Asma Zahra

Bio: Asma Zahra is an academic researcher from COMSATS Institute of Information Technology. The author has contributed to research in topics: Firefly algorithm & Energy management. The author has an hindex of 5, co-authored 9 publications receiving 84 citations.

Uncertainty Assisted Robust Tuberculosis Identification With Bayesian Convolutional Neural Networks

Abstract: Tuberculosis (TB) is an infectious disease that can lead towards death if left untreated. TB detection involves extraction of complex TB manifestation features such as lung cavity, air space consolidation, endobronchial spread, and pleural effusions from chest x-rays (CXRs). Deep learning based approach named convolutional neural network (CNN) has the ability to learn complex features from CXR images. The main problem is that CNN does not consider uncertainty to classify CXRs using softmax layer. It lacks in presenting the true probability of CXRs by differentiating confusing cases during TB detection. This paper presents the solution for TB identification by using Bayesian-based convolutional neural network (B-CNN). It deals with the uncertain cases that have low discernibility among the TB and non-TB manifested CXRs. The proposed TB identification methodology based on B-CNN is evaluated on two TB benchmark datasets, i.e., Montgomery and Shenzhen. For training and testing of proposed scheme we have utilized Google Colab platform which provides NVidia Tesla K80 with 12 GB of VRAM, single core of 2.3 GHz Xeon Processor, 12 GB RAM and 320 GB of disk. B-CNN achieves 96.42% and 86.46% accuracy on both dataset, respectively as compared to the state-of-the-art machine learning and CNN approaches. Moreover, B-CNN validates its results by filtering the CXRs as confusion cases where the variance of B-CNN predicted outputs is more than a certain threshold. Results prove the supremacy of B-CNN for the identification of TB and non-TB sample CXRs as compared to counterparts in terms of accuracy, variance in the predicted probabilities and model uncertainty.

IoT based ransomware growth rate evaluation and detection using command and control blacklisting

Abstract: Internet of things (IoT) is internetworking of various physical devices to provide a range of services and applications. IoT is a rapidly growing field, on an account of this; the security measurements for IoT should be at first concern. In the modern day world, the most emerging cyber-attack threat for IoT is ransomware attack. Ransomware is a kind of malware with the aim of rendering a victim's computer unusable or inaccessible, and then asking the user to pay a ransom to revert the destruction. In this paper we are evaluating ransomware attacks statistics for the past 2 years and the present year to estimate growth rate of the most emerging ransomware families from the last 3 years to evaluate most threatening ransomware attacks for IoT. Growth rate results shows that the number of attacks for Cryptowall and locky ransomware are notably increasing therefore, these ransomware families are potential threat to IoT. Moreover, we present a Cryptowall ransomware attack detection model based on the communication and behavioral study of Cryptowall for IoT environment. The proposed model observes incoming TCP/IP traffic through web proxy server then extracts TCP/IP header and uses command and control (C&C) server black listing to detect ransomware attacks.

Efficient Energy Management System Using Firefly and Harmony Search Algorithm

Abstract: In this paper, performance of energy management controller (EMC) based on meta-heuristic algorithms: Harmony Search Algorithm (HSA) and Firefly Algorithm (FA) are evaluated. Critical peak pricing (CPP) scheme is implemented to calculate the electricity cost. Appliances are categorized into three groups on the basis of power consumption. Electricity cost minimization and electricity load shifting from peak hours towards off peak hours are the main objectives of the paper. In simulation results, adopted approach reduces the Peak to Average Ratio (PAR) and total electricity cost. Furthermore, HSA shows better results than FA in terms of PAR and electricity cost.

Anti-ulcerogenic activity of Typhonium flagelliforme aqueous leaf extract against ethanol-induced gastric mucosal injury in rats

Abstract: Typhonium flagelliforme (Araceae) is an indigenous medicinal plant of Malaysiawhich is endowed with curative properties against a variety of illness including injuries, oedema, coughs, pulmonary ailments, bleeding and cancer. In this study,T. flagelliforme aqueous leaf extract was used to investigate its gastroprotective effect in adult Sprague Dawley rats which were divided into four groups. The rats were orally pre-treated with sterile distilled water (ulcer control groups), omeprazole 20 mg/kg (reference group), 250 and 500 mg/kg of T. flagelliforme(experimental groups) one hour before oral administration of absolute ethanol to generate gastric mucosal injury. After an additional hour, the rats were sacrificed and the ulcer areas of the gastric walls were determined. The ulcer control group exhibited severe mucosal injury, whereas groups pre-treated with T. flagelliforme extracts exhibited significant protection of gastric mucosal injury. These finding were also confirmed by histological studies. These results suggest that T. flagelliforme promotes ulcer protection as ascertained grossly by significant reduction of ulcer area and histology by comparatively decreases in ulcer areas, reduction or absence of edema and leucocytes infiltration of submucosal layer compared to ulcer control group. Key words: Typhonium flagelliforme, rodent tuber, gastric ulcer, histology, aqueous extract.

Energy Efficiency Using Genetic and Crow Search Algorithms in Smart Grid

Abstract: Demand Side Management (DSM) is an efficient and robust strategy for energy management, Peak to Average Ratio (PAR) reduction and cost minimization. Many DSM techniques have been proposed for industrial, residential and commercial areas in last years. In this paper, we have design Home Energy Management Scheduler (HEMS) using two algorithms Genetic Algorithm (GA) and Crow Search Algorithm (CSA) for electricity cost and PAR minimization. Real Time Pricing (RTP) signals are used for electricity bill calculation. Simulation results demonstrate that our proposed scheme efficiently achieved our targeted objectives. However, GA performs superior than CSA due to high convergence rate. Furthermore, a trade-off exists between electricity cost and user waiting time; when electricity cost is low, user waiting time is high and vice versa.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

In vivo antioxidant and antiulcer activity of Parkia speciosa ethanolic leaf extract against ethanol-induced gastric ulcer in rats

Abstract: Background: The current study was carried out to examine the gastroprotective effects of Parkia speciosa against ethanolinduced gastric mucosa injury in rats. Methodology/Principal Findings: Sprague Dawley rats were separated into 7 groups. Groups 1–2 were orally challenged with carboxymethylcellulose (CMC); group 3 received 20 mg/kg omeprazole and groups 4–7 received 50, 100, 200 and 400 mg/kg of ethanolic leaf extract, respectively. After 1 h, CMC or absolute ethanol was given orally to groups 2–7. The rats were sacrificed after 1 h. Then, the injuries to the gastric mucosa were estimated through assessment of the gastric wall mucus, the gross appearance of ulcer areas, histology, immunohistochemistry and enzymatic assays. Group 2 exhibited significant mucosal injuries, with reduced gastric wall mucus and severe damage to the gastric mucosa, whereas reductions in mucosal injury were observed for groups 4–7. Groups 3–7 demonstrated a reversal in the decrease in Periodic acid-Schiff (PAS) staining induced by ethanol. No symptoms of toxicity or death were observed during the acute toxicity tests. Conclusion: Treatment with the extract led to the upregulation of heat-shock protein 70 (HSP70) and the downregulation of the pro-apoptotic protein BAX. Significant increases in the levels of the antioxidant defense enzymes glutathione (GSH) and superoxide dismutase (SOD) in the gastric mucosal homogenate were observed, whereas that of a lipid peroxidation marker (MDA) was significantly decreased. Significance was defined as p,0.05 compared to the ulcer control group (Group 2). Citation: Al Batran R, Al-Bayaty F, Jamil Al-Obaidi MM, Abdualkader AM, Hadi HA, et al. (2013) In Vivo Antioxidant and Antiulcer Activity of Parkia speciosa

Mechanisms of Gastroprotective Effects of Ethanolic Leaf Extract of Jasminum sambac against HCl/Ethanol-Induced Gastric Mucosal Injury in Rats.

Abstract: Jasminum sambac is used in folk medicine as the treatment of many diseases. The aim of the present investigation is to evaluate the gastroprotective effects of ethanolic extracts of J. sambac leaves against acidified ethanol-induced gastric ulcers in rats. Seven groups of rats were orally pre-treated with carboxymethylcellulose (CMC) as normal group, CMC as ulcer group, 20 mg/kg of omeprazole as positive group, 62.5, 125, 250, and 500 mg/kg of extract as the experimental groups, respectively. An hour later, CMC was given orally to normal group and acidified ethanol solution was given orally to the ulcer control, positive control, and the experimental groups. The rats were sacrificed after an hour later. Acidity of gastric content, the gastric wall mucus, ulcer areas, and histology and immunohistochemistry of the gastric wall were assessed. Gastric homogenates were determined for prostaglandin E2 (PGE2), superoxide dismutase (SOD), andmalondialdehyde (MDA) content. Ulcer group exhibited significantly severe mucosal injury as compared with omeprazole or extract which shows significant protection towards gastric mucosal injury the plant promotes ulcer protection as it shows significant reduction of ulcer area grossly, and histology showed marked reduction of edema and leucocytes infiltration of submucosal layer compared with ulcer group. Immunohistochemistry showed overexpression of Hsp70 protein and downexpression of Bax protein in rats pretreated with extract. Significant increased in the pH, mucus of gastric content and high levels of PGE2, SOD and reduced amount of MDA was observed.

From ants to whales: metaheuristics for all tastes

Abstract: Nature-inspired metaheuristics comprise a compelling family of optimization techniques. These algorithms are designed with the idea of emulating some kind natural phenomena (such as the theory of evolution, the collective behavior of groups of animals, the laws of physics or the behavior and lifestyle of human beings) and applying them to solve complex problems. Nature-inspired methods have taken the area of mathematical optimization by storm. Only in the last few years, literature related to the development of this kind of techniques and their applications has experienced an unprecedented increase, with hundreds of new papers being published every single year. In this paper, we analyze some of the most popular nature-inspired optimization methods currently reported on the literature, while also discussing their applications for solving real-world problems and their impact on the current literature. Furthermore, we open discussion on several research gaps and areas of opportunity that are yet to be explored within this promising area of science.