• Knowledge Management Research
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• v.20 no.2
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• pp.25-42
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• 2019

AI speakers which are wireless speakers with smart features have released from many manufacturers and adopted by many customers. Though smart features including voice recognition, controlling connected devices and providing information are embedded in many mobile phones, AI speakers are sitting in home and has a role of the central en-tertainment and information provider. Many surveys have investigated the important factors to adopt AI speakers and influ-encing factors on satisfaction. Though most surveys on AI speakers are cross sectional, we can track customer attitude toward AI speakers longitudinally by analyzing customer reviews on AI speakers. However, there is not much research on the change of customer attitude toward AI speaker. Therefore, in this study, we try to grasp how the attitude of AI speaker changes with time by applying text mining-based analysis. We collected the customer reviews on Amazon Echo which has the highest share of AI speakers in the global market from Amazon.com. Since Amazon Echo already have two generations, we can analyze the characteristics of reviews and compare the attitude ac-cording to the adoption time. We identified all sub topics of customer reviews and specified the topics for smart features. And we analyzed how the share of topics varied with time and analyzed diverse meta data for comparisons. The proportions of the topics for general satisfaction and satisfaction on music were increasing while the proportions of the topics for music quality, speakers and wireless speakers were decreasing over time. Though the proportions of topics for smart fea-tures were similar according to time, the share of the topics in positive reviews and importance metrics were reduced in the 2nd generation of Amazon Echo. Even though smart features were mentioned similarly in the reviews, the influential effect on satisfac-tion were reduced over time and especially in the 2nd generation of Amazon Echo.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1449-1461
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• 2018

As the number of software vulnerabilities grows year by year, attacks on software are also taking place a lot. As a result, the security administrator must identify and patch vulnerabilities in the software. However, it is important to prioritize the patches because patches for all vulnerabilities are realistically hard. In this paper, we propose a scoring system that expands the scale of risk assessment metric by taking into consideration attack patterns or weaknesses cause vulnerabilities with the vulnerability information provided by the NIST(National Institute of Standards and Technology). The proposed scoring system is expanded based on the CWSS and uses only public vulnerability information to utilize easily for any company. In this paper, we applied the automated scoring system to software vulnerabilities, and showed the expanded metrics with consideration for influence of attack pattern and weakness are meaningful.

• The Journal of Korean Association of Computer Education
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• v.22 no.2
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• pp.21-28
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• 2019

In this research, Problem Solving and Programming - the chapter common among four different types of middle school informatics textbooks based on the national curriculum revised in 2015 - was analyzed to measure its effects on cultivating students' curiosities. Romey's analysis was applied to these textbooks on four analytic elements - texts, data, activities, and evaluation. The results showed that each type of textbook showed a differing degree of encouraging students' inquisitive tendencies on each analytic element; two out of four textbooks were well developed for texts, three for data, three for activities, and all four for evaluation. In terms of Romey's index points, two textbooks had low indexes of texts, such as 0.185 and 0.413. Data indices were extremely low in one textbook at 0.147. Three of four textbooks exhibited high indices of activities at 0.969, 0.608 and 0.627. Evaluation indices were high in all four textbooks at 1.333, 1.268, 1.274, and 0.764. These revised textbooks overall showed higher metrics than the previously designed textbooks with regards to promoting students' inquisitive nature.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.1-9
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• 2019

The purposes of the study are to investigate Koreans' perception about Vietnam by analyzing social big data and to seek changing direction in perception. For the purposes, the texts about Vietnam in Naver Blog and Twitter and the number of search and click for Vietnam in Naver were analyzed by Social Metrics of Daum Soft and Datalab of Naver. The study also analyzed the annual change of their interest in Vietnam based on social media. The results showed that Koreans still remember the Vietnam war, have a positive emotion toward Vietnam, and view Vietnam as a country where we can gain mutual benefit by exchange. The findings also indicated that Koreans perceive Vietnam as a favorite tourist spot regardless of age. Meanwhile, children under 12 showed a different pattern of an annual change in perception. It might be a positive sign that Koreans' interest region toward Vietnam would be diversified because children under 12 would be the central axis of cultural contents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.75-82
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• 2018

In this paper, we consider a precoder design for downlink multiuser multiple-input multiple-output (MU-MIMO) in distributed antenna systems (DAS). In DAS, remote radio heads (RRHs) are placed at geographically different locations within a cell area. Three different precoder design schemes are proposed to maximize the separate or joint signal-to-leakage-plus-noise ratio (SLNR) metrics by considering RRH sum power or per-RRH power constraints. The analytical closed-form form solution for each optimization problem is presented. Through computer simulation, we show that the joint SLNR based precoding schemes have better signal-to-interference-plus-noise ratio (SINR) and bit error rate (BER) performances than the separate SLNR based schemes. Also, it is shown that the precoding scheme with RRH sum power constraint has better performance than the precoding scheme with per-RRH power constraint.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.527-530
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• 2014

DASH is a well-known streaming technology, which was proposed in 2010 by MPEG and standardized in 2011. Major multimedia contents service providers, including Apple, Microsoft, and Adobe are all using this technology to support their media streaming services. Whenever a new service is requested to the server, the DASH technology helps servicing the multimedia streaming to client by recognizing the capacity of network and by adapting the quality of the multimedia contents. In DASH, the quality of multimedia contents will be automatically lowered to meet the fluctuating network status, when undesirable breaks interrupt the network. In this paper, we classified and analysed the advantages and disadvantages of DASH researches in three aspects: bit-rate measurement method, bandwidth aggregation method; rate adaptation metrics, algorithms and logics; user's experiences and QoE.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.17-32
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• 2019

Purpose: CMMI is a process model used to assess or improve an organization's software development capabilities. This paper deals with the quality indicators when using CMMI and their priorities for possible improvement. Methods: The 22 process areas and 167 practices of CMMI are matched with 60 indicators of Quality Scorecard(QSC) first to analyze the balance of CMMI in terms of prevention, appraisal, and final result categories and second to isolate a set of key areas for quality focused performance measures. Results: A total of 86.2% (144 out of 167) CMMI practices were mapped to QSC. According to the CMMI level of maturity, level 2 and 3 accounted for more than 75% of the total. The practices at the maturity level of 4 and 5 were mapped to more than 52% of the final result's measurements. It has been observed that CMMI practices need further elaboration at higher levels to consider prevention, appraisal, and final results simultaneously. Conclusion: In order to improve the quality performance of the organization by applying CMMI, the final result measures should be refined in metrics, cycles, and methods, and then corrective actions could be conducted to improve the performance of CMMI practices. This strategy would help the practitioners benefit from CMMI in fostering the overall quality level of key activities for the organization's business goals.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.574-580
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• 2019

Conventional energy efficient routing protocols apply high weight to energy among routing metrics, causing nodes to concentrate on energy efficient paths and quickly exhaust energy on those paths. The unbalanced energy consumption of these wireless sensor networks causes network division and malfunction, and reduces network lifetime. Therefore, in this paper, it proposes a link cost based routing protocol to solve the unbalanced energy consumption of wireless sensor networks. The proposed routing protocol calculates the link cost by applying the weight of the routing metric differently according to the network problem situation and selects the path with the lowest value. As a result of the performance analysis, it confirmed that the proposed routing protocol has 22% longer network life, 2% energy consumption standard deviation and 2% higher data reception rate than the existing AODV protocol.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.135-141
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• 2019

Recently, there has been active researches about building an artificial intelligence agent that can learn how to play a game by using re-enforcement learning. The performance of the learning can be diverse according to what kinds of deep learning activation functions they used when they train the agent. This paper compares the activation functions when we train our agent for learning how to play a 2D shooting game by using re-enforcement learning. We defined performance metrics to analyze the results and plotted them along a training time. As a result, we found ELU (Exponential Linear Unit) with a parameter 1.0 achieved best rewards than other activation functions. There was 23.6% gap between the best activation function and the worst activation function.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.51 no.6
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• pp.632-639
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• 2018

To develop the high-value added seafood products from a regional speciality seafood, the seasoned dried pen shell Atrina pectinata adductor (SDPA) and seasoned smoke-dried pen shell adductor (SSPA) samples were prepared, and their optimal processing conditions, quality metrics, and shelf-life characteristics were examined. SDPA and SSPA samples were produced by thawing of frozen pen shell adductor, and cutting it into 6-7 mm slices, hot-air drying ($60^{\circ}C$, 20 min) or smoking ($110^{\circ}C$, 20 min), seasoning ($4^{\circ}C$, 12 h) with seasoning powder (60% sorbitol, 15% sucrose, 16% salt and 9.0% monosodium glutamate), hot-air drying ($60^{\circ}C$, 3 h), torching, vacuum-packaging in a laminated plastic film bag, heat treating with hot-water ($85^{\circ}C$, 15 min), and cooling. The moisture content of SDPA and SSPA samples was 44.5 and 43.0%, respectively, and the water activity was 0.845 and 0.842. The total amino acids in SDPA and SSPA samples were 20,986.8 and 21,312.4 mg/100 g, respectively, and the major amino acids in both products were aspartic acid, serine, glutamic acid, proline, glycine, alanine, valine, leucine, phenylalanine, lysine and arginine. The primary minerals were Na, S, K and P. Incubating tests indicated that the quality of SDPA and SSPA samples was maintained for 30 days of storage.