• Title/Summary/Keyword: Ambient Service Model

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Implementation of Dynamic Context-Awareness Platform for Internet of Things(IoT) Loading Waste Fire-Prevention based on Universal Middleware (유니버설미들웨어기반의 IoT 적재폐기물 화재예방 동적 상황인지 플랫폼 구축)

  • Lee, Hae-Jun;Hwang, Chi-Gon;Yoon, Chang-Pyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.8
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    • pp.1231-1237
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    • 2022
  • It is necessary to dynamic recognition system with real time loading height and pressure of the loading waste, the drying of wood, batteries, and plastic wastes, which are representative compositional wastes, and the carbonization changes on the surface. The dynamic context awareness service constituted a platform based on Universal Middleware system using BCN convergence communication service as a Ambient SDK model. A context awareness system should be constructed to determine the cause of the fire based on the analysis data of fermentation heat point with natural ignition from the load waste. Furthermore, a real-time dynamic service platform that could be apply to the configuration of scenarios for each type from early warning fire should be built using Universal Middleware. Thus, this issue for Internet of Things realize recognition platform for analyzing low temperature fired fire possibility data should be dynamically configured and presented.

Temperature effect analysis of a long-span cable-stayed bridge based on extreme strain estimation

  • Yang, Xia;Zhang, Jing;Ren, Wei-Xin
    • Smart Structures and Systems
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    • v.20 no.1
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    • pp.11-22
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    • 2017
  • The long-term effect of ambient temperature on bridge strain is an important and challenging problem. To investigate this issue, one year data of strain and ambient temperature of a long-span cable-stayed bridge is studied in this paper. The measured strain-time history is decomposed into two parts to obtain the strains due to vehicle load and temperature alone. A linear regression model between the temperature and the strain due to temperature is established. It is shown that for every $1^{\circ}C$ increase in temperature, the stress is increased by 0.148 MPa. Furthmore, the extreme value distributions of the strains due to vehicle load, temperature and the combination effect of them during the remaining service period are estimated by the average conditional exceedance rate approach. This approach avoids the problem of declustering of data to ensure independence. The estimated results demonstrate that the 95% quantile of the extreme strain distribution due to temperature is up to $1.488{\times}10^{-4}$ which is 2.38 times larger than that due to vehicle load. The study also indicates that the estimated extreme strain can reflect the long-term effect of temperature on bridge strain state, which has reference significance for the reliability estimation and safety assessment.

System identification of an in-service railroad bridge using wireless smart sensors

  • Kim, Robin E.;Moreu, Fernando;Spencer, Billie F.
    • Smart Structures and Systems
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    • v.15 no.3
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    • pp.683-698
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    • 2015
  • Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

Ambient Information System with Three steps Medical Service Model for Chronological Disease Care (3단 의료정보 분석기법을 이용한 만성질환 관리 앰비언트 정보 시스템)

  • Kim, Dae gun;Kim, Mun Jung;Kim, Hee Jae;Youn, Chan Hyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2010.11a
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    • pp.1815-1817
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    • 2010
  • TMSM을 통한 검진 및 센싱 결과를 바탕으로 다량의 복잡한 의료 정보를 지능적으로 통합하는 의료서비스 방식과 앰비언트 정보 시스템을 통한 시각화 시스템은 환자의 상태를 실시간으로 모니터링하며, 환자의 응급상황에 대하여 보다 유연하고 조기 적으로 대처할 수 있게 하여 정보 인지적 부담을 덜고, 인적, 진단 비용을 절약할 수 있다.

Effects of E-servicescape and Positive Emotion on Purchase Intention for Fashion Products (인터넷 패션쇼핑몰의 e-서비스스케이프가 구매의도에 미치는 영향)

  • Lee, Chaeyeon;Park, Eunjoo
    • Korean Journal of Human Ecology
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    • v.22 no.1
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    • pp.157-166
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    • 2013
  • The purpose of this paper is to develop and test a conceptual model of purchase intentions, positive emotion, and e-servicescape that is defined as the online environment factors that exist during service delivery. Survey research method was used to gather data regarding consumers' perceptions of e-servicescape. Surveys were administered to 681 college students who experienced purchasing fashion products on the Internet. The results showed that e-servicescapes perceived by fashion consumers were composed of three dimensions: (1) Aesthetic appeal, (2) Ambient conditions, and (3) Layout & functionality. These dimensions of e-servicescape influenced consumers to lead positive emotions and purchase intentions. Additionally, positive emotions constituted a key variable for the purchase intention of fashion products during online exchange. The study revealed that consumers' interpretations of online environments exerted a powerful influence over positive emotion and purchase intentions. Also, it strongly endorsed the view that the purchase intentions of customers were linked to the extent to which they feel positive emotions by the e-service provider. This study provides insights into how consumers' interpretations of e-servicescape affect their subsequent positive emotions and ultimately their intentions to purchase. The findings of this study also have numerous implications for both services managers and internet developers related to fashion products.

Improved Sensor Filtering Method for Sensor Registry System (센서 레지스트리 시스템을 위한 개선된 센서 필터링 기법)

  • Chen, Haotian;Jung, Hyunjun;Lee, Sukhoon;On, Byung-Won;Jeong, Dongwon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.1
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    • pp.7-14
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    • 2022
  • Sensor Registry System (SRS) has been devised for maintaining semantic interoperability of data on heterogeneous sensor networks. SRS measures the connectability of the mobile device to ambient sensors based on positions and only provides metadata of sensors that may be successfully connected. The step of identifying the ambient sensors which can be successfully connected is called sensor filtering. Improving the performance of sensor filtering is one of the core issues of SRS research. In reality, GPS sometimes shows the wrong position and thus leads to failed sensor filtering. Therefore, this paper proposes a new sensor filtering strategy using geographical embedding and neural network-based path prediction. This paper also evaluates the service provision rate with the Monte Carlo approach. The empirical study shows that the proposed method can compensate for position abnormalities and is an effective model for sensor filtering in SRS.

RESISTANCE ESTIMATION OF A PWM-DRIVEN SOLENOID

  • Jung, H.G.;Hwang, J.Y.;Yoon, P.J.;Kim, J.H.
    • International Journal of Automotive Technology
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    • v.8 no.2
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    • pp.249-258
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    • 2007
  • This paper proposes a method that can be used for the resistance estimation of a PWM (Pulse Width Modulation)-driven solenoid. By using estimated solenoid resistance, the PWM duty ratio was compensated to be proportional to the solenoid current. The proposed method was developed for use with EHB (Electro-Hydraulic Braking) systems, which are essential features of the regenerative braking system of many electric vehicles. Because the HU (Hydraulic Unit) of most EHB systems performs not only ABS/TCS/ESP (Electronic Stability Program) functions but also service braking function, the possible duration of continuous solenoid driving is so long that the generated heat can drastically change the level of solenoid resistance. The current model of the PWM-driven solenoid is further developed in this paper; from this a new resistance equation is derived. This resistance equation is solved by using an iterative method known as the FPT (fixed point theorem). Furthermore, by taking the average of the resistance estimates, it was possible to successfully eliminate the effect of measurement noise factors. Simulation results showed that the proposed method contained a sufficient pass-band in the frequency response. Experimental results also showed that adaptive solenoid driving which incorporates resistance estimations is able to maintain a linear relationship between the PWM duty ratio and the solenoid current in spite of a wide variety of ambient temperatures and continuous driving.

The Influence of Store Environment on Service Brand Personality and Repurchase Intention (점포의 물리적 환경이 서비스 브랜드 개성과 재구매의도에 미치는 영향)

  • Kim, Hyoung-Gil;Kim, Jung-Hee;Kim, Youn-Jeong
    • Journal of Global Scholars of Marketing Science
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    • v.17 no.4
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    • pp.141-173
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    • 2007
  • The study examines how the environmental factors of store influence service brand personality and repurchase intention in the service environment. The service industry has been experiencing the intensified competition with the industry's continuous growth and the influence from rapid technological advancement. Under the circumstances, it has become ever more important for the brand competitiveness to be distinctively recognized against competition. A brand needs to be distinguished and differentiated from competing companies because they are all engaged in the similar environment of the service industry. The differentiation of brand achievement has become increasingly important to highlight certain brand functions to include emotional, self-expressive, and symbolic functions since the importance of such functions has been further emphasized in promoting consumption activities. That is the recent role of brand personality that has been emphasized in the service industry. In other words, customers now freely and actively express their personalities or egos in consumption activities, taking an important role in construction of a brand asset. Hence, the study suggests that it is necessary to disperse the recognition and acknowledgement that the maintenance of the existing customers contributes more to boost repurchase intention when it is compared to the efforts to create new customers, particularly in the service industry. Meanwhile, the store itself can offer a unique environment that may influence the consumer's purchase decision. Consumers interact with store environments in the process of,virtually, all household purchase they make (Sarel 1981). Thus, store environments may encourage customers to purchase. The roles that store environments play are to provide informational cues to customers about the store and goods and communicate messages to stimulate consumers' emotions. The store environments differentiate the store from competing stores and build a unique service brand personality. However, the existing studies related to brand in the service industry mostly concentrated on the relationship between the quality of service and customer satisfaction, and they are mostly generalized while the connective studies focused on brand personality. Such approaches show limitations and are insufficient to investigate on the relationship between store environment and brand personality in the service industry. Accordingly, the study intends to identify the level of contribution to the establishment of brand personality made by the store's physical environments that influence on the specific brand characteristics depending on the type of service. The study also intends to identify what kind of relationships with brand personality exists with brand personality while being influenced by store environments. In addition, the study intends to make meaningful suggestions to better direct marketing efforts by identifying whether a brand personality makes a positive influence to induce an intention for repurchase. For this study, the service industry is classified into four categories based on to the characteristics of service: experimental-emotional service, emotional -credible service, credible-functional service, and functional-experimental service. The type of business with the most frequent customer contact is determined for each service type and the enterprise with the highest brand value in each service sector based on the report made by the Korea Management Association. They are designated as the representative of each category. The selected representatives are a fast-food store (experimental-emotional service), a cinema house (emotional-credible service), a bank (credible-functional service), and discount store (functional-experimental service). The survey was conducted for the four selected brands to represent each service category among consumers who are experienced users of the designated stores in Seoul Metropolitan City and Gyeonggi province via written questionnaires in order to verify the suggested assumptions in the study. In particular, the survey adopted 15 scales, which represent each characteristic factor, among the 42 unique characteristics developed by Jennifer Aaker(1997) to assess the brand personality of each service brand. SPSS for Windows Release 12.0 and LISREL were used in the analysis of data verification. The methodology of the structural equation model was used for the study and the pivotal findings are as follows. 1) The environmental factors ware classified as design factors, ambient factors, and social factors. Therefore, the validity of measurement scale of Baker et al. (1994) was proved. 2) The service brand personalities were subdivided as sincerity, excitement, competence, sophistication, and ruggedness, which makes the use of the brand personality scales by Jennifer Aaker(1997) appropriate in the service industry as well. 3) One-way ANOVA analysis on the scales of store environment and service brand personality showed that there exist statistically significant differences in each service category. For example, the social factors were highest in discount stores, while the ambient factors and design factors were highest in fast-food stores. The discount stores were highest in the sincerity and excitement, while the highest point for banks was in the competence and ruggedness, and the highest point for fast-food stores was in the sophistication, The consumers will make a different respond to the physical environment of stores and service brand personality that are inherent to the corresponding service interface. Hence, the customers will make a different decision-making when dealing with different service categories. In this aspect, the relationships of variables in the proposed hypothesis appear to work in a different way depending on the exposed service category. 4) The store environment factors influenced on service brand personalities differently by category of service. The factors of store's physical environment are transferred to a brand and were verified to strengthen service brand personalities. In particular, the level of influence on the service brand personality by physical environment differs depending on service category or dimension, which indicates that there is a need to apply a different style of management to a different service category or dimension. It signifies that there needs to be a brand strategy established in order to positively influence the relationship with consumers by utilizing an appropriate brand personality factor depending on different characteristics by service category or dimension. 5) The service brand personalities influenced on the repurchase intention. Especially, the largest influence was made in the sophistication dimension of service brand personality scale; the unique and characteristically appropriate arrangement of physical environment will make customers stay in the service environment for a long time and will lead to give a positive influence on the repurchase intention. 6) The store environment factors influenced on the repurchase intention. Particularly, the largest influence was made on the social factors of store environment. The most intriguing finding is that the service factor among all other environment factors gives the biggest influence to the repurchase intention in most of all service types except fast-food stores. Such result indicates that the customers pay attention to how much the employees try to provide a quality service when they make an evaluation on the service brand. At the same time, it also indicates that the personal factor is directly transmitted to the construction of brand personality. The employees' attitude and behavior are the determinants to establish a service brand personality in the process of enhancing service interface. Hence, there should be a reinforced search for a method to efficiently manage the service staff who has a direct contact with customers in order to make an affirmative improvement of the customers' brand evaluation at the service interface. The findings suggest several managerial implications. 1) Results from the empirical study indicated that store environment factors have a strong positive impact on a service brand personality. To increase customers' repurchase intention of a service brand, the management is required to effectively manage store environment factors and create a friendly brand personality based on the corresponding service environment. 2) Mangers and researchers must understand and recognize that the store environment elements are important marketing tools, and that brand personality influences on consumers' repurchase intention. Based on such result of the study, a service brand could be utilized as an efficient measure to achieve a differentiation by enforcing the elements that are most influential among all other store environments for each service category. Therefore, brand personality established involving various store environments will further reinforce the relationship with customers through the elevated brand identification of which utilization to induce repurchase decision can be used as an entry barrier. 3) The study identified the store environment as a component of service brand personality for the store's effective communication with consumers. For this, all communication channels should be maintained with consistency and an integrated marketing communication should be executed to efficiently approach to a larger number of customers. Mangers and researchers must find strategies for aligning decisions about store environment elements with the retailers' marketing and store personality objectives. All ambient, design, and social factors need to be orchestrated so that consumers can take an appropriate store personality. In this study, the induced results from the previous studies were extended to the service industry so as to identify the customers' decision making process that leads to repurchase intention and a result similar to those of the previous studies. The findings suggested several theoretical and managerial implications. However, the situation that only one service brand served as the subject of analysis for each service category, and the situation that correlations among store environment elements were not identified, as well as the problem of representation in selection of samples should be considered and supplemented in the future when further studies are conducted. In addition, various antecedents and consequences of brand personality must be looked at in the aspect of the service environment for further research.

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Wireless operational modal analysis of a multi-span prestressed concrete bridge for structural identification

  • Whelan, Matthew J.;Gangone, Michael V.;Janoyan, Kerop D.;Hoult, Neil A.;Middleton, Campbell R.;Soga, Kenichi
    • Smart Structures and Systems
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    • v.6 no.5_6
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    • pp.579-593
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    • 2010
  • Low-power radio frequency (RF) chip transceiver technology and the associated structural health monitoring platforms have matured recently to enable high-rate, lossless transmission of measurement data across large-scale sensor networks. The intrinsic value of these advanced capabilities is the allowance for high-quality, rapid operational modal analysis of in-service structures using distributed accelerometers to experimentally characterize the dynamic response. From the analysis afforded through these dynamic data sets, structural identification techniques can then be utilized to develop a well calibrated finite element (FE) model of the structure for baseline development, extended analytical structural evaluation, and load response assessment. This paper presents a case study in which operational modal analysis is performed on a three-span prestressed reinforced concrete bridge using a wireless sensor network. The low-power wireless platform deployed supported a high-rate, lossless transmission protocol enabling real-time remote acquisition of the vibration response as recorded by twenty-nine accelerometers at a 256 Sps sampling rate. Several instrumentation layouts were utilized to assess the global multi-span response using a stationary sensor array as well as the spatially refined response of a single span using roving sensors and reference-based techniques. Subsequent structural identification using FE modeling and iterative updating through comparison with the experimental analysis is then documented to demonstrate the inherent value in dynamic response measurement across structural systems using high-rate wireless sensor networks.

Decentralized Structural Diagnosis and Monitoring System for Ensemble Learning on Dynamic Characteristics (동특성 앙상블 학습 기반 구조물 진단 모니터링 분산처리 시스템)

  • Shin, Yoon-Soo;Min, Kyung-Won
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.4
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    • pp.183-189
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    • 2021
  • In recent years, active research has been devoted toward developing a monitoring system using ambient vibration data in order to quantitatively determine the deterioration occurring in a structure over a long period of time. This study developed a low-cost edge computing system that detects the abnormalities in structures by utilizing the dynamic characteristics acquired from the structure over the long term for ensemble learning. The system hardware consists of the Raspberry Pi, an accelerometer, an inclinometer, a GPS RTK module, and a LoRa communication module. The structural abnormality detection afforded by the ensemble learning using dynamic characteristics is verified using a laboratory-scale structure model vibration experiment. A real-time distributed processing algorithm with dynamic feature extraction based on the experiment is installed on the Raspberry Pi. Based on the stable operation of installed systems at the Community Service Center, Pohang-si, Korea, the validity of the developed system was verified on-site.