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| 1 | Performance Valuation of Joint and Crack Sealants in Cold Clhtes Using DSR and BBR Tests显示文摘 | Haithem Soliman Ahmed Shalaby Leonnie Kavanagh | | Journal of Matemls in Civil Eneeting0，20，7： | 1 |
| 2 | AWS-Policy:an extension for autonomic web service description显示文摘 | HAITHEM MEZNIA WALID CHAINBIB KHALED GHEDIRAC | 2012 | Procedia Computer Science2012，，10： | 1 |
| 3 | Predictive Current Control of Voltage-Source Inverters显示文摘 | Haithem Abu Rub | 2004 | IEEE Trans on Industrial Electronics2004，51，3： | 1 |
| 4 | Fe-clay-plate as a heterogeneous catalyst in photo-Fenton oxidation of phenol as probe molecule for water treatment 显示文摘 | Haithem Bel HadjLtaief Patrick Da Costa Patricla Beaunier | 2014 | Applied Clay Science2014，9192，： | 1 |
| 5 | Lignin turnover kinetics in an agricultural soil is monomer specific显示文摘 | Haithem Bahri Marie-France Dignac Cornelia Rumpel Daniel P. Rasse Claire Chenu André Mariotti | 2006 | Soil Biology and Biochemistry2006，，7： | 1 |
| 6 | Preddictive current control of voltage source inverters 显示文摘 | HAITHEM ABU RUB | 2004 | IEEE Transactions on Industrial Electronic2004，51，3： | 1 |
| 7 | Predictive current control of voltage-source inverters显示文摘 | HAITHEM A R JAROSLAW G ZBIGNIEW K | 2004 | IEEE Transactions on Industrial Electronic2004，51，3： | 1 |
| 8 | Predictive Current Control of Voltage--Souree Inventers 显示文摘 | Abu--Rub Haithem Guzinski Jaroslaw Krzeminski Zbigniew and Toliiyat Harnid A | 2004 | IEEE Transactions on Industrial Electronic2004，3，51： | 1 |
| 9 | Performance evaluation of joint and crack seal- ants in cold climates using DSR and BBR tests显示文摘 | Soliman Haithem Shalaby Ahmed Kavanagh Leon- nie | 2008 | Journal of Materials in Civil Engineering2008，20，7： | 1 |
| 10 | Predictive current control of voltage source inverters显示文摘 | HAITHEM A R | 2004 | IEEE Transactions on Industrial Electronics2004，51，3： | 1 |
| 11 | Perform- ance evaluation of joint and crack sealants in cold climates lsing DSR and BBR tests 显示文摘 | Haithem Soliman Ahmed Shalaby | 2008 | Journal of Materials in Civil Engineering2008，20，7： | 1 |
| 12 | Performance evaluation of joint and crack sealants in cold climates using DSR and BBR tests显示文摘 | Soliman Haithem Shalaby Ahmed Kavanagh Leonnie | | 0，，07： | 1 |
| 13 | Neuromuscular fatigue and recovery profiles in individuals with intellectual disability显示文摘Purpose: This study aimed to explore neuromuscular fatigue and recovery profiles im individuals with intellectual disability(ID) after exhausting submaximal contraction.Methods: Ten men with ID were compared to 10 men without ID. The evaluation of neuromuscular function consisted in brief(3 s) isometric maximal voluntary contraction(IMVC) of the knee extension superimposed with electrical nerve stimulation before, immediately after, and during33 min after an exhausting submaximal isometric task at 15% of the IMVC. Force, voluntary activation level(VAL), potentiated twitch(Ptw), and electromyography(EMG) signals were measured during IMVC and then analyzed.Results: Individuals with ID developed lower baseline IMVC, VAL, Ptw; and RMS/M_(max) ratio(root-mean-square value normalized to the maximal peak-to-peak amplitude of the M-wave) than controls(p < 0.05). Nevertheless, the time to task failure was significantly longer in ID vs. controls(p < 0.05). The 2 groups presented similar IMVC decline and recovery kinetics after the fatiguing exercise. However. individuals with ID presented higher VAL and RMS/M_(max) ratio declines but lower Ptw decline compared to those without ID. Moreover, individuals with ID demonstrated a persistent central fatigue but faster recovery from peripheral fatigue.Conclusion: These differences in neuromuscular fatigue profiles and recovery kinetics should be acknowledged when prescribing training programs for individuals with ID. | Rihab Borji Firas Zghal Nidhal Zarrouk Vincent Martin Sonia Sahli Haithem Rebai | 2019 | Journal of Sport and Health Science2019，8，3： | 0 |
| 14 | Chest Radiographs Based Pneumothorax Detection Using Federated Learning显示文摘Pneumothorax is a thoracic condition that occurs when a person’s lungs collapse,causing air to enter the pleural cavity,the area close to the lungs and chest wall.The most persistent disease,as well as one that necessitates particular patient care and the privacy of their health records.The radiologists find it challenging to diagnose pneumothorax due to the variations in images.Deep learning-based techniques are commonly employed to solve image categorization and segmentation problems.However,it is challenging to employ it in the medical field due to privacy issues and a lack of data.To address this issue,a federated learning framework based on an Xception neural network model is proposed in this research.The pneumothorax medical image dataset is obtained from the Kaggle repository.Data preprocessing is performed on the used dataset to convert unstructured data into structured information to improve the model’s performance.Min-max normalization technique is used to normalize the data,and the features are extracted from chest Xray images.Then dataset converts into two windows to make two clients for local model training.Xception neural network model is trained on the dataset individually and aggregates model updates from two clients on the server side.To decrease the over-fitting effect,every client analyses the results three times.Client 1 performed better in round 2 with a 79.0%accuracy,and client 2 performed better in round 2 with a 77.0%accuracy.The experimental result shows the effectiveness of the federated learning-based technique on a deep neural network,reaching a 79.28%accuracy while also providing privacy to the patient’s data. | Ahmad Almadhor Arfat Ahmad Khan Chitapong Wechtaisong Iqra Yousaf Natalia Kryvinska Usman Tariq Haithem Ben Chikha | 2023 | Computer Systems Science & Engineering2023，47，11： | 0 |
| 15 | Automatic Classification of Superimposed Modulations for 5G MIMO Two-Way Cognitive Relay Networks显示文摘To promote reliable and secure communications in the cognitive radio network,the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation.In this paper,we address the classification of superimposed modulations dedicated to 5G multipleinput multiple-output(MIMO)two-way cognitive relay network in realistic channels modeled with Nakagami-m distribution.Our purpose consists of classifying pairs of users modulations from superimposed signals.To achieve this goal,we apply the higher-order statistics in conjunction with the Multi-BoostAB classifier.We use several efficiency metrics including the true positive(TP)rate,false positive(FP)rate,precision,recall,F-Measure and receiver operating characteristic(ROC)area in order to evaluate the performance of the proposed algorithm in terms of correct superimposed modulations classification.Computer simulations prove that our proposal allows obtaining a good probability of classification for ten superimposed modulations at a low signal-to-noise ratio,including the worst case(i.e.,m=0.5),where the fading distribution follows a one-sided Gaussian distribution.We also carry out a comparative study between our proposal usingMultiBoostAB classifier with the decision tree(J48)classifier.Simulation results show that the performance of MultiBoostAB on the superimposed modulations classifications outperforms the one of J48 classifier.In addition,we study the impact of the symbols number,path loss exponent and relay position on the performance of the proposed automatic classification superimposed modulations in terms of probability of correct classification. | Haithem Ben Chikha Ahmad Almadhor | 2022 | Computers, Materials & Continua2022，，1： | 0 |
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