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Developing Embedded Kernel for System-On-a-Chip Platform of Heterogeneous Multiprocessor Architecture

Developing Embedded Kernel for System-On-a-Chip Platform of ...

引用

IEEE international conference on Embedded and Real-Time Computing systems and Applications (RTCSA)

作者： Jing Chen Jian-Hong Liu Department of Electrical Engineering National Cheng Kung University Tainan Taiwan

It has been common that modern embedded system products are built on platforms with system-on-a-chip (SOC) in which two or more different processor cores are put into one single chip and form the architecture of heterogeneous multiprocessor. Although providing high performance at low cost, such architecture brings new design challenges as well as increased complexity in developing embedded software especially at the level of kernel or operating system software. this paper presents our experience in developing an embedded microkernel that runs on embedded system of heterogeneous multiprocessor architecture composed of one general purpose processor (GPP) and one special purpose processor (SPP). Aside from following the traditional approach of monolithic operating system, the option of dual kernels based on microkernel architecture with uniform message-passing mechanism was taken to develop a symmetric embedded microkernel which can be compiled to run separately on each of the different processor cores in the system. the design and the approach not only reduce the software complexity in developing a kernel to manage different processors in a system but also enable a symmetric view from processors of different architectures. A prototype kernel was implemented on a reference design of Texas Instrument's TMS320DSC25 which is a heterogeneous multiprocessor SOC with a GPP of ARM7TDMI core and an SPP of C5409 DSP core

关键词： Kernel System-on-a-chip Computer architecture Embedded system Embedded software Operating systems Costs software performance software systems software development management

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P²LSA and P²LSA+: Two Paralleled Probabilistic Latent Semantic Analysis Algorithms Based on the MapReduce Model

P<SUP>2</SUP>LSA and P<SUP>2</SUP>LSA+: Two Paralleled Proba...

引用

12th international conference on intelligent Data engineering and Automated Learning (IDEAL 2011)

作者： Jin, Yan Gao, Yang Shi, Yinghuan Shang, Lin Wang, Ruili Yang, Yubin Nanjing Univ State Key Lab Novel Software Technol Nanjing 210093 Jiangsu Peoples R China Massey Univ Sch Engn & Adv Technol Palmerston North New Zealand

ISBN: (纸本)9783642238772

Two novel paralleled Probabilistic Latent Semantic Analysis (PLSA) algorithms based on the MapReduce model are proposed, which are P(2)LSA and P(2)LSA+, respectively. When dealing with a large-scale data set, P(2)LSA and P(2)LSA+ can improve the computing speed with the Hadoop platform. the Expectation-Maximization (EM) algorithm is often used in the traditional PLSA method to estimate two hidden parameter vectors, while the parallel PLSA is to implement the EM algorithm in parallel. the EM algorithm includes two steps: E-step and M-step. In P(2)LSA, the Map function is adopted to perform the E-step and the Reduce function is adopted to perform the M-step. However, all the intermediate results computed in the E-step need to be sent to the M-step. Transferring a large amount of data between the E-step and the M-step increases the burden on the network and the overall running time. Different from P(2)LSA, the Map function in P(2)LSA+ performs the E-step and M-step simultaneously. therefore, the data transferred between the E-step and M-step is reduced and the performance is improved. Experiments are conducted to evaluate the performances of P(2)LSA and P(2)LSA+. the data set includes 20000 users and 10927 goods. the speedup curves show that the overall running time decrease as the number of computing nodes increases. Also, the overall running time demonstrates that P(2)LSA+ is about 3 times faster than P(2)LSA.

关键词： Paralleled PLSA PLSA MapReduce

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Novel DC-input ΣΔ capacitance-to-digital convertor for biosensor applications

Novel DC-input ΣΔ capacitance-to-digital convertor for bio...

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Annual IEEE Northeast Workshop on Circuits and systems (NEWCAS)

作者： Ghazal Nabovati Ebrahim Ghafar-Zadeh Mohamad Sawan Departement of Electrical Engineering Polytechnique Polystim Neurotechnologies Laboratory Montreal Canada York University Toronto ON CA

In this paper we present a novel DC-input ΣΔ modulator architecture for CMOS capacitive sensors based on charge to digital conversion. this new core-CBCM ΣΔ modulator is designed in Cadence software using TSMC 0.35 μm technology, and based on circuit parameters a behavioral model in Matlab is developed. By using behavioral time-domain simulations in Matlab, optimized values of parameters in ΣΔ modulator are determined to improve the overall circuit performance. the simulation results show that the proposed ΣΔ modulator has the dynamic range of 100-110 fF and can reach to the resolution of 10 bits.

关键词： Modulation Capacitance MATLAB CMOS integrated circuits Capacitive sensors Sensitivity Decoding

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Networked Mobile Robots for Smart Agriculture

Networked Mobile Robots for Smart Agriculture

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intelligent systems and Embedded Design (ISED), international conference on

作者： Rohan Karthikeya Chekuri Priya Darshni M Sivraj P Department of Electrical and Electronics Engineering Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331522612

ISBN: (纸本)9798331522629

Amidst the dynamic landscape of agriculture, the integration of robotic technologies emerges as a transformative force. this paper unveils a robotic plant health monitoring and intervention system, integrating machine learning and networking, tailored to revolutionize automation of agricultural practices. the centralized network server, in the system, utilizes Python scripts for socket communication with robots, as well as for implementing algorithms for optimized robot selection and path planning. Surveillance robots, equipped with ESP32-S with camera and Wroom modules navigate around the field and capture real-time images. the server on receiving these images does crop disease detection using Convolutional Neural Networks (CNNs), achieving high accuracy. Spray bots then target affected crops and spray pesticides and fertilizers as necessary using a 5V pump with precision. Unlike the surveillance robots, the spray bots are equipped with only ESP32 Wroom which controls both the movement and spray action. the system also features a software implementation that illustrates tasks like robot selection, networked communication, surveillance, and pesticide application autonomously executed in an agricultural field, highlighting the potential for scalable field deployment. the integrated solution ensures timely interventions, enhances yield quality, reduces environmental impact, and demonstrates potential of the concept - Internet of Robots in driving sustainable agricultural practices. Future iterations aim for full autonomy to further optimize system operation.

关键词： Smart agriculture Surveillance Sockets Plants (biology) Robot vision systems Pesticides software Real-time systems Servers Mobile robots

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Dynamic State Estimation and Anomaly Detection in Smart Grid Using Point-Based Gaussian Approximation Filtering

Dynamic State Estimation and Anomaly Detection in Smart Grid...

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IEEE international Symposium on Cyberspace Safety and Security

作者： Ziyu Guo Wei Heng Shang Li Xiaodong Wang National Mobile Communications Research Lab. Southeast University Electrical Engineering Department Columbia University

ISBN: (纸本)9781479989386

We consider the problem of dynamic state estimation and anomaly detection in smart grid, which is a typical cyber-physical system that is described by a nonlinear model. the state estimation problem is solved by the point-based Gaussian approximation filter, which incorporates different quadrature rules to compute the posteriors. this filtering method is compared with its traditional counterpart - the extended Kalman filter - and much higher tracking accuracy is achieved as expected. the point-based Gaussian approximation filter is then combined with the widely-used anomaly processing method to detect the bad measurement and sudden load change in smart grid. the innovation vector, which is used in the update step of filtering, is first examined for the presence of anomalies, and then processed to perform skewness-test for anomaly discrimination.

关键词： State estimation Quadrature rules Gaussian approximation filter Anomaly detection

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Visual category recognition for the improved storage and retrieval performance of the CCTV camera system

Visual category recognition for the improved storage and ret...

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international conference on Hybrid intelligent systems (HIS)

作者： Asif Ali Khan Syed Faiz Akbar Shah Fahad Ullah Nasru Minallah Department of Computer Systems Engineering UET Peshawar KPK Pakistan

In this paper, we propose a category level object recognition system for the efficient use of CCTV cameras in terms of storage and retrieval. We investigate the performance of the proposed approach by using four different classifiers. More specifically, we considered image sequences with cars, bikes and pedestrian as our three targeted object categories for classification and ultimately efficient storage and retrieval with reference to our CCTV cameras system. We utilized Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Cartesian Genetic Programming (CGP) algorithms for the considered object categories classification. the Linear Discriminant Analysis (LDA), KNN and Support Vector Machine (SVM) are Statistical algorithms while Cartesian Genetic Programming (CGP) is Evolutionary Algorithm. More specifically, we utilized the standard “Caltech 101” dataset for investigating the performance of our proposed classifiers. Scale Invariant Feature Transform (SIFT) has been used to extract the scale, orientation and translational invariant features from the considered images which are input to the classifiers. Our empirical results show that in most of the cases, the results of LDA and SVM are relatively the same. To be specific, LDA gives an average accuracy of 85.3% and SVM 83.6%. Similarly, KNN gives an average accuracy of 74.6% while CGP outperforming the three gives accuracy rate of 89%.

关键词： Support vector machines Training Feature extraction Testing Accuracy Cameras Genetic programming

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I-assistant: An intelligent Teaching Assistant System for Classroom Teaching

I-assistant: An Intelligent Teaching Assistant System for Cl...

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international conference on Educational and Information Technology (ICEIT)

作者： Xinyan Zhang Jing Geng Yuqi Chen Shengze Hu Tao Huang National Engineering Research Center of Educational Big Data Central China Normal University Wuhan China Faculty of Artificial Intelligence in Education Central China Normal University Wuhan China

intelligent teaching assistant system provides help for teachers in teaching through information technology to reduce the burden of teachers. Most of today’s intelligent teaching assistant systems are still providing teachers with simple functions to assist them in completing some simple tasks in daily teaching. However, the effective integration of intelligent algorithms and classroom instruction has been somewhat neglected. To solve the problem, we design I-assistant, an intelligent teaching assistant system, which combines intelligent algorithms and classrooms to assist teachers to conduct precise teaching. I-assistant consists of four modules, class cognitive level module, class subject ability module, classroom state module, and subject design and evaluation module. In the first three modules, we use artificial intelligence algorithms to analyze student homework, tests as well as video data to present student learning situation visually. In the last module, the system helps teachers with instructional design and promotes effective and accurate teaching in classroom.

关键词： Education Learning (artificial intelligence) Behavioral sciences Information technology Task analysis Monitoring

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Wireless sensor networks - new challenges in software engineering

Wireless sensor networks - new challenges in software engine...

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international conference on Emerging Technologies and Factory Automation (ETFA)

作者： J. Blumenthal M. Handy F. Golatowski M. Haase D. Timmermann Institute of Applied Microelectronics and Computer Science Department of Electrical Engineering and Information Technology University of Rostock Rostock Germany

software development for wireless sensor networks requires novel programming paradigms and technologies. this article describes the concept of a new service oriented software architecture for mobile sensor networks. With this architecture, a flexible, scalable programming of applications based on an adaptive middleware is possible. the middleware supports mechanisms for cooperative data mining, self-organization, networking, and energy optimization to build higher-level service structures. the purpose of our research activities is the development of a framework, which radically simplifies the development of software for sensor network applications.

关键词： Wireless sensor networks intelligent networks software engineering Electromechanical sensors Programming Sensor systems Sensor phenomena and characterization Application software Middleware Biomedical monitoring

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ID-based Deniable threshold Ring Authentication

ID-based Deniable Threshold Ring Authentication

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IEEE international Symposium on Cyberspace Safety and Security

作者： Chunhua Jin Chunxiang Xu Linzhi Jiang Fagen Li School of Computer Science and Engineering University of Electronic Science and Technology of China

ISBN: (纸本)9781479989386

Deniable threshold ring authentication allows at least t members of a group participants to authenticate a message m without revealing which t members have generated the authenticator, and the verifier cannot convince any third party the message m is authenticated. It can be applied in anonymous and privacy communication scenarios. In this paper, we present a non-interactive identity-based deniable threshold ring authentication scheme. Our scheme is provably secure in the random oracle model under the bilinear Diffie-Hellman assumption. To the best of our knowledge, our scheme is the first identity based deniable threshold ring authentication scheme. Our scheme is very efficient since it only requires one pairing operation in authentication phase and one pairing operation in verification phase regardless of the number of the ring.

关键词： Deniable threshold ring authentication Anonymous Privacy Identity-based cryptography Random oracle model

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intelligent system based supervision for energy management of water chiller plant

Intelligent system based supervision for energy management o...

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international conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Monruthai Radeerom Kritsanat tharathanmathikorn Faculty of Information Technology Rangsit University Pathumthani Thailand

ISBN: (纸本)9781479979622

For almost a decade, intelligent systems have shown great potential for solving non-linear control problems. this paper exhibits a possibility of using a neuro-fuzzy system to advise a chiller plant. this plant, located at Building No.11 of Rangsit University, consists of three water chillers. Nonlinear dynamic characteristics, resulting from outdoor conditions, and equipment within the plant such as pumps and modulation valves, are discussed herein. the objective of this research is to minimize energy cost while maintaining high performance of the plant. In this paper, identification and prediction of a non-linear discrete time system using a neuro-fuzzy system is investigated. To develop an algorithm for achieving such an objective, the first step is to learn the relationship of outdoor temperature, humidity, and cooling load of the building, or the plant dynamics, from historical data. After being trained completely, the neuro-fuzzy system is used to predict the cooling load for Building No.11 at Rangsit University and operating optimal points of the water chiller plant. We use the visual studio to develop an advised chiller plant management program. this program learns the information from both historical and presents data of the chiller plant. After that, we compared energy costs before (May-July 2014) and after (August-October 2014) using advisory management of the chiller plant program. the system can reduce electrical cost within 5%. Furthermore, it can be trained by plant operators continuously.

关键词： Cooling Buildings Artificial neural networks Temperature distribution Training intelligent systems Temperature measurement

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