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检索条件"丛书名=Communications in Computer and Information Science"

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Many-Objective Artificial Bee Colony Algorithm Based on Decision Variable Grouping 5th

Many-Objective Artificial Bee Colony Algorithm Based on Deci...

引用

5th International Conference on Neural Computing for Advanced Applications (NCAA)

作者： Xiao, Dong Liao, Futao Zhang, Shaowei Wang, Hui Hu, Min Nanchang Inst Technol Sch Informat Engn Nanchang 330099 Jiangxi Peoples R China

ISBN: (纸本)9789819770038;9789819770045

The artificial bee colony (ABC) algorithm has exhibited commendable performance in addressing single-objective optimization problems (SOPs) and multi-objective optimization problems (MOPs). However, limited research has been conducted in applying ABC to tackle many-objective optimization problems (MaOPs). The primary impediment arises from the inherent inability of traditional Pareto dominance to exert sufficient selection pressure, leading to a sharp increase in the proportion of incomparable solutions within the population. To address these challenges, this study proposes a novel many-objective ABC algorithm based on decision variable grouping (DVGABC) for MaOPs. Firstly, the decision variables are divided into two groups: convergence and diversity, updated during the employed bee stage and the onlooker bee stage, respectively. Then, a new fitness function based on strength Pareto dominance is proposed. Finally, the DTLZ benchmark suite is used to validate the effectiveness of DVGABC. The results obtained demonstrate the superiority of DVGABC over five other well-established algorithms on two performance metrics.

关键词： Swarm intelligence Artificial bee colony Many-objective optimization Decision variable grouping

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Redefining Mobility Management for Improved Handover Efficiency in Internet-Connected Vehicles 5th

Redefining Mobility Management for Improved Handover Efficie...

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5th International Symposium on Intelligent Computing Systems

作者： Shah, Peer A. Bibi, Sumiya Ali, Hassan Osman Higher Coll Technol Dept CIS Fujairah U Arab Emirates COMSATS Univ Islamabad Dept CS Attock Pakistan

ISBN: (纸本)9783031829307;9783031829314

Over the past three decades, wireless communication has seen a significant surge, with Vehicular Networks emerging as a prominent area of interest for researchers. Managing mobility in these networks presents a considerable challenge. Vehicles moving between roadside units or base stations can experience disruptions in real-time services such as Voice over IP (VoIP), media streaming, safety-critical data transmission, and gaming. Due to the typically high speed of vehicles, these movements often result in handovers and packet loss. This research introduces a novel approach to mobility management and handover execution for mobile vehicles travelling on highways, differing from traditional methods. The proposed model predicts a vehicle's movement from one base station to the next using a probabilistic method by the correspondent node, which then initiates the binding refresh procedure accordingly. This approach reduces control traffic overhead and packet loss, leading to more efficient use of limited wireless resources. The performance of the proposed algorithm has been evaluated through simulation, demonstrating its effectiveness in reducing packet loss, handover delay, and control traffic overhead.

关键词： Vehicular Networks Mobility Management Intelligent Transportation System Efficient Handover Roadside Unit

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X-Ray Insights: A Siamese with CNN and Spatial Attention Network for Innovative Person Identification 4th

X-Ray Insights: A Siamese with CNN and Spatial Attention Net...

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4th International Conference on Intelligent Systems and Pattern Recognition-ISPR

作者： Hazem, Farah Akram, Bennour Mekhaznia, Tahar Al-Sarem, Mohammed Shukla, Piyush Kumar Khalaf, Osamah Ibrahim Echahid Cheikh Larbi Tebessi Univ LAMIS Lab Tebessa Algeria Taibah Univ Coll Comp Sci & Engn Medina Saudi Arabia Technol Univ Madhya Pradesh Bhopal Madhya Pradesh India Al Nahrain Univ Dept Solar Al Nahrain Res Ctr Renewable Energy Baghdad Iraq

ISBN: (纸本)9783031821554;9783031821561

In the security and healthcare domains, using data from medical imaging for precise individual identification and verification has become increasingly vital. This necessity is particularly pronounced in scenarios where old and traditional identification techniqhes prove inadequate, such as during natural disasters or instances of physical impairment. Chest X-ray radiographs offer a promising avenue for reliable identification owing to their ability to capture distinctive anatomical features of the rib cage, lungs, and heart. Our research introduces a new approach to person identification utilizing chest X-ray radiographs, employing ResNet50 with spatial attention within a Siamese and Triplet network architecture. In contrast to conventional convolutional neural networks (CNNs), the inclusion of ResNet50 with spatial attention enhances the model's capability to discern global dependencies within images, potentially facilitating the extraction of discriminative characteristics for identification purposes. This research contributes to the existing by presenting a tailored methodology explicitly crafted for processing chest X-ray images, thereby presenting a viable solution for reliable identification in security and medical contexts, particularly in emergency scenarios. To validate the efficacy of the proposed method and explore its practical applications, rigorous validation and testing procedures are imperative.

关键词： Siamese network Triplet loss Spatial Attention person identification Chest X-rays deep learning ResNet50

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Causal Inference in the Multiverse of Hazard 6th

Causal Inference in the Multiverse of Hazard

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6th Pacific Causal Inference Conference

作者： Lai, En-Yu Huang, Yen-Tsung Inst Stat Sci 128Acad RdSection 2 Taipei 115201 Taiwan

ISBN: (纸本)9789819778119;9789819778126

Hazard is a crucial estimand in both applied and methodological contexts. However, its causal interpretation is challenging due to inherent selection biases and the ambiguity in defining populations for comparison across different treatment groups. To address these issues, we introduce a novel definition of counterfactual hazard based on the framework of possible worlds. Rather than conditioning on prior survival status as a conditional probability, our definition involves intervening in the prior status, treating it as a marginal probability. Using single-world intervention graphs, we show that the proposed counterfactual hazard represents a controlled direct effect. Conceptually, intervening in survival status at each time point creates a new possible world. The proposed hazards at these time points represent risks in these hypothetical scenarios, forming a "multiverse."

关键词： counterfactual process hazard survival analysis possible-world semantics

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Transmission Line Equipment Defect Detection Based on Improved YOLO Network 5th

Transmission Line Equipment Defect Detection Based on Improv...

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5th International Conference on Neural Computing for Advanced Applications (NCAA)

作者： Zhu, Jiajun Wang, Tao Wang, Lin Luo, Zhiheng Shandong Jianzhu Univ Sch Informat & Elect Engn Jinan 250101 Peoples R China

ISBN: (纸本)9789819770069;9789819770076

Inspections of power transmission systems are essential as they directly impact the safety and stability of the entire power transmission infrastructure. With the advancement of technology, the utilization of unmanned aerial vehicles (UAVs) for power line inspections has progressively gained widespread acceptance. Accurately assessing the operational status of critical components such as insulators holds paramount importance in ensuring the security of power transmission systems. However, employing UAVs for power line inspections results in the generation of large volumes of image data, while manual inspection methods prove inefficient and error-prone. To address these challenges, this study proposes an advanced target recognition algorithm. This algorithm effectively tackles the considerable parameter and computational costs associated with the CBS downsampling network by adopting the ADown downsampling network, simultaneously enhancing the propagation of gradient information. Furthermore, an innovative redesign of the generalized efficient layer aggregation network (GELAN) incorporates the integration of the Dilated Reparam Block (DRB) network, ultimately yielding theDRNCSPELAN4 module. This module amplifies the receptive field while reducing the burden of parameter and computational costs. The concatenated design of these two structures facilitates efficient extraction of feature information and optimization of gradient utilization, thereby achieving superior target detection outcomes. Experimental findings reveal not only an improvement of 1.6% and 1.0% in respective mAP50 and mAP50-95 values when compared to the original YOLOv8 model, but also varying degrees of reductions in model parameters and computational costs.

关键词： power transmission systems GELAN DRB YOLOv8

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Centralized Stochastic Multi-agent Pathfinding Under Partial Observability 4th

Centralized Stochastic Multi-agent Pathfinding Under Partial...

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4th Workshops on Agents and Robots for Reliable Engineered Autonomy

作者： Shani, Guy Stern, Roni Raveh, Itay Katz, Inon Ben Gur Univ Negev Beer Sheva Israel

ISBN: (纸本)9783031731792;9783031731808

Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents where each agent aims to reach a given goal location without conflicting with the other agents. In MAPF applications with physical robots, we can expect the agents to have stochastic behavior and imperfect localization. Planning for such centrally-controlled agents can be viewed as a special case of Partially Observable Markov Decision Process (POMDP), but off-the-shelf POMDP solvers cannot scale to plan for even a very small number of agents, due to the exponentially large size of the state and action spaces. Instead, we propose the Online Prioritized Planning (OPP) approach, where each agent computes and follows its individually-optimal policy until a potential conflict is detected. OPP resolves detected potential conflicts by replanning online for a subset of the agents so as to avoid positions that are potentially occupied by other agents. We describe how OPP can be implemented and propose two extensions that encourage the agents to leverage localization actions when needed. We evaluate OPP and its extensions empirically to highlight the pros and cons of our approach and show it can scale better than an offline baseline.

关键词： Multi-agent path finding POMDP

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Exploring the Innovation Capabilities of Mauritian SMEs: A Factor Analysis Approach 4th

Exploring the Innovation Capabilities of Mauritian SMEs: A F...

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4th International Conference on Society 5.0

作者： Padachi, Kesseven Mauree-Narrainen, Diroubinee Boolaky, Aleesha Chittoo, Hemant Ramphul, Needesh Weilbach, Lizette Univ Technol Mauritius Port Louis Mauritius Univ Pretoria Pretoria South Africa

ISBN: (纸本)9783031714115;9783031714122

Amidst a rapidly evolving business landscape, Small and Medium Enterprises (SMEs) face increasing pressure to innovate and adapt to remain competitive. However, despite the critical role of innovation in driving business growth and competitiveness, there exists a notable gap in understanding the innovation capabilities of SMEs in Mauritius. To address this gap, this paper undertakes a comprehensive exploration of the innovation landscape among Mauritian SMEs, drawing upon survey data collected from 280 SMEs across various sectors. The survey instrument, designed to capture key dimensions of innovation capability based on authoritative literature, delved into critical areas including knowledge exploitation, entrepreneurial acumen, risk management, networking proficiency, development capacity, and change management strategies. Utilizing factor analysis, the study identified four distinct factors shaping innovation capabilities within Mauritian SMEs: customer and market acquisition, radical innovation and knowledge management, risk management, and networking. These findings underscore the imperative for SMEs to embrace innovation as a strategic pathway for sustainable growth and competitive advantage. Notably, the study highlights the essential role of internalizing and leveraging external knowledge in driving innovation within organizations, fostering dynamic adaptation and resilience. By clarifying key drivers of innovation, this research offers actionable insights for policymakers, business leaders, and stakeholders seeking to cultivate a conducive innovation ecosystem in Mauritius. Ultimately, the study contributes to filling a critical knowledge gap and provides a foundation for informed decision-making aimed at enhancing innovation and driving economic prosperity in Mauritius' SME sector.

关键词： Innovation capabilities Innovation capacity SME Factor analysis

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Decentralised Vehicle Allocation for Community-Based Ride-Sharing Services 12th

Decentralised Vehicle Allocation for Community-Based Ride-Sh...

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2023 International Conference on Smart Cities and Green ICT Systems and International Conference on Vehicle Technology and Intelligent Transport Systems

作者： Nagarajan, Avinash McGibney, Alan Fenton, Pio Castineiras, Ignacio Munster Technol Univ Dept Comp Sci Cork Ireland Munster Technol Univ NIMBUS Ctr Cork Ireland Munster Technol Univ Teaching & Learning Unit Cork Ireland

ISBN: (纸本)9783031709654;9783031709661

This paper presents the design, implementation and evaluation of the vehicle fleet allocation in a community-based ride-sharing service. Independent communities of a city compete for the allocation of vehicle resources, which use to handle the transport requests of its own neighbours via ride-sharing. This vehicle allocation problem (VAP) is formulated as a decentralised, iterative negotiation process among independent communities with the underlying ride-sharing service operated by each community is formulated as a vehicle routing problem with both dynamic resources and requests. Two separate solution designs are evaluated: on the one hand, a Multi-Objective and Multi-Agent Reinforcement Learning algorithm, involving Deep Q-Learning with Graph Convolutional Networks, is applied to compute the vehicle allocation;on the other hand, a reactive-based simulation on top of a greedy decision-making process is applied to compute the underlying ride-sharing problem of each community. Existing benchmarks (e.g. Google HashCode) and public datasets (e.g. NYC taxis) are aligned to the proposed problem formulation, evaluating the solution approach under different community connectivity-levels and transport request distributions. Ride-sharing services have demonstrated scalable efficiency. This efficiency is achieved through a centralised Mixed-Integer Programming formulation, which optimally addresses the vehicle allocation problem.

关键词： Integer programming

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AmbiTag Blue: Bluetooth Low Energy Based Environment Monitoring and Data Logging Solution 2nd

AmbiTag Blue: Bluetooth Low Energy Based Environment Monitor...

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2nd International Conference on Agriculture-Centric Computation

作者： Verma, Ridhima Kumar, Suman IIT Ropar Dept Elect Engn Ropar India

ISBN: (纸本)9783031744396;9783031744402

Data loggers play a crucial role in agriculture by providing valuable insights into various environmental factors and parameters that directly influence crop growth, livestock health, and overall farm productivity. In this paper a Bluetooth Low Energy (BLE) based data logger is proposed for environmental monitoring applications. The device logs temperature and humidity data and stores it in flash memory, enabling retrieval via BLE connectivity with mobile devices. Leveraging the advanced features of BLE 5.0, AmbiTag Blue offers significant advantages over conventional USB-based loggers. By harnessing the power and efficiency of BLE technology, AmbiTag Blue provides a reliable and versatile solution for real-time environmental data logging. The field experiments demonstrated the feasibility of the developed logger.

关键词： Bluetooth Low Energy Data logger Internet of Things

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Applying Language Models for Recognizing and Normalizing Sensitive information from Electronic Health Records Text Notes

Applying Language Models for Recognizing and Normalizing Sen...

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2024 International Workshop on Deidentification of Electronic Medical Record Notes

作者： Huang, Sheng-Xuan Cheng, Hung-An Li, Zheng-Hao Coll Elect Engn & Comp Sci Dept Elect Engn Taipei Taiwan Natl Kaohsiung Univ Sci & Technol 415 Jiangong Rd Kaohsiung 807618 Taiwan

ISBN: (纸本)9789819779659;9789819779666

Electronic medical records (EMRs) are often populated with private or confidential information related to patients. In the setting of the hospital environment, fragments of information could be collected across various electronic health record systems that could be used to deduce the true identities of patients mentioned in EMR text notes. Therefore, applying a de-identification procedure is a crucial means of safeguarding privacy, especially when handling EMR text notes. By preventing the identification of individuals and reducing the risks associated with personal information, it contributes to regulatory compliance, facilitates research and data sharing, and mitigates the risk of data misuse. In 2023, the Ministry of Education in Taiwan sponsored a large nationwide competition, AI-CUP 2023-privacy Protection and standardization of EMR Challenge to seek automatic de-identification and standardization solutions. As one of the participating teams, we first tried to apply zero-shot, one- shot, and few-shot configurations based on ChatGPT, but the preliminary experimental results showed that ChatGPT cannot follow the prompt to generate the prediction results of its recognized SHIs based on the official output format. Therefore, we decided to primarily utilize the Pythia-160m-deduped pre-trained model to develop our system. Through multiple experiments, the developed system achieved official micro- and macro-F-scores of 0.744356 and 0.5960788 respectively on the PPSEMR test set.

关键词： Electronic medical records text notes Sensitive health information Pythia ChatGPT de-identification

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