This paper introduces a system that can effectively save home energy by applying a small embedded system through remote control. We used a wireless router based on OpenWrt for the platform to develop an embedded syste...
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Privacy preservation is a crucial issue for smart buildings where all kinds of messages, e.g., power usage data, control commands, events, alarms, etc. are transmitted to accomplish the management of power. Without ap...
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Privacy preservation is a crucial issue for smart buildings where all kinds of messages, e.g., power usage data, control commands, events, alarms, etc. are transmitted to accomplish the management of power. Without appropriate privacy protection schemes, electricity customers are faced with various privacy risks. Meanwhile, the natures of smart grids and smart buildings—such as having limited computation power of smart devices and constraints in communication network capabilities, while requiring being highly reliable—make privacy preservation a challenging task. In this paper, we propose a group key scheme to safeguard multicast privacy with the provisions of availability, fault-tolerance, and efficiency in the context of smart buildings as a part the smart grid. In particular, hybrid architecture accommodating both centralized and contributory modes is constructed in order to achieve both fault-tolerance and efficiency with only one set of group key installed. Key trees are sophisticatedly managed to reduce the number of exponentiation operations. In addition, an individual rekeying scheme is introduced for occasional joining and leaving of member smart meters. Experimental results, on a simulation platform, show that our scheme is able to provide significant performance gains over state-of-the-art methods while effectively preserving the participants’ privacy.
Project work is an important part of university education and workplace activities. However, cooperation problems are common in the learning process. The purpose of the study we present is to address these challenges ...
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Project work is an important part of university education and workplace activities. However, cooperation problems are common in the learning process. The purpose of the study we present is to address these challenges by designing a Cooperation technology course and studying its outcomes. We applied social constructivist and reflective learning approaches and used various technologies as platforms for project work. Based on study data, we analyze collaborative workflows in and between student groups, use of technological ecologies, and the outcomes of their work. As a result, we provide implications for combining social constructivist and reflective learning approaches in course design.
In this paper, we will investigate a more challenging vehicle matching problem. The problem is formulated as invariant image feature matching among opposite viewpoints of cameras, i.e. complementary object matching. F...
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ISBN:
(纸本)9781467361989
In this paper, we will investigate a more challenging vehicle matching problem. The problem is formulated as invariant image feature matching among opposite viewpoints of cameras, i.e. complementary object matching. For example, a front vehicle object may be given as a query to retrieve a rear vehicle object of the same vehicle. To solve the complementary object matching, invariant image feature is first extracted based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, the ASIFT feature is expanded via a special vehicle database. As a result, cross-camera vehicle matching with the help of complementary part can be greatly improved. Experimental results demonstrate the effectiveness of the proposed algorithm and the feasibility to video forensics applications.
The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect a...
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ISBN:
(纸本)9781479900145
The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications.
This paper proposes a music recommendation approach based on various similarity information via Factorization Machines (FM). We introduce the idea of similarity, which has been widely studied in the filed of informati...
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This paper proposes a music recommendation approach based on various similarity information via Factorization Machines (FM). We introduce the idea of similarity, which has been widely studied in the filed of information retrieval, and incorporate multiple feature similarities into the FM framework, including content-based and context-based similarities. The similarity information not only captures the similar patterns from the referred objects, but enhances the convergence speed and accuracy of FM. In addition, in order to avoid the noise within large similarity of features, we also adopt the grouping FM as an extended method to model the problem. In our experiments, a music-recommendation dataset is used to assess the performance of the proposed approach. The datasets is collected from an online blogging Web site, which includes user listening history, user profiles, social information, and music information. Our experimental results show that, with various types of feature similarities the performance of music recommendation can be enhanced significantly. Furthermore, via the grouping technique, the performance can be improved significantly in terms of Mean Average Precision, compared to the traditional collaborative filtering approach.
This paper deals with a contribution of computational analysis of verbal humor to natural language cognition. After a brief introduction to the growing area of computational humor and of its roots in humor theories, i...
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This paper deals with a contribution of computational analysis of verbal humor to natural language cognition. After a brief introduction to the growing area of computational humor and of its roots in humor theories, it describes and compares the results of a human-subject and computer experiment. The specific interest is to compare how well the computer, equipped with the resources and methodologies of the Ontological Semantic technology, a comprehensive meaning access approach to natural language processing, can model several aspects of the cognitive behaviors of humans processing jokes from the Internet.
Cell selection in current LTE-Advanced depend on reference signal received power or reference signal received quality which results to low user association probability. Therefore, we propose an aggregate objective cel...
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ISBN:
(纸本)9781479906963
Cell selection in current LTE-Advanced depend on reference signal received power or reference signal received quality which results to low user association probability. Therefore, we propose an aggregate objective cell selection technique based on enhanced inter-cell interference coordination technique developed by 3GPP in Rel-10 known as almost blank subframe. We also adopt the use of cell range expansion technique as means to encourage offloading. Cell range expansion was introduced in LTE-advanced, it encourages user equipment to select a small cell with a weakest signal as thier serving cell by adding a positive bias in cell selection process. Simulation shows that the proposed scheme results to high user association probability, while giving superior performance in average throughput compared to conventional single objective base cell selection for cell range expansion.
SWEET routing protocol is one of the many protocols developed for cluster formation and routing in wireless sensor networks. The SWEET protocol is a decentralized clustering protocol, it uses timers and interim update...
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SWEET routing protocol is one of the many protocols developed for cluster formation and routing in wireless sensor networks. The SWEET protocol is a decentralized clustering protocol, it uses timers and interim updated cluster head estimation probability. This paper focus on the details of the initialization waiting time, sleeping mode and base station in order to increase the life cycle of the network. The initial waiting time's resizing procedure is carried by a weighting factor which is computed from the delay slot time and delay frame time. Other improvements are the introduction of sleeping mode energy saving technique. The last contribution is through the enabled base station's ability to become a cluster head. A simulation based performance evaluation of our proposed EN-SWEET protocol shows superiority in energy efficiency.
Maximum heart rate (MHR) is commonly used to estimate exercise intensity with the Karvonen formula, and there are several methods of calculating it. In this study, we used pedaling experiments on a cycle ergometer to ...
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ISBN:
(纸本)9789898565716
Maximum heart rate (MHR) is commonly used to estimate exercise intensity with the Karvonen formula, and there are several methods of calculating it. In this study, we used pedaling experiments on a cycle ergometer to evaluate methods of determining MHR in order to select the ones most suitable for the Karvonen formula. In the experiments, 43 subjects rode an aerobike. The results show that, for people in their 20s, two methods are suitable for estimating exercise intensity with the Karvonen formula. The main physical parameters affecting exercise intensity were also extracted, based on the experimental results.
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