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检索条件"主题词=Software Algorithms"

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Tourism Enhancement Through Hybrid Mobile Application with Web Scraping and Recommendation System Using KNN and MF

Tourism Enhancement Through Hybrid Mobile Application with W...

引用

International Conference on Engineering and Emerging Technologies (ICEET)

作者： Thirupathi Regula Anshar Ali Dhanasekar N Department of IT College of Computing and Information Sciences University of Technology and Applied Science Muscat Oman

ISBN: (数字)9798331532895

ISBN: (纸本)9798331532901

Mobile applications have become an essential part of daily life. The tourists develop their tourist attractions and other facilities, which were being struggled after making plans within constraints. However, it is still incomplete and calls for some fine-tuning mechanisms with a view to creating the ideal tourist itinerary. This research has proposed a hybrid mobile app that integrates web scraping with machine learning technology to enhance the trip experience of visitors. The software does web scraping to scrape data in real time from several sites for bookings of hotels, flights, cabs, and food services with one interface. In solving the challenge of personalized tour planning, this app makes use of powerful machine learning techniques: K-Nearest Neighbors and matrix factorization-based recommendation algorithms. These algorithms consider user preferences for budget, length of travel, ratings, and other constraints while making personalized recommendations for tourism sites and activities. software is constantly reacting to user feedback and behavior to enhance the relevance of recommendations over time. Unique in its method, it enables trip planning not only by unifying services but also makes sure travelers make informed and cost-effective decisions. It represents a huge step forward in intelligent, user-centric travel solutions by embedding the powers of web scraping for extensive data gathering and machine learning for personalization.

关键词： Machine learning algorithms software algorithms Machine learning Nearest neighbor methods software Real-time systems Mobile handsets Mobile applications Planning Recommender systems

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Construction of Perceptual Security Dataset for Video Selective Encryption Based on Double-Blind Subjective Experiment

Construction of Perceptual Security Dataset for Video Select...

引用

Information Communication and software Engineering (ICICSE), IEEE International Conference on

作者： Ying Zhao Cheng Yang Bo Tang State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China

ISBN: (纸本)9781665430302

The development of information technology has provided opportunities for the application of Ultra High Definition (UHD) video, but the security problems such as privacy leakage cannot be ignored. Video selective encryption algorithm is an efficient and effective way to protect the privacy of users. However, the previous studies on the performance evaluation of video selective encryption scheme are insufficient. PSNR and SSIM, which are commonly used to evaluate the image quality, cannot fully reflect the encryption effect of selective encryption algorithm, which makes it difficult to evaluate and compare the security protection ability of selective encryption scheme for video content. To build an accurate security evaluation scheme of video selective encryption algorithm needs to rely on a large number of encrypted video data, but the existing datasets have the problems of small number of videos, single video resolution and selective encryption method, and the subjective experiment scheme is lack of scientific. In order to solve this problem, this paper selects a variety of resolutions and common scene video sequences, and uses different selective encryption schemes to encrypt them, so as to build a dataset for selective encryption. The method of double-blind subjective experiment provides a real and accurate subjective score for the perception security and visual quality of the video in the dataset. The subjective score shows that the dataset covers the encryption sequence of each security level, which can provide an effective reference for the follow-up research on video selective encryption and perceptual security index.

关键词： Performance evaluation Image quality Privacy Visualization Video sequences software algorithms Encryption

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Signal processing for preserving the environment

Signal processing for preserving the environment

引用

International Conference on Pattern Recognition

作者： C.H. Chen Electrical and Computer Engineering Dept University of Massachusetts Dartmouth MA USA

Summary form only given. Signal processing has now had many benefits to our daily life though we may not be aware of. For examples: microprocessors (a kind of signal processor) are used to control gas consumption to make our cars more fuel efficient and signal processing is used to predict the major weather changes. Signal processing has played important roles in our environment including land water and air, through monitoring, control and prediction functions. In this presentation, the recent progress of signal processing, including hardware, software and algorithms, the neural networks, and the roles of remote sensing, will be reviewed first. This is followed by presenting several examples of using signal processing to preserve our environment. Some notable examples are: monitoring of landmines, pollutants in waterways, the salinity in the coastal zones, and the changes in environment; control of oil spills, flood mapping and control; inspection of damages of forest fires; prediction of major storms; etc. It is noted that signal processing is closely linked to pattern recognition in many of these examples. Signal processing in conjunction with pattern recognition will play an increasingly important role in all of these activities that aim to preserve our precious environmental resources.

关键词： Signal processing Signal processing algorithms Remote monitoring Pattern recognition Microprocessors Fuels Weather forecasting Neural network hardware software algorithms Neural networks

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Development of Filled Circle Drawing in High-Level Synthesis Oriented Game Programming Library

Development of Filled Circle Drawing in High-Level Synthesis...

引用

IEEE International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Yuki Yamagata Akira Yamawaki Department of Electrical Engineering and Electronics Kyushu Institute of Technology Kitakyushu Japan

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

We are developing a high-level synthesizable software game library to realize high performance and low power mobile terminals executing game applications. High-level synthesis, HLS, is a technology that automatically converts software into hardware. Games developed by HLS oriented game software library are executed by high-speed and low-power hardware reconfigured on reconfigurable devices in mobile terminals. This paper develops a circle drawing processing as one of functions in HLS oriented game software library. We employ Michener's algorithm which is suitable for hardware implementation as a circle drawing algorithm because it just consists of simple integer operations. We also show the program description method so that HLS tool can convert the circle drawing processing based on Michener's algorithm to a good hardware module. The experiments evaluate the execution time and the amount of hardware of the hardware module HLS generated.

关键词： Hardware software Games software algorithms Tools Field programmable gate arrays Programming

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Graphicionado: A high-performance and energy-efficient accelerator for graph analytics 49

Graphicionado: A high-performance and energy-efficient accel...

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IEEE/ACM International Symposium on Microarchitecture (MICRO)

作者： Tae Jun Ham Lisa Wu Narayanan Sundaram Nadathur Satish Margaret Martonosi Princeton University University of California Berkeley Parallel Computing Lab Intel Corporation

ISBN: (纸本)9781509035090

Graphs are one of the key data structures for many real-world computing applications and the importance of graph analytics is ever-growing. While existing software graph processing frameworks improve programmability of graph analytics, underlying general purpose processors still limit the performance and energy efficiency of graph analytics. We architect a domain-specific accelerator, Graphicionado, for high-performance, energy-efficient processing of graph analytics workloads. For efficient graph analytics processing, Graphicionado exploits not only data structure-centric datapath specialization, but also memory subsystem specialization, all the while taking advantage of the parallelism inherent in this domain. Graphicionado augments the vertex programming paradigm, allowing different graph analytics applications to be mapped to the same accelerator framework, while maintaining flexibility through a small set of reconfigurable blocks. This paper describes Graphicionado pipeline design choices in detail and gives insights on how Graphicionado combats application execution inefficiencies on general-purpose CPUs. Our results show that Graphicionado achieves a 1.76-6.54x speedup while consuming 50-100x less energy compared to a state-of-the-art software graph analytics processing framework executing 32 threads on a 16-core Haswell Xeon processor.

关键词： software Programming software algorithms Machine learning algorithms System-on-chip Pipelines Memory management

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Multi-resolution Texture Segmentation Using Fractal Dimension

Multi-resolution Texture Segmentation Using Fractal Dimensio...

引用

International Conference on Computer Science and software Engineering

作者： Taoi Hsu Kuo-Jui Hu Chung Cheng Institute of Tech. School of Defense Science Shih Hsin University China National Defense University China

ISBN: (纸本)9781424439027

An efficient algorithm for segmenting a textured image into different regions is developed based on a set of fractal dimension estimated from calculated variogram. An edge detector is employed to detect texture boundary based on the multi-resolution framework including gradient pyramid construction followed by the reliable information obtained in the rough resolution as mask to constrain the calculation region in the rest resolution. Combined with mask and gradient in each resolution is propagating down to the finest resolution giving a more accurate boundaries estimation. The utility of the proposed method is demonstrated on a number of synthesis and natural textures.

关键词： Fractals Image segmentation Image edge detection Feature extraction Surface texture Motion estimation Computer science software engineering software algorithms Detectors

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FPGA implementation of MFNN for image registration

FPGA implementation of MFNN for image registration

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IEEE International Conference on Field-Programmable Technology (FPT)

作者： D.C. Gharpure M.S. Puranik Department of Instrumentation Science University of Pune Pune India

The multilayer feedforward neural network (MFNN) is modified to simplify hardware realization and at the same time retain the accuracy of detection. The results obtained have been found to be comparable to the software simulation algorithm which is used as a test base. The MFNN implementation involves low hardware complexity, good noise immunity and fast circuitry.

关键词： Field programmable gate arrays Image registration Multi-layer neural network Neural networks Feedforward neural networks Neural network hardware Circuit simulation software algorithms Circuit testing software testing

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A self-learning multiple-class classifier using multi-dimensional quasi-Gaussian analog circuits

A self-learning multiple-class classifier using multi-dimens...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Zhuoli Sun Kyunghee Kang Tadashi Shibata Department of Electrical Engineering and Information Systems University of Tokyo Tokyo Japan

A hardware-implementation-friendly classifier architecture having self-learning function has been developed for multiple-class classification. The similarity between two vectors is evaluated using a quasi Gaussian function which has been implemented by the summation of output currents from simple bump circuits. Binary weights are assigned to sample vectors and their values are determined by iteration similar to the SVM learning but in much simpler a way. Only one classifier is sufficient for N-class classification in contrast to N(N-1)/2 classifiers necessary in the SVM. The performances of the algorithm and circuits have been verified by software and SPICE simulations.

关键词： Analog circuits Support vector machines Support vector machine classification Circuit simulation Application software Hardware software algorithms Pattern recognition Speech recognition Statistical learning

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Concurrent program execution

Concurrent program execution

引用

Southeastern Symposium on System Theory

作者： V. Swaminathan J. Bowles Electrical and Computer Engineering University of South Carolina Columbia SC USA

The authors present the issues in concurrent program execution, and survey some of the current research in this area. Programs for multiprocessor systems require a completely different approach from those for uniprocessor systems. The effective use of multiprocessor systems requires a program representation which clearly indicates sections (tasks) that can be executed concurrently, mechanisms for synchronizing these different concurrent modules, methods for ensuring data integrity, and algorithms that schedule and allocate these modules to the available processors efficiently. Most current work in these areas make very limiting assumptions about the nature of the program, or the nature of the underlying hardware architecture, so that they are not truly flexible.< >

关键词： Parallel processing Hardware Concurrent computing Program processors Reliability Availability Computational modeling Multiprocessing systems System software software algorithms

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Towards a Heuristic Algorithm for Partitioning Network Community

Towards a Heuristic Algorithm for Partitioning Network Commu...

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International Symposium on Intelligent Information Technology Application, IITA

作者： Chengying Mao School of Software Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9781424452125

Community detection is one of the key problems in the field of complex network analysis. In the paper, we mainly focus on the two-part division problem for network, i.e. community (or graph) partitioning. Based on the in-depth analysis on the partitioning results, a two-stage heuristic algorithm named SPC is proposed. It firstly identifies two pseudo-centers, and then generates two semi-communities by removing some undecided nodes. In the next step, it adopts an experience rule to classify such nodes. The experiment results show that the SPC algorithm is effective and can yield the best partitioning results for most instances.

关键词： Heuristic algorithms Partitioning algorithms Complex networks Algorithm design and analysis Intelligent networks Information technology Application software software algorithms Finance Information analysis

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