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Data Analysis of Network Parameters for Secure Implementations of SDN-Based Firewall

Computers, Materials & Continua 2023年第11期77卷 1575-1598页

作者： Rizwan Iqbal Rashid Hussain Sheeraz Arif Nadia Mustaqim Ansari tayyab ahmed shaikh Department of Telecommunication Engineering Dawood University of Engineering&TechnologyKarachiPakistan Faculty of Engineering Sciences and Technology Hamdard UniversityKarachiPakistan Faculty of Information Technology Salim Habib UniversityKarachiPakistan Department of Electronic Engineering Dawood University of Engineering&TechnologyKarachiPakistan

Software-Defined Networking(SDN)is a new network technology that uses programming to complement the data plane with a control plane.To enable safe connection,however,numerous security challenges must be addressed.Flooding attacks have been one of the most prominent risks on the internet for decades,and they are now becoming challenging difficulties in SDN networks.To solve these challenges,we proposed a unique firewall application built on multiple levels of packet filtering to provide a flooding attack prevention system and a layer-based packet detection system.This study offers a systematic strategy for wrapping up the examination of SDN operations.The Mininet simulator examines the effectiveness of SDN-based firewalls at various network tiers.The fundamental network characteristics that specify how SDN should operate.The three main analytical measures of the network are jitter,response time,and throughput.During regular operations,their behavior evaluates in the standard SDN conditions of Transmission Control Protocol(TCP)flooding and User Datagram Protocol(UDP)flooding with no SDN occurrences.Low Orbit Ion Cannon(LOIC)is applied to launch attacks on the transmission by the allocated server.Wireshark and MATLAB are used for the behavioral study to determine how sensitive the parameters are used in the SDN network and monitor the fluctuations of those parameters for different simulated scenarios.

关键词： Software defined networking firewall POX controller open v switch Mininet OpenFlow

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Low-complexity signal detection for massive MIMO systems via trace iterative method

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Journal of Systems Engineering and Electronics 2024年第3期35卷 549-557页

作者： IMRAN A.Khoso ZHANG Xiaofei ABDUL Hayee shaikh IHSAN A.Khoso ZAHEER ahmed Dayo College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China School of Electrical Engineering Korea UniversitySeoul 02841Korea School of Mathematics South China University of TechnologyGuangzhou 510641China Department of Computer Science Huanggang Normal UniversityHuanggang 438000China

Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.

关键词： signal detection low-complexity linear minimum mean square error(MMSE) massive multiple-input multiple-output(MIMO) trace iterative method(TIM)

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Effect of ankle versus thigh tourniquets on post-operative pain in foot and ankle surgery

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World Journal of Orthopedics 2024年第2期15卷 163-169页

作者： Ashish Mishra ahmed Barakat Jitendra Mangwani Jakub Kazda Sagar Tiwatane Sana Mohammed Aamir shaikh Linzy Houchen-Wolloff Vipul Kaushik Department of Trauma and Orthopedics University Hospitals LeicesterLeicester LE15WWUnited Kingdom Department of Trauma and Orthopedics Leicester University Hospitals-NHS TrustLeicester LE15WWLeicestershireUnited Kingdom Academic Team of Musculoskeletal Surgery University Hospitals of Leicester NHS TrustLeicester LE39QPUnited Kingdom Department of Anaesthesia York&Scarborough Teaching Hospitals NHS Foundation TrustNorth Yorkshire YO318HEUnited Kingdom Department of Anaesthesia Royal Free London NHS TrustLondon NW32QGUnited Kingdom Department of Trauma&Orthopaedics Breach Candy Hospital TrustMumbai 400026India Department of Physiotherapy University Hospitals of Leicester NHS TrustLeicester LE39QPUnited Kingdom Department of Anasthesia University Hospitals of Leicester NHS TrustLeicester LE15WWUnited Kingdom

BACKGROUND Tourniquets are commonly used in elective extremity orthopaedic surgery to reduce blood loss,improve visualization in the surgical field,and to potentially reduce surgical time.There is a lack of consensus in existing guidelines regarding the optimal tourniquet pressure,placement site,and duration of use.There is a paucity of data on the relationship between the site of a tourniquet and postoperative pain in foot and ankle surgery.AIM To explore the relationship between tourniquet site and intensity of post-operative pain scores in patients undergoing elective foot and ankle surgery.METHODS Retrospective analysis of prospectively collected data on 201 patients who underwent foot and ankle surgery in a single institution was undertaken.Intraoperative tourniquet duration,tourniquet pressure and site,and postoperative pain scores using Visual Analogue Score were collected in immediate recovery,at six hours and at 24 h post-op.Scatter plots were used to analyse the data and to assess for the statistical correlation between tourniquet pressure,duration,site,and pain scores using Pearson correlation coefficient.RESULTS All patients who underwent foot and ankle surgery had tourniquet pressure of 250 mmHg for ankle tourniquet and 300 mmHg for thigh.There was no correlation between the site of the tourniquet and pain scores in recovery,at six hours and after 24 h.There was a weak correlation between tourniquet time and Visual Analogue Score immediately post-op(r=0.14,P=0.04)but not at six or 24 h post-operatively.CONCLUSION This study shows that there was no statistically significant correlation between tourniquet pressure,site and postop pain in patients undergoing foot and ankle surgery.The choice of using a tourniquet is based on the surgeon's preference,with the goal of minimizing the duration of its application at the operative site.

关键词： Lower limb surgery Tourniquet time Tourniquet pressure Tourniquet site Post-operative pain Pain scores

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National guidelines for the diagnosis and treatment of hilar cholangiocarcinoma

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World Journal of Gastroenterology 2024年第9期30卷 1018-1042页

作者： Faisal Saud Dar Zaigham Abbas Irfan ahmed Muhammad Atique Usman Iqbal Aujla Muhammad Azeemuddin Zeba Aziz Abu Bakar Hafeez Bhatti Tariq Ali Bangash Amna Subhan Butt Osama Tariq Butt Abdul Wahab Dogar Javed Iqbal Farooqi Faisal Hanif Jahanzaib Haider Siraj Haider Syed Mujahid Hassan Adnan Abdul Jabbar Aman Nawaz Khan Muhammad Shoaib Khan Muhammad Yasir Khan Amer Latif Nasir Hassan Luck Ahmad Karim Malik Kamran Rashid Sohail Rashid Mohammad Salih Abdullah Saeed Amjad Salamat Ghias-un-Nabi tayyab Aasim Yusuf Haseeb Haider Zia Ammara Naveed Department of Hepatopancreatic Biliary Surgery&Liver Transplant Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Hepatogastroenterology and Liver Transplantation Dr.Ziauddin University HospitalKarachi 75600SindhPakistan University of Aberdeen Aberdeen B243FXUnited Kingdom Department of Pathology Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Gastroenterology&Hepatology Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Radiology Aga Khan UniversityKarachi 74800Pakistan Department of Oncology Hameed Latif HospitalLahore 54000Pakistan Division of Hepatopancreatic Biliary Surgery&Liver Transplantation Shifa International HospitalIslamabad 44000Pakistan Department of Hepatopancreatic Biliary Surgery&Liver Transplant Shaikh Zayed Hospital and Post Graduate Medical InstituteLahore 54000Pakistan Department of Medicine Aga Khan University HospitalKarachi 74800Pakistan Department of Liver Transplant Pir Abdul Qadir Shah Jeelani Institute of Medical SciencesGambat 66020Pakistan Department of Medicine&Gastroenterology Lifecare Hospital and Research CentrePeshawar 25000Khyber PakhtunkhwaPakistan Department of Hepatopancreatobiliary&Liver Transplant Bahria International HospitalLahore 54000Pakistan Department of Surgery Hepatopancreatobiliary&Liver TransplantDow University of Health SciencesKarachi 74800Pakistan Department of Gastroenterology Hepatology&NutritionPir Abdul Qadir Shah Jeelani Institute of Medical SciencesGambat 66020Pakistan Department of Oncology Dr.Ziauddin HospitalKarachi 74800Pakistan Department of Radiology Rehman Medical InstitutePeshawar 25000Pakistan Army Liver Transplant Unit Pak Emirates Military HospitalRawalpindi 46000Pakistan Department of Gastroenterology Sindh Institute of Urology and TransplantationKarachi 75500Pakistan Rashid Nursing Home and Cancer Clinic Rashid Nursing Home and Cancer ClinicRawalpindi 46000Pakistan Department of Gastroentero

A consensus meeting of national experts from all major national hepatobiliary centres in the country was held on May 26,2023,at the Pakistan Kidney and Liver Institute&Research Centre(PKLI&RC)after initial consultations with the experts.The Pakistan Society for the Study of Liver Diseases(PSSLD)and PKLI&RC jointly organised this meeting.This effort was based on a comprehensive literature review to establish national practice guidelines for hilar cholangiocarcinoma(hCCA).The consensus was that hCCA is a complex disease and requires a multidisciplinary team approach to best manage these patients.This coordinated effort can minimise delays and give patients a chance for curative treatment and effective palliation.The diagnostic and staging workup includes high-quality computed tomography,magnetic resonance imaging,and magnetic resonance cholangiopancreato-graphy.Brush cytology or biopsy utilizing endoscopic retrograde cholangiopancreatography is a mainstay for diagnosis.However,histopathologic confirmation is not always required before resection.Endoscopic ultrasound with fine needle aspiration of regional lymph nodes and positron emission tomography scan are valuable adjuncts for staging.The only curative treatment is the surgical resection of the biliary tree based on the Bismuth-Corlette classification.Selected patients with unresectable hCCA can be considered for liver transplantation.Adjuvant chemotherapy should be offered to patients with a high risk of recurrence.The use of preoperative biliary drainage and the need for portal vein embolisation should be based on local multidisciplinary discussions.Patients with acute cholangitis can be drained with endoscopic or percutaneous biliary drainage.Palliative chemotherapy with cisplatin and gemcitabine has shown improved survival in patients with irresectable and recurrent hCCA.

关键词： Hilar cholangiocarcinoma Bismuth-Corlette classification Memorial Sloan Kettering Cancer Centre Staging Preoperative biliary drainage Portal vein embolisation Surgical resection Hepatectomy

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Deep Learning Framework for Precipitation Prediction Using Cloud Images

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Computers, Materials & Continua 2022年第8期72卷 4201-4213页

作者： Mirza Adnan Baig Ghulam Ali Mallah Noor ahmed shaikh Shah Abdul Latif University Khairpur77150Pakistan

Precipitation prediction(PP)have become one of the significant research areas of deep learning(DL)and machine vision(MV)techniques are frequently used to predict the weather variables(WV).Since the climate change has left significant impact upon weather variables(WV)and continuously changes are observed in temperature,humidity,cloud patterns and other factors.Although cloud images contain sufficient information to predict the precipitation pattern but due to changes in climate,the complex cloud patterns and rapid shape changing behavior of clouds are difficult to consider for rainfall prediction.Prediction of rainfall would provide more meticulous assistance to the farmers to know about the weather conditions and to care their cash crops.This research proposes a framework to classify the dark cloud patterns(DCP)for prediction of precipitation.The framework consists upon three steps to classify the cloud images,first step tackles noise reduction operations,feature selection and preparation of datasets.Second step construct the decision model by using convolutional neural network(CNN)and third step presents the performance visualization by using confusion matrix,precision,recall and accuracy measures.This research contributes(1)real-world clouds datasets(2)method to prepare datasets(3)highest classification accuracy to predict estimated as 96.90%.

关键词： Machine vision SIFT features dark cloud patterns precipitation agriculture

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Supporting tuberculosis program in active contact tracing:a case study from Pakistan

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Infectious Diseases of Poverty 2022年第2期11卷 72-76页

作者： Babar Tasneem shaikh ahmed Khan Laghari Sulaiman Durrani Alina Chaudhry Nabeela Ali Integrated Health System Strengthening and Service Delivery(IHSS-SD)Activity JSI Research&Training Institute Inc.Mezzanine FloorThe Grand Hotel Street 1Sector E-11/1Islamabad 44000Pakistan

Tuberculosis(TB)is on the rise in Pakistan and there could be multiple reasons including poverty,difficulty in access to TB treatment services,non-compliance with treatment,social stigma etc.According to the TB program managers,limited treatment and testing sites for tuberculosis and lack of trained human resources play a major role in compromising TB management.A major lacuna in the TB control program is the absence of active contact tracing strategy.This is essential for a disease where positive cases are known to be able to infect a further 10-15 individuals in a year.Tackling tuberculosis in Pakistan has been beleaguered by funding challenges and other systems’bottlenecks such as lack of skilled human resources and insufficient supply of medicines,despite the fact that disease burden is one of the highest in the world.Although it is a notifiable disease,active case finding,contact tracing and reporting is notoriously low throughout the country.Access to diagnostics and treatment facilities has been limited and stigma attached to the disease remains deeply entrenched among the communities.Researchers have shown that enhanced and active approaches to contact investigation effectively identifies additional patients with TB among household contacts at a relatively modest cost.USAID’s Integrated Health Systems Strengthening and Service Delivery Activity extended support to the Health Departments of Sindh and Khyber Pakhtunkhwa provinces.In collaboration with the two provincial TB programs,community based active contact tracing was conducted on 17,696 individuals,based on the index cases.Among the contacts traced,243 cases were diagnosed as drug sensitive or drug resistant TB.Awareness sessions were conducted to sensitize people on the various aspects of disease and importance of getting tested.The project also supported establishing three satellite Programmatic Management of Drug Resistant Tuberculosis(PMDT)sites for drug resistant TB treatment,enhancing the programs’diagnostic and testing capacity.

关键词： Active contact tracing Community awareness Tuberculosis Pakistan

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Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space

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Computers, Materials & Continua 2023年第11期77卷 2031-2047页

作者： Mudassir Khalil Muhammad Imran Sharif ahmed Naeem Muhammad Umar Chaudhry Hafiz tayyab Rauf Adham E.Ragab Department of Computer Engineering Bahauddin Zakariya UniversityMultan60000Pakistan Department of Computer Science Kansas State UniversityManhattanKS66506USA Department of Computer Science University of Management and TechnologyLahore54000Pakistan Centre for Smart Systems AI and CybersecurityStaffordshire UniversityStoke-on-TrentST42DEUK Industrial Engineering Department Collage of EngineeringKing Saud UniversityPO Box 800Riyadh11421Saudi Arabia

Early detection of brain tumors is critical for effective treatment planning.Identifying tumors in their nascent stages can significantly enhance the chances of patient survival.While there are various types of brain tumors,each with unique characteristics and treatment protocols,tumors are often minuscule during their initial stages,making manual diagnosis challenging,time-consuming,and potentially ambiguous.Current techniques predominantly used in hospitals involve manual detection via MRI scans,which can be costly,error-prone,and time-intensive.An automated system for detecting brain tumors could be pivotal in identifying the disease in its earliest phases.This research applies several data augmentation techniques to enhance the dataset for diagnosis,including rotations of 90 and 180 degrees and inverting along vertical and horizontal axes.The CIELAB color space is employed for tumor image selection and ROI determination.Several deep learning models,such as DarkNet-53 and AlexNet,are applied to extract features from the fully connected layers,following the feature selection using entropy-coded Particle Swarm Optimization(PSO).The selected features are further processed through multiple SVM kernels for classification.This study furthers medical imaging with its automated approach to brain tumor detection,significantly minimizing the time and cost of a manual diagnosis.Our method heightens the possibilities of an earlier tumor identification,creating an avenue for more successful treatment planning and better overall patient outcomes.

关键词： Brain tumor deep learning feature extraction feature selection feature fusion transfer learning

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Decision Support System for Diagnosis of Irregular Fovea

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Computers, Materials & Continua 2022年第6期71卷 5343-5353页

作者： Ghulam Ali Mallah Jamil ahmed Muhammad Irshad Nazeer Mazhar Ali Dootio Hidayatullah shaikh Aadil Jameel Shah Abdul Latif University Khairpur77150Pakistan Sukkur IBA University Sukkur7720Pakistan Shaheed Benazir University Layari Karachi77202Pakistan

Detection of abnormalities in human eye is one of the wellestablished research areas of Machine Learning.Deep Learning techniques are widely used for the diagnosis of RetinalDiseases(RD).Fovea is one of the significant parts of retina which would be prevented before the involvement of Perforated Blood Vessels(PBV).Retinopathy Images(RI)contains sufficient information to classify structural changes incurred upon PBV but Macular Features(MF)and Fovea Features(FF)are very difficult to detect because features ofMFand FF could be found with Similar Color Movements(SCM)with minor variations.This paper presents novel method for the diagnosis of Irregular Fovea(IF)to assist the doctors in diagnosis of irregular fovea.By considering all above problems this paper proposes a three-layer decision support system to explore the hindsight knowledge of RI and to solve the classification problem of IF.The first layer involves data preparation,the second layer builds the decision model to extract the hidden patterns of fundus images by using Deep Belief Neural Network(DBN)and the third layer visualizes the results by using confusion matrix.This paper contributes a data preparation algorithm for irregular fovea and a highest estimated classification accuracy measured about 96.90%.

关键词： Machine learning deep belief neural network eye disease fovea

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Multi-material Bio-inspired Soft Octopus Robot for Underwater Synchronous Swimming

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Journal of Bionic Engineering 2022年第5期19卷 1229-1241页

作者： Faheem ahmed Muhammad Waqas Bushra shaikh Umair Khan Afaque Manzoor Soomro Suresh Kumar Hina Ashraf Fida Hussain Memon Kyung Hyun Choi Department of Mechatronics Engineering Jeju National UniversityJeju 63243South Korea Department of Electrical Engineering Sukkur IBA UniversityAirport RoadSukkur 65200SindhPakistan Advanced Micro Mechatronics and Energy Lab Sukkur IBA UniversitySukkur 65200Pakistan Department of Ocean Sciences Jeju National UniversityJeju 63243South Korea

Inspired by the simple yet amazing morphology of the Octopus, we propose the design, fabrication, and characterization of multi-material bio-inspired soft Octopus robot (Octobot). 3D printed molds for tentacles and head were used. The tentacles of the Octobot were casted using Ecoflex-0030 while head was fabricated using relatively flexible material, i.e., OOMOO-25. The head is attached to the functionally responsive tentacles (each tentacle is of 79.12 mm length and 7 void space diameter), whereas Shape Memory Alloy (SMA) muscle wires of 0.5 mm thickness are used in Octobot tentacles for dual thrust generation and actuation of Octobot. The tentacles were separated in two groups and were synchronously actuated. Each tentacle of the developed Octobot contains a pair of SMA muscles (SMA-α and SMA-β). SMA-α muscles being the main actuator, was powered by 9 V, 350 mA power supply, whereas SMA-β was used to provide back thrust and thus helps to increase the actuation frequency. Simulation work of the proposed model was performed in the SolidWorks environment to verify the vertical velocity using the octopus tentacle actuation. The design morphology of Octobot was optimized using simulation and TRACKER software by analyzing the experimental data of angle, displacement, and velocity of real octopus. The as-developed Octobot can swim at variable frequencies (0.5–2 Hz) with the average speed of 25 mm/s (0.5 BLS). Therefore, the proposed soft Octopus robot showed an excellent capability of mimicking the gait pattern of its natural counterpart.

关键词： Bio-inspired Octopus Octobot Sub-surface Soft robotics Swimming

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Top-k Outlier Detection from Uncertain Data

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International Journal of Automation and computing 2014年第2期11卷 128-142页

作者： Salman ahmed shaikh Hiroyuki Kitagawa Graduate School of Systems and Information Engineering University of Tsukuba

Uncertain data are common due to the increasing usage of sensors, radio frequency identification(RFID), GPS and similar devices for data collection. The causes of uncertainty include limitations of measurements, inclusion of noise, inconsistent supply voltage and delay or loss of data in transfer. In order to manage, query or mine such data, data uncertainty needs to be considered. Hence,this paper studies the problem of top-k distance-based outlier detection from uncertain data objects. In this work, an uncertain object is modelled by a probability density function of a Gaussian distribution. The naive approach of distance-based outlier detection makes use of nested loop. This approach is very costly due to the expensive distance function between two uncertain objects. Therefore,a populated-cells list(PC-list) approach of outlier detection is proposed. Using the PC-list, the proposed top-k outlier detection algorithm needs to consider only a fraction of dataset objects and hence quickly identifies candidate objects for top-k outliers. Two approximate top-k outlier detection algorithms are presented to further increase the efficiency of the top-k outlier detection algorithm.An extensive empirical study on synthetic and real datasets is also presented to prove the accuracy, efficiency and scalability of the proposed algorithms.

关键词： Top-k distance-based outlier detection uncertain data Gaussian uncertainty cell-based approach PC-list based approach

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