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检索条件"丛书名=Lecture Notes in Electrical Engineering"

共 22049 条记录，以下是121-130 订阅

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0.7 V, 215 nW Tunable Universal Gm-C Filter 55th

0.7 V, 215 nW Tunable Universal Gm-C Filter

引用

55th Meeting of the Italian Electronics Society

作者： Namdari, Ali Aiello, Orazio Caviglia, Daniele D. Univ Genoa DITEN Genoa Italy

ISBN: (纸本)9783031715204;9783031715181;9783031715174

In this paper, an ultra-low-power, inverter-based, universal Gm-C filter is proposed. The proposed filter benefits from the orthogonal tunability of center frequency (f(0)) and quality factor (Q) and is designed using 180 nm TSMC technology node parameters. To significantly reduce the proposed filter's power consumption, all transistors are biased in the subthreshold region at a 0.7 V supply voltage. Additionally, the quality factor and center frequency of the proposed filter are varied by the variations of the capacitance parameters. The power consumption for the proposed Gm-C filter is 215 nW at the center frequency of 4.5 kHz.

关键词： Low-power Inverter Gm-C Universal filter CMOS Tunablity

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Evaluation of Blockchain Security for IoT Technology Services: Survey 5th

Evaluation of Blockchain Security for IoT Technology Service...

引用

5th International Conference on Data Science, Machine Learning and Applications

作者： Hizam, Nuras Naser Saeed Shelar, Madhukar Commerce Management & Comp Sci CMCS Coll Nasik 422013 India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

People are enamoured with the Cryptocurrencies Bitcoin and Ethereum, which have recently gained enormous popularity. The success of various Cryptocurrencies is due to blockchain. Every sector is aware of and using the advantages of blockchain. Because of the daily expansion of the technological revolution, practically everything is now done digitally. As a result, security, the most important factor, is required. Blockchain acts as a super hero by offering a protected conduit for transactions. It is a chain of blocks, as the namewould imply. Digital data is referred to as a block, and the public database is referred to as a chain. It is utilized in supply chains, healthcare, property records, and other areas. The purpose of this paper to expose the implementation of the blockchain in IoT Platforms and provides an in-depth analysis of several categories of consensus protocols implemented in different blockchain systems, as well as the advantages and disadvantages of every algorithm. We additionally present an underlying comparison of several algorithms to help in better comprehend consensus protocol choosing. We elicit the IoT issues being taken into account as well as the specifics of the blockchain-based solutions.

关键词： Cryptocurrencies Bitcoin Ethereum Block chain Consensus algorithms IoT

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Accident Severity Detection Using Machine Learning Algorithms 5th

Accident Severity Detection Using Machine Learning Algorithm...

引用

5th International Conference on Data Science, Machine Learning and Applications

作者： Kumar, B. Naveen Kumar, N. Sunil Kumar, U. Naresh Annamacharya Inst Technol & Sci Autonomous Dept CSE Rajampet 516126 Andhra Pradesh India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

The mobility management skills, including the capacity to make scientific decisions can be improved as well as the reduction of personal injuries and property losses by timely and precise identification of traffic events. The detection effect is significantly impacted by the imbalance in the statistics on traffic incidents. Consequently, An technique for identifying traffic events inferred via factor analysis and adjusted random forests (FA-WRF) is developed. Analyze the flow of traffic parameters change rule to establish the first incident variable. The component analysis (FA) approach is used to minimize the original incident variables' dimension. Using the Bootstrap improved technique, establishing the information collection criteria for the training set. Upon training, The decision tree's categorization impact is measured using the MCC coefficient value. The random forest (RF) procedure's overall ability to discriminate for imbalanced data can be improved by using the tree is used as a weight value to make sure that specimens with better classification skills have more influence during the voting phase. The area under the receiver operating characteristic curve, the classification rate, and the false alarm rate, and the recognition rate are typical metrics used to evaluate the effectiveness of detecting systems. The results of the experiment show how well the FA-WRF-based model performs in terms of categorization. It does just as well when classifying imbalanced data as the Support Vector Machine does.

关键词： Random Forest Logistic Regression XGBoost Support Vector Machines

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A Comprehensive Survey on Enhancing Patient Care Through Deep Learning and IoT-Enabled Healthcare Innovations 5th

A Comprehensive Survey on Enhancing Patient Care Through Dee...

引用

5th International Conference on Data Science, Machine Learning and Applications

作者： Valaboju, Sabitha Devi, T. Rupa Devi, D. Gayathri Sudheer, P. CVR Coll Engn Hyderabad Telangana India Keshav Mem Inst Technol Hyderabad Telangana India Vignan Bharathi Inst Technol Hyderabad Telangana India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

This study explores recent transformative advancements in deep learning-based healthcare technologies, revolutionizing patient care by enabling personalized precision medicine and extending access through IoT and cyberphysical systems. Diagnostic methodologies for critical conditions like cancer, diabetes, and heart failure are examined, utilizing computational intelligence to enhance patient identification and treatment. The focus lies on electronic health records (EHRs), investigating contemporary deep learning techniques for cancer prediction and framework-based mechanisms for healthcare optimization. Key algorithms like SVMs, Autoencoders, and CNNs are explored, showing applicability in clinical settings and genomic sequence-based diagnostics. Healthcare's unique processing techniques, spanning gene-based strategies, clinical tests, observation, and diagnostic models, are scrutinized for predictive and treatment potential. Integration of statistical and medical references is highlighted for efficient predictions alongside patient-specific data. The research advocates for AI-powered DSS integration, with CNNs as potent tools for customized medical interventions, marking a significant step towards elevated patient care and precision medicine realization.

关键词： Deep learning IoT-driven Healthcare Innovations Electronic Health Records (HER) Computational intelligence

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In-Depth Analysis of the electrical Ruggedness of Double-Sided Cooled Power Modules 55th

In-Depth Analysis of the Electrical Ruggedness of Double-Sid...

引用

55th Meeting of the Italian Electronics Society

作者： Catalano, Antonio Pio Scognamillo, Ciro d'Alessandro, Vincenzo Univ Federico II Dept Elect Engn & Informat Technol Naples Italy

ISBN: (纸本)9783031715204;9783031715181;9783031715174

In this contribution, the electrical ruggedness of double-sided cooled (DSC) power modules (PMs) for energy conversion applications is explored through simulations. Attention is focused on the spacing between the interfacing substrates of these assemblies, which is closely related to the size of the bumps. First, highly detailed finite element method (FEM) simulations in COMSOL Multiphysics are employed to evaluate voltage distribution, electric field, and parasitic capacitances of these structures. Subsequently, the above assessments are used to perform realistic SPICE simulations of a typical turn-off event;the maximum electric field waveform is monitored during the turn-off to evaluate the electrical ruggedness of the assemblies. A comparison between designers' estimations and the actual performance of the DSC PMs is also presented.

关键词： Double-sided cooled electrical ruggedness FEM simulations Power modules SPICE simulations

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Machine Learning Approaches for Dairy(Milk) Quality Assurance 5th

Machine Learning Approaches for Dairy(Milk) Quality Assuranc...

引用

5th International Conference on Data Science, Machine Learning and Applications

作者： Rajini, A. Sravani, T. Bhavans Vivekananda Coll Sci Humanities & Commerc Dept Math & Stat Secunderabad India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

Milk is the basic need of people in their day-to-day life. The quality of milk is an important factor to take into consideration for optimal health because it is consumed by all age groups in various ways. In this study, we used multiple machine learning models to estimate quality of milk based on 7 different parameters. pH, temperature, taste, odor, fat, turbidity, and color are the parameters taken into consideration. To predict the quality of milk, various M.L models used were Decision Tree Classifier, Gradient Boosting, Multi-layer Perceptron, Random Forest Classification, Multinomial Regression, KNN, Support vector classifier, XGB, Naive Bayes. Our analysis found that odor and turbidity were the most significant features for predicting milk quality. It was observed that, By comparing all the models based on evaluation metrics and confusion matrix it was found that gradient boost model was the best among all the other models. The developed models can be useful for predicting milk quality in real-time and improving the efficiency of milk quality control in the dairy industry.

关键词： Milk quality Prediction XG Boost models Random forest model KNN Turbidity

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Resume Parser Using Machine Learning 5th

Resume Parser Using Machine Learning

引用

5th International Conference on Data Science, Machine Learning and Applications

作者： Srinitha, M. Mounika, N. Kiran, K. Sai Priya, V. Sathya Lanke, Pallavi BV Raju Inst Technol Dept Comp Sci & Engn Narsapur 502313 Telangana India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

Resume parsing is a crucial process for recruiters to identify suitable candidates for job vacancies. However, manual resume screening can be a time-consuming and tedious task, especially when dealing with a large volume of resumes. The use of machine learning techniques in resume parsing can automate this process and help recruiters quickly identify relevant candidates. This paper presents an abstract of a review of different approaches for resume parsing using machine learning techniques. We discuss the challenges of resume parsing, the preprocessing steps involved, the feature extraction techniques used, and the evaluation of different machine learning algorithms used for resume parsing. The "genism" library may summarize resumes for this system to use, and once classification has been completed as per the job description, prospective candidates may be rated using clustering methods to determine which resumes are most similar to the specified job description.

关键词： Resume parser Machine learning Gensim library Job description and internet-based recruitment

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Anomalous I-V Characteristics of 4H-SiC p-i-n Diode at Cryogenic Temperature 55th

Anomalous I-V Characteristics of 4H-SiC p-i-n Diode at Cryog...

引用

55th Meeting of the Italian Electronics Society

作者： Rinaldi, Nicola Di Benedetto, Luigi Licciardo, Gian Domenico Liguori, Rosalba Rubino, Alfredo Univ Salerno Dept Ind Engn Via Giovanni Paolo II 132 I-84084 Fisciano Italy

ISBN: (纸本)9783031715204;9783031715181;9783031715174

A vertical 4H-SiC p-i-n diode fabricated by Aluminum implantation is characterized in the cryogenic temperature range, i.e. lower than 123K. An anomalous characteristic is shown under current bias conditions and it can limit its use in fields of applications, like temperature sensing. To investigate the thermo-electrical behaviour, Deep Level Transient Spectroscopy (DLTS) analysis has been performed and an electron trap at 97 meV below the minimum edge of the conduction band with a capture cross section of 1.14 center dot 10(-13) cm(2) and a hole trap at 375 meV from valence band with a capture cross section of 4.4 center dot 10(-13) cm(2) have been found. We suppose that the anomalous behaviour of the I-V characteristics can be ascribed to the hole traps.

关键词： 4H polytype Silicon Carbide Cryogenic Devices DLTS

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AlN/β-Ga2O3 HEMT for Low-Noise Amplifier 27th

AlN/β-Ga2O3 HEMT for Low-Noise Amplifier

引用

27th International Symposium on VLSI Design and Test

作者： Das, Akash Tomar, Aishwarya Das, Subhankar Kumar, Rahul Birla Inst Technol & Sci Pilani Campus Pilani 333031 Rajasthan India

ISBN: (纸本)9789819783830;9789819752690;9789819752683

This study proposes an AlN/beta-Ga2O3 high electron mobility transistor (HEMT) using a 0.10 mu m gate length where AIN is used as a barrier and beta-Ga2O3 as a channel material. DC and Noise characteristics of AlN/Ga2O3 with different AIN barrier thicknesses at 1-20 GHz microwave frequencies have been explored. The simulation has been performed using the Silvaco TCAD software. The device has exhibited a high unity current gain cut-off frequency (f(t)) of 100 GHz and extrinsic transconductance of 255 mS/mm. Also, the device showed current drive capability as high as 2000 mA/mm. The microwave noise characteristics of the device were investigated from 0 to 20 GHz with respect to different gate bias voltages and drain currents. At a gate bias of -2 V and drain bias of 15 V, the device has shown a minimum noise figure (F-min) of 0.71 dB and max unilateral power gain (GU(max)) of 24 dB at 10 GHz. Also, it shows a noise resistance of 47.94 K Omega at 10 GHz, which is very appropriate for low-noise applications in the X-band frequency range. These findings indicate the expertise of AlN/Ga2O3 in the field of low-noise and high-power amplifiers.

关键词： High electron mobility transistor (HEMT) Ga2O3 Two-dimensional electron gas (2DEG) Noise figure

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High Throughput Multiple Device Diagnosis System for Hierarchical Test Designs 27th

High Throughput Multiple Device Diagnosis System for Hierarc...

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27th International Symposium on VLSI Design and Test

作者： Chhabra, Atul Nandakumar, Bharath Chillarige, Sameer Malhotra, Dushyant Grover, Vatsal Cadence Design Syst Noida India

ISBN: (纸本)9789819783830;9789819752690;9789819752683

The need for additional computational power for gaming, AI/ML, and video conferencing applications coupled with the ability to pack more transistors at lower geometries resulted in multi-core designs with 100s of identical cores packed in a SoC. Hierarchical test is a partitioned-test method designed to implement DFT and Test for these designs. This method eases computing resources and run times required for automatic test pattern generation (ATPG) on very large designs but poses unique challenges and opportunities for diagnosis. We discuss a generic diagnosis methodology for hierarchical test designs and propose a high throughput algorithm to increase the speed-up. Experiment results on industrial designs indicate no loss of diagnosis accuracy with the proposed approach and up to 15X speed-up is achieved using multiple device diagnostics mode.

关键词： Automatic test pattern generation

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