Earticle

1992년 한·중 수교 이후, 농산물과 농업식품 관련 무역이 급증하고 이외 양국간 경제교류도 활성화되어 현재 상호 중요한 경제파트너가 되고 있으며, 정치·외교적으로도 긴밀한 관계는 계속되고 있다. 한·중 양국은 지리적으로도 가까운 이웃나라로서, 식생활과 소비성향, 문화가 서로 비슷하고 농업에 있어서도 생산 작물과 가공산업 측면에서 긴밀하고 비교적 상호보완적 특성을 지니고 있다. 즉, 한국은 비교적 높은 품질, 안전성 및 가공기술이라는 특징이 있고, 중국은 체제 특유의 농업정책, 저임금 및 비교적 풍부한 자원이라는 차별성이 있다. 이러한 상황을 기반으로, 본 연구에서 한국의 청주시와 중국의 수광시를 대상으로 하고, GEM 모델을 활용하여, 산업기반, 기업의 역량, 시장환경이 농업식품가공기업의 경영성과와 클러스터성과에 미치는 영향에 대한 비교연구를 실증분석으로 수행하고자 하였다. 설문 수집을 통한 실증분석의 결과, 한국의 청주시와 중국의 수광시 모두 산업기반, 기업의 역량, 국내 시장환경이 농업식품가공기업의 경영성과에 유의한 정(+)의 영향을 나타냈으며, 농업식품가공 기업의 경영성과가 클러스터성과에 유의한 정(+)의 효과를 보였다. 또한, ‘농업식품가공기업의 경영성과’가 세 가지의 선행변수(산업기반, 기업의 역량, 국내시장환경)와 ‘클러스터성과’ 사이에 매개효과를 보였으며, 그 세부 결과는 양 국가간 다소 차이를 보였다. 끝으로 본 연구는 청주시에 입지하고 있는 농업식품가공기업의 경우, 해외시장에 대한 글로벌 전략이 매우 필요 하며, 수광시의 농업식품가공기업의 경우, 기업 내 부서 간의 협력이 보완된다면 경영성과가 보다 향상될 수 있다는 등 시사점을 제시하였다.

Since establishing diplomatic relation in 1992, Korea and China have enjoyed diverse advantages through economic cooperation, especially in commercial trade as well as agricultural product trade. Nowadays, Korea is the biggest exporter of agricultural product to China, and China is the fourth largest importer of agricultural product from Korea. Moreover, regional/cultural similarity and industrial complementarity between the two countries provide significant potentials for further development of agricultural product trade. Specifically, Korea has some comparative advantages in terms of relatively high-quality agricultural product, food safety, and high-level food processing technology. China specializes in other comparative advantages in terms of strong national policy, low labor cost, and abundant resources. Based on the fact above, with the GEM model, we investigate the effects of industrial groundings (G), enterprises’ capabilities (E), and market environment (M) on firms’ business performances and cluster’s performance in Cheongju Korea and Shouguang China. We analyzed survey data of agricultural food processing enterprises in two cities (Cheongju Korea and Shouguang China). We found that three independent variables (G, E, and M) affected firms’ business performance, and then firms’ business performances affected cluster’s performance. Furthermore, mediating effects of firms’ business performances were shown between three independent variables and cluster’s performance. There were some differences between Cheongju Korea and Shouguang China. Implications are as follows. The firms in Cheongju have strong advantages over those in Shouguang in terms of social infrastructures and cooperation within the organization, but need to globally expand their markets. In contrast, the firms in Shouguang enjoy advantages over those in Cheongju in terms of the amount of natural resources, but have to develop cooperation within the organization to improve both of the firms’ business performances and the food safety through R&D capabilities.

Background/Objective. The COVID-19 has accelerated the conduct of online classes around the world. To administer distant learning, schools are now relying on learning management systems. With the problems of the abrupt shift to an online modality, there must be measures in place to cluster students’ characteristics in order to assist their learning requirements, struggles, and academic performances. Methods/Statistical Analysis. Based on Delone and McLean’s IS Success model, this study used quantitative approaches and exploratory techniques to explain the higher education learners’ clusters. From March to April 2021, 303 samples were randomly selected from students participating in online programs at a higher education school on Taft Avenue in Manila. Sex, school, frequency of use, time duration, and experience with the LMS were all factors in the study. Both Hierarchical Cluster Analysis and K-Means Cluster Analysis were used to classify the samples. Findings. The results revealed that there are four clusters formed which are labeled as: service-oriented, system quality-oriented, holistic-oriented, and LMS-averse. Based on the results, information quality has the greatest influence. Since the clustering analysis is non-inferential and it is used as an exploratory technique, the researchers do not guarantee a unique solution as this depends on the elements of the subjects and the variables used. Improvements/Applications. The academic stakeholders can use the cluster analysis to make the appropriate interventions to improve the online course content and enhance the students’ academic performance. Some of these appropriate interventions include creating course policies, planning the necessary training of teachers and students, and developing the online delivery of the lessons.

클러스터 산업환경을 이용한 산·학·연의 산업 활동에 있어서 적응 만족을 갖게 하는데 있으며, 이를 위해 정책제도적 지원과 클러스터 사업운영을 기반으로 기업성과를 얻기 위한 요인들을 분석하여 클러스터 성과에 미치는 전반적 영향을 확인하여 관련 정책의 지속적 발전이 필요하다. 수도권과 충청 지역에 소재한 클러스터에 소속된 기업체를 대상으로 설문을 통해 정책과 이에 참여하는 기업간의 분야별 상호관계를 분석하여 어떤 부분을 중점 개선해야 할 지를 확인해 보았다. 8개의 가설 검증하기 위해 SEM(structural equation model)을 이용하였는데, 결과는 다음과 같다. 클러스터 사업운영이 참여기업 태도에 영향을 미쳤고, 참여기업 태도가 기업성과에 영향을 미쳤다. 또한 정책제도적 지원이 기업성과에 영향을 미쳤고, 기업성과가 클러스터 성과에 영향을 미쳤다. 클러스터 사업운영이 클러스터 성과에도 영향을 미쳤다. 그리고 매개변수(참여기업 태도, 기업성과)로도 간접효과 영향을 주었다. 결과적으로 정책제도적 지원, 클러스터 사업운영을 기반으로 한 참여기업 태도 등이 융합적인 형태로 수용할 경우, 클러스터 성과에 더 많은 영향을 미칠 수 있음을 보여주었다.

This study aims at offering satisfying adaptation to the industrial cluster environment in the industry-academic industrial activities, and to analyse various factors that affect the organizational performance based on the institutional support and cluster operation so as to verify their overall effects on the cluster performance. A survey was conducted using a written questionnaire with the companies located within the clusters in the metropolitan and Chungcheong regions. 165 companies returned the questionnaire and finally 147 of them were accepted as valid for the study. The SEM (structural equation model) was used to verify hypothesis, and the results of the study can be summarized as follows: 1) The cluster operation affected the organizational behaviour of the participants. 2) The organizational behaviour of the participants affected their performance. 3) The institutional support affected the corporate performance. 4) Corporate performance affected the cluster performance. 5) The cluster operation affected its own performance. Other parameters (such as the organizational behavior of the participants, corporate performance etc) were found to be the factors indirectly influencing the cluster performance. In conclusion, the study suggests that amalgamation of institutional support and organizational behaviour of the participants based on the cluster operation can become more influential to the clusters’ performance.

최근 클라우드 서비스에 관한 기술이 많이 나오고 있으며 그 중 컨테이너를 관리하는 기술이 주목받고 있다. 컨테이 너 관리 플랫폼은 애플리케이션을 더욱 효율적이고 편리하게 하지만 응용 프로그램 성능에 영향을 주는 요소가 많이 있다. 본 논문에서는 컨테이너 관리 플랫폼 중 대표적인 Kubernetes 환경에서 MySQL 클러스터의 성능에 관한 연구한다. Kubernetes에서는 최소 단위 pod 및 데이터베이스 sharding이 MySQL 클러스터의 성능에 미치는 영 향을 탐색하기 위한 실험을 수행한다. 실험 결과에 따르면 pod는 MySQL 클러스터의 성능을 향상할 수 있지만 sharding이 긍정적 효과와 부정적인 효과가 모두 있다. 쿼리 프로세스를 분석하고 부정적인 영향을 미치는 요소를 찾은 다음에 MySQL 클러스터 매개변수를 조정하며, 조정된 MySQL 클러스터의 성능이 향상됨을 보인다. 마지막 으로, Kubernetes에서 MySQL 클러스터를 효과적으로 배치하는 방법을 제시한다.

Recently, there are many technologies related to cloud services, and among them, the technology for managing containers is drawing attention. Container management platforms make applications more efficient and convenient, but there are many factors that affect application performance. In this paper, we study the performance of MySQL cluster in Kubernetes, a representative container management platform. Kubernetes conducts an experiment to explore the effect of minimal unit pod and database sharding on the performance of MySQL cluster. Experimental results show that pods can improve the performance of MySQL clusters, but sharding has both positive and negative effects. After analyzing the query process and finding negative influences, it adjusts the MySQL cluster parameters, and shows that the performance of the tuned MySQL cluster is improved. Finally, we show you how to effectively deploy a MySQL cluster in Kubernetes.

새정부의 120대 국정과제 중 일부 과제에서 '국가산업단지'와 '연구개발특구'와 같은 혁신클러스터 중심의 신산업 창출 촉진 필요성이 논의되고 있는 반면, 국고지원 측면에서는 균특회계 지원 및 예타면제 등에서 사업평가 요건이 강화되고 있는 추세이다. 이러한 정부기조에 따라 연구개발특구, 국가산업단지와 같은 지역의 클러스터 사업의 국고지원에 있어서 과거보다도 특허성과 관련 성과지표의 중요성은 증대될 것으로, 이에 대한 현황점검이 필요한 시점이다. 본 연구에서는 연구개발특구를 지원하는 ‘연구개발특구육성(R&D)사업’과 국가산업단지를 지원하는 ‘산업집적지경쟁력강화사업’의 과제를 대상으로 과제에서 창출된 특허출원, 특허등록, 등록특허의 평균점수와 같은 특허성과의 현황과 영향을 미치는 요인을 분석하였다. 분석결과, R&D규모 및 과제특성 요인 중 일부는 개별 클러스터 또는 공통적으로 특허성과 창출에 통계적으로 유의한 영향을 미치는 것으로 나타났다. 본 연구는 지역클러스터 사업의 변화가 필요한 시점에서 혁신클러스터 사업을 통해 창출된 특허성과를 양적 성과 및 질적 성과로 구분하여 다양한 특허성과에 미치는 영향요인을 연구개발과제 단위에서 검토하였다는 점에서 의의가 존재한다.

While some of the new government's National Agenda are discussing the need to promote the creation of New Industries centered on Innovation Clusters such as ‘National Industrial Cluster’ and ‘R&D Special District’, R&D program evaluation requirements are being strengthened in support of Special Account for the Balanced National Development and Preliminary Feasibility Analysis Exemption in terms of national financial support. Under this government stance, the importance of indicators for patent performance will increase compared to the past in national financial support for regional cluster R&D programs such as R&D Special District and National Industrial Cluster, therefore, it is necessary to analyze the current status. This paper analyzed the current status and factors affecting patent performance, such as the average score of patent applications, patent registration, and patent application created by the result of the R&D Special District Development (R&D) Program and the Korea Industrial Cluster Program. As a result of the analysis, it was found that some of the R&D scale and project characteristic factors had a statistically significant effect on the creation of patent performance in individual clusters or in common. This paper is meaningful in that it analyzed the influencing factors on various patent performance by dividing the patent performance generated through the innovative cluster R&D program into quantitative and qualitative performance when the regional cluster R&D program is needed to change.

The K-means algorithm is widely used at the initial stage of data analysis in data mining process, partly because of its low time complexity and the simplicity of practical implementation. Cluster validity indices are used along with the algorithm in order to determine the number of clusters as well as the clustering results of datasets. In this paper, we present a performance comparison of sixteen indices, which are selected from forty indices in literature, while considering their applicability to nonhierarchical clustering algorithms. Data sets used in the experiment are generated based on multivariate normal distribution. In particular, four error types including standardization, outlier generation, error perturbation, and noise dimension addition are considered in the comparison. Through the experiment the effects of varying number of points, attributes, and clusters on the performance are analyzed. The result of the simulation experiment shows that Calinski and Harabasz index performs the best through the all datasets and that Davis and Bouldin index becomes a strong competitor as the number of points increases in dataset.

이 연구는 대전지역의 중소벤처기업을 중심으로 혁신클러스터 활동(구성원간의 관심과 관계성, 정보교류와 정보습 득 활동, 수요와 공급 간의 해결 활동)이 기업 경영성과에 미치는 영향을 연구하고, 관련 정책에 대한 시사점을 제시하는데 목적이 있다. 이를 위해 대전지역 소재 중소벤처기업 CEO 212명의 설문결과를 확보하고 SPSS 21을 이용하여 연구가설을 검증하였다. 실증분석결과 구성원 간의 정보교류 및 정보습득 활동과 수요와 공급자 간의 해결 활동은 경영성과에 긍정적인 관계가 확인되었으나, 구성원 간의 관심과 관계성은 경영성과에 영향이 없음이 확인되었다. 본 연구를 통해 혁신클러스터내 의 기업들이 지속적인 성장과 발전을 위해서는 혁신클러스터 활동에 적극적인 참여와 정부의 다양한 지원제도나 정책 등이 확대되어야 하고, 기업들은 상호간의 만족도를 높이거나, 협력을 위한 공감대 형성을 위해 더욱 분발하고 노력을 해야 할 것이다. 부족한 관심과 관계성을 높이기 위해 혁신클러스터 기업협회들은 다양한 프로그램을 통해 구성원 간의 관계 개선을 위해 노력해야 한다는 시사점을 제시하였으며, 향후 다양한 혁신클러스터 활동의 매개변수에 대한 추가분석을 통해 경영성 과 간의 체계적인 이론을 정립할 필요가 있다.

This study was designed to provide implications for related policies by researching the impact on business management performances focusing on the activities within the innovation clusters based on small and medium venture companies in Daejeon area. The questionnaires from 212 CEOs of small and medium venture businesses in Daejeon were analyzed and verified the research hypothesis using SPSS 21. From the empirical analysis, we confirmed the following results; activity of information exchange, information acquisition and solving activity between demand and supplier showed positive effects on business management performance, however the concern and relationship have no effects on business management performance. From this study, we suggest that the active participation in activity of innovation cluster and various supporting systems or policies have to expand for sustainable growth and development of companies within innovation cluster. We also propose that companies needs to try to more efforts on enhance the mutual satisfaction or forming a consensus for cooperation. This study also propose the implications that the companies, innovation cluster must try on efforts to improve relation among members for enhancing the lack of concerns and relationship.

Distributed data processing like hadoop cluster based on mass storage device can be organized by high performance server or embedded systems. High performance CPUs like Xeon Processor have disadvantages on costs which can be occur during purchasing and maintaining. On this research, we confirm low-power hardware environment using RAID0 to improve performance for replacing high performance server environment.

본 연구는 판교 테크노벨리를 대상으로 결속형 및 교량형 사회적 자본이 산업단지 내 기술적 혁신성과에 미치는 영향을 고찰하였다. 특히 본 연구에서는 사회적 자본의 선행요인으로 “정보기술 활용”의 역할에 주목하였다. 정보기술을 활용함으로써 내․외부 구성원과의 커뮤니케이션 및 정보교환이 활성화되고 이에 다양한 관계망을 확장시켜 네트워크화 할 수 있기 때문이다. 연구결과 정보기술 활용은 결속형 자본과 교량형 자본에 모두 긍정적 영향을 미치는 것으로 검증되었다. 하지만 사회적 자본이 기술적 혁신성과에 미치는 영향에 있어서는 뚜렷한 차이가 발견되었다. 판교 테크노 벨리의 경우 신뢰나 협력을 중심으로 한 강한 결속 관계보다는 다양한 네트워크를 통해 형성되는 교량형 자본의 효과가 기술적 혁신 성과에 유의하게 작용하고 있음을 알 수 있었다. 이러한 현상은 판교 테크노벨리의 구조적 특성상 IT기반의 기업들이 대부분 입주되어 있으며 비교적 쉽게 정보를 공유하며 다양한 사람들과 자연스럽게 네트워크가 형성되는 특성에 기인한다고 해석된다.

This study investigates the effect of bonding and bridging social capital on the technological innovation performance in the Pangyo Techno Valley. In particular, we consider the information technology (IT) usage in industrial cluster as an antecedent of social capital. IT instigates the intra and extra communication and information sharing between employees, thereby promoting the formation of a network of various members. Results show that the IT usage factor positively affects both bridging and bonding social capital, but an evident difference exists among the effects of social capital on the technological innovation performance. In case of Pangyo industrial cluster, bridging social capital exerts significant effect on the technological innovation performance, whereas bonding social capital shows insignificance. Bridging social capital is composed of the interactions of various networks. Bonding social capital is based on the strong tie from trust and internal cooperation. Results are related with the characteristics of Pangyo Techno Valley, where various IT ventures need active communication and information sharing with other organizations for technological innovation performance.

행정안전부 재해연보에 따르면 우리나라에서는 매년 호우로 인한 피해가 지속되며, 자연재해 중 재산피해 비중이 가장 높다. 이에 본 연구는 강우 규모, 지리적 위치, 피해 규모 등과 같은 지역적 특성을 고려하여 군집분석(K-means)을 통해 경기도 내 지자체를 분류하고, 이를 바탕으로 호우피해예측 함수를 개발하였다. 분석 대상은 경기도 내 지자체이며, 2013년부터 2023년까지의 데이터를 활용하였다. 예측 변수는 기상요소와 사회·경제적 요인으로 구성하였다. 예측 모델로는 선행연구에서 예측 성능이 우수했던 의사결정나무 기반 배깅(Decision Tree Bagging, DT-Bagging)과 장단기메모리(Long Short-Term Memory, LSTM)을 적용하였다. 두 가지 모델의 예측 성능 비교를 위해 평균제곱오차(Mean Square Error, MSE), 평균제곱근오차(Root Mean Square Error, RMSE), 정규화 평균제곱근오차(Normalized Root Mean Squared Error, NRMSE)를 사용하였다. 예측 성능 비교 결과, DT-Bagging 함수가 LSTM 함수 대비 97.2%의 향상률을 보였다. 따라서 본 연구는 지자체 특성에 기반한 정밀한 호우피해예측과 재난관리 체계 구축에 기여할 수 있을 것으로 기대된다.

According to the Ministry of the Interior and Safety's Disaster Yearbook, heavy rain continues to cause damage in South Korea every year, and property damage accounts for the largest proportion of natural disasters. Therefore, this study classified local governments in Gyeonggi Province using K-means clustering analysis, considering regional characteristics such as rainfall intensity, geographic location, and damage scale. Based on this, a heavy rain damage prediction function was developed. The analysis focused on local governments in Gyeonggi-do, using data from 2013 to 2023. Predictor variables consisted of meteorological and socioeconomic factors. Decision Tree Bagging (DT-Bagging) and Long Short-Term Memory (LSTM) models, which have demonstrated excellent predictive performance in previous studies, were used as prediction models. Mean Square Error (MSE), Root Mean Square Error (RMSE), and Normalized Root Mean Squared Error (NRMSE) were used to compare the predictive performance of the two models. The prediction performance comparison results showed that the DT-Bagging function achieved a 97.2% improvement over the LSTM function. Therefore, this study is expected to contribute to the establishment of a precise flood damage prediction and disaster management system based on the characteristics of local governments.

1990년대부터 추진된 우리나라 산업클러스터 정책은 산·학·연 네트워크를 통해 기업의 혁신과 성과창출을 유발하고 궁극적으로는 산업 경 쟁력 강화와 지역 간 균형 발전을 목표로 하고 있다. 본 연구는 산업클러스터의 지원시스템과 기업 성과에서 기업 역량과의 관계를 규명한 연 구로 산업조직론의 SCP Paradigm을 이론적 배경으로 하여 산업클러스터의 지원시스템이 기업의 어떤 역량을 통해 성과로 연결되는지 실증 분석하였다. 대구광역시에 위치한 370여개의 벤처기업을 대상으로 분석 결과 산업클러스터의 체계성은 기업 역량 모두에 유의미한 영향을 미치고, 특히 마케팅 역량에 더 큰 영향을 미치는 결과를 알 수 있었다. 기업 역량과 기업성과의 관계에 있어 R&D역량과 기업 재무적 성과와 관계를 제외한 다른 기업 역량들과 재무적·비재무적 성과와의 관계는 유의미한 영향을 미치는 것으로 분석되었고, 특히 마케팅 역량이 기업의 재무적 성과에 가장 큰 영향을 미치는 것으로 나타났다. 본 연구의 시사점은 SCP Paradigm을 바탕으로 산업클러스터와 기업 성과에 대한 연구에 다양한 방향을 제시할 수 있다는 것과 기술벤처기 업에 대한 산업클러스터의 지원 정책에서 기존 R&D와 생산운영 중심에서 마케팅 역량을 강화하는 지원체계에 대한 정책 집중이 필요하다는 것을 시사한다.

The Korean industrial cluster policy, which has been promoted since the 1990s, aims at strengthening industrial competitiveness and balanced regional development through inducing innovation and creating performance through industry network, academia, and government. This study examines the relationship between government’s industrial cluster support system and firm performance in terms of corporate capacity. In this study, 370 venture companies located in Daegu city were surveyed about the capability of industrial clusters. The effect of industrial cluster support system on corporate capacity and performance is analyzed based on SCP paradigm of industrial organization theory. As a result, the industrial cluster systematicity has a significant effect on 3 different corporate capabilities such as marketing, operation, and R&D capability. Especially, the systematicity has a greater impact on marketing capability. Except for the relationship between R&D capability and corporate financial performance, 3 different corporate capabilities have significant effect on firm’s financial/non-financial performance. In particular, among 3 different corporate capability, marketing capability has the greatest effect on corporate financial performance. The implication of this study is that research based on SCP Paradigm can present various directions for research on industrial clusters and corporate performance. So far, industrial cluster support policy for technology venture companies has been focused on R&D and production operation. However, this study suggests that support policy to strengthen firm’s marketing capability is also needed.

정부지원과 기업 경영성과 간 관계에서 기업 고유의 특성과 공간적 특성의 중요성을 강조하는 많은 논의들이 있지 만, 기업 특성과 클러스터 특성이 통합적으로 경영성과에 미치는 영향에 대한 실증연구는 부족한 실정이다. 본 연구는 정부 자금지원의 구체적인 투입에 따른 재무적, 비재무적 성과를 실증분석하고, 정부 자금지원과 기업 경영성과 간에 영향을 조절 할 것으로 예측되는 기업 특성 및 클러스터 특성을 탐색하여, 개인 및 집단의 2수준 위계적 선형모형(HLM)으로 분석하였다. 데이터는 사업자등록번호 기준으로 기업 및 클러스터 수준으로 재정리하여 최종적으로 기업수 83,395개사 및 클러스터 641 개의 패널데이터가 활용되었다. 연구 결과, 정부 자금지원은 기업의 매출액과 특허 모두에 정(+)의 효과를 주는 것으로 나타 나, 정부 지원이 시장실패를 보완할 수 있는 유효한 수단이라는 것을 보여준다. 위계적 선형모형으로 분석한 결과, 정부 자금 지원과 인적자본역량, 흡수역량, 클러스터 네트워크 밀도와 결합할 경우, 모두 매출액과 유의한 정(+)의 효과가 나타났다. 본 연구는 2수준 위계적 선형모형으로 분석하여, 기업 특성인 인적자본역량과 흡수역량, 클러스터 특성인 클러스터 네트워크 밀 도가 조절효과로 정부 자금지원과 기업경영성과를 조절하는 역할을 수행함을 밝혀 이론적, 실무적 시사점을 제공한다.

Regarding the discourse on the correlation between governmental financial support and firm performance, much emphasis has been placed on the role of individual corporate characteristics as well as spatial features. However, there is a notable scarcity of empirical research examining the integrated impact of corporate and cluster characteristics on managerial performance. This study addresses this gap by empirically analyzing the financial and non-financial outcomes resulting from specific allocations of governmental financial support. Additionally, it explores corporate and cluster characteristics predicted to moderate the influence between governmental financial support and firm performance. The analysis employs a two-level hierarchical linear model (HLM) at individual and group levels. The data, reorganized based on business registration numbers at the firm and cluster levels, ultimately utilized panel data from 83,395 firms and 641 clusters. The research findings indicate that governmental financial support demonstrates a positive effect (+) on both sales and patents for firms, suggesting its effectiveness in complementing market failures. Results from the hierarchical linear model analysis show that when combined with human capital capacity, absorptive capacity, and cluster network density, governmental financial support exhibits significant positive effects on sales. This study contributes theoretical and practical insights by analyzing the relationship between governmental financial support and firm performance using a two-level hierarchical linear model. It highlights the role of corporate characteristics such as human capital and absorptive capacity, along with cluster characteristics like cluster network density, in moderating the effects of governmental financial support on firm performance.

Cluster industries are geographically concentrated and inter-connected by the flow of goods and services, which is stronger than the flow linking them to the rest of the economy. Photonics industries are one of the fastest growing high-tech industries in the world today. Especially, the city of Gwangju(South Korea) industrial cluster, a specialized complex in photonics industry, produced remarkable results in developing high-quality technologies since it launched the cluster program in 2005. Gwangju photonics industrial cluster will be ranked top level of the world photonics industry. In this sense, this study is aimed at proposing a new research model in which corporate performance influence factors of photonics industrial cluster (i.e., business environment, cooperative relationship, and industry-university-research institute partnership) affect absorptive capacity positively, leading to corporate performance eventually. This study developed a research model to explain the Korean photonics industrial cluster effects, and collected 91 survey responses from photonics based company managers in industrial cluster complex. To prove the validity of the proposed research model, PLS analysis is applied with valid 91 questionnaires. By employing PLS technique, the measurement reliability and validity of research variables are tested and the path analysis is conducted to do the hypothesis testing. In brief, the finding of this study suggests that corporate performance influence factors of photonics industrial cluster affect absorptive capacity positively, and corporate performance as well.

Web Map Tile Services (WMTS) have been widely used for quick and convenient sharing of geospatial information. In practice, when streaming requests to servers increase in scale, unacceptable response times and service unavailability might result. To address this scalability problem, we implemented a scalable WMTS framework on a high performance cluster (HPC), enabling the realization of elastic deployment as the client users grow in number. This scalable and high-concurrency WMTS is built totally with open-source software, including Nginx, GeoWebCache, and MongoDB. In this architecture, Nginx acts as a powerful load balancer for routing client requests; GeoWebCache is customized to publish the required WMTS and process client requests; while MongoDB is used to store the large volume of tile images in the HPC. Evaluation experiments were carried out to assess the efficiency and scalability of our WMTS system, using one synthetic workload. Experimental results illustrate that this distributed WMTS framework can achieve about 15% performance improvement when the service nodes are increased with a 0.5~2s reduction in the load time and a 5~10MB increase in network throughput.

In Web Server Cluster (WSC), replication techniques are necessary when providing accesses to data at different locations. In WSC, when designing the cluster architecture, the elements of availability and reliability for cases of data sharing or backing-up data are given the top priority. This is to ensure that the response time and throughput is still within the acceptable range. In ensuring the values of response time and throughput have not surpassed the limit, thus the replication technique must be employed intelligently. The replication technique that is been proposed is based on asynchronous replication technique. In doing so, we have managed to improve the reliability of the web cluster system. We have also managed to control the response time to a very nominal value but at the same time able to provide utmost throughput.

Working with data involves two major factors, storing the data and performing computations by accessing the data. MySQL is the first Database Management Software that provided an effective and efficient method for data storage and computations. However, with the huge amount of data that is getting generated every day from various fields, need for the advanced methods for managing and analyzing the big data is very much obvious. One of such platforms, which were developed exclusively for Big Data Analytics, is Apache Spark. Though MySQL is preferred for small amount of Data and Spark is meant for big data, many of the functionalities are found similar in both and they can be considered for a comparative study. In this work we have executed a set of queries with common functionalities for a dataset on both the frameworks. The obtained results are analyzed by visualizing aids to arrive at appropriate conclusion.

The cluster-based routing protocol (CBRP) is a grouping mechanism that supports unicast and multicast path discovery for low congestion and packet loss in routing mechanisms for multi-hop wireless mesh networks. No simulation analyses or comparisons with other routing protocols have been reported. In this paper, we have evaluated the performance of the CBRP and compared it to AODV and OLSR through software simulations. The scheme indicates several better performance levels in terms of the channel capacity, path discovery, packet delivery ratio, and end-to-end delay, at the sacrifice of routing overhead degradation.

Selection of cohort models plays a vital role to increase the accuracy of a biometric authentication system as well as to reduce the computational cost. This paper proposes a novel approach for cohort selection called Max-Min-Centroid-Cluster (MMCC) method. The clusters of cohorts are generated by K-means clustering technique. The union of the clusters having largest and smallest centroid value is taken as cohort subset. The cohort scores, after normalization using different cohort based score normalization techniques, are used in authentication process of the system. Evaluation has been carried out on FEI face datasets. The performance of this novel methodology is analyzed using T-norm and Aggarwal (max rule) normalization techniques. Experimental results exhibit the efficacy of the proposed method.

Web application server cluster has been widely used to improve the performance of web application servers. Because web load is highly variable, we need to dynamically manage cluster’s deployment so as to reduce power consumption and meanwhile satisfy load performance demand. To facilitate researchers to evaluate a management strategy or choose key parameters for it, we propose a CloudSim-based simulation platform in this paper. It can simulate different cluster deployment algorithm, request scheduling algorithm and load feature, where cluster’s deployment includes the on/off state, CPU frequency and request scheduling parameter(s) of each server. By the aid of HookTimer component, the platform supports periodical and conditional deployment trigger modes, and can calculate some common performance indicators. The usage of interface, dynamic proxy technique and XML configuration file make the platform have good extensibility and configurability. In addition, a request-number-triggered management strategy is proposed and simulated by the platform. The simulation results demonstrate the feasibility of the platform.