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检索条件"主题词=Software algorithms"

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Enabling Hyperparameter Tuning of Machine Learning Classifiers in Production

Enabling Hyperparameter Tuning of Machine Learning Classifie...

引用

IEEE International Conference on Cognitive Machine Intelligence (CogMI)

作者： Sandeep Singh Sandha Mohit Aggarwal Swapnil Sayan Saha Mani Srivastava University of California Los Angeles Arm Research Austin

ISBN: (纸本)9781665416221

Machine learning (ML) classifiers are widely adopted in the learning-enabled components of intelligent Cyber-physical Systems (CPS) and tools used in designing integrated circuits. Due to the impact of the choice of hyperparameters on an ML classifier performance, hyperparameter tuning is a crucial step for application success. However, the practical adoption of existing hyperparameter tuning frameworks in production is hindered due to several factors such as inflexible architecture, limitations of search algorithms, software dependencies, or closed source nature. To enable state-of-the-art hyperparameter tuning in production, we propose the design of a lightweight library (1) having a flexible architecture facilitating usage on arbitrary systems, and (2) providing parallel optimization algorithms supporting mixed parameters (continuous, integer, and categorical), handling runtime failures, and allowing combined classifier selection and hyperparameter tuning (CASH). We present Mango, a black-box optimization library, to realize the proposed design. Mango is currently used in production at Arm for more than 25 months and is available open-source (https://***/ARM-software/mango). Our evaluation shows that Mango outperforms other black-box optimization libraries in tuning hyperparameters of ML classifiers having mixed param-eter search spaces. We discuss two use cases of Mango deployed in production at Arm, highlighting its flexible architecture and ease of adoption. The first use case trains ML classifiers on the Dask cluster using Mango to find bugs in Arm's integrated circuits designs. As a second use case, we introduce an AutoML framework deployed on the Kubernetes cluster using Mango. Finally, we present the third use-case of Mango in enabling neural architecture search (NAS) to transfer deep neural networks to TinyML platforms (microcontroller class devices) used by CPS/IoT applications.

关键词： Runtime software algorithms Pipelines Production Computer architecture Libraries Classification algorithms

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Optimal Planning of Distributed Generation and Capacitor Banks in Distribution Networks

Optimal Planning of Distributed Generation and Capacitor Ban...

引用

International Middle-East Power System Conference, MEPCON

作者： Ghada Abdulnasser Abdelfatah Ali Essam E. M. Mohamed South Valley University Qena Egypt

ISBN: (纸本)9781665419994

For many years, the constantly rising electricity demands have led to a growing concern. A reduction in power loss, as well as improvement of voltage profiles would be the consequence of optimizing both the location and size of capacitor banks (CBs) and distributed generation (DGs). This can be obtained as a result of the improvement in both voltage stability index (VSI) and voltage magnitude deviations (VD). However, this process must be carried out carefully since the improper size and/or location of DGs may negatively impact the distribution networks. This research presents an optimization-based algorithm for optimal sizing and placement of DGs and CBs. For this purpose, the Jellyfish search algorithm (JS) is employed to solve the optimization model. To elucidate the efficiency of the proposed algorithm, different cases have been considered, starting with the CBs allocation only, the DGs allocation only, and then the allocation of both the CBs and DGs. While their active and reactive power capabilities are taken into consideration. Furthermore, a multi-objective optimization that considers the technical, economic, and emission objectives are also carried out. The results show that the JS delivers preferable results in terms of improving technical, economic, and emission objectives. Furthermore, the results indicate a superior operation when having a controllable power factor (pf) DGs. The calculations have been done for the IEEE-33 bus system using MATLAB software.

关键词： Economics Reactive power Capacitors Stability criteria software algorithms Voltage Distribution networks

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Research and Development of Rear Combined Lamp Detection System Based on Machine Vision

Research and Development of Rear Combined Lamp Detection Sys...

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China International Forum o Solid State Lighting: International Forum on Wide Bandgap Semiconductors China (SSLChina: IFWS)

作者： Pan Mingqing Wang Huailei Luo Xu Deng Liang Changzhou Xingyu Automotive Lighting System Co. LTD. Nanjing University of Aeronautics and Astronautics Hohai University Changzhou city Jiangsu Province P.R.China

ISBN: (纸本)9781665495479

As an important part of the car, the rear combination lamp of the car has been developed from the traditional single lighting function to multi-functional intelligent lighting components. The dynamic steering display and dazzling welcome lighting effects have been developed for the appearance of the car. The detection method of the combined lamp is significant to ensure the quality of the product. In this paper, an automatic detection system for rear combination lamps is designed based on machine vision. The test results show that the system can efficiently detect the functions and characteristics of the rear combination lamps.

关键词： Image segmentation LED lamps Shape Photonic band gap software algorithms Lighting Object segmentation

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New Low-Power Architectures of Support Vector Machine Classifier for Speech Recognition System

New Low-Power Architectures of Support Vector Machine Classi...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Gracieth C. Batista Duarte L. Oliveira Osamu Saotome Electronic Engineering Division Technological Institute of Aeronautics &#x2013 IEEA &#x2013 ITA &#x2013 SJC Brazil

ISBN: (数字)9781728176703

ISBN: (纸本)9781728176710

This paper proposes two architectures for an Artificial Intelligence (AI) algorithm applied in hardware. We have a first asynchronous proposal, 10-stage pipeline architecture, and a second proposal, Globally Asynchronous Locally Synchronous (GALS) pipeline architecture, for Support Vector Machine (SVM) non-linear classifier prototyped in a Field Programmable Gate Array (FPGA) – INTEL-ALTERA device. The training dataset was generated from a Hybrid Training Algorithm implemented in Matlab software. Such an algorithm is composed of the Particle Swarm Optimization (PSO) algorithm application, followed by the SVM Training. For the speech signal pre-processing part, techniques of Mel-frequency Cepstral Coefficients (MFCCs) extraction and Discrete Cosine Transform were used. The whole idea was to develop an Automatic Speech Recognition (ASR) System with minimum use of the area as possible, low power consumption, and minimum human intervention. The first and second proposals results were, respectively, 30.79mW and 36.28mW of power consumption, 4.6%, and 2.1% of used LUTs. In recognition success rate, both proposals achieved 99% accuracy.

关键词： Support vector machines Training Power demand software algorithms Pipelines Computer architecture Classification algorithms

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Active Equalization Control System and Design of Lithium Battery

Active Equalization Control System and Design of Lithium Bat...

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Chinese Automation Congress (CAC)

作者： Bo Zhang Dairong Hu Guangxu Zhou Hao Wang Jian Xiang Yunhai Zhu Shandong Provincial Key Laboratory of Automotive Electronic Technology Institute of Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China Jinan Branch of China Iron Tower Co. Ltd Jinan China Qilu University of Technology (Shandong Academy of Sciences) Jinan China

ISBN: (纸本)9781665426480

Aiming at the inconsistency in the use of lithium battery pack, an active balance control strategy is proposed in this paper. The principle of bidirectional flyback equalization circuit is analyzed. The SPI interface of MC9S12XEP100 is used to communicate with LTC3300 in serial, and the hardware system circuit is designed. According to the communication protocol of the equalization controller, the equalization command is written and executed, and an active equalization control method is designed. The experimental results show that the designed hardware circuit and software algorithm are feasible, the data transfer is stable and normal, and the energy flow between batteries can be realized, and the battery balance control requirements can be met.

关键词： MOSFET Protocols Microcontrollers software algorithms Microcomputers Lithium batteries Hardware

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DEVIATE: A Deep Learning Variance Testing Framework 21

DEVIATE: A Deep Learning Variance Testing Framework

引用

IEEE International Conference on Automated software Engineering (ASE)

作者： Hung Viet Pham Mijung Kim Lin Tan Yaoliang Yu Nachiappan Nagappan University of Waterloo Purdue University Microsoft Research

ISBN: (纸本)9781665447843

Deep learning (DL) training is nondeterministic and such nondeterminism was shown to cause significant variance of model accuracy (up to 10.8%). Such variance may affect the validity of the comparison of newly proposed DL techniques with baselines. To ensure such validity, DL researchers and practitioners must replicate their experiments multiple times with identical settings to quantify the variance of the proposed approaches and baselines. Replicating and measuring DL variances reliably and efficiently is challenging and *** propose a ready-to-deploy framework DEVIATE that (1) measures DL training variance of a DL model with minimal manual efforts, and (2) provides statistical tests of both accuracy and variance. Specifically, DEVIATE automatically analyzes the DL training code and extracts monitored important metrics (such as accuracy and loss). In addition, DEVIATE performs popular statistical tests and provides users with a report of statistical p-values and effect sizes along with various confidence levels when comparing to selected *** demonstrate the effectiveness of DEVIATE by performing case studies with adversarial training. Specifically, for an adversarial training process that uses the Fast Gradient Signed Method to generate adversarial examples as the training data, DEVIATE measures a max difference of accuracy among 8 identical training runs with fixed random seeds to be up to 5.1%.Tool and demo links: https://***/lin-tan/DEVIATE

关键词： Training Deep learning software algorithms Training data Manuals software software measurement

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Application of Improved Random Forest Method and C4.5 Algorithm as Classifier to Ransomware Detection Based on the Frequency Appearance of API Calls

Application of Improved Random Forest Method and C4.5 Algori...

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Information Technology International Seminar (ITIS)

作者： Dwi Kuswanto Husni M. Rozin Anjad Informatic Engineering Department University Trunojoyo of Madura Bangkalan Jawa Timur

ISBN: (纸本)9781665408080

The signature base technique cannot recognize new types of Ransomware without first analyzing it. For that, we need a method to detect Ransomware using machine learning. This study aims to apply the improved Random Forest method to detect Ransomware in a random. The Forest used the feature evaluator and filter instances to increase the accuracy of the regular Random Forest. This study will use the improved Random Forest method with the C4.5 algorithm as a classifier to detect Ransomware. In this study, several stages were done to detect Malware using an improved Random Forest, namely extracting API calls, then selecting features based on the occurrence ratio of Malware, performing evaluator, resampling features, and then classifying them. The feature used API calls in the Malware based on the frequency that appears the most. Implementation of Ransomware detection using the improved Random Forest method obtained an accuracy value of 96% with an API call ratio value of 0.02 with 188 features. The results show that the Ransomware detection software is ineffective for all conditions. Because some Ransomware has not had the same API call, which affected failed the detection.

关键词： Seminars System testing Machine learning algorithms software algorithms Forestry Feature extraction Classification algorithms

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Multi-Radar Cooperative Task Planning using NSGA-II Algorithm

Multi-Radar Cooperative Task Planning using NSGA-II Algorith...

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IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Xiang Liu Chao Zhang Yanjun Cao Li Han Zhiming Wu The 54th Research Institute of China Electronics Technology Corporation Shijiazhuang China China University of Geosciences Wuhan China

ISBN: (纸本)9781665478373

Adopting multi-radar cooperative plan technology to realize the unified tasks planning can improve the efficiency of existing radars. By studying the characteristics of multi-radar cooperative planning tasks, the NSGA-II algorithm adopted in this paper can quickly complete multi-radar cooperative task planning. The result has the characteristics of uniform data distribution, high convergence and high robustness, and has better task optimization effect. It is a good idea to solve multi-radar for collaborative tasks planning.

关键词： software algorithms software quality Radar Robustness Planning software reliability Security

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Approaches to Intellectual Property of Robotics Industry

Approaches to Intellectual Property of Robotics Industry

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International Scientific-Practical Conference Problems of Infocommunications Science and Technology

作者： Daniil Shmatkov Serhii Hlibko Iurii Georgiievskyi Scientific and Research Institute of Providing Legal Framework for the Innovative Development of the National Academy of Legal Sciences of Ukraine Kharkiv Ukraine

ISBN: (纸本)9781665406833

The purpose of this study is to identify common approaches to obtaining rights to various intellectual property objects in the field of robotics through a qualitative and quantitative assessment of applications and received protection certificates. As a result of researching the activities of eleven well-known companies, we identified filed and active trademarks, patent applications, and copyright certificates. A qualitative analysis of the documents showed that, with a significant preference for patents, companies are not too interested in registering copyright, despite the fact that every four out of five inventions implement information and communication technologies and services and are carried out using software developments, which is copyright according to various national and international regulations. While patent protection has significant advantages, software algorithms can be more comprehensively protected with additional tools. The results of this study can be useful to various SMEs and startups for building strategies for obtaining intellectual property rights and practical activities.

关键词： Patents Technological innovation Text analysis Service robots Buildings software algorithms Intellectual property

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ArCode: Facilitating the Use of Application Frameworks to Implement Tactics and Patterns

ArCode: Facilitating the Use of Application Frameworks to Im...

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Working IEEE/IFIP Conference on software Architecture

作者： Ali Shokri Joanna C. S. Santos Mehdi Mirakhorli Rochester Institute of Technology Rochester NY United States

The following topics are dealt with: software architecture; software maintenance; software engineering; object-oriented programming; Internet; application program interfaces; software metrics; software quality; busine... 详细信息

ISBN: (纸本)9781728162607;9781728162614

关键词： Training Java software architecture Object oriented modeling software algorithms Training data software

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