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

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An Integrated Wildfire Detection, Monitoring, Warning and Emergency Response System Based on Unmanned Aerial Vehicles

An Integrated Wildfire Detection, Monitoring, Warning and Em...

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Intelligent systems Conference (IntelliSys)

作者： Aretoulaki, Eleni Ponis, Stavros Plakas, George Tzanetou, Dimitra Kitsantas, Antonios Natl Tech Univ Athens Sch Mech Engn Athens Greece

ISBN: (纸本)9783031477171;9783031477188

Nowadays, the adverse impacts of climate change are visible on a global scale. Especially natural disasters, such as wildfires, tend to be exacerbated by unusual climatic conditions. The ever-increasing rate of unpredictable natural disasters which endanger both the environment and human lives, in addition to the obsolesce, inadequacy and inefficiency of current crises management and evacuation methods have brought to the surface the need for a more innovative approach to forest fire prevention and response as well as mitigation of its socioeconomic and environmental consequences. This paper presents an integrated methodology for the development of an early warning and wildfire management system, focusing on the rapid detection of the initial source of the fire, the estimation of fire propagation as well as the facilitation of its immediate containment and extinguishing before it spreads and cannot be controlled and the timely evacuation of endangered areas. The proposed system utilizes emerging Industry 4.0 technologies, i.e., Unmanned Aerial Vehicles (UAVs), Internet of Things (IoT) and Big Data Analytics for data collection, processing and analysis as well as Social Networking technologies able to facilitate two-way communication between residents or visitors of a forested suburban area and the local authorities. The proposed solution after its successful implementation is expected to complement preexisting governmental civil protection mechanisms and provide a plethora of socioeconomic and environmental benefits.

关键词： Unmanned aerial vehicles (UAVs) Internet of things (IoT) Crisis management Cloud based platforms Humanitarian logistics Wildfire detection

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Expediting Investigation of Examinations Malpractice Involving Suspected Jointly Written Answer Scripts 13th

Expediting Investigation of Examinations Malpractice Involvi...

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13th Computer Science Online Conference

作者： Zimba, Gilbert Nyirenda, Mayumbo Univ Zambia Dept Comp Sci Lusaka Zambia

ISBN: (纸本)9783031705946;9783031705953

Examination malpractice, particularly involving external assistance in answering questions, poses a significant challenge for Examining Boards. Detecting cases where candidates receive help in writing their answers, resulting in jointly written answer scripts with different handwriting, is a complex and time-consuming process. Currently, this task falls to handwriting experts who employ subjective methods to examine documents, leading to delays and prolonged investigations. The study proposed the development of a web-based application to streamline the process of collecting handwriting samples on follow-ups on who might have been involved in the malpractice, reducing the need for physical travel to examination centers. Furthermore, the study sought to incorporate AI into the process of handwriting identification and verification. AI offers a more objective and efficient approach. To achieve these objectives, the study collected information through a questionnaire from members of staff at the Examinations Council of Zambia (ECZ) who are involved in handling Malpractice cases. The developed web-based application using the Django framework mitigated the need for physical travel to examination centers resulting in reduced delays. In the Machine Learning Model for writer identification, the prediction was 89% for True Positives and 10% for False Positives. In the Machine Learning Model for Binary Classification, the prediction was 52% on True Positives and 67% on True Negatives. The AI Model for writer verification (Binary classification) did not perform well, this may be because the Model was trained in the Hindi alphabet.

关键词： Malpractice AI Django Framework Machine Learning Model Jointly Written Answer Scripts

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The Uniform Anti-plagiarism System (JSA): The Role of Layout in Diploma Thesis Page Classification 20th

The Uniform Anti-plagiarism System (JSA): The Role of Layout...

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20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Karas, Daniel Spiewak, Martyna Natl Informat Proc Inst Warsaw Poland

ISBN: (纸本)9783031665936;9783031665943

The examination of thesis diplomas for instances of plagiarism can be a difficult and time-consuming task. However, some parts of these documents are more important and are more susceptible to being plagiarized than others. This work investigates four distinct approaches to the detection and exclusion of such irrelevant fragments from the process of plagiarism detection to reduce the cognitive load inflicted upon supervisors. We evaluate the relevance of image and text data on solving this task by exploring models that are multimodal, purely image-based, purely text-based, and based on handcrafted features.

关键词： Visual document understanding Transformers Multimodal Neural network

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Clinical Applications of Rehabilitation Robots Among Patients With Stroke 18th

Clinical Applications of Rehabilitation Robots Among Patient...

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Shin, Joon-Ho Minist Hlth & Welf South Korea Dept Rehabil Med Natl Rehabil Ctr Samgaksanro 58 Seoul 01022 South Korea Natl Rehabil Ctr Translat Res Program Rehabil Robots Seoul South Korea

ISBN: (纸本)9783031449802;9783031449819

There is growing evidence to support robotic rehabilitation for upper limb among stroke patients. This paper reviews the evidence of robotic rehabilitation depending on the types of rehabilitation robotic devices. A comparison study of end-effector and exoskeleton robots in chronic stroke patients with moderate-to-severe upper limb impairment found that improvements in activity and participation were significantly better in the end-effector group than exoskeleton group. Another comparison study which compared the effectiveness of active-assistive robot versus passive robot (PSV) found discrepant results, with the PSV group showing better outcomes in participation-related measures. Taken together, robotic rehabilitation for upper limb among stroke patients is a promising approach, however further research is needed to optimize the design and application of robotic devices.

关键词： Robotic rehabilitation Stroke Upper limb

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Data-Driven Urban Air Mobility Flight Energy Consumption Prediction and Risk Assessment

Data-Driven Urban Air Mobility Flight Energy Consumption Pre...

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Intelligent systems Conference (IntelliSys)

作者： Ayalew, Yonas Bedada, Wendwosen Homaifar, Abdollah Freeman, Kenneth North Carolina A&T State Univ Greensboro NC 27411 USA NASA Ames Res Ctr Mountain View CA 94035 USA

ISBN: (纸本)9783031477140;9783031477157

The current technological advancements revolutionizing the concept of Urban Air Mobility (UAM), has a concurrent need to quantify the operational safety of these vehicles in terms of their associated risk. Providing safety certification of flight operations of UAM vehicles is critical as the concept relies on battery powered electrically Vertical Takeoff and Landing (eVTOL) vehicles, to operate in the current Air traffic control. In this paper, a data-driven method for UAM vehicle energy consumption prediction and risk quantification with conditional value-at-risk based on energy consumption distribution is presented. Significant factors affecting energy consumption, such as density altitude, aircraft design, airspeed, and collision avoidance algorithms, are considered in the data-driven based energy consumption prediction of multiple eVTOL flights. Additionally, a risk metric was deployed to evaluate the risk associated with worst case energy dissipating flights. Our result shows that the proposed approach provides a generalized method to quantify operational safety of UAM network over a given region.

关键词： Data-driven Density altitude Electrically vertical takeoff and landing Energy consumption Flight risk assessment Risk Urban air mobility

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New Vectors, Models, Trends and Patterns in Ransomware Attacks 13th

New Vectors, Models, Trends and Patterns in Ransomware Attac...

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13th Computer Science Online Conference

作者： Brenishki, Angel Rusev, Rumen Shoilekova, Kamelia Angel Kanchev Univ Ruse 8 Studentska Str Ruse 7000 Bulgaria

ISBN: (纸本)9783031702990;9783031703003

The ransomware is evolving and becoming more aggressive, specialized and dangerous. The latest attacks and trends show that this type of malware is more dangerous and sophisticated than ever. This type of malware holds data hostage by encrypting it until ransom money is paid. And as cybercriminals become more sophisticated, the attacks become more frequent and lucrative.

关键词： ransomware malware social engineering encryption cybersecurity cybercrime

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A Decomposed Fuzzy Analytical Hierarchy Process to Assess the Risks of Autonomous Vehicles

A Decomposed Fuzzy Analytical Hierarchy Process to Assess th...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Aslantas, Meltem Gundogdu, Fatma Kutlu Natl Def Univ Ataturk Strateg Studies & Grad Inst Ind Engn Dept TR-34334 Istanbul Turkiye Natl Def Univ Turkish Air Force Acad Ind Engn Dept TR-34149 Istanbul Turkiye

ISBN: (纸本)9783031671944;9783031671951

Intelligent Transportation System (ITS) is a new field that integrates transportation management and control, infrastructure, operations, and policies. ITS has focused on autonomous vehicles (AVs) to eliminate the need for drivers, promote traffic control, reduce transportation and infrastructure expenses, and enhance customer convenience in recent years. However, AVs pose different uncertainties and risks due to their advanced technology, performance under diverse road conditions, and increased vulnerability to security threats. Fuzzy set theory is considered an appropriate method for evaluating AV risks that encompass uncertainties. Decomposed fuzzy sets (DFS), which is recently proposed, are a useful theory that involves posing positive and negative inquiries to assist decision-makers in providing more efficient and consistent responses. In this study, the main risk factors of AVs have been determined. The most and least critical risk factors of Avs have been found based on decomposed fuzzy analytic hierarchy process enhances the safety of outcomes when used with DFS, primarily relying on the pairwise comparison technique. A comparison of techniques was conducted utilizing the classical Analytic Hierarchy Process (AHP) approach. The defined order of risks is considered as beneficial for policy makers, politicians, vehicle technology manufacturers, and other stakeholders.

关键词： Autonomous Vehicles AHP Risk Assessment Decomposed Fuzzy Sets

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Determining the Digits of Turkish Sign Languages Using Deep Learning Techniques 1

引用

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

作者： Karatas, Emine Cinarer, Gokalp Yozgat Bozok Univ Yozgat Turkiye

ISBN: (数字)9783031628719

ISBN: (纸本)9783031628702;9783031628719

Sign language is a physical language that enables people with disabilities to communicate with each other by using hand and facial movements as a whole to express themselves. It is very important that sign language is learned by everyone and used as a communication tool for the disabled to adapt to social life and to express themselves easily. For this reason, people's learning of sign languages, which are specific to the country's spoken language, will increase the quality of life of people with disabilities. In this study, 12981 images of the numbers 0-10 in Turkish Sign Language taken from different angles were used as a data set. In the last stage of the study, the detection of digits over images was carried out with CNN, Resnet-50, VGG-16, Densenet-201, and Inception-V3 deep learning architectures. In the study, an effective model of deep learning algorithms is proposed to determine which number an action corresponds to in sign language. Examining the models, VGG-16 and Densenet-201 were the architectures that gave the highest accuracy with 100% accuracy. After these architectures, Inception-V3 architecture comes with 99.91% success in determining the numbers. It has been seen that it is very successful in detecting numbers in Turkish Sign Language using deep learning models.

关键词： Hand Gesture Recognition Sign Language Translation Deep Learning

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A Survey on Personalized Movie Recommendation System Using Machine Learning 8th

A Survey on Personalized Movie Recommendation System Using M...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Teppalwar, Vansh Sahoo, Kanhu Charan Jaiswal, R. C. Munot, Mousami, V SCTR Pune Inst Comp Technol Pune India

ISBN: (纸本)9789819713196;9789819713202

In the era of big data, recommender systems (RS) have emerged as vital information filtering tools, particularly in digital entertainment and e-commerce domains. This survey paper delves into the intricate realm of RS, with a primary focus on movie recommender systems. In an age where the Internet inundates users with unfiltered information, RSs act as indispensable software tools, adept at validating and ranking available options while aligning with user preferences. It meticulously evaluates filtering techniques, including collaborative, content-based, and hybrid methods.

关键词： Recommender systems Personalized movie recommendation

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Implementing a Smart Low-Cost System for Diagnosing Bacteria in Women

Implementing a Smart Low-Cost System for Diagnosing Bacteria...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Sabir, Mohannad K. Ibraheem, Muntaha R. Hameed, Rabab A. Al-Shamma, Omran Univ Baghdad Al Khwarizmi Coll Engn Biomed Dept Baghdad Iraq Univ Informat Technol & Commun Baghdad Iraq

ISBN: (纸本)9783031671913;9783031671920

A checking test known as the bacteria culture test is required to determine harmful bacteria. This traditional isolation and cultivation technique often used in clinical microbiology is time-consuming and laborious. Thus, it is essential to implement new smart, efficient, and cost-effective tools for accurate and rapid identification of bacteria. This work developed a smart low-cost system for diagnosing five types of bacteria in a woman's vagina. The crucial components of the proposed system comprise a five-sensor array, a controller (Arduino board), and a computer (laptop). Furthermore, the system software includes data saving, plotting code, and an artificial neural network for diagnosing bacteria. Three commonly used classifiers were used for comparative purposes: a Support Vector Machine, Random Forest, and Logistic Regression. The system with the Random Forest classifier achieved the highest scores in accuracy, precision, and F1 score, while the Logistic Regression classifier performed theworst. The proposed system added a clinically smart and helpful tool for the diagnosis of bacteria systems and the decision-making process.

关键词： Bacteria Diagnosis Smart systems Sensor Array Arduino Applications Machine Learning Classifiers

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