A Majority Vote Based Classifier Ensemble for Web Service Classification

Service oriented architecture is a glue that allows web applications to work in collaboration. It has become a driving force for the service-oriented computing (SOC) paradigm. In heterogeneous environments the SOC paradigm uses web services as the basic building block to support low costs as well as easy and rapid composition of distributed applications. A web service exposes its interfaces using the Web Service Description Language (WSDL). A central repository called universal description, discovery and integration (UDDI) is used by service providers to publish and register their web services. UDDI registries are used by web service consumers to locate the web services they require and metadata associated with them. Manually analyzing WSDL documents is the best approach, but also most expensive. Work has been done on employing various approaches to automate the classification of web services. However, previous research has focused on using a single technique for classification. This research paper focuses on the classification of web services using a majority vote based classifier ensemble technique. The ensemble model overcomes the limitations of conventional techniques by employing the ensemble of three heterogeneous classifiers: Naïve Bayes, decision tree (J48), and Support Vector Machines. We applied tenfold cross-validation to test the efficiency of the model on a publicly available dataset consisting of 3738 real world web services categorized into 5 fields, which yielded an average accuracy of 92 %. The high accuracy is owed to two main factors, i.e., enhanced pre-processing with focused feature selection, and majority based ensemble classification

HCF-CRS: A Hybrid Content based Fuzzy Conformal Recommender System for providing recommendations with confidence

A Recommender System (RS) is an intelligent system that assists users in finding the items of their interest (e.g. books, movies, music) by preventing them to go through huge piles of data available online. In an effort to overcome the data sparsity issue in recommender systems, this research incorporates a content based filtering technique with fuzzy inference system and a conformal prediction approach introducing a new framework called Hybrid Content based Fuzzy Conformal Recommender System (HCF-CRS). The proposed framework is implemented to be used in the domain of movies and it provides quality recommendations to users with a confidence level and an improved accuracy. In our proposed framework, first, a Content Based Filtering (CBF) technique is applied to create a user profile by considering the history of each user. CBF is useful in the situations like: lack of demographic information and the data sparsity problems. Second, a Fuzzy based technique is incorporated to find the similarities and differences between the user profile and the movies in the dataset using a set of fuzzy rules to get a predicted rating for each movie. Third, a Conformal prediction algorithm is implemented to calculate the non-conformity measure between the predicted ratings produced by fuzzy system and the actual ratings from the dataset. A p-value (confidence measure) is computed to give a level of confidence to each recommended item and a bound is set on the confidence level called a significance level ε, according to which the movies only above the specified significance level are recommended to user. By building a confidence centric hybrid conformal recommender system using the content based filtering approach with fuzzy logic and conformal prediction algorithm, the reliability and the accuracy of the system is considerably enhanced. The experiments are evaluated on MovieLens and Movie Tweetings datasets for recommending movies to the users and they are compared with other state-of-the-art recommender systems. Finally, the results confirm that the proposed algorithms perform better than the traditional ones

Association of renal biomarkers in COVID-19 patients: A retrospective study

Background: The new severe acute respiratory syndrome coronavirus 2 is the cause of the transmissible sickness known as coronavirus disease 2019 (COVID-19) (SARS-CoV-2). Although it often presents as an acute respiratory infection, it can also have a negative impact on the kidneys, heart, gastrointestinal, and nervous system. The aims of this study to find out the association of renal biomarkers among dialysis patients in COVID-19 positive and negative. Methods: A retrospective study was conducted in the Department of medical laboratory technology, the university of Haripur, Khyber Pakhtunkhwa, Pakistan. A Total of 129 Dialysis patients blood samples were collected from March 2022 to April 2022 in which 13 males and 20 females are COVID-19 positive while 41 males and 55 females are COVID-19 negative. The obtained data was statistically analyzed by using PRISM version 5.0 by applying two-way ANOVA and Comparisons between Covid positive and negative patients RFTs by using Bonferroni posttest. Results: Male patients with chronic kidney disease (on dialysis) with COVID-19 negative and positive their mean urea difference was 95.20mg/dl and 159.6mg/dl, while COVID-19 negative and positive the mean creatinine difference was 8.534mg/dl and 13.81mg/dl respectively. While there was no significance difference in uric acid concentration in CKD patients with COVID-19 negative and positive. Female patients with chronic kidney disease (on dialysis) with COVID-19 negative and positive their mean urea difference was 103.20mg/dl and 152.6mg/dl, while COVID-19 negative and positive the mean creatinine difference was 8.114mg/dl and 8.584mg/dl respectively. While there was no significance difference in uric acid concentration in CKD patients with COVID-19 negative and positive. Conclusion: This study concludes that there is positive relationship or association of renal biomarkers in COVID-19 positive patients. Significance association between urea and creatinine in COVID-19 positive

Securing Cognitive Radio Networks using blockchains

Due to the increase in industrial applications of Internet of Things (IoT), number of internet connected devices have been increased accordingly. This has resulted in big challenges in terms of accessibility, scalability, connectivity and adaptability. IoT is capable of creating connections between devices on wireless medium but the utilization of scarce spectrum in efficient manner for the establishment of these connections is the biggest concern. To accommodate spectrum allocation problem different radio technologies are being utilized. One of the most efficient technique being used is cognitive radio, which dynamically allocate the unlicensed spectrum for IoT applications. Spectrum sensing being the fundamental component of Cognitive Radio Network (CRN) is threatened by security attacks. Process of spectrum sensing is disturbed by the malicious user (MU) which attacks the primary signal detection and affects the accuracy of sensing outcome. The presence of such MU in system, sending false sensing data can degrade the performance of cognitive radios. Therefore, in this article a blockchain based method is proposed for the MU detection in network. By using this method an MU can easily be discriminated from a reliable user through cryptographic keys. The efficiency of the proposed mechanism is analyzed through proper simulations using MATLAB. Consequently, this mechanism can be deployed for the validation of participating users in the process of spectrum sensing in CRN for IoTs.publishe

Antimicrobial Resistance

Klebsiella pneumoniae (K. pneumoniae) pose an emerging threat to public health sector worldwide. They are one of the potent nosocomial pathogens and cause variety of infections including pneumonia, septicaemia, wound infections, urinary tract infections and catheter-associated infections. From the last two decades, these pathogens are becoming more powerful due to the acquisition of resistomes on different types of plasmids and transposons. There are four main mechanisms of antibacterial resistance such as efflux pump, target alteration, membrane permeability and notably enzymes hydrolysis. K. pneumoniae produce different types of enzymes but most importantly extended spectrum-β-lactamase (ESBL), carbapenemase and metallo-β-lactamase (MBL). K. pneumoniae carbapenemases (KPCs) and New Delhi metallo-β-lactamase (NDM) producing isolates displayed resistance not only against the β-lactam drugs (penicillins, cephalosporins and carbapenems) but also to other classes of antibiotics (aminoglycosides and quinolones). Therapeutic options available to treat serious infections caused by these extensively drug-resistant pathogens are limited to colistin, tigecycline and fosfomycin. Hence, combination therapy has also been recommended to treat such bacteria with clinical side effects, therefore, new treatment regime must be required. Moreover, we are relying on conventional diagnostic tools, however, novel techniques must be required for robust identification of multi-drug-resistant bacteria

Hurdles in Vaccine Development against Respiratory Syncytial Virus

Respiratory syncytial virus (RSV) infection is a major cause of severe respiratory disease in infants and young children worldwide and also forms a serious threat for the elderly. Vaccination could significantly relieve the burden of the RSV disease. However, unfortunately there is no licensed vaccine available so far. This is partly due to disastrous outcome of a clinical trial of formalin-inactivated RSV (FI-RSV) in children in 1960s; leading to enhanced respiratory disease upon natural infection. These findings contributed significantly to the delay of RSV vaccine development. Other key obstacles in development of RSV vaccine such as a peak of severe disease at 2–3 months of age, challenging biochemical behavior of key vaccine antigens and dependence on animal models that may not truly reflect human disease processes. These challenges could be overcome through maternal immunization, structure-based engineering of vaccine antigens, the design of a novel platform for safe infant immunization, and the development of improved animal models. Currently, several vaccine candidates are in pre-clinical and clinical trials targeting the diverse age groups; young children or older adults from the infection or can reduce incidence, mortality and morbidity among the RSV infected individuals

On the Flow of Generalized Burgers' Fluid Induced by Sawtooth Pulses

This paper presents a study for the MHD flow of an incompressible generalized Burgers' fluid through a rectangular duct in porous medium. The flow is generated due to the velocity sawtooth pulses applied on the duct. Exact solutions of the governing equations are obtained by using the Laplace transform and double finite Fourier sine transform in this order. The obtained solutions satisfy all the initial and boundary conditions and are written as a sum of steady and transient solutions. Graphs are plotted for both developing and retarding flows. The effects of magnetic parameter, porosity parameter, and various parameters of interest on the flow characteristics are discussed. The problem reduces to the flow between two plates in the absence of side walls

Extracorporeal Shockwave Lithotripsy versus Ureteroscopy: A First Line Distal Ureteric Stone Treatment

Background: Despite the emergence of many novel minimally invasive techniques including percutaneous nephrolithotomy, ureteroscopy, extracorporeal shock wave lithotripsy, many urologists still prefer open surgery for the management of ureteric stones. The present study compared the efficacy of extracorporeal shockwave lithotripsy (ESWL) with ureteroscopy (URS) for the treatment of distal ureteral calculi. Methods: A single-blinded, randomized controlled trial, which was conducted between January 2018 to June 2019 at the Sindh Institute of Urology and Transplantation, Karachi, Pakistan. All patients diagnosed with unilateral, solitary, and distal ureteral stones were randomized in two groups. The patients in Group A underwent with ESWL and group B underwent ureteroscopy. The outcome of procedures was assessed after 3 months. Data was analyzed via Statistical Package for the Social Sciences (SPSS version 25). Chi-squared test was applied to compare the clinical efficacy of both techniques. A p<0.05 was considered as statistically significant. Results: Out of 106 patients, majority were females n=61(58%). Overall, the mean age of population was 41.9 ± 10.4 years, and the mean stone size was 13.1 ± 4.3 mm. Both the groups were almost comparable with respect to age and size of stones. There was a significant difference in outcome of both the procedures, as the residual stones were more in ESWL and URS i.e., 64.0% vs. 33.9% (p=0.019). Conclusion: In hospitals, both of the techniques are suitable for treatment purpose. However, the present results suggest that URS is a more effective procedure than ESWL (p=0.019) for treating ureteral stones and should be utilized as the first-line treatment for distal ureteral calculi. Keywords: Lithotripsy; Ureteroscopy; Ureteral Calculi

In-vivo Kinetics of Silymarin (Milk Thistle) on Healthy Male Volunteers

Purpose: The study was aimed at evaluating the in vivo kinetics of silymarin tablets, a product with antihepatotoxic and free radical scavenging activities.Methods: Silimarin® (Amson Vaccines & Pharma Pvt Ltd) was used as the test product while another silymarin tablet brand, Silliver® (Abbott Laboratories Pak Ltd) was the reference product. The tablets were administered to healthy male volunteers orally at a dose of 200 mg following an overnight fast according to a randomized cross-over design. Scheduled blood samples were collected, centrifuged and the plasma assayed using a sensitive and validated reversed phase high performance liquid chromatographic (RP-HPLC) method. Various pharmacokinetic parameters were calculated based on the non-compartmental model.Results: Non-significant difference (p < 0.05) was observed in the area under the curve (AUC) of the two brands with values of 10.8 ± 0.4 μg h/ml and 11.2 ± 0.7 μg h/ml, respectively. There was, however, a significant difference (p < 0.05) in the Cmax of the two brands. Other pharmacokinetic parameters evaluated did not show any statistical difference (p < 0.05) between the two products except for meanresidence time Conclusion: The test product can be used as an alternative to the brand, Silliver®-Abbot (reference), only in conditions where maximum plasma concentration (Cmax) is not an important consideration