• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.81-92
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• 2006

Recently, the number of mobile phone and PDA users has been rapidly increased. Such monitoring and control applications as geographical and traffic information systems are being used widely with wireless devices. In this paper, we introduce the mobile M/VC application framework that supports the rapid constructions of mobile monitoring and control (M/VC) applications. The mobile M/VC application framework uses the mobile Observer/Observable pattern that extends the Java's Observer/Observable for automatic interactions of server and client objects in wireless environments. It also provides the Multiplexer and Demultiplexer classes that supports the assembly feature of Observer and Observable objects. To construct an application using the framework, developers just need to create necessary objects from the Observable and MobileObserver classes and inter-connect them structurally(like the plug-and-play style) through the Multiplexer and Demultiplexer objects. Then, the state change of Observable objects is notified to the connected Observer objects and user's input with Observer objects is propagated to Observable objects. These mechanism is the main process for monitoring and control applications. Therefore, the mobile M/VC application framework can improve the productivity of mobile applications and enhance the reusability of such components as Observer and Observable objects in wireless environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.61-67
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• 2016

With the current high distribution rate of smart devices and the recent development of computing technology, user interest in multimedia, such as photos, videos, and so on, has rapidly increased, which is a departure from the simple pattern of information retrieval. Because of these increasing interests, image processing techniques, which generate and process images for diverse applications, are being developed. In entertainment recently, there are some techniques that present a celebrity's image as a mosaic comprising many small images. In addition, studies into the mosaic technique are actively conducted. However, conventional mosaic techniques result in a long processing time as the number of database images increases, because they compare the images in the databases sequentially. Therefore, to increase search efficiency, this paper proposes an algorithm to generate a mosaic image using a discrete cosine transform (DCT) hash. The proposed photo mosaic-generation algorithm is composed of database creation and mosaic image generation. In database creation, it first segments images into blocks with a predefined size. And then, it computes and stores a DCT hash set for each segmented block. In mosaic generation, it efficiently searches for the most similar blocks in the database via DCT hash for every block of the input image, and then it generates the final mosaic. With diverse experimental results, the proposed photo mosaic-creation algorithm can effectively generate a mosaic, regardless of the various types of images and sizes.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.4
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• pp.95-102
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• 2016

Computer security incident such as confidential information leak and data destruction are constantly growing and it becomes threat to information in digital devices. To respond against the incident, digital forensic techniques are also developing to help digital incident investigation. With the development of digital forensic technology, a variety of forensic artifact has been developed to trace the behavior of users. Also, a diversity of forensic tool has been developed to extract information from forensic artifact. However, there is a issue that information from forensic tools has its own forms. To solve this problem, it needs to process data when it is output from forensic tools. Then it needs to compare and analyze processed data to identify how data is related each other and interpret the implications. To reach this, it calls for effective method to store and output data in the course of data processing. This paper aims to propose DFIOC (Digital Forensic Indicators Of Compromise) that is capable of transcribing a variety of forensic artifact information effectively during incident analysis and response. DFIOC, which is XML based format, provides "Evidence" to represent various forensic artifacts in the incident investigation. Furthermore, It provides "Forensic Analysis" to report forensic analysis result and also gives "Indicator" to investigate the trace of incidence quickly. By logging data into one sheet in DFIOC format for forensic analysis process, it is capable of avoiding unnecessary data processing. Lastly, since collected information is recorded in a normalized format, data input and output becomes much easier as well as it will be convenient to use for identification of collected information and analysis of data relationship.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.310-318
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• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.

• Journal of the Korea Organic Resources Recycling Association
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• v.27 no.2
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• pp.5-12
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• 2019

The study is carried out to survey the proper management and to propose an eco - friendly separation system through efficient screening and resource recovery of excavated materials containing waste from various excavating fields such as reconstruction of landfill sites for reuse, reclamation of unsanitary landfill and residential land development of waste dumping sites. The current status and screening process and analytical characteristics of the excavated materials containing waste were reviewed. Through the analysis of the samples such as separated combustibles, recyclable soils and residues collected from the on-site visits we were able to understand the characteristics of separated materials and excavated materials containing waste such as calorific value, elementary composition, TOC, foreign material content and LOI. It has been found that elimination of the moisture of excavations, removal of attached soil from the surfaces of the excavated combustibles and the quantitative supply method of the input devices are the main operating factors as essential factors for the optimal separation of excavated materials containing waste. For efficient management and recycling of excavated materials containing, it is necessary to set criteria of ash content in separated combustibles and criteria organic matter content in separated soils.

• Therapeutic Science for Rehabilitation
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• v.8 no.1
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• pp.51-62
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• 2019

Objective: To develop and verify the usability of a cognitive rehabilitation system with diverse cognitive functional levels based on tangible objects for the elderly population. Methods: A study was conducted to investigate the system's strengths and weaknesses by upgrading it with responses from two groups of 15 patients and 4 occupational therapists. After undergoing three forms of training - regarding executive function, memory, and concentration for a total of 20-30 min, the participants were asked to answer a structured questionnaire about contents of the three forms of training, hardware including the tablet PC functioning as a CPU and display media and tangible objects, and satisfaction of experiential usage of the system. Results: Both groups responded that the most interesting training area was executive function while the least interesting was concentration. Six participants reported that the size of the screen of the tablet PC was inappropriate, and five responded that the size of the tool was inappropriate. All therapists and 40% of the patients responded that they were satisfied with this system. Conclusion: This system's features include easy manipulation of tangible tools for performing training tasks, easy selection of and training in cognitive areas based on users' needs, and automatic adjustment of difficulty level based on users' performance. The training environment was designed to be similar to the natural environment by using tangible objects in both hands as input devices for the system, and the system was considered as an alternative to the lack of community cognitive rehabilitation specialists.

• Membrane Journal
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• v.33 no.4
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• pp.181-190
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• 2023

Wastewater purification is one of the most important techniques for controlling environmental pollution and fulfilling the demand for freshwater supply. Various technologies, such as different types of distillations and reverse osmosis processes, need higher energy input. Capacitive deionization (CDI) is an alternative method in which power consumption is deficient and works on the supercapacitor principle. Research is going on to improve the electrode materials to improve the efficiency of the process. A reverse electrodialysis (RED) is the most commonly used desalination technology and osmotic power generator. Among many studies conducted to enhance the efficiency of RED, MXene, as an ion exchange membrane (IEM) and 2D nanofluidic channels in IEM, is rising as a promising way to improve the physical and electrochemical properties of RED. It is used alone and other polymeric materials are mixed with MXene to enhance the performance of the membrane further. The maximum desalination performances of MXene with preconditioning, Ti₃C₂T_x, Nafion, and hetero-structures were respectively measured, proving the potential of MXene for a promising material in the desalination industry. In terms of osmotic power generating via RED, adopting MXene as asymmetric nanofluidic ion channels in IEM significantly improved the maximum osmotic output power density, most of them surpassing the commercialization benchmark, 5 Wm^-2. By connecting the number of unit cells, the output voltage reaches the point where it can directly power the electronic devices without any intermediate aid. The studies around MXene have significantly increased in recent years, yet there is more to be revealed about the application of MXene in the membrane and osmotic power-generating industry. This review discusses the electrodialysis process based on MXene composite membrane.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.1
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• pp.1-8
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• 2009

The objective of this study is to design a system that automatically monitors the state of interior spaces like offices where lots of people are coming and going through image data and environment data, which includes temperature, humidity, and other conditions, and implement and test related application programs. In practice, there are lots of image data automatically obtained by unmanned equipments, such as certain types of CCTVs, for monitoring situation in usual interior spaces. This image data can be used as a more effective manner by establishing a system that recognizes situation in specific interior spaces based on the relationship between image and environment data. For instance, it is possible to perform unmanned on/off controls for various electronic equipments, such as air conditioners, lights, and other devices, through analyzing the data acquisited from environment sensors (temperature, humidity, and illumination) as dynamic states are not maintained for a specified period of time. For implementing these controls, this study analyzes environment data acquisited from temperature and humidity sensors and image data input from wireless cameras to recognize situation and that can be used to automatically control environment variables configured by users. Experiments were applied in a laboratory where unmanned controls were effectively performed as automatic on/off controls for the air conditioner and lights installed in the laboratory as certain motions were detected or undetected for a specified period of time.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.703-709
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• 2023

It is most desirable to train with a real crane in an environment similar to that of a port for crane operation training in charge of loading and unloading in a port, but it has time and space limitations and cost problems. In order to overcome these limitations, VR(Virtual Reality) based crane training programs and related devices are receiving a lot of attention. In this paper, we designed and implemented a VR-based harbor crane simulator operating on an HMD. The simulator developed in this paper consists of a crane simulator program that operates on the HMD, an IoT driving terminal that processes trainees' crane operation input, and a training server that stores trainees' training information. The simulator program provides VR-based crane training scenarios implemented with Unity3D, and the IoT driving terminal developed based on Arduino is composed of two controllers and transmits the user's driving operation to the HMD. In particular, the crane simulator in this paper uses a training server to create a database of environment setting values for each educator, progress and training time, and information on driving warning situations. Through the use of such a server, trainees can use the simulator in a more convenient environment and can expect improved educational effects by providing training information.

• Journal of IKEEE
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• v.27 no.1
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• pp.45-52
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• 2023

Cold-junction correction(CJC) and disconnection detection circuit design of various thermocouples(TC) and multi-channel TC interface circuit using them were designed. The CJC and disconnection detection circuit consists of a CJC semiconductor device, an instrumentation amplifier(IA), two resistors and a diode for disconnection detection. Based on the basic circuit, a multi-channel interface circuit was also implemented. The CJC was implemented using compensation semiconductor and IA, and disconnection detection was detected by using two resistor and a diode so that IA input voltage became -0.42V. As a result of the experiment using R-type TC, the error of the designed circuit was reduced from 0.14mV to 3㎶ after CJC in the temperature range of 0℃ to 1400℃. In addition, it was confirmed that the output voltage of IA was saturated from 88mV to -14.2V when TC was disconnected from normal. The output voltage of the designed circuit was 0V to 10V in the temperature range of 0℃ to 1400℃. The results of the 4-channel interface experiment using R-type TC were almost identical to the CJC and disconnection detection results for each channel. The implemented multi-channel interface has a feature that can be applied equally to E, J, K, T, R, and S-type TCs by changing the terminals of CJC semiconductor devices and adjusting the IA gain.