Development Of Computer Systems Research Articles

Magnetic domain wall neuron with lateral inhibition

The development of an efficient neuromorphic computing system requires the use of nanodevices that intrinsically emulate the biological behavior of neurons and synapses. While numerous artificial synapses have been shown to store weights in a manner analogous to biological synapses, the challenge of developing an artificial neuron is impeded by the necessity to include leaking, integrating, firing, and lateral inhibition features. In particular, previous proposals for artificial neurons have required the use of external circuits to perform lateral inhibition, thereby decreasing the efficiency of the resulting neuromorphic computing system. This work therefore proposes a leaky integrate-and-fire neuron that intrinsically provides lateral inhibition, without requiring any additional circuitry. The proposed neuron is based on the previously proposed domain-wall magnetic tunnel junction devices, which have been proposed as artificial synapses and experimentally demonstrated for non-volatile logic. Single-neuron micromagnetic simulations are provided that demonstrate the ability of this neuron to implement the required leaking, integrating, and firing. These simulations are then extended to pairs of adjacent neurons to demonstrate, for the first time, lateral inhibition between neighboring artificial neurons. Finally, this intrinsic lateral inhibition is applied to a ten-neuron crossbar structure and trained to identify handwritten digits and shown via direct large-scale micromagnetic simulation for 100 digits to correctly identify the proper signal for 94% of the digits.

Big data simulation software for breast cancer growth repository system

The development of the simulation software aims at anticipating the growth of breast cancer. Based on certain numerical iterative methods, this simulation works with discretization and Partial Differential Equation (PDE). As a class of Helmholtz equations, PDE approach are known to govern the growth of this type of cancer. Considering both time and place, the Helmholtz equation’s accuracy visualizes breast cancer and its growth. This growth is of breast cancer is captured and the convergence results in sequential and parallel computing environ-ment is expressed through the numerical libraries available in the repository system. Currently, both the parallel performance measurement and Numerical analysis that involve execution time, speedup, efficiency, effectiveness and temporal performance are being investigated. The process of breast cancer visualization requires a huge memory and expensive calculations. It is observed that both the distributed memory and distributed processors of the parallel computer systems development were required in most of the studies conducted on the growth of this cancer. It is considered as an important computation platform needed to the development of parallel repository system leading to an increase in the speed and a decrease in the cost. The simulation software has several beneficial characteristics such as high performance estimation, multidimensional visualization of breast cancer and being friendly. It also provides a real time solution and strength. This soft-ware is expected to increase the level of confidence in terms of computer-aided decision making which can be reflected positively on com-prehensive breast cancer screening; breast cancer diagnosis; and clinical assessments and treatment.

Analysis of teaching reform mode based on cognitive computing system – An example of dragon boat teaching

It is a technical difficulty for the cognitive system to quickly analyze the characteristic data in massive data. A new method of cognitive fusion is proposed. In the embedded ARM server system, the software development and design of cognitive computing system are designed, the database of cognitive computing system is constructed, the hierarchical structure design algorithm of process constraint is used for cognitive information fusion, and the fuzzy scheduling and depth calculation are used to cluster the information, and it is carried out in the embedded ARM server environment. The integrated development and design of the system takes the reform of dragon boat teaching technology as an example. The test results show that using this system to reform the Dragon Boat teaching technology improves the artificial intelligence of dragon boat teaching, the error rate of teaching resources transmission is low, and the overall reliability and balance of the system is good.

Observation results on pedestrian-vehicle interactions at non-signalized intersections towards simulation

The modelling and simulation of pedestrian-vehicle interactions is an open challenge for both research and practical computational solutions aiming at supporting urban/traffic decision makers and managers. The social cost of pedestrian-car accidents pushes the development of more effective and expressive computational models and simulation systems, integrating analytical knowledge, data and experience about pedestrian-vehicle interactions. The paper presents the results of a significant data gathering campaign focused on the considered phenomenon and aimed at supporting the extension and calibration of an existing model. A video-recorded naturalistic observation was executed in an area of the City of Milan (Italy) characterized by a significant presence of elderly inhabitants and by a high number of road accidents involving pedestrians in the past years. The achieved results include both macroscopic and microscopic indicators about pedestrian-vehicle interactions at the observed non-signalized intersection, with reference to: (i) traffic volumes; (ii) Level of Service; (iii) drivers compliance to pedestrians right of way on zebra crossing; (iv) age-driven pedestrian crossing behaviour, focusing on motor skills (speeds and trajectories) and decision making (accepted time gap to cross). Since elderlies represent one of the most vulnerable pedestrians in terms of road accidents, data analysis is focused on comparing results among two samples composed of adults and aged pedestrians. Results showed that crossing behaviour is characterized by three main phases: approaching, appraising (evaluation of the distance and speed of oncoming vehicles) and crossing. Moreover, results showed a significant difference in the crossing behaviour of adult and elderly pedestrians. The final objective of the research is to support the development of a microscopic agent-based tool for simulating pedestrian-vehicle interactions at non-signalized crosswalks.

Development of computational software system "Bakis" for solving aquatic radioecological problems

Development of computational software system "Bakis" for solving aquatic radioecological problems

Guest Editorial Special Issue on Data-Driven Computational Intelligence for e-Governance, Socio-Political, and Economic Systems

The three papers in this special section focus on data driven computational intelligence for electronic governance, socio-political and economic systems. These papers reflect the design and development of computational tools and systems to exploit data generated through the interaction of citizens and organization to provide optimized e-governance services. Contagion in bank failures threatens world economics. Wireless sensing and distributed embedded computation is spurring a growth in connected computing artifacts - enabling accessibility to a plethora of new and diverse, multi-modal sources of quantitative, qualitative, environmental and user centered data. Examples of these data sources include geolocation, social media and online interaction from different personalized devices, mobile phone data, audio, visual, text, digitally associated opinions, human affect and sociometric sensor data. A key challenge is to harmonize and extract meaningful features and associations from these data streams as well as to handle dynamically and real-time generated data where quantities of interest might be spatially and temporally distributed in terms of their relationships for modelling and predicting particular events, behaviors and conditions.

Language, emotion, and the emotions: A computational introduction

AbstractIn this paper, the second in the pair, we discuss how psychologists, linguists, and computer scientists model emotion from a computational perspective. First, we draw some parallels between the formalization of the emotions in the human body and the development of computational systems. Then we look at three influential schools for formalizing emotion in language, and we use a specific example to show that they do not have the same concerns and expressive power. We give some examples of computational resources for emotions, insisting on why the variety of languages and cultures makes it impossible to apply a monolithic universal approach. We then turn to emotion and opinion and briefly overview opinion mining and emotion generation. Instead of describing techniques and technologies and providing quantitative results, we try to present a “big picture” of emotion processing.

Computerized and distance learning systems (the case of medical diagnostics)

The purpose of this paper is to analyze the current state and the possibility of developing computer systems of various types in education (the case of medicine). Particular emphasis is on the use of case studies that combine linguistic and multimedia components and on intellectual technologies to implement the learning process, individually controlled at different stages. The considered methods of knowledge engineering in the construction of intelligent systems form the skills of individual and teamwork. A separate aspect is the methods and means of distance learning with the use of telemedical and internet technologies in teaching and continuous professional development. Ontologies are used as a means of cognitive visual representation of knowledge. They find application in the presentation of medical knowledge that characterize pathological processes. Intellectual maps and concept maps are used as the primary analysis of logical relationships of characteristics. Role games contribute to the development of knowledge extraction for expert systems. This allows all members of the group to simulate the roles of a knowledge engineer and an expert. In addition, the teacher corrects, if necessary, this process and indicates in conclusion on the mistakes made and the unused possibilities for optimizing the dialogue between the student-cognitive scientist and the student-expert. Based on case-method it is proposed to implement examples and questions from clinical practice, including video fragments. This allows you to monitor the correctness of the actions of students during inspections and manipulations. The expert system and remote methods of work are used for the analysis of microscopic drugs under the supervision of the teacher. Building an intellectual learning system that includes cases is the basis for acquiring the skills of differential diagnosis in the process of examining a virtual patient. Telemedical technologies, using different video cameras, suggest remote teaching of not only theoretical, but also clinical subjects with examination of patients, including testing of students and video examinations. As a result of the research, the author proposed schemes of computerized and intellectualized technology for teaching medical subjects of various types (morphological, clinical, and cybernetic). This contributes to the increase of knowledge, taking into account the individual abilities of students on personal programs, forms skills to extract and analyze the information received. Videoconferencing allows you to improve your skills remotely at the place of work in the process of contact with lecturers and teachers. Specially developed approaches presuppose remote examination and diagnostics under the supervision of the teacher. In addition, demonstration of patients with various pathologies during telelectures. These approaches offer opportunities for individual mastering of knowledge based on modern methods of electronic education and intellectual technologies. Personalization of the approach to learning allows you to repeat the insufficiently mastered sections of the material. Distance learning methods will allow setting and solving tasks of continuous improvement of professional skill of medical workers on a fundamentally new level. In principle, the use of many of these approaches is possible in other areas of education.

Is Indian Computing academics units are interested in the areas of IT? A Case of Cloud Computing & Virtualization

Computing is one of the emerging and rapidly changing fields. The field is responsible for the development of diverse areas. Initially within Computing, Computer Science was core and main subject and gradually many other subjects have been originated viz. Computer Engineering, Computing, Computer Applications, Information Technology, Information Systems, Informatics, Information Management etc. Though there is a difference in between Computing related fields and Information related fields. Computer Science is theoretical in nature and mainly deals with the mathematical affairs for the study, evaluation, design and development of computer systems. Though Computer Engineering is mainly focuses on design and development and partially software systems. As far as Computer Application is concerned it is purely concentrated on software technologies. Information Technology whereas concentrated on the information related affairs and allied technologies viz. Networking Technologies, Database Technologies, Communication Technology, Multimedia Technology, Web Technology etc. In India, common academic programs of Computing and IT mainly concentrated on the nomenclature Computer Science, Computer Application, and Information Technology. Among the emerging subjects, few important are Big Data Technologies, Cloud Computing etc. and these are rising as an academic program as well in different universities internationally. Though the areas of Information Technology in Indian academics have several disparities compared to international universities. However, in recent past Indian academics, mainly private bodies are moving towards some of the applied areas of IT within the department, programs of Computing. This paper deals with the basics of computing and IT related subjects especially the trend of applied computing emphasizing cloud computing in Indian private universities.

EVOLUTION OF HIGH-FREQUENCY TRADE

Present day exchange trade using computer algorithm (or high frequency robots) that can make independent trade decisions and function without man’s involvement is becoming quite usual. Intensive technological upgrading of finance markets fostered the development of high-frequency trade, thus ways of conducting trade transactions were transformed. In line with technology development the speed of transactions being carried out by high-frequency robots increased considerably during the last two decades. The majority of research dealing with assessment of highfrequency trade impact mention the wide spread of the latter and, consequently the growth in its market share, especially on stock exchanges. At the same time the drawback of various research is the limited analysis of reasons for high-frequency trade popularity and preconditions of its evolution. Apart from this many researchers neglected the fact that the development of high-frequency trade was promoted not only by technological evolution of computer systems but by legislative regulation, first of all in the USA. High-frequency trade was initially developed on US stock exchange and even today it is actually the only one news-maker in the field. The article reviews the key stages of exchange trade development, which foster establishment and evolution of high – frequency trade and shows legislative initiatives that caused its popularity. The authors present arguments for and against highfrequency trade and analyze current legislative initiatives that disclose potential trend aimed at the development of the system regulating high-frequency robots’ functioning.

救急外来のデータを標準コード化し，業務の効率改善と簡便なデータ解析を両立した電子システムの開発とその評価(Development and evaluation of computer system that enables emergency department efficiency improvement and collection of coded data during normal clinical workflow)

要旨【目的】救急外来での情報技術（IT）導入による効果が期待されているが，現場業務との親和性が高くないと業務効率を低下させる恐れがある。救急外来での業務遂行を効率化しつつ，臨床研究および医療の質の向上のためのコード化医療データを蓄積可能なITシステムを開発導入し，その有用性につき評価した。【対象】Filemaker ProにてUIを整備し，カルテ記載支援や患者情報の一覧表示が可能で，かつ自動コード化技術により標準化されたデータが蓄積されるシステムを開発した。1か月間のシステム使用後に使用者を対象として質問紙調査を行った。【結果】システム総合評価は10点中7.2点であり，初期研修医の評価がとくに高かった。業務の効率化に直接役立つ機能が評価され，具体的には「患者情報の共有や検索に役立つ｣｢情報収集時のチェックリストとして機能しつつカルテ作成時間の短縮につながる」という評価が得られた。音声入力やスマートフォンの活用が今後の期待として挙がった。【結語】本システムは業務効率化を実現し，広く現場に受け入れられた。結果として現在の電子カルテよりも標準化されたデータの蓄積，あらゆる検索軸での患者データ検索，既往歴などの時系列情報の引き継ぎなどが可能になった。救急医療現場で役立つITシステム開発には臨床・研究・開発の3者の視点を融合したシステム開発マネジメントが必須である。

Supervised machine learning scheme for electromyography-based pre-fall detection system

Falls are the leading cause of disability and death among the elderly. Over the years, several inertial-based wearable devices for automatic fall and pre-fall detection have been devised. Under controlled condition, these systems show a high performance for unbalance detection (up to 100% of specificity and sensitivity), however the mean lead time before the impact is about 200–400 ms. Although this period of time is enough to active an impact reduction system (i.e wearable airbag) to minimize injury, it is necessary to increase it so as to improve the system efficiency and reliability. A user's muscle behavior analysis could be more strategic than that of a kinematic evaluation one, permitting a rapid recognition of an imbalance event. This also holds true for several research studies on muscles response during a state of imbalance, whereas a limit number of them deal with the development of wearable electromyography (EMG)-based systems for human imbalance detection, suitable for predicting a lack of balance in real time. With respects these limitations, the main purpose of this work has been the development of a low computational cost expert system for real time and automatic fall risk detection. The analysis of this is achieved through lower limb muscles behavior monitoring. A Machine Learning scheme has been chosen in order to overcome the well-known drawbacks of threshold approaches widely used in pre-fall systems, in which the algorithm parameters have to be set according to the users’ specific physical characteristics. Ten kinds of time-domain features, commonly used in the analysis of the lower-limb muscle activity, have been investigated. With a view to reducing the processing complexity, the Markov Random Field (MRF) based Fisher-Markov feature selector was tested. It showed a high degree of accuracy in the EMG-based features selection for lack of balance detection. The Co-Contraction Index, Integrated EMG and Willison Amplitude features have been also considered. The supervised classification phase has been obtained through a low computational cost and a high classification accuracy level Linear Discriminant Analysis. The developed system shows high performance in terms of sensitivity and specificity (about 90%) in controlled conditions, with a mean lead-time before the impact of about 775 ms. Therefore, the feasibility of a quick and wearable surface EMG-based unbalance detection system, by using Machine Learning methodology, has been demonstrated. The system may recognize a fall event during the initial phase, increasing the decision making time and minimizing the incorrect and inappropriate activations of the protection system, in real life scenario.

Twenty-Two Columns of Lowbrow Revolution The Commodore VIC-20 and the Beginning of the Home Computer Era

This article examines the development of the VIC-20 computer system as producedby the American computer company Commodore International during the early 1980s.This analysis demonstrates that thanks to the requirements of the American computermarket in the early 1980s, those responsible for its development acted more like a teamof collaborative artists rather than a true, by-the-book engineering team. This allowedthem to develop the first computer that sold over one million units and created the homecomputing market. This analysis also demonstrates that this form of development nolonger has a place in today’s computer development world.

Artificial Intelligence & Robotics – Synthetic Brain in Action

Artificial intelligence is a theory. It is the development of computer systems that are able to perform tasks that would require human intelligence. Examples of these tasks are visual perception, speech recognition, decision-making, and translation between languages. The base object in this reference is the agent who is the actor” taking birth in the software and culminating itself in the hardware body. The connection between those two is that the control of the robot is a software agent that reads data from the sensors decides what to do next and then directs the effectors to act in the physical world. The aim of this paper is to provide basic, background information on two emerging technologies: artificial intelligence (AI) and robotics and their scope in India. Thus, a first major feature of these two disciplines is product diversity. In addition, it is possible to characterize them as disruptive, enabling and interdisciplinary.

Pedagogical Agility, and Agile Methodologies, in Computer System Development Education

Two propositions are stated regarding 'agility' in the education process. First, what is known as agile software development should be given primacy in college and university courses in computer systems development. The second proposition is that concepts of 'organisational agility' should be adopted under the heading of agile education, to better reflect the continuous, dynamic and revolutionary and disruptive changes in the computer industry which have had widespread implications in world economies and many industries. Curriculum decision making, teaching and learning practices, and outcomes assessment approaches in colleges and universities have not kept pace, and the concept of agile education is proposed as the solution.

Pedagogical agility and agile methodologies in computer system development education

Two propositions are stated regarding 'agility' in the education process. First, what is known as agile software development should be given primacy in college and university courses in computer systems development. The second proposition is that concepts of 'organisational agility' should be adopted under the heading of agile education, to better reflect the continuous, dynamic and revolutionary and disruptive changes in the computer industry which have had widespread implications in world economies and many industries. Curriculum decision making, teaching and learning practices, and outcomes assessment approaches in colleges and universities have not kept pace, and the concept of agile education is proposed as the solution.

Color Transfer Pulse-Coupled Neural Networks for Underwater Robotic Visual Systems

With rapid developments in cloud computing, artificial intelligence, and robotic systems, ever more complex tasks, such as space and ocean exploration, are being implemented by intelligent robots. Here, we propose an underwater image enhancement scheme for robotic visual systems. The proposed algorithm and its implementation enhances and outputs an image captured by an underwater robot in real time. In this scheme, pulse-coupled neural network (PCNN)-based image enhancement and color transfer algorithms are combined to enhance the underwater image. To avoid color imbalance in the underwater image and enhance details while suppressing noise, color correction is first carried out on the underwater image before converting it into the hue–saturation–intensity domain and enhancing it by PCNN. The enhanced result improves the color and contrast of the source image and enhances the details and edges of darker regions. Experiments are performed on real world data to demonstrate the effectiveness of the proposed scheme.

Potent pairing: ensemble of long short-term memory networks and support vector machine for chemical-protein relation extraction.

Biomedical researchers regularly discover new interactions between chemical compounds/drugs and genes/proteins, and report them in research literature. Having knowledge about these interactions is crucially important in many research areas such as precision medicine and drug discovery. The BioCreative VI Task 5 (CHEMPROT) challenge promotes the development and evaluation of computer systems that can automatically recognize and extract statements of such interactions from biomedical literature. We participated in this challenge with a Support Vector Machine (SVM) system and a deep learning-based system (ST-ANN), and achieved an F-score of 60.99 for the task. After the shared task, we have significantly improved the performance of the ST-ANN system. Additionally, we have developed a new deep learning-based system (I-ANN) that considerably outperforms the ST-ANN system. Both ST-ANN and I-ANN systems are centered around training an ensemble of artificial neural networks and utilizing different bidirectional Long Short-Term Memory (LSTM) chains for representing the shortest dependency path and/or the full sentence. By combining the predictions of the SVM and the I-ANN systems, we achieved an F-score of 63.10 for the task, improving our previous F-score by 2.11 percentage points. Our systems are fully open-source and publicly available. We highlight that the systems we present in this study are not applicable only to the BioCreative VI Task 5, but can be effortlessly re-trained to extract any types of relations of interest, with no modifications of the source code required, if a manually annotated corpus is provided as training data in a specific file format.

Real-time computational photon-counting LiDAR

The availability of compact, low-cost, and high-speed MEMS-based spatial light modulators has generated widespread interest in alternative sampling strategies for imaging systems utilizing single-pixel detectors. The development of compressed sensing schemes for real-time computational imaging may have promising commercial applications for high-performance detectors, where the availability of focal plane arrays is expensive or otherwise limited. We discuss the research and development of a prototype light detection and ranging (LiDAR) system via direct time of flight, which utilizes a single high-sensitivity photon-counting detector and fast-timing electronics to recover millimeter accuracy three-dimensional images in real time. The development of low-cost real time computational LiDAR systems could have importance for applications in security, defense, and autonomous vehicles.

Comparative Analysis of Frequency Scaling Algorithms for Signal Processing in Small-Size Mobile Platforms

Introduction. With the development of hardware and computer systems, which improve qualitative characteristics of synthetic aperture radars, with their dimensions limited, many new systems have appeared that allow using more accessible and widespread mobile platforms such as a car, quadcopters, unmanned aerial vehicles (UAV). Problem. The use of new types of platforms leads to additional distortions associated with features of the geometry of the radar performance and more severe trajectory instabilities. Thus, new synthetic aperture radar systems should have special requirements for both software and hardware, which differ from classical systems. Objective. The aim of the work is the comparison various algorithms that are used in modern radiovision systems to obtain high-quality radar images that can be integrated into various kinds of mobile platforms. Methods. The method of frequency scaling and various modifications of this method are taken as a basic algorithm, including additional algorithms for compensating trajectory instabilities. For comparison of algorithms, the system geometry for automobiles and aircraft systems are considered and simulations were performed with the presence of point reflectors at different distances and the distortion of the platform motion. Results. The difference of the considered algorithms in the form of flowcharts and mathematical formulas is shown. Based on results of the simulation the use of the basic frequency scaling algorithm at distances corresponding to the geometry of the automobile system leads to the distortion of the response along the azimuth. In addition, the use of the modified algorithm for compensating trajectory distortion allows correct focusing the targets at different distances. Conclusion. The proposed combination of modified algorithms of trajectory distortion and frequency scaling allows focusing the image evenly throughout the frame and improving the quality of the image in the near zone.