Search results for: visual sensor networks

Authors: Chun-Qing Li, Guoyang Fu, Wei Yang

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A significant portion of current water networks is made of cast iron pipes. Due to aging and deterioration with corrosion being the most predominant mechanism, the failure rate of cast iron pipes is very high. Although considerable research has been carried out in the past few decades, most are on the effect of corrosion on the structural capacity of pipes using strength theory as the failure criterion. This paper presents a reliability-based methodology for the assessment of corrosion affected cast iron pipe cracking failures. A nonlinear limit state function taking into account all three fracture modes is proposed for brittle metal pipes with mixed mode fracture. A stochastic model of the load effect is developed, and time-dependent reliability method is employed to quantify the probability of failure and predict the remaining service life. A case study is carried out using the proposed methodology, followed by sensitivity analysis to investigate the effects of the random variables on the probability of failure. It has been found that the larger the inclination angle or the Mode I fracture toughness is, the smaller the probability of pipe failure is. It has also been found that the multiplying and exponential coefficients k and n in the power law corrosion model and the internal pressure have the most influence on the probability of failure for cast iron pipes. The methodology presented in this paper can assist pipe engineers and asset managers in developing a risk-informed and cost-effective strategy for better management of corrosion-affected pipelines.

Keywords: corrosion, inclined surface cracks, pressurized cast iron pipes, stress intensity

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Authors: Nitish Suvarna, Anjali Awasthi

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In an era marked by rapid technological advancements, the integration of Autonomous Vehicles into supply chain networks represents a transformative shift, promising to redefine the paradigms of logistics and transportation. This thesis delves into a comprehensive assessment of the impact of autonomous vehicles on supply chain performance, with a particular focus on network design, operational efficiency, and environmental sustainability. Employing the advanced simulation capabilities of anyLogistix (ALX), the study constructs a digital twin of a conventional supply chain network, encompassing suppliers, production facilities, distribution centers, and customer endpoints. The research methodically integrates Autonomous Vehicles into this intricate network, aiming to unravel the multifaceted effects on transportation logistics including transit times, cost-efficiency, and sustainability. Through simulations and scenarios analysis, the study scrutinizes the operational resilience and adaptability of supply chains in the face of dynamic market conditions and disruptive technologies like Autonomous Vehicles. Furthermore, the thesis undertakes carbon footprint analysis, quantifying the environmental benefits and challenges associated with the adoption of Autonomous Vehicles in supply chain operations. The insights from this research are anticipated to offer a strategic framework for industry stakeholders, guiding the adoption of Autonomous Vehicles to foster a more efficient, responsive, and sustainable supply chain ecosystem. The findings aim to serve as a cornerstone for future research and practical implementations in the realm of intelligent transportation and supply chain management.

Keywords: autonomous vehicle, agri-food supply chain, ALX simulation, anyLogistix

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Authors: Emad A. Mohammed

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The concept of hydraulic flow units (HFU) has been used for decades in the petroleum industry to improve the prediction of permeability. This concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir rock quality index (RQI). Both indices are based on reservoir porosity and permeability of core samples. It is assumed that core samples with similar FZI values belong to the same HFU. Thus, after dividing the porosity-permeability data based on the HFU, transformations can be done in order to estimate the permeability from the porosity. The conventional practice is to use the power law transformation using conventional HFU where percentage of error is considerably high. In this paper, neural network technique is employed as a soft computing transformation method to predict permeability instead of power law method to avoid higher percentage of error. This technique is based on HFU identification where Amaefule et al. (1993) method is utilized. In this regard, Kozeny and Carman (K–C) model, and modified K–C model by Hasan and Hossain (2011) are employed. A comparison is made between the two transformation techniques for the two porosity-permeability models. Results show that the modified K-C model helps in getting better results with lower percentage of error in predicting permeability. The results also show that the use of artificial intelligence techniques give more accurate prediction than power law method. This study was conducted on a heterogeneous complex carbonate reservoir in Oman. Data were collected from seven wells to obtain the permeability correlations for the whole field. The findings of this study will help in getting better estimation of permeability of a complex reservoir.

Keywords: permeability, hydraulic flow units, artificial intelligence, correlation

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Authors: Anton V. Bourdine, Vladimir A. Burdin, Oleg R. Delmukhametov

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This work presents a fast and simple method for the design of large core silica optical fibers with differential mode delay (DMD) management. Some results are reported concerned with refractive index profile optimization for 42 µm core 16-LP-mode optical fiber for next-generation optical networks. Here special refractive index profile form provides total DMD reducing over all mode staff under desired enhanced mode effective area. Method for the simulation of 'real manufactured' few-mode optical fiber (FMF) core geometry differing from the desired optimized structure by core non-symmetrical ellipticity and refractive index profile deviation including local fluctuations is proposed. Results of the following analysis of optimized FMF with inserted geometry distortions performed by earlier on developed modification of rigorous mixed finite-element method showed strong DMD degradation that requires additional higher-order mode management. In addition, this work also presents a method for design mode division multiplexer channel precision spatial positioning scheme at FMF core end that provides one of the potentiality solutions of described DMD degradation problem concerned with 'distorted' core geometry due to features of optical fiber manufacturing techniques.

Keywords: differential mode delay, few-mode optical fibers, nonlinear Shannon limit, optical fiber non-circularity, ‘real manufactured’ optical fiber core geometry simulation, refractive index profile optimization

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Authors: Chuang-Hung Lin, Cheng-Yuan Hsu, Jia-Yan Lin

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It is an indispensible strategy to adopt greenery approach on architectural bases so as to improve ecological habitats, decrease heat-island effect, purify air quality, and relieve surface runoff as well as noise pollution, all of which are done in an attempt to achieve sustainable environment. How we can do with plant design to attain the best visual quality and ideal carbon dioxide fixation depends on whether or not we can appropriately make use of greenery according to the nature of architectural bases. To achieve the goal, it is a need that architects and landscape architects should be provided with sufficient local references. Current greenery studies focus mainly on the heat-island effect of urban with large scale. Most of the architects still rely on people with years of expertise regarding the adoption and disposition of plantation in connection with microclimate scale. Therefore, environmental design, which integrates science and aesthetics, requires fundamental research on landscape environment technology divided from building environment technology. By doing so, we can create mutual benefits between green building and the environment. This issue is extremely important for the greening design of the bases of green buildings in cities and various open spaces. The purpose of this study is to establish plant selection and allocation strategies under different building sunshade levels. Initially, with the shading of sunshine on the greening bases as the starting point, the effects of the shades produced by different building types on the greening strategies were analyzed. Then, by measuring the PAR( photosynthetic active radiation), the relative DLI( daily light integral) was calculated, while the DLI Map was established in order to evaluate the effects of the building shading on the established environmental greening, thereby serving as a reference for plant selection and allocation. The discussion results were to be applied in the evaluation of environment greening of greening buildings and establish the “right plant, right place” design strategy of multi-level ecological greening for application in urban design and landscape design development, as well as the greening criteria to feedback to the eco-city greening buildings.

Keywords: daily light integral, plant design, urban open space

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Authors: Jaydip M. Desai, Antonio Valdevit, Arthur Ritter

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Robotic surgery is used to enhance minimally invasive surgical procedure. It provides greater degree of freedom for surgical tools but lacks of haptic feedback system to provide sense of touch to the surgeon. Surgical robots work on master-slave operation, where user is a master and robotic arms are the slaves. Current, surgical robots provide precise control of the surgical tools, but heavily rely on visual feedback, which sometimes cause damage to the inner organs. The goal of this research was to design and develop a real-time simulink based robotic system to study force feedback mechanism during instrument-object interaction. Setup includes three Velmex XSlide assembly (XYZ Stage) for three dimensional movement, an end effector assembly for forceps, electronic circuit for four strain gages, two Novint Falcon 3D gaming controllers, microcontroller board with linear actuators, MATLAB and Simulink toolboxes. Strain gages were calibrated using Imada Digital Force Gauge device and tested with a hard-core wire to measure instrument-object interaction in the range of 0-35N. Designed simulink model successfully acquires 3D coordinates from two Novint Falcon controllers and transfer coordinates to the XYZ stage and forceps. Simulink model also reads strain gages signal through 10-bit analog to digital converter resolution of a microcontroller assembly in real time, converts voltage into force and feedback the output signals to the Novint Falcon controller for force feedback mechanism. Experimental setup allows user to change forward kinematics algorithms to achieve the best-desired movement of the XYZ stage and forceps. This project combines haptic technology with surgical robot to provide sense of touch to the user controlling forceps through machine-computer interface.

Keywords: surgical robot, haptic feedback, MATLAB, strain gage, simulink

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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Authors: Mohammed E. A. Brixi Nigassa, Nassima Labdelli, Ahmed Slami, Arnaud Pothier, Sofiane Soulimane

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According to the world health organization (WHO), there are almost 285 million people with visual disability, 39 million of these people are blind. Nevertheless, there is a code for these people that make their life easier and allow them to access information more easily; this code is the Braille code. There are several commercial devices allowing braille reading, unfortunately, most of these devices are not ergonomic and too expensive. Moreover, we know that 90 % of blind people in the world live in low-incomes countries. Our contribution aim is to concept an original microactuator for Braille reading, as well as being ergonomic, inexpensive and lowest possible energy consumption. Nowadays, the piezoelectric device gives the better actuation for low actuation voltage. In this study, we focus on piezoelectric (PZT) material which can bring together all these conditions. Here, we propose to use one matrix composed by six actuators to form the 63 basic combinations of the Braille code that contain letters, numbers, and special characters in compliance with the standards of the braille code. In this work, we use a finite element model with Comsol Multiphysics software for designing and modeling this type of miniature actuator in order to integrate it into a test device. To define the geometry and the design of our actuator, we used physiological limits of perception of human being. Our results demonstrate in our study that piezoelectric actuator could bring a large deflection out-of-plain. Also, we show that microactuators can exhibit non uniform compression. This deformation depends on thin film thickness and the design of membrane arm. The actuator composed of four arms gives the higher deflexion and it always gives a domed deformation at the center of the deviceas in case of the Braille system. The maximal deflection can be estimated around ten micron per Volt (~ 10µm/V). We noticed that the deflection according to the voltage is a linear function, and this deflection not depends only on the voltage the voltage, but also depends on the thickness of the film used and the design of the anchoring arm. Then, we were able to simulate the behavior of the entire matrix and thus display different characters in Braille code. We used these simulations results to achieve our demonstrator. This demonstrator is composed of a layer of PDMS on which we put our piezoelectric material, and then added another layer of PDMS to isolate our actuator. In this contribution, we compare our results to optimize the final demonstrator.

Keywords: Braille code, comsol software, microactuators, piezoelectric

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Authors: Joanna Estkowska

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The Sensory Integration Method is aimed primarily at children with learning disabilities. It can also be used as a complementary method in treatment of children with cerebral palsy, autistic, mentally handicapped, blind and deaf. Autism is holistic development disorder that manifests itself in the specific functioning of a child. The most characteristic are: disorders in communication, difficulties in social relations, rigid patterns of behavior and impairment in sensory processing. In addition to these disorders may occur abnormal intellectual development, attention deficit disorders, perceptual disorders and others. This study was focused on the application sensory integration techniques in science education of autistic students. The lack of proper sensory integration causes problems with complicated processes such as motor coordination, movement planning, visual or auditory perception, speech, writing, reading or counting. Good functioning and cooperation of proprioceptive, tactile and vestibular sense affect the child’s mastery of skills that require coordination of both sides of the body and synchronization of the cerebral hemispheres. These include, for example, all sports activities, precise manual skills such writing, as well as, reading and counting skills. All this takes place in stages. Achieving skills from the first stage determines the development of fitness from the next level. Any deficit in the scope of the first three stages can affect the development of new skills. This ultimately reflects on the achievements at school and in further professional and personal life. After careful analysis symptoms from the emotional and social spheres appear to be secondary to deficits of sensory integration. During our research, the students gained knowledge and skills in the classroom of experience by learning biology, chemistry and physics with application sensory integration techniques. Sensory integration therapy aims to teach the child an adequate response to stimuli coming to him from both the outside world and the body. Thanks to properly selected exercises, a child can improve perception and interpretation skills, motor skills, coordination of movements, attention and concentration or self-awareness, as well as social and emotional functioning.

Keywords: autism spectrum disorder, science education, sensory integration, special educational needs

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Authors: Sruthi Raveendran

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Developmental dyslexia, characterized by reading difficulties despite normal intelligence, presents a significant challenge for bilingual children navigating languages with varying degrees of orthographic transparency. This study bridges a critical gap in dyslexia interventions for bilingual populations in India by examining how consistency and predictability of letter-sound relationships in a writing system (orthographic transparency) influence the ability to understand and manipulate the building blocks of sound in language (phonological processing). The study employed a computerized visual rhyme-judgment task with concurrent EEG (electroencephalogram) recording. The task compared reaction times, accuracy of performance, and event-related potential (ERP) components (N170, N400, and LPC) for rhyming and non-rhyming stimuli in two orthographies: English (opaque orthography) and Kannada (transparent orthography). As hypothesized, the results revealed advantages in phonological processing tasks for transparent orthography (Kannada). Children with dyslexia were faster and more accurate when judging rhymes in Kannada compared to English. This suggests that a language with consistent letter-sound relationships (transparent orthography) facilitates processing, especially for tasks that involve manipulating sounds within words (rhyming). Furthermore, brain activity measured by event-related potentials (ERP) showed less effort required for processing words in Kannada, as reflected by smaller N170, N400, and LPC amplitudes. These findings highlight the crucial role of orthographic transparency in optimizing reading performance for bilingual children with dyslexia. These findings emphasize the need for language-specific intervention strategies that consider the unique linguistic characteristics of each language. While acknowledging the complexity of factors influencing dyslexia, this research contributes valuable insights into the impact of orthographic transparency on phonological awareness in bilingual children. This knowledge paves the way for developing tailored interventions that promote linguistic inclusivity and optimize literacy outcomes for children with dyslexia.

Keywords: developmental dyslexia, phonological awareness, rhyme judgment, orthographic transparency, Kannada, English, N170, N400, LPC

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Authors: Linda Dusman, Linda Baker

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The Bearman Study of Audience Engagement examined the potential for real-time music education during online symphony orchestra concerts. It follows on the promising results of a preliminary study of STEAM (Science, Technology, Engineering, Arts, and Mathematics) education during live concerts, funded by the National Science Foundation with the Baltimore Symphony Orchestra. For the Bearman Study, audience groups were recruited to attend two previously recorded concerts of the National Orchestral Institute (NOI) in 2020 or the Utah Symphony in 2021. They used a smartphone app called EnCue to present real-time program notes about the music being performed. Short notes along with visual information (photos and score fragments) were designed to provide historical, cultural, biographical, and theoretical information at specific moments in the music where that information would be most pertinent, generally spaced 2-3 minutes apart to avoid distraction. The music performed included Dvorak Symphony No. 8 and Mahler Symphony No. 5 at NOI, and Mendelssohn Scottish Symphony and Richard Strauss Metamorphosen with the Utah Symphony, all standard repertoire for symphony orchestras. During each phase of the study (2020 and 2021), participants were randomly assigned to use the app to view program notes during the first concert or to use the app during the second concert. A total of 139 participants (67 in 2020 and 72 in 2021) completed three online questionnaires, one before attending the first concert, one immediately after the concert, and the third immediately after the second concert. Questionnaires assessed demographic background, expertise in music, engagement during the concert, learning of content about the composers and the symphonies, and interest in the future use of the app. In both phases of the study, participants demonstrated that they learned content presented on the app, evidenced by the fact that their multiple-choice test scores were significantly higher when they used the app than when they did not. In addition, most participants indicated that using the app enriched their experience of the concert. Overall, they were very positive about their experience using the app for real-time learning and they expressed interest in using it in the future at both live and streaming concerts. Results confirmed that informal real-time learning during concerts is possible and can generate enhanced engagement and interest in classical music.

Keywords: audience engagement, informal education, music technology, real-time learning

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Authors: A. Atli, K. Candelier, J. Alteyrac

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Environmental and sustainability concerns push the industries to manufacture alternative materials having less environmental impact. The Wood Plastic Composites (WPCs) produced by blending the biopolymers and natural fillers permit not only to tailor the desired properties of materials but also are the solution to meet the environmental and sustainability requirements. This work presents the elaboration and characterization of the fully green WPCs prepared by blending a biopolymer, BIOPLAST® GS 2189 and spruce sawdust used as filler with different amounts. Since both components are bio-based, the resulting material is entirely environmentally friendly. The mechanical, thermal, structural properties of these WPCs were characterized by different analytical methods like tensile, flexural and impact tests, Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and X-ray Diffraction (XRD). Their water absorption properties and resistance to the termite and fungal attacks were determined in relation with different wood filler content. The tensile and flexural moduli of WPCs increased with increasing amount of wood fillers into the biopolymer, but WPCs became more brittle compared to the neat polymer. Incorporation of spruce sawdust modified the thermal properties of polymer: The degradation, cold crystallization, and melting temperatures shifted to higher temperatures when spruce sawdust was added into polymer. The termite, fungal and water absorption resistance of WPCs decreased with increasing wood amount in WPCs, but remained in durability class 1 (durable) concerning fungal resistance and quoted 1 (attempted attack) in visual rating regarding to the termites resistance except that the WPC with the highest wood content (30 wt%) rated 2 (slight attack) indicating a long term durability. All the results showed the possibility to elaborate the easy injectable composite materials with adjustable properties by incorporation of BIOPLAST® GS 2189 and spruce sawdust. Therefore, lightweight WPCs allow both to recycle wood industry byproducts and to produce a full ecologic material.

Keywords: biodegradability, color measurements, durability, mechanical properties, melt flow index, MFI, structural properties, thermal properties, wood-plastic composites, WPCs

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Authors: Ayesha Khatun

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In 21st century where markets are unstable, technologies rapidly proliferate, competitors multiply, products and services become obsolete almost overnight and customers demand low cost high value product, leveraging and harnessing knowledge is not just a potential source of competitive advantage rather a necessity in technology based and information intensive industries. Knowledge management focuses on leveraging the available knowledge and sharing the same among the individuals in the organization so that the employees can make best use of it towards achieving the organizational goals. Knowledge is not a discrete object. It is embedded in people and so difficult to transfer outside the immediate context that it becomes a major competitive advantage. However, internal transfer of knowledge among the employees is essential to maximize the use of knowledge available in the organization in an unstructured manner. But as knowledge is the source of competitive advantage for the organization it is also the source of competitive advantage for the individuals. People think that knowledge is power and sharing the same may lead to lose the competitive position. Moreover, the very nature of tacit knowledge poses many difficulties in sharing the same. But sharing tacit knowledge is the vital part of knowledge management process because it is the tacit knowledge which is inimitable. Knowledge management has been made synonymous with the use of software and technology leading to the management of explicit knowledge only ignoring personal interaction and forming of informal networks which are considered as the most successful means of sharing tacit knowledge. Factors responsible for effective sharing of tacit knowledge are grouped into –individual, organizational and technological factors. Different factors under each category have been identified. Creating a positive organizational culture, encouraging personal interaction, practicing reward system are some of the strategies that can help to overcome many of the barriers to effective sharing of tacit knowledge. Methodology applied here is completely secondary. Extensive review of relevant literature has been undertaken for the purpose.

Keywords: knowledge, tacit knowledge, knowledge management, sustainable competitive advantage, organization, knowledge sharing

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Authors: Hendrick Maxil Zárate Rocha, Ricardo da Silva Pereira, Manoel Fernandes Martins Nogueira, Carlos R. Pereira Belchior, Maria Emilia de Lima Tostes

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This study investigates experimentally the effects of hydrogen addition in the intake manifold of a diesel generator operating with a 7% biodiesel-diesel oil blend (B7). An experimental apparatus setup was used to conduct performance and emissions tests in a single cylinder, air cooled diesel engine. This setup consisted of a generator set connected to a wirewound resistor load bank that was used to vary engine load. In addition, a flowmeter was used to determine hydrogen volumetric flowrate and a digital anemometer coupled with an air box to measure air flowrate. Furthermore, a digital precision electronic scale was used to measure engine fuel consumption and a gas analyzer was used to determine exhaust gas composition and exhaust gas temperature. A thermopar was installed near the exhaust collection to measure cylinder temperature. In-cylinder pressure was measured using an AVL Indumicro data acquisition system with a piezoelectric pressure sensor. An AVL optical encoder was installed in the crankshaft and synchronized with in-cylinder pressure in real time. The experimental procedure consisted of injecting hydrogen into the engine intake manifold at different mass concentrations of 2,6,8 and 10% of total fuel mass (B7 + hydrogen), which represented energy fractions of 5,15, 20 and 24% of total fuel energy respectively. Due to hydrogen addition, the total amount of fuel energy introduced increased and the generators fuel injection governor prevented any increases of engine speed. Several conclusions can be stated from the test results. A reduction in specific fuel consumption as a function of hydrogen concentration increase was noted. Likewise, carbon dioxide emissions (CO2), carbon monoxide (CO) and unburned hydrocarbons (HC) decreased as hydrogen concentration increased. On the other hand, nitrogen oxides emissions (NOx) increased due to average temperatures inside the cylinder being higher. There was also an increase in peak cylinder pressure and heat release rate inside the cylinder, since the fuel ignition delay was smaller due to hydrogen content increase. All this indicates that hydrogen promotes faster combustion and higher heat release rates and can be an important additive to all kind of fuels used in diesel generators.

Keywords: diesel engine, hydrogen, dual fuel, combustion analysis, performance, emissions

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Authors: Jiří F. Urbánek, David Král

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Small and Middle Enterprises (SME) have a specific mission, characteristics, and behavior in global business competitive environments. They must respect policy, rules, requirements and standards in all their inherent and outer processes of supply - customer chains and networks. Paper aims and purposes are to introduce computational assistance, which enables us the using of prevailing operation system MS Office (SmartArt...) for mathematical models, using DYVELOP (Dynamic Vector Logistics of Processes) method. It is providing for SMS´s global environment the capability and profit to achieve its commitment regarding the effectiveness of the quality management system in customer requirements meeting and also the continual improvement of the organization’s and SME´s processes overall performance and efficiency, as well as its societal security via continual planning improvement. DYVELOP model´s maps - the Blazons are able mathematically - graphically express the relationships among entities, actors, and processes, including the discovering and modeling of the cycling cases and their phases. The blazons need live PowerPoint presentation for better comprehension of this paper mission – added value analysis. The crisis management of SMEs is obliged to use the cycles for successful coping of crisis situations.  Several times cycling of these cases is a necessary condition for the encompassment of the both the emergency event and the mitigation of organization´s damages. Uninterrupted and continuous cycling process is a good indicator and controlling actor of SME continuity and its sustainable development advanced possibilities.

Keywords: blazons, computational assistance, DYVELOP method, small and middle enterprises

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Authors: Yuxiao Jiang, Lingjun Meng, Mengyu Zhan, Lichunyi Zhang, Yingxia Yun

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On August 8th of 2015, a serious explosion occurred in Binhai New Area of Tianjin. This explosion led to the suspension of Tianjin-Binhai Light Rail Line 9 which was an important transportation mean connecting the old and new urban areas and the suspension causes inconvenience to commuters traveling from Tianjin to Binhai or Binhai to Tianjin and residents living by Line 9. On this regard, this paper intends to give suggestions on how to develop multi-mode transportation system rapidly and effectively after a disaster and tackle with the problems in terms of transportation infrastructure facilities. The paper proposes the idea of traffic resilience which refers to the city’s ability to restore its transportation system and reduce risks when the transportation system is destroyed by a disaster. By doing questionnaire research, on the spot study and collecting data from the internet, a GIS model is established so as to analyze the alternative traffic means used by different types of residents and study the transportation supply and demand. The result shows that along the Line 9, there is a larger demand for alternative traffic means in the place which is nearer to the downtown area. Also, the distribution of bus stations is more reasonable in the place nearer to downtown area, however, the traffic speed in the area is slower. Based on traffic resilience, the paper raises strategies to develop post-disaster multi-mode transportation system such as establishing traffic management mechanism timely and effectively, building multi-mode traffic networks, improving intelligent traffic systems and so on.

Keywords: traffic resilience, multi-mode transportation system, public traffic, transportation demand

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Authors: Andile Mkhohlakali, Tien-Chien Jen, James Tshilongo, Happy Mabowa

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Among different parameters, oxygen is one of the most important analytes of interest, dissolved oxygen (DO) concentration is very crucial and significant for various areas of physical, chemical, and environmental monitoring. Herein we report oxygen-sensitive luminophores -based lanthanum(III) trifluoromethanesulfonate), [La]³⁺ was encapsulated into SiO₂-based xerogel matrix. The nanosensor is composed of organically modified silica nanoparticles, doped with the luminescent oxygen–sensitive lanthanum(III) trifluoromethanesulfonate complex. The precursor materials used for sensing film were triethyl ethoxy silane (TEOS) and (3-Mercaptopropyltriethoxysilane) (MPTMS- TEOS) used for SiO2-baed matrices. Brunauer–Emmett–Teller (BET), and BJH indicate that the SiO₂ transformed from microporous to mesoporous upon the addition of La³⁺ luminophore with increased surface area (SBET). The typical amorphous SiO₂ based xerogels were revealed with X-Ray diffraction (XRD) and Selected Area Electron Diffraction (SAED) analysis. Scanning electron microscope- (SEM) and transmission electron microscope (TEM) showed the porous morphology and reduced particle for SiO₂ and La-SiO₂ xerogels respectively. The existence of elements, siloxane networks, and thermal stability of xerogel was confirmed by energy dispersive spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), and Thermographic analysis (TGA). UV-Vis spectroscopy and photoluminescence (PL) have been used to characterize the optical properties of xerogels. La-SiO₂ demonstrates promising characteristic features of an active sensing film for dissolved oxygen in the water. Keywords: Sol-gel, ORMOSILs, encapsulation, Luminophores quenching, O₂-sensing

Keywords: sol-gel, ORMOSILs, luminophores quenching, O₂-sensing

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Authors: Alice V. Brown, Patrick Egan, Dorothy Bagshaw, Jackie Oakley, Emma Vieira, Louise Southalan, Duc Dau, Lucy Spanswick, Lindey Andrews, Mandy Wilson, Jocelyn Jones

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Western Australia has recently adopted a 10-year plan to end homelessness across its State, with sections of the plan focused particularly on the Aboriginal and Torres Strait Islander population. In 2022, we engaged with 70-90 Aboriginal people experiencing homelessness in Perth, Western Australia, through qualitative interviews and creative methods, listening to their experiences of homelessness and their views on how services, State plans, and policies could better support them. This research was driven by the Aboriginal community through a Community Ownership Group of 16 Aboriginal Elders, elected by Elders’ groups, from across the Perth metropolitan area. The Community Ownership Group met every six weeks across the 15-month project timeline to guide the research team, endorse methods chosen, and provide richer context to research findings to ensure they adequately represent the experiences of Aboriginal people. These meetings were audio-recorded when possible and documented through meeting notes, verbal and visual minutes, and film, providing insights into homelessness from the perspective of Aboriginal Elders. In this paper, we compare the views of those experiencing homelessness with the views of the Aboriginal Elders -many of whom have experienced homelessness firsthand- and literature regarding how those experiencing homelessness can be better supported. We detail the ‘survival-directed thinking’ of those we engaged with who was in the throes of homelessness, leading them to focus more on immediate solutions such as food and housing. We then compare these narratives to Elders’ views that have been more regularly focused on connection to culture and long-term plans for healing homelessness, alongside immediate outreach -views also reflected in the literature. Through these comparisons, we highlight the importance of engaging both with those currently experiencing homelessness as well as with Aboriginal Elders as important cultural caretakers and authorities. We demonstrate how these varied voices uncover both long and short-term perspectives on how homelessness can be better managed in policy and service provision. We also highlight the potential role Aboriginal Elders can play in supporting the Aboriginal homeless community and their transition into housing.

Keywords: Aboriginal and Torres strait islander peoples, aboriginal elders, homelessness, community-led research

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Authors: Denise Levy

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Nuclear technology is part of our everyday life and its beneficial applications help to improve the quality of our lives. Nevertheless, in Brazil, most often the media and social networks tend to associate radiation to nuclear weapons and major accidents, and there is still great misunderstanding about the peaceful applications of nuclear science. The Educational Portal Radioatividades (Radioactivities) is a corporate social responsibility initiative that takes advantage of the growing impact of Internet to offer high quality scientific information for teachers and students throughout Brazil. This web-based initiative focusses on the positive applications of nuclear technology, presenting the several contributions of ionizing radiation in different contexts, such as nuclear medicine, agriculture techniques, food safety and electric power generation, proving nuclear technology as part of modern life and a must to improve the quality of our lifestyle. This educational project aims to contribute for democratization of scientific education and social inclusion, approaching society to scientific knowledge, promoting critical thinking and inspiring further reflections. The website offers a wide variety of ludic activities such as curiosities, interactive exercises and short courses. Moreover, teachers are offered free web-based material with full instructions to be developed in class. Since year 2013, the project has been developed and improved according to a comprehensive study about the realistic scenario of ICTs infrastructure in Brazilian schools and in full compliance with the best e-learning national and international recommendations.

Keywords: information and communication technologies, nuclear technology, science communication, society and education

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Authors: Biruhi Tesfaye, Avinash M. Potdar

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The laboratory test process to determine the California bearing ratio (CBR) of black cotton soils is not only overpriced but also time-consuming as well. Hence advanced prediction of CBR plays a significant role as it is applicable In pavement design. The prediction of CBR of treated soil was executed by Artificial Neural Networks (ANNs) which is a Computational tool based on the properties of the biological neural system. To observe CBR values, combined eggshell and waste glass was added to soil as 4, 8, 12, and 16 % of the weights of the soil samples. Accordingly, the laboratory related tests were conducted to get the required best model. The maximum CBR value found at 5.8 at 8 % of eggshell waste glass powder addition. The model was developed using CBR as an output layer variable. CBR was considered as a function of the joint effect of liquid limit, plastic limit, and plastic index, optimum moisture content and maximum dry density. The best model that has been found was ANN with 5, 6 and 1 neurons in the input, hidden and output layer correspondingly. The performance of selected ANN has been 0.99996, 4.44E-05, 0.00353 and 0.0067 which are correlation coefficient (R), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE) respectively. The research presented or summarized above throws light on future scope on stabilization with waste glass combined with different percentages of eggshell that leads to the economical design of CBR acceptable to pavement sub-base or base, as desired.

Keywords: CBR, artificial neural network, liquid limit, plastic limit, maximum dry density, OMC

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Authors: Ahmad Alsolami, Darren Mundy, Manuel Hernandez-Perez

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Social media networks, such as Twitter, offer the perfect opportunity to either positively or negatively affect political attitudes on large audiences. The existence of influential users who have developed a reputation for their knowledge and experience of specific topics is a major factor contributing to this impact. Therefore, knowledge of the mechanisms to identify influential users on social media is vital for understanding their effect on their audience. The concept of the influential user is related to the concept of opinion leaders' to indicate that ideas first flow from mass media to opinion leaders and then to the rest of the population. Hence, the objective of this research was to provide reliable and accurate structural mechanisms to identify influential users, which could be applied to different platforms, places, and subjects. Twitter was selected as the platform of interest, and Saudi Arabia as the context for the investigation. These were selected because Saudi Arabia has a large number of Twitter users, some of whom are considerably active in setting agendas and disseminating ideas. The study considered the scientific methods that have been used to identify public opinion leaders before, utilizing metrics software on Twitter. The key findings propose multiple novel metrics to compare Twitter influencers, including the number of followers, social authority and the use of political hashtags, and four secondary filtering measures. Thus, using ratio and percentage calculations to classify the most influential users, Twitter accounts were filtered, analyzed and included. The structured approach is used as a mechanism to explore the top ten influencers on Twitter from the political domain in Saudi Arabia.

Keywords: Twitter, influencers, structured mechanism, Saudi Arabia

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Authors: Radwa Mabrook

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Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: collaborative culture, content creation, experimental culture, virtual reality

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Authors: Jonathan Turner, Julie Doyle, Laura O’Philbin, Dympna O’Sullivan

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People living with dementia should be at the centre of decision-making regarding goals for daily living. These goals include basic activities (dressing, hygiene, and mobility), advanced activities (finances, transportation, and shopping), and meaningful activities that promote well-being (pastimes and intellectual pursuits). However, there is limited involvement of people living with dementia in the design of technology to support their goals. A project is described that is co-designing intelligent computer-based support for, and with, people affected by dementia and their carers. The technology will support self-management, empower participation in shared decision-making with carers and help people living with dementia remain healthy and independent in their homes for longer. It includes information from the patient’s care plan, which documents medications, contacts, and the patient's wishes on end-of-life care. Importantly for this work, the plan can outline activities that should be maintained or worked towards, such as exercise or social contact. The authors discuss how to integrate care goal information from such a care plan with data collected from passive sensors in the patient’s home in order to deliver individualized planning and interventions for persons with dementia. A number of scientific challenges are addressed: First, to co-design with dementia patients and their carers computerized support for shared decision-making about their care while allowing the patient to share the care plan. Second, to develop a new and open monitoring framework with which to configure sensor technologies to collect data about whether goals and actions specified for a person in their care plan are being achieved. This is developed top-down by associating care quality types and metrics elicited from the co-design activities with types of data that can be collected within the home, from passive and active sensors, and from the patient’s feedback collected through a simple co-designed interface. These activities and data will be mapped to appropriate sensors and technological infrastructure with which to collect the data. Third, the application of machine learning models to analyze data collected via the sensing devices in order to investigate whether and to what extent activities outlined via the care plan are being achieved. The models will capture longitudinal data to track disease progression over time; as the disease progresses and captured data show that activities outlined in the care plan are not being achieved, the care plan may recommend alternative activities. Disease progression may also require care changes, and a data-driven approach can capture changes in a condition more quickly and allow care plans to evolve and be updated.

Keywords: care goals, decision-making, dementia, self-care, sensors

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Authors: M. Macchiaroli, L. Dolores, V. Pellecchia

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With the recent Resolution n. 580/2019/R/idr, the Italian Regulatory Authority for Energy, Networks, and Environment (ARERA) for the Urban Water Management has introduced, for water managements characterized by persistent critical issues regarding the planning and organization of the service and the implementation of the necessary interventions for the improvement of infrastructures and management quality, a new mechanism for determining tariffs: the regulatory scheme of Convergence. The aim of this regulatory scheme is the overcoming of the Water Service Divided in order to improve the stability of the local institutional structures, technical quality, contractual quality, as well as in order to guarantee transparency elements for Users of the Service. Convergence scheme presupposes the identification of the cost items to be considered in the tariff in parametric terms, distinguishing three possible cases according to the type of historical data available to the Manager. The study, in particular, focuses on operations that have neither data on tariff revenues nor data on operating costs. In this case, the Manager's Constraint on Revenues (VRG) is estimated on the basis of a reference benchmark and becomes the starting point for defining the structure of the tariff classes, in compliance with the TICSI provisions (Integrated Text for tariff classes, ARERA's Resolution n. 665/2017/R/idr). The proposed model implements the recent studies on optimization models for the definition of tariff classes in compliance with the constraints dictated by TICSI in the application of the Convergence mechanism, proposing itself as a support tool for the Managers and the local water regulatory Authority in the decision-making process.

Keywords: decision-making process, economic evaluation of projects, optimizing tools, urban water management, water tariff

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Authors: Wan-Ting Liao, Angela K. Tzeng

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Empathy has been an important issue in psychology, education, as well as cognitive neuroscience. Empathy has two major components: cognitive and emotional. Cognitive component refers to the ability to understand others’ perspectives, thoughts, and actions, whereas emotional component refers to understand how others feel. Empathy can be induced, attitude can then be changed, and with enough attitude change, helping behavior can occur. This finding leads us to two questions: is attitude change really necessary for prosocial behavior? And, what roles cognitive and affective empathy play? For the second question, participants with different psychopathic personality (PP) traits are critical because high PP people were found to suffer only affective empathy deficit. Their cognitive empathy shows no significant difference from the control group. 132 college students voluntarily participated in the current three-stage study. Stage 1 was to collect basic information including Interpersonal Reactivity Index (IRI), Psychopathic Personality Inventory-Revised (PPI-R), Attitude Scale, Visual Analogue Scale (VAS), and demographic data. Stage two was for empathy induction with three controversial scenarios, namely domestic violence, depression with a suicide attempt, and an ex-offender. Participants read all three stories and then rewrite the stories by one of two perspectives (empathetic vs. objective). They would then complete the VAS and Attitude Scale one more time for their post-attitude and emotional status. Three IVs were introduced for data analysis: PP (High vs. Low), Responsibility (whether or not the character is responsible for what happened), and Perspective-taking (Empathic vs. Objective). Stage 3 was for the action. Participants were instructed to freely use the 17 tokens they received as donations. They were debriefed and interviewed at the end of the experiment. The major findings were people with higher empathy tend to take more action in helping. Attitude change is not necessary for prosocial behavior. The controversy of the scenarios and how familiar participants are towards target groups play very important roles. Finally, people with high PP tend to show more public prosocial behavior due to their affective empathy deficit. Pre-existing value and belief as well as recent dramatic social events seem to have a big impact and possibly reduce the effect of the independent variables (IV) in our paradigm.

Keywords: empathy, cognitive, emotional, psychopathy

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Authors: George Mahalu

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The Chua diode has been configured over time in various ways, using electronic structures like as operational amplifiers (OAs) or devices with gas or semiconductors. When discussing the use of semiconductor devices, tunnel diodes (Esaki diodes) are most often considered, and more recently, transistorized configurations such as lambda diodes. The paper-work proposed here uses in the modeling a lambda diode type configuration consisting of two Junction Field Effect Transistors (JFET). The original scheme is created in the MULTISIM electronic simulation environment and is analyzed in order to identify the conditions for the appearance of evolutionary unpredictability specific to nonlinear dynamic systems with chaos-induced behavior. The chaotic deterministic oscillator is one autonomous type, a fact that places it in the class of Chua’s type oscillators, the only significant and most important difference being the presence of a nonlinear device like the one mentioned structure above. The chaotic behavior is identified both by means of strange attractor-type trajectories and visible during the simulation and by highlighting the hypersensitivity of the system to small variations of one of the input parameters. The results obtained through simulation and the conclusions drawn are useful in the further research of ways to implement such constructive electronic solutions in theoretical and practical applications related to modern small signal amplification structures, to systems for encoding and decoding messages through various modern ways of communication, as well as new structures that can be imagined both in modern neural networks and in those for the physical implementation of some requirements imposed by current research with the aim of obtaining practically usable solutions in quantum computing and quantum computers.

Keywords: chaos, lambda diode, strange attractor, nonlinear system

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Authors: Travis Morris

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The purpose of this study is to measure the intersection of environmental security entities in terrorist propaganda. To the best of author’s knowledge, this is the first study of its kind to examine this intersection within terrorist propaganda. Rosoka, natural language processing software and frame analysis are used to advance our understanding of how environmental frames function as emotive triggers. Violent jihadi demagogues use frames to suggest violent and non-violent solutions to their grievances. Emotive triggers are framed in a way to leverage individual and collective attitudes in psychological warfare. A comparative research design is used because of the differences and similarities that exist between two variants of violent jihadi propaganda that target western audiences. Analysis is based on salience and network text analysis, which generates violent jihadi semantic networks. Findings indicate that environmental frames are used as emotive triggers across both data sets, but also as tactical and information data points. A significant finding is that certain core environmental emotive triggers like “water,” “soil,” and “trees” are significantly salient at the aggregate level across both data sets. All environmental entities can be classified into two categories, symbolic and literal. Importantly, this research illustrates how demagogues use environmental emotive triggers in cyber space from a subcultural perspective to mobilize target audiences to their ideology and praxis. Understanding the anatomy of propaganda construction is necessary in order to generate effective counter narratives in information operations. This research advances an additional method to inform practitioners and policy makers of how environmental security and propaganda intersect.

Keywords: propaganda analysis, emotive triggers environmental security, frames

Procedia PDF Downloads 138

Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

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Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: Feng Huang, Carlos G. Ochoa, Haitao Zhao

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Poyang Lake, the largest freshwater lake in China, is located at the middle-lower reaches of the Yangtze River basin. It has great value in socioeconomic development and is internationally recognized as an important lacustrine and wetland ecosystem with abundant biodiversity. Impacted by ongoing climate change and anthropogenic activities, especially the regulation of the Three Gorges Reservoir since 2003, Poyang Lake has experienced significant water regime evolution, resulting in challenges for the management of water resources and the environment. Quantifying the contribution of hydrologic and topographic changes to water regime alteration is necessary for policymakers to design effective adaption strategies. Long term hydrologic data were collected and the back-propagation neural networks were constructed to simulate the lake water level. The impacts of hydrologic and topographic changes were differentiated through scenario analysis that considered pre-impact and post-impact hydrologic and topographic scenarios. The lake water regime was characterized by hydrologic indicators that describe monthly water level fluctuations, hydrologic features during flood and drought seasons, and frequency and rate of hydrologic variations. The results revealed different contributions of hydrologic and topographic changes to different features of the lake water regime.Noticeable changes were that the water level declined dramatically during the period of reservoir impoundment, and the drought was enhanced during the dry season. The hydrologic and topographic changes exerted a synergistic effect or antagonistic effect on different lake water regime features. The findings provide scientific reference for lacustrine and wetland ecological protection associated with water regime alterations.

Keywords: back-propagation neural network, scenario analysis, water regime, Poyang Lake

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Authors: Vaishali D. Khairnar

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The main aim is to provide lower-latency and highly reliable communication facilities for vehicles in the automobile industry; vehicle-to-everything (V2X) communication basically intends to increase expressway road security and its effectiveness. The Ultra-Reliable Low-Latency Communications (URLLC) algorithm and cellular networks are applied in combination with Mobile Broadband (MBB). This is particularly used in express way safety-based driving applications. Expressway vehicle drivers (humans) will communicate in V2X systems using the sixth-generation (6G) communication systems which have very high-speed mobility features. As a result, we need to determine how to ensure reliable and consistent wireless communication links and improve the quality to increase channel gain, which is becoming a challenge that needs to be addressed. To overcome this challenge, we proposed a unique multi-user scheduling algorithm for ultra-massive multiple-input multiple-output (MIMO) systems using 6G. In wideband wireless network access in case of high traffic and also in medium traffic conditions, moreover offering quality-of-service (QoS) to distinct service groups with synchronized contemporaneous traffic on the highway like the Mumbai-Pune expressway becomes a critical problem. Opportunist MAC (OMAC) is a way of proposing communication across a wireless communication link that can change in space and time and might overcome the above-mentioned challenge. Therefore, a multi-user scheduling algorithm is proposed for MIMO systems using a cross-layered MAC protocol to achieve URLLC and high reliability in V2X communication.

Keywords: ultra-reliable low latency communications, vehicle-to-everything communication, multiple-input multiple-output systems, multi-user scheduling algorithm

Procedia PDF Downloads 88