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International Conference on COMmunication Systems and NETworkS (COMSNETS)

作者： Ramakrushnan, Karthik Challa, Akhil Patil, Harshal Subramanian, Shankar C. Vivekanandan, Gunasekaran Sivaram, Sriram Indian Inst Technol Madras Dept Engn Design Chennai Tamil Nadu India Madras Engn Ind Pvt Ltd Chennai Tamil Nadu India

ISBN: (纸本)9781728131870

Wheel slip regulation (WSR) is an approach to achieve anti-lock braking, where the parameter, wheel slip ratio, is made to operate around a reference value. WSR algorithms can be rule-based or model-based. Model-based solutions require real-time information on vehicle parameters including tire model parameters that increases the challenge in their real-world implementation. Hence, this work proposes a novel triphase rule-based WSR algorithm for Heavy Commercial Road Vehicles, that employ an electro-pneumatic brake system. Since the direct measurement of wheel slip is not feasible, estimates from an Extended Kalman Filter are used to monitor and regulate slip. A real-time reference adaptation scheme is proposed to detect low friction road surfaces. The proposed algorithm is evaluated in a Hardware-in-Loop experimental setup, and shown to adapt to the road surface, prevent wheel lock, and reduce braking distance up to 19 % compared to the case without control.

关键词： Wheel slip regulation rule-based algorithm Extended Kalman Filter Reference slip Vehicle safety

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An explainable algorithm for detecting drug-induced QT-prolongation at risk of torsades de pointes (TdP) regardless of heart rate and T-wave morphology

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COMPUTERS IN BIOLOGY AND MEDICINE 2021年 131卷 104281-104281页

作者： Alahmadi, Alaa Davies, Alan Royle, Jennifer Goodwin, Leanna Cresswell, Katharine Arain, Zahra Vigo, Markel Jay, Caroline Univ Manchester Dept Comp Sci Manchester Lancs England Univ Manchester Sch Hlth Sci Div Informat Imaging & Data Sci Manchester Lancs England CRUK Manchester Inst Digital Expt Canc Med Team Manchester Lancs England Christie NHS Fdn Manchester Lancs England Manchester Univ NHS Fdn Trust NIHR Manchester Biomed Res Ctr BRC Canc Precis Med & Canc Prevent & Early Detect Manchester Lancs England

Torsade de points (TdP), a life-threatening arrhythmia that can increase the risk of sudden cardiac death, is associated with drug-induced QT-interval prolongation on the electrocardiogram (ECG). While many modern ECG machines provide automated measurements of the QT-interval, these automated QT values are usually correct only for a noise-free normal sinus rhythm, in which the T-wave morphology is well defined. As QT-prolonging drugs often affect the morphology of the T-wave, automated QT measurements taken under these circumstances are easily invalidated. An additional challenge is that the QT-value at risk of TdP varies with heart rate, with the slower the heart rate, the greater the risk of TdP. This paper presents an explainable algorithm that uses an understanding of human visual perception and expert ECG interpretation to automate the detection of QT-prolongation at risk of TdP regardless of heart rate and T-wave morphology. It was tested on a large number of ECGs (n = 5050) with variable QT-intervals at varying heart rates, acquired from a clinical trial that assessed the effect of four known QT-prolonging drugs versus placebo on healthy subjects. The algorithm yielded a balanced accuracy of 0.97, sensitivity of 0.94, specificity of 0.99, F1-score of 0.88, ROC (AUC) of 0.98, precision-recall (AUC) of 0.88, and Matthews correlation coefficient (MCC) of 0.88. The results indicate that a prolonged ventricular repolarisation area can be a significant risk predictor of TdP, and detection of this is potentially easier and more reliable to automate than measuring the QT-interval distance directly. The proposed algorithm can be visualised using pseudo-colour on the ECG trace, thus intuitively `explaining' how its decision was made, which results of a focus group show may help people to self-monitor QT-prolongation, as well as ensuring clinicians can validate its results.

关键词： Drug-induced LQTS QT-Prolongation Torsades de pointes TdP Automated ECG interpretation Human-like algorithm rule-based algorithm Visual perception Machine perception Explainable AI

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Detection of Fake Tweets Using Sentiment Analysis

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SN Computer Science 2020年第2期1卷 1-7页

作者： Monica, C. Nagarathna, N. Department of Computer Science B. M. S. College of Engineering Bengaluru 560019 India

Social platform is one of the most commonly used sites in the today’s world, and people from different places exchange information, express opinions, etc. Twitter is one of the most convenient platforms where Twitter data are frequently used for research and are one of the largest micro-blogging platforms. As there is an increase in number of spam accounts, there is a need to distinguish between genuine and fake user accounts. In Twitter, there is rise in the number of spam accounts, to spread malicious information among the users. So, to overcome the problem of spam in Twitter, an analysis of the opinions and the emotions of users in the form of tweets have been carried out. In this paper, we present a model which performs sentimental analysis on real-time data that are collected on a particular topic of interest for the users who recently posted on that topic. Using this model, we compute the sentiment score of each user with the content-based features to detect spam in Twitter. The proposed method makes use of a custom rule-based algorithm for detection of bots and compares it with few other algorithms like MLP, decision tree and random forest to see how efficient the model is in detection of spam accounts. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Deep learning algorithm Machine learning algorithm rule-based algorithm Sentiment analysis Spam Twitter

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Implementing rule-based and Naive Bayes algorithm on Incremental Sentiment Analysis System for Indonesian Online Transportation Services Review 10

Implementing Rule-based and Naive Bayes Algorithm on Increme...

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10th Annual International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： Fiarni, Cut Maharani, Herastia Irawan, Enriko Inst Teknol Harapan Bangsa Dept Informat Syst Bandung Indonesia

ISBN: (纸本)9781538647394

The emerging trend on smartphone application and service use on a daily basis, has also increased the volume of online opinion regarding various topics on the internet. In Indonesia, one of the most popular topics to share, post and comment is online-based transportation service (TNCs). These comments could lead to valuable knowledge that would be tremendous assets for supporting critical business intelligence applications. The knowledge gained from social media can potentially lead to the development of novel services that are better tailored to users' needs and also meet the objectives of businesses offering them. The problem to build an effective Indonesian sentiment analysis system is that there is still no availability of the corpus, complete with each word characteristic, whether it subjective, adjective, adverb, noun, etc. Another problem is because their cultural heritage, or for politeness reason, Indonesian people often used negation in their sentence. So instead of saying "ugly", they say "not good", or instead of saying expensive, they said "not cheap", which could lead to miss-classify of the sentiment. Thus, this research focus on building model that has the ability to classify TNC element target on its sentiment class, by considering negation form sentences and then implement it in the proposed sentiment analysis system. Another important feature is system's ability to learning new keywords for TNC elements and sentiment. This proposed approach would use rule based algorithm to classify target object, the polarity of sentiment and negation from online opinion. And used Naive Bayes algorithm for the incremental feature. Result from this study show that the proposed system is able to classify user opinion with 90% precision and 70% recall. This concludes that from evaluation results, the proposed algorithm performs well to automatically analyze sentiment.

关键词： rule-based algorithm Naive Bayes Negation Sentiment Analysis Indonesian Online Transportation Service

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In-season early mapping of rice area and flooding dynamics from optical and SAR satellite data

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EUROPEAN JOURNAL OF REMOTE SENSING 2019年第1期52卷 206-220页

作者： Stroppiana, D. Boschetti, Mirco Azar, R. Barbieri, M. Collivignarelli, F. Gatti, L. Fontanelli, G. Busetto, L. Holecz, F. CNR Sez Secondaria Milano Ist Rilevamento Elettromagnet Ambiente Via Bassini 15 I-20133 Milan Italy SARMAP SA Cascine Di Barico Purasca Switzerland Rothamsted Harpenden Herts England

Rice mapping products were derived from Sentinel-1A and Landsat-8 OLI multi-temporal imagery over Northern Italy at the early stages of the 2015 growing season. A rule-based algorithm was applied to synthetic statistical metrics (TSDs-Temporal Spectra Descriptors) computed from temporal datasets of optical spectral indices and SAR backscattering coefficient. Temporal series are available up to the tillering/full canopy cover stage which is identified as the optimum timing for delivering in-season information on rice area (i.e. mid July). The approach relies on a-priori knowledge on crop dynamics to adapt time horizons for TSD computation and thresholds to local conditions. Output products consist of maps of rice cultivated areas, rice seeding techniques (dry and flooded rice) and flooding practices. Validation showed rice mapping overall accuracy to be 87.8% with commission and omission errors of 3.5% and 24.7%, respectively. Mapping of rice seeding technique showed good agreement with farmer declarations aggregated at the municipality scale (dry rice r(2)=0.71 and flooded rice r(2)=0.91). Finally, flood maps have an overall accuracy above 70%. Geo-products on rice areas and flooding occurrence are relevant information for water management at regional scale especially during summer in presence of multiple crops and water shortage.

关键词： Paddy rice dry seeding rice rule-based algorithm Landsat OLI sentinel 1

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A real-time walking pattern recognition method for soft knee power assist wear

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2020年第3期17卷

作者： Wang, Wenkang Zhang, Liancun Liu, Juan Zhang, Bainan Huang, Qiang Beijing Inst Technol Beijing Adv Innovat Ctr Intelligent Robots & Syst 5 South Zhongguancun St Beijing 100081 Peoples R China Beijing Inst Technol Sch Mechatron Engn Beijing Peoples R China Beijing Univ Civil Engn & Architecture Beijing Adv Innovat Ctr Intelligent Robots & Syst Sch Elect & Informat Engn Beijing Peoples R China China Acad Space Technol Inst Manned Space Syst Engn Beijing Peoples R China Beijing Inst Technol Key Lab Biomimet Robots & Syst Minist Educ Beijing Peoples R China

Real-time recognition of walking-related activities is an important function that lower extremity assistive devices should possess. This article presents a real-time walking pattern recognition method for soft knee power assist wear. The recognition method employs the rotation angles of thighs and shanks as well as the knee joint angles collected by the inertial measurement units as input signals and adopts the rule-based classification algorithm to achieve the real-time recognition of three most common walking patterns, that is, level-ground walking, stair ascent, and stair descent. To evaluate the recognition performance, 18 subjects are recruited in the experiments. During the experiments, subjects wear the knee power assist wear and carry out a series of walking activities in an out-of-lab scenario. The results show that the average recognition accuracy of three walking patterns reaches 98.2%, and the average recognition delay of all transitions is slightly less than one step.

关键词： Walking pattern recognition rule-based algorithm real-time recognition inertial measurement units soft knee power assist wear

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Design and performance evaluation of series hybrid electric vehicle using backward model

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JOURNAL OF ENGINEERING-JOE 2020年第11期2020卷 1095-1102页

作者： Rana, Lalit B. Shrestha, Ashish Phuyal, Sudip Mali, Bijen Lakhey, Ojaswi Maskey, Ramesh K. Pokhara Univ Dept Elect & Elect Engn Kaski 33700 Nepal Kathmandu Univ Dept Elect & Elect Engn Dhulikhel 45200 Nepal Kathmandu Univ Ctr Elect Power Engn Dhulikhel 45200 Nepal NEA Engn Co Kathmandu 44600 Nepal Kathmandu Univ Sch Engn Dhulikhel 45200 Nepal

Hybrid electric vehicles (HEVs) are becoming a more promising means of transportation mainly because of environmental issues and depletion of fossil fuel resources. This study deals with the basic theoretical knowledge for describing their behaviour in acceleration, cruising, deceleration and control strategies. Preliminary design calculations for a series HEV bus are carried out in MATLAB environment using a backward model. In addition to this, the rule-based algorithm is implemented to compare fuel consumption, battery's state of charge (SOC) and energy-saving possibilities. The model is firstly tested for highway and city drive cycles for SOC limits of 0.6 and 0.7. Further, prolonged simulations are conducted for both the highway and city drive cycles for four different SOC limits and three parameters of the hybrid vehicle (SOC of battery, fuel power and average charging power) are observed and compared with each other. The performance indexes of both drive cycles are estimated and it is found that higher performance indexes are obtained using power-split mode and greater SOC lower limit as internal combustion engine is more efficient when operated in this mode.

关键词： hybrid electric vehicles battery powered vehicles energy consumption energy conservation performance evaluation series hybrid electric vehicle backward model environmental issues power-split mode highway drive cycles series HEV bus design cruising strategies transportation acceleration strategies SOC limits deceleration strategies city drive cycles energy-saving battery state of charge fuel consumption rule-based algorithm MATLAB environment control strategies fossil fuel resources depletion

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DENTITION LABELING AND ROOT CANAL RECOGNITION USING GAN AND rule-based SYSTEM 24

DENTITION LABELING AND ROOT CANAL RECOGNITION USING GAN AND ...

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International Conference on Technologies and Applications of Artficial Intelligence (TAAI)

作者： Chin, Chiun-Li Lin, Jo-Wei Wei, Chia-Shin Hsu, Ming-Chen Med Informat Chung Shan Med Univ Dept Taichung Taiwan

ISBN: (纸本)9781728146669

Dentition identification and root canal are very common in dentistry. Dentition identification helps dentists to diagnose the teeth conditions of patient and discuss about their treatments, while root canal is one of the common treatments. The goal of this paper is to label tooth dentition and identify root canal via GAN and rule-based algorithm. Before inputting images into GAN, the original images were sharpened to make the learning task easier. Next, we use the rule-based algorithm to identify root canal. For evaluating proposed method, we invite three dentists to evaluate the accuracy of the results, and they consider that the results are reliable. We also discuss the impact that iterations have on accuracy. The model becomes stable when iteration comes to 12000, and the accuracy reaches 93.7%.

关键词： tooth dentition root canal GAN rule-based algorithm

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A rule-based electronic phenotyping algorithm for detecting clinically relevant cardiovascular disease cases

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BMC Research Notes 2017年第1期10卷 1-7页

作者： Esteban, Santiago Rodríguez Tablado, Manuel Ricci, Ricardo Ignacio Terrasa, Sergio Kopitowski, Karin Family and Community Medicine Division Hospital Italiano de Buenos Aires Tte. J. D. Peron Buenos Aires 4272 Argentina Research Department Instituto Universitario Del Hospital Italiano de Buenos Aires Buenos Aires Argentina

Background: The implementation of electronic medical records (EMR) is becoming increasingly common. Error and data loss reduction, patient-care efficiency increase, decision-making assistance and facilitation of event surveillance, are some of the many processes that EMRs help improve. In addition, they show a lot of promise in terms of data collection to facilitate observational epidemiological studies and their use for this purpose has increased significantly over the recent years. Even though the quantity and availability of the data are clearly improved thanks to EMRs, still, the problem of the quality of the data remains. This is especially important when attempting to determine if an event has actually occurred or not. We sought to assess the sensitivity, specificity, and agreement level of a codes-based algorithm for the detection of clinically relevant cardiovascular (CaVD) and cerebrovascular (CeVD) disease cases, using data from EMRs. Methods: Three family physicians from the research group selected clinically relevant CaVD and CeVD terms from the international classification of primary care, Second Edition (ICPC-2), the ICD 10 version 2015 and SNOMED-CT 2015 Edition. These terms included both signs, symptoms, diagnoses and procedures associated with CaVD and CeVD. Terms not related to symptoms, signs, diagnoses or procedures of CaVD or CeVD and also those describing incidental findings without clinical relevance were excluded. The algorithm yielded a positive result if the patient had at least one of the selected terms in their medical records, as long as it was not recorded as an error. Else, if no terms were found, the patient was classified as negative. This algorithm was applied to a randomly selected sample of the active patients within the hospital's HMO by 1/1/2005 that were 40-79 years old, had at least one year of seniority in the HMO and at least one clinical encounter. Thus, patients were classified into four groups: (1) Negative patients (2) P

关键词： Cardiovascular disease Cerebrovascular disease Electronic medical records Electronic phenotyping algorithms rule-based algorithm

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A rule-based energy management scheme for uninterrupted electric vehicles charging at constant price using photovoltaic-grid system

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RENEWABLE ENERGY 2018年 125卷 384-400页

作者： Bhatti, Abdul Rauf Salam, Zainal Govt Coll Univ Faisalabad Dept Elect Engn Faisalabad 38000 Pakistan UTM Ctr Elect Energy Syst Johor Baharu 81310 Johor Malaysia

This work proposes a rule-based energy management scheme (REMS) for electric vehicle (EV) charging from photovoltaic-grid(PV-grid) system. The main feature of this scheme is that it provides uninterrupted daytime charging at a constant price. In order to simulate the system, the models of PV output power, EV power demand, state of charge (SOC) estimation of energy storage unit (ESU) and grid electricity prices are developed. The uninterrupted and constant price charging is achieved by managing the energy flow between PV, ESU and grid according to the rules defined by REMS. Furthermore, the valley filling operation is implemented during the grid off-peak hours. The resiliency of REMS is validated under various weather conditions, different ESU prices and at grid parities. For comparison, its performance is benchmarked against the standard grid-based EV charging. The results demonstrate a decline in charging price by 16.1% besides reducing the burden on the grid by 93.7% with the implementation of REMS. In addition, the vehicle-to-grid (V2G) technology is incorporated in the charging system to improve the payback schedule of the existing PV-grid system. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Constant price charging Renewable energy Electric vehicles Energy management scheme Photovoltaic-grid system rule-based algorithm

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