Impact of Terrorism on Stock Market: A Case of South Asian Stock Markets

The purpose of this study is to examine the impact of terrorism on stock markets of South Asia namely, Karachi Stock Exchange 100 index (Pakistan), Bombay Stock Exchange (India), Colombo Stock Exchange (Sri Lanka) and Chittagong Stock Exchange (Bangladesh). Monthly panel data has been used for the period of January 2000 to December 2016. Terrorism events happened during the period of 2000 to 2016 have been incorporated to examine the impact of terrorism on stock market returns of South Asia. DCC GARCH through R software is used to analyze the impact of terrorism on stock market returns and to analyze the spillover effect of terrorism in one country and on the stock markets of other countries of South Asia. The results indicate that terrorism has significant and negative effect on stock market returns of Pakistan, India and Bangladesh but insignificant in Sri Lanka. Results also shows that stock markets return of Pakistan, India, and Bangladesh are significant and positively correlated with each other except the Stock market of Sri Lanka

PREDICTIVE MODELING USING CAPILLARY PRESSURE MODELS AND FLUID DENSITIES AND THEIR EFFECT ON RESERVOIR FLUID DISTRIBUTION AND DYNAMICS

Capillary pressure has always been a point of concern for reservoir modeling. It describes the initial pressure at which the de-saturation will be initiated and at the other extreme; it defines the irreducible saturation of the displaced fluid. In this study, Brooks & Corey and Van Genuchten models are used to predict maximum displacement pressure data with reference to non-uniformity in pore-size distribution. Both models are compared and a correlation has been developed to predict maximum displacement pressure with reference to variation in pore-size distribution index for Van Genuchten model. Further, the fluid distribution and water-oil contact level with reference to free-water level has been calculated using both models for reservoir modeling. The obtained results show that Van Genuchten model gives higher thickness for transition zones and difference in water-oil contact level with reference to free water level, as compared to Brooks and Corey correlation. Furthermore, on comparative basis, these differences increase with the decrease in uniformity in pore size distribution. Thus, the degree of uncertainty and complexity in developing reservoirs and analyzing fluid dynamics increases, in case of tighter or heterogeneous formations. Further, this study also shows that density also plays an important role in fluid dynamics and distribution with the reservoir

Does market portfolio index really affect foreign exchange exposure? An empirical evidence from Malaysian non financial firms

Financial theory holds that fluctuations in exchange rate significantly influence open market firms by affecting their cash flows and firm value. Because of high market openness and fluctuations in Malaysian exchange rate, this study first investigates the extent to which 224 sampled firms of Malaysia face foreign exchange risk during the period of 2008 to 2014. It is found that 37% of the firms are exposed to (total) foreign exchange rate exposure during sample period. The dominance of Malaysian firms with positive β1 in each year implies that most of the Malaysian firms in the sample are net-exporters. To test the sensitivity of market portfolio index in exposure model, the Malaysian market index, i.e., FBMEMAS, is added in the exposure model and foreign exchange exposure for Malaysian firms is re-estimated over the sample period. It is obvious from the results that the number of significant coefficients of market index remains surprisingly high throughout the sample period than that of tradeweighted Index (TWI). A 67% of total firms have significant relationship with market index over the sample period as compared to 9% of TWI which shows drastic decreased in foreign exchange exposure by 76%. These results confirm that sometimes market portfolio index as a whole become strongly correlated with exchange rate changes and, in result, it dramatically reduces foreign exchange exposure

Why Banks Need Adequate Capital Adequacy Ratio? A Study of Lending & Deposit Behaviors of Banking Sector of Pakistan

This study focuses on the impact of Capital Adequacy Ratio on bank’s lending and deposit behavior and also on the importance of maintaining certain level of capital reserve. CAR is examined using two different ratios leverage ratio and risk-based capital ratio. This study is beneficial for the banking industry in determining enough CAR and to make decision for taking deposits and issuing loans. The sample of the study includes 25 banks of Pakistan; 20 conventional and 5 Islamic banks and the study period is of 10 years. Panel data methodology is used. Data is collected from secondary sources. Findings show that CAR has impact on change in capital and change in loans

Classification of Graphomotor Impressions Using Convolutional Neural Networks: An Application to Automated Neuro-Psychological Screening Tests

Graphomotor impressions are a product of complex cognitive, perceptual and motor skills and are widely used as psychometric tools for the diagnosis of a variety of neuro-psychological disorders. Apparent deformations in these responses are quantified as errors and are used are indicators of various conditions. Contrary to conventional assessment methods where manual analysis of impressions is carried out by trained clinicians, an automated scoring system is marked by several challenges. Prior to analysis, such computerized systems need to extract and recognize individual shapes drawn by subjects on a sheet of paper as an important pre-processing step. The aim of this study is to apply deep learning methods to recognize visual structures of interest produced by subjects. Experiments on figures of Bender Gestalt Test (BGT), a screening test for visuo-spatial and visuo-constructive disorders, produced by 120 subjects, demonstrate that deep feature representation brings significant improvements over classical approaches. The study is intended to be extended to discriminate coherent visual structures between produced figures and expected prototypes

The Nexus between sustainability of business model innovation, financial knowledge, and environment: A developing economy perspective

This study intends to investigate how aspects such as financial knowledge and the rate of technological advancement influence the lifetime of enterprises in developing nations like Pakistan. For this purpose, a survey study was designed to obtain data from 325 business owners in different parts of the country. Structural Equation Modelling (SEM) was utilized to analyze this dataset. According to the analysis outcomes, not only do practices connected to financial literacy and innovation play a crucial role in a firm’s long-term viability, but they also have a substantial beneficial impact on the company’s viability. The research concluded that an increase in financial knowledge, expertise, and experience in corporate operations helps the continued viability of firms. Knowledge of financial concerns also predicted the company’s ability to innovate and adapt. In addition to the environmental sustainability of the business. As a result, it was concluded that it plays the role of a mediator in the link between innovation and the ongoing existence of businesses. Because of this, financial literacy is now acknowledged as a vital knowledge resource for determining one’s financial course of action, which was not the case previously. According to the study’s conclusions, for businesses to continue to be sustainable, authorities need to enhance their financial literacy level and adopt sustainability models into their day-to-day operations

Robust CNN architecture for classification of reach and grasp actions from neural correlates: an edge device perspective

Brain-computer interfaces (BCIs) systems traditionally use machine learning (ML) algorithms that require extensive signal processing and feature extraction. Deep learning (DL)-based convolutional neural networks (CNNs) recently achieved state-of-the-art electroencephalogram (EEG) signal classification accuracy. CNN models are complex and computationally intensive, making them difficult to port to edge devices for mobile and efficient BCI systems. For addressing the problem, a lightweight CNN architecture for efficient EEG signal classification is proposed. In the proposed model, a combination of a convolution layer for spatial feature extraction from the signal and a separable convolution layer to extract spatial features from each channel. For evaluation, the performance of the proposed model along with the other three models from the literature referred to as EEGNet, DeepConvNet, and EffNet on two different embedded devices, the Nvidia Jetson Xavier NX and Jetson Nano. The results of the Multivariant 2-way ANOVA (MANOVA) show a significant difference between the accuracies of ML and the proposed model. In a comparison of DL models, the proposed models, EEGNet, DeepConvNet, and EffNet, achieved 92.44 ± 4.30, 90.76 ± 4.06, 92.89 ± 4.23, and 81.69 ± 4.22 average accuracy with standard deviation, respectively. In terms of inference time, the proposed model performs better as compared to other models on both the Nvidia Jetson Xavier NX and Jetson Nano, achieving 1.9 sec and 16.1 sec, respectively. In the case of power consumption, the proposed model shows significant values on MANOVA (p < 0.05) on Jetson Nano and Xavier. Results show that the proposed model provides improved classification results with less power consumption and inference time on embedded platforms

Beyond the Horizon, Backhaul Connectivity for Offshore IoT Devices

The prevalent use of the Internet of Things (IoT) devices over the Sea, such as, on oil and gas platforms, cargo, and cruise ships, requires high-speed connectivity of these devices. Although satellite based backhaul links provide vast coverage, but they are inherently constrained by low data rates and expensive bandwidth. If a signal propagated over the sea is trapped between the sea surface and the Evaporation Duct (ED) layer, it can propagate beyond the horizon, achieving long-range backhaul connectivity with minimal attenuation. This paper presents experimental measurements and simulations conducted in the Industrial, Scientific, and Medical (ISM) Band Wi-Fi frequencies, such as 5.8 GHz to provide hassle-free offshore wireless backhaul connectivity for IoT devices over the South China Sea in the Malaysian region. Real-time experimental measurements are recorded for 10 km to 80 km path lengths to determine average path loss values. The fade margin calculation for ED must accommodate additional slow fading on top of average path loss with respect to time and climate-induced ED height variations to ensure reliable communication links for IoT devices. Experimental results confirm that 99% link availability of is achievable with minimum 50 Mbps data rate and up to 60 km distance over the Sea to connect offshore IoT devices

Establishment of health related physical fitness evaluation system for school adolescents aged 12–16 in Pakistan: a cross-sectional study

BackgroundThe decline in adolescent physical fitness is a significant global public health concern, and Pakistan is no exception. The country’s absence of a health-related physical fitness (HRPF) evaluation system has compounded this issue. To bridge this gap, this study aims to develop a scientifically-based HRPF evaluation system for the adolescent population that meets international standards. The evaluation system identifies at-risk children and improves adolescent health outcomes, including obesity, cardiovascular and musculoskeletal disorders, chronic diseases, and psychological illnesses, through crucial physical fitness evaluation. This study specifically aims to establish an HRPF evaluation system for school adolescents aged 12–16 in Pakistan.MethodsA cross-sectional study was conducted among 2,970 school adolescents aged 12–16 years in the South Punjab, Pakistan. The study used a stratified sampling technique to select participants. The HRPF evaluation system included four components: cardiorespiratory endurance, core muscular endurance, muscular strength, and body composition. Data were collected through standardized tests and anthropometric measurements.ResultsThe study’s results indicated that the HRPF evaluation scoring system was feasible and valid for evaluating the HRPF of school adolescents in the South Punjab region of Pakistan. The results of the evaluation system categorized participants into five groups based on their performance: excellent (6.2%), good (24.9%), medium (50.7%), poor (17%), and very poor (1.2%).ConclusionThe study establishes an HRPF evaluation system for Pakistani school adolescents. This system lays the foundation for implementing effective strategies to improve their physical health. The findings offer valuable insights to policymakers, health professionals, and educators, enabling them to promote fitness and devise impactful interventions for enhancing HRPF in this population