Development Of Computing Applications Research Articles

From Pixels to Principles: A Decade of Progress and Landscape in Trustworthy Computer Vision

The rapid development of computer vision technologies and applications has brought forth a range of social and ethical challenges. Due to the unique characteristics of visual technology in terms of data modalities and application scenarios, computer vision poses specific ethical issues. However, the majority of existing literature either addresses artificial intelligence as a whole or pays particular attention to natural language processing, leaving a gap in specialized research on ethical issues and systematic solutions in the field of computer vision. This paper utilizes bibliometrics and text-mining techniques to quantitatively analyze papers from prominent academic conferences in computer vision over the past decade. It first reveals the developing trends and specific distribution of attention regarding trustworthy aspects in the computer vision field, as well as the inherent connections between ethical dimensions and different stages of visual model development. A life-cycle framework regarding trustworthy computer vision is then presented by making the relevant trustworthy issues, the operation pipeline of AI models, and viable technical solutions interconnected, providing researchers and policymakers with references and guidance for achieving trustworthy CV. Finally, it discusses particular motivations for conducting trustworthy practices and underscores the consistency and ambivalence among various trustworthy principles and technical attributes.

Code Smell Detection and Software Refactoring Research: A Systematic Literature Review

Today we are experiencing rapid enhancements in software systems and their development. The software industry's demand for tools and techniques for software development, especially automatic and less time-consuming, is increasing daily. Software refactoring and code smell detection are now expanded from code-level changes to the architecture, model, and requirements restructuring. We are moving from an object-oriented paradigm towards cloud computing, web development and mobile application development and so much more. Therefore, code smell and refactoring techniques are talk of the town in various research communities in their objectives. In this paper we will study the existing tools and techniques, research progress by doing a systematic literature review in the field of code smell detection and software refactoring’s. We will also classify the existing research techniques, identify the trends in code smell detection and refactoring and try to highlight the gaps in the area for researchers.

The design methods meshwork: Activating the Design Methods Group Newsletter through digital history

This article elaborates a computationally enabled approach to the study of design methods in 1960s North America. This entails the construction, visualization, and analysis of a digital database built from entries of the Design Methods Group Newsletter, a periodical published monthly between 1966-71. The article proposes a workflow that combines methods such as topic modeling and network visualization to activate the Newsletter as a source of anecdotal and informal knowledge, and to enable histories of connectivity and transaction that may elude archival investigations on singular actors or institutions. In doing so, the article contributes arguments and techniques for the study of design methods as a complex social, technical, and intellectual meshwork. The meshwork brings discursive themes, techniques, actors, and institutions at the same level of investigation and allows for layered cartographies of the field that advanced the systematic study of design and ushered in the development of early computer applications.

A Comprehensive Review on Enhancing Daily Life through various Computer Applications and softwares (Computer Applucations)

In this research paper comprehensive review of computer applications and their impact on daily lifestyles. It is increasing integrating of technology into various aspects and of our lives has led to the development of numerous computer applications and software’s that facilitate productivity, entertainment, social networking, and overall well-being. In this research I will explore the diverse range of computer applications and its software used in day to day life, analyzing the benefits, challenges, and future prospects of users.

THE USE OF PARALLEL CORPORA IN TEACHING LANGUAGES AND TRANSLATION PRACTICE

Nowadays the methodology of teaching foreign languages and translation practice involves using and development of modern computer applications called parallel corpora of texts of various genres. Such developments haven‘t been developed in Kazakhstan yet, though parallel texts or so-called bitexts were used for comparative analysis in applied linguistics long before.In teaching translation practice, parallel corpora can be applied for getting referential information, for getting samples of translation made by professionals. They can be used for studying the techniques and methods of translation. In teaching a foreign language, parallel corpora can be applied to choose the most appropriate equivalents of the studied vocabulary, trace its meaning in authentic contexts.The paper considers a number of methodological techniques when using corpora, methods for their construction, types of corpora, as well as the use of special programs for parallel texts. Currently, machine translation itself is based on parallel texts. In the future, a parallel corpus with fully aligned and marked translation units will bring translation studies in the Kazakh language to a new level. Such a corpus can act as a translation memory for the creation of professional machine translation applications, including a simultaneous interpreter program for a conference, an application for translating the spoken text into written text in another language.

РАЗРАБОТКА ОБРАЗОВАТЕЛЬНОГО ПРИЛОЖЕНИЯ, МОДЕЛИРУЮЩЕГО ПРОЦЕССЫ ПРОМЫШЛЕННОГО ПРОИЗВОДСТВА В ИГРОВОМ ДВИГАТЕЛЕ UNITY 3D PERSONAL

Relevance Over time, people's thinking begins to change. They perceive information differently, analyze it differently. As a result, they may have an incorrect or even rare manifestation of the process of any appearance or appearance. Today, written sources, various illustrations, and sometimes video materials are used for use. However, learning means not only the accumulation of knowledge, but also their awareness, embedding them in the mass of the student's already existing experience. If this happens, the requested book will not always be sufficient. When it comes to the fact that a person should not just learn something new, but master, comprehend and apply knowledge in practice, then it is impossible to use it without working out the study of the material on experience. Education based on computer games provides excellent opportunities for learning. Of course, in real life it is possible to simulate this or that situation in the field of application, but this is far from simple and requires quite a lot of time and material costs. In addition, simulating a whole system of situations or even a whole virtual world is a task just for computer games. The development of the educational process in educational institutions requires expectations, and at present there is the possibility of using computer-based learning systems. Training requires the development of high-tech computer applications using modern real-life technologies. As a result, high production processes and an increased understanding of high work skills have been achieved. For the user chose which control. Applications must correctly display the progress of the technological process, its parameters, as well as information in texts or audio format about the process and its elements. Aim of research Development of an educational application in the genre of a simulator that simulates the structure and operation of a neutralization and wastewater treatment plant at manufacturing enterprises in the UNITY 3D PERSONAL development environment. Research methods UNITY 3D PEROSNAL programming environment. Results This article presents the development of an application designed to implement the functions of teaching students and schoolchildren on the basis of Institute of Chemical Technology and Engineering, Ufa State Petroleum Technological University, working out safety precautions by employees of manufacturing enterprises.

The MARRTA Project: Safety and Risk Analysis in Radiation Oncology

<h3>Purpose/Objective(s)</h3> To improve the patient safety and quality in the radiotherapy treatment, by applying the risk matrix methodology to the process. to obtain a theoretical risk model with the potential errors and failures of that process, and to develop a computer application to introduce the model and offer the possibility of applying this methodology in an exhaustive and as simple as possible way to different professionals involved in the treatment <h3>Materials/Methods</h3> 23 working group meetings at the headquarters of the Spanish Nuclear Safety Council in Madrid, in which the results of the different proposals previously discussed and agreed by the different professional societies involved in the process representatives (Radiation Oncologists, Medical Physicists/Dosimetrists and Radiologic Technologists), were integrated. We analyzed IMRT, IGRT and SBRT techniques performed with LINAC. Radiosurgery, brachytherapy, metabolic treatments with non-encapsulated sources. <h3>Results</h3> Development of a Process Map: The different professional's tasks were analyzed. The process was divided into 7 phases (Therapeutic decision, Volume localization, Volume delineation, Treatment planning, Post-planning verification, Initial treatment session and Daily treatment), and the process map was prepared. Possible errors and failures (Initiating Events) identification: Once the analysis was done, the possible Initiating Events (IE) with consequences for the patients were identified, analyzed and consensed in the working group meetings. A total of 138 initiating events identified, analyzed and consensed are presented, separated in the different stages of the process, in Table 1. Identification of possible Barriers and Reducers of Frequency and Consequences: 125 barriers, 60 frequency reducers and 35 consequence reducers were identified. Computer application development: The MARRTA computer application was developed presenting the risk model resulting that includes: list of stages and sub-stages, flow chart, list of IE with their associated barriers and frequency and consequence reducers, and the risk of each of these IE. One can create new risk models by modifying the existing ones (indicating in the model to modify what applies and what does not to his department) or he can create a new one from scratch. It allows: Calculation of the risk of each one of the IE, statistics of the number of IE of very high risk, high, medium and low risk at each stage/sub-stage and analysis of the importance of the barriers and frequency and consequence reducers. <h3>Conclusion</h3> the MARRTA computer application provides radiotherapy departments with a tool to easily apply the risk matrix methodology to perform risk analysis in an exhaustive and easy way, and to modify the model to adapt to its particular map of processes and risks.

Knowledge domain and emerging trends in brachytherapy: A scientometric analysis

AbstractObjectiveAssessing the current scientific situation helps to recognize the gaps and strengths of brachytherapy research projects. This research project was conducted to assess the knowledge domain and emerging trends in brachytherapy through a scientometric perspective.MethodsFor the present research, the Web of Science database was considered as the data source. Integrated data was transferred to Bibliometrix R Package V3.1. In this study, the scientometric approach was performed by CiteSpace 5.8.R3 to draw the trends and signify issues in the research area. Eventually, scientometric indicators were evaluated at the level of authors, documents, journals, organizations, and countries.ResultsA total of 31,362 documents from 64,740 Independent researchers were retrieved. The United States, Germany, and Canada were the most active countries in brachytherapy‐related research projects. In the present study, Luc Beaulieu, Christine Kirisits, and Ronald Nath were identified as the most influential authors. Eventually, keywords clusters were constructed by using the method of co‐citation analysis. In this case, the main clusters were cervical cancer and prostate cancer.ConclusionAssessing the scientific trends in brachytherapy indicated that new insights have been gained into this cancer treatment technique. In this case, development of computer applications and artificial intelligence alongside deep learning utilization provides new horizons for oncology and radiotherapy researchers.

Realization of a sign-distinguishable higher-order optical differentiation

A differential operation, which can highlight features of images, is of significant importance in fields such as machine vision. As a front-end action, optical differentiation can overcome the shortcomings of traditional computer differentiation and runs at the speed of light. Compared with the conventional first-order optical differentiation technique, a higher-order one with the correct sign of a differential field obtained can facilitate the recognition of finer features, although relevant studies are relatively scarce. Here, we propose a method to realize sign-distinguishable arbitrary-order optical differentiation by coupling the momentum and polarization of a light field, the feasibility of which is further confirmed by a proof-of-principle experiment. We hope our method will promote the development of optical analog computing, image recognition, and other relevant applications.

A Discussion on the Practical Teaching Reform of Intelligent Mobile Terminal Technology Course

In this intelligent era, there is a high market demand for professional engineering talents in the computer industry. Based on engineering education accreditation, this paper briefly discusses the practical teaching reform of the intelligent mobile terminal technology course, which involves integrating theory with practical, taking students as the center, focusing on practical teaching, strengthening students’ practical skills and computer application development skills, as well as promoting the construction and development of engineering accreditation.

Operon

The past decade has witnessed the rapid development of cloud computing and data-centric applications. While these innovations offer numerous attractive features for data processing, they also bring in new issues about the loss of data ownership. Though some encrypted databases have emerged recently, they can not fully address these concerns for the data owner. In this paper, we propose an ownership-preserving database (OPDB), a new paradigm that characterizes different roles' responsibilities from nowadays applications and preserves data ownership throughout the entire application. We build Operon to follow the OPDB paradigm, which utilizes the trusted execution environment (TEE) and introduces a behavior control list (BCL). Different from access controls that merely handle accessibility permissions, BCL further makes data operation behaviors under control. Besides, we make Operon practical for real-world applications, by extending database capabilities towards flexibility, functionality and ease of use. Operon is the first database framework with which the data owner exclusively controls its data across different roles' subsystems. We have successfully integrated Operon with different TEEs, i.e. , Intel SGX and an FPGA-based implementation, and various database services on Alibaba Cloud, i.e. , PolarDB and RDS PostgreSQL. The evaluation shows that Operon achieves 71% - 97% of the performance of plaintext databases under the TPC-C benchmark while preserving the data ownership.

For Sustainable Career Development: Framework and Assessment of the Employability of Business English Graduates.

Employability is an important indicator of the competency of the employees. Employability model is a useful analytical framework for studying the ever-changing relationship between higher education and the job market. At present, the demand for business English graduates is increasing, however, there is a skill gap between their educational readiness and the recruitment requirements. In order to solve this problem, this study adopted mixed methods research and carried out the research design according to the exploratory sequence design to construct an employability model for business English graduates. A 46-item scale was developed to measure the employability of business English graduates’ employability. After assessment, it was found that the employability of business English graduates was multi-dimensional, with three dimensions—professional knowledge, generic competencies, and career management and 10 sub-dimensions—English language skills, foreign trade competencies, computer and internet application skills, social skills, learning and development, personal traits, thinking ability, work ethics, career identity and planning, and service awareness. This study verified that the employability of business English graduates reached the standard of talent training and met the requirements of employers. There were employability differences in gender, places of origin and educational institutions. From this study, it could be inferred that cultivation of business English majors should be multi-dimensional.

Drone usage for pavement damage identification

Abstract: The timely use of appropriate renovation measures can effectively extend the life of road surfaces. For this purpose, it is necessary to carry out a detailed identification of damage, and then on its basis to assess the condition of road surfaces. Due to the development of advanced measurement techniques and computer applications, damage to pavements can be monitored faster and more accurately. This article presents a method of identifying damage to the pavement of a large area of the square with the use of a drone. The applicated method allowed to visualize and differentiate various surface defects faster and more preciously. The method also enabled determine causes and genesis of damage more greatly. Keywords: Drone; Pavement damage; DJI SPARK, Damage Identification

Image compression using singular value decomposition by extracting red, green, and blue channel colors

This paper presents an image compression using singular value decomposition (SVD) by extracting the red, green, and blue (RGB) channel colors. Image compression is needed in the development of various multimedia computer services and applications for example in the telecommunications and storage technologies. Now a days, video technology, digital broadcast codec and teleconferencing become popular and always requires high image compression process for display. Hence, efficient image compression is compulsory to reduce the number of storage sizes and maintain the image quality. Therefore, this article proposes image compression using SVD, which this method is efficiently reducing the image storage size and at the same time maintaining the image quality. The SVD removes redundant pixel values based on RGB colors to make the storage image size decreased. Based on the experimental analysis on two different type of image extensions (i.e., jpg and png), the SVD is capable to reduce the image size and at the same time preserving the image quality.

Big data and artificial intelligence (AI) methodologies for computer-aided drug design (CADD).

There have been numerous advances in the development of computational and statistical methods and applications of big data and artificial intelligence (AI) techniques for computer-aided drug design (CADD). Drug design is a costly and laborious process considering the biological complexity of diseases. To effectively and efficiently design and develop a new drug, CADD can be used to apply cutting-edge techniques to various limitations in the drug design field. Data pre-processing approaches, which clean the raw data for consistent and reproducible applications of big data and AI methods are introduced. We include the current status of the applicability of big data and AI methods to drug design areas such as the identification of binding sites in target proteins, structure-based virtual screening (SBVS), and absorption, distribution, metabolism, excretion and toxicity (ADMET) property prediction. Data pre-processing and applications of big data and AI methods enable the accurate and comprehensive analysis of massive biomedical data and the development of predictive models in the field of drug design. Understanding and analyzing biological, chemical, or pharmaceutical architectures of biomedical entities related to drug design will provide beneficial information in the biomedical big data era.

Improving Performance with SIMD Intrinsics

Computer application development has a long history. With the continuous development of hardware, both the software and the programming languages and frameworks that make application development possible have also changed. As we move forward in time, as more and more powerful computers become available, the level of programming languages has also risen to a higher level. Increasingly high-level APIs and languages have become available, pointers, memory allocations and releases have slowly disappeared from the area of the programming. However, with the transition to high-level languages, the optimization of programs or the possibility of it has been relegated to the background, because some efficiency-enhancing options are not available in high-level languages. This paper therefore delves deeper into the benefits of SSE/AVX based SIMD concurrency capabilities that are “forgotten” in everyday programming. The presented tests will show that there are reserves in the CPU that can be used to push certain performance limits further away.

A Survey of Performance Tuning Techniques and Tools for Parallel Applications

Automatic parallelization of sequential programs combined with auto-tuning is an alternative to manual parallelization. With wider research directions and the increased number of performance tuning tools that have been developed, it has become increasingly difficult to choose a particular tuning tool. This paper reviews the fundamentals of different performance optimization and tuning techniques. It also surveys several tuning frameworks and classifies them into different groups based on their criteria. Developing benchmarks for HPC and validating their accuracy are demanding tasks for computer architects, researchers, and application developers. In addition to providing a survey of performance-tuning tools, we also performed a detailed review of current benchmarks and discussed the requirements for future benchmarks. We performed a detailed comparison of these tuning tools based on other features such as speedup and infrastructure details. We believe that this study will be a very useful resource for parallel computing communities, especially for early-stage parallel computing and performance researchers to gain exposure to existing performance optimization options.

Correlation and regression models of tomato yield in response to plant growth by different bacterial inoculants and inoculation methods

AbstractThe focus of this research is to evaluate the performance of Bacillus, Pseudomonas, Azotobacter, and Azospirillum for their plant growth abilities in vitro and in vivo. The best performing bacterial isolates from preliminary screening (in vitro) were able to produce indole acetic acid (IAA) and gibberellic acid (GA3) of 0.25–22.63 and 5.9–31.8 μg ml–1, respectively, eight best isolates were further tested for their efficacy in promoting crop growth and yield of tomato (Lycopersicon esculentum Mill.) by different application methods namely seed coating, soil application, and seedling root dip method. The factorial data analysis provided evidence that the interaction of bacterial isolates and different inoculation procedures together generated better yield in the greenhouse pot experiment. The findings suggest that the inoculation of Azospirillum strain ASP25 by seedling root dip method produced greater yields. Correlation and regression models hypothesize that all the variables are positively correlated with yield at P &lt; .01 and growth variables like number of fruits per plant (r2 = .886), shoot length (r2 = .695), and root volume (r2 = .554) at P ≤ .0001 contribute to the yield parameter individually and by multiple regression model all the plant growth variables together increased fruit yield per plant by 89% (r2 = .899). These results demonstrate that a high yield is always linked to a healthy vegetative development. However, as technology in agriculture progresses, the proposed method points to the usage and development of computer applications to estimate crop output.

Proportional impact prediction model of animal waste fat-derived biodiesel by ANN and RSM technique for diesel engine

Instead of many experimental studies made for the suitability of biodiesel for use in diesel engine, it has become easier to determine by fewer experiments with the development of computer applications. In this research, it was aimed to determine the optimum ratio of animal waste fat biodiesel (AWFBD) and the corresponding engine responses by using artificial neural network (ANN) and response surface methodology (RSM). In addition, a comparison was made with test results to evaluate the performance of ANN and RSM. According to the regression results obtained from RSM, absolute fraction of variance (R2) values greater than 0.95 emerged for all answers. Correlation coefficient (R) values obtained from ANN were found to be higher than 0.97. The developed ANN model was able to predict engine responses with mean absolute percentage error (MAPE) in the range of 3.787–10.730%. MAPE values for RSM were obtained between 2.004 and 11.461%. Combined desirability factor obtained from RSM was found as 0.72288% and optimum engine parameters were found as 22% AWFBD ratio and 1350-Watt engine load. In addition, according to the verification test between the optimum results and the prediction results, it was concluded that there is a good agreement with a maximum error rate of 3.863%.

Mpi4py: Status Update After 12 Years of Development

MPI for Python (mpi4py) has evolved to become the most used Python binding for the message passing interface (MPI). We report on various improvements and features that mpi4py gradually accumulated over the past decade, including support up to the MPI-3.1 specification, support for CUDA-aware MPI implementations, and other utilities at the intersection of MPI-based parallel distributed computing and Python application development.