Development Of Computer Systems Research Articles

The Effect of the Dataset Size on the Accuracy of Software Defect Prediction Models: An Empirical Study

The ongoing development of computer systems requires massive software projects. Running the components of these huge projects for testing purposes might be a costly process; therefore, parameter estimation can be used instead. Software defect prediction models are crucial for software quality assurance. This study investigates the impact of dataset size and feature selection algorithms on software defect prediction models. We use two approaches to build software defect prediction models: a statistical approach and a machine learning approach with support vector machines (SVMs). The fault prediction model was built based on four datasets of different sizes. Additionally, four feature selection algorithms were used. We found that applying the SVM defect prediction model on datasets with a reduced number of measures as features may enhance the accuracy of the fault prediction model. Also, it directs the test effort to maintain the most influential set of metrics. We also found that the running time of the SVM fault prediction model is not consistent with dataset size. Therefore, having fewer metrics does not guarantee a shorter execution time. From the experiments, we found that dataset size has a direct influence on the SVM fault prediction model. However, reduced datasets performed the same or slightly lower than the original datasets.

Computing views, remodeling environments

This article traces the development and expansion of early computer systems for analyzing views at three state-owned agencies in the United States and Great Britain: the US Forest Service, the Central Electricity Generating Board of England and Wales, and the Greater London Authority. Following the technology over four decades, from 1968 to 2012, the article traces assumptions incorporated into initial programs and propagated through to the present. These programs were designed to address questions about visual environments and proximities by numerical calculations alone, without the need for field observations. Each historical episode provides unique insights into the role of abstraction and calculation in the production of landscapes and the built environment, and shows how computer-generated view data became an important currency in planning control, not primarily for aesthetic but for financial and political reasons.

Key provisions of digital land management theory and methods

The article discusses some of the new positions of theory and methods of digital land management (DLM). The goals and objectives of digitization of the land building industry in the country’s land management system (LMS) are highlighted. Significant reduction in financial costs and relatively rapid restoration of all the functions of land management are possible only through its automation, information and complete digitization. The work carried out in the field of DLM is aimed at improving and implementing an intelligent system of planning, land-building and optimization of both land of all categories and agricultural resources, use and protection of land in agricultural production at different levels of generalization. These are field, economy, municipality, subject of the Russian Federation, country, foreign territories, operating on the basis of digital, remote, geo-information technologies and computer-generated methods. Smart land management assumes the basic spatial basis of the implementation of digital transformation of the following priorities: smart land use, smart field, smart farm, smart storage, smart greenhouse, smart garden, etc. Implementation of this concept is carried out in the form of the realization and introduction of the technological geo-information platform of DLM as the main mechanism for the implementation of agricultural policy of the state, rational use and protection of land resources and is key in relation to the sectors of the economy, which have a spatial link. The issues discussed in the article are directly related to the creation of essentially a new content of land management which corresponds to the zeitgeist. And the non-formation basis is the data derived from traditional ways of obtaining information, new technologies among them: unmanned aerial vehicles, laser scanning high-resolution satellite imagery, development of computer systems, network solutions based on cloud storage information, big data “Big Data” and block-chain “Blockchain”, etc. This modernization and rearmament of the industry should be accompanied by adjustments about the new provisions of the theory and methods of land management, its goals and objectives, the emergence of new concepts and terms and their interpretations.

Research and development of a quantum computing system as an information process.

Over the past few decades, there has been a significant breakthrough in the field of quantum computing. Research is attracting growing interest, which has recently led to the development of quantum information systems prototypes and methods for their development. The paper describes the characteristics of the information system as an object of architecture and the representation of quantum gates using quantum circuits. A functional-component structure of a quantum information system has been built and a software implementation of a quantum information system has been made on its basis.

Predictive Analysis about Traffic, Vehicles, and Road Congested Area: A Systematic Survey

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Social Dimensions in CPS & IoT Based Automated Production Systems

Since the 1970s, the application of microprocessor in industrial machinery and the development of computer systems have transformed the manufacturing landscape. The rapid integration and automation of production systems have outpaced the development of suitable human design criteria, creating a deepening gap between humans and systems in which human was seen as an important source of errors and disruptions. Today, the situation seems different: the scientific and public debate about the concept of Industry 4.0 has raised awareness about the central role humans have to play in manufacturing systems, the design of which must be considered from the very beginning. The future of industrial systems, as represented by Industry 4.0, will rely on the convergence of several research fields such as Intelligent Manufacturing Systems (IMS), Cyber-Physical Systems (CPS), Internet of Things (IoT), but also socio-technical fields such as social approaches within technical systems. This article deals with different human social dimensions associated with CPS and IoT and focuses on their conceptual evolution regarding automated production systems’ sociability, notably by bringing humans back in the loop. Hereby, this paper aims to take stock of current research trends to show the importance of integrating human operators as a part of a socio-technical system based autonomous and intelligent products or resources. Consequently, different models of sociability as a way to integrate humans in the broad sense and/or the develop future automated production systems have been identified from the literature and analysed.

Neutrosophic Statistics for Project Management. Application to a Computer System Project

This research aims to apply a mathematical procedure of the project evaluation and review technique (PERT) in a neutrosophic environment. For such purpose, the elements of the three PERT estimates are considered neutrosophic elements, more specifically, trapezoidal neutrosophic numbers. The technique used is novel and attractive since it allows to overcome the limitations of the different Fuzzy PERT methods and handle indeterminacy mathematically. On this occasion, the neutrosophic PERT method is applied to managing a computer system development project. The PERT method made it possible to estimate the minimum duration of the project, the beta parameters of the duration of each activity, and the identification and calculation of the critical path, with the help of specialized software.

Forensic Expertise in the Era of the Fourth Industrial Revolution (Industry 4.0)

The fourth industrial revolution basing on computer and information technologies, various software, hardware is rapidly gaining momentum in the modern world. First of all, these include big data processing technologies, blockchain, Internet of things, virtual and augmented reality, 3D printing, printed electronics, artificial intelligence, robotics, biotechnology. Alongside the positive effects, it is expected that the revolution will lead to some negative social consequences, including the growth of intellectual and high-tech crime. The article aims to analyze the causes and conditions of emerging new crime resulting from Industry 4.0 and their effect on the development of forensic science.The author highlights that the specific factors which will determine the future of forensic activity are: the appearance of creative and well-educated individuals, the emergence of “grey areas” in law, the development of global partnerships interested in international supranational rule-making, increasing of transnational crime. The rapid development of science and technology will require investigators and courts to promptly solve various specific scientific and technical tasks, eventually determining the objects and subjects of new forensic examinations, primarily from the field of information technology. Specialists predict a breakthrough in the development of cognitive computing and expert systems equipped with artificial intelligence, which has considerable potential in forensic science. There are signs of the shaping of a common forensic space, which will include not only existing elements of the institute of forensic examination (state and non-state institutions) but large industrial corporations, as well as the most active, technologically advanced individuals.

Intelligent and robust computational prediction model for DNA N4-methylcytosine sites via natural language processing

DNA N4-methylcytosine (4 ​mC) is an essential epigenetic modification and performs crucial roles in restriction-modification systems. The 4 ​mC involves many essential cellular processes, namely: correcting DNA replication and controlling DNA replication errors in the prokaryotic organism. In order to understand their biological functional mechanisms, the prediction of 4 ​mC modification is indispensable. Although computationally, it was targeted but the desired outcomes were not obtained. Thus, the development of an intelligent computational prediction system that truly expresses 4 ​mC modification sites is imperative. An efficient and high throughput discriminative intelligent computational system called “iDNA-4mC-DL” is introduced using the natural language processing method “word2vec” along with a convolution neural network. The obtained outcomes authenticated that the proposed iDNA-4mC-DL system performs outstandingly on six publicly available benchmark and independent datasets compared to current tools. It is, thus, highly estimated that the proposed model might be a more supportive and applied tool for rudimentary research and academia.

Incorporating Heuristic Evaluation (HE) in the Evaluation of Visual Design of the Eco-Tourism Smartphone App

Heuristic Evaluation (HE) has proven to be important in the development of different computer systems but has not been incorporated in the development of eco-tourism smartphone applications. This results inusability issues that significantly affect user experience (UX) as discussed in literature. This study reports the HE in the design and development of Niranur Agro Farm (NAF) eco-tourism smartphone applications, which could improve UX. Eight experts participated in this study, utilizing the SMART mobile usability heuristic developed for mobile application and the severity rating scale to determine usability issues. The HE findings indicated that 22 usability issues were identified. One issue was rated 4 (catastrophe), four issues were rated 3 (major problem), twelve issues were rated 2 (minor problem) and five issues were rated 1 (cosmetics). Although there are issues rated as 4 and 3, the majority of the issues were considered to be minor (1 and 2 on the scale). Results indicated that it is crucial to incorporate HE into the design and development of the eco-tourism smartphone app to minimize the usability issues faced by users. It further validated that utilizing a specific heuristic for smartphone applications would ensure that all usability issues are correctly categorized and remedied.

Experience of individual computer system developments in the field of vestibular science and suggestions of organizational supports for their wide distribution

Personal experience of computer system development in the field of vestibular science was reviewed, and suggestions are made for wide distribution of developed systems in the future.

The Shape of Story: A Semiotic Artistic Visualization of a Communal Storytelling Experience

Telling stories is a central part of human culture. The development of computational systems that can understand and respond to human language is an integral part of AI research in general and narrative technologies in particular. In this paper, we describe a system that is able to understand human spoken English sentences and portray that understanding via a semiotic visual language in real-time. We then employ this system in a communal storytelling environment as part of an interactive art installation and create a medium for collaborative creative expression.

Deep Learning in Image Analysis for COVID-19 Diagnosis: a Survey

COVID-19 achieved the highest concentration of confirmed cases in the Americas with a significant impact in Latin America and the Caribbean region, where access to water and sanitation is restricted. In this scenario, we surveyed deep learning techniques applied to extract information from images to detect pneumonia caused by SARS-COV-2, directly assisting health professionals through an automatic case screening. We identify the main public and private image datasets and deep network architectures. Thereby, we identified challenges and research directions. Thus, our goal is to provide a theoretical basis to contribute to the development of computational systems to aid the diagnosis of COVID-19.

Technologies for Supporting Creativity in Design: A View of Physical and Virtual Environments with Regard to Cognitive and Social Processes

Abstract Creative activities are becoming more and more necessary in professional areas, such as in design, towards the development of new products that should be adapted to current (or future) users and usages. In a competitive context, it is crucial, especially for companies, to face the challenge of coming up with innovative products. However, creative activities are particularly difficult to perform, and they are associated with important risks. In this context, we report on major findings based on the analysis of designers’ cognitive processes involved in creativity, which has led to the development of computational systems used in physical environments. We also present studies related to technologies that are used in virtual spaces in order to support creativity. This last kind of technology seems to be more and more promising in the actual societal context, which requires remote working, all the more so during the current health crisis. More specifically, we discuss how virtual environments, particularly those from multiplayer games, not only redesign the way individuals work but can also contribute to enhancing creativity. Finally, we suggest perspectives towards the development of innovative new tools that aim to enhance creative performance in individual and collective situations.

High Biofidelity 3D Biomodel Reconstruction from Soft and Hard Tissues (Knee), FEM, and 3D Printing: A Three-Dimensional Methodological Proposal.

The modelling of biological structures has allowed great advances in Engineering, Biology, and Medicine. In turn, these advances are seen from the design of footwear and sports accessories, to the design of prostheses, accessories and rehabilitation treatments. The reproduction of the various tissues has gone through an important evolution thanks to the development of computer systems and programs. However, knowledge of the medical-biological and engineering areas continues to be required, and it involves a considerable investment of time and resources. The resulting biomodels still require great precision. The present work shows a methodology that allows to optimize computational resources and reduce elaboration time of biomodels. Through this methodology, it is possible to generate a biomodel of high biofidelity of a human knee. This biomodel is constituted by hard tissues (cortical and trabecular bones) and soft tissues (ligaments and meniscus) resulting in the modelling of the lower third of the femur, the tibial plateaus, the anterior cruciate ligament, posterior cruciate ligament, external lateral ligament, interior lateral ligaments, and the meniscus. With this model and methodology, it is possible to perform numerical analyses that will provide results very similar to those of real life. As, the methodology allows to assign the mechanical properties to each tissue and the anatomical structure.

Can Machine Learning and AI Replace Otoscopy for Diagnosis of Otitis Media?

* Abbreviations: AI — : artificial intelligence AOM — : acute otitis media OCT — : optical coherence tomography OME — : otitis media with effusion TM — : tympanic membrane In this issue of Pediatrics , Crowson et al1 provide a glimpse to the future for otitis media (OM) diagnosis, perhaps. Data acquisition from 126 normal and 212 abnormal ear images met study quality criteria when children were brought to the operating room for an examination under anesthesia for tympanostomy tube placement for either recurrent acute otitis media (AOM) or otitis media with effusion (OME). To meet the quality criteria, 75% of the surface area of the tympanic membrane (TM) had to be visible and there had to be sufficient resolution to assess major landmarks. The otolaryngologist classified each ear at the time of myringotomy as effusion present or absent. If an effusion was present, the effusion was categorized as either serous, serous/mucoid, mucopurulent, or purulent. However, the deep learning model was used to target only a binary output of no effusion as normal or any effusion or any degree of TM pathology as abnormal. The model achieved a mean image classification accuracy of 83.8% (95% confidence interval: 82.7%–84.8%). In the hands of an experienced and trained clinician intent on making a correct diagnosis, … Address correspondence to Michael E. Pichichero, MD, Research Institute at Rochester General Hospital, 1425 Portland Ave, Rochester, NY 14621. E-mail: michael.pichichero{at}rochesterregional.org

A Computer System for Classification of Burns and Determination of Fluid and Nutritional Needs for Burn Patients

Background: The assessment and classification of burin severity and extent is very important for proper treatment. A computer system to assess burns seems to be crucial for the determination of fluid and nutritional requirements. The aim of the work: The objectives of this work are to design a computer system to assess and classify burns according to burn depth and extent and to implement the designed system for the assessment of fluid and nutritional needs using a database system for the automation of the entire process. Then test the computer system in reality through clinical application of the system on fifty patients with acute burn injury. Patients and Methods:This study was divided into two parts: Development of a burn management computer system [BMS]to facilitate the process of documentation, classification, and management of acute burn patients. The BMS contains three subsystems: Database, Classification, and Management subsystems. The second part was the clinical application of the system on fifty patients to test the efficacy, accuracy, and applicability of this system in comparison to the traditional method used at our unit. Results:Clinical application of the BMS has showed a reduction in the burn percentage calculation with 7.36%. It also decreased the amount of fluid calculated automatically by the system by about 7.28%, while the reduction in nutrition calculated automatically by the BMS was about 2.7%. Burn Management System has showed an overall shorter time in dealing with the cases. Conclusion: Clinical application of the BMS showed an accurate estimation of the burn percent, accurate and rapid calculation of resuscitation fluids and nutritional needs, and easy electronic documentation of patients’ data that required a minimal effort.

Research on Security Mechanism of Service Interoperability Based on Power Grid Computer System

With the gradual development of the power grid computer system, more and more intelligent power equipment is connected to the service system, and the security of service interoperability in the computer system is gradually concerned. This paper evaluates the security problems of power grid computer system, combines PKI system with OPC UA protocol, and uses data transmission technologies such as digital digest and symmetric encryption to ensure the security of data transmission.

Steganographic Methods Resistant to JPEG Compression

The active development of computer systems and information technologies implies an increase in the importance of ensuring the protection and security of information during its transfer or storage. Today, the fulfillment of the necessary data confidentiality requirements tends to the direction of cryptography and steganography. The choice of the applied method of encoding information directly depends on the goals of the user, as well as the available software. The main requirement for the message encoding process is the availability of acceptable computational complexity of the implementation.
 The article discusses methods of ensuring data confidentiality employing digital steganography, using BMP images as container files, and carrying out their subsequent compression to the JPEG format without losing hidden information. Mathematical methods of constructing a stegosystem for encoding ASCII are studied — a message, each character of which is encoded with exactly one byte. As a result, a computer program was created based on the Microsoft Visual Studio 2017 programming environment and the C# programming language (.NET Framework). The stereotype, in this case, is a sequence of steps between image pixels, into which information is embedded. In this case, the algorithm allows you to memorize not the entire sequence of steps (that is, not the entire keystroke), but only the first five characters of the key or half of the key.

DEVELOPMENT OF COMPUTER SYSTEM COMPONENTS IN CRITICAL APPLICATIONS: PROBLEMS, THEIR ORIGINS AND SOLUTIONS

The article is devoted to analysis of problems of the computer system development in the domain ofcritical applications. The main trends of this development were highlighted, which consisted in increased demands for performance based on parallelization of calculations, processing of approximate data and ensuring functional safety in accordance with the need for structuring for parallelism and fuzziness of the natural world, as well as with increased responsibility in decisions made. Analysis of problems encountered in implementation of existing solutions was carried out. There was a lag behind theorieslimited by the model of exact data from the practice of processing approximate data for modern systems receiving initial data from sensors, including safety-related systems. The problems of matrix structures, which underlie the design of modern computer systems and demonstrate low efficiency in performance and power consumption, as well as in providing functional safety, important for critical applications, are disclosed. The application of fault-tolerant solutions as the basis of functional safety and distrust of these solutions, which is manifested in the practice of using dangerous imitation modes, were noted. They recreate emergency conditions to improve the checkability in solving the problem of hidden faults, since a fault-tolerant solution does not become fail-safe when there is a shortage of checkability. An analysis was given to the sources of the problems considered and the possibilities of solving them from the point of view of a resource-based approach, which identifies the problem of hidden faults as a challenge of growth with a lag of components from the development of the system. The role of matrix structures in the backlog of components and the need to solve the problem by repeating the version redundancy for these structures are shown. Methodof introduction of version redundancy into matrix structure on the basis of strongly connected versions for solution of problems of fault tolerance and checkability in complex is proposed. The effectiveness of the method is estimated on an example of the iterative array multiplier using its software model.