• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.343-347
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• 2022

To date, the use of artificial intelligence has already brought certain results in such areas of art as poetry, painting, and music. The development of AI and its application in the creative process opens up new perspectives, expanding the capabilities of authors and attracting a new audience. The purpose of the article is to analyze the essential, artistic, and technological limitations of AI art. The article discusses the methods of attracting AI to artistic practices, carried out a comparative analysis of the methods of using AI in visual art and in the process of writing music, identified typical features in the creative interaction of the author of a work of art with AI. The basic principles of working with AI have been determined based on the analysis of ways of using AI in visual art and music. The importance of neurobiology mechanisms in the course of working with AI has been determined. The authors conclude that art remains an area in which AI still cannot replace humans, but AI contributes to the further formation of methods for modifying and rethinking the data obtained into innovative art projects.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.233-240
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• 2021

The majority of the Web's success can be related to its productivity and flexibility. Web Services (WSs) have the means to create new patterns for the delivery of software capabilities. The WS easily provides the use of existing components available via the Internet. WSs are a new trend that shares ubiquitous systems with others, so the popularity of the Web is increased day by day with their associated systems. This paper will explore and adopt the possibility of developing a technique that will automate instructors' scheduling of timetables within a Web services environment. This technique has an advantage that facilitates users to reduce the time cost and effort by reducing errors and costs for institutes. Providing dependable tables to avoid mistakes related to instituting schedules is ensured by an automated repetitive manual procedure. Automated systems are increasingly developed based on organizations and their customers. Still, the setting's difficulty of automation systems increases to rise as the system architecture and applications must accomplish various requirements and specifications of ever-demanding project scenarios. The automation system is composed of an operating system, platforms, devices, machines, control system, and information technology. This architecture provides more productivity and optimized services. The main purpose of this paper is to apply an automation system to enhance both quality and productivity. This paper also covers an agile method of proving an automation system by Finite State Machine (FSM) and Attributed Graph Grammar (AGG) tool.

• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.513-520
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• 2021

The purpose of the article is to study the impact of digitalization on the transformation of the banking system, taking into account current innovative development trends. The article analyzes the impact of key factors on the development of the digital economy. Ukraine's ranking positions in terms of digital competitiveness are shown. The necessity of using digital technologies in the sphere of banking activity is substantiated. The dynamics of changes in the number of operating banks in Ukraine is analyzed. The directions of introduction of information technologies in the sphere of banking activity are determined. An analysis of changes in the share of the population of individual EU member states that use the Internet for Internet banking. It is noted that modern transformation trends, digitalization of the economy have a significant impact on the landscape of the banking sector, in this context, the rating of Ukrainian banks in the categories of "Internet Banking" and "Mobile Banking". The advantages and disadvantages of using the capabilities of Internet banking are identified. Based on the study, the importance of expanding the boundaries of digitalization of the domestic banking system is substantiated, which will further increase the level of availability of online services in the field of banking. Prospects for further research are identified in the study of the impact of digitalization on the development of the banking system of foreign countries.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.193-203
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• 2022

After the everyday use of systems and applications of artificial intelligence in our world. Consequently, machine learning technologies have become characterized by exceptional capabilities and unique and distinguished performance in many areas. However, these applications and systems are vulnerable to adversaries who can be a reason to confer the wrong classification by introducing distorted samples. Precisely, it has been perceived that adversarial examples designed throughout the training and test phases can include industrious Ruin the performance of the machine learning. This paper provides a comprehensive review of the recent research on adversarial machine learning. It's also worth noting that the paper only examines recent techniques that were released between 2018 and 2021. The diverse systems models have been investigated and discussed regarding the type of attacks, and some possible security suggestions for these attacks to highlight the risks of adversarial machine learning.

• 웰빙융합연구
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• 제5권3호
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• pp.27-41
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• 2022

Purpose: In this study, pollutants generated in industrial areas were measured using a Portable Air Quality Measurement System(PAQMS). This study intends to examine in detail improvement measures and operational capabilities to operate a more efficient PAQMS. Research design, data and methodology: This study compares and analyzes the measurement values of the PAQMS and the measurement values of the national air quality measurement network. It is intended to develop a PAQMS corresponding to the data of the national measurement network by minimizing the errors that occur during comparative measurement and analysis and supplementing and improving the problems that occur during the current equipment calibration. Results: A PAQMS is an essential equipment for faster and more accurate measurement and analysis of pollutants in case of untimely measurement and civil complaints due to Micro Climate(local weather and environmental influences). Currently, there are many atmospheric measurement equipment in Korea, but only equipment for each item is produced and sold. Currently, these devices on the market must satisfy various conditions such as stable power, temperature, and humidity to calculate accurate measurement values. Conclusions: Therefore, there is no equipment that satisfies the conditions for performing detailed measurement in the field where accurate measurement is required. In this study, these field work conditions and contents for stable measurement were mentioned in the text.

• International journal of advanced smart convergence
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• 제11권2호
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• pp.7-12
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• 2022

Safety and security are the topmost priority in every environment. With the aid of Artificial Intelligence (AI), many objects are becoming more intelligent, conscious, and curious of their surroundings. The recent scientific breakthroughs in autonomous vehicular designs and development; powered by AI, network of sensors and the rapid increase of Internet of Things (IoTs) could be utilized in maintaining safety and security in our environments. AI based on deep learning architectures and models, such as Deep Neural Networks (DNNs), is being applied worldwide in the automotive design fields like computer vision, natural language processing, sensor fusion, object recognition and autonomous driving projects. These features are well known for their identification, detective and tracking abilities. With the embedment of sensors, cameras, GPS, RADAR, LIDAR, and on-board computers in many of these autonomous vehicles being developed, these vehicles can properly map their positions and proximity to everything around them. In this paper, we explored in detail several ways in which these enormous features embedded in these autonomous vehicles, such as the network of sensors fusion, computer vision and natural image processing, natural language processing, and activity aware capabilities of these automobiles, could be tapped and utilized in safeguarding our lives and environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4275-4291
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• 2021

With the unprecedented growth of textual information on the Internet, an efficient automatic summarization system has become an urgent need. Recently, the neural network models based on the encoder-decoder with an attention mechanism have demonstrated powerful capabilities in the sentence summarization task. However, for paragraphs or longer document summarization, these models fail to mine the core information in the input text, which leads to information loss and repetitions. In this paper, we propose an abstractive document summarization method by applying guidance signals of key sentences to the encoder based on the hierarchical encoder-decoder architecture, denoted as KI-HABS. Specifically, we first train an extractor to extract key sentences in the input document by the hierarchical bidirectional GRU. Then, we encode the key sentences to the key information representation in the sentence level. Finally, we adopt key information representation guided selective encoding strategies to filter source information, which establishes a connection between the key sentences and the document. We use the CNN/Daily Mail and Gigaword datasets to evaluate our model. The experimental results demonstrate that our method generates more informative and concise summaries, achieving better performance than the competitive models.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2020년도 추계학술대회
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• pp.237-240
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• 2020

The fine-tuned neural network (NN) model for a whole temporal portion in a video does not always yield the best quality (e.g., PSNR) performance over all regions of each frame in the temporal period. For certain regions (usually homogeneous regions) in a frame for super-resolution (SR), even a simple bicubic interpolation method may yield better PSNR performance than the fine-tuned NN model. When there are multiple NN models available at the receivers where each NN model is trained for a group of images having a specific category of image characteristics, the performance of Quality enhancement can be improved by selectively applying an appropriate NN model for each image region according to its image characteristic category to which the NN model was dedicatedly trained. In this case, it is necessary to signal which NN model is applied for each region. This is very advantageous for image restoration and quality enhancement (IRQE) applications at user terminals with limited computing capabilities.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.101-108
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• 2023

Decision Support Systems (DSS) is an Information Systems (IS) application that aids in decision-making processes for many business concepts and Customer Relationship Management (CRM) is one of them and it depends on the firm's tasks for developing and retaining customers while achieving their satisfaction and enhancing the sense of belongingness for their products and services. Profit maximization, the process of customer value, and building strategic values for the firm are the three empirical benefits of CRM that are achieved through analytical, operational, and direction (AOD) capabilities respectively. This research focuses on the application of DSS models of what-if analysis (WIA) for CRM at (AOD) and also shows the dependence on the Information Success model (ISM). Hypothetical data are analyzed for (AOD) by three types of (WIA) to attain CRM and profit maximization and this analytical method can be used by any customer-oriented firm as a general model and for the purpose of the study we have compared the CRM between patients and hospital management.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.49-56
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• 2023

Computer architecture serves as a link between application requirements and underlying technology capabilities such as technical, mathematical, medical, and business applications' computational and storage demands are constantly increasing. Machine learning these days grown and used in many fields and it performed better than traditional computing in applications that need to be implemented by using mathematical algorithms. A mathematical algorithm requires more extensive and quicker calculations, higher computer architecture specification, and takes longer execution time. Therefore, there is a need to improve the use of computer hardware such as CPU, memory, etc. optimization has a main role to reduce the execution time and improve the utilization of computer recourses. And for the importance of execution time in implementing machine learning supervised module linear regression, in this paper we focus on optimizing machine learning algorithms, for this purpose we write a (Diabetes prediction program) and applying on it a Practical Swarm Optimization (PSO) to reduce the execution time and improve the utilization of computer resources. Finally, a massive improvement in execution time were observed.