In this paper, we propose soft dead pixels detection method by analysing different response at hot and cold images. Abnormal pixels are able to effect detecting a small target. It also makes confusing real target or not cause of changing target size. Almost exist abnormal pixels after image signal processing even if dead pixels are removed by dead pixel compensation are called soft dead pixels. They are showed defect in final image. So removing or compensating dead pixels are very important for detecting object. The key idea of this proposed method, detecting dead pixels, is that most of soft deads have different response characteristics between hot image and cold image. General infrared cameras do NUC to remove FPN. Working 2-reference NUC must be needed getting data, hot & cold images. The way which is proposed dead pixel detection is that we compare response, NUC gain, at each pixel about two different temperature images and find out dead pixels if the pixels exceed threshold about average gain of around pixels.

The Ministry of National Defense announced 'Defense Reform 2.0' that aims to strengthen the country's security for decrease of regional uncertainties, growing requirements for advanced technologies, and a need for more efficiency in the Republic of Korea(RoK) Armed Forces this year. It said RoK Armed Forces have to change efficiently in preparation for rapid decline in military service resources as demographic cliff turning into reality, and the rapid evolution of the "battlefield environment" caused by developments in military science and technologies. RoK Navy combat Management System(CMS) made by domestic proprietary technology since 2000s and development centered on Agency for Defense Development require design changes for added requirements. So in this paper, I propose method of design a low cost and high efficiency navy CMS architecture based on high performance server and virtualization technology. And I create a test environment for analysis performance and compare the performance of proposed navy CMS and existing navy CMS.

Today, we are living in the era of data and information. With the advent of Internet of Things (IoT), the popularity of social networking sites, and the development of mobile devices, a large amount of data is being produced in diverse areas. The collection of such data generated in various area is called big data. As the importance of big data grows, there has been a growing need to share big data containing information regarding an individual entity. As big data contains sensitive information about individuals, directly releasing it for public use may violate existing privacy requirements. Thus, privacy-preserving data publishing (PPDP) has been actively studied to share big data containing personal information for public use, while preserving the privacy of the individual. K-anonymity, which is the most popular method in the area of PPDP, transforms each record in a table such that at least k records have the same values for the given quasi-identifier attributes, and thus each record is indistinguishable from other records in the same class. As the size of big data continuously getting larger, there is a growing demand for the method which can efficiently anonymize vast amount of dta. Thus, in this paper, we develop an efficient k-anonymity method by using Spark distributed framework. Experimental results show that, through the developed method, significant gains in processing time can be achieved.

Pattern classification system is often an important component of intelligent systems. In this paper, we present a pattern classification system consisted of the feature selection module, knowledge base construction module and decision module. We introduce a feature impact evaluation selection method based on fuzzy cluster analysis considering computational approach and generalization capability of given data characteristics. A fuzzy neural network, OFUN-NET based on unsupervised learning data mining technique produces knowledge base for representative clusters. 240 blemish pattern images are prepared and applied to the proposed system. Experimental results show the feasibility of the proposed classification system as an automating defect inspection tool.

Text classification has been studied for a long time in the Natural Language Processing field. In this paper, we propose an article- and paragraph-level genre classification system using Word2Vec-based LSTM, GRU, and CNN models for large-scale English corpora. Both article- and paragraph-level classification performed best in accuracy with LSTM, which was followed by GRU and CNN in accuracy performance. Thus, it is to be confirmed that in evaluating the classification performance of LSTM, GRU, and CNN, the word sequential information for articles is better than the word feature extraction for paragraphs when the pre-trained Word2Vec-based word embeddings are used in both deep learning-based article- and paragraph-level classification tasks.

In this paper, we propose a displacement measurement method based on deep learning using image data obtained from tensile tests of a material specimen. We focus on the fact that the sequential images during the tension are generated and the displacement of the specimen is represented in the image data. So, we designed sample generation model which makes sequential images of specimen. The behavior of generated images are similar to the real specimen images under tensile force. Using generated images, we trained and validated our model. In the deep neural network, sequential images are assigned to a multi-channel input to train the network. The multi-channel images are composed of sequential images obtained along the time domain. As a result, the neural network learns the temporal information as the images express the correlation with each other along the time domain. In order to verify the proposed method, we conducted experiments by comparing the deformation measuring performance of the neural network changing the displacement range of images.

In this paper, we studied about the extraction of the parameter and implementation of speechreading system to recognize the Korean 8 vowel. Face features are detected by amplifying, reducing the image value and making a comparison between the image value which is represented for various value in various color space. The eyes position, the nose position, the inner boundary of lip, the outer boundary of upper lip and the outer line of the tooth is found to the feature and using the analysis the area of inner lip, the hight and width of inner lip, the outer line length of the tooth rate about a inner mouth area and the distance between the nose and outer boundary of upper lip are used for the parameter. 2400 data are gathered and analyzed. Based on this analysis, the neural net is constructed and the recognition experiments are performed. In the experiment, 5 normal persons were sampled. The observational error between samples was corrected using normalization method. The experiment show very encouraging result about the usefulness of the parameter.

Data Distribution Service(DDS) provides the communications service programmers need to distribute time-critical data between embedded and/or enterprise devices or nodes. In this paper, I propose efficient methods for transmitting and receiving messages of various characteristics in real-time using DDS middleware. For high-frequency characteristic data, I describe several DDS packet types and various default and extended DDS QoS policies. In particular, the batching method is probably the best solution when considering several performance aspects. For large-capacity characteristic data. I will show a method using extended DDS QoS policies, a segmentation and reassembly method, and transmitting and receiving a large-capacity data with low priority method considering network conditions. Finally, I simulate and compare the result of performance for each methods. This results will help determine efficient methods for transmitting and receiving messages of various characteristics using DDS middleware.

The verification for the design limit margin of the power device for the information communication and surveillance systems using HALT(Highly Accelerated Life Test) reliability test is described. The HALT reliability test performs with a step stress method which change condition until the marginal step in a design and development phase. The HALT test methods are the low temperature(cold) step stress test, the high temperature(hot) step stress test, the thermal shock cyclic stess test, and the high temperature destruct limit(hot DL) step stress test. The power device is checked the operating performance during the test. In this paper, the HALT was performed to find out the design limit margin of the power device.

Social engineering attack means to get information of Social engineering attack means to get information of opponent without technical attack or to induce opponent to provide information directly. In particular, social engineering does not approach opponents through technical attacks, so it is difficult to prevent all attacks with high-tech security equipment. Each company plans employee education and social training as a countermeasure to prevent social engineering. However, it is difficult for a security officer to obtain a practical education(training) effect, and it is also difficult to measure it visually. Therefore, to measure the social engineering threat, we use the results of social engineering training result to calculate the risk by system asset and propose a attack graph based probability. The security officer uses the results of social engineering training to analyze the security threats by asset and suggests a framework for quick security response. Through the framework presented in this paper, we measure the qualitative social engineering threats, collect system asset information, and calculate the asset risk to generate probability based attack graphs. As a result, the security officer can graphically monitor the degree of vulnerability of the asset's authority system, asset information and preferences along with social engineering training results. It aims to make it practical for companies to utilize as a key indicator for establishing a systematic security strategy in the enterprise.

In recent years, there has been an increasing number of ways to distribute document-based malicious code using vulnerabilities in document files. Because document type malware is not an executable file itself, it is easy to bypass existing security programs, so research on a model to detect it is necessary. In this study, we extract main features from the document structure and the JavaScript contained in the stream object In addition, when JavaScript is inserted, keywords with high occurrence frequency in malicious code such as function name, reserved word and the readable string in the script are extracted. Then, we generate a machine learning model that can distinguish between normal and malicious. In order to make it difficult to bypass, we try to achieve good performance in a black box type algorithm. For an experiment, a large amount of documents compared to previous studies is analyzed. Experimental results show 98.9% detection rate from three different type algorithms. SVM, which is a black box type algorithm and makes obfuscation difficult, shows much higher performance than in previous studies.

In this paper, we propose an efficient friendly forces location data sharing algorithm in a troops using a low bandwidth radio. The future battlefield is a 'Network Centric Warfare' with a concept of identifying the position and power of the enemy and friendly forces and leading the battlefield to victory through proper links at the time of our need. One of the basic elements in the 'Network Centric Warfare' is to share friendly forces location data. The bandwidth and transmission rates of radio used in battalion are low. Nevertheless, we should share our locations data almost in real time for effective fighting in a war situation. This paper describes the efficient method of friendly forces location data sharing based on low bandwidth radio. In particular, the concept of 'network-centered warfare' is reflected in the troop below the battalion to present an integrated and efficient way to shared location data of friendly forces.

This paper presents an idea and framework to automate a full cycle business process management and re-engineering by integrating traditional business process management systems, process mining, data mining, machine learning, and simulation. We build our framework on the cloud-based platform such that various data sources can be incorporated. We design our systems to be extensible so that not only beneficial for practitioners of BPM, but also for researchers. Our framework can be used as a test bed for researchers without the complication of system integration. The automation of redesigning phase and selecting a baseline process model for deployment are the two main contributions of this study. In the redesigning phase, we deal with both the analysis of the existing process model and what-if analysis on how to improve the process at the same time, Additionally, improving a business process can be applied in a case by case basis that needs a lot of trial and error and huge data. In selecting the baseline process model, we need to compare many probable routes of business execution and calculate the most efficient one in respect to production cost and execution time. We also discuss the challenges and limitation of the framework, including the systems adoptability, technical difficulties and human factors.

The purpose of this study was to investigate the bodice prototype method suitable for the upper body shape of old-old aged women using the 3D anthropometric data. And it was to provide the basic data for the upper body garments of old-old aged women. In the overall appearance evaluation, the B pattern was rated as 4.00, and it was evaluated as the most suitable for the bodice prototype of the old-old aged woman. The E pattern was rated lower than normal, and the L pattern and the S pattern were found to be inadequate for older female bodice prototypes. As a result of the measurement of the waist and bust air gap of bodice prototype, the air gap of the bust was not significantly different between the patterns. But the waist air gap showed the largest difference between the L pattern and the S pattern. As a result of evaluating the appearance, the amount of space in the state of 3D simulation, and the air gap, the pattern B appeared to be the most appropriate prototype for the old-old aged women's body shape. However, there is a tendency that the shoulder end point is biased toward the back, so it is necessary to set the inclination of the back shoulder line to be more gentle. Conversely, the front shoulder should be more inclined. In the case of the 3D simulation, the B pattern showed that the other parts generally fit well. In the case of the 3D simulation program used in this study, it was evaluated that it is suitable only for the normal body shape because it is impossible to set the isometric angle which is one of the characteristics of the older female body shape. A study on the bodice prototype suitable for the bent body shape should be carried out through experiments on the actual body shape of various elderly women. In order to cope with the increase of elderly people who are familiar with digital, I think it is necessary to develop an avatar that reflects the old female body shape.

When the injection molding system molds some plastic products, defective product rate will be increased if plastic materials have some excessive moisture content. Therefore, it is very important to control the dehumidification and drying of plastic material. Since the moisture content of the plastic material may change from time to time depending on the material and the molding process, it is necessary to observe the change in real time and maintain a constant moisture content. To solve these problems, I proposed a smart factory system model for plastic molding in this paper. In addition, I designed the interface module to be installed in the dehumidifying dryer which is the core of this process. In addition to this, performance tests were conducted to check the effectiveness and the results were verified as valid.

In this study, we designed a model that can measure the level of user's concentration by measuring and analyzing EEG data of the subjects who are performing Continuous Performance Test based on visual stimulus. This study focused on alpha and beta waves, which are closely related to concentration in various brain waves. There are a lot of research and services to enhance not only concentration but also brain activity. However, there are formidable barriers to ordinary people for using routinely because of high cost and complex procedures. Therefore, this study designed the model using the portable EEG measurement device with reasonable cost and Visual Continuous Performance Test which we developed as a simplified version of the existing CPT. This study aims to measure the concentration level of the subject objectively through simple and affordable way, EEG analysis. Concentration is also closely related to various brain diseases such as dementia, depression, and ADHD. Therefore, we believe that our proposed model can be useful not only for improving concentration but also brain disease prediction and monitoring research. In addition, the combination of this model and the Brain Computer Interface technology can create greater synergy in various fields.

The purpose of this study is to contribute to the improvement of indoor air quality management in dental clinic by investigating the level of indoor air quality recognition among dental clinic workers. The questionnaire survey was conducted for about 4 weeks from May 20 to June 20, 2018 in dental clinics located in Jeollanamdo area and 143 were used as the analysis data. The method of indoor air quality management in dental clinic was preferred to "natural ventilation" method and the number of natural ventilation was 1 to 2 times per day and the results of survey on indoor environment satisfaction showed that satisfaction level was lowest in noise and smell items. The types of subjective symptoms experienced by workers working at dental clinics are "cough", "eye burn", and "headache" and a survey on the degree of the relationship between subjective symptoms and indoor air quality showed that 94.4% (135) of respondents answered "very relevant" and "slightly related". As a result of multiple regression analysis, the variables affecting the indoor air quality satisfaction of the dental clinic staff were analyzed as the items such as lighting, noise, main work, number of patients, comparing indoor and outdoor air quality and among them, "comparing indoor and outdoor air quality" was analyzed as having a great influence. To improve the indoor air quality satisfaction of dental clinic worker adequate ventilation, designate the person responsible for the indoor air quality management and periodic measurement efforts will be necessary.

The purpose of this study is to propose a management method to maintain the pleasant indoor air quality of the dental clinic by measuring and analyzing the indoor air quality of the dental clinic. The measurement was conducted in two rooms, a lobby where many residents stay in the reception room for waiting for medical treatment, and a VIP room where treatment activities are mainly performed. Measurement items are Temperature, Humidity, $CO_2$, CO, $NO_2$, $CH_2O$, VOC, $PM_{10}$ and measurement were taken on April 27, 2018. As a result of analyzing the temperature and humidity of the dental clinic, it was analyzed that the average indoor temperature was maintained at $25^{\circ}C$ and the humidity was kept at around 50%, maintaining proper indoor temperature and humidity environment. $CO_2$ was 855ppm in the VIP Room, which satisfied the maintenance standard. In the case of the lobby, it was analyzed to be 1,160ppm, which exceeded the maintenance standard and it is judged that the carbon dioxide generated by the respiration of the people staying in the lobby is the main reason. The mean concentration of formaldehyde in the VIP room was analyzed as $436{\mu}g/m^3$, exceeding the maintenance standard, and $2,100{\mu}g/m^3$ for the VOC exceeded the recommended standard. It was analyzed that the concentration was relatively higher due to the use of disinfectant and other drugs. The mean concentration of PM-10 in the lobby was analyzed as $65{\mu}g/m^3$ and it was analyzed that it satisfied the maintenance standard. To maintain a pleasant indoor air quality in a dental clinic it is necessary to minimize the effects of formaldehyde, VOC, $CO_2$ in the VIP rooms and lobby. For this purpose, the entire ventilation system and air purification system of the dental clinic should be installed. In case of the VIP room, local exhaust ventilation should be installed and workers should wear personal protective equipment.

As the competition of 21 cyber universities in Korea has been on a continual increase, they are focusing on improving the quality of the e-learning education in cyber universities. In this study, we intended to derive the failure factors of the previous chatting system in the 2010s and the success factors from previous studies. Next, we identified priorities among five factors(Reliability, UI Convenience, Usability, Network effect, Operational policy) using AHP and the practical ways to implement the chatting service. We applied the chatting system to all the curriculums of S cyber university. Our study finds that the chat service affects the satisfaction of education. Finally, we propose the utilization plan to improve the e-learning education of cyber university through the findings of this research.

In this study, it is analyzed that keywords of the interest in the 4th industrial revolution for science and Technician K women's university students, areas to prioritize in the strategy of 4th industry revolution, to research compare analyze the recognition of science technology such as the most necessary education, human resource development of universities and companies in Korea and abroad according to the technology trend required in the 4th Industrial revolution era and which area to prepare for the 4th industrial revolution. The survey result shows different thoughts of science and Technician(KOFST) and the women university students. In the 1) 4th industrial revolution, the 96% of former are interested, while 60% of latter are interested. And in the most used keywords, the former group used AI(24%), Fusion new industry(21%) the most, while the latter group used AI(34%), Robot(18%). And, 3) in the strategic priority, the science technology experts are interested in education, R&D system innovation(27%), IoT, Information and Communication(26%) and the university students are interested in IoT, Information and Communication(31%), AI(28%). Finally, 4) the science technology experts thought of Autonomous Vehicle(20%), 3D Printer(7%), AI(16%) important, while the women university students thought of AI(27%), VR/Augmented Reality(17%), and Autonomous Vehicle(16%) the most necessary education. In the 4th industrial revolution, we need people with ability to solve complicated problems with creativity based on understanding and absorbing new knowledge and thinking of converged idea.

The Korean government announced its goal of commercializing autonomous vehicle by year 2020. With such changes, it is expecting to decrease car accident mortality by half. To commercialize autonomous car, not only worries on safety of autonomous vehicle has to be solved but at the same time, institutional system has to be clear to distinguish legal responsibilities in case of accident. This paper will present the legal improvement direction of the introduction of autonomous vehicles as follows. First, it is necessary to re-establish concept of 'driver' institutionally. Second, it is appropriate to focus on Level 3 autonomous vehicle which is about to be commercialized in year 2020 and organize legal responsibility. Third, we should have a clear understanding on how level 3 autonomous vehicle will be commercialized in the future. Fourth, it is necessary to revise The Traffic Law, Act on Special Cases concerning the Settlement of Traffic Accident, and Automobile Accident Compensation Security Law in line with level 3 autonomous vehicle. Fifth, it is necessary to review present car insurance system. Sixth, present Product Liability Law is limited to movable products (Article 2), however, it is necessary to include intangible product which is software. Seventh, we should review on making special law related to autonomous car including civil, criminal, administrative, and insurance perspectives.

In modern society, the optimal physical environment is constantly changing due to IT development, and it is provided with convenience. In this age environment, the children are growing up thinking that the value of community consciousness through relationship with others is not important in the social reality in which various ways and environments that can be done by themselves are succeeding. No matter how rapidly the world changes, a diverse learning environment is needed that establishes desirable human relationships and recognizes community consciousness and values. The purpose of this study was to investigate the effects of general children(elementary school 4th, 5th, and 6th graders) on the communication and peer relationship of the children participating in the archery experiential learning program, to emphasize the importance of physical activity programs, and also by analyzing the relationship between communication and improvement of peer relationship and to understand the effect of the archery experiential training learning which is one of exercise program. In order to verify the research problems, 30 experimental group and 30 comparative group were composed of 4th, 5th, and 6th grade elementary schools in Gwangsan-gu, Gwangju metropolitan city. The experiment group was participated in the archery experiential learning program for a total of 10 sessions, once a week for 60 minutes, and conducted a questionnaire survey. In this study, we examined the effect of archery experiential learning program on improving children 's communication and peer relationship ability. Thus, it showed that archery experiential learning program can be one of the important educational methods to promote the healthy character and development of children.

The purpose of this study is to present effective basic data for business management through analysis of importance and performance of personal information protection of the elderly welfare center workers. For this purpose, the questionnaire on the protection of personal information was reconstructed based on the diagnostic level of the personal information security management level of the public institution and the questionnaire was conducted on 105 employees of the elderly welfare center in Chungbuk area. Based on the responses to the importance and the degree of performance of the personal information protection of the elderly welfare center employees, technical statistics and corresponding sample T-tests were conducted and the importance-performance analysis (IPA) was used. Followings are the results of this study: First, there is a statistically significant difference between the importance and the implementation of the management system for the protection of personal information of the workers in the elderly welfare center, establishment and implementation of protection measures, establishment and implementation of infringement measures. Second, IPA analysis on the protection of personal information of the workers in the elderly welfare center shows that the establishment and implementation of protection measures are the areas to maintain good performance. Third, in IPA analysis of the sub-factors of the personal information protection of the workers in the welfare center of the elderly, in the construction and management of the management system, in performing the role of the personal information protection officer and establishing and implementing protection measures, The factors of prevention of information disclosure and exposure and the safe use and management of personal information processing system were analyzed as areas requiring intensive improvement. This study is meaningful as a basic research that can raise the awareness of the personal information protection of the workers in the elderly welfare center and induce the improvement of the related work.

In this paper, we extracted relevant patent data and conducted statistical analysis to understand the technical development trend related to Wireless Power Transfer (WPT) for Light Rail Transit (LRT). Recently, with the development of WPT technologies, the Light Rail Transit (LRT) industry is concentrating on applying WPT to the power supply system of trains because of their advantages compared wired counterpart, such as low maintenance cost and high stability. This technology is divided into three areas: wireless feeding and collecting technology, high-frequency power converter technology and orbital and infrastructure technology. From each specific area, key words in patent document were extracted by TF-IDF method and analyzed by social network. In the keyword network, core word of each specific technology were extracted according to their degree centrality. Then, the multi-word phrases were also built to represent the concept of core technologies. Finally, based on the analysis results, the development strategies for each specifics technical area of WPT in LRT filed will be provided.

The purpose of this study was social withdrawal, depression, and self - esteem affect adolescents' mobile phone dependency. For this study, I used data from the first grade of junior high school during the 7th (2016) Korean child and youth panel survey provided by Korea Youth Policy Institute. A total of 1,937 people were selected as the final target except those who do not have a mobile phone. The analysis method was SPSS 23.0 and AMOS 20.0. As a result of the study, First, the higher the depression of adolescents, the higher the dependence on mobile phones. Second, the social withdrawal and depression of adolescents have a significant impact on mobile phone dependence through self-esteem. In conclusion, I would like to provide policy data so that youths can develop and implement preventive programs that can prevent personality education and erroneous mobile phone dependency that can develop healthy and positive growth.

The purpose of the present study was to test the impact of depression on mobile phone dependency among elementary school students, to test the mediating effect of self-esteem between depression and mobile phone dependency, and to draw out theoretical and practical implications in terms of preventing or reducing mobile phone dependency. Based on previous studies, a longitudinal research model between the aforementioned three variables has been identified. The present study analyzed the 4th, 5th, and 6th wave data from Korea Children and Youth Panel Study 2010 (KCYPS 2010). The major results were as follows. First, depression could have a significant negative effect on self-esteem. Second, self-esteem could have a significant negative effect on mobile phone dependency. Third, the influence of depression on mobile phone dependency was not significant. Fourth, gender could be a significant moderating variable between depression and self-esteem. Finally, a number of implications of these findings were also discussed.

This study conducted to identify the impact of organizational factors on the characteristics of category management system, market orientation and collaboration orientation, in domestic retail industry, and also to identify the relationship between organizational factors and category management system's characteristics varies depending on the business type, retailer and supplier. To accomplish these research purposes, the study performed statistical analyses using a total of 94 samples. The results of the study can be summarized as follows. First, the organizational factors that affect market orientation of the category management system were found to be information technology infrastructure and organizational management system, and the organizational factors that affect collaborative orientation of the category management system were found to be partnerships and organizational management systems. Second, the relationship between market orientation and collaborative orientation of the category management system does not differ by the business type.

The purpose of this study is to investigate the mediating effect of learners' learning flow in the effect of presence on academic achievement in web-based e-learning. For this purpose, this study analyzed the influencing relationship between the each factor based on the structural model with the learning flow as a mediator variable. Based on existing theoretical studies, learning satisfaction and academic achievement, which represent learning outcomes, are set as dependent variables, and teaching presence, cognitive presence, and social presence are set as independent variables. Data collected from a total of 256 e-learning learners were used in the analysis of this study. According to the results of the analysis, teaching presence, cognitive presence, and social presence were found to have a significant effect on academic achievement when a learning flow is a mediator variable. Concretely, teaching presence, cognitive presence, and social presence have a positive effect on the learning flow, while learning flow has a positive effect on learning satisfaction. On the other hand, learning flow has a negative effect on academic achievement. As a result of verifying the mediating effect of learning flow on the relationship between presence, learning satisfaction, and academic achievement, there was meditating effect in the aggregate. This study implies that in order to increase the level of learning satisfaction and academic achievement, it is necessary to make the teaching-learning design in the provision of contents and materials for e-learning so that the learner can feel the presence. The results of this study can be used as a basic data for seeking support and promotion strategies for enhancement of future learning flow and presence.

In this paper, we propose to investigate the existing SW education related studies and to collect the total effect size for the improvement of computational thinking(CT) through meta-analysis and to confirm the effect size according to various variables. So, we have objectively identified and generalized the practical effects of SW education on the various variable. The results of the meta-analysis showed that 1) the overall effect of SW educational activities on CT improvement was 'Hedges' g=0.643', so SW educational activity can get a CT improvement of about 24% over other educational activities. 2) EPL is a SW teaching-learning method that greatly improves students' CT. 3) Since SW education can be guaranteed to improve CT among elementary school students and university students, essential SW education for these should be further promoted. And it was found that SW education activity were more effective for CT improvement in small cities & rural areas than big cities, but the cause was not identified, so further study will be required.