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Transforming Obesity Care Through Artificial Intelligence: Real-Case Implementations and Personalized Solutions

Transforming Obesity Care Through Artificial Intelligence: R...

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Computational Intelligence Approaches and applications (ICCIAA), International conference on

作者： Mayyas Al-Remawi Rami A. Abdel-Rahem Faisal Al-Akayleh Faisal Aburub Ahmed S.A. Ali Agha Department of Pharmaceutics and Pharmaceutical Technology University of Petra Amman Jordan Department of Chemistry Faculty of Arts and Sciences University of Petra Amman Jordan Faculty of Administrative & Financial Sciences University of Petra Amman Jordan Department of Pharmaceutical Sciences The University of Jordan Amman Jordan

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

Obesity is a multifactorial condition that significantly increases the risk of metabolic syndrome, cardiovascular disease, and various other comorbidities. Conventional obesity management strategies-encompassing body mass index (BMI) measurements, dietary counseling, and caloric tracking-often fail to account for the heterogeneity of individual genetic, behavioral, and metabolic factors. Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has emerged as a transformative approach, offering data-driven, personalized solutions that integrate electronic health records (EHRs), wearable sensor data, and multi-omics information. This article examines contemporary AI applications for obesity care, highlighting real-case implementations, technical and ethical considerations, and the future potential for optimizing patient outcomes. By leveraging advanced analytics, healthcare providers can enhance diagnostic precision, tailor interventions to individualized needs, and support sustained weight control, thus redefining the paradigm of obesity management.

关键词： Deep learning Obesity Ethics Weight control Force measurement Imaging Medical services Genetics Real-time systems Wearable sensors

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Detecting End Effector Command Pose Error Using Perfect Bit Field Imaging

Detecting End Effector Command Pose Error Using Perfect Bit ...

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International Carpathian Control conference (ICCC)

作者： Tomáš Buchta Jaroslav Hlava Tomáš Martinec Jaroslav Buchta Yegor Boyarchikov Department of Mechatronic Systems and Robotics Technical University of Liberec Liberec Czechia Institute of Mechatronics and Computer Engineering Technical University of Liberec Liberec Czechia

ISBN: (数字)9798331501273

ISBN: (纸本)9798331501280

This paper presents a novel approach to improving the precision of robotic arm operations in complex environments by using Perfect Bit Field Imaging (PBFI) for end effector command pose error detection. Accurate pose determination is essential for tasks such as manipulation, assembly, and autonomous navigation, particularly in space or hazardous settings where precision is critical. PBFI leverages high-resolution industrial cameras to capture detailed pixel-level information that can be used to correct the end effector’s position. The system’s key advantage is its low-cost nature, making it an attractive alternative to expensive sensor-based approaches. advanced image processing techniques are used to interpret bit fields, allowing for quick and reliable pose corrections that reduce the need for recalibration and minimize the impact of external disturbances. Additionally, the approach is adaptable to various robotic arm configurations and operational conditions, making it suitable for a wide range of industrial and space-based applications. This research opens new avenues for enhancing robotic precision in challenging environments, contributing to the advancement of cost-effective autonomous systems.

关键词： Accuracy Service robots Image processing Robot vision systems Refining End effectors Real-time systems Error correction Robots Optimization

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Effective Analysis of Industry-Relevant Cyber-Physical systems via Statistical Model Checking 1

引用

20th International conference of the Italian-Association-for-Artificial-Intelligence (AIxIA)

作者： Pappagallo, Angela Sapienza Univ Rome Comp Sci Dept Rome Italy

ISBN: (数字)9783031084218

ISBN: (纸本)9783031084218;9783031084201

Many autonomous Cyber-Physical systems (e.g., devices for Internet of Things, Unmanned Autonomous Vehicles, medical devices, etc.) are mission-critical (i.e., errors result in loss of money) or safetycritical (i.e., errors result in damage or even death for humans). This motivates research on efficient formal verification methods for such Cyber-Physical systems. Unfortunately, this is not an easy task, as verifying a Cyber-Physical System entails evaluating a huge number of scenarios (scenario explosion). Furthermore, a unified mathematical model for the (discrete) cyber part and the (continuous) physical part is currently not available. Such obstructions may be mitigated by using Statistical Model Checking, which uses statistical methods to sample the set of scenarios while basing on possibly black-box models of the System Under Verification. In this paper, we review 5 recent real-world and industry-relevant case studies from the literature that involved usage of Statistical Model Checking. Such case studies range on very different application areas, namely: i) intelligent services for peak shaving in smart grids, ii) InSilico Clinical Trial for medical services, iii) applications for wireless sensor networks;iv) aircraft data networks;v) plug-in electric vehicles. This shows the maturity, feasibility and flexibility of Statistical Model Checking when applied to real-world case studies.

关键词： Cyber Physical System

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Wireless Sensing for Simultaneous Human Vocal Sound and Heart Sound Recognition

Wireless Sensing for Simultaneous Human Vocal Sound and Hear...

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International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yu Rong Kumar Vijay Mishra Daniel W. Bliss Center for Wireless Information Systems and Computational Architectures (WISCA) Arizona State University Tempe AZ USA United States Army Research Laboratory Adelphi MD USA

Remote vibrometry using wireless signals is a recently introduced novel technique with a wide range of applications such as remote microphones and structural health monitoring. These use cases require high sensitivity and coherence in the sensing system. In this context, radar is a suitable all-weather sensor compared to conventional acoustic acquisition. We investigate human vocal sound and heart sound detection and separation using a single millimeter-wave radar sensor and advanced array processing techniques to achieve superior motion sensitivity.

关键词： Heart Wireless communication Wireless sensor networks Sensitivity Speech recognition Signal processing Acoustics

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Implicit Neural Fusion of RGB and Far-Infrared 3D Imagery for Invisible Scenes

Implicit Neural Fusion of RGB and Far-Infrared 3D Imagery fo...

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IEEE/RSJ International conference on Intelligent Robots and systems (IROS)

作者： Xiangjie Li Shuxiang Xie Ken Sakurada Ryusuke Sagawa Takeshi Oishi Institute of Industrial Science The University of Tokyo Tokyo Japan National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Japan

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Optical sensors, such as the Far Infrared (FIR) sensor, have demonstrated advantages over traditional imaging. For example, 3D reconstruction in the FIR field captures the heat distribution of a scene that is invisible to RGB, aiding various applications like gas leak detection. However, less texture information and challenges in acquiring FIR frames hinder the reconstruction process. Given that implicit neural representations (INRs) can integrate geometric information across different sensors, we propose Implicit Neural Fusion (INF) of RGB and FIR for 3D reconstruction of invisible scenes in the FIR field. Our method first obtains a neural density field of objects from RGB frames. Then, with the trained object density field, a separate neural density field of gases is optimized using limited view inputs of FIR frames. Our method not only demonstrates outstanding reconstruction quality in the FIR field through extensive experiments but also can isolate the geometric information of the invisible, offering a new dimension of scene understanding.

关键词： Training Gases Three-dimensional displays Finite impulse response filters Robot vision systems sensor fusion Rendering (computer graphics) Cameras Image reconstruction Synthetic data

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Defective Microstrip Structure Based Phase Shifter with Reduced Size for Phased Antenna Array applications

Defective Microstrip Structure Based Phase Shifter with Redu...

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IEEE International Workshop on Intelligent Data Acquisition and advanced Computing systems: Technology and applications

作者： Hajra Khan Shahid Khan Jamal Nasir Syed Ahson Ali Shah Mariana Dalarsson Mohammad Alibakhshikenari Department of Electrical and Computer Engineering COMSATS University Islamabad Pakistan Applied Bioelectronics Laboratory Hanyang University Seoul South Korea School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Signal Theory and Communications Universidad Carlos III de Madrid Spain

In this work, we propose a small-size and low-cost phase shifter based on defective microstrip structure (DMS) technique, with a modified reconfigurable unit cell (MRDMS) for WLAN applications at 5.2 GHz. The phase shifter is made up of an MRDMS unit, created by etching slots on a simple microstrip line with an outline of three bridges. To further increase the phase shift, a T-shaped slot is introduced in the central bridge and PIN diodes on the edges of the outer bridges are used. By switching the diodes on and off, the MRDMS unit cell is capable of operating in a variety of different modes to give a phase shift of 37.71° at 5.2 GHz. Additionally, MRDMS unit cells are cascaded for higher phase shift as required. Cascaded two- and four-cell phase shifters were designed and simulated in HFSS and a parametric study on various parameters was conducted to show the detailed operating properties of the proposed phase shifter. Compared to previously reported research, the present study shows that two cascaded phase shifters introduce 75.08° phase shifts and 151.75°, respectively. To the best of our knowledge, this is the maximum phase shift obtained by a phase shifter based on MRDMS.

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Hybrid Image-Based Motion Tracking and Adaptive Polynomial Kalman Filter for a Bio-Inspired Dual-Sheath Needle System

Hybrid Image-Based Motion Tracking and Adaptive Polynomial K...

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IEEE International conference on Robotics and Biomimetics

作者： Dileep Sivaraman Cholatip Wiratkapun Branesh M. Pillai Jackrit Suthakorn Boriphat Methachan Sakol Nakdhamabhorn Songpol Ongwattanakul Department of Biomedical Engineering Center for Biomedical and Robotics Technology (BART LAB) Faculty of Engineering Mahidol University Thailand Department of Radiology Breast Diagnostic Center Division of Diagnostic Radiology Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand Functional Materials for Novel Engineering Applications National Science and Technology Development Agency Thailand

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

This preliminary study investigated sensor-fusion methods for accurate motion estimation in a bio-inspired dual-sheath needle system designed for biopsy applications. The needle system draws inspiration from the segmented dual-sheath mechanism of ovipositors found in Hymenoptera species, which allows controlled and precise movement. The aim is to develop a reliable tracking system for both the needle tip and base, which is essential for accurate needle placement during biopsy procedures. A hybrid tracking approach was used to achieve this, combining image-based tracking of the needle tip with an Inertial Measurement Unit (IMU) sensor for needle-base tracking. An Adaptive Polynomial Kalman Filter (APKF) was applied to improve the motion estimation accuracy. Performance tests on a linear-rail system demonstrated the ability of the developed system to provide accurate and consistent motion estimates. The results suggest that this bio-inspired needle system using sensor fusion and advanced filtering holds promise for use in medical robotics, potentially improving the precision of biopsy procedures.

关键词： Accuracy Tracking Motion segmentation Motion estimation Biopsy Needles Robot sensing systems Polynomials Kalman filters Biomedical imaging

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Volcano-structured Double-gated Field Emitter Arrays;Emission Characteristics and applications

Volcano-structured Double-gated Field Emitter Arrays;Emissio...

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International conference on Vacuum Electronics

作者： Hidenori Mimura Yoichiro Neo Masayoshi Nagao Kunio Tsutaki Yoshihiro Kajikawa Takatsugu Munehiro Research Institute of Electronics Shizuoka Uiversity Hamamatsu Japan National Institute of Advanced Industrial Science and Technology Tsukuba Japan Microwave Tubes Division NEC Network and Sensor Systems Ltd. Sagamihara Japan

Volcano-structured double-gated field emitter arrays (VDG-FEAs) have realized both highly focusing electron beam and high emission current. The prototype image sensor using Spindt-type VDG-FEA has obtained a reproduced image with uniform image intensity without magnetic focusing. we describe a compact image sensor using the VDG-FEA. We are developing a 300 GHz band traveling wave tube (TWT) using a thermal cathode. We believe that the VDG-FEA is a promising cathode for the 300 GHz TWT in the future.

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Machine Learning-Driven Hybrid Adaptive Beamforming for Efficient Interference Mitigation in Dense Wireless sensor Networks

Machine Learning-Driven Hybrid Adaptive Beamforming for Effi...

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Visual Analytics and Data Visualization (ICVADV), International conference on

作者： P. Loganathan A.T. Priyeshkumar K. Kodeeswari K Jose Reena I. Poonguzhali M. Balaji Department of Electronics and Communication Engineering Excel Engineering College(Autonomous) Namakkal Department of Electronics and Communication Engineering Mahendra College of Engineering Salem Department of Electronics and Communication Engineering Kongu Engineering College(Autonomous) Erode Department of Computer Applications B. S. Abdur Rahman Crescent Institute of Science and Technology Vandalur Department of Electronics and Communication Engineering Panimalar Engineering College Chennai Department of Electronics and Communication Engineering Vivekananda College of Technology for Women Tiruchenhode

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The Adaptive Beamforming Algorithm (ABA) represents a promising approach to suppress interference in dense wireless sensor networks (WSNs), enhancing signal fidelity and network throughput. In dense WSNs, the proximity of sensor nodes leads to high interference levels, which degrade energy efficiency and communication reliability. This is exacerbated by static beamforming methods that oversimplify time and frequency utilization. This work proposes a set of adaptive beamforming solutions, including digital, machine learning (ML)-empowered, and hybrid beamforming approaches. The Adaptive Array Signal Processing (AASP) method introduces real-time interference analysis with null steering to suppress unwanted signals and maximize the signal-to-interference-plus-noise ratio (SINR). Hybrid beamforming, combining analog and digital domains, balances computational cost with performance. Additionally, a deep learning-based beam steering module dynamically adjusts beam patterns based on interference forecasts. Extensive simulations demonstrate the proposed methods' superiority over conventional beamforming, achieving significant SINR improvement, enhanced network throughput, and improved energy efficiency. In ultra-dense environments, the results indicate a 10-fold reduction in interference power alongside better scalability. Proactive interference mitigation using ML models further ensures adaptability to varying network conditions. These techniques establish a baseline for deploying adaptive beamformers in dense WSNs, addressing scalability and real-time computational challenges. They also pave the way for implementing advanced 5G/6G-capable sensor systems, enabling resilient communication in high-interference environments. Key-words: signal to interference plus noise ratio(SINR), adaptive beamforming, interference mitigation, hybrid beamforming, null steering, beam steering, computational efficiency.

关键词： Wireless sensor networks Adaptive systems Array signal processing Scalability Prevention and mitigation Interference Throughput Real-time systems Energy efficiency Signal to noise ratio

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advanced Real-Time Volumetric Modeling of Stockpiles in Industrial applications Using Depth Camera

Advanced Real-Time Volumetric Modeling of Stockpiles in Indu...

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International Research conference on Smart Computing and systems Engineering (SCSE)

作者： K. D. Gayantha M. H. P. P. Thilakarathna W. G. C. W. Kumara P. M. K. Alahakoon P. R. D. S. Rudrigu Dept. of Electrical & Telecom. Eng. Faculty of Engineering South Eastern Univ. of Sri Lanka Oluvil Sri Lanka Dept. of Computer Science & Eng. Faculty of Engineering South Eastern Univ. of Sri Lanka Oluvil Sri Lanka Siam City Cement (Lanka) Ltd Puttalam Sri Lanka

ISBN: (数字)9798331523268

ISBN: (纸本)9798331523275

Accurately estimating the volume of dynamically changing stockpiled materials is one of the most critical challenges in effective material management for Siam City Cement (Lanka) Limited. Traditional approaches, such as manual surveying or simple volumetric approximations, are not only laborious and time-consuming but also prone to errors, which may result in less-than-optimal outcomes with regard to resource utilization and operating costs. This paper presents a novel method based on 3D point cloud data acquired by a Kinect depth camera prototype for the estimation of stockpile volumes with increased efficiency and accuracy. The system allows accurate volumetric modeling in real-time using advanced computational algorithms, which turns out to be a striking improvement over traditional methods. It involves registration of several point cloud captures, reorientation of data by using Principal Component Analysis (PCA), noise filtering using clustering techniques, and creation of the accurate surface representation by using Delaunay triangulation. The above approach ensures the limitation brought by the Kinect’s field of view and its depth resolution are effectively compensated. However, to enhance the system’s robustness and scalability, the proposed design will incorporate a Light Detection and Ranging (LiDAR) sensor in its future version. The LiDAR has greater depth accuracy, the ability to acquire data faster, and consistent performance in varying environmental conditions, thus overcoming the intrinsic limitations of the Kinect sensor and enabling easy adaptation to industrial-scale applications. Such research can provide the development of a more reliable and automated volumetric estimation system that will transform material management: reduce manual effort, increase precision, and enable real-time monitoring of stockpile dynamics. This new solution aligns with modern industrial requirements by offering a practical and scalable tool for material inventory optimiz

关键词： Solid modeling Accuracy Laser radar Three-dimensional displays Shape Volume measurement Estimation Cameras Real-time systems sensors

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