• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.67-77
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• 2019

Today, companies are making efforts to improve the performance of workers by utilizing various IT-based mobile and internet devices. In pharmaceutical companies, salespeople are using the e-brochure to search for diverse expertise in real time. Through the e-brochure, pharmacists and doctors can be provided with the information they need, thereby increasing confidence in pharmaceuticals and salespeople. Salespeople can also use e-brochures to improve their work performance and to be more satisfied with their jobs. This study examines which functions of e-brochures satisfy salespeople and what attitudes to the e-brochures they need to have. This paper explains the effect of satisfaction and attitude to the e-brochures on job satisfaction through self-efficacy with statistical analysis. As a statistical result, the functions of e-brochures (professional knowledge, massive amount of data, easy searching, information updates, and the reflection of feedback) and attitudes to the e-brochures (importance, intention to use, belief in improvement, efficacy to use, and negative cognition) influence on self-efficacy of salespeople. Further, self-efficacy has mediating effects on the relationship between the functions of e-brochures / attitudes to e-brochures and job satisfaction. Exceptionally, the mediating effect of self-efficacy was not significant in relation to information updates / reflection of feedback and job satisfaction. These results will explain what functions should be focused for the future development of e-brochures. It will also suggest what attitudes the salespeople should have about e-brochures. Through these efforts, salespeople will be able to utilize new technology of e-brochures to satisfy their jobs and improve their performance.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.167-176
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• 2020

Recommendation Systems is the top requirements for many people and researchers for the need required by them with the proper suggestion with their personal indeed, sorting and suggesting doctor to the patient. Most of the rating prediction in recommendation systems are based on patient's feedback with their information regarding their treatment. Patient's preferences will be based on the historical behaviour of similar patients. The similarity between the patients is generally measured by the patient's feedback with the information about the doctor with the treatment methods with their success rate. This paper presents a new method of predicting Top Ranked Doctor's in recommendation systems. The proposed Recommendation system starts by identifying the similar doctor based on the patients' health requirements and cluster them using K-Means Efficient Clustering. Our proposed K-Means Clustering with Content Based Doctor Recommendation for Cancer (KMC-CBD) helps users to find an optimal solution. The core component of KMC-CBD Recommended system suggests patients with top recommended doctors similar to the other patients who already treated with that doctor and supports the choice of the doctor and the hospital for the patient requirements and their health condition. The recommendation System first computes K-Means Clustering is an unsupervised learning among Doctors according to their profile and list the Doctors according to their Medical profile. Then the Content based doctor recommendation System generates a Top rated list of doctors for the given patient profile by exploiting health data shared by the crowd internet community. Patients can find the most similar patients, so that they can analyze how they are treated for the similar diseases, and they can send and receive suggestions to solve their health issues. In order to the improve Recommendation system efficiency, the patient can express their health information by a natural-language sentence. The Recommendation system analyze and identifies the most relevant medical area for that specific case and uses this information for the recommendation task. Provided by users as well as the recommended system to suggest the right doctors for a specific health problem. Our proposed system is implemented in Python with necessary functions and dataset.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.5
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• pp.137-145
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• 2003

Nowadays, people can communicate with each other on any time at my place by development of wireless communications. But, the openness of mobile communications Poses serious security threats and the security is necessary on mobile communications to support the secure communication channel. The most commonly method is stream cipher for mobile communications. Generally, this stream cipher is implemented by LFSR(Linear Feedback Shift Register). On this paper proposes the modified mechanism of the S box is usually used in block cipher to advance security og the stream cipher and this mechanism is the modified three one in consideration og the randomness. Generally, S box that is function with nonlinear property makes data more strong by attack. The randomness test of the proposed algorithm is used Ent Pseudorandom Number Sequence Test Program and by the test result it proves that it has better randomness and serial correlation value than the based stream cipher on respective test.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2023-2030
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• 2022

A novel pulse fitting analysis (PFA) method is presented for the acquisition of nuclear spectra. The charging process of the feedback capacitor in the resistive feedback charge-sensitive preamplifier is equivalent to the impulsive pulse, and its impulse response function (IRF) can be obtained by non-linear fitting of the falling edge of the nuclear pulse. The integral of the IRF excluding the baseline represents the energy deposition of the particles in the detector. In addition, since the non-linear fitting process in PFA method is difficult to achieve in the conventional architecture of spectroscopy system, a new multi-channel analyzer (MCA) based on Zynq SoC is proposed, which transmits all the data of nuclear pulses from the programmable logic (PL) to the processing system (PS) by high-speed AXI-Stream in order to implement PFA method with precision. The linearity of new MCA has been tested. The spectrum of ¹³⁷Cs was obtained using LaBr₃(Ce) scintillator detector, and was compared with commercial MCA by ORTEC. The results of tests indicate that the MCA based on PFA method has the same performance as the commercial MCA based on pulse height analysis (PHA) method and excellent linearity for γ-rays with different energies, which infers that PFA method is an effective and promising method for the acquisition of spectra. Furthermore, it provides a new solution for nuclear pulse processing algorithms involving regression and iterative processes.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.1-27
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• 2012

Many companies have recently become interested in using social networking sites such as Twitter and Facebook as a new channel to communicate with their customers. For example, companies often offer "special deals" (e.g., coupons, discounts, free samples, etc.) to their customers who participate in promotions or events on social networking sites. Companies often make important announcements on their products or services on social networking sites. By doing so, customers are encouraged to continue to have relationships with companies on social networking sites and to recommend the companies' presence on social networking sites to other potential customers. Moreover, customers who keep close relationships with companies on social networking sites often provide the companies with valuable suggestions and feedback. For instance, Starbucks has more than 2 million followers on Twitter, and often receive suggestions and feedback for their product offerings and services from the followers on Twitter. Although companies realize potential benefits of using social networking sites as a channel to communicate with their customers, it appears that many companies have difficulty forging long-lasting relationships with customers on social networking sites. It is often reported that many customers who had followed companies on Twitter later stopped following them for various reasons. Therefore, it is an important issue to understand what motivates customers to continue to keep relationships with companies on social networking sites. Nonetheless, due attention has yet paid to this issue until recently. This study intends to contribute to our understanding on customers' intention to continue to follow companies on Twitter and to spread positive word-of-mouth about companies on Twitter. Specifically, we identify seven potential factors that customers perceive as important in evaluating their experience with companies on Twitter. The seven factors include similarity, receptivity, interactivity, ubiquitous connectivity, enjoyment, usefulness and transparency. We posit that the seven perception factors can affect the two types of satisfaction, emotional and cognitive, which can in turn influence on customers' intention to follow companies on Twitter and to spread positive word-of-mouth about companies on Twitter. Research hypotheses formulated in this study were tested with data collected from a questionnaire survey administered to customers who had been following companies on Twitter. The data was analyzed with the partial least square (PLS) approach to structural equation modeling. The results of data analysis based on 177 usable responses were generally supportive of our predictions for the effects of the seven factors identified and the two types of satisfaction. In particular, out results suggest that emotional satisfaction was strongly influenced by perceived similarity, perceived receptivity, perceived enjoyment, and perceived transparency. Cognitive satisfaction was significantly influenced by perceived similarity, perceived interactivity, perceived enjoyment, and perceived transparency. While cognitive satisfaction was found to have significant and positive effects on both continued following and word-of-mouth intentions, emotional satisfaction had a significant and positive effect only on word-of-mouth intention.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11A
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• pp.1263-1270
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• 2004

A low-power 64-point FFT/IFFT processor core is designed, which is an essential block in OFDM-based wireless LAM modems. The radix-2/418 DIF (Decimation-ln-Frequency) FFT algorithm is implemented using R2SDF (Radix-2 Single-path Delay Feedback) structure. Some design techniques for low-power implementation are considered from algorithm level to circuit level. Based on the analysis on infernal data flow, some unnecessary switching activities have been eliminated to minimize power dissipation. In circuit level, constant multipliers and complex-number multiplier in data-path are designed using truncation structure to reduce gate counts and power dissipation. The 64-point FFT/IFFT core designed in Verilog-HDL has about 28,100 gates, and timing simulation results using gate-level netlist with extracted SDF data show that it can safely operate up to 50-MHz＠2.5-V, resulting that a 64-point FFT/IFFT can be computed every 1.3-${\mu}\textrm{s}$. The functionality of the core was fully verified by FPGA implementation using various test vectors. The average SQNR of over 50-dB is achieved, and the average power consumption is about 69.3-mW with 50-MHz＠2.5-V.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.107-113
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• 2016

Following the recent advancement in the use of social networks, a vast amount of different online reviews is created. These variable online reviews which provide feedback data of contents' are being used as sources of valuable information to both contents' users and providers. With the increasing importance of online reviews, studies on opinion mining which analyzes online reviews to extract opinions or evaluations, attitudes and emotions of the writer have been on the increase. However, previous sentiment analysis techniques of opinion-mining focus only on the classification of reviews into positive or negative classes but does not include detailed information analysis of the user's satisfaction or sentiment grounds. Also, previous designs of the sentiment analysis technique only applied to one content domain that is, either product or movie, and could not be applied to other contents from a different domain. This paper suggests a sentiment analysis technique that can analyze detailed satisfaction of online reviews and extract detailed information of the satisfaction level. The proposed technique can analyze not only one domain of contents but also a variety of contents that are not from the same domain. In addition, we design a system based on Hadoop to process vast amounts of data quickly and efficiently. Through our proposed system, both users and contents' providers will be able to receive feedback information more clearly and in detail. Consequently, potential users who will use the content can make effective decisions and contents' providers can quickly apply the users' responses when developing marketing strategy as opposed to the old methods of using surveys. Moreover, the system is expected to be used practically in various fields that require user comments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.179-187
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• 2018

This study purpose is to improve athletes by investigating the relation between the leadership behavior type of athletes and athlete satisfaction and exercise flow. The sampling method was non-probabilistic sampling method. The number of questionnaires was 381 for analyzing the data. SPSS/PC+ Window 21.0 version statistical program were used for analyzing the questionnaire answers. Frequency analysis, factor analysis, correlation analysis and multiple regression analysis were used. The study results are as follows. First, there were positive correlations between leadership behavior type of athletes and athlete satisfaction and exercise flow, but not between authoritative behavior of leader behavior type and exercise flow. Second, the effect of leadership behavior type of athletes on satisfaction of athletes was positive on social interaction related with training, instruction, and social support, on task execution related with training and instruction, and on coaching related with training, instruction, and positive feedback. Third, the effect of leadership behavior type of athletes on flow of exercise was positive on cognitive commitment related with training, instructions and positive feedback, and on behavioral commitment related with training, instructions, positive feedback, and social interaction. So, athletes will be able to perform good exercise skills if they come to the game in flowing exercise satisfaction and exercise.

• Journal of Korea Water Resources Association
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• v.43 no.7
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• pp.609-623
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• 2010

In this paper the feedback loop mechanisms that are inherent in the management of water supply systems were identified based on the system dynamics modeling methodology. As a result, a system dynamics (SD) computer simulation model that can be used to aid efficient management of water supply systems was developed. The developed SD model can be used to predict operating conditions of water supply systems including the effects of pipe maintenance on the entire system. The developed model is consisted of water supply, pipe maintenance and water supply business finance model. The operation and maintenance data from a study water supply system were used to verify the model and to predict the past and future operating conditions of the system. The policy leverage that greatly affects the operating condition was evaluated by the sensitivity analyses for the operational indices due to changes in the exogenous variables. It was found that while the pipe maintenance related exogenous variables had great effects on the leakage and conditions of pipes, they did not have great effects on the major operational indices such as revenue water ratio. It is considered that the social costs due to leaks and pipe breaks and the corresponding mechanism of propagation of the costs must be modeled to better evaluate the effects of pipe maintenance on the operational conditions of water supply systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.465-469
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• 2000

This paper describes a single-chip full-custom implementation of pipelined adaptive decision-feedback equalizer (PADFE) using a 0.25-${\mu}{\textrm}{m}$ CMOS technology for wide-band wireless digital communication systems. To enhance the throughput rate of ADFE, two pipeline stage are inserted into the critical path of the ADFE by using delayed least-mean-square (DLMS) algorithm Redundant binary (RB) arithmetic is applied to all the data processing of the PADFE including filter taps and coefficient update blocks. When compared with conventional methods based on two's complement arithmetic, the proposed approach reduces arithmetic complexity, as well as results in a very simple complex-valued filter structure, thus suitable for VLSI implementation. The design parameters including pipeline stage, filter tap, coefficient and internal bit-width and equalization performance such as bit error rate (BER) and convergence speed are analyzed by algorithm-level simulation using COSSAP. The singl-chip PADFE contains about 205,000 transistors on an area of about 1.96$\times$1.35-$\textrm{mm}^2$. Simulation results show that it can safely operate with 200-MHz clock frequency at 2.5-V supply, and its estimated power dissipation is about 890-mW.