作者：
Zhang, YichengChen, JianYu, YangASTAR
Inst Infocomm Res I2R 1 Fusionopolis Way21-01 Connexis Singapore 138632 Singapore Shandong Univ
Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Nanyang Technol Univ
Sch Elect & Elect Engn Singapore 639798 Singapore
A more electric aircraft is expected to have low emissions, decreased fuel consumption, high efficiency, and low maintenance costs. To fully enjoy those benefits, major technical obstacles must be overcome first. In t...
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A more electric aircraft is expected to have low emissions, decreased fuel consumption, high efficiency, and low maintenance costs. To fully enjoy those benefits, major technical obstacles must be overcome first. In terms of power management, an increasing number of power electronic components used in aircraft power systems and their ever-increasing functional sophistication will lead to high modeling and computational complexities, making real-time power management a daunting challenge. To address this challenge, in this paper we will first propose a novel architecture for real-time power scheduling, which allows a user to easily incorporate fault diagnosis, stability analysis and power scheduling together, and then present a locally tactical power scheduling strategy based on a Lagrangian relaxation, which allows a user to adopt different computation techniques to undertake local computations within sub-systems in parallel to ensure good scalability of the distributed strategy. Moreover, the power scheduling is calculated based on an adaptive scheduling horizon to further reduce the computational complexity. Simulations are carried out to illustrate the effectiveness of our proposed distributed architecture, in particular, the optimality of the solution and the balanced computational complexity.
We present DADS, the first distributed, online, scalable, and cost-effective dynamic slicer for continuously-running distributed programs with respect to user-specified budget constraints. DADS is distributed by desig...
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ISBN:
(纸本)9781450370431
We present DADS, the first distributed, online, scalable, and cost-effective dynamic slicer for continuously-running distributed programs with respect to user-specified budget constraints. DADS is distributed by design to exploit distributed and parallel computing resources. With an online analysis, it avoids tracing hence the associated time and space costs. Most importantly, DADS achieves and maintains practical scalability and cost-effectiveness tradeoffs according to a given budget on analysis time by continually and automatically adjusting the configuration of its analysis algorithm on the fly via reinforcement learning. Against eight real-world Java distributedsystems, we empirically demonstrated the scalability and cost-effectiveness merits of DADS. The open-source tool package of DADS with a demo video is publicly available.
The proceedings contain 91 papers. The topics discussed include: a personal distributedreal-time collaborative system;a customized reinforcement learning based binary offloading in edge cloud;efficient post-quantum i...
ISBN:
(纸本)9781728190747
The proceedings contain 91 papers. The topics discussed include: a personal distributedreal-time collaborative system;a customized reinforcement learning based binary offloading in edge cloud;efficient post-quantum identity-based encryption with equality test;D2D-enabled reliable data collection for mobile crowd sensing;deep spatio-temporal attention model for grain storage temperature forecasting;secure and verifiable data access control scheme with policy update and computation outsourcing for edge computing;proactive content caching for internet-of-vehicles based on peer-to-peer federated learning;a similarity clustering-based deduplication strategy in cloud storage systems;and DyRAC: cost-aware resource assignment and provider selection for dynamic cloud workloads.
The article presents a parallel processing method instead of traditional serial processing method used in the software of petroleum pipe welding seam tracking system. Firstly, it analyses the shortages of serial proce...
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Robotics Cognitive Architectures (RCA) are becoming a key element in the design of robots that need to be aware of its surrounding space and of their role in it. This is especially important for robots that interact w...
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This paper presents AC-VC (Almost Causal Voice Conversion), a phonetic posteriorgrams based voice conversion system that can perform any-to-many voice conversion while having only 57.5 ms future look-ahead. The comple...
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ISBN:
(纸本)9781665437400
This paper presents AC-VC (Almost Causal Voice Conversion), a phonetic posteriorgrams based voice conversion system that can perform any-to-many voice conversion while having only 57.5 ms future look-ahead. The complete system is composed of three neural networks trained separately with non-parallel data. While most of the current voice conversion systems focus primarily on quality irrespective of algorithmic latency, this work elaborates on designing a method using a minimal amount of future context thus allowing a future real-time implementation. According to a subjective listening test organized in this work, the proposed AC-VC system achieves parity with the non-causal ASR-TTS baseline of the Voice Conversion Challenge 2020 in naturalness with a MOS of 3.5. In contrast, the results indicate that missing future context impacts speaker similarity. Obtained similarity percentage of 65% is lower than the similarity of current best voice conversion systems.
Aquaponics is essentially a compound agricultural farming model that combines aquaculture and hydroponics, which is used to improve resource utilization and promote sustainable development. It can be used to solve foo...
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ISBN:
(纸本)9781665417396
Aquaponics is essentially a compound agricultural farming model that combines aquaculture and hydroponics, which is used to improve resource utilization and promote sustainable development. It can be used to solve food and environmental problems in the world. The environment of aquaponics is sensitive. As aquatic organisms and plants are cultivated at the same time, aquaponics has stricter requirements on the environment. Internet of Things (IoT) technology has made many successful applications in modern agriculture, especially in realizing intelligent environmental monitoring and control, which is important for the further development of aquaponics. In recent years, many studies have focused on using IoT technology to guide the construction of aquaponic system. This paper describes the composition of aquaponic system in detail. The complexity of this system needs intelligent means to ensure its normal operation by enumerating and explaining the important parameters of aquaponics, as well as the intelligent monitoring and control strategies of aquaponic water environment in literatures. The key information is summarized to support the further promotion of automatic aquaponics solutions.
parallel and distributed community detection in large-scale complex networks, such as social networks, is a challenging task. parallel and distributed algorithm with high accuracy and low computational complexity is o...
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parallel and distributed community detection in large-scale complex networks, such as social networks, is a challenging task. parallel and distributed algorithm with high accuracy and low computational complexity is one of the essential issues in the community detection field. In this paper, we propose a novel fast, and accurate Spark-based parallel label diffusion and label selection-based (PLDLS) community detection algorithm with twostep of label diffusion of core nodes along with a new label selection (propagation) method. We have used multi factor criteria for computing node's importance and adopted a new method for selecting core nodes. In the first phase, utilizing the fact that nodes forming triangles, tend to be in the same community, parallel label diffusion of core nodes is performed to diffuse labels up to two levels. In the second phase, through an iterative and parallel process, the most appropriate labels are assigned to the remaining nodes. PLDLS proposes an improved robust version of LPA by putting aside randomness parameter tuning. Furthermore, we utilize a fast and parallel merge phase to get even more dense and accurate communities. Conducted experiments on real-world and artificial networks, indicates the better accuracy and low execution time of PLDLS in comparison with other examined methods.
Nowadays, autonomous driving and driver assistance applications are being developed at an accelerated pace. This rapid growth is primarily driven by the potential of such smart applications to significantly improve sa...
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ISBN:
(纸本)9781728144030
Nowadays, autonomous driving and driver assistance applications are being developed at an accelerated pace. This rapid growth is primarily driven by the potential of such smart applications to significantly improve safety on public roads and offer new possibilities for modern transportation concepts. Such indispensable applications typically require wireless connectivity between the vehicles and their surroundings, i.e. roadside infrastructure and cloud services. Nevertheless, such connectivity to external networks exposes the internal systems of individual vehicles to threats from remotely-launched attacks. In this realm, it is highly crucial to identify any misbehavior of the software components which might occur owing to either these threats or even software/hardware malfunctioning. In this paper, we introduce AutoSec, a host-based anomaly detection algorithm which relies on observing four timing parameters of the executed software components to accurately detect malicious behavior on the operating system level. To this end, AutoSec formulates the task of detecting anomalistic executions as a clustering problem. Specifically, AutoSec devises a hybrid clustering algorithm for grouping a set of collected timing traces resulted from executing the legitimate code. During the runtime, AutoSec simply classifies a certain execution as an anomaly, if its timing parameters are distant enough from the boundaries of the predefined clusters. To show the effectiveness of AutoSec, we collected timing traces from a testbed composed of a set of real and virtual control units communicating over a CAN bus. We show that using our proposed AutoSec, compared to baseline methods, we can identify up to 21% less false positives and 18% less false negatives.
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