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Recently, converging Big Data and IoT(Internet of Things)has become mainstream, and public sector is no exception. In particular, this combinationis applicable to crime prevention in Korea. Crime prevention has evolved from CPTED (Crime Prevention through Environmental Design) to ubiquitous crime prevention;however, such a physical engineering method has the limitation, for instance, unexpected exposureby CCTV installed on the street, and doesn't have the function that automatically alarms passengers who pass through a criminal zone.To overcome that, this paper offers a crime prevention method using Big Data from public organizations along with IoT. We expect this work will help construct an intelligent crime-prevention system to protect the weak in our society.

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Web systems evolve by adding new functionalities or modifying them to meet users’ requirements. Web systems require retesting to ensure that existing functionalities are according to users’ expectations. Retesting a web system is challenging due to high cost and time consumption. Existing ‘systematic literature review’ (SLR) studies do not comprehensively present the ontology-based regression testing approaches. Therefore, this study focuses on ontology-based regression testing approaches because ontologies have been a growing research solution in regression testing. Following this, a systematic search of studies was performed using the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines. A total of 24 peer-reviewed studies covering ontologies (semantic and inference rules) and regression testing, published between 2007 and 2019, were selected. The results showed that mainly ontology-based regression testing approaches were published in 2011–2012 and 2019 because ontology got momentum in research in other fields of study during these years. Furthermore, seven challenges to ontology-driven regression testing approaches are reported in the selected studies. Cost and validation are the main challenges examined in the research studies. The scalability of regression testing approaches has been identified as a common problem for ontology-based and other benchmark regression testing approaches. This SLR presents that the safety of critical systems is a possible future research direction to prevent human life risks.

Company A, an embedded system manufacturer, has been managing multiple development projects. Executives need to understand the risk level of every project and prioritize resource distribution. Traditional project monitoring tools or excel sheets are too complex for calculating the risk factors across a functional organization. Two new charts, "Spear-head Chart" and "Float Chart" were designed to assist high level decision making processes. Two charts were used for weekly executive meetings in order to monitor project progress and rectify project direction. One page graphical monitoring tools in Company A are good enough for high management decision making. Authors explain the characteristics of two charts and propose its practical implementation in real working environment. Spear-head chart was also implemented as a system.

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Recently, in pursuit of sustainable competitiveness, IT (information technology) service projects have been increasingly undertaken to introduce new technologies and advancements such as big data analytics, AI (artificial intelligence), Cloud Computing, mobile computing, IoT (Internet of Things), and business process changes.However, the project success rates of IT service projects have declined because of the various kinds of risks associated with the characteristics of these projects, such as software invisibility, unclear user requirements, the complexity of IT systems and new technologies, and agency conflicts such as different goals, different risk attitude, and information asymmetry among project participants. The profits and success rates of IT service projects have fallen because of risks and agency conflicts.In this study, we analyzed the gaps in average profits rates by revenue group for IT service companies in South Korea by one-way ANOVA (analysis of variance) analysis of SPSS V20 statistical tool. The result showed that the average profit rate of the revenue group over 1 billion USD was twice than the revenue groups of less 1 billion USD, and the gaps of average profit rates among revenue Group 1 and other revenue groups were statistically significant.

The demand for extracting keywords related to national issues from various sources and using them to retrieve R&D information has increased rapidly recently. In order to satisfy this demand, three methodologies are proposed in this study: a hybrid methodology for extracting and integrating national issue keywords, a methodology for packaging R&D information that corresponds to national issues, and a methodology for generating an associative issue network related to relevant R&D information. Data analysis techniques, such as text mining, social network analysis, and association rules mining, are utilized to establish these methodologies.