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37th International conference on VLSI Design (VLSID) / 23rd International conference on Embedded systems (ES)

作者： Viswanath, Vinod Chakraborty, Kanad Real Intent Inc Sunnyvale CA 94089 USA

ISBN: (纸本)9798350384406

Functional verification problems such as clock domain crossing ( CDC), reset domain crossing (RDC), x-propagation and design for testability (DFT) readiness have been the mainstay of hardware verification flow for some time now. With the ever-increasing chip complexity for modern-day mobile, multicore systems-on-chip (SoCs) with built-in advanced image processing, and scalable AI microcontrollers with billions of gates and numerous clock domains with ultralow device geometries, these problems are not only more significant nowadays, but need to be addressed very early in the design process for a timely tape out and first-pass Silicon success;failing which, there will be prohibitively expensive design bug fixes and costly design iterations. Static methods that perform search and analysis techniques to check for failures under all possible test modes, scenarios, and cases, have emerged as a very promising paradigm for solving these problems early, during RTL design. This paper describes a novel static verification, debug, and sign-off tool, Meridian DFT, that can detect specific design issues affecting testability at early RTL in presence of one or more test modes and provide ways to debug and quantify such issues. We present results on large scale (100+ million gates) industrial designs from mobile SoC and AI/Edge domain chips.

关键词： Static Sign-off design-for-test (DFT) fault coverage early RTL exploration

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Predictive Modeling of Landslide Susceptibility in Soft Soil Canal Regions: A Focus on Early Warning systems

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INTERNATIONAL JOURNAL OF advanced COMPUTER SCIENCE AND applications 2023年第12期14卷 1039-1049页

作者： Anh, Dang Tram Danh, Luong Vinh Quoc Nguyen, Chi-Ngon Can Tho Univ Can Tho City Vietnam

The Mekong Delta (MD) has suffered significant losses in land resources, economic damage, and human and property casualties due to recent landslides. An early warning system for landslides is a valuable tool for identifying the effectiveness and timely detection of changes in the soil to promptly determine solutions and minimize damage caused by landslides in an area. In this study, we apply a machine learning approach based on the Long Short-Term Memory (LSTM) algorithm to experiment with early warning of landslide events on soft soil in the MD. Horizontal pressure, the change in inclination angles of the sensor pile due to the soil mass sliding in both the x and y directions, and the warning levels are determined based on the deformation and displacement of the soil along the riverbank, considered candidate factors for inputs in the model. Data from the established sensor system is used to train the model, creating a training and testing dataset of 374,415 samples. The accuracy of the detection and classification threshold of the system is proposed to be measured using the average F1 score derived from precision and recall values. The optimal prediction results are gleaned from an observational window of 4 minutes and 30 seconds to project roughly 2 hours into the future. The validation process resulted in recall, precision, and F1 -score stands at 0.8232 with a remarkably low standard deviation of about 1%. The successful application of this research can help identify abnormal events leading to riverbank landslides due to loading, thereby creating conditions for developing a reliable information system to provide managers with the ability to suggest timely solutions to protect the lives, property of residents and infrastructures.

关键词： Landslide early warning soft soil Mekong Delta long short-term memory

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Composite and Stretchable Silicone for Niche Profiling applications

Composite and Stretchable Silicone for Niche Profiling Appli...

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2024 IEEE sensors conference

作者： Panchaml, Padmanabh Pundrikaksha Mukherjee, Anupam Liu, Teng-Chung Lin, Kun-Han Chiu, Wen-Hsin Liu, Chiang Lo, Cheng-Yao Natl Tsing Hua Univ Inst NanoEngn & MicroSyst Hsinchu 300044 Taiwan Gen Silicones Dept Mkt 9-1 Lane 52Nan Kang St Hsinchu 300104 Taiwan Natl Tsing Hua Univ Dept Kinesiol Hsinchu 300044 Taiwan Univ Taipei Grad Inst Sports Equipment Technol Taipei 111036 Taiwan Natl Tsing Hua Univ Dept Power Mech Engn Hsinchu 300044 Taiwan

ISBN: (纸本)9798350363524;9798350363517

In this work, we developed a silicone and polyurethane (PU)-based composite, which supports stretchable applications. Through material survey, comparison, and mechanical characterization, it was proved that the roll-to-roll manufactured product shows cohesive bonding force over 2 Kg/cm(2), outperforming existing commercialized ones. Eight composite formulations were evaluated through ASTM D5459-95 standard, which indicated outstanding elastic recovery (between 89.72% and 93.65%), permanent deformation (between 6.35% and 10.28%) and stress retention (between 68.34% and 92.32%). In addition, a three-dimensional profiling that incorporated the developed composite further demonstrated its supportiveness on advanced sensing systems that require material stretchability.

关键词： Composite Joule heating polyurethane sensor silicone

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Efficiency and Accuracy for Partial Shading Detection in Series-Parallel Configuration of Photovoltaic Generation systems 13

Efficiency and Accuracy for Partial Shading Detection in Ser...

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13th International conference on Renewable Energy Research and applications

作者： Wu, Han-Cheng Cheng, Chun-Wei Teng, Jen-Hao Natl Sun Yat Sen Univ Dept Elect Engn Kaohsiung Taiwan

ISBN: (纸本)9798350375596;9798350375589

Photovoltaic Generation systems (PVGSs) are frequently impacted by Partial Shading (PS) conditions, which can significantly reduce their power output. The maximum Power Point Tracking (MPPT) methods can enhance PVGS performance. MPPT's effectiveness can be improved considerably with PS Detection (PSD) results, which help select the most suitable MPPT strategy. Most PSD methods investigate a PVGS with the series configuration;however, PVGSs are usually arranged in series-parallel, total-cross-tied, series-parallel with total-cross-tied configurations, etc. The applicability of existing PSD methods in different PVGS configurations requires in-depth explorations. Therefore, this paper investigates the efficiency and accuracy of a PSD in the series-parallel configuration of PVGSs. The PSD method proposed in this paper estimates the solar irradiance and temperature of a PVGS based on two measured voltage and current sets. A PS Factor (PSF) is then used to detect whether a PS occurs. This paper uses a series-parallel PVGS composed of 5x5 PV panels to verify the proposed PSD method. Different PS patterns, including column, row, diagonal, and corner, are examined for the PVGS. Experimental results show that for both two-row and corner PS patterns, the proposed method can efficiently and accurately detect whether a PS occurs in 3s with a tracking time interval of 1s. Simulation results show that the PSD accuracies of single-row and diagonal PSs reach 100%, corner PS reach 99.8%, and single-column PSs reach 89.74% under solar irradiance variations.

关键词： Photovoltaic Generation System Partial Shading Detection Maximum Power Point Tracking Series-Parallel Configuration

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Dual-functional Internet of Meta-material Things Networks: Integrated Sensing and Communication

Dual-functional Internet of Meta-material Things Networks: I...

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IEEE conference on Global Communications (IEEE GLOBECOM) - Intelligent Communications for Shared Prosperity

作者： xu, Zhiquan Liu, xu Zhang, Hongliang Song, Lingyang Peking Univ Sch Elect Engn & Comp Sci Beijing Peoples R China Peking Univ Sch Elect Beijing Peoples R China Peking Univ Sch Elect & Comp Engn Shenzhen Grad Sch Shenzhen Peoples R China

ISBN: (纸本)9798350310900

The Internet of Meta-material Things (Meta-IoT) has significant potential for future IoT applications due to its ability to function without a battery and its ease of maintenance. Specially, the environmental information can be obtained by analyzing the frequency response of Meta-IoT sensor from the reflected signals. Through the reflection, these Meta-IoT sensors can also provide additional paths for improving communication performance while performing sensing. In this paper, we design a dual-functional Meta-IoT network for integrated sensing and communication (ISAC), i.e., the Meta-IoT sensors can sense environmental conditions and facilitate communication simultaneously. However, ensuring the quality of both sensing and communication for multiple users is not trivial since the impact of the sensor structure on sensing and communication at the same time. Moreover, a customized beamforming scheme is required to balance the performance of two functions. To address these challenges, we optimize the sensor structure and the transmit beamforming. Simulation results show that the communication performance can be significantly improved with the proposed scheme while the sensing performance is guaranteed.

关键词： Integrated sensing and communication MetaIoT meta-material sensor

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An Energy Efficient Clustering for Underwater Acoustic sensor Networks using 6G Technology 5

An Energy Efficient Clustering for Underwater Acoustic Senso...

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5th IEEE International conference on Recent Trends in Computer Science and Technology, ICRTCST 2024

作者： Siddiqui, Shams Tabrez Hashmi, Syed Ghyasuddin Ali, Mohammed Maqsood Syed, Ziauddin Qidwai, Khalid Ali Salim, Abu Jazan University College of Engineering and Computer Science Department of Computer Science Jazan Saudi Arabia Applied College Jazan University Department of Business Administration Jazan Saudi Arabia

ISBN: (纸本)9798350351378

These underwater Acoustic sensor Networks (UWSNs) present unique challenges due to the harsh and dynamic underwater environment, making efficient communication protocols essential for their operation. This paper introduces an innovative Energy Efficient Clustering Routing Protocol (EECRP) specifically designed for UWSNs, leveraging the advancements of 6G technology. EECRP employs a distributed clustering mechanism and energy-efficient routing strategy to optimize energy consumption, prolong network lifetime, and enhance communication reliability. The protocol integrates with 6G technologies, such as terahertz communication and quantum communication security, to further enhance performance and security in UWSNs. Through simulation and comparative analysis, EECRP demonstrates superior performance compared to existing routing protocols in terms of energy efficiency, throughput, and scalability. EECRP's contributions lie in its novel approach to routing in UWSNs, emphasizing energy efficiency, sustainability, and integration with advanced technologies. This research paves the way for the adoption and deployment of EECRP in various underwater applications, facilitating scientific research, environmental monitoring, and technological innovation in underwater communication systems. © 2024 IEEE.

关键词： Scalability

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Integrating KLV Metadata with UAV Motion Imagery and Geo-Tagging for Enhanced GIS Playback 3

Integrating KLV Metadata with UAV Motion Imagery and Geo-Tag...

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3rd International conference for Advancement in Technology, ICONAT 2024

作者： Sakshi Gupta, Charu Patra, Tushar Kanti Bharat Electronics Limited Central Research Laborartory Uttar Pradesh India

ISBN: (纸本)9798350354171

With the growth of motion imagery, the ability to visually analyze video data and extract key features has advanced significantly. This technology incorporates essential geo-tagging, sensor, and platform orientation data into the video stream, providing geographic context for viewing and analysis. Recently, the use of multiple drones for detection and rescue operations has surged. These services leverage high-speed 5G networks to capture 4 K videos, processed through MEC (Mobile Edge Computing) servers for functions such as object detection. This paper focuses on reading, extracting, and interpreting metadata embedded in KLV Tags, associating location data with spatio-temporal motion imagery. The Precision Time Stamps of the MISP Time System in the metadata help correlate motion imagery with metadata, overlaying synchronized imagery on GIS at the respective location. The process involves reading the KLV Tag video stream, extracting KLV Tags in Hex format, converting them to text, and interpreting them using the MISB format. The system filters required information from the tags to associate location, extent of video frames, and sensor location with image frames of archived video based on precision time stamps. Geographical boundaries of video frames are overlaid on GIS, synchronizing spatio-temporal motion imagery with location metadata, enhancing the utility of motion imagery in various applications. © 2024 IEEE.

关键词： 5G mobile communication systems

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A Review on Attack Graph Analysis for IoT Vulnerability Assessment: Challenges, Open Issues, and Future Directions

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IEEE ACCESS 2023年 11卷 44350-44376页

作者： Bin Hamed Almazrouei, Omar Saif Musabbeh Magalingam, Pritheega Hasan, Mohammad Kamrul Shanmugam, Mohana Univ Teknol Malaysia Razak Fac Technol & Informat Adv Informat Dept Kuala Lumpur 54100 Malaysia Univ Kebangsaan Malaysia Fac Informat Sci & Technol Ctr Cyber Secur Bangi 43600 Malaysia Univ Tenaga Nas Coll Comp & Informat Kajang 43000 Malaysia

Vulnerability assessment in industrial IoT networks is critical due to the evolving nature of the domain and the increasing complexity of security threats. This study aims to address the existing gaps in the literature by conducting a comprehensive survey on the use of attack graphs for vulnerability assessment in IoT networks. Attack graphs serve as a valuable cybersecurity tool for modeling and analyzing potential attack scenarios on systems, networks, or applications. The survey covers the research conducted between 2016 and 2021(34 peer-reviewed journal articles and 28 conference papers), identifying and categorizing the main methodologies and technologies employed in generating and analyzing attack graphs. In this review, core modeling techniques for IoT vulnerability assessment are highlighted, such as Markov Decision Processes (MDP), Feature Pyramid Networks (FPN), K-means clustering, and logistic regression models, along with other techniques involving genetic algorithms like fast-forward (FF), contingent fast-forwards (CFF), advanced reinforcement-learning algorithms, and HARMs models. The evaluation of the performance of these attack graph models using IoT networks or devices as case studies is also emphasized. This survey provides valuable insights into the state-of-the-art attack graph techniques for IoT network vulnerability assessment, identifying various applications, performances, research opportunities, and challenges. As a reference source, it serves to inform academicians and practitioners interested in leveraging attack graphs for IoT network vulnerability assessment and guides future research directions in this area.

关键词： Internet of Things Computer security Systematics Databases Metadata Wireless sensor networks Terminology Attack graph the Internet of Things network vulnerabilities vulnerability assessment

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Modeling and simulation of the capacitive NEMS pressure sensor based on suspended graphene membranes

Modeling and simulation of the capacitive NEMS pressure sens...

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2024 International conference on Next Generation Electronics and Photonics, INGEP 2024

作者： Liu, Quan Zhang, Zhe Ding, Jie Zhang, Wendong Fan, xuge Advanced Research Institute of Multidisciplinary Sciences Beijing Institute of Technology China Yangtze Delta Region Academy Beijing Institute of Technology. China School of Integrated Circuits and Electronics Beijing Institute of Technology China State Key Laboratory of Dynamic Measurement Technology North University of China China National Key Laboratory for Electronic Measurement Technology North University of China China

Nanoelectromechanical systems (NEMS) employing graphene have garnered significant attention for their potential applications in pressure sensors. Compared to other electrical readout mechanisms, capacitive sensing is a promising alternative one due to its less dependence on material properties and environmental factors. Graphene, with its unique properties, is an excellent candidate for high-performance NEMS pressure sensors. However, there are few studies on theoretical modeling of capacitive NEMS pressure sensors based on suspended graphene membrane. This paper presents the design, modeling and simulation of capacitive NEMS pressure sensors based on circular suspended graphene membrane. The impact of parameters of graphene membrane on the sensor performance is studied through COMSOL finite element analysis software. The results show that the sensitivity increased with the increase of the radius of graphene membrane but decreased with the increase of the thickness of graphene membrane, and the polar plate spacing determines the trade-off between the sensitivity and the measurement range. Further, decreasing the polar plate spacing increases the sensitivity but changes the capacitance-pressure relationship from linear to nonlinear. © Published under licence by IOP Publishing Ltd.

关键词： Microchannels

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Efficient Drone-Based Mobile Wireless sensor Network for Spatio-Temporal Environmental Monitoring 18

Efficient Drone-Based Mobile Wireless Sensor Network for Spa...

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18th IEEE International conference on advanced Networks and Telecommunications systems, ANTS 2024

作者： Kapoor, Ayshika Kumar, Dheeraj Indian Institute of Technology Department of Electronics and Communication Engineering Uttarakhand Roorkee India

ISBN: (纸本)9798350391725

The technological advancements in wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) or drones have made significant contributions in various fields, benefiting human society. Although WSNs have been widely used for environmental monitoring, their utility is constrained by inherent limitations, which make them suitable only for small-scale sensing tasks. On the other hand, UAVs provide quick access to large areas, including challenging terrains, allowing faster data collection that is both less labor-intensive and more cost-effective. In this paper, we present an efficient method to collect data for environmental monitoring using a drone-based mobile WSN system. The framework discretizes the region to be monitored into a 3D spatial-temporal field, where the field is further divided into sub-grids for the deployment of drones in each sub-grid. The drones utilize their built-in sensors to move around the designated region in a pre-defined trajectory to collect spatio-temporal data. In order to obtain parameter values at intermediate points within the surveyed region, interpolation techniques such as inverse distance weighting (IDW) and nearest neighbors (NN) are applied, ensuring comprehensive data coverage. To validate the feasibility of our proposed system, experiments are performed for temperature modeling applications using a simulated dataset, a real-world NYC weather dataset, and a real-time REST API dataset. The obtained results demonstrate that the proposed model is well-suited for large-scale sensing, even in remote areas, exhibiting cost-effectiveness and substantial reductions in labor and resource requirements, providing a robust and efficient solution for real-time environmental data collection and analysis. © 2024 IEEE.

关键词： Environmental monitoring

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