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31st IEEE International Conference on Image Processing Challenges and Workshops, ICIPCW 2024

作者： Phuong, Thao Nguyen Sakaino, Hidetomo Duy, Vinh Nguyen FPT Consulting Japan Japan Waseda University Department of Computer Science and Communications Engineering Japan

ISBN: (纸本)9798331515942

Reconstructing the 2D or 3D shape of an object from several 2D drawings is a crucial problem in computer-Aided design (CAD). Despite the advancement of deep neural networks, automatic isometric image generation from three orthographic views line drawings using deep learning remains unresolved. Existing image-To-image translation techniques often generate images from just one input image. In this paper, we propose a novel method for the above task using a GAN-based model, namely IsoGAN. This method takes three images of object's front, side, and top view as input, then analyzes the spatial and geometrical relations between each view and finally generates the corresponding isometric view image of the object. Extensive experiments on SPARE3D dataset show promising results of IsoGAN on isometric view generation task, demonstrating the effectiveness of the proposed IsoGAN. © 2024 IEEE.

关键词： Deep neural networks

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Prioritizing Vulnerability Assessment Items Using LLM Based on IoT Device Documentations 11

Prioritizing Vulnerability Assessment Items Using LLM Based ...

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11th International Conference on Internet of Things: Systems, Management and Security, IOTSMS 2024

作者： Ikegami, Yuka Negishi, Ryotaro Hasegawa, Kento Hidano, Seira Fukushima, Kazuhide Hashimoto, Kazuo Togawa, Nozomu Waseda University Department of Computer Science and Communications Engineering Japan Kddi Research Inc Japan

ISBN: (纸本)9798350366501

With the rapid increase in demand for IoT devices, malicious attacks targeting vulnerabilities in IoT devices have been frequent in recent years. It is highly expected that the vulnerabilities can be removed from them through vulnerability assessment. However, the wide variety of IoT devices is not standardized, and it is difficult to set up vulnerability assessment items mechanically for those IoT devices, which causes a major obstacle to automate the vulnerability assessment for IoT devices. In this paper, we propose a method to prioritize vulnerability assessment items for every IoT device by effectively utilizing a large language model (LLM). The proposed method generates the answers that take into account the specifications of individual IoT devices using LLM by introducing Retrieval Augmented Generation (RAG), and determines how much suitable each vulnerability assessment item is for every IoT device by calculating the suitability using semantic entropy. Performing security tests based on the suitability must improve time efficiency while maintaining the coverage of the tests. Through the evaluation experiments, we obtained a suitability of vulnerability assessment items for the two types of IoT devices, which indicates 0.8 or higher in both the devices in terms of area under the curve (AUC). © 2024 IEEE.

关键词： Semantics

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Public Vehicle Passenger Counting System using Infrared Imaging with Data Analytics

Public Vehicle Passenger Counting System using Infrared Imag...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Besmonte, John Michael B. Dela Cueva, Jherome Ivan C. Jimenez, Justito Vicente A. Valenzuela, Danzkyle Dominic D. Guico, Maria Leonora C. Galicia, Jan Kevin A. Ateneo de Manila University Department of Electronics Computer and Communications Engineering Quezon City Philippines

ISBN: (纸本)9798350350821

The research was dedicated to devising and implementing a comprehensive monitoring system tailored specifically for the e-jeeps operating within the confines of Ateneo de Manila University. Leveraging advanced GPS sensors, this system enabled the real-time tracking of e-jeepneys while simultaneously providing crucial insights into their speed and estimated time of arrival at various points across the campus. the research unearthed intriguing findings regarding the relationship between passenger count and environmental conditions. While a minimal correlation was observed, it was noted to be contingent upon the specific time of day, indicating potential variations in passenger behavior influenced by diurnal factors. In order to streamline data management and visualization, the researchers capitalized on the robust infrastructure provided by various Google applications and cloud services. This integration facilitated the seamless uploading and synthesis of sensorderived data, empowering the creation of a dynamically updated dashboard providing comprehensive insights into e-jeepney operations The study represents a significant milestone in the realm of transportation management, successfully culminating in the development and deployment of a sophisticated monitoring system. © 2024 IEEE.

关键词： Information management

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Optical Ciphering Scheme for Cancellable Speaker Identification System

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computer Systems Science & engineering 2023年第4期45卷 563-578页

作者： Walid El-Shafai Marwa A.Elsayed Mohsen A.Rashwan Moawad I.Dessouky Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi EAbd El-Samie Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Communications Faculty of EngineeringCairo UniversityCairoEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Most current security and authentication systems are based on personal *** security problem is a major issue in the field of biometric *** is due to the use in databases of the original *** biometrics will forever be lost if these databases are *** privacy is the most important goal of cancelable *** order to protect privacy,therefore,cancelable biometrics should be non-invertible in such a way that no information can be inverted from the cancelable biometric templates stored in personal identification/verification *** methodology to achieve non-invertibility is the employment of non-invertible *** work suggests an encryption process for cancellable speaker identification using a hybrid encryption *** system includes the 3D Jigsaw transforms and Fractional Fourier Transform(FrFT).The proposed scheme is compared with the optical Double Random Phase Encoding(DRPE)encryption *** evaluation of simulation results of cancellable biometrics shows that the algorithm proposed is secure,authoritative,and *** encryption and cancelability effects are good and reveal good ***,it introduces recommended security and robustness levels for its utilization for achieving efficient cancellable biometrics systems.

关键词： Cancellable biometrics jigsaw transform FrFT DRPE speaker identification

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Diabetest: Mobile Application for T2DM Detection Among Filipino Young Adults Using Facial Texture

Diabetest: Mobile Application for T2DM Detection Among Filip...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Pulmano, Tricia Z. Salvador, Lester Niel S.J. Guico, Maria Leonora C. Galicia, Jan Kevin A. Ateneo de Manila University Department of Electronics Computer and Communications Engineering Quezon City Philippines

ISBN: (纸本)9798350350821

Diabetes is increasing in both prevalence and incidence worldwide. The International Diabetes Federation (IDF) showed that in 2021, 15.51 percent of the total adult population have diabetes. Current invasive and costly DM detection methods raise the need for more available and accessible non-invasive detection systems for diabetes given the prevalence of diabetes in Filipino adults. The research focused on the development of a mobile application employing Facial Texture Analysis as a novel method for detection of diabetes among Filipino adults, ages 21-40. The mobile application, which was built using Python, allows the user to upload a facial image which the application processes. The photo will undergo resizing, facial block extraction, texture feature extraction using the Gabor filter, and diabetes classification using the Support Vector Machine model, trained with a 70:30 training-to-testing ratio, which was stored in a web server. © 2024 IEEE.

关键词： Gabor filters

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Counting and Weight Estimation of Penaeus Vannamei Through Image Processing 6

Counting and Weight Estimation of Penaeus Vannamei Through I...

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6th International Conference on Electrical, Control and Instrumentation engineering, ICECIE 2024

作者： Sevilla, Luis Carlo Tirana, Joshua Miguel Libatique, Nathaniel Joseph C. Galicia, Jan Kevin A. Guico, Maria Leonora C. Ateneo de Manila University Department of Electronics Computer and Communications Engineering Quezon City Philippines

ISBN: (纸本)9798350380040

Shrimp farming stands as a prominent and rapidly expanding sector of aquaculture in the Philippines, yet its sustainability is hindered by substantial feed costs, which represent a significant portion of total expenses for both small-holder and commercial farms. This study aims to address this challenge by developing an algorithm that accurately counts and estimates the weight of Penaeus Vannamei shrimps, thereby optimizing feeding patterns and fostering healthier growth. The research implements a measurement station with fixed lighting and camera height to generate a comprehensive dataset of shrimp images and corresponding weights. Utilizing YOLOv8 for detection and counting, coupled with supervised machine learning incorporating Area-based, Perimeter-based, Color-based, and GLCM-based estimation methods across multiple image batches. The study identifies Exponential GPR as the most effective regression model for the dataset. Furthermore, it reveals that Area-based and GLCM-based estimations exhibit the highest accuracy, with respective MSE, MAE, and R^2 values of 1.6814, 0.9005, 0.96 and 1.0638, 0.62359, 0.68. These findings offer valuable insights into optimizing efficiency and cost reduction strategies within shrimp farming operations, based on accurate counting and weight estimation algorithms. © 2024 IEEE.

关键词： Shellfish

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Implementation of a Gesture-Detecting Smart Glove for Quadcopter Navigation 12

Implementation of a Gesture-Detecting Smart Glove for Quadco...

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12th IEEE Conference on Systems, Process and Control, ICSPC 2024

作者： Castillo, Jose Xavier C. Guico, Maria Leonora C. Galicia, Jan Kevin A. Ateneo de Manila University Department of Electronics Computer and Communications Engineering Quezon City Philippines

ISBN: (纸本)9798350391398

Drone and unmanned aerial vehicle (UAV) technology is at the forefront of development and innovation, with many applications and functions. Yet, human-UAV interactions are generally limited to handheld controllers or computer interfaces. This can limit the on-the-go applications of UAV systems and restrict pilots to focusing solely on piloting the UAV, preventing them from performing other tasks simultaneously. This research seeks to alleviate this problem by creating a new method of controlling a UAV using an electronic flex-sensor glove with gesture recognition and wireless transmission capability, serving as a basis for future studies involving flex-sensor gloves. The smart glove has gesture recognition capabilities using flex sensors attached to three fingers and an accelerometer below the knuckles. These sensors detect finger bending and hand orientation, which are translated into gestures. The gestures detected by the glove correspond to specific drone movements and behaviors. These commands are sent as PPM signals to a Flysky FS-i6X transmitter, which then transmits movement commands to a quadcopter drone through radio frequencies. The drone successfully receives and interprets commands from the flex glove as if the commands came directly from the transmitter itself. © 2024 IEEE.

关键词： Drones

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ArchaeoBot: Design and Development of an Autonomous Robot for Detecting and Brushing Artifacts 12

ArchaeoBot: Design and Development of an Autonomous Robot fo...

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12th IEEE Conference on Systems, Process and Control, ICSPC 2024

作者： Dizon, Enrico Martin J. Masa, Angelica T. Oppus, Carlos M. Rafael, Ralph Anthony R. Ateneo de Manila University Department of Electronics Computer and Communications Engineering Quezon City Philippines

ISBN: (纸本)9798350391398

This research aimed to design and develop ArchaeoBot, an autonomous robot for detecting and brushing artifacts. The integration of a crawler robot with a robotic arm and an attached brush and ESP32-CAM, which feeds footage into a YOLOv8 machine learning algorithm for object identification, was implemented. To assess the functionality of the robot, data was gathered qualitatively and quantitatively during the testing procedure within the sandbox. Testing showed that ArchaeoBot is effective in identifying and brushing artifacts accordingly. The overall detection accuracy and brushing position accuracy of the prototype are 91.50% and 93.88%, respectively. © 2024 IEEE.

关键词： Machine design

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On-Demand Coordinated Spectrum and Resource Provisioning under an Open C-RAN Architecture for Dense Small Cell Networks

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IEEE Transactions on Mobile Computing 2024年第1期23卷 673-688页

作者： Wu, Sau-Hsuan Ko, Chun-Hsien Chao, Hsi-Lu National Yang Ming Chiao Tung University Institute of Communications Engineering College of Electrical and Computer Engineering Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Institute of Information Engineering Department of Computer Science Hsinchu30010 Taiwan

Mobile networks have seen more than a thousand times traffic increases in the past decade. Network operators face an ever increasing demand and cost to deploy denser networks in order to maintain the quality of services. In view of this paradigm shift, an open cloud radio access network (C-RAN) service model is studied in this work. Integrating the cross-layer functions of spectrum resource sharing, channel and power allocation, and interference management in a C-RAN architecture, we explore the feasibility of providing a scalable yet efficient broadband wireless service with dense small cell networks (DSN). The proposed methods and architecture can be applied to DSN that support the functions of (further enhanced) inter-cell interference cancelation (feICIC/ICIC) techniques of 3GPP standard, and have the potential to provide a cost-effective solution for high-quality DSN. Simulation results across an area of 100 km2 show that the proposed scheme can offer an aggregate downlink throughput of 21 Gbps over a maximum channel bandwidth of 20 MHz, which is 5 times the throughput with a typical ICIC method. Moreover, the service satisfaction degree can reach 85% under the proposed C-RAN architecture, making it a promising and cost-effective solution for future broadband wireless services. © 2002-2012 IEEE.

关键词： Radio access networks

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Design and Implementation of Advanced Driver Assistance Systems

Design and Implementation of Advanced Driver Assistance Syst...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Ali, Waleed Abd-Elshafi Saleh, Hatem Abdelhamid Eid, Haneen Salah Fathi, Ahmed Mohamed Mohamed, Abd-El Rahman Amr Higher Institute of Engineering EL- Shorouk Academy Department of Communications and Computer Engineering Cairo Egypt Misr University for Science and Technology Department of Electronics and Communications Engineering Giza Egypt

ISBN: (纸本)9798350351408

Advanced Driver Assistance Systems (ADAS) are a pivotal advancement in automotive technology, enhancing vehicle safety and driving experience. In our project, we have successfully designed and built a robotic prototype car. We have implemented a comprehensive control system for the car's movement, and the following features of ADAS systems: Bump Detection, Precise Lane Tracking, Adaptive Cruise Control, Traffic Sign Recognition, and Blind Spot Detection. Bump detection systems are equipped to detect and alert drivers of speed bumps and other road irregularities, in which we use NVIDIA Jetson Nano, Astra Pro Plus Depth camera as RGB and Depth sensor and use Custom AI Model based on YOLOv5 to detect different Bumps on the road and we use Python, TensorRT, and OpenCV. Lane Departure Warning (LDW) alerts drivers when their vehicle unintentionally drifts out of their lane, we use NVIDIA Jetson Nano as our main microcontroller unit (MCU) responsible for our Machine learning and Astra Pro Plus Depth camera as our RGB sensor, we use Python, Python's libraries such as OpenCV, and NumPy to implement LDW. Adaptive Cruise Control (ACC) adjusts the vehicle's speed automatically to maintain a safe distance from the vehicle ahead, we use NVIDIA Jetson Nano, Astra Pro Plus Depth camera as RGB and Depth sensor and use Custom AI Model based on YOLOv5 to detect different vehicles on the road, we use Python, TensorRT, and OpenCV. Traffic Sign Recognition can interpret and display traffic signs to keep drivers informed about speed limits, no-entry signs, and more, we use NVIDIA Jetson Nano, and Astra Pro Plus Depth camera as our RGB sensor and use Custom AI Model based on YOLOv5 to detect different Traffic Signs on the road, we use Python, TensorRT, and OpenCV. Blind Spot Detection (BSD) technology helps drivers identify vehicles in their blind spots and alerts them to avoid dangerous maneuvers, we use ESP32 as an MCU and Ultrasonic sensor, and use C++ to program the BSD feature. © 2024

关键词： Advanced driver assistance systems

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