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| 1 | 一种Galileo E5信号双环路捕获跟踪方法显示文摘Galileo导航系统是实现多系统联合定位的优良选择,故对Galileo信号接收的研究具有重要的理论和实际意义。当前Galileo E5信号主要采用二进制偏移载波调制,其信号接收存在精度和效率等多方面的不足。针对Galileo E5信号的特点,提出结合捕获和跟踪的双环路组合跟踪方法。研究使用并行码相位搜索的方法,实现对Galileo E5信号准确捕获,粗略估计出伪随机噪声码相位和载波频率。通过紧密耦合的码跟踪环路和载波跟踪环路,对这2个参数进行精确锁定跟踪。仿真结果显示:跟踪信号在0~1 000 ms内功率谱密度集中在频带之内,包络恒定,相位连续变化,实现了Galileo E5信号的连续稳定跟踪。 | 唐作栋 龚晓峰 Subhan KHAN ZHU Yiqun | 2020 | 重庆理工大学学报(自然科学)2020，34，7： | 2 |
| 2 | Suitable energy platform significantly improves charge separation of g-C3N4 for CO2 reduction and pollutant oxidation under visible-light显示文摘The photocatalytic activities of g-C3N4 can be significantly improved by increasing life time of the photogenerated charges. Here, in this work we introduced TiO2 as proper energy platform to accept the photogenerated electrons from g-C3N4 during photocatalysis. The nanophotocatalysts formed from the combination of a suitable amount of TiO2 nanoparticles and g-C3N4 nanosheets showed 8.75 and 4.22% enhancement in photocatalytic activities for CO2 reduction and 2-chlorophenol(2-CP) degradation under visible light illumination as compared to bare g-C3N4. Based on the surface photovoltage spectra, photoluminescence spectra and examination of formed hydroxyl radicals, it was confirmed that these enhanced photoactivities were attributed to the much-improved charge separation via the electron transfer from g-C3N4 to TiO2. From trapping experiments,it was found that hydroxyl radicals were the major species involved in the photocatalytic degradation of 2-CP.This study is helpful to synthesize efficient photocatalysts to cope with energy and environmental issues. | Amir Zada Nauman Ali Fazle Subhan Natasha Anwar Muhammad Ishaq Ali Shah Muhammad Ateeq Zahid Hussain Khair Zaman Momin Khan | 2019 | Progress in Natural Science:Materials International2019，29，2： | 1 |
| 3 | Performance Evaluation of Supervised Machine Learning Techniques for Efficient Detection of Emotions from Online Content显示文摘Emotion detection from the text is a challenging problem in the text analytics.The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions.However,most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets,resulting in performance degradation.To overcome this issue,this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset.The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision,recall ad f-measure.Finally,a classifier with the best performance is recommended for the emotion classification. | Muhammad Zubair Asghar Fazli Subhan Muhammad Imran Fazal Masud Kundi Adil Khan Shahboddin Shamshirband Amir Mosavi Peter Csiba Annamaria RVarkonyi Koczy | 2020 | Computers, Materials & Continua2020，，6： | 0 |
| 4 | National guidelines for the diagnosis and treatment of hilar cholangiocarcinoma显示文摘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. | 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 | 2024 | World Journal of Gastroenterology2024，30，9： | 0 |
| 5 | Plasticity of leaf morphology of Bruguiera sexangula to salinity zones in Bangladesh's Sundarbans显示文摘Bruguiera sexangula(Lour.)Poir is an exclusive evergreen mangrove species to the Sundarbans of Bangladesh.It grows well in moderate saline zones with full sunlight.This study presents leaf morphological plasticity in B.sexangula to saline zones.Leaves were sampled from different saline zones and various morphological traits were measured.The results exposed a wide deviations of leaf size parameters:leaf length varied 6.6–17.3 cm;width 2.7–7.8 cm;upper quarter width 2.2–6.5 cm;down quarter width 2.5–7.3 cm;and petiole length 0.17–1.43 cm.Leaf length was significantly larger in fresh water than in other salinity zones,whereas,leaf width,upper and lower leaf quarters were significantly larger in medium saline zone.Leaf shape parameters showed a large variation among saline zones.Leaf base angle was significantly larger in both medium and strong salinity zones.Tip angle was significantly greater in medium salinity zone.Leaf perimeter was significantly larger in fresh water but leaf area was significantly bigger in medium saline zone.Leaf index and specific leaf area were maximum in moderate saline zone.Plasticity index was the highest in moderate saline for almost all the parameters presented.The ordination(PCA)showed clusters of leaf samples although there were some overlap among them which suggested a salt-stress relationship among salinity zones.The results indicate that B.sexangula had a plasticity strategy on leaf morphological parameters to salinity in the Sundarbans.This study will provide basic information of leaf plasticity of this species among saline zones which will help for site selection of coastal planting and will also provide information for policy makers to take necessary steps for its conservation. | Md.Salim Azad Abdus Subhan Mollick Rawnak Jahan Khan Ranon Md.Nabiul Islam Khan Md.Kamruzzaman | 2022 | Journal of Forestry Research2022，33，6： | 0 |
| 6 | 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 |
| 7 | Empirical Analysis of Neural Networks-Based Models for Phishing Website Classification Using Diverse Datasets显示文摘Phishing attacks pose a significant security threat by masquerading as trustworthy entities to steal sensitive information,a problem that persists despite user awareness.This study addresses the pressing issue of phishing attacks on websites and assesses the performance of three prominent Machine Learning(ML)models—Artificial Neural Networks(ANN),Convolutional Neural Networks(CNN),and Long Short-Term Memory(LSTM)—utilizing authentic datasets sourced from Kaggle and Mendeley repositories.Extensive experimentation and analysis reveal that the CNN model achieves a better accuracy of 98%.On the other hand,LSTM shows the lowest accuracy of 96%.These findings underscore the potential of ML techniques in enhancing phishing detection systems and bolstering cybersecurity measures against evolving phishing tactics,offering a promising avenue for safeguarding sensitive information and online security. | Shoaib Khan Bilal Khan Saifullah Jan Subhan Ullah Aiman | 2023 | Journal of Cyber Security2023，5，1： | 0 |
| 8 | Plant Derived Antiviral Products for Potential Treatment of COVID-19: A Review显示文摘COVID-19 caused by SARS-CoV-2 is declared global pandemic.The virus owing high resemblance with SARS-CoVand MERS-CoV has been placed in family of beta-coronavirus.However,transmission and infectivity rate of COVID-19 is quite higher as compared to other members of family.Effective management strategy with potential drug availability will break the virus transmission chain subsequently reduce the pressure on the healthcare system.Extensive research trials are underway to develop novel efficient therapeutics against SARS-CoV-2.In this review,we have discussed the origin and family of coronavirus,structure,genome and pathogenesis of virus SARS-CoV-2 inside human host cell;comparison among SARS,MERS,SARS-CoV-2 and common flu;effective management practices;treatment with immunity boosters;available medication with ongoing clinical trials.We suggest medicinal plants could serve as potential candidates for drug development against COVID-19 infection. | Rashid Iqbal Khan Mazhar Abbas Khurram Goraya Muhammad Zafar-ul-Hye Subhan Danish | 2020 | Phyton-International Journal of Experimental Botany2020，89，3： | 0 |
| 9 | Position Vectors Based Efcient Indoor Positioning System显示文摘With the advent and advancements in the wireless technologies,Wi-Fi ngerprinting-based Indoor Positioning System(IPS)has become one of the most promising solutions for localization in indoor environments.Unlike the outdoor environment,the lack of line-of-sight propagation in an indoor environment keeps the interest of the researchers to develop efcient and precise positioning systems that can later be incorporated in numerous applications involving Internet of Things(IoTs)and green computing.In this paper,we have proposed a technique that combines the capabilities of multiple algorithms to overcome the complexities experienced indoors.Initially,in the database development phase,Motley Kennan propagation model is used with Hough transformation to classify,detect,and assign different attenuation factors related to the types of walls.Furthermore,important parameters for system accuracy,such as,placement and geometry of Access Points(APs)in the coverage area are also considered.New algorithm for deployment of an additional AP to an already existing infrastructure is proposed by using Genetic Algorithm(GA)coupled with Enhanced Dilution of Precision(EDOP).Moreover,classication algorithm based on k-Nearest Neighbors(k-NN)is used to nd the position of a stationary or mobile user inside the given coverage area.For k-NN to provide low localization error and reduced space dimensionality,three APs are required to be selected optimally.In this paper,we have suggested an idea to select APs based on Position Vectors(PV)as an input to the localization algorithm.Deducing from our comprehensive investigations,it is revealed that the accuracy of indoor positioning system using the proposed technique unblemished the existing solutions with signicant improvements. | Ayesha Javed Mir Yasir Umair Alina Mirza Abdul Wakeel Fazli Subhan Wazir Zada Khan | 2021 | Computers, Materials & Continua2021，，5： | 0 |
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