检索结果-内蒙古大学图书馆

A Parallel High-Utility Itemset Mining Algorithm Based on Hadoop

Complex System Modeling and Simulation 2023年第1期3卷 47-58页

作者： Zaihe Cheng Wei Shen Wei Fang Jerry Chun-Wei Lin School of Internet of Things Wuxi Institute of TechnologyWuxi 214121China School of Artificial Intelligence and Computer Science Jiangnan UniversityWuxi 214122China Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence Jiangnan UniversityWuxi 214122China Department of Computer Science Electrical Engineering and Mathematical SciencesWestern Norway University of Applied SciencesBergen 5020Norway

High-utility itemset mining(HUIM)can consider not only the profit factor but also the profitable factor,which is an essential task in data ***,most HUIM algorithms are mainly developed on a single machine,which is inefficient for big data since limited memory and processing capacities are available.A parallel efficient high-utility itemset mining(P-EFIM)algorithm is proposed based on the Hadoop platform to solve this problem in this *** P-EFIM,the transaction-weighted utilization values are calculated and ordered for the itemsets with the MapReduce *** the ordered itemsets are renumbered,and the low-utility itemsets are pruned to improve the dataset *** the Map phase,the P-EFIM algorithm divides the task into multiple independent *** uses the proposed S-style distribution strategy to distribute the subtasks evenly across all nodes to ensure ***,the P-EFIM uses the EFIM algorithm to mine each subtask dataset to enhance the performance in the Reduce *** are performed on eight datasets,and the results show that the runtime performance of P-EFIM is significantly higher than that of the PHUI-Growth,which is also HUIM algorithm based on the Hadoop framework.

关键词： pattern mining data mining Hadoop parallel high-utility itemset mining big data

来源：评论

学校读者我要写书评

暂无评论

Sign Language to Sentence Formation:A Real Time Solution for Deaf People

引用

computers, Materials & Continua 2022年第8期72卷 2501-2519页

作者： Muhammad Sanaullah Muhammad Kashif Babar Ahmad Tauqeer Safdar Mehdi Hassan Mohd Hilmi Hasan Amir Haider Bahauddin Zakariya University Department of Computer ScienceMultan60000Pakistan Air University Department of Computer ScienceMultan60000Pakistan Air University Department of Computer ScienceIslamabad44000Pakistan Centre for Research in Data Science Department of Computer and Information SciencesUniversiti Teknologi PETRONASSeri Iskandar32610PerakMalaysia Department of Intelligent Mechatronics Engineering Sejong UniversitySeoul05006Korea

Communication is a basic need of every human being to exchange thoughts and interact with the *** peoples usually confab through different spoken languages,whereas deaf people cannot do ***,the Sign Language(SL)is the communication medium of such people for their conversation and interaction with the *** SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed *** acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words *** signs for singular words such as I,eat,drink,home are unalike the plural words as school,cars,players.A special training is required to gain the sufficient knowledge and practice so that people can differentiate and understand every gesture/sign *** researches have been performed to articulate the computer-based solution to understand the single gesture with the help of a single hand *** complete understanding of such communications are possible only with the help of this differentiation of gestures in computer-based solution of SL to cope with the real world ***,there is still a demand for specific environment to automate such a communication solution to interact with such type of special *** research focuses on facilitating the deaf community by capturing the gestures in video format and then mapping and differentiating as single or multiple gestures used in ***,these are converted into the respective words/sentences within a reasonable *** provide a real time solution for the deaf people to communicate and interact with the society.

关键词： Sign language machine learning conventional neural network image processing deaf community

来源：评论

学校读者我要写书评

暂无评论

Breakthrough in breast tumor detection and diagnosis: a noise-resilient, rotation-invariant framework

引用

Multimedia Tools and Applications 2025年 1-27页

作者： Nosheen, Fariha Khan, Salabat Sharif, Muhammad Kim, Do Hyeun Alkanhel, Reem AbdelSamee, Nagwan Department of Computer Science COMSATS University Islamabad Attock Campus Attock43600 Pakistan Department of Computer Engineering Jeju National University Jeju Special Self-Governing Province Jeju-Si63243 Korea Republic of Big Data Research Center Jeju National University Jeju63243 Korea Republic of Department of Information Technology College of Computer and Information Sciences Princess Nourahbint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

The fact that early-stage breast cancer typically presents no signs, poses a global risk to the lives of women. Digital mammography is just one method among many that can detect breast cancer in its early stages. Despite extensive research, most methods for detecting breast cancers still produce a large number of false positives. The difficulty in improving detection accuracy is in reducing false positives by differentiating masses from normal tissues. Using the textural properties of the masses, this study aims to develop a computer-aided diagnosis system that reduces the number of false positive and negative mammography results. The suggested method initially partitions regions of interest (ROI) into small patches to extract an abnormality region and micro-pattern, which permits the extraction of specific information about the image's content in targeted areas. Reducing the computational complexity of an image analysis operation is accomplished by partitioning a ROI into smaller patches rather than processing the complete image at once. Due to the significant impact the noise has on detection accuracy in mammograms, a textural descriptor that is insensitive to noise is introduced to describe image features such as lines, spots, flat areas, and edges. By expanding the rotation-invariant and noise-tolerant descriptor histograms, we generate an improved histogram that preserves the original regional patterns and spatial relationships between masses. To distinguish between "normal" and "mass" and "benign" and "malignant", Support Vector Machines (SVM) is employed with grid search based hyperparameter optimization. Our proposed approach was evaluated using the Digital database for Screening Mammography (DDSM), which contains over 1024 ROI cases. This database is a well-established benchmark for testing new mammography analysis methods. Each case in the DDSM database has been analyzed and interpreted by qualified radiologists, with comprehensive information provided thr

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Pelvic bone region segmentation (PBRS) from X-ray image using convolutional neural network (CNN) 26

Pelvic bone region segmentation (PBRS) from X-ray image usin...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Ul Alam, Syed Alif Binte Alam, Saadia Saha, Sourav Haque, Mahmudul Rahman, Rashedur Kobashi, Syoji Independent University Bangladesh Department of Computer Science and Engineering Dhaka1229 Bangladesh Independent University Bangladesh Center for Computational & Data Sciences Dhaka1229 Bangladesh University of Hyogo Graduate School of Engineering Shosha Hyogo Himeji2167 Japan

ISBN: (纸本)9798350359015

Pelvic and hip fractures offer considerable public health risks with high morbidity and mortality rates. Because of the complicated bone structure of the pelvic bone region, detecting fractures is difficult. Though X-ray imaging is routinely utilised for detecting fractures, manual fracture diagnosis is prone to inaccuracies. This paper proposes the use of deep learning algorithms for automated segmentation of the pelvic bone region in X-ray images. In our work, we have investigated U-Net based pelvic area segmentation models with various convolutional neural network (CNN) backbones. The DenseNet121-based U-Net design emerged as the most optimal model, establishing a compromise between performance and computational efficiency. Although it had a modest loss in IoU and F1 scores when compared to InceptionNetV3, it had a remarkable 59.44% reduction in the number of parameters. © 2023 IEEE.

关键词： deep learning pelvic bone segmentation x-ray

来源：评论

学校读者我要写书评

暂无评论

Towards Federated Learning on Fresh datasets 20

Towards Federated Learning on Fresh Datasets

引用

20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023

作者： Wu, Chen Xiao, Mingjun Wu, Jie Xu, Yin Zhou, Jinrui Sun, He University of Science and Technology of China School of Data Science China University of Science and Technology of China School of Computer Science and Technology & Suzhou Institute for Advanced Research China Temple University Department of Computer and Information Sciences United States

ISBN: (纸本)9798350324334

Federated Learning (FL) is an emerging privacy-preserving distributed computing paradigm that enables numerous clients to collaboratively train machine learning models without the need for transmitting the private datasets of clients to the FL server. Unlike most existing research where the local datasets of clients are considered to be unchanging over time during the whole FL process, we consider such scenarios in this paper where the local datasets of clients need to be updated periodically, and the server can stimulate clients to use as fresh as possible datasets to train their local models. Our objective is to determine a client selection strategy to minimize the loss of global model for FL with a limited budget. To this end, we leverage the concept of Age of Information (AoI) to quantify the freshness of local datasets and theoretically analyze the convergence bound of our AoI-aware FL system. Based on the convergence bound, we formalize our problem as a restless multi-armed bandit problem. Then, we devise a Whittle's-Index-based Client Selection algorithm, called WICS, to tackle the client selection problem. Extensive simulations show that the proposed algorithm can reduce the training loss and improve learning accuracy compared to state-of-the-art algorithms. © 2023 IEEE.

关键词： Budget control

来源：评论

学校读者我要写书评

暂无评论

The Application of Affective Measures in Text-Based Emotion Aware Recommender Systems

The Application of Affective Measures in Text-Based Emotion ...

引用

12th International Conference on data science, Technology and Applications, data 2023

作者： Leung, John Kalung Griva, Igor Kennedy, William G. Kinser, Jason M. Park, Sohyun Young Lee, Seo Computational Sciences and Informatics Computational and Data Sciences Department George Mason University Korea 119-4 Songdomunhwa-ro Yeonsu-gu Incheon21985 Korea Republic of Department of Mathematical Sciences George Mason University 4400 University Drive FairfaxVA22030 United States Center for Social Complexity Computational and Data Sciences Department College of Science George Mason University 4400 University Drive FairfaxVA22030 United States Computational Sciences and Informatics Computational and Data Sciences Department College of Science George Mason University 4400 University Drive FairfaxVA22030 United States Department of Communications George Mason University Korea 119-4 Songdomunhwa-ro Yeonsu-gu Incheon21985 Korea Republic of

ISBN: (纸本)9789897586644

This paper presents an innovative approach to address the problems researchers face in Emotion Aware Recommender Systems (EARS): the difficulty and cumbersome collecting voluminously good quality emotion-tagged datasets and an effective way to protect users’ emotional data privacy. Without enough goodquality emotion-tagged datasets, researchers cannot conduct repeatable affective computing research in EARS that generates personalized recommendations based on users’ emotional preferences. Similarly, if we fail to protect users’ emotional data privacy fully, users could resist engaging with EARS services. This paper introduced a method that detects affective features in subjective passages using the Generative Pre-trained Transformer Technology, forming the basis of the affective index and Affective Index Indicator (AII). Eliminate the need for users to build an affective feature detection mechanism. The paper advocates for a Separation of Responsibility approach where users protect their emotional profile data while EARS service providers refrain from retaining or storing it. Service providers can update users’ affective indices in memory without saving their privacy data, providing affective-aware recommendations without compromising user privacy. This paper offers a solution to the subjectivity and variability of emotions, data privacy concerns, and evaluation metrics and benchmarks, paving the way for future EARS research. © 2023 by SCITEPRESS–science and Technology Publications, Lda.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Hybrid Genetic Algorithm and Ant Colony Algorithm for Solving Travelling Salesman Problem 9

Hybrid Genetic Algorithm and Ant Colony Algorithm for Solvin...

引用

9th IEEE International Conference on computational Intelligence and Applications, ICCIA 2024

作者： Thongpiem, Jirawat Punkong, Narong Ratanavilisagul, Chiabwoot Kosolsombat, Somkiat Faculty of Applied Science Department of Computer and Information Sciences Bangkok Thailand Digital Technology for Business Faculty of Management Science Kanchanaburi Thailand Data Science and Innovation College of Interdisciplinary Studies Thammasat University Pathum Thani Thailand

ISBN: (纸本)9798350352214

The traveling salesman problem (TSP) is a combinatorial optimization problem and a NP-complete problem. It is a well-known problem for comparison of algorithm performance. Many researchers try to solve the TSP by the meta-heuristic algorithms. Ant Colony Optimization (ACO) algorithm is a popular method to solve the TSP. To enhance performance of ACO for solving TSP, the recently proposed improving the ACO algorithm by the results from searching for 2-OPT algorithms that are applied with pheromones of ants. Moreover, when the population of ACO occurs trapping in local optimum, the pheromone of ants is re-initialized to solve trapping in local optimum problem. This algorithm is called Modified Ant Colony Optimization with updating Pheromone by Leader and Re-initialization Pheromone (MACO-LR). However, performance searching of MACO-LR can be improved. In this research, we propose to solve TSP using Hybrid Genetic Algorithm and Ant Colony Algorithm (HGAACO) to optimize the total travelled distance. The proposed technique is tested on twenty-three maps from the Traveling Salesman Problem Library (TSPLIB) and it is composed with MACO-LR. The results from the experiment show the proposed technique can enhance performance searching of MACO-LR. © 2024 IEEE.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

Quantum routing with teleportation

引用

Physical Review Research 2024年第3期6卷 033313页

作者： Dhruv Devulapalli Eddie Schoute Aniruddha Bapat Andrew M. Childs Alexey V. Gorshkov NIST/ Computer Computational and Statistical Sciences Division Institute for Advanced Computer Studies Department of Computer Science Berkeley California 94720 USA

We study the problem of implementing arbitrary permutations of qubits under interaction constraints in quantum systems that allow for arbitrarily fast local operations and classical communication (LOCC). In particular, we show examples of speedups over swap-based and more general unitary routing methods by distributing entanglement and using LOCC to perform quantum teleportation. We further describe an example of an interaction graph for which teleportation gives a logarithmic speedup in the worst-case routing time over swap-based routing. We also study limits on the speedup afforded by quantum teleportation—showing an O(NlogN) upper bound on the separation in routing time for any interaction graph—and give tighter bounds for some common classes of graphs.

关键词： Entanglement manipulation Measurement-based quantum computing Quantum algorithms Quantum circuits Quantum computing models Quantum networks Quantum repeaters Quantum teleportation

来源：评论

学校读者我要写书评

暂无评论

Multiplicative resonant enhancement of chemical detection

引用

Physical Review Applied 2024年第5期22卷 054006页

作者： Wenchao Ma Raphaël Pestourie Zin Lin Alan Aguirre-Soto Hadley D. Sikes Steven G. Johnson Department of Chemistry School of Computational Science and Engineering Bradley Department of Electrical and Computer Engineering School of Engineering and Sciences Department of Chemical Engineering Department of Mathematics

Optical resonances can increase the sensitivity of measurements to material perturbations and also accelerate photochemical reactions. Here, we show that these two effects can be combined multiplicatively, to enhance the detection via weak or low-concentration photochemical reactions far beyond what could previously be attained. For an optical resonance with quality factor Q, the sensitivity of our detection scheme is enhanced by ∼Q2 (where ∼ denotes approximate proportionality), as demonstrated by both theoretical arguments and numerical simulations of a simple optical-grating resonance coupled with reaction-diffusion equations. Such an approach opens a door to further improvements by careful design of the resonance: even a three-parameter optimization of the grating resonance yields an additional ≈7 times improvement.

关键词： Analytical chemistry Fano resonance Metrology Nanophotonics Optimization problems Photochemistry Devices Reaction diffusion systems

来源：评论

学校读者我要写书评

暂无评论

Pretrained Sentence Embedding and Semantic Sentence Similarity Language Model for Text Classification in NLP 3

Pretrained Sentence Embedding and Semantic Sentence Similari...

引用

3rd International Conference on Artificial Intelligence and Signal Processing, AISP 2023

作者： Valli Mayil, V. Ratha Jeyalakshmi, T. Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India Jain University School of Sciences Department of Data Science & Analytics Karnataka Banglore India

ISBN: (纸本)9798350320749

A key task in the field of Natural Language Processing (NLP) is determining semantic similarity between text sentences. Sentence pair modeling, Textual similarity and language modeling are few important tasks in NLP. Traditional machine learning algorithms require an enormous quantity of training data, but it is a timeconsuming process. Pre-trained models can be modified for a variety of downstream applications since they use methods for generically learning the characteristics of neural network topologies and language representations. Bidirectional Encoder Representations from Transformers- BERT & GPT are the popular architectures in NLP which enable to use minimal fine-tuning effort to produce effective results. In this work a fine-tuned BERT model that is suitable for semantic sentence similarity which predicts the entailment, neutral and contradictory categories of sentence pairs is presented. The fine-tuning feature promotes the training phase of model whichis widely effective across different types of semantic similarity models. The performance analysis of our system shows that the fine-tuned model reduces the number of neurons in the neural network there by reducing storage and time spent in expensive training task to create deep learning model. © 2023 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：