Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Malware Detection Techniques in Android

-The malware threat for mobile phones is expected to increase with the functionality enhancement of mobile phones. This threat is increased with the surge in population of smart phones instilled with stable Internet access which provides attractive targets for malware developers. Currently, in the smartphone market, Android is currently the most popular smartphone operating system. Due to this popularity and also to its open source nature, Android-based smartphones are now an ideal target for attackers. Since the number of malware designed for Android devices is increasing fast, Android users are looking for security solutions aimed at preventing malicious actions from damaging their smartphones. Anti-malware products promises to effectively protect against malware on mobile devices and many products are available for free or at reasonable prices. From this perspective, we propose and analyse some potential limitation-oriented techniques for effective malware detection.
A Survey and Comparative Analysis of Data Mining Techniques for Network Intrusion Detection Systems

— Despite of growing information technology widely, security has remained one challenging area for computers and networks. In information security, intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of a resource. Currently many researchers have focused on intrusion detection system based on data mining techniques as an efficient artifice. Data mining is one of the technologies applied to intrusion detection to invent a new pattern from the massive network data as well as to reduce the strain of the manual compilations of the intrusion and normal behavior patterns. This article reviews the current state of art data mining techniques, compares various data mining techniques used to implement an intrusion detection system such as Decision Trees, Artificial Neural Network, Naïve Bayes, Support Vector Machine and K-Nearest Neighbour Algorithm by highlighting advantages and disadvantages of each of the techniques. Finally, a discussion of the future technologies and methodologies which promise to enhance the ability of computer systems to detect intrusion is provided and current research challenges are pointed out in the field of intrusion detection system.
ROLE OF MINERALS AND VITAMIN SUPPLEMENTATION IN PATIENTS WITH CARDIAC PROBLEMS

Objective: To see the role of Vitamins and minerals supplementation on physical status of patients suffering from Congestive Heart Failure (dilated cardiomyopathy). Methods: This nonrandomized clinical trial was conducted in department of cardiology, Allied Hospital Faisalabad, Pakistan. In this nonrandomized clinical trial, Forty three Patients with dilated cardiomyopathy who were not showing any significant improvements in physical performance on optimal treatment of heart failure were included. Vitamin D (200,000 IU) supplementation on weekly basis for a period of 12 weeks was added to heart failure treatment. And its effect was seen on 6 minutes’ walk distance and Pro-BNP levels. SPSS version 19 was used for data analysis. Dependent sample t-test was used to see the significant effect of vitamin D supplementation on pre-intervention vitamin D levels, 6MWD and ProBNP. Taking p-value <0.05 as significant. Results: On clinical assessment most of the patients were in NYHA class II (65%), the percentages of NYHA Class I, III and IV was 19%, 9% and 7% respectively. The baseline mean vitamin D level of the study group was 16.59±3.54ng/ml and it raised to 31.97±3.64ng/ml after 12 weeks of supplementation with vitamin D, p value <0.0005. The mean distance travelled by the study group before the intervention was 806±380ft while it increased to 945±393ft after the intervention, p value of 0.008. The mean of pro-BNP level of the study group before the intervention was 1024±635 while it improved to 159±80 after the intervention with a significant p value <0.0005. Conclusion: Vitamin D supplementation decreases the severity of HF as reflected by reduction in serum pro-BNP levels and significant increase in six minutes’ walk distance. World Journal of Pharmaceutical Research SJIF Impact Factor 8.074 Volume 7, Issue 13, 109-115. Research Article ISSN 2277– 7105 Article Received on 13 May 2018, Revised on 04 June 2018, Accepted on 25 June 2018, DOI: 10.20959/wjpr201813-12851 *Corresponding Author Dr. Hira Ijaz PMDC # 90945-P.
Analyzing and Tracing of Various Packet Dropping Attacks Using Containing Order Rough Set

: Intrusion detection systems (IDS) aim at determining attacks against information systems in general. It is difficult to provide secure information systems and maintain them in a secure state for their entire lifetime. Maintenance of such information system is technically difficult as well as economically costly. With the invention of new vulnerabilities to information system new techniques for determining these vulnerabilities have been implemented. Today containing order rough set (CORS) has appeared as a useful mathematical tool for dealing with uncertain data. The main theme of this paper is the analysis and evaluation of packet dropping attack data set through the applications of containing order rough set (CORS) and other concerned notations, formalizes method of data analysis of various packet dropping attacks and rule generation.
Survey on Various Code Coverage Tools

— software testing one of the challenging tasks is to select the test inputs. Code coverage techniques are used to express the amount to which the code of a program is tested. Many coverage tools are available in working environment,. Here we have studied seven code coverage tools and out of which one tool was actually evaluated for their proposed features. A comparative study is presented on the basis of the set criteria.
Renewable Energy Resources Interfacing to Grid at Distribution Level Using Id-Iq Current Control Strategy for Power Quality Improvement

Electric utilities and end users of electric power are becoming increasingly concerned about meeting the growing energy demand. Urbanization and industrialization have changed the lifestyle of human society and the need for electrical energy has enhanced significantly. As the conventional energy sources are not capable of serving the purpose, the researchers have turned their face towards Renewable Energy Sources (RES). Energy sources are scattered across the globe, therefore the available green energy at the distribution level is also used to generate electricity. The hybrid combination of wind/solar systems has proved to be a reliable source to the utility. For extracting maximum power from the RES, battery bank is connected across it. Due to the problem associated with the chemical batteries the wind/solar hybrid combination is directly connected to the grid. There are many issues related to the interconnection of RES to the grid which are addressed with the growth in power electronics field. However the power quality issue occurs due to the presence of non-linear loads at the point of common coupling . Shunt active filter has proved to mitigate the problems associated with the non-linear loads. Researchers have limited their work to interconnection of RES to ideal grid voltages which is not the practical case. In this paper the wind/solar hybrid system is modeled and is interconnected to the unbalanced and distorted grid. Also, RES interfacing inverter is added with shunt active filter functionality and hence overall cost curtailment of the project can be achieved.
Efficient minimization Techniques for Threshold Logic Gate

- In this paper an efficient minimization and optimization techniques are discussed using digital logic network using threshold logic. Almost same energy consumption changing speedup is possible using threshold network and many complex functions can be implemented using threshold logic with lesser number of logic gate and logic level for which these optimization techniques becomes popular for digital system design and applications. In this article, we analysis different present optimization techniques of capacitive threshold-logic gate (CTLG), resonant tunneling diode (RTD), single electronics transistor based threshold gate (SET), Charge Recycling (CR) CMOS threshold logic gate and Memristor Threshold Logic and also analysis systematically among them.
NANOCOMPOSITE, ITS TOXICITY REDUCTION, AND SUSTAINED RELEASE

Objectives: Polyoxometalates (POMs) are proved to be important for applications in medicine and in material science. Here, we represent nanocomposite formation of tungsten-containing potent anticancer polyanion, K6H [CoW11O39 (CpTi)]. 13H2O (CoW11CpTi) with biocompatible ChitosanYC-100 (CSYC100) with the goal to reduce its heavy metal toxicity. Methods: Synthesis of “POM-CSYC100 nanocomposite” was attained without the aid of any cross-linker through electrostatic interaction technique. Nanocomposites were characterized using Fourier transform infrared spectroscopy, dynamic light scattering, transmission electron microscopy, and thermogravimetric analysis. The release profile recorded was slow and sustained at physiological pH. In vitro cytotoxicity assays which show an attribute to reduce the toxicity of these POM were performed on C2C12 (mouse myoblast cell line) and A-549 (lung cancer cell line), which proved the reduced toxicity of nanocomposites as compared to the bare drugs. Results: Sustained release studies showed there was a slow and steady release of CoW11CpTi for 11 hrs, with the 98% of collective release at the end. From in vitro cytotoxic assay, it was deduced that CoW11CpTi -CSYC100 nanocomposite at the concentrations of 1.25 mM, and lower did not exhibit toxic effect on C2C12 cells as 95% total C2C12 cell mass remained viable. While in the case of A549 cells highest 5 mM concentration of bare CoW11CpTi is toxic to the cancer cells and after encapsulation cell viability increases from 10% to 55%. Conclusion: Thus, this study has designated the probability of using POM-chitosan nanocomposite for less toxic and effective biomedicinal applications.
Color Image Segmentation Using K-Means Clustering and Otsu’s Adaptive Thresholding

— In this paper, an approach for color image segmentation is presented. In this method foreground objects are distinguished clearly from the background. As the HSV color space is similar to the way human eyes perceive color, hence in this method, first RGB image is converted to HSV (Hue, Saturation, Value) color model and V (Value) channel is extracted, as Value corresponds directly to the concept of intensity/brightness in the color basics section. Next an Otsu’s multi-thresholding is applied on V channel to get the best thresholds from the image. The result of Otsu’s multi-thresholding may consist of over segmented regions, hence K-means clustering is applied to merge the over segmented regions. Finally background subtraction is done along with morphological processing. This proposed system is applied on Berkley segmentation database. The proposed method is compared with three different types of segmentation algorithms that ensure accuracy and quality of different types of color images. The experimental results are obtained using metrics such as PSNR and MSE, which proves the proposed algorithm, produces better results as compared to other algorithms.
Optimized Feature Extraction based Artificial Intelligence Technique for Empirical Analysis of Stock Market Data

Stock market forecasting is considered as a challenging task in financial time series forecasting. The core idea of a successful stock market forecast is to get the best results with the least amount of input data required and the least complex stock market model. So in this paper, to achieve these goals, this paper proposes a new algorithm Cuckoo Neural for Financial Market (CN_FM), which integrates Cuckoo Search (CS) with a Feed forward back propagation Neural Network (FFBPNN) and build a stock price forecasting proficient system. This research follows some basic steps to design a model for sentiment analysis from Stock market dataset and firstly data is pre-processed to remove the unwanted text. In pre-processing steps the techniques such as normalization, punctuation, stop word removal and tokenization are applied. The extracted features are optimized using CS and in turns used to train the FFBPNN. The results obtained from experiments in the stock market show that the proposed method can reduce the dimensions and produce accurate results for emotion-based text categorization with an accuracy of 99.44%.
THE IMPACT OF BODY MASS INDEX IN PREGNANT WOMEN AND THEIR OBSTETRIC OUTCOMES IN A TERTIARY CARE HOSPITAL OF SOUTH INDIA

OBJECTIVE To assess the prevalence of overweight and obesity, and the impact of body mass index (BMI) on maternal and neonatal outcomes, in a UK obstetric population. STUDY DESIGN: A retrospective study was conducted and data was collected from births between August 2013 to August 2015 within a tertiary referral unit, with over 3600 births per year. STUDY PERIOD: August 2013 – August 2015 STUDY SITE: This study was carried out in OWAISI HOSPITAL AND RESEARCH CENTRE as a clinical audit and therefore did not require approval from a Research Ethics Committee. Women were categorised according to World Health Organization classification: underweight (BMI < 18.50 kg/m2); normal weight (BMI 18.50–24.99 kg/m2; reference group); Over weight (BMI 25.00–29.99 kg/m2); obese class I (BMI 30.00– 34.99 kg/m2); obese class II (BMI 35–39.99 kg/m2); and obese class III (BMI _ 40 kg/m2). Maternal and neonatal outcomes were examined using logistic regression, adjusted for confounding variables. RESULTS : The study highlights a relationship between increasing BMI (from overweight to obese class III) and increasing risk of adverse outcomes, including gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy, caesarean section, macrosomia, and neonatal unit admission, with women in the highest obesity group at risk of additional adverse out-comes, including stillbirth, a longer postnatal stay, and wound problems following caesarean section.By categorising women into overweight and obesity sub classifications (classes I –III), this study clearly demonstrates an increasing risk of adverse outcomes across BMI categories, with women who are overweight also at significant risk both in terms of maternal and neonatal outcomes.
An Integrated Health Care System using IOT

:IoT is nothing but Internet of things. Now a day’s smart technology is used in many ways. Every cloud technology and have some issues based on the availability. IoT is the global communication network utilized in many ways. Many fields are used by the IoT to provide continue services for the users. Wireless sensor network with IoT is the most popular and widely used in many applications such as agriculture, medical and other mentoring devices. In this paper, the amalgamative system is developed to maintain the energy at medical device to transfer the data to the cloud by using the Advanced Wireless Sensor Network technique adopted with IoT features
Image Deblurring and Restoration using Wavelet Transform

: This paper proposes image deblurring process used for removal of noise as well as blurred in an image in frequency domain. Wavelet transform is used for the removal of low frequency noise components in degraded image. The proposed noise removal function produces better result than the existing algorithm. It preserves the important information of the image while retrieving.
Prevalence of Vulvovaginal Infections and Species Specific Distribution of Vulvovaginal Candidiasis in Married Women of North India

Abnormal vaginal discharge is a frequent complaint of women of child bearing age seeking gynaecological care. The frequency of different types of vulvovaginal infections (VVI) showed regional variations. Objectives of the present study were to determine the prevalence of different types of VVI and species specific distribution of vulvovaginal candidiasis (VVC) in North India. A total of 200 married women diagnosed by a gynaecologist for VVI were recruited for the present study. Vaginal swabs from these participants were processed for detection of bacterial vaginosis (BV), VVC and trichomoniasis based on European (IUSTI/WHO) guidelines on the management of vaginal discharge (2011). Species specific distribution of VVC was assessed by HiChrome Candida differential agar, Germ tube test as well as Scanning electron microscopy. The findings of the present study indicate that BV was the most prevalent infection (48.5%) followed by VVC (31%) and mixed infections (20.5%). However, no case of trichomoniasis was detected. Candida albicans was found to be the most prevalent species. Out of non-albicans Candida (NAC) species, C. tropicalis was found to be the most prevalent species. Overall distribution of C. albicans and NAC species indicated marginally high prevalence of NAC species (53%) than C. albicans (47%). When VVI were compared between pregnant and non-pregnant subjects, VVC was more prevalent in pregnant females while BV and mixed infections (MI) were more prevalent in non-pregnant females. Furthermore, in pregnant women C. tropicalis (42.8%) was the most prevalent species while in non-pregnant females C. albicans (43.9%) was the most prevalent species. In conclusion, BV was the most prevalent VVI in North India. C. albicans was the single most prevalent species in VVC while among NAC species, C. tropicalis was found to occur at highest frequency. K e y w o r d s Bacterial vaginosis,
Fuzzy Decision on Transformer Fault Diagnosis using Dissolved Gas Analysis and IEC Ratio Codes

This paper emphasizes on the use of fuzzy approach in dealing with the incipient fault conditions of power transformer. DGA (Dissolved Gas in Oil Analysis) cannot provide better fault diagnosis results when multiple faults are involved. The boundary values specified by the ratio methods are of limited concern . Considering the limitations of convergence of the conventional neural networks in the local minima, fuzzy logic may take care of the uncertainties in fault conditions. Fuzzy decision is used to deal with various incipient fault conditions including the normal condition with major faults as per the IEC Ratio codes. The comparative of the fuzzy system, conventional IEC method of fault diagnosis and Roger’s ratio diagnosis of some oil samples of transformer and data from research paper are presented. Rule based fuzzy decision on various faults is made using IEC Ratio codes.
A Fast and Efficient RBTRC-MAC Protocol for Event-Driven Wireless Sensor Networks

: Event-driven wireless sensor networks have been identified as one of the key areas in the field of wireless communication, where most of the time the network will be in light traffic load situation. When an event has detected, large number of packets will be generated. A MAC protocol designed for this kind of WSNs should be able to swiftly adapt to both light and heavy traffic load situations of the network. Here, implemented a receiver-centric MAC protocol called RC-MAC that integrates duty cycling and receiver centric scheduling. To handle heavy traffic load situation triggered by an event, RC-MAC takes advantage of tree based topology and multichannel technique to assist medium access scheduling. Different parent children sets are assigned to different channels. During light traffic load situation, there will be idle listening of sender in existing RC-MAC protocol, when short beacon interval is used. It reduces energy efficiency of existing RC-MAC. Also, during heavy traffic load situation, packet scheduling is not used in existing RC-MAC. So, a randomization of beacon technique enabled RC-MAC is designed to provide energy efficiency in both short beacon interval and large beacon interval cases. Also, packet scheduling is introduced along with receiver-centric scheduling and hence provides better end to end delay compared to existing approach.
Multispectral Image Classification

we proposed a spectral-spatial information based classification method for classification of diseased trees in high-resolution multispectral satellite imagery. The proposed method consist Guided filter which is used to extract spatial information, with Support Vector Machine. Using the proposed method we are able to map diseased trees from the study area with better classification accuracy compared with existing methods. In this study, the Japanese Wilt in forested areas of Japan was classified into two class as „diseased trees‟ and „all other land cover area‟ according to the 6 attributes in the spectral data set of the forest. The Wilt Data Set which was obtained from UCI machine learning repository database was used for classification.
Effects of Organic Acids Application on Olsen- extractable P and Eggplant (Solanum melongena) Yield

This study investigated two low molecular weight organic acids (LMWOA), oxalic and citric acid, ability to mineralize fixed P in soils and the effects on production of eggplant when compared to conventional triple superphosphate fertilizer (TSP). Two calcareous soils were used: An alkaline (pH 7.6-7.8) Vertisol in the Houston Black soil series and a slightly acidic (pH 6.5-6.8) Mollisol in the Tarpley soil series. The Houston Black soil test indicated no significant difference in extractable P when comparing treatments of oxalic, citric acid or applied triple superphosphate (TSP) fertilizer (P > 0.05). Similarly, eggplant yields indicated no significant difference (P > 0.05) between treatments for this soils series. In the Tarpley series, LMWOA treatments produced significantly less extractable P and eggplant yield (P < 0.05) when compared to applied TSP fertilizer. Original Research Article Osorio and Mix; IJPSS, 10(3): 1-12, 2016; Article no.IJPSS. 24271 2
Directly Compressible Materials via Co-Processing

Direct compression is the preferred method for the preparation of tablets. The present review outlines the importance of the functionality of the directly compressible adjuvants in the formulation of tablets. Tablet manufacturing has been changed by the direct-compression process and high-speed machines. These two developments have increased the demands on the functionality of excipients in terms of flow and compression properties. Particle engineering of individual excipients and excipients combinations using coprocessing, by sub particle modifications, has provided an attractive tool for developing high functionality excipients that are suited to modern tablet manufacturing processes. The co-processing is the most widely explored method for the preparation of directly compressible excipients because it is cost effective. Hence, the present review focuses on the properties of the co-processed directly compressible adjuvants available in the market.