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| 1 | Optimal Cooperative Spectrum Sensing Based on Butterfly Optimization Algorithm显示文摘Since the introduction of the Internet of Things(IoT),several researchers have been exploring its productivity to utilize and organize the spectrum assets.Cognitive radio(CR)technology is characterized as the best aspirant for wireless communications to augment IoT competencies.In the CR networks,secondary users(SUs)opportunistically get access to the primary users(PUs)spectrum through spectrum sensing.The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs.Therefore,several cooperative SUs are engaged in cooperative spectrum sensing(CSS)to ensure reliable sensing results.In CSS,security is still a major concern for the researchers to safeguard the fusion center(FC)against abnormal sensing reports initiated by the malicious users(MUs).In this paper,butterfly optimization algorithm(BOA)-based soft decision method is proposed to find an optimized weighting coefficient vector correlated to the SUs sensing notifications.The coefficient vector is utilized in the soft decision rule at the FC before making any global decision.The effectiveness of the proposed scheme is compared for a variety of parameters with existing schemes through simulation results.The results confirmed the supremacy of the proposed BOA scheme in both the normal SUs’environment and when lower and higher SNRs information is carried by the different categories of MUs. | Noor Gul Saeed Ahmed Atif Elahi Su Min Kim Junsu Kim | 2022 | Computers, Materials & Continua2022，，4： | 1 |
| 2 | Symptomatic Meckel’s diverticulum in children: a 16-year review显示文摘 | Maria Menezes Farhan Tareen Atif Saeed Nasir Khan Prem Puri | 2008 | Pediatric Surgery International2008，，5： | 1 |
| 3 | General Solution for Unsteady Natural Convection Flow with Heat and Mass in the Presence of Wall Slip and Ramped Wall Temperature显示文摘This work is focused on the effect of heat and mass transfer with unsteady natural convection flow of viscous fluid along with ramped wall temperature under the assumption of the slip wall condition at the boundary. Analytical solutions are obtained by using Laplace transformation to the non-dimensional set of governing equations containing velocity, temperature and concentration. Moreover, the expression for skin-friction is derived by differentiating the analytical solutions of fluid velocity. Numerical tables for Skin-friction, Sherwood number and Nusselt-number are examined. For the physical aspects of the flow, we use various values of involved physical parameters such as Prandtl number(Pr), slip parameter(η), Schmidt number(Sc), buoyancy ratio parameter(N), Sherwood number(Sh), and time(t). Additionally, the general solutions are plotted graphically and a comprehensive theoretical section of numerical discussions is included. | Saeed Ullah Jan Sami Ul Haq Syed Inayat Ali Shah Ilyas Khan Muhammad Atif Khan | 2019 | Communications in Theoretical Physics2019，71，6： | 0 |
| 4 | An Abstractive Summarization Technique with Variable Length Keywords as per Document Diversity显示文摘Text Summarization is an essential area in text mining,which has procedures for text extraction.In natural language processing,text summarization maps the documents to a representative set of descriptive words.Therefore,the objective of text extraction is to attain reduced expressive contents from the text documents.Text summarization has two main areas such as abstractive,and extractive summarization.Extractive text summarization has further two approaches,in which the first approach applies the sentence score algorithm,and the second approach follows the word embedding principles.All such text extractions have limitations in providing the basic theme of the underlying documents.In this paper,we have employed text summarization by TF-IDF with PageRank keywords,sentence score algorithm,and Word2Vec word embedding.The study compared these forms of the text summarizations with the actual text,by calculating cosine similarities.Furthermore,TF-IDF based PageRank keywords are extracted from the other two extractive summarizations.An intersection over these three types of TD-IDF keywords to generate the more representative set of keywords for each text document is performed.This technique generates variable-length keywords as per document diversity instead of selecting fixedlength keywords for each document.This form of abstractive summarization improves metadata similarity to the original text compared to all other forms of summarized text.It also solves the issue of deciding the number of representative keywords for a specific text document.To evaluate the technique,the study used a sample of more than eighteen hundred text documents.The abstractive summarization follows the principles of deep learning to create uniform similarity of extracted words with actual text and all other forms of text summarization.The proposed technique provides a stable measure of similarity as compared to existing forms of text summarization. | Muhammad Yahya Saeed Muhammad Awais Muhammad Younas Muhammad Arif Shah Atif Khan M.Irfan Uddin Marwan Mahmoud | 2021 | Computers, Materials & Continua2021，，3： | 0 |
| 5 | Synthesis,Characterization,Biological and Docking Simulations of 4-(Benzylideneamino) Benzoic Acids显示文摘The present research paper presents the synthesis, characterization, biological and computational studies of 4-(benzylideneamino) benzoic acid derivatives(3a~3g). Derivatives 3a~3c displayed best antidiabetic potential with a glucose-lowering effect compared to the reference drug Glibenclamide. Biochemical parameters including plasma glucose, serum triglycerides, cholesterol, alanine amino transferase and aspartate amino transferase levels showed significant alterations in concentrations relative to the control. Similarly, the derivatives 3a, 3d and 3e displayed potent in vitro antibacterial potential. Molecular docking simulations delineated that the ligands and complexes were stabilized at the active site by electrostatic and hydrophobic forces, consistent with the corresponding experimental results. In silico study of the binding pattern predicted that the synthesized ligands, 3d and 3a could serve as a potential surrogate for hit-to-lead generation and the design of novel antibacterial drugs. | HAMID Aziz AAMER Saeed FARUKH Jabeen ABDUL Basit IRFAN Zia Qureshi ABDUL Aziz ATIF Haroon ASHFAQ Ur Rehman | 2021 | Chinese Journal of Structural Chemistry2021，40，3： | 0 |
| 6 | A Secure Method for Data Storage and Transmission in Sustainable Cloud Computing显示文摘Cloud computing is a technology that provides secure storage space for the customer’s massive data and gives them the facility to retrieve and transmit their data efficiently through a secure network in which encryption and decryption algorithms are being deployed.In cloud computation,data processing,storage,and transmission can be done through laptops andmobile devices.Data Storing in cloud facilities is expanding each day and data is the most significant asset of clients.The important concern with the transmission of information to the cloud is security because there is no perceivability of the client’s data.They have to be dependent on cloud service providers for assurance of the platform’s security.Data security and privacy issues reduce the progression of cloud computing and add complexity.Nowadays;most of the data that is stored on cloud servers is in the form of images and photographs,which is a very confidential form of data that requires secured transmission.In this research work,a public key cryptosystem is being implemented to store,retrieve and transmit information in cloud computation through a modified Rivest-Shamir-Adleman(RSA)algorithm for the encryption and decryption of data.The implementation of a modified RSA algorithm results guaranteed the security of data in the cloud environment.To enhance the user data security level,a neural network is used for user authentication and recognition.Moreover;the proposed technique develops the performance of detection as a loss function of the bounding box.The Faster Region-Based Convolutional Neural Network(Faster R-CNN)gets trained on images to identify authorized users with an accuracy of 99.9%on training. | Muhammad Usman Sana Zhanli Li Tayybah Kiren Hannan Bin Liaqat Shahid Naseem Atif Saeed | 2023 | Computers, Materials & Continua2023，，5： | 0 |
| 7 | Aluminium phthalocyanine chloride thin films for temperature sensing显示文摘This study presents the fabrication and temperature sensing properties of sensors based on aluminium phthalocyanine chloride(AlPcCl)thin films.To fabricate the sensors,50-nm-thick electrodes with 50-μm gaps between them are deposited on glass substrates.AlPcCl thin films with thickness of 50–100 nm are deposited in the gap between electrodes by thermal evaporation.The resistance of the sensors decreases with increasing thickness and the annealing at 100℃ results in an increase in the initial resistance of sensors up to 24%.The sensing mechanism is based on the change in resistance with temperature.For temperature varying from 25℃ to 80℃,the change in resistance is up to 60%.Simulation is carried out and results obtained coincide with experimental data with an error of±1%. | Muhammad Tariq Saeed Chani Abdullah M.Asiri Kh.S.Karimov Atif Khan Niaz Sher Bhadar Khan Khalid.A.Alamry | 2013 | Chinese Physics B2013，22，11： | 0 |
| 8 | De-Noising Brain MRI Images by Mixing Concatenation and Residual Learning(MCR)显示文摘Brain magnetic resonance images(MRI)are used to diagnose the different diseases of the brain,such as swelling and tumor detection.The quality of the brain MR images is degraded by different noises,usually salt&pepper and Gaussian noises,which are added to the MR images during the acquisition process.In the presence of these noises,medical experts are facing problems in diagnosing diseases from noisy brain MR images.Therefore,we have proposed a de-noising method by mixing concatenation,and residual deep learning techniques called the MCR de-noising method.Our proposed MCR method is to eliminate salt&pepper and gaussian noises as much as possible from the brain MRI images.The MCR method has been trained and tested on the noise quantity levels 2%to 20%for both salt&pepper and gaussian noise.The experiments have been done on publically available brain MRI image datasets,which can easily be accessible in the experiments and result section.The Structure Similarity Index Measure(SSIM)and Peak Signal-to-Noise Ratio(PSNR)calculate the similarity score between the denoised images by the proposed MCR method and the original clean images.Also,the Mean Squared Error(MSE)measures the error or difference between generated denoised and the original images.The proposed MCR denoising method has a 0.9763 SSIM score,84.3182 PSNR,and 0.0004 MSE for salt&pepper noise;similarly,0.7402 SSIM score,72.7601 PSNR,and 0.0041 MSE for Gaussian noise at the highest level of 20%noise.In the end,we have compared the MCR method with the state-of-the-art de-noising filters such as median and wiener de-noising filters. | Kazim Ali Adnan N.Qureshi Muhammad Shahid Bhatti Abid Sohail Muhammad Hijji Atif Saeed | 2023 | Computer Systems Science & Engineering2023，45，5： | 0 |
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