Miracle-dz/UniFAR-FTUs huggingface dataset:
A Relationship Between Allergic Rhinitis and ABO Blood Group and Related it with Genetics in Population Based Cohort Study in Kut

*Correspondence to: Oras N. Hamad Assist lecturer in University of Wasit/Collage of Medicine, Iraq. ABSTRACT Objectives: To find out prevalence of ABO blood groups and to investigate their association with allergic rhinitis and relate it with Genetics. Materials and Methods: This cross sectional study was done at Kut city in Iraq from January 2015 to December 2015. 109 Participants including both sexes (18-60 years of age) were enrolled for the study during Hematology module. ABO blood group of study population was done by antisera method. A detailed history of study population regarding age, sex, family history and others was recorded on a preformed proforma. Results: In our study population, O blood group came out to be the most common (46.8%). History of allergic rhinitis was reported by 55.9% of our study population. Allergic rhinitis were found high among individuals with Rh+ blood group (94.5%) but the ratio was close in female and male in (55% , 53%) respectively. A significant association between allergic rhinitis (AR) and incident rheumatic arthritis (RA) was found in this population-based cohort study. RA can occur in > 31.2% of patients with AR. Blood group B was found to be at lowest risk level for allergic rhinitis (11.01%). The study showed association between blood groups and allergies rhinitis as 0.072 statistically significant p value. Conclusion: In the study population blood group O being the most common is at high risk level for developing allergic rhinitis while blood group B being the most protected one. This statistically significant association of various blood groups with allergic rhinitis development could help in identifying people at risk as an aid to preventive measures.
A Review on Enhanced Machine Learning Approach for Detection of Malicious Urls and Spam in Social Network

— Nowadays online social network such as Twitter, Face Book plays a vital role in daily life. Twitter can suffer from malicious tweets. The tweets contain suspicious URLs for phishing, spam and malware distribution. Conventional Twitter spam detection techniques have used features of account such as the ratio of tweets comprising URLs and relation features or the account creation date in the Twitter graph. However, the account features can easily fabricated by malicious users. Furthermore extraction of relation features from the Twitter graph is time as well as resource consuming. Conventional techniques for the detection of suspicious URL have categorised URLs using different features comprising lexical features of URLs, HTML content, dynamic behaviour and URL redirection. The aim of this paper related to detect the suspicious URLs by using the system, known as WARNINGBIRD. In this paper, we have concentrated on support vector machines (SVMs), the supervised learning models with associated learning algorithms which are used to analyze data used for classification and regression analysis. As WARNINGBIRD does not depend on the features of malicious landing pages that may not be reachable, it is robust while protecting against condition redirection. Specifically the WARNINGBIRD focuses on the correlations of multiple redirect chains which share the same redirection servers.
A Review On Leveraging Big Data Analytics In Health Care Sector For Enhanced Diagnosis And Competent Patient Health Care Monitoring System

: Health care needs well-organized system, techniques and tools to exploit the full benefits of personal healthcare system and healthcare-related data. The sources of health care data are generated by record keeping, patients care and medical diagnosis etc., there is vital requirement of applying Big Data Analytics (BDA) to enormous amount of health care data for enhanced treatment, disease prediction and surveillance. The key objective of this review paper is to provide deep study on the field of Big Data in healthcare sector. BDA is to analyze the immense quantity of dataset. In this paper, we propose the conceptual architecture of BDA in healthcare sector and highlight the applications of BDA, its potential challenges and future directions in healthcare domain.
Enhancing Stability & Cost Reduction Of Multigrid System By UPFC

In some decades, the demand for electrical power has increased but the generation and transmission remained limited due to limited resources and environmental restrictions. The increased demand for electrical power has also increased the complexity in the transmission system. It resulted in the form of the question of stability of power system. Here the stability of power system with possible minimum cost is the main aspect of the present analysis. This problem is solved by using the Solid State devices, known as Flexible AC transmission systems (FACTS) devices. The UPFC is one of the most promising devices of FACTS devices for power system stability with reduction in cost of power. This paper has a comprehensive review on the research and developments in the matter of enhancing power system stability with cost reduction in multigrid network of power supply with the use of UPFC.
Use of Palm Oil Mill Effluent as Fermentative Medium by Lipase Producing Bacteria

This work was carried out to evaluate palm oil mill effluent (POME) as a fermentative medium for lipase production at laboratory scale using two bacterial isolates (Bacillus cereus and Pseudomonas aeruginosa). The physicochemical analysis of raw POME showed high organic load of COD (78750 mg/l), BOD (15050 mg/l), oil and grease (7645 mg/l), TS (4125 mg/l) and TSS (1650 mg/l). The extracellular lipase producing bacteria Bacillus cereus, Proteus vulgarius, Pseudomonas aeruginosa and Staphylococcus aureus were isolated from palm oil mill industrial effluents. Optimization of physical and chemical factors was done to improve lipase production using the respective bacterial isolates. Percentage biomass improvement, Oil and grease (O&G) reduction and lipase activities were measured with varying pH (4-10), incubation temperature (20-55°C), incubation time (144hrs.), carbon source concentration, nitrogen source concentration, and various metal ions. Enhanced lipase activity for both isolates was observed at 35°C, pH 6&7 for Bacillus cereus and Pseudomonas aeruginosa respectively, after 144hrs of incubation. Corn meal best supported the activities of Bacillus cereus and Pseudomonas aeruginosa at respective concentrations of 3.5wt/v and 2.5wt/v. Soy meal at concentration 2.5wt /v supported the lipase activities of both isolates while Ca showed good lipase activity among the metal ions with both isolates. The present study showed increased lipase activities of both bacterial isolates and demonstrated POME as very good source of fermentation medium for production of extracellular lipases.
Implementing Captcha as Graphical Passwords Based on Hard AI Problems

We present captcha as graphical passwords inmany security primitives square measure supported laborious mathematical issues. Exploitation laborious AI issues for security is rising as AN exciting new paradigm, however has been beneath explored. During this paper, we have a tendency to gift a brand new security primitive supported laborious AI issues, namely, a unique family of graphical watchword systems designed on high of Captcha technology, that we have a tendency to decision Captcha as graphical passwords (CaRP). CaRP is each a Captcha and a graphical watchword theme. CaRP addresses variety of security issues altogether, like on-line guess attacks, relay attacks, and, if combined with dual-view technologies, shoulder-surfing attacks. Notably, a CaRP watchword is found solely probabilistic ally by automatic on-line guess attacks although the watchword is within the search set. CaRP additionally offers a unique approach to deal with the well-known image hotspot drawback in standard graphical watchword systems, like Pass Points, that usually ends up in weak watchword decisions.CaRP isn't a nostrum, however it offers cheap security and usefulness and seems to suit well with some sensible applications for rising on-line security.
Ant Colony Based Optimistic Route Discovery and Packet Distribution Approach

- Energy consumption, time requirement and speed management are the most important problem in wireless sensor networks. So considering the non-uniform network, new method called power control optimization based on the PACA (parallel ant colony algorithm) is presented for the energy consumption optimization. The new mechanism can search the multiple paths and optimize the route of data transmission to homogenize the energy consumption of the nodes. In the simulation, three different network nodes distribution are adopted and the new mechanism is compared with the fixed power routing method. The results show that the new mechanism can homogenize the nodes’ energy consumption, required less time to route discovery and relatively high speed and extend the whole network’s life effectively.
ASSESSMENT OF QUALITY OF IMAGES BASED ON GLCM HOMOGENEITY BY EXTRACTING FEATURES

— Now days images are used in many other fields. Image processing is a method to convert an image into digital form and perform some operations on it and extract some useful information from image. Quality of an image plays fundamental role to take important decision and therefore, its assessment is essential prior to application. The objective approaches of image quality assessment play an important role for the development of compression standards and various multimedia applications. The Gray Level Co-occurrence Matrix method represents a highly efficient technique of extracting second order statistical texture features and to extract the textural features of an image. GLCM method is proposed to extract the textural features of an image. SSIM combines the image gray intensity with textural features to measure the image structural information . These methods are used to predict the visual quality by comparing a distorted image against a reference image. In this paper we are study the homogeneity approach of image quality assessment.
RANDOMIZED SWAPNILs PACKET MARKING AND TRACEBACKING (RSPMT) TECHNIQUE FOR EFFICIENT IP TRACEBACK

The an efficient packet marking technique called swapnil’s packet marking and tracebacking (SPMT) technique that requires the amount of packets equal to the hop distance between the attack initiator and the server (destination) [1], which is less than 31 hops [3] [4], and can undergo certain kind of attacks like constant ID field value, and absence of router in the network chosen for marking. In this paper, we present a randomized version of SPMT called as Randomized Swapnil’s packet marking and tracebacking (RSPMT) technique to avoid such attacks. Even though RSPMT may take more packets for effective traceback, it is more resilient to the kind of attacks that are possible on SPMT.
A Survey on Vehicle Health Monitoring and Prediction System

Vehicle health monitoring utilizes the sensor data on the vehicle, mine the data and predicts the health of the car. It provides an idea on when the vehicle would need maintenance. The model also can warn when driver dozes off or in case of drunken driving. The purpose of this research paper is to provide an overview of the existing Vehicle Health Monitoring System. It discusses the different ways in which Vehicle Health can be monitored. Vehicle health monitoring can be distributed or on-board data mining. Computation or mining in vehicle are restricted by less memory and processor capacity, still an onboard mining is more advantageous than fully distributed datamining system. This paper survey the existing model for computationally efficient Onboard Vehicle Health monitoring system.
Redundancy detection protocol for area coverage control in heterogeneous wireless sensor networks

In a wireless sensor network, eliminating redundancies in area coverage in the deployment zone represents a major challenge where the stake is its lifetime increase. Current works dealing with this topic use different deterministic or probabilistic techniques for nodes redundancies check. In this paper, we propose a quasi-quadratic time distributed algorithm based on a deterministic approach enabling each node to know its exact status even in the context of heterogeneous sensing ranges. Simulations show that this novel technique is more accurate and precise in comparison with other traditional ones.
PWM Soft Switched DC–DC Converter with Coupled Inductor

In this paper, pulse width modulation soft switched DC-DC converter without high voltage & current stress is described. This converter does not require any extra switch to achieve soft switching, which considerably simplifies the control circuit. In this proposed converter, the switch is turned on under zero-current and is turned-off at almost zero-voltage condition. In this converter , it is desirable to control the output voltage by pulse width modulation because of its simplicity and constant frequency. The circuit is simulated using PSPICE and the output voltage is obtained as 100V for 50V input.
Hybrid Filter Bank with Digital Synthesis Filter

Hybrid Filter bank (HFB) is a combination of analysis filter and digital filter. The objective of the work is to minimize the error of the reconstructed image (B/W, colour) received from different paths using hybrid filter bank system. The original image is given as input to the HFB system. There are two different paths in the system in order to get the reconstructed image at the receiver with less error. The two different paths are low and high resolution path. In the high resolution path, the image is transmitted without delay to the receiver. In the low resolution path, the image is transmitted with different fractional delays. Firstly the response of analysis filter and digital synthesis filter of HFB are analyzed with different delays. The image given to the HFB system with high and low resolution path is analyzed. The output is obtained from high resolution path and low resolution path for the given original image. The difference between these two outputs provides the error for the reconstructed image. The original images 128x128, 256x256 are given as input to the system. The error is measured in terms of PSNR values. The original images are analyzed for two different analysis filter (Chebyshev and Butterworth) and digital synthesis filter (FIR and IIR). Also the different parameters such as Average difference (AD), Structural Content (SC), Mean Square Error (MSE), Normalized Cross Correlation (NCC), Normalized Absolute Error (NAE) are analyzed.
A New Fragile Approach for Optimization in Invisible Image Watermarking by Using Symmetric Key Algorithms

- In the information technology and communication, the most important factor has been the security of information and one of the methods is watermarking. The Watermarking aims to validate the host and the undeniable identity of the legal owner. In this paper, we will concentrate on hidden watermarks. At one time, it deals with two different images in BMP to hide information. The message will be dividing evenly in both images to maximize the security of image watermarking. It utilizes the LSB manipulation method and the images addresses used as key are also encrypted for performance improvement with existing Symmetric key algorithms. There are two options to choose either DES or AES algorithm to get optimized output. We are using spatial domain for hiding actual information inside images. This paper gives a brief idea about the new image watermarking approach that make use of LSB algorithm for embedding the data into the bit map images (.bmp) which is implemented through the Microsoft . NET framework.
A Tree Similarity Algorithm for Semantic Search in Information Retrieval

: rdered, labeled trees are trees in which each node has a label and the left-to-right order of its children (if it has any) is fixed. Although similarity search on textual data has been extensively studied, searching for similar trees is still an open problem due to the high complexity of computing the similarity between trees, especially for large numbers of tress Tree-structured data are becoming ubiquitous nowadays and manipulating them based on similarity is essential for many applications. A weighted tree similarity algorithm has been developed earlier which combines matching and missing values between two taxonomy trees. It is shown in this paper that this algorithm has some limitations when the same sub-tree appears at different positions in a pair of trees. In this paper, we introduce a generalized formula to combine matching and missing values. Subsequently, two generalized weighted tree similarity algorithms are proposed.
The NLRP3 Inflammasome as a promising target for Coronary Artery Disease: Current and Pipeline NLRP3 Inhibitors

Coronary Artery Disease (CAD) represents a major health burden worldwide. It is driven by chronic inflammation of the arterial vasculature supplying the heart, in response to pro-inflammatory assaults such as high LDL cholesterol. The resultant atherosclerosis can cause occlusive disease and acute cardiovascular events. The pro-inflammatory cytokine, IL-1β is a central component of this inflammatory response and signalling is activated and amplified by the NLRP3 inflammasome. Rational therapeutic targeting of these mediators could modify atherosclerotic disease progression; myocardial remodelling and CAD patient outcomes. Here we discuss promising current and pipeline inhibitors of the NLRP3 inflammasome family. first priming step is initiated by lipid and lipoprotein endogenous danger signals and pathogen associated molecules free fatty acids; ox-LDL: oxidised low density lipoprotein; cholesterol LPS: lipopolysaccharide) and cytokines (IL-1β and TNFα) that signal through MyD88 to activate NF-ƘB mediated upregulation of NLRP3 and IL1B mRNA. The second signal is provided by diverse intracellular and extracellular molecules (ROS: reactive oxygen species released from mitochondria; lysosomally degraded ox-LDL and cholesterol crystals) and extracellular ATP binding to the K+ channel P2X7R. This initiates NLRP3 inflammasome component (NLRP3; ASC; Pro-caspase-1) assembly and activation of caspase-1 to cleave the pro-peptides and release IL-1β and IL-18. These mediators then prime other immune cells. Intracellular molecules are also released by pyroptopsis.
Therapeutic Effects of Powder and Alcoholic Aqueous Extract of Vitellaria paradoxa on Diabetic Rats

The objective of this work study the therapeutic effect of powder and alcoholic aqueous extract of Vitellaria paradoxa in blood glucose and lipid profile of diabetic rats. In the experiment thirty rats were divided into six groups (n=5). Streptozotocine was intraperitoneally given at dose 65 mg|kg body weight, animals showing fasting blood glucose higher than 300mg/dl were selected and used as diabetic rats. Vitellaria Paradoxa powder and alcoholic aqueous extracts were administered at dose levels (10,20g/kg/diet powder), (100,200 mg/kg body weight orally extract). Hypoglycemic and hypolipidemic effects of the Vitellaria Paradoxa were evaluated by the determination of blood glucose, plasma insulin, total cholesterol, triglyceride, LDL-cholesterol, ALT, AST, creatinine, uric acid and bilirubin. Also, evaluated some blood antioxidant parameters by the determination of MDA, SOD and GSH. The results showed high exhibited levels of insulin in Vitellaria Paradoxa powder and extract comparing with diabetic control. The results showed that the diabetic rats receiving Vitellaria Paradoxa powder and alcoholic aqueous extract had significantly lower levels of serum total cholesterol, triglyceride and LDL-cholesterol levels than those of diabetic control group. All treated groups showed significant increase in superoxide dismutase compared with diabetic control group. [Ali Monahi Nazal Al Shammari. Therapeutic Effects of Powder and Alcoholic Aqueous Extract of Vitellaria paradoxa on Diabetic Rats. J Am Sci 2019;15(2):43-51]. ISSN 1545-1003 (print); ISSN 2375-7264 (online). http://www.jofamericanscience. org. 6. doi:10.7537/marsjas150219.06.
Performance Analysis of Certain Classifiers for Liver CT Images

: Liver is the largest internal organ and is vital for the human body’s survival. It is prone to many diseases such as Liver tumor, Fibrosis, etc. In order to know the condition of the liver, the most commonly preferred method is biopsy. But since it is a very complex and complicated procedure it is being replaced by computer-aided diagnosis (CAD) where the liver is classified into various types like normal, abnormal etc. In this study, we have compared the performance of the CAD systems namely six classifiers for CT image classification. The data of 26 patients was taken into consideration and their status was confirmed by a radiologist. The images were separated into normal and abnormal based on textural features and based on these features the performance of each classifier has been evaluated for the parameters such as accuracy, specificity and sensitivity. Amongst all the classifiers we found out that the best results were obtained for k-NN with accuracy of 88.5%.
The Study of Correlation between type of Au- ditors’ Report & the Quality of Accrued Inter- est in Companies Listed in Tehran Stock Ex- change

Strong capital market is the ichle of economic development and growth. The accounting earnings and its components are among the most important information which is considered by individuals when taking decision. In fact, accounting earnings which is measured and reported based on the accruals, provides more accurate evaluation from the operation of a business unit and its financial situation. Managers start out manipulating earnings in different ways, one of which is the manipulation of accruals which causes the reduction in the quality of reported earnings. Since the earnings quality is one of the important items for the users of financial reports, specially investors, to take proper decisions, and reliance on these information is relevant only to the type of auditors’ comment, therefore, in this study, in order to find out the quality of earnings based on the type of auditors’ comment, we study the type of relation between auditors’ comment and earnings quality which is measured through abnormal accruals. The research has been conducted in Tehran Stock Exchange in the time interval of the years 2004 to 2008. In terms of reasoning, the research is inductive-deductive and as to data collection, it is a descriptive-correlation research and is based on real information in the companies’ financial statement. Also, in terms of purpose, the research is a developmental research. In this study, the members of statistical population are 125 companies in each year. The results obtained from the study shows that there is a significant relation between accruals and qualified opinion with explanatory clause regarding continued operation.