Sentiment Analysis of Product Reviews to Identify Deceptive Rating Information in Social Media: A SentiDeceptive Approach

M. Irfan Marwat,Javed Ali Khan,Dr. Mohammad Dahman Alshehri,Muhammad Asghar Ali,Hizbullah,Haider Ali,Muhammad Assam 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.3

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

Differential antioxidative and biochemical responses to aluminium stress in Brassica juncea cultivars

Javed Ahmad,Mohd Affan Baig,Arlene Asthana Ali,Asma Abdulkareem Al‑Huqail,Mohamed Mohamed Ibrahim,Mohammad I rfan Q ureshi 한국원예학회 2018 Horticulture, Environment, and Biotechnology Vol.59 No.5

Aluminium (Al) toxicity in acidic soils limits crop production worldwide. We evaluated eleven genotypes of Brassica juncea (Mustard) under Al stress on basis of their growth and shortlisted two best among them for further comparative analysis. Our objective was to elucidate individual and differential oxidative damage and defence response elicited by Al treatment in selected mustard genotypes, ‘Pusa Tarak’ and ‘Pusa Vijay’. Thirty-day-old plants of both genotypes were subjected to Al stress for a period of 24 h and 72 h. Concentration of superoxides was visible much higher in leaves of ‘Pusa Vijay’ both at 24 h and 72 h, also confirmed by oxidative stress marker thiobarbituric acid reactive substances (TBARS). The activities of the enzymatic antioxidants superoxide dismutase (SOD), ascorbate peroxidase (APX), glutathione reductase (GR), glutathione S-transferase (GST), and catalase (CAT) were significantly higher in ‘Pusa Tarak’ compared to control and ‘Pusa Vijay’ at both time stages. Levels of non-enzymatic antioxidants glutathiones and ascorbates were already higher in ‘Pusa Vijay’; however, Al treatment increased their levels in both genotypes with non-significant changes on inter-genotypes basis. More and significant decline by Al in chlorophylls was observed in ‘Pusa Vijay’. Interestingly, increase in proline content by Al was much prominent in ‘Pusa Tarak’ compared to ‘Pusa Vijay’. The in vitro antioxidant capacity estimation of mustard genotypes, evaluated by measuring 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and hydroxyl radical scavenging (HRSA) activities proved that extract of ‘Pusa Tarak’ can detoxify more radicals than ‘Pusa Vijay’. We conclude that ‘Pusa Tarak’ can upregulate cellular antioxidants and osmoregulation, and quench more radicals compared to ‘Pusa Vijay’. The results will contribute for selection of better Brassica genus to be grown in Al rich acidic soils, and help in designing strategies for crop breeding and cultivation.

Effect of High Reynolds Number on Hydromagnetic Peristaltic Flow in an Inclined Channel Using Finite Element Method

Tariq Javed,A. H. Hamid,B. Ahmed,N. Ali 한국물리학회 2017 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.71 No.12

An analysis of the peristaltic flow in an inclined channel for different wave forms is carried out in this paper. The developed mathematical model is represented by a set of partial differential equations. The finite element method is implemented to solve the governing equations for stream function and vorticity. The obtained results are valid beyond the long wavelength and low Reynolds number limits. Important features of peristaltic transport are discussed for the variation of magnetic field, Reynolds and wave numbers. The obtained results, when compared with the results available in literature are in good agreement.

Rhizobium Inoculation for Mitigating the Salinity Stress in Maize (zea Mays) under Gnotobiotic Conditions

Qasim Ali,Zahir Ahmad Zahir,Hafiz Naeem Asghar,Muhammad Javed Akhtar,Muhammad Kamran,Muhammad Yahya Khan,Sanaullah Yasin 한국토양비료학회 2014 한국토양비료학회 학술발표회 초록집 Vol.2014 No.6

Bacteriocinogenic Potential of Newly Isolated Strains of Enterococcus faecium and Enterococcus faecalis from Dairy Products of Pakistan

Imran Javed,Safia Ahmed,Muhammad Ishtiaq Ali,Basher Ahmad,Pir Bux Ghumro,Abdul Hameed,Ghulam Jilani Chaudry 한국미생물 · 생명공학회 2010 Journal of microbiology and biotechnology Vol.20 No.1

Comparative Analysis for Chronic Disease Prediction via Deep Machine Learning Approaches

Rabia Javed,Tahir Abbas,Jamshaid Iqbal Janjua,Sadaqat Ali Ramay,M. Kashan Basit,Muhammad Irfan 한국차세대컴퓨팅학회 2023 한국차세대컴퓨팅학회 학술대회 Vol.2023 No.12

Globally, chronic diseases have a significant impact on health. The diagnosis of chronic diseases has seen extensive usage of machine learning techniques. Early disease detection and treatment lower the risk of increasing disease severity and, consequently, related mortality. The major goal of this research is to provide a technique that increases classification accuracy while also shortening computing time. This comparative research shows the impact of distinct model architectures and features on disease prediction accuracy in addition to assessing the advantages and disadvantages of each technique. These discoveries have implications for personalized healthcare, allowing medical professionals to select the best models for various chronic conditions. Additionally, this research can direct the creation of better forecasting technologies, as well as influence healthcare legislation and budget allocation. In our study comparative analysis of the state-of-the-art approaches has been presented. Using a hybrid model combination of CNN and RNN could be more beneficial. In conclusion, our comparison research improves our comprehension of the potential of deep machine learning for chronic disease prediction, highlighting the significance of adjusting model selection to certain disease types. To progress the field of chronic disease prediction, future research should concentrate on improving these models, and further explore their applicability across various and larger datasets.

Numerical analysis and parametric optimization of surge protection devices in a long up-pumping water pipeline

Mubashir Ali Siddiqui,Hassan Ahmed,Muhammad Bilal Javed,Umair Shahid 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.1

This study aims to present a parametric analysis of combined use of two surge protection devices in a relatively very long up-pumping water supply pipeline. Transient conditions are induced by sudden pump tripping. The effects of four parameters of hydropneumatic tank, i.e., polytropic exponent, initial air volume, orifice diameter and wave celerity and two parameters of surge tank, i.e., tank volume and tank orifice diameter are investigated on pressure surges. The parameters are optimized to achieve reduced pressure fluctuations throughout the pipe length. A numerical model is developed to perform hydraulic transient analysis in the pipeline system. Governing partial differential equations for unsteady flows are solved by the method of characteristics (MOC) and are subsequently converted into algebraic form using finite difference method. To establish the authenticity of the model, it is experimentally validated by comparing the model results with the experimental results. The validated model is then employed to analyze the effects of various parameters of the two surge protection devices on pressure fluctuations along the pipe length. The results obtained from the study are optimized for safe operation and economic use of the system.

A review of photocatalytic CO2 reduction: exploring sustainable carbon emission mitigation from thermodynamics to kinetics and strategies for enhanced efficiency

Akbar Hassan,Javed Muhammad Subhan,Iqbal Syeda Tehreem,Khan Muhammad Iftikhar,Anwar Tauseef,Anjum Faiza,Ahmad Ashfaq,Muneeb Muhammad,Ali Asghar,Won Chun Oh 한국세라믹학회 2024 한국세라믹학회지 Vol.61 No.3

To mitigate the increased CO 2 emission, CO 2 reduction to multi-carbon fuels or other useable substances is an appealing yet essential approach. Since, reduction of CO 2 is a thermodynamically uphill process, an economical CO 2 fi xation is only achievable if energy source used is of renewable energy such as solar energy. Photocatalytic CO 2 reduction is a complex pro- cess due to its dependency on catalyst design, selectivity, effi ciency, and photostability. The competence of a photocatalytic CO2 reduction reaction is eff ected by factors, such as the type of photocatalyst used their band-gap energy, surface area, and structure of the crystal. This review discusses the kinetics and thermodynamics of photocatalytic CO 2 reduction and consid- ers the eff ects of parameters like defects and impurity doping on photocatalysis. The study also focusses on the selectivity of products, i.e., methane, methanol, formaldehyde, etc. This comprehensive review provides insights into the development and improvement of photocatalytic effi ciency for CO 2 photoreduction, contributing to the reduction of carbon emissions and a more sustainable future.

Comparison of Safety and Efficacy of Botox and Neuronox in the Management of Benign Essential Blepharospasm: A Split-face Study

Sayali Sane,Mohammad Javed Ali,Milind N Naik 대한안과학회 2019 Korean Journal of Ophthalmology Vol.33 No.5

Purpose: To compare the efficacy and safety of Botox and Neuronox in the management of benign essentialblepharospasm (BEB). Methods: We performed a triple-masked, randomized control study to compare Botox and Neuronox in 48 eyesof 24 patients with BEB. All 24 patients randomly received Botox or Neuronox in the periorbital region in amasked, randomized split-face manner, keeping the injection sites and doses uniform. The toxin preparation,injection, and clinical evaluations were done by three independent observers. Objective outcome measuresincluded improvement in the severity of spasm, grading of the functional visual status, changes in palpebralfissure height, lagophthalmos, superficial punctate keratitis and Schirmer’s test at 2 weeks, 6 weeks, and uponconclusion of the effect of the toxin. Subjective outcome measures included duration of the effect and a forcedchoice stating which half of the face was better. Evaluations were performed through clinical measurements,external digital photography, and high-definition videography. Results: The mean duration of relief from spasms was 3.78 months (standard deviation, 1.58 months; range, 1to 6 months). The improvement in the objective parameters like severity of spasm and functional visual statuswas statistically significant at the 2-week and 6-week follow-up visits (p < 0.001). The changes in palpebral fissureheight, lagophthalmos, and superficial punctate keratitis were equally observed in both groups. At 2 and6 weeks, three of 24 (12.5%) and one of 24 (4%) patients, respectively, reported an unequal effect betweenthe two sides of the face, but this difference was not statistically significant. At final follow-up (conclusion of thetoxin effect), patients reported equal effect with no preference for either hemiface. No statistically significantdifferences were found in the comparative analysis between the Neuronox and Botox groups. Conclusions: Neuronox and Botox are comparable in terms of their safety and efficacy in the management of BEB.

Trends in Stroke Presentations before and during the COVID-19 Pandemic: A Meta-Analysis

Noman Ishaque,Asif Javed Butt,Joseph Kamtchum-Tatuene,Ali Zohair Nomani,Sarah Razzaq,Nida Fatima,Chetan Vekhande,Radhika Nair,Naveed Akhtar,Khurshid Khan,Maher Saqqur,Ashfaq Shuaib 대한뇌졸중학회 2022 Journal of stroke Vol.24 No.1

Background and Purpose There are reports of decline in the rates of acute emergency presentations during coronavirus disease 2019 (COVID-19) pandemic including stroke. We performed a meta-analysis of the impact of COVID-19 pandemic on rates of stroke presentations and on rates of reperfusion therapy. Methods Following the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines, we systematically searched the literature for studies reporting changes in stroke presentations and treatment rates before and during the COVID-19 pandemic. Aggregated data were pooled using meta-analysis with random-effect models. Results We identified 37 observational studies (n=375,657). Pooled analysis showed decline in rates of all strokes (26.0%; 95% confidence interval [CI], 22.4 to 29.7) and its subtypes; ischemic (25.3%; 95% CI, 21.0 to 30.0), hemorrhagic (27.6%; 95% CI, 20.4 to 35.5), transient ischemic attacks (41.9%; 95% CI, 34.8 to 49.3), and stroke mimics (45.6%; 95% CI, 33.5 to 58.0)during months of pandemic compared with the pre-pandemic period. The decline was most evident for mild symptoms (40% mild vs. 25%–29% moderate/severe). Although rates of intravenous thrombolytic (IVT) and endovascular thrombectomy (EVT) decreased during pandemic, the likelihood of being treated with IVT and EVT did not differ between the two periods, both in primary and in comprehensive stroke centers (odds ratio [OR], 1.08; 95% CI, 0.94 to 1.24 and OR,0.95; 95% CI, 0.83 to 1.09, respectively). Conclusions Rates of all strokes types decreased significantly during pandemic. It is of paramount importance that general population should be educated to seek medical care immediately for stroke-like symptoms during COVID-19 pandemic. Whether delay in initiation of secondary prevention would affect eventual stroke outcomes in the long run needs further study.