Search results for: Technology Enhanced Learning (TEL).

Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars, and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: Remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction.

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Authors: Reza Ariaeinejad, Norm Archer

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Self-management is becoming a new emphasis for healthcare systems around the world. But there are many different problems with adoption of new health-related intervention systems. The situation is even more complicated for chronically ill patients with disabilities, illiteracy, and impairment in judgment in addition to their conditions, or having multiple co-morbidities. Providing online decision support to manage patient health and to provide better support for chronically ill patients is a new way of dealing with chronic disease management. In this study, the importance of mobile technology through an m-Health system that supports self-management interventions including the care provider, family and social support, education and training, decision support, recreation, and ongoing patient motivation to promote adherence and sustainability of the intervention are discussed. A proposed theoretical model for adoption and sustainability of system use is developed, based on UTAUT2 and IS Continuance of Use models, both of which have been pre-validated through longitudinal studies. The objective of this paper is to show the importance of using mobile technology in adoption and sustainability of use of an m-Health system which will result in commercially sustainable self-management support for chronically ill patients.

Keywords: M-health, e-health, self-management, disease.

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Authors: Geir Sigurðsson

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This paper compares ancient Daoist and Confucian approaches to the human body as a locus for learning, edification or personal cultivation. While pointing out some major differences between ancient Chinese and mainstream Western visions of the body, it seeks at the same time inspiration in some seminal Western phenomenological and post-structuralist writings, in particular from Maurice Merleau-Ponty and Pierre Bourdieu. By clarifying the somewhat dissimilar scopes of foci found in Daoist and Confucian philosophies with regard to the role of and attitude to the body, the conclusion is nevertheless that their approaches are comparable, and that both traditions take the physical body to play a vital role in the cultivation of excellence. Lastly, it will be argued that cosmological underpinnings prevent the Confucian li from being rigid and invariable and that it rather emerges as a flexible learning device to train through active embodiment a refined sensibility for one’s cultural environment.

Keywords: Body, Confucianism, Daoism, li, phenomenology, ritual.

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: Adaptive sampling, batch bulk methyl methacrylate polymerization, large margin nearest neighbor regression, machine learning.

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Authors: Wooyoung Jung, Ghang Lee

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This paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM services. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.

Keywords: BIM adoption, BIM services, Hype Cycle model, Technology diffusion model.

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Authors: Dimitar Karastoyanov, Vladimir Monov

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The paper is concerned with the technological process of renovation of shafts used in industrial manufacturing for extruding of sheet material. In the classical renovation technologies, a chrome based coating is applied to the working surface of the shaft in galvanic baths. The process, however, is known to be exclusively harmful due to the waste cyanide products. In this work, we present an advanced nanotechnology based on nonelectric chemical laying of a nickel coating with included nanoparticles. The technology is environmentally harmless and the new coating features an increased hardness and wear resistance. Results from experimental tests of the nanostructured nickel coating are presented and discussed.

Keywords: Materials processing, nanoparticles, nickel coating, shafts renovation.

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Authors: Liang Wang, Wei Zhang

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Nowadays sustainable development has increasingly become an important research topic of engineering education all over the world. Engineering Education for Sustainable Development (EESD) highlighted the importance of addressing sustainable development in engineering practice. However, whether and how the professional engineering learning and experience affect those perceptions is an interesting research topic especially in Chinese context. Our study fills this gap by investigating perceptions bias of EESD among first-grade engineering students, fourth-grade engineering students and experienced engineers using a triple-dimensional model. Our goal is to find the effect of engineering learning and experience on sustainable development and make these learning and experiences more accessible for students and engineers in school and workplace context. The data (n = 138) came from a Likert questionnaire based on the triple-dimensional model of EESD adopted from literature reviews and the data contain 48 first-grade students, 56 fourth-grade students and 34 engineers with rich working experience from Environmental Engineering, Energy Engineering, Chemical Engineering and Civil Engineering in or graduated from Zhejiang University, China. One-way ANOVA analysis was used to find the difference in different dimensions among the three groups. The statistical results show that both engineering students and engineers have a well understanding of sustainable development in ecology dimension of EESD while there are significant differences among three groups as to the socio-economy and value rationality dimensions of EESD. The findings provide empirical evidence that both engineering learning and professional engineering experience are helpful to cultivate the cognition and perception of sustainable development in engineering education. The results of this work indicate that more practical content should be added to students’ engineering education while more theoretical content should be added to engineers’ training in order to promote the engineering students’ and engineers’ perceptions of sustainable development. In addition, as to the design of engineering courses and professional practice system for sustainable development, we should not only pay attention to the ecological aspects, but also emphasize the coordination of ecological, socio-economic and human-centered sustainable development (e.g., engineer's ethical responsibility).

Keywords: Engineering education, sustainable development, experienced engineers, engineering students.

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Authors: Ren-Junn Hwang, Chung-Chien Lu, Jain-Shing Wu

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Cloud outsource storage is one of important services in cloud computing. Cloud users upload data to cloud servers to reduce the cost of managing data and maintaining hardware and software. To ensure data confidentiality, users can encrypt their files before uploading them to a cloud system. However, retrieving the target file from the encrypted files exactly is difficult for cloud server. This study proposes a protocol for performing multikeyword searches for encrypted cloud data by applying k-nearest neighbor technology. The protocol ranks the relevance scores of encrypted files and keywords, and prevents cloud servers from learning search keywords submitted by a cloud user. To reduce the costs of file transfer communication, the cloud server returns encrypted files in order of relevance. Moreover, when a cloud user inputs an incorrect keyword and the number of wrong alphabet does not exceed a given threshold; the user still can retrieve the target files from cloud server. In addition, the proposed scheme satisfies security requirements for outsourced data storage.

Keywords: Fault-tolerance search, multi-keywords search, outsource storage, ranked search, searchable encryption.

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Authors: L. Nevrivova, K. Lang, M. Kotoucek, D. Vsiansky

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This entry concerned with dense silica bricks microstructure was produced as a part of a project within the Technology Agency of the Czech Republic which is being implemented in cooperation of the biggest producer of refractories the P-D Refractories CZ company with the research organisation Brno University of Technology. The paper is focused on the influence of mixture homogenisation and the influence of grain size of the mineraliser on the resulting utility properties of the material as well as its microstructure. It has a decisive influence on the durability of the material in a building structure. This paper is a continuation of a previously published study dealing with the suitability of various types of mineralising agents in terms of density, strength and mineral composition of silica brick. The entry describes the influence of the method of mixture homogenisation and the influence of granulometry of the applied Femineralising agent on the resulting silica microstructure. Porosity, density, phase composition and microstructure of the experimentally prepared silica bricks samples were examined and the results were discussed in context with the technology of homogenisation and firing temperature used. The properties of silica bricks samples were compared to the sample without any Fe-mineraliser.

Keywords: Silica bricks, Fe-mineraliser, mineralogical composition, new developed silica bricks.

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Authors: Helen Zhang

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Accurate segmentation of the airways from CT scans is crucial for early diagnosis of lung cancer. However, the existing airway segmentation algorithms often rely on thin-slice CT scans, which can be inconvenient and costly. This paper presents a set of machine learning-based 3D super-resolution algorithms along heterogenous dimensions to improve the resolution of thicker CT scans to reduce the reliance on thin-slice scans. To evaluate the efficacy of the super-resolution algorithms, quantitative assessments using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural SIMilarity index) were performed. The impact of super-resolution on airway segmentation accuracy is also studied. The proposed approach has the potential to make airway segmentation more accessible and affordable, thereby facilitating early diagnosis and treatment of lung cancer.

Keywords: 3D super-resolution, airway segmentation, thin-slice CT scans, machine learning.

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Authors: Haoyi Sheng

Abstract:

China's aging tendency is becoming increasingly severe, which leads to the embarrassing situation of "getting old before getting wealthy". The traditional pension model does not comply with the need of today. Relying on "Internet Plus", it can efficiently integrate information and resources and meet the personalized needs of elderly care. It can reduce the operating cost of community elderly care facilities and lay a technical foundation for providing better services for the elderly. The key for providing help for the elderly in the future is to effectively integrate technology, make good use of technology, and improve the efficiency of elderly care services. The effective integration of traditional home care, community care, intelligent elderly care equipment and medical resources to create the "Internet Plus" community intelligent pension service mode has become the future development trend of aging care. The research method of this paper is to collect literature and conduct theoretical research on community pension firstly. Secondly, the combination of suitable aging design and "Internet Plus" is elaborated through research. Finally, this paper states the current level of intelligent technology in old-age care and looks into the future by understanding multiple levels of "Internet Plus". The development of community intelligent pension mode and content under "Internet Plus" has enormous development potential. In addition to the characteristics and functions of ordinary houses, residential design of endowment housing has higher requirements for comfort and personalization, and the people-oriented is the principle of design.

Keywords: Ageing tendency, "Internet plus", community intelligent elderly care, elderly care service model, technology.

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Authors: Abdelrahman A. Ramzy, Bassel S. Abdallah, Mohamed E. Bahgat, Sarah M. Abdelkader, Sherif H. ElGohary

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Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Keywords: ADHD, autism, epilepsy, EEG, SVM.

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Authors: Farzana Sharmin, Mohammad Tipu Sultan, Benqian Li

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Advancement of new media technology and consumption of social media have altered the way of communication in the tourism industry, mostly for consumers’ travel planning, online purchase, and experience sharing activity. There is an accelerating trend among young consumers’ to utilize this new media technology. This paper aims to analyze the attitude of young consumers’ about social media use for travel purposes. The convenience random sample method used to collect data from an urban area of Shanghai (China), consists of 225 young consumers’. This survey identified behavioral determinants of social media consumption by the extended theory of planned behavior (TPB). The instrument developed support on previous research to test hypotheses. The results of structural analyses indicate that attitude towards the use of social media is affected by external factors such as availability and accessibility of technology. In addition, subjective norm and perceived behavioral control have partially influenced the attitude of respondents’. The results of this study could help to improve social media travel marketing and promotional strategies for respective groups.

Keywords: Social media, theory of planned behavior, travel behavior, young consumer.

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Authors: W. Zekri

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This paper explores Zohra Drif’s memoir, Inside the Battle of Algiers, which narrates her desires as a student to become a revolutionary activist. She exemplified, in her narrative, the different roles, she and her fellows performed as combatants in the Casbah during the Algerian Revolution 1954-1962. This book review aims to evaluate the concept of women’s agency through education and language learning, and its impact on empowering women’s desires. Close-reading method and thematic analysis are used to explore the text. The analysis identified themes that refine the meaning of agency which are social and cultural supports, education, and language proficiency. These themes aim to contribute to the representation in Inside the Battle of Algiers of a woman guerrilla who engaged herself to perform national acts of resistance.

Keywords: Agency, education, learning, women.

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Authors: S. Hajeb, M. Javadi, S. M. Hashemi, P. Parvizi

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Road Traffic Accidents are a major cause of disability and death throughout the world. The control of intelligent vehicles in order to reduce human error and boost ease congestion is not accomplished solely by the aid of human resources. The present article is an attempt to introduce an intelligent control system based on RFID technology. By the help of RFID technology, vehicles are connected to computerized systems, intelligent light poles and other available hardware along the way. In this project, intelligent control system is capable of tracking all vehicles, crisis management and control, traffic guidance and recording Driving offences along the highway.

Keywords: RFID, Intelligent highway, Traffic violation

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Authors: Hassan Haghighi, Sajad Ghorbani, Maryam Mohebati, Mohammad Mahdi Javanmard

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One of the most important aspects expected from ERP systems is to integrate various operations existing in administrative, financial, commercial, human resources, and production departments of the consumer organization. Also, it is often needed to integrate the new ERP system with the organization legacy systems when implementing the ERP package in the organization. Without relying on an appropriate software architecture to realize the required integration, ERP implementation processes become error prone and time consuming; in some cases, the ERP implementation may even encounters serious risks. In this paper, we propose a new architecture that is based on the agent oriented vision and supplies the integration expected from ERP systems using several independent but cooperator agents. Besides integration which is the main issue of this paper, the presented architecture will address some aspects of intelligence and learning capabilities existing in ERP systems

Keywords: enterprise resource planning, software architecture, agent oriented architecture, integration, intelligence, learning.

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Authors: Yelena Chaiko

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This paper presents a developed method for controlling multi-renewable energy generators. The control system depends basically on three sensors (wind anemometer, solar sensor, and voltage sensor). These sensors represent PLC-s analogue inputs. Controlling the output voltage supply can be achieved by an enhanced method of interlocking between the renewable energy generators, depending on those sensors and output contactors.

Keywords: Renewable, energy, control, model, generator.

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Authors: Roberto Iglesias, Theocharis Kyriacou, Ulrich Nehmzow, Steve Billings

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Fundamental sensor-motor couplings form the backbone of most mobile robot control tasks, and often need to be implemented fast, efficiently and nevertheless reliably. Machine learning techniques are therefore often used to obtain the desired sensor-motor competences. In this paper we present an alternative to established machine learning methods such as artificial neural networks, that is very fast, easy to implement, and has the distinct advantage that it generates transparent, analysable sensor-motor couplings: system identification through nonlinear polynomial mapping. This work, which is part of the RobotMODIC project at the universities of Essex and Sheffield, aims to develop a theoretical understanding of the interaction between the robot and its environment. One of the purposes of this research is to enable the principled design of robot control programs. As a first step towards this aim we model the behaviour of the robot, as this emerges from its interaction with the environment, with the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving Average models with eXogenous inputs). This method produces explicit polynomial functions that can be subsequently analysed using established mathematical methods. In this paper we demonstrate the fidelity of the obtained NARMAX models in the challenging task of robot route learning; we present a set of experiments in which a Magellan Pro mobile robot was taught to follow four different routes, always using the same mechanism to obtain the required control law.

Keywords: Mobile robotics, system identification, non-linear modelling, NARMAX.

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Authors: G. Petruzzelli, F. Pedron, M. Grifoni, F. Gorini, I. Rosellini, B. Pezzarossa

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Composting is a controlled technology to enhance the natural aerobic process of organic wastes degradation. The resulting product is a humified material that is principally recyclable for agricultural purpose. The composting process is one of the most important tools for waste management, by the European Community legislation. In recent years composting has been increasingly used as a remediation technology to remove biodegradable contaminants from soil, and to modulate heavy metals bioavailability in phytoremediation strategies. An optimization in the recovery of resources from wastes through composting could enhance soil fertility and promote its use in the remediation biotechnologies of contaminated soils.

Keywords: Agriculture, biopile, compost, soil clean-up, waste recycling.

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Authors: Inam Shamsher, Zaheer Ahmad, Jehanzeb Khan Orakzai, Awais Adnan

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This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. In the proposed system individual characters are recognized using our own proposed method/ algorithms. The feature detection methods are simple and robust. Supervised learning is used to train the feed forward neural network. A prototype of the system has been tested on printed Urdu characters and currently achieves 98.3% character level accuracy on average .Although the system is script/ language independent but we have designed it for Urdu characters only.

Keywords: Algorithm, Feed Forward Neural Networks, Supervised learning, Pattern Matching.

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Authors: Insung Jung, Gi-Nam Wang

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In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Hafiz Muhammad Obaid, Umais Tayyab, Shabbir Majeed Ch.

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In this paper, a CMOS differential operational transresistance amplifier (OTRA) is presented. The amplifier is designed and implemented in a standard umc90-nm CMOS technology. The differential OTRA provides wider bandwidth at high gain. It also shows much better rise and fall time and exhibits a very good input current dynamic range of 50 to 50 μA. The OTRA can be used in many analog VLSI applications. The presented amplifier has high gain bandwidth product of 617.6 THz Ω. The total power dissipation of the presented amplifier is also very low and it is 0.21 mW.

Keywords: CMOS, differential, operational transresistance amplifier, OTRA, 90 nm, VLSI.

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Authors: H. S. Hassan, E. Shehab, J. Peppard

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Changing technology and increased constituent demand for government services derive the need for governmental responsiveness. The government organisations in the developing countries will be under increased pressure to change their bureaucratic systems to be able to respond rapidly to changing and increasing requirements and rapid technology advancements. This paper aims to present a conceptual framework for explaining the main barriers and drivers of public e-service development. Therefore, the framework provides a basic context within which the process and practice of E-Service can be implemented successfully in the public sector organisations. The framework is flexible enough to be adopted by governments at different levels; national or local by developing countries around the world.

Keywords: Developing countries, E-service, Governmentservices, Public administration.

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Authors: Elizabeth D. Ramos

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Peace education supports a holistic appreciation for the value of life and the interdependence of all living systems. Peace education aims to build a culture of peace. One way of building a culture of peace is through environmental stewardship. This study sought to find out the environmental stewardship practices in selected Higher Education Institutions (HEIs) in the Philippines and how these environmental stewardship practices lead to building a culture of peace. The findings revealed that there is still room for improvement in implementing environmental stewardship in schools through academic service learning. In addition, the following manifestations are implemented very satisfactorily in schools: 1) waste reduction, reuse, and recycling, 2) community service, and 3) clean and green surroundings. Administrators of schools in the study lead their staff and students in implementing environmental stewardship. It could be concluded that those involved in environmental stewardship display an acceptable culture of peace, particularly solidarity, respect for persons, and inner peace.

Keywords: Academic service learning, environmental stewardship, leadership support, peace, solidarity.

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Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: Convolutional Neural Network, Deep Learning, Deep Learning Based FER, Facial Emotion Recognition.

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: Facial expression recognition, image pre-processing, deep learning, CNN.

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Authors: Kholoud H. Al-Zedjali, Abir S. Al-Harrasi, Ali H. Al-Badi

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Recently there has been a dramatic proliferation in the number of social networking sites (SNSs) users; however, little is published about what motivates college students to use SNSs in education. The main goal of this research is to explore the college students’ motives for using SNSs in education. A conceptual framework has therefore been developed to identify the main factors that influence/motivate students to use social networking sites for learning purposes. To achieve the research objectives a quantitative method was used to collect data. A questionnaire has been distributed amongst college students. The results reveal that social influence, perceived enjoyment, institute regulation, perceived usefulness, ranking up-lift, attractiveness, communication tools, free of charge, sharing material and course nature all play an important role in the motivation of college students to use SNSs for learning purposes.

Keywords: Social networking sites (SNSs), education, college students.

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Authors: S. N. Hussain, H. M. A. Asghar, E. P. L. Roberts, N. W. Brown

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Arvia®, a spin-out company of University of Manchester, UK is commercialising a water treatment technology for the removal of low concentrations of organics from water. This technology is based on the adsorption of organics onto graphite based adsorbents coupled with their electrochemical regeneration in a simple electrochemical cell. In this paper, the potential of the process to adsorb microorganisms and electrochemically disinfect them present in water has been demonstrated. Bench scale experiments have indicated that the process of adsorption using graphite adsorbents with electrochemical regeneration can be used for water disinfection effectively. The most likely mechanisms of disinfection of water through this process include direct electrochemical oxidation and electrochemical chlorination.

Keywords: Arvia, Adsorption, Electrochemical Regeneration, Nyex

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: Customer relationship management, churn prediction, telecom industry, deep learning, Artificial Neural Networks, ANN.

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Authors: Narasimham Challa, Jayaram Pradhan

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Cryptographic algorithms play a crucial role in the information society by providing protection from unauthorized access to sensitive data. It is clear that information technology will become increasingly pervasive, Hence we can expect the emergence of ubiquitous or pervasive computing, ambient intelligence. These new environments and applications will present new security challenges, and there is no doubt that cryptographic algorithms and protocols will form a part of the solution. The efficiency of a public key cryptosystem is mainly measured in computational overheads, key size and bandwidth. In particular the RSA algorithm is used in many applications for providing the security. Although the security of RSA is beyond doubt, the evolution in computing power has caused a growth in the necessary key length. The fact that most chips on smart cards can-t process key extending 1024 bit shows that there is need for alternative. NTRU is such an alternative and it is a collection of mathematical algorithm based on manipulating lists of very small integers and polynomials. This allows NTRU to high speeds with the use of minimal computing power. NTRU (Nth degree Truncated Polynomial Ring Unit) is the first secure public key cryptosystem not based on factorization or discrete logarithm problem. This means that given sufficient computational resources and time, an adversary, should not be able to break the key. The multi-party communication and requirement of optimal resource utilization necessitated the need for the present day demand of applications that need security enforcement technique .and can be enhanced with high-end computing. This has promoted us to develop high-performance NTRU schemes using approaches such as the use of high-end computing hardware. Peer-to-peer (P2P) or enterprise grids are proven as one of the approaches for developing high-end computing systems. By utilizing them one can improve the performance of NTRU through parallel execution. In this paper we propose and develop an application for NTRU using enterprise grid middleware called Alchemi. An analysis and comparison of its performance for various text files is presented.

Keywords: Alchemi, GridNtru, Ntru, PKCS.

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