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| 1 | 印度河上游流域冰川度日因子变化及其影响因素显示文摘当前,基于正积温的度日模型广泛应用于冰川消融研究中,该模型的核心参数是度日因子。根据印度河上游Sachen、Gharko、Barpu冰川2014-2016年的物质平衡和气温实测资料,计算得到消融期内各冰川研究区的度日因子,并分析了度日因子的时空变化特征及影响因素。研究结果显示:Sachen、Gharko、Barpu冰川度日因子均值分别为2. 83 mm·d^-1·℃-1、3. 74 mm·d^-1·℃^-1、3. 91 mm·d^-1·℃^-1;各冰川度日因子皆随着海拔升高而递增,海拔递增率分别为0. 003 7 mm·d^-1·℃^-1·m^-1、0. 007 4 mm·d^-1·℃^-1·m^-1、0. 004 1 mm·d^-1·℃^-1·m^-1;对于同一观测点而言,度日因子不是一个常数,会随着时间的变化而改变,冰川度日因子随着年际变化呈增加的趋势;度日因子受表碛影响显著,度日因子整体上随着表碛厚度的增加而递减。然而表碛厚度低于2 cm时,表碛的覆盖作用促进了冰川的消融,表碛覆盖区冰川度日因子大于裸露区冰川;冰川朝向的变化对度日因子产生了一定的影响,面向阳坡的冰川度日因子随海拔递增率大于阴坡。 | 巫建逢 张寅生 高海峰 邹小娟 Muhammad Atif Wazir | 2020 | 干旱区研究2020，37，1： | 2 |
| 2 | 印度河上游Bagrot山谷降水稳定同位素变化及与水汽来源的关系显示文摘利用2015年8月—2016年7月在印度河上游流域Bagrot山谷降水稳定同位素(δ^(18)O和δD)观测结果以及当地气象资料,利用同位素示踪及统计分析方法,并结合HYSPLIT模型,对研究区降水稳定同位素变化特征、大气水线以及水汽来源进行了分析。结果表明:观测期间Bagrot山谷降水稳定同位素的季节变化明显,δ^(18)O与δD秋冬季偏低,春夏季偏高,且与气温变化一致,存在显著的温度效应,而降水量效应不明显。而且发现研究区局地大气水线截距和斜率均低于全球的,反映了降水过程中云下二次蒸发作用较为强烈,因此,不同的降水形态导致该研究区局地大气水线的斜率和截距不同。当液态降水(降雨)发生时,由于在较为干旱的气候环境下,雨滴在降落的过程中受到二次蒸发相对较强,使得局地大气水线的斜率和截距偏低;而当固态降水(降雪)发生时,由于温度较低,受再循环水汽和二次蒸发的影响较小,导致局地大气水线的斜率和截距均偏高。Bagrot山谷及其周边地区,从南到北局地大气水线的斜率相差不大,而其截距总体上随着纬度升高而降低,可能与云下二次蒸发导致稳定同位素发生的不平衡分馏逐渐强烈有关。通过Bagrot山谷站点降水稳定同位素观测结果并结合HYSPLIT模型的后向追踪,研究还发现,研究区全年主要受西风环流以及局地环流的影响。但与研究区以北的临近站点(慕士塔格、和田等)相比有所不同,由于Bagrot山谷位置更靠南,其仍然偶尔受到来自南方的海洋性水汽影响。这一研究结果可能对该地区树轮稳定同位素记录的解译具有一定的指示意义。 | 王邺凡 余武生 张寅生 张腾 高海峰 MUHAMMAD Atif Wazir | 2019 | 干旱区地理2019，42，2： | 2 |
| 3 | Use of Ethnomedicinal Plants by the People Living around Indus River显示文摘 | Sakina Mussarat Nasser M. AbdEl-Salam Akash Tariq Sultan Mehmood Wazir Riaz Ullah Muhammad Adnan John R. S. Tabuti | 2014 | Evidence-Based Complementary and Alternative Medicine2014，，： | 1 |
| 4 | Prevalence of HBV infection in suspected population of conflict-affected area of war against terrorism in North Waziristan FATA Pakistan显示文摘 | Amjad Ali Muhammad Nisar Muhammad Idrees Habib Ahmad Abrar Hussain Shazia Rafique Sabeen Sabri Habib ur Rehman Liaqat Ali Shariatullah Wazir Tariq Khan | 2012 | Infection, Genetics and Evolution2012，，8： | 1 |
| 5 | Variation in patient dose due to differences in calibration and dosimetry protocols显示文摘For precise and accurate patient dose delivery,the dosimetry system must be calibrated properly according to the recommendations of standard dosimetry protocols such as TG-51 and TRS-398. However, the dosimetry protocol followed by a calibration laboratory is usually different from the protocols that are followed by different clinics, which may result in variations in the patient dose.Our prime objective in this study was to investigate the effect of the two protocols on dosimetry measurements.Dose measurements were performed for a Co-60 teletherapy unit and a high-energy Varian linear accelerator with 6 and 15 MV photon and 6, 9, 12, and 15 MeV electron beams, following the recommendations and procedures of the AAPM TG-51 and IAEA TRS-398 dosimetry protocols. The dosimetry systems used for this study were calibrated in a Co-60 radiation beam at the Secondary Standard Dosimetry Laboratory(SSDL) PINSTECH,Pakistan, following the IAEA TRS-398 protocol. The ratio of the measured absorbed doses to water in clinical setting,D_w(TG-51/TRS-398), was 0.999 and 0.997 for 6 and15 MV photon beams,whereas these ratios were 1.013,1.009, 1.003, and 1.000 for 6, 9, 12, and 15 MeV electron beams, respectively. This difference in the absorbed dosesto-water D_w ratio may be attributed mainly due to beam quality(K_Q) and ion recombination correction factor. | Wazir Muhammad Asad Ullah Gulzar Khan Tahir Zeb Khan Tauseef Jamaal Fawad Ullah Matiullah Khan Amjad Hussain | 2018 | Nuclear Science and Techniques2018，29，5： | 0 |
| 6 | Seroprevalence of HDV among non-hospitalized HBs Ag positive patients from KPK-region of Pakistan显示文摘Objective: To study the seroprevalence of hepatitis B virus(HBV) and hepatitis delta virus(HDV) infections in patients visiting outpatient department of a major tertiary care hospital in Khyber Pakhtunkhwa region of Pakistan.Methods: Blood samples were collected from non-hospitalized patients. Serological analysis was done by ELISA and viral DNA was amplified by PCR. The amplified DNA was analyzed by agarose gel electrophoresis.Results: Altogether, 946 blood samples were screened, overall percentage of HBs Agpositive patients remained 22.41%(prevalence: 224.10/1 000; CI: 0.197 5 ± 0.250 7) with the highest incidence rates among relatively younger age groups(20–29 years). The prevalence of HBV–HDV co-infection was found to be 46.75/1 000; CI: 0.031 8 ± 0.061 7.In HBs Ag-positive patients, anti-HBc-total was detected in 86.79% while 25.00% were positive for anti-HBc-immunoglobulin M. Similarly, among these patients, HBV DNA was detected in 64.13% and 10.85% were co-infected with HDV. Different symptoms were associated with the prevailing infection, including malaise(62%), anorexia(66%) and fatigue(73%). The most commonly associated symptom was abdominal discomfort. Among these patients, certain risk factors, including surgery, visit to dentist and intravenus infusions were frequently associated with the infection(x^2= 95.23; df = 11; P < 0.000 1).Conclusions: Overall, this study confirmed higher prevalence of active HBV/HDV infection, among young patients from Khyber Pakhtunkhwa region having no prior history of viral hepatitis. | Ismail Jalil Muhammad Arshad Zara Rafaque Fazle Raziq Robina Wazir Sajid Malik Javid Iqbal Dasti | 2016 | Asian Pacific Journal of Tropical Biomedicine2016，6，7： | 0 |
| 7 | A qualitative exploration of Pakistan’s street children, as a consequence of the poverty-disease cycle显示文摘Background:Street children are a global phenomenon,with an estimated population of around 150 million across the world.These children include those who work on the streets but retain their family contacts,and also those who practically live on the streets and have no or limited family contacts.In Pakistan,many children are forced to work on the streets due to health-related events occurring at home which require children to play a financially productive role from an early stage.An explanatory framework adapted from the poverty-disease cycle has been used to elaborate these findings.Methods:This study is a qualitative study,and involved 19 in-depth interviews and two key informant interviews,conducted in Rawalpindi,Pakistan,from February to May 2013.The data was audio taped and transcribed.Key themes were identified and built upon.The respondents were contacted through a gatekeeper ex-street child who was a member of the street children community.Results:We asked the children to describe their life stories.These stories led us to the finding that street children are always forced to attain altered social roles because health-related problems,poverty,and large family sizes leave them no choice but to enter the workforce and earn their way.We also gathered information regarding high-risk practices and increased risks of sexual and substance abuse,based on the street children’s increased exposure.These children face the issue of social exclusion because diseases and poverty push them into a life full of risks and hazards;a life which also confines their social role in the future.Conclusion:The street child community in Pakistan is on the rise.These children are excluded from mainstream society,and the absence of access to education and vocational skills reduces their future opportunities.Keeping in mind the implications of health-related events on these children,robust inter-sectoral interventions are required. | Muhammad Ahmed Abdullah Zeeshan Basharat Omairulhaq Lodhi Muhammad Hisham Khan Wazir Hameeda Tayyab Khan Nargis Yousaf Sattar Adnan Zahid | 2014 | Infectious Diseases of Poverty2014，3，1： | 0 |
| 8 | Blockchain Based Enhanced ERP Transaction Integrity Architecture and PoET Consensus显示文摘Enterprise Resource Planning(ERP)software is extensively used for the management of business processes.ERP offers a system of integrated applications with a shared central database.Storing all business-critical information in a central place raises various issues such as data integrity assurance and a single point of failure,which makes the database vulnerable.This paper investigates database and Blockchain integration,where the Blockchain network works in synchronization with the database system,and offers a mechanism to validate the transactions and ensure data integrity.Limited research exists on Blockchain-based solutions for the single point of failure in ERP.We established in our study that for concurrent access control andmonitoring of ERP,private permissioned Blockchain using Proof of Elapsed Time consensus is more suitable.The study also investigated the bottleneck issue of transaction processing rates(TPR)of Blockchain consensus,specifically ERP’s TPR.The paper presents systemarchitecture that integrates Blockchain with an ERP system using an application interface. | Tehreem Aslam Ayesha Maqbool Maham Akhtar Alina Mirza Muhammad Anees Khan Wazir Zada Khan Shadab Alam | 2022 | Computers, Materials & Continua2022，，1： | 0 |
| 9 | Enhanced Fingerprinting Based Indoor Positioning Using Machine Learning显示文摘Due to the inability of the Global Positioning System(GPS)signals to penetrate through surfaces like roofs,walls,and other objects in indoor environments,numerous alternative methods for user positioning have been presented.Amongst those,the Wi-Fi fingerprinting method has gained considerable interest in Indoor Positioning Systems(IPS)as the need for lineof-sight measurements is minimal,and it achieves better efficiency in even complex indoor environments.Offline and online are the two phases of the fingerprinting method.Many researchers have highlighted the problems in the offline phase as it deals with huge datasets and validation of Fingerprints without pre-processing of data becomes a concern.Machine learning is used for the model training in the offline phase while the locations are estimated in the online phase.Many researchers have considered the concerns in the offline phase as it deals with huge datasets and validation of Fingerprints becomes an issue.Machine learning algorithms are a natural solution for winnowing through large datasets and determining the significant fragments of information for localization,creating precise models to predict an indoor location.Large training sets are a key for obtaining better results in machine learning problems.Therefore,an existing WLAN fingerprinting-based multistory building location database has been used with 21049 samples including 19938 training and 1111 testing samples.The proposed model consists of mean and median filtering as pre-processing techniques applied to the database for enhancing the accuracy by mitigating the impact of environmental dispersion and investigated machine learning algorithms(kNN,WkNN,FSkNN,and SVM)for estimating the location.The proposed SVM with median filtering algorithm gives a reduced mean positioning error of 0.7959 m and an improved efficiency of 92.84%as compared to all variants of the proposed method for 108703 m^(2) area. | Muhammad Waleed Pasha Mir Yasir Umair Alina Mirza Faizan Rao Abdul Wakeel Safia Akram Fazli Subhan Wazir Zada Khan | 2021 | Computers, Materials & Continua2021，，11： | 0 |
| 10 | IRMIRS:Inception-ResNet-Based Network for MRI Image Super-Resolution显示文摘Medical image super-resolution is a fundamental challenge due to absorption and scattering in tissues.These challenges are increasing the interest in the quality of medical images.Recent research has proven that the rapid progress in convolutional neural networks(CNNs)has achieved superior performance in the area of medical image super-resolution.However,the traditional CNN approaches use interpolation techniques as a preprocessing stage to enlarge low-resolution magnetic resonance(MR)images,adding extra noise in the models and more memory consumption.Furthermore,conventional deep CNN approaches used layers in series-wise connection to create the deeper mode,because this later end layer cannot receive complete information and work as a dead layer.In this paper,we propose Inception-ResNet-based Network for MRI Image Super-Resolution known as IRMRIS.In our proposed approach,a bicubic interpolation is replaced with a deconvolution layer to learn the upsampling filters.Furthermore,a residual skip connection with the Inception block is used to reconstruct a high-resolution output image from a low-quality input image.Quantitative and qualitative evaluations of the proposed method are supported through extensive experiments in reconstructing sharper and clean texture details as compared to the state-of-the-art methods. | Wazir Muhammad Zuhaibuddin Bhutto Salman Masroor Murtaza Hussain Shaikh Jalal Shah Ayaz Hussain | 2023 | Computer Modeling in Engineering & Sciences2023，，8： | 0 |
| 11 | Anomalous Situations Recognition in Surveillance Images Using Deep Learning显示文摘Anomalous situations in surveillance videos or images that may result in security issues,such as disasters,accidents,crime,violence,or terrorism,can be identified through video anomaly detection.However,differentiat-ing anomalous situations from normal can be challenging due to variations in human activity in complex environments such as train stations,busy sporting fields,airports,shopping areas,military bases,care centers,etc.Deep learning models’learning capability is leveraged to identify abnormal situations with improved accuracy.This work proposes a deep learning architecture called Anomalous Situation Recognition Network(ASRNet)for deep feature extraction to improve the detection accuracy of various anomalous image situations.The proposed framework has five steps.In the first step,pretraining of the proposed architecture is performed on the CIFAR-100 dataset.In the second step,the proposed pre-trained model and Inception V3 architecture are used for feature extraction by utilizing the suspicious activity recognition dataset.In the third step,serial feature fusion is performed,and then the Dragonfly algorithm is utilized for feature optimization in the fourth step.Finally,using optimized features,various Support Vector Machine(SVM)and K-Nearest Neighbor(KNN)based classification models are utilized to detect anomalous situations.The proposed framework is validated on the suspicious activity dataset by varying the number of optimized features from 100 to 1000.The results show that the proposed method is effective in detecting anomalous situations and achieves the highest accuracy of 99.24%using cubic SVM. | Qurat-ul-Ain Arshad Mudassar Raza Wazir Zada Khan Ayesha Siddiqa Abdul Muiz Muhammad Attique Khan Usman Tariq Taerang Kim Jae-Hyuk Cha | 2023 | Computers, Materials & Continua2023，，7： | 0 |
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