• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Smart Structures and Systems
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• v.30 no.6
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.

• Steel and Composite Structures
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• v.43 no.3
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• pp.327-340
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• 2022

A vast amount of experimental and analytical research has been conducted related to the seismic behavior and performance of concrete filled steel tubular (CFT) columns. This research has resulted in a wealth of information on the component behavior. However, analytical and experimental data for structural systems with CFT columns is limited, and the well-known behavior of steel or concrete structures is assumed valid for designing these systems. This paper presents the development of an analytical model for nonlinear analysis of composite moment resisting frame (CFT-MRF) systems with CFT columns and steel wide-flange (WF) beams under seismic loading. The model integrates component models for steel WF beams, CFT columns, connections between CFT columns and WF beams, and CFT panel zones. These component models account for nonlinear behavior due to steel yielding and local buckling in the beams and columns, concrete cracking and crushing in the columns, and yielding of panel zones and connections. Component tests were used to validate the component models. The model for a CFT-MRF considers second order geometric effects from the gravity load bearing system using a lean-on column. The experimental results from the testing of a four-story CFT-MRF test structure are used as a benchmark to validate the modeling procedure. An analytical model of the test structure was created using the modeling procedure and imposed-displacement analyses were used to reproduce the tests with the analytical model of the test structure. Good agreement was found at the global and local level. The model reproduced reasonably well the story shear-story drift response as well as the column, beam and connection moment-rotation response, but overpredicted the inelastic deformation of the panel zone.

• Biomedical Science Letters
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• v.29 no.1
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• pp.11-25
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• 2023

In hepatocellular carcinoma (HCC), chromosome 4 open-reading frame 47 (C4orf47) has not been so far investigated for its prognostic value or association with infiltrating immune cells. We performed bioinformatics analysis on HCC data and analyzed the data using online databases such as TIMER, UALCAN, Kaplan-Meier plotter, LinkedOmics, and GEPIA2. We found that C4orf47 expression in HCC was higher compared to normal tissues. High C4orf47 expression was associated with a worse prognosis in HCC. The correlation between C4orf47 and infiltrating immune cells is positively associated with CD4+T cells, B cells, neutrophils, macrophages, and dendritic cells in HCC. Moreover, high C4orf47 expression was correlated with a poor prognosis of infiltrating immune cells. Analysis of C4orf47 gene co-expression networks revealed that 12501 genes were positively correlated with C4orf47, whereas 7200 genes were negatively correlated. The positively related genes of C4orf47 are associated with a high hazard ratio in different types of cancer, including HCC. Regarding the biological functions of C4orf47 gene, it mainly regulates RNA metabolic process, DNA replication, and cell cycle. The C4orf47 gene may play a prognostic role by regulating the global transcriptome process in HCC. Our findings demonstrate that high C4orf47 expression correlates with poor prognosis and tumor-infiltrating immune cells in HCC. We suggest that C4orf47 is a novel prognostic biomarker and potential immune therapeutic target for HCC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1679-1685
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• 2022

In this paper, we propose an optimal multi-hop transmission scheme to maximize the end-to-end data rate from the source to the destination node in a wireless powered communication network. The frame structure for multi-hop transmission is presented to transmit multi-hop data while harvesting energy. Then, the transmission time of each node that maximizes the end-to-end transmission rate is determined through mathematical analysis in consideration of different harvested energy and link quality among nodes. We derive an optimization problem through system modeling of the considered wireless powered multi-hop transmission, and prove that there is a global optimal solution by verifying the convexity of this optimization problem. This analysis facilitates to find the optimal solution of the considered optimization problem. The proposed optimal multi-hop transmission scheme maximizes the end-to-end rate by allocating the transmission time for each node that equalizes the transmission rates of all links.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.1-8
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• 2005

In this paper, we propose a two-stage head tracking algorithm adequate for real-time active camera system having pan-tilt-zoom functions. In the color convergence stage, we first assume that the shape of a head is an ellipse and its model color histogram is acquired in advance. Then, the min-shift method is applied to roughly estimate a target position by examining the histogram similarity of the model and a candidate ellipse. To reflect the temporal change of object color and enhance the reliability of mean-shift based tracking, the target histogram obtained in the previous frame is considered to update the model histogram. In the updating process, to alleviate error-accumulation due to outliers in the target ellipse of the previous frame, the target histogram in the previous frame is obtained within an ellipse adaptively shrunken on the basis of the model histogram. In addition, to enhance tracking reliability further, we set the initial position closer to the true position by compensating the global motion, which is rapidly estimated on the basis of two 1-D projection datasets. In the subsequent stage, we refine the position and size of the ellipse obtained in the first stage by using shape information. Here, we define a robust shape-similarity function based on the gradient direction. Extensive experimental results proved that the proposed algorithm performs head hacking well, even when a person moves fast, the head size changes drastically, or the background has many clusters and distracting colors. Also, the propose algorithm can perform tracking with the processing speed of about 30 fps on a standard PC.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.27-39
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• 2009

Compulsive consumption is regarded as a global phenomenon that can adversely affect consumer well-being. Although the topic has been studied in different cultural settings, we have seen relatively little theory development and explanations of compulsive behavior Nearly all previous empirical studies attempt to explain this behavior by correlating measures of compulsive behavior with independent variables taken within the same time frame. However, recent developments in social sciences suggest that such a phenomenon may best understood in the context of the person's earlier-in-life experiences. Using the life course paradigm as an overarching framework, the present research extends previous work on this topic. Following hypotheses were drawn from literature review: H1: The earlier in childhood and adolescence a person experiences family dislocation, the greater his or her likelihood of exhibiting compulsive behaviors in adulthood. H2: The earlier in life the young person experienced family dislocation, the greater the number of family disruption events the young person experienced prior entering adulthood years. H3: Family dislocation leads to (a) increased frequency of socio.oriented family communications and (b) decreased frequency of concept-oriented family communication. H4: Young adults who were raised in families characterized by a strong socio-oriented communication structure are more likely to exhibit compulsive consumption tendencies than those who were raised in families characterized by a weak socio-oriented family communication structure. H5: Young adults who were raised in families characterized by a strong concept-oriented communication structure are less likely to exhibit compulsive consumption tendencies than those who were raised in families characterized by a week concept-oriented family communication structure. H6: The relationship between family disruption events experienced during adolescence and perceived stressfulness of these events is moderated by (a) global family support, (b) emotional family support, and (c) material family support. Those reporting higher levels of family support as teenagers are less likely to report experiencing stress due to family disruption events. H7: Perceived stressfulness of family disruption events experienced during adolescent years are associated with compulsive consumption tendencies in early adulthood. H8: The greater the number of family disruption events young adults experienced during their adolescent years the more frequent was their communication about consumption with their peers. H9: The more frequent was the young persons' communication with their peers about consumption during their adolescent years, the more likely they are to report compulsive buying tendencies as young adults. We use a sample of 120 Thai undergraduate students attending classes taught in English as part of a four-year international program. Product-moment correlations, hierarchical regression analysis and partial correlation were used to analyze data. Results of testing hypotheses showed that hypothesis 2, 4, 7 and 9 were supported and hypothesis 1, 3, 5, 6 and 8 were not supported. Our study did not find a significant relationship between the age when a person experienced family dislocation and their compulsive behavior tendencies expressed as young adults. We did not find a significant relationship between family dislocation and family communication structures. But we found a significant positive relationship between socio-oriented communication structure and compulsive buying and a significant relationship between our peer communication and compulsive buying measures. Also we found perceived stressfulness due to the disruptive events to have a significant positive relationship between the perceived stressfulness and compulsive buying. Implications from these findings, limitations of this research and future research suggestions were discussed.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.73.2-74
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• 2015

The gas cloud G2 falling toward Sagittarius A* (Sgr A*), the supermassive black hole at the center of the Milky Way, is supposed to provide valuable information on the physics of accretion flows and the environment of the black hole. We observed Sgr A* with four European stations of the Global Millimeter Very Long Baseline Interferometry Array (GMVA) at 86 GHz on 1 October 2013 when parts of G2 had already passed the pericenter. We searched for possible transient asymmetric structure - such as jets or winds from hot accretion flows - around Sgr A* caused by accretion of material from G2. The interferometric closure phases (which are zero if the spatial brightness distribution of the target is symmetric, and deviate from zero otherwise) remained zero within errors during the observation time. We thus conclude that Sgr A* did not show significant asymmetric (in the observer frame) outflows in late 2013. Using simulations, we constrain the size of the outflows that we could have missed to ${\approx}2.5$ mas along the major axis, ${\approx}0.4$ mas along the minor axis of the beam, corresponding to approximately 232 and 35 Schwarzschild radii, respectively; we thus probe spatial scales on which the jets of radio galaxies are suspected to convert magnetic into kinetic energy. As probably less than 0.2 Jy of the flux from Sgr A* can be attributed to accretion from G2, one finds an effective accretion rate ${\eta}M{\leq}1.5{\times}10^9kg/s{\approx}7.7{\times}10^{-9}M_{earth}/yr$ for material from G2. Exploiting the kinetic jet power-accretion power relation of radio galaxies, one finds that the rate of accretion of matter that ends up in jets is limited to $M{\leq}10^{17}kg/s{\approx}0.5M_{Earth}/yr$ less than about 20% of the mass of G2. Accordingly, G2 appears to be largely stable against loss of angular momentum and subsequent (partial) accretion at least on time scales ${\leq}1$ year.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.1
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• pp.99-110
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• 2013

This study analyzed universities's entrepreneurship education curriculum and variety programs through visiting to five entrepreneurship centers. Through these analyzes, the study presents a basic frame work for prosperous entrepreneurship education in Korea. We have selected for visiting research universities in the middle east of the United states; University of Iowa, University of Missouri(Kansas City), Saint Louis University, University of Louisville and George Washington University. We visited entrepreneurship center of each university in order to have in-depth interview with professor who is responsible for building entrepreneurship curriculum and administrative director of entrepreneurial programs so that we research how university progresses entrepreneurship education at undergraduate level. The study, at the time of 61 universities selected for LINC project by the Korea Ministry of Education who expects Industrial-Academia cooperative effects just installed each entrepreneurship center, analyzed case study of operational practice and entrepreneurship education curriculum for the effective operation of entrepreneurship centers in universities. We believe that the study will be able to provide a richer and more accurate information and ideas since the all the analysis is based on the firsthand interview by visiting.