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检索条件"主题词=software algorithms"

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A Mobile App-Based Indoor Mobility Detection Approach Using Bluetooth Signal Strength

A Mobile App-Based Indoor Mobility Detection Approach Using ...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Muztaba Fuad Anthony Smith Debzani Deb Department of Computer Science Winston-Salem State University Winston-Salem NC USA

ISBN: (数字)9798350370997

ISBN: (纸本)9798350371000

In an indoor space, determining a person's mobility patterns has research significance and applicability in real-world scenarios. When mobility patterns are determined, layout optimization can be implemented in indoor spaces to improve efficiency. This research aimed to determine a person's path using Received Signal Strength Indicator (RSSI) data collected from Bluetooth-enabled mobile devices. Mobile app-based mobility detection using Bluetooth RSSI has the advantage of low cost and easy implementation. The research methodology involves developing a Bluetooth RSSI mobility application system to determine the path of a moving mobile device using a vectorized algorithm. The paper presents challenges in creating such a software system, its architecture, the data collection and analysis process, and the results of mobility detection. This research shows that Bluetooth-enabled mobile devices and Bluetooth RSSI data can be used to determine the path in an indoor space with workable accuracy.

关键词： Bluetooth Costs software algorithms Layout Computer architecture Data collection software systems

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Extending GPU Ray-Tracing Units for Hierarchical Search Acceleration

Extending GPU Ray-Tracing Units for Hierarchical Search Acce...

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IEEE/ACM International Symposium on Microarchitecture (MICRO)

作者： Aaron Barnes Fangjia Shen Timothy G. Rogers Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

ISBN: (数字)9798350350579

ISBN: (纸本)9798350350586

Specialized ray-tracing acceleration units have become a common feature in GPU hardware, enabling real-time ray-tracing of complex scenes for the first time. The ray-tracing unit accelerates the traversal of a hierarchical tree data structure called a bounding volume hierarchy to determine whether rays have intersected triangle primitives. Hierarchical search algorithms are a fundamental software pattern common in many important domains, such as recommendation systems and point cloud registration, but are difficult for GPUs to accelerate because they are characterized by extensive branching and recursion. The ray-tracing unit overcomes these limitations with specialized hardware to traverse hierarchical data structures efficiently, but is mired by a highly specialized graphics API, which is not readily adaptable to general-purpose computation. We present the Hierarchical Search Unit (HSU), a flexible datapath to accelerate a more general class of hierarchical search algorithms, of which ray-tracing is one. We synthesize a baseline ray-intersection datapath and maximize functional unit reuse while extending the ray-tracing unit to support additional computations and a more general set of instructions. We demonstrate that the unit can improve the performance of three hierarchical search data structures in approximate nearest neighbors search algorithms and a B-tree key-value store index. For a minimal extension to the existing unit, our HSU improves the state-of-the-art GPU approximate nearest neighbor implementation by an average of 24.8% using the GPU's general computing interface.

关键词： Tree data structures software algorithms Graphics processing units Ray tracing Approximation algorithms Search problems Hardware software Standards Recommender systems

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Is Artificial Intelligence Transforming the CRM (Customer Relationship) Experience? An Empirical Study in Indian Retail Industry

Is Artificial Intelligence Transforming the CRM (Customer Re...

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Intelligent & Innovative Practices in Engineering & Management (IIPEM), International Conference on

作者： Anuradha Gupta Amit Kumar Bhanja Nasa Dhanraj Jyoti Kumar Chandel Monalisha Patel PGDAV College University of Delhi Delhi Department of Management School of Management Sciences Varanasi School of Commerce Presidency University Bengaluru India Department of Management Birla Institute of Technology Mesra Jaipur Campus Jaipur Rajasthan Mittal School of Business Lovely Professional University Punjab

ISBN: (数字)9798350390049

ISBN: (纸本)9798350390056

The environment of Customer Relationship Management (CRM) is rapidly evolving with substantial developments. Leading businesses are progressively applying automation and artificial intelligence technologies to understand buying behavior of customers, improve brand communication, and enhance relationships. Modern CRM systems generates extensive data sets on customer interactions and behaviors, which AI algorithms analyze to reveal hidden insights on individual preferences, future behaviors, and personalized cross-sell recommendations. AI-driven automation simplifies CRM processes, enabling businesses to personalize interactions, promptly respond to inquiries, and build loyalty. By consistently attracting and meeting customer needs, businesses increase customer value and foster stronger relationships. This paper delves into AI's pivotal role in enhancing CRM, specifically within the retail sector. The blend of machine learning and artificial intelligence has transformed CRM software. These technologies empower businesses to delve deeper into their customers' behaviors and preferences, automate repetitive tasks, and offer highly personalized experiences. For instance, ML algorithms can sift through extensive customer data, uncover patterns, and forecast future behaviors, allowing companies to customize their offerings and marketing approaches accordingly. AI-driven chatbots can deliver immediate customer support, addressing queries and resolving issues promptly, even beyond regular business hours. This piece examines the crucial impact of ML and AI in elevating CRM software capabilities. Sample of 213 people from Indian retail industry were considered for survey to know the "impact of Artificial Intelligence Transforming the CRM (Customer Relationship) Experience in Indian Retail Industry". It can be concluded that there is significant influence of Artificial Intelligence Transforming the CRM (Customer Relationship) Experience in Indian Retail Industry.

关键词： Industries Surveys Automation software algorithms Customer relationship management Machine learning Companies software Artificial intelligence Business

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Research on the Application of Machine Learning in Orderly Charging Demand Prediction and Scheduling Optimization of Charging Piles

Research on the Application of Machine Learning in Orderly C...

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software Engineering, Social Network Analysis and Intelligent Computing (SSAIC), Asia-Pacific Conference on

作者： Shan He Yuming Zhao Dehuang Bi Xun Li Jing Ge Zhili Zeng Shenzhen Power Supply Bureau Co. Ltd Shenzhen Guangdong China China Southern Power Grid Electric Vehicle Service Co. Ltd Shenzhen Guangdong China

ISBN: (数字)9798350393682

ISBN: (纸本)9798350393699

Electric vehicles are gaining popularity among consumers and governments due to their environmentally friendly nature, efficiency, and energy-saving capabilities. With the popularity of electric vehicles, charging piles, as their important supporting facilities, are also facing huge market demand. However, there is currently a mismatch between the number and distribution of charging piles and the charging needs of electric vehicles, which has led to problems such as uneven utilization of charging piles, long waiting times for charging, and excessive load on the power grid. These problems not only affect the travel experience and satisfaction of electric vehicle users, but also pose security and stability challenges to the power system. Therefore, how to effectively predict and optimize the orderly charging needs of charging piles has become an urgent problem to be solved. In order to solve this problem, this paper studies the application of machine learning in the orderly charging demand prediction and scheduling optimization of charging piles. Machine learning is a technology that enables artificial intelligence and automated decision-making through data analysis and model building. In the field of intelligent transportation, machine learning has broad application prospects and can help improve transportation efficiency, safety, and environmental friendliness. This article proposes a solution based on the ensemble learning algorithm BPNB model. By combining the Adaboost algorithm with the BP neural network, this model addresses the limitations of the BP neural network. The BPNB model is a comprehensive learning approach that integrates the Adaboost algorithm and BP neural network algorithm, enhancing the generalization capability and stability of the BP neural network. The study presented in this article introduces a fresh perspective and methodology for the application of machine learning in intelligent transportation. Furthermore, it offers an effective solution

关键词： Machine learning algorithms Neural networks software algorithms Transportation Power system stability Electric vehicles Prediction algorithms

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Experiential Learning System with Generative Art Using Virtual Spaces

Experiential Learning System with Generative Art Using Virtu...

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IEEE Annual International Computer software and Applications Conference (COMPSAC)

作者： Shun Furuichi Kaoru Sumi School of Systems Information Science Future University Hakodate Hakodate Hokkaido Japan

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Generative art is algorithmically generated art that is synthesized by computer software algorithms or mathematical autonomous processes. The learner wears HoloLens2 and learns by transforming and observing three-dimensional (3D) generative art projected on a virtual space. In this study, we developed an experiential learning system for learning mathematics and programming by experiencing generative art in a virtual space. We conducted a comparative study to see if this system would make a difference in learning efficiency compared to learning with a conventional two-dimensional (2D) learning medium such as textbooks. The results showed that there was no significant difference in the learning efficiency between conventional learning and learning using the generative art displayed in the virtual space in terms of learning the volume and surface area of the torus body, however, there was a difference in the way the subjects drew the torus body. We deduced that HoloLens2 will be an effective educational supplementary tool to 3D visualize 3D figures while giving a programming insight through reflections in code obtained from changing the size of the 3D figure.

关键词： Learning systems Visualization Three-dimensional displays Art Shape Two-dimensional displays software algorithms

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A Memory-Efficient Accelerator for 128-Parallel Sequence-to-Graph Alignment in Variant-Enriched Regions

A Memory-Efficient Accelerator for 128-Parallel Sequence-to-...

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IEEE Biomedical Circuits and Systems (BIOCAS)

作者： Zhe-Wei Shen Jheng-Syun Huang Yi-Chang Lu Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan

ISBN: (数字)9798350354959

ISBN: (纸本)9798350354966

For decades, sequence-to-sequence alignment is a crucial tool in bioinformatics that identifies the similarity between a query and the reference genome sequence. Because one single reference sequence is insufficient to express the diversity of genes, the concept of the reference genome graph has been proposed, which utilizes a graph structure to represent genetic variations and has a better recording of biological information. As results, different sequence-to-graph alignment algorithms have been developed to address the new demand. Although there are several fast methods available, in the regions enriched with genetic variations, the non-heuristic Smith-Waterman method is still the main approach to guarantee finding the optimal solutions at the cost of lengthy processing time. To alleviate this issue, we design a memory-efficient hardware accelerator for variation-enriched sequence-to-graph alignment on an Intel Arria 10 FPGA. According to our experiment, the proposed 128parallel accelerator operates at 200 MHz, and achieves more than 9X speed-ups when compared to the PaSGAL software for the MHC gene dataset in the human genome GRCh38.

关键词： Costs software algorithms Genomics software Distance measurement Recording Bioinformatics Hardware acceleration Field programmable gate arrays Periodic structures

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An Internal Environment Anomaly Detection System for Secondary Water Supply Pump Houses Based on the Improved PatchCore Algorithm

An Internal Environment Anomaly Detection System for Seconda...

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Chinese Automation Congress (CAC)

作者： Yongtao Yu Xiaoqiang Lu Junchen Gong School of Automation Shenyang Aerospace University Shenyang China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

With the growing public awareness regarding tap water safety, the secondary water supply pump room, acting as the final checkpoint before water enters homes, plays a crucial role in ensuring a safe internal environment. However, pump rooms face challenges such as disordered spatial distribution and a shortage of maintenance staff, leading to significant difficulties and costs in maintenance and supervision. This paper introduces an anomaly detection system for the internal environment of secondary water supply pump rooms, based on an enhanced PatchCore algorithm. The system is designed to alleviate the burden and costs associated with manual monitoring by providing continuous 24-hour anomaly detection through automated equipment. It incorporates 5G communication and edge computing technologies within edge-end devices, showcasing superior capabilities in data transmission speed, detection efficiency, information security, and intelligent processing. On the software front, the system employs an improved PatchCore algorithm that has been trained and tested on a dataset constructed from real-world scenarios of secondary water supply pump rooms, achieving an AUROC metric of up to 0.996 and an inference speed of 23.6ms per image. Anomaly information from the pump rooms is transmitted to an IOT platform, email, and server for remote access by personnel. This research offers an effective solution for the intelligent monitoring of pump rooms and provides valuable practical insights for safeguarding the security and reliability of secondary water supply systems.

关键词： Costs software algorithms Stability analysis Maintenance software reliability Anomaly detection Water resources Monitoring Edge computing Synthetic data

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Time-varying Formation Control for Multiple Omni-WMRs Based on ROS

Time-varying Formation Control for Multiple Omni-WMRs Based ...

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Chinese Automation Congress (CAC)

作者： Dengguo Luo Kaibin Su Jun Zhao Huimin Zeng Artificial Intelligence Key Laboratory of Sichuan Province School of Automation and Information Engincering Sichuan University of Science and Engineering Yibin China School of Automation and Information Engincering Sichuan University of Science and Engineering Yibin China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

The present study introduces a time-varying formation control algorithm designed for multiple omni-directional mobile robots (Omni-WMRs). The algorithm employs a leader-follower strategy, which tackles the challenge of time-varying consistency in multi-robot formation control within complex environments by devising a communication topology and an error control method that ensure consistency. To validate this algorithm, a multi-robot experimental platform based on ROS was designed and constructed, utilizing its modularity and scalability to facilitate dynamic adjustments and efficient cooperation within the multi-robot system. Experimental results show that the control algorithm and experimental platform can achieve precise target trajectory tracking and flexible formation control in complex environments, maintaining consistency errors within acceptable ranges, and demonstrating efficiency and stability in practical applications.

关键词： Trajectory tracking Heuristic algorithms software algorithms Formation control Stability analysis software Topology Multi-robot systems Mobile robots Time-varying systems

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Metamorphic relationship generation based on Faure Sequence Initialized Slime Mould Algorithm

Metamorphic relationship generation based on Faure Sequence ...

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International Conference on Electronics Information and Emergency Communication

作者： Tingzhi Hong Leiyan Qian Jiayi Fang Tongshuai Wang Zhicheng Zhu Xin Qin Wei Nai Zan Yang School of Electronic Information Huzhou College Huzhou China Huzhou Key Laboratory for Urban Multidimensional Perception and Intelligent Computing Huzhou China Pablic Teaching and Research Department Huzhou College Huzhou China

ISBN: (数字)9798350361896

ISBN: (纸本)9798350361902

Metamorphic relationship is an extremely important software testing method in the field of software engineering, and after years of research by scholars, a relatively complete system has been formed. However, the objective function of the metamorphic relationship generation algorithm is essentially a non-differentiable L1 norm, which means that the algorithm can finally be transformed into a non-smooth optimization problem. If traditional gradient dependent methods like gradient descent (GD) or stochastic gradient descent (SGD) are used, the objective function cannot be solved. The coordinate descent (CD) or sub-gradient descent (SubGD) methods usually used to solve the objective function are prone to falling into the trap of local minima, making it difficult to find the global optimal solution. Therefore, it is necessary to find a derivative-free optimization method to solve the objective function of metamorphic relationship generation algorithm. In this paper, a novel slime mold algorithm (SMA), which is called the Faure sequence initialized SMA (FSSMA) has been proposed for global optimization of the objective function. FSSMA can effectively overcome the shortcomings of CD and SubGD methods. Through numerical experiments, the effectiveness and computational efficiency of FSSMA have been demonstrated.

关键词： software testing Search methods software algorithms Optimization methods Linear programming Computational efficiency software engineering

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Towards an Automatic Framework for Solving Optimization Problems with Quantum Computers

Towards an Automatic Framework for Solving Optimization Prob...

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Quantum software (QSW), IEEE International Conference on

作者： Deborah Volpe Nils Quetschlich Mariagrazia Graziano Giovanna Turvani Robert Wille Department of Electronics and Telecommunications Politecnico di Torino Italy Chair for Design Automation Technical University of Munich Germany Department of Applied Science and Technology Politecnico di Torino Italy Software Competence Center Hagenberg GmbH (SCCH) Austria

ISBN: (数字)9798350368475

ISBN: (纸本)9798350368482

Optimizing objective functions stands to benefit significantly from leveraging quantum computers, promising enhanced solution quality across various application domains in the future. However, harnessing the potential of quantum solvers necessitates formulating problems according to the Quadratic Unconstrained Binary Optimization (QUBO) model, demanding significant expertise in quantum computation and QUBO formulations. This expertise barrier limits access to quantum solutions. Fortunately, automating the conversion of conventional optimization problems into QUBO formulations presents a solution for promoting accessibility to quantum solvers. This article addresses the unmet need for a comprehensive automatic framework to assist users in utilizing quantum solvers for optimization tasks while preserving interfaces that closely resemble conventional optimization practices. The framework prompts users to specify variables, optimization criteria, as well as validity constraints and, afterwards, allows them to choose the desired solver. Subsequently, it automatically transforms the problem description into a format compatible with the chosen solver and provides the resulting solution. Additionally, the framework offers instruments for analyzing solution validity and quality. Comparative analysis against existing libraries and tools in the literature highlights the comprehensive nature of the proposed framework. Two use cases (the knapsack problem and linear regression) are considered to show the completeness and efficiency of the framework in real-world applications. Finally, the proposed framework represents a significant advancement towards automating quantum computing solutions and widening access to quantum optimization for a broader range of users. The framework is publicly available on GitHub (https://***/cda-tum/mqt-qao) as part of the Munich Quantum Toolkit (MQT).

关键词： Computers Quantum computing Automation Linear regression software algorithms Transforms Quantum annealing

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