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Predicting the binding affinity between compounds and proteins with reasonable accuracy is crucial in drug discovery. Computational prediction of binding affinity between compounds and targets greatly enhances the probability of finding lead compounds by reducing the number of wet-lab experiments. Machine-learning and deep-learning techniques using ligand-based and target-based approaches have been used to predict binding affinities, thereby saving time and cost in drug discovery efforts. In this review, we discuss about machine-learning and deep-learning models used in virtual screening to improve drug-target interaction (DTI) prediction. We also highlight current knowledge and future directions to guide further development in this field.

As cybersecurity issues become ever more prevalent in today’s society, it is imperative that our computer science and engineering programs train students to work in cybersecurity fields. The University of Cincinnati’s Department Electrical Engineering and Computer Science, part of a NSA Center of Excellence, is developing a new B.S. in Cybersecurity Engineering which will be coordinated with cybersecurity programs in Information Technology and in Political Science. We describe our current cybersecurity certificate progran and our proposed new B.S. in Cybersecurity Engineering, which will meet the criteria to apply for ABET EAC accreditation.

In today's society, the popularization rate of computers in the whole country and even all over the world is increasing rapidly year by year. This makes People's Daily work closely connected with computers, information technology and the Internet. As an auxiliary tool, the computer provides great convenience for the process of teaching. Intelligent tools make the learning process more convenient, so the significance of computer science and technology to computer education is huge. In the teaching process, teachers should try their best to use the advantages of computers to assist teaching, and provide students with better network learning environment and learning conditions. Different from the traditional teaching methods, the application of computer technology to education has gradually formed a new type of computer education. This has caused a great change to the current situation of China's education development, and at the same time, China's education model is also faced with various problems.

Data is the most crucial component of a successful ML system. Once a machine learning model is developed, it gets obsolete over time due to presence of new input data being generated every second. In order to keep our predictions accurate we need to find a way to keep our models up to date. Our research work involves finding a mechanism which can retrain the model with new data automatically. This research also involves exploring the possibilities of automating machine learning processes. We started this project by training and testing our model using conventional machine learning methods. The outcome was then compared with the outcome of those experiments conducted using the AutoML methods like TPOT. This helped us in finding an efficient technique to retrain our models. These techniques can be used in areas where people do not deal with the actual working of a ML model but only require the outputs of ML processes.

Machine Translation Systems are part of Natural Language Processing (NLP) that makes communication possible among people using their own native language through computer and smart media devices. This paper describes recent progress in language dictionaries and machine translation commonly used for communications and social interaction among people or Internet users worldwide who speak different languages. Problems of accuracy and quality related to computer translation systems encountered in web & Apps-based translation are described and discussed. Possible programming solutions to the problems are also put forward to create software tools that are able to analyze and synthesize language intelligently based on semantic representation of sentences and phrases. Challenges and problems on Apps-based machine translation on smart devices towards AI, NLP, smart learning and understanding still remain until now, and need to be addressed and solved through collaboration between computational linguists and computer scientists.

Computer animations are widely used to improve comprehension. They are used in almost all disciplines. However, a poorly designed animation may not improve learning as such animations may increase the cognitive load. As a result, quite a lot of research is being focused on design principles that would be effective with respect to the cognitive load theory and can be integrated into animations to improve comprehension. This research work found the answer through a well-designed experimental study. The present study first identified effective design principles through an extensive literature review. Thereafter, an experimental study was designed in which 50 students of fourth semester of CSE (Computer Science and Engineering) participated willingly. The participants were randomly divided into two groups of 25 students each. The Group-1 was taught using modern animations, which were designed according to the selected design principles, whereas Group-2 was taught with conventional animations with auditory explanation only. A t-test was conducted on the post-test scores and found that the variances between the groups were equal (F=1.144, Sig = 0.290). Further, the two-tailed value was observed and found to be

The past 30 years have seen increased adoption of learning management systems (LMSs) in education. Several studies have investigated the usability of LMSs for students. However, very few studies have assessed the usability from the instructors’ perspective. Usability issues can pose challenges for instructors who use LMSs to create, manage and deliver courses. These challenges require instructors to spend extra time and energy on tackling the challenges rather on teaching-related tasks, which will have negative impacts on learners’ experiences and learning outcomes. This paper aims to identify usability challenges in LMSs for instructors. We used Canvas as an example and conducted user testing with 35 university instructors in computer science and engineering disciplines. Pre- and post-interviews were transcribed and analyzed together with the observation data during their use of Canvas to carry out tasks. The results show that, although Canvas has made continuous efforts to improve its usability, instructors still face some usability challenges. Instructors are a diverse user group for LMSs. Further research should consider recruiting participants from other disciplines and investigating other LMSs to identify possibilities for improving general usability of digital tools for instructors.

Fifty years after the publication of the first algorithms for the automatic detection of Atrial Fibrillation (AF), this cardiac condition is still the most studied from the computer science and engineering perspectives. Machine learning techniques are widely applied to a variety of problems, including detection, characterization, prediction and simulation, in general with promising results. In the last years, the Big Data + Deep Learning binomial is getting most of the attention in academia and industry, but on many occasions this approach fails on capitalizing all the knowledge acquired in previous decades of research. This article, written as a companion to the keynote with the same title presented in the CinC 2020 conference, tries to illustrate the importance of exploiting expert knowledge and classical approaches in synergy with the most advanced deep learning methods, which by themselves have fundamental limitations. The discussion is built around the AF detection problem and the conclusions extracted from the Physionet/CinC Challenge 2017, but the main points can be relevant in other problems for which humans have a better answer than computers, and this answer can be described.

The university has been applying a teaching methodology based on continuous assessment over the last few years. The main advantage of this methodology is that students acquire the knowledge gradually, so that they consolidate it better in their memory; however, they run the risk of forgetting what was studied in the first parts of the course when they finish it. To motivate students to review what they learnt, we have implemented an augmented reality mobile application and methodology with which students review the contents of the subject through the serious game. Moreover, the game focuses on the specific difficulties of each student by reinforcing those questions that are most difficult for them. In this paper, we also present how the game has been customized for various courses from the Degree in Computer Science and Engineering at the University of Cadiz and which results were obtained.

A thesis report submitted to the School of Computer Science and Engineering, Nanyang Technological University, Singapore, in partial fulfilment of the requirements for the degree of Doctor of Philosophy.

Cybersecurity education has been emphasized by several national organizations in the United States, including the National Academy of Engineering, which recognizes securing cyberspace as one of the 14 Engineering Grand Challenges. To prepare students for such challenges and to enhance cybersecurity education opportunities at our large research university, we implemented an NSF-funded cybersecurity education project. This project is a collaborative effort between faculty and graduate students in the Engineering Education, Computer Science (CS) and Computer Engineering (CPE) departments at a major US research university. In this effort, we integrated cybersecurity learning modules into multiple existing core CS and CPE courses following Jerome Bruner's spiral-theory model, which has previously been used to reformulate several academic curricula. In this paper, we present our cybersecurity curriculum initiative, describe the spiral-theory based process we developed to implement the curriculum and provide an in-depth description of four reusable cybersecurity learning modules that we developed. A core tenet of spiral theory holds to revisit topics as students advance through their curriculum. This work applies this approach to Cybersecurity education by carefully designing the learning objectives of the modules and its contents. For evaluating these learning modules we implemented pre and post-tests to assess students' technical knowledge, their perceptions towards the modules' learning objectives, and how it influenced their motivation to learn cybersecurity. Our findings are overwhelmingly positive and the students' feedback has helped us improve these learning modules. Since its inception, our initiative has educated more than $2\,000$ students and is currently being used to revise the affected courses' syllabi.

Trust has long been a focus of research in the areas of psychology and marketing. However, it has not been studied extensively in computer science and engineering. In this study, the notion of trust was investigated from the perspective of statistical analysis and automatic machine-based classification of speech. A gender-balanced database of speech samples representing individuals with low and high public trust was created and analyzed statistically to determine acoustic speech parameters correlated with trust. The effect of gender was analyzed. An automatic trust classification based on acoustic speech parameters was conducted using a neural network.

Pattern recognition is a task of searching particular patterns or features in the given input. The data mining, computer networks, genetic engineering, chemical structure analysis, web services etc. are few rapidly growing applications where pattern recognition has been used. Graphs are very powerful model applied in various areas of computer science and engineering. This paper proposes a graph based algorithm for performing the graphical symbol recognition. In the proposed approach, a graph based filtering prior to the matching is performed which significantly reduces the computational complexity. The proposed algorithm is evaluated using a large number of input drawings and the simulation results show that the proposed algorithm outperforms the existing algorithms.

Since 2011 Thomas Schedel has been working as a research assistant at the Institute of Information Systems (iisys) at Hof University. In 2016 he successfully finished the Ph.D. program "Computer Science and Engineering" (CSE) at Aalborg University in Denmark. In his thesis - supervised by Henrik Legind Larsen (Aalborg University) and Claus Atzenbeck (Institute of Information Systems, Hof University) - he claims that considering temporal aspects in addition to spatial and visual properties in spatial parser design will lead to significant increase in parsing accuracy, detection of richer structures and thus higher parser performance. For the purpose of providing evidence, parsers for recognizing spatial, visual and temporal object relations have been implemented and tested in a series of user surveys. It turned out, that in none of the test cases pure spatial or visual parser could outperform the spatio-temporal parser. Instead, the spatio-temporal parser was able to compensate limitations of conventional parsers. Furthermore, differences in parsing accuracy were successfully tested for statistical significance. The results indicate a non-trivial effect that is recognizable by humans. We have shown that the addition of a temporal parser shifts machine detected structures significantly closer to what knowledge workers intend to express. Due to its significant contributions to the research area of spatial hypermedia the thesis has been awarded with the Informatikpreis 2016 (given by the German Fachbereichstag Informatik, FBTI).

Instructional strategies for e-content development have to be entirely different from that for traditional printed materials, such as text books and manuals. This is due to the fact that, technically and socially both have different instructional processes. Due to the advent of ICT development in recent times, many Computer Technology subject contents are being uploaded in e-learning modes. Training imparted through e-modes has increased in recent times specifically in India. This paper demonstrates the effectiveness of our suggestion on Real World Problem centric Instructional approach. Specific issues on the e-mode have been inferred through a social study conducted on Indian learners (respondents). The paper justifies the adaptation of ‘First Principles of Instruction’ through our experimental study. Due to reasons elaborated in the paper this proven Instructional approach using ‘First Principles of Instruction’ would be well suited for e-content development of Computer Science and Engineering subjects.

In recent decade, a wave of apprehension swept across the Pearl of Oriental with regards to the disappearance of high value tangible and intangible heritages due to urban renewal and redevelopment. The flourish of computer science and engineering, however, offers a rosy spectacle for heritage preservation. Virtual heritage is no longer an idea in cloud-cuckoo-land. In this research paper, we propose the ground breaking five dimensional GIS virtual heritage. Whilst traditional two dimensional GIS stores the information of X and Y axis, the recent three dimensional GIS includes the information of building height and other information is useful to urban planners when they make decision in change in use of land. The fourth dimension includes time with collective memories of Hong Kongers. The invaluable intangible heritage can be kept by record of oral history. Changes in ethnic minorities, different walks of lives provide dazzling and interesting angles of the modern city. We also include the concept of the fifth dimension of automated virtual and augmented heritage with drone and robots’ help in taking 360 degree virtual reality videos and photos. Whilst strand of literatures on VR, AR, 3D GIS and memories scatter in different areas of research, combination of all these technologies is the first of its kind. Research on automated VR and AR is scarce or non-exist. It is expected that the 5D GIS virtual heritage offers a new angle to historian, economists, sociologists, urban planners.

We report the experience of adopting an innovative technique for creating tutorial videos which complement lectures and facilitate students' learning. Our technique relies on: 1) preparing starter pages consisting of code fragments or writings/figures on a drawing tablet; 2) illustrating complex ideas on the drawing tablet; 3) recording all computer desktop activities (e.g., development of code on a programming IDE, illustration on the drawing tablet); and 4) sharing the recorded tutorial videos with students online. Our technique has been adopted in creating tutorial series for four Computer Science and Engineering courses, ranging from the first year to the third year. Analytics of these online tutorial videos is presented to show the average amount of time which each registered student spent on watching them. Course evaluation results indicate that our technique is perceived as effective for achieving the course learning outcomes. Comparison of students' performance on complex topics (arrays and loops) also indicates a positive impact of our approach.

Nowadays, information technologies are used in almost every field of Computer Science and Engineering. One of the most used areas is the health sector. With the use of digital hospital systems, patient data is now stored in a computerized environment, thereby creating biomedical data sets. These datasets, which are very large in size, are very difficult to analyze and interpret by a human. The machine learning algorithms are mainly used to analyze and interpreted these data sets. In this study, the performances of 5 machine learning algorithms have been compared by employing 5 different biomedical data sets and the results obtained were compared statistically. Results reveal that the KNN algorithm performs better for small biomedical data sets, whereas the ANN algorithm performs better for large data sets in terms of classification problem for the health sector.

Computer Organization and Design (COD) is a fundamentally required early-stage undergraduate course in most computer science and engineering curricula. During the two sessions (lecture and project part) of one COD course, educational platforms play an important role in cultivating students' computational thinking, especially the ability of viewing the hardware and software in a computer system as a whole (computer system thinking ability for short in this paper). In order to improve teaching quality, in this paper, we discuss the deployment of an inexpensive in-house Field Programmable Gate Array (FPGA) cloud platform, which can provide students with hardware-software co-design methodology and practice. The platform includes 32 FPGA nodes and the scale can be dynamically changed. Each cloud node is heterogeneously composed of an ARM processor and a tightly-coupled reconfigurable fabric to provide students with hands-on hardware and software programming experiences. We illustrate our efforts to make the FPGA cloud as an easy-to-use resource pool to elastically support a class with 92 undergrads via Internet access and to monitor students' experimental behaviors. We also present key insights in our teaching activities that indicate such appliance is feasible to provide practice of both basic principles and emerging co-design techniques for students. We believe that our cost-effective FPGA cloud is of significant interests to educators looking forward to improving computer system-related courses.

The Expert Systems With Applications (ESWA) is a leading journal in the fields of computer science and engineering. Motivated by its outstanding performance, this paper seeks to develop a comprehensive overview of research activities in ESWA since its inception in 1990. In this regard, bibliometric techniques have been utilized to characterize the status quo, dynamics, and development trends of research patterns in ESWA. In doing so, the work used Scopus database as a source of data required. A data visualization software, visualization of similarities (VOS) viewer, was used to map the bibliographic material. The Scopus database yielded 12,254 documents published in ESWA from 105 countries with an average of 408 documents/year. The most productive country was Taiwan (2,069 documents; 17.0%). National Cheng Kung University, Taiwan, was the most productive institution (219 documents; 1.8%). The major topics which will continue to be active include genetic algorithms, data mining, neural networks, support vector machines, classification and machine learning, feature selection, particle swarm optimization, fuzzy logic, and clustering. The outcomes underline the significant growth of ESWA through time. The vitality of topics addressed in ESWA to solve real-world problems boosts the progress and advancements of knowledge in this journal.

Computer education is in the midst of a major transformation as a result of the rapid emergence of new technologies, intersection of computing with other disciplines and growing interest among students in computing courses. Such transformation prompted educators to redefine the way computing education is delivered and experiment a wide range of learning approaches. One of these approaches is the integration of hardware prototyping platforms such as Arduino, Raspberry Pi and Intel Internet of Things as part of project-based learning. These platforms have become in recent years instrumental tools for improving students' learning process and promoting proactive thinking. The aim of this study is to investigate the usefulness of integrating low cost open-source hardware platforms into engineering and computer science courses. In particular, we explore the use of an experiential learning approach using these kits for improving the students' learning experience in computer science and engineering courses. Throughout this paper, we discuss the outcome of our investigation and provide insights on how to make classrooms more experiential using the hardware prototyping paradigm.

In the current software industry most of the complex softwares are configurable. Configurable software include different features that are considered essential for the functioning. Certain configurable features can have higher impact on system functional behaviour when compare to other features. A combination of different features selected result into a configuration space. There is a enormous increase in configuration space as the number of features increases. Each configuration in configuration space produces different system performance. Hence, there is a need to study the impact of different configuration on the system performance. Predictive models offer solutions to analyze system performance for a given configuration set. In this paper different machine learning techniques are compared and we propose a comparative results using WEKA tool. We propose a Neural network model with statistical techniques for predicting system performance for input configuration.

Sustainable Environmental Development is one of the hot topics nowadays. Industries were advised to reduce and control pollution by using pollution control equipment. Computers are also contributing some amount in the pollution and power consumption. On the other hand, miniaturization, less power consumption, and environment-friendly devices are invented by the researchers every day. One such device is Raspberry Pi. Size of the Raspberry Pi is not bigger than a credit card with high computing capacity and low power consumption. Pi can run Linux as well as Windows 10 in its higher versions. This paper aims to suggest the Pi can be used for practicing most of the laboratory courses in the computer science engineering curriculum. Most laboratory courses are practiced in C, C++, and Java languages. Apart from above-mentioned languages, some laboratory courses make use of front end and back end tools. Above-mentioned languages can be executed in Raspberry Pi. Following points are analyzed between normal computer and Pi, execution time, power consumption, and environmental effect. In all the comparison, Pi gives much higher advantage over existing system.

Healthcare is a broad subject with many different challenges, yet it is important and relatable to everyone. The aging Baby Boomer generation is an important healthcare issue today. In Canada, and many other developed nations, the number of citizens reaching the age of retirement and seniority is growing faster than the rate of citizens working and providing health related services. As people age they tend to require more frequent checkups and health services, ultimately putting a bigger resource drain on healthcare infrastructure. New advancements in Computer Science and Engineering are allowing the development of next generation applications with the purpose of providing healthcare services in a cost effective and efficient way. This paper proposes a multi-agent system for tracking and monitoring health data for patients. Furthermore, agents within the system use reinforcement learning techniques to build an adaptive user interface for each human user. The actions and behaviour of users are monitored and used to modify their respective user interface over time. To demonstrate the feasibility of the architecture, two scenarios are provided. We conclude with several possible future directions for this research.

The purpose of this mobile application proposed for System programming of Computer Science and Engineering is to provide study material, question bank, games like word search puzzle, videos etc. This application also provides answers to the questions in the question bank to help student to clear their doubts in handy manner. It is a type of Modern learning content delivery system. This application will clear all doubts related to System Programming.Students can use this application anywhere, at free of cost. This application can be useful for android based mobile as well as tablets. Students can access all chapters related to the subject System programming. User can check their concept by solving quiz. Student can improve their programming skills by trying Hands-On feature, which is provided in this application. Main vision of this application is to provide a complete set of notes for System programming subject.

From Last two decades internet technology is at top position. Due to internet technology, it is easy for communication, data transfer or sharing files. Internet technology is one of the major parts of computer science and engineering & electronics and telecommunication. There are many techniques and different subject of Computer Science & Engineering, Information Technology, and Electronics & Telecommunication contribute to develop educational technology. Such as, Data structure, discrete mathematics, database management system, operating system, computer networks, communication engineering, digital signal processing, computer organization, etc. This core subject generally used for making the applications with help of languages and tools like different programming languages, matlab, Xilinx, structure query language, Mongo DB, etc. In this research paper, evaluation & statistical analysis of modern tools and education technology in Student outcomes of C.S.E, I.T. and E&TC engineering graduates using T-test is explained.

We describe our experience designing and delivering a general education technological fluency course that frames the discussion of computer science and engineering technology (electronics and programming) in the context of sound-art: art that uses sound as its medium. This course is aimed at undergraduate students from a wide variety of backgrounds and is designed to fit into the ``Intellectual Explorations'' area of a general undergraduate program. The goal is to introduce computer engineering and computational principles to non-CS students through an exploration of sound-art, experimental and electronic music, noise-making circuits, hardware hacking, and circuit bending.

In this paper, we design a smart phone UX/UI and a tap pattern recognition algorithm that can recognize tap patterns from a tapping user's fingers on the screen, and implement an application that provides user-customizable smart phones’s services from the tap patterns. A user can generate a pattern by tapping the input pad several times and register it by using a smart phone’s favorite program. More specifically, when the user inputs a tap pattern on the input pad, the proposed ∙제1저자 : 김영빈 ∙교신저자 : 김유희 ∙투고일 : 2014. 5. 20, 심사일 : 2014. 6. 23, 게재확정일 : 2014. 8. 8. * 동국대학교 컴퓨터공학과(Department of Computer Science and Engineering, Dongguk University) ** 신한대학교 IT융합공학부 컴퓨터공학전공(Department of Computer Science and Engineering, Shinhan University) 96 Journal of The Korea Society of Computer and Information August 2014 application searches a stored similar tap pattern and can run a service registered on it by measuring tap pattern similarity. Our experimental results show that the proposed method helps to guarantee the higher recognition rate and shorter input time for a variety of tap patterns. ▸

Mining data streams has recently become an important active research work and more widespread in several fields of computer science and engineering. It has proven successfully in many domains such as wireless sensor networks, ATM transactions, search engines, web analysis and weather monitoring. Data steams can be considered a subfield of machine learning, data mining and knowledge discovery. Data Mining is a step in the process of knowledge discovery from large amount of data. Traditional data mining techniques can not be easily applied to the data stream mining due to unique characteristics of data streams. In this research work, we will survey the main techniques and applications of data mining and data stream mining. We then study, the computational and miming challenges in particular, on-line mining of continuous, high-speed massive data streams.

This paper proposes the creation of a Learning Management System (LMS) named CloudLab with support to Virtual Laboratory (VL). It aims at distance training of Computer Science and Engineering students in Hardware, to meet the needs of education and research institutions. That CloudLab has important features such as remote access to design tools with teacher mentoring and monitoring, file management, viewing videos and pictures of networks social and interpersonal communication via asynchronous messages. A practical experiment was conducted with students of Computer Science that demonstrated the effectiveness of the system and its acceptance by students and teachers involved.

In order to find meaningful patterns of research trends in the computer science and engineering field, we crawl a significant amount of bibliographic information, 3 million or more scholarly papers published from 1956 to 2015. We also make a list of target key words and analyze their frequency rate over the past 60 years based on the terms extracted from the titles and abstracts of the papers. We apply k-means clustering analysis for the target key words, and present a meaningful chronological pattern of target key words in the computer science engineering field over the past 60 years.

This paper presents a novel interdisciplinary approach to aid with the growing concern about how to showcase computer science and engineering degrees to pre-university level students. This novel approach is based on empowering students to create their own music-related game using real music instruments. In order to allow the students to program their games we have used the Greenfoot Introductory Learning Environment to teach object-oriented programming skills with the java programming language. We have also taught the students music theory and practice. All these skills were required to allow the students to successfully develop their musical games that interact with the music instruments.

UML diagrams form an important part of the software design specification. The source of these diagrams is requirement specification which is created from the user’s need and requirements. In our work, we identify that two important areas in computer science and engineering, software engineering (SE) and natural language processing (NLP), form the core of this development. An algorithm for undertaking study of this approach is also presented. Herein, we also list the main usage of our technique to handle a more generalized environment such as non-software engineering domain.

The First Workshop on Personalised Multilingual Hypertext Retrieval (PMHR 2011) was held on the 6th June 2011 in conjunction with the 22nd ACM conference on Hypertext and Hypermedia in Eindhoven, The Netherlands. The aims of PMHR 2011 were to promote collaboration and the exchange of ideas between researchers working on hypertext and adaptive hypertexts, crosslingual information retrieval, personalised search, personalisation for the web and hypertexts, and recommender systems. The workshop had a specific focus on research in user modelling and multilingual personalisation for hypertext retrieval.

Ontologies perform the cumbersome task of translating data on the web into a form suitable for manipulation by machines. The discovery of concepts and relationships from unstructured text is a crucial and challenging task in constructing ontology (s). A pragmatic solution is offered by a metaontology as it supplements the ontology with related concept pairs and relationships. An ideal approach to construct a metaontology is to employ databases as they save on the time required to store, retrieve and update data. The relationships in the database are augmented by converting them into a graph to determine transitive relationships. Accuracy is ensured by integrating only those relationships with the ontology which have a high degree of certainty. This is affirmed by the evaluation and the results obtained using the ontology constructed along the lines of the metaontology.

Fe.g. is an animated flowchart with example which can be used for algorithm based subjects. In Fe.g., first the working of algorithm is demonstrated with the help of animated flowchart and then the step by step working of algorithm with the help of example. So this activity is considered for the subject System Programming of Third Year Computer Science and engineering. One group pre-test pots-test model is considered to test the effectiveness of this activity. The results are also explained in this paper.

Cashew is a commercial commodity that plays a major role in earning foreign revenue among export commodities in India. The purpose of this research work is to explore image processing techniques and approaches on Indian cashew variety identification based on their kernels. Colour is an important quality factor for grading, marketing, and end users. Our primary objective is to develop a cost-effective intelligent model to identify the cashew kernels. Colour features in the RGB (red-green-blue) colour space are extracted and computed. A feed-forward neural network is trained to classify sample cashew kernels. An intelligent classification system based on computer vision system can be developed for automated grading and sorting to speed up the classification of cashew kernels. This will solve the major problems of many of the cashew export industries also, gives justice to the cashew growing farmers in accurate grading. The classification system is evaluated on cashew kernels of 6 different grades. The result of our study shows that, the system gives about 80% classification rate.

Interlanguage is an important issue in the field of second language acquisition for the past forty years. This study classifies the errors into three levels-lexicon, syntax and discourse, and then analyses the error examples to reflect the cause of interlanguage. The result may make some suggestions to the English teachers in English teaching.

Gary McGraw interviews Greg Morrisett, the Allen B. Cutting Professor of Computer Science and associate dean for computer science and engineering at Harvard University. His current work is on applications of advanced type systems, model checkers, proof-carrying code, and inline reference monitors for building efficient and provably secure systems. He's also working on languages for sensor networks. Hear the full podcast of the interview at www.computer.org/security/podcasts/ or www.cigital.com/silverbullet/. The Web extra is the full transcript of the interview.

Computer science and engineering education is faced with the need to respond to rapid changes in a global economy while still fulfilling the role of teaching the fundamentals. This paper presents techniques for assessing the development of an advanced database concepts course for undergraduates that responds to an industry perspective of the technological advances in the field. Cooperative learning and hands-on assignments relating theory to practice are the pedagogical foundation for an advanced undergraduate course. An alumni survey illustrates that students perceived that the course activities and strategies enabled them to attain the course objectives.

The idea of using web-based technologies in education as a means of interactive learning has been erging for several topics in computer science and engineering. It proves to be more effective in the learning process and hence rapidly expanding. In this paper we introduce an integrated environment for active learning in the information theory course and related fields. Our environment is designed to meet the learning preferences of computer engineering learners. The environment integrates several different materials to support the learners' preferred style. It includes a movie-like welcome component, an animated hyper-text introduction for the basic concepts of information theory, a communication model simulator, and an interactive set of exercises for self assessment. All the components of the environment are integrated into a single interface based on Java2D of Sun Microsysts. Being a Java applet, our environment is portable and web-based enabled, which makes it possible for learners to study at their convenience. An initial study shows that our integrated environment is a useful tool for learners of information theory and related fields.

Since the introduction of inking technology, computer science and engineering education has experienced a flurry of new instructional approaches. Many studies have assessed qualitative improvements over traditional classroom presentation techniques. In this paper, we present quantitative results on the improved student perception of teaching when using Classroom Presenter instead of PowerPoint for classroom presentation. We present an overview on how Classroom Presenter was used in a large undergraduate digital design course and discuss the assessment of results and their analysis. Our data shows with statistical significance that students perceive lectures with Classroom Presenter as more interesting and more adequately paced.

With the wide development of smartphones, mobile data usage has enjoyed rapid growth in recent years. Unfortunately many users are plagued with Phantom Data Usage (PDU), which refers to the unexpected mobile data usage that does not accord with user perception. We investigate about 400 real PDU issues and find the causes of PDU are not only the exceptions of applications, for example, software bugs or malware, but also the user’s personalized misuse. Based on the observations that each user preserves specific data usage patterns under particular environmental context, we present PDS, a PDU detection system, which automatically detects whether the current data usage is consumed as expected. Results from our evaluation experiments show that 72% of PDU cases detected by PDS are confirmed by users. MOE (Min. of Education, S’pore) Published version

Research has substantially increased in modern times due to availability and search facility of literature sources through Internet. Carrying out research and proving that it is done is a necessity for excellent academic career and for satisfying requirements of Master or PhD degrees in most universities. There is no recipe book for producing the research with desired taste and quantity, however, general methodology does exist. This paper presents crucial parts concerning research process in Computer Science and Engineering (CSE). The paper discusses the important parts of research methodology in CSE including research problem formulation, literature review, research design, and research communication. The paper presents each phase of the research process with essential ingredients, moreover, wherever required, the paper also provides pointers for further reading. The presented discussion is in the context of research applicable in CSE field. Therefore, we expect that this paper would become a good starting point for newbie researchers in CSE.

Machine learning and cloud computing techniques can help accelerate timing closure for FPGA designs without any modification to original RTL code. RTL is generally frozen closer to system delivery target to avoid injecting new unforeseen bugs or significantly affecting design characteristics. In these circumstances, developers trying to close timing are either at the mercy of random trials through placement seed exploration or through vendor-provided design space exploration tools that run a few compilation trials with changes to the CAD tool options (or parameters). Instead, we propose evaluating multiple CAD runs in parallel on the cloud, supported by a Bayesian learning and classification framework for generating multiple CAD parameter combinations most likFPGA CAD tool parametersely to help attain timing closure. We maintain a database of FPGA CAD tool parameters (input) along with associated variations in timing slack (output)to enable the learning process. A key engineering resource we use here is cheap and abundant parallelism made possible through cloud computing frameworks such as the Google Compute Engine. Across a range of open-source benchmarks, we show that learning helps improve total negative slack (TNS) scores by 10.5× (geomean) when compared to a single baseline run of Quart us 14.1 and by 7× (geomean) when compared to Alter a Quart us 14.1 Design Space Explorer (DSE). Accepted version

Mohsen Malmir1 http://mplab.ucsd.edu/~mmalmir/ Karan Sikka1 http://mplab.ucsd.edu/~ksikka/ Deborah Forster1 dforster@ucsd.edu Javier Movellan2 http://www.emotient.com/ Garrison W. Cottrell3 http://cseweb.ucsd.edu/~gary/ 1 Machine Perception Lab. University of California San Diego, San Diego, CA, USA 2 Emotient, Inc. 4435 Eastgate Mall, Suite 320, San Diego, CA, USA 3 Computer Science and Engineering Dept. University of California San Diego, San Diego, CA, USA

It is now clear that information technology (IT) construed broadly has the power to revolutionize all areas of science and engineering (S&E) research and education. If exploited, this transformative power can change S&E forever. The National Science Foundation (NSF) is working toward this end, and, as a result, past efforts in supercomputing and high-performance networking are being subsumed into a broader, integrated vision of a more capable, ubiquitous, and accessible cyberinfrastructure (CI). We cannot attain this overnight, or alone, or without substantial research in computer science and engineering. This paper will outline the potential for revolution, the vision of CI, some of the challenges, and a possible path toward reaching that vision.

Computer vision is becoming a mainstream subject of study in computer science and engineering. With the rapid explosion of multimedia and the extensive use of video and image-based communications over the World Wide Web, there is a strong demand for educating students to become knowledgeable in computer imaging and vision. The purpose of this paper is to review the status of computer vision education today.

Introduction to computer science and programming are courses that play an important role in students' performance in computer and engineering degrees. It is in this course that students learn the main basic concepts and computational structures to be applied in all kind of computer systems. Despite its importance, many teachers and many studies report difficulties observed in learning of these subjects, resulting in a high rate of failure and lack of motivation among students. There are many experiments reported in the literature that attempted to solve this problem, such as: different pedagogical approaches, the use of special hardware like tablets, and the use of learning objects; however, all these formats are applied based on traditional classroom learning formats which results in the same type of result. Even some innovative approaches that did not present a formal validation of the process ended up losing as a methodology. Considering this scenario and the importance of this discipline in students' curriculum, we propose a blended model, that uses distance learning environments allied to new technologies, aimed to contribute with students performance and knowledge acquirement. In this blended model, one programming course was developed and applied to 92 students in computer science and engineering degrees, with course material consisting of video lectures and animations that were used to show and to explain critical concepts of the discipline where students often have problems. All this material was implanted by a Learning Management System (LMS), which showed statistical reports about all activities, including collaborative and interactive activities. We also used together with the LMS a dedicated community on Facebook and, in this article we present our analysis and some conclusions obtained by observing the interactions of students on Facebook and on LMS. We did a few meetings between students and teachers and also developed a methodology for tutoring with our tutors to improve our students' participation in the activities proposed during the course. In this paper, we describe the methodology in which we developed everything. We also present the results achieved in terms of students' performance and provides comparison with other students who attended conventional courses in programming.