Search results for: digital learning environments

Authors: J. Silvestre, L. Almeida, R. Marau, P. Pedreiras

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Currently, there are many local area industrial networks that can give guaranteed bandwidth to synchronous traffic, particularly providing CBR channels (Constant Bit Rate), which allow improved bandwidth management. Some of such networks operate over Ethernet, delivering channels with enough capacity, specially with compressors, to integrate multimedia traffic in industrial monitoring and image processing applications with many sources. In these industrial environments where a low latency is an essential requirement, JPEG is an adequate compressing technique but it generates VBR traffic (Variable Bit Rate). Transmitting VBR traffic in CBR channels is inefficient and current solutions to this problem significantly increase the latency or further degrade the quality. In this paper an R(q) model is used which allows on-line calculation of the JPEG quantification factor. We obtained increased quality, a lower requirement for the CBR channel with reduced number of discarded frames along with better use of the channel bandwidth.

Keywords: Industrial Networks, Multimedia.

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Authors: O. P. Rishi, Rekha Govil, Madhavi Sinha

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Online learning with Intelligent Tutoring System (ITS) is becoming very popular where the system models the student-s learning behavior and presents to the student the learning material (content, questions-answers, assignments) accordingly. In today-s distributed computing environment, the tutoring system can take advantage of networking to utilize the model for a student for students from other similar groups. In the present paper we present a methodology where using Case Based Reasoning (CBR), ITS provides student modeling for online learning in a distributed environment with the help of agents. The paper describes the approach, the architecture, and the agent characteristics for such system. This concept can be deployed to develop ITS where the tutor can author and the students can learn locally whereas the ITS can model the students- learning globally in a distributed environment. The advantage of such an approach is that both the learning material (domain knowledge) and student model can be globally distributed thus enhancing the efficiency of ITS with reducing the bandwidth requirement and complexity of the system.

Keywords: CBR, ITS, student modeling, distributed system, intelligent agent.

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Authors: Jafreezal Jaafar, Eric McKenzie

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This paper presents a solution for the behavioural animation of autonomous virtual agent navigation in virtual environments. We focus on using Dempster-Shafer-s Theory of Evidence in developing visual sensor for virtual agent. The role of the visual sensor is to capture the information about the virtual environment or identifie which part of an obstacle can be seen from the position of the virtual agent. This information is require for vitual agent to coordinate navigation in virtual environment. The virual agent uses fuzzy controller as a navigation system and Fuzzy α - level for the action selection method. The result clearly demonstrates the path produced is reasonably smooth even though there is some sharp turn and also still not diverted too far from the potential shortest path. This had indicated the benefit of our method, where more reliable and accurate paths produced during navigation task.

Keywords: Agent, navigation, Dempster Shafer, fuzzy logic.

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Authors: Xun Liang

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In this paper, we probe into the traffic assignment problem by the chromosome-learning-based path finding method in simulation, which is to model the driver' behavior in the with-in-a-day process. By simply making a combination and a change of the traffic route chromosomes, the driver at the intersection chooses his next route. The various crossover and mutation rules are proposed with extensive examples.

Keywords: Chromosome learning, crossover, mutation, traffic path finding.

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Authors: Salina Budin, Nor Liawati Abu Othman, Shaira Ismail

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This study attempts to determine kinesthetic, verbal and visual intelligences among mechanical engineering undergraduate students and explores any probable relation with students’ learning styles and academic performance. The questionnaire used in this study is based on Howard Gardner’s multiple intelligences theory comprising of five elements of learning style; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering. Additional questions on students’ perception of learning styles and their academic performance are included in the questionnaire. The results show that one third of the students are strongly dominant in the kinesthetic intelligent (33%), followed by a combination of kinesthetic and visual intelligences (29%) and 21% are strongly dominant in all three types of intelligences. There is a statistically significant correlation between kinesthetic, verbal and visual intelligences and students learning styles and academic performances. The ANOVA analysis supports that there is a significant relationship between academic performances and level of kinesthetic, verbal and visual intelligences. In addition, it has also proven a remarkable relationship between academic performances and kinesthetic, verbal and visual learning styles amongst the male and female students. Thus, it can be concluded that, academic achievements can be enhanced by understanding as well as capitalizing the students’ types of intelligences and learning styles.

Keywords: Kinesthetic intelligent, verbal intelligent, visual intelligent, learning style, academic performances.

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Authors: Wei Lifan, Zhang Huaiyu, Yang Yunbin, Li Jia

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Through the analysis of the process digital design based on digital mockup, the fact indicates that a distributed cooperative supporting environment is the foundation conditions to adopt design approach based on DMU. Data access authorization is concerned firstly because the value and sensitivity of the data for the enterprise. The access control for administrators is often rather weak other than business user. So authors established an enhanced system to avoid the administrators accessing the engineering data by potential approach and without authorization. Thus the data security is improved.

Keywords: access control, DMU, PLM, virtual prototype.

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Authors: Abdul Rashid Ahmadi, Samiullah Paracha, Hamidullah Sokout, Mohammad Hanif Gharanai

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Conventional educational practices, do not offer all the required skills for teachers to successfully survive in today’s workplace. Due to poor professional training, a big gap exists across the curriculum plan and the teacher practices in the classroom. As such, raising the quality of teaching through ICT-enabled training and professional development of teachers should be an urgent priority. ‘Mobile Learning’, in that vein, is an increasingly growing field of educational research and practice across schools and work places. In this paper, we propose a novel Mobile learning system that allows the users to learn through an intelligent mobile learning in cooperatively every-time and every-where. The system will reduce the training cost and increase consistency, efficiency, and data reliability. To establish that our system will display neither functional nor performance failure, the evaluation strategy is based on formal observation of users interacting with system followed by questionnaires and structured interviews.

Keywords: Computer Assisted Learning, Intelligent Tutoring system, Learner Centered Design, Mobile Mediated Learning and Teacher education (MMLTE).

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Authors: Mimi Mohaffyza Mohamad, Yee Mei Heong, Nurfirdawati Muhammad Hanafi Tee Tze Kiong

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This study is conducted to investigate the disparity of between learning styles and cognitive abilities specifically in Vocational Education.  Felder and Silverman Learning Styles Model (FSLSM) was applied to measure the students’ learning styles while the content in Building Construction Subject consists; knowledge, skills and problem solving were taken into account in constructing the elements of cognitive abilities. Building Construction is one of the vocational courses offered in Vocational Education structure. There are four dimension of learning styles proposed by Felder and Silverman intended to capture student learning preferences with regards to processing either active or reflective, perception based on sensing or intuitive, input of information used visual or verbal and understanding information represent with sequential or global learner. Felder-Solomon Learning Styles Index was developed based on FSLSM and the questions were used to identify what type of student learning preferences. The index consists 44 item-questions characterize for learning styles dimension in FSLSM. The achievement test was developed to determine the students’ cognitive abilities. The quantitative data was analyzed in descriptive and inferential statistic involving Multivariate Analysis of Variance (MANOVA). The study discovered students are tending to be visual learners and each type of learner having significant difference whereas cognitive abilities there are different finding for each type of learners in knowledge, skills and problem solving. This study concludes the gap between type of learner and the cognitive abilities in few illustrations and it explained how the connecting made. The finding may help teachers to facilitate students more effectively and to boost the student’s cognitive abilities.

Keywords: Learning Styles, Cognitive Abilities, Dimension of Learning Styles, Learning Preferences.

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Authors: Shahrinaz Ismail, Zulhelmi Mohammed, Nur Waheda Md Yusof, Mohd Sharifuddin Ahmad

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The burst of Web 2.0 technology and social networking tools manifest different styles of learning and managing knowledge among both knowledge workers and adult learners. In the Western countries, open-learning concept has been made popular due to the ease of use and the reach that the technology provides. In Malaysia, there are still some gaps between the learners- acceptance of technology and the full implementation of the technology in the education system. There is a need to understand how adult learners, who are knowledge workers, manage their personal knowledge via social networking tools, especially in their learning process. Four processes of personal knowledge management (PKM) and four cognitive enablers are proposed supported by analysed data on adult learners in a university. The model derived from these processes and enablers is tested and presented, with recommendations on features to be included in adult learners- learning environment.

Keywords: Personal knowledge management, adult learners, social network, learning environment.

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Authors: Lejla A. Bexheti, Visar S. Shehu, Adrian A. Besimi

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The Learning Management Systems present learning environment which offers a collection of e-learning tools in a package that allows a common interface and information sharing among the tools. South East European University initial experience in LMS was with the usage of the commercial LMS-ANGEL. After a three year experience on ANGEL usage because of expenses that were very high it was decided to develop our own software. As part of the research project team for the in-house design and development of the new LMS, we primarily had to select the features that would cover our needs and also comply with the actual trends in the area of software development, and then design and develop the system. In this paper we present the process of LMS in-house development for South East European University, its architecture, conception and strengths with a special accent on the process of migration and integration with other enterprise applications.

Keywords: e-learning tools, LMS, migration, user feedback.

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Lèvy flight, situation awareness, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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Authors: Ellips Masehian, Yalda Katebi

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This paper presents a new sensor-based online method for generating collision-free near-optimal paths for mobile robots pursuing a moving target amidst dynamic and static obstacles. At each iteration, first the set of all collision-free directions are calculated using velocity vectors of the robot relative to each obstacle and target, forming the Directive Circle (DC), which is a novel concept. Then, a direction close to the shortest path to the target is selected from feasible directions in DC. The DC prevents the robot from being trapped in deadlocks or local minima. It is assumed that the target's velocity is known, while the speeds of dynamic obstacles, as well as the locations of static obstacles, are to be calculated online. Extensive simulations and experimental results demonstrated the efficiency of the proposed method and its success in coping with complex environments and obstacles.

Keywords: Dynamic Environment, Moving Target, RobotMotion Planning.

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Authors: Begol, Moslem, Maghooli, Keivan

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Image Edge Detection is one of the most important parts of image processing. In this paper, by fuzzy technique, a new method is used to improve digital image edge detection. In this method, a 3x3 mask is employed to process each pixel by means of vicinity. Each pixel is considered a fuzzy input and by examining fuzzy rules in its vicinity, the edge pixel is specified and by utilizing calculation algorithms in image processing, edges are displayed more clearly. This method shows significant improvement compared to different edge detection methods (e.g. Sobel, Canny).

Keywords: Fuzzy Systems, Edge Detection, Fuzzy edgedetection

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Authors: Malathi Balakrishnan, Gananathan M. Nadarajah, Saraswathy Vellasamy, Evelyn Gnanam William George

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The purpose of the study is to explore how the fun game-learning approach enhances teacher trainers’ higher order thinking skills. Two-day fun filled fun game learning-approach was introduced to teacher trainers as a Continuous Professional Development Program (CPD). 26 teacher trainers participated in this Transformation of Teaching and Learning Fun Way Program, organized by Institute of Teacher Education Malaysia. Qualitative research technique was adopted as the researchers observed the participants’ higher order thinking skills developed during the program. Data were collected from observational checklist; interview transcriptions of four participants and participants’ reflection notes. All the data were later analyzed with NVivo data analysis process. The finding of this study presented five main themes, which are critical thinking, hands on activities, creating, application and use of technology. The studies showed that the teacher trainers’ higher order thinking skills were enhanced after the two-day CPD program. Therefore, Institute of Teacher Education will have more success using the fun way game-learning approach to develop higher order thinking skills among its teacher trainers who can implement these skills to their trainee teachers in future. This study also added knowledge to Constructivism learning theory, which will further highlight the prominence of the fun way learning approach to enhance higher order thinking skills.

Keywords: Constructivism, game-learning approach, higher order thinking skill, teacher trainer.

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Authors: María-Dolores Afonso-Suárez, Nayra Pumar-Carreras, Juan Ruiz-Alzola

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This research addresses the use of an e-Learning creation methodology for learning objects. Throughout the process, indicators are being gathered, to determine if it responds to the main objectives of an engineering discipline. These parameters will also indicate if it is necessary to review the creation cycle and readjust any phase. Within the project developed for this study, apart from the use of structured methods, there has been a central objective: the establishment of a learning atmosphere. A place where all the professionals involved are able to collaborate, plan, solve problems and determine guides to follow in order to develop creative and innovative solutions. It has been outlined as a blended learning program with an assessment plan that proposes face to face lessons, coaching, collaboration, multimedia and web based learning objects as well as support resources. The project has been drawn as a long term task, the pilot teaching actions designed provide the preliminary results object of study. This methodology is been used in the creation of learning content for the African countries of Senegal, Mauritania and Cape Verde. It has been developed within the framework of the MACbioIDi, an Interreg European project for the International cooperation and development. The educational area of this project is focused in the training and advice of professionals of the medicine as well as engineers in the use of applications of medical imaging technology, specifically the 3DSlicer application and the Open Anatomy Browser.

Keywords: Teaching contents engineering, e-learning, blended learning, international cooperation, 3DSlicer, open anatomy browser.

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Authors: Amir Abolfazl Suratgar, Mohammad Bagher Tavakoli, Abbas Hoseinabadi

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In this paper a modification on Levenberg-Marquardt algorithm for MLP neural network learning is proposed. The proposed algorithm has good convergence. This method reduces the amount of oscillation in learning procedure. An example is given to show usefulness of this method. Finally a simulation verifies the results of proposed method.

Keywords: Levenberg-Marquardt, modification, neural network, variable learning rate.

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Authors: Daniel Kade, Oğuzhan Özcan, Rikard Lindell

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Motion capturing technology has been used for quite a while and several research has been done within this area. Nevertheless, we discovered open issues within current motion capturing environments. In this paper we provide a state-of-the-art overview of the addressed research areas and show issues with current motion capturing environments. Observations, interviews and questionnaires have been used to reveal the challenges actors are currently facing in a motion capturing environment. Furthermore, the idea to create a more immersive motion capturing environment to improve the acting performances and motion capturing outcomes as a potential solution is introduced. It is hereby the goal to explain the found open issues and the developed ideas which shall serve for further research as a basis. Moreover, a methodology to address the interaction and systems design issues is proposed. A future outcome could be that motion capture actors are able to perform more naturally, especially if using a non-body-worn solution.

Keywords: Immersive acting environment, Interaction in a mediated environment, Motion capturing, MoCap.

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Authors: Kiyohiro Yamazaki

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This paper considers a forming process of a single competitive factor in the digital camera industry from the viewpoint of product platform. To make product development easier for companies and to increase product introduction ratios, development efforts concentrate on improving and strengthening certain product attributes, and it is born in the process that the product platform is formed continuously. It is pointed out that the formation of this product platform raises product development efficiency of individual companies, but on the other hand, it has a trade-off relationship of causing unification of competitive factors in the whole industry. This research tries to analyze product specification data which were collected from the web page of digital camera companies. Specifically, this research collected all product specification data released in Japan from 1995 to 2003 and analyzed the composition of image sensor and optical lens; and it identified product platforms shared by multiple products and discussed their application. As a result, this research found that the product platformation was born in the development of the standard product for major market segmentation. Every major company has made product platforms of image sensors and optical lenses, and as a result, this research found that the competitive factors were unified in the entire industry throughout product platformation. In other words, this product platformation brought product development efficiency of individual firms; however, it also caused industrial competition factors to be unified in the industry.

Keywords: Digital camera industry, product evolution trajectory, product platform, unification of competitive factors.

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Authors: Pintipa Seubsang, Suttipong Boonphadung

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Recently, Thai education system is engaged in serious and promising reforms. One of the crucial elements in most of these educational reforms is the teacher professional development. Teachers today are under growing pressure to perform. However, most new teachers are not adequately prepared to meet the expectation. Consequently, this paper seeks to investigate the opinion of mentor teachers and university supervisors about professional development in the aspect of learning management skill of the preservice teachers in Rajabhat Universities, then compare the opinion between the mentor teachers and university supervisors about professional development in the aspect of learning management skill of the pre-service teachers. The study involved a cohort of 40 university supervisors and 77 mentor teachers. The research concludes by showing that mentor teachers viewed pre-service teacher as a professional teacher with an effective learning management skill. However, in the perspective of the university supervisor, pre-service teachers still have inadequate learning management skill.

Keywords: Learning management, Professional development, Pre-service teacher.

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Authors: N. Chaitawittanun, M. Munlin

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Due to rapid advancement of powerful image processing software, digital images are easy to manipulate and modify by ordinary people. Lots of digital images are edited for a specific purpose and more difficult to distinguish form their original ones. We propose a clustering method to detect a copy-move image forgery of JPEG, BMP, TIFF, and PNG. The process starts with reducing the color of the photos. Then, we use the clustering technique to divide information of measuring data by Hausdorff Distance. The result shows that the purposed methods is capable of inspecting the image file and correctly identify the forgery.

Keywords: Image detection, forgery image, copy-paste.

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Authors: Jesús A. Pérez, Sam Coppieters, Dimitri Debruyne

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In the past decade, the use of digital image correlation (DIC) techniques has increased significantly in the area of experimental mechanics, especially for materials behavior characterization. This non-contact tool enables full field displacement and strain measurements over a complete region of interest. The DIC algorithm requires a random contrast pattern on the surface of the specimen in order to perform properly. To create this pattern, the specimen is usually first coated using a white matt paint. Next, a black random speckle pattern is applied using any suitable method. If the applied paint coating is too thick, its top surface may not be able to exactly follow the deformation of the specimen, and consequently, the strain measurement might be underestimated. In the present article, a study of the influence of the paint thickness on the strain underestimation is performed for different strain levels. The results are then compared to typical paint coating thicknesses applied by experienced DIC users. A slight strain underestimation was observed for paint coatings thicker than about 30μm. On the other hand, this value was found to be uncommonly high compared to coating thicknesses applied by DIC users.

Keywords: Digital Image Correlation, paint coating thickness, strain.

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Authors: Pavel Psota, Vít Lédl, Jan Václavík, Roman Doleček, Pavel Mokrý, Petr Vojtíšek

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This paper presents advanced time average digital holography by means of frequency shift and phase modulation. This technique can measure amplitudes of vibrations at ultimate dynamic range while the amplitude distribution evaluation is done independently in every pixel. The main focus of the paper is to gain insight into behavior of the method at low amplitudes of vibrations. In order to reach that, a set of experiments was performed. Results of the experiments together with novel noise suppression show the limit of the method to be below 0.1 nm.

Keywords: Acousto-optical modulator, digital holography, low amplitudes, vibrometry.

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Authors: Jingjing Lan, Jun Yu, Muthukumaraswamy Annamalai Arasu

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This paper presents a digital non-linear pulse-width modulation (PWM) controller in a high-voltage (HV) buck-boost DC-DC converter for the piezoelectric transducer of the down-hole acoustic telemetry system. The proposed design controls the generation of output signal with voltage higher than the supply voltage and is targeted to work under high temperature. To minimize the power consumption and silicon area, a simple and efficient design scheme is employed to develop the PWM controller. The proposed PWM controller consists of serial to parallel (S2P) converter, data assign block, a mode and duty cycle controller (MDC), linearly PWM (LPWM) and noise shaper, pulse generator and clock generator. To improve the reliability of circuit operation at higher temperature, this design is fabricated with the 1.0-μm silicon-on-insulator (SOI) CMOS process. The implementation results validated that the proposed design has the advantages of smaller size, lower power consumption and robust thermal stability.

Keywords: DC-DC power conversion, digital control, high temperatures, pulse-width modulation.

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Authors: Suleiman Musa, Shuaibu Sidi Safiyanu

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This study examined the digital preservation in Nigeria university libraries. A comparison between the university of Nigeria Nsukka (UNN) and Ahmadu Bello University Zaria (ABU, Zaria). The study utilized primary source of data obtained from two selected institution librarians. Finding revealed varying results in terms of skills acquired by librarians before and after digitization of the two institutions. The study reports that journals publication, text book, CD-ROMS, conference papers and proceedings, theses, dissertations and seminar papers are among the information resources available for digitization. The study further documents that copyright issue, power failure, and unavailability of needed materials are among the challenges facing the digitization of library of the institution. On the basis of the finding, the study concluded that digitization of library enhances efficiency in organization and retrieval of information services. The study therefore recommended that software should be upgraded with backup, training of the librarians on digital process, installation of antivirus and enhancement of technical collaboration between the library and MIS.

Keywords: Digitalization, preservation, libraries, comparison.

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: Fake news detection, types of fake news, machine learning, natural language processing, classification techniques.

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Emilija Miletic, Milos Krstic, Maxim Piz, Michael Methfessel

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In this work we present a solution for DAGC (Digital Automatic Gain Control) in WLAN receivers compatible to IEEE 802.11a/g standard. Those standards define communication in 5/2.4 GHz band using Orthogonal Frequency Division Multiplexing OFDM modulation scheme. WLAN Transceiver that we have used enables gain control over Low Noise Amplifier (LNA) and a Variable Gain Amplifier (VGA). The control over those signals is performed in our digital baseband processor using dedicated hardware block DAGC. DAGC in this process is used to automatically control the VGA and LNA in order to achieve better signal-to-noise ratio, decrease FER (Frame Error Rate) and hold the average power of the baseband signal close to the desired set point. DAGC function in baseband processor is done in few steps: measuring power levels of baseband samples of an RF signal,accumulating the differences between the measured power level and actual gain setting, adjusting a gain factor of the accumulation, and applying the adjusted gain factor the baseband values. Based on the measurement results of RSSI signal dependence to input power we have concluded that this digital AGC can be implemented applying the simple linearization of the RSSI. This solution is very simple but also effective and reduces complexity and power consumption of the DAGC. This DAGC is implemented and tested both in FPGA and in ASIC as a part of our WLAN baseband processor. Finally, we have integrated this circuit in a compact WLAN PCMCIA board based on MAC and baseband ASIC chips designed from us.

Keywords: WLAN, AGC, RSSI, baseband processor

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Authors: Erh-Wen Hu, Cyril S. Ku, Andrew T. Russo, Bogong Su, Jian Wang

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Unlike general-purpose processors, digital signal processors (DSP processors) are strongly application-dependent. To meet the needs for diverse applications, a wide variety of DSP processors based on different architectures ranging from the traditional to VLIW have been introduced to the market over the years. The functionality, performance, and cost of these processors vary over a wide range. In order to select a processor that meets the design criteria for an application, processor performance is usually the major concern for digital signal processing (DSP) application developers. Performance data are also essential for the designers of DSP processors to improve their design. Consequently, several DSP performance benchmarks have been proposed over the past decade or so. However, none of these benchmarks seem to have included recent new DSP applications. In this paper, we use a new benchmark that we recently developed to compare the performance of popular DSP processors from Texas Instruments and StarCore. The new benchmark is based on the Selectable Mode Vocoder (SMV), a speech-coding program from the recent third generation (3G) wireless voice applications. All benchmark kernels are compiled by the compilers of the respective DSP processors and run on their simulators. Weighted arithmetic mean of clock cycles and arithmetic mean of code size are used to compare the performance of five DSP processors. In addition, we studied how the performance of a processor is affected by code structure, features of processor architecture and optimization of compiler. The extensive experimental data gathered, analyzed, and presented in this paper should be helpful for DSP processor and compiler designers to meet their specific design goals.

Keywords: digital signal processors, DSP benchmark, instruction level parallelism, modified cyclomatic complexity, performance analysis.

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Authors: S. Shanthi, V. Muralibhaskaran

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Mammography has been one of the most reliable methods for early detection of breast cancer. There are different lesions which are breast cancer characteristic such as microcalcifications, masses, architectural distortions and bilateral asymmetry. One of the major challenges of analysing digital mammogram is how to extract efficient features from it for accurate cancer classification. In this paper we proposed a hybrid feature extraction method to detect and classify all four signs of breast cancer. The proposed method is based on multiscale surrounding region dependence method, Gabor filters, multi fractal analysis, directional and morphological analysis. The extracted features are input to self adaptive resource allocation network (SRAN) classifier for classification. The validity of our approach is extensively demonstrated using the two benchmark data sets Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammograph (DDSM) and the results have been proved to be progressive.

Keywords: Feature extraction, fractal analysis, Gabor filters, multiscale surrounding region dependence method, SRAN.

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Authors: Phanu Waraporn

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This paper discusses the designing of knowledge integration of clinical information extracted from distributed medical ontologies in order to ameliorate a machine learning-based multilabel coding assignment system. The proposed approach is implemented using a decision tree technique of the machine learning on the university hospital data for patients with Coronary Heart Disease (CHD). The preliminary results obtained show a satisfactory finding that the use of medical ontologies improves the overall system performance.

Keywords: Medical Ontology, Knowledge Integration, Machine Learning, Medical Coding, Text Assignment.

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