Search results for: successful learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8980

Search results for: successful learning

2050 Deep-Learning to Generation of Weights for Image Captioning Using Part-of-Speech Approach

Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

Abstract:

Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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2049 Modeling and Implementation of a Hierarchical Safety Controller for Human Machine Collaboration

Authors: Damtew Samson Zerihun

Abstract:

This paper primarily describes the concept of a hierarchical safety control (HSC) in discrete manufacturing to up-hold productivity with human intervention and machine failures using a systematic approach, through increasing the system availability and using additional knowledge on machines so as to improve the human machine collaboration (HMC). It also highlights the implemented PLC safety algorithm, in applying this generic concept to a concrete pro-duction line using a lab demonstrator called FATIE (Factory Automation Test and Integration Environment). Furthermore, the paper describes a model and provide a systematic representation of human-machine collabora-tion in discrete manufacturing and to this end, the Hierarchical Safety Control concept is proposed. This offers a ge-neric description of human-machine collaboration based on Finite State Machines (FSM) that can be applied to vari-ous discrete manufacturing lines instead of using ad-hoc solutions for each line. With its reusability, flexibility, and extendibility, the Hierarchical Safety Control scheme allows upholding productivity while maintaining safety with reduced engineering effort compared to existing solutions. The approach to the solution begins with a successful partitioning of different zones around the Integrated Manufacturing System (IMS), which are defined by operator tasks and the risk assessment, used to describe the location of the human operator and thus to identify the related po-tential hazards and trigger the corresponding safety functions to mitigate it. This includes selective reduced speed zones and stop zones, and in addition with the hierarchical safety control scheme and advanced safety functions such as safe standstill and safe reduced speed are used to achieve the main goals in improving the safe Human Ma-chine Collaboration and increasing the productivity. In a sample scenarios, It is shown that an increase of productivity in the order of 2.5% is already possible with a hi-erarchical safety control, which consequently under a given assumptions, a total sum of 213 € could be saved for each intervention, compared to a protective stop reaction. Thereby the loss is reduced by 22.8%, if occasional haz-ard can be refined in a hierarchical way. Furthermore, production downtime due to temporary unavailability of safety devices can be avoided with safety failover that can save millions per year. Moreover, the paper highlights the proof of the development, implementation and application of the concept on the lab demonstrator (FATIE), where it is realized on the new safety PLCs, Drive Units, HMI as well as Safety devices in addition to the main components of the IMS.

Keywords: discrete automation, hierarchical safety controller, human machine collaboration, programmable logical controller

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2048 Machine Learning-Driven Prediction of Cardiovascular Diseases: A Supervised Approach

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

Abstract:

Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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2047 Comparative Analysis of Predictive Models for Customer Churn Prediction in the Telecommunication Industry

Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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2046 Lessons Learned from Push-Plus Implementation in Northern Nigeria

Authors: Aisha Giwa, Mohammed-Faosy Adeniran, Olufunke Femi-Ojo

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Four decades ago, the World Health Organization (WHO) launched the Expanded Programme on Immunization (EPI). The EPI blueprint laid out the technical and managerial functions necessary to routinely vaccinate children with a limited number of vaccines, providing protection against diphtheria, tetanus, whooping cough, measles, polio, and tuberculosis, and to prevent maternal and neonatal tetanus by vaccinating women of childbearing age with tetanus toxoid. Despite global efforts, the Routine Immunization (RI) coverage in two of the World Health Organization (WHO) regions; the African Region and the South-East Asia Region, still remains short of its targets. As a result, the WHO Regional Director for Africa declared 2012 as the year for intensifying RI in these regions and this also coincided with the declaration of polio as a programmatic emergency by the WHO Executive Board. In order to intensify routine immunization, the National Routine Immunization Strategic Plan (2013-2015) stated that its core priority is to ensure 100% adequacy and availability of vaccines for safe immunization. To achieve 100% availability, the “PUSH System” and then “Push-Plus” were adopted for vaccine distribution, which replaced the inefficient “PULL” method. The NPHCDA plays the key role in coordinating activities in area advocacy, capacity building, engagement of 3PL for the state as well as monitoring and evaluation of the vaccine delivery process. eHealth Africa (eHA) is a player as a 3PL service provider engaged by State Primary Health Care Boards (SPHCDB) to ensure vaccine availability through Vaccine Direct Delivery (VDD) project which is essential to successful routine immunization services. The VDD project ensures the availability and adequate supply of high-quality vaccines and immunization-related materials to last-mile facilities. eHA’s commitment to the VDD project saw the need for an assessment of the project vis-a-vis the overall project performance, evaluation of a process for necessary improvement suggestions as well as general impact across Kano State (Where eHA had transitioned to the state), Bauchi State (currently manage delivery to all LGAs except 3 LGAs currently being managed by the state), Sokoto State (eHA currently covers all LGAs) and Zamfara State (Currently, in-sourced and managed solely by the state).

Keywords: cold chain logistics, health supply chain system strengthening, logistics management information system, vaccine delivery traceability and accountability

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2045 KCBA, A Method for Feature Extraction of Colonoscopy Images

Authors: Vahid Bayrami Rad

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In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

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2044 Chinese Language Teaching as a Second Language: Immersion Teaching

Authors: Lee Bih Ni, Kiu Su Na

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This paper discusses the Chinese Language Teaching as a Second Language by focusing on Immersion Teaching. Researchers used narrative literature review to describe the current states of both art and science in focused areas of inquiry. Immersion teaching comes with a standard that teachers must reliably meet. Chinese language-immersion instruction consists of language and content lessons, including functional usage of the language, academic language, authentic language, and correct Chinese sociocultural language. Researchers used narrative literature reviews to build a scientific knowledge base. Researchers collected all the important points of discussion, and put them here with reference to the specific field where this paper is originally based on. The findings show that Chinese Language in immersion teaching is not like standard foreign language classroom; immersion setting provides more opportunities to teach students colloquial language than academic. Immersion techniques also introduce a language’s cultural and social contexts in a meaningful and memorable way. It is particularly important that immersion teachers connect classwork with real-life experiences. Immersion also includes more elements of discovery and inquiry based learning than do other kinds of instructional practices. Students are always and consistently interpreted the conclusions and context clues.

Keywords: a second language, Chinese language teaching, immersion teaching, instructional strategies

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2043 Community Integration: Post-Secondary Education (PSE) and Library Programming

Authors: Leah Plocharczyk, Matthew Conner

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This paper analyzes the relatively new trend of PSE programs which seek to provide education, vocational training, and a college experience to individuals with an intellectual and developmental disability (IDD). Specifically, the paper examines the degree of interaction between PSE programs and the libraries of their college campuses. Using ThinkCollege, a clearinghouse and advocate for PSE programs, the researchers identified 293 programs throughout the country. These were all contacted with an email survey asking them about the nature of their involvement, if any, with the academic libraries on their campus. Where indicated by the responses, the libraries of PSE programs were contacted for additional information about their programming. Responses to the survey questions were tabulated and analyzed quantitatively. Written comments were analyzed for themes which were then tabulated. This paper presents the results of this study. They show obvious preferences for library programming, such as group formal instruction, individual liaisons, embedded reference, and various instructional designs. These are discussed in terms of special education principles of mainstreaming, level of restriction, training demands and cost effectiveness. The work serves as a foundation for best practices that can advance the field.

Keywords: disability studies, instructional design, universal design for learning, assessment methodology

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2042 An Efficient Algorithm for Solving the Transmission Network Expansion Planning Problem Integrating Machine Learning with Mathematical Decomposition

Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

Abstract:

To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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2041 New Perspectives on Musician’s Focal Dystonia Causes and Therapy

Authors: Douglas Shabe

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The world of the performing musician is one of high pressure that comes from the expected high standards they have to live up to and that they expect from themselves. The pressure that musicians put themselves under can manifest itself in physical problems such as focal dystonia. Knowledge of the contributing factors and potential rehabilitation strategies cannot only give players hope for recovery but also the information to prevent it from happening in the first place. This dissertation presents a multiple case study of two performing brass musicians who developed focal dystonia of the embouchure, also known as embouchure dystonia, combined with an autoethnography of the author’s experience of battling embouchure dystonia and our attempts at recovery. Extensive research into the current state of focal dystonia research was done to establish a base of knowledge. That knowledge was used to develop interview questions for the two participants and interpret the findings of the qualitative data collected. The research knowledge, as well as the qualitative data from the case studies, was also used to interpret the author’s experience. The author determined that behavioral, environmental, and psychological factors were of prime importance in the subjects’ development of focal dystonia and that modifications of those factors are essential for the best chance at recovery.

Keywords: focal dystonia, embouchure dystonia, music teaching and learning, music education

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2040 Self-Regulation in Composition Writing: The Case of Variation of Self-Regulation Dispositions in Opinion Essay and Technical Writing

Authors: Dave Kenneth Tayao Cayado, Carlo P. Magno, Venice Cristine Dangaran

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The present study determines whether there will be differences in the self-regulation dispositions that learners utilize when writing different types of composition. There were 7 self-regulation factors that were used to develop a scale in this study such as memory strategy, goal setting, self-evaluation, seeking assistance, learning responsibility, environmental structuring, and organizing. The scale was made specific for writing a composition. The researcher-made scale was administered to 150 participants who all came from a university in the Philippines. The participants were asked to write two compositions namely opinion essay and research introduction/review of related literature. The zero-order correlation revealed that all the factors of self-regulation are correlated with one another. However, only seeking assistance and self-evaluation are correlated with opinion essay and technical writing is not correlated to any of the self-regulation factors. However, when path analysis was used, it was shown that seeking assistance can predict opinion essay scores whereas memory strategy, self-evaluation, and organizing can predict technical writing scores.

Keywords: opinion essay, self-regulation, technical writing, writing skills

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2039 Tasting Terroir: A Gourmet Adventure in Food and Wine Tourism

Authors: Sunita Boro, Saurabh Kumar Dixit

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Terroir, an intricate fusion of geography, climate, soil, and human expertise, has long been acknowledged as a defining factor in the character of wines and foods. This research embarks on an exploration of terroir's profound influence on gastronomic tourism, shedding light on the intricate interplay between the physical environment and culinary artistry. Delving into the intricate science of terroir, we scrutinize its role in shaping the sensory profiles of wines and foods, emphasizing the profound impact of specific regions on flavor, aroma, and texture. We deploy a multifaceted methodology, amalgamating sensory analysis, chemical profiling, geographical information systems, and qualitative interviews to unearth the nuanced nuances of terroir expression. Through an exhaustive review of the literature, we elucidate the historical roots of terroir, unveil the intricate cultural dimensions shaping it, and provide a comprehensive examination of prior studies in the field. Our findings underscore the pivotal role of terroir in promoting regional identities, enhancing the economic viability of locales, and attracting gastronomic tourists. The paper also dissects the marketing strategies employed to promote terroir-driven food and wine experiences. We elucidate the utilization of storytelling, branding, and collaborative endeavors in fostering a robust terroir-based tourism industry. This elucidates both the potential for innovation and the challenges posed by oversimplification or misrepresentation of terroir. Our research spotlights the intersection of terroir and sustainability, emphasizing the significance of environmentally conscious practices in terroir-driven productions. We discern the harmonious relationship between sustainable agriculture, terroir preservation, and responsible tourism, encapsulating the essence of ecological integrity in gastronomic tourism. Incorporating compelling case studies of regions and businesses excelling in the terroir-based tourism realm, we offer in-depth insights into successful models and strategies, with an emphasis on their replicability and adaptability to various contexts. Ultimately, this paper not only contributes to the scholarly understanding of terroir's role in the world of food and wine tourism but also provides actionable recommendations for stakeholders to leverage terroir's allure, preserve its authenticity, and foster sustainable and enriching culinary tourism experiences.

Keywords: terroir, food tourism, wine tourism, sustainability

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2038 Power Recovery from Waste Air of Mine Ventilation Fans Using Wind Turbines

Authors: Soumyadip Banerjee, Tanmoy Maity

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The recovery of power from waste air generated by mine ventilation fans presents a promising avenue for enhancing energy efficiency in mining operations. This abstract explores the feasibility and benefits of utilizing turbine generators to capture the kinetic energy present in waste air and convert it into electrical power. By integrating turbine generator systems into mine ventilation infrastructures, the potential to harness and utilize the previously untapped energy within the waste air stream is realized. This study examines the principles underlying turbine generator technology and its application within the context of mine ventilation systems. The process involves directing waste air from ventilation fans through specially designed turbines, where the kinetic energy of the moving air is converted into rotational motion. This mechanical energy is then transferred to connected generators, which convert it into electrical power. The recovered electricity can be employed for various on-site applications, including powering mining equipment, lighting, and control systems. The benefits of power recovery from waste air using turbine generators are manifold. Improved energy efficiency within the mining environment results in reduced dependence on external power sources and associated cost savings. Additionally, this approach contributes to environmental sustainability by utilizing a previously wasted resource for power generation. Resource conservation is further enhanced, aligning with modern principles of sustainable mining practices. However, successful implementation requires careful consideration of factors such as waste air characteristics, turbine design, generator efficiency, and integration into existing mine infrastructure. Maintenance and monitoring protocols are necessary to ensure consistent performance and longevity of the turbine generator systems. While there is an initial investment associated with equipment procurement, installation, and integration, the long-term benefits of reduced energy costs and environmental impact make this approach economically viable. In conclusion, the recovery of power from waste air from mine ventilation fans using turbine generators offers a tangible solution to enhance energy efficiency and sustainability within mining operations. By capturing and converting the kinetic energy of waste air into usable electrical power, mines can optimize resource utilization, reduce operational costs, and contribute to a greener future for the mining industry.

Keywords: waste to energy, wind power generation, exhaust air, power recovery

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2037 Involvement in Community Planning: The Case Study of Bang Nang Li Community, Samut Songkram Province, Thailand

Authors: Sakapas Saengchai, Vilasinee Jintalikhitdee, Mathinee Khongsatid, Nattapol Pourprasert

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This paper studied the participation of people of the five villages of Bang Nang Li Community in Ampawa District, Samut Songkram Province, in designing community planning. The population was 2,755 villagers from the 5 villages with 349 people sampled. The level of involvement was measured by using Likert Five Scale for: preparing readiness of local people in the community, providing information for community and self analysis and learning, designing goals and directions for community development, designing strategic plans for community projects, and operating according to the plans. All process items reported a medium level of involvement except the item of preparing readiness for local people that presented the highest mean score. A test of a correlation between personal factors and level of involvement in designing the community planning unveiled no correlation between gender, age and career. Contrarily, the findings revealed that the villagers’ educational level and community membership status had a correlation with their level of involvement in designing the community planning.

Keywords: community development, community planning, people participation, educational level

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2036 Layer-By-Layer Deposition of Poly (Amidoamine) and Poly (Acrylic Acid) on Grafted-Polylactide Nonwoven with Different Surface Charge

Authors: Sima Shakoorjavan, Mahdieh Eskafi, Dawid Stawski, Somaye Akbari

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In this study, poly (amidoamine) dendritic material (PAMAM) and poly (acrylic acid) (PAA) as polycation and polyanion were deposited on surface charged polylactide (PLA) nonwoven to study the relationship of dye absorption capacity of layered-PLA with the number of deposited layers. To produce negatively charged-PLA, acrylic acid (AA) was grafted on the PLA surface (PLA-g-AA) through a chemical redox reaction with the strong oxidizing agent. Spectroscopy analysis, water contact measurement, and FTIR-ATR analysis confirm the successful grafting of AA on the PLA surface through the chemical redox reaction method. In detail, an increase in dye absorption percentage by 19% and immediate absorption of water droplets ensured hydrophilicity of PLA-g-AA surface; and the presence of new carbonyl bond at 1530 cm-¹ and a wide peak of hydroxyl between 3680-3130 cm-¹ confirm AA grafting. In addition, PLA as linear polyester can undergo aminolysis, which is the cleavage of ester bonds and replacement with amid bonds when exposed to an aminolysis agent. Therefore, to produce positively charged PLA, PAMAM as amine-terminated dendritic material was introduced to PLA molecular chains at different conditions; (1) at 60 C for 0.5, 1, 1.5, 2 hours of aminolysis and (2) at room temperature (RT) for 1, 2, 3, and 4 hours of aminolysis. Weight changes and spectrophotometer measurements showed a maximum in weight gain graph and K/S value curve indicating the highest PAMAM attachment at 60 C for 1 hour and RT for 2 hours which is considered as an optimum condition. Also, the emerging new peak around 1650 cm-1 corresponding to N-H bending vibration and double wide peak at around 3670-3170 cm-1 corresponding to N-H stretching vibration confirm PAMAM attachment in selected optimum condition. In the following, regarding the initial surface charge of grafted-PLA, lbl deposition was performed and started with PAA or PAMAM. FTIR-ATR results confirm chemical changes in samples due to deposition of the first layer (PAA or PAMAM). Generally, spectroscopy analysis indicated that an increase in layer number costed dye absorption capacity. It can be due to the partial deposition of a new layer on the previously deposited layer; therefore, the available PAMAM at the first layer is more than the third layer. In detail, in the case of layer-PLA starting lbl with negatively charged, having PAMAM as the first top layer (PLA-g-AA/PAMAM) showed the highest dye absorption of both cationic and anionic model dye.

Keywords: surface modification, layer-by-layer technique, dendritic materials, PAMAM, dye absorption capacity, PLA nonwoven

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2035 Educational Knowledge Transfer in Indigenous Mexican Areas Using Cloud Computing

Authors: L. R. Valencia Pérez, J. M. Peña Aguilar, A. Lamadrid Álvarez, A. Pastrana Palma, H. F. Valencia Pérez, M. Vivanco Vargas

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This work proposes a Cooperation-Competitive (Coopetitive) approach that allows coordinated work among the Secretary of Public Education (SEP), the Autonomous University of Querétaro (UAQ) and government funds from National Council for Science and Technology (CONACYT) or some other international organizations. To work on an overall knowledge transfer strategy with e-learning over the Cloud, where experts in junior high and high school education, working in multidisciplinary teams, perform analysis, evaluation, design, production, validation and knowledge transfer at large scale using a Cloud Computing platform. Allowing teachers and students to have all the information required to ensure a homologated nationally knowledge of topics such as mathematics, statistics, chemistry, history, ethics, civism, etc. This work will start with a pilot test in Spanish and initially in two regional dialects Otomí and Náhuatl. Otomí has more than 285,000 speaking indigenes in Queretaro and Mexico´s central region. Náhuatl is number one indigenous dialect spoken in Mexico with more than 1,550,000 indigenes. The phase one of the project takes into account negotiations with indigenous tribes from different regions, and the Information and Communication technologies to deliver the knowledge to the indigenous schools in their native dialect. The methodology includes the following main milestones: Identification of the indigenous areas where Otomí and Náhuatl are the spoken dialects, research with the SEP the location of actual indigenous schools, analysis and inventory or current schools conditions, negotiation with tribe chiefs, analysis of the technological communication requirements to reach the indigenous communities, identification and inventory of local teachers technology knowledge, selection of a pilot topic, analysis of actual student competence with traditional education system, identification of local translators, design of the e-learning platform, design of the multimedia resources and storage strategy for “Cloud Computing”, translation of the topic to both dialects, Indigenous teachers training, pilot test, course release, project follow up, analysis of student requirements for the new technological platform, definition of a new and improved proposal with greater reach in topics and regions. Importance of phase one of the project is multiple, it includes the proposal of a working technological scheme, focusing in the cultural impact in Mexico so that indigenous tribes can improve their knowledge about new forms of crop improvement, home storage technologies, proven home remedies for common diseases, ways of preparing foods containing major nutrients, disclose strengths and weaknesses of each region, communicating through cloud computing platforms offering regional products and opening communication spaces for inter-indigenous cultural exchange.

Keywords: Mexicans indigenous tribes, education, knowledge transfer, cloud computing, otomi, Náhuatl, language

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2034 Solving of Types Mathematical Routine and Non-Routine Problems in Algebra

Authors: Verónica Díaz Quezada

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The importance given to the development of the problem solving skill and the requirement to solve problems framed in mathematical or real life contexts, in practice, they are not evidence in relation to the teaching of proportional variations. This qualitative and descriptive study aims to (1) to improve problem solving ability of high school students in Chile, (ii) to elaborate and describe a didactic intervention strategy based on learning situations in proportional variations, focused on solving types of routine problems of various contexts and non-routine problems. For this purpose, participant observation was conducted, test of mathematics problems and an opinion questionnaire to thirty-six high school students. Through the results, the highest academic performance is evidenced in the routine problems of purely mathematical context, realistic, fantasy context, and non-routine problems, except in the routine problems of real context and compound proportionality problems. The results highlight the need to consider in the curriculum different types of problems in the teaching of mathematics that relate the discipline to everyday life situations

Keywords: algebra, high school, proportion variations, nonroutine problem solving, routine problem solving

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2033 Knowledge Management (KM) Practices: A Study of KM Adoption among Doctors in Kuwait

Authors: B. Alajmi, L. Marouf, A. S. Chaudhry

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In recent years, increasing emphasis has been placed upon issues concerning the evaluation of health care. In this regard, knowledge management has also been considered an important component of the evaluation process. KM facilitates the transfer of existing knowledge or the development of new knowledge among healthcare staff and patients. This research aimed to examine how hospitals in Kuwait employ knowledge management practices, including capturing, sharing, and generating, and the perceived impact of KM practices on performance of hospitals in Kuwait. Through adopting a quantitative survey method with 277 sample of doctors, the study found that in terms of the three major knowledge management practices – knowledge capturing, sharing, and generating – the adoption of KM practices were rated very low in the sampled hospitals in Kuwait. Hospitals paid little attention to the main activities that support the transfer of expertise among doctors in hospitals. However, as predicted by previous studies, knowledge management practices were perceived to have an impact on hospitals’ performance. Through knowledge capturing, sharing, and generating, hospitals could improve the services they provide through documenting best practices, transforming their hospitals into learning organizations in which lessons learned are captured, stored, and made available for others to learn from.

Keywords: knowledge management, hospitals, knowledge management practices, knowledge management tools, performance

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2032 Gender Discrepancies in Current Pedagogical and Curricular Practices in EFL Higher Education Settings

Authors: Hamad Aldosari

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The purpose of this study is to investigate the status of sexism, or gender discrepancies, in current pedagogical and curricular practices in EFL learning higher education settings. Qualitative and quantitative analyses of both course contents and pedagogies in Saudi higher education institutions are to be discussed with reference to female/male topic presentation in dialogs and reading passages, sex-based activity types, stereotyped sex roles and the masculine generic conceptions of male superiority subliminally related in EFL curriculum and pedagogical practices, as well as the causes and effects of segregated language education practices in Saudi Arabia from a holistic vantage point of analysis. Analysis findings show that language educational practices including educational settings and segregation are gender-biased in attitude, but with regard to curriculum, sexism has not been traced. Findings also show that sexism is rampant due to socio-cultural aspects of language education rather than to religious reasons: a finding that seems to mirror the institutionalized unfair sex discrimination to the disadvantage of women in the Arabian societies at large.

Keywords: genderism, sex segregation, Saudi Arabia, EFL

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2031 Application of Natural Language Processing in Education

Authors: Khaled M. Alhawiti

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Reading capability is a major segment of language competency. On the other hand, discovering topical writings at a fitting level for outside and second language learners is a test for educators. We address this issue utilizing natural language preparing innovation to survey reading level and streamline content. In the connection of outside and second-language learning, existing measures of reading level are not appropriate to this errand. Related work has demonstrated the profit of utilizing measurable language preparing procedures; we expand these thoughts and incorporate other potential peculiarities to measure intelligibility. In the first piece of this examination, we join characteristics from measurable language models, customary reading level measures and other language preparing apparatuses to deliver a finer technique for recognizing reading level. We examine the execution of human annotators and assess results for our finders concerning human appraisals. A key commitment is that our identifiers are trainable; with preparing and test information from the same space, our finders beat more general reading level instruments (Flesch-Kincaid and Lexile). Trainability will permit execution to be tuned to address the needs of specific gatherings or understudies.

Keywords: natural language processing, trainability, syntactic simplification tools, education

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2030 The Effects of Lighting Environments on the Perception and Psychology of Consumers of Different Genders in a 3C Retail Store

Authors: Yu-Fong Lin

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The main purpose of this study is to explore the impact of different lighting arrangements that create different visual environments in a 3C retail store on the perception, psychology, and shopping tendencies of consumers of different genders. In recent years, the ‘emotional shopping’ model has been widely accepted in the consumer market; in addition to the emotional meaning and value of a product, the in-store ‘shopping atmosphere’ has also been increasingly regarded as significant. The lighting serves as an important environmental stimulus that influences the atmosphere of a store. Altering the lighting can change the color, the shape, and the atmosphere of a space. A successful retail lighting design can not only attract consumers’ attention and generate their interest in various goods, but it can also affect consumers’ shopping approach, behavior, and desires. 3C electronic products have become mainstream in the current consumer market. Consumers of different genders may demonstrate different behaviors and preferences within a 3C store environment. This study tests the impact of a combination of lighting contrasts and color temperatures in a 3C retail store on the visual perception and psychological reactions of consumers of different genders. The research design employs an experimental method to collect data from subjects and then uses statistical analysis adhering to a 2 x 2 x 2 factorial design to identify the influences of different lighting environments. This study utilizes virtual reality technology as the primary method by which to create four virtual store lighting environments. The four lighting conditions are as follows: high contrast/cool tone, high contrast/warm tone, low contrast/cool tone, and low contrast/warm tone. Differences in the virtual lighting and the environment are used to test subjects’ visual perceptions, emotional reactions, store satisfaction, approach-avoidance intentions, and spatial atmosphere preferences. The findings of our preliminary test indicate that female subjects have a higher pleasure response than male subjects in a 3C retail store. Based on the findings of our preliminary test, the researchers modified the contents of the questionnaires and the virtual 3C retail environment with different lighting conditions in order to conduct the final experiment. The results will provide information about the effects of retail lighting on the environmental psychology and the psychological reactions of consumers of different genders in a 3C retail store lighting environment. These results will enable useful practical guidelines about creating 3C retail store lighting and atmosphere for retailers and interior designers to be established.

Keywords: 3C retail store, environmental stimuli, lighting, virtual reality

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2029 Potentiality of a Community of Practice between Public Schools and the Private Sector for Integrating Sustainable Development into the School Curriculum

Authors: Aiydh Aljeddani, Fran Martin

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The critical time in which we live requires rethinking of many potential ways in order to make the concept of sustainability and its principles an integral part of our daily life. One of these potential approaches is how to attract community institutions, such as the private sector, to participate effectively in the sustainability industry by supporting public schools to fulfill their duties. A collaborative community of practice can support this purpose and can provide a flexible framework, which allows the members of the community to participate effectively. This study, conducted in Saudi Arabia, aimed to understand the process of a collaborative community of practice of involving the private sector as a member of this community to integrate the sustainability concept in school activities and projects. This study employed a qualitative methodology to understand this authentic and complex phenomenon. A case study approach, ethnography and some elements of action research were followed in this study. The methods of unstructured interviews, artifacts, observation, and teachers’ field notes were used to collect the data. The participants were three secondary teachers, twelve chief executive officers, and one school administrative officer. Certain contextual conditions, as shown by the data, should be taken into consideration when policy makers and school administrations in Saudi Arabia desire to integrate sustainability into school activities. The first of these was the acknowledgement of the valuable role of the members’ personality, efforts, abilities, and experiences, which played vital roles in integrating sustainability. Second, institutional culture, which was not expected to emerge as an important factor in this study, has a significant role in the integration of sustainability. Credibility among the members of the community towards the integration of the sustainability concept and its principles through school activities is another important condition. Fourth, some chief executive officers’ understanding of Corporate Social Responsibility (CSR) towards contribution to sustainability agenda was shallow and limited and this could impede the successful integration of sustainability. Fifth, a shared understanding between the members of the community about integrating sustainability was a vital condition in the integration process. The study also revealed that the integration of sustainability could not be an ongoing process if implemented in isolation of the other community institutions such as the private sector. The study finally offers a number of recommendations to improve on the current practices and suggests areas for further studies.

Keywords: community of practice, public schools, private sector, sustainable development

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2028 Image Captioning with Vision-Language Models

Authors: Promise Ekpo Osaine, Daniel Melesse

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Image captioning is an active area of research in the multi-modal artificial intelligence (AI) community as it connects vision and language understanding, especially in settings where it is required that a model understands the content shown in an image and generates semantically and grammatically correct descriptions. In this project, we followed a standard approach to a deep learning-based image captioning model, injecting architecture for the encoder-decoder setup, where the encoder extracts image features, and the decoder generates a sequence of words that represents the image content. As such, we investigated image encoders, which are ResNet101, InceptionResNetV2, EfficientNetB7, EfficientNetV2M, and CLIP. As a caption generation structure, we explored long short-term memory (LSTM). The CLIP-LSTM model demonstrated superior performance compared to the encoder-decoder models, achieving a BLEU-1 score of 0.904 and a BLEU-4 score of 0.640. Additionally, among the CNN-LSTM models, EfficientNetV2M-LSTM exhibited the highest performance with a BLEU-1 score of 0.896 and a BLEU-4 score of 0.586 while using a single-layer LSTM.

Keywords: multi-modal AI systems, image captioning, encoder, decoder, BLUE score

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2027 Integration of Technology into Nursing Education: A Collaboration between College of Nursing and University Research Center

Authors: Lori Lioce, Gary Maddux, Norven Goddard, Ishella Fogle, Bernard Schroer

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This paper presents the integration of technologies into nursing education. The collaborative effort includes the College of Nursing (CoN) at the University of Alabama in Huntsville (UAH) and the UAH Systems Management and Production Center (SMAP). The faculty at the CoN conducts needs assessments to identify education and training requirements. A team of CoN faculty and SMAP engineers then prioritize these requirements and establish improvement/development teams. The development teams consist of nurses to evaluate the models and to provide feedback and of undergraduate engineering students and their senior staff mentors from SMAP. The SMAP engineering staff develops and creates the physical models using 3D printing, silicone molds and specialized molding mixtures and techniques. The collaboration has focused on developing teaching and training, or clinical, simulators. In addition, the onset of the Covid-19 pandemic has intensified this relationship, as 3D modeling shifted to supplied personal protection equipment (PPE) to local health care providers. A secondary collaboration has been introducing students to clinical benchmarking through the UAH Center for Management and Economic Research. As a result of these successful collaborations the Model Exchange & Development of Nursing & Engineering Technology (MEDNET) has been established. MEDNET seeks to extend and expand the linkage between engineering and nursing to K-12 schools, technical schools and medical facilities in the region to the resources available from the CoN and SMAP. As an example, stereolithography (STL) files of the 3D printed models, along with the specifications to fabricate models, are available on the MEDNET website. Ten 3D printed models have been developed and are currently in use by the CoN. The following additional training simulators are currently under development:1) suture pads, 2) gelatin wound models and 3) printed wound tattoos. Specification sheets have been written for these simulations that describe the use, fabrication procedures and parts list. These specifications are available for viewing and download on MEDNET. Included in this paper are 1) descriptions of CoN, SMAP and MEDNET, 2) collaborative process used in product improvement/development, 3) 3D printed models of training and teaching simulators, 4) training simulators under development with specification sheets, 5) family care practice benchmarking, 6) integrating the simulators into the nursing curriculum, 7) utilizing MEDNET as a pandemic response, and 8) conclusions and lessons learned.

Keywords: 3D printing, nursing education, simulation, trainers

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2026 Ensuring Sustainable Urban Mobility in Indian Cities: Need for Creating People Friendly Roadside Public Spaces

Authors: Pushplata Garg

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Mobility, is an integral part of living and sustainability of urban mobility, is essential not only for, but also for addressing global warming and climate change. However, very little is understood about the obstacles/hurdles and likely challenges in the success of plans for sustainable urban mobility in Indian cities from the public perspective. Whereas some of the problems and issues are common to all cities, others vary considerably with financial status, function, the size of cities and culture of a place. Problems and issues similar in all cities relate to availability, efficiency and safety of public transport, last mile connectivity, universal accessibility, and essential planning and design requirements of pedestrians and cyclists are same. However, certain aspects like the type of means of public transportation, priority for cycling and walking, type of roadside activities, are influenced by the size of the town, average educational and income level of public, financial status of the local authorities, and culture of a place. The extent of public awareness, civic sense, maintenance of public spaces and law enforcement vary significantly from large metropolitan cities to small and medium towns in countries like India. Besides, design requirements for shading, location of public open spaces and sitting areas, street furniture, landscaping also vary depending on the climate of the place. Last mile connectivity plays a major role in success/ effectiveness of public transport system in a city. In addition to the provision of pedestrian footpaths connecting important destinations, sitting spaces and necessary amenities/facilities along footpaths; pedestrian movement to public transit stations is encouraged by the presence of quality roadside public spaces. It is not only the visual attractiveness of streetscape or landscape or the public open spaces along pedestrian movement channels but the activities along that make a street vibrant and attractive. These along with adequate spaces to rest and relax encourage people to walk as is observed in cities with successful public transportation systems. The paper discusses problems and issues of pedestrians for last mile connectivity in the context of Delhi, Chandigarh, Gurgaon, and Roorkee- four Indian cities representing varying urban contexts, that is, of metropolitan, large and small cities.

Keywords: pedestrianisation, roadside public spaces, last mile connectivity, sustainable urban mobility

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2025 Experimental Recovery of Gold, Silver and Palladium from Electronic Wastes Using Ionic Liquids BmimHSO4 and BmimCl as Solvents

Authors: Lisa Shambare, Jean Mulopo, Sehliselo Ndlovu

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One of the major challenges of sustainable development is promoting an industry which is both ecologically durable and economically viable. This requires processes that are material and energy efficient whilst also being able to limit the production of waste and toxic effluents through effective methods of process synthesis and intensification. In South Africa and globally, both miniaturisation and technological advances have substantially increased the amount of electronic wastes (e-waste) generated annually. Vast amounts of e-waste are being generated yearly with only a minute quantity being recycled officially. The passion for electronic devices cannot ignore the scarcity and cost of mining the noble metal resources which contribute significantly to the efficiency of most electronic devices. It has hence become imperative especially in an African context that sustainable strategies which are environmentally friendly be developed for recycling of the noble metals from e-waste. This paper investigates the recovery of gold, silver and palladium from electronic wastes, which consists of a vast array of metals, using ionic liquids which have the potential of reducing the gaseous and aqueous emissions associated with existing hydrometallurgical and pyrometallurgical technologies while also maintaining the economy of the overall recycling scheme through solvent recovery. The ionic liquids 1-butyl-3-methyl imidazolium hydrogen sulphate (BmimHSO4) which behaves like a protic acid and was used in the present research for the selective leaching of gold and silver from e-waste. Different concentrations of the aqueous ionic liquid were used in the experiments ranging from 10% to 50%. Thiourea was used as the complexing agent in the investigation with Fe3+ as the oxidant. The pH of the reaction was maintained in the range of 0.8 to 1.5. The preliminary investigations conducted were successful in the leaching of silver and palladium at room temperature with optimum results being at 48hrs. The leaching results could not be explained because of the leaching of palladium with the absence of gold. Hence a conclusion could not be drawn and there was the need for further experiments to be run. The leaching of palladium was carried out with hydrogen peroxide as oxidant and 1-butyl-3-methyl imidazolium chloride (BmimCl) as the solvent. The experiments at carried out at a temperature of 60 degrees celsius and a very low pH. The chloride ion was used to complex with palladium metal. From the preliminary results, it could be concluded that pretreatment of the treatment e-waste was necessary to improve the efficiency of the metal recovery process. A conclusion could not be drawn for the leaching experiments.

Keywords: BmimCl, BmimHSO4, gold, palladium, silver

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2024 The Role of Vocabulary in Reading Comprehension

Authors: Engku Haliza Engku Ibrahim, Isarji Sarudin, Ainon Jariah Muhamad

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It is generally agreed that many factors contribute to one’s reading comprehension and there is consensus that vocabulary size one of the main factors. This study explores the relationship between second language learners’ vocabulary size and their reading comprehension scores. 130 Malay pre-university students of a public university participated in this study. They were students of an intensive English language programme doing preparatory English courses to pursue bachelors degree in English. A quantitative research method was employed based on the Vocabulary Levels Test by Nation (1990) and the reading comprehension score of the in-house English Proficiency Test. A review of the literature indicates that a somewhat positive correlation is to be expected though findings of this study can only be explicated once the final analysis has been carried out. This is an ongoing study and it is anticipated that results of this research will be finalized in the near future. The findings will help provide beneficial implications for the prediction of reading comprehension performance. It also has implications for the teaching of vocabulary in the ESL context. A better understanding of the relationship between vocabulary size and reading comprehension scores will enhance teachers’ and students’ awareness of the importance of vocabulary acquisition in the L2 classroom.

Keywords: vocabulary size, vocabulary learning, reading comprehension, ESL

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2023 Using Students’ Perceptions for Measuring Teacher Effectiveness

Authors: Muhammad Akram, Qamar Naseem, Imtiaz Ahmad

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The purpose of this study was to correlate students’ perceptions of teacher effectiveness with their academic achievement in English and Mathematics at the secondary level (grade 9th) based on five national professional standards for teacher evaluation in Pakistan (subject matter knowledge, instructional planning and strategies, assessment, learning environment, effective communication. A Students’ Perceptions of Teacher Effectiveness Questionnaire (SPTEQ) was developed by the researchers to collect data from 2009 students from forty public girls and boys high/ higher secondary schools in district Khanewal, Pakistan. The overall reliability of the SPTEQ was α=.86. The study found a significant positive relationship among all the five factors of teacher effectiveness construct. The study also showed significant, positive relationship between teacher effectiveness factors and students’ achievement in English and mathematics. No significant differences were found between male and female students’ perceptions about their English teacher effectiveness. The implications include students’ personal attachments with their teachers that might convince them to overrate their teachers.

Keywords: communication, students’ achievement, teacher effectiveness, teaching strategies, teaching strategies

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2022 Hyperspectral Data Classification Algorithm Based on the Deep Belief and Self-Organizing Neural Network

Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

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In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

Procedia PDF Downloads 326
2021 Towards Expanding the Use of the Online Judge UnitJudge for Java Programming Exercises and Web Development Practices in Computer Science Education

Authors: Iván García-Magariño, Javier Bravo-Agapito, Marta López-Fernández

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Online judges have proven their utility in partial auto-evaluation of programming short exercises in the last decades. UnitJudge online judge has the advantage of facilitating the evaluation of separate units to provide more segregate and meaningful feedback to students in complex exercises and practices. This paper discusses the use of UnitUdge in advanced Java object-oriented programming exercises and web development practices. This later usage has been proposed by means of the Selenium Java library and classes to provide the web address. Consequently, UnitJudge is an online judge system that can be applied in several subjects, and therefore, many other students would take advantage of self-testing their exercises. This paper presents the experiments with a Java programming exercise for learning Java object-oriented classes with a generic type. Considering 10 students who voluntarily used UnitJudge, 80% successfully learned this concept, passing the judge exercise with correct results.

Keywords: online judges, programming skills, computer science education, auto-evaluation

Procedia PDF Downloads 79