• Journal of Communications and Networks
• /
• v.18 no.3
• /
• pp.493-501
• /
• 2016

In-network storage is an effective technique for avoiding network congestion and reducing power consumption in continuous data collection in wireless sensor networks. In recent years, network coding based storage design has been proposed as a means to achieving ubiquitous access that permits any query to be satisfied by a few random (nearby) storage nodes. To maintain data consistency in continuous data collection applications, the readings of a sensor over time must be sent to the same set of storage nodes. In this paper, we present an efficient approach to updating data at storage nodes to maintain data consistency at the storage nodes without decoding out the old data and re-encoding with new data. We studied a transmission strategy that identifies a set of storage nodes for each source sensor that minimizes the transmission cost and achieves ubiquitous access by transmitting sparsely using the sparse matrix theory. We demonstrate that the problem of minimizing the cost of transmission with coding is NP-hard. We present an approximation algorithm based on regarding every storage node with memory size B as B tiny nodes that can store only one packet. We analyzed the approximation ratio of the proposed approximation solution, and compared the performance of the proposed coding approach with other coding schemes presented in the literature. The simulation results confirm that significant performance improvement can be achieved with the proposed transmission strategy.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.3D
• /
• pp.205-212
• /
• 2012

The national highway traffic counts system consists of short duration counts and continuous counts. Unlike continuous counts, short duration counts are performed by collection of a few days period and thus, the magnitude of deviation of collected data from AADT varies depending upon when data collection takes place. Therefore, this study was done to find out the best months and days of data collection of each highway classification in order to enhance the accuracy of AADT estimation. Continuous counts, another type of the national traffic counts system, are performed by collection of 365-day period using a permanent traffic counter. Therefore, it is necessary to keep the number of days for which the counter malfunctions to a minimum in order to enhance the accuracy of data. However, from time to time the permanent traffic counter malfunctions due to various causes and thus, cannot collect data. Therefore, this study was done to find out whether the age of counter, the ratio of heavy vehicle volume to total traffic volume, etc. could be the direct causes of counter's malfunction based on the number of maintenance for a certain time period.

• Journal of Mechanical Science and Technology
• /
• v.19 no.12
• /
• pp.2312-2320
• /
• 2005

The aerodynamic effects of leading-edge accretion can raise important safety concerns since the formulation of ice causes severe degradation in aerodynamic performance as compared with the clean airfoil. The objective of this study is to develop a numerical simulation strategy for predicting the particle trajectory around an MS-0317 airfoil in the test section of the NASA Glenn Icing Research Tunnel and to investigate the impingement characteristics of droplets on the airfoil surface. In particular, predictions of the mean velocity and turbulence diffusion using turbulent flow solver and Continuous Random Walk method were desired throughout this flow domain in order to investigate droplet dispersion. The collection efficiency distributions over the airfoil surface in simulations with different numbers of droplets, various integration time-steps and particle sizes were compared with experimental data. The large droplet impingement data indicated the trends in impingement characteristics with respect to particle size ; the maximum collection efficiency located at the upper surface near the leading edge, and the maximum value and total collection efficiency were increased as the particle size was increased. The extent of the area impinged on by particles also increased with the increment of the particle size, which is similar as compared with experimental data.

• Journal of Korea Artificial Intelligence Association
• /
• v.2 no.1
• /
• pp.15-24
• /
• 2024

This study is about the effect of chatbot service quality on customer satisfaction and continuous use intention. Data collection was conducted for 13 days from October 23 to November 5, 2023, and a survey was conducted on customers who have used chatbot services. A total of 572 questionnaires were targeted, of which 545 valid data were used for analysis, excluding those that responded insincerely or did not meet the purpose of the study. The analysis results of this study are as follows: First, chatbot service quality partially had a significant effect on satisfaction. Second, customer satisfaction had a significant effect on continuous use intention. Therefore, in order to have a positive impact on continuous use intention, it is necessary to focus on marketing strategies related to chatbot service quality. Also, research focusing on data analysis and performance evaluation is crucial for enhancing chatbot services, necessitating studies that address real-time changes. Through sophisticated data analysis and variable measurement, chatbot services can be effectively improved, leading to enhanced customer satisfaction.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.16 no.4
• /
• pp.153-161
• /
• 2021

Real-time access is required to handle continuous and unstructured data and should be flexible in management under dynamic state. Platform can be built to allow data collection, storage, and processing from local-server or multi-server. Although the former centralize method is easy to control, it creates an overload problem because it proceeds all the processing in one unit, and the latter distributed method performs parallel processing, so it is fast to respond and can easily scale system capacity, but the design is complex. This paper provides data collection and processing on one platform to derive significant insights from various data held by an enterprise or agency in the latter manner, which is intuitively available on dashboards and utilizes Spark to improve distributed processing performance. All service utilize dockers to distribute and management. The data used in this study was 100% collected from Kafka, showing that when the file size is 4.4 gigabytes, the data processing speed in spark cluster mode is 2 minute 15 seconds, about 3 minutes 19 seconds faster than the local mode.

• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.443-452
• /
• 2020

Worker's awkward postures and unreasonable physical load can be corrected by monitoring construction activities, thereby increasing the safety and productivity of construction workers and projects. However, manual identification is time-consuming and contains high human variance. In this regard, an automated activity recognition system based on inertial measurement unit can help in rapidly and precisely collecting motion data. With the acceleration data, the machine learning algorithm will be used to train classifiers for automatically categorizing activities. However, input acceleration data are extracted either from designed experiments or simple construction work in previous studies. Thus, collected data series are discontinuous and activity categories are insufficient for real construction circumstances. This study aims to collect acceleration data during long-term continuous work in a construction project and validate the feasibility of activity recognition algorithm with the continuous motion data. The data collection covers two different workers performing formwork at the same site. An accelerator, as well as portable camera, is attached to the worker during the entire working session for simultaneously recording motion data and working activity. The supervised machine learning-based models are trained to classify activity in hierarchical levels, which reaches a 96.9% testing accuracy of recognizing rest and work and 85.6% testing accuracy of identifying stationary, traveling, and rebar installation actions.

• International conference on construction engineering and project management
• /
• 2007.03a
• /
• pp.279-288
• /
• 2007

Attempts to achieve a higher productivity have led studies to focus on process improvement. Information has been found as an essential element for process improvement. This research has introduced and focused on two types of information, namely: related jobsite information along the process and feedback information. Related jobsite information along the process which needs to be processed and delivered in a timely manner, accurate, and real time is required to streamline the decision making process. Whereas feedback information about process' current practices which have to be captured and stored is a useful for continuous improvement in identifying the problem origin and determining corrective action. In the current practices, although these two types of information are essential for process improvement, construction process has faced barriers in obtaining that information. Therefore, this research will propose a new information system to overcome the aforementioned barriers. The new information system consists of RFID as an automatic identification and data collection device integrated with database to support construction processes. The new system attempts to provide related jobsite information along the process and feedback information to support decision making process and continuous process improvement respectively. A case study of prefabrication installation process in housing projects has been selected to be implemented in conceptual model of RFID application in construction industry. Conceptual model will be presented in this paper as an initial stage of this ongoing research. Expected outcomes of the new system and future works will be discussed briefly.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.8
• /
• pp.591-595
• /
• 2009

Most existing routing protocols for object detection and tracking in wireless sensor networks concentrate on finding ways to detect and track one and more individual objects, e.g. people, animals, and vehicles, but they do not be interested in detecting and tracking of continuous objects, e.g., poison gas and biochemical. Such continuous objects have quite different properties from the individual objects since the continuous objects are continuously distributed across a region and usually occupy a large area, Thus, the continuous objects could be detected by a number of sensor nodes so that sensing data are redundant and highly correlated. Therefore, an efficient data collection and report scheme for collecting and locally aggregating sensing data is needed, In this paper, we propose the Continuous Object Tracking Mechanism based on Dynamic Rectangle Zone for detecting, tracking, and monitoring the continuous objects taking into account their properties.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.2
• /
• pp.1-7
• /
• 2017

Recently, NAND flash memory, which is used as a storage medium, is replacing HDD (Hard Disk Drive) at a high speed due to various advantages such as fast access speed, low power, and easy portability. In order to apply NAND flash memory to a computer system, a Flash Translation Layer (FTL) is indispensably required. FTL provides a number of features such as address mapping, garbage collection, wear leveling, and hot data identification. In particular, hot data identification is an algorithm that identifies specific pages where data updates frequently occur. Hot data identification helps to improve overall performance by identifying and managing hot data separately. MHF (Multi hash framework) technique, known as hot data identification technique, records the number of write operations in memory. The recorded value is evaluated and judged as hot data. However, the method of counting the number of times in a write request is not enough to judge a page as a hot data page. In this paper, we propose hot data identification which considers not only the number of write requests but also the persistence of write requests.

• Journal of Korean Society for Quality Management
• /
• v.47 no.2
• /
• pp.237-254
• /
• 2019

Purpose: The purpose of this study is to analyze correlation of perceived cosmetics brand apps attributes and use intentions, mediating role of customer satisfaction, and relationship between customer satisfaction and continuous usage intention. Then provide basic data for development management strategy of beauty industry and enhancement of competitiveness corresponding to smart era. Methods: The questionnaires were surveyed by an online company(EMBRAIN). After data collection, frequency analysis was performed on the general attributes of questionnaire survey using SPSS 22.0, and data conclusions were derived by verifying reliability and validity of data and hypotheses. Results: First, perceived cosmetic brand app attributes have a positive effect on customer satisfaction, Second, perceived cosmetic brand app attributes have a positive effect on continuous usage intention. Third, customer satisfaction was found to have a mediating role in the effect of perceived cosmetic brand app attributes on continuous usage intention. Fourth, involvement proved to control the relationship between perceived cosmetic brand app attributes perceived interactivity and customer satisfaction. Finally, Involvement has proven to control the relationship between cosmetic brand app attributes perceived interactivity and continuous usage intention. Conclusion: Consumers buying products from cosmetics brand apps will be more likely to use cosmetics brand apps if they feel comfortable with calculation process, search, booking confirmation and payment methods.