes and urinary urgency. There were also episodes of aggression towards his wife and staff. At the time, the patient takes no prescribed medications. He has difficulty eating, dressing, and some problems with personal hygiene. In the initial visit, the patient was alert, cooperating, and performed simple tasks; however, he has a hearing impairment, slowed spontaneous speech, and amnestic deficit to the short story. Ideomotor apraxia is not present. He scored 20 points in the MMSE. From a motor function, he has deficits using Medical Research Council (MRC) 3-/5 in bilateral lower limbs and requires maximum assistance from sit to stand with existing premature fatigue. He’s unable to walk for about 1 month. Tremors and hypertonia are absent. BERG was unable to be administered, and BARTHEL was obtained 45/100. An Amyloid Angiopathy is suspected and then confirmed at the neurological examination. Therehabilitation objectives were the recovery of mobility and reinforcement of the UE/LE, especially legs, for recovery of standing and walking. The cognitive aspect was also an essential factor for the patient's recovery. The literature doesn’t demonstrate any particular studies regarding motor and cognitive rehabilitation on this pathology. Failing to manage his attention on exercise and tending to be disinterested and falling asleep constantly, we used golf-specific gestures to stimulate his mind to work and get results because the patient has memory recall of golf related movement. We worked for 4 months with a frequency of 3 sessions per week. Every session lasted for 45 minutes. After 4 months of work, the patient walked independently with the use of a stick for about 120 meters without stopping. MRC 4/5 AI bilaterally andpostural steps performed independently with supervision. BERG 36/56. BARTHEL 65/100. 6 Minutes Walking Test (6MWT), at the beginning, it wasn’t measurable, now, he performs 151,5m with Numeric Rating Scale 4 at the beginning and 7 at the end. Cognitively, he no longer has episodes of aggression, although the short-term memory and concentration deficit remains. Amyloid Angiopathy is a mix of motor and cognitive disorder. It is worth the thought that cerebral amyloid angiopathy manifests with functional deficits due to strokes and bleedings and, as such, has an important rehabilitation indication, as classical stroke is not associated with amyloidosis. Exploring the motor patterns learned at a young age and remained in the implicit and explicit memory of the patient allowed us to set up effective work and to obtain significant results in the short-middle term. Surely many studies will still be done regarding this pathology and its rehabilitation, but the importance of the cognitive sphere applied to the motor sphere could represent an important starting point.

Keywords: amyloid angiopathy, cognitive rehabilitation, golf, motor disorder

Procedia PDF Downloads 95

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

Procedia PDF Downloads 31

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 45

Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, a new set of metrics and measurement system is needed to better quantify the environmental, social and economic impacts of circular zero-waste design. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. Lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. In particular, the forestry-based plants which have been an invaluable outlet for woody biomass surplus, forest health improvement, timber production enhancement, and especially reduction of wildfire risk. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. It proposes not only models for integration of forestry, aquaculture, and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. Typically, life cycle analyses measure environmental impacts of different industrial production stages and are not integrated with indicators of material use circularity. This concept paper proposes the further development of a new set of metrics that would illustrate not only the typical life-cycle analysis (LCA), which shows the reduction in greenhouse gas (GHG) emissions, but also the zero-waste circularity measures of mass balance of the full value chain of the raw material and energy content/caloric value. These new measures quantify key impacts in making hyper-efficient use of natural resources and eliminating waste to landfills. The project utilized traditional LCA using the GREET model where the standalone biomass energy plant case was contrasted with the integration of a jet-fuel biorefinery. The methodology was then expanded to include combinations of co-hosts that optimize the life cycle of woody biomass from tree to energy, CO₂, heat and wood ash both from an energy/caloric value and for mass balance to include reuse of waste streams which are typically landfilled. The major findings of both a formal LCA study resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. If proven as a model, the expedited roll-out of these innovative scenarios can set a new standard for circular zero-waste projects that advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable bio-economy paradigm where waste streams become valuable inputs, supporting local and rural communities in simple, sustainable ways.

Keywords: bio-economy, biomass energy, financing, metrics

Procedia PDF Downloads 135

Authors: Irum Naz

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In the Arabian higher education context, linguistic proficiency in the English language is considered crucial for the developmental sustainability, economic growth, and stability of communities and societies. Qatar’s educational reforms package, through the 2030 vision, identifies the acquisition of English at K-12 as an essential survival communication tool for globalization, believing that Qatari students need better preparation to take on the responsibilities of leadership and to participate effectively in the country’s surging economy. The idea of introducing Qatari students to modern curricula benchmarked to high-student-performance curricula in developed countries is one of the components of reformatory design principles of Education for New Era reform project that is mutually consented to and supported by the Office of Shared Services, Communications Office, and Supreme Education Council. In appreciation of the government’s vision, the English Language Centre (ELC) at the Community College of Qatar ran an internal educational audit and conducted evaluative research to understand and appraise the value, impact, and practicality of the existing ELC language development program. This study sought to identify the type of change that could identify and improve the quality of Foundation Program courses and the manners in which second language learners could be assisted to transit smoothly between (ELC) levels. Following the interpretivist paradigm and mixed research method, the data was gathered through a bicyclic research model and a triangular design. The analyses of the data suggested that there was a need for improvement in the ELC program as a whole, and particularly in terms of curriculum, student learning outcomes, and the general learning environment in the department. Key findings suggest that the target program would benefit from significant revisions, which would include narrowing the focus of the courses, providing sets of specific learning objectives, and preventing repetition between levels. Another promising finding was about the assessment tools and process. The data suggested that a set of standardized assessments that more closely suited the programs of study should be devised. It was also recommended that students undergo a more comprehensive placement process to ensure that they begin the program at an appropriate level and get the maximum benefit from their learning experience. Although this ties into the idea of curriculum revamp, it was expected that students could leave the ELC having had exposure to courses in English for specific purposes. The idea of a more reliable exit assessment for students was raised frequently so ELC could regulate itself and ensure optimum learning outcomes. Another important recommendation was the provision of a Student Learning Center for students that would help them to receive personalized tuition, differentiated instruction, and self-driven and self-evaluated learning experience. In addition, an extra study level was recommended to be added to the program to accommodate the different levels of English language proficiency represented among ELC students. The evidence collected in the course of conducting the study suggests that significant change is needed in the structure of the ELC program, specifically about curriculum, the program learning outcomes, and the learning environment in general.

Keywords: educational audit, ESL, optimum learning outcomes, Qatar’s educational reforms, self-driven and self-evaluated learning experience, Student Learning Center

Procedia PDF Downloads 153

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Rijnbout-St.James Willem, Lindner Volkhard, Scholand Mary Beth, Ashton M. Tillett, Di Gennaro Michael Jude, Smith Silvia Enrica

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Introduction: Fibrosing lung diseases are characterized by changes in the lung interstitium and are classified based on etiology: 1) environmental/exposure-related, 2) autoimmune-related, 3) sarcoidosis, 4) interstitial pneumonia, and 4) idiopathic. Among interstitial lung diseases (ILD) idiopathic forms, idiopathic pulmonary fibrosis (IPF) is the most severe. Pathogenesis of IPF is characterized by an increased presence of proinflammatory mediators, resulting in alveolar injury, where injury to alveolar epithelium precipitates an increase in collagen deposition, subsequently thickening the alveolar septum and decreasing gas exchange. Identifying biomarkers implicated in the pathogenesis of lung fibrosis is key to developing new therapies and improving the efficacy of existing therapies. The transforming growth factor-beta (TGF-B1), a mediator of tissue repair associated with WNT5A signaling, is partially responsible for fibroblast proliferation in ILD and is the target of Pirfenidone, one of the antifibrotic therapies used for patients with IPF. Canonical TGF-B signaling is mediated by the proteins SMAD 2/3, which are, in turn, indirectly regulated by Collagen Triple Helix Repeat Containing 1 (CTHRC1). In this study, we tested the following hypotheses: 1) CTHRC1 is more elevated in the ILD cohort compared to unaffected controls, and 2) CTHRC1 is differently expressed among ILD types. Material and Methods: CTHRC1 levels were measured by ELISA in 171 plasma samples from the deidentified University of Utah ILD cohort. Data represent a cohort of 131 ILD-affected participants and 40 unaffected controls. CTHRC1 samples were categorized by a pulmonologist based on affectation status and disease subtypes: IPF (n = 45), sarcoidosis (4), nonspecific interstitial pneumonia (16), hypersensitivity pneumonitis (n = 7), interstitial pneumonia (n=13), autoimmune (n = 15), other ILD - a category that includes undifferentiated ILD diagnoses (n = 31), and unaffected controls (n = 40). We conducted a single-factor ANOVA of plasma CTHRC1 levels to test whether CTHRC1 variance among affected and non-affected participants is statistically significantly different. In-silico analysis was performed with Ingenuity Pathway Analysis® to characterize the role of CTHRC1 in the pathway of lung fibrosis. Results: Statistical analyses of CTHRC1 in plasma samples indicate that the average CTHRC1 level is significantly higher in ILD-affected participants than controls, with the autoimmune ILD being higher than other ILD types, thus supporting our hypotheses. In-silico analyses show that CTHRC1 indirectly activates and phosphorylates SMAD3, which in turn cross-regulates TGF-B1. CTHRC1 also may regulate the expression and transcription of TGFB-1 via WNT5A and its regulatory relationship with CTNNB1. Conclusion: In-silico pathway analyses demonstrate that CTHRC1 may be an important biomarker in ILD. Analysis of plasma samples indicates that CTHRC1 expression is positively associated with ILD affectation, with autoimmune ILD having the highest average CTHRC1 values. While characterizing CTHRC1 levels in plasma can help to differentiate among ILD types and predict response to Pirfenidone, the extent to which plasma CTHRC1 level is a function of ILD severity or chronicity is unknown.

Keywords: interstitial lung disease, CTHRC1, idiopathic pulmonary fibrosis, pathway analyses

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Authors: Md Shafiqul Bari, Md Shafiqul Islam Sikdar

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This paper summarizes the current knowledge on Agroforestry practices in the Barind tract of Bangladesh. The part of greater Rajshahi, Dinajpur, Rangpur and Bogra district of Bangladesh is geographically identified as the Barind tract. The hard red soil of these areas is very significant in comparison to that of the other parts of the country. A typical dry climate with comparatively high temperature prevails in the Barind area. Scanty rainfall and excessive extraction of groundwater have created an alarming situation among the Barind people and others about irrigation to the rice field. In addition, the situation may cause an adverse impact on the people whose livelihood largely depends on agriculture. The groundwater table has been declined by at least 10 to 15 meters in some areas of the Barind tract during the last 20 years. Due to absent of forestland in the Barind tract, the soil organic carbon content can decrease more rapidly because of the higher rate of decomposition. The Barind soils are largely carbon depleted but can be brought back to carbon-carrying capacity by bringing under suitable Agroforestry systems. Agroforestry has tremendous potential for carbon sequestration not only in above C biomass but also root C biomass in deeper soil depths. Agroforestry systems habitually conserve soil organic carbon and maintain a great natural nutrient pool. Cultivation of trees with arable crops under Agroforestry systems help in improving soil organic carbon content and sequestration carbon, particularly in the highly degraded Barind lands. Agroforestry systems are a way of securing the growth of cash crops that may constitute an alternative source of income in moments of crisis. Besides being a source of fuel wood, a greater presence of trees in cropping system contributes to decreasing temperatures and to increasing rainfall, thus contrasting the negative environmental impact of climate changes. In order to fulfill the objectives of this study, two experiments were conducted. The first experiment was survey on the impact of existing agroforestry system on the livelihood security in the Barind tract of Bangladesh and the second one was the role of agroforestry system on the improvement of soil properties in a multilayered coconut orchard. Agroforestry systems have been generated a lot of employment opportunities in the Barind area. More crops mean involvement of more people in various activities like involvements in dairying, sericulture, apiculture and additional associated agro-based interventions. Successful adoption of Agroforestry practices in the Barind area has shown that the Agroforestry practitioners of this area were very sound positioned economically, and had added social status too. However, from the findings of the present study, it may be concluded that the majority rural farmers of the Barind tract of Bangladesh had a very good knowledge and medium extension contact related to agroforestry production system. It was also observed that 85 per cent farmers followed agroforestry production system and received benefits to a higher extent. Again, from the research study on orchard based mutistoried agroforestry cropping system, it was evident that there was an important effect of agroforestry cropping systems on the improvement of soil chemical properties. As a result, the agroforestry systems may be helpful to attain the development objectives and preserve the biosphere core.

Keywords: agroforestry systems, Barind tract, carbon sequestration, climate changes

Procedia PDF Downloads 180

Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

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Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

Procedia PDF Downloads 153

Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

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Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

Procedia PDF Downloads 42

Authors: Linda Fellag, Arlene Caney

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E-learning has earned an essential place in academia because it promotes learner autonomy, student engagement, and technological aptitude, and allows for flexible learning. However, despite advantages, educators have been slower to embrace e-learning for ESL and other non-traditional students for fear that such students will not succeed without the direct faculty contact and academic support of face-to-face classrooms. This study aims to determine if a non-traditional student-friendly online course can produce student retention and performance rates that compare favorably with those of students in standard online sections of the same course aimed at traditional college-level students. One Music faculty member is currently collaborating with an English instructor to redesign an online college-level Music Appreciation course for non-traditional college students. At Community College of Philadelphia, Introduction to Music Appreciation was recently designated as one of the few college-level courses that advanced ESL, and developmental English students can take while completing their language studies. Beginning in Fall 2017, the course will be critical for international students who must maintain full-time student status under visa requirements. In its current online format, however, Music Appreciation is designed for traditional college students, and faculty who teach these sections have been reluctant to revise the course to address the needs of non-traditional students. Interestingly, presenters maintain that the online platform is the ideal place to develop language and college readiness skills in at-risk students while maintaining the course's curricular integrity. The two faculty presenters describe how curriculum rather than technology drives the redesign of the digitized music course, and self-study materials, guided assignments, and periodic assessments promote independent learning and comprehension of material. The 'scaffolded' modules allow ESL and developmental English students to build on prior knowledge, preview key vocabulary, discuss content, and complete graded tasks that demonstrate comprehension. Activities and assignments, in turn, enhance college success by allowing students to practice academic reading strategies, writing, speaking, and student-faculty and peer-peer communication and collaboration. The course components facilitate a comparison of student performance and retention in sections of the redesigned and existing online sections of Music Appreciation as well as in previous sections with at-risk students. Indirect, qualitative measures include student attitudinal surveys and evaluations. Direct, quantitative measures include withdrawal rates, tests of disciplinary knowledge, and final grades. The study will compare the outcomes of three cohorts in the two versions of the online course: ESL students, at-risk developmental students, and college-level students. These data will also be compared with retention and student outcomes data of the three cohorts in f2f Music Appreciation, which permitted non-traditional student enrollment from 1998-2005. During this eight-year period, the presenter addressed the problems of at-risk students by adding language and college success support, which resulted in strong retention and outcomes. The presenters contend that the redesigned course will produce favorable outcomes among all three cohorts because it contains components which proved successful with at-risk learners in f2f sections of the course. Results of their study will be published in 2019 after the redesigned online course has met for two semesters.

Keywords: college readiness, e-learning, music appreciation, online courses

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Authors: Leah Li Echiverri, Haoyu Shang, Yue Li

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Wenzhou-Kean University (WKU) is a Sino-US Cooperative University in China. It practices the English Immersion Program (EIP), where all the courses are taught in English. Class discussions and presentations are pervasively interwoven in designing students’ learning experiences. This WKU model has brought positive influences on students and is in some way ahead of traditional college English majors. However, literature to support the perceptions on the positive outcomes of this teaching and learning model remain scarce. The distinctive profile of Chinese-ESL students in an English Medium of Instruction (EMI) environment contributes further to the scarcity of literature compared to existing studies conducted among ESL learners in Western educational settings. Hence, the study investigated the students’ perceptions towards the English Immersion Program and determine how it influences Chinese-ESL students’ academic performance (AP). This research can provide empirical data that would be helpful to educators, teaching practitioners, university administrators, and other researchers in making informed decisions when developing curricular reforms, instructional and pedagogical methods, and university-wide support programs using this educational model. The purpose of the study was to establish the relationship between the English Immersion Program and Academic Performance among Chinese-ESL students enrolled at WKU for the academic year 2020-2021. Course length, immersion location, course type, and instructional design were the constructs of the English immersion program. English language learning, learning efficiency, and class participation were used to measure academic performance. Descriptive-correlational design was used in this cross-sectional research project. A quantitative approach for data analysis was applied to determine the relationship between the English immersion program and Chinese-ESL students’ academic performance. The research was conducted at WKU; a Chinese-American jointly established higher educational institution located in Wenzhou, Zhejiang province. Convenience, random, and snowball sampling of 283 students, a response rate of 10.5%, were applied to represent the WKU student population. The questionnaire was posted through the survey website named Wenjuanxing and shared to QQ or WeChat. Cronbach’s alpha was used to test the reliability of the research instrument. Findings revealed that when professors integrate technology (PowerPoint, videos, and audios) in teaching, students pay more attention. This contributes to the acquisition of more professional knowledge in their major courses. As to course immersion, students perceive WKU as a good place to study, providing them a high degree of confidence to talk with their professors in English. This also contributes to their English fluency and better pronunciation in their communication. In the construct of designing instruction, the use of pictures, video clips, and professors’ non-verbal communication, and demonstration of concern for students encouraged students to be more active in-class participation. Findings on course length and academic performance indicated that students’ perception regarding taking courses during fall and spring terms can moderately contribute to their academic performance. In conclusion, the findings revealed a significantly strong positive relationship between course type, immersion location, instructional design, and academic performance.

Keywords: class participation, English immersion program, English language learning, learning efficiency

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Authors: O. Zlatkin-Troitschanskaia, J. Fischer, C. Lautenbach, H. A. Pant

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In 21st century higher education (HE), the diversity among students has increased in recent years due to the internationalization and higher mobility. Offering and providing equal and fair opportunities based on students’ individual skills and abilities instead of their social or cultural background is one of the major aims of HE. In this context, valid, objective and transparent assessments of students’ preconditions and academic competencies in HE are required. However, as analyses of the current states of research and practice show, a substantial research gap on assessment practices in HE still exists, calling for the development of effective solutions. These demands lead to significant conceptual and methodological challenges. Funded by the German Federal Ministry of Education and Research, the research program 'Modeling and Measuring Competencies in Higher Education – Validation and Methodological Challenges' (KoKoHs) focusses on addressing these challenges in HE assessment practice by modeling and validating objective test instruments. Including 16 cross-university collaborative projects, the German-wide research program contributes to bridging the research gap in current assessment research and practice by concentrating on practical and policy-related challenges of assessment in HE. In this paper, we present a differentiated overview of existing assessments of HE at the national and international level. Based on the state of research, we describe the theoretical and conceptual framework of the KoKoHs Program as well as results of the validation studies, including their key outcomes. More precisely, this includes an insight into more than 40 developed assessments covering a broad range of transparent and objective methods for validly measuring domain-specific and generic knowledge and skills for five major study areas (Economics, Social Science, Teacher Education, Medicine and Psychology). Computer-, video- and simulation-based instruments have been applied and validated to measure over 20,000 students at the beginning, middle and end of their (bachelor and master) studies at more than 300 HE institutions throughout Germany or during their practical training phase, traineeship or occupation. Focussing on the validity of the assessments, all test instruments have been analyzed comprehensively, using a broad range of methods and observing the validity criteria of the Standards for Psychological and Educational Testing developed by the American Educational Research Association, the American Economic Association and the National Council on Measurement. The results of the developed assessments presented in this paper, provide valuable outcomes to predict students’ skills and abilities at the beginning and the end of their studies as well as their learning development and performance. This allows for a differentiated view of the diversity among students. Based on the given research results practical implications and recommendations are formulated. In particular, appropriate and effective learning opportunities for students can be created to support the learning development of students, promote their individual potential and reduce knowledge and skill gaps. Overall, the presented research on competency assessment is highly relevant to national and international HE practice.

Keywords: 21st century skills, academic competencies, innovative assessments, KoKoHs

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Authors: Athina Thanou, Eirini Eleni Tsiropoulou, Symeon Papavassiliou

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The problem of museum visitor experience and congestion management – in various forms - has come increasingly under the spotlight over the last few years, since overcrowding can significantly decrease the quality of visitors’ experience. Evidence suggests that on busy days the amount of time a visitor spends inside a crowded house museum can fall by up to 60% compared to a quiet mid-week day. In this paper we consider the aforementioned problem, by treating museums as evolving social systems that induce constraints. However, in a cultural heritage space, as opposed to the majority of social environments, the momentum of the experience is primarily controlled by the visitor himself. Visitors typically behave selfishly regarding the maximization of their own Quality of Experience (QoE) - commonly expressed through a utility function that takes several parameters into consideration, with crowd density and waiting/visiting time being among the key ones. In such a setting, congestion occurs when either the utility of one visitor decreases due to the behavior of other persons, or when costs of undertaking an activity rise due to the presence of other persons. We initially investigate how visitors’ behavioral risk attitudes, as captured and represented by prospect theory, affect their decisions in resource sharing settings, where visitors’ decisions and experiences are strongly interdependent. Different from the majority of existing studies and literature, we highlight that visitors are not risk neutral utility maximizers, but they demonstrate risk-aware behavior according to their personal risk characteristics. In our work, exhibits are organized into two groups: a) “safe exhibits” that correspond to less congested ones, where the visitors receive guaranteed satisfaction in accordance with the visiting time invested, and b) common pool of resources (CPR) exhibits, which are the most popular exhibits with possibly increased congestion and uncertain outcome in terms of visitor satisfaction. A key difference is that the visitor satisfaction due to CPR strongly depends not only on the invested time decision of a specific visitor, but also on that of the rest of the visitors. In the latter case, the over-investment in time, or equivalently the increased congestion potentially leads to “exhibit failure”, interpreted as the visitors gain no satisfaction from their observation of this exhibit due to high congestion. We present a framework where each visitor in a distributed manner determines his time investment in safe or CPR exhibits to optimize his QoE. Based on this framework, we analyze and evaluate how visitors, acting as prospect-theoretic decision-makers, respond and react to the various pricing policies imposed by the museum curators. Based on detailed evaluation results and experiments, we present interesting observations, regarding the impact of several parameters and characteristics such as visitor heterogeneity and use of alternative pricing policies, on scalability, user satisfaction, museum capacity, resource fragility, and operation point stability. Furthermore, we study and present the effectiveness of alternative pricing mechanisms, when used as implicit tools, to deal with the congestion management problem in the museums, and potentially decrease the exhibit failure probability (fragility), while considering the visitor risk preferences.

Keywords: museum resource and visitor management, congestion management, propsect theory, cyber physical social systems

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Authors: Alexandra Steed

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Alexandra Steed URBAN was commissioned to undertake the South Essex Green and Blue Infrastructure Study (SEGBI) on behalf of the Association of South Essex Local Authorities (ASELA): a partnership of seven neighboring councils within the Thames Estuary. Located on London’s doorstep, the 70,000-hectare region is under extraordinary pressure for regeneration, further development, and economic expansion, yet faces extreme challenges: sea-level rise and inadequate flood defenses, stormwater flooding and threatened infrastructure, loss of internationally important habitats, significant existing community deprivation, and lack of connectivity and access to green space. The brief was to embrace these challenges in the creation of a document that would form a key part of ASELA’s Joint Strategic Framework and feed into local plans and master plans. Thus, helping to tackle climate change, ecological collapse, and social inequity at a regional scale whilst creating a relationship and awareness between urban communities and the surrounding landscapes and nature. The SEGBI project applied a ‘land-based’ methodology, combined with a co-design approach involving numerous stakeholders, to explore how living infrastructure can address these significant issues, reshape future planning and development, and create thriving places for the whole community of life. It comprised three key stages, including Baseline Review; Green and Blue Infrastructure Assessment; and the final Green and Blue Infrastructure Report. The resulting proposals frame an ambitious vision for the delivery of a new regional South Essex Estuary (SEE) Park – 24,000 hectares of protected and connected landscapes. This unified parkland system will drive effective place-shaping and “leveling up” for the most deprived communities while providing large-scale nature recovery and biodiversity net gain. Comprehensive analysis and policy recommendations ensure best practices will be embedded within planning documents and decisions guiding future development. Furthermore, a Natural Capital Account was undertaken as part of the strategy showing the tremendous economic value of the natural assets. This strategy sets a pioneering precedent that demonstrates how the prioritisation of living infrastructure has the capacity to address climate change and ecological collapse, while also supporting sustainable housing, healthier communities, and resilient infrastructures. It was only achievable through a collaborative and cross-boundary approach to strategic planning and growth, with a shared vision of place, and a strong commitment to delivery. With joined-up thinking and a joined-up region, a more impactful plan for South Essex was developed that will lead to numerous environmental, social, and economic benefits across the region, and enhancing the landscape and natural environs on the periphery of one of the largest cities in the world.

Keywords: climate change, green and blue infrastructure, landscape architecture, master planning, regional planning, social equity

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Authors: Tristance Kee

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With an unprecedented increase in elderly population around the world, the severe lack of quality housing and health-and-safety provisions to serve this cohort cannot be ignored any longer. Many elderly citizens, especially singletons, live in unsafe housing conditions with poorly executed planning and design. Some suffer from deteriorating mobility, sight and general alertness and their sub-standard living conditions further hinder their daily existence. This research explains how concepts such as Universal Design and Co-Design operate in a high density city such as Hong Kong, China where innovative design can become an alternative solution where government and the private sector fail to provide quality elderly friendly facilities to promote a sustainable urban development. Unlike other elderly research which focuses more on housing policies, nursing care and theories, this research takes a more progressive approach by providing an in-depth impact assessment on how innovative design can be practical solutions for creating a more sustainable built environment. The research objectives are to: 1) explain the relationship between innovative design for elderly and a healthier and sustainable environment; 2) evaluate the impact of human ergonomics with the use of universal design; and 3) explain how innovation can enhance the sustainability of a city in improving citizen’s sight, sound, walkability and safety within the ageing population. The research adopts both qualitative and quantitative methodologies to examine ways to improve elderly population’s relationship to our built environment. In particular, the research utilizes collected data from questionnaire survey and focus group discussions to obtain inputs from various stakeholders, including designers, operators and managers related to public housing, community facilities and overall urban development. In addition to feedbacks from end-users and stakeholders, a thorough analysis on existing elderly housing facilities and Universal Design provisions are examined to evaluate their adequacy. To echo the theme of this conference on Innovation and Sustainable Development, this research examines the effectiveness of innovative design in a risk-benefit factor assessment. To test the hypothesis that innovation can cater for a sustainable development, the research evaluated the health improvement of a sample size of 150 elderly in a period of eight months. Their health performances, including mobility, speech and memory are monitored and recorded on a regular basis to assess if the use of innovation does trigger impact on improving health and home safety for an elderly cohort. This study was supported by district community centers under the auspices of Home Affairs Bureau to provide respondents for questionnaire survey, a standardized evaluation mechanism, and professional health care staff for evaluating the performance impact. The research findings will be integrated to formulate design solutions such as innovative home products to improve elderly daily experience and safety with a particular focus on the enhancement on sight, sound and mobility safety. Some policy recommendations and architectural planning recommendations related to Universal Design will also be incorporated into the research output for future planning of elderly housing and amenity provisions.

Keywords: elderly population, innovative design, sustainable built environment, universal design

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Authors: Eli Avraham

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The Arab Spring was widely covered in the global media and the number of Western tourists traveling to the area began to fall. The goal of this study was to analyze which media strategies marketers in Middle Eastern countries chose to employ in their attempts to repair the negative image of the area in the wake of the Arab Spring. Several studies were published concerning image-restoration strategies of destinations during crises around the globe; however, these strategies were not part of an overarching theory, conceptual framework or model from the fields of crisis communication and image repair. The conceptual framework used in the current study was the ‘multi-step model for altering place image’, which offers three types of strategies: source, message and audience. Three research questions were used: 1.What public relations crisis techniques and advertising campaign components were used? 2. What media policies and relationships with the international media were adopted by Arab officials? 3. Which marketing initiatives (such as cultural and sports events) were promoted? This study is based on qualitative content analysis of four types of data: 1) advertising components (slogans, visuals and text); (2) press interviews with Middle Eastern officials and marketers; (3) official media policy adopted by government decision-maker (e.g. boycotting or arresting newspeople); and (4) marketing initiatives (e.g. organizing heritage festivals and cultural events). The data was located in three channels from December 2010, when the events started, to September 31, 2013: (1) Internet and video-sharing websites: YouTube and Middle Eastern countries' national tourism board websites; (2) News reports from two international media outlets, The New York Times and Ha’aretz; these are considered quality newspapers that focus on foreign news and tend to criticize institutions; (3) Global tourism news websites: eTurbo news and ‘Cities and countries branding’. Using the ‘multi-step model for altering place image,’ the analysis reveals that Middle Eastern marketers and officials used three kinds of strategies to repair their countries' negative image: 1. Source (cooperation and media relations; complying, threatening and blocking the media; and finding alternatives to the traditional media) 2. Message (ignoring, limiting, narrowing or reducing the scale of the crisis; acknowledging the negative effect of an event’s coverage and assuring a better future; promotion of multiple facets, exhibitions and softening the ‘hard’ image; hosting spotlight sporting and cultural events; spinning liabilities into assets; geographic dissociation from the Middle East region; ridicule the existing stereotype) and 3. Audience (changing the target audience by addressing others; emphasizing similarities and relevance to specific target audience). It appears that dealing with their image problems will continue to be a challenge for officials and marketers of Middle Eastern countries until the region stabilizes and its regional conflicts are resolved.

Keywords: Arab spring, cultural events, image repair, Middle East, tourism marketing

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Authors: Diego Giuseppe Romano, Gianvito Apuleo, Jiri Duda

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Mobility is one of the most important societal needs for amusement, business activities and health. Thus, transport needs are continuously increasing, with the consequent traffic congestion and pollution increase. Aeronautic effort aims at smarter infrastructures use and in introducing greener concepts. A possible solution to address the abovementioned topics is the development of Small Air Transport (SAT) system, able to guarantee operability from today underused airfields in an affordable and green way, helping meanwhile travel time reduction, too. In the framework of Horizon2020, EU (European Union) has funded the Clean Sky 2 SAT TA (Transverse Activity) initiative to address market innovations able to reduce SAT operational cost and environmental impact, ensuring good levels of operational safety. Nowadays, most of the key technologies to improve passenger comfort and to reduce community noise, DOC (Direct Operating Costs) and pilot workload for SAT have reached an intermediate level of maturity TRL (Technology Readiness Level) 3/4. Thus, the key technologies must be developed, validated and integrated on dedicated ground and flying aircraft demonstrators to reach higher TRL levels (5/6). Particularly, SAT TA focuses on the integration at aircraft level of the following technologies [1]: 1)    Low-cost composite wing box and engine nacelle using OoA (Out of Autoclave) technology, LRI (Liquid Resin Infusion) and advance automation process. 2) Innovative high lift devices, allowing aircraft operations from short airfields (< 800 m). 3) Affordable small aircraft manufacturing of metallic fuselage using FSW (Friction Stir Welding) and LMD (Laser Metal Deposition). 4)       Affordable fly-by-wire architecture for small aircraft (CS23 certification rules). 5) More electric systems replacing pneumatic and hydraulic systems (high voltage EPGDS -Electrical Power Generation and Distribution System-, hybrid de-ice system, landing gear and brakes). 6) Advanced avionics for small aircraft, reducing pilot workload. 7) Advanced cabin comfort with new interiors materials and more comfortable seats. 8) New generation of turboprop engine with reduced fuel consumption, emissions, noise and maintenance costs for 19 seats aircraft. (9) Alternative diesel engine for 9 seats commuter aircraft. To address abovementioned market innovations, two different platforms have been designed: Reference and Green aircraft. Reference aircraft is a virtual aircraft designed considering 2014 technologies with an existing engine assuring requested take-off power; Green aircraft is designed integrating the technologies addressed in Clean Sky 2. Preliminary integration of the proposed technologies shows an encouraging reduction of emissions and operational costs of small: about 20% CO₂ reduction, about 24% NO_x reduction, about 10 db (A) noise reduction at measurement point and about 25% DOC reduction. Detailed description of the performed studies, analyses and validations for each technology as well as the expected benefit at aircraft level are reported in the present paper.

Keywords: affordable, European, green, mobility, technologies development, travel time reduction

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Authors: Maria Lazari, Lorenzo Sanavia

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Mechanics of unsaturated soils has been an active field of research in the last decades. Efficient constitutive models that take into account the partial saturation of soil are necessary to solve a number of engineering problems e.g. instability of slopes and cuts due to heavy rainfalls. A large number of constitutive models can now be found in the literature that considers fundamental issues associated with the unsaturated soil behaviour, like the volume change and shear strength behaviour with suction or saturation changes. Partially saturated soils may either expand or collapse upon wetting depending on the stress level, and it is also possible that a soil might experience a reversal in the volumetric behaviour during wetting. Shear strength of soils also changes dramatically with changes in the degree of saturation, and a related engineering problem is slope failures caused by rainfall. There are several states of the art reviews over the last years for studying the topic, usually providing a thorough discussion of the stress state, the advantages, and disadvantages of specific constitutive models as well as the latest developments in the area of unsaturated soil modelling. However, only a few studies focused on the coupling between partial saturation states and time effects on the behaviour of geomaterials. Rate dependency is experimentally observed in the mechanical response of granular materials, and a viscoplastic constitutive model is capable of reproducing creep and relaxation processes. Therefore, in this work an elasto-viscoplastic constitutive model for unsaturated soils is proposed and validated on the basis of experimental data. The model constitutes an extension of an existing elastoplastic strain-hardening constitutive model capable of capturing the behaviour of variably saturated soils, based on energy conjugated stress variables in the framework of superposed continua. The purpose was to develop a model able to deal with possible mechanical instabilities within a consistent energy framework. The model shares the same conceptual structure of the elastoplastic laws proposed to deal with bonded geomaterials subject to weathering or diagenesis and is capable of modelling several kinds of instabilities induced by the loss of hydraulic bonding contributions. The novelty of the proposed formulation is enhanced with the incorporation of density dependent stiffness and hardening coefficients in order to allow the modeling of the pycnotropy behaviour of granular materials with a single set of material constants. The model has been implemented in the commercial FE platform PLAXIS, widely used in Europe for advanced geotechnical design. The algorithmic strategies adopted for the stress-point algorithm had to be revised to take into account the different approach adopted by PLAXIS developers in the solution of the discrete non-linear equilibrium equations. An extensive comparison between models with a series of experimental data reported by different authors is presented to validate the model and illustrate the capability of the newly developed model. After the validation, the effectiveness of the viscoplastic model is displayed by numerical simulations of a partially saturated slope failure of the laboratory scale and the effect of viscosity and degree of saturation on slope’s stability is discussed.

Keywords: PLAXIS software, slope, unsaturated soils, Viscoplasticity

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Authors: Roshni Raha, Karthikeyan S.

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The world's largest livestock population resides in India. Existing strategies must be modified to increase the production of livestock and their by-products in order to meet the demands of the growing human population. Even though India leads the world in both milk production and the number of cows, average production is not very healthy and productive. This may be due to the animals' poor nutrition caused by a chronic under-availability of high-quality fodder and feed. This article explores Azolla pinnata to be a promising source to produce high-quality unconventional feed and fodder for effective livestock production and good quality breeding in India. This article is an exploratory study using a literature survey and experimentation analysis. In the realm of agri-biotechnology, azolla sp gained attention for helping farmers achieve sustainability, having minimal land requirements, and serving as a feed element that doesn't compete with human food sources. It has high methionine content, which is a good source of protein. It can be easily digested as the lignin content is low. It has high antioxidants and vitamins like beta carotene, vitamin A, and vitamin B12. Using this concept, the paper aims to investigate and develop a model of using azolla plants as a novel, high-potential feed source to combat the problems of low production and poor quality of animals in India. A representative sample of animal feed is collected where azolla is added. The sample is ground into a fine powder using mortar. PITC (phenylisothiocyanate) is added to derivatize the amino acids. The sample is analyzed using HPLC (High-Performance Liquid Chromatography) to measure the amino acids and monitor the protein content of the sample feed. The amino acid measurements from HPLC are converted to milligrams per gram of protein using the method of amino acid profiling via a set of calculations. The amino acid profile data is then obtained to validate the proximate results of nutrient enhancement of the composition of azolla in the sample. Based on the proximate composition of azolla meal, the enhancement results shown were higher compared to the standard values of normal fodder supplements indicating the feed to be much richer and denser in nutrient supply. Thus azolla fed sample proved to be a promising source for animal fodder. This would in turn lead to higher production and a good breed of animals that would help to meet the economic demands of the growing Indian population. Azolla plants have no side effects and can be considered as safe and effective to be immersed in the animal feed. One area of future research could begin with the upstream scaling strategy of azolla plants in India. This could involve introducing several bioreactor types for its commercial production. Since azolla sp has been proved in this paper as a promising source for high quality animal feed and fodder, large scale production of azolla plants will help to make the process much quicker, more efficient and easily accessible. Labor expenses will also be reduced by employing bioreactors for large-scale manufacturing.

Keywords: azolla, fodder, nutrient, protein

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 35