감정은 학습능력, 행동, 판단력 등 삶의 많은 부분에 영향을 끼치므로 인간의 본질을 이해하는 데 중요한 역할을 한다. 그러나 감정은 개인이 느끼는 강도가 다르며, 시각 영상 자극을 통해 감정을 유도하는 경우 감정이 지속적으로 유지되지 않는다. 이러한 문제점을 극복하기 위하여 총 4가지 감정자극(행복, 슬픔, 공포, 보통) 시 생체신호(뇌전도, 맥파, 피부전도도, 피부 온도)를 획득하고, 이로부터 특징을 추출하여 분류기의 입력으로 사용하였다. 감정 패턴을 확률적으로 해석하여 다른 공간으로 매핑시켜주는 역할을 하는 Restricted Boltzmann Machine (RBM)과 Multilayer Neural Network (MNN)의 은닉층 노드를 이용하여 비선형적인 성질의 감정을 구별하는 Deep Belief Network (DBN) 감정 패턴 분류기를 설계하였다. 그 결과, DBN의 정확도(약 94%)는 오류 역전파 알고리즘의 정확도(약 40%)보다 높은 정확도를 가지며 감정 패턴 분류기로서 우수성을 가짐을 확인하였다. 이는 향후 인지과학 및 HCI 분야 등에서 활용 가능할 것으로 사료된다.

Productivity improvement is one of the important goals which firms’ technology developments aim at. Firms’ improved productivity from technology development means that their inputs can produce more outputs through technology development, which makes firms’ productivity improvement from technology development more and more important in the age of technology advance and convergence like today. This research empirically analyzes the influence of the external technology collaboration network diversity on the productivity improvement of the small and medium-sized enterprises (SMEs) from technology development and the moderating effect of the chief technology officer (CTO)-driven technology development on this influence. This study constructs the research model reflecting the moderating impact of the CTO-driven technology development and tests it with the ordinary least squares regression through the IBM SPSS version 23 by using the 2,000 data about South Korean SMEs. This research empirically reveals two points. One is that SMEs’ external technology collaboration network diversity has a positive influence on their productivity improvement from technology development. The other is that the positive effect of SMEs’ external technology collaboration network diversity on their productivity improvement from technology development is moderated by the CTO-driven technology development. The two points revealed in this study present two meaningful implications in not only the practical but also academic point of view. The practical implication is that it is effective for SMEs to use CTOs in increasing their productivity improvement from technology development. The academic implication is that making technology collaboration with more diverse external partners can increase SMEs’ productivity improvement from technology development.

This paper introduces the implementation of runtime synchronization method when mobile network is broken during the game play. In case of network failure, the game is restored using the saved play record. Before the network failure, the previous game play is recorded in the server. The runtime synchronization is performed using the recorded game play in 2-times, 4-times, 8-times and 12-times according to the paused time and the game is played continuously. Using the proposed method, the user can play the mobile game uninterrupted. The project mobile game is implemented, and shows the effectiveness of the proposed method.

Deep learning techniques are being studied and developed throughout the medical, agricultural, aviation, and automotive industries. It can be applied to construction fields such as concrete cracks and welding defects. One of the best performing techniques of deep running is CNN technique. In this study, we analyzed the classification of handwritten images using CNN technique before applying them to construction field. Deep running is generally more accurate with deeper layers, but analysis cost is high. In addition, many variations can occur depending on training options. Therefore, this study performed a parametric study to be a reference when CNN technique was applied through accuracy analysis according to training options.

최근 국내외에서는 수질안정성 향상 및 부지면적 저감을 위해 막여과 공정도입이 활발한 추세이며 특히, 정수처리 분야에서는 정밀여과(Microfiltration) 및 한외여과(Ultrafiltration) 공정이 많이 적용되고 있다. 막여과 공정의 경제성 향상을 위해서는 세정 시점의 예측 및 세정 주기 연장이 매우 중요한 요소이다. 따라서, 본 연구에서는 인공신경망(Artificial neural network)을 활용하여 UF 공정차압(Transmembrane pressure) 예측 모델을 개발하고자 한다. 입력변수로는 유입수 온도, pH, 탁도 등의 일평균값을 이용하였다.

본 연구에서는 고밀 시가화지역 내 녹지들의 경관생태학적 특성과 연결성을 분석함으로써 잠재적인 녹지패치들의 활용가능성을 평가하고, 이를 통해 생활권 내 녹지 네트워크를 형성하기 위한 도시정원의 도입 방안을 제시하고자 한다. 이를 위해, 서울시에서 공원 서비스 소외지역 및 중점녹화지구로 분류된 역삼동 일대를 대상지로 선정하였다. 우선, 대상지 일대 고밀 시가화지역 내 녹지의 현황을 가로녹지, 개인정원, 자투리공지, 공원, 옥상정원의 5개 항목으로 분류하여 파악하고, 녹지 네트워크 분석 및 잠재적 녹지의 가치를 평가하기 위하여 FRAGSTATS를 통한 경관지수 분석 및 다중버퍼생성분석을 통한 연결성평가를 실시하였다. 연구결과, 대상지 내 녹지면적은 가로녹지, 개인정원, 자투리공지, 공원, 옥상정원의 순으로 분포되어 있었다. 녹지의 유형별 특징으로는 가로녹지의 경우 핵심지역면적 (TCA)이 1,618m2로 가장 높은 값을 보여 선형 연결 녹지임에도 공원(1,128m2)에 상응하는 크기를 보였고, 개인정원의 경우 패치의 모양이 불규칙하면서도(ED=78.1m/㏊), 최근린 평균거리가 33.9m로 낮아 사유지내에서의 자유로운 정원 조성을 통해 고밀 시가화지역의 녹지군을 형성할 수 있음을 나타내었다. 자투리공지의 경우 대상지 내 가장 고루 분포하는(LPI=5.7%, SHEI=0.9) 녹지유형이나 외부교란에 노출되어 있어(TCA=66m2), 이를 고려한 정원으로의 활용 방안을 시사하였다. 대상지 내 녹지네트워크 형성에 있어서도 50m의 버퍼 범위를 연결녹지로 상정한 경우 전체 대상지 의 84%가 소규모 녹지네트워크에 의해 커버되는 것으로 나타났으며, 자투리공지의 연결만으로도(27%) 가로녹지(26%) 조성에 상응하는 네트워크 구축효과가 기대되었다. 이에, 주택지역을 중심으로 다양한 활동이 가능한 자투리 공공녹지 에 지역기반의 커뮤니티 가든 등 도시정원 조성을 장려하고, 가로녹지, 개인정원, 옥상정원도 동시에 적극 활용함으로써 고밀 시가화지역 내에 녹지네트워크를 효과적으로 구축할 수 있다고 판단되었다.

This study empirically analyzes the effect of IT SME ventures’ external information network diversity on their production period reduction and productivity improvement generated from technology development. This research constructs a mediating model based on the open innovation perspective and tests it with the 138 samples of South Korean IT SME ventures based on the ordinary least squares regression. This research is expected to make a good contribution by shedding a new light on the following three points about the critical role of IT SME ventures’ external information network diversity in increasing their production period reduction and productivity improvement generated from technology development which has scarcely been illuminated in the extant studies in the field of the management of technology for SMEs. First, IT SME ventures’ external information network diversity positively influences their production period reduction. Second, the external information network diversity positively influences IT SMEs’ ventures’ productivity improvement. Third, IT SME ventures’ production period reduction partially mediates the influence of IT SME ventures’ external network diversity on their productivity improvement. These three fresh points are expected to provide useful theoretical and practical implications. Related to the theoretical implication, this research provides a fresh implication that IT SME ventures’ external information network diversity positively influences not only their production period reduction but also productivity improvement generated from technology development. Concerning the practical implication, this study suggests that the CEOs in IT SME ventures make strategic efforts to use more diverse external information sources in order to increase their production period reduction and productivity improvement generated from technology development.

Network externality can be defined as the effect that one user of a good or service has on the value of that product to other people. When a network externality is present, the value of a product or service is dependent on the number of others using it. There exist asymmetries in network externalities between the online and traditional offline marketing channels. Technological capabilities such as interactivity and real-time communications enable the creation of virtual communities. These user communities generate significant direct as well as indirect network externalities by creating added value through user ratings, reviews and feedback, which contributes to eliminate consumers’ concern for buying products without the experience of ‘touch and feel’. The offline channel offers much less scope for such community building, and consequently, almost no possibility for the creation of network externality. In this study, we analyze the effect of network externality on the competition between online and conventional offline marketing channels using game theory. To do this, we first set up a two-period game model to represent the competition between online and offline marketing channels under network externalities. Numerical analysis of the Nash equilibrium solutions of the game showed that the pricing strategies of online and offline channels heavily depend not only on the strength of network externality but on the relative efficiency of online channel. When the relative efficiency of online channel is high, the online channel can greatly benefit by the network externality. On the other hand, if the relative efficiency of online channel is low, the online channel may not benefit at all by the network externality.

For the asset management of a water pipe network, it would be necessary to understand the extent of the maintenance cost required for the water pipe network for the future. This study would develop a method to draw the optimum cost required for the maintenance of the water pipe network in waterworks facilities to maintain the aim revenue water ratio and to achieve the target revenue water ratio, considering the water service providers’ waterworks condition and revenue water ratio comprehensively. This study conducted a survey with 96 water service providers as of the early 2015 and developed models to estimate the optimum maintenance cost of the water pipe network, considering the characteristics of the water service providers. Since the correlation coefficient of all the developed models was higher than 0.95, it turned out that it had significant reliability, which was statistically significant. As a result of applying the developed models to the actual water service providers, it was drawn that increasing revenue water ratio to more than a certain level can reduce the maintenance cost of the water pipe network by a great deal. In other words, it is judged that it would be the most efficient to secure the reliability of waterworks management by increasing the short-term revenue water ratio to more than a certain level and gradually increase the revenue water ratio from the long-term perspective. It is expected that the proposed methodology proposed in this study and the results of the study will be used as a basic research for planning the maintenance of water pipe network or establishing a plan for waterworks facilities asset management.

Supply chain is usually represented by a network (which is called supply chain network) that contains some nodes. In a supply chain network these nodes are suppliers, plants, distribution centers and customers which are some facilities connected by some arcs to each other. The arcs connect the nodes in the direction of their production flow, meaning that each arc shows a route between the facilities for transporting the products. A multi-stage supply chain network (MSCN) is defined as a sequence of multiple supply chain network stages. This paper addresses a typical supply chain network problem which is based on a two-stage single-product system under uncertain conditions such that both cost and constraint parameters are interval numbers. The combination of these uncertain parameters are considered in this typical problem for the first time. In this case, two different order relations (the order relations UC ≤ and HW ≤ ) for interval numbers are considered. Then, two solution procedures are developed in order relations for the interval two-stage supply chain network design problem. The efficiency of the proposed method is illustrated by a numerical example where it is proved that the relation HW ≤ shows better performance than the relation UC ≤ .

SNS (Social network service) characteristics are perceived to simplify use. We carried out empirical studies on these parameters to observe the impact on the image of catering SNS online by word-of-mouth. The subjects of the study were as follows: 32.3% (392 persons) 19 years old, 67.7% (821 persons) over 19 years, 51.0% (619 persons) in their 20s, 22.1% (268 persons) in their 30s, 17.6% in their 50s, and 9.3% (112 persons) over 50 years. After verifying the hypothesis proposed that SNS characteristics perceived the ease of use, the significant factor identified in usability were connectivity Speed (β=0.213), playfulness (β=0.246), information (β=0.115), and reciprocity (β=0.357). Dual reciprocity had the most impact. It was observed that a longer impact of these significant factors improved the feel and fun of use. If SNS companies cater to, quick and easy, diverse, reliable and latest information, they can increase the ease of use, and availability, depending on the goals. Also, significant factors in the SNS features and online word of mouth was playfulness (β=0.312), information (β=0.207), reciprocity (β=0.066) and perceived ease of use, and usefulness (β=0.293), double playfulness had the maximum impact. These features provided more fun, reliable information, and could quickly deliver the latest information. The more the perceived usefulness, and ease of use, higher was the online word-of-mouth effect. SNS usage characteristics of connectivity Speed did not show any statistical significance in online word-of-mouth. Thus, catering businesses need to find ways to increase the ease of use, make the usefulness multifaceted, constantly checking the catering information on the SNS and ensuring to get the latest information is from diverse and reliable sources. This would increase the fun for the customer making the SNS to actively be utilized as a marketing tool.

연구자의 성장경로에 있어서 박사학위를 취득한 이후 시점은 변곡점이 형성되는 전환기로 경험에 커다란 영향을 미치는 것으로 나타나고 있다. 교수의 지도를 받는 학생의 입장에서 벗어나 독립된 연구자로 발전하는 중요한 시기이다. 또한 신진연구자 시기는 개인 연구역량의 축적과 더불어 독립적인 연구자로서 대외적인 명성과 네트워크를 형성하기시작하는 시기이다. 본 연구에서는 박사학위 취득 후 안정적인 연구자로서 자리 잡기 전까지의 경험에 주목하였다. 이 기간 동안 포닥 연구원의 경험이 지식이전 활동에 어떠한 영향을미치는 지 탐색하고자 한다. 본 연구의 목적은 대학 신진연구자를 중심으로 논문 성과와 공저자 관계로 나타나는 지식이전 활동에 영향을 미치는 요인을 분석하는 것이다. 박사취득 후대학의 전임교원으로 임용되기 전까지 경험이 연구자의 논문 성과에 어떠한 영향을 미치는지를 분석하였다. 2008년도 신진연구자지원사업을 수행한 대학 연구자를 대상으로 국가과학기술정보시스템에서 제공하는 연구자 정보를 활용하여 학력 및 경험사항, 연구 성과 등에 대한 정보를 수집하고 STATA를 활용하여 회귀분석을 실시하였다. 분석 결과, 포닥 기간의 경험 중 기관의 다양성이 논문 성과와 연구 네트워킹 형성에 긍정적인 영향을 미치는 것으로나타났다. 포닥 경험의 상호작용 측면에서 포닥 경험 기간이 길고 국외 포닥 경험이 있는 경우 연구 네트워킹 형성에 긍정적인 영향을 미치고, 포닥 경험 기간 중 경험한 기관이 많고 국외 포닥 경험이 있는 경우 논문 성과와 연구 네트워킹 형성에 긍정적인 영향을 미치는 것으로 나타났다. 본 연구의 결과는 포닥 기간의 경험이 연구성과에 영향을 미치는 요인 중 하나의 변수로 고려할 수 있고 포닥 연구원 지원제도와 관련된 정부 정책을 수립하는데 큰 시사점을 제시할 것으로 판단된다.

The objective of this study is to investigate patent trends of Daegu city which tries to introduce environment friendly energy and to develop new technology or new industry sprung from technology convergence on smart decentralized energy technology and other technologies. After applying network analysis to corresponding groups of technology or industry convergence, strategy for future energy convergence industry is provided. Patent data applied in Daegu city area are used to obtain research goal. The technology which contains several IPC codes (IPC Co-occurrence) is considered as a convergence technology. Path finder network analysis is used for visualizing and grouping by using IPC codes. The analysis results categorized 13 groups in energy convergence industry and reclassified them into 3 cluster groups (Smart Energy Product Production Technology Group, Smart Energy Convergence Supply Technology Group, Smart Energy Indirect Application Technology Group) considering the technical characteristics and policy direction. Also, energy industry has evolved rapidly by technological convergence with other industries. Especially, it has been converged with IT industry, and there is a trend that energy industry will be converged with service industry and manufacturing industry such as textile, automobile parts, mechanics, and logistics by employing infrastructure as well as network. Based on the research results on core patent technology, convergence technology and inter-industry analysis, the direction of core technology research and development as well as evolution on decentralized energy industry is identified. By using research design and methodology in this study, the trend of convergence technology is investigated based on objective data (patent data). Above all, we can easily confirm the core technology in the local industry by analyzing the industrial competitiveness in the macro level. Based on this, we can identify convergence industry and technology by performing the technological convergence analysis in the micro level. 1

The calibration of Very Long Baseline Interferometry (VLBI) data has long been a time consuming process. The Korean VLBI Network (KVN) is a simple array consisting of three identical antennas. Because four frequencies are observed simultaneously, phase solutions can be transferred from lower frequencies to higher frequencies in order to improve phase coherence and hence sensitivity at higher frequencies. Due to the homogeneous nature of the array, the KVN is also well suited for automatic calibration. In this paper we describe the automatic calibration of single-polarisation KVN data using the KVN Pipeline and comparing the results against VLBI data that has been manually reduced. We nd that the pipelined data using phase transfer produces better results than a manually reduced dataset not using the phase transfer. Additionally we compared the pipeline results with a manually reduced phase-transferred dataset and found the results to be identical.

본 연구에서는 국내 위치기반소셜 네트워크(LBSN)의 공간분포 특징을 분석하였다. LBSN에서 발생하는 정보의 특징은 사용자들이 작성한 콘텐츠가 지역과 밀접한 관계를 갖는 내용이기에 해당 지역이 갖는 특징들을 반영하고 있다는 점이다. 본 연구에서는 가장 대표적인 서비스인 포스퀘어를 사례로 베뉴와 팁에 관한 정보를 수집하여 데이터의 지역 간의 특징 및 차이를 분석하였다. LBSN자료의 정량적인 특징인 베뉴 및 팁의 수와 함께 정성적인 특징인 베뉴의 범주, 팁의 콘텐츠에 대한 정성적인 분석을 통해 지역별로 나타나는 콘텐츠의 특징을 분석하였다. 분석결과 도시지역을 대표하는 서울특별시와 관광지역인 제주도에 있어, 베뉴의 범주와 팁 텍스트의 질적인 특징들을 확인할 수 있었다.

Substantial knowledge about how electronic word of mouth (eWOM) relates to influentials, or, individuals who either intentionally or unintentionally have a great impact on the network, is lacking because influence patterns are hardly quantifiable when human and societal components are not deeply understood. The eWOM networks in social media platforms drive the theoretical and practical progress of the social structure of eWOM and the social role of influentials. The purpose of this study is to explore the diffusion of eWOM in a Twitter network by drawing from the Diffusion of Innovation theory in conjunction with Social Network Analysis (SNA) approach. Through a large amount of data collected from Twitter regarding the terrorist attack in Paris on November 13, 2015, this study examined the social structure of eWOM network groups and identifies the social role of influential users in the network of #prayforparis. To identify influentials of eWOM in Twitter networks, SNA was conducted with NodeXL, which is an Excel add-in network analysis software. The Twitter data set was uploaded at 11 am, on November 17, 2015 by applying hashtag prayforparis through Twitter Search Network feature of NodeXL. A total of 19,592 tweets (vertices) were downloaded with a total of 20,297 edges (relations between vertices). “Justin Bieber” was identified as the most influential and dominant user in the network of #prayforparis because he has the highest in-degree (4,196) and highest betweenness centrality (51,772,745.861). Justin Bieber lost one of his friends in the terrorist attack, and his tweet about the sadness from the loss was retweeted more than 50,000 times and received 77,000 likes. Throughout the network, top word pairs respectively repeated more than 4,000 times were “thomas, prayforparis,” “rt, justinebieber,” “rip, thomas,” and “justinbiber, rip.” “Ally Brook” and “Louis Tomlin” ranked 3rd and 5th respectively with the highest betweenness centrality also demonstrated the celebrity power in the eWOM network of #prayforparis. While the three celebrities as dominant influentials were prominent in the Twitter network of #prayforparis, the social roles of fans were also acknowledged. The celebrities’ fans and fan sites have constantly diffused the celebrities’ posts by retweeting and by mentioning every tweet posted by the celebrities that they support. Without the celebrities and their fans, the #prayforparis network would have depicted a completely different style of diffusion of eWOM. The study confirmed social role of fans that constantly presented idiosyncratic manners by identifying and by linking to the public figure. The distinctive characteristics of the fans also enabled identifying the social role of the celebrity while spreading the new ideas with hashtag. The celebrity played a key role as an information hub even in a network of socio-political events such as the #prayforparis Twitter network. Thus, identified overwhelming influence of the celebrities in the eWOM network extends the areas of marketing choices and applicable strategies with celebrities.