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PAKE - PoS Tagger Augmented Keyword Extraction

PAKE - PoS Tagger Augmented Keyword Extraction

引用

2024 ieee international conference on computing, applications and systems, COMPAS 2024

作者： Kohinoor, Md Saidur Rahman Miah, Ayesha Loylus Ali, Shah Fayez Hossain, Md Sabir Bijoy, Md. Hasan Imam Sakib, Shadman King Fahd U. of Petroleum and Minerals Information and Computer Science Dhahran31261 Saudi Arabia InteX Research Lab Ai and Nlp Discipline Sylhet3100 Bangladesh Daffodil International University Computer Science and Engineering Dhaka1216 Bangladesh University of Maryland Baltimore County Department of Information Systems MD21250 United States

ISBN: (纸本)9798331529765

The state-of-the-art techniques for automatic keyword extraction majorly deal with the collection of long documents. However, for several reasons, these do not provide satisfactory results for shorter lengths of documents. Moreover, with the ever-increasing amounts of information available, a keyword extraction system that automatically deals with varying lengths of text can lessen the workload and make the entire process of manually assigning the keywords less time-consuming. For this, the widely used Natural Language Processing (NLP) techniques are examined in the context of extensive data. Therefore, this research introduces PAKE - PoStagger Augmented Keyword Extraction system as a practical amalgamation of statistical and textual-based features based on an unsupervised key phrase extracting algorithm to stand out as a suitable alternative to the existing solutions. The effectiveness is demonstrated by comparing it with six state-of-the-art unsupervised methods, and the results are illustrated using four datasets. © 2024 ieee.

关键词： Natural language processing systems

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Going Beyond Backscatter: Rethinking Low-Power Wireless Transmitters using Tunnel Diodes 23

Going Beyond Backscatter: Rethinking Low-Power Wireless Tran...

引用

29th Annual international conference on Mobile computing and Networking, MobiCom 2023

作者： Shah, Moteen Amin Bijoy, Adithya Gulati, Manoj Yan, Wenqing Varshney, Ambuj Electronics and Telecommunications Veermata Jijabai Technological Institute Maharashtra Mumbai60022429 India Computer Science and Engineering Indian Institute of Technology Delhi Delhi60032730 India School of Computing National University of Singapore Singapore60017161 Singapore Uppsala University Uppsala60003858 Sweden

ISBN: (纸本)9781450399906

A stark disparity exists in the energy consumption for performing transmissions and the tasks of sensing and processing in wireless embedded systems. We present our early work to design a novel transmitter that enables transmissions at a similar energy consumption as other tasks in wireless embedded systems. In particular, the proposed transmitter does not require a carrier emitting device, which is essential to support backscatter transmitters, but has also limited their widespread deployment. The proposed transmitter exploits the capability of tunnel diode oscillators to function as a low-power, self-oscillating mixer. This property enables us to mix a weak baseband signal with a locally generated carrier signal at a peak power consumption below 100 microwatts. Nevertheless, the tunnel diode oscillator trades off the stability for low energy consumption leading to poor link reliability. In this study, we investigate error correction codes to increase link reliability. Our experiments demonstrate the potential of the transmitter to support short-range transmissions with a low energy consumption and enhanced link reliability. © 2023 ACM.

关键词： embedded systems

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Exploring the Performance of You only Look Once Model for Object Detection in VQA Images

Exploring the Performance of You only Look Once Model for Ob...

引用

2024 international conference on Artificial Intelligence and Quantum Computation-Based Sensor applications, ICAIQSA 2024

作者： Asudani, Deepak Suresh Nagwani, Naresh Kumar Singh, Pradeep National Institute of Technology Department of Computer Science and Engineering Chhattisgarh Raipur India

ISBN: (纸本)9798331517953

Identifying objects is among the most crucial and complex problems in computer vision. The effectiveness of object detection tasks has significantly increased due to advancements in deep learning architectures. Object detectors are classified into single-stage (SSD) and two-stage (TSD). SSD model architecture evaluates the spatial region proposals in a single pass. TSDs employ a more complex architecture to focus on selective region proposals. Object detection is an essential component of visual question answering (VQA), which requires algorithms to respond to text-based inquiries about images. While many object detection algorithms are available, real-time application is still somewhat difficult. This paper explores the object detection approaches for VQA systems through a comparative analysis of various YOLO variants. The study compares the effectiveness of YOLOv8s and YOLOv8n architectures against TSD approaches in detecting object positions with bounding boxes. Experiments were conducted on the MS-COCO and two versions of the PASCAL-VOC (2007 and 2012) datasets. The paper outlines the data preprocessing steps required to convert source datasets to the YOLO model format. The experimental evaluations on the PASCAL-VOC dataset indicate that the TSD Faster-RCNN model, using ResNet101 pretrained architecture, achieves the highest mAP of 78.80. In contrast, the SSD YOLOv8s model achieves the highest mAP of 89.63 using the CSPDarkNet53 model architecture. YOLO is essential for real-time object detection, allowing VQA systems to process images in a single forward pass. The study concludes that the SSD YOLOv8s model efficiently identifies objects and generates bounding boxes with higher accuracy compared to other models. © 2024 ieee.

关键词： real time systems

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Data Fusion Using Ultra Wideband time-of-Flight Positioning for Mobile Robot applications

Data Fusion Using Ultra Wideband Time-of-Flight Positioning ...

引用

ieee international conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Lima, Jose Pinto, Andre F. Ribeiro, Francisco Pinto, Milena Pereira, Ana I. Pinto, Vitor H. Costa, Paulo Inst Politecn Braganca Res Ctr Digitalizat & Intelligent Robot CeDRI Campus Santa Apolonia Braganca Portugal Inst Politecn Braganca Lab Sustainabil & Technol Mt Reg SusTEC Braganca Portugal INESC Technol & Sci Porto Portugal Univ Porto Fac Engn SYSTEC DIGI2 Rua Dr Roberto Frias P-4200465 Porto Portugal Univ Porto Fac Engn ARISE Rua Dr Roberto Frias P-4200465 Porto Portugal Fed Ctr Technol Educ Celso Suckow Fonseca CEFET R Fonseca Brazil Univ Porto Fac Engn ECE Dept Rua Dr Roberto Frias P-4200465 Porto Portugal

ISBN: (纸本)9798350301212

Self-localization of a robot is one of the most important requirements in mobile robotics. There are several approaches to providing localization data. The Ultra Wide Band time of Flight provides position information but lacks the angle. Odometry data can be combined by using a data fusion algorithm. This paper addresses the application of data fusion algorithms based on odometry and Ultra Wide Band time of Flight positioning using a Kalman filter that allows performing the data fusion task which outputs the position and orientation of the robot. The proposed solution, validated in a real developed platform can be applied in service and industrial robots.

关键词： Data fusion

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Machine Learning-Enhanced Microfluidic SIW Sensor for Water-in-Fuel Detection applications 14

Machine Learning-Enhanced Microfluidic SIW Sensor for Water-...

引用

14th international conference on Information and Communication systems, ICICS 2023

作者： Altakhaineh, Amjaad T. Alia'afreh, Saqer S. Mutah University Electrical Engineering Department Alkarak Jordan Mutah University Electrical Engineerng Department Alkarak Jordan

ISBN: (纸本)9798350307870

This paper presents a half-mode substrate-integrated waveguide (HMSIW) sensor with a microfluidic integrated channel for detecting microliter water-in-diesel at 7.1 GHz. A microfluidic channel is embedded into the HMSIW structure, allowing interaction with the fields of TE103 mode. The sensor's performance is assessed by following the resonance frequency fluctuations as water concentration varies in a 65 mumathrm{L} sample using an examination of dielectric permittivity behavior. The resonance frequency is highly sensitive, shifting by 6.4 MHz per 0.05% water content. A back-propagation artificial neural network (BP-ANN) model is also deployed to allow cognitive capabilities, attaining a stunning detection range down to 0.01%. This sensor offers a potential option for real-time monitoring and quality control in fuel systems because to its multipurpose capabilities. © 2023 ieee.

关键词： Microwave sensors

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Ultra-Low-Power Wearable Vibration Sensor with Highly Accurate embedded Classifier 44

Ultra-Low-Power Wearable Vibration Sensor with Highly Accura...

引用

44th Annual international conference of the ieee-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Yun, Inyeol Jeung, Jinpyeo Kim, Yoonsik Song, Yonghun Chung, Yoonyoung Pohang Univ Sci & Technol POSTECH Dept Elect Engn Pohang 37679 South Korea

ISBN: (数字)9781728127828

ISBN: (纸本)9781728127828

Reducing the power consumption of wearable sensors is a very important issue in relation to the device usage time and form factor. However, continuous wireless communication to analyze the measured signal in real-time significantly increases the power consumption of the wearable sensor. In this study, we propose a wearable vibration sensor that operates with extremely low power through an embedded signal classifier, which exhibits high accuracy and low calculation load. We demonstrate cough detection through the proposed sensor system. The result exhibits an accuracy of 93.0%, which is 24.3% higher than the conventional embedded classification algorithm. Also, the proposed approach reduces the average power consumption of the wearable sensor by 8.8 times.

关键词： Vibrations Wireless communication Power demand Power measurement Vibration measurement Sensor systems real-time systems

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Image Encryption Through Aperiodic Josephus Permutation And Novel Cyclic Shift Operation 3

Image Encryption Through Aperiodic Josephus Permutation And ...

引用

3rd international conference on Advances in computing, Communication, embedded and Secure systems, ACCESS 2023

作者： Vithayathil, Asha J. Sreekumar, A. Cochin University of Science and Technology Department of Computer Applications Cochin India

ISBN: (纸本)9798350346169

In recent years, chaos based cryptography has become a prevalent and efficient way to secure digital images because of the similarities between chaotic properties and the traits needed for encryption. This paper proposes an image encryption algorithm combining a chaotic map, Josephus problem, cyclic shift operation, and XOR operation. The proposed encryption procedure follows the traditional permutation-substitution or confusion-diffusion structure. Here, the Henon map and the novel key generation phase generate image-sensitive chaotic streams, which are used for permutation and diffusion. The aperiodic Josephus permutation and bit-level chaotic cycle shift method accomplish the permutation stage by altering the position and value of each pixel. And this proposed permutation thwarts statistical cryptanalysis by dropping the correlation between neighboring pixels to approximately equal zero. The substitution stage is achieved with modulus and XOR operations on the scrambled image and the chaotic matrix. We compare the proposed method with other recent image encryption algorithms in the simulation experiment and security analysis, and the results confirm that the proposed method has better performance and higher security. © 2023 ieee.

关键词： Cryptography

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Photovoltaic Energy Production Forecasting and Operational Analytics: A real-World Study

Photovoltaic Energy Production Forecasting and Operational A...

引用

ieee international conference on Pervasive computing and Communications (PerCom)

作者： Alexakos, Alexandros Amaxilatis, Dimitrios Zaroliagis, Christos Univ Patras Dept Comp Engn & Informat Patras Greece SparkWorks Ltd Galway Ireland Comp Technol Inst Patras Greece Press Diophantus Patras Greece

ISBN: (纸本)9781665416474

Photovoltaic energy production is one of the major parts for the shift of our societies away from fossil fuels. Their irregular nature however poses a challenge for electricity grid managers. PV energy production forecasting and monitoring is extremely important to guarantee that the grid will be able to supply consumers at all times and without any unexpected interruptions. Our goal is to provide build a system that can effectively monitor all aspects of the operation of a PV power station and provide owners, facility managers and power grid administrators with high quality forecasts and operational insights. To better understand and evaluate our work, we test our system in a real-world case study from Arta, Greece, and benchmark the effectiveness of both mathematical models and machine learning based solutions with regards to both precision, consistency and trustworthiness.

关键词： Monitoring Internet of things embedded systems Solar panels Photovoltaic systems Smart grids Forecasting Solar power output Machine Learning Random Forests Feature selection Prediction accuracy Renewable energy system

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Intelligent Mode-Locking Enabled by real-time Reinforcement Learning

Intelligent Mode-Locking Enabled by Real-Time Reinforcement ...

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2023 Asia Communications and Photonics conference/2023 international Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Wang, Jiajin Pu, Guoqing Fang, Zhiwei Luo, Chao Wu, Yong Yi, Lilin School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University State Key Lab of Advanced Communication Systems and Networks Shanghai China

ISBN: (纸本)9798350312614

A real-time embedded approach to realize intelligent mode-locked fiber lasers based on reinforcement learning is proposed. The reinforcement learning is deployed in a Field programmable gate array (FPGA) to complete the inference process and real-time control. Benefited from the dedicated quantization and deployment strategy, the FPGA finishes a single forward inference in 6.4 us, which is about 32-times faster than an Nvidia RTX-3050 GPU, and the proposed solution manifests ultrahigh power efficiency. © 2023 ieee.

关键词： FPGA intelligent mode-locked fiber lasers real-time control reinforcement learning

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Controlling the Reliability of Measuring Channels in Automated Monitoring systems

Controlling the Reliability of Measuring Channels in Automat...

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2024 international conference on Industrial Engineering, applications and Manufacturing, ICIEAM 2024

作者： Krasnov, Andrey N. Kolovertnov, Gennady Yu. Prakhova, Marina Yu. Ufa State Petroleum Technological University Department Of Automation Telecommunications And Metrology Ufa Russia

ISBN: (纸本)9798350395013

The development of automation systems for the production facilities of the oil and gas sector comprises several paths, one of which is the introduction of automated monitoring systems that can perform technical diagnostics of the facility in real-time. In many cases, using these systems can improve the reliability of the facility's operations and, in some cases, it facilitates the transition to low-staffed operations. The efficiency of these systems depends on the reliability of the data transferred over measuring channels. This article presents a reliability-control algorithm based on the direct and reverse facility models. It can identify partial probe failures, i.e. the loss of metrological reliability, based on the invariance tests of some parameters, as well as the changes in the parameters of the facility considered. Model construction uses the statistics obtained in normal, pre-emergency, and emergency operating modes of a fuel pump station. Model verification confirmed its adequacy. Using the algorithms considered as additional measuring channel control tools is recommended for any facility. © 2024 ieee.

关键词： Reliability

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