Search results for: living and learning conditions

Authors: Tajinder Pal Singh

Abstract:

Teaching of mathematics to engineering students is an open ended problem in education. The main goal of mathematics learning for engineering students is the ability of applying a wide range of mathematical techniques and skills in their engineering classes and later in their professional work. Most of the undergraduate engineering students and faculties feels that no efforts and attempts are made to demonstrate the applicability of various topics of mathematics that are taught thus making mathematics unavoidable for some engineering faculty and their students. The lack of understanding of concepts in engineering mathematics may hinder the understanding of other concepts or even subjects. However, for most undergraduate engineering students, mathematics is one of the most difficult courses in their field of study. Most of the engineering students never understood mathematics or they never liked it because it was too abstract for them and they could never relate to it. A right balance of application and concept based teaching can only fulfill the objectives of teaching mathematics to engineering students. It will surely improve and enhance their problem solving and creative thinking skills. In this paper, some practical (informal) ways of making mathematics-teaching application based for the engineering students is discussed. An attempt is made to understand the present state of teaching mathematics in engineering colleges. The weaknesses and strengths of the current teaching approach are elaborated. Some of the causes of unpopularity of mathematics subject are analyzed and a few pragmatic suggestions have been made. Faculty in mathematics courses should spend more time discussing the applications as well as the conceptual underpinnings rather than focus solely on strategies and techniques to solve problems. They should also introduce more ‘word’ problems as these problems are commonly encountered in engineering courses. Overspecialization in engineering education should not occur at the expense of (or by diluting) mathematics and basic sciences. The role of engineering education is to provide the fundamental (basic) knowledge and to teach the students simple methodology of self-learning and self-development. All these issues would be better addressed if mathematics and engineering faculty join hands together to plan and design the learning experiences for the students who take their classes. When faculties stop competing against each other and start competing against the situation, they will perform better. Without creating any administrative hassles these suggestions can be used by any young inexperienced faculty of mathematics to inspire engineering students to learn engineering mathematics effectively.

Keywords: Application based learning, conceptual learning, engineering mathematics, word problem.

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Authors: K. Divya, G. Sugumaran

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This paper proposes an improved Maximum Power Point Tracking of PhotoVoltaic system using Deterministic Partical Swarm Optimization technique. This method has the ability to track the maximum power under varying environmental conditions i.e. partial shading conditions. The advantage of this method, particles moves in the restricted value of velocity to achieve the maximum power. SEPIC converter is employed to boost up the voltage of PV system. To estimate the value of the proposed method, MATLAB simulation carried out under partial shading condition.

Keywords: DPSO, Partial shading condition, P&O, PV, SEPIC.

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Authors: Abdurazzag Ali Aburas, Indira Rustempasic, Indira Muhic, Busra Gheith Yildiz

Abstract:

At present time, competition, unpredictable fluctuations have made communication engineering education in the global sphere really difficult. Confront with new situation in the engineering education sector. Communication engineering education has to be reformed and ready to use more advanced technologies. We realized that one of the general problems of student`s education is that after graduating from their universities, they are not prepared to face the real life challenges and full skilled to work in industry. They are prepared only to think like engineers and professionals but they also need to possess some others non-technical skills. In today-s environment, technical competence alone is not sufficient for career success. Employers want employees (graduate engineers) who have good oral and written communication (soft) skills. It does require for team work, business awareness, organization, management skills, responsibility, initiative, problem solving and IT competency. This proposed curriculum brings interactive, creative, interesting, effective learning methods, which includes online education, virtual labs, practical work, problem-based learning (PBL), and lectures given by industry experts. Giving short assignments, presentations, reports, research papers and projects students can significantly improve their non-technical skills. Also, we noticed the importance of using ICT technologies in engineering education which used by students and teachers, and included that into proposed teaching and learning methods. We added collaborative learning between students through team work which builds theirs skills besides course materials. The prospective on this research that we intent to update communication engineering curriculum in order to get fully constructed engineer students to ready for real industry work.

Keywords: communication engineering, curriculum education, ICT, industry

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Authors: Marilena Ianculescu, Adriana Alexandru

Abstract:

Internet of Health Things (IoHT) has already proved to be a persuasive means to support a proper assessment of the living conditions by collecting a huge variety of data. For a customized health management of a senior patient, IoHT provides the capacity to build a dynamic solution for sustaining the shift inside the patient-physician relationship by allowing a real-time and continuous remote monitoring of the health status, well-being, safety and activities of the senior, especially in a non-clinical environment. Thus, is created a win-win solution in which both the patient and the physician enhance their involvement and shared decision-making, with significant outcomes. Health monitoring systems in smart environments are becoming a viable alternative to traditional healthcare solutions. The ongoing “Non-invasive monitoring and health assessment of the elderly in a smart environment (RO-SmartAgeing)” project aims to demonstrate that the existence of complete and accurate information is critical for assessing the health condition of the seniors, improving wellbeing and quality of life in relation to health. The researches performed inside the project aim to highlight how the management of IoHT devices connected to the RO-SmartAgeing platform in a secure way by using a role-based access control system, can allow the physicians to provide health services at a high level of efficiency and accessibility, which were previously only available in hospitals. The project aims to identify deficient aspects in the provision of health services tailored to a senior patient’s specificity and to offer a more comprehensive perspective of proactive and preventive medical acts.

Keywords: Health management, Internet of Health Things, remote monitoring, senior patient.

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Authors: Natarajan. E, Ganapathy Sundaram. E

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Fixed-bed slow pyrolysis experiments of rice husk have been conducted to determine the effect of pyrolysis temperature, heating rate, particle size and reactor length on the pyrolysis product yields. Pyrolysis experiments were performed at pyrolysis temperature between 400 and 600°C with a constant heating rate of 60°C/min and particle sizes of 0.60-1.18 mm. The optimum process conditions for maximum liquid yield from the rice husk pyrolysis in a fixed bed reactor were also identified. The highest liquid yield was obtained at a pyrolysis temperature of 500°C, particle size of 1.18-1.80 mm, with a heating rate of 60°C/min in a 300 mm length reactor. The obtained yield of, liquid, gas and solid were found be in the range of 22.57-31.78 %, 27.75-42.26 % and 34.17-42.52 % (all weight basics) respectively at different pyrolysis conditions. The results indicate that the effects of pyrolysis temperature and particle size on the pyrolysis yield are more significant than that of heating rate and reactor length. The functional groups and chemical compositions present in the liquid obtained at optimum conditions were identified by Fourier Transform-Infrared (FT-IR) spectroscopy and Gas Chromatography/ Mass Spectroscopy (GC/MS) analysis respectively.

Keywords: Slow pyrolysis, Rice husk, Recycling, Biomass.

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Authors: Yuan J. Lui

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Prospective readers can quickly determine whether a document is relevant to their information need if the significant phrases (or keyphrases) in this document are provided. Although keyphrases are useful, not many documents have keyphrases assigned to them, and manually assigning keyphrases to existing documents is costly. Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm. The algorithm approaches the problem of keyphrase extraction as a classification task, and uses a combination of statistical and computational linguistics techniques, a new set of attributes, and a new machine learning method to distinguish keyphrases from non-keyphrases. The experiments indicate that this algorithm performs better than other keyphrase extraction tools and that it significantly outperforms Microsoft Word 2000-s AutoSummarize feature. The domain independence of this algorithm has also been confirmed in our experiments.

Keywords: classification, keyphrase extraction, machine learning, summarization

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Authors: Vidhu Mitha Goutham, Ruma Mukherjee

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The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.

Keywords: Attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation.

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Authors: Swapna Bhargavi Gantasala

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If teamwork is the key to organizational learning, productivity and growth, then, why do some teams succeed in achieving these, while others falter at different stages? Building teams in higher education institutions has been a challenge and an open-ended constructivist approach was considered on an experimental basis for this study to address this challenge. For this research, teams of students from the MBA program were chosen to study the effect of teamwork in learning, the motivation levels among student team members, and the effect of collaboration in achieving team goals. The teams were built on shared vision and goals, cohesion was ensured, positive induction in the form of faculty mentoring was provided for each participating team and the results have been presented with conclusions and suggestions.

Keywords: Collaboration, Leadership, Motivation, Reinforcement Teamwork.

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Authors: Nikolina Ribarić

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This paper compares the readiness of chemistry teachers to use information and communication technologies in chemistry in 2018 and 2021. A survey conducted in 2018 on a sample of teachers showed that most teachers occasionally use visualization and digitization tools in chemistry teaching (65%), but feel that they are not educated enough to use them (56%). Also, most teachers do not have adequate equipment in their schools and are not able to use ICT in teaching or digital tools for visualization and digitization of content (44%). None of the teachers find the use of digitization and visualization tools useless. Furthermore, a survey conducted in 2021 shows that most teachers occasionally use visualization and digitization tools in chemistry teaching (83%). Also, the research shows that some teachers still do not have adequate equipment in their schools and are not able to use ICT in chemistry teaching or digital tools for visualization and digitization of content (14%). Advances in the use of ICT in chemistry teaching are linked to pandemic conditions and the obligation to conduct online teaching. The share of 14% of teachers who still do not have adequate equipment to use digital tools in teaching is worrying.

Keywords: Chemistry, digital content, e-learning, ICT, visualization.

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Authors: Ackmez Mudhoo, Pravish Rye Moorateeah, Romeela Mohee

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This paper presents the results of the preliminary investigation of microwave (MW) irradiation pretreatments on the anaerobic digestion of food residues using biochemical methane potential (BMP) assays. Low solids systems with a total solids (TS) content ranging from 5.0-10.0% were analyzed. The inoculum to bulk mass of substrates to water ratio was 1:2:2 (mass basis). The experimental conditions for pretreatments were as follows: a control (no MW irradiation), two runs with MW irradiation for 15 and 30 minutes at 320 W, and another two runs with MW irradiation at 528 W for 30 and 60 minutes. The cumulative biogas production were 6.3 L and 8.7 L for 15min/320 W and 30min/320 W MW irradiation conditions, respectively, and 10.5 L and 11.4 L biogas for 30min/528 W and 60min/528 W, respectively, as compared to the control giving 5.8 L biogas. Both an increase in exposure time of irradiation and power of MW had increased the rate and yield of biogas. Singlefactor ANOVA tests (p<0.05) indicated that the variations in VS, TS, COD and cumulative biogas generation were significantly different for the pretreatment conditions. Results from this study indicated that MW irradiation had enhanced the biogas production and degradation of total solids with a significant improvement in VS and COD solubilization.

Keywords: microwave irradiation, pretreatment, anaerobic digestion, food residues.

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Authors: Jacqueline R. T. Alipo-on, Francesca I. F. Escobar, Myles J. T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis on the ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heart beat types. The dataset used in this work is the synthetic MIT-Beth Israel Hospital (MIT-BIH) Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: Heartbeat classification, convolutional neural network, electrocardiogram signals, ECG signals, generative adversarial networks, long short-term memory, LSTM, ResNet-50.

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Authors: Jérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag

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Term Extraction, a key data preparation step in Text Mining, extracts the terms, i.e. relevant collocation of words, attached to specific concepts (e.g. genetic-algorithms and decisiontrees are terms associated to the concept “Machine Learning" ). In this paper, the task of extracting interesting collocations is achieved through a supervised learning algorithm, exploiting a few collocations manually labelled as interesting/not interesting. From these examples, the ROGER algorithm learns a numerical function, inducing some ranking on the collocations. This ranking is optimized using genetic algorithms, maximizing the trade-off between the false positive and true positive rates (Area Under the ROC curve). This approach uses a particular representation for the word collocations, namely the vector of values corresponding to the standard statistical interestingness measures attached to this collocation. As this representation is general (over corpora and natural languages), generality tests were performed by experimenting the ranking function learned from an English corpus in Biology, onto a French corpus of Curriculum Vitae, and vice versa, showing a good robustness of the approaches compared to the state-of-the-art Support Vector Machine (SVM).

Keywords: Text-mining, Terminology Extraction, Evolutionary algorithm, ROC Curve.

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Authors: Sajed A. Habib

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Problem-based learning (PBL) is a student-centered pedagogy that originated in the medical field and has also been used extensively in other knowledge disciplines with recognized advantages and limitations. PBL has been used in various undergraduate engineering programs with mixed outcomes. The current fourth industrial revolution (digital era or Industry 4.0) has made it essential for many science and engineering students to receive effective training in advanced courses such as industrial automation and robotics. This paper presents a case study at Assumption University of Thailand, where a PBL-like approach was used to teach some aspects of automation and robotics to selected groups of undergraduate engineering students. These students were given some basic level training in automation prior to participating in a subsequent training session in order to solve technical problems with increased complexity. The participating students’ evaluation of the training sessions in terms of learning effectiveness, skills enhancement, and incremental knowledge following the problem-solving session was captured through a follow-up survey consisting of 14 questions and a 5-point scoring system. From the most recent training event, an overall 70% of the respondents indicated that their skill levels were enhanced to a much greater level than they had had before the training, whereas 60.4% of the respondents from the same event indicated that their incremental knowledge following the session was much greater than what they had prior to the training. The instructor-facilitator involved in the training events suggested that this method of learning was more suitable for senior/advanced level students than those at the freshmen level as certain skills to effectively participate in such problem-solving sessions are acquired over a period of time, and not instantly.

Keywords: Automation, industry 4.0, model-based design training, problem-based learning.

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Authors: Joseph Maloba Makokha

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Idea generation is an important part of the design process, and many strategies to support this stage have been developed. As artificial intelligence (AI) gains adoption in many domains, we need to understand its role, if any, in the design process. This paper introduces the concept of a “Disruptive Interjector”, an AI system that frequently interjects with suggestions based on observing what a user does. The concept emanates from a study that was conducted with pairs of humans on one hand, and human-AI pairs on the other collaborating on idea generation by sketching. Results from a study show that participants who collaborated with, and took cues from the AI sketch suggestions generated more ideas; and also had more ideas ranked by experts as “creative” compared to two humans working together on the same tasks. It is notable that while researchers from diverse fields of engineering, psychology, art and others have explored conditions and environments that enhance people's creativity - and have provided insights on creativity in general - there still exists a gap on the role that AI can play on creativity. We attempt to narrow this gap.

Keywords: Artificial intelligence, design collaboration, creativity, human-machine collaboration, machine learning.

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Authors: Vladimir Aleksandrovich Rogov, Ghorbani Siamak

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Determination of optimal conditions of machining parameters is important to reduce the production cost and achieve the desired surface quality. This paper investigates the influence of cutting parameters on surface roughness and natural frequency in turning of aluminum alloy AA2024. The experiments were performed at the lathe machine using two different cutting tools made of AISI 5140 and carbide cutting insert coated with TiC. Turning experiments were planned by Taguchi method L₉ orthogonal array.Three levels for spindle speed, feed rate, depth of cut and tool overhang were chosen as cutting variables. The obtained experimental data has been analyzed using signal to noise ratio and analysis of variance. The main effects have been discussed and percentage contributions of various parameters affecting surface roughness and natural frequency, and optimal cutting conditions have been determined. Finally, optimization of the cutting parameters using Taguchi method was verified by confirmation experiments.

Keywords: Turning, Cutting conditions, Surface roughness, Natural frequency, Taguchi method, ANOVA, S/N ratio.

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Authors: Lorena Alemán de la Garza, Marcela Georgina Gómez-Zermeño

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This paper presents the SolarSPELL case study that aims to generate information on the use of indicators that help evaluate the pedagogical quality of a digital library resources. SolarSPELL is a solar-powered digital library with WiFi connectivity. It offers a variety of open educational resources selected for their potential for the digital transformation of educational practices and the achievement of the 2030 Agenda for Sustainable Development, adopted by all United Nations Member States. The case study employed a quantitative methodology and the research instrument was applied to 55 teachers, directors and librarians. The results indicate that it is possible to strengthen the pedagogical quality of open educational resources, through actions focused on improving temporal and technological parameters. They also reveal that users believe that SolarSPELL improves the teaching-learning processes and motivates the teacher to improve his or her development. This study provides valuable information on a tool that supports teaching-learning processes and facilitates connectivity with renewable energies that improves the teacher training in active methodologies for ecosystem learning.

Keywords: Educational innovation, digital library, pedagogical quality, solar energy, teacher training, sustainable development.

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Authors: Idris Elfeituri

Abstract:

In the current study, energy and exergy analysis of a 65 MW steam power plant was carried out. This study investigated the effect of variations of overall conductance of the super heater on the performance of an existing steam power plant located in Derna, Libya. The performance of the power plant was estimated by a mathematical modelling which considers the off-design operating conditions of each component. A fully interactive computer program based on the mass, energy and exergy balance equations has been developed. The maximum exergy destruction has been found in the steam generation unit. A 50% reduction in the design value of overall conductance of the super heater has been achieved, which accordingly decreases the amount of the net electrical power that would be generated by at least 13 MW, as well as the overall plant exergy efficiency by at least 6.4%, and at the same time that would cause an increase of the total exergy destruction by at least 14 MW. The achieved results showed that the super heater design and operating conditions play an important role on the thermodynamics performance and the fuel utilization of the power plant. Moreover, these considerations are very useful in the process of the decision that should be taken at the occasions of deciding whether to replace or renovate the super heater of the power plant.

Keywords: Exergy, super-heater, fouling, steam power plant, off-design.

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Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

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In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: Image processing, Illumination equalization, Shadow filtering, Object detection, Colour models, Image segmentation.

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Authors: Fotis N. Koumboulis, Michael G. Skarpetis, Maria P. Tzamtzi

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The problem of robust disturbance rejection (RDR) using a proportional state feedback controller is studied for the case of Left Invertible MIMO generalized state space linear systems with nonlinear uncertain structure. Sufficient conditions for the problem to have a solution are established. The set of all proportional feedback controllers solving the problem subject to these conditions is analytically determined.

Keywords: System theory, uncertain systems, robust control, singular systems.

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Authors: Proud Arunrangsiwed

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Crisis management strategies could be found in various curriculums, not only in schools of business, but also schools of communication. Young students, such as freshmen and sophomores of undergraduate schools, may not care about learning crisis management strategies. Moreover, crisis management strategies are not a topic art students are familiar with. The current paper discusses a way to adapt entertainment media into a crisis management lesson, and the importance of learning crisis management strategies in the school of animation. Students could learn crisis management strategies by watching movies with content about a crisis and responding to crisis responding. The students should then participate in follow up discussions related to the strategies that were used to address the crisis, as well as their success in solving the crisis.

Keywords: Situational crisis communication theory, crisis response strategies, media effect, unintentional effect.

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Authors: L. A. Muhammad, M. S. Argungu

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Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

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Authors: Ryuji Yamazaki, Masahiro Kochi, Weiran Zhu, Hiroko Kase

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In care for older adults, behavioral and psychological symptoms of dementia (BPSD) like agitation and aggression are distressing for patients and their caretakers, often resulting in premature institutionalization with increased costs of care. To improve mood and mitigate symptoms, as a non-pharmaceutical approach, emotion-oriented therapy like reminiscence work is adopted in face-to-face communication. Telecommunication support is expected to be provided by robotic media as a bridge for digital divide for those with dementia and facilitate social interaction both verbally and nonverbally. The purpose of this case study is to explore the conditions in which robotic media can effectively attract attention from older adults with dementia and promote their well-being. As a pilot study, we introduced the pillow-phone Hugvie^®, a huggable humanly shaped communication medium to five residents with dementia at a care facility, to investigate how the following conditions work for the elderly when they use the medium; 1) no sound, 2) radio, non-interactive, 3) daily conversation, and 4) reminiscence work. As a result, under condition 4, reminiscence work, the five participants kept concentration in interacting with the medium for a longer duration than other conditions. In condition 4, they also showed larger amount of utterances than under other conditions. These results indicate that providing topics related to personal histories through robotic media could affect communication positively and should, therefore, be further investigated. In addition, the issue of ethical implications by using persuasive technology that affects emotions and behaviors of older adults is also discussed.

Keywords: BPSD, reminiscence, tactile telecommunication, utterances.

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Authors: José R. G. Braga, Joice B. Mendes, Guilherme H. Caponetto, Alexandre C. B. Ramos

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With major technological advances and to reduce the cost of training apprentices for real-time critical systems, it was necessary the development of Intelligent Tutoring Systems for training apprentices in these systems. These systems, in general, have interactive features so that the learning is actually more efficient, making the learner more familiar with the mechanism in question. In the home stage of learning, tests are performed to obtain the student's income, a measure on their use. The aim of this paper is to present a framework to model an Intelligent Tutoring Systems using the UML language. The various steps of the analysis are considered the diagrams required to build a general model, whose purpose is to present the different perspectives of its development.

Keywords: Computer based training, Hypermedia, Software modeling.

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Authors: Gracia V. Navarro, Maria V. Gonzalez, Carlos G. Reed

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The eudaimonic perspective in philosophy and psychology suggests that a good life is closely related to developing oneself in order to contribute to the well-being and happiness of other people and of the world as a whole. Educational psychology can help to achieve this through the design and validation of educative models. Since 2004, the University of Concepcion and other Chilean universities apply an educative model to train socially responsible professionals, people that in the exercise of their profession contribute to generate equity for the development and assess the impacts of their decisions, opting for those that serve the common good. The main aim is to identify if a relationship exists between achieved learning, attitudes toward social responsibility, self-attribution of socially responsible behavior, value type, professional behavior observed and, participation in a specific model to train socially responsible (SR) professionals. The Achieved Learning and Attitudes Toward Social Responsibility Questionnaire, interview with employers and Values Questionnaire and Self-attribution of SR Behavior Questionnaire is applied to 394 students and graduates, divided into experimental and control groups (trained and not trained under the educative model), in order to identify the professional behavior of the graduates. The results show that students and graduates perceive cognitive, affective and behavioral learning, with significant differences in attitudes toward social responsibility and self-attribution of SR behavior, between experimental and control. There are also differences in employers' perceptions about the professional practice of those who were trained under the model and those who were not. It is concluded that the educative model has an impact on the learning of social responsibility and educates for a full life. It is also concluded that it is necessary to identify mediating variables of the model effect.

Keywords: Educative model, good life, professional social responsibility (SR), values.

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Authors: H. A. Taner, V. Önen

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A suitable choice of flotation parameters and reagents have a strong effect on the effectiveness of flotation process. The objective of this paper is to give an overview of the flotation of chalcopyrite with the different conditions and dispersants. Flotation parameters such as grinding time, pH, type, and dosage of dispersant were investigated. In order to understand the interaction of some dispersants, sodium silicate, sodium hexametaphosphate and sodium polyphosphate were used. The optimum results were obtained at a pH of 11.5 and a grinding time of 10 minutes. A copper concentrate was produced assaying 29.85% CuFeS₂ and 65.97% flotation recovery under optimum rougher flotation conditions with sodium silicate.

Keywords: Chalcopyrite, dispersant, flotation, copper.

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Authors: E. Thipe, T. Workneh, A. Odindo, M. Laing

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The postharvest quality management of tomatoes is important to limit the amount of losses that occur due to deterioration between harvest and consumption. This study was undertaken to investigate the effects of pre- and postharvest integrated agrotechnologies, involving greenhouse microclimate and postharvest storage conditions, on the postharvest quality attributes of four tomato cultivars. Tomato fruit firmness, colour (hue angle (h°) and L* value), pH and total soluble solids for the cultivars Bona, Star 9037, Star 9009 and Zeal, grown in a fan-pad evaporativelycooled and an open-ended naturally-ventilated tunnel, were harvested at the mature-green stage. The tomatoes were stored for 28 days under cold storage conditions, with a temperature of 13°C and RH of 85%, and under ambient air conditions, with a temperature of 23± 2°C and RH of 52± 4%. This study has provided information on the effect of integrated pre-harvest and postharvest agro-technologies, involving greenhouse microclimate and postharvest storage environment on the postharvest quality attributes of four of the tomato cultivars in South Africa. NVT-grown tomatoes retained better textural qualities, but ripened faster by changing from green to red faster, although these were reduced under cold storage conditions. FPVT-grown tomatoes had lower firmness, but ripened slowly with higher colour attributes. With cold storage conditions, the firmness of FPVT-grown tomatoes was maintained. Cultivar Bona firmness and colour qualities depreciated the fastest, but it had higher TSS content and lower pH values. Star 9009 and Star 9037 presented better quality, by retaining higher firmness and ripening slowly, but they had the lowest TSS contents and high pH values, especially Star 9037. Cold storage improved the firmness of tomato cultivars with poor textural quality and faster colour changes.

Keywords: Greenhouse, micro-climate, tomato, postharvest quality, storage.

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Authors: Zain M. Al-Houri, Abbas S. Al-Omari

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Roadways in Amman city face many problems consequent upon poor drainage systems. Evaluation tools are necessary to identify those roads needing improvement in their drainage system, and those needing regular maintenance. This work aims at evaluating drainage conditions in selected roadways in Amman city with the intent of identifying the problems encountered in their drainage systems. Three sites in the vicinity of Amman city have been selected and then inspected via several field visits to determine the state of their existing drainage systems and define the major problems encountered in these systems. The evaluation tool used in this study is based on visual inspection supported by photographs that depicted the defined problems. Following the field assessment, the drainage system in each road was rated as excellent, fair, good, or poor. The study reveals that more than 60% of the roadways in the selected sites were in poor drainage conditions, which lead to tremendous environmental problems. This assessment serves as a guide for local decision makers to help plan for the maintenance of Amman city roadways drainage systems, and propose ways of managing the associated problems.

Keywords: Amman Stormwater, Drainage systems, Environmental problems, Roadways drainage.

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Authors: Rohit Choudhry, Kumkum Garg

Abstract:

In this paper, we propose a hybrid machine learning system based on Genetic Algorithm (GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators of highly correlated stocks, not only the stock to be predicted. The genetic algorithm is used to select the set of most informative input features from among all the technical indicators. The results show that the hybrid GA-SVM system outperforms the stand alone SVM system.

Keywords: Genetic Algorithms, Support Vector Machines, Stock Market Forecasting.

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Authors: Mia Sorensen

Abstract:

The introduction of haptic elements in a graphic user interfaces are becoming more widespread. Since haptics are being introduced rapidly into computational tools, investigating how these models affect Human-Computer Interaction would help define how to integrate and model new modes of interaction. The interest of this paper is to discuss and investigate the issues surrounding Haptic and Graphic User Interface designs (GUI) as separate systems, as well as understand how these work in tandem. The development of these systems is explored from a psychological perspective, based on how usability is addressed through learning and affordances, defined by J.J. Gibson. Haptic design can be a powerful tool, aiding in intuitive learning. The problems discussed within the text is how can haptic interfaces be integrated within a GUI without the sense of frivolity. Juxtaposing haptics and Graphic user interfaces has issues of motivation; GUI tends to have a performatory process, while Haptic Interfaces use affordances to learn tool use. In a deeper view, it is noted that two modes of perception, foveal and ambient, dictate perception. These two modes were once thought to work in tandem, however it has been discovered that these processes work independently from each other. Foveal modes interpret orientation is space which provide for posture, locomotion, and motor skills with variations of the sensory information, which instructs perceptions of object-task performance. It is contended, here, that object-task performance is a key element in the use of Haptic Interfaces because exploratory learning uses affordances in order to use an object, without meditating an experience cognitively. It is a direct experience that, through iteration, can lead to skill-sets. It is also indicated that object-task performance will not work as efficiently without the use of exploratory or kinesthetic learning practices. Therefore, object-task performance is not as congruently explored in GUI than it is practiced in Haptic interfaces.

Keywords: Affordances, Graphic User Interface, HapticInterfaces, Tool-Use, Object-Naming, Object-Task Performance

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Authors: Murniza Muhamad, Halimah Badioze Zaman, Azlina Ahmad

Abstract:

This study aims to conduct a preliminary investigation to determine the topic to be focused in developing Virtual Laboratory For Biology (VLab-Bio). Samples involved in answering the questionnaire are form five students (equivalent to A-Level) and biology teachers. Time and economical resources for the setting up and construction of scientific laboratories can be solved with the adaptation of virtual laboratories as an educational tool. Thus, it is hoped that the proposed virtual laboratory will help students to learn the abstract concepts in biology. Findings show that the difficult topic chosen is Cell Division and the learning objective to be focused in developing the virtual lab is “Describe the application of knowledge on mitosis in cloning".

Keywords: biology education, computer simulation, virtual laboratory, virtual reality

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