• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.199-206
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• 2021

Rhetorical relations between two text fragments are essential information and support natural language processing applications such as Question - Answering (QA) system and automatic text summarization to produce an effective outcome. Question - Answering (QA) system facilitates users to retrieve a meaningful response. There is a demand for rhetorical relation based datasets to develop such a system to interpret and respond to user requests. There are a limited number of datasets for developing an Arabic QA system. Thus, there is a lack of an effective QA system in the Arabic language. Recent research works reveal that unsupervised learning can support the QA system to reply to users queries. In this study, researchers intend to develop a rhetorical relation based dataset for implementing unsupervised learning applications. A web crawler is developed to crawl Arabic content from the web. A discourse-annotated corpus is generated using the rhetorical structural theory. A Naïve Bayes based QA system is developed to evaluate the performance of datasets. The outcome shows that the performance of the QA system is improved with proposed dataset and able to answer user queries with an appropriate response. In addition, the results on fine-grained and coarse-grained relations reveal that the dataset is highly reliable.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.110-122
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• 2023

Over the last few decades, various innovative technologies have emerged that have significantly contributed to making life easier for humans. Various information and communication technologies (ITCs) have emerged as a result of the global technological revolution, including big data, IoT, 4G and 5G networks, cloud computing, mobile computing, and artificial intelligence. These technologies have been adopted in urban planning and development, which gave rise to the concept of smart cities in the 1990s. A smart city is a type of city that uses ITCs to exchange and share information to enhance the quality of services for its citizens. With the global population increasing at unprecedented levels, cities are overwhelmed with a myriad of challenges, such as the energy crisis, environmental pollution, sanitation and sewage challenges, and water quality issues, and therefore, have become a convergence point of economic, social, and environmental risks. The concept of a smart city is a multidisciplinary, unified approach that has been adopted by governments and municipalities worldwide to overcome these challenges. Though challenging, this transformation is essential for cities with differing technological and social features, which all have the potential to determine the success or failure of the digital transformation of cities into smart cities. In recent years, researchers, businesses, and the government have all turned their attention to the emerging field of smart cities. Accordingly, this paper aims to represent a thorough understanding of the movement toward smart cities. The key themes identified are smart city definitions and concepts, smart city dimensions, and smart city architecture of different layers. Furthermore, this article discusses the challenges and some examples of smart cities.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.35-41
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• 2024

As online activities have rapidly increased due to recent digital changes and the impact of COVID-19, the importance of large-scale data processing and maintenance is increasing. This study compares the performance of the two main types of databases widely used for data storage and management: Relational Database Management Systems (RDBMS) and Non-Relational Databases (NoSQL). Specifically, we measured and evaluated the execution time of data insertion, query, and deletion functions using MySQL, a representative example of RDBMS, and Redis, a representative example of NoSQL. The experimental results showed that Redis showed performance about 5.84 times faster in data insertion, 6.61 times faster in query, and 12.33 times faster in deletion than MySQL. These results demonstrate that Redis provides superior performance, especially in environments requiring large-scale data processing and maintenance. Therefore, companies and online service providers can choose NoSQL databases such as Redis to ensure more efficient data management solutions. We hope this study will be an essential reference when selecting a database based on data processing performance.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.3
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• pp.57-63
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• 2011

The internet is currently becoming popularized and generalized in our daily life. Recently, a lot of hacking tools have appeared on the internet. And damage size and seriousness the measurement is impossible. The password security protects oneself and information is the tool which is essential for from the internet, if this emphasizes no matter how, does not go to extremes. If applies a encryption, a 7 character password is sufficient, so long as attackers don't pick easily guessed values. In this paper, entering password using the virtual keyboard, I propose a new and improved one time password algorithm using information a part of ID and final approval time.

• Korean Security Journal
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• no.31
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• pp.157-185
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• 2012

Today, the emergence of cyberspace and advancement of globalization caused not only the transformation of our productive and conventional life but also the revolutionary transition of use of destructive violence such as crime and warfare. This transition of environmental condition connects various security threats which separatedly existed in individual, local, national, and global levels in the past, and transformed the mechanical sum of all levels of security threats into the organic sum of multi-dimensional security threats. This article proposes that the sum of multi-dimensional security threats is caused by the interconnectivity of various different levels of security threats and the integrated interdisciplinary perspective is essential to properly understand the fundamental existence of today's security problem and the reality of fear that we face today. The holistic security, the concept proposed here, is to suggest the mode of networked response to multi-dimensional security threats. The holistic security is suggested to overcome the conventional divisional approach based on the principle of "division of labor" and bureaucratic principles, which means more concretely that national security and criminal justice are divided and intelligence, military, police, prosecution, fire-fighting, private security, and etc. are strictly separated into its own expertise and turf. Also, this article introduces integrated security approaches tried by international organization and major countries overseas with the respect of the holistic security. The author have spent some substantial experience of participant observation, meetings, seminar, conference, and expert interviews regarding the issues discussed in the article in various countries including the United States, Russia, Austria, Germany, Canada, Mexico, Israel, and Uzbekistan for the last ten years. Intelligence and information on various levels of security threats and security approaches introduced in this paper is obtained from such opportunities.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.9-14
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• 2017

Recently, the Internet of Things are developing in accordance with the technology of implementation in low-cost, small-size, low power consumption and smart sensor that can communicate using the internet. Especially, key management researches for secure information transmission based on the Internet of Things (IoT) are actively performing. But, Internet of Things(IoT) are uses sensor. Therefore low-power consumption and small-memory are restrictive condition. As a result, managing the key is difficult as a general security measure. However, The problem of secure key management is an essential challenge For the continuous development of the Internet of things. In this paper, we propose a key distribution and management technique in secure Internet of things. In the key generation and management stage, it satisfies the conditions and without physically constrained for IoT based communication.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.483-496
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• 2018

Purpose: This paper proposes a quality strategy based on the evolution of technology in the age of the 4th Industrial Revolution. Methods: We examine the theory of past quality activities and the changes in quality paradigm, and analyze key words for the technologies and key issues of the 4th Industrial Revolution. Based on existing quality management, we find a quality strategy that should be pursued during the 4th Industrial Revolution. Results: Quality has been recognized as an essential component of corporate competitiveness. The paradigm of quality has also changed with the pass of time and industry development. From this viewpoint, the following eight quality strategies are proposed for the development of the technology of the 4th Industrial Revolution period, such as Market-to-customer fusion quality, symbiotic quality, big data quality, technical accuracy and zero-defect quality, facility predictability quality, software quality, process flexibility quality, and information protection stability and security quality. Conclusion: Quality for customer satisfaction is still important nowadays. However, in the 4th Industrial Revolution era, where various business models and methods of manufacturing are expected, the big data utilization, software quality, and the reliability and security of information protection to support it are important.

• Journal of KIISE:Information Networking
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• v.32 no.1
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• pp.1-11
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• 2005

Internet has become an essential part of our daily lives. Many of the day to day activities can already be carried out over Internet, and its convenience has greatly increased the number of Internet users. Hut as Internet gains its popularity, the illicit incidents over Internet has also proliferated. The intruder trace-back technology is the one that enables real time tracking the position of the hacker who attempts to invade the system through the various bypass routes. In this paper, the RTS algorithm which is the TCP connection trace-back system using the watermarking technology on Internet is proposed. Furthermore, the trace-bark elements are modeled by analyzing the Proposed trace-back algorithm, and the results of the simulation under the virtual topology network using ns-2, the network simulation tool are presented.