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检索条件"主题词=Software Algorithms"

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Quantum Computing Platforms: Assessing the Impact on Quality Attributes and SDLC Activities

Quantum Computing Platforms: Assessing the Impact on Quality...

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Working IEEE/IFIP Conference on software Architecture

作者： Balwinder Sodhi Ritu Kapur Indian Institute of Technology Ropar Punjab India

Practical quantum computing is rapidly becoming a reality. To harness quantum computers' real potential in software applications, one needs to have an in-depth understanding of all such characteristics of quantum computing platforms (QCPs), relevant from the software Engineering (SE) perspective. Restrictions on copying, deletion, the transmission of qubit states, a hard dependency on quantum algorithms are few, out of many, examples of QCP characteristics that have significant implications for building quantum ***, developing quantum software requires a paradigm shift in thinking by software engineers. This paper presents the key findings from the SE perspective, resulting from an in-depth examination of state-of-the-art QCPs available today. The main contributions that we present include i) Proposing a general architecture of the QCPs, ii) Proposing a programming model for developing quantum software, iii) Determining architecturally significant characteristics of QCPs, and iv) Determining the impact of these characteristics on various Quality Attributes (QAs) and software Development Life Cycle (SDLC) *** show that the nature of QCPs makes them useful mainly in specialized application areas such as scientific computing. Except for performance and scalability, most of the other QAs (e.g., maintainability, testability, and reliability) are adversely affected by different characteristics of a QCP.

关键词： Quantum algorithm software architecture Scalability Qubit Buildings software algorithms Computer architecture

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Nano Version Control and the Repo as the Next Data Structure in Computer Science and Artificial Intelligence

Nano Version Control and the Repo as the Next Data Structure...

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Ethics and Explainability for Responsible Data Science (EE-RDS)

作者： Lukasz Machowski Tshilidzi Marwala Synthesis Software Technologies Johannesburg South Africa University of Johannesburg Johannesburg South Africa

ISBN: (纸本)9781665483599

A new data structure called the Nano Version Control (NanoVC) Repo emerges from its origins in the fundamental data structures of computer science as well as from Git. It is acknowledged as a first-class data structure with the added benefit that the software industry already knows how to reason with it because of their experience with using it to version control software. The NanoVC Repo shines a light on the value of nano-scale modelling and in-memory representation of history. An initial implementation shows promising results where it out-performs Git implementations by 2–3 orders of magnitude. A parallel for fairness, transparency and explainability is made between Git (as used for versioning software algorithms) and the NanoVC Repo, which can be used for data structures. Applications of the NanoVC Repo are in computer science, storage and databases, data modelling, distributed and cloud computing, data quality, event streaming, artificial intelligence, and agent-based simulation. The hope is that this data structure is the next major step in computer science and artificial intelligence applications.

关键词： Computer science Industries Computational modeling software algorithms Distributed databases Data structures software

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Air Navigation: The Method of Airborne Vehicles' Classification Based on Fuzzy Colored Petri Nets

Air Navigation: The Method of Airborne Vehicles' Classificat...

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Open Innovations Association (FRUCT), Conference of

作者： Ivan Linnik Elena Linnik Rena Timirgaleeva Igor Grishin Aleksander Tamargazin Humanitarian and Pedagogical Academy Yalta Russia Lomonosov Moscow State University Moscow Russia National Aviation University Kyiv Ukraine

ISBN: (纸本)9789526924458;9781665414159

Based on mathematical methods of fuzzy colored Petri nets proposed is a method of airborne vehicles' identification in controlled airspace allowing to reduce the dependence of the degree of fuzzy net model of the corresponding software's verification on the degree of dynamic interacting processes in the subject area. Proposed are the data of fuzzy rule-oriented requirements of the fuzzy logical system of airborne vehicles' classification in the process of airspace control. Developed is a unified algorithm of these requirements' implementation. Further, the fuzzy rule-oriented requirements are in structural conformity with the requirements of the Sugeno fuzzy logical system of the first-order. This view of the airborne vehicles' classification process using the fuzzy logical system allows considering both the non-stochastic and subjective nature of operators' decision-making. The developed unified algorithm of the fuzzy rule-oriented requirements' implementation within the Sugeno system of the first-order is the basis for the software of the fuzzy logical system of airborne vehicles' classification.

关键词： Atmospheric modeling Heuristic algorithms Petri nets software algorithms Process control Production software

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Development of A Distributed Intelligent System for Load Management in Micro Energy Systems

Development of A Distributed Intelligent System for Load Man...

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IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

作者： Shahboz Hafizov Alexander Voloshin Evgeniy Voloshin Shakhnoza Mirzoeva National research universiry MPEI Moscow Russia

ISBN: (数字)9781665404761

ISBN: (纸本)9781665446426

Market pricing mechanisms in the Russian Federation exist only for price zones, in other cases, prices are regulated by the government, especially in places of technologically isolated power systems, diesel power plants are often used, which significantly increases the price of electricity. To solve this problem, new generation plants can be built based on renewable energy sources, and demand management technology can be applied to reduce consumption and reduce the cost of electricity during peak hours. Real-time pricing is proposed as an effective way of managing demand from consumers. To analyze the impact of a price-dependent load control method on the cost of electricity, a real-time pricing algorithm based on market mechanisms and a model for studying the correctness of the algorithm in the Matlab software package were developed. It is shown that when using a price-dependent load control method, the demand for electricity during peak hours decreases.

关键词： software algorithms Pricing Load management Real-time systems Mathematical model Matlab Load modeling

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A Boolean Network Tomography based Method for Deterministic Multi-point Fault Detection

A Boolean Network Tomography based Method for Deterministic ...

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2021 IEEE Global Communications Conference (GLOBECOM)

作者： Sukun Zhang Hai Wan Xibin Zhao School of Software BNRist Tsinghua University Beijing China

ISBN: (纸本)9781728181059

Time-sensitive networking (TSN) is a deterministic network, where failures will seriously affect the quality of the real-time data transmission service. Hence, fault localization is critical in TSN. In the application domain of TSN, an ideal link failure detection method needs to have properties including execution time deterministic, low detection traffic overhead, multi-point fault detection capability for arbitrary typologies. However, current state-of-the-art fault detection algorithms can not achieve these properties simultaneously. In this paper, we propose a Boolean network tomography-based multi-point fault detection method that leverages the deterministic transmission mechanism of TSN to guarantee that the detection time is upper bounded. The method includes an offline preparation phase and an online operation phase. In the preparation phase, we use a detection flow generation algorithm to get a set of detection flows that can identify up to $K$ faults with as few paths as possible. In the operation phase, detection packets are realized as time-sensitive flows routing along the detection paths. They are sent periodically to the controller which performs a topology discovery algorithm to infer the faulty links based on the arrival status of each detection packet. Comprehensive experiments are conducted and the results show that compared with existing fault detection methods, the proposed algorithm can accurately identify multiple faulty links in deterministic time, and the generated detection paths set needs fewer paths than the prior methods.

关键词： Fault diagnosis Fault detection software algorithms Tomography Approximation algorithms Routing Real-time systems

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Review of Firmware Homology Detection: a System Aspect

Review of Firmware Homology Detection: a System Aspect

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Song Yan Wang Binbin Yu Xiaohu Li Tinghui Zhu Shanshan He Daojing Yang Guisong Chan Sammy State Grid Shanghai Municipal Electrical Power Research Institute Shanghai China School of software engineering East China Normal University Shanghai China East China Normal University Shanghai China University of Shanghai for Science and Technology Shanghai China City University of Hong Kong Hong Kong China

ISBN: (纸本)9781665418164

In recent years, Internet of Things (IoT) devices have received extensive attention and can be seen everywhere in daily life. Attacks against firmware vulnerabilities are becoming more and more frequent. Homology analysis technology is a hot topic in recent years. Firmware vulnerability analysis based on homology analysis can classify the firmware of different versions or even different devices, and detect the vulnerabilities in the firmware by detecting the homology of the open source library. This paper provides a literature review of firmware homology detection. Firstly, the background of firmware vulnerability analysis and the research status of homology detection at home and abroad are briefly introduced. Then, under the source code based homology analysis technology, according to whether it chooses to use the intermediate form to explain the source code and the different intermediate forms, three different homology analysis technologies based on text, token and structure are divided, and the three technologies are compared horizontally. Then, in the non source code based homology analysis technology, the overall process of homology detection based on binary files is introduced, as well as the main technologies such as byte stream comparison and reverse analysis. Finally, various homology analysis methods are analyzed and compared from the aspects of efficiency and accuracy, and the research focus and direction in this field are summarized and prospected.

关键词： Codes Plagiarism Face recognition software algorithms Semantics Syntactics software

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Machine Learning System-Enabled GPU Acceleration for EDA

Machine Learning System-Enabled GPU Acceleration for EDA

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International Symposium on VLSI Design, Automation and Test

作者： Tsung-Wei Huang University of Utah Salt Lake City UT

ISBN: (纸本)9781665419154;9781665430289

Electronic design automation (EDA) contains many of the most challenging computational problems that optimize circuit layouts across billions of transistors. Most existing EDA algorithms are architecturally constrained by CPU parallelism, and their performances stagnate at about 8-16 cores To achieve new transformational performance milestones, new EDA algorithms must harness the power of heterogeneous parallelism comprising manycore CPUs and GPUs. However, these milestones are too difficult to achieve without a suitable software system to assist developers in the implementation complexities built into heterogeneous parallelism. Thanks to the advancement of machine learning, various software systems have been introduced to streamline the design of heterogeneous programs, and these results have inspired new heterogeneous parallel EDA solutions. In this talk, we present our research on GPU acceleration for placement and timing analysis by harnessing the power of machine learning systems. As an example, we achieve 500× speed-up for static timing analysis on a million-gate design.

关键词： Design automation Machine learning algorithms software algorithms Graphics processing units Machine learning Parallel processing Very large scale integration

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Coverage-Based Grammar-Guided Genetic Programming Generation of Test Suites

Coverage-Based Grammar-Guided Genetic Programming Generation...

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Congress on Evolutionary Computation

作者： Alfredo Ibias Pablo Vazquez-Gomis Miguel Benito-Parejo DTRS research group Universidad Complutense de Madrid Madrid Spain

software testing is fundamental to ensure the reliability of software. To properly test software, it is critical to generate test suites with high fault finding ability. We propose a new method to generate such test suites: a coverage-based grammar-guide genetic programming algorithm. This evolutionary computation based method allows us to generate test suites that conform with respect to a specification of the system under test using the coverage of such test suites as a guide. We considered scenarios for both black-box testing and white-box testing, depending on the different criteria we work with at each situation. Our experiments show that our proposed method outperforms other baseline methods, both in performance and execution time.

关键词： software testing software algorithms Genetic programming Evolutionary computation software software reliability Genetic communication

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A Novel Approach of SVM for Fault Detection and Classification in a Series Compensated Line

A Novel Approach of SVM for Fault Detection and Classificati...

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Innovations in Power and Advanced Computing Technologies (i-PACT)

作者： Satyabrata Sahoo Subodh Kumar Mohanty School of Electrical Engineering KIIT deemed to be University Bhubaneswar India

ISBN: (纸本)9781665426923

Detection and classification of fault in a series compensated transmission line is quite a challenging task. This paper presents a method based on a machine learning algorithm that uses Support Vector Machine using Gaussian Kernel to detect and classify the various faults in lines. This developed method takes one cycle pre and post current samples to test the SVM. This algorithm is tested on a two area 400 kV, 50 Hz source power network simulated in PSCAD software platform. The algorithm takes into consideration the post fault current data in one cycle, which is fed into the system at runtime. Various faulted conditions have been checked using varying resistances, fault distance and its types.

关键词： Support vector machines Technological innovation Machine learning algorithms Fault detection software algorithms Training data Support vector machine classification

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DRNet: QoS-aware Routing for SDN using Deep Reinforcement Learning

DRNet: QoS-aware Routing for SDN using Deep Reinforcement Le...

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International Conference on Communication Technology (ICCT)

作者： Jianjia Li Kai Jiang Jiru Wang Liang Qin Wenting Wei Key Lab of Information System Requirement NanJing China State Key Laboratory of Integrated Service Networks Xidian University Xi'an China Key Lab of Information System Requirement NanJingChina

ISBN: (纸本)9781665432078

software-defined network (SDN) has been considered as a promising paradigm for next-generation network architecture. Thanks to its flexibility and programmability, SDN enables more flexible routing deployments over networks. However, with the emergence of new applications with differentiated demands, traditional routing strategies are difficult to meet QoS requirements from diversified applications while maintaining high performance due to the lack of interaction with their external environment. In this paper, a QoS-aware routing algorithm based on deep reinforcement learning (DRL) is proposed, termed as DRNet. Specifically, the traffic demand matrix, as well as the current network state, is fed into the DRNet model to train a DRL agent by DQN, which can decide a feasible optimal path from a set of available loop-free paths in the network. To reduce the exploration space of DRNet agent, only a portion of the candidate paths with the same source-destination are selected in each training step, so that only part of the Q-table would be updated. To verify the effectiveness of DRNet, we design and implement a simulation platform using OMNET++ and evaluate QoS metrics. The simulation results confirm that our algorithm outperforms existing shortest path routing method based on the Dijkstra algorithm and can achieve better performance than the Deep Deterministic Policy Gradient (DDPG) algorithm while learning.

关键词： Training Simulation software algorithms Neural networks Quality of service Reinforcement learning Routing

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