The proceedings contain 574 papers. The topics discussed include: a new semi supervised FCM algorithm based on mahalanobis distance;machine vision recognition of auto-hub;knowledge-aided adaptive subspace detection in...
ISBN:
(纸本)9780769547190
The proceedings contain 574 papers. The topics discussed include: a new semi supervised FCM algorithm based on mahalanobis distance;machine vision recognition of auto-hub;knowledge-aided adaptive subspace detection in partially homogeneous environments;dictionary learning research based on sparse representation;a different approach to off-line signature verification using the optimal DTW algorithm;a real-time process scheduling policy in windows;online time series forecasting based on biorthogonal wavelet kernel support vector machine;scene visualization based on semantic-visual association;SCG and LM improved BP neural network load forecasting and programming network parameter settings and data preprocessing;research on clustering algorithm for massive data based on hadoop platform;research on java bytecode parse and obfuscate tool;and design of the solar photovoltaic system data acquisition board.
The proceedings contain 1062 papers. The topics discussed include: a comparison of the colorimetric characterization algorithms for different displays;a data processing software package for passive seismic monitoring ...
ISBN:
(纸本)9781424497638
The proceedings contain 1062 papers. The topics discussed include: a comparison of the colorimetric characterization algorithms for different displays;a data processing software package for passive seismic monitoring of hydraulic fracturing;a infeasible interior point homotopy method for solving horizontal linear complementarity problem;a 3-dimension topology generation approach for networks-on-chip;a delaunay triangulation based method for optimizing backbone wireless mesh networks;a conceptual framework for ontology-based expertise knowledge map;a mobile guide system framework for museums based on local location-aware approach;a model of tourism information service composition based on fuzzy Petri net;a fuzzy linguistic based model for teaching assessment;a highly accurate software scanned cell projection algorithm and its parallelization;a conception of constructing digital campus based on next generation Internet;and a simplified discontinuous deformation analysis for simulating rock fall.
The automobile service industry's explosive growth highlights the need for creative approaches to boost operational effectiveness and user experience. This study introduces a Hybrid Garage Assistance system, integ...
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ISBN:
(纸本)9798331513894
The automobile service industry's explosive growth highlights the need for creative approaches to boost operational effectiveness and user experience. This study introduces a Hybrid Garage Assistance system, integrating Classical Machine Learning (ML) techniques with Generative AI to optimize garage service discovery and analysis. The system employs sophisticated data processing methods, including Term Frequency-Inverse Document Frequency (TF-IDF) vectorization and regex-based service detection, to extract actionable insights from unstructured garage *** to the system are machine learning models Random Forest (RF) and XGBoost (XGB) which achieve high precision and recall in classifying garage services. A hybrid search mechanism, combining cosine similarity with ML-driven predictions, ensures the delivery of highly personalized search results. To further refine decision-making, the system incorporates Generative AI models such as Perplexity for web-based research, Gemini for location-specific analysis, Mistral for email sending and GPT-4 for detailed service recommendations and dall-e for creating user specific parts images. These advanced tools provide users with comprehensive information that enables them to make well-informed decisions about garage *** evaluation of the system is conducted using robust metrics, including precision, recall, F1-score, and system latency. Experimental results reveal a precision of 85%, recall of 70.8%, and an F1-score of 77.2%, demonstrating the efficacy of integrating classical ML with generative AI. The system's average latency of 5.9 seconds ensures a seamless and responsive user *** hybrid framework highlights the potential of blending classical ML and Large Language Models (LLMs) to enhance search and recommendation functionalities, offering a scalable and robust blueprint for future advancements in the automotive service sector. The system's Propose a Multi-Agent system With high accuracy,
In a decentralized Process Management system, several process engines cooperate to execute a single process instance by using direct Machine-to-Machine communication and local coordination of the process flow. In this...
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ISBN:
(纸本)9789819608041;9789819608058
In a decentralized Process Management system, several process engines cooperate to execute a single process instance by using direct Machine-to-Machine communication and local coordination of the process flow. In this paper, we analyze the software architecture elements of a decentralized Process Management system. We explain the involved components, connectors, data, and the relationships between them. We also describe the state transitions of decentralized processes during execution.
In serverless computing, the service provider takes full responsibility for function management. However, serverless computing has many challenges regarding data security and function scheduling. To address these chal...
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For tourism recommendation system, users’ behavior preference and service demand may change with the different context they are in, especially with the season, weather, geographical location and user attributes. Tour...
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service organized all kinds of services to one for the *** the cloud environment, the services and related QoSs (Quality of services) in every cloud may be *** this paper, how to compose those services together in the...
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Task scheduling in cloud-fog computing is challenging, particularly for large-scale Bag-of-Jobs (BoJ) applications. To address this complexity, we propose a new task-scheduling model that balances execution speed and ...
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IT service operations involve handling sensitive customer data, which gets logged into the system in the form of tickets describing the issues faced by customer. An authorized agent tasked with resolving a ticket may ...
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ISBN:
(纸本)9783031800191;9783031800207
IT service operations involve handling sensitive customer data, which gets logged into the system in the form of tickets describing the issues faced by customer. An authorized agent tasked with resolving a ticket may get exposed to sensitive customer information, which can lead to privacy breach, impacting the customer and potentially damaging the reputation of the organization. To address this issue, we propose a framework that minimizes sensitive data exposure to preserve privacy in IT service operations. Our framework quantifies the sensitive data misuse by an agent based on the information aggregated at their end. The sensitive data within ticket is masked and the flow of ticket is regulated to restrict the sensitive data aggregation. Additionally, we introduce a simulator, PESO (Privacy Enabled service Operation), to study and demonstrate the implications of privacy settings on various service operation parameters.
This study examines computerscience students’ perceptions of their service learning experiences, comparing fully online and on-campus modalities. service learning is a teaching approach that integrates community eng...
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