• International Journal of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.27-30
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• 2019

Factory monitoring systems are gaining importance in wide areas of industry. Especially, there have been many efforts in implementation of vibration measurement and analysis for monitoring the status of rotating machines. In this paper, a digital signal processor (DSP) based monitoring system dedicated to the vibration monitoring and analysis on rotating machines is discussed. Vibration signals are acquired and processed for the continuous monitoring of the machine status. Time domain signals and fast Fourier transform (FFT) are used for vibration analysis. All of the signal processing procedures are done in the DSP to reduce the production and maintenance cost. The developed system could also provide remote and mobile monitoring capabilities to operator via internet connection. This paper describes the overview of the functional blocks of the implemented system. Test results based on signals from small-size single phase motors are discussed for monitoring and defect diagnosis of the machine status.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.395-402
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• 2023

The implementation of a hybrid network utilizing Power Line Communication (PLC) and Wi-Fi technologies has been demonstrated to improve signal strength and coverage in areas with poor connectivity due to internet shadow areas. In this study we strategically positioned Wi-Fi relays and utilized the capabilities of PLC technology to significantly improve signal strength and coverage in areas with poor connectivity. We also analyzed the effects of metallic obstacles on Wi-Fi signal propagation and proposed a solution to strengthen the signal enough to pass through them. Our experiment demonstrated the feasibility and potential of using this hybrid network in industrial scenarios for real-time data transmission. Overall, the results suggest that the use of PLC and Wi-Fi hybrid networks can be a cost-effective and efficient solution for overcoming internet connectivity challenges and has the potential to provide high-speed internet access to areas with unreliable signals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5427-5445
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• 2019

While deep neural networks have achieved remarkable performance in representation learning, a huge amount of labeled training data are usually required by supervised deep models such as convolutional neural networks. In this paper, we propose a new representation learning method, namely generative adversarial networks (GAN) based bagging deep convolutional autoencoders (GAN-BDCAE), which can map data to diverse hierarchical representations in an unsupervised fashion. To boost the size of training data, to train deep model and to aggregate diverse learning machines are the three principal avenues towards increasing the capabilities of representation learning of neural networks. We focus on combining those three techniques. To this aim, we adopt GAN for realistic unlabeled sample generation and bagging deep convolutional autoencoders (BDCAE) for robust feature learning. The proposed method improves the discriminative ability of learned feature embedding for solving subsequent pattern recognition problems. We evaluate our approach on three standard benchmarks and demonstrate the superiority of the proposed method compared to traditional unsupervised learning methods.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1197-1206
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• 2003

This paper describes the IPP (Internet Printing Protocol), a standard that makes network setup for printers potentially much easier and, not so incidentally, also user can print over the Internet and specifies an implementation of IPP client/server system. It allows the system administrator and operators to control IPP system users and printer devices. The focus of this effort is optimized capabilities the security features for authentication, authorization, and policies, also improved compatibility with existing WP devices. Finally this paper presents conclusions and further researches.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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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 advanced smart convergence
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• v.13 no.4
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• pp.145-154
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• 2024

The advancement of generative AI technologies has significantly impacted various domains in software engineering, particularly in automating test case generation. As software systems become increasingly complex, manual test case creation faces limitations in terms of efficiency and coverage. This study analyzes the capabilities and limitations of major generative AI models-ChatGPT, Copilot, and Gemini-in generating software test cases. We focus on evaluating their performance in boundary value analysis, exception handling, and property-based testing. Using the ArrayUtils.indexOf() function from the Apache Commons Lang library as the test subject, we conducted experiments to compare the quality and effectiveness of the test cases generated by each model. Our findings indicate that while generative AI can efficiently produce a substantial number of high-quality test cases, there are instances of incorrect test cases and test codes. To address these issues, we propose guidelines for developers to enhance the reliability and consistency of test case generation using generative AI. Future research will explore the application of these models to more complex software systems and further methods to improve their test generation capabilities.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.59-66
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• 2017

Cloud computing has evolved into a core computing infrastructure for the internet that encompasses content, as well as communications, applications and commerce. By providing powerful computing and communications capabilities in the palm of the hand everywhere with a variety of smart devices, mobile applications such as virtual reality, sensing and navigation have emerged and radically changed the patterns people live. The data that is generated is getting bigger. Cloud computing, on the other hand, has problems with system load and speed due to the collection, processing and control of remote data. To solve this problem, fog computing has been proposed in which data is collected and processed at an edge. In this paper, we propose a system that dynamically selects a fog server that acts as a cloud in the edge. It serves as a mediator in the cloud, and provides information on the services and systems belonging to the cloud to the mobile device so that the mobile device can act as a fog. When the role of the fog system is complete, we provide it to the cloud to virtualize the fog. The heterogeneous problem of data of mobile nodes can be solved by using mDBaaS (Mobile DataBase as a Service) and we propose a system design method for this.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.277-288
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• 2002

A service broker supporting customers plays an important role in internet marketplaces. Recently. several intelligent brothers have been developed for electronic commerce, outline shopping mall, and electronic marketplaces. While these systems provide interesting shopping experiences, they fall short in fully exploiting the capabilities, such as the service integration and automatic execution required by internet market places. In this respect, we propose a workflow-based service broker system. Dependent services in our approach are modeled as workflow processes, which are automatical1y processed by a workflow engine. In the proposed system all data exchanges are realized through XML providing platform independent, extensible, open. and interoperable architecture.

• International Journal of Knowledge Content Development & Technology
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• v.11 no.1
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• pp.29-48
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• 2021

The paper discusses the ICT infrastructure as far as the availability of (computers, local or wide area networks, Internet connectivity and its reliability, size of the bandwidth and its optimization, etc.) in the S&T research institution. It also examined the profile of the research scientists and looked at the type of ICT infrastructure that is available for their use as well as the reliability of the Internet connectivity within these research institutions. It looked at the broadband capacities of the research institutions and the ICT capabilities in respect of the technical and managerial support back-up that are available to the research institutions. The study used the survey research method with a questionnaire as well as personal observation to gather the data. From the data gathered, it was realized that the internet connectivity and the size of the bandwidth that the R&D institutions subscribed to differed significantly. Again, the extent to which the research scientists were able to access the internet in their respective institutions depended on the quality of the local network in place. Generally, the investments in ICT were made for different management objectives, and these were meant to facilitate the generation of new knowledge as well as make measurable improvements in R&D activities.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.514-523
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• 2024

In the Internet of Medical Things, due to the sensitivity of medical information, data typically need to be retained locally. The training model of heart disease data can predict patients' physical health status effectively, thereby providing reliable disease information. It is crucial to make full use of multiple data sources in the Internet of Medical Things applications to improve model accuracy. As network communication speeds and computational capabilities continue to evolve, parties are storing data locally, and using privacy protection technology to exchange data in the communication process to construct models is receiving increasing attention. This shift toward secure and efficient data collaboration is expected to revolutionize computer modeling in the healthcare field by ensuring accuracy and privacy in the analysis of critical medical information. In this paper, we train and test a multiparty decision tree model for the Internet of Medical Things on a heart disease dataset to address the challenges associated with developing a practical and usable model while ensuring the protection of heart disease data. Experimental results demonstrate that the accuracy of our privacy protection method is as high as 93.24%, representing a difference of only 0.3% compared with a conventional plaintext algorithm.