• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of the Korean Institute of Landscape Architecture
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• v.34 no.4 s.117
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• pp.18-36
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• 2006

The purpose of this research was to establish a green-networks from the perfective of landscape ecology in order to improve the function of urban green spaces. The study site was Dalsu-Gu in Daegu City. This research consisted of three phases. In the first phase, field surveys were carried out in order to understand existing distribution pattern of green spaces in the study site. 533 green spaces surveyed in the first phase were classified into 7 patterns and 24 types. The total area of the green spaces in Dalsu-gu was 3,329ha. Specifically the area of the 'urban nature parks' type was 57.49% of the total area of green spaces in Dalsu-gu, and it was expected that 'urban nature parks' type can play important roles in the green-networks in Dalsu-gu. Two analysis with green spaces in 9 types including 'urban nature parks', 'rivers' and 'neighborhood parks' were performed to establish a basic network frame of the green-networks. In the second phase, 'mutual connectivity analysis' and 'mutual matrix analysis' were performed to select core green spaces of a green-networks using 'areas of each green space and a distance between each space' and 'a rate of green spaces and a rate of water permeable pavement'. The results of the second phase indicated that, in mutual connectivity analysis, large green spaces apart from each other were evaluated as having higher mutual connectivity than small green spaces near to each other. In mutual matrix analysis, the green spaces with higher mutual connectivity and the small green spaces near to each other were evaluated as having better mutual matrix. In the last phase, we structured a basic frame of the green-networks in Dalsu-Gu. The results suggested that the basic frame of the green-networks in Dalsu-Gu was composed on four green-network axes and its shape mirrored a cruciform(+) of northwest${\longleftrightarrow}$southeast directions and southwest${\longleftrightarrow}$northeast directions, The Duryu neighborhood park is at the central point of this green-networks.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.143-150
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• 2021

Process model is an integral part of software industry. Different process models are used now a days in the industry for different software projects. Process models need to be tailored to address some specific project needs. Agile models are considered as the most widely used process models nowadays. They have distinctive features and the ability to address the dynamic needs of today's software development. Extreme programming (XP) is one of the extensively used agile process model especially for small projects. Many researchers have tried to mold XP to overcome its shortcomings and for better working in specific scenarios. Therefore, many customized versions of XP process model are available today. In this paper, we are going to analyze the latest customizations of XP. For this purpose, a systematic literature review is conducted on studies published from 2012 till 2018 in renowned online search libraries. This comprehensive review highlights the purpose of customizations, along with the areas in which customizations are made, and phases & practices which are being customized. This work will serve the researchers to discover the modern versions of XP process model as well as will provide a baseline for future directions for customizations.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.103-114
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• 2021

A conceptual model can be used to manage complexity in both the design and implementation phases of the system development life cycle. Such a model requires a firm grasp of the abstract principles on which a system is based, as well as an understanding of the high-level nature of the representation of entities and processes. In this context, models can have distinct architectural characteristics. This paper discusses model multiplicity (e.g., unified modeling language [UML]), model singularity (e.g., object-process methodology [OPM], thinging machine [TM]), and a heterogeneous model that involves multiplicity and singularity. The basic idea of model multiplicity is that it is not possible to present all views in a single representation, so a number of models are used, with each model representing a different view. The model singularity approach uses only a single unified model that assimilates its subsystems into one system. This paper is concerned with current approaches, especially in software engineering texts, where multimodal UML is introduced as the general-purpose modeling language (i.e., UML is modeling). In such a situation, we suggest raising the issue of multiplicity versus singularity in modeling. This would foster a basic appreciation of the UML advantages and difficulties that may be faced during modeling, especially in the educational setting. Furthermore, we advocate the claim that a multiplicity of views does not necessitate a multiplicity of models. The model singularity approach can represent multiple views (static, behavior) without resorting to a collection of multiple models with various notations. We present an example of such a model where the static representation is developed first. Then, the dynamic view and behavioral representations are built by incorporating a decomposition strategy interleaved with the notion of time.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.165-170
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• 2006

In the Civil Aviation field, the international trend (through ICAO, EUROCONTROL) is to adopt one positioning system that allows to follow more flight phases. This will allow to release themselves by ground installations and optimize the traffic flows following the aRea Navigation (RNAV) concept. In order to realize this goal the European Scientific Community are focusing on Augmentation Systems based on Satellite infrastructure (SBAS - Satellite Based Augmentation System) and on Ground based ones (GBAS - Ground Based Augmentation System). The goal of this work is to present some results on SBAS and GBAS performances. Regarding SBAS, the Department of Applied Sciences of Parthenope University, after the acquisition of a Novatel OEM4 SBAS receiver has created a monitoring station that reflect as much as possible a standardized measure environment for EGNOS Data Collection Network (EDCN), established by Eurocontrol. The Department of Applied Science has decided to carry out a own monitoring survey to verify the performance of EGNOS that can be achieved in South Europe region, a zone not very covered by official (EDCN) monitoring network. Regarding GBAS, we started from a data set of measurements carried out at the GBAS of Milan-Linate airport where we work on a ground installation (GMS - Ground Monitoring Station) that supervises the GBAS signal and that represent, for our purposes, the Aircraft subsystem. So the set of data collected is to be considered in RTK mode and after the measures session we processed them with the software PEGASUS v 4.11. Both experiences give us the possibility to evaluate the GNSS1 performance that can be achieved.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.12-18
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• 2021

This paper proposes a framework for the development of the health recommender system, designed to cater COVID-19 symptoms' self-assessment and monitoring as well as to provide recommendations for self-care and medical treatments. The aim is to provide an online platform for Patient Under Investigation (PUI) and close contacts with positive COVID-19 cases in Malaysia who are under home quarantine to perform daily self-assessment in order to monitor their own symptoms' development. To achieve this, three main phases of research methods have been conducted where interviews have been done to thirty former COVID-19 patients in order to investigate the symptoms and practices conducted by the Malaysia Ministry of Health (MOH) in assessing and monitoring COVID-19 patients who were under home quarantine. From the interviews, an algorithm using user-based collaborative filtering technique with Pearson correlation coefficient similarity measure is designed to cater the self-assessment and symptoms monitoring as well as providing recommendations for self-care treatments as well as medical interventions if the symptoms worsen during the 14-days quarantine. The proposed framework will involve the development of the health recommender system for COVID-19 self-assessment and treatments using the progressive web application method with cloud database and PHP codes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2709-2734
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• 2020

The growing demand to make wireless data services 5G compatible has necessitated the development of an energy-efficient approach for an effective new wireless environment. In this paper, we first propose a cognitive sensor node (CSN) based game theory for deriving energy via a primary user-transmitted radio frequency signal. Cognitive users' time was segmented into three phases based on a time switching protocol: energy harvest, spectrum sensing and data transmission. The proposed model chooses the optimal energy-harvesting phase as the effected factor. We further propose a distributed energy-harvesting model as a utility function via pricing techniques. The model is a non-cooperative game where players can increase their net benefit in a selfish manner. Here, the price is described as a function pertaining to transmit power, which proves that the proposed energy harvest game includes Nash Equilibrium and is also unique. The best response algorithm is used to achieve the green connection between players. As a result, the results obtained from the proposed model and algorithm show the advantages as well as the effectiveness of the proposed study. Moreover, energy consumption was reduced significantly (12%) compared to the benchmark algorithm because the proposed algorithm succeeded in delivering energy in micro which is much better compared to previous studies. Considering the reduction and improvement in power consumption, we could say the proposed model is suitable for the next wireless environment represented in 5G.

• Korean Journal of Social Welfare Studies
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• v.42 no.4
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• pp.61-102
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• 2011

The purpose of this article is to anatomize the political dynamics of South Korea's healthcare policymaking through the integrative analytical framework combining the policy network perspective and the advocacy coalition theory. This framework is expected to be advantageous to the analysis of Korea's turbulent healthcare policy change from a systematic and process-driven point of view. A target of analysis is the two decades of turbulence to transform the health insurance system into a single payer system. Through the analysis, this article tries to illuminate the dynamics of Korea's healthcare policymaking, by connecting environmental context, policy networks, advocacy coalitions, and policy outputs. For a case study, this article classifies the debates to inaugurate a single payer system into four sub-phases and conducts longitudinal comparative research.

• Journal of Korea Water Resources Association
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• v.36 no.5
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• pp.715-724
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• 2003

It is true that SOC facilities, such as dams, need long life cycles since more time has to be invested for the phases of planning, examination, feasibility study, design, contract, construction, and maintenance. This longer life cycle is easily exposed to the risk. And thus, brings additional cost by the delayed project, convenient loss according to the additional run of use, and benefit lose of not to using the facilities. So, the purpose of this study is to try to find a solution to reduce these time consuming problems which could diminish the whole national competition. Hence, this study is to show efficient, systematical project performance and network model by using reciprocal analyses between the construction period and cost based on economical analysis of each phase of life cycles. In addition, on the basis of these outputs, the Fast Track Method is suggested as an alternative solution as a new Approach in Life Cycle's Analysis.