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Small and Medium Enterprises and Global Risks: Evidence from Manufacturing SMEs in Turkey

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International Journal of Disaster Risk Science 2020年第1期11卷 59-73页

作者： ali Asgary ali ihsan Ozdemir Hale Ozyürek Disaster and Emergency Management School of Administrative StudiesYork UniversityTorontoON M3J 1P3Canada Business Administration Department Business SchoolAnkara Yildirim Beyazit UniversityEsenboga CampusAnkaraTurkey KOSGEB(Small and Medium Industry Development Organization) AnkaraTurkey

This study investigated how small and medium enterprises(SMEs) in a country perceive major global risks. The aim was to explore how country attributes and circumstances affect SME assessments of the likelihood,impacts, and rankings of global risks, and to find out if SME risk assessment and rankings differ from the global rankings. Data were gathered using an online survey of manufacturing SMEs in Turkey. The results show that global economic risks and geopolitical risks are of major concern for SMEs, and environmental risks are at the bottom of their ranking. Among the economic risks, fiscal crises in key economies and high structural unemployment or underemployment were found to be the highest risks for the SMEs. Failure of regional or global governance, failure of national governance, and interstate conflict with regional consequences were found to be among the top geopolitical risks for the SMEs. The SMEs considered the risk of largescale cyber-attacks and massive incident of data fraud/theft to be relatively higher than other global technological *** social instability and failure of urban planning were among the top societal risks for the SMEs. Although the global environmental and disaster risks were ranked lowest on the list, man-made environmental damage and disasters and major natural hazard-induced disasters were ranked the highest among this group of risks. Overall, the results show that SMEs at a country level, for example Turkey, perceive global risks differently than the major global players.

关键词： Global risks Risk assessment Risk matrix Small and medium enterprises Turkey

Malingering or simulation in ophthalmology-visual acuity

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International Journal of Ophthalmology(English edition) 2011年第5期4卷 558-566页

作者： ali ihsan Incesu Güngr Sobaci S.B Konya Egitim-Arastirma Hastanesi Gz Klinigi GATA Gz Klinigi

Simulation can be defined as malingering, or sometimes functional visual loss (FVL). It manifests as either simulating an ophthalmic disease (positive simulation), or denial of ophthalmic disease (negative simulation). Conscious behavior and compensation or indemnity claims are prominent features of simulation. Since some authors suggest that this is a manifestation of underlying psychopathology, even conversion is included in this context. In today's world, every ophthalmologist can face with simulation of ophthalmic disease or disorder. In case of simulation suspect, the physician's responsibility is to prove the simulation considering the disease/disorder first, and simulation as an exclusion. In simulation examinations, the physician should be firm and smart to select appropriate test(s) to convince not only the subject, but also the judge in case of indemnity or compensation trials. Almost all ophthalmic sensory and motor functions including visual acuity, visual field, color vision and night vision can be the subject of simulation. Examiner must be skillful in selecting the most appropriate test. Apart from those in the literature, we included all kinds of simulation in ophthalmology. In addition, simulation examination techniques, such as, use of OCT (optical coherence tomography), frequency doubling perimetry (FDP), and modified polarization tests were also included. In this review, we made a thorough literature search, and added our experiences to give the readers up-to-date information on malingering or simulation in ophthalmology.

关键词： malingering simulation conversion hysteria

Enabling Reachability Across Multiple Domains Without Controller Synchronization in SDN

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Computers, Materials & Continua 2021年第10期69卷 945-965页

作者： Nauman Khan Rosli Bin Salleh ihsan ali Zahid Khan Noman Mazhar Roobaea Alroobaea Fahad Almansour Usman ali Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of MalayaMalaysia Department of Computer Science and IT University of MalakandPakistan Robotics and Internet-of-Things Lab Prince Sultan UniversityRiyadhSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Sciences and Arts RassQassim UniversityBuraydah51452Saudi Arabia

Software-defined networking(SDN)makes network agile and flexible due to its programmable *** extensive network has multiple domains in SDN for the scalability and performance of the ***,the inter-domain link is also crucial for the stability of the entire network on the data plane *** than one inter-domain connection enhances the scalability of the data plane ***,it faces a reachability problem with the principal root,which causes forwarding loops and packet drops in the network,thereby degrading network *** proposed solution is a multiple controller architecture;however,this approach increases the complexity and affects network ***,in this study,we propose a framework that avoids forwarding loops and packet drops without the synchronization of multiple-domain controllers in the network using an avoid loop with test packet ***,we collect the link status for improved routing and load balancing for the upcoming flow across inter-domain links to prevent congestion and increase throughput in real *** proposed methodology can significantly reduce the controller workload against multiple controller architecture,minimize flow setup latency,and improve throughput.

关键词： Multiple domain packet drop forwarding loop load balancing SDN multiple controller

Prevalence of multi-drug resistant uropathogenic Escherichia coli in Potohar region of Pakistan

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Asian Pacific Journal of Tropical Biomedicine 2016年第1期6卷 60-66页

作者： ihsan ali Zara Rafaque Safia Ahmed Sajid Malik Javid Iqbal Dasti Department of Microbiology Qauid-i-Azam University Department of Animal Sciences Qauid-i-Azam University

Objective:To scrutinize patterns of multi-drug-resistant uropathogenic Escherichia coli(UPEC) strains and particularly of fluoroquinolone-resistance this is an alternative choice for the treatment of urinary tract ***:Bacterial samples(n = 250) were collected from out-patients from August 2012 to August 2014 *** susceptibility profiling and determination of minimum inhibitory concentrations(MICs) and minimum bactericidal concentrations were performed according to the guidelines of Clinical and Laboratory Standards Institute(CLSI,2012).Genes,qnrA,qnrB and qnrS were identified by DNA amplification and ***:The highest percentage of UPEC isolates were resistant to co-trimoxazole(82%) followed by cephalothin(80%),2nd Gen,3rd Gen and 4th Gen cephalosporins,*** against gentamicin,amikacin remained 29% and 4%.For other drugs including nitrofurantoin,tetracycline,carbapenem and beta-lactam inhibitors remained below 10%.Altogether,59% of the isolates were resistant to at least three antibiotics including one ***,MICs for ciprofloxacin remained(MIC≥256 μg/mL) and for levofloxacin(MIC≥16 μg/mL and 32 μg/mL).No significant differences were observed regarding MIC values of extended spectrumβ-lactamase(ESBL) and non-ESBL *** qnrS and qnrB positive isolates MICs remained above 32 μg/*** of UPEC was significantly higher among females and 40% of the isolates were ESBL ***:Higher percentages of ESBL producing UPEC were associated with urinary tract ***,the majority of these isolates were multi-drug resistant and fluoroquinolone-resistant.

关键词： Fluoroquinolone-resistant Uropathogenic E.coli Multi-drug resistant Extended spectrum beta-lactamase

Hyper Elliptic Curve Based Certificateless Signcryption Scheme for Secure IIoT Communications

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Computers, Materials & Continua 2022年第5期71卷 2515-2532页

作者： Usman ali Mohd Yamani Idna Idris Jaroslav Frnda Mohamad Nizam Bin Ayub Roobaea Alroobaea Fahad Almansour Nura Modi Shagari Insaf Ullah ihsan ali Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala Lumpur50603Malaysia Department of Computer Science University of SwatSaidu Sharif19130Pakistan Center for Research in Mobile Cloud Computing University of MalayaKuala Lumpur50603Malaysia Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and CommunicationsUniversity of Zilina01026 ZilinaSlovakia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Sciences and Arts in RassQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science Hamdard Institute of Engineering and TechnologyIslamabad44000Pakistan

Industrial internet of things (IIoT) is the usage of internet of things(IoT) devices and applications for the purpose of sensing, processing andcommunicating real-time events in the industrial system to reduce the unnecessary operational cost and enhance manufacturing and other industrial-relatedprocesses to attain more profits. However, such IoT based smart industriesneed internet connectivity and interoperability which makes them susceptibleto numerous cyber-attacks due to the scarcity of computational resourcesof IoT devices and communication over insecure wireless channels. Therefore, this necessitates the design of an efficient security mechanism for IIoTenvironment. In this paper, we propose a hyperelliptic curve cryptography(HECC) based IIoT Certificateless Signcryption (IIoT-CS) scheme, with theaim of improving security while lowering computational and communicationoverhead in IIoT environment. HECC with 80-bit smaller key and parameterssizes offers similar security as elliptic curve cryptography (ECC) with 160-bitlong key and parameters sizes. We assessed the IIoT-CS scheme security byapplying formal and informal security evaluation techniques. We used Realor Random (RoR) model and the widely used automated validation of internet security protocols and applications (AVISPA) simulation tool for formalsecurity analysis and proved that the IIoT-CS scheme provides resistance tovarious attacks. Our proposed IIoT-CS scheme is relatively less expensivecompared to the current state-of-the-art in terms of computational cost andcommunication overhead. Furthermore, the IIoT-CS scheme is 31.25% and 51.31% more efficient in computational cost and communication overhead,respectively, compared to the most recent protocol.

关键词： IoT security authentication protocols hyperelliptic curve cryptography certificateless public key cryptography

Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

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Computers, Materials & Continua 2022年第1期70卷 1053-1067页

作者： Lijo Jacob Varghese K.Dhayalini Suma Sira Jacob ihsan ali Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Peer-to-Peer(P2P)electricity trading is a significant research area that offers maximum fulfilment for both prosumer and *** also decreases the quantity of line loss incurred in Smart Grid(SG).But,uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and *** recent times,numerous Machine Learning(ML)-enabled load predictive techniques have been developed,while most of the existing studies did not consider its implicit features,optimal parameter selection,and prediction *** order to overcome fulfill this research gap,the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm(MOGOA)with Deep Extreme Learning Machine(DELM)-based short-term load predictive technique i.e.,MOGOA-DELM model for P2P Energy Trading(ET)in *** proposed MOGOA-DELM model involves four distinct stages of operations namely,data cleaning,Feature Selection(FS),prediction,and parameter *** addition,MOGOA-based FS technique is utilized in the selection of optimum subset of ***,DELM-based predictive model is also applied in forecasting the load *** proposed MOGOA model is also applied in FS and the selection of optimalDELM parameters to improve the predictive *** inspect the effectual outcome of the proposed MOGOA-DELM model,a series of simulations was performed using UK Smart Meter *** the experimentation procedure,the proposed model achieved the highest accuracy of 85.80%and the results established the superiority of the proposed model in predicting the testing data.

关键词： Peer to Peer energy trade smart grid load forecasting machine learning feature selection

Deep Optimal VGG16 Based COVID-19 Diagnosis Model

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Computers, Materials & Continua 2022年第1期70卷 43-58页

作者： M.Buvana K.Muthumayil S.Senthil kumar Jamel Nebhen Sultan S.Alshamrani ihsan ali Department of Computer Science and Engineering PSNA College of Engineering and TechnologyDindigul624622India Department of Information Technology PSNA College of Engineering and TechnologyDindigul624622India Department of Electrical and Electronics Engineering New Prince Shri Bhavani College of Engineering and TechnologyChennai600073India Prince Sattam Bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia Department of Information Technology College of Computer and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala Lumpur50603Malaysia

Coronavirus(COVID-19)outbreak was first identified in Wuhan,China in December *** was tagged as a pandemic soon by the WHO being a serious public medical *** spite of the fact that the virus can be diagnosed by qRT-PCR,COVID-19 patients who are affected with pneumonia and other severe complications can only be diagnosed with the help of Chest X-Ray(CXR)and Computed Tomography(CT)*** this paper,the researchers propose to detect the presence of COVID-19 through images using Best deep learning model with various *** features like Speeded-Up Robust Features(SURF),Features from Accelerated Segment Test(FAST)and Scale-Invariant Feature Transform(SIFT)are used in the test images to detect the presence of *** optimal features are extracted from the images utilizing DeVGGCovNet(Deep optimal VGG16)model through optimal learning *** task is accomplished by exceptional mating conduct of Black Widow *** this strategy,cannibalism is *** this phase,fitness outcomes are rejected and are not satisfied by the proposed *** results acquired from real case analysis demonstrate the viability of DeVGGCovNet technique in settling true issues using obscure and testing ***16 model identifies the imagewhich has a place with which it is dependent on the distinctions in *** impact of the distinctions on labels during training stage is studied and predicted for test *** proposed model was compared with existing state-of-the-art models and the results from the proposed model for disarray grid estimates like Sen,Spec,Accuracy and F1 score were promising.

关键词： COVID 19 multi-feature extraction vgg16 optimal learning rate

Physico-chemical analysis and antimicrobial potential of Apis dorsata,Apis mellifera and Ziziphus jujube honey samples from Pakistan

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Asian Pacific Journal of Tropical Biomedicine 2014年第8期4卷 633-641页

作者： Hira Fahim Javid Iqbal Dasti ihsan ali Safia Ahmed Muhammad Nadeem Department of Microbiology Qauid-i-Azam University IslamabadPakistan PCSIR Research Laboratories Thokar Niaz BaigLahorePakistan

Objective:To evaluale physico-chemical properties and antimicrobial potential of indigenous honey samples against different reference strains including Escherichia coli ATCC *** aerogenes ATCC *** aeruginosa ATCC *** subtilis *** aureus ATCC *** typhi ATCC 14028,Klebsiella pneumonia ATCC *** niger ATCC *** oligasparus *** albicans ATCC14053 and Candida utilis ATCC ***:By using standard methods samples were evaluated for their antimicrobial properties including additive effect of starch and non—peroxidase activity,antioxidative properties(phenol contents,flavonoid contents,1,1-diphenyl-2-pierylhydrazyl radical scavenging activity).Prior to this evaluation,complete physico-chemical properties including pH,color,ash contents,protein contents,moisture contents,hydroxymethyl furfural contents,total sugar contents,reducing sugar and non-reducing sugar contents were ***:Relatively higher ash contents were found in the Siddar honey i.e.(0.5900±0.0336)%and small honey showed relatively higher protein contents i.e.(777.598±9.880) mg/*** moisture contents of tested honey samples ranged between 13.8%—16,6%,total sugar contents foam 61.672%-72.420%and non-reducing sugar contents from 1.95%—3.93%.Presences of phenolic contents indicate higher antioxidant potential of these honey *** bacteria showed clear inhibition zones in response to tested honey samples whereas fungi and yeast showed inhibition at higher concentrations of these honey *** Escherichia *** *** *** aeruginosa and Aspergillus niger,overall the small honey showed the higher activity than other honey ***:Physico-chemical analysis of honey samples confirmed good quality of honey according to the standards set by European Union Commission and Codex alimcntarius *** of these honey samples confirms antim

关键词： Ziziphus jujube honey Antimicrobial properties Non-peroxidase activity Antioxidative properties

Optimal Deep Reinforcement Learning for Intrusion Detection in UAVs

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Computers, Materials & Continua 2022年第2期70卷 2639-2653页

作者： V.Praveena A.Vijayaraj P.Chinnasamy ihsan ali Roobaea Alroobaea Saleh Yahya Alyahyan Muhammad Ahsan Raza Department of Computer Science and Engineering Dr.N.G.P Institute of TechnologyCoimbatore641048India Department of Information Technology Vignan’s Foundation for ScienceTechnology&ResearchGuntur522213India Department of Information Technology Sri Shakthi Institute of Engineering and TechnologyCoimbatore641062India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala Lumpur50603Malaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science Community College in DwadmiShaqra University11961Saudi Arabia Department of Information Technology Bahauddin Zakariya UniversityMultan60000Pakistan

In recent years,progressive developments have been observed in recent technologies and the production cost has been continuously *** such scenario,Internet of Things(IoT)network which is comprised of a set of Unmanned Aerial Vehicles(UAV),has received more attention from civilian tomilitary *** network security poses a serious challenge to UAV networks whereas the intrusion detection system(IDS)is found to be an effective process to secure the UAV *** IDSs are not adequate to handle the latest computer networks that possess maximumbandwidth and data *** order to improve the detection performance and reduce the false alarms generated by IDS,several researchers have employed Machine Learning(ML)and Deep Learning(DL)algorithms to address the intrusion detection *** this view,the current research article presents a deep reinforcement learning technique,optimized by BlackWidow Optimization(DRL-BWO)algorithm,for UAV *** addition,DRL involves an improved reinforcement learning-based Deep Belief Network(DBN)for intrusion *** parameter optimization of DRL technique,BWO algorithm is *** helps in improving the intrusion detection performance of UAV *** extensive set of experimental analysis was performed to highlight the supremacy of the proposed *** the simulation values,it is evident that the proposed method is appropriate as it attained high precision,recall,F-measure,and accuracy values such as 0.985,0.993,0.988,and 0.989 respectively.

关键词： Intrusion detection UAV networks reinforcement learning deep learning parameter optimization