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| 1 | Mycorrhiza and Phosphate Solubilizing Bacteria:Potential Bioagents for Sustainable Phosphorus Management in Agriculture显示文摘Phosphorus(P)is a critical nutrient that plays an essential role in improving soil fertility for optimum plant growth and productivity.It is one of the most deficient macro-nutrients in agricultural soils after nitrogen and is considered inadequate for plant growth and production.To P availability in soils,the farmers are applying huge amounts of synthetic P fertilizers that adversely affect the wider environment,groundwater,soil fertility and microbial population.Many beneficial microbes are known to release and supply soluble P for improving growth and yield of a variety of plants in a sustainable manner in P deficient soils.Thus,inoculation of these microbes,including arbuscular mycorrhizal fungi(AMF)and phosphate solubilizing bacteria(PSB)to soil to enhance crop production without harming the environment,is an alternative approach to chemical fertilizers.The combined role of AMF and PSB in P solubilization is not well understood and the application and mode of action of these microbial groups are often naive due to variation in the environment.Therefore,the current review article would develop a better understanding of the interactive role and mechanisms of AMF and PSB in improving P availability from both organic and inorganic sources in a sustainable crop production system.Finally,the current review would loop out further avenues for researchers interested to commercially produce effective AMF and PSB-based biofertilizers for sustainable management of phosphorus over a wide range of agricultural crops worldwide. | Fazli Wahid Muhammad Sharif Shah Fahad Amjad Ali Muhammad Adnan Rafiullah Shah Saud Subhan Danish Muhammad Arif Ali Niaz Ahmed Hüseyin Arslan Doğan Arslan Murat Erman Ayman EL Sabagh Fatemeh Gholizadeh Rahul Datta | 2022 | Phyton-International Journal of Experimental Botany2022，91，2： | 2 |
| 2 | Fuzzy-Based Sentiment Analysis System for Analyzing Student Feedback and Satisfaction显示文摘The feedback collection and analysis has remained an important subject matter for long.The traditional techniques for student feedback analysis are based on questionnaire-based data collection and analysis.However,the student expresses their feedback opinions on online social media sites,which need to be analyzed.This study aims at the development of fuzzy-based sentiment analysis system for analyzing student feedback and satisfaction by assigning proper sentiment score to opinion words and polarity shifters present in the input reviews.Our technique computes the sentiment score of student feedback reviews and then applies a fuzzy-logic module to analyze and quantify student’s satisfaction at the fine-grained level.The experimental results reveal that the proposed work has outperformed the baseline studies as well as state-of-the-art machine learning classifiers. | Yun Wang Fazli Subhan Shahaboddin Shamshirband Muhammad Zubair Asghar Ikram UllahAmmara Habib | 2020 | Computers, Materials & Continua2020，，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 | 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 |
| 5 | 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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