Search results for: competitive and cooperative learning.

Authors: Sello Mokwena, Monyepao Thabang

Abstract:

In this study, we propose a comprehensive approach to address the challenges in person re-identification models. By combining a centroid tracking algorithm with a Siamese convolutional neural network model, our method excels in detecting, tracking, and capturing robust person features across non-overlapping camera views. The algorithm efficiently identifies individuals in the camera network, while the neural network extracts fine-grained global features for precise cross-image comparisons. The approach's effectiveness is further accentuated by leveraging the camera network topology for guidance. Our empirical analysis of benchmark datasets highlights its competitive performance, particularly evident when background subtraction techniques are selectively applied, underscoring its potential in advancing person re-identification techniques.

Keywords: Camera network, convolutional neural network topology, person tracking, person re-identification, Siamese.

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Authors: M. Zerikat, M. Bendjebbar, N. Benouzza

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In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.

Keywords: Induction motor, fuzzy-logic control, neural network control, indirect field oriented control.

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Authors: Rosie Borup, Hanifa Shah

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This paper aims to describe how student satisfaction is measured for work-based learners as these are non-traditional learners, conducting academic learning in the workplace, typically their curricula have a high degree of negotiation, and whose motivations are directly related to their employers- needs, as well as their own career ambitions. We argue that while increasing WBL participation, and use of SSD are both accepted as being of strategic importance to the HE agenda, the use of WBL SSD is rarely examined, and lessons can be learned from the comparison of SSD from a range of WBL programmes, and increased visibility of this type of data will provide insight into ways to improve and develop this type of delivery. The key themes that emerged from the analysis of the interview data were: learners profiles and needs, employers drivers, academic staff drivers, organizational approach, tools for collecting data and visibility of findings. The paper concludes with observations on best practice in the collection, analysis and use of WBL SSD, thus offering recommendations for both academic managers and practitioners.

Keywords: Student satisfaction data, work based learning, employer engagement, NSS.

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Authors: Waleed Maqableh, Ahmad Al-Hamad, Manjit Sidhu

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Augmented reality (AR) technology has the capability to provide many benefits in the field of education as a modern technology which aided learning and improved the learning experience. This paper evaluates AR based application with multiple markers interaction technique (touch-to-print) which is designed for analyzing the kinematics of 4BL mechanism in mechanical engineering. The application is termed as AR-4BL-MAST and it allows the users to touch the symbols on a paper in natural way of interaction. The evaluation of this application was performed with mechanical engineering students and human–computer interaction (HCI) experts to test its effectiveness as a tangible user interface application where the statistical results show its ability as an interaction technique, and it gives the users more freedom in interaction with the virtual mechanical objects.

Keywords: Augmented reality, engineering, four-bar linkage, Multimedia, user interface, visualization.

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Authors: Prashant Kumar Tiwari, Yog Raj Sood

Abstract:

This paper proposes an investment cost recovery based efficient and fast sequential optimization approach to optimal allocation of thyristor controlled series compensator (TCSC) in competitive power market. The optimization technique has been used with an objective to maximizing the social welfare and minimizing the device installation cost by suitable location and rating of TCSC in the system. The effectiveness of proposed approach for location of TCSC has been compared with some existing methods of TCSC placement, in terms of its impact on social welfare, TCSC investment recovery and optimal generation as well as load patterns. The results have been obtained on modified IEEE 14-bus system.

Keywords: Double auction market, Investment cost recovery, Optimal location, Social welfare, TCSC

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Authors: Shahlan Surat, Saemah Rahman, Saadiah Kummin

Abstract:

When teachers reflect and evaluate whether their teaching methods actually have an impact on students’ learning, they will adjust their practices accordingly. This inevitably improves their students’ learning and performance. The approach in meta-teaching can invigorate and create a passion for teaching. It thus helps to increase the commitment and love for the teaching profession. This study was conducted to determine the level of metacognitive thinking of teachers in the process of teaching and learning in the classroom. Metacognitive thinking teachers include the use of metacognitive knowledge which consists of different types of knowledge: declarative, procedural and conditional. The ability of the teachers to plan, monitor and evaluate the teaching process can also be determined. This study was conducted on 377 graduate teachers in Klang Valley, Malaysia. The stratified sampling method was selected for the purpose of this study. The metacognitive teaching inventory consisting of 24 items is called InKePMG (Teacher Indicators of Effectiveness Meta-Teaching). The results showed the level of mean is high for two components of metacognitive knowledge; declarative knowledge (mean = 4.16) and conditional (mean = 4.11) whereas, the mean of procedural knowledge is 4.00 (moderately high). Similarly, the level of knowledge in monitoring (mean = 4.11), evaluating (mean = 4.00) which indicate high score and planning (mean = 4.00) are moderately high score among teachers. In conclusion, this study shows that the planning and procedural knowledge is an important element in improving the quality of teachers teaching in the classroom. Thus, the researcher recommended that further studies should focus on training programs for teachers on metacognitive skills and also on developing creative thinking among teachers.

Keywords: Metacognitive thinking skills, procedural knowledge, conditional knowledge, declarative knowledge, meta-teaching and regulation of cognitive.

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Authors: Alex Elentukh

Abstract:

The paper is based on data collected from final exams administered during five years teaching the graduate course in software engineering. The visualization instrument with four distinct personas has been used to improve effectiveness of each class. The study offers a plethora of clues toward students' behavioral preferences. Diversity among students (professional background, physical proximity) is too significant to assume a single face of a learner. This is particularly true for a body of on-line graduate students in computer science. Conclusions of the study (each learner is unique and each class is unique) are extrapolated to demystify the notion of an 'average software engineer'. An immediate direction for an educator is to assure a course applies to a wide audience of very different individuals. On another hand, a student should be clear about his/her abilities and preferences - to follow the most effective learning path.

Keywords: K.3.2 computer & information science education, learner profiling, adaptive learning, software engineering.

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Authors: Sarah E. Stief, Anne Theresa Eidhoff, Markus Voeth

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Despite all progress firms are facing the increasing need to adapt and assimilate digital technologies to transform their business activities in order to pursue business development. By using new digital technologies, firms can implement major business improvements in order to stay competitive and foster new growth potentials. The corresponding phenomenon of digital transformation has received some attention in previous literature in respect to industries such as media and publishing. Nevertheless, there is a lack of understanding of the concept and its organization within firms. With the help of twenty-three in-depth field interviews with German experts responsible for their company’s digital transformation, we examined what digital transformation encompasses, how it is organized and which opportunities and challenges arise within firms. Our results indicate that digital transformation is an inevitable task for all firms, as it bears the potential to comprehensively optimize and reshape established business activities and can thus be seen as a strategy of business development.

Keywords: Business development, digitalization, digital strategies, digital transformation.

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Authors: Chong-Yang Qiao

Abstract:

Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: Mobile augmented reality, remote collaboration, user experience, cognitive model.

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Authors: M. Rezki, A. Belaidi

Abstract:

This paper deals with a method of learning to solve a real problem in biomedical engineering from a technical study of muscle fatigue. Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles (viewpoint: anatomical and physiological). EMG is used as a diagnostics tool for identifying neuromuscular diseases, assessing low-back pain and muscle fatigue in general. In order to study the EMG signal for detecting fatigue in a muscle, we have taken a real problem which touches the tramway conductor the handle bar. For the study, we have used a typical autonomous platform in order to get signals at real time. In our case study, we were confronted with complex problem to do our experiments in a tram. This type of problem is recurring among students. To teach our students the method to solve this kind of problem, we built a similar system. Through this study, we realized a lot of objectives such as making the equipment for simulation, the study of detection of muscle fatigue and especially how to manage a study of biomedical looking.

Keywords: EMG, health platform, conductor’s tram, muscle fatigue.

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Authors: N. Zerzouri, H. Labar, S. Kechida

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During recent years wind turbine technology has undergone rapid developments. Growth in size and the optimization of wind turbines has enabled wind energy to become increasingly competitive with conventional energy sources. As a result today-s wind turbines participate actively in the power production of several countries around the world. These developments raise a number of challenges to be dealt with now and in the future. The penetration of wind energy in the grid raises questions about the compatibility of the wind turbine power production with the grid. In particular, the contribution to grid stability, power quality and behavior during fault situations plays therefore as important a role as the reliability. In the present work, we addressed two fault situations that have shown their influence on the generator and the behavior of the wind over the defects which are briefly discussed based on simulation results.

Keywords: Doubly fed induction generator (DFIG), Wind energy, grid fault

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Authors: Muslihah Wook, Zawiyah M. Yusof, Mohd Zakree Ahmad Nazri

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Data mining has been integrated into application systems to enhance the quality of the decision-making process. This study aims to focus on the integration of data mining technology and Knowledge Management System (KMS), due to the ability of data mining technology to create useful knowledge from large volumes of data. Meanwhile, KMS vitally support the creation and use of knowledge. The integration of data mining technology and KMS are popularly used in business for enhancing and sustaining organizational performance. However, there is a lack of studies that applied data mining technology and KMS in the education sector; particularly students- academic performance since this could reflect the IHL performance. Realizing its importance, this study seeks to integrate data mining technology and KMS to promote an effective management of knowledge within IHLs. Several concepts from literature are adapted, for proposing the new integrative data mining technology and KMS framework to an IHL.

Keywords: Data mining, Institutions of Higher Learning, Knowledge Management System, Students' academic performance.

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Authors: Mohamed Chabi, Mohammad Shahid Jamil, Mahmoud I Syam

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The purpose of this study is to determine whether paper assessment especially in the subject mathematics will ever be completely replaced by online assessment using Learning Management System and Content Management System such as blackboard. Testing students has moved from the traditional scribbling and sketching on paper towards working online on a screen and keyboard. It is found that online assessment by using selective types of questions like multiple choices, true or false and final answer questions don’t reflect the actual understanding of students in solving the problems and teachers can’t determine the weakness points of students. In addition, it is showed that OBMCQs are a very good tool for self-assessment and when teachers are testing for knowledge and facts. But when it comes to the skills, OBMCQs are poor tools for measuring the ability to apply knowledge to complex math problem. 

Keywords: Paper assessment, online assessment, learning management system, content management system.

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Authors: Jui P. Hung, Hsia C. Chang, Yuan L. Lai

Abstract:

Introduction applicability of high-speed cutting stock problem (CSP) is presented in this paper. Due to the orders continued coming in from various on-line ways for a professional cutting company, to stay competitive, such a business has to focus on sustained production at high levels. In others words, operators have to keep the machine running to stay ahead of the pack. Therefore, the continuous stock cutting problem with setup is proposed to minimize the cutting time and pattern changing time to meet the on-line given demand. In this paper, a novel method is proposed to solve the problem directly by using cutting patterns directly. A major advantage of the proposed method in series on-line production is that the system can adjust the cutting plan according to the floating orders. Examples with multiple items are demonstrated. The results show considerable efficiency and reliability in high-speed cutting of CSP.

Keywords: Cutting stock, Optimization, Heuristics

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Authors: Lingzhi Li, Jiankun Zhang, Tiantian Gu

Abstract:

Hazard management that can prevent fatal accidents and property losses is a fundamental process during the buildings’ construction stage. However, due to lack of safety supervision resources and operational pressures, the conduction of hazard management is poor and ineffective in China. In order to improve the quality of construction safety management, it is critical to explore the use of information technologies to ensure that the process of hazard management is efficient and effective. After exploring the existing problems of construction hazard management in China, this paper develops the griddization management model for construction hazard management. First, following the knowledge grid infrastructure, the griddization computing infrastructure for construction hazards management is designed which includes five layers: resource entity layer, information management layer, task management layer, knowledge transformation layer and application layer. This infrastructure will be as the technical support for realizing grid management. Second, this study divides the construction hazards into grids through city level, district level and construction site level according to grid principles. Last, a griddization management process including hazard identification, assessment and control is developed. Meanwhile, all stakeholders of construction safety management, such as owners, contractors, supervision organizations and government departments, should take the corresponding responsibilities in this process. Finally, a case study based on actual construction hazard identification, assessment and control is used to validate the effectiveness and efficiency of the proposed griddization management model. The advantage of this designed model is to realize information sharing and cooperative management between various safety management departments.

Keywords: Construction hazard, grid management, griddization computing, process.

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Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

In recent years, new product development became more and more competitive and globalized, and the designing phase is critical for the product success. The concept of modularity can provide the necessary foundation for organizations to design products that can respond rapidly to market needs. The paper describes data structures and algorithms of intelligent Web-based system for modular design taking into account modules compatibility relationship and given design requirements. The system intelligence is realized by developed algorithms for choice of modules reflecting all system restrictions and requirements. The proposed data structure and algorithms are illustrated by case study of personal computer configuration. The applicability of the proposed approach is tested through a prototype of Web-based system.

Keywords: Data structures, algorithms, intelligent web-based system, modular design.

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Authors: Wang Zhanquan, Yang Zeping, Gu Chunhua, Zhu Fazhi, Guo Weibin

Abstract:

Recently, Massive Open Online Courses (MOOCs) are becoming the new trend of education. There are many problems under the environment of Database Principle curriculum teaching process in MOOCs, such as teaching ideas and theories which are out of touch with the reality, how to carry out the technical teaching and interactive practice in the MOOCs environment, thus the methods of database course under the environment of MOOCs are proposed. There are three processes to deal with problem solving in the research, which are problems proposed, problems solved, and inductive analysis. The present research includes the design of teaching contents, teaching methods in classroom, flipped classroom teaching mode under the environment of MOOCs, learning flow method and large practice homework. The database designing ability is systematically improved based on the researching methods.

Keywords: Problem solving-driven, MOOCs, teaching art, learning flow.

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Authors: C.Kia, M.R.Arshad, A.H.Adom, P.A.Wilson

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This paper presents recent work on the improvement of the robotics vision based control strategy for underwater pipeline tracking system. The study focuses on developing image processing algorithms and a fuzzy inference system for the analysis of the terrain. The main goal is to implement the supervisory fuzzy learning control technique to reduce the errors on navigation decision due to the pipeline occlusion problem. The system developed is capable of interpreting underwater images containing occluded pipeline, seabed and other unwanted noise. The algorithm proposed in previous work does not explore the cooperation between fuzzy controllers, knowledge and learnt data to improve the outputs for underwater pipeline tracking. Computer simulations and prototype simulations demonstrate the effectiveness of this approach. The system accuracy level has also been discussed.

Keywords: Fuzzy logic, Underwater target tracking, Autonomous underwater vehicles, Artificial intelligence, Simulations, Robot navigation, Vision system.

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Authors: Eric Ho

Abstract:

Pedagogical approaches in Asia nowadays are imported from the West. In Confucian Heritage Culture (CHC), however, there is a dichotomy between the perceived benefits of Western pedagogies and the real classroom practices in Chinese societies. The success of Hong Kong students in large-scale international assessments has proved that both the strengths of both Western pedagogies and CHC educational approaches should be integrated for the sake of the students. University students aim to equip themselves with employability skills upon graduation. Formative assessments allow students to receive detailed, positive, and timely feedback and they can identify their strengths and weaknesses before they start working. However, there remains a question of whether university year 1 students who come from an examination-driven secondary education background are ready to respond to more formative assessments. The findings show that year 1 students are less concerned about competition in the university and more open to new teaching approaches that will allow them to improve as professionals in their major study areas.

Keywords: Formative assessment, higher education, learning styles, Confucian heritage culture.

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Authors: Ashly Joseph, Jithu Paulose

Abstract:

In an era where misleading information may quickly circulate on digital news channels, it is crucial to have efficient and trustworthy methods to detect and reduce the impact of misinformation. This research proposes an innovative framework that combines Natural Language Processing (NLP), Reinforcement Learning (RL), and Blockchain technologies to precisely detect and minimize the spread of false information in news articles on social media. The framework starts by gathering a variety of news items from different social media sites and performing preprocessing on the data to ensure its quality and uniformity. NLP methods are utilized to extract complete linguistic and semantic characteristics, effectively capturing the subtleties and contextual aspects of the language used. These features are utilized as input for a RL model. This model acquires the most effective tactics for detecting and mitigating the impact of false material by modeling the intricate dynamics of user engagements and incentives on social media platforms. The integration of blockchain technology establishes a decentralized and transparent method for storing and verifying the accuracy of information. The Blockchain component guarantees the unchangeability and safety of verified news records, while encouraging user engagement for detecting and fighting false information through an incentive system based on tokens. The suggested framework seeks to provide a thorough and resilient solution to the problems presented by misinformation in social media articles.

Keywords: Natural Language Processing, Reinforcement Learning, Blockchain, fake news mitigation, misinformation detection.

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Authors: A. Al-Rashidi, A. El-Hamalawi

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In this paper, a performance study was conducted to investigate single and dual-axis PV systems to generate electricity in five different sites in Kuwait. Relevant data were obtained by using two sources for validation purposes. A commercial software, PVsyst, was used to analyse the data, such as metrological data and other input parameters, and compute the performance parameters such as capacity factor (CF) and final yield (YF). The results indicated that single and dual-axis PV systems would be very beneficial to electricity generation in Kuwait as an alternative source to conventional power plants, especially with the increased demand over time. The ranges were also found to be competitive in comparison to leading countries using similar systems. A significant increase in CF and YF values around 24% and 28.8% was achieved related to the use of single and dual systems, respectively.

Keywords: Single-axis and dual-axis photovoltaic systems, capacity factor, final yield, renewable energy, Kuwait.

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Authors: A. Eman Mohammed

Abstract:

Algae-based fuel are considered a promising sources of clean energy, and because it has many advantages over traditional biofuel, research and business ventures have driven into developing and producing Algal-biofuel. But its production stages create a cost structure that it is not competitive with traditional fuels. Therefore, cost becomes the main obstacle in commercial production purpose. However, the present research which aims at using cost structure model, and designed MS-Dose program, to investigate the a mount of production cost and determined the parameter had great effect on it, second to measured the amount of contribution rate of algae in process the pollution by capturing Co2 from air . The result generated from the model shows that the production cost of biomass is between $0.137 /kg for 100 ha and $0.132 /kg for 500 ha which was less than cost of other studies, while gallon costs between $3.4 - 3.5, more than traditional sources of oil about $1 ,which regarded as a rate of contribution of algal in capturing CO2 from air.

Keywords: Cost Structure Model, Operation Costs(Production Cost), Capital Costs, Algae.

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Authors: Rosina C. Chia, Elmer Poe, Karl L. Wuensch

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A virtual collaborative classroom was created at East Carolina University, using videoconference technology via regular internet to bring students from 18 different countries, 2 at a time, to the ECU classroom in real time to learn about each other-s culture. Students from two countries are partnered one on one, they meet for 4-5 weeks, and submit a joint paper. Then the same process is repeated for two other countries. Lectures and student discussions are managed with pre-determined topics and questions. Classes are conducted in English and reading assignments are placed on the website. Administratively all partners are independent, students pay fees and get credits at their home institution. Familiarity with technology, knowledge in cultural understanding and attitude change were assessed, only attitude changes are reported in this paper. After taking this course, all students stated their comfort level in working with, and their desire to interact with, culturally different others grew stronger and their xenophobia and isolationist attitudes decreased.

Keywords: Attitude change, interactive cultural learning, multicultural education, real time virtual learning.

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Authors: D. Hişam, S. İkizoğlu

Abstract:

Identifying the problem behind balance disorder is one of the most interesting topics in medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three ML models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest (RF) Classifier was the most accurate model.

Keywords: Vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting.

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Authors: G. Reinhart, S. Schindler

Abstract:

Due to dynamic evolution, the ability of a manufacturing technology to produce a special product is changing. Therefore, it is essential to monitor the established techniques and processes to detect whether a company-s production will fit future circumstances. Concerning the manufacturing technology planning process, companies must decide when to change to a new technology for maintaining and increasing competitive advantages. In this context, the maturity assessment of the focused technologies is crucial. This article presents an approach for defining the maturity of a manufacturing technology from a strategic point of view. The concept is based on the approach of technology readiness level (TRL) according to NASA (National Aeronautics and Space Administration), but also includes dynamic changes. Therefore, the model takes into account the concept of the technology life cycle. Furthermore, it enables a company to estimate the ideal date for implementation of a new manufacturing technology.

Keywords: Maturity Assessment, Manufacturing Technology Planning, Technology Life Cycle, Technology Readiness Level.

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

Abstract:

The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluates the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: lexical semantics, feature representation, semantic decision, convolutional neural network, electronic medical record

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Authors: K´evin Fernagut, Olivier Flauzac, Erick M. Gallegos R, Florent Nolot

Abstract:

The adoption of modern lightweight virtualization often comes with new threats and network vulnerabilities. This paper seeks to assess this with a different approach studying the behavior of a testbed built with tools such as Kernel-based Virtual Machine (KVM), LinuX Containers (LXC) and Docker, by performing stress tests within a platform where students experiment simultaneously with cyber-attacks, and thus observe the impact on the campus network and also find the best solution for cyber-security learning. Interesting outcomes can be found in the literature comparing these technologies. It is, however, difficult to find results of the effects on the global network where experiments are carried out. Our work shows that other physical hosts and the faculty network were impacted while performing these trials. The problems found are discussed, as well as security solutions and the adoption of new network policies.

Keywords: Containerization, containers, cyber-security, cyber-attacks, isolation, performance, security, virtualization, virtual machines.

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Authors: A. Evans, M. McKinley

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Knowledge management (KM) is generally considered to be a positive process in an organisation, facilitating opportunities to achieve competitive advantage via better quality information handling, compilation of expert know-how and rapid response to fluctuations in the business environment. The KM paradigm as portrayed in the literature informs the processes that can increase intangible assets so that corporate knowledge is preserved. However, in some instances, knowledge management exists in a universe of dynamic tension among the conflicting needs to respect privacy and intellectual property (IP), to guard against data theft, to protect national security and to stay within the laws. While the Knowledge Management literature focuses on the bright side of the paradigm, there is also a different side in which knowledge is distorted, suppressed or misappropriated due to personal or organisational motives (the paradox). This paper describes the ethical paradoxes that occur within the taxonomy and deontology of knowledge management and suggests that recognising both the promises and pitfalls of KM requires wisdom.

Keywords: business ethics, data, knowledge, knowledgemanagement, privacy, protection.

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Authors: L. Mortari, A. Bevilacqua, R. Silva

Abstract:

The experience presented in this paper aims to understand how educational research can support the introduction and optimization of teaching innovations in legal education. In this increasingly complex context, a strong need to introduce paths aimed at acquiring not only professional knowledge and skills but also reflective, critical and problem-solving skills emerges. Through a peer observation intertwined with an analysis of discursive practices, researchers and the teacher worked together through a process of participatory and transformative accompaniment whose objective was to promote the active participation and engagement of students in learning processes, an element indispensable to work in the more specific direction of strengthening key competences. This reflective faculty development path led the teacher to activate metacognitive processes, becoming thus aware of the strengths and areas of improvement of his teaching innovation.

Keywords: Discursive analysis, faculty development, legal education, peer observation, teaching innovation.

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Authors: Gregor Radonjič, Aleksandra P. Korda, Damijan Krajnc

Abstract:

The aim of the study was to investigate whether there is the promotion of product ecodesign measures as a result of adopting ISO 14001 certification in manufacturing companies in the Republic of Slovenia. Companies gave the most of their product development attention to waste and energy reduction during manufacturing process and reduction of material consumption per unit of product. Regarding the importance of different ecodesign criteria reduction of material consumption per unit of product was reported as the most important criterion. Less attention is paid to endof- life issues considering recycling or packaging. Most manufacturing enterprises considered ISO 14001 standard as a very useful tool or at least a useful tool helping them to accelerate and establish product ecodesign activities. Two most frequently considered ecodesign drivers are increased competitive advantage and legal requirements and two most important barriers are high development costs and insufficient market demand.

Keywords: ecodesign, environmental management system, ISO 14001, products

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