• Journal of Industrial Convergence
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• v.19 no.6
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• pp.37-47
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• 2021

Today, people share information and communicate with others using various information and communication media such as e-mail, smartphones, SNS, etc. However, it is being used in malicious attacks to send a large amount of illegal spam or to use it for fraud by using illegally collected personal information and devices that are vulnerable to security. Illegal spam, smishing, and fraudulent mail(SCAM) cause a lot of direct and indirect damage to companies and users, including not only social costs such as mental fatigue, but also unnecessary consumption of IT infrastructure resources and economic losses. Although there are regulations related to spam, violators of the law are still on the rise by circumventing the law, and victims are constantly occurring, so it is necessary to review what the problem is. This study examined domestic and foreign spam-related regulations and spam-related response activities, identified problems, and suggested improvement countermeasures. Through this study, it was intended to suggest directions for improving spam-related systems in order to block illegal spam and prevent fraudulent damage.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.603-608
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• 2024

Nonresponse and missing values are caused by sample dropouts and avoidance of answers to surveys. In this case, problems with the possibility of information loss and biased reasoning arise, and a replacement of missing values with appropriate values is required. In this paper, as an alternative to missing values imputation, we compare several replacement methods, which use mean, linear regression, random forest, K-nearest neighbor, autoencoder and denoising autoencoder based on deep learning. These methods of imputing missing values are explained, and each method is compared by using continuous simulation data and real data. The comparison results confirm that in most cases, the performance of the random forest imputation method and the denoising autoencoder imputation method are better than the others.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1503-1517
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• 1994

Intelligent Motion Planning System(IMPS) is presented for a robot to achieve an efficient path toward the given target point in two dimensional unknown environment is constructed with unrestricted obstacle shapes. IMPS consists of three components for making intelligent motion. These components are real-time motion planning algorithm based on a discontinous boundary method, fuzzy neural network decision system for heuristic knowledge representation, and world modeling with forgetting and reinforcing memory cells. First of all, in real-time motion planning algorithm, the behavior-based architectural method is used to generate subgoal. A behavior generates a subgoal independently by using the method of discontinuous boundary in sensed area. The discontinuous boundary method is a new proposed fast obstacle avoidance algorithm. The second component is fuzzy neural network decision system for accomplishing the subgoal. The heuristic rules are imbedded on the fuzzy neural network to make an intelligent decision. The last one is a forgetting, reinforcing memory technique for the construction of external world map. The activation values of all activated memory cells in grid space are decreased monotonically and after all they are burned out. Therefore, after sufficient journey, robot can have a stationary world map even if the dynaic obstacles exist. Using the IMPS, several simulations show the efficient achievement of target point in unknown enviroment with obstcles of various shapes.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.12
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• pp.149-158
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• 2005

This paper proposes a congestion avoidance algorithm which provides stable throughput and transmission rate regardless of buffer size by limiting the TCP congestion window in fixed bandwidth networks. Additive Increase, Multiplicative Decrease (AIMD) is the most commonly used congestion control algorithm. But, the AIMD-based TCP congestion control method causes unnecessary packet losses and retransmissions from the congestion window increment for available bandwidth verification when used in fixed bandwidth networks. In addition, the saw tooth variation of TCP throughput is inappropriate to be adopted for the applications that require low bandwidth variation. We present an algorithm in which congestion window can be limited under appropriate circumstances to avoid congestion losses while still addressing fairness issues. The maximum congestion window is determined from delay information to avoid queueing at the bottleneck node, hence stabilizes the throughput and the transmission rate of the connection without buffer and window control process. Simulations have performed to verify compatibility, steady state throughput, steady state packet loss count, and the variance of congestion window. The proposed algorithm can be easily adopted to the sender and is easy to deploy avoiding changes in network routers and user programs. The proposed algorithm can be applied to enhance the performance of the high-speed access network which is one of the fixed bandwidth networks.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.10 s.352
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• pp.8-17
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• 2006

Recently, the high-speed Internet users increase rapidly and broadband networks have been widely deployed. However, the current TCP congestion control algorithm was designed for relatively narrowband network environments, and thus its performance is inefficient for traffic transport in broadband networks. To remedy this problem, the TCP having an enhanced congestion control algorithm is required for broadband networks. In this paper, we propose an improved TCP congestion control that can sufficiently utilize the large available bandwidth in broadband networks. The proposed algorithm predicts the available bandwidth by using ACK information and RTT variation, and prevents large packet losses by adjusting congestion window size appropriately. Also, it can rapidly utilize the large available bandwidth by enhancing the legacy TCP algorithm in congestion avoidance phase. In order to evaluate the performance of the proposed algorithm, we use the ns-2 simulator. The simulation results show that the proposed algorithm improves not only the utilization of the available bandwidth but also RTT fairness and the fairness between contending TCP flows better than the HSTCP in high bandwidth delay product network environment.

• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.141-151
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• 2019

Korea has passed the Act on the Integrated Control of Pollutant-Discharging Facilities in 2015, and the integrated environmental management under the BAT standard is underway. To summarize the nature of integrated environmental management, it is the regulation by the integration of the management of the multi-pollutant source and the technical standard of BATs. In general, in environmental economics, regulation-based on technical standards are known to be inefficient. This paper attempts to evaluate the efficiency of BAT standards from an economic point of view. A simple multi-pollutant model demonstrates that the inefficiency of the environmental tax with imperfect information in a single pollutant situation is amplified under multi-pollutant conditions. The simultaneous introduction of BAT and IPPC can be partially explained by this logic. It is also highlighted by the strengthening of BAT standards by EU, as a countermeasure to the potential deterioration of air quality caused by the change of effective environmental taxes accompanying the fuel and emission price changes.

• Knowledge Management Research
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• v.23 no.2
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• pp.143-168
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• 2022

Using Herzberg's motive hygiene theory, this study also investigated the influence of motivation factors and hygiene factors on acceptance and resistance of mobile facial recognition payment services, and the influence of consumer innovation as a parameter on acceptance and resistance from motivation factors and hygiene factors. A survey was conducted on Chinese users who had experience using mobile payment services. IBM SPSS Statistics 26 and SmartPLS 3.0 were used for statistical analysis. As a result of the analysis, the motivating factors of mobile facial recognition payment services have a positive (+) impact on acceptance, and there were no significant results on resistance. In addition, hygiene factors have been shown to have negative (-) effects on acceptance and positive (+) effects on resistance. Consumer innovation, which is a parameter in relation to motivation factors and acceptance and resistance, had a partial mediation effect, and a partial mediation effect was also seen in the relationship between hygiene factors and resistance, but no mediation effect was found in the relationship between hygiene factors and acceptance. The motivating factors found through research results such as rapidity, ubiquity, perceived usability, perceived ease of use, privacy concerns, security, status quo inertia, use barriers, and loss avoidance, which are factors of non-contact and hygiene, can be used as basic data for activating mobile facial recognition payment services.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.175-185
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• 2023

Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• Asia Marketing Journal
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• v.12 no.4
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• pp.55-78
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• 2011

Recently strategic alliance between business firms has become prevalent to overcome increasing competitive threats and to supplement resource limitation of individual firms. As one of allianced sales promotion activities, a new type of discount program, so called "Alliance Card Discount", is introduced with the partnership of credit cards and loyalty cards. The program mainly pursues short-term sales growth by larger discount scheme while spends less through cost share among alliance partners. Thus this program can be regarded as cost efficient discount promotion. But because there is no solid evidence that it can really deliver profitable sales growth, an empirical study for its effects on sales and profit should be conducted. This study has two basic research questions concerning the effects of allianced discount program ; 1)the possibility of sales increase 2) the profitability of the discount driven sales. In F&B industry, sales increase mainly comes from increased guest count. Especially in family restaurants, to increase the number of guests we need to enlarge the size of visitor group (number of visitors for one group) because customers visit by group in a special occasion. And because they pay the bill by group(table), the increase of sales per table is a key measure for sales improvement. The past researches for price & discount sensitivity and reference discount rate explain that price sensitive consumers have narrow reference discount zone and make rational purchase decision. Differently from all time discount scheme of regular sales promotions, the alliance card discount program only provides the right to get discount like discount coupon. And because it is usually once a month opportunity given by the past month usage level, customers tend to perceive alliance card discount as a rare chance to get. So that we can expect customers try to maximize the discount effect when they use the limited discount opportunity. Considering group visiting practice and low visit frequency of family restaurants, the way to maximize discount effect should be the increase the size of visit group. And their sensitivity to discount and rational consumption behavior defer the additional spending for ordering high price menu, even though they get considerable amount of savings from the discount. From the analysis of sales data paid by alliance discount cards for four months, we found the below. 1) The relation between discount rate and number of guest per table is positive : 25% discount results one additional guest 2) The relation between discount rate and the spending per guest is negative. 3) However, total profit amount per table is increased when discount rate is increased. 4) Reward point accumulation & redemption did not show any significant relationship with the increase of number of guests. These results suggest that the allianced discount program substantially contributes to sales increase and profit improvement by increasing the number of guests per table. Though the spending per guest is decreased by discount rate increase, the total amount of profit per table is improved. It seems the incremental profit by increased guest count offsets the profit decrease. Additional intriguing finding is the point reward system does not have any significant impact on the increase of number of guest, even if the point accumulation & redemption of loyalty program are usually regarded as another saving offers by customers. In sum, because it is proved that allianced discount program with credit cards and loyalty cards is effective to both sales drive and profit increase, the alliance card program could be recommended as strategically buyable program.