• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.286-291
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• 2020

In this paper, we propose a system that recommends music through tempo-oriented music classification and sensor-based human activity recognition. The proposed method indexes music files using tempo-oriented music classification and recommends suitable music according to the recognized user's activity. For accurate music classification, a dynamic classification based on a modulation spectrum and a sequence classification based on a Mel-spectrogram are used in combination. In addition, simple accelerometer and gyroscope sensor data of the smartphone are applied to deep spiking neural networks to improve activity recognition performance. Finally, music recommendation is performed through a mapping table considering the relationship between the recognized activity and the indexed music file. The experimental results show that the proposed system is suitable for use in any practical mobile device with a music player.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.301-307
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• 2023

Deep learning requires building a deep neural network, collecting a large amount of training data, and then training the built neural network for a long time. If training does not proceed properly or overfitting occurs, training will fail. When using deep learning tools that have been developed so far, it takes a lot of time to collect training data and learn. However, due to the rapid advent of the mobile environment and the increase in sensor data, the demand for real-time deep learning technology that can dramatically reduce the time required for neural network learning is rapidly increasing. In this study, a real-time deep learning system was implemented using an Arduino system equipped with a fine dust sensor. In the implemented system, fine dust data is measured every 30 seconds, and when up to 120 are accumulated, learning is performed using the previously accumulated data and the newly accumulated data as a dataset. The neural network for learning was composed of one input layer, one hidden layer, and one output. To evaluate the performance of the implemented system, learning time and root mean square error (RMSE) were measured. As a result of the experiment, the average learning error was 0.04053796, and the average learning time of one epoch was about 3,447 seconds.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.13-26
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• 2009

Wireless Sensor Networks (WSNs) is one of the key technologies that make it possible to provide u-service in a ubiquitous society, however, it has disadvantages such as difficulty of managing sensor nodes and weaknesses of stability or mobility in large-scale WSNs. In order to solve these problems, 6LoWPAN that integrates with WSNs and IP networks has been studied widely. In this paper, we propose a Location Tracking Service Based on Google Map (LTSGM) system using 6LoWPAN. Since LTSGM system provides visual location information of sensor nodes through Google Map, it is possible to makes it easier than ever to manage sensor nodes in large-scale WSNs. Moreover, LTSGM can be used for various services such as applications for disaster or crime because it can trace the location of mobile nodes. Implementation of LTSGM system will be a test platform for 6LoWPAN.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.431-439
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• 2007

In the ubiquitous which is rapidly developing with ultra speed these days, constructing the u-Campus which is using the sensor-network as its base is keep developing. Also, any information related equipments like PC and mobile, computing is possible whenever and wherever you want and due to the development of the wireless network, the service environment is continually developing. In this article, I'd like to suggest the u-Campus which is very suitable to the user's environment which had used application of mobile. In u-Campus, various techniques are adopted and applied along with development of info-communication related technidques. Especially, the new type of campus which is constructed by adopting the ubiquitous computing net-work technique to the campus of university is the u-Campus. In this article, by suggesting u-Yuhan designing methods, more effective and advanced school activities of students to make possible.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.278-287
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• 2013

Modern information technologies continue to provide industries with new and improved methods. With the rapid development of Machine to Machine (M2M) communication, a smart container supply chain management is formed based on high performance sensors, computer vision, Global Positioning System (GPS) satellites, and Globle System for Mobile (GSM) communication. Existing supply chain management has limitation to real time container tracking. This paper focuses on the studies and implementation of real time container chain management with the development of the container identification system and automatic alert system for interrupts and for normal periodical alerts. The concept and methods of smart container modeling are introduced together with the structure explained prior to the implementation of smart container tracking alert system. Firstly, the paper introduces the container code identification and recognition algorithm implemented in visual studio 2010 with Opencv (computer vision library) and Tesseract (OCR engine) for real time operation. Secondly it discusses the current automatic alert system provided for real time container tracking and the limitations of those systems. Finally the paper summarizes the challenges and the possibilities for the future work for real time container tracking solutions with the ubiquitous mobile and satellite network together with the high performance sensors and computer vision. All of those components combine to provide an excellent delivery of supply chain management with outstanding operation and security.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.89-94
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• 2018

This paper investigated the design method of the smart sensor for implementing IoT (Internet of Things) service. The power supply of sensor consistently acquisting data is based on the energy harvesting technology and designed with piezoelectric transducer not affected by surrounding circumstances. The wireless communication interface for the transmission of data is designed with BLE (Bluetooth Low Energy). BLE is highly adequate wireless communication technology for low power consumption and short distance wireless communication. The main application of BLE is beacon whose usage range is extended from O2O (Online to Offline) service, navigator based on indoor positioning technology, and anti-theft/lost child prevention service to mobile game. This paper studied the method to extend wireless coverage for complementing the short wireless transmission distance of BLE. The wireless sensor network based on CATV network is proposed for the easy construction of BLE sensor network and extended wireless coverage.

• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.401-406
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• 2007

This study discusses the development of a u-Health care system that can detect quickly and cope actively with emergent situations of chronic disease patients who lead everyday life. If a patient's emergent situation is detected by personal health care host(PHCH), which is composed of acceleration and vibration sensors, GPS, and CDMA communication module, a text message on the patient's current location is transmitted to the hospital and the guardian's mobile terminal so that they can cope with the situation immediately. Especially, the system analyzes data from sensors by using neural network and determines emergent situations such as syncope and convulsion promptly. The exact location of patients can also be found in the electronic map by using GPS information. The experiments show that this system is very effective to find emergencies promptly for chronic disease patients who cannot take care of themselves and it is expected to save many lives.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.23-29
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• 2011

We try to build the base for implementation of smart water treatment plant through identifying status by data acquisition such as temperature, humidity, flow, level, pump status and CCTV by using USN terminal such as Zigbee, Wi-Fi, UHF at the center of the flowmeter calibration center in K-water institute. The data obtained from various sensors is transmitted to data processing device through different types of USN network, the processed data is implemented to monitor by smart phone and we try to perform low cost and high efficient USN-based pilot project by implementing remote monitoring system using network performance analysis and mobile devices.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.151-155
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• 2017

With the rapid growth of the up-to-date wireless network and Internet technologies, huge and various types of things around us are connected to the Internet and build the hyper-connected society, and lots of smart applications using these technologies are actively developed recently. IoT connects human, things, space, and data with various types of networks to construct the hyper-connected network that can create, collect, share and appling realtime information. Furthermore, most of the smart applications are concentrated on the service that can collect and store realtime contexts using various sensors and cloud technology, and provide intelligence by making inferences and decisions from them nowadays. In this paper, we design a smart application that can accurately control and process the current state of the specific context in realtime by using the state-of-the-art ICT techniques such as various sensors and cloud technologies on the IoT based mobile computing environment.

• Convergence Security Journal
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• v.5 no.3
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• pp.9-14
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• 2005

In this treatise when, proposed to supplement studying contents relationship conversion service and cooperation studying service function to LMS that analyze existing e-learning model's limitation for ubiquitous environment e-learning model that can study regardless of, ubiquitously, some contents and do based on SCORM ubiquitous-network and next generation sensor technology etc.