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Liver Ailment Prediction Using Random Forest Model

computers, Materials & Continua 2023年第1期74卷 1049-1067页

作者： Fazal Muhammad Bilal Khan Rashid Naseem Abdullah A Asiri Hassan A Alshamrani Khalaf A Alshamrani Samar M Alqhtani Muhammad Irfan Khlood M Mehdar Hanan Talal Halawani Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan City University of Science and Information Technology PeshawarPakistan Department of IT and Computer Science Pak-Austria Fachhochschule Institute of Applied Sciences and TechnologyHaripurPakistan Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia

Today,liver disease,or any deterioration in one’s ability to survive,is extremely common all around the *** research has indicated that liver disease is more frequent in younger people than in older *** the liver’s capability begins to deteriorate,life can be shortened to one or two days,and early prediction of such diseases is *** several machine learning(ML)approaches,researchers analyzed a variety of models for predicting liver disorders in their early *** a result,this research looks at using the Random Forest(RF)classifier to diagnose the liver disease early *** dataset was picked from the University of California,Irvine ***’s accomplishments are contrasted to those of Multi-Layer Perceptron(MLP),Average One Dependency Estimator(A1DE),Support Vector Machine(SVM),Credal Decision Tree(CDT),Composite Hypercube on Iterated Random Projection(CHIRP),K-nearest neighbor(KNN),Naïve Bayes(NB),J48-Decision Tree(J48),and Forest by Penalizing Attributes(Forest-PA).Some of the assessment measures used to evaluate each classifier include Root Relative Squared Error(RRSE),Root Mean Squared Error(RMSE),accuracy,recall,precision,specificity,Matthew’s Correlation Coefficient(MCC),F-measure,and *** has an RRSE performance of 87.6766 and an RMSE performance of 0.4328,however,its percentage accuracy is *** widely acknowledged result of this work can be used as a starting point for subsequent *** a result,every claim that a new model,framework,or method enhances forecastingmay be benchmarked and demonstrated.

关键词： Liver ailment random forest machine learning

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A Survey on Digital Twins: Enabling Technologies, Use Cases, Application, Open Issues, and More

IEEE Journal of Selected Areas in Sensors

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IEEE Journal of Selected Areas in Sensors 2025年 2卷 84-107页

作者： Hassija, Vikas Chamola, Vinay De, Rajdipta Das, Soham Chakrabarti, Arjab Sangwan, Kuldip Singh Pandey, Amit Deemed to be University School of Computer Engineering Bhubaneswar751024 India BITS-Pilani Department of Electrical and Electronics Engineering Pilani Campus Pilani333031 India BITS Pilani Department of Mechanical Engineering Pilani Campus Pilani333031 India Bennett University Computer Science Engineering and Technology Department Greater Noida201310 India

Digital Twins, sophisticated digital replicas of physical entities, have been gaining significant attention, especially after NASA's endorsement, and are poised to revolutionize numerous fields, such as medicine and construction. These advanced models offer dynamic, real-time simulations, leveraging enabling technologies, such as artificial intelligence, machine learning, IoT, cloud computing, and Big Data analytics to enhance their functionality and applicability. In the medical field, Digital Twins facilitate personalized treatment plans and predictive maintenance of medical equipment by simulating human organs with precision. In construction, they enable efficient building design and urban planning, optimizing resource use, and reducing costs through predictive maintenance. Startups are innovatively employing Digital Twins in various sectors, from smart cities - where they optimize traffic flow, energy consumption, and waste management - to industrial machinery, ensuring predictive maintenance and minimizing downtime. This survey delves into the diverse use cases, market potential, and challenges of Digital Twins, such as data security and interoperability, while emphasizing their transformative impact on industries. The future prospects are promising, with continuous advancements in AI, ML, IoT, and cloud computing driving further expansion and application of Digital Twin technologies. © 2024 IEEE.

关键词： Predictive maintenance

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Simultaneous partial discharge and current measurements in a needle-plane configuration at different pressures 23

Simultaneous partial discharge and current measurements in a...

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23rd International School on Condensed Matter Physics on Recent Progress in Advanced Materials and Applications, ISCMP 2024

作者： Gillis, T. Fagnard, J.-F. Vanderbemden, P. Department of Electrical Engineering and Computer Science Montefiore Institute B28 University of Liège Belgium

Phase-resolved partial discharge (PRPD) measurement has been used for decades as a method of monitoring defects in electrically insulating materials. More recently, it has seen a renewed interest in the context of flash sintering, a novel ceramic densification process where the sample to be densified is subjected to an electric field in addition to the usual application of heat. In the context of flash sintering, the monitoring of partial discharge (PD) activity has shown that this activity increases when approaching the onset of the thermal runaway phenomenon leading to the quick densification of the material, and is influenced by environmental factors such as relative humidity or pressure. A new microcontroller-based PRPD measurement system architecture has recently been proposed as a means to explore this PD activity in further details. While PDRD measurement is traditionally carried out by comparing the measured partial discharge pattern to the waveform of the voltage applied to the device under test (DUT), we show in this work that expanding this bespoke measurement system to be able to simultaneously monitor the waveform of the current going through the DUT allows for the collection of data related to the electrical power transferred to the DUT during the process that displays peculiar features. In the present work, the DUT consists of a classical needle-plane setup. As pressure decreases down from atmospheric levels, the threshold voltage leading up to the apparition of discharges decreases following a trend similar to the classical Paschen curve. Additionally, the nature of the discharge activity transitions from low-amplitude, rapid-firing tightly packed trains of pulses to high-amplitude, longer-lasting and more spread out pulses. Simultaneous measurement of the discharges, applied voltage and current going through the DUT shows that this second type of discharge activity can be synchronous with an asymmetric, distorted current waveform having the same per

关键词： Threshold voltage

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Image-based Criticality-Aware Fire Detection

Image-based Criticality-Aware Fire Detection

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2024 International Conference on Frontiers of Information Technology, FIT 2024

作者： Arshad, Alina Shamsi, Jawwad Ahmed Khan, Muhammad Burhan Bawany, Narmeen Zakaria Department of Software Engineering National University of Computer and Emerging Sciences Karachi Pakistan Department of Computer Science National University of Computer and Emerging Sciences Karachi Pakistan Department of Electrical Engineering National University of Computer and Emerging Sciences Karachi Pakistan Faculty of Science Jinnah University for Women Karachi Pakistan

ISBN: (纸本)9798331510503

Context-aware fire detection is a significant task in the era of new urban monitoring. Severe damage might result from fire events. To minimize the occurrence of these events, timely detection of fire accidents is necessary. Various machine-learning and deep learning methods are used for fire detection. Most of them do not focus on the extent of the fire or the damage it causes. All these methods need the detection of the criticality of the fire event. This work proposes an identification system based on Large Vision Models (LVMs) for fire detection. We proposed an intelligent criticality-aware fire detection system that can detect fire and its varying scales from small to large and generate alarming alerts accordingly. The model integrates advanced computer vision techniques with LVMs to explain the hidden context in a textual format. The system is tested on real-time data collected from surveillance cameras and achieves an accuracy of 86.67% in correctly identifying the context-based criticality of the fire events depicted in the input data. This proposed framework can revolutionize surveillance applications by enhancing security and responding to crucial fire incidents in real-time. The system provides an efficient method for allocating resources and facilitates rapid response to incidents to prioritize activities intelligently. Using this approach, we identified and prioritized fire incidents in the urban environment. © 2024 IEEE.

关键词： Fire detectors

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A Scalable Open-Set ECG Identification System Based on Compressed CNNs

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IEEE Transactions on Neural Networks and Learning Systems 2023年第8期34卷 4966-4980页

作者： Wu, Shun-Chi Wei, Shih-Ying Chang, Chun-Shun Swindlehurst, A. Lee Chiu, Jui-Kun National Tsing Hua University Department of Engineering and System Science Hsinchu30013 Taiwan University of California at Irvine Department of Electrical Engineering and Computer Science IrvineCA92697 United States

Deep learning (DL) is known for its excellence in feature learning and its ability to deliver high-accuracy results. Its application to ECG biometric recognition has received increasing interest but is also accompanied by several deficiencies. In this study, we focus on applying DL, especially convolutional neural networks (CNNs), to ECG biometric identification to address these deficiencies. Using prestored user-specific feature vectors, the proposed scheme can exclude unregistered subjects to realize 'open-set' identification. With the help of its scalable structure and 'transfer learning,' new subjects can be enrolled in an existing system without the need for storing the ECGs of those previously enrolled. Finally, schemes based on the quantum evolutionary algorithm (QEA) are presented to prune unnecessary filters in the proposed CNN model. The performance of the proposed scheme was evaluated using the ECGs of 285 subjects from the PTB dataset. The experimental results demonstrate an identification rate of more than 99% in closed-set identification. Although incorporating the proposed method for unregistered subject exclusion degraded the identification performance slightly, the ability of the approach to resist a dictionary attack was evident. Finally, using the QEA-based filter pruning method and its two-stage extension reduced the number of floating-point operations required to complete one identity recognition to 1.20% and 0.22% of the original value without significantly impacting the identification accuracy. © 2012 IEEE.

关键词： Biometrics

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A Fine Grained Stochastic Geometry-Based Analysis on LEO Satellite Communication Systems

IEEE Networking Letters

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IEEE Networking Letters 2023年第4期5卷 237-240页

作者： Sun, Yanshi Ding, Zhiguo Hefei University of Technology School of Computer Science and Information Engineering Hefei230009 China Khalifa University Department of Electrical Engineering and Computer Science Abu Dhabi United Arab Emirates The University of Manchester Department of Electrical and Electronic Engineering ManchesterM13 9PL United Kingdom

Recently, stochastic geometry has been applied to provide tractable performance analysis for low earth orbit (LEO) satellite networks. However, existing works mainly focus on analyzing the 'coverage probability', which provides limited information. To provide more insights, this letter provides a more fine grained analysis on LEO satellite networks modeled by a homogeneous Poisson point process (HPPP). Specifically, the distribution and moments of the conditional coverage probability given the point process are studied. The developed analytical results can provide characterizations on LEO satellite networks, which are not available in existing literature, such as 'user fairness' and 'what fraction of users can achieve a given transmission reliability'. Simulation results are provided to verify the developed analysis. Numerical results show that, in a dense satellite network, it is beneficial to deploy satellites at low altitude, for the sake of both coverage probability and user fairness. © 2019 IEEE.

关键词： Stochastic systems

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On the Online Weighted Non-Crossing Matching Problem 19

On the Online Weighted Non-Crossing Matching Problem

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19th Scandinavian Symposium on Algorithm Theory, SWAT 2024

作者： Boyar, Joan Kamali, Shahin Larsen, Kim S. Lavasani, Ali Mohammad Li, Yaqiao Pankratov, Denis Department of Mathematics and Computer Science University of Southern Denmark Odense Denmark Department of Electrical Engineering and Computer Science York University Toronto Canada Department of CSSE Concordia University Montreal Canada

ISBN: (纸本)9783959773188

We introduce and study the weighted version of an online matching problem in the Euclidean plane with non-crossing constraints: 2n points with non-negative weights arrive online, and an algorithm can match an arriving point to one of the unmatched previously arrived points. In the vanilla model, the decision on how to match (if at all) a newly arriving point is irrevocable. The goal is to maximize the total weight of matched points under the constraint that straight-line segments corresponding to the edges of the matching do not intersect. The unweighted version of the problem was introduced in the offline setting by Atallah in 1985, and this problem became a subject of study in the online setting with and without advice in several recent papers. We observe that deterministic online algorithms cannot guarantee a non-trivial competitive ratio for the weighted problem. We study various regimes of the problem which permit non-trivial online algorithms. In particular, when weights are restricted to the interval [1, U] we give a deterministic algorithm achieving competitive ratio Ω ( 2−2√logU). We also prove that deterministic online algorithms cannot achieve competitive ratio better than O ( 2−√logU) . Interestingly, we establish that randomization alone suffices to achieve competitive ratio 1/3 even when there are no restrictions on the weights. Additionally, if one allows an online algorithm to revoke acceptances, then one can achieve a competitive ratio ≈ 0.2862 deterministically for arbitrary weights. We also establish a lower bound on the competitive ratio of randomized algorithms in the unweighted setting, and improve the best-known bound on advice complexity to achieve a perfect matching. © Joan Boyar, Shahin Kamali, Kim S. Larsen, Ali Mohammad Lavasani, Yaqiao Li, and Denis Pankratov.

关键词： Geometry

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Reliable and secure memristor-based chaotic communication against eavesdroppers and untrusted foundries

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Discover Internet of Things 2023年第1期3卷 1-17页

作者： Vishwakarma, Rahul Monani, Ravi Hedayatipour, Ava Rezaei, Amin Department of Computer Engineering & amp Computer Science California State University Long Beach Long BeachCA United States Department of Electrical Engineering California State University Long Beach Long BeachCA United States

Chaos is a deterministic phenomenon that occurs in a non-linear dynamic system under specific condition when the trajectories of the state vector become periodic and extremely sensitive to the initial conditions. While traditional resistor-based chaotic communications are primarily concerned with the safe transfer of information across networks, the transceivers themselves can be compromised due to outsource manufacturing. With the growth of wireless sensors in resource-constrained implantable and wearable devices, chaotic communication may be a good fit if the information transmitted is reliable and the transmitter devices are secure. We believe that memristor, as the fourth fundamental two-terminal circuit element, can close the gap between reliable communication and secure manufacturing since its resistance can be programmed and saved by the designer and not the foundry. Thus, in this paper, we propose a memristor-based Chua’s chaotic transceiver that is both reliable in the presence of eavesdroppers and secure against untrusted foundries. Specifically, we consider the pair of transmitter and receiver under the same memristor value to show the possibility of uninterrupted communication as well as cases where different values of memristors are used to find out the possible range in which the message can still be meaningfully decoded. Experimental results confirm that both reliable communication and secure design can be achieved via our proposed memristor-based chaos transceivers. © The Author(s) 2023.

关键词： Wearable technology

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IMPACT ASSESSMENT OF THE ORDER TYPES MIX IN THE GREEK DAY-AHEAD ELECTRICITY MARKET 14

IMPACT ASSESSMENT OF THE ORDER TYPES MIX IN THE GREEK DAY-AH...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Moustakas, Konstantinos Papazoglou, Georgios K. Bakirtzis, Emmanouil A. Karangelos, Efthymios Papavasiliou, Anthony Hellenic Energy Exchange S A Athens Greece School of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Electrical Engineering and Computer Science Universite de Liege Liege Belgium

ISBN: (纸本)9781837242689

The Greek Day-Ahead Electricity Market facilitates a diverse array of order types and offers participants a plethora of choices. While Block Orders are theoretically supported, their accessibility is confined to a subset of market participants so as to ensure the Market Clearing Price formation and the technical feasibility of the resulting Market Schedules. This paper presents a quantitative analysis of the implications of lifting the currently applicable restrictions on the availability of Block Orders in the Greek Day-Ahead Electricity Market, based on past historical data. Clustering techniques are used to convert anonymized past Hourly Hybrid Orders into plausible Block Orders A market clearing simulator is then used to derive the outcome of the market given the created plausible Block Orders. Simulations are conducted under Coupling and Isolated conditions for three Indicative weeks in 2022 and while exploring various scenarios for the specifications of the new Block Orders and the categories of participants who could use them. Assessment metrics encompass Marginal Clearing Price (MCP) statistics, instances of Paradoxically Rejected Block Orders, and Lost Opportunity Cost, shedding light on whether restrictions should be upheld or mitigated. © The Institution of engineering & Technology 2024.

关键词： Costs

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Causal Digital Twins for Physical System Control 59

Causal Digital Twins for Physical System Control

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59th Annual Conference on Information sciences and Systems, CISS 2025

作者： Mohseni-Sehdeh, Saeed Saad, Walid Sakaguchi, Kei Yu, Tao Virginia Tech Bradley Department of Electrical and Computer Engineering AlexandriaVA22305 United States Institute of Science Tokyo Department of Electrical and Electronic Engineering Tokyo Japan

ISBN: (纸本)9798331513269

Digital twins (DTs) are virtual representations of physical systems, replicating their behavior, dynamics, and interactions with the environment. Hosted on computational platforms, DTs have access to more extensive information and computational power than their physical counterparts (PTs), making them suitable for control applications. This paper proposes a novel DT-based control architecture that leverages causal learning to achieve autonomous control. In this framework, the DT employs causal inference to determine the desired system behavior and, subsequently, instructs the PT accordingly. By incorporating causal learning, a DT can gain self-training capabilities, enabling it to generate and analyze hypothetical scenarios based on cause-and-effect relationships. Simulation results show that DT-based control outperforms the traditional local control method by 49% in terms of the tracking performance measured through the mean squared error. Additionally, causal learning demonstrates 16% better tracking performance over statistical learning in a self-training scenario, as measured by the mean squared error. © 2025 IEEE.

关键词： Digital elevation model

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