EAST: Energy Efficient Adaptive Scheme for Transmission in Wireless Sensor Networks

In this paper, we propose Energy-efficient Adaptive Scheme for Transmission (EAST) in WSNs. EAST is IEEE 802.15.4 standard compliant. In this approach, open-loop is used for temperature-aware link quality estimation and compensation. Whereas, closed-loop feedback helps to divide network into three logical regions to minimize overhead of control packets on basis of Threshold transmitter power loss (RSSIloss) for each region and current number of neighbor nodes that help to adapt transmit power according to link quality changes due to temperature variation. Simulation results show that propose scheme; EAST effectively adapts transmission power to changing link quality with less control packets overhead and energy consumption compared to classical approach with single region in which maximum transmitter power assigned to compensate temperature variation

Testing of Android testing tools: development of a benchmark for the evaluation

With the ever growing trend of smart phones and tablets, Android is becoming more and more popular everyday. With more than one billion active users i to date, Android is the leading technology in smart phone arena. In addition to that, Android also runs on Android TV, Android smart watches and cars. Therefore, in recent years, Android applications have become one of the major development sectors in software industry. As of mid 2013, the number of published applications on Google Play had exceeded one million and the cumulative number of downloads was more than 50 billionii. A 2013 survey also revealed that 71% of the mobile application developers work on developing Android applicationsiii. Considering this size of Android applications, it is quite evident that people rely on these applications on a daily basis for the completion of simple tasks like keeping track of weather to rather complex tasks like managing one’s bank accounts. Hence, like every other kind of code, Android code also needs to be verified in order to work properly and achieve a certain confidence level. Because of the gigantic size of the number of applications, it becomes really hard to manually test Android applications specially when it has to be verified for various versions of the OS and also, various device configurations such as different screen sizes and different hardware availability. Hence, recently there has been a lot of work on developing different testing methods for Android applications in Computer Science fraternity. The model of Android attracts researchers because of its open source nature. It makes the whole research model more streamlined when the code for both, application and the platform are readily available to analyze. And hence, there has been a great deal of research in testing and static analysis of Android applications. A great deal of this research has been focused on the input test generation for Android applications. Hence, there are a several testing tools available now, which focus on automatic generation of test cases for Android applications. These tools differ with one another on the basis of their strategies and heuristics used for this generation of test cases. But there is still very little work done on the comparison of these testing tools and the strategies they use. Recently, some research work has been carried outiv in this regard that compared the performance of various available tools with respect to their respective code coverage, fault detection, ability to work on multiple platforms and their ease of use. It was done, by running these tools on a total of 60 real world Android applications. The results of this research showed that although effective, these strategies being used by the tools, also face limitations and hence, have room for improvement. The purpose of this thesis is to extend this research into a more specific and attribute-­‐ oriented way. Attributes refer to the tasks that can be completed using the Android platform. It can be anything ranging from a basic system call for receiving an SMS to more complex tasks like sending the user to another application from the current one. The idea is to develop a benchmark for Android testing tools, which is based on the performance related to these attributes. This will allow the comparison of these tools with respect to these attributes. For example, if there is an application that plays some audio file, will the testing tool be able to generate a test input that will warrant the execution of this audio file? Using multiple applications using different attributes, it can be visualized that which testing tool is more useful for which kinds of attributes. In this thesis, it was decided that 9 attributes covering the basic nature of tasks, will be targeted for the assessment of three testing tools. Later this can be done for much more attributes to compare even more testing tools. The aim of this work is to show that this approach is effective and can be used on a much larger scale. One of the flagship features of this work, which also differentiates it with the previous work, is that the applications used, are all specially made for this research. The reason for doing that is to analyze just that specific attribute in isolation, which the application is focused on, and not allow the tool to get bottlenecked by something trivial, which is not the main attribute under testing. This means 9 applications, each focused on one specific attribute. The main contributions of this thesis are: A summary of the three existing testing tools and their respective techniques for automatic test input generation of Android Applications. • A detailed study of the usage of these testing tools using the 9 applications specially designed and developed for this study. • The analysis of the obtained results of the study carried out. And a comparison of the performance of the selected tools

Objectives of Governance: A Comparison of Islamic and Western Traditions in the Context of Pakistan

An Islamic state led by a Caliph works to achieve objectives of Islamic governance. The objectives of governance between Western (secular democratic system) and Islamic traditions have close proximity, at least in words. These objectives include collective action (ijtimaiyat) and social justice (Aadalah). Collective action is used to provide basic human rights, while the comparable Islamic term ijtimaiya is aimed at providing basic protections. A Western nation state is defined by having legitimacy to tax and maintain an army for defence, while in Islam, comparable terms, though having difference, are Zakat and Jihad. It is required that an Islamic state should achieve effective internal governance by developing legal instruments for achieving the objectives, even if it works under Khilafah, or democracy

Correlation of Red Cell Distribution Width with Severity of Cardiovascular Diseases

Objectives: To determine the correlation of red cell distribution width (RDW) with severity of cardiovascular diseases. Methodology: This study was conducted at the Department of Pathology, Aziz Fatima Medical and Dental College, Faisalabad, over a period of one year from October 2019 to September 2020. A total of 150 participants were included in the study consisting of 75 patients of cardiovascular disease in case group and 75 participants without any cardiovascular disease in control group. All patients in the study underwent trans radial or transfemoral rout coronary angiography using 5F optitorque catheter for trans radial rout or 6F Judkins catheters for transfemoral rout. All the patient had angiography within 24 hours of admission in the hospital. Results: The patients who were diagnosed with Coronary artery Disease (CAD) had significantly higher mean age (51.45 ± 11.29 years) as compared (44.56 ± 9.45 years) to group B without out CAD. There were 53 (70.67%) males in group A, and 42 (56%) males in group B. The rate of hypertension (61.33%) was significantly higher among patient who diagnosed with CAD. The mean value of RDW CV was found significantly (p-value < 0.05) raised among patients of CAD (14.36 ± 1.02vs. 13.52 ± 0.89). The RDW SD was also significantly higher in group A (43.67 ± 4.39 vs. 41.65 ± 3.46, p-value = 0.002) in comparison to group B. Age and male gender were found to be a significant (p-value < 0.05) contributor for CVD with an odds ratio of 1.18 and 3 respectively. Conclusion: RDW is an effective easily available marker for the assessment of severity of coronary artery disease and helps in risk stratification of CAD patients for further events

Knowledge about asthma: A cross-sectional survey in 4 major hospitals of Karachi, Pakistan

Objective: To determine knowledge and misconceptions about asthma among the local population..Methods: This cross-sectional study was conducted at four tertiary care hospitals; Aga Khan University Hospital, Civil Hospital Karachi, Jinnah Postgraduate Medical Centre and Ojha Institute of Chest Diseases, Karachi, from October to November 2016, and comprised hospital attendants. The questionnaire used in the study comprised 26 questions answered with a true, false or not sure answer.SPSS 20 was used for data analysis.Results: There were 400 participants. The overall mean age was 41.2±14.2 years, and 214(53.5%) of the participants were males. Moreover, 75(19%) participants thought that asthma was a psychological disorder while 181(45%) considered it an infectious disease. Nearly 174(43.5%) believed that inhaled medications had significant side effects. Besides, 264(66%) participants considered steam inhalation to be an effective treatment for asthma, 269(67%) thought that patients with asthma should avoid rice in their diet and 167(42%) considered milk as a common trigger.CONCLUSIONS: Participants\u27 knowledge about asthma was poor and misconceptions were common about the condition

A novel approach for the effective prediction of cardiovascular disease using applied artificial intelligence techniques

Aims: The objective of this research is to develop an effective cardiovascular disease prediction framework using machine learning techniques and to achieve high accuracy for the prediction of cardiovascular disease. Methods: In this paper, we have utilized machine learning algorithms to predict cardiovascular disease on the basis of symptoms such as chest pain, age and blood pressure. This study incorporated five distinct datasets: Heart UCI, Stroke, Heart Statlog, Framingham and Coronary Heart dataset obtained from online sources. For the implementation of the framework, RapidMiner tool was used. The three‐step approach includes pre‐processing of the dataset, applying feature selection method on pre‐processed dataset and then applying classification methods for prediction of results. We addressed missing values by replacing them with mean, and class imbalance was handled using sample bootstrapping. Various machine learning classifiers were applied out of which random forest with AdaBoost dataset using 10‐fold cross‐validation provided the high accuracy. Results: The proposed model provides the highest accuracy of 99.48% on Heart Statlog, 93.90% on Heart UCI, 96.25% on Stroke dataset, 86% on Framingham dataset and 78.36% on Coronary heart disease dataset, respectively. Conclusions: In conclusion, the results of the study have shown remarkable potential of the proposed framework. By handling imbalance and missing values, a significantly accurate framework has been established that could effectively contribute to the prediction of cardiovascular disease at early stages

Response Surface Methodology for the production of endopolygalacturonase by a novel Bacillus licheniformis

Background: Polygalacturonase is one of the most important commercial pectinase. The production cost and the mesophilic nature of the present polygalacturonase is a big problem in its application in the juice industry. A lot of work is going on for the isolation of thermophilic bacterial strains which can utilize pectin as the only carbon source.Methods: Bacterial strains were isolated from rotten fruits and vegetables and cultured at 50 – 70oC. The strains were than screened for endopolygalacturonase activity and identified on the basis of 16S rRNA sequence. Different growth parameters for the production of endopolygalacturonase by Bacillus licheniformis IEB-8 were optimized using Response Surface Methodology under Center Composite Design using JMP-12 software. Endopolygalacturonase was purified in two steps; ammonium sulfate precipitation and then by size exclusion column chromatography.Results: Only four strains, IEB-8, IEB-11, IEB-12 and IEB-13 showed growth above 60oC. Among these four, only IEB-8 was found to be endopolygalacturonase positive, which was identified as Bacillus licheniformis by 16S rRNA gene sequence. Purification fold of 2.57 and 7.48 in the specific activity were achieved using ammonium sulfate precipitation and gel filtration chromatography respectively. Molecular weight of the purified endopolygalacturonase was found to be 42 kDa. The purified endopolygalacturonase showed an optimum pH of 7 and optimum temperature of 55oC.Conclusion: Bacillus licheniformis IEB-8 is a novel bacteria which can efficiently be utilized in the industry for the production of endopolygalacturonase very cheaply. Furthermore, the high optimum working temperature of endopolygalacturonase, increases its significance for its industrial applications.Keywords: Endopolygalacturonase; Bacillus licheniformis; Thermophilic; Response Surface Methodology; Ammonium sulfate precipitatio

Determination of non-organ specific autoantibodies in patients with chronic hepatitis C and association with HLA DRΒ1 (*04) allele

The regulation of immune mechanisms is controlled by major histocompatibility complex/human leukocyte antigen (MHC/HLA). Polymorphisms of the HLA region have an impact on susceptibility to complex infectious and autoimmune diseases. The present study was carried out to determine the frequencies of ASMA, AMA, ANA, dsDNA, and anti-LKM-1 auto-antibodies in hepatitis C patients and to determine their association with the HLA DRβ1 (*04) locus. It was a cross-sectional, analytical study, and 86 patients with chronic HCV were recruited. The presence of auto-antibodies (ASMA, AMA, ANA, dsDNA, and anti-LKM-1) was determined by indirect immunofluorescence and ELISA, while the HLA DRβ1 (*04) allele was assessed by sequence-specific conventional PCR. ANA was detected in 41%, ASMA in 17.4%, AMA in 7%, LKM-1 in 5.8% dsDNA in 4.6% of CHC patients while HLA-DRβ1 (*04) was present in 3.5% of patients, but this was not significantly associated with these auto-antibodies

A Machine Learning-Based Framework for Accurate and Early Diagnosis of Liver Diseases: A Comprehensive Study on Feature Selection, Data Imbalance, and Algorithmic Performance

The liver is the largest organ of the human body with more than 500 vital functions. In recent decades, a large number of liver patients have been reported with diseases such as cirrhosis, fibrosis, or other liver disorders. There is a need for effective, early, and accurate identification of individuals suffering from such disease so that the person may recover before the disease spreads and becomes fatal. For this, applications of machine learning are playing a significant role. Despite the advancements, existing systems remain inconsistent in performance due to limited feature selection and data imbalance. In this article, we reviewed 58 articles extracted from 5 different electronic repositories published from January 2015 to 2023. After a systematic and protocol-based review, we answered 6 research questions about machine learning algorithms. The identification of effective feature selection techniques, data imbalance management techniques, accurate machine learning algorithms, a list of available data sets with their URLs and characteristics, and feature importance based on usage has been identified for diagnosing liver disease. The reason to select this research question is, in any machine learning framework, the role of dimensionality reduction, data imbalance management, machine learning algorithm with its accuracy, and data itself is very significant. Based on the conducted review, a framework, machine learning-based liver disease diagnosis (MaLLiDD), has been proposed and validated using three datasets. The proposed framework classified liver disorders with 99.56%, 76.56%, and 76.11% accuracy. In conclusion, this article addressed six research questions by identifying effective feature selection techniques, data imbalance management techniques, algorithms, datasets, and feature importance based on usage. It also demonstrated a high accuracy with the framework for early diagnosis, marking a significant advancement

Production, Partial Purification and Characterization of Protease through Response Surface Methodology by Bacillus subtilis K-5

Abstract The aim of present study was the production of protease from local Bacillus subtilis through solid state fermentation. Response Surface Methodology (RSM) was used for the optimization of all the culture conditions. Casein (1% w/v) was used as a substrate in nutrient agar medium for the screening of enzyme production potential and showed maximum zone of clearance (4.6 cm). It was identified as Bacillus subtilis K-5 by genetic identification based on 16S rRNA and blast technology of NCBI. Among culture conditions, incubation temperature, incubation time, pH of the medium and moisture level of the substrate were optimized. Maximum protease production was observed at 37oC, pH 9.0 with incubation time of 36 h and moisture to substrate ratio of 1: 0.75. Maximum protease production of 70.21 U/mL was recorded when wheat bran was used as an agro-industrial substrate. The activity of crude protease was observed 99.63 % at 60oC and pH 10.0 with protein concentration 0.63 mg/mL and specific activity of 111.56 U/mg. Protein contents of 0.57 mg/mL (specific activity of 124.72 U/mg) and protein contents of 0.44 mg/mL (specific activity of 143.65 U/mg) were observed by 70% saturation with ammonium sulphate and gel chromatography, respectively. Line Weaver Burk plot was used to find its Vmax and Km, which were 344. 83 mg/mL/min and 100.04 mg/mL, respectively. The study concluded that Bacillus subtilis K-5 is thermophilic and alkaliphilic strain which produces active protease and can be used as potential microorganism for industries