• International journal of advanced smart convergence
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• v.6 no.3
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• pp.29-37
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• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5820-5834
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• 2017

This paper investigates the channel selection problem with dynamic users and the asymmetric interference relation in distributed opportunistic spectrum access systems. Since users transmitting data are based on their traffic demands, they dynamically compete for the channel occupation. Moreover, the heterogeneous interference range leads to asymmetric interference relation. The dynamic users and asymmetric interference relation bring about new challenges such as dynamic random systems and poor fairness. In this article, we will focus on maximizing the tradeoff between the achievable utility and access cost of each user, formulate the channel selection problem as a directional graphical game and prove it as an exact potential game presenting at least one pure Nash equilibrium point. We show that the best NE point maximizes both the personal and system utility, and employ the stochastic learning approach algorithm for achieving the best NE point. Simulation results show that the algorithm converges, presents near-optimal performance and good fairness, and the directional graphical model improves the systems throughput performance in different asymmetric level systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.109-134
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• 2018

Collaborative Filtering (CF) is widely used in recommendation field, which can be divided into rating-based CF and learning-to-rank based CF. Although many methods have been proposed based on these two kinds of CF, there still be room for improvement. Firstly, the data sparsity problem still remains a big challenge for CF algorithms. Secondly, the malicious rating given by some illegal users may affect the recommendation accuracy. Existing CF algorithms seldom took both of the two observations into consideration. In this paper, we propose a recommendation method based on listwise learning-to-rank by incorporating users' social information. By taking both ratings and order of items into consideration, the Plackett-Luce model is presented to find more accurate similar users. In order to alleviate the data sparsity problem, the improved matrix factorization model by integrating the influence of similar users is proposed to predict the rating. On the basis of exploring the trust relationship between users according to their social information, a listwise learning-to-rank algorithm is proposed to learn an optimal ranking model, which can output the recommendation list more consistent with the user preference. Comprehensive experiments conducted on two public real-world datasets show that our approach not only achieves high recommendation accuracy in relatively short runtime, but also is able to reduce the impact of malicious ratings.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.494-507
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• 2020

This study proposed the movie recommendation system based on the user's personal information and movies rated using the method of k-clique and normalized discounted cumulative gain. The main idea is to solve the problem of cold-start and to increase the accuracy in the recommendation system further instead of using the basic technique that is commonly based on the behavior information of the users or based on the best-selling product. The personal information of the users and their relationship in the social network will divide into the various community with the help of the k-clique method. Later, the ranking measure method that is widely used in the searching engine will be used to check the top ranking movie and then recommend it to the new users. We strongly believe that this idea will prove to be significant and meaningful in predicting demand for new users. Ultimately, the result of the experiment in this paper serves as a guarantee that the proposed method offers substantial finding in raw data sets by increasing accuracy to 87.28% compared to the three most successful methods used in this experiment, and that it can solve the problem of cold-start.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.302-322
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• 2021

In the system of ciphertext policy attribute-based encryption (CP-ABE), only when the attributes of data user meets the access structure established by the encrypter, the data user can perform decryption operation. So CP-ABE has been widely used in personal health record system (PHR). However, the problem of key abuse consists in the CP-ABE system. The semi-trusted authority or the authorized user to access the system may disclose the key because of personal interests, resulting in illegal users accessing the system. Consequently, aiming at two kinds of existing key abuse problems: (1) semi-trusted authority redistributes keys to unauthorized users, (2) authorized users disclose keys to unauthorized users, we put forward a CP-ABE scheme that has authority accountability, user traceability and supports arbitrary monotonous access structures. Specifically, we employ an auditor to make a fair ruling on the malicious behavior of users. Besides, to solve the problem of user leaving from the system, we use an indirect revocation method based on trust tree to implement user revocation. Compared with other existing schemes, we found that our solution achieved user revocation at an acceptable time cost. In addition, our scheme is proved to be fully secure in the standard model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2590-2606
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• 2014

A problem related to deployment of femtocells is how to manage access of users to radio resources. On one hand, all resources of the femtocell can be reserved for users belonging to a closed subscriber group (CSG), which is a set of users defined by a femtocell subscriber. This approach, known as closed access, however, increases interference to users not included in the CSG as those users do not have a permission to access this femtocell. Contrary, resources can be shared by all users with no priority in an open access mode. In this case, the femtocell subscriber shares radio as well as backhaul resources with all other users. Thus, throughput and quality of service of the subscriber and the CSG users can be deteriorated. To satisfy both the CSG as well as non-CSG users, a hybrid access is seen as a compromise. In this paper, we propose a new approach for sharing radio resources among all users. As in common cases, the CSG users have a priority for usage of a part of resources while rest of the resources is shared by all users proportionally to their requirements. As the simulation results show, the proposed resource sharing scheme significantly improves throughput of the CSG users and their satisfaction with granted bitrates. At the same time, throughput and satisfaction of the non-CSG users is still guaranteed roughly at the same level as if conventional sharing schemes are applied.

• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.901-911
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• 2005

With the development of e-commerce and the proliferation of easily accessible information, information filtering has become a popular technique to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. While many collaborative filtering systems have succeeded in capturing the similarities among users or items based on ratings to provide good recommendations, there are still some challenges for them to be more efficient, especially the user bias problem, non-transitive association problem and cold start problem. Those three problems impede us to capture more accurate similarities among users or items. In this paper, we provide probabilistic model approaches for UCHM and ICHM which are suggested to solve the addressed problems in hopes of achieving better performance. In this probabilistic model, objects (users or items) are classified into groups and predictions are made for users considering the Gaussian distribution of user ratings. Experiments on a real-word data set illustrate that our proposed approach is comparable with others.

• IE interfaces
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• v.15 no.1
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• pp.73-81
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• 2002

In mobile phone, complex user interface tend to cause the degradation of product usability. This problem is mainly due to the small hardware user interface of mobile phone. That is, because many functions must be operated in small hardware interface, the principle of one-to-one mapping between a function and a control is disregarded in design, often. In order to resolve this problem, users' characteristics must be considered in the user interface design of mobile phone. So, users' basic characteristics that must be considered in the user interface design of mobile phone were studied through two experiments, questionnaire survey and user testing.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.4
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• pp.1-19
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• 2003

This paper studies power and rate control for data users on the forward link of CDMA system with two cells. The QoS for data users is specified by delay and error rate constraints as well as a family of utility functions representing system throughput and fairness among data users. Optimal power and rate allocation problem is mathematically formulated as a nonlinear programming problem, which is to maximize total utility under delay and error rate constraints, and optimal power and rate allocation scheme (OPRAS) is proposed to obtain a good solution in a fast time. Computational experiments show that the proposed scheme OPRAS works very well and increases total utility compared to the separate power and rate allocation scheme (SPARS) which considers each cell individually.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.77-85
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• 2018

Multi-User Multiple-Input Multiple-Output (MU-MIMO) is the core technology for improving the channel capacity compared to Single-User MIMO (SU-MIMO) by using multiuser gain and spatial diversity. Key problem for the MU-MIMO is the user selection which is the grouping the users optimally. To solve this problem, we adopt Extreme Value Theory (EVT) at the beginning of the proposed algorithm, which defines a primary user set instead of a single user that has maximum channel power according to a predetermined threshold. Each user in the primary set is then paired with all of the users in the system to define user groups. By comparing these user groups, the group that produces a maximum sum rate can be determined. Through computer simulations, we have found that the proposed method outperforms the conventional technique yielding a sum rate that is 0.81 bps/Hz higher when the transmit signal to noise ratio (SNR) is 30 dB and the total number of users is 100.