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American Journal of Analytical Chemistry 2012年第4期3卷 328-337页

作者： Somia Gul Najma Sultana Muhammad Saeed Arayne Sana Shamim mahwish akhtar College of Pharmacy Dow University of Health Sciences Karachi Pakistan Faculty of Pharmacy Jinnah University for Women Karachi Pakistan United Biotech (Pvt) Ltd. Karachi Pakistan

A simple reversed phase HPLC method was developed and validated for the simultaneous determination of sparfloxacin (SPFX), diclofenac sodium, meloxicam, ibuprofen, flurbiprofen, naproxen and mefenemic acid in a relatively short time with high linearity in bulk material, pharmaceutical formulations and human serum. Purospher STAR C18 (250 × 4.6 mm, 5 μm) column was utilized with mobile phase, methanol and water (90:10, v/v pH 2.70 adjusted by phosphoric acid), was delivered at a flow rate of 1.5 ***–1. Eluent was monitored using UV detector at 240 nm. The proposed method is specific, accurate (98.42% - 102.75%), precise (intra-day and inter-day variation 0.011% - 1.85%) and linear (R2 > 0.999) with in the desired range 0.15 - 40 μ***–1 and the detection and quantification limit was 1.19E+08 – 0.150 μ***–1 and 3.62E+08 – 0.4574 μ***–1 respectively for SPFX and NSAIDs. The analysis of variance (ANOVA) and student’s t-test were applied to verify the results. The anticipated method is applicable to routine analysis of SPFX and NSAIDs in pharmaceutical formulations as well as in human serum samples. It has also applied on interaction of SPFX with NSAIDs.

关键词： Sparfloxacin NSAIDs HPLC Interactions ANOVA

Enhancing Skin Cancer Diagnosis with Deep Learning:A Hybrid CNN-RNN Approach

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Computers, Materials & Continua 2024年第4期79卷 1497-1519页

作者： Syeda Shamaila Zareen Guangmin Sun mahwish Kundi Syed Furqan Qadri Salman Qadri Faculty of Information Technology Beijing University of TechnologyBeijing100124China Computer Science International Engineering Collage Maynooth UniversityKildareW23 F2H6Irland Research Center for Data Hub and Security Zhejiang LabHangzhou311121China Computer Science Department MNS University of AgricultureMultan59220Pakistan

Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep learning-basedConvolutional and Recurrent Neural Network (CNN-RNN) model with a ResNet-50 architecture which usedas the feature extractor to enhance skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, the model demonstrates robust performance on a dataset of 9000 skin lesionphotos from nine cancer types. Using pre-trained ResNet-50 for spatial data extraction and Long Short-TermMemory (LSTM) for temporal dependencies, the model achieves a high average recognition accuracy, surpassingprevious methods. The comprehensive evaluation, including accuracy, precision, recall, and F1-score, underscoresthe model’s competence in categorizing skin cancer types. This research contributes a sophisticated model andvaluable guidance for deep learning-based diagnostics, also this model excels in overcoming spatial and temporalcomplexities, offering a sophisticated solution for dermatological diagnostics research.

关键词： Skin cancer classification deep learning Convolutional Neural Network(CNN) RNN ResNet-50

Privacy-Preserving Information Fusion Technique for Device to Server-Enabled Communication in the Internet of Things:A Hybrid Approach

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Computers, Materials & Continua 2024年第7期80卷 1305-1323页

作者： Amal Al-Rasheed Rahim Khan Tahani Alsaed mahwish Kundi Mohamad Hanif Md.Saad Mahidur R.Sarker Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science AbdulWali Khan University MardanMardan23200Pakistan Faculty of Computing and Informatics University Malaysia SabahKota KinabaluSabah88400Malaysia Applied College Taibah UniversityMadinah41477Saudi Arabia Maynooth International Engineering College Maynooth UniversityCo KildareW23 X021Irland Department of Mechanical Engineering Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia Institute of Visual Informatics Universiti Kebangsaan MalaysiaBangiSelangor43600Malaysia University of Design Innovation and Technology(UDIT)Av.Alfonso XIII97Madrid28016Spain

Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare *** addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,***,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled *** this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT *** window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission ***,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s *** contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of ***,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the *** proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information *** and analytical results ha

关键词： Internet of things information fusion differential privacy dynamic programming Laplace function

New Method for Optimization and Simultaneous Determination of Sparfloxacin and Non Steroidal Anti-Inflammatory Drugs: Its In-Vitro Application

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Double Encryption Using Trigonometric Chaotic Map and XOR of an Image

American Journal of Analytical Chemistry（美国分析化学） 2012年第4期

作者： Somia Gul Najma Sultana Muhammad SaeedArayne Sana Shamim mahwish akhtar

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Computers, Materials & Continua 2021年第12期69卷 3033-3046页

作者： Orawit Thinnukool Thammarat Panityakul mahwish Bano College of Arts Media and TechnologyChiang Mai UniversityChiang Mai50200Thailand Division of Computational Science Prince of Songkla UniversityHat YaiSongkhla90110Thailand Department of Mathematics Air UniversityIslamabad44000Pakistan

In the most recent decades,a major number of image encryption plans have been *** vast majority of these plans reached a highsecurity level;however,their moderate speeds because of their complicated processes made them of no use in real-time *** by this,we propose another efficient and rapid image encryption plan dependent on the Trigonometric chaotic *** contrast to the most of current plans,we utilize this basic map to create just a couple of arbitrary rows and ***,to additionally speed up,we raise the processing unit from the pixel level to the row/column *** security of the new plot is accomplished through a substitution permutation network,where we apply a circular shift of rows and columns to break the solid connection of neighboring *** that point,we join the XOR operation with modulo function to cover the pixels values and forestall any leaking of ***-security tests and simulation analyses are carried out to exhibit that the scheme is very secure and exceptionally quick for real-time image processing at 80 fps(frames per second).

关键词： Double image encryption target image random image trigonometric chaotic map

Tracking and Analysis of Pedestrian’s Behavior in Public Places

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Computers, Materials & Continua 2023年第1期74卷 841-853页

作者： mahwish Pervaiz Mohammad Shorfuzzaman Abdulmajeed Alsufyani Ahmad Jalal Suliman A.Alsuhibany Jeongmin Park Department of Computer Science Bahria UniversityIslamabadPakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science Air UniversityIslamabadPakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-si15073Gyeonggi-doKorea

Crowd management becomes a global concern due to increased population in urban *** management of pedestrians leads to improved use of public *** of pedestrian’s is a major factor of crowd management in public *** are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the *** this paper,we have proposed a new method for pedestrian’s behavior *** filter has been used to detect pedestrian’s usingmovement based ***,we have performed occlusion detection and removal using region shrinking method to isolate occluded *** verification is performed on each human silhouette and wavelet analysis and particle gradient motion are extracted for each *** Wolf Optimizer(GWO)has been utilized to optimize feature set and then behavior classification has been performed using the Extreme Gradient(XG)Boost *** has been evaluated using pedestrian’s data from avenue and UBI-Fight datasets,where both have different *** mean achieved accuracies are 91.3%and 85.14%over the Avenue and UBI-Fight datasets,*** results are more accurate as compared to other existing methods.

关键词： Crowd management kalman filter region shrinking XG-Boost classifier

Frequency of Bcr-Abl Fusion Oncogene Splice Variants Associated with Chronic Myeloid Leukemia (CML)

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Journal of Cancer Therapy 2011年第2期2卷 176-180页

作者： Zafar Iqbal Fatima Manzoor Mudassar Iqbal Shahid Ali Nadeem Sheikh mahwish Khan Aamer Aleem Tanveer akhtar Hematology Oncology and Pharmacogenetic Engineering Sciences (HOPES) Group Health Sciences Research Laboratories

BCR-ABL fusion oncogene originates from the reciprocal translocation of chromosome 9 and 22 t(9;22) (q34;q11). It translates a chimeric protein, p210, characterized by constitutive activation of its tyrosine kinase, which triggers leukemogenic pathways resulting in onset of chronic myeloid leukemia (CML). In CML, the classic fusion is b2a2 or b3a2 fusing exon 13 (b2) or exon 14 (b3) of BCR to exon 2 (a2) of ABL. The type of bcr/abl transcripts may be associated with different prognosis and hence useful in therapeutic plan. This study was conducted to calculate the frequency of these splice variants as the frequencies of different fusion oncogenes associated with leukaemia can vary in different geographical regions due to interplay of genetic variation in different ethnic populations, diverse environmental factors and living style. A very sensitive nested RT-PCR was established to detect BCR-ABL splice variants in CML. Sensitivity of RT-PCR assay was of the order of 10–6. Thirty CML patients were subjected to BCR-ABL analysis. Out of 30 Pakistani patients, 19 (64%) expressed b3a2 while 11 (36%) expressed b2a2 transcript. This shows that BCR-ABL splice variants differ in their frequencies which may have an effect on biology and implications for prognosis and management of BCR-ABL positive Leukemias.

关键词： BCR-ABL positive Leukemia Leukemia genetics Philadelphia Chromosome Chronic Myeloid Leukemia BCR-ABL Alternative Splicing BCR-ABL splice variants Leukemia alternative splicing Pharmacogenetics

Automatic Anomaly Monitoring in Public Surveillance Areas

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Intelligent Automation & Soft Computing 2023年第3期35卷 2655-2671页

作者： Mohammed Alarfaj mahwish Pervaiz Yazeed Yasin Ghadi Tamara al Shloul Suliman A.Alsuhibany Ahmad Jalal Jeongmin Park Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science Bahria UniversityIslamabadPakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science Air UniversityIslamabadPakistan Department of Computer Engineering Korea Polytechnic University237 Sangidaehak-ro Siheung-siGyeonggi-do15073Korea

With the dramatic increase in video surveillance applications and public safety measures,the need for an accurate and effective system for abnormal/sus-picious activity classiﬁcation also *** it has multiple applications,the problem is very *** this paper,a novel approach for detecting nor-mal/abnormal activity has been *** used the Gaussian Mixture Model(GMM)and Kalmanﬁlter to detect and track the objects,*** that,we performed shadow removal to segment an object and its *** object segmentation we performed occlusion detection method to detect occlusion between multiple human silhouettes and we implemented a novel method for region shrinking to isolate occluded *** c-mean is utilized to verify human silhouettes and motion based features including velocity and opticalﬂow are extracted for each identiﬁed *** Wolf Optimizer(GWO)is used to optimize feature set followed by abnormal event classiﬁcation that is performed using the XG-Boost classiﬁ*** system is applicable in any surveillance appli-cation used for event detection or anomaly *** of proposed system is evaluated using University of Minnesota(UMN)dataset and UBI(Uni-versity of Beira Interior)-Fight dataset,each having different type of *** mean accuracy for the UMN and UBI-Fight datasets is 90.14%and 76.9%*** results are more accurate as compared to other existing methods.

关键词： Abnormal event classiﬁcation gray wolf optimizer region shrinking xg-boost classiﬁer

Microstructure and thermoelectric properties of nanoparticled copper selenide alloys synthesized using a microwave-assisted hydrothermal method

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ChemPhysMater 2023年第3期2卷 207-216页

作者： mahwish Khan Jinze Zhai Wenbin Su Fahad Mehmood Tingting Chen Juanjuan Feng Hongchao Wang Chunlei Wang School of Physics State Key Laboratory of Crystal MaterialsShandong UniversityJinan 250100China

With the fabrication of high-performance thermoelectric(TE)materials,developments are being made in enhanc-ing the figure of merit,zT,of TE ***-like binary copper selenide(Cu_(2) Se)chalcogenides recently gained significant recognition because of their anomalous but fascinating electrical and thermal transport *** this study,a facile synthesis technique was adopted in fabricating Cu_(2) Se nanoparticles using a rapid microwave-assisted hydrothermal route at different reaction *** results were compared with those of the Cu_(2) Se solid-state(SS)sample synthesized using the traditional melting and annealing technique.X-ray diffrac-tion patterns revealed successful synthesis of nanoparticles and a phase transition from orthorhombic𝛼-phase and cubic𝛽-phase to a single orthorhombic structure after *** electron microscopic images revealed that although the grain sizes of the nanoparticle(NP)bulk samples increased with the reaction time of the microwave hydrothermal process,the grain sizes were significantly smaller than that of the SS ***,NP bulk samples exhibited plenty of nano-grains and pores that are absent in the SS *** size and distribution of the grains and pores were measured to study their effects on the transport of carriers and *** NP30 sample exhibited the highest power factor of 983.3μW K−2 m at 673 K among the NP samples,exhibiting intermediate values of resistivity and Seebeck coefficient that are close to those of the SS ***,the NP samples exhibited appreciably lower thermal conductivity than the SS sample that is attributed to strengthened phonon *** minimum thermal conductivity of the NP05 sample,0.78 WK−1 m−1 at 348 K,is 1.7 times lower than that of the SS ***,a maximum zT of 0.56 at 673 K,being approximately 1.3 times higher than that of the SS sample owing to the optimized thermal conductivity,was achieved for the NP30 *** value

关键词： Cu_(2)Se alloys Microwave hydrothermal synthesis Nanoparticles Multiscale microstructure Thermoelectric performance

Polymorphic information and genetic diversity in Brassica speciesrevealed by RAPD markers

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BIOCELL 2020年第4期44卷 769-776页

作者： ALI RAZA ABU BAKR UMER FAROOQ WAQAR AHMAD KHAN AHSAN IQBAL SADETTINÇELİK mahwish ALI RAO SOHAIL AHMAD KHAN Centre of Agricultural Biochemistry and Biotechnology University of AgricultureFaisalabad38040Pakistan Department of Environmental Sciences COMSATS Institute of Information TechnologyVehari61170Pakistan Institute of Molecular Biology&Biotechnology Bahauddin Zakariya UniversityMultan66000Pakistan Department of Plant Breeding and Genetics University of AgricultureFaisalabad38040Pakistan Department of Forestry GençVocational SchoolBingol UniversityGenç-Bingol12500Turkey Department of Biological Sciences National University of Medical SciencesRawalpindi46000Pakistan Key Lab of Biology and Genetic Improvement of Oil Crops Oil Crops Research InstituteChinese Academy of Agricultural ScienceWuhan430062China

Randomly amplified polymorphic DNA(RAPD)is a tremendously convenient approach used to discriminate between Brassica species owing to its accuracy and *** primers generate adequate genetic information that can be used in the primer-marker *** this work,twenty RAPD-PCR based markers were executed to generate polymorphic data,like polymorphic information content(PIC),mean resolving power(MRP),resolving power(RP),effective multiplex ratio(EMR),and marker index(MI)for the first time and genetic distance among and between six Brassica species were *** results indicated that 20 primers produced a total of 231 scored band and generated 87%polymorphic *** PIC,MRP,RP,MI,and EMR values were 0.088,0.65,6.7,0.78,and 8.9,*** showed an overall negative correlation with MRP,RP,MI,and EMR,whereas MRP,RP,and EMR,were positively correlated with each *** identities ranged from 41.99%(between Brassica napus and Brassica oleracea)to 68.83%(between Brassica campestris and Brassica oleracea).Dendrogram results showed no clustering between species except between Brassica campestris and Brassica ***,these results will be helpful to acquire useful information about the markers and their use to determine the genomic structures of Brassica ***,based on genetic distance and polymorphic information,new hybrids can be developed for effective oilseed production.

关键词： Brassica Dendrogram DNA markers Genetic distance Gel electrophoresis Polymorphism