Search results for: safety training

Authors: Tao Song, Hao Cheng, Guangfeng Tian, Chuang Xu

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An autonomous emergency braking system is an advanced driving assistance system that enables vehicle collision avoidance and pedestrian collision avoidance to improve vehicle safety. At present, because the pedestrian target is small, and the mobility is large, the pedestrian AEB system is faced with more technical difficulties and higher functional requirements. In this paper, a method of pedestrian target selection based on a variable width funnel is proposed. Based on the current position and predicted position of pedestrians, the relative position of vehicle and pedestrian at the time of collision is calculated, and different braking strategies are adopted according to the hazard level of pedestrian collisions. In the CNCAP standard operating conditions, comparing the method of considering only the current position of pedestrians and the method of considering pedestrian prediction position, as well as the method based on fixed width funnel and variable width funnel, the results show that, based on variable width funnel, the choice of pedestrian target will be more accurate and the opportunity of the intervention of AEB system will be more reasonable by considering the predicted position of the pedestrian target and vehicle's lateral motion.

Keywords: automatic emergency braking system, pedestrian target selection, TTC, variable width funnel

Procedia PDF Downloads 153

Authors: Pallab Das, Nabam Zomleen

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Effective dissipation of lateral loads that are coming due to seismic force determines the strength, durability and safety concern of the structure. Masonry infill has high stiffness and strength capabilities which can be put into an effective utilization for lateral load dissipation by incorporating it into building construction, but masonry behaves in highly nonlinear manner, so it is highly important to find out generalized, yet a rational approach to determine its nonlinear behavior and failure mode and it’s response when it is incorporated into building. But most of the countries do not specify the procedure for design of masonry infill wall. Whereas, there are many analytical modeling method available in literature, e.g. equivalent diagonal strut method, finite element modeling etc. In this paper the masonry infill is modeled and 6-storey bare framed building and building with masonry infill is analyzed using SAP-200014 in order to find out inter-storey drift by time-history analysis and capacity curve by Pushover analysis. The analysis shows that, while, the structure is well within CP performance level for both the case, whereas, there is considerable reduction of inter-storey drift of about 28%, when the building is analyzed with masonry infill wall.

Keywords: capacity curve, masonry infill, nonlinear analysis, time history analysis

Procedia PDF Downloads 377

Authors: M. Kastek, M. Kowalski, M. Szustakowski, H. Polakowski, T. Sosnowski

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Development of highly efficient security systems is one of the most urgent topics for science and engineering. There are many kinds of threats and many methods of prevention. It is very important to detect a threat as early as possible in order to neutralize it. One of the very challenging problems is detection of dangerous objects hidden under human’s clothing. This problem is particularly important for safety of airport passengers. In order to develop methods and algorithms to detect hidden objects it is necessary to determine the thermal signatures of such objects of interest. The laboratory measurements were conducted to determine the thermal signatures of dangerous tools hidden under various clothes in different ambient conditions. Cameras used for measurements were working in spectral range 0.6-12.5 μm An infrared imaging Fourier transform spectroradiometer was also used, working in spectral range 7.7-11.7 μm. Analysis of registered thermograms and hyperspectral datacubes has yielded the thermal signatures for two types of guns, two types of knives and home-made explosive bombs. The determined thermal signatures will be used in the development of method and algorithms of image analysis implemented in proposed monitoring systems.

Keywords: hyperspectral detection, nultispectral detection, image processing, monitoring systems

Procedia PDF Downloads 341

Authors: Antonella D'Alessandro, Filippo Ubertini, Annibale Luigi Materazzi

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The progress of nanotechnology resulted in the development of new instruments in the field of civil engineering. In particular, the introduction of carbon nanofillers into construction materials can enhance their mechanical and electrical properties. In construction, concrete is among the most used materials. Due to the characteristics of its components and its structure, concrete is suitable for modification, at the nanometer level too. Moreover, to guarantee structural safety, it is desirable to achieve a widespread monitoring of structures. The ideal thing would be to realize structures able to identify their behavior modifications, states of incipient damage or conditions of possible risk for people. This paper presents a research work about novel cementitious composites with conductive carbon nanoinclusions able of monitoring their state of deformation, with particular attention to concrete. The self-sensing ability is achieved through the correlation between the variation of stress or strain and that of electrical resistance. Carbon nanofillers appear particularly suitable for such applications. Nanomodified concretes with different carbon nanofillers has been tested. The samples have been subjected to cyclic and dynamic loads. The experimental campaign shows the potentialities of this new type of sensors made of nanomodified concrete for diffuse Structural Health Monitoring.

Keywords: carbon nanofillers, cementitious nanocomposites, smart sensors, structural health monitoring.

Procedia PDF Downloads 330

Authors: Maedeh Gharazi

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Distinguishing proof of entrepreneurial open doors in the field of nutrition counseling is a focal issue in utilizing nutrition experts and addressing the needs of patients with chronic diseases better. To this end, this review has been directed keeping in mind the end goal to investigate the supply and interest patterns of diabetes sustenance advising as a fundamental stride toward recognizing the entrepreneurial open doors for nutrition advisors in Tehran, Iran. To execute this expressive overview concentrate on, a survey in light of Likert scale was sent via email to 100 dynamic experts in the field of nutrition counseling services in Tehran, of whom 52 reacted to its inquiries. At that point, the mean estimations of members' reactions were ascertained utilizing SPSS programming and contrasted to each other. The outcome acquired in view of members' reactions uncovered that the requirement for "healthful guiding as a treatment group" was basically not met in diverse age, training and salary gatherings of diabetic patients. Along these lines, nutrition counseling as a treatment group can be considered as a suitable field for entrepreneurial exercises.

Keywords: nutrition counseling, chronic diseases, diabetes, likert scale, SPSS programming

Procedia PDF Downloads 336

Authors: Ramon Santana

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The use of biometric identifiers in the field of information security, access control to resources, authentication in ATMs and banking among others, are of great concern because of the safety of biometric data. In the general architecture of a biometric system have been detected eight vulnerabilities, six of them allow obtaining minutiae template in plain text. The main consequence of obtaining minutia templates is the loss of biometric identifier for life. To mitigate these vulnerabilities several models to protect minutiae templates have been proposed. Several vulnerabilities in the cryptographic security of these models allow to obtain biometric data in plain text. In order to increase the cryptographic security and ease of reversibility, a minutiae templates protection model is proposed. The model aims to make the cryptographic protection and facilitate the reversibility of data using two levels of security. The first level of security is the data transformation level. In this level generates invariant data to rotation and translation, further transformation is irreversible. The second level of security is the evaluation level, where the encryption key is generated and data is evaluated using a defined evaluation function. The model is aimed at mitigating known vulnerabilities of the proposed models, basing its security on the impossibility of the polynomial reconstruction.

Keywords: fingerprint, template protection, bio-cryptography, minutiae protection

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

Procedia PDF Downloads 190

Authors: Mohamed Attia, Vissarion Papadopoulos

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There is no doubt that there is a continuous deterioration of structures as a result of multiple hazards which can be divided into natural hazards (e.g., earthquakes, floods, winds) and other hazards due to human behavior (e.g., ship collisions, excessive traffic, terrorist attacks). There have been numerous attempts to address the catastrophic consequences of these hazards and traditional solutions through structural design and safety factors within the design codes, but there has not been much research addressing solutions through the use of new materials that have high performance and can be more effective than usual materials such as reinforced concrete and steel. To illustrate the effect of one of the new high-performance materials, carbon nanotube-reinforced polymer (CNT/polymer) bearings with different weight fractions were simulated as structural components of seismic isolation using ABAQUS in the connection between a bridge superstructure and the substructure. The results of the analyzes showed a significant increase in the time period of the bridge and a clear decrease in the bending moment at the base of the bridge piers at each time step of the time-history analysis in the case of using CNT/polymer bearings compared to the case of direct contact between the superstructure of the bridge and the substructure.

Keywords: seismic isolation, bridges damage, earthquake hazard, earthquake resistant structures

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Authors: Suleiman Musa, Shuaibu Sidi Safiyanu

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This study examined the digital preservation in Nigeria university libraries. A comparison between the university of Nigeria Nsukka (UNN) and Ahmadu Bello University Zaria (ABU, Zaria). The study utilized primary source of data obtained from two selected institution librarians. Finding revealed varying results in terms of skills acquired by librarians before and after digitization of the two institutions. The study reports that journals publication, text book, CD-ROMS, conference papers and proceedings, theses, dissertations and seminar papers are among the information resources available for digitization. The study further documents that copyright issue, power failure, and unavailability of needed materials are among the challenges facing the digitization of library of the institution. On the basis of the finding, the study concluded that digitization of library enhances efficiency in organization and retrieval of information services. The study therefore recommended that software should be upgraded with backup, training of the librarians on digital process, installation of antivirus and enhancement of technical collaboration between the library and MIS.

Keywords: digitalization, preservation, libraries, comparison

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Authors: Bayu Anggara, Arita Dewi Nugrahini, Didik Purwadi

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Dry sorting workstation needs labor to produce green tea in Gambung Tea Factory. Observation results show that there is labor who are not working at the moment and doing overtime jobs to meet production targets. The measurement of the level of labor effectiveness has never been done before. The purpose of this study is to determine the level of labor effectiveness and provide recommendations for improvement based on the results of the Pareto diagram and Ishikawa diagram. The method used to measure the level of labor effectiveness is Overall Labor Effectiveness (OLE). OLE had three indicators which are availability, performance, and quality. Recommendations are made based on the results of the Pareto diagram and Ishikawa diagram for indicators that do not meet world standards. Based on the results of the study, the OLE value was 68.19%. Recommendations given to improve labor performance are adding mechanics, rescheduling rest periods, providing special training for labor, and giving rewards to labor. Furthermore, the recommendations for improving the quality of labor are procuring water content measuring devices, create material standard policies, and rescheduling rest periods.

Keywords: Ishikawa diagram, labor effectiveness, OLE, Pareto diagram

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Hemadri Raut

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The city is a blend of the possible interactions of the built form, open spaces and their spatial organization layout in a geographical area to obtain an integrated pattern and environment with building facades being a dominant figure in the body of a city. Façades of each city have their own inherent properties responsive to the human behaviour, weather conditions, safety factors, material availability and composition along with the necessary aesthetics in coordination with adjacent building facades. Cities experience a huge transformation in the culture, lifestyle; socioeconomic conditions and technology nowadays because of the increasing population, urban sprawl, industrialization, contemporary architectural style, post-disaster consequences, war reconstructions, etc. This leads to the loss of the actual identity and architectural character of the city which in turn induces chaos and turbulence in the city. This paper attempts to identify and learn from the traditional elements that would make us more aware of the unique identity of the local communities in a city. It further studies the architectural style, color, shape, and design techniques through the case studies of contextual cities. The work focuses on the observation and transformation of the image of the city through these considerations in the designing of the facades to achieve the reconciliation of the people with urban spaces.

Keywords: building facades, city, community, heritage, identity, transformation, urban

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Authors: G. Infante Dennis, S. Balinas Elvira, C. Valencia Yolanda, Cunanan

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This paper examined the feed-backs, concerns, and insights of the teachers, supervisors, and teacher-trainers on the nature and qualities of the K-12 grade 8 design, content, approaches, and materials. Specifically, it sought to achieve the following objectives: 1) to describe the critical nature and qualities of the design, content, teaching-learning-and-evaluation approaches, and the materials to be utilized in the implementation of the grade 8 curriculum; 2) to extract the possible challenges relevant to the implementation of the design, content, teaching-learning-and-evaluation approaches, and the materials of the grade 8 curriculum in terms of the linguistic and technical competence of the teachers, readiness to implement, willingness to implement, and capability to make relevant adaptations; 3) to present essential demands on the successful and meaningful implementation of the grade 8 curriculum in terms of teacher-related factors, school-related factors, and student-related concerns.

Keywords: curriculum reforms, K-12, teacher-training, language teaching, learning

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Authors: Amanda Burrell, Tonia Gary, David Wright, Kumara Ward

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This paper explores the concept of academic identity as it relates to the lecture, in particular, the digitized lecture delivered to a camera, in the absence of a student audience. Many academics have the performance aspect of the role thrust upon them with little or no training. For the purpose of this study, we look at the performance of the academic identity and examine tailored film presence coaching for its contributions toward academic identity, specifically in relation to feelings of self-confidence and diminishment of discomfort or stage fright. The case is articulated through the lens of scholar-practitioners, using expert facilitated participatory action research. It demonstrates in our sample of experienced academics, all reported some feelings of uncertainty about presenting lectures to camera prior to coaching. We share how power poses and reframing fear, produced improvements in the ease and competency of all participants. We share exactly how this insight could be adapted for self-coaching by any academic when called to present to a camera and consider the relationship between this and academic identity.

Keywords: academic identity, digitized lecture, embodied learning, performance coaching

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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Traffic calming measures are different design features or strategies used to reduce the speed of a traveling vehicle on a particular road. These calming measures are common on rural roads of Oman. Some of these measures are road speed limits, vertical deflections, horizontal deflections, and road signs. In general, vertical deflections such as rumble strips, road studs (cat’s eye), speed tables, and speed humps are widely used. In this paper, as vehicle speeding is a major cause of road traffic crashes and high fatalities in Oman, the effectiveness of existing traffic calming measures at current locations on rural roads is assessed. The study was conducted on the rural roads of Dhofar Governorate, which is located in the south of Oman. A special focus is given to the calming measures implemented on the mountain roads of Dhofar. It is shown that vertical deflection calming measures are effective in reducing vehicle speed to 20 to 40 kph, depending on the vertical deflection type and spacing. Calming measures are also proposed at locations with a high probability of traffic crashes based on the number of traffic crashes at these locations, road type, and road geometry.

Keywords: road safety, rural roads, speed, traffic calming measures, traffic crash

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Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Nevine Henry Wasef

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The research discusses how Egyptian citizens perceive the performance of public sector officials, particularly the ethical values manifested in their behavior. It aims at answering the question of how Egyptian citizens’ perception of public officials affects citizens' trust in the government at large and the process of public service delivery specifically. The hypothesis is that public opinion about civil servants’ ethical values would be proportional to citizens’ trust in the government, which means that the more citizens regard administrators with high ethical standards, the higher trust in the government they would have and vice versa. The research would focus on the independent variable of trust in the government and the dependent variable of public perception of administrators’ ethical performance. The data would be collected through surveys designed to measure the public evaluation of public officials they are interacting with and the quality of services delivered to them. The study concludes that implementing ethical values in public administration has a crucial role in improving citizens’ trust in the government based on various case studies of governments that successfully adopted ethical training programs for their civil servants.

Keywords: trust, distrust, ethics, performance, integrity, values, public service

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Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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Authors: Freda E. Asem, R. D. Osei, D. B. Sarpong, J. K. Kuwornu

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While market access remains important, Ghana’s major handicap is her inability to sustain export growth on the open market. The causes of these could be attributed to inefficiency, lack of competitiveness and supply-side constraints. This study examined the challenges faced by smallholder horticultural farmers and how it relates to their technical efficiency. The study employed mixed methods to address the problem. Using the Millennium Development Account (MiDA) Farmer Based Organization survey data on farm households in 23 districts in Ghana, the study assessed the technical efficiency of smallholder horticultural farmers (taking into account production risks). Focus group discussions (FGDs) and in-depth interviews were also conducted on smallholder mango, pineapple, and chilli pepper farmers selected districts in Ghana. Results revealed the constraints faced by smallholder horticultural farmers to be marketing, training, funding, accessibility, and affordability of inputs, land, access to credit, and the disconnect between themselves and policy makers and implementers.

Keywords: productivity, gender, policy, efficiency, constraints

Procedia PDF Downloads 478

Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

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The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

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Authors: Muhammad Affan, Muhammad Ilyas Raza, Muhammad Harris Hashmi

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This work is attributed to the battery management unit design of student Satellites under Pakistan National Student Satellite Program (PNSSP). The aim has been to design a customized, low-cost, efficient, reliable and less-complex battery management scheme for the Satellite. Nowadays, Lithium Ion (Li-ion) batteries have become the de-facto standard for remote applications, especially for satellites. Li-ion cells are selected for secondary storage. The design also addresses Li-ion safety requirements by monitoring, balancing and protecting cells for safe and prolonged operation. Accurate voltage measurement of individual cells was the main challenge because all the actions triggered were based on the digital voltage measurement. For this purpose, a resistive-divider network is used to maintain simplicity and cost-effectiveness. To cater the problem of insufficient i/o pins on microcontroller, fast multiplexers and de-multiplexers were used. The discrepancy inherited in the given design is the dissipation of heat due to the dissipative resistors. However, it is still considered to be the optimum adoption, considering the simple and cost-effective nature of the passive balancing technique. Furthermore, it is a completely unique solution, customized to meet specific requirements. However, there is still an option for a more advanced and expensive design.

Keywords: satellite, battery module, passive balancing, dissipative

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Authors: Temitope Adewale, Oladapo Raji

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The study was designed to investigate the assessment of women's involvement in fishing. In order to give the study a direction, five research questions, as well as two hypotheses, were postulated, and a total of fifty (50) respondents each were selected from two local government areas for the study. This brings a total of one hundred (100) respondents selected from these local government areas in Lagos state. The outcome of the finding indicates that the percentage of the respondents’ age, 49% was between 31 and 35 years, 56% has a working experience of 6-10 years, 61% were married, 69% had secondary education as their educational level. However, findings show that socio-economic characteristics (x2 =15.504, df=6, p < 0.05) and income (r=0.83, p < 0.05) have a significant relationship on the fishing. It was established that the Women in Fish production/processing were faced with a lot of constraints such as high cost of inputs, inadequate electricity supply, lack of adequate capital, non-availability of the improved oven, non-availability of extension agents, inadequate fish landing, lack of transportation facilities, lack of training on financial management and loan acquisition which affected the level of output of women in Fish processing adversely.

Keywords: women, fishing, agriculture, Lagos

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Authors: Olga Castiblanco, Diego Vizcaíno

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Changing the traditional way of using experimentation in science teaching is quite a challenge. This research results talk about the characterization of physics experiments, not because of the topic it deals with, nor depending on the material used in the assemblies, but related to the possibilities it offers to enrich interaction in the classroom and thereby contribute to the development of scientific thinking skills. It is an action-research of type intervention in the classroom, with four courses of Physics Teaching undergraduate students from a public university in Bogotá. This process allows characterizing typologies such as discrepant, homemade, illustrative, research, recreational, crucial, mental, and virtual experiments. Students' production and researchers' reports on each class were the most relevant data. Content analysis techniques let to categorize the information and obtain results on the richness that each typology of experiment offers when interacting in the classroom. Results show changes in the comprehension of new teachers' role, far from being the possessor and transmitter of the truth. Besides, they understand strategies to engage students effectively since the class advances extending ideas, reflections, debates, and questions, either towards themselves, their classmates, or the teacher.

Keywords: physics teacher training, non-traditional experimentation, contextualized education, didactics of physics

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

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Authors: Rungpansa Noichan, Bart Julien Dewancker

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Access to the mass transit system, including rapid elevated and underground transport has become an outstanding issue for many cities. The mass transit access development should focus on behavioral responses of the different passenger groups. Moreover, it should consider about the appearance of intent-oriented action related accessibility that was explored from user’s satisfaction and attitudes related to services quality. This study aims to evaluate mass transit accessibility from passenger’s satisfaction, therefore, understanding the passenger’s attitudes about mass transit accessibility. The study area of this research is Bangkok Mass Transit system (BTS Skytrain) at Saphan Taksin station. 200 passengers at Saphan Taksin station were asked to rate the questionnaires survey that considers accessibility aspects of convenience, safety, feeder connectivity, and other dimensions. The survey was to find out the passenger attitudes and satisfaction for access to the BTS station, and the result shows several factors that influence the passenger choice of using the BTS as a public transportation mode and passenger’s opinion that needs to concern for the development mass transit system and accessibility performance.

Keywords: urban transportation, user satisfaction, accessibility, Bangkok mass transit

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Authors: Yue Wang

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Five years passed since the newest English curriculum reform policy was published in China, hand-wringing spread among teachers who accused that this is another 'Wearing New Shoes to Walk the Old Road' policy. This paper provides a thoroughly philosophical policy analysis of serious efforts that had been made to support this reform and reveals the hindrances that bridled the reform to yield the desired effect. Blame could be easily put on teachers for their insufficient pedagogical content knowledge, conservative resistance, and the handicaps of large class sizes and limited teaching times, and so on. However, the underlying causes for this implementation failure are the interrelated factors in the NCEE-centred education system, such as the reluctant from students, the lack of school and education bureau support, and insufficient teacher training. A further discussion of 2017 to 2020’s NCEE reform on English prompt new possibilities for the authentic pedagogical approach reform in secondary English classes. In all, the pedagogical approach reform at the secondary level is heading towards a brighter future with the initiation of new NCEE reform.

Keywords: English curriculum, failure, NCEE, new possibilities, pedagogical, policy analysis, reform

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Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is the coagulation using alum and poly aluminum chloride (PACL), and the value of usage per day is a hundred thousand baht. Therefore, determining the dosage of alum and PACL are the most important factors to be prescribed. Water production is economical and valuable. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for prediction chemical dose used to coagulation such as alum and PACL, which input data consists of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of Bangkhen water treatment plant (BKWTP) Metropolitan Waterworks Authority. The data collected from 1 January 2019 to 31 December 2019 cover changing seasons of Thailand. The input data of ANN is divided into three groups training set, test set, and validation set, which the best model performance with a coefficient of determination and mean absolute error of alum are 0.73, 3.18, and PACL is 0.59, 3.21 respectively.

Keywords: soft jar test, jar test, water treatment plant process, artificial neural network

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Authors: Mariam Adel Hakim Fouad

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This quantitative examine investigates innovative arts teachers' perceptions regarding the implementation of an Inclusive innovative Arts curriculum. The study employs a descriptive method utilizing a 5-point Likert scale questionnaire comprising 15 objects to acquire data from innovative arts educators. The Census, with a disproportionate stratified sampling approach, became utilized to pick out 226 teachers from five academic circuits (Circuit A, B, C, D & E) within Offinso Municipality, Ghana. The findings suggest that most innovative arts instructors maintain a wonderful belief in enforcing an inclusive, innovative arts curriculum. Wonderful perceptions and attitudes amongst teachers are correlated with improved scholar engagement and participation in class sports. This has a look at recommends organizing workshops and in-carrier schooling periods centered on inclusive innovative arts schooling for creative Arts instructors. Moreover, it shows that colleges of education and universities accountable for trainer schooling integrate foundational guides in creative arts and special schooling into their number one schooling teacher training packages.

Keywords: arts-in-health, evidence based medicine, arts for health, expressive arts therapiesarts, cultural heritage, digitalization, ICTarts, design, font, identity

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Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

Abstract:

Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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