In this work, we propose an energy-efficient HTTP adaptive streaming for high-quality video over heterogeneous networks (HetNets). To support high-quality video and overcome the limitations of a single network, the pr...
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In this work, we propose an energy-efficient HTTP adaptive streaming for high-quality video over heterogeneous networks (HetNets). To support high-quality video and overcome the limitations of a single network, the proposed system downloads the video segments by concurrently using the HetNets. In the proposed system, the segment bitrate, number of requested segments, network sleep time, and size of requested data through each wireless network are determined adaptively to provide seamless high-quality video streaming in an energy and cost efficient way. The proposed system is fully implemented in an Android-based mobile device and tested in an actual wireless network environments.
A new method based on the well-known technique of Grammatical Evolution, is introduced for data classification. The method constructs classification programs in a C - like programming language in order to classify the...
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Nowadays situation monitoring of production machinery is key factor in achieving production efficiency. Recent production equipment has often several sensors and monitoring facilities built-in but mostly for condition...
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ISBN:
(纸本)9789949236206
Nowadays situation monitoring of production machinery is key factor in achieving production efficiency. Recent production equipment has often several sensors and monitoring facilities built-in but mostly for condition monitoring of a single unit. Mostly gathered data is only available to machine manufacturer. System for online machine monitoring using heterogeneous WSN has been proposed previously. Several methods of lathe condition monitoring have been researched. Currently easily dep.oyable online condition monitoring system based on measurements of power consumption of milling machine is proposed and its efficiency researched.
Power consumption is becoming an increasingly important component of processor design. As technology node shrinks both static and dynamic power become more relevant. This is particularly critical for the cache hierarc...
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Power consumption is becoming an increasingly important component of processor design. As technology node shrinks both static and dynamic power become more relevant. This is particularly critical for the cache hierarchy. Previous implementations mainly focus on reducing only one kind of power in the cache, either static or dynamic. However, for a more robust approach that will remain relevant as technology continues to shrink, both aspects of power need to be addressed. Recent processors, e.g. Intel Core or IBM Power8, implement simultaneous multithreading (SMT) cores to hide high memory latencies. In these systems, the dynamic energy in the L1 cache is even more stressed since this cache level is shared by several threads running on the same core. This paper proposes and evaluates the use of phase adaptive caches in all structures of a 3-level cache hierarchy of a SMT cores. Compared to the use of conventional caches, our work results on significant dynamic and leakage energy savings with scarce performance impact.
This paper presents an innovative framework concept combined with online labs for teaching and learning of engineering subjects. The concept integrates comprehensive approaches of different classical and innovative as...
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This paper presents an innovative framework concept combined with online labs for teaching and learning of engineering subjects. The concept integrates comprehensive approaches of different classical and innovative aspects. The paper gives an overview of current state-of-art technologies in remote and virtual labs and some existing activities for transnational online experimentation frameworks. New comprehensive teaching and learning concept for robotics and smart devices is presented together with practical results. The implemented remote lab portal - DistanceLab is presented in detail focusing on three different remote labs: Virtual microcontroller lab, Smart greenhouse lab, and Mobile robot lab.
Classification techniques based on Artificial Intelligence are computational tools that have been applied todetection of intrusions(IDS) with encouraging results. They are able tosolve problems related toinformation s...
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Classification techniques based on Artificial Intelligence are computational tools that have been applied todetection of intrusions(IDS) with encouraging results. They are able tosolve problems related toinformation security in an efficient way. The intrusion detection implies the use of huge amount of information. For this reason heuristic methodologies have been proposed. In this paper, decision trees, Naive Bayes, and supervised classifying systems UCS, are combined toimprove the performance of a classifier. In order tovalidate the system, a scenariobased on real data of the NSL-KDD99 datasetis used.
The 2U-size cubesat RAIKO was launched to the International Space Station (ISS) in July 2012, and released to space in October 2012. The preset sequences of the 30-min initial separation phase were successfully carrie...
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ISBN:
(纸本)9781624102219
The 2U-size cubesat RAIKO was launched to the International Space Station (ISS) in July 2012, and released to space in October 2012. The preset sequences of the 30-min initial separation phase were successfully carried out, and 46 photos were taken and stored to memory by the onboard CMOS and CCD sensors. Four Japanese universities collaborated in joint operations of RAIKO, which included successful S-band command/telemetry operations at a telemetry downlink rate of 100 kbps using the 100-mW onboard transmitter. In addition, Ku-band beacon signals were successfully monitored to determine the orbit and atmospheric disturbances. This paper presents an outline of RAIKO, the ground station network, the operation method, and associated results. The cubesat RAIKO inherited the satellite bus technology of a 50-kg microsatellite, and various technology demonstrations were achieved. Through the joint operation of RAIKO, the ground station network was practically improved and will contribute to the operations of future micro- and nanosatellites.
Community networks have emerged under the mottos of “break the strings that are limiting you”, “don't buy the network, be the network” or “a free net for everyone is possible”. Such networks create a measura...
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Community networks have emerged under the mottos of “break the strings that are limiting you”, “don't buy the network, be the network” or “a free net for everyone is possible”. Such networks create a measurable social impact as they provide to the community the right and opportunity of communication. As any other network that mixes wired and wireless links, the routing protocol must face several challenges that arise from the unreliable nature of the wireless medium. Link quality tracking helps the routing layer to select links that maximize the delivery rate and minimize traffic congestion. Moreover, link quality prediction has proved to be a technique that surpasses link quality tracking by foreseeing which links are more likely to change its quality. In this work, we focus on link quality prediction by means of a time series analysis. We apply this prediction technique in the routing layer of large-scale, distributed and decentralized networks. We demonstrate that this type of prediction achieves about a success probability of about 98% in both the short and long term.
Classification techniques based on Artificial Intelligence are computational tools that have been applied to detection of intrusions (IDS) with encouraging results. They are able to solve problems related to informati...
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Classification techniques based on Artificial Intelligence are computational tools that have been applied to detection of intrusions (IDS) with encouraging results. They are able to solve problems related to information security in an efficient way. The intrusion detection implies the use of huge amount of information. For this reason heuristic methodologies have been proposed. In this paper, decision trees, Naive Bayes, and supervised classifying systems UCS, are combined to improve the performance of a classifier. In order to validate the system, a scenario based on real data of the NSL-KDD99 dataset is used.
In this study, we proposed a multi-piecewise thinning description method. Thinning is a preprocessing technology often applied in the fields of binary image processing; it is used to transform thick elements in an ima...
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ISBN:
(纸本)9781479944750
In this study, we proposed a multi-piecewise thinning description method. Thinning is a preprocessing technology often applied in the fields of binary image processing; it is used to transform thick elements in an image into lines with a single pixel width. Because lines include closed and open lines, an effective description method is required for post-processing procedures. Regarding the proposed method, branch points of thinning lines are first identified and used as a basis for segmenting the lines, which are originally connected, into multiple line segments. Subsequently, we employed the find contour function available in the OpenCV library to describe the coordinates of the contours of the line segments. The starting and endpoints of closed lines can be directly obtained using the contour results of closed lines. By contrast, the starting and endpoints of open lines are achieved by first using turning points to confirm the position of line-end points and employing the adjacent pixels of the line-end and branch points before the contour results of open lines can be used. The experimental results indicated that the proposed method effectively achieved accurate descriptions for thinned lines.
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