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The Palestinian Terrestrial Vertebrate Fauna Preserved at the Biology Exhibitions of the Universities of the Gaza Strip

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Research in Ecology 2020年第4期2卷 9-21页

作者： Abdel Fattah N Abd Rabou nour j musallam Eman j musallam Kamal E Elkahlout Kamal j Elnabris Tarek A El-Bashiti Ismail I Abdel Aziz Reham M Ishneiwra Eqbal S Radwan Hana S Saada Ashraf A Shafei Nedal A Fayyad Saleh N Mwafy Huda E Abu Amra Ramy A Abu Alajeen Mohammed F Abu Owda Randa N Alfarra Haifaa A Hassouna Reem A Hassouna Mohammed R Al-Agha Mohammed A Abd Rabou Department of Biology and Biotechnology Islamic University of GazaGaza StripPalestine Department of English Islamic University of GazaGaza StripPalestine Department of Biology Al-Azhar UniversityGaza StripPalestine Department of Biology Al-Aqsa UniversityGaza StripPalestine Department of Geography Al-Aqsa UniversityGaza StripPalestine Department of Curricula and Teaching Methods Islamic University of GazaGaza StripPalestine Department of Curricula and Teaching Methods Ministry of EducationGaza StripPalestine Department of Pharmaceutical Sciences University of PalestineGaza StripPalestine Department of Environment and Earth Sciences Islamic University of GazaGaza StripPalestine Department of Information Technology University College of Applied SciencesGaza StripPalestine

The Gaza Strip(365 km^(2))of Palestine(27,000 km^(2))is home to a wealth of terrestrial vertebrate *** of these faunistic species find their ways to preservation at the local ***,the current study comes to document the Palestinian terrestrial vertebrate fauna acquired by the biology exhibitions(BEs)of Al-Azhar University,Islamic University of Gaza and Al-Aqsa University that are located at the Gaza City of the Gaza *** amphibians,reptiles,birds and mammals preserved at BEs of the universities in question were surveyed and scientifically classified during a three-month period extending from january to March,*** study showed that all BEs of local universities are underdeveloped,lacking attention and suffer from specimen scarcity and good *** BE at Al-Azhar University is the best in the arrangement and preservation of bird specimens.A total number of 200 specimens belonging to 54 terrestrial vertebrate fauna species,39 families and 17 orders was recorded at *** constituted 40.7%of the total species recorded,followed by birds(38.9%),mammals(14.8%)and amphibians(5.6%).The Islamic University of Gaza was considered the best in terms of the number of preserved species(39.8%),followed by Al-Azhar University(36.3%)and Al-Aqsa University(23.9%).The Common Toad(Bufo viridis)was the most preserved among the amphibian species *** was the biggest reptilian order,comprising 20 species(8 lizards and 12 snakes),with the Syrian Black Snake(Coluber jugularis asianus)was the *** Palestine Viper(Vipera palaestinae)is endemic to Palestine and most venomous and dangerous to human *** Great White Pelican(Pelecanus onocrotalus)was the largest Palestinian bird preserved at BE of Al-Azhar *** Egyptian Mongoose(Herpestes ichneumon)and the Common Badger(Meles meles)were the biggest mammalian specimens preserved,while the Palestine Mole-rat(Spalax leucodon ehrenbergi)was the only Palestine endemic spe

关键词： Terrestrial vertebrate fauna Preservation Biology exhibitions Gaza universities Gaza Strip Palestine

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Resolution of Unity of Generalized Bargmann Spaces by means of Displaced Fock states

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Chinese Physics Letters 2002年第11期19卷 1576-1578页

作者： nour Eddine Askour and Zouha r Mouayn Department of Mathematics Faculty of Sciences and Technics (M’Ghila)

We resolve the unity of generalized Bargmann spaces in C^n [j. Math. Phys. 41 (2000) 3507] by means of displaced Fock states

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Feature extraction for machine learning-based intrusion detection in IoT networks

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Digital Communications and Networks 2024年第1期10卷 205-216页

作者： Mohanad Sarhan Siamak Layeghy nour Moustafa Marcus Gallagher Marius Portmann University of Queensland BrisbaneQLD4072Australia University of New South Wales CanberraACT2612Australia

A large number of network security breaches in IoT networks have demonstrated the unreliability of current Network Intrusion Detection Systems(NIDSs).Consequently,network interruptions and loss of sensitive data have occurred,which led to an active research area for improving NIDS *** an analysis of related works,it was observed that most researchers aim to obtain better classification results by using a set of untried combinations of Feature Reduction(FR)and Machine Learning(ML)techniques on NIDS ***,these datasets are different in feature sets,attack types,and network ***,this paper aims to discover whether these techniques can be generalised across various *** ML models are utilised:a Deep Feed Forward(DFF),Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),Decision Tree(DT),Logistic Regression(LR),and Naive Bayes(NB).The accuracy of three Feature Extraction(FE)algorithms is detected;Principal Component Analysis(PCA),Auto-encoder(AE),and Linear Discriminant Analysis(LDA),are evaluated using three benchmark datasets:UNSW-NB15,ToN-IoT and *** PCA and AE algorithms have been widely used,the determination of their optimal number of extracted dimensions has been *** results indicate that no clear FE method or ML model can achieve the best scores for all *** optimal number of extracted dimensions has been identified for each dataset,and LDA degrades the performance of the ML models on two *** variance is used to analyse the extracted dimensions of LDA and ***,this paper concludes that the choice of datasets significantly alters the performance of the applied *** believe that a universal(benchmark)feature set is needed to facilitate further advancement and progress of research in this field.

关键词： Feature extraction Machine learning Network intrusion detection system IoT

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Developing crash modification factors for roundabouts using a cross-sectional method

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journal of Traffic and Transportation Engineering(English Edition) 2020年第3期7卷 362-374页

作者： Mohammad nour Al-Marafi Kathirgamalingam Somasundaraswaran Ron Ayers School of Civil Engineering and Surveying Faculty of HealthEngineering and SciencesUniversity of Southern QueenslandT oow oom baQLD 4350Australia

The objective of the current study was to evaluate traffic and geometric features and their influences on the safety performance of roundabouts by developing suitable crash modification factors(CMFs).The cross-sectional method can be applied as an alternative method to estimate the CMFs when before-and-after studies are impractical to apply,e.g.,lack of data from the period after implementing *** accomplish the study objective,CMFs were derived from generalised linear models(GLMs),i.e.,negative binomial(NB)regression,using data collected on regional roundabouts in Toowoomba City,*** years of crash data from 49 roundabouts included all recorded crashes as well as traffic and geometric features for the entire *** candidate models were developed using the *** models were selected based on statistical significance,goodness-of-fit(GOF)measures,and cumulative residual(CURE)*** results show that increasing the number of entry lanes,entry width,entry radius,traffic volume,circulatory roadway width,weaving width,and speed limit have positive effects on roundabout *** the other hand,increasing the number of legs,number of exit lanes,exit width,exit radius,weaving length,central island diameters,and presence of fixed object on a central island have negative effects on roundabout *** study shows that quantifying the risk factors can support road safety stakeholders to identify safety improvements at roundabouts more effectively and efficiently.

关键词： Safety performance Generalised linear models Crash modification factors Cross-sectional method Roundabouts

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In Vitro assessment of the nutritive value of expanded soybean meal for dairy cattle

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journal of Animal Science and Biotechnology 2012年第2期3卷 93-99页

作者： Eman A Elwakeel Evan C Titgemeyer Zongjia j Cheng Abdelaziz M nour Mohamed EA Nasser Department of Animal & Fish Production Faculty of Agriculture Alexandria University Department of Animal Sciences and Industry Kansas State University American Soybean Association-International Marketing

Little information is available about the nutritive value of expanded soybean meal, which is produced by expansion of soybeans prior to solvent extraction of the oil. During processing, expanded soybean meal is subjected to additional heat, which might increase the concentration of ruminally undegraded protein. Processing of soybeans with heat during oil extraction could affect lysine availability by increasing ruminally undegraded protein or by impairing intestinal digestion. Our objective was to compare solvent and expanded soybeans with regard to chemical composition and nutritive value for dairy cattle. Samples of expanded soybean meal （n = 14） and solventextracted soybean meal （n = 5） were obtained from People＇s Republic of China to study effects of the expansion process on nutritive value for dairy cattle. Solvent-extracted soybean meal （n = 2） and mechanically extracted （heated） soybean meal （n = 2） from the United States served as references for comparison. Samples were analyzed for crude fat, long-chain fatty acids, crude protein, amino acids, chemically available lysine, in situ ruminal protein degradation, and in vitro intestinal digestibility. No differences were found between solvent-extracted soybean meals from China and expanded soybean meals from China for crude fat, crude protein, amino acids, or chemically available lysine. In situ disappearance of nitrogen, ruminally undegraded protein content, and in vitro intestinal digestion of the ruminally undegraded protein were generally similar between solvent-extracted soybean meals made in China and expanded soybean meals made in China; variation among soybean meals was small. Results indicate that the additional heat from the expansion process was not great enough to affect the nutritive value of soybean meal protein for ruminants. Although expansion may improve the oil extraction process, the impact on the resulting soybean meal is minimal and does not require consideration when formulating ruminant di

关键词： Digestibility Escape Lysine Protein Rumen

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Microstructure and Magnetic Properties of Fe-Ni Alloy Fabricated by Selective Laser Melting Fe/Ni Mixed Powders

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journal of Materials Science & Technology 2013年第8期29卷 757-760页

作者： Baicheng Zhang nour-Eddine Fenineche Hanlin Liao Christian Coddet LERMPS Universit de Technologie de Belfort-MontbliardSite de SvenansBelfort Cedex 90010France

Fe-Ni alloy, as a widely applied ferromagnetic material, is synthesized using selective laser melting （SLM）. The chemical compositions and microstructure of the SLM Fe-Ni alloy are characterized by X-ray diffraction （XRD）, energy dispersive X-ray spectroscopy and scanning electron microscopy. It was found that the samples exhibited fine grains with homogenous distribution when a low laser scanning velocity was used. Moreover, the magnetic properties of the samples with different laser parameters are also measured. It shows that the SLM Fe-30%Ni alloy possesses a low coercivity and high saturation magnetization. It also can be obtained that SLM is an alternative faster method to prepare soft magnetic material with complex shapes. Moreover, the magnetic properties can be influenced by the laser parameters.

关键词： Selective laser melting (SLM) Fe-Ni alloy Soft magnetic materials Magnetic property

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Privacy-preserved learning from non-i.i.d data in fog-assisted IoT:A federated learning approach

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Digital Communications and Networks 2024年第2期10卷 404-415页

作者： Mohamed Abdel-Basset Hossam Hawash nour Moustafa Imran Razzak Mohamed Abd Elfattah Faculty of Computers and Informatics Zagazig UniversityZagazigSharqiyah44519Egypt School of Engineering and Information Technology University of New South Wales@ADFACanberraACT2600Australia Deakin University Geelong Waurn Ponds CampusAustralia Computer Science Department Misr Higher Institute for Commerce and ComputersMansoura35511Egypt

With the prevalence of the Internet of Things(IoT)systems,smart cities comprise complex networks,including sensors,actuators,appliances,and cyber *** complexity and heterogeneity of smart cities have become vulnerable to sophisticated cyber-attacks,especially privacy-related attacks such as inference and data poisoning *** Learning(FL)has been regarded as a hopeful method to enable distributed learning with privacypreserved intelligence in IoT *** though the significance of developing privacy-preserving FL has drawn as a great research interest,the current research only concentrates on FL with independent identically distributed(i.i.d)data and few studies have addressed the non-i.i.d *** is known to be vulnerable to Generative Adversarial Network(GAN)attacks,where an adversary can presume to act as a contributor participating in the training process to acquire the private data of other *** paper proposes an innovative Privacy Protection-based Federated Deep Learning(PP-FDL)framework,which accomplishes data protection against privacy-related GAN attacks,along with high classification rates from non-i.i.d ***-FDL is designed to enable fog nodes to cooperate to train the FDL model in a way that ensures contributors have no access to the data of each other,where class probabilities are protected utilizing a private identifier generated for each *** PP-FDL framework is evaluated for image classification using simple convolutional networks which are trained using MNIST and CIFAR-10 *** empirical results have revealed that PF-DFL can achieve data protection and the framework outperforms the other three state-of-the-art models with 3%–8%as accuracy improvements.

关键词： Privacy preservation Federated learning Deep learning Fog computing Smart cities

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Trans-arterial chemoperfusion for the treatment of liver metastases of breast cancer and colorectal cancer: Clinical results in palliative care patients

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World journal of Clinical Oncology 2017年第4期8卷 343-350页

作者： Tatjana Gruber-Rouh Marcel Langenbach Nagy NN Naguib nour-Eldin M nour-Eldin Thomas j Vogl Stephan Zangos Martin Beeres Institute for Diagnostic and Interventional Radiology University Hospital Frankfurt

AIM To evaluate the clinical value and efficiency of transarterial chemoperfusion(TACP) in patients with liver metastases from breast cancer(BC) and colorectal cancer(CRC).METHODS We treated 36 patients with liver metastases of BC(n = 19, 19 females) and CRC(n = 17; 8 females, 9 males) with repeated TACP. The treatment interval was 4 wk. TACP was performed with gemcitabine(1000 mg/m2) and mitomycin(10 mg/m2), administered within 1 h after positioning the catheter tip in the hepatic artery. Before treatment, the size, location, tumour volume, vascularization and number of liver tumours were evaluated using magnetic resonance imaging(MRI). Tumour response was evaluated according to the Response Evaluation Criteria in Solid Tumors *** TACP using gemcitabine and mitomycin for metastases from CRC and BC was performed without any serious side effects. The follow-up MRI showed a therapeutic response in 84.2% of the BC patients-stable disease 47.4% and partial response 36.8%. A progression was seen in 15.8%.CRC patients showed a therapeutic response in 52.9% of cases. A progression of the disease was documented in 47.1% of the patients with CRC. These data show that TACP in patients with liver metastases of BC leads to a significantly better therapeutic response compared with CRC patients(P = 0.042). The median survival time was 13.2 mo for the BC patients, which is significantly longer than for CRC patients at 9.3 mo(P = 0.001).CONCLUSION TACP for liver metastases of BC appears to be a safe and effective palliative treatment with improved outcomes in comparison to patients with CRC.

关键词： Colorectal neoplasms Breast neoplasms Neoplasm metastasis Neoplasms Drug therapy

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Enhancing IoT anomaly detection performance for federated learning

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Digital Communications and Networks 2022年第3期8卷 314-323页

作者： Brett Weinger jinoh Kim Alex Sim Makiya Nakashima nour Moustafa K.john Wu Stony Brook University Stony BrookNYUSA Lawrence Berkeley National Laboratory BerkeleyCAUSA Texas A&M University CommerceTXUSA University of New South Wales CanberraAustralia

Federated Learning (FL) with mobile computing and the Internet of Things (IoT) is an effective cooperative learning approach. However, several technical challenges still need to be addressed. For instance, dividing the training process among several devices may impact the performance of Machine Learning (ML) algorithms, often significantly degrading prediction accuracy compared to centralized learning. One of the primary reasons for such performance degradation is that each device can access only a small fraction of data (that it generates), which limits the efficacy of the local ML model constructed on that device. The performance degradation could be exacerbated when the participating devices produce different classes of events, which is known as the class balance problem. Moreover, if the participating devices are of different types, each device may never observe the same types of events, which leads to the device heterogeneity problem. In this study, we investigate how data augmentation can be applied to address these challenges and improving detection performance in an anomaly detection task using IoT datasets. Our extensive experimental results with three publicly accessible IoT datasets show the performance improvement of up to 22.9% with the approach of data augmentation, compared to the baseline (without relying on data augmentation). In particular, stratified random sampling and uniform random sampling show the best improvement in detection performance with only a modest increase in computation time, whereas the data augmentation scheme using Generative Adversarial Networks is the most time-consuming with limited performance benefits.

关键词： Data augmentation Federated learning Internet of things Anomaly detection Machine learning

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Transport network downsizing based on optimal sub-network

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Communications in Transportation Research 2022年第1期2卷 317-332页

作者： Matthieu Guillot Angelo Furno El-Houssaine Aghezzaf nour-Eddin El Faouzi Univ Gustave Eiffel Univ LyonENTPELICITF-69518LyonFrance Department of Industrial Systems Engineering and Product Design Faculty of Engineering and ArchitectureGhent UniversityGhentBelgium Industrial Systems Engineering(ISyE) Flanders MakeLommelBelgium

Transportation networks are sized to efficiently achieve some set of service *** particular circumstances,such as the COVID-19 pandemic,the demand for transportation can significantly change,both qualitatively and quantitatively,resulting in an over-capacitated and less efficient *** this paper,we address this issue by proposing a framework for resizing the network to efficiently cope with the new *** framework includes a model to determine an optimal transportation sub-network that guarantees the following:(i)the minimal access time from any node of the urban network to the new sub-network has not excessively increased compared to that of the original transportation network;(ii)the delay induced on any itinerary by the removal of nodes from the original transportation network has not excessively increased;and(iii)the number of removed nodes from the transportation network is within a preset known factor.A solution is optimal if it induces a minimal global *** modelled this problem as a Mixed Integer Linear Program and applied it to the public bus transportation network of Lyon,France,in a case *** order to respond to operational issues,the framework also includes a decision tool that helps the network planners to decide which bus lines to close and which ones to leave open according to specific trade-off *** results on real data in Lyon show that the optimal sub-network from the MILP model can be used to feed the decision tool,leading to operational scenarios for network planners.

关键词： Public transportation network Linear programming Decision tool Downsizing networks Case study

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