Search results for: Network music education APP

Authors: T. Alghamdi, G. Alaghband

Abstract:

In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution neural network, edges, face recognition, support vector machine.

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Authors: Michael K. Adu, Boniface K. Alese, Olumide S. Ogunnusi

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This paper brings to fore the inherent advantages in application of mobile agents to procure software products rather than downloading software content on the Internet. It proposes a system whereby the products come on compact disk with mobile agent as deliverable. The client/user purchases a software product, but must connect to the remote server of the software developer before installation. The user provides an activation code that activates mobile agent which is part of the software product on compact disk. The validity of the activation code is checked on connection at the developer’s end to ascertain authenticity and prevent piracy. The system is implemented by downloading two different software products as compare with installing same products on compact disk with mobile agent’s application. Downloading software contents from developer’s database as in the traditional method requires a continuously open connection between the client and the developer’s end, a fixed network is not economically or technically feasible. Mobile agent after being dispatched into the network becomes independent of the creating process and can operate asynchronously and autonomously. It can reconnect later after completing its task and return for result delivery. Response Time and Network Load are very minimal with application of Mobile agent.

Keywords: Activation code, internet, mobile agent, software developer, software products.

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Authors: Justin D. Olmanson, Fitsum F. Abebe, Valerie Jones, Eric Kyle, Lyrica Lucas, Katherine Robbins, Guieswende Rouamba, Xianquan Liu

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While emerging technologies continue to emerge, research into their use in learning contexts often focuses on a subset of educational practices and ways of using technologies. In this study we begin to explore the extent to which educational designs are influenced by larger societal and education-related factors not usually explicitly considered when designing or identifying technology-supported education experiences for research study. We examine patterns within and between factors via a content analysis across ten years and 19 different journals of published peer-reviewed research on technology-supported writing. Our findings have implications for how researchers, designers, and educators approach technology-supported educational design within and beyond the field of writing and literacy.

Keywords: Writing, emerging technology, learning, curriculum, pedagogy.

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Authors: Ε. Giovanis

Abstract:

In this paper we apply an Adaptive Network-Based Fuzzy Inference System (ANFIS) with one input, the dependent variable with one lag, for the forecasting of four macroeconomic variables of US economy, the Gross Domestic Product, the inflation rate, six monthly treasury bills interest rates and unemployment rate. We compare the forecasting performance of ANFIS with those of the widely used linear autoregressive and nonlinear smoothing transition autoregressive (STAR) models. The results are greatly in favour of ANFIS indicating that is an effective tool for macroeconomic forecasting used in academic research and in research and application by the governmental and other institutions

Keywords: Linear models, Macroeconomics, Neuro-Fuzzy, Non-Linear models

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Authors: Shengbiao Wu, Weihua Cao, Min Wu, Can Liu

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This paper presents an intelligent tuning method of microwave filter based on complex neural network and improved space mapping. The tuning process consists of two stages: the initial tuning and the fine tuning. At the beginning of the tuning, the return loss of the filter is transferred to the passband via the error of phase. During the fine tuning, the phase shift caused by the transmission line and the higher order mode is removed by the curve fitting. Then, an Cauchy method based on the admittance parameter (Y-parameter) is used to extract the coupling matrix. The influence of the resonant cavity loss is eliminated during the parameter extraction process. By using processed data pairs (the amount of screw variation and the variation of the coupling matrix), a tuning model is established by the complex neural network. In view of the improved space mapping algorithm, the mapping relationship between the actual model and the ideal model is established, and the amplitude and direction of the tuning is constantly updated. Finally, the tuning experiment of the eight order coaxial cavity filter shows that the proposed method has a good effect in tuning time and tuning precision.

Keywords: Microwave filter, scattering parameter (s-parameter), coupling matrix, intelligent tuning.

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Authors: Huan Chen, Bo-Chao Cheng, Chih-Chuan Cheng, Yi-Geng Chen, Yu Ling Chou

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Wireless Sensor Network (WSN) comprises of sensor nodes which are designed to sense the environment, transmit sensed data back to the base station via multi-hop routing to reconstruct physical phenomena. Since physical phenomena exists significant overlaps between temporal redundancy and spatial redundancy, it is necessary to use Redundancy Suppression Algorithms (RSA) for sensor node to lower energy consumption by reducing the transmission of redundancy. A conventional algorithm of RSAs is threshold-based RSA, which sets threshold to suppress redundant data. Although many temporal and spatial RSAs are proposed, temporal-spatial RSA are seldom to be proposed because it is difficult to determine when to utilize temporal or spatial RSAs. In this paper, we proposed a novel temporal-spatial redundancy suppression algorithm, Codebookbase Redundancy Suppression Mechanism (CRSM). CRSM adopts vector quantization to generate a codebook, which is easily used to implement temporal-spatial RSA. CRSM not only achieves power saving and reliability for WSN, but also provides the predictability of network lifetime. Simulation result shows that the network lifetime of CRSM outperforms at least 23% of that of other RSAs.

Keywords: Redundancy Suppression Algorithm (RSA), Threshold-based RSA, Temporal RSA, Spatial RSA and Codebookbase Redundancy Suppression Mechanism (CRSM)

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Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

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Advancements in the field of artificial intelligence (AI) made during this decade have forever changed the way we look at automating spacecraft subsystems including the electrical power system. AI have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. In this paper, a mathematical modeling and MATLAB–SIMULINK model for the different components of the spacecraft power system is presented. Also, a control system, which includes either the Neural Network Controller (NNC) or the Fuzzy Logic Controller (FLC) is developed for achieving the coordination between the components of spacecraft power system as well as control the energy flows. The performance of the spacecraft power system is evaluated by comparing two control systems using the NNC and the FLC.

Keywords: Spacecraft, Neural network, Fuzzy logic control, Photovoltaic array.

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Authors: Eklas Hossain, Sheroz Khan, Ahad Ali

Abstract:

Power line communications may be used as a data communication channel in public and indoor distribution networks so that it does not require the installing of new cables. Industrial low voltage distribution network may be utilized for data transfer required by the on-line condition monitoring of electric motors. This paper presents a pilot distribution network for modeling low voltage power line as data transfer channel. The signal attenuation in communication channels in the pilot environment is presented and the analysis is done by varying the corresponding parameters for the signal attenuation.

Keywords: Data communication, indoor distribution networks, low voltage, power line.

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Authors: Sum Lau, Wing Chung Cleo Lau, Wing Yan Chu, Long Ching Ip, Wan Yin Lo, Jo Long Sam Yau, Ka Ho Hui, Sze Yi Mak

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Biomedical engineering (BME) is an interdisciplinary subject where knowledge about biology and medicine is applied to novel applications, solving clinical problems. This subject is crucial for cities such as Hong Kong where the burden on the medical system is rising due to reasons like ageing population. Hong Kong, who is actively boosting technological advancements in recent years, sets BME, or biotechnology as a major category, as reflected in the 2018-19 Budget where biotechnology was one of the four pillars for development. Over the years, while resources in terms of money and space have been provided, there has been a lack of talents, expressed by both the academia and industry. While exogenous factors, such as COVID-19, may have hindered talents from outside Hong Kong to come, endogenous factors should also be considered. In particular, since there are already a few local universities offering BME programmes, their curriculum or style of education requires to be reviewed to intensify the network of the BME community and support post-academic career development. It was observed that while undergraduate (UG) studies focus on knowledge teaching with some technical training and postgraduate (PG) programmes concentrate on upstream research, the programmes are generally confined to the academic sector and lack connections to the industry. In light of that, a “Biomedical Innovation and Outreach Programme 2022” (“B.I.O.2022”) was held to connect students and professors from academia with clinicians and engineers from the industry, serving as a comparative approach to conventional education methods (UG and PG programmes from tertiary institutions). Over 100 participants, including undergraduates, postgraduates, secondary school students, researchers, engineers, and clinicians, took part in various outreach events such as conference and site visits, all held from June to July 2022. As a case study, this programme aimed to tackle the aforementioned problems with the theme of “4Cs” (connection, communication, collaboration, and commercialisation). The effectiveness of the programme is investigated by its ability to serve as adult and continuing education, and the effectiveness of causing social change to tackle current societal challenges, with the focus on tackling the lack of talents engaging in BME. In this study, B.I.O. 2022 is found to be able to complement the traditional educational methods, particularly in terms of knowledge exchange between the academia and the industry. With enhanced communications between participants from different career stages, there were students who followed up to visit or even work with the professionals after the programme. Furthermore, connections between the academia and industry could foster the generation of new knowledge, which ultimately pointed to commercialisation, adding value to the BME industry while filling the gap in terms of human resources. With the continuation of events like B.I.O. 2022, it provides a promising starting point for development and relationship strengthening of a BME community in Hong Kong, and shows potential as an alternative way of adult education or learning with societal benefits.

Keywords: Biomedical engineering, adult education, social change, comparative methods, lifelong learning, innovation, professional community.

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Authors: Travis Wiens, Greg Schoenau, Rich Burton

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It is well known that a linear dynamic system including a delay will exhibit limit cycle oscillations when a bang-bang sensor is used in the feedback loop of a PID controller. A similar behaviour occurs when a delayed feedback signal is used to train a neural network. This paper develops a method of predicting this behaviour by linearizing the system, which can be shown to behave in a manner similar to an integral controller. Using this procedure, it is possible to predict the characteristics of the neural network driven limit cycle to varying degrees of accuracy, depending on the information known about the system. An application is also presented: the intelligent control of a spark ignition engine.

Keywords: Control and automation, artificial neural networks, limit cycle

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Authors: Eylem Koç, Hasan Arda Burhan

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Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.

Keywords: Analytic Network Process, BOCR, location selection, multi-actor decision making, multi-criteria decision making, real life problem.

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Authors: N. Paparisteidi, D. Rodamitou

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This article focuses on the skills development and path planning of students studying computer science at EPITECH: French private institute of higher education. We examine students’ points of view and experience in a blended learning model based on a skills development curriculum. The study is based on the collection of four main categories of data: semi-participant observation, distribution of questionnaires, interviews, and analysis of internal school databases. The findings seem to indicate that a skills-based program on active learning enables students to develop their learning strategies as well as their personal skills and to actively engage in the creation of their career path and contribute to providing additional information to curricula planners and decision-makers about learning design in higher education.

Keywords: Active learning, blended learning, higher education, skills development.

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Authors: Sawsan J. Al-Husseini

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Transformational leadership (TL) has been found to have an important influence on knowledge and knowledge management (KM). It can contribute to organizational learning, employees’ creativity, encourage followers to participate in educational programs and develop the skills needed to achieve exceptional performance. This research sought to examine the impact of TL on knowledge donating and collecting and the differences between these impacts in public and private higher education institutes (HEIs) in Iraq. A mixed method approach was taken and 580 valid responses were collected to test the causal relationships between the factors, then 12 interviews were conducted with the leaders of HEIs to give more insight of the findings from quantitative stage. Employing structural equation modelling with AMOS v.24, the research found that TL would be ideal in an educational context, promoting knowledge sharing activities in both sectors. The interviews revealed differences between public and private HEIs in terms of the effects relationships. Guidelines are developed for academics as well as leaders and provided evidence to support the use of TL to encourage knowledge sharing activities within higher education in developing countries particularly Iraq.

Keywords: Transformational leadership, knowledge sharing, higher education, multi-groups.

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Authors: Dariush Jafari, S. Mostafa Nowee

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In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.

Keywords: Thermodynamic modeling, ANN, solubility, ternary electrolyte system.

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Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira

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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.

Keywords: Artificial neural networks, digital image processing, pattern recognition.

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Authors: Ladan Darougaran, Hossein Shahinzadeh, Hajar Ghotb, Leila Ramezanpour

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In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages- number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols [5]. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency whit Genetic Algorithm.

Keywords: Data aggregation, wireless sensor networks, energy efficiency, simulated annealing algorithm, genetic algorithm.

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Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

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Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: Causality, defect causes, social network analysis, association rule mining.

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Authors: M. Bouguerra, F. Laaouad, I. Habi, R. Azaizia

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In Algeria, now, the oil pumping plants are fed with electric power by independent local sources. This type of feeding has many advantages (little climatic influence, independent operation). However it requires a qualified maintenance staff, a rather high frequency of maintenance and repair and additional fuel costs. Taking into account the increasing development of the national electric supply network (Sonelgaz), a real possibility of transfer of the local sources towards centralized sources appears.These latter cannot only be more economic but more reliable than the independent local sources as well. In order to carry out this transfer, it is necessary to work out an optimal strategy to rebuilding these networks taking in account the economic parameters and the indices of reliability.

Keywords: Optimization, reliability, electric network.

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Authors: Osifeko Olalekan Remigious, Osifeko Christiana Osikorede, Folarin Bolanle Eunice, Olugbenga Adebola Shodiya

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During these difficult economic times, nations are looking for ways to improve their finances, preserve the environment as well as the socio-political climate and educational institutions, which are needed to increase their economy and preserve their sustainable development. Sport is one of the ways through which sustainable development can be achieved. The purpose of this study was to examine and understanding barriers to participation in sport. A total of 1,025 students were purposively selected from five schools (School of Arts and Social Sciences, School of Languages, School of Education, School of Sciences and School of Vocational and Technical Education) in Michael Otedola College of Primary Education (MOCPED). A questionnaire, with a tested reliability coefficient of 0.71, was used for data collection. The collected data were subjected to the descriptive survey research design. The findings showed that sports facilities, funding and lecture schedules were significant barriers to sports participation. It was recommended that sports facilities be provided by the Lagos State government.

Keywords: MOCPED sports, sustainable development, sports participation, state government.

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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: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

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The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: Angle of internal friction, Cone penetrating test, General regression neural network, Soil modulus of elasticity.

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Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design & modeling, neural networks, genetic optimization.

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Authors: A. Baith Mohamed, Ayman Abdel-Hamid, Kareem Youssri Mohamed

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Current proposals for E-passport or ID-Card is similar to a regular passport with the addition of tiny contactless integrated circuit (computer chip) inserted in the back cover, which will act as a secure storage device of the same data visually displayed on the photo page of the passport. In addition, it will include a digital photograph that will enable biometric comparison, through the use of facial recognition technology at international borders. Moreover, the e-passport will have a new interface, incorporating additional antifraud and security features. However, its problems are reliability, security and privacy. Privacy is a serious issue since there is no encryption between the readers and the E-passport. However, security issues such as authentication, data protection and control techniques cannot be embedded in one process. In this paper, design and prototype implementation of an improved E-passport reader is presented. The passport holder is authenticated online by using GSM network. The GSM network is the main interface between identification center and the e-passport reader. The communication data is protected between server and e-passport reader by using AES to encrypt data for protection will transferring through GSM network. Performance measurements indicate a 19% improvement in encryption cycles versus previously reported results.

Keywords: RFID "Radio Frequency Identification", EPC"Electronic Product Code", ICAO "International Civil Aviation Organization", IFF "Identify Friend or Foe"

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Authors: Nazeema Ahmed

Abstract:

Mental health in higher education has received increasing attention over the past few decades. The high academic demands of the engineering degree, coupled with students’ mental health challenges, have led to higher education institutions offering psychotherapeutic services to students. This paper discusses an evaluation of the psychotherapy service at the University of Cape Town. The aim was to determine (i) the efficacy of the service; and (ii) the impact of race, gender, and language of the therapist on the students’ therapeutic process. An online survey was sent to 109 students who attended psychotherapy. The majority expressed favorable experiences of psychotherapy, with reports of increased capacity to engage with their academic work. Most students did not experience the gender, race, or language of the psychologists to be barriers to their therapy. The findings point to a need for ongoing psychological support for students.

Keywords: Psychotherapy, efficacy, engineering, education.

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Authors: Faizal A. Samman, Thomas Hollstein, Manfred Glesner

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A synchronous network-on-chip using wormhole packet switching and supporting guaranteed-completion best-effort with low-priority (LP) and high-priority (HP) wormhole packet delivery service is presented in this paper. Both our proposed LP and HP message services deliver a good quality of service in term of lossless packet completion and in-order message data delivery. However, the LP message service does not guarantee minimal completion bound. The HP packets will absolutely use 100% bandwidth of their reserved links if the HP packets are injected from the source node with maximum injection. Hence, the service are suitable for small size messages (less than hundred bytes). Otherwise the other HP and LP messages, which require also the links, will experience relatively high latency depending on the size of the HP message. The LP packets are routed using a minimal adaptive routing, while the HP packets are routed using a non-minimal adaptive routing algorithm. Therefore, an additional 3-bit field, identifying the packet type, is introduced in their packet headers to classify and to determine the type of service committed to the packet. Our NoC prototypes have been also synthesized using a 180-nm CMOS standard-cell technology to evaluate the cost of implementing the combination of both services.

Keywords: Network-on-Chip, Parallel Pipeline Router Architecture, Wormhole Switching, Two-Level Priority Service.

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Authors: F. Sarabchi, A. H. Darvishan, H. Yeganeh, H. Ahmadian

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Next generation networks with the idea of convergence of service and control layer in existing networks (fixed, mobile and data) and with the intention of providing services in an integrated network, has opened new horizon for telecom operators. On the other hand, economic problems have caused operators to look for new source of income including consider new services, subscription of more users and their promotion in using morenetwork resources and easy participation of service providers or 3rd party operators in utilizing networks. With this requirement, an architecture based on next generation objectives for service layer is necessary. In this paper, a new architecture based on IMS model explains participation of 3rd party operators in creation and implementation of services on an integrated telecom network.

Keywords: Service model, IMS, API, Scripting language, JAIN, Parlay.

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Authors: A. Hossein Sahoolizadeh, B. Zargham Heidari, C. Hamid Dehghani

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In this paper, a new face recognition method based on PCA (principal Component Analysis), LDA (Linear Discriminant Analysis) and neural networks is proposed. This method consists of four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii) feature extraction using LDA and iv) classification using neural network. Combination of PCA and LDA is used for improving the capability of LDA when a few samples of images are available and neural classifier is used to reduce number misclassification caused by not-linearly separable classes. The proposed method was tested on Yale face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.

Keywords: Face recognition Principal component analysis, Linear discriminant analysis, Neural networks.

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Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

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This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: Constructive alignment, constructivist theory, educational game, outcome-based education.

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Authors: Bushra Malik, Saad Zafar

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Inadequate curriculum for software engineering is considered to be one of the most common software risks. A number of solutions, on improving Software Engineering Education (SEE) have been reported in literature but there is a need to collectively present these solutions at one place. We have performed a mapping study to present a broad view of literature; published on improving the current state of SEE. Our aim is to give academicians, practitioners and researchers an international view of the current state of SEE. Our study has identified 70 primary studies that met our selection criteria, which we further classified and categorized in a well-defined Software Engineering educational framework. We found that the most researched category within the SE educational framework is Innovative Teaching Methods whereas the least amount of research was found in Student Learning and Assessment category. Our future work is to conduct a Systematic Literature Review on SEE.

Keywords: Mapping Study, Software Engineering, Software Engineering Education, Literature Survey.

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Authors: Afif Saleh Abugharsa

Abstract:

The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.

Keywords: ZigBee, wireless sensor networks, IEEE 802.15.4, low power, low data rate

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