• Asia pacific journal of information systems
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• v.18 no.1
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• pp.145-162
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• 2008

One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.21-30
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• 2014

Hypertension is one of the major causes of death in the world as it is related with cardiovascular or cerebrovascular disease, so it is needed to provide continuos management for blood pressure. This study selected Health Level 7 Fast Health Interoperability Resources (HL7 FHIR) as a bio-signal data exchange service model that can provide constant blood pressure management in the rapidly growing mobile health care environment. The HL7 FHIR framework developed communicates with the IEEE 11073-10407 Personal Health Device (PHD) protocol through the bluetooth Health Device Profile (HDP) between the manager (smart phone) and the agent (hemomanometer) and acquires information about blood pressure. According to the test results, it performed its tasks successfully including hypertension patients' blood pressure monitoring, management on measured records, generation of document, or transmission of measured information. Because in the actual, clinical environment, it is possible to transmit measured information through the TCP/IP protocol, it will be needed to conduct constant research on it and vitalize it in the field of mobile health care afterwards.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.551-554
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• 2008

JVM(Java Virtual Machine) has GUI(Graphical User Interface) facility and Platform Independance and is used on the embedded device such as set-top box and smart phone. This needs JVM to execute Java application in the embedded device. CVM(Classic Virtual Machine) which is the kind of JVM is designed for embedded device to have limited resources. To support GUI facility of JAVA uses PBP(Personal Basis Profile) which is included on CVM. The PBP defines the GUI Stardard API to support GUI facility. When the GUI Stardard API is implemented, JNI(Java Native Interface) is used to connect between Java Native Method and Native function in Operating System. In this pater, PBP which is defined by CVM has designed and implemented on the Real-Time Operating System, iRTOS.

• Safety and Health at Work
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• v.13 no.2
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• pp.148-154
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• 2022

Background: Bus driving is a mentally demanding activity that requires prolonged attention to ensure safety. The aim of the study was to assess mental fatigue caused by driving a public bus and to find a profile of workers at higher risk. Methods: We evaluated changes of critical flicker fusion (CFF) (index of central arousal) and heart rate variability (HRV) (index of autonomic balance) in a 6-hour driving shift on a real route, in 31 professional bus drivers, and we tested the influence of personal factors such as sleep quality, BMI, and age. Paired t-test was used to test differences of CFF and HRV between both initial and final phase of driving, while multiple linear regression tested the influence of personal variables on the indexes of mental fatigue. Results: Results showed that CFF significantly decreased after 6 hours of bus driving (41.91 Hz, sd 3.31 vs. 41.15 Hz, sd 3.15; p = 0.041), and heart rate significantly decreased in the final phase of driving, with respect to the initial phase (85 vs. 78 bpm, p = 0.027). Increasing age (beta = -0.729, p = 0.022), risk of obstructive sleep apnea syndrome (beta = -0.530, p = 0.04), and diurnal sleepiness (beta = -0.406, p = 0.017) showed a significant effect on influencing mental fatigue. Conclusion: Elderly drivers at higher risk of sleep disorders are more prone to mental fatigue, when exposed to driving activity. Monitoring indexes of central arousal and autonomic balance, coupled with the use of structured questionnaires can represent a useful strategy to detect profile of workers at higher risk of mental fatigue in such duty.

• Convergence Security Journal
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• v.8 no.4
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• pp.105-113
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• 2008

Mobile computing environment is known to be quite difficult to provide user with a stable Quality of Service (QoS) due to vehicle mobility nature. In order to protect the inherent characteristics of wireless network such as low bandwidth and high transmission delay along with the vehicle's mobility, many works are conducted to apply caching and prefetching methods. This paper presents a novel prefetching technique which is based on owner's profile. It is the scheme with the vehicle velocity, the visit frequency and resident time of specific region for vehicle owner's past given period, and the user profile which has owner's personal inclination about a certain place. The proposed scheme shown relatively superior performance in terms of the utilization ratio of prefetched information and the failure ratio of information retrieval than the previous methods.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.11-17
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• 2022

Data mining is the task of accessing useful information from a large capacity of data. It can also be referred to as searching for correlations that can provide clues about the future in large data warehouses by using computer algorithms. It has been used in the tourism field for marketing, analysis, and business improvement purposes. This study aims to analyze the tourist profile in Turkey through data mining methods. The reason relies behind the selection of Turkey is the fact that Turkey welcomes millions of tourist every year which can be a role model for other touristic countries. In this study, an anonymous and large-scale data set was used under the law on the protection of personal data. The dataset was taken from a leading tourism company that is still active in Turkey. By using the k-means clustering algorithm on this data, key parameters of profiles were obtained and people were clustered into groups according to their characteristics. According to the outcomes, distinguishing characteristics are gathered under three main titles. These are the age of the tourists, the frequency of their vacations and the period between the reservation and the vacation itself. The results obtained show that the frequency of tourist vacations, the time between bookings and vacations, and age are the most important and characteristic parameters for a tourist's profile. Finally, planning future investments, events and campaign packages can make tourism companies more competitive and improve quality of service. For both businesses and tourists, it is advantageous to prepare individual events and offers for the three major groups of tourists.

• The Journal of Korean Academic Society of Nursing Education
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• v.30 no.2
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• pp.160-169
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• 2024

Purpose: This study aimed to identify the career decision profiles for nursing students and analyze their career barriers, preparation behaviors, decision-making self efficacy, and adaptability according to the career decision profiles. Methods: This cross-sectional study used content analysis. A total of 219 nursing students enrolled in two private Korean universities participated in this study. The data were collected in person and via email between December 8 and 31, 2020. Results: The decidedness and comfort results were statistically significant. Four clusters were identified: undecided-uncomfortable, decided-uncomfortable, decided-comfortable, and undecided-comfortable. Most participants were found to be decided-uncomfortable, followed by decided-comfortable, undecided-uncomfortable, and undecided-comfortable. The self efficacy scores were higher for the decision-comfortable profile than for the undecided-uncomfortable and decided-uncomfortable profiles. The mean adaptability scores were higher for the decision-comfortable profile than for the undecided-comfortable profile. Career barriers were negatively correlated with preparation behavior, decision-making self efficacy, and adaptability, while preparative behaviors were positively correlated with decision-making self efficacy and adaptability. Decision-making self efficacy was positively correlated with adaptability. The mean career barriers, preparation behaviors, decision-making self efficacy, and adaptability scores differed significantly across profiles. The mean career barrier score was higher for the undecided-uncomfortable than for the decided-comfortable profile; preparation behaviors exhibited no significant differences. Conclusion: Tailored career coaching and counseling programs based on personal characteristics and areas of interest are needed for freshmen and senior nursing students to reduce career barriers and to improve preparation behaviors, decision-making self efficacy, and adaptability.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.21-41
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• 2010

This paper proposes a system that can serve users with appropriate search results through real time filtering, and implemented adaptive user profiling based personalized information retrieval system(PIRS) using users' implicit feedbacks in order to deal with the problem of existing search systems such as Google or MSN that does not satisfy various user' personal search needs. One of the reasons that existing search systems hard to satisfy various user' personal needs is that it is not easy to recognize users' search intentions because of the uncertainty of search intentions. The uncertainty of search intentions means that users may want to different search results using the same query. For example, when a user inputs "java" query, the user may want to be retrieved "java" results as a computer programming language, a coffee of java, or a island of Indonesia. In other words, this uncertainty is due to ambiguity of search queries. Moreover, if the number of the used words for a query is fewer, this uncertainty will be more increased. Real-time filtering for search results returns only those results that belong to user-selected domain for a given query. Although it looks similar to a general directory search, it is different in that the search is executed for all web documents rather than sites, and each document in the search results is classified into the given domain in real time. By applying information filtering using real time directory classifying technology for search results to personalization, the number of delivering results to users is effectively decreased, and the satisfaction for the results is improved. In this paper, a user preference profile has a hierarchical structure, and consists of domains, used queries, and selected documents. Because the hierarchy structure of user preference profile can apply the context when users perfomed search, the structure is able to deal with the uncertainty of user intentions, when search is carried out, the intention may differ according to the context such as time or place for the same query. Furthermore, this structure is able to more effectively track web documents search behaviors of a user for each domain, and timely recognize the changes of user intentions. An IP address of each device was used to identify each user, and the user preference profile is continuously updated based on the observed user behaviors for search results. Also, we measured user satisfaction for search results by observing the user behaviors for the selected search result. Our proposed system automatically recognizes user preferences by using implicit feedbacks from users such as staying time on the selected search result and the exit condition from the page, and dynamically updates their preferences. Whenever search is performed by a user, our system finds the user preference profile for the given IP address, and if the file is not exist then a new user preference profile is created in the server, otherwise the file is updated with the transmitted information. If the file is not exist in the server, the system provides Google' results to users, and the reflection value is increased/decreased whenever user search. We carried out some experiments to evaluate the performance of adaptive user preference profile technique and real time filtering, and the results are satisfactory. According to our experimental results, participants are satisfied with average 4.7 documents in the top 10 search list by using adaptive user preference profile technique with real time filtering, and this result shows that our method outperforms Google's by 23.2%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.371-378
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• 2014

As people are taking part in more versatile social activities, it becomes more frequent and more important for people to share personal information each other in appropriate level. Unfortunately, although the rapid spread of smart devices and advance of network technologies have brought many applications for information sharing into our hands, they do not provide effective mechanism for sharing personal information on collocated people. In this paper, we introduce an android application named WhoAmI which provides the functionality of sharing personal information on nearby users over Wi-Fi Direct as well as Wi-Fi network environment. According to the predefined access level such as business, community or friend, WhoAmI naturally provides profile information to accessible users. In addition, the information such as music, photo, movie can be effectively shared through the application.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.77-90
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• 2023

This study aims to investigate the potential of alternative credit assessment through Social Networking Sites (SNS) as a complementary tool to conventional loan review processes. It seeks to discern the impact of SNS usage characteristics and loan product attributes on credit loan repayment. To achieve this objective, we conducted a binomial logistic regression analysis examining the influence of SNS usage patterns, loan characteristics, and personal attributes on credit loan conditions, utilizing data from Company A's credit loan program, which integrates SNS data into its actual loan review processes. Our findings reveal several noteworthy insights. Firstly, with respect to profile photos that reflect users' personalities and individual characteristics, individuals who choose to upload photos directly connected to their personal lives, such as images of themselves, their private circles (e.g., family and friends), and photos depicting social activities like hobbies, which tend to be favored by individuals with extroverted tendencies, as well as character and humor-themed photos, which are typically favored by individuals with conscientious traits, demonstrate a higher propensity for diligently repaying credit loans. Conversely, the utilization of photos like landscapes or images concealing one's identity did not exhibit a statistically significant causal relationship with loan repayment. Furthermore, a positive correlation was observed between the extent of SNS usage and the likelihood of loan repayment. However, the level of SNS interaction did not exert a significant effect on the probability of loan repayment. This observation may be attributed to the passive nature of the interaction variable, which primarily involves expressing sympathy for other users' comments rather than generating original content. The study also unveiled the statistical significance of loan duration and the number of loans, representing key characteristics of loan portfolios, in influencing credit loan repayment. This underscores the importance of considering loan duration and the quantity of loans as crucial determinants in the design of microcredit products. Among the personal characteristic variables examined, only gender emerged as a significant factor. This implies that the loan program scrutinized in this analysis does not exhibit substantial discrimination based on age and credit scores, as its customer base predominantly consists of individuals in their twenties and thirties with low credit scores, who encounter challenges in securing loans from traditional financial institutions. This research stands out from prior studies by empirically exploring the relationship between SNS usage and credit loan repayment while incorporating variables not typically addressed in existing credit rating research, such as profile pictures. It underscores the significance of harnessing subjective, unstructured information from SNS for loan screening, offering the potential to mitigate the financial disadvantages faced by borrowers with low credit scores or those ensnared in short-term liquidity constraints due to limited credit history a group often referred to as "thin filers." By utilizing such information, these individuals can potentially reduce their credit costs, whereas they are supposed to accrue a more substantial financial history through credit transactions under conventional credit assessment system.