Search results for: "Process-oriented Learning and Information Exchange" (PROLIX).

Authors: May George

Abstract:

Inference plays an important role in the learning process and it can lead to a rapid acquisition of a second language. When learning a non-native language i.e., a critical language like Arabic, the students depend on the teacher’s support most of the time to learn new concepts. The students focus on memorizing the new vocabulary and stress on learning all the grammatical rules. Hence, the students became mechanical and cannot produce the language easily. As a result, they are unable to predicate the meaning of words in the context by relying heavily on the teacher, in that they cannot link their prior knowledge or even identify the meaning of the words without the support of the teacher. This study explores how the teacher guides students learning during the inference process and what are the processes of learning that can direct student’s inference.

Keywords: Inference, Reading, Arabic, and Language Acquisition.

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Authors: Kathaleeya Chanda, Panupong Chanplin, Suppara Charoenpoom

Abstract:

This purposes of the development of creative instruction model through digital media are to: 1) enable learners to learn from instruction media application; 2) help learners implementing instruction media correctly and appropriately; and 3) facilitate learners to apply technology for searching information and practicing skills to implement technology creatively. The sample group consists of 130 cases of secondary students studying in Bo Kluea School, Bo Kluea Nuea Sub-district, Bo Kluea District, Nan Province. The probability sampling was selected through the simple random sampling and the statistics used in this research are percentage, mean, standard deviation and one group pretest – posttest design. The findings are summarized as follows: The congruence index of instruction media for occupation and technology subjects is appropriate. By comparing between learning achievements before implementing the instruction media and learning achievements after implementing the instruction media, it is found that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. For the learning achievements from instruction media implementation, pretest mean is 16.24 while posttest mean is 26.28. Besides, pretest and posttest results are compared and differences of mean are tested, the test results show that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. This can be interpreted that the learners achieve better learning progress.

Keywords: Teaching learning model, digital media, creative instruction model, facilitate learners.

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Authors: Gilbert Makanda, Roelf Sypkens

Abstract:

A mathematical model for knowledge acquisition in teaching and learning is proposed. In this study we adopt the mathematical model that is normally used for disease modelling into teaching and learning. We derive mathematical conditions which facilitate knowledge acquisition. This study compares the effects of dropping out of the course at early stages with later stages of learning. The study also investigates effect of individual interaction and learning from other sources to facilitate learning. The study fits actual data to a general mathematical model using Matlab ODE45 and lsqnonlin to obtain a unique mathematical model that can be used to predict knowledge acquisition. The data used in this study was obtained from the tutorial test results for mathematics 2 students from the Central University of Technology, Free State, South Africa in the department of Mathematical and Physical Sciences. The study confirms already known results that increasing dropout rates and forgetting taught concepts reduce the population of knowledgeable students. Increasing teaching contacts and access to other learning materials facilitate knowledge acquisition. The effect of increasing dropout rates is more enhanced in the later stages of learning than earlier stages. The study opens up a new direction in further investigations in teaching and learning using differential equations.

Keywords: Differential equations, knowledge acquisition, least squares nonlinear, dynamical systems.

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Authors: Andrey V. Timofeev

Abstract:

The paper presents new results concerning selection of optimal information fusion formula for ensembles of C-OTDR channels. The goal of information fusion is to create an integral classificator designed for effective classification of seismoacoustic target events. The LPBoost (LP-β and LP-B variants), the Multiple Kernel Learning, and Weighing of Inversely as Lipschitz Constants (WILC) approaches were compared. The WILC is a brand new approach to optimal fusion of Lipschitz Classifiers Ensembles. Results of practical usage are presented.

Keywords: Lipschitz Classifier, Classifiers Ensembles, LPBoost, C-OTDR systems, ν-OTDR systems.

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Authors: Somtop Keawchuer

Abstract:

The objectives of this research are to compare the satisfaction of students, towards the happiness learning, sorted by their personal profiles, and to figure out the factors that affect the students’ happiness learning. This paper used survey method to collect data from 362 students. The survey was mainly conducted in the Faculty of Management Science, Suan Sunandha Rajabhat University, including 3,443 students. The statistics used for interpreting the results included the frequencies, percentages, standard deviations and One-way ANOVA. The findings revealed that the students are aware and satisfaction that all the factors in 3 categories (knowledge, skill and attitude) influence the happiness learning at the highest levels. The comparison of the satisfaction levels of the students toward their happiness learning leads to the results that the students with different genders, ages, years of study, and majors of the study have the similar satisfaction at the high level.

Keywords: Happiness Learning, Satisfaction, Students.

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Authors: Jiří Barta, Tomáš Ludík, Jiří Urbánek

Abstract:

Topics Disaster and Emergency Management are highly debated among experts. Fast communication will help to deal with emergencies. Problem is with the network connection and data exchange. The paper suggests a solution, which allows possibilities and perspectives of new flexible communication platform to the protection of communication systems for crisis management. This platform is used for everyday communication and communication in crisis situations too.

Keywords: Communication Platform, Crisis Management, Crisis Communication, Information Systems, Interoperability, Security Environment.

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Authors: Karen Armstrong

Abstract:

Group work, projects and discussions are important components of teacher education courses whether they are face-toface, blended or exclusively online formats. This paper examines the varieties of tasks and challenges with this learning format in a face to face class teacher education class providing specific examples of both failure and success from both the student and instructor perspective. The discussion begins with a brief history of collaborative and cooperative learning, moves to an exploration of the promised benefits and then takes a look at some of the challenges which can arise specifically from the use of new technologies. The discussion concludes with guidelines and specific suggestions.

Keywords: collaborative learning, cooperative computersupported collaborative learning (CSCL), e-learning, group dynamics

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Authors: Omid Noroozi

Abstract:

Digital dialogue games have opened up opportunities for learning skills by engaging students in complex problem solving that mimic real world situations, without importing unwanted constraints and risks of the real world. Digital dialogue games can be motivating and engaging to students for fun, creative thinking, and learning. This study explored how undergraduate students engage with argumentative discourse activities which have been designed to intensify debate. A pre-test, post-test design was used with students who were assigned to groups of four and asked to debate a controversial topic with the aim of exploring various 'pros and cons' on the 'Genetically Modified Organisms (GMOs)'. Findings reveal that the Digital dialogue game can facilitate argumentation-based learning. The digital Dialogue game was also evaluated positively in terms of students’ satisfaction and learning experiences.

Keywords: Argumentation, dialogue, digital game, learning, motivation.

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Authors: M. N. Norshita, B. Z. Halimah, T. S. Tengku Mohammad

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The implementation of electronic government started since the initiation of Multimedia Super Corridor (MSC) by the Malaysia government. The introduction of ICT in the public sector especially e-Government initiatives opens up a new book in the government administration throughout the world. The aim or this paper is to discuss the implementation of e-government in Malaysia, covering the result of public user self assessment on Malaysia's electronic government applications. E-services, e-procurement, Generic Office Environment (GOE), Human Resources Management Information System (HRMIS), Project Monitoring System (PMS), Electronic Labor Exchange (ELX) and e-syariah(religion) were the seven flagship application assessed. The study adopted a crosssectional survey research approach and information system literature were used. The analysis was done for 35 responden in pilot test and there was evidence from public user's perspective to suggest that the e-government applications were generally successful.

Keywords: Electronic government, flagship, multimedia super corridor, public user.

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Authors: Na Li, Samuel Simon Araya, Søren Knudsen Kær

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This study investigates the effects of operating parameters of different current density, temperature and pressure on the performance of a proton exchange membrane (PEM) water electrolysis stack. A 7-cell PEM water electrolysis stack was assembled and tested under different operation modules. The voltage change and polarization curves under different test conditions, namely current density, temperature and pressure, were recorded. Results show that higher temperature has positive effect on overall stack performance, where temperature of 80 ℃ improved the cell performance greatly. However, the cathode pressure and current density has little effect on stack performance.

Keywords: PEM electrolysis stack, current density, temperature, pressure.

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Authors: S. Kotsiantis, E. Koumanakos, D. Tzelepis, V. Tampakas

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This paper explores the effectiveness of machine learning techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. To this end, a number of experiments have been conducted using representative learning algorithms, which were trained using a data set of 164 fraud and non-fraud Greek firms in the recent period 2001-2002. The decision of which particular method to choose is a complicated problem. A good alternative to choosing only one method is to create a hybrid forecasting system incorporating a number of possible solution methods as components (an ensemble of classifiers). For this purpose, we have implemented a hybrid decision support system that combines the representative algorithms using a stacking variant methodology and achieves better performance than any examined simple and ensemble method. To sum up, this study indicates that the investigation of financial information can be used in the identification of FFS and underline the importance of financial ratios.

Keywords: Machine learning, stacking, classifier.

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Authors: Mariani Md Nor, Y. Saeednia

Abstract:

Self-directed learning (SDL) was developed initially for adult learning. Guglielmino constructed a scale to measure SDL. Recent researchers have applied this concept to children. Although there are sufficient theoretical evidences to present the possibility of applying this concept to children, empirical evidences were not provided. This study aimed to examine the quality of SDL and construct a scale to measure SDL among young children. A modified scale of Guglielmino-s scale was constructed and piloted with 183 subjects of age 9. Findings suggest that the qualities of SDL in young ages are apparently congruent with that of adults.

Keywords: SDLR, Self-Directed Learning, Young Children.

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Authors: Christine K. Fulmer

Abstract:

Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.

Keywords: Constructivist theoretical approach, experiential learning, pedagogy, problem-based learning, social work education.

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Authors: Ahmed O. Apampa, Yinusa A. Jimoh

Abstract:

The paper examines the mechanism of pozzolan-soil reactions, using a recent study on the chemical stabilization of a Class A-2-7 (3) lateritic soil, with corn cob ash (CCA) as case study. The objectives are to establish a nexus between cation exchange capacity of the soil, the alkaline forming compounds in CCA and percentage CCA addition to soil beyond which no more improvement in strength properties can be achieved; and to propose feasible chemical reactions to explain the chemical stabilization of the lateritic soil with CCA alone. The lateritic soil, as well as CCA of pozzolanic quality Class C were separately analysed for their metallic oxide composition using the X-Ray Fluorescence technique. The cation exchange capacity (CEC) of the soil and the CCA were computed theoretically using the percentage composition of the base cations Ca²⁺, Mg²⁺ K⁺ and Na²⁺ as 1.48 meq/100 g and 61.67 meq/100 g respectively, thus indicating a ratio of 0.024 or 2.4%. This figure, taken as the theoretical amount required to just fill up the exchangeable sites of the clay molecules, compares well with the laboratory observation of 1.5% for the optimum level of CCA addition to lateritic soil. The paper went on to present chemical reaction equations between the alkaline earth metals in the CCA and the silica in the lateritic soil to form silicates, thereby proposing an extension of the theory of mechanism of soil stabilization to cover chemical stabilization with pozzolanic ash only. The paper concluded by recommending further research on the molecular structure of soils stabilized with pozzolanic waste ash alone, with a view to confirming the chemical equations advanced in the study.

Keywords: Cation exchange capacity, corn cob ash, lateritic soil, soil stabilization.

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Authors: Chidentree Treesatayapun

Abstract:

A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.

Keywords: Neuro-Fuzzy, learning algorithm, nonlinear discrete time.

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Authors: Hector Barrios-Piña, Georgia García-Arellano, Salvador García-Rodríguez, Gerardo Bocanegra-García, Shashi Kant

Abstract:

This work shows the methodology of application and the effectiveness of the Flipped Learning technique for Civil Engineering laboratory classes. It was experimented by some of the professors of the Department of Civil Engineering at Tecnológico de Monterrey while teaching their laboratory classes. A total of 28 videos were created. The videos primarily demonstrate instructions of the experimental practices other than the usage of tools and materials. The technique allowed the students to prepare for their classes in advance. A survey was conducted on the participating professors and students (semester of August-December 2019) to quantify the effectiveness of the Flipped Learning technique. The students reported it as an excellent way of improving their learning aptitude, including self-learning whereas, the professors felt it as an efficient technique for optimizing their class session, which also provided an extra slot for class-interaction. A comparison of grades was analyzed between the students of the traditional classes and with Flipped Learning. It did not distinguish the benefits of Flipped Learning. However, the positive responses from the students and the professors provide an impetus for continuing and promoting the Flipped Learning technique in future classes.

Keywords: Flipped learning, laboratory classes, educational innovation, civil engineering, higher education, competences.

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Authors: Kristina Davoian, Wolfram-M. Lippe

Abstract:

Evolutionary Programming (EP) represents a methodology of Evolutionary Algorithms (EA) in which mutation is considered as a main reproduction operator. This paper presents a novel EP approach for Artificial Neural Networks (ANN) learning. The proposed strategy consists of two components: the self-adaptive, which contains phenotype information and the dynamic, which is described by genotype. Self-adaptation is achieved by the addition of a value, called the network weight, which depends on a total number of hidden layers and an average number of neurons in hidden layers. The dynamic component changes its value depending on the fitness of a chromosome, exposed to mutation. Thus, the mutation step size is controlled by two components, encapsulated in the algorithm, which adjust it according to the characteristics of a predefined ANN architecture and the fitness of a particular chromosome. The comparative analysis of the proposed approach and the classical EP (Gaussian mutation) showed, that that the significant acceleration of the evolution process is achieved by using both phenotype and genotype information in the mutation strategy.

Keywords: Artificial Neural Networks (ANN), Learning Theory, Evolutionary Programming (EP), Mutation, Self-Adaptation.

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Authors: Rossukhon Makaramani, Supanan Sittilerd

Abstract:

This study is about an application of King Bhumibol Adulyadej’s “Learn Wisely” (LW) concept in instructional design and management process at the Faculty of Education, Suan Sunahdha Rajabhat University. The concept suggests four strategies for true learning. Related literature and significant LW methods in teaching and learning are also reviewed and then applied in designing a pedagogy learning module. The design has been implemented in three classrooms with a total of 115 sophomore student teachers. After one consecutive semester of managing and adjusting the process by instructors and experts using collected data from minutes, assessment of learning management, satisfaction and learning achievement of the students, it is found that the effective SSRU model of LW instructional method comprises of five steps.

Keywords: Instructional Design, Learn Wisely Strategy, Pedagogy Learning Module, Teaching Method.

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Authors: Panagiotis Kosmas, Panayiotis Zaphiris

Abstract:

Embodied Cognition (EC) as a learning paradigm is based on the idea of an inseparable link between body, mind, and environment. In recent years, the advent of theoretical learning approaches around EC theory has resulted in a number of empirical studies exploring the implementation of the theory in education. This systematic literature overview identifies the mainstream of EC research and emphasizes on the implementation of the theory across learning environments. Based on a corpus of 43 manuscripts, published between 2013 and 2017, it sets out to describe the range of topics covered under the umbrella of EC and provides a holistic view of the field. The aim of the present review is to investigate the main issues in EC research related to the various learning contexts. Particularly, the study addresses the research methods and technologies that are utilized, and it also explores the integration of body into the learning context. An important finding from the overview is the potential of the theory in different educational environments and disciplines. However, there is a lack of an explicit pedagogical framework from an educational perspective for a successful implementation in various learning contexts.

Keywords: Embodied cognition, embodied learning, education, technology, schools.

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Authors: Sid-Ahmed. Selouani, Tang-Ho Lê, Chadia Moghrabi, Benoit Lanteigne, Jean Roy

Abstract:

A Web-based learning tool, the Learn IN Context (LINC) system, designed and being used in some institution-s courses in mixed-mode learning, is presented in this paper. This mode combines face-to-face and distance approaches to education. LINC can achieve both collaborative and competitive learning. In order to provide both learners and tutors with a more natural way to interact with e-learning applications, a conversational interface has been included in LINC. Hence, the components and essential features of LINC+, the voice enhanced version of LINC, are described. We report evaluation experiments of LINC/LINC+ in a real use context of a computer programming course taught at the Université de Moncton (Canada). The findings show that when the learning material is delivered in the form of a collaborative and voice-enabled presentation, the majority of learners seem to be satisfied with this new media, and confirm that it does not negatively affect their cognitive load.

Keywords: E-leaning, Knowledge Network, Speech recognition, Speech synthesis.

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Authors: José Paulo Leal, Ricardo Queirós

Abstract:

Standards for learning objects focus primarily on content presentation. They were already extended to support automatic evaluation but it is limited to exercises with a predefined set of answers. The existing standards lack the metadata required by specialized evaluators to handle types of exercises with an indefinite set of solutions. To address this issue existing learning object standards were extended to the particular requirements of a specialized domain. A definition of programming problems as learning objects, compatible both with Learning Management Systems and with systems performing automatic evaluation of programs, is presented in this paper. The proposed definition includes metadata that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements of the evaluation engine; and the roles of different assets - tests cases, program solutions, etc. The EduJudge project and its main services are also presented as a case study on the use of the proposed definition of programming problems as learning objects.

Keywords: Content Packaging, eLearning Services, Interoperability, Learning Objects.

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

Abstract:

This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. Crisp description for a concept usually cannot represent human knowledge completely and practically. In the proposed Learning Classifier System initial population is constructed as a random collection of HPR–trees (related production rules) and crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is suggested for the proposed system and based on Subsumption Matrix (SM), a suitable fitness function is proposed. Suitable genetic operators are proposed for the chosen chromosome representation method. For implementing reinforcement a suitable reward and punishment scheme is also proposed. Experimental results are presented to demonstrate the performance of the proposed system.

Keywords: Hierarchical Production Rule, Data Mining, Learning Classifier System, Fuzzy Subsumption Relation, Subsumption matrix, Reinforcement Learning.

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Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

Abstract:

Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: Basketball, deep learning, feature extraction, single-camera, tracking.

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Authors: Amudha Kadirvelu, Sunil Gurtu, Sivalal Sadasivan

Abstract:

Pharmacology curriculum plays an integral role in medical education. Learning pharmacology to choose and prescribe drugs is a major challenge encountered by students. We developed pharmacology applied learning activities for first year medical students that included realistic clinical situations with escalating complications which required the students to analyze the situation and think critically to choose a safe drug. Tutor feedback was provided at the end of session. Evaluation was done to assess the students- level of interest and usefulness of the sessions in rational selection of drugs. Majority (98 %) of the students agreed that the session was an extremely useful learning exercise and agreed that similar sessions would help in rational selection of drugs. Applied learning sessions in the early years of medical program may promote deep learning and bridge the gap between pharmacology theory and clinical practice. Besides, it may also enhance safe prescribing skills.

Keywords: Medical education, pharmacology curriculum, applied learning, safe prescribing.

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Authors: Dante J. Dorantes-González, Aldrin Balsa-Yepes

Abstract:

Existing learning techniques such as problem-based learning, project-based learning, or case study learning are learning techniques that focus mainly on technical details, but give no specific guidelines on learner’s experience and emotional learning aspects such as arousal salience and valence, being emotional states important factors affecting engagement and retention. Some approaches involving emotion in educational settings, such as social and emotional learning, lack neuroscientific rigorousness and use of specific neurobiological mechanisms. On the other hand, neurobiology approaches lack educational applicability. And educational approaches mainly focus on cognitive aspects and disregard conditioning learning. First, authors start explaining the reasons why it is hard to learn thoughtfully, then they use the method of neurobiological mapping to track the main limbic system functions, such as the reward circuit, and its relations with perception, memories, motivations, sympathetic and parasympathetic reactions, and sensations, as well as the brain cortex. The authors conclude explaining the major finding: The mechanisms of nonconscious learning and the triggers that guarantee long-term memory potentiation. Afterward, the educational framework for practical application and the instructors’ guidelines are established. An implementation example in engineering education is given, namely, the study of tuned-mass dampers for earthquake oscillations attenuation in skyscrapers. This work represents an original learning technique based on nonconscious learning mechanisms to enhance long-term memories that complement existing cognitive learning methods.

Keywords: Emotion, emotion-enhanced memory, learning technique, STEM.

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

Abstract:

Currently the most prevalent deep learning methods require a large amount of data for training, whereas few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: Few-shot learning, triplet network, adaptive margin, deep learning.

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Authors: Christopher Reichstein, Ralf-Christian Härting, Martina Häußler

Abstract:

With a continuously increasing speed of information exchange on the World Wide Web, retailers in the E-Commerce sector are faced with immense possibilities regarding different online purchase processes like dynamic price settings. By use of Dynamic Pricing, retailers are able to set short time price changes in order to optimize producer surplus. The empirical research illustrates the basics of Dynamic Pricing and identifies six influencing factors of Dynamic Pricing. The results of a structural equation modeling approach show five main drivers increasing the potential of dynamic price settings in the E-Commerce. Influencing factors are the knowledge of customers’ individual willingness to pay, rising sales, the possibility of customization, the data volume and the information about competitors’ pricing strategy.

Keywords: E-commerce, empirical research, experts, Dynamic Pricing (DP), influencing factors, potentials.

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Authors: Pelin Demirçivi, Gülhayat Nasün-Saygılı

Abstract:

Boron minerals are very useful for various industrial activities, such as glass industry and detergent industry, due to its mechanical and chemical properties. During the production of boron compounds, many of these are introduced into the environment in the form of waste. Boron is also an important micro nutrient for the plants to vegetate but if it exists in high concentrations, it could have toxic effects. The maximum boron level in drinking water for human health is given as 0.3 mg/L in World Health Organization (WHO) standards. The toxic effects of boron should be noted especially for dry regions, thus, in recent years, increasing attention has been paid to remove the boron from waste waters. In this study, boron removal is implemented by ion exchange process using Amberlite IRA-743 resin. Amberlite IRA-743 resin is a boron specific resin and it belongs to the polymerizate sorbent group within the aminopolyol functional group. Batch studies were performed to investigate the effects of various experimental parameters, such as adsorbent dose, initial concentration and pH, on the removal of boron. It is found that, when the adsorbent dose increases removal of boron from the liquid phase increases. However, an increase in the initial concentration decreases the removal of boron. The effective pH values for removal of boron are determined between 8.5 and 9. Equilibrium isotherms were also analyzed by Langmuir and Freundlich isotherm models. The Langmuir isotherm is obeyed better than the Freundlich isotherm.

Keywords: Amberlite resin, boron removal, ion exchange, isotherm models.

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: Deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator.

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Authors: Salwa Aftab, Sehrish Riaz

Abstract:

The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.

Keywords: Academic performance, correlation, grade sensitivity, learning motivation, regression.

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