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

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Decomposed Fuzzy Analytical Hierarchy Process Method for Business Processes Management Software Selection 1

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Sarucan, Ahmet Baysal, Mehmet Emin Engin, Orhan Konya Tech Univ Dept Ind Engn Konya Turkiye

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

Software has been developed to help organizations manage their business processes. This is called Business Process Management (BPM) software. Organizations may have to make a decision whether to improve their business processes with the help of this software or to replace one software module with another software module. It is important to determine the criteria to satisfy the needs and get the opinions of the decision makers to make an efficient decision in this problem. For this purpose, Decomposed Fuzzy Analytic Hierarchy Process (DF-AHP) method is proposed in this study. The applicability of the proposed method in a financial institution is demonstrated. It was found that the module used by the organization is systematically backward. It needs to be changed. The business process life cycle of the financial institution has been evaluated in 6 main groups as criteria. These groups are Modeling, Design, Deployment, Execution & Operation, Monitoring & Control and Analysis. The business process management software identified were Activiti, Bonita, jBPM, Process Maker, uEngine, Camunda and YAWL. As a result, jBPM was selected as the best software in the Business Process Management category.

关键词： Business Processes Management Decomposed Fuzzy Analytic Hierarchy Process Multi-Criteria Decision-Making

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"Slice and Dice": A Corpus-Based Study of Russian Binomials 9th

"Slice and Dice": A Corpus-Based Study of Russian Binomials

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Maria, Kochneva Tatiana, Petrova St Petersburg Univ St Petersburg Russia

ISBN: (纸本)9789819732883;9789819732890

This article deals with idiomaticity of a special type of collocations-binomials-on Russian language material. A corpus study was conducted to obtain quantitative data on the frequency, fixity, and the strength of attraction between words of 147 Russian binomials with the structure "A i B" (where A, B are nouns, and "i" is a coordinating conjunction "and"). Statistical methods were used to reveal the measures of mutual information (MI) and logarithmic probability (log-likelihood). The data analysis allows us to conclude that the process of ideomatization is influenced by both the frequency of the entire collocation and the frequency of the words included in this collocation. Therefore, the collocative strength of the binomial was singled out as a statistical sign of idiomaticity. Overall results support the idea of a holistic storage of binomials in mental lexicon. High-frequency binomials with collocative power are included in the process of ideomatization and are stored in the mental lexicon as a whole.

关键词： Idiomaticity Ideomatization Binomials Mental lexicon Statistical measures Russian

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AC-MambaSeg: An Adaptive Convolution and Mamba-Based Architecture for Enhanced Skin Lesion Segmentation 7th

AC-MambaSeg: An Adaptive Convolution and Mamba-Based Archite...

引用

7th International Conference on Green Technology and Sustainable Development

作者： Viet-Thanh Nguyen Van-Truong Pham Thi-Thao Tran Hanoi Univ Sci & Technol Sch Elect & Elect Engn Dept Automat Engn Hanoi Vietnam

ISBN: (纸本)9783031761966;9783031761973

Skin lesion segmentation is a critical task in computer-aided diagnosis systems for dermatological diseases. Accurate segmentation of skin lesions from medical images is essential for early detection, diagnosis, and treatment planning. In this paper, we propose a new model for skin lesion segmentation namely AC-MambaSeg, an enhanced model that has the hybrid CNN-Mamba backbone and integrates advanced components such as Convolutional Block Attention Module (CBAM), Attention Gate, and Selective Kernel Bottleneck. AC-MambaSeg leverages the VMamba framework for efficient feature extraction, while CBAM and SelectiveKernel Bottleneck enhance its ability to focus on informative regions and suppress background noise. We evaluate the performance of AC-MambaSeg on diverse datasets of skin lesion images including ISIC2018 and PH2;then compare it against existing segmentation methods. Our model shows promising potential for improving computer-aided diagnosis systems and facilitating early detection and treatment of dermatological diseases. Our source code is available at: https://***/vietthanh2710/AC-MambaSeg.

关键词： Skin Lesion Segmentation Visual Mamba Convolution CBAM Attention gate Selective Kernels

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Machine Learning-Driven Three-Phase Current Relay Protection System for Small Transient Periods in Sustainable Power systems 2nd

Machine Learning-Driven Three-Phase Current Relay Protection...

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2nd International Conference on Forthcoming networks and Sustainability in the AIoT Era (FoNeS-AIoT)

作者： Ahmed, Saadaldeen Rashid Hussain, Abadal-Salam T. Shah, Pritesh Sulaiman, Sazan Kamal Itankar, Nilisha Taha, Taha A. Ahmed, Omer K. Alayan Univ Coll Engn Artificial Intelligence Engn Dept Nasiriyah Iraq Bayan Univ Comp Sci Dept Erbil Kurdistan Iraq Al Kitab Univ Tech Engn Coll Dept Med Instrumentat Tech Engn Kirkuk Iraq Symbiosis Int Deemed Univ SIU Symbiosis Inst Technol SIT Pune Campus Pune 412115 Maharashtra India Knowledge Univ Coll Engn Dept Comp Engn Erbil Iraq Northern Tech Univ Unit Renewable Energy Kirkuk Iraq

ISBN: (纸本)9783031628801;9783031628818

This study focuses on improving the effectiveness of three-phase current relay protection systems, which is a significant problem. It is achieved through the use of machine learning techniques. The primary objective is to enhance defect detection capabilities by utilizing artificial neural networks (ANNs). Especially during brief, intermittent durations. The process encompasses ameticulous design of the relay protection system, delineating crucial elements such as relays, sensors, and communication infrastructure. Artificial neural networks (ANNs) are vital to machine learning methodologies since they are employed to represent intricate connections within present patterns. This gets around the troubles that emerge. Encompassing conventional relay protection techniques. The dataset employed for training and testing comprises numerous transitory circumstances. It facilitates the development of strong and resilient model training. The results exhibit amazing performance increases. With accuracy surpassing 95%. The proposed technique is demonstrated to be superior by conducting a comparative study against traditional relay protection systems. The system displays resilience and generalization. Including sensitivity to parameter adjustments. It affirms its efficacy in varied operational situations. Future work requires further development of the machine learning model. Dataset expansion. Include in the research of new technologies for real-time application situations. This research contributes to enhancing relay protection systems and supporting grid stability. Including dependability in contemporary power networks.

关键词： 11 kV Power System MATLAB SimPowerSystem Three-phase Current Current Relay Pickup Current Circuit Breaker

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The Classification of the Children Capacity by Cluster 1

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Narantuya, Jamyandorj Ganbat, Tsend Narantuya, Munkhjargal Mongolian Acad Sci Brain & Mind Res Inst Ulaanbaatar Mongolia Univ Otgontenger Ulaanbaatar Mongolia Natl Univ Mongolia Ulaanbaatar Mongolia

ISBN: (数字)9789819733057

ISBN: (纸本)9789819733040;9789819733057

The research is focused on the classification of children capacity that digital divide depending on gender ages, registration time of tasks performance on the smart devices, and comprehension for teacher's tasks in preschool children. Research data is comprehension and tasks performance of 120 children at 3-5-years-old preschool children. Using machine learning cluster analysis on the data, it was divided into three clusters, first cluster was included 4-5-years-old participants, and second cluster was included 3-year-old participants. We determined that the capacity of the participants, such as similarity to the age and gender categories of the participants, personality, and common mode. We suggest that research can be used by teachers, educators, and educational decision-makers in the educational system, to produce the assessment of children's abilities by age and gender, and to create an evaluation model for monitoring and evaluating the activities of teachers and students. Also, it can be used by children's app developers, young researchers, and the proper use of smart devices by parents of young children.

关键词： Data analysis HCPC Clustering Machine learning

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HAPmamba: Linear-Time Sequence Modeling for Terrain Classification by Legged Robots 27th

HAPmamba: Linear-Time Sequence Modeling for Terrain Classifi...

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27th International Conference on Climbing and Walking Robots and Mobile Machine Support Technologies (CLAWAR)

作者： Wilinskil, Michal Lysakowski, Mikolaj Walas, Krzysztof Poznan Univ Tech Inst Robot & Machine Intelligence Ul Piotrowo 3A PL-60965 Poznan Poland IDEAS NCBR Warsaw Poland

ISBN: (纸本)9783031707216;9783031707223

This paper proposes a neural network model for terrain classification using force/torque signals registered with sensors mounted on robot feet. The proposed model is based on the latest architecture for Linear-Time Sequence Modeling using Selective State Spaces, called Mamba. We obtained lightweight models with very low inference times, which are two times faster than comparable transformer-based solutions. We evaluated HAPmamba alongside other state-of-the-art approaches, and while the classification measures are comparable, HAPmamba is the fastest among all evaluated models.

关键词： Legged robots Deep learning methods haptic data terrain classification time sequence

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The Role of Digitalization in Entrepreneurship 4th

The Role of Digitalization in Entrepreneurship

引用

4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Abdellah, Hadj-Ali Sidi Mohamed Ben Abdellah Univ LIREFMO Lab Dhar El Mahraz Fez Morocco

ISBN: (纸本)9783031686597;9783031686603

Since the appearance of the Internet for the general public around 1995, our habits, approach to consumption, modes of production in a global manner have evolved significantly, which has pushed companies to begin their digitalization. The concept of digital entrepreneurship has become widespread during this last period, because it expresses the implementation of new projects, or the transformation of existing projects using digital technologies. The current business environment has also seen a major shift towards digital environments. Today, digital is profoundly changing the managerial function, customer relations are becoming digital, new technologies are appearing, and models based on sharing and collaboration are emerging. The arrival of new competitors also threatens the profitability of organizations;Generally, we are more and more connected, the objects around us are also connected, this technological evolution has been accompanied by new behaviors of Internet users, who have new expectations, access information more easily, as a result they need increasingly volatile and ephemeral Instant information, as well as extensive and constantly renewing digital services. Managerial action can be strengthened by the digital revolution;and the company can take digital as a central core of decisions and strategic positioning. This article has tried to enrich this stream of research through the treatment of 3 axes: the first axis was devoted to a theoretical model to better approach entrepreneurship and the managerial function within organizations the second axis mentioned the role of the digital revolution for the smooth running of the managerial function and finally the third axis tried to emerge the role of digital at the business level in periods of crises such as the case of covid 19. This work will be enriched by a questionnaire on Google forms and the results will be processed by SPSS software.

关键词： entrepreneurship management digital covid-19 SPSS

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Determinants Associated with Treatment Discontinuation in Tacna Health Network Tuberculosis Patients 12th

Determinants Associated with Treatment Discontinuation in Ta...

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

作者： Tapia-Tenorio, Alex Eduardo Laura-De la Cruz, Kevin Mario Ballon-Bahamondes, Roberto Daniel Mendoza-Del Valle, Luz Anabella Koctong-Choy, Amanda Hilda Cardenas-Rueda, Pedro Ronald Tozo-Burgos, Jose Giancarlo Univ Nacl Jorge Basadre Grohmann Tacna Peru Univ Privada Tacna Granada Spain Univ Nacl Mayor De San Marcos Lima Peru

ISBN: (纸本)9783031602177;9783031602184

The objective of this study was to ascertain the factors contributing to medication non-adherence among tuberculosis patients within the Tacna Health Network. The present study used a cross-sectional design with a retrospective case-control approach. A total of thirteen patients were documented as having experienced abandonment at multiple facilities. Subsequently, we conducted visits to these respective locations. The selection of these locations was not based on randomization, but rather on considerations of convenience. The group of 117 patients who completed the treatment were utilized as the control group. The discontinuation of tuberculosis treatment has been found to be associated with various factors, including the assessment conducted by a multidisciplinary team consisting of doctors, nurses, nutritionists, psychologists, and social workers. Additionally, irregularities in the first and second phases of treatment, as well as the number of days of non-attendance during these phases, the duration between non-attendance and the initial visit, and the frequency of visits in the first and second phases, have also been identified as contributing factors.

关键词： determinants TB medication desertion

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An Approach to Detect Violations of Social Distancing Norms in the Public Domain 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Chandak, M. B. Rawat, Sunita Shri Ramdeobaba Coll Engn & Management Nagpur Maharashtra India

ISBN: (数字)9789819713264

ISBN: (纸本)9789819713257;9789819713264

The COVID-19 virus is an ongoing global crisis with more than 247,000 deaths globally. Almost all countries globally have concluded the fact that prevention is the best strategy. Also in some countries, the lack of medical facilities has increased the importance of prevention. "Social distancing" has been one of the best methods to avoid the virus spreading globally. The presented research work illustrates the framework for monitoring and automation finding the social distancing problem at public locations. The designed model is based on "deep learning" and "object detection" approaches. The input to the framework is CCTV surveillance camera recordings. The latest tool from Amazon, namely "Amazon Object Rekognition [AOR]", is used in the implementation of the algorithm designed for detecting the violation of social distancing norms. The AOR detects the "humans" as an object from the surveillance video. The designed framework is capable of computing the distance between two objects and classifying the distance as "high risk", "low risk" and "safe distance". A details analysis in the form of case studies for different locations is presented in the research work. The system design also creates alert indicators for safety and prevention.

关键词： Social distancing Object detection Object tracking COVID-19 Amazon Rekognition Video surveillance

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Analysis of the Urban Air Mobility for the Unmanned Aerial Vehicle

Analysis of the Urban Air Mobility for the Unmanned Aerial V...

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International Scientific and Technical Conference on Integrated Computer Technologies in Mechanical Engineering - Synergetic Engineering (ICTM)

作者： Yena, Maksym Bykov, Andriy Karatanov, Oleksandr Natl Aerosp Univ Kharkiv Aviat Inst 17 Chkalova St UA-61070 Kharkiv Ukraine

ISBN: (纸本)9783031614149;9783031614156

The research topic Unmanned Aerial Vehicle (UAV) Traffic Management Models, Methods and Information Technology concerns the development and testing of technologies to help control and manage UAV traffic to ensure safe, efficient and controlled flights. This is important to ensure the safety of the skies, as well as the efficient use of airways and to prevent collisions and conflicts. The study includes the study of traffic management models and algorithms, as well as the evaluation of their effectiveness and applicability in real conditions. The study briefly describes the main aviation groups that can be involved in providing flight traffic management, the main problems in the USA and possible problems in Ukraine, and also considers the main ways of solving problems and implementing a centralized, competitive system of monitoring and regulation of small aviation elements. The main mathematical features and limitations are analyzed. The goal of this research is to contribute to the improvement of UAV traffic management by proposing innovative solutions and strategies. By enhancing the quality of traffic control, the safety of airspace operations can be ensured, collisions and conflicts can be prevented, and the efficient utilization of airways can be achieved. The findings of this study have the potential to benefit both the aviation industry and regulatory bodies involved in UAV traffic management.

关键词： Traffic Management Unmanned Aerial Vehicles Automated Control Flight Path Optimization Monitoring and Detection systems Air Traffic Safety Intelligent Flight Control Aviation Unmanned Aviation Devices Navigation Route Planning Efficiency Security Control UTM

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