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共 2975 条记录，以下是2851-2860 订阅

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Combining Computer Vision and Word processing to Classify Film Genres

Combining Computer Vision and Word Processing to Classify Fi...

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Digital Signal processing and its Applications (DSPA), international conference on

作者： Nikita Andriyanov Vitaly Dementev Data Analysis and Machine Learning Department Financial University under the Government of the Russian Federation Moscow Russia Radio Engineering Telecommunications and Information Security Department Ulyanovsk State Technical University Ulyanovsk Russia

the paper investigates various deep learning approaches for classifying movies by genre. To prepare the initial dataset, a system for parsing textual information and images from the Internet Movie Database, IMDB (https://***/) was implemented. Pandas (Python library) methods were applied to generate the dataset. Particular attention was paid to the preparation of target information and the choice of the learning loss function due to the fact that the problem was reduced to a multi-label classification. A number of transfer learning algorithms have been implemented for convolutional neural network models and transformer architectures when processing movie posters, as well as simple machine learning models and deep learning transformer-type models for text classification. the paper proposes a method for complexing extracted features from heterogeneous data in another neural network to improve classification accuracy. It was possible to achieve an increase in the average cosine distance for the test sample by 3% higher than when using standard models and about 7% in sense of intersection over union metric.

关键词： Measurement Deep learning Computer vision Computational modeling Computer architecture Motion pictures Transformers

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Hardware Implementation of Blind Source Separation Algorithm Using ZYBO Z7& Xilinx System Generator

Hardware Implementation of Blind Source Separation Algorithm...

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international conference on Renewable Energies for Developing Countries (REDEC)

作者： Mohcin Mekhfioui Amal Satif Omar Mouhib Rachid Elgouri Abdelkader Hadjoudja Laamari Hlou Laboratory of Electrical Engineering and Energy Systems Faculty of Science Ibn Tofail University Kenitra Morocco

ISBN: (数字)9781728155951

ISBN: (纸本)9781728155968

Blind Source Separation (BSS) is termed as the extraction of source signals from mixed data without or with little knowledge about the source signals. It is used in many fields of research such as military, medical and industry. Among the many challenges that must be overcome to apply BSS to a real system, implementation restrictions are the most difficult. Software implementations require a significant amount of overhead to make them applicable to real-time systems and have a lower maximum speed of operation than hardware implementations. When speed is desired, the algorithm should be implemented on specialized hardware such as a Field Programmable Gate Array(FPGA) which allows the user to take advantage of parallel computational abilities. this paper describes the methodology for implementing real-time DSP applications on FPGA and the concept of hardware software cosimulation of the Second Order Blind Identification (SOBI) algorithm using MATLAB Simulink and Xilinx System Generator (XSG). Performances of efficient architectures are implemented on FPGA ZYBO Z7 Zynq-7020.

关键词： Field programmable gate arrays Blind source separation Generators Signal processing algorithms Hardware Real-time systems Software packages

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Hardware models for automated partitioning and mapping in multi-core systems

Hardware models for automated partitioning and mapping in mu...

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IEEE international Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications

作者： Lukas Krawczyk Erik Kamsties University of Applied Sciences Fachhochschule Dortmund Germany

Multi-core CPUs offer several major benefits in mobile and embedded systems. For instance, they provide better energy efficiency and more computing power at the same clock speed compared to single-core CPUs. these benefits do not come for free: A program has to be divided into tasks, which can be executed in parallel on different cores. Partitioning of software and mapping on cores are nontrivial activities that require detailed knowledge about the multi-core CPU, e.g., if shared memories are available, their size, and other properties. Such programmers' information about a CPU is typically stored in processor handbooks. If this information would be available in a machine readable model, we call it hardware model, the partitioning and mapping activities can be automated. In this paper, we propose a hardware model and illustrate it using an example of a Freescale multi-core CPU. We then discuss a small case study, which illustrates the use of the hardware model in partitioning, mapping, and code generation.

关键词： Hardware Embedded systems Data models System-on-chip Unified modeling language Multicore processing

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All You Should Know About Large Language Models (LLMs)

All You Should Know About Large Language Models (LLMs)

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international conference on Advanced Communication Technologies and Networking (CommNet)

作者： Abadila Alaktif Meriyem Chergui Imane Daoudi Abdelkrim Ammoumou C3S ENSEM EST Hassan II University Casablanca Morocco

ISBN: (数字)9798350367027

ISBN: (纸本)9798350367034

this article examines recent advancements in Large Language Models (LLMs), focusing on efficiency improvements and practical implementation. through analysis of literature from 2021 to present, we identify key innovations making these models more accessible. We highlight three main areas of progress: enhanced Transformer architectures enabling longer text processing with fewer resources, novel fine-tuning techniques for efficient task adaptation, and expanded applications beyond language processing into vision, speech, and reinforcement learning. the review evaluates efficiency innovations including patternbased approaches and dynamic attention mechanisms, comparing their benefits and trade-offs. Our analysis provides insights for researchers and practitioners working to make LLMs more practical and accessible, particularly addressing deployment challenges like memory and computational constraints.

关键词： Adaptation models Technological innovation Reviews Computational modeling Large language models Focusing Speech enhancement Transformers Computational efficiency Text processing

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Evolution of nanomechanical olfactory sensor as an artificial nose

Evolution of nanomechanical olfactory sensor as an artificia...

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international conference and Workshop on Computing and Communication (IEMCON)

作者： Riya Dam Sahil Sarkar Rishab Sarbadhikary Avirup Ghosh Souvik Ghosh Mechanical Engineering Department University of Engineering & Management Kolkata Electronics and Communication Engineering Department University of Engineering & Management Kolkata

ISBN: (纸本)9781509009978

In this paper we have focussed in the working principle of the cantilever array based nanomechanical systems that are used for olfaction. In vertebrates, the physiology of olfaction is composed of a large number of cells which react in parallel but differential fashion to certain odours. Studies have shown that highly sensitive cantilevers, having high length to thickness ratio and capable of optical deflection measurement permit them to become extremely sensitive to force measurement in the dimension of pico-nanometer. Medical tests based on breath analysis can be benefited by this phenomenon. Our objective is to find out the prospects of differential olfactory characteristics that are materialized in the nanomechanical systems. Time based multiplexing of the signal for analysis and formation of a pattern through artificial neural network model can bring a huge development over faster and intelligent diagnosis of a variety of disease.

关键词： Micromechanical devices Signal processing Olfactory Sensor arrays Nanobioscience

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High throughput FPGA implementation of Min-Sum LDPC Decoder Architecture for Wireless Communication Standards

High throughput FPGA implementation of Min-Sum LDPC Decoder ...

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Digital Signal processing and its Applications (DSPA), international conference on

作者： Pavel Nikishkin Ruslan Goriushkin Nikita Vinogradov Evgeny Likhobabin Vladimir Vityazev Ryazan State Radio Engineering University RSREU Ryazan Russia

this paper presents a min-sum decoder design for Quasi-Cyclic (QC) Low-Density Parity-Check (LDPC) codes. the design is supported various LDPC Parity-Check matrices including the WiMAX (IEEE 802.16e) and the WiFi (IEEE 802.11n) standards matrices. New techniques such as pipelining of the decoding architecture core are proposed. these core calculate variable-to-check (VTC) and new check-to-variable (CTV) messages and also update estimate of posterior probabilities (APPs). the parallel multicore decoding architecture implies a prior shift of values based on the LDPC matrix and simultaneous calculation of values for the core. Proposed decoder is implemented on the Zynq-7000 Mini-ITX Evaluation Board (XC7Z100-2FFG900).

关键词： Multicore processing Signal processing algorithms WiMAX Probability throughput Parity check codes Decoding

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Implementing a Pickup and Delivery Problem with Time Windows algorithm on a GPU cluster

Implementing a Pickup and Delivery Problem with Time Windows...

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international conference on Computer Sciences and Convergence Information Technology (ICCIT)

作者： Geeratiya Srimool Putchong Uthayopas Juta Pichitlamkhen Department of Computer Engineering Faculty of Engineering Kasetsart University Bangkok Thailand Department of Industrial Engineering Faculty of Engineering Kasetsart University Bangkok Thailand

this work presents an implementation of a high speed Pickup and Delivery Problem with Time Window (PDPTW) problem using GPU cluster. this problem represents a class of a major logistic problem. the software implemented is tested on 8 nodes GPU cluster equipped with two of Tesla M2050 (448 cores) card on each node. the result shows a speedup of nearly 7 times for a small problem and 43 times using 4 nodes for a large problem. In the presentation, some factors that affect the performance will be discussed.

关键词： Graphics processing unit Instruction sets Vehicles parallel processing Clustering algorithms Handheld computers

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Evolving Big Data Stream Classification with MapReduce

Evolving Big Data Stream Classification with MapReduce

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IEEE international conference on Cloud Computing, CLOUD

作者： Ahsanul Haque Brandon Parker Latifur Khan Bhavani thuraisingham Department of computer Science The University of Texas at Dallas Richardson USA

Big Data Stream mining has some inherent challenges which are not present in traditional data mining. Not only Big Data Stream receives large volume of data continuously, but also it may have different types of features. Moreover, the concepts and features tend to evolve throughout the stream. Traditional data mining techniques are not sufficient to address these challenges. In our current work, we have designed a multi-tiered ensemble based method HSMiner to address aforementioned challenges to label instances in an evolving Big Data Stream. However, this method requires building large number of AdaBoost ensembles for each of the numeric features after receiving each new data chunk which is very costly. thus, HSMiner may face scalability issue in case of classifying Big Data Stream. To address this problem, we propose three approaches to build these large number of AdaBoost ensembles using MapReduce based parallelism. We compare each of these approaches from different aspects of design. We also empirically show that, these approaches are very useful for our base method to achieve significant scalability and speedup.

关键词： Big data Indexes Data mining Scalability Sorting Distributed databases parallel processing

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A study of strategies to restrain the C&C activities of structured P2P botnets

A study of strategies to restrain the C&C activities of stru...

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international conference on Computer Sciences and Convergence Information Technology (ICCIT)

作者： Tianzuo Wang Bo Liu Huaimin Wang Hao Ren Xiaolong Ma School of Computer Science National Laboratory for Parallel and Distributed Processing National University of Defense and Technology Changsha China

Botnets are threatening the Internet heavily, and more and more botnets are utilizing the P2P technology to build their C&C (Command and Control) mechanisms. Some research have been made to compare the resilience of structured P2P botnets and unstructured ones, against elimination of nodes, but the problem that which eliminating strategy is the best is rarely studied. In this paper, we proposed a new metric called the half point, to measure the effectiveness of different strategies. We also selected seven different eliminating strategies and compared them. through extensive simulations, we find that RBC is the best eliminating strategy. Further analysis shows that for the strategy RBC, the average degree of nodes in the botnet have the most significant influence. the bigger the average degree is, the bigger the half point of RBC is, which implies that node eliminating may not be a reasonable choice for mitigating botnets with big average degree. Results of this paper can provide guidance for restraining structured P2P botnets.

关键词： C&C mechanism betweenness centrality coreness eliminating strategy half point restrain structured P2P botnets

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A C++ Library for Memory Layout and Performance Portability of Scientific Applications 28th

A C++ Library for Memory Layout and Performance Portabilit...

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28th international European conference on parallel and Distributed Computing , Euro-Par 2022

作者： Incardona, Pietro Gupta, Aryaman Yaskovets, Serhii Sbalzarini, Ivo F. Technische Universität Dresden Faculty of Computer Science Dresden Germany Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany Center for Systems Biology Dresden Dresden01307 Germany Center for Scalable Data Analytics and Artificial Intelligence ScaDS.AI Dresden/Leipzig Germany

ISBN: (纸本)9783031312083

We present a C++14 library for performance portability of scientific computing codes across CPU and GPU architectures. Our library combines generic data structures like vectors, multi-dimensional arrays, maps, graphs, and sparse grids with basic, reusable algorithms like convolutions, sorting, prefix sum, reductions, and scan. the memory layout of the data structures is adapted at compile-time using tuples with optional memory mirroring between CPU and GPU. We combine this transparent memory mapping with generic algorithms under two alternative programming interfaces: a CUDA-like kernel interface for multi-core CPUs, Nvidia GPUs, and AMD GPUs, as well as a lambda interface. We validate and benchmark the presented library using micro-benchmarks, showing that the abstractions introduce negligible performance overhead, and we compare performance against the current state of the art. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graphics processing unit

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