• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.25-35
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• 2020

In the Korean litigation system, structural maldistribution of evidence still remains a conundrum. Numerous solutions have been discussed so far and, today, few people deny the need for adopting a system similar to the discovery procedure in the United States. In the intellectual property (IP) domain, a wide range of legislative attempts have been made to improve the litigation system, especially for patent litigation. However, the adoption of discovery in copyright litigation is seldom discussed, despite the fact that copyright infringement lawsuits increasingly involve highly technical issues, especially in case of copyrightable computer programs. The lack of discussion on discovery adoption forms a stark contrast with the active attempts to adapt and adopt discovery procedure for patent litigation. In copyright infringement lawsuits, especially for copyrighted computer programs, securing evidence takes on crucial importance. However, in reality, there are numerous obstacles. Some lawsuits proceed even without properly securing the infringed work. To address this issue, the current litigation system needs to be improved by adopting a procedure similar to discovery. This paper reviews what solutions are being utilized today, and how we should approach the issue.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.161-172
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• 2021

Neuromorphic architecture is drawing attention as a next-generation computing that supports artificial intelligence technology with low energy. However, FPGA embedded boards based on Neuromorphic architecturehave limited resources due to size and power. In this paper, we compared and evaluated the image reduction method using the interpolation method that rescales the size without considering the feature points and the DCT (Discrete Cosine Transform) method that preserves the feature points as much as possible based on energy. The scaled images were compared and analyzed for accuracy through CNN (Convolutional Neural Networks) in a PC environment and in the Nengo framework of an FPGA embedded board.. As a result of the experiment, DCT based classification showed about 1.9% higher performance than that of interpolation representation in both CNN and FPGA nengo environments. Based on the experimental results, when the DCT method is used in a limited resource environment such as an embedded board, a lot of resources are allocated to the expression of neurons used for classification, and the recognition rate is expected to increase.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.143-150
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• 2021

There is a need for an artificial intelligent technology that can reduce various types of safety accidents by analyzing the risk factors that cause safety accidents in industrial site. In this paper, user safety profiling methods are proposed that can prevent safety accidents in advance by specifying and modeling user information data related to safety accidents. User information data is classified into normal and abnormal conditions through deep learning based artificial intelligence analysis. As a result of verifying user safety profiling technology using more than 10 types of industrial field data, 93.6% of user safety profiling accuracy was obtained.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.127-133
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• 2020

As the usages of artificial intelligence is increased, the demand to algorithms for small portable devices increases. Also as the embedded system becomes high-performance, it is possible to implement algorithms for high-speed computation and machine learning as well as operating systems. As the machine learning algorithms process repetitive calculations, it depend on the cloud environment by network connection. For an stand alone system, low power consumption and fast execution by optimized algorithm are required. In this study, for the purpose of smart control, an energy measurement sensor is connected to an embedded system, and a real-time monitoring system is implemented to store measurement information as a database. Continuously measured and stored data is applied to a learning algorithm, which can be utilized for optimal power control, and a system interfacing various sensors required for energy measurement was constructed.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.53-62
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• 2020

In the end-user domain of an IoT environment, there are more and more intelligent M2M devices that provide resources to create and share application services. Therefore, it can be very useful to manage trust by transferring the role of the existing centralized service provider to end users in a P2P environment. However, in a decentralized M2M computing environment where end users independently provide or consume services, mutual trust building is the most important factor. This is because malicious users trying to build malfunctioning services can cause security problems in M2M computing environments such as IoT. In this paper, we provide an integrated analysis and approach for trust evaluation of M2M application services, and an optimized trust evaluation model that can guarantee reliability among users of the M2M community.

• Journal of Software Assessment and Valuation
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• v.16 no.1
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• pp.81-88
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• 2020

Various methods of differentiating and servicing digital content for individual users have been studied. Searching for association rules is a very useful way to discover individual preferences in digital content services. The Apriori algorithm is useful as an association rule extractor using frequent itemsets. However, the Apriori algorithm is not suitable for application to an actual content service because it considers only the reference count of each content. In this paper, we propose a new algorithm based on the Apriori that searches association rules by using purchase history and usage-time for each item. The proposed algorithm utilizes the usage time with the weight value according to purchase items. Thus, it is possible to extract the exact preference of the actual user. We implement the proposed algorithm and verify the performance through the actual data presented in the actual content service system.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.153-162
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• 2020

Digital image forgery detection is one of very important fields in the field of digital forensics. As the forged images change naturally through the advancement of technology, it has made it difficult to detect forged images. In this paper, we use passive forgery detection for copy paste forgery in digital images. In addition, it detects copy-paste forgery using the L₀ Norm-based LE operator, and compares the detection accuracy with the forgery detection using the existing L₂, L₁ Norm-based LE operator. In comparison of detection rates, the proposed lower triangular(Ayalneh and Choi) window was more robust to BAG mismatch detection than the conventional window filter. In addition, in the case of using the lower triangular window, the performance of image forgery detection was measured increasingly higher as the L₂, L₁ and L₀ Norm LE operator was performed.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.143-151
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• 2020

The digital content's security and authentication are important in the field of digital content application. There are some methods to perform the authentication. The digital watermarking is one of authentication methods. Paper presents a digital watermark authentication method that works in the application of digital image. The proposed watermark has the triple status information and performs the embedding and the detection without original Content. When authenticating the owner information of digital content, an autocorrelation function is used. In addition, a spread spectrum method is used to be adaptive to the signal of the original content in the frequency domain(DWT Domain). Therefore, the possibility of errors occurring in the detection of hidden information was reduced. it also has a advantage what Watermarking in DWT has faster embedding and detection time than other transformation domains(DFT, DCT, etc.). if it has a an image of size N=mXm, the computational amount can be reduced from O(N·logN) to O(N). The particular advantage is that it can hide more information(bits) per bit.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.47-57
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• 2021

Neuromorphic technology is proposed to complement the shortcomings of existing artificial intelligence technology by mimicking the human brain structure and computational process with hardware. NA-IDE has also been proposed for developing neuromorphic hardware-based IoT applications. To implement an SNN model in NA-IDE, commonly used input data must be transformed for use in the SNN model. In this paper, we implemented a neural coding method encoder component that converts image data into a spike train signal and uses it as an SNN input. The decoder component is implemented to convert the output back to image data when the SNN model generates a spike train signal. If the decoder component uses the same parameters as the encoding process, it can generate static data similar to the original data. It can be used in fields such as image-to-image and speech-to-speech to transform and regenerate input data using the proposed encoder and decoder.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.59-73
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• 2021

Recently, artificial intelligence has spread rapidly and popularized and expanded to the voice recognition personal service sector, and major countries have established artificial intelligence promotion strategies, but in the case of South Korea's defense domain, its influence is low with a geopolitical location with North Korea. This paper presents a total of six strategies for promoting South Korea's defense artificial intelligence, including establishing roadmaps, securing manpower, installing the artificial intelligence base, and strengthening cooperation among stakeholders in order to increase the impact of South Korea's defense artificial intelligence and successfully promote artificial intelligence. These suggestions are expected to establish the foundation for expanding the base of artificial intelligence.