• The KIPS Transactions:PartC
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• v.9C no.6
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• pp.945-952
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• 2002

For a successful inter-system handoff, several important issues must be handled and additional new features must be considered. This paper focuses on the cellular structure of small cells which are required for the high density of population and a handoff scheme designed between two heterogenous networks. Incase of inter-system handoff (ISHO), the time required to complete the handoff can vary and depends on the structure of networks. And also the transmission of additional signals can increase the probability of failure for ISHO. Here we propose the sub-boundary cell base station (Sub-BBS) to alleviate the role of the BBS. The Sub-BBS is adjacent to BBS in the same regional mobile network. 쪼en the mobile terminal enters Sub-BBS, the network starts finding a new route and after entering BBS, it initiates the transformation process. The proposed scheme significantly reduces the ISHO failure rate compared to the existing one which is the most recent and known as efficient.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.167-172
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• 2005

A rapid growth in the number of Internet users and in massive media contents tends to cause server overload and high network traffic. As a consequence, it can be safely assumed that the quality of service is on the brink of deterioration. A solution of this problem is the development of the Content Distribution Network. Therefore, in this paper, we propose a transmission model using CDN. This model uses regional media server which closes to client, and uses MDC coding and multi-channel to reduce packet loss and delay. In conclusion, this study improved performance of multimedia service by reducing packet loss and delay.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.4
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• pp.395-403
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• 2014

Recent technological advancement has a profound effect on the ways that the war is being conducted and fought. The advanced communications, information, computing and sensor technologies enable the combat units to be integrated in the battlefield management network. By exchanging and sharing real-time battlefield information that is critical for the successful outcome of military engagement, the legacy forces are becoming much more effective and lethal than ever before, The bigger picture of such phenomena can be summarized as the concept of Network Centric Warfare(NCW). The main purpose of this study is to compare the outcome of regional combat engagement between the legacy forces and the future combat systems(FCS). The FCS capitalizes on the advanced technologies within the frame of NCW. This study uses the modeling and simulation methodology to assess the effectiveness of two different combat forces. The simulation results show that the FCS is more effective, hence vindicating the superiority of technologically advanced combat units.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.153-158
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• 2016

As the number of social network users increases, the information on event such as social issues and disasters receiving attention in each region is promptly posted by the bucket through social media site in real time, and its social ripple effect becomes huge. This study proposes a detection method of events that draw attention from users in specific region at specific time by using twitter data with regional information. In order to collect Twitter data, we use Twitter Streaming API. After collecting data, We implemented event detection system by analyze the frequency of a keyword which contained in a twit in a particular time and clustering the keywords that describes same event by exploiting keywords' co-occurrence graph. Finally, we evaluates the validity of our method through experiments.

• Asian Journal of Innovation and Policy
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• v.10 no.2
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• pp.212-235
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• 2021

In spite of the increasing popularity of the Ricardian model for the study of the impact of climate change on agriculture, there has been few attempts to examine the role of interregional spillovers in this framework and all of them rely on geographical proximity-based weighting schemes. We remedy to this gap by focusing on the spatial externalities of surface water flow used for irrigation purposes and demonstrate that farmland value, the usual dependent variable used in the Ricardian framework, is a function of the climate variables experienced locally and in the upstream locations. This novel approach is tested empirically on a spatial panel model estimated across the counties of the Southwest USA over 1997-2012. This region is one of the driest in the country, hence its agriculture relies heavily on irrigated surface water. The results highlight how the weather conditions in upstream counties significantly affect downstream agriculture, thus the actual impact of climate change on agriculture and subsequent adaptation policies cannot overlook the streamflow network anymore.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.212-222
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• 2021

Multiple waves of COVID-19 highlighted one crucial aspect of this pandemic worldwide that factors affecting the spread of COVID-19 infection are evolving based on various regional and local practices and events. The introduction of vaccines since early 2021 is expected to significantly control and reduce the cases. However, virus mutations and its new variant has challenged these expectations. Several countries, which contained the COVID-19 pandemic successfully in the first wave, failed to repeat the same in the second and third waves. This work focuses on COVID-19 pandemic control and management in Saudi Arabia. This work aims to predict new cases using deep learning using various important factors. The proposed method is called Deep Learning and Dynamic Weighing-based (DLDW) COVID-19 cases prediction method. Special consideration has been given to the evolving factors that are responsible for recent surges in the pandemic. For this purpose, two weights are assigned to data instance which are based on feature importance and dynamic weight-based time. Older data is given fewer weights and vice-versa. Feature selection identifies the factors affecting the rate of new cases evolved over the period. The DLDW method produced 80.39% prediction accuracy, 6.54%, 9.15%, and 7.19% higher than the three other classifiers, Deep learning (DL), Random Forest (RF), and Gradient Boosting Machine (GBM). Further in Saudi Arabia, our study implicitly concluded that lockdowns, vaccination, and self-aware restricted mobility of residents are effective tools in controlling and managing the COVID-19 pandemic.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.249-256
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• 2021

An issue of security and threat is urgent as well as it concerns everyone: a person, community, state, etc. Today, the question of cybersecurity has become especially relevant due to general digitalization and the spread of the cyberculture. In terms of it, the growing popularity of videogames can be observed. Their impact on society differs significantly, therefore, it needs thorough consideration. The purpose of the article is to disclose the role of videogames in cybersecurity. To achieve the stated purpose, such methods as analysis, synthesis, systematization and practical involvement of videogames have been used. As a result, three levels of possible threat of videogames has been distinguished: videogames as a possibly dangerous software, as a tool of propaganda and spread of stereotypes, as a space for the creation of virtual communities. In conclusion, it is stated that videogames can be not only a threat, but also a tool for strengthening the cybersecurity.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.276-280
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• 2021

The article presents the concept of ICT - competence, which is considered as the most important characteristic of professional competence, which includes a combination of the following components: motivational-value (orientation of the individual to the development of his ITC-competence in future professional activities); technological (complex of skills and abilities of ICT activities); cognitive (a system of knowledge of modern technologies of future professional activity); it is determined that the pedagogical support of the formation of ICT competence of future specialists is the individualization of the process training, due to their personal and professional needs and the specifics of a regional university, providing the necessary conditions for the implementation of this process.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.120-126
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• 2021

The article analyzes the possibility of using information and innovation experience in training public administration specialists, and also explores the system of training public administration and management specialists abroad. It was determined that in the European Union, Japan and other developed countries, three concepts of qualified personnel training will be developed: the concept of specialized training is focused on the present or near future and is relevant for the respective workplace; the concept of multidisciplinary training is effective from an economic point of view, as it increases intra-production and non-production mobility of an employee; the concept of learner-centered learning with the aim of developing human qualities.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.