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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.
Congestion-Aware Handover in LTE Systems for Load Balancing in Transport Network
Safdar Nawaz Khan Marwat,Sven Meyer,Thushara Weerawardane,Carmelita Goerg 한국전자통신연구원 2014 ETRI Journal Vol.36 No.5
Long-Term Evolution employs a hard handoverprocedure. To reduce the interruption of data flow,downlink data is forwarded from the serving eNodeB(eNB) to the target eNB during handover. In cellularnetworks, unbalanced loads may lead to congestion inboth the radio network and the backhaul network,resulting in bad end-to-end performance as well ascausing unfairness among the users sharing the bottlenecklink. This work focuses on congestion in the transportnetwork. Handovers toward less loaded cells can helpredistribute the load of the bottleneck link; such amechanism is known as load balancing. The results showthat the introduction of such a handover mechanism intothe simulation environment positively influences thesystem performance. This is because terminals spendmore time in the cell; hence, a better reception is offered. The utilization of load balancing can be used to furtherimprove the performance of cellular systems that areexperiencing congestion on a bottleneck link due to anuneven load.
AZIZ, Tariq,MARWAT, Jahanzeb,MUSTAFA, Sheraz,KUMAR, Vikesh Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.12
The primary purpose of the study is to investigate the volatility spillovers from global economic policy uncertainty and macroeconomic factors to the Islamic stock market returns. The study focuses on the Islamic stock indices of emerging economies including Indonesia, Malaysia, and Turkey. The Macroeconomic factors are industrial production, consumer price index, exchange rate. EGARCH model is employed for investigation of volatility spillovers. The results show that the global economic policy uncertainty has a significant spillover effect only on the returns of Turkish Islamic stock index. Similarly, the shocks in macroeconomic factors have little influence on the volatility of Islamic indices returns. The volatility of Indonesian and the Turkish Islamic stock indices returns is not influenced from the fluctuations in macroeconomic factors. However, there is significant volatility spillover only from industrial production to the returns of Malaysian Islamic index. The results suggest that the Islamic stock markets are less likely to influence from the global economic policies and macroeconomic factors. The stability of Islamic stocks provide opportunity for diversification of portfolios, particularly in stressed market conditions. The major price factors of Islamic markets could be firms' specific factors or investors' behaviors. The findings are helpful for policy makers and investors in formulating policies and portfolios.
AZIZ, Tariq,MARWAT, Jahanzeb,ZEESHAN, Asma,PARACHA, Yaser,AL-HADDAD, Lara Korea Distribution Science Association 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.3
The study investigates the diversification behavior of Islamic stocks against US financial uncertainty. Considering limitations found in the literature, a comprehensive index of financial uncertainty (FU) is used, developed by Jurado, Ludvigson, and Ng (2015). The empirical analysis uses monthly data from four Islamic markets - Saudi Arabia, Malaysia, Indonesia, and Turkey - for the period from January 2010 to September 2019. Results of the bivariate EGARCH models show that Islamic stocks can be used for diversification purpose against the financial uncertainty of the US because the volatility of US uncertainty does not propagate in the Islamic stock markets. Moreover, findings show that the spillover effect of financial uncertainty varies with the FU forecast horizon. The spillover effect of FU increases with an increase in the FU forecast horizon and becomes significant over 3-month and 12-month periods in the case of Saudi Arabia. The current volatility of Islamic stock returns is independent of the size of shocks in past volatility. The leverage effect and asymmetry have been found in Saudi Arabia and Malaysia. The findings validate the arguments of the literature that Islamic markets are resilient facing uncertainties and perform well during crisis periods. The findings are important for investors in making better portfolio decisions.
Linkage between US Financial Uncertainty and Stock Markets of SAARC Countries
AZIZ, Tariq,MARWAT, Jahanzeb,MUSTAFA, Sheraz,ZEESHAN, Asma,IQBAL, Yasir Korea Distribution Science Association 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.2
The primary purpose of the study is to investigate the volatility spillover from financial uncertainty (FU) of the United States (US) to the stock markets of SAARC member countries including India, Sri-Lanka, Pakistan, and Bangladesh. The empirical literature overlooked SAARC countries and the FU index. Based on the estimation method, the data of FU is available for three different forecast horizons including 1-month, 3-months, and 12-months. For empirical analysis, monthly data is used from February 2013 to September 2019. EGARCH model is employed to investigate the volatility spillover effects. The findings of the study show that the spillover effect of FU varies with the forecast horizon. The FU with a higher forecast horizon has a significant spillover effect on more countries. The spillover effect of US financial uncertainty is negative in most of the SAARC countries. Bangladesh stock market is influenced by FU with all three forecast horizons whereas the volatility of the Pakistan stock market is not influenced by FU with any forecast horizon. The findings are consistent with the concept of "limited trade openness" in the financial markets of emerging economies. The emerging economies avoid financial market openness to minimize the risk of spillover of other countries.
Reassessment of Volatility Transmission Among South Asian Equity Markets
Tariq AZIZ,Jahanzeb MARWAT,Sheraz MUSTAFA,Vikesh KUMAR,Lara AL-HADDAD 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.1
This study investigates the nexus among the South Asian economies. Effects of shocks in the equity market of one country on the equity market of the other country are examined. For empirical analysis, the time series monthly data is used for the period from February 2013 to August 2019. The study focuses on the four larger economies of the region, namely, India, Bangladesh, Pakistan, and Sri Lanka. To investigate for asymmetric effects of positive and negative shocks, EGARCH model is used. The findings show the mix nature of the spillovers between the various pairs of countries. The equity market of Pakistan has two-way spillover effects with the equity market of Bangladesh, but has no association with the equity markets of India and Sri Lanka. The volatility in the equity market of India significantly influences the volatility of the financial markets of Bangladesh and Sri Lanka. Similarly, the capital market of Sri Lanka has a negative association with the equity market of India as well as Bangladesh, but does not affect the equity market of any other country. These findings validate the argument in the literature that geographic location influences the nexus among equity markets. The findings are important for policy-makers and investors
Wajahat Khalid,Muhammad Ramzan Abdul Karim,Mohsin Ali Marwat The Korean Electrochemical Society 2024 Journal of electrochemical science and technology Vol.15 No.1
The text highlights the growing need for eco-friendly energy storage and the potential of metal-organic frameworks (MOFs) to address this demand. Despite their promise, challenges in MOF-based energy storage include stability, reproducible synthesis, cost-effectiveness, and scalability. Recent progress in supercapacitor materials, particularly over the last decade, has aimed to overcome these challenges. The review focuses on the morphological characteristics and synthesis methods of MOFs used in supercapacitors to achieve improved electrochemical performance. Various types of MOFs, including monometallic, binary, and tri-metallic compositions, as well as derivatives like hybrid nanostructures, sulfides, phosphides, and carbon composites, are explored for their energy storage potential. The review emphasizes the quest for superior electrochemical performance and stability with MOF-based materials. By analyzing recent research, the review underscores the potential of MOF-based supercapacitors to meet the increasing demands for high power and energy density solutions in the field of energy storage.