Search results for: architecture description languages

Authors: Norma Binti Alias, Che Rahim Che The, Norfarizan Mohd Said, Sakinah Abdul Hanan, Akhtar Ali

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This paper discusses on the transportation of magnetic drug targeting through blood within vessels, tissues and cells. There are three integrated mathematical models to be discussed and analyze the concentration of drug and blood flow through magnetic nanoparticles. The cell therapy brought advancement in the field of nanotechnology to fight against the tumors. The systematic therapeutic effect of Single Cells can reduce the growth of cancer tissue. The process of this nanoscale phenomena system is able to measure and to model, by identifying some parameters and applying fundamental principles of mathematical modeling and simulation. The mathematical modeling of single cell growth depends on three types of cell densities such as proliferative, quiescent and necrotic cells. The aim of this paper is to enhance the simulation of three types of models. The first model represents the transport of drugs by coupled partial differential equations (PDEs) with 3D parabolic type in a cylindrical coordinate system. This model is integrated by Non-Newtonian flow equations, leading to blood liquid flow as the medium for transportation system and the magnetic force on the magnetic nanoparticles. The interaction between the magnetic force on drug with magnetic properties produces induced currents and the applied magnetic field yields forces with tend to move slowly the movement of blood and bring the drug to the cancer cells. The devices of nanoscale allow the drug to discharge the blood vessels and even spread out through the tissue and access to the cancer cells. The second model is the transport of drug nanoparticles from the vascular system to a single cell. The treatment of the vascular system encounters some parameter identification such as magnetic nanoparticle targeted delivery, blood flow, momentum transport, density and viscosity for drug and blood medium, intensity of magnetic fields and the radius of the capillary. Based on two discretization techniques, finite difference method (FDM) and finite element method (FEM), the set of integrated models are transformed into a series of grid points to get a large system of equations. The third model is a single cell density model involving the three sets of first order PDEs equations for proliferating, quiescent and necrotic cells change over time and space in Cartesian coordinate which regulates under different rates of nutrients consumptions. The model presents the proliferative and quiescent cell growth depends on some parameter changes and the necrotic cells emerged as the tumor core. Some numerical schemes for solving the system of equations are compared and analyzed. Simulation and computation of the discretized model are supported by Matlab and C programming languages on a single processing unit. Some numerical results and analysis of the algorithms are presented in terms of informative presentation of tables, multiple graph and multidimensional visualization. As a conclusion, the integrated of three types mathematical modeling and the comparison of numerical performance indicates that the superior tool and analysis for solving the complete set of magnetic drug delivery system which give significant effects on the growth of the targeted cancer cell.

Keywords: mathematical modeling, visualization, PDE models, magnetic nanoparticle drug delivery model, drug release model, single cell effects, avascular tumor growth, numerical analysis

Procedia PDF Downloads 426

Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

Procedia PDF Downloads 102

Authors: Naoko Ono, Junko Kato

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According to the Ministry of Justice, 9,044,000 foreigners visited Japan in 2010. The number of foreign residents in Japan was over 2,134,000 at the end of 2010. Further, medical tourism has emerged as a new area of business. Against this background, language barriers put the health of foreigners in Japan at risk, because they have difficulty in accessing health care and communicating with medical professionals. Medical interpreting training is urgently needed in response to language problems resulting from the rapid increase in the number of foreign workers in Japan over recent decades. Especially, there is a growing need in medical settings in Japan to speak international languages for communication, with Tokyo selected as the host city of the 2020 Summer Olympics. Due to the limited number of practical activities on medical interpreting, it is difficult for learners to acquire the interpreting skills. In order to eliminate the shortcoming, a web-based English-Japanese medical interpreting training system was developed. We conducted a literature review to identify learning contents, core competencies for medical interpreters by using Pubmed, PsycINFO, Cochrane Library, and Google Scholar. Selected papers were investigated to find core competencies in medical interpreting. Eleven papers were selected through literature review indicating core competencies for medical interpreters. Core competencies in medical interpreting abstracted from the literature review, showed consistency in previous research whilst the content of the programs varied in domestic and international training programs for medical interpreters. Results of the systematic review indicated five core competencies: (a) maintaining accuracy and completeness; (b) medical terminology and understanding the human body; (c) behaving ethically and making ethical decisions; (d) nonverbal communication skills; and (e) cross-cultural communication skills. We developed an e-leaning program for training medical interpreters. A Web-based Medical Interpreter Training Program which cover these competencies was developed. The program included the following : online word list (Quizlet), allowing student to study online and on their smartphones; self-study tool (Quizlet) for help with dictation and spelling; word quiz (Quizlet); test-generating system (Quizlet); Interactive body game (BBC);Online resource for understanding code of ethics in medical interpreting; Webinar about non-verbal communication; and Webinar about incompetent vs. competent cultural care. The design of a virtual environment allows the execution of complementary experimental exercises for learners of medical interpreting and introduction to theoretical background of medical interpreting. Since this system adopts a self-learning style, it might improve the time and lack of teaching material restrictions of the classroom method. In addition, as a teaching aid, virtual medical interpreting is a powerful resource for the understanding how actual medical interpreting can be carried out. The developed e-learning system allows remote access, enabling students to perform experiments at their own place, without being physically in the actual laboratory. The web-based virtual environment empowers students by granting them access to laboratories during their free time. A practical example will be presented in order to show capabilities of the system. The developed web-based training program for medical interpreters could bridge the gap between medical professionals and patients with limited English proficiency.

Keywords: e-learning, language education, moodle, medical interpreting

Procedia PDF Downloads 357

Authors: Laurence Weinberg, Dominic Walpole, Dong-Kyu Lee, Michael D’Silva, Jian W. Chan, Lachlan F. Miles, Bradley Carp, Adam Wells, Tuck S. Ngun, Siven Seevanayagam, George Matalanis, Ziauddin Ansari, Rinaldo Bellomo, Michael Yii

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Background: There have been multiple recent advancements in the selection, optimization and management of cardiac surgical patients. However, there is limited data regarding the outcomes of nonagenarians undergoing cardiac surgery, despite this vulnerable cohort increasingly receiving these interventions. This study describes the patient characteristics, management and outcomes of a group of nonagenarians undergoing cardiac surgery in the context of contemporary peri-operative care. Methods: A retrospective observational study was conducted of patients 90 to 99 years of age (i.e., nonagenarians) who had undergone cardiac surgery requiring a classic median sternotomy (i.e., open-heart surgery). All operative indications were included. Patients who underwent minimally invasive surgery, transcatheter aortic valve implantation and thoracic aorta surgery were excluded. Data were collected from four hospitals in Victoria, Australia, over an 8-year period (January 2012 – December 2019). The primary objective was to assess six-month mortality in nonagenarians undergoing open-heart surgery and to evaluate the incidence and severity of postoperative complications using the Clavien-Dindo classification system. The secondary objective was to provide a detailed description of the characteristics and peri-operative management of this group. Results: A total of 12,358 adult patients underwent cardiac surgery at the study centers during the observation period, of whom 18 nonagenarians (0.15%) fulfilled the inclusion criteria. The median (IQR) [min-max] age was 91 years (90.0:91.8) [90-94] and 14 patients (78%) were men. Cardiovascular comorbidities, polypharmacy and frailty, were common. The median (IQR) predicted in-hospital mortality by EuroSCORE II was 6.1% (4.1-14.5). All patients were optimized preoperatively by a multidisciplinary team of surgeons, cardiologists, geriatricians and anesthetists. All index surgeries were performed on cardiopulmonary bypass. Isolated coronary artery bypass grafting (CABG) and CABG with aortic valve replacement were the most common surgeries being performed in four and five patients, respectively. Half the study group underwent surgery involving two or more major procedures (e.g. CABG and valve replacement). Surgery was undertaken emergently in 44% of patients. All patients except one experienced at least one postoperative complication. The most common complications were acute kidney injury (72%), new atrial fibrillation (44%) and delirium (39%). The highest Clavien-Dindo complication grade was IIIb occurring once each in three patients. Clavien-Dindo grade IIIa complications occurred in only one patient. The median (IQR) postoperative length of stay was 11.6 days (9.8:17.6). One patient was discharged home and all others to an inpatient rehabilitation facility. Three patients had an unplanned readmission within 30 days of discharge. All patients had follow-up to at least six months after surgery and mortality over this period was zero. The median (IQR) duration of follow-up was 11.3 months (6.0:26.4) and there were no cases of mortality observed within the available follow-up records. Conclusion: In this group of nonagenarians undergoing cardiac surgery, postoperative six-month mortality was zero. Complications were common but generally of low severity. These findings support carefully selected nonagenarian patients being offered cardiac surgery in the context of contemporary, multidisciplinary perioperative care. Further, studies are needed to assess longer-term mortality and functional and quality of life outcomes in this vulnerable surgical cohort.

Keywords: cardiac surgery, mortality, nonagenarians, postoperative complications

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Authors: Asiye Nisa Kartal

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An attempt to recognize the undiscovered bounds of Istiklal Street in Istanbul between its sensory experiences (intangible qualities) and physical setting (tangible qualities) could be taken as the first inspiration point for this study. ‘The dramatic physical changes’ and ‘their current impacts on sensory attributions’ of Istiklal Street have directed this study to consider the role of changing the physical layout on sensory dimensions which have a subtle but important role in the examination of urban places. The public places have always been subject to transformation, so in the last years, the changing socio-cultural structure, economic and political movements, law and city regulations, innovative transportation and communication activities have resulted in a controversial modification of Istanbul. And, as the culture, entertainment, tourism, and shopping focus of Istanbul, Istiklal Street has witnessed different changing stages within the last years. In this process, because of the projects being implemented, many buildings such as cinemas, theatres, and bookstores have restored, moved, converted, closed and demolished which have been significant elements in terms of the qualitative value of this area. And, the multi-layered socio-cultural, and architectural structure of Istiklal Street has been changing in a dramatical and controversial way. But importantly, while the physical setting of Istiklal Street has changed, the transformation has not been spatial, socio-cultural, economic; avoidably the sensory dimensions of Istiklal Street which have great importance in terms of intangible qualities of this area have begun to lose their distinctive features. This has created the challenge of this research. As the main hypothesis, this study claims that the physical transformations have led to change in the sensory characteristic of Istiklal Street, therefore the Sensescape of Istiklal Street deserve to be recorded, decoded and promoted as expeditiously as possible to observe the sensory reflections of physical transformations in this area. With the help of the method of ‘Sensewalking’ which is an efficient research tool to generate knowledge on sensory dimensions of an urban settlement, this study suggests way of ‘mapping’ to understand how do ‘changes of physical setting’ play role on ‘sensory qualities’ of Istiklal Street which have been changed or lost over time. Basically, this research focuses on the sensory mapping of Istiklal Street from the 1990s until today to picture, interpret, criticize the ‘sensory mapping of Istiklal Street in present’ and the ‘sensory mapping of Istiklal Street in past’. Through the sensory mapping of Istiklal Street, this study intends to increase the awareness about the distinctive sensory qualities of places. It is worthwhile for further studies that consider the sensory dimensions of places especially in the field of architecture.

Keywords: Istiklal street, sense, sensewalking, sensory mapping

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Authors: Giuliana Scuderi, Patrick Teuffel

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The proven vulnerability of the existing social housing building heritage to natural or induced earthquakes requires the development of new design concepts and conceptual method to preserve materials and object, at the same time providing new performances. An integrate intervention between civil engineering, building physics and architecture can convert the social housing districts from a critical part of the city to a strategic resource of revitalization. Referring to bio-mimicry principles the present research proposes a taxonomy with the exoskeleton of the insect, an external, light and resistant armour whose role is to protect the internal organs from external potentially dangerous inputs. In the same way, a “building exoskeleton”, acting from the outside of the building as an enclosing cage, can restore, protect and support the existing building, assuming a complex set of roles, from the structural to the thermal, from the aesthetical to the functional. This study evaluates the structural efficiency of shape memory alloys devices (SMADs) connecting the “building exoskeleton” with the existing structure to rehabilitate, in order to prevent the out-of-plane collapse of walls and for the passive dissipation of the seismic energy, with a calibrated operability in relation to the intensity of the horizontal loads. The two case studies of a masonry structure and of a masonry structure with concrete frame are considered, and for each case, a theoretical social housing building is exposed to earthquake forces, to evaluate its structural response with or without SMADs. The two typologies are modelled with the finite element program SAP2000, and they are respectively defined through a “frame model” and a “diagonal strut model”. In the same software two types of SMADs, called the 00-10 SMAD and the 05-10 SMAD are defined, and non-linear static and dynamic analyses, namely push over analysis and time history analysis, are performed to evaluate the seismic response of the building. The effectiveness of the devices in limiting the control joint displacements resulted higher in one direction, leading to the consideration of a possible calibrated use of the devices in the different walls of the building. The results show also a higher efficiency of the 00-10 SMADs in controlling the interstory drift, but at the same time the necessity to improve the hysteretic behaviour, to maximise the passive dissipation of the seismic energy.

Keywords: adaptive structure, biomimetic design, building exoskeleton, social housing, structural envelope, structural retrofitting

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Authors: Francesco Lubrano, Fabrizio Bertone, Federico Stirano

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Modern societies strongly depend on Critical Infrastructures (CI). Hospitals, power supplies, water supplies, telecommunications are just few examples of CIs that provide vital functions to societies. CIs like hospitals are very complex environments, characterized by a huge number of cyber and physical systems that are becoming increasingly integrated. Ensuring a high level of security within such critical infrastructure requires a deep knowledge of vulnerabilities, threats, and potential attacks that may occur, as well as defence and prevention or mitigation strategies. The possibility to remotely monitor and control almost everything is pushing the adoption of network-connected devices. This implicitly introduces new threats and potential vulnerabilities, posing a risk, especially to those devices connected to the Internet. Modern medical devices used in hospitals are not an exception and are more and more being connected to enhance their functionalities and easing the management. Moreover, hospitals are environments with high flows of people, that are difficult to monitor and can somehow easily have access to the same places used by the staff, potentially creating damages. It is therefore clear that physical and cyber threats should be considered, analysed, and treated together as cyber-physical threats. This means that an integrated approach is required. SAFECARE, an integrated cyber-physical security solution, tries to respond to the presented issues within healthcare infrastructures. The challenge is to bring together the most advanced technologies from the physical and cyber security spheres, to achieve a global optimum for systemic security and for the management of combined cyber and physical threats and incidents and their interconnections. Moreover, potential impacts and cascading effects are evaluated through impact propagation models that rely on modular ontologies and a rule-based engine. Indeed, SAFECARE architecture foresees i) a macroblock related to cyber security field, where innovative tools are deployed to monitor network traffic, systems and medical devices; ii) a physical security macroblock, where video management systems are coupled with access control management, building management systems and innovative AI algorithms to detect behavior anomalies; iii) an integration system that collects all the incoming incidents, simulating their potential cascading effects, providing alerts and updated information regarding assets availability.

Keywords: cyber security, defence strategies, impact propagation, integrated security, physical security

Procedia PDF Downloads 157

Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

Procedia PDF Downloads 61

Authors: Natarajan Ramasamy, Gurulingamurthy Haralur, Ramesh Nivarthu, Nikhil Kumar Singha

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Elastomers are polymeric materials with varied backbone architectures ranging from linear to dendrimeric structures and wide varieties of monomeric repeat units. These elastomers show strongly viscous and weakly elastic when it is not cross-linked. But when crosslinked, based on the extent the properties of these elastomers can range from highly flexible to highly stiff nature. Lightly cross-linked systems are well studied and reported. Understanding the nature of highly cross-linked rubber based upon chemical structure and architecture is critical for varieties of applications. One of the critical parameters is cross-link density. In the current work, we have studied the highly cross-linked state of linear, lightly branched to star-shaped branched elastomers and determined the cross-linked density by using different models. Change in hardness, shift in Tg, change in modulus and swelling behavior were measured experimentally as a function of the extent of curing. These properties were analyzed using varied models to determine cross-link density. We used hardness measurements to examine cure time. Hardness to the extent of curing relationship is determined. It is well known that micromechanical transitions like Tg and storage modulus are related to the extent of crosslinking. The Tg of the elastomer in different crosslinked state was determined by DMA, and based on plateau modulus the crosslink density is estimated by using Nielsen’s model. Usually for lightly crosslinked systems, based on equilibrium swelling ratio in solvent the cross link density is estimated by using Flory–Rhener model. When it comes to highly crosslinked system, Flory-Rhener model is not valid because of smaller chain length. So models based on the assumption of polymer as a Non-Gaussian chain like 1) Helmis–Heinrich–Straube (HHS) model, 2) Gloria M.gusler and Yoram Cohen Model, 3) Barbara D. Barr-Howell and Nikolaos A. Peppas model is used for estimating crosslink density. In this work, correction factors are determined to the existing models and based upon it structure-property relationship of highly crosslinked elastomers was studied.

Keywords: dynamic mechanical analysis, glass transition temperature, parts per hundred grams of rubber, crosslink density, number of networks per unit volume of elastomer

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Authors: Muhammad Khairi bin Sulaiman

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The utilization of Building Information Modelling (BIM) in the construction industry has provided an opportunity for designers in the Architecture, Engineering and Construction (AEC) industry to proceed from the conventional method of using manual drafting to a way that creates alternative designs quickly, produces more accurate, reliable and consistent outputs. By using BIM Software, designers can create digital content that manipulates the use of data using the parametric model of BIM. With BIM software, more alternative designs can be created quickly and design problems can be explored further to produce a better design faster than conventional design methods. Generally, BIM is used as a documentation mechanism and has not been fully explored and utilised its capabilities as a design tool. Relative to the current issue, Modular Coordination (MC) design as a sustainable design practice is encouraged since MC design will reduce material wastage through standard dimensioning, pre-fabrication, repetitive, modular construction and components. However, MC design involves a complex process of rules and dimensions. Therefore, a tool is needed to make this process easier. Since the parameters in BIM can easily be manipulated to follow MC rules and dimensioning, thus, the integration of BIM software with MC design is proposed for architects during the design stage. With this tool, there will be an improvement in acceptance and practice in the application of MC design effectively. Consequently, this study will analyse and explore the function and customization of BIM objects and the capability of BIM software to expedite the application of MC design during the design stage for architects. With this application, architects will be able to create building models and locate objects within reference modular grids that adhere to MC rules and dimensions. The parametric modeling capabilities of BIM will also act as a visual tool that will further enhance the automation of the 3-Dimensional space planning modeling process. (Method) The study will first analyze and explore the parametric modeling capabilities of rule-based BIM objects, which eventually customize a reference grid within the rules and dimensioning of MC. Eventually, the approach will further enhance the architect's overall design process and enable architects to automate complex modeling, which was nearly impossible before. A prototype using a residential quarter will be modeled. A set of reference grids guided by specific MC rules and dimensions will be used to develop a variety of space planning and configuration. With the use of the design, the tool will expedite the design process and encourage the use of MC Design in the construction industry.

Keywords: building information modeling, modular coordination, space planning, customization, BIM application, MC space planning

Procedia PDF Downloads 81

Authors: Tsang K. L. V., Lewis L. A., Griffith S., Tucker P.

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Background:  Many children with high incidence disabilities, such as autism spectrum disorder (ASD), struggle to participate in the community in a socially acceptable manner. There are limitations for clinical settings to provide natural, real-life scenarios for them to practice the life skills needed to meet their real-life challenges. Virtual reality (VR) offers potential solutions to resolve the existing limitations faced by clinicians to create simulated natural environments for their clients to generalize the facilitated skills. Research design: The research aimed to develop a prototype of an interactive VR system to provide realistic and immersive environments for clients to practice skills. The descriptive qualitative methodology is employed to design and develop the Artificial Interactive Reality Unified System (AIRUS) prototype, which provided insights on how to use advanced VR technology to create simulated real-life social scenarios and enable users to interact with the objects and people inside the virtual environment using natural eye-gazes, hand and body movements. The eye tracking (e.g., selective or joint attention), hand- or body-tracking (e.g., repetitive stimming or fidgeting), and facial tracking (e.g., emotion recognition) functions allowed behavioral data to be captured and managed in the AIRUS architecture. Impact of project: Instead of using external controllers or sensors, hand tracking software enabled the users to interact naturally with the simulated environment using daily life behavior such as handshaking and waving to control and interact with the virtual objects and people. The AIRUS protocol offers opportunities for breakthroughs in future VR-based psychosocial assessment and intervention in occupational therapy. Implications for future projects: AI technology can allow more efficient data capturing and interpretation of object identification and human facial emotion recognition at any given moment. The data points captured can be used to pinpoint our users’ focus and where their interests lie. AI can further help advance the data interpretation system.

Keywords: occupational therapy, psychosocial assessment and intervention, simulated interactive environment, virtual reality

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Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

Procedia PDF Downloads 142

Authors: Smita Singh

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Objective: The Faculty of Chemistry Education at Humboldt University has developed ‘Studium’, a web application designed to enhance long-term self-regulated learning (SRL) and academic achievement. Leveraging advanced generative AI, ‘Studium’ offers a dynamic and adaptive educational experience tailored to individual learning preferences and languages. The application includes evolving tools for personalized notetaking from preferred sources, customizable presentation capabilities, and AI-assisted guidance from academic documents or textbooks. It also features workflow automation and seamless integration with collaborative platforms like Miro, powered by AI. This study aims to propose a model that combines generative AI with traditional features and customization options, empowering students to create personalized learning environments that effectively address the challenges of SRL. Method: To achieve this, the study included graduate and undergraduate students from diverse subject streams, with 15 participants each from Germany and India, ensuring a diverse educational background. An exploratory design was employed using a speed dating method with enactment, where different scenario sessions were created to allow participants to experience various features of ‘Studium’. The session lasted for 50 minutes, providing an in-depth exploration of the platform's capabilities. Participants interacted with Studium’s features via Zoom conferencing and were then engaged in semi-structured interviews lasting 10-15 minutes to gain deeper insights into the effectiveness of ‘Studium’. Additionally, online questionnaire surveys were conducted before and after the session to gather feedback and evaluate satisfaction with self-regulated learning (SRL) after using ‘Studium’. The response rate of this survey was 100%. Results: The findings of this study indicate that students widely acknowledged the positive impact of ‘Studium’ on their learning experience, particularly its adaptability and intuitive design. They expressed a desire for more tools like ‘Studium’ to support self-regulated learning in the future. The application significantly fostered students' independence in organizing information and planning study workflows, which in turn enhanced their confidence in mastering complex concepts. Additionally, ‘Studium’ promoted strategic decision-making and helped students overcome various learning challenges, reinforcing their self-regulation, organization, and motivation skills. Conclusion: This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like “Studium” can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners. This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like ‘Studium’ can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners.

Keywords: self-regulated learning (SRL), generative AI, AI-assisted educational platforms

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Authors: Andrei Bejan, Luminita Marin, Dalila Belei

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Phenothiazine with electron-rich nitrogen and sulfur heteroatoms has a high electron-donating ability which promotes a good conjugation and therefore low band-gap with consequences upon charge carrier mobility improving and shifting of light emission in visible domain. Moreover, its non-planar butterfly conformation inhibits molecular aggregation and thus preserves quite well the fluorescence quantum yield in solid state compared to solution. Therefore phenothiazine and its derivatives are promising hole transport materials for use in organic electronic and optoelectronic devices as light emitting diodes, photovoltaic cells, integrated circuit sensors or driving circuits for large area display devices. The objective of this paper was to obtain a series of new phenothiazine derivatives by introduction of different electron withdrawing substituents as formyl, carboxyl and cyanoacryl units in order to create a push pull system which has potential to improve the electronic and optical properties. Bromine atom was used as electrono-donor moiety to extend furthermore the existing conjugation. The understudy compounds were structural characterized by FTIR and 1H-NMR spectroscopy and single crystal X-ray diffraction. Besides, the single crystal X-ray diffraction brought information regarding the supramolecular architecture of the compounds. Photophysical properties were monitored by UV-vis and photoluminescence spectroscopy, while the electrochemical behavior was established by cyclic voltammetry. The absorption maxima of the studied compounds vary in a large range (322-455 nm), reflecting the different electronic delocalization degree, depending by the substituent nature. In a similar manner, the emission spectra reveal different color of emitted light, a red shift being evident for the groups with higher electron withdrawing ability. The emitted light is pure and saturated for the compounds containing strong withdrawing formyl or cyanoacryl units and reach the highest quantum yield of 71% for the compound containing bromine and cyanoacrilic units. Electrochemical study show reversible oxidative and reduction processes for all the compounds and a close correlation of the HOMO-LUMO band gap with substituent nature. All these findings suggest the obtained compounds as promising materials for optoelectronic devices.

Keywords: electrochemical properties, phenothiazine derivatives, photoluminescence, quantum yield

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Authors: Domenica Bona

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Colin Chant and David Goodman argue that historians of Chinese pre-industrial cities tend to underestimate revolutions and overestimate cyclic patterns: periods of peace and prosperity in the earl part of each d nast , followed b peasants’ rebellions and upheavals. Boyd described these cyclic patterns as part of the background of Chinese town planning and architecture. Thus old ideals of city planning-square plan, southward orientation and a palace along the central axis - are revived again and again in the ascendant phases of several d nastic c cles (e.g. Chang’an, Kaifen, and Beijing). Along this line of thought, m paper questions the relationship between the “magic square rule” and modern Chinese urban- planning. As a matter of fact, the classical theme of “cosmic Taoist urbanism” is still a reference for planning cities and new urban developments, whenever there is the intention to express nationalist ideals and “cultural straightforwardness.” Besides, some case studies can be related to “modern d nasties”: the first Republic under the Kuo Min Tang, the red People’s Republic and the post-Maoist open country of Deng Xiao Ping. Considering the project for the new capital of Nanjing in the Thirties, Beijing’s Tianan Men area in the ifties, and Shenzhen’s utian CBD in late 20th century, I argue that cyclic patterns are still in place, though with deformations related to westernization, private interests and lack of spirituality. How far new Chinese cities are - or simply seem to be - westernized? Symbolism, invisible frameworks, repeating features and behavioural patterns make urban China just “superficiall” western. This can be well noticed in cities previousl occupied b foreigners, like Hong Kong, or in newly founded ones, like Shenzhen, where both Asians and non-Asian people can feel the gender-shift from New-York-like landscapes to something else. Current planning in main metropolitan areas shows a blurred relationship between public policies and private investments: two levels of decisions and actions, one addressing the larger scale and infrastructures, the other concerning the micro scale and development of single plots. While zoning is instrumental in this process, master plans are often laid out over a very poor cartography, so much that any relation between the formal characters of new cities and the centuries-old structure of the related territory gets lost.

Keywords: China, contemporary cities, cultural heritage, shenzhen, urban planning

Procedia PDF Downloads 356

Authors: Esshili Awatef, Manitz Marie-Pierre, Eßlinger Manuela, Gerhardt Alexandra, Plümper Jennifer, Wachholz Simone, Friebe Astrid, Juckel Georg

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Maternal immune activation (MIA) resulting from maternal viral infection during pregnancy is a known risk factor for schizophrenia. The neural mechanisms by which maternal infections increase the risk for schizophrenia remain unknown, although the prevailing hypothesis argues that an activation of the maternal immune system induces changes in the maternal-fetal environment that might interact with fetal brain development. It may lead to an activation of fetal microglia inducing long-lasting functional changes of these cells. Based on post-mortem analysis showing an increased number of activated microglial cells in patients with schizophrenia, it can be hypothesized that these cells contribute to disease pathogenesis and may actively be involved in gray matter loss observed in such patients. In the present study, we hypothesize that prenatal treatment with the inflammatory agent Poly(I:C) during embryogenesis at contributes to microglial activation in the offspring, which may, therefore, represent a contributing factor to the pathogenesis of schizophrenia and underlines the need for new pharmacological treatment options. Pregnant rats were treated with intraperitoneal injections a single dose of Poly(I:C) or saline on gestation day 17. Brains of control and Poly(I:C) offspring, were removed and into 20-μm-thick coronal sections were cut by using a Cryostat. Brain slices were fixed and immunostained with ba1 antibody. Subsequently, Iba1-immunoreactivity was detected using a secondary antibody, goat anti-rabbit. The sections were viewed and photographed under microscope. The immunohistochemical analysis revealed increases in microglia cell number in the prefrontal cortex, in offspring of poly(I:C) treated-rats as compared to the controls injected with NaCl. However, no significant differences were observed in microglia activation in the cerebellum among the groups. Prenatal immune challenge with Poly(I:C) was able to induce long-lasting changes in the offspring brains. This lead to a higher activation of microglia cells in the prefrontal cortex, a brain region critical for many higher brain functions, including working memory and cognitive flexibility. which might be implicated in possible changes in cortical neuropil architecture in schizophrenia. Further studies will be needed to clarify the association between microglial cells activation and schizophrenia-related behavioral alterations.

Keywords: Microglia, neuroinflammation, PolyI:C, schizophrenia

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Authors: Edward Shizha, Edward Makwarimba

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This literature review explores current research on the educational strengths and barriers of newcomer and refugee youth in Canada. Canada’s shift in immigration policy in the past three decades, from Europe to Asian and African countries as source continents of recent immigrants to Canada, has tremendously increased the ethnic, linguistic, cultural and religious diversity of the population, including that of students in its education system. Over 18% of the country’s population was born in another country, of which 70% are visible minorities. There has been an increase in admitted immigrants and refugees, with a total of 226,203 between July 2020 and June 2021. Newcomer parents and their children in all major destination countries, including Canada, face tremendous challenges, including racism and discrimination, lack of English language skills, poverty, income inequality, unemployment, and underemployment. They face additional challenges, including discrimination against those who cannot speak the official languages, English or French. The severity of the challenges depends on several intersectional factors, including immigrant status (asylum seeker, refugee, or immigrant), age, gender, level of education and others. Through the lens of intersectionality as an explanatory perspective, this literature review examines the educational attainment and outcomes of newcomer and refugee youth in Canada in order to understand their educational needs, educational barriers and strengths. Newcomer youths’ experiences are shaped by numerous intersectional and interconnected sociocultural, sociopolitical, and socioeconomic factors—including gender, migration status, racialized status, ethnicity, socioeconomic class, sexual minority status, age, race—that produce and perpetuate their disadvantage. According to research, immigrants and refugees from visible minority ethnic backgrounds experience exclusions more than newcomers from other backgrounds and groups from the mainstream population. For many immigrant parents, migration provides financial and educational opportunities for their children. Yet, when attending school, newcomer and refugee youth face unique challenges related to racism and discrimination, negative attitudes and stereotypes from teachers and other school authorities, language learning and proficiency, differing levels of acculturation, and different cultural views of the role of parents in relation to teachers and school, and unfamiliarity with the social or school context in Canada. Recognizing discrepancies in educational attainment of newcomer and refugee youth based on their race and immigrant status, the paper develops insights into existing research and data gaps related to educational strengths and challenges for visible minority newcomer youth in Canada. The paper concludes that the educational successes or failures of the newcomer and refugee youth and their settlement and integration into the school system in Canada may depend on where their families settle, the attitudes of the host community and the school officials (teachers, guidance counsellors and school administrators) after-school support programs and their own set of coping mechanisms. Conceivably a unique approach to after-school programming should provide learning supports and opportunities that consider newcomer and refugee youth’s needs, experiences, backgrounds and circumstances. This support is likely to translate into significant academic and psychological well-being of newcomer students.

Keywords: deficit discourse, discrimination, educational outcomes, newcomer and refugee youth, racism, strength-based approach, whiteness

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: M. Kharrat, G. Moreau, Z. Aboura

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The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

Procedia PDF Downloads 152

Authors: Sumeyra Karatas, Veysel Karatas, Reyhan Safak, Gamze Bulut-Ozturk, Ozgul Kartal

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Productive struggle entails a student's cognitive exertion to comprehend mathematical concepts and uncover solutions not immediately apparent. The significance of productive struggle in learning mathematics is accentuated by influential educational theorists, emphasizing its necessity for learning mathematics with understanding. Consequently, supporting productive struggle in learning mathematics is recognized as a high-leverage and effective mathematics teaching practice. In this study, the investigation into the role of productive struggle in learning mathematics led to the development of a comprehensive rubric for productive struggle pedagogy through an exhaustive literature review. The rubric consists of eight primary criteria and 37 sub-criteria, providing a detailed description of teacher actions and pedagogical choices that foster students' productive struggles. These criteria encompass various pedagogical aspects, including task design, tool implementation, allowing time for struggle, posing questions, scaffolding, handling mistakes, acknowledging efforts, and facilitating discussion/feedback. Utilizing this rubric, a team of researchers and teachers designed eight 90-minute lesson plans, employing a productive struggle pedagogy, for a two-week unit on solving systems of linear equations. Simultaneously, another set of eight lesson plans on the same topic, featuring identical content and problems but employing a traditional lecture-and-practice model, was designed by the same team. The objective was to assess the impact of supporting productive struggle on students' mathematics learning, defined by the strands of mathematical proficiency. This quasi-experimental study compares the control group, which received traditional lecture- and practice instruction, with the treatment group, which experienced a productive struggle in pedagogy. Sixty-six 10th and 11th-grade students from two algebra classes, taught by the same teacher at a high school, underwent either the productive struggle pedagogy or lecture-and-practice approach over two-week eight 90-minute class sessions. To measure students' learning, an assessment was created and validated by a team of researchers and teachers. It comprised seven open-response problems assessing the strands of mathematical proficiency: procedural and conceptual understanding, strategic competence, and adaptive reasoning on the topic. The test was administered at the beginning and end of the two weeks as pre-and post-test. Students' solutions underwent scoring using an established rubric, subjected to expert validation and an inter-rater reliability process involving multiple criteria for each problem based on their steps and procedures. An analysis of covariance (ANCOVA) was conducted to examine the differences between the control group, which received traditional pedagogy, and the treatment group, exposed to the productive struggle pedagogy, on the post-test scores while controlling for the pre-test. The results indicated a significant effect of treatment on post-test scores for procedural understanding (F(2, 63) = 10.47, p < .001), strategic competence (F(2, 63) = 9.92, p < .001), adaptive reasoning (F(2, 63) = 10.69, p < .001), and conceptual understanding (F(2, 63) = 10.06, p < .001), controlling for pre-test scores. This demonstrates the positive impact of supporting productive struggle in learning mathematics. In conclusion, the results revealed the significance of the role of productive struggle in learning mathematics. The study further explored the practical application of productive struggle through the development of a comprehensive rubric describing the pedagogy of supporting productive struggle.

Keywords: effective mathematics teaching practice, high school algebra, learning mathematics, productive struggle

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Authors: Donghyun Lee, Cam Nguyen

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Multi-band systems offer a great deal of benefit in modern communication and radar systems. In particular, multi-band antenna-array radar systems with their extended frequency diversity provide numerous advantages in detection, identification, locating and tracking a wide range of targets, including enhanced detection coverage, accurate target location, reduced survey time and cost, increased resolution, improved reliability and target information. An accurate calibration is a critical issue in antenna array systems. The amplitude and phase errors in multi-band and multi-polarization antenna array transceivers result in inaccurate target detection, deteriorated resolution and reduced reliability. Furthermore, the digital beam former without the RF domain phase-shifting is less immune to unfiltered interference signals, which can lead to receiver saturation in array systems. Therefore, implementing integrated front-end architecture, which can support calibration function with low insertion and filtering function from the farthest end of an array transceiver is of great interest. We report a dual K/Ka-band T/R/Calibration switch module with quasi-elliptic dual-bandpass filtering function implementing a Q-enhanced metamaterial transmission line. A unique dual-band frequency response is incorporated in the reception and calibration path of the proposed switch module utilizing the composite right/left-handed meta material transmission line coupled with a Colpitts-style negative generation circuit. The fabricated fully integrated T/R/Calibration switch module in 0.18-μm BiCMOS technology exhibits insertion loss of 4.9-12.3 dB and isolation of more than 45 dB in the reception, transmission and calibration mode of operation. In the reception and calibration mode, the dual-band frequency response centered at 24.5 and 35 GHz exhibits out-of-band rejection of more than 30 dB compared to the pass bands below 10.5 GHz and above 59.5 GHz. The rejection between the pass bands reaches more than 50 dB. In all modes of operation, the IP1-dB is between 4 and 11 dBm. Acknowledgement: This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: microwaves, millimeter waves, T/R switch, wireless communications, wireless communications

Procedia PDF Downloads 156

Authors: Kuniaki Kudo, Raviraj Solanki, Kaushal Patel, Yash Virani

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This research mainly concerns optimizing UI test automation for large-scale web applications. The test target application is the HHAexchange homecare management WEB application that seamlessly connects providers, state Medicaid programs, managed care organizations (MCOs), and caregivers through one platform with large-scale functionalities. This study focuses on user interface automation testing for the WEB application. The quality assurance team must execute many manual users interface test cases in the development process to confirm no regression bugs. The team automated 346 test cases; the UI automation test execution time was over 17 hours. The business requirement was reducing the execution time to release high-quality products quickly, and the quality assurance automation team modernized the test automation framework to optimize the execution time. The base of the WEB UI automation test environment is Selenium, and the test code is written in Python. Adopting a compilation language to write test code leads to an inefficient flow when introducing scalability into a traditional test automation environment. In order to efficiently introduce scalability into Test Automation, a scripting language was adopted. The scalability implementation is mainly implemented with AWS's serverless technology, an elastic container service. The definition of scalability here is the ability to automatically set up computers to test automation and increase or decrease the number of computers running those tests. This means the scalable mechanism can help test cases run parallelly. Then test execution time is dramatically decreased. Also, introducing scalable test automation is for more than just reducing test execution time. There is a possibility that some challenging bugs are detected by introducing scalable test automation, such as race conditions, Etc. since test cases can be executed at same timing. If API and Unit tests are implemented, the test strategies can be adopted more efficiently for this scalability testing. However, in WEB applications, as a practical matter, API and Unit testing cannot cover 100% functional testing since they do not reach front-end codes. This study applied a scalable UI automation testing strategy to the large-scale homecare management system. It confirmed the optimization of the test case execution time and the detection of a challenging bug. This study first describes the detailed architecture of the scalable test automation environment, then describes the actual performance reduction time and an example of challenging issue detection.

Keywords: aws, elastic container service, scalability, serverless, ui automation test

Procedia PDF Downloads 98

Authors: Mohamed Malek Khenissi, Mohamed Montassar Ben Slama, Anis Belhaj Mohamed, Moncef Saidi

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Northern Tunisia is well known by its different and complex structural and geological zones that have been the result of a geodynamic history that extends from the early Mesozoic era to the actual period. One of these zones is the salt province, where the Halokinesis process is manifested by a number of NE/SW salt structures such as Jebel Ech-Cheid which represents masses of materials characterized by a high plasticity and low density. The salt masses extrusions that have been developed due to an extension that started from the late Triassic to late Cretaceous. The evolution of salt bodies within sedimentary basins have not only contributed to modify the architecture of the basin, but it also has certain geochemical effects which touch mainly source rocks that surround it. It has been demonstrated that the presence of salt structures within sedimentary basins can influence its temperature distribution and thermal history. Moreover, it has been creating heat flux anomalies that may affect the maturity of organic matter and the timing of hydrocarbon generation. Field samples of the Bahloul source rock (Cenomanan-Tunonian) were collected from different sights from all around Ech Cheid salt structure and evaluated using Rock-eval pyrolysis and GC/MS techniques in order to assess the degree of maturity evolution and the heat flux anomalies in the different zones analyze. The Total organic Carbon (TOC) values range between 1 to 9% and the (Tmax) ranges between 424 and 445°C, also the distribution of the source rock biomarkers both saturated and aromatic changes in a regular fashions with increasing maturity and this are shown in the chromatography results such as Ts/(Ts+Tm) ratios, 22S/(22S+22R) values for C31 homohopanes, ββ/(ββ+αα)20R and 20S/(20S+20R) ratios for C29 steranes which gives a consistent maturity indications and assessment of the field samples. These analyses are carried to interpret the maturity evolution and the heat flux around Ech Cheid salt structure through the geological history. These analyses also aim to demonstrate that the salt structure can have a direct effect on the geothermal gradient of the basin and on the maturity of the Bahloul Formation source rock. The organic matter has reached different stages of thermal maturity, but delineate a general increasing maturity trend. Our study confirms that the J. Ech Cheid salt body have on the first hand: a huge influence on the local distribution of anoxic depocentre at least within Cenomanian-Turonian time. In the second hand, the thermal anomaly near the salt mass has affected the maturity of Bahloul Formation.

Keywords: Bahloul formation, depocentre, GC/MS, rock-eval

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Authors: David Shengelia, Giorgi Chichinadze, Tamara Tsutsunava, Giorgi Beridze, Irakli Javakhishvili

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The Loki pre-Alpine crystalline massif crops out within the Caucasus region. The massif basement is represented by the Upper Devonian gneissose quartz-diorites, the Lower-Middle Paleozoic metamorphic allochthonous complex, and different magmatites. Earlier, the metamorphic complex was considered as indivisible set represented by the series of different temperature metamorphits. The degree of metamorphism of separate parts of the complex is due to different formation conditions. This fact according to authors of the abstract was explained by the allochthonous-flaky structure of the complex. It was stated that the complex thrust over the gneissose quartz diorites before the intrusion of Sudetic granites. During the detailed mapping, the authors turned out that the metamorphism issues need to be reviewed and additional researches to be carried out. Investigations were accomplished by using the following methodologies: finding of key sections, a sampling of rocks, microscopic description of the material, analytical determination of elements in the rocks, microprobe analysis of minerals and new interpretation of obtained data. According to the author’s recent data within the massif four tectonic plates: Lower Gorastskali, Sapharlo-Lok-Jandari, Moshevani and “mélange” overthrust sheets have been mapped. They differ from each other by composition, the degree of metamorphism and internal structure. It is confirmed that the initial rocks of the tectonic plates formed in different geodynamic conditions during overthrusting due to tectonic compression form a thick tectonic sheet. Based on the detailed laboratory investigations additional mineral assemblages were established, temperature limits were specified, and a renewed trend of metamorphism facies and subfacies was elaborated. The results are the following: 1. The Lower Gorastskali overthrust sheet is a fragment of ophiolitic association corresponding to the Paleotethys oceanic crust. The main rock-forming minerals are carbonate, chlorite, spinel, epidote, clinoptilolite, plagioclase, hornblende, actinolite, hornblende, albite, serpentine, tremolite, talc, garnet, and prehnite. Regional metamorphism of rocks corresponds to the greenschist facies lowest stage. 2. The Sapharlo-Lok-Jandari overthrust sheet metapelites are represented by chloritoid, chlorite, phengite, muscovite, biotite, garnet, ankerite, carbonate, and quartz. Metabasites containing actinolite, chlorite, plagioclase, calcite, epidote, albite, actinolitic hornblende and hornblende are also present. The degree of metamorphism corresponds to the greenschist high-temperature chlorite, biotite, and low-temperature garnet subfacies. Later the rocks underwent the contact influence of Late Variscan granites. 3. The Moshevani overthrust sheet is represented mainly by metapelites and rarely by metabasites. Main rock-forming minerals of metapelites are muscovite, biotite, chlorite, quartz, andalusite, plagioclase, garnet and cordierite and of metabasites - plagioclase, green and blue-green hornblende, chlorite, epidote, actinolite, albite, and carbonate. Metamorphism level corresponds to staurolite-andalusite subfacies of staurolite facies and partially to facies of biotite muscovite gneisses and hornfelse facies as well. 4. The “mélange” overthrust sheet is built of different size rock fragments and blocks of Moshevani and Lower Gorastskali overthrust sheets. The degree of regional metamorphism of first and second overthrust sheets of the Loki massif corresponds to chlorite, biotite, and low-temperature garnet subfacies, but of the third overthrust sheet – to staurolite-andalusite subfacies of staurolite facies and partially to facies of biotite muscovite gneisses and hornfelse facies.

Keywords: regional metamorphism, crystalline massif, mineral assemblages, the Caucasus

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Authors: Ercan Kızılay, Mustafa Demi̇rel, Selçuk Coşkun

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Railway signaling systems consist of vital products that regulate railway traffic and provide safe route arrangements and maneuvers of trains. SIL 4 signal lamps are produced by many manufacturers today. There is a need for systems that enable these signal lamps to be controlled by commands from the interlocking. These systems should act as fail-safe and give error indications to the interlocking system when an unexpected situation occurs for the safe operation of railway systems from the RAMS perspective. In the past, driving and proving the lamp in relay-based systems was typically done via signaling relays. Today, the proving of lamps is done by comparing the current values read over the return circuit, the lower and upper threshold values. The purpose is an analog electronic object controller with the possibility of easy integration with vital systems and the signal lamp itself. During the study, the EN50126 standard approach was considered, and the concept, definition, risk analysis, requirements, architecture, design, and prototyping were performed throughout this study. FMEA (Failure Modes and Effects Analysis) and FTA (Fault Tree) Analysis) have been used for safety analysis in accordance with EN 50129. Concerning these analyzes, the 1oo2D reactive fail-safe hardware design of a controller has been researched. Electromagnetic compatibility (EMC) effects on the functional safety of equipment, insulation coordination, and over-voltage protection were discussed during hardware design according to EN 50124 and EN 50122 standards. As vital equipment for railway signaling, railway signal object controllers should be developed according to EN 50126 and EN 50129 standards which identify the steps and requirements of the development in accordance with the SIL 4(Safety Integrity Level) target. In conclusion of this study, an analog railway signal object controller, which takes command from the interlocking system, is processed in driver cards. Driver cards arrange the voltage level according to desired visibility by means of semiconductors. Additionally, prover cards evaluate the current upper and lower thresholds. Evaluated values are processed via logic gates which are composed as 1oo2D by means of analog electronic technologies. This logic evaluates the voltage level of the lamp and mitigates the risks of undue dimming.

Keywords: object controller, railway electronic, analog electronic, safety, railway signal

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Authors: S. Arias

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New housing developments and the technological changes that this implies, adapt the styles of living of its residents, as well as new family structures and forms of work due to the particular needs of a specific group of people which involves different techniques of dealing with, organize, equip and use a particular territory. Currently, own their own space is increasingly important and the cities are faced with the challenge of providing the opportunity for such demands, as well as energy, water and waste removal necessary in the process of construction and occupation of new human settlements. Until the day of today, not has failed to give full response to these demands and needs, resulting in cities that grow without control, badly used land, avenues and congested streets. Buildings and dwellings have an important impact on the environment and on the health of the people, therefore environmental quality associated with the comfort of humans to the sustainable development of natural resources. Applied to architecture, this concept involves the incorporation of new technologies in all the constructive process of a dwelling, changing customs of developers and users, what must be a greater effort in planning energy savings and thus reducing the emissions Greenhouse Gases (GHG) depending on the geographical location where it is planned to develop. Since the techniques of occupation of the territory are not the same everywhere, must take into account that these depend on the geographical, social, political, economic and climatic-environmental circumstances of place, which in modified according to the degree of development reached. In the analysis that must be undertaken to check the degree of sustainability of the place, it is necessary to make estimates of the energy used in artificial air conditioning and lighting. In the same way is required to diagnose the availability and distribution of the water resources used for hygiene and for the cooling of artificially air-conditioned spaces, as well as the waste resulting from these technological processes. Based on the results obtained through the different stages of the analysis, it is possible to perform an energy audit in the process of proposing recommendations of sustainability in architectural spaces in search of energy saving, rational use of water and natural resources optimization. The above can be carried out through the development of a sustainable building code in develop technical recommendations to the regional characteristics of each study site. These codes would seek to build bases to promote a building regulations applicable to new human settlements looking for is generated at the same time quality, protection and safety in them. This building regulation must be consistent with other regulations both national and municipal and State, such as the laws of human settlements, urban development and zoning regulations.

Keywords: building regulations, housing, sustainability, technology

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Authors: Gilberto Goracci, Fabio Curti

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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

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Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

Abstract:

Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

Abstract:

Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: Hao Huang

Abstract:

INTRODUCTION: The Association of American Colleges and Universities (AACU) recommends the development of ‘high-impact practices,’ in an effort to increase rates of student retention and student engagement at undergraduate institutions. To achieve these goals, the Scripps College Humanities Institute and HI Fellows Seminar not only featured distinguished academics presenting their scholarship about current immigration policy and its consequences in the USA and around the world but integrated socially significant community leaders and creative activists/artivists in public talks, student workshops and collaborative art events. Students participated in experiential learning that involved guest personal presentations and discussions, oral history interviews that applied standard oral history methodologies, detailed cultural documentation, collaborative artistic interventions, and weekly posts in Internet Digital Learning Environment Sakai collaborative course forums and regular responses to other students’ comments. Our teaching pedagogies addressed the four learning styles outlined in Kolb’s Learning Style Inventory. PROJECT DESCRIPTION: Over the academic year 2017-18, the Scripps College Humanities Institute and HI Fellows Seminar presented a Fall 2017 topic, ‘The World at Our Doorsteps: Immigration and Deportation in Los Angeles’. Our purpose was to address how current federal government anti-immigration measures have affected many students of color, some of whom are immigrants, many of whom are related to and are friends with people who are impacted by the attitudes as well as the practices of the U.S. Citizenship and Immigration Services. In Spring 2018, we followed with the topic, ‘Exclusive Nationalisms: Global Migration and Immigration’. This addresses the rise of white supremacists who have ascended to position of power worldwide, in America, Europe, Russia, and xenophobic nationalisms in China, Myanmar and the Philippines. Recent scholarship has suggested the existence of categories of refugees beyond the political or social, who fit into the more inclusive category of migrants. ASSESSMENT METHODOLOGIES: Assessment methodologies not only included qualitative student interviews and quantitative student evaluations in standard rubric format, but also Outcome Assessments, Formative Evaluations, and Outside Guest Teacher feedback. These indicated that the most effective educational practices involved collaborative inquiry in undergraduate research, community-based learning, and capstone projects. Assessments of E-portfolios, written and oral coursework, and final creative projects with associated 10-12 page analytic paper revealed that students developed their understanding of how government and social organizations work; they developed communication skills that enhanced working with others from different backgrounds; they developed their ability to thoughtfully evaluate their course performance by adopting reflective practices; they gained analytic and interpretive skills that encouraged self-confidence and self- initiative not only academically, but also with regards to independent projects. CONCLUSION: Most importantly, the Scripps Humanities Institute experiential learning project spurred on real-world actions by our students, such as a public symposium on how to cope with bigots, a student tutoring program for immigrant staff children, student negotiations with the administration to establish meaningful, sustainable diversity and inclusion programs on-campus. Activism is not only to be taught to and for our students– it has to be enacted by our students.

Keywords: immigration, migration, human rights, learning assessment

Procedia PDF Downloads 126