• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.133-144
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• 2020

The number of elderly people with dementia is increasing as fast as the proportion of older people due to aging, which creates a social and economic burden. In particular, dementia care costs, including indirect costs such as increased care costs due to lost caregiver hours and caregivers, have grown exponentially over the years. In order to reduce these costs, it is urgent to introduce a management system to care for dementia patients. Therefore, this study proposes a sensor-based abnormal behavior detection system to manage dementia patients who live alone or in an environment where they cannot always take care of dementia patients. Existing studies were merely evaluating behavior or evaluating normal behavior, and there were studies that perceived behavior by processing images, not data from sensors. In this study, we recognized the limitation of real data collection and used both the auto-encoder, the unsupervised learning model, and the LSTM, the supervised learning model. Autoencoder, an unsupervised learning model, trained normal behavioral data to learn patterns for normal behavior, and LSTM further refined classification by learning behaviors that could be perceived by sensors. The test results show that each model has about 96% and 98% accuracy and is designed to pass the LSTM model when the autoencoder outlier has more than 3%. The system is expected to effectively manage the elderly and dementia patients who live alone and reduce the cost of caring.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.4
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• pp.56-67
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• 2004

This study analyzes human error of workers performing simple repetitive tasks, and in order to prepare preventative measures, 486 people were used as subjects. The results of the study are like the following. First, the biggest cause of human error showed to be the worker himself in $77.8\%$ of the cases, machinery showed to be the cause in $16.3\%$ of the cases and management showed to be the cause in $6.0\%$ of the cases. The results show that most of the human error occurred due to the worker performing simple repetitive tasks and the human errors showed to be caused more by bad ergonomics and long hours rather than by problems with machinery. In addition, the area with the highest rate of human error showed to be the Human Information Processing System with Task Input Error being the highest with $46.9\%$, followed by Judgement and Memory Error with $36.4\%$ and Recognition Verification Error with $16.7\%$. Although fully automated tasks may reduce the rate of human error we must focus on lowering the rate of problems arising from spontaneous errors caused by workers performing simple repetitive tasks by continuously renewing plans and budgets in order to standardize tasks by incorporating cyclic positioning according to experience and positional exchange and by inspecting the workplace to increase efficiency of the workers.

• Culinary science and hospitality research
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• v.17 no.3
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• pp.20-32
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• 2011

The purpose of this study is to analyze customers' behavior in using word-of-mouth(WOM) information about Korean local food restaurants. The questionnaire developed for this study was distributed to 500 customers living in Jeonbuk area and a total of 455 copies (91.0%) were used for analysis. The statistical analysis was conducted using SPSS Win(12.0). The results were summarized as follows. The recommendation of people experienced'($M=3.57{\pm}1.24$) and 'word-of-mouth through people around'($M=3.52{\pm}1.20$) were major word-of-mouth information sources of Korean local foods; 'taste of food'($M=4.16{\pm}1.15$) and 'service quality'($M=3.79{\pm}1.11$) were important attributes in word-of-mouth information. In addition, to the question about the reasons for recommending the restaurant to the people around, the most people replied that 'flavor, nutrition and quality of local foods can be kept only in the specific location' ($3.53{\pm}1.08$), followed by 'to keep the memory of the visit to the areas in mind through local foods'($3.51{\pm}1.03$). These results showed that people usually recommend a restaurant based on the quality of the food itself or local characteristics. As a result, it is deemed that word-of-mouth effect is an important factor for the spread of Korean local foods.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.11
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• pp.1318-1332
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• 1999

본 논문에서는 입출력 응용을 위해 collective I/O 기법을 기반으로 한 실행시간 시스템의 설계, 구현 그리고 그 성능평가를 기술한다. 여기서는 모든 프로세서가 동시에 I/O 요구에 따라 스케쥴링하며 I/O를 수행하는 collective I/O 방안과 프로세서들이 여러 그룹으로 묶이어, 다음 그룹이 데이터를 재배열하는 통신을 수행하는 동안 오직 한 그룹만이 동시에 I/O를 수행하는 pipelined collective I/O 등의 두 가지 설계방안을 살펴본다. Pipelined collective I/O의 전체 과정은 I/O 노드 충돌을 동적으로 줄이기 위해 파이프라인된다. 이상의 설계 부분에서는 동적으로 충돌 관리를 위한 지원을 제공한다. 본 논문에서는 다른 노드의 메모리 영역에 이미 존재하는 데이터를 재 사용하여 I/O 비용을 줄이기 위해 collective I/O 방안에서의 소프트웨어 캐슁 방안과 두 가지 모형에서의 chunking과 온라인 압축방안을 기술한다. 그리고 이상에서 기술한 방안들이 입출력을 위해 높은 성능을 보임을 기술하는데, 이 성능결과는 Intel Paragon과 ASCI/Red teraflops 기계 상에서 실험한 것이다. 그 결과 응용 레벨에서의 bandwidth는 peak point가 55%까지 측정되었다.Abstract In this paper we present the design, implementation and evaluation of a runtime system based on collective I/O techniques for irregular applications. We present two designs, namely, "Collective I/O" and "Pipelined Collective I/O". In the first scheme, all processors participate in the I/O simultaneously, making scheduling of I/O requests simpler but creating a possibility of contention at the I/O nodes. In the second approach, processors are grouped into several groups, so that only one group performs I/O simultaneously, while the next group performs communication to rearrange data, and this entire process is pipelined to reduce I/O node contention dynamically. In other words, the design provides support for dynamic contention management. Then we present a software caching method using collective I/O to reduce I/O cost by reusing data already present in the memory of other nodes. Finally, chunking and on-line compression mechanisms are included in both models. We demonstrate that we can obtain significantly high-performance for I/O above what has been possible so far. The performance results are presented on an Intel Paragon and on the ASCI/Red teraflops machine. Application level I/O bandwidth up to 55% of the peak is observed.he peak is observed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.726-734
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• 2015

Relational databases used by structuralizing data are the most widely used in data management at present. However, in relational databases, service becomes slower as the amount of data increases because of constraints in the reading and writing operations to save or query data. Furthermore, when a new task is added, the database grows and, consequently, requires additional infrastructure, such as parallel configuration of hardware, CPU, memory, and network, to support smooth operation. In this paper, in order to improve the web information services that are slowing down due to increase of data in the relational databases, we implemented a model to extract a large amount of data quickly and safely for users by processing Hadoop Distributed File System (HDFS) files after sending data to HDFSs and unifying and reconstructing the data. We implemented our model in a Web-based civil affairs system that stores image files, which is irregular data processing. Our proposed system's data processing was found to be 0.4 sec faster than that of a relational database system. Thus, we found that it is possible to support Web information services with a Hadoop-based big data processing technique in order to process a large amount of data, as in conventional relational databases. Furthermore, since Hadoop is open source, our model has the advantage of reducing software costs. The proposed system is expected to be used as a model for Web services that provide fast information processing for organizations that require efficient processing of big data because of the increase in the size of conventional relational databases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.381-385
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• 2010

An aging Society solitary life old mans are increasing. The nurses have to visit old mans and must confirm their disease, because they do not act well. It is very difficult to take care old man, because the number of Nurses are small. This problem is solved by collection of data about condition of old mans from long distance. Data communication with Ethernet have benefit to collection of measurement of old man's condition. The Data storage system an long distance place are storaged data and after several day data was transmitted to the DB over the Ethernet. For Miniaturization of such system the system must be OS-less Embedded Ethernet Server system. Such system manages the file management system only with H/W. The Storage device is used SD-card. SD Card is small size and operates with small power. By using 512MB sd memory card, it is possible to storage during 5~6 years, 10 byte of temperature value per second. In this paper, we make a Embedded Ethernet Server using W3100A, Atmega128 MCU and data stroage device using SD-Card. This system operates with O/S-less Embedded Ethernet Server. We talk about file System, Storage and Ethernet. We explained about MCU Atmega128, Interface between LAN LSIand W3100A, Interface between W3100A and Phyceiver RTL8201, data I/O between MCU and SD-Card and File System. We shows the experiment device and result of monitoring.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.3-11
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• 2016

In the environment of Internet of Things (IoT), IoT devices are limited by physical components such as power supply and memory, and also limited to their network performance in bandwidth, wireless channel, throughput, payload, etc. Despite these limitations, resources of IoT devices are shared with other IoT devices. Especially, remote management of the information of devices and patients are very important for the IoT healthcare service, moreover, providing the interoperability between the healthcare device and healthcare platform is essential. To meet these requirements, format of the message and the expressions for the data information and data transmission need to comply with suitable international standards for the IoT environment. However, the ISO/IEEE 11073 PHD (Personal Healthcare Device) standards, the existing international standards for the transmission of health informatics, does not consider the IoT environment, and therefore it is difficult to be applied for the IoT healthcare service. For this matter, we have designed and implemented the IoT healthcare system by applying the oneM2M, standards for the Internet of Things, and ISO/IEEE 11073 DIM (Domain Information Model), standards for the transmission of health informatics. For the implementation, the OM2M platform, which is based on the oneM2M standards, has been used. To evaluate the efficiency of transfer syntaxes between the healthcare device and OM2M platform, we have implemented comparative performance evaluation between HTTP and CoAP, and also between XML and JSON by comparing the packet size and number of packets in one transaction.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.54-62
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• 2015

Although NAND flash-based SSD (Solid-State Drive) provides superior performance in comparison to HDD (Hard Disk Drive), it has a major drawback in write endurance. As a result, the lifetime of SSD is determined by the workload and thus it becomes a big challenge in current technology trend of such as the shifting from SLC (Single Level Cell) to MLC (Multi Level cell) and even TLC (Triple Level Cell). Most previous studies have dealt with wear-leveling or improving SSD lifetime regarding hardware architecture. In this paper, we propose the optimal configuration of host I/O stack focusing on file system, I/O scheduler, and link power management using JEDEC enterprise workloads in terms of WAF (Write Amplification Factor) which represents the efficiency perspective of SSD life time especially for host write processing into flash memory. Experimental analysis shows that the optimum configuration of I/O stack for the perspective of SSD lifetime is MinPower-Dead-XFS which prolongs the lifetime of SSD approximately 2.6 times in comparison with MaxPower-Cfq-Ext4, the best performance combination. Though the performance was reduced by 13%, this contributions demonstrates a considerable aspect of SSD lifetime in relation to I/O stack optimization.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.18-27
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• 2010

In u-GIS environment, GeoSensor environment requires that dynamic data captured from various sensors and static information in terms of features in 2D or 3D are fused together. GeoSensors, the core of this environment, are distributed over a wide area sporadically, and are collected in any size constantly. As a result, storage space could be exceeded because of restricted memory in DSMS. To solve this kind of problems, a lot of related studies are being researched actively. There are typically 3 different methods - Random Load Shedding, Semantic Load Shedding, and Sampling. Random Load Shedding chooses and deletes data in random. Semantic Load Shedding prioritizes data, then deletes it first which has lower priority. Sampling uses statistical operation, computes sampling rate, and sheds load. However, they are not high accuracy because traditional ones do not consider spatial characteristics. In this paper 'Pre-Filtering based Post Load Shedding' are suggested to improve the accuracy of spatial query and to restrict load shedding in DSMS. This method, at first, limits unnecessarily increased loads in stream queue with 'Pre-Filtering'. And then, it processes 'Post-Load Shedding', considering data and spatial status to guarantee the accuracy of result. The suggested method effectively reduces the number of the performance of load shedding, and improves the accuracy of spatial query.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.6
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• pp.375-382
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• 2016

In the present study, the wave hindcasting has been performed, and then the characteristics of storm waves at Gangnueng port was investigated, in which the high waves are observed. Comparing the numerical results with the wave measurements at Gangneung port, Niigata, and Hamada, there were good agreements between them. In particular, the Pearson correlation coefficients of significant wave heights and peak periods at Gangneung port were 0.92 and 0.72, respectively. Then the extreme wave analysis on the significant wave heights was carried out for the estimation of the frequency of storm waves. In this analysis, the storm waves over the threshold were fitted to GPD(Generalized Pareto Distribution). According to this analysis, the return period of the storm wave on February, 24, 2008, one of the large storm waves at Gangneung port, was 8.2 months. Among the computed significant wave heights larger than one-year wave, 58.3% of them were resulted from the storm, while the others were from the typhoon. Additionally, the regression analysis on the waves larger than one-month wave has been conducted, and then the relationship between the computed significant wave heights and the significant wave period, $T_{1/3}=7H_s^{0.25}$ was obtained.