Search results for: Individual learning

Authors: M. Ramezanifard, J. Dargahi, S. Najarian, N. Narayanan

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One of the major disadvantages of the minimally invasive surgery (MIS) is the lack of tactile feedback to the surgeon. In order to identify and avoid any damage to the grasped complex tissue by endoscopic graspers, it is important to measure the local softness of tissue during MIS. One way to display the measured softness to the surgeon is a graphical method. In this paper, a new tactile sensor has been reported. The tactile sensor consists of an array of four softness sensors, which are integrated into the jaws of a modified commercial endoscopic grasper. Each individual softness sensor consists of two piezoelectric polymer Polyvinylidene Fluoride (PVDF) films, which are positioned below a rigid and a compliant cylinder. The compliant cylinder is fabricated using a micro molding technique. The combination of output voltages from PVDF films is used to determine the softness of the grasped object. The theoretical analysis of the sensor is also presented. A method has been developed with the aim of reproducing the tactile softness to the surgeon by using a graphical method. In this approach, the proposed system, including the interfacing and the data acquisition card, receives signals from the array of softness sensors. After the signals are processed, the tactile information is displayed by means of a color coding method. It is shown that the degrees of softness of the grasped objects/tissues can be visually differentiated and displayed on a monitor.

Keywords: Minimally invasive surgery, Robotic surgery, Sensor, Softness, Tactile.

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Authors: Stephanie Fabris Russo, Daiane Costa Guimarães, Jonas Pedro Fabris, Maria Emilia Camargo, Suzana Leitão Russo, José Augusto Andrade Filho

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Among renewable energy sources, solar energy is the one that has stood out. Solar radiation can be used as a thermal energy source and can also be converted into electricity by means of effects on certain materials, such as thermoelectric and photovoltaic panels. These panels are often used to generate energy in homes, buildings, arenas, etc., and have low pollution emissions. Thus, a technological prospecting was performed to find patents related to the use of photovoltaic plates in urban residences. The patent search was based on ESPACENET, associating the keywords photovoltaic and home, where we found 136 patent documents in the period of 1994-2015 in the fields title and abstract. Note that the years 2009, 2010, 2011, 2012, 2013 and 2014 had the highest number of applicants, with respectively, 11, 13, 23, 29, 15 and 21. Regarding the country that deposited about this technology, it is clear that China leads with 67 patent deposits, followed by Japan with 38 patents applications. It is important to note that most depositors, 50% are companies, 44% are individual inventors and only 6% are universities. On the International Patent classification (IPC) codes, we noted that the most present classification in results was H02J3/38, which represents provisions in parallel to feed a single network by two or more generators, converters or transformers. Among all categories, there is the H session, which means Electricity, with 70% of the patents.

Keywords: Prospecting, technology forecasting, photovoltaic, urban residences.

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Authors: Bin Mu, Site Li, Shijin Yuan

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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model.

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Authors: Young-Seok Choi

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Cerebellar ataxia is a steadily progressive neurodegenerative disease associated with loss of motor control, leaving patients unable to walk, talk, or perform activities of daily living. Direct motor instruction in cerebella ataxia patients has limited effectiveness, presumably because an inappropriate closed-loop cerebellar response to the inevitable observed error confounds motor learning mechanisms. Could the use of EEG based BCI provide advanced biofeedback to improve motor imagery and provide a “backdoor” to improving motor performance in ataxia patients? In order to determine the feasibility of using EEG-based BCI control in this population, we compare the ability to modulate mu-band power (8-12 Hz) by performing a cued motor imagery task in an ataxia patient and healthy control.

Keywords: Cerebellar ataxia, Electroencephalogram, brain-computer interface, motor imagery.

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Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

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The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyse huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic wellbeing is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that support the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: COVID-19, big data, data analysis, indexing, NoSQL, sharding, scalability, poverty.

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Authors: Guanhao Tong, Li Li, Ben David

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This study aims to provide an explanatory account of how the leisure tourist experience emerges from tourists and their surroundings through a critical realist lens. This was achieved by applying Archer’s realist social theory as the underlying theoretical ground to unpack the interplays between the external (tourism system or structure) and the internal (tourists or agency) factors. This theory argues that social phenomena can be analysed in three domains - structure, agency, and culture (SAC), and along three phases – structure conditioning, sociocultural interactions, and structure elaboration. From the realist perspective, the world is an open system; events and discourses are irreducible to present individuals and collectivities. Therefore, identifying the processes or mechanisms is key to help researchers understand how social reality is brought about. Based on the contextual nature of the tourist experience, the research focuses on Chinese tourists (from mainland China) to London as a destination and British culture conveyed through the concept of the destination image. This study uses an intensive approach based on Archer’s M/M approach to discover the mechanisms/processes of the emergence of the tourist experience. Individual interviews were conducted to reveal the underlying causes of lived experiences of the tourists. Secondary data were also collected to understand how British destinations are portrayed to Chinese tourists.

Keywords: Chinese Tourists, Destination Image, M/M Approach, Realist Social Theory, social mechanisms, tourist experience.

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Authors: Thienhuong Hoang

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This qualitative, quantitative mixed-method study explores how students- motivation and interest in creative hands-on activities affected their conceptual understanding of science. The objectives of this research include developing a greater understanding about how creative activities, incorporated into the classroom as instructional strategies, increase student motivation and their learning or mastery of science concepts. The creative activities are viewed as a motivational tool, a specific type of task, which have an impact on student goals. Pre-and-post tests, pre-and-post interviews, and student responses measure motivational-goal theory variables, interest in the activity, and conceptual change. Implications for education and future research will be discussed.

Keywords: Science education, motivation, conceptual understanding, instructional strategies.

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Authors: Anders Troedsson

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For us humans, risk and insecurity are intimately linked to vulnerabilities - where there is vulnerability, there is potentially risk and insecurity. Reducing vulnerability through compensatory measures means decreasing the likelihood of a certain external event be qualified as a risk/threat/assault, and thus also means increasing the individual’s sense of security. The paper suggests that a meaningful way to approach the study of risk/ insecurity is to organize thinking about the vulnerabilities that external phenomena evoke in humans as perceived by them. Such phenomena are, through a set of given vulnerabilities, potentially translated into perceptions of "insecurity." An ontological discussion about salient timespace characteristics of external phenomena as perceived by humans, including such which potentially can be qualified as risk/threat/assault, leads to the positing of two dimensions which are central for describing what in the paper is called the essence of risk/threat/assault. As is argued, such modeling helps analysis steer free of the subjective factor which is intimately connected to human perception and which mediates between phenomena “out there” potentially identified as risk/threat/assault, and their translation into an experience of security or insecurity. A proposed set of universally given vulnerabilities are scrutinized with the help of the two dimensions, resulting in a modeling effort featuring four realms of vulnerabilities which together represent a dynamic whole. This model in turn informs modeling on human security.

Keywords: Human vulnerabilities, human security, inert-immediate, material-immaterial, timespace.

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Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

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The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: Recognition of shape, generalized hough transformation, histogram, Spatiogram, learning.

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Authors: Judy Yarwood, Lesley Seaton, Philippa Seaton

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A catastrophic earthquake measuring 6.3 on the Richter scale struck the Christchurch, New Zealand Central Business District on February 22, 2012, abruptly disrupting the business of teaching and learning at Christchurch Polytechnic Institute of Technology. This paper presents the findings from a study undertaken about the complexity of delivering an educational programme in the face of this traumatic natural event. Nine interconnected themes emerged from this multiple method study: communication, decision making, leader- and follower-ship, balancing personal and professional responsibilities, taking action, preparedness and thinking ahead, all within a disruptive and uncertain context. Sustainable responses that maximise business continuity, and provide solutions to practical challenges, are among the study-s recommendations.

Keywords: Business continuity, earthquake, education, sustainability

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Authors: Gabriel Chavira, Jorge Orozco, Salvador Nava, Eduardo Álvarez, Julio Rolón, Roberto Pichardo

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Ambient Intelligence promotes a shift in computing which involves fitting-out the environments with devices to support context-aware applications. One of main objectives is the reduction to a minimum of the user’s interactive effort, the diversity and quantity of devices with which people are surrounded with, in existing environments; increase the level of difficulty to achieve this goal. The mobile phones and their amazing global penetration, makes it an excellent device for delivering new services to the user, without requiring a learning effort. The environment will have to be able to perceive all of the interaction techniques. In this paper, we present the PICTAC model (Perceiving touch Interaction through TAgging Context), which similarly delivers service to members of a research group.

Keywords: Ambient Intelligence, Tagging Context, Touch Interaction, Touching Services.

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Authors: Rabia Bibi, Muhammad Shahzad Faisal, Khalid Iqbal, Atif Inayat

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Internet is growing rapidly and new community-based content is added by people every second. With this fast-growing community-based content, if a user requires answers of particular questions, then reviews are required from experts or community. However, it is difficult to get quality answers. The Muslim community all over the world is seeking help to get their questions and issues discussed to get answers. Online web portals of religious schools and community-based question answering sites are two big platforms to solve the issues of users. In the case of religious schools, there are experts and qualified religious scholars (mufti) who can give the expert opinion. However, the quality of community-based content cannot be guaranteed as it may not be an answer that satisfies the question of a user. Users on CQA sites may include spammers or individual criticizing the questioner instead of providing useful answers. In this paper, we research strategies to naturally distinguish the right content. As an experiment, we concentrate on Yahoo! Answers, and Quora, popular online QA sites, where questions are asked, answered, edited, and organized by a large community of users. We present the classification of data to categorize both relevant and irrelevant answers. Specifically, we demonstrate that the proposed framework can isolate quality answers from the rest with an exactness near that of people.

Keywords: Community-based question and answering, evaluation and prediction of quality answer, answer classification, Islamic content, answer ranking.

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Authors: Eiko Takaoka, Yoshiyuki Fukushima, Koichiro Hirose, Tadashi Hasegawa

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Although, all high school students in Japan are required to learn informatics, many of them do not learn this topic sufficiently. In response to this situation, we propose a support package for high school informatics classes. To examine what students learned and if they sufficiently understood the context of the lessons, a questionnaire survey was distributed to 186 students. We analyzed the results of the questionnaire and determined the weakest units, which were “basic computer configuration” and “memory and secondary storage”. We then developed a package for teaching these units. We propose that our package be applied in high school classrooms.

Keywords: Computer Science Unplugged, computer science outreach, high school curriculum, experimental evaluation.

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Authors: Yufang Cheng, Hsiu-Hua Yang

Abstract:

This work develops a novel intelligent “model of dynamic decision-making" usingcell assemblies network architecture in robot's movement. The “model of dynamic decision-making" simulates human decision-making, and follows commands to make the correct decisions. The cell assemblies approach consisting of fLIF neurons was used to implement tasks for finding targets and avoiding obstacles. Experimental results show that the cell assemblies approach of can be employed to efficiently complete finding targets and avoiding obstacles tasks and can simulate the human thinking and the mode of information transactions.

Keywords: Cell assemblies, fLIF, Hebbian learning rule.

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Authors: Jerry Szatko, Edan L. Jorgensen, Stacia Jorgensen

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A crucial component to the success of any financial advising relationship is for the financial professional to understand the perceptions, preferences and thought-processes carried by the financial clients they serve. Armed with this information, financial professionals are more quickly able to understand how they can tailor their approach to best match the individual preferences and needs of each personal investor. Our research explores the use of a quantitative assessment tool in the financial services industry to assist in the identification of the personal investor’s consumer behaviors, especially in terms of financial risk tolerance, as it relates to their financial decision making. Through this process, the Unitifi Consumer Insight Tool (UCIT) was created and refined to capture and categorize personal investor financial behavioral categories and the financial personality tendencies of individuals prior to the initiation of a financial advisement relationship. This paper discusses the use of this tool to place individuals in one of four behavior-based financial risk tolerance categories. Our discoveries and research were aided through administration of a web-based survey to a group of over 1,000 individuals. Our findings indicate that it is possible to use a quantitative assessment tool to assist in predicting the behavioral tendencies of personal consumers when faced with consumer financial risk and decisions.

Keywords: Behavior based advising, behavioral finance, financial advising, financial advisor tools, financial risk tolerance.

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Authors: Domingo López-Rodríguez, Enrique Mérida-Casermeiro, Juan M. Ortiz-de-Lazcano-Lobato

Abstract:

Hopfield model of associative memory is studied in this work. In particular, two main problems that it possesses: the apparition of spurious patterns in the learning phase, implying the well-known effect of storing the opposite pattern, and the problem of its reduced capacity, meaning that it is not possible to store a great amount of patterns without increasing the error probability in the retrieving phase. In this paper, a method to avoid spurious patterns is presented and studied, and an explanation of the previously mentioned effect is given. Another technique to increase the capacity of a network is proposed here, based on the idea of using several reference points when storing patterns. It is studied in depth, and an explicit formula for the capacity of the network with this technique is provided.

Keywords: Associative memory, Hopfield network, network capacity, spurious patterns.

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Authors: Amer Momani, Tarek Al-Hawari, Abdallah Alakayleh

Abstract:

This study explains how to construct an actionable activity-based costing and management system to accurately track and account the total costs of architectural aluminum projects. Two Activity-Based Costing (ABC) models were proposed to accomplish this purpose. First, the learning and development model was introduced to examine how to apply an ABC model in an architectural aluminum firm for the first time and to be familiar with ABC concepts. Second, an actual ABC model was built on the basis of the results of the previous model to accurately trace the actual costs incurred on each project in a year, and to be able to provide a quote with the best trade-off between competitiveness and profitability. The validity of the proposed model was verified on a local architectural aluminum company.

Keywords: Activity-based costing, activity-based management, construction, architectural aluminum.

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Authors: Ibrahim Hamidu Magem

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Employee engagement has continued to gain popularity among practitioners, consultants and academicians recent years. This is due to the fact that the engaged employees are central to organizational success in today’s highly competitive and rapidly changing business environment. Employee engagement depicts a situation whereby employee’s harnessed themselves to their work roles. The importance of employee engagement to organizations cannot be overemphasized in today’s rapidly changing business environment. Organizations both large and small are constantly striving to improve their performance, retain employees, reduce absenteeism, and create loyal customers among others. To be able to achieve these organizations need a team of highly engaged employees. In line with this, the study attempts to provide a valuable framework for understanding the antecedents and consequences of employee engagement in organizations. The paper categorizes the antecedents of employee engagement into individual and organizational factors which it is assumed that the existence of such factors could result into engaged employees that will be of benefit to organizations. Therefore, it is recommended that organizations should revisit and redesign its employee engagement system to enable them attain their organizational goals and objectives. In addition, organizations should note that engagement is personal but organizational engagement programmes should be about everyone in the organization. The findings from this paper adds to existing studies about employee engagement and also provide awareness to academics and practitioners about the importance of employee engagement to improve organizations efficiency and effectiveness, as well as to impact to overall firm performance.

Keywords: Antecedent, employee engagement, job involvement, organization.

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Authors: Alireza Gholami, Amir H. D. Markazi

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In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms.

Keywords: Adaptive algorithm, fuzzy systems, membership functions, observer.

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Authors: Sheng Teng Huang, Shigeru Yoshida

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Strategic alliances generally mean the cooperation or collaboration between firms which pursue for a synergy that each member hopes the benefits from the alliances would be much more than those from individual efforts. Past researches provide us sufficient theories and considerations for alliance forming in liner shipping market. This research reviews important academic journals for the past decade regarding to the most important reasons to form the alliances. We would explain the motive of alliances and details of shipping cooperation in literature review. The paper also empirically investigates the key service quality requirements improved through alliances by using quality function deployment (QFD). Moreover, the research investigates famous shipping reports, shipping consultant websites and most recent shipping publications to find out the executive-s viewpoint of several leading carriers among top 20 to assess current shipping strategic alliance on Asia/Europe route. These comments provide meaningful managerial reasons to consider alliance formations and search if there is any gap between the theories and industrial practice. Analysis of the empirical investigation and top management-s perspective on current market situation will contribute us some meaningful managerial suggestions to evaluate these theories applied to current strategic alliances.

Keywords: Liner shipping, Strategic alliances, quality function deployment, service quality.

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Authors: Caihong Sun, Xizi Zhang

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Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: Factorization machines, feature engineering, negative ratings, recommendation systems.

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Authors: Mihai Caramihai, Irina Severin

Abstract:

Despite the extensive use of eLearning systems, there is no consensus on a standard framework for evaluating this kind of quality system. Hence, there is only a minimum set of tools that can supervise this judgment and gives information about the course content value. This paper presents two kinds of quality set evaluation indicators for eLearning courses based on the computational process of three known metrics, the Euclidian, Hamming and Levenshtein distances. The “distance" calculus is applied to standard evaluation templates (i.e. the European Commission Programme procedures vs. the AFNOR Z 76-001 Standard), determining a reference point in the evaluation of the e-learning course quality vs. the optimal concept(s). The case study, based on the results of project(s) developed in the framework of the European Programme “Leonardo da Vinci", with Romanian contractors, try to put into evidence the benefits of such a method.

Keywords: eLearning, European programme, metrics, quality evaluation

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Authors: Zixuan Xu, Yichun Lou, Yang Song, Zihuai Lin

Abstract:

MediaPipe is an open-source machine learning computer vision framework that can be ported into a multi-platform environment, which makes it easier to use it to recognize human activity. Based on this framework, many human recognition systems have been created, but the fundamental issue is the recognition of human behavior and posture. In this paper, two methods are proposed to recognize human gestures based on MediaPipe, the first one uses the Adaptive Boosting algorithm to recognize a series of fitness gestures, and the second one uses the Fast Dynamic Time Warping algorithm to recognize 413 continuous fitness actions. These two methods are also applicable to any human posture movement recognition.

Keywords: Computer Vision, MediaPipe, Adaptive Boosting, Fast Dynamic Time Warping.

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Authors: Hossein Morshedlou, Ahmad Abdollahzade Barforoush

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Recent developments in storage technology and networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data streams.

Keywords: Data Stream, Classification, Concept Shift, History.

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Authors: Ashiquer Rahman, Hares Mohammad, Ummey Salma

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A country’s hourly compensation and unemployment rates are two of its most crucial components. They are not merely statistics but they have profound effects on individual, families, country, and the economy. They are inversely related to one another. The increased hourly compensation in the manufacturing sector can have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, in order to determine the effect of hourly compensation on unemployment rate, we use the panel data regression models and evaluate the expected link between hourly compensation and unemployment rate. We estimate the fixed effects model (FEM), evaluate the error components model (ECM), and determine which model (the FEM or ECM) is better through pooling all 60 observations. We then analyze and review the data by comparing countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of this extensive research on how the hourly compensation affects unemployment rate. Additionally, this paper offers relevant and useful guideline for the government and academic community to use an econometrics and social approach for the hourly compensation on unemployment rate to eliminate the problem.

Keywords: Hourly compensation, unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model.

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Authors: Andreas L. Savvides

Abstract:

For a long time as a result of accommodating car traffic, planning ideologies in the past put a low priority on public space, pedestrianism and the role of city space as a meeting place for urban dwellers. In addition, according to authors such as Jan Gehl, market forces and changing architectural perceptions began to shift the focus of planning practice from the integration of public space in various pockets around the contemporary city to individual buildings. Eventually, these buildings have become increasingly more isolated and introverted and have turned their backs to the realm of the public space adjoining them. As a result of this practice, the traditional function of public space as a social forum for city dwellers has in many cases been reduced or even phased out. Author Jane Jacobs published her seminal book “The Death and Life of Great American Cities" more than fifty years ago, but her observations and predictions at the time still ring true today, where she pointed out how the dramatic increase in car traffic and its accommodation by the urban planning ideology that was brought about by the Modern movement has prompted a separation of the uses of the city. At the same time it emphasizes free standing buildings that threaten urban space and city life and result in underutilized and lifeless urban cores. In this discussion context, the aim of this paper is to showcase a reversal of just such a situation in the case of the Dasoupolis neighborhood in Strovolos, Cyprus, where enlightened urban design practice has see the reclamation of pedestrian space in a car dominated area.

Keywords: Urban Design, Public Space, Right to the City, Accessibility, Mobility

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Authors: Asha Rani, Christian Micheloni, Gian Luca Foresti

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In this paper, a neural tree (NT) classifier having a simple perceptron at each node is considered. A new concept for making a balanced tree is applied in the learning algorithm of the tree. At each node, if the perceptron classification is not accurate and unbalanced, then it is replaced by a new perceptron. This separates the training set in such a way that almost the equal number of patterns fall into each of the classes. Moreover, each perceptron is trained only for the classes which are present at respective node and ignore other classes. Splitting nodes are employed into the neural tree architecture to divide the training set when the current perceptron node repeats the same classification of the parent node. A new error function based on the depth of the tree is introduced to reduce the computational time for the training of a perceptron. Experiments are performed to check the efficiency and encouraging results are obtained in terms of accuracy and computational costs.

Keywords: Neural Tree, Pattern Classification, Perceptron, Splitting Nodes.

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Authors: Mabel Ortiz, Claudio Díaz

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This paper explores Chilean pre-service teachers' perceptions about the provision of corrective feedback in a wiki environment during the collaborative writing of an argumentative essay. After conducting a semi-structured interview on 22 participants, the data were processed through the content analysis technique. The results show that students have positive perceptions about corrective feedback, provided through a wiki virtual environment, which in turn facilitates feedback provision and impacts language learning effectively. Some of the positive perceptions about virtual feedback refer to permanent access, efficiency, simultaneous revision and immediacy. It would then be advisable to integrate wiki-based feedback as a methodology for the language classroom and collaborative writing tasks.

Keywords: Argumentative essay, focused corrective feedback, perception, wiki environment.

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Authors: Magdi M. Nabi, Ding-Li Yu

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Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward and feedback control.

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

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This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: Extreme learning, LIRA neural classifier, speaker identification, voice recognition.

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