Proposed System Framework Research Articles

Earthquake early warning-enabled smart base isolation system

Recent deployments of Earthquake Early Warning (EEW) system in Japan and some other earthquake-prone regions provide the vital warning signals prior to the arrival of destructive ground motions. The EEW system uses the different traveling speed of seismic P- and S-waves to achieve the goal of earthquake warning. This technology is primarily used to produce warning signals to alert the public to avoid potential risks, such as to evacuate from buildings. It is also used to mitigate other risks such as reducing train speed of Shinkansen trains. The present study suggests a new seismic-risk mitigation technique by connecting a base isolation system with the EEW. Base isolation is a mature technology which decouples structure from its base and lengthens its natural period of vibration. However, existing base isolation devices must possess certain lateral resistance to withstand service lateral forces such as wind, and such stiffness hinders the effectiveness of vibration isolation. In addition, supplementary damping devices are sometimes added to control excessive displacements in isolation level. This paper proposes a smart system which changes the property of a base isolation system upon EEW signal. In normal times when earthquake risk is not present, the base isolation system is locked by shear keys. When an earthquake is signalled by the EEW system, a mechanical system releases the base isolation system. When the earthquake ceases, the system resets and base isolation is locked again. On-board vibration sensors are added to activate the system in case of EEW fails to detect incoming waves. A crucial benefit of the system is that supplementary damper is no longer required to control excessive isolator displacements, and elastic stiffness of base isolation is no longer required to re-enter the base isolation system. The result is that it maximizes the vibration isolation effectiveness. A conceptual framework of proposed system is described and demonstrated by laboratory-scaled experiments. A 6-storey test frame is excited on a shake table subjected to historical earthquakes. Results indicates that the proposed system is effective in reducing earthquake responses on the building. It is an IoT-enabled earthquake-risk mitigation system.

A smart mechatronic base isolation system using earthquake early warning

In earthquake-prone countries such as Japan, effects of earthquakes are one of the major design objectives in buildings and infrastructures. Recent advances in earthquake engineering have improved the safety and reliability of buildings and infrastructures. Better understanding of geomorphology of earthquakes also enables us to better predict and estimate propagation of such natural hazard. For example, the Earthquake Early Warning (EEW) system in Japan provides advanced warnings using the different arrival times of P and S waves. On the other hand, techniques and methods in passive, semi-active and active vibration control have flourished. Base-isolation is a proven technique which enhances earthquake resilience of buildings and bridges. In general, this technique involves decoupling a superstructure from its foundation and lengthens its natural period of vibration. This technique is mature and commercialization has taken place worldwide. However, wind-resistance of base-isolated structures is generally a concern as the lateral stiffness of a base-isolated structure is low and serviceability wind effects may induce unacceptable lateral movement and/or vibration of the structure. This paper presents a new concept which the base-isolation system is activated by EEW system through a mechatronic system. In other times the structure is not base-isolated and provides strong lateral resistance against wind loads. As a backup design, the proposed system also equips with its own network of accelerometers which can trigger base isolation system independent from EEW system. The smart mechatronic base isolation system is fully automated, and resets itself after each ground motion. The paper describes the conceptual framework of proposed system and presents laboratory-scaled proof-of-concept experiments. Four historical earthquake time histories were used as ground excitations. Structural responses are compared between the two triggering mechanisms and results are discussed. Finally, the concept of Internet of Things (IoT) which make use of EEW is discussed, allowing connectivity between a single control unit and a network of infrastructures to achieve economy of scale.

Integrated-system to minimizing cyber harassment in kingdom of Saudi Arabia (KSA)

The proposed system framework consists two main databases: Lexicon dictionary and Summarized previous cases, by depending on Senti-ment analysis and N-Gram algorithms to match the terms and documents. In the first branch, the judge opens the cyber case and therefore the system will highlight the technical terms automatically. Furthermore, the technical terms matched with Lexicon dictionary will be high-lighted. After that, the judge opens the highlighted terms (as links), and description page will be appeared. The description page contains details about the technical terms (definitions, explanations, examples, etc). On the other side, the second branch aims to retrieve the related legal cases (from the database) judged by courts in UK and KSA. The related cases are the most closed cases to the current legal case by inserting keywords based on the current case. The judge benefits from these cases through the judgment issued to give the fair judgment. N-gram algorithm is used to find the related cases because it has smart approach to expect the most closed document and texts. The system provides the judge with laws used in issuing the judgment in KSA and UK courts.

Services Modeling based on SOA and BPM for Information System Flexibility Improvement

The lack of identify services mechanism which is related to the development of information systems could be impact in wasting time, over budget and can not adapt to the changing environment. This phenomenon is happened by the belief that lack of capturing user requirement. This is due to consider the business environment is always running normally. In fact, the development of the system needs a way to anticipate the business environment that unpredictable changes.Therefore, the phenomenon on the need for modeling services can able to respond to the changing needs of users still have a chancein this study. It explores modeling services to synergize SOA and BPM.Several previous studies generally use a business driven approach, technical partially driven to develop the service modeling. This leads to the question of how a service should be modeled so that it can be applied in different contexts and business processes also. It is support user needs in diversity and heterogeneous system environments. This Conditions occurs in corporate university. The case studies in this research is a Learning Management System (LMS) in Academic Enterprise System (EAS). The research stages are: (1) Analysis of Synergy in SOA and BPM, (2) Analysis of User Experience in LMS Academic Enterprise System (L-EAS), <br /> (3) Analysis of Modeling Framework, (4) Proposed Framework that aligning SOA and BPM. The result of this study is proposed system framework based on services to increase the flexibility of information systems at LMS Academic Enterprise System (L-EAS).

A conversational case-based reasoning approach to assisting experts in solving professional problems

Nowadays, organizations attempt to retrieve, collect, preserve and manage knowledge and experience of experts in order to reuse them later and to promote innovation. In this sense, Experience Management is one of the important organizational issues. This article is discussed the main ideas of a future Conversational Case-Based Reasoning (CCBR) intended to assist the experts of after-sales service in a French industrial company. The aim of this research is to formalize the experience of experts in after-sales service in order to better reuse them for similar problems in future. The research opts for an action research method which consists of two main parts: description of failure and proposition of decision protocol. The data were complemented by questionnaires, documentary analysis (including technical reports and other technical documents), observation and many interviews with experts. The findings include several aspects: the formalization of Problem-solving Cards, proposing the structure of case base, as well as the framework of proposed system. These formalizations permit after-sales service experts to provide effective diagnosis and problem-solving.

A Novel Trail Detection and Scene Understanding Framework for a Quadrotor UAV With Monocular Vision

Vision-based trail detection and autonomous scene understanding play a key role for unmanned aerial vehicles (UAVs) working in complex outdoor environments such as isolated disaster sites. This paper investigates the problems associated with trail detection and tracking, as well as autonomous scene understanding using a quadrotor UAV. A framework that integrates support vector machine-based trail detection with a trail tracker is proposed to accomplish trail direction estimation and tracking at a low cost of computation and in real time. To accurately perform online parameter estimation, a performance test is designed and implemented to evaluate the accuracy. Moreover, the simple linear iterative clustering superpixel segmentation algorithm is utilized in the proposed system framework to guarantee the scene segmentation accuracy. Visual detection for significant objects or people is implemented by using single shot multibox detector algorithm. A series of experiments are conducted by using a quadrotor platform DJI M100 and experimental results show the validity and practicality of the proposed approach.

Toward mining user movement behaviors in indoor environments

In this paper, we explore a new mining paradigm, called User Visited Patterns (abbreviated as UVP), to discover user visited behavior in the mall-like indoor environment. It is a highly challenging issue, in the indoor environment, to retrieve the frequent UVP, especially when the concern of user privacy is highlighted nowadays. The mining of UVP will face the critical challenge from spatial uncertainty. In this paper, the proposed system framework utilizes the probabilistic mining to identify top-k UVP over uncertain dataset collected from the RFID-based sensing result. Moreover, we redesign the indoor symbolic model to enhance the accuracy and efficiency. Our experimental studies show that the proposed system framework can overcome the impact from location uncertainty and efficiently discover high-quality UVP, to provide insightful observation for marketing collaborations.

Wireless LAN Service Quality Optimization in Academic Environments

This paper targets optimized service quality (SQ) – a metric that compares the perceived performance by users with the expected performance – sufficient to satisfy users’ quality of experience (QoE). The perceived performance was obtained in a field survey from an academic environment, and using Interval Type-2 Fuzzy Logic (IT2FL), uncertainties inherent in the field data were efficiently modeled for accurate estimation of the SQ. To obtain the expected performance, two unsupervised tools: the Principal Component Analysis (PCA) and Self-organizing Map (SOM) were exploited to abstract the most relevant features, and observe similarity patterns between the abstract features. An Adaptive Neuro-Fuzzy Inference System (ANFIS) was then used to optimize the system performance. Results obtained showed that ANFIS sufficiently optimized and modeled the SQ – as the root mean square error (RMSE) values of the train and test data were approximately the same – for all the study sites considered. However, combining the three campuses produced the least mean absolute error (MAE) of 0.0979 for train data, and the highest MAE of 0.7345 for test data. Further, the least MAE of 0.4707 for test data was obtained from town campus Annex. The wide variation in MAE observed in the train and test data might not be unconnected with the high degree of uncertainties associated with interference, site topology and terrain issues – exhibited by the system under study, as well as the quality of data collected. The proposed system framework has the potentials to develop into a complete location-based system.

Equipment Utilization Enhancement in Photolithography Area Through a Dynamic System Control Using Multi-Fidelity Simulation Optimization With Big Data Technique

Photolithographic (Photo) plays a key role in semiconductor manufacturing because of its importance to advanced process shrinking. Even with a small improvement in its operational efficiency, the cost competitiveness in production can be enhanced as a result of the huge amount of share capital cost. However, it is difficult to stabilize the throughput rhythm of Fabs, while keeping a high equipment utilization for Photo. In the light of Industry 4.0 and big data, a huge potential of maintaining a desired system performance by (near) real-time dynamic system control is highly anticipated. But it also poses challenges to intelligently handling mass data acquisition and allocating computing resources. This research aims to maximize the equipment utilization in Photo by an efficient multi-model simulation optimization approach with big data techniques in the era of Industry 4.0. dynamic Photo configurator and abnormality detector are the two critical units in our proposed system framework; the former can make a quick decision to optimize the system configuration while receiving the adjustment request from the latter. The results from an empirical study show the practical viability of proposed approach that the capacity loss in Photo has been effectively improved.

A research port test bed based on distributed optical sensors and sensor fusion framework for ad hoc situational awareness

Abstract. Maritime study sites utilized as a physical experimental test bed for sensor data fusion, communication technology and data stream analysis tools can provide substantial frameworks for design and development of e-navigation technologies. Increasing safety by observation and monitoring of the maritime environment by new technologies meets forward-looking needs to facilitate situational awareness. Further, such test beds offer a solid basis for standardizing new technologies to advance growth by reducing time to market of up-to-date industrial products and technologies. Especially optical sensor technologies are well suited to provide a situational and marine environmental assessment of waterways for (i) online detection of relevant situations, (ii) collection of data for further analysis and (iii) reuse of data, e.g. for training or testing of assistant systems. The test bed set-up has to consider maintainability, flexibility and extensibility for efficient test set-ups. This means that new use cases and applications within the test bed infrastructure, here presented by a research port, can be easily developed and extended by installing new sensors, actuators and software components. Furthermore, the system supports reliable remote communication between onshore and offshore participants. A series of in situ experiments at the research port of Bremerhaven and in other maritime environments were performed, representing applications and scenarios to demonstrate the capability for the proposed system framework and design.

Cost-Effective Online Trending Topic Detection and Popularity Prediction in Microblogging

Identifying topic trends on microblogging services such as Twitter and estimating those topics’ future popularity have great academic and business value, especially when the operations can be done in real time. For any third party, however, capturing and processing such huge volumes of real-time data in microblogs are almost infeasible tasks, as there always exist API (Application Program Interface) request limits, monitoring and computing budgets, as well as timeliness requirements. To deal with these challenges, we propose a cost-effective system framework with algorithms that can automatically select a subset of representative users in microblogging networks in offline, under given cost constraints. Then the proposed system can online monitor and utilize only these selected users’ real-time microposts to detect the overall trending topics and predict their future popularity among the whole microblogging network. Therefore, our proposed system framework is practical for real-time usage as it avoids the high cost in capturing and processing full real-time data, while not compromising detection and prediction performance under given cost constraints. Experiments with real microblogs dataset show that by tracking only 500 users out of 0.6 million users and processing no more than 30,000 microposts daily, about 92% trending topics could be detected and predicted by the proposed system and, on average, more than 10 hours earlier than they appear in official trends lists.

Delay-Optimal Virtualized Radio Resource Scheduling in Software-Defined Vehicular Networks via Stochastic Learning

Due to the high density of vehicles and various types of vehicular services, it is challenging to guarantee the quality of vehicular services in current Long-Term Evolution (LTE) networks in a cost-efficient manner. Fortunately, with the development of fifth-generation (5G) technology, the installation of a large number of small cells is foreseen as one of the practical ways to achieve the low-delay requirement in vehicular environments. However, it may cause a huge operating expense and capital expenditure to mobile network operators due to the limited backhaul capacity and the explosion of signaling. In this paper, we integrate software-defined networking and radio resource virtualization into an LTE system for vehicular networks, i.e., software-defined heterogeneous vehicular network (SERVICE) . Based on this proposed system framework, a delay-optimal virtualized radio resource scheduling scheme is proposed via stochastic learning. The delay optimal problem is formulated as an infinite-horizon average-cost partially observed Markov decision process (POMDP). Then, an equivalent Bellman equation is derived to solve it. The proposed scheme can be divided into two stages, i.e., macro virtualization resource allocation (MaVRA) and micro virtualization resource allocation (MiVRA). The former is executed based on large timescale variables (traffic density), whereas the latter is operated according to short timescale variables (channel state and queue state). Simulation results show that the proposed scheme outperforms traditional schemes.

SNS기반 건설현장 정보소통 및 공유 시스템 구축

건설 프로젝트에서의 정보관리를 위해 PMIS와 같은 IT기반 서비스들이 활용되고 있지만 실제 현장에서는 발생 정보에 대한 신속한 대처 및 정보손실, 보안위험 등의 문제를 해결해 주지 못하고 있다. 따라서 본 연구는 최근 기업 내 참여와 정보공유의 목적으로 사용되고 있는 SNS를 건설현장에 도입하고 이를 활용한 건설 정보 관리 체계를 제안하였다. 이를 위해 문헌 고찰과 현장 인터뷰를 통해 요구사항을 분석하고 활용 전략을 수립하여 시스템을 개발하였으며 실제 현장에서의 정보관리 체계 구축 가능성 여부를 위해 성능 테스트를 실시하여, 개발 결과물 및 이를 활용한 정보 관리 체계가 건설 현장에서 효율적인 정보 관리에 도움을 줄 수 있다는 것을 검증하였다. Although various IT-based services including PMIS are used at construction field, there have been limits on communications, such as fast reaction, information loss, and information security in the real world. Therefore, this paper proposes to adapt a social network service (SNS) that has already been used for information management and sharing information at the company level in other industries in order to support construction information management and communication in a fast and accurate manner. Following the requirement analysis through literature review and site interviews, the paper presents an SNS-based construction information communication and sharing system named PMIS+. PMIS+ was tested and validated for its feasibility at construction sites and it was proved that the proposed system and information management framework using the system could be helpful for effective information management at construction fields.

An Information System Framework and Prototype for Collaboration and Standardization in Chinese Liquor Production

This paper proposes an information system framework for production collaboration and standardization in Chinese liquor industry, and examines the key implementation issues of information systems in Chinese liquor production. A descriptive single case study is conducted to explore and identify the benefits, challenges, and success factors of information system implementation in Chinese liquor production by taking a famous Chinese liquor producer as the target case company. The case study shows that the proposed information system framework is helpful to improve collaboration and standardization in Chinese liquor production. Some benefits and challenges of implementing information systems are different from those described in previous studies because of various distinct, real-world features of Chinese liquor production. The proposed system framework offers the possibility to improve the Chinese liquor producer's production efficiency and market competition by better production collaboration and standardization.

A Novel Deployment Scheme for Green Internet of Things

The Internet of Things (IoT) has been realized as one of the most promising networking paradigms that bridge the gap between the cyber and physical world. Developing green deployment schemes for IoT is a challenging issue since IoT achieves a larger scale and becomes more complex so that most of the current schemes for deploying wireless sensor networks (WSNs) cannot be transplanted directly in IoT. This paper addresses this challenging issue by proposing a deployment scheme to achieve green networked IoT. The contributions made in this paper include: 1) a hierarchical system framework for a general IoT deployment, 2) an optimization model on the basis of proposed system framework to realize green IoT, and 3) a minimal energy consumption algorithm for solving the presented optimization model. The numerical results on minimal energy consumption and network lifetime of the system indicate that the deployment scheme proposed in this paper is more flexible and energy efficient compared to typical WSN deployment scheme; thus is applicable to the green IoT deployment.

A Low Cost Knowledge Based System Framework for Design of Bending Die

This paper presents a low cost knowledge based system (KBS) framework for design of bending die. Considerations for development of KBS are discussed at some length. The proposed framework divides the task of development of expert system into different modules for major activities of bending die design. The procedure of development of KBS modules is also described at length. Production rules for each module are recommended to be coded in the AutoLISP language and designed to be loaded into the prompt area of AutoCAD or through user interface created using Visual Basic. Each module of the proposed framework is user interactive. Development of one module of the proposed framework is also described at length. This module is capable to assess manufacturability of bending sheet metal parts. An illustrative example is also included to demonstrate the usefulness of this module. The proposed system framework is flexible enough to accommodate new acquired knowledge. As the proposed system is implementable on a PC having AutoCAD software, therefore its low cost of implementation makes it affordable even by small scale sheet metal industries.

An online visualization system for streaming log data of computing clusters

Monitoring a computing cluster requires collecting and understanding log data generated at the core, computer, and cluster levels at run time. Visualizing the log data of a computing cluster is a challenging problem due to the complexity of the underlying dataset: it is streaming, hierarchical, heterogeneous, and multi-sourced. This paper presents an integrated visualization system that employs a two-stage streaming process mode. Prior to the visual display of the multi-sourced information, the data generated from the clusters is gathered, cleaned, and modeled within a data processor. The visualization supported by a visual computing processor consists of a set of multivariate and time variant visualization techniques, including time sequence chart, treemap, and parallel coordinates. Novel techniques to illustrate the time tendency and abnormal status are also introduced. We demonstrate the effectiveness and scalability of the proposed system framework on a commodity cloud-computing platform.

An Expert System Framework for Design of Bending Die

This paper presents an expert system framework for design of bending die. Considerations for development of expert system are discussed at some length. The proposed framework divides the task of development of expert system into different modules for major activities of bending die design. It gives stress on automation of four major activities of die design viz. manufacturability assessment, process planning, design/selection of die components and modeling of die components and die assembly. A procedure of development of expert system modules is also described at length. Production rules for each module are recommended to be coded in the AutoLISP language and designed to be loaded into the prompt area of AutoCAD or through user interface created using Visual Basic. Each module of the proposed framework is user interactive. The proposed system framework is flexible enough to accommodate new acquired knowledge. As the proposed system is implementable on a PC having AutoCAD software, therefore its low cost of implementation makes it affordable even by small scale sheet metal industries.

Virtual Machine-based Intrusion Detection System Framework in Cloud Computing Environment

Cloud computing an emerging approach by sharing infrastructure is an overwhelming trend. While in the process of cloud deployment, the security issues can not be underestimated. Traditional Intrusion Detection System (IDS) because of lower detection rate and higher false rate couldn’t be suitable the cloud here. Extensibility is the main requirement for IDS framework of cloud environment in this paper as follows. First the cross-platform and strong isolation properties of virtualization have been fully reflected here, that is to say, an extensible VM-based multiple IDSs are deployed in each layer to monitor specific virtual component. Moreover, during the process, we also propose the cloud alliance concept by the communication agents exchanging the mutual alerts mainly to resist Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) - the single point attack of failure. On this basis, we have the identity certification of the communication agents to improve the reliability of the alerts. Through the comparison of simulation results, the proposed system framework has a great advantage for monitoring VMs on the detection rate.

Mobile Agent Application and Integration in Electronic Anamnesis System

Electronic anamnesis is to transform ordinary paper trails to digitally formatted health records, which include the patient's general information, health status, and follow-ups on chronic diseases. Its main purpose is to let the records could be stored for a longer period of time and could be shared easily across departments and hospitals. Which means hospital management could use less resource on maintaining ever-growing database and reduce redundancy, so less money would be spent for managing the health records. In the foreseeable future, building up a comprehensive and integrated medical information system is a must, because it is critical to hospital resource integration and quality improvement. If mobile agent technology is adopted in the electronic anamnesis system, it would help the hospitals to make the medical practices more efficiently and conveniently. Nonetheless, most of the hospitals today are still using paper-based health records to manage the medical information. The reason why the institutions continue using traditional practices to manage the records is because there is no well-trusted and reliable electronic anamnesis system existing and accepted by both institutions and patients. The threat of privacy invasion is one of the biggest concerns when the topic of electronic anamnesis is brought up, because the security threats drag us back from using such a system. So, the medical service quality is difficult to be improved substantially. In this case, we have come up a theory to remove such security threats and make electronic anamnesis more appealing for use. Our theory is to integrate the mobile agent technology with the backbone of electronic anamnesis to construct a hierarchical access control system to retrieve the corresponding information based upon the permission classes. The system would create a classification for permission among the users inside the medical institution. Under this framework, permission control center would distribute an access key to each user, so they would only allow using the key to access information correspondingly. In order to verify the reliability of the proposed system framework, we have also conducted a security analysis to list all the possible security threats that may harm the system and to prove the system is reliable and safe. If the system is adopted, the doctors would be able to quickly access the information while performing medical examinations. Hence, the efficiency and quality of healthcare service would be greatly improved.