• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.145-146
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• 2010

This paper proposed a new concept of global healthcare system based on M2M technology with the combination of networks by using IPv6 techniques. The proposed system consists of 6LoWPAN based wearable sensors, gateway for the connection of different networks, and server program offering health information. Thus our approach presents an intelligent system which allows direct exchange of information between machines without human assistance with the epoch-making extension of measurement environment in healthcare areas appropriately.

• STI Policy Review
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• v.8 no.2
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• pp.49-74
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• 2017

What are some of the explanations for cross-national diversity of foresight performance among technological followers? Why are some countries more successful than others in learning how to develop national innovation system foresight? This paper argues that the answers are linked to organizational capacities at three different levels: governmental, policy network and social learning. To corroborate this argument, the paper chose Iran and Korea as benchmarking partners, and attempts to find out what makes Iran a slow learner in building innovation system foresight. The conceptual model is an improved model of Saritas's, by integrating Borras' and Andersen's conceptions and classifications. The data are collected from comprehensive interviews in both countries and second-hand data of international indexes. The paper, finally, concludes that it is the weakness of analytical-systemic capacity that impedes and delays the emergence of systemic foresight in Iran, and that this weakness stems from the adverse impacts of the dominant institutions, surrounding the innovation system. The final point is that it is not sufficient for Iran to learn the methods and techniques of foresight from Korea. It should learn how to open its macro-policy towards the global market and design appropriate industrial strategy in a coherent policy-strategy portfolio.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.277-283
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• 2018

Some innovative researchers have had a dream of self-thinking intelligent computer. Alphago, at last, showed its possibility. With it, most computer engineers including even students can learn easily how to do it. As the interest to the deep learning has been growing, people's expectation is also naturally growing. In this research, we tried to enhance the game ability of a 7-poker system by applying machine learning techniques. In addition, we also tried to apply emotion analysis of a player to trace ones emotional changes. Methods and outcomes are to be explained in this paper.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.760-767
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• 2018

Advanced driver assistance system(ADAS) is a major technique in the intelligent vehicle field. The techniques for ADAS can be separated in two classes, i.e., methods that directly control the movement of vehicle and that indirectly provide convenience to driver. In this paper, we propose a novel system that gives a visual assistance to driver by translating a night road image to a day road image. We use the black box images capturing the front road view of vehicle as inputs. The black box images are cropped into three parts and simultaneously translated into day images by the proposed image translation module. Then, the translated images are recollected to original size. The experimental result shows that the proposed method generates realistic images and outperforms the conventional algorithms.

• Journal of Multimedia Information System
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• v.6 no.2
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• pp.61-66
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• 2019

VANET (Vehicular Ad-hoc Network) is a mobile Ad-hoc Network which deals with the moving vehicles. VANET supports Intelligent Transport Systems (ITS) which is related to different modes of transport and traffic management techniques. VANETs enabled users to be informed and make them safer. VANET uses IEEE 802.11p standard wireless access protocol for communication. An important and necessary issue of VANET is to design routing protocols. In a network, communication takes place by the use of the routing protocols. There are mainly two types of communications used such as Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) in VANET. Vehicles can send and receive messages among them and also to and from infrastructure used. In this paper, AODV, DSR and DSDV are compared by analysing the results of simulation on various metrics such as average throughput, instant throughput, packet delivery ratio and residual energy. Findings indicates utilization of AODV and DSR is more applicable for these metrics as compared to DSDV. A network simulator (NS2) is used for simulation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.208-214
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• 2021

Recently, much of the intelligent security scenario and criminal investigation demands for matching photo and non-photo. Existing face recognition system can not sufficiently guarantee these needs. In this paper, we propose an algorithm to improve the performance of heterogeneous face recognition systems by reducing the different modality between sketches and photos of the same person. The proposed algorithm extracts each image's texture features through texture descriptors (gray level co-occurrence matrix, multiscale local binary pattern), and based on this, generates a transformation matrix through eigenfeature regularization and extraction techniques. The score value calculated between the vectors generated in this way finally recognizes the identity of the sketch image through the score normalization methods.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.12-22
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• 2021

Since the technical realization of self-aligned planar complementary metal-oxide-semiconductor field-effect transistors in 1960s, semiconductor manufacturing has aggressively pursued scaling that fruitfully resulted in tremendous advancement in device performances and realization of features sizes smaller than 10 nm. Due to many intrinsic material and technical obstacles, continuing the scaling progress of semiconductor devices has become increasingly arduous. As an effort to circumvent the areal limit, stacking devices in a three-dimensional fashion has been suggested. This approach is commonly called monolithic three-dimensional (M3D) integration. In this work, we examined technical issues that need to be addressed and overcome to fully realize energy efficiency, short latency and cost competency. Full-fledged M3D technologies are expected to contribute to various new fields of artificial intelligence, autonomous gadgets and unknowns, which are to be discovered.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.347-351
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• 2022

Farmers E-Market is a website that allows agricultural workers to direct market their products to buyers without the use of a middleman. That theory is blockchain system will be used by authors to accomplish this. The system, which is built on a public blockchain system, supports sustainability, shippers, and consumers. Farmers can keep track of their farming activities. Customers can review the product's history and track its journey through carriers to delivery after making a purchase. Farmers are encouraged to get information about their interests promptly in a blockchain-enabled system like this. This functionality is being used by small-scale farmers to form groups based on their location to attract large-scale customers, renegotiate farming techniques or volumes, and enter into contracts with buyers. The analysis shows the use of blockchain technology with a farmer's portal that keeps the video of trading data of crops, taking into account the qualities of blockchain such as values and create or transaction data. The proposal merges python as a programming language with a blockchain system to benefit farmers, vendors, and individuals by preserving transactions.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.288-294
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• 2021

There are various ways to be infected with malicious code due to the increase in Internet use, such as the web, affiliate programs, P2P, illegal software, DNS alteration of routers, word processor vulnerabilities, spam mail, and storage media. In addition, malicious codes are produced more easily than before through automatic generation programs due to evasion technology according to the advancement of production technology. In the past, the propagation speed of malicious code was slow, the infection route was limited, and the propagation technology had a simple structure, so there was enough time to study countermeasures. However, current malicious codes have become very intelligent by absorbing technologies such as concealment technology and self-transformation, causing problems such as distributed denial of service attacks (DDoS), spam sending and personal information theft. The existing malware detection technique, which is a signature detection technique, cannot respond when it encounters a malicious code whose attack pattern has been changed or a new type of malicious code. In addition, it is difficult to perform static analysis on malicious code to which code obfuscation, encryption, and packing techniques are applied to make malicious code analysis difficult. Therefore, in this paper, a method to detect malicious code through dynamic analysis and static analysis using Trojan-type Downloader/Dropper malicious code was showed, and suggested to malicious code detection and countermeasures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4308-4325
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• 2021

The importance and necessity of artificial intelligence, particularly machine learning, has recently been emphasized. In fact, artificial intelligence, such as intelligent surveillance cameras and other security systems, is used to solve various problems or provide convenience, providing solutions to problems that humans traditionally had to manually deal with one at a time. Among them, information security is one of the domains where the use of artificial intelligence is especially needed because the frequency of occurrence and processing capacity of dangerous codes exceeds the capabilities of humans. Therefore, this study intends to examine the definition of artificial intelligence and machine learning, its execution method, process, learning algorithm, and cases of utilization in various domains, particularly the cases and contents of artificial intelligence technology used in the field of information security. Based on this, this study proposes a method to apply machine learning technology to the method of classifying and detecting malware that has rapidly increased in recent years. The proposed methodology converts software programs containing malicious codes into images and creates training data suitable for machine learning by preparing data and augmenting the dataset. The model trained using the images created in this manner is expected to be effective in classifying and detecting malware.