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2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Maharjan, Aditi Yadav, Prabhesh Rai, Chulindra Mandal, Ajay Kumar Basavaraju, D.R. Computer Science and Engineering- Internet of Things Faculty of Engineering & Technology' Karnataka Bengaluru India

ISBN: (纸本)9798350367461

The global airline industry serves over two billion traveller annually and faces continuous challenges about luggage handling. Lost luggage, mishandling of luggage are most common problem for the traveller. With the number of traveller even small percentage of baggage mishandling translates to significant number of effected *** system examines the current implementation of Amazon Web Services (AWS) and Radio Frequency Identification (RFID) in in luggage handling and proposes the adoption of Internet of Things (IoT) technology to develop reusable luggage tags. The main goal of this paper is to explore the problems and limitations in existing luggage handling systems and propose and IoT-based solution to enhance the baggage tracking efficiency. Existing systems did not provide the facility to name the luggage in the application or end-user interfaceThe research focuses on three main goals: evaluating the effectiveness of current RFID and AWS-based systems, developing a reusable IoT-enabled luggage tag and also evaluating the impact on reducing mishandling of luggage. The proposed system integrates smart, reusable tags with IoT capabilities allowing real time tracking of the *** proposed system demonstrated that the IoT based luggage tracking system outperformed RFID systems in terms of tracking efficiency and accuracy. Overall, integrating IoT technology into luggage tracking systems provides a better solution to the challenges faced by the passenger of air travel. The system also reduces the changes of lost luggage incidents and promotes environmental sustainability by the use of reusable tags. © 2024 IEEE.

关键词： Baggage handling

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Syllable and Morpheme Segmentation of Macedonian Language 46

Syllable and Morpheme Segmentation of Macedonian Language

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46th ICT and Electronics Convention, MIPRO 2023

作者： Mitreska, M. Zdravkova, K. Faculty of Computer Science and Engineering Skopje Macedonia

ISBN: (纸本)9789532331042

Communication is the key to human development. Approximately 5% of the world's population experience some form of hearing disability. Modern assistive devices and technologies can improve the communication skills of hearing impaired people by transcribing the speech into text. The creation of such an application depends on the language specific morphosyntactic properties. It usually starts with the syllabification. The research presented in this paper focuses on the development of an automatic system for rule-based and sonority-based syllable and morpheme segmentation of Macedonian language, which can be easily incorporated into an efficient speech recognition system. The segmentation rules for breaking the words down into syllables and into morphemes were created according to the new orthography of the Macedonian language. For the sonority-based approach, a novel phonological distance measure was introduced capable of efficient syllable clustering. The implementation of the framework is developed in Python using several data structures for optimized performance and CPU usage. Both segmentation strategies were evaluated using the electronic lexicon consisting of more than one million words. A linguistic expert was consulted during the entire process. The consistency of the obtained results promises their sustainability for further speech processing applications. © 2023 MIPRO Croatian Society.

关键词： Speech recognition

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Fingerprint Fraud Explainability Using Grad-Cam for Forensic Procedures 23

Fingerprint Fraud Explainability Using Grad-Cam for Forensic...

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23rd International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2024

作者： Manai, Elyes Mejri, Mohamed Fattahi, Jaouhar Department of Computer & Software Engineering Faculty of Science and Engineering Laval University Quebec Canada

ISBN: (纸本)9781643685380

This paper investigates the application of GradCAM, an explainable AI (XAI) technique, to enhance the transparency and precision of fingerprint authentication systems in forensics, particularly in detecting fingerprint mutilation-a common method used to evade biometric security measures. Employing the SOCOfing dataset, which contains both unaltered and synthetically altered fingerprint images, we apply GradCAM to visualize and understand the decision-making process of a convolutional neural network (CNN) model trained to recognize and classify these alterations. Our study not only demonstrates the model's effectiveness in identifying different types of fingerprint modifications but also identifies areas where the model's performance can be enhanced. Through detailed visual analysis, we uncover the model's focus points and assess its reliability across various alteration types and difficulty levels. The insights gained underline the potential of XAI in improving the robustness and reliability of biometric verification systems, paving the way for more secure and equitable AI applications in high-stakes environments. © 2024 IOS Press. All rights reserved.

关键词： Convolutional neural networks

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Self-Learning Robot Manipulator Controller Using Reinforcement Learning

Self-Learning Robot Manipulator Controller Using Reinforceme...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Xhin, Ong Yu Jo, Hudyjaya Siswoyo Swinburne University of Technology Faculty of Engineering Computer & Science Sarawak Malaysia

ISBN: (纸本)9798350350821

Traditionally, robot control has relied on mathematical solutions, particularly inverse kinematics (IK), to determine the joint angles needed for a desired end-effector pose. However, these solutions face significant challenges as robots increase in complexity with higher degrees-of-freedom (DoF) and adaptability requirements. This work introduces an approach for controlling robot manipulators by addressing the IK problem using the artificial intelligence (AI) technique. In this paper, a deep reinforcement learning approach is proposed to solve the IK problem for a 6-DoF industrial robot manipulator. The Deep Deterministic Policy Gradient (DDPG) algorithm is employed to train an agent capable of learning the robot's motion, allowing for random initial and target positions and orientations. Several reward functions are implemented to enhance the accuracy of the robot's movement towards the desired position and orientation. This proposed approach demonstrates a high success rate and low mean error, outperforming other state-of-the-art methods. Furthermore, the approach is validated on a physical robot, confirming its practical applicability and effectiveness. © 2024 IEEE.

关键词： Deep reinforcement learning

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Enhancing Decisions of Goalkeeper and Kicker Players in the RoboCup 2D Simulation League through Behavioral Cloning 20

Enhancing Decisions of Goalkeeper and Kicker Players in the ...

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20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024

作者： Nasiri, Mohammad Hesam Zonouzi, Seyed Hassan Majid Salimi-Badr, Armin Shahid Beheshti University Faculty of Computer Science and Engineering Tehran Iran

ISBN: (纸本)9798350383942

RoboCup is recognized as a landmark project in the robotics and artificial intelligence industry, providing a crucial platform for the advancement of research and innovations in autonomous and multi-agent systems. This study delves into the use of behavioral cloning in the RoboCup 2D Simulation League to imitate the best decisions and improve the performance of the goalkeeper along with the kicker players. To improve the performance of our soccer team in the league, we have developed a new approach that combines behavioral cloning and game log parsing. To achieve this, we played extensively against the champion team Helios and analyzed the actions and decisions of their goalkeeper and kicker players. This data was used to create a large dataset that our team could use to improve their imitation skills. Our innovative log generator tool and game logs parser made the labeling process easier and will also be useful for future research in the league. Novel features are extracted to represent the state of the game considering the limitations of each player including their head direction along with their field of view. Next, a neural structure is trained to imitate the behavior of kicker players and the goalkeeper. Moreover, the time limit for decision-making in each turn is considered. This study showed that using behavioral cloning for imitation learning noticeably improved our team's actions and decisions due to the enhancement of the number of accurate passes, on-target shoots, and saves by the goalkeeper. © 2024 IEEE.

关键词： Decision making

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Research on API Sequence Recommendation Based on Code Property Graph 5

Research on API Sequence Recommendation Based on Code Proper...

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5th International Conference on computer, Big Data and Artificial Intelligence, ICCBD+AI 2024

作者： Luo, Xianchao Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9798331533991

The utilization of APIs not only enhances software reusability but also improves development efficiency and reduces costs. However, with the continuous increase in the number of APIs, developers face difficulties in quickly recalling and comprehending the appropriate API call sequences and their constraints. Thus, there is a need for an efficient API sequence recommendation tool. The key task in achieving efficient API sequence recommendation is to understand the semantic structure of the code context. However, most researchers currently lack an analysis of program structure in API sequence recommendation studies, leading to a decrease in the accuracy of these tools. To achieve a deeper understanding of the semantic context of code, this paper employs semantic syntax information and incorporates control structure information to improve the accuracy of API sequence recommendations. Specifically, this study first employs early fusion techniques based on the abstract syntax tree to incorporate control flow edges and data dependency edges - two types of heterogeneous edges - to construct a new representation of code known as a code property graph. This graph is then used to analyze the semantic syntax information and control structures of the code. Subsequently, a relational graph attention network model is employed to analyze the code property graph. Experimental results indicate that the accuracy of API sequence recommendations significantly improves with the incorporation of code control structures. © 2024 IEEE.

关键词： computer software reusability

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A comprehensive review of effective parameters to improve the performance of the Savonius turbine using a computational model and comparison with practical results

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Water-Energy Nexus 2024年第1期7卷 266-274页

作者： Jebelli, Ali Lotfi, Nafiseh Saeid Zare, Mohammad Yagoub, Mustapha C.E. Department of Engineering and Design Robotic Century Inc Alberta Canada Faculty of New Science and Technologies Tehran University Tehran Iran School of Electrical Engineering and Computer Science University of Ottawa ON Canada

Amidst growing global concerns over climate change and escalating greenhouse gas emissions from fossil fuels, the pursuit of renewable energy sources has become critical. This study focuses on harnessing hydropower using Savonius turbines, which are known for their efficiency in generating energy at lower flow rates. However, the intrinsic low efficiency of these turbines necessitates precise optimization tailored to specific river or channel conditions. In this research, we optimized the performance of Savonius turbines by analyzing key parameters such as the height-to-diameter ratio, blade twist, and the integration of multi-stage configurations with deflectors. Our findings reveal significant efficiency improvements through strategic modifications. Specifically, by reducing the height-to-diameter ratio from 1.2 to 0.8 and maintaining a Tip Speed Ratio (TSR) of 0.6, the power coefficient increased by 15%, from 0.33 to 0.38. Further optimization was achieved by adjusting the blade twist angle, with an increase in power coefficient up to an optimal angle of 45°, beyond which efficiency declined. Implementing a two-stage turbine setup with a 90-degree phase difference between stages further improved the power coefficient to 0.51 at the same TSR. Additionally, the use of deflectors, particularly at a 90° angle, significantly boosted the power coefficient, highlighting their effectiveness in optimizing water flow impact on the turbine. This comprehensive study not only advances the understanding of Savonius turbine optimization but also contributes to broader renewable energy applications. The research offers critical insights into sustainable hydroelectric power generation, providing practical solutions to enhance turbine performance for real-world applications. © 2024

关键词： Clean energy

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A Sub-nanosecond Delay Floating-voltage Level Shifter for SiC MOSFETs Gate Driver Application 6

A Sub-nanosecond Delay Floating-voltage Level Shifter for Si...

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6th International Conference on Energy Systems and Electrical Power, ICESEP 2024

作者： Wan, Yue Xia, Yinshui Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9798350353563

In order to meet the requirements for the design of SiC gate driver in terms of speed and dv/dt immunity, a sub-nanosecond delay level shifter based on a high-voltage (HV) digital level shifter circuit is proposed. It can decrease the response time compared with the existing level-shifting circuitry, enabling its application in high-voltage scenarios such as closed-loop drive circuits for silicon carbide. The edge detection circuit and simple pull-up branches are utilized to reduce the transmission delay and power consumption. The circuit is simulated at a frequency of 10MHz in a 018um BCD process with Virtuoso, and the results demonstrate that the average transmission delay is about 380ps and the charging response time of the slow path is reduced to 3.3ns. © 2024 IEEE.

关键词： Delay circuits

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Detection and Classification Model for Respiratory Diseases Using Machine Learning Techniques 6

Detection and Classification Model for Respiratory Diseases ...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Tanti, Lili Triandi, Budi Riza, Bob Subhan Thanri, Yan Yang Iriani, Juli Pusapasari, Ratih Faculty of Engineering and Computer Science Universitas Potensi Utama Medan Indonesia

ISBN: (纸本)9798331539603

In this study, we aim to develop a respiratory disease detection and classification model using machine learning techniques. Respiratory diseases are a significant global health problem, and early detection is critical to improving patient outcomes. In this study, we collected data from multiple sources to analyze and compare the performance of several machine learning algorithms, including kNN, SVM, Gradient Boosting, Adaboost, Neural Network, Random Forest, Naïve Bayes, and Logistic Regression. These models were evaluated based on performance metrics such as Area Under the Curve (AUC), classification accuracy, F1 Score, precision, and recall. The results showed that Random Forest and Naïve Bayes models performed best in terms of accuracy and class separation ability. This study also emphasized the importance of feature analysis and correlation in improving model effectiveness. These findings are expected to contribute to the development of more accurate diagnostic tools for respiratory diseases, as well as support more timely and effective medical interventions. © 2024 CRWN.

关键词： Lung cancer

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Speech Quality Assessment and Emotions - Effect on the PESQ Metric 15

Speech Quality Assessment and Emotions - Effect on the PESQ ...

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15th International Conference Elektro, ELEKTRO 2024

作者： Zgank, Andrej Donaj, Gregor Vlaj, Damjan University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia

ISBN: (纸本)9798350372359

This paper analyzes how emotional speech influ-ences the quality assessment process. The objective metrics for speech quality assessment are usually evaluated with neutral speech recordings, but human interaction frequently involves emotions. Those can modify speech signals' acoustic and phonetic characteristics largely, which are essential from the objective speech quality assessment perspective. The proposed analysis was carried out with the English and Slovenian Interface emotional speech database, which includes two neutral and six emotional speaking styles. Speex codec was used to simulate the degradations, which were then assessed with the lTV - T P.862 PESQ objective metric. The results' analysis showed that in both languages surprise, in English fear, and in Slovenian disgust influenc the speech quality assessment significantly. © 2024 IEEE.

关键词： Quality control

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