• Smart Media Journal
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• v.5 no.3
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• pp.74-80
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• 2016

In this paper, we propose an accident-prevention smart monitoring system for Haenyeo(Woman diver) using Zigbee module and GPS sensor. This system can collect such information as the diving location, the body temperature, the depth of diving, and the diving time of a Woman diver working under the water and then respond immediately to an accident occurring. The research developed a smart Teawak and smart swimming goggles which can measure the state of a Woman diver and her diving activities. Smart Teawak, the buoy tool while a Woman diver is collecting seafoods under water, is able to receive GPS and transmit the data from smart swimming goggles and Zigbee Module to IHSS(IoT based Haenyeo Safety service Software) server. In addition, IHSS, a responsive web, provides the diving location and the state of a Woman diver on the smart phone. As a result, the system will be useful in the aspects of Woman diver' health care and the safety, furthermore, which will significantly contribute to global marketing of Woman diver with its being designated as a UNESCO intangible cultural asset.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.739-748
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• 2014

In this paper, we propose pyramid appearance and global structure action descriptors on both RGB and depth motion history images and a model-free method for human action recognition. In proposed algorithm, we firstly construct motion history image for both RGB and depth channels, at the same time, depth information is employed to filter RGB information, after that, different action descriptors are extracted from depth and RGB MHIs to represent these actions, and then multimodality information collaborative representation and recognition model, in which multi-modality information are put into object function naturally, and information fusion and action recognition also be done together, is proposed to classify human actions. To demonstrate the superiority of the proposed method, we evaluate it on MSR Action3D and DHA datasets, the well-known dataset for human action recognition. Large scale experiment shows our descriptors are robust, stable and efficient, when comparing with the-state-of-the-art algorithms, the performances of our descriptors are better than that of them, further, the performance of combined descriptors is much better than just using sole descriptor. What is more, our proposed model outperforms the state-of-the-art methods on both MSR Action3D and DHA datasets.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.379-388
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• 2019

Recently, a technique for acquiring spatial information data using UAV (Unmanned Aerial Vehicle) has been greatly developed. It is a very crucial issue of the GIS (Geographic Information System) mapping system that passes way point in the unmanned airframe and finally measures the accurate image and stable localization to the desired destination. Though positioning using DGPS (Differential Global Navigation System) or RTK-GPS (Real Time Kinematic-GPS) guarantee highly accurate, they are more expensive than the construction of a single positioning system using a single GPS. In the case of a low-priced single GPS system, the stability of the positioning data deteriorates. Therefore, it is necessary to supplement the uncertainty of the absolute position data of the UAV and to improve the accuracy of the current position data economically in the operating state of the UAV. The aim of this study was to present an algorithm enhancing the stability of position data in a single GPS mode of UAV with multiple GPS. First, the arrangement of multiple GPS receivers through the center of gravity of the UAV were examined. Next, MD (Mahalanobis Distance) is applied to detect instantaneous errors of GPS data in advance and eliminate outliers to increase the accuracy of previously collected multiple GPS data. Processing procedure for multiple GPS reception data by applying the center of the triangular method were presented to improve the position accuracy. Second, UAV navigation systems integrated multiple GPS through configuration of the UAV specifications were implemented. Using the unmanned airframe equipped with multiple GPS receivers, GPS data is measured with the TCM (Triangular Center Method). In addition, UAV equipped with multiple GPS were operated in study area and locational accuracy of multiple GPS of UAV with VRS (Virtual Reference Station) GNSS surveying were compared. The result showed that the error factors are compensated, and the error range are reduced, resulting in the reliability of the corrected value. In conclusion, the result in this paper is expected to realize high-precision position estimation at low cost in UAV using multiple low-cost GPS receivers.

• Journal of Convergence for Information Technology
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• v.8 no.4
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• pp.225-230
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• 2018

Despite a quantitative increase in the export of small and medium sized businesses due to various policies supporting export that have been continually promoted by the government, the majority of export growth has been centered around conglomerates. As research has shown that export companies are superior in terms of job creation and growth compared to domestic companies, the conversion of domestic companies to export companies will not only result in job creation and increase in exports, but it will also enable the improvement of such companies. It is therefore important to support the export of small and medium sized businesses and maintain their status as export companies with supporting policies. The purpose of this study is to analyze the present state of the export environment of Korean and foreign small and medium sized businesses in order to elicit ideas for establishing strategies for the promotion of export and maintaining the status as an export company.

• Journal of Neurogastroenterology and Motility
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• v.24 no.4
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• pp.512-527
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• 2018

This review provides a comprehensive overview of brain imaging studies of the brain-gut interaction in functional gastrointestinal disorders (FGIDs). Functional neuroimaging studies during gut stimulation have shown enhanced brain responses in regions related to sensory processing of the homeostatic condition of the gut (homeostatic afferent) and responses to salience stimuli (salience network), as well as increased and decreased brain activity in the emotional response areas and reduced activation in areas associated with the top-down modulation of visceral afferent signals. Altered central regulation of the endocrine and autonomic nervous responses, the key mediators of the brain-gut axis, has been demonstrated. Studies using resting-state functional magnetic resonance imaging reported abnormal local and global connectivity in the areas related to pain processing and the default mode network (a physiological baseline of brain activity at rest associated with self-awareness and memory) in FGIDs. Structural imaging with brain morphometry and diffusion imaging demonstrated altered gray- and white-matter structures in areas that also showed changes in functional imaging studies, although this requires replication. Molecular imaging by magnetic resonance spectroscopy and positron emission tomography in FGIDs remains relatively sparse. Progress using analytical methods such as machine learning algorithms may shift neuroimaging studies from brain mapping to predicting clinical outcomes. Because several factors contribute to the pathophysiology of FGIDs and because its population is quite heterogeneous, a new model is needed in future studies to assess the importance of the factors and brain functions that are responsible for an optimal homeostatic state.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.186-198
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• 2021

The introduction of digital technologies affects most socio-economic processes and activities in the economy, from agriculture to public services. Even though the world is currently only in the early stages of digital transformation, the digital economy is growing rapidly, especially in developing countries. Shortly, digital platforms will be able to replace the "invisible hand" of the market and turn it into digital. Some digital platforms have already reached global reach in some sectors of the economy. The growing value of data and artificial intelligence is reflected in the high capitalization of these enterprises. Their growing role has far-reaching consequences for the organization of economic activity and integration into the field of e-business. However, their importance and level of development in different countries differ significantly. The main purpose of this article is an assessment of the level and trends of the digital economy in the world and the identification of homogeneous groups of states following the main trends in the development of its components from among the EU countries. The methodology of the conducted research is based on the use of general scientific research methods in the analysis of secondary sources and the application of statistical methods of correlation-regression and cluster analysis. Macroeconomic indicators and components of DESI (Digital Economy and Society Index) were used for the analysis. Results. Based on the analysis established that most developed countries have a medium level of digitalization of the business environment and a high level of digitalization of socially oriented public services, while countries with lower GDP focus their policies on building digital infrastructure and training qualified personnel. The study summarizes and analyzes current trends in digital technology, analyzes the level and dynamics of integration of digital technologies of the studied EU countries, the level of development of e-business and e-commerce. The conceptualization of mechanisms of creation of added value in the digital economy is offered and the possible consequences of digitalization of the economy of developing countries are generalized.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.151-159
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• 2021

This article addresses the issue of finding optimal solutions using the information technologies of accounting and analysis in modern companies. The aim of the study is to reveal available information technologies for the needs of small, medium and large businesses operating in modern conditions. This goal is achieved by using systematization, comparison, and analysis of information, obtained under the survey and open management statistics. For the first time, the paper systematizes up-to-date information of 2021 about the most popular programs, online services, platforms and cloud services that are used to improve accounting and analytical processes in enterprises of various sizes. The main global trends in software development in terms of COVID-19 pandemic have been identified. In particular, the study defines the countries that occupy the leading positions in the informatization of business processes. An attempt was made to classify information technologies by their use by various volume of businesses. The analysis of research results of the Internet search query frequency regarding the use of information technologies enabled to determine the most popular software products worldwide. The peculiarities of information technologies, their advantages and disadvantages were examined and the common and distinctive features were compared. It was determined that for the new enterprises to implement information technologies, it is necessary to conduct a step-by-step study of all available software products. The software evaluation algorithm was described to help select the optimal software for the specific business processes. The paper also describes the way to solve the problem of using accounting and analysis software for the businesses of a specific kind of activity.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.109-116
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• 2022

The energy corporation of Kosovo continuously monitors and analyzes the impact of its own activities on the environment. Regarding the environmental situation, energy corporation of Kosovo- ECK regularly informs and reports objectively to the competent state institutions, local municipal institutions and interested parties. ECK, through numerous contacts with the competent authorities, firstly with different ministers, harmonizes the positions regarding environmental issues in the direction of achieving certain environmental standards or legal requirements in order to gradually be in accordance with them, based on the real possibilities, especially the financial ones. From this point of view, the environmental issue is very sensitive, quite complex and represents one of the biggest challenges of society currently and in the future. The researched variables show a continuous increase in the need for electricity production in Kosovo and this increase in production conditions a wide range of environmental impacts both at the local, regional and global levels. The aim of the work is to reduce the emission of pollutants through the main variables without inhibiting the economic development of the country, i.e. to bring the pollution as a result of the activities of the ECK operation into compliance with the permitted environmental norms. As a result of ECK's operational activities, the following follows: Air pollution mainly as a result of emissions from TCs in the air, transport, etc. Water pollution - as a result of technological water discharges, Land degradation - as a result of surface mining activities of the entire mining area. The purpose of the paper is to research and analyze the main water variables in the area of the Kosova B power plant, which is to determine the degree of their pollution from the activities of the power plants, as well as to assess the real state of surface water quality and control the degree of pollution of these waters. Methodology of the work: The analyzes of the water samples were done in the company Institute "INKOS" JSC by simultaneous methods using different reagents.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.175-181
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• 2022

COVID-19 is an acute respiratory syndrome that affects the host's breathing and respiratory system. The novel disease's first case was reported in 2019 and has created a state of emergency in the whole world and declared a global pandemic within months after the first case. The disease created elements of socioeconomic crisis globally. The emergency has made it imperative for professionals to take the necessary measures to make early diagnoses of the disease. The conventional diagnosis for COVID-19 is through Polymerase Chain Reaction (PCR) testing. However, in a lot of rural societies, these tests are not available or take a lot of time to provide results. Hence, we propose a COVID-19 classification system by means of machine learning and transfer learning models. The proposed approach identifies individuals with COVID-19 and distinguishes them from those who are healthy with the help of Deep Visual Embeddings (DVE). Five state-of-the-art models: VGG-19, ResNet50, Inceptionv3, MobileNetv3, and EfficientNetB7, were used in this study along with five different pooling schemes to perform deep feature extraction. In addition, the features are normalized using standard scaling, and 4-fold cross-validation is used to validate the performance over multiple versions of the validation data. The best results of 88.86% UAR, 88.27% Specificity, 89.44% Sensitivity, 88.62% Accuracy, 89.06% Precision, and 87.52% F1-score were obtained using ResNet-50 with Average Pooling and Logistic regression with class weight as the classifier.

• Journal of Korea Trade
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• v.26 no.6
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• pp.118-135
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• 2022

Purpose - The purpose of this study is to investigate the relationships among Chinese state-owned enterprises (SOEs), previous M&A experience, and the probability of deal completion in cross-border mergers and acquisitions (CBMAs). Since Chinese SOEs tend to be recognized by host countries as agents of their home country government, this study argues that SOEs will face difficulties in completing CBMA deals. However, the study expects that these difficulties may vary depending on whether the firm has previous M&A experience because firms can gain the knowledge and capabilities necessary to implement subsequent M&As successfully from past M&A experience. Design/methodology - To investigate our argument, we conduct a logistic regression using a sample of 363 CBMA deals from 304 Chinese publicly listed firms during 2007 to 2017. We used SOEs as an independent variable, experience of domestic and foreign M&As as moderating variables, respectively, and CBMA deal completion as the dependent variable. Findings - The study shows a negative and significant relationship between Chinese SOEs and the completion likelihood of CBMA deals. We find that this negative relationship is strengthened when the firm had prior domestic M&A experience, whereas foreign M&A experience alleviated the negative relationship. Originality/value - The issue of government ownership has remained unclear since government intervention has both advantages and disadvantages in pursuing CBMAs. Our findings support literature that argues Chinese SOEs face legitimacy concerns in the host countries, thereby lowering their CBMA deal completion likelihood. Furthermore, the study enriches the literature by identifying different moderating effects of domestic and foreign M&A experience on the negative relationship between SOEs and CBMA deal completion.