• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.871-874
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• 2013

사용자 경험은 사용자가 제품을 사용 하면서 상호 작용을 통해 얻게 된 경험을 의미 하며 과정지향적인 인터랙티브 제품 일수록 보다 나은 경험을 위해 경험요소를 계획 하고 구성 하는 사용자 경험 디자인의 비중이 높다. 이는 어플리케이션의 기술적 완성도 및 상업적 성공 여부에도 영향을 미친다. 본 논문은, 인터랙션 디자인 분야의 사용자 모델 퍼소나(persona)와 이를 도입한 퍼소나 기반 시나리오 기법(Persona-Based Scenario)을 통하여 도출해낸 요구 사항을 토대로 기존의 사용자 경험 설계 연구 보다 사용자 중심적으로 향상된 인터랙션 프레임워크를 제공 하는데 목적을 두고 있다.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.2
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• pp.93-100
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• 2022

In this paper, we propose a machine learning-based method for supporting resource management of IoT software platforms in a multi-modal sensing scenario. We assume that an IoT device installed with a oneM2M-compatible software platform is connected with various sensors such as PIR, sound, dust, ambient light, ultrasonic, accelerometer, through different embedded system interfaces such as general purpose input output (GPIO), I2C, SPI, USB. Based on a collected dataset including CPU usage and user-defined priority, a machine learning model is trained to estimate the level of nice value required to adjust according to the resource usage patterns. The proposed method is validated by comparing with a rule-based control strategy, showing its practical capability in a multi-modal sensing scenario of IoT devices.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.121-127
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• 2008

User needs in residential environment have very complicated and variety connection with others. u-home system for the near future is need to be combined acceptance of exist user needs as well as needs on new technology relating with u-Home. The study proposes a User Behavior Analysis Framework - UBAF for applying the user needs to the system more efficiently and developing the system by classifying patterns for the needs based on date of user behavior analysis. UBAF is a developing framework getting the basic idea of combining system modeling methods on SE and user modeling methods considering on HCI. It will be applicable to develop the system with core user behaviors by applying a standard way on u-Home. For example, the study transforms information into knowledge the system modeling and user modeling with analyzing a scenario for indoor temperature controlling on u-Home.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• Management & Information Systems Review
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• v.31 no.1
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• pp.205-219
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• 2012

This study is to understand how why users fail to service and how users use service recovery strategics. This study use equity theory to understand how perceived justices have influence on trust and to identify how trust has influence on service quality. This study used scenario techquie to get user experience of service failure in smartphone application. Scenario is composed of 16 sub scenario and we conducted survey with each case. The results show that interpersonal justice and distributed justice have significantly influence on trust. However, procedural justice has not influence on trust. Service quality is influenced by trust. This paper conclude with statements of implications and limitations of the study results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1594-1617
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• 2018

In this paper, we consider a spectrum access scenario which consists of two groups of users, namely Primary Users (PUs) and Secondary Users (SUs) in Cooperative Cognitive Radio Networks (CCRNs). SUs cooperatively relay PUs messages based on Amplify-and-Forward (AF) and Decode-and-Forward (DF) cooperative techniques, in exchange for accessing some of the spectrum for their secondary communications. From the literatures, we found that the Conventional Distributed Algorithm (CDA) and Pragmatic Distributed Algorithm (PDA) aim to maximize the PU sum-rate resulting in a lower sum-rate for the SU. In this contribution, we have investigated a suit of distributed matching algorithms. More specifically, we investigated SU-based CDA (CDA-SU) and SU-based PDA (PDA-SU) that maximize the SU sum-rate. We have also proposed the All User-based PDA (PDA-ALL), for maximizing the sum-rates of both PU and SU groups. A comparative study of CDA, PDA, CDA-SU, PDA-SU and PDA-ALL is conducted, and the strength of each scheme is highlighted. Different schemes may be suitable for different applications. All schemes are investigated under the idealistic scenario involving perfect coding and perfect modulation, as well as under practical scenario involving actual coding and actual modulation. Explicitly, our practical scenario considers the adaptive coded modulation based DF schemes for transmission flexibility and efficiency. More specifically, we have considered the Self-Concatenated Convolutional Code (SECCC), which exhibits low complexity, since it invokes only a single encoder and a single decoder. Furthermore, puncturing has been employed for enhancing the bandwidth efficiency of SECCC. As another enhancement, physical layer security has been applied to our system by introducing a unique Advanced Encryption Standard (AES) based puncturing to our SECCC scheme.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.214-227
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• 2007

A context-aware service in ubiquitous computing environments aims to supply services according to users' situation information that is dynamically occurring. The existing context-aware workflow systems, such as FollowMe and uFlow, provide context-aware services based on a workflow, which uses users' situation information as transition conditions of a service. But they can't apply users' new service demands, which may dynamically occur even when a workflow is on going, to a workflow scenario. In this paper we propose a context-aware workflow system, which can reapply users' new service demands into an initial workflow without interrupting or deleting the workflow. The proposed system can provide context-aware services without interrupting of service by recognizing exactly a place holder that has to be changed in a workflow scenario and by reconstructing only the changed parts through an incremental parsing method. Therefore, a user can immediately apply his new service demands to an on-going workflow scenario, and he can be guaranteed continuous executions of context-aware services according to a workflow scenario, which includes new service demands.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1568-1574
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• 2009

One of the most difficult problems in user requirement engineering is the communication gap that exists between different end-users, stakeholders, and software engineers. Since scenarios allow different stakeholders to describe and review the problem in their own language instead of some abstract model, they are also a solution to the problem. We propose a progressive, iterative and interleaved process of using scenario at different requirement engineering stages including elicitation, analysis and validation. This process model has been applied to our TRES System. In our proposed system, we combine prototype, scenarios and use cases in a single and comprehensive framework to avoid most of the shortcomings in other tools. Our system is an XML-based system for scenario-driven requirement engineering. Within the TRES system, scenarios are stories capture information about users and their tasks, including the context of use. In our TRES system, scenarios are stored in XML-based database and described using XML notation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1325-1344
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• 2019

Recently, to satisfy mobile users' increasing data transmission requirement, energy efficiency (EE) resource allocation in distributed antenna systems (DASs) has become a hot topic. In this paper, we aim to maximize EE in DASs subject to constraints of the minimum data rate requirement and the maximum transmission power of distributed antenna units (DAUs) with different density distributions. Virtual cell is defined as DAUs selected by the same user equipment (UE) and the size of virtual cells is dependent on the number of subcarriers and the transmission power. Specifically, the selection rule of DAUs is depended on different scenarios. We develop two scenarios based on the density of DAUs, namely, the sparse scenario and the dense scenario. In the sparse scenario, each DAU can only be selected by one UE to avoid co-channel interference. In order to make the original non-convex optimization problem tractable, we transform it into an equivalent fractional programming and solve by the following two sub-problems: optimal subcarrier allocation to find suitable DAUs; optimal power allocation for each subcarrier. Moreover, in the dense scenario, we consider UEs could access the same channel and generate co-channel interference. The optimization problem could be transformed into a convex form based on interference upper bound and fractional programming. In addition, an energy-efficient DAU selection scheme based on the large scale fading is developed to maximize EE. Finally, simulation results demonstrate the effectiveness of the proposed algorithm for both sparse and dense scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1624-1641
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• 2015

Instantaneous relay (relay-without-delay) using interference alignment is a promising approach to neutralizing interference and improving system capacity. In Wang Chenwei's work, a 2-user scenario required both source and relay to access the global channel state information (CSI). This paper shows a new method of interference alignment improves the degrees of freedom (DoF) prominently for the 3-user MIMO interference channel with instantaneous relay. This new method is focused on the relay node that completes the alignment interference neutralization so the global CSI is obtained only once and the pressure on the base station can be mitigated. In addition, the 3-user MIMO interference channels with instantaneous relay can achieve 2M DoF when source and destination have M antennas, respectively. This method shows 33% improvement over the conventional method using interference alignment which obtains 3M/2 DoF.