• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.33-42
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• 2012

Rapid evolution of wired and wireless technologies results in various types of embedded systems, and the software to be embedded into those devices now needs the flexibility rather than the fixedness which was well-known property for the embedded software in the past. Mobile agent is one of the useful distributed technologies of reducing network load and latency because of its disconnected operations and high asynchrony. In this paper, a component-based mobile agent framework, called EmHUMAN, is designed and implemented for structural embedding into the devices showing different functions and resource constraints. It consists of 3 layers of components. Based on those components, a structural embedding, considering resource constraints of required functions, amount of storage space, computing power, network bandwidth, ${\ldots} $ etc can be performed. The components in each layer can be extended with addition of new components, removing some components and modifying components. EmHUMAN plays the role of a framework for developing mobile agent based distributed systems. It is also a mobile agent system by itself. EmHUMAN provides several utilities as built-in API's, and thus high effectiveness in programming mobile agents can be achieved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3550-3566
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• 2020

As a widely used way to exfiltrate information, wireless covert channel (WCC) brings a serious threat to communication security, which enables the wireless communication process to bypass the authorized access control mechanism to disclose information. Unlike the covert channel on the network layer, wireless covert channels on the physical layer (WCC-P) is a new covert communication mode to implement and improve covert wireless communication. Existing WCC-P scheme modulates the secret message bits into the Gaussian noise, which is also called covert digital communication system based on the joint normal distribution (CJND). Finding the existence of this type of covert channel remains a challenging work due to its high undetectability. In this paper, we exploit the square autocorrelation coefficient (SAC) characteristic of the CJND signal to distinguish the covert communication from legitimate communication. We study the sharp increase of the SAC value when the offset is equal to the symbol length, which is caused by embedding secret information. Then, the SAC value of the measured sample is compared with the threshold value to determine whether the measured sample is CJND sample. When the signal-to-noise ratio reaches 20db, the detection accuracy can reach more than 90%.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.2
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• pp.55-60
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• 2002

This paper presents a controller for the multiple DC motors using the CAN(Controller Area Network). The controller has a benefit of reducing the cable connections and making the controller boards compact through the network including expansibility. CAN, among the field buses, is a serial communication methodology which has the physical layer and the data link layer in the ISO's OSI (Open System Interconnect) 7 layered reference model. It provides the user with many powerful features including multi-master functionality and the ability to broadcast / multicast telegrams. When we use a microprocessor chip embedding the CAN function, the system becomes more economical and reliable to react shortly in the data transmission. The controller, we proposed, is composed of two main controllers and a sub controller, which have built with a one-chip microprocessor having CAN function. The sub controller is plugged into the Pentium PC to perform a CAN communication, and connected to the main controllers via the CAN. Main controllers are responsible for controlling two motors respectively. Totally four motors, actuators for the biped robot in our laboratory, are controlled in the experiment. We show that the four motors are controlled properly to actuate the biped robot through the network in real time.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.149-160
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• 2017

Sentiment analysis is the process of determining whether a piece of document, text or conversation is positive, negative, neural or other emotion. Sentiment analysis has been applied for several real-world applications, such as chatbot. In the last five years, the practical use of the chatbot has been prevailing in many field of industry. In the chatbot applications, to recognize the user emotion, sentiment analysis must be performed in advance in order to understand the intent of speakers. The specific emotion is more than describing positive or negative sentences. In light of this context, we propose deep learning models for conducting multi-class sentiment analysis for identifying speaker's emotion which is categorized to be joy, fear, guilt, sad, shame, disgust, and anger. Thus, we develop convolutional neural network (CNN), long short term memory (LSTM), and multi-layer neural network models, as deep neural networks models, for detecting emotion in a sentence. In addition, word embedding process was also applied in our research. In our experiments, we have found that long short term memory (LSTM) model performs best compared to convolutional neural networks and multi-layer neural networks. Moreover, we also show the practical applicability of the deep learning models to the sentiment analysis for chatbot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.528-550
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• 2024

Warehousing demand prediction is an essential part of the supply chain, providing a fundamental basis for product manufacturing, replenishment, warehouse planning, etc. Existing forecasting methods cannot produce accurate forecasts since warehouse demand is affected by external factors such as holidays and seasons. Some aspects, such as consumer psychology and producer reputation, are challenging to quantify. The data can fluctuate widely or do not show obvious trend cycles. We introduce a new model for warehouse demand prediction called MAGRU, which stands for Multi-layer Attention with GRU. In the model, firstly, we perform the embedding operation on the input sequence to quantify the external influences; after that, we implement an encoder using GRU and the attention mechanism. The hidden state of GRU captures essential time series. In the decoder, we use attention again to select the key hidden states among all-time slices as the data to be fed into the GRU network. Experimental results show that this model has higher accuracy than RNN, LSTM, GRU, Prophet, XGboost, and DARNN. Using mean absolute error (MAE) and symmetric mean absolute percentage error(SMAPE) to evaluate the experimental results, MAGRU's MAE, RMSE, and SMAPE decreased by 7.65%, 10.03%, and 8.87% over GRU-LSTM, the current best model for solving this type of problem.

• Journal of the Microelectronics and Packaging Society
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• v.19 no.3
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• pp.77-82
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• 2012

In this paper, the research of IC embedded PCB process is carried out. For embedding chips into PCB, solder-balls on chips were etched out and ABF(Ajinomoto Build-ip Film), prepreg and Cu foil was laminated on that to fabricate 6 layer build-up board. The chip of which solder ball was removed was successfully interconnected with PCB by laser drilling and Cu plating. However, de-lamination phenomenon occurred between chip surface and ABF during reflow and thermal shock. To solve this problem, de-smear and plasma treatment was applied to PI(polyimide) passivation layer on chip surface to improve the surface roughness. The properties of chip surface(PI) was investigated in terms of AFM(Atomic Force Micrometer), SEM and XPS (X-ray Photoelectron Spectroscopy). As results, nano-size anchor was evenly formed on PI surface when plasma treatment was combined with de-smear(NaOH+KMnO4) process and it improved thermal shock reliability ($260^{\circ}C$-10sec solder floating).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.40-46
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• 2011

Wireless Sensor Networks(WSNs) have shown a lot of good outcomes in providing a various functions depending on industrial expectations by deploying ad-hoc networking with helps of light loaded and battery powered sensor nodes. In particular, it is strongly requested to develop an algorithm of cross-layer control between 2-layer and 3-layer to deriver the sensing data from the end node to the sink node on time. In this paper, based on the above observation we have proposed an IEEE802.15.4 based self priority routing scheme under UC Berkely TinyOS platform. The proposed beacon based priority routing (BPR) algorithm scheme utilizes beacon periods in sending message with embedding the high priority data and thus provides high quality of service(QoS) in the given criteria. The performance measures are the packet Throughput, delivery, latency, total energy consumption. Simulation results under TinyOS Simulator(TOSSIM) have shown the proposed scheme outcome the conventional Ad hoc On-Demand Distance Vector(AODV) Routing.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.3
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• pp.1-7
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• 2021

In this paper, by embedding a bare-die chip-type drive amplifier into the PCB composed of ABF and FR-4, it implements an embedded active device that can be applied in 28 GHz band modules. The ABF has a dielectric constant of 3.2 and a dielectric loss of 0.016. The FR-4 where the drive amplifier is embedded has a dielectric constant of 3.5 and a dielectric loss of 0.02. The proposed embedded module is processed into two structures, and S-parameter properties are confirmed with measurements. The two process structures are an embedding structure of face-up and an embedding structure of face-down. The fabricated module is measured on a designed test board using Taconic's TLY-5A(dielectric constant : 2.17, dielectric loss : 0.0002). The PCB which embedded into the face-down expected better gain performance due to shorter interconnection-line from the RF pad of the Bear-die chip to the pattern of formed layer. But it is verified that the ground at the bottom of the bear-die chip is grounded Through via, resulting in an oscillation. On the other hand, the face-up structure has a stable gain characteristic of more than 10 dB from 25 GHz to 30 GHz, with a gain of 12.32 dB at the center frequency of 28 GHz. The output characteristics of module embedded into the face-up structure are measured using signal generator and spectrum analyzer. When the input power (P_in) of the signal generator was applied from -10 dBm to 20 dBm, the gain compression point (P_1dB) of the embedded module was 20.38 dB. Ultimately, the bare-die chip used in this paper was verified through measurement that the oscillation is improved according to the grounding methods when embedding in a PCB. Thus, the module embedded into the face-up structure will be able to be properly used for communication modules in millimeter wave bands.

• Journal of Acupuncture Research
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• v.29 no.2
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• pp.29-36
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• 2012

The purpose of this article is to review all the wrinkle treatments reported so far, and to introduce a method of dermal subcision, especially localized fine wrinkles. In order to remove wrinkles, laser, ulthera and drug therapy are commonly used in western medicine while Miso facial rejuvenation acupuncture, $Jung-An$ acupuncture and needle-embedding therapy are used in oriental medicine. However, as researches on fine wrinkles have been insufficiently conducted until now. Dermal subcision stated in this study is considered to be a safe and effective way to ameliorate fine linear-shaped wrinkles around or below eyes and mouth by increasing the circulation of qi and blood. also, reproducing dermal layer. More and further related cases and researches are expected in the future.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.5
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• pp.266-276
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• 2013

LSB-based steganography is a simple and well known information hiding technique. In most LSB based techniques, a secret message is embedded into a specific position of LSB in the cover pixels. On the other hand, the main threat of LSB-based steganography is steganalysis. This paper proposes an asynchronous-cellular-automata(ACA)-based steganographic method, where secret bits are embedded into the selected position inside the cover pixel by ACA rule 51 and a secret key. As a result, it is very difficult for malicious users to retrieve a secret message from a cover image without knowing the secret key, even if the extraction algorithm is known. In addition, another layer of security is provided by almost random (rule-based) selection of a cover pixel for embedding using ACA and a different secret key. Finally, the experimental results show that the proposed method can be secured against the well-known steganalysis RS-attack.