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检索条件"丛书名=Lecture Notes in Networks and Systems"

共 9894 条记录，以下是1411-1420 订阅

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Design of Low Power Booth Multiplier with Enhance Pre-logic Mechanism Using Verilog 1

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Parsodia, Apurv Jindal, Poonam Natl Inst Technol Kurukshetra Sch VLSI Design & Embedded Syst Design Thanesar Haryana India Natl Inst Technol Kurukshetra Dept Elect & Commun Engn Thanesar Haryana India

ISBN: (数字)9789819713233

ISBN: (纸本)9789819713226;9789819713233

A Booth Radix-4 multiplier is a commonly used digital circuit for performing high-speed multiplication of binary numbers in modern microprocessors. Low power consumption is a critical requirement for modern electronic devices and designing a low power Booth Radix-4 multiplier has become an important research area. This paper proposes a low-power Booth Radix-4 multiplier with improved design by using pre-logic to generate the enable signal (pre-encoder) that uses a new approach to reduce the power consumption by minimizing the switching activity in the circuit by disabling traditional booth encoder and decoder and thus prevent from reductant working. The proposed multiplier achieves a significant reduction in power consumption compared to existing Radix-4 Booth multipliers while maintaining high performance and accuracy. The research shows the improved power performance with respect to existing Radix-4 Booth multipliers while maintaining high performance and accuracy. The design is implemented using Verilog HDL and simulated using Xilinx Vivado 2020.2. Simulation results demonstrate that the total power is reduced by 5.082% while dynamic power, static power consumption is reduced by 3.002%, 71.298%, respectively, and whereas a significant reduction of LUT by 17.8082%

关键词： Booth algorithm Power multiplier Low power multiplier Partial product Radix-4 Booth multiplier

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Fuzzy Spatial Analysis of the Hellenistic House in the Izmir Mount Nif Ballicaoluk Settlement

Fuzzy Spatial Analysis of the Hellenistic House in the Izmir...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Yaman, Tutku Tuncali Onem, Ilkay Gizem Marmara Univ Fac Business Adm Dept Management Informat Syst Istanbul Turkiye Istanbul Univ Inst Social Sci Archaeol Program Istanbul Turkiye

ISBN: (纸本)9783031671944;9783031671951

Ballicaoluk archaeological site, located in the eastern region of Mount Nif, was excavated as part of the Mount Nif Excavation Project. The remains of an ancient settlement unearthed about 3.5 ha. land on the hilltop. Within the excavations in the AC 24-25 and AD 24-25 plan squares, a residential area dated to the Hellenistic period according to the finds and architectural remains was excavated. The subject of this paper is confined to two adjacent trenches, AC24c-AD24d. The finds were grouped into four clusters using a c-fuzzy clustering method, which has shown effective outcomes in previous archaeological studies. The relationships between the groups and the areas identified by archaeological expertise within the structure were determined using spatial spread, elevation, and type of the finds. This method aims to offer insights into the functions of different regions within the archaeological site by effectively integrating the archaeological context with quantitative analysis through sophisticated clustering techniques. The application of fuzzy methodologies is considered suitable for addressing both the spatial and qualitative ambiguity inherent in archaeological material. According to the results of fuzzy clustering, four contextually meaningful clusters were created. This paper seeks to promote wider acceptance and comprehension of fuzzy methods in archaeology, given their efficacy in managing the spatial and qualitative uncertainties frequently associated with archaeological data.

关键词： Nif Smyrna Spatial Analysis Fuzzy Clustering Archaeology

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Using Semi-Markov Models for Generating, Validating, and Analyzing Artificial Smart Home Processes 1

引用

16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： McClean, Sally Wang, Dongwei Yang, Lingkai McChesney, Ian Tariq, Zeeshan Prasad, Shalini Univ Ulster Sch Comp Belfast BT15 Antrim North Ireland Chinese Inst Coal Sci Res Inst Mine Artificial Intelligence Beijing 100013 Peoples R China

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

Improvements in medicine have led to huge increases in longevity, with a corresponding rise in demands for healthcare. Such changes have been accompanied by major developments in sensor technologies and smart homes, which can generate event data arising from a person's Activities of Daily Living (ADLs). By identifying these underlying activities, technology can support older people in their homes through reminding them of routine activities, detection of anomalous behavior, and sending alarms to care providers. However, the lack of suitable large datasets of ADL process executions, for testing algorithms at scale, has been a barrier to the development and deployment of such solutions. ADL event data shares characteristics with datasets found in organizational task mining, characteristics such as relatively low volume and rich human-environment interactions. We here draw upon techniques from organizational process and task mining involving a semi-Markov modelling approach to characterize ADL sequences and activity durations and use these models to generate large artificial smart home process datasets. The methodology is evaluated on a public domain sensorized and annotated smart home dataset. Outputs are validated qualitatively through an analysis of the state transition matrices and graphs of activity duration, and quantitatively using both an entropy-based approach to compare duration distributions and conformance analysis techniques from process mining, demonstrating the viability of our approach at scale.

关键词： artificial smart home processes semi-Markov models process mining

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Using Permutation Entropy to Evaluate Spatial Predictability in Urban Crime 1

引用

16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Dang, Minling Yu, Zhiwen Chen, Liming Wang, Zhu Guo, Bin Nugent, Chris Northwestern Polytech Univ Xian Peoples R China Harbin Engn Univ Harbin Peoples R China Dalian Univ Technol Dalian Peoples R China Ulster Univ Belfast North Ireland

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

Predicting where the crime occurs is essential and significant for preventive policing which is an important action for economic benefits, urban building and human safety. Predictability is a theoretical bound for the prediction performance in human behaviour based on limited data. Current approaches to predictability are usually based on human mobility, with the development of electronic information systems in the police system, more datasets about urban crime can be obtained. Therefore, it is possible to study the predictability of urban crime. To address this, this study uses permutation entropy as the measure to evaluate the spatial predictability of urban crime. The method has been evaluated using urban cities' public crime datasets (Washington DC, Denver, New York, and Vancouver) from years 2010-2022. The results prove the hypothesis of correlation between the space scales of data and the level of spatial predictability, which can guide the prediction of the urban crime algorithms.

关键词： Permutation Entropy Predictability Urban crime

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Uncovering Business Accounts Among Retail Shoppers: Insights from Supermarket Transactions Using an Intelligent Decision Support System

Uncovering Business Accounts Among Retail Shoppers: Insights...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Guler, Eslem Zeybek, Omer Migros Ticaret AS R&D Dept TR-34735 Istanbul Turkiye

ISBN: (纸本)9783031671913;9783031671920

Customer segmentation is crucial to retail operations, pivotal in marketing strategies, and improving operational efficiency. This study proposes an innovative approach to optimizing customer segmentation and enhancing business efficiency. The primary objective is to classify customers currently shopping in supermarkets but exhibit behaviors indicative of potential interest in preferring the wholesale channel. Although the propensity of retail customers to buy specific products and their probability of churn have been well documented by previous marketing analytics research, less is known about service-oriented customer segmentation. By leveraging customer behavior and transactional sales-related data from a retail grocer serving both retail and wholesale channels, this research aims to identify retail customers exhibiting wholesale behavior patterns. Various unsupervised classification algorithms were employed during the estimation process. Among them, the KMeans algorithm, known for its usage in segmentation models, was chosen as the primary classification model. Implementing this strategy has the potential to streamline customer targeting efforts, ultimately maximizing the effectiveness of directing individuals toward the most relevant retail outlet. By discovering these patterns, we aim to direct customers toward the retailer's most efficient service channel, streamlining customer targeting efforts and enhancing operational efficiency.

关键词： Machine Learning Customer Analytics

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Smart IoT Devices: An Efficient and Elegant Revolution Using Smart Switches 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Rao, Annam Takshitha Kumar, Aman Choudhary, Rupali Kanjia, Khush Dhumane, Amol Zade, Nilima Deokar, Shubhangi Symbiosis Int Symbiosis Inst Technol Dept Comp Sci & Engn Pune Campus Mulshi Pune 411021 Maharashtra India

ISBN: (数字)9789819713134

ISBN: (纸本)9789819713127;9789819713134

In the age of "ubiquitous computing," the Internet of Things (IoT) has emerged as a dominant force, heralding a new paradigm in device communication and interaction. Integrating everyday objects, from household appliances to industrial machinery, with internet connectivity, IoT enhances automation, control, and data monitoring. While the technology's evolution traces back to the early internet, its transformative impact today spans intelligent home thermostats to interconnected vehicles and revolutionary smart switches. A notable challenge is ensuring seamless integration among these diverse devices, highlighting the need for robust platforms like Sinric Pro. Sinric Pro stands as a comprehensive IoT solution, facilitating efficient device management and enabling easy prototyping and deployment. The fusion of Sinric with the versatile ESP8266 microcontroller further broadens IoT application possibilities, allowing even basic engineers to connect hardware to the cloud effortlessly. The collaboration streamlines device management, paves the way for intuitive mobile and web applications, and holds promise for advancing IoT's reach in the future. The landscape of IoT in home automation and energy efficiency has seen promising strides, yet certain challenges remain. Further research is imperative to bridge the gaps between theoretical propositions and practical applications.

关键词： Ubiquitous computing Internet of Things (IoT) Device communication Automation Smart switches Integration platforms Sinric Pro ESP8266 microcontroller Smart environments Device management Cloud connectivity Home automation

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Sustainability Performance Evaluation in Faculties: A COPRAS-Based Assessment 1

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Guleryuz, Sezin Istanbul Univ Artificial Intelligence & Data Engn Dept Istanbul Turkiye

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

Higher education institutions, particularly in the axis of 'Sustainable Environment' have increasingly emphasized education, research, social responsibility, environmental awareness, and sustainability in recent years. Bartin University is also moving forward, intending to become a green campus, intensifying its efforts within the framework of the GreenMetric World University Rankings for Environmental Sustainability. Thus, evaluating the sustainability performance of faculties is crucial to achieving this goal. In this study, the UI GreenMetric model was utilized during the implementation phase of the problem. The nine faculties of Bartin University are evaluated according to five criteria: Setting and Infrastructure, Energy and Climate Change, Waste Management, Water Usage and Transportation, Education and Research. Since evaluating performance involves various interests and significant levels of uncertainty, this research utilizes the Spherical Fuzzy Complex Proportional Assessment (SF-COPRAS) technique to rank faculties. The uniqueness of this study stems from its utilization of this technique based on SFS, a novel concept within the sustainability field.

关键词： COPRAS GreenMetric University Ranking Sustainability Spherical fuzzy sets

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A Smart Sugeno Interval Type-2 Fuzzy Bee Colony Optimization to Stable an Autonomous Mobile Robot Controller

A Smart Sugeno Interval Type-2 Fuzzy Bee Colony Optimization...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Amador-Angulo, Leticia Castillo, Oscar Tijuana Inst Technol Div Grad Studies Tijuana Mexico

ISBN: (纸本)9783031671913;9783031671920

In this paper the main objective consists in the implementation of a Sugeno inference system applied to an interval type-2 Fuzzy logic system (SIT2FLS) in the adjustment dynamic of parameters in a Bee Colony Optimization algorithm (BCO) to have a stable trajectory of a line. This paper present two important ideas, the first goal of BCO is found of the optimal design of the Membership Functions (MFs) in a Mamdani Type-1 Fuzzy Logic System (MT1FLS), the second idea was implemented a SIT2FLS to find the optimal values in alpha and beta parameters in the BCO algorithm, which is the originality in this paper, and an analysis of the execution time and the errors obtained by the Mean Square Error (MSE) is presented. The results indicated that the BCO algorithm has better stabilization and excellence results when the executed a SIT2FLS to find the optimal values in beta and alpha parameters the BCO algorithm is presented. The main conclusions found with the proposal are that convergence is faster in finding minor results as well as the stabilization of the problem studied. In addition, to highlight the efficiency and good results of the SIT2FLS a comparative with a Mamdani IT2FLS (MIT2FLS) is presented.

关键词： Bee Colony Optimization Interval Type-2 Fuzzy Logic System Fuzzy Logic System Autonomous Mobile Robot Stabilization

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An Overview on the Use of Machine Learning Algorithms for Identifying Anomalies in Industrial Valves 12th

An Overview on the Use of Machine Learning Algorithms for Id...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Ugarte, Lesly Ttito Bernardini, Flavia Univ Fed Fluminense Inst Comp Niteroi RJ Brazil

ISBN: (纸本)9783031602146;9783031602153

Valves used in industrial systems may present anomalous behaviour or eventually fail throughout their useful life. The automatic detection of these anomalies and failures is quite important nowadays, specially due to the increasing movement of industry 4.0 and Digital Twins technologies. In order to detect their anomalies or failures, data captured by sensors in these valves can be used for analysis and prediction tasks. More specifically, these time series data are analyzed and used for constructing machine-learning based models for predicting, which may contribute to better preventive maintenance and longer valve life. The objective of this work is to present the results obtained when executing a Systematic Literature Review (SLR) in order to identify the state of the art on using Machine Learning (ML) algorithms and methods to identify anomalies in industrial valves. Case studies could be identified on different types of valves, including hydraulic, solenoid, gas, nuclear and compression valves. This indicates a long future to develop and propose solutions in this field of science. An increasing focus on the use of deep learning models could also be observed, although there are also simpler methods under scrutiny. Finally, it could be observed that it is quite difficult to find available datasets in order to replicate the obtained results, as well as advance in new ideas and methods in this area.

关键词： anomaly detection industry 4.0 digital twins machine learning time series analysis

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Integrating Fuzzy Cognitive Mapping and Picture Fuzzy TOPSIS for Long-Term Retail Performance Evaluation 1

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Sari, Irem Ucal Ozkirim, Ceren Ilgin, Ugurcan Istanbul Tech Univ Dept Ind Engn Istanbul Turkiye

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

Efficient performance evaluation holds pivotal importance in the dynamic landscape of the retail sector. This paper presents a methodology that integrates Fuzzy Cognitive Map (FCM) and Picture Fuzzy Technique for Order Preference by Similarity to Ideal Solution (PF-TOPSIS) for comprehensive performance measurement. Emphasizing the overarching significance of retail performance assessment in organizational success, this approach begins by acknowledging the multifaceted nature of retail operations. Through FCM, the intricate interrelationships among long-term influential criteria shaping retail performance are identified and elucidated, facilitating a deeper understanding of underlying dynamics. Subsequently, leveraging PF-TOPSIS, retailers are assessed based on identified criteria, while accounting for inherent uncertainties in real-world data. This integrated framework empowers retailers to gain insights into critical performance factors and prioritize strategic actions for sustained success. By offering a holistic perspective that considers both qualitative and quantitative dimensions, our methodology enhances the accuracy and reliability of performance evaluation in the retail domain. Through an application on a company in the tire industry, the effectiveness and applicability of this approach are demonstrated, providing valuable guidance for retail practitioners and researchers navigating the intricacies of performance assessment and strategic decision-making in the retail landscape.

关键词： Retailer Performance Management Fuzzy Cognitive Mapping Picture Fuzzy TOPSIS

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