Reliability Prediction and Web Service Selection Using Soft Computing Techniques for Service-Oriented Systems

Building a wide variety of distributed systems is a complex task these days. Since, service oriented architecture (SOA) is a major framework for distributed systems, it’s reliability is the major concern while developing a related software. The assessment of reliability in service-oriented systems (SOS) mainly depends on the accessibility of web-services, which leans on different parameters i.e. unpredictable internet, communication links and the location of web services. Hence, reliability needs to be predicted for the better functioning of a system. Selection of an optimal web-service is also an important concern in SOS. Since, for an abstract task to perform in SOS, a large number of functionally equivalent web service candidates are available. The same web service candidate can perform differently with different users. So, a technique is required for building the personalized web service ranking framework for designers. Hence, for predicting the reliability of SOS and for selection of an optimal web service candidate from functionally equivalent set of web service candidates a most effective approach is desired. In this work, a novel methodology is proposed for predicting the reliability of Web Service candidate which basically uses the past failure experience of similar service users and a personalized framework for selection of an optimal Web Service candidate from functionally equivalent candidates' set which basically is associated with the past Web-Service usage experience of similar users. In this work, no additional invocation of Web service is required. The experimental results are compared with many other techniques proposed by other authors in literature which shows the effectiveness of proposed approach

Soft fault detection using MIBs in computer networks

To improve network reliability and management in today\u27s high-speed communication system, a statistical anomaly network intrusion detection system (NIDS) has been investigated, for network soft faults using the Management Information Base (Mm) traffic parameters provided by Simple Network Management Protocol (SNMP), for both wired and wireless networks. The work done would be a contribution to a system to be designed MIB Anomaly Intrusion Detection, a hierarchical multi-tier and multiobservation-window Anomaly Intrusion Detection system. The data was derived from many experiments that had been carried out in the test bed that monitored 27 MIB traffic parameters simultaneously, focusing on the soft network faults. The work here has been focused on early detection, i.e., detection at low values of the ratio of fault to background traffic. The performance of this system would be measured using traffic intensity scenarios, as the fault traffic decreased from 10% to 0.5% of the background

An Efficient and Optimal IRIS Recognition System using MATLAB GUI

A biometric system is used for recognition of individual based on their physical or personal characteristics. Biometric system includes face recognition, fingerprint recognition, voice recognition , the Iris recognition etc. various study has shown that iris recognition is the most efficient biometrics. hence the work presented here involved designing a user friendly GUI based efficient and optimal iris recognition system using MATLAB® GUI. So that one with least knowledge of technology can use it. in order to generate the base templates of iris, we have used Masek and Kovesi’s algorithm with some necessary changes. We have used the Image processing toolbox and GUIDE toolbox of MATLAB, to make the GUI for iris recognition system. There are so many methods to design an Iris recognition system having their own pros and cons. Some methods are calculation intensive but they lead in performance while other are less calculation intensive but they lack in performance. To design the iris recognition system we have focused on both the sides i.e. calculation intensity and performance, to make the system efficient and optimal. In order to use this GUI based iris recognition system first, one need to just select an input eye image that one want to recognize from the iris image database and then just click on recognize button in GUI. now you are done. After the recognition process is complete it shows all the results related to that particular recognition process. like the name or number of the recognized person, segmented eye image, noise template etc and MATLAB’s output window shows the hamming distance related to the matching process of the recognition system. We have used the IIT Delhi’s iris image dataset for the verification and testing of our GUI based iris recognition system. DOI: 10.17762/ijritcc2321-8169.150512

Evaluation of Module Based Medical Ethics Training Among Medical Students of a Tertiary Care Teaching Hospital in National Capital Region, India.

Introduction: The medical education world-wide is adapting competency based learning; it is high-time that the medical syllabus is inculcated with integrated-medical ethics training. An educational training program with a pre- and post-test method of analysis has better student outcome with respect to retention, thinking and understanding. Objective: To assess the understanding and application of medical ethics in students after structured module based training.Methods: One hundred and fifty students of 1st professional Bachelor of Medicine and Bachelor of Surgery (MBBS) were provided a 10 hours’ duration module based teaching of basic principles and core concepts of medical ethics in patient care. The assessment was conducted using a pre and post analysis questionnaire having 15 multiple choice questions with one correct response. Data were analysed using paired student’s t-test for comparing pre- and post-test scores. P < 0.05 was considered as significantResults: Total post-test correct responses were highly significant than pre-test responses. Gender wise, both males and females- post-test response significantly improved (p<0.001), indicating that there is improvement in understanding the principles and key concepts of medical ethics provided during the training. Upon completion of the training, most students strongly agreed that the training has inspired them towards the moral code of conduct, attitude and behavioural change and it provided necessary information on medical ethics.Conclusion: Our study demonstrates that the structured medical ethics training module yielded a significant enhancement of not only the knowledge and understanding level of the students but also in their perception, attitude and behavioural interest about the importance of ethical medical practice in the future patient care

Load Flow Analysis with UPFC under Unsymmetrical Fault Condition

This paper addresses the comparative load flow analysis with and without Unified Power Flow Controller (UPFC) for six buses, three phase transmission line under unsymmetrical faults (L-G, L-L and L-L-G) in simulation model. Unified Power Flow Controller (UPFC) is a typical Flexible AC Transmission System (FACTS) device playing a vital role as a stability aid for large transient disturbances in an interconnected power system. The main objective of this paper is to improve transient stability of the six bus system. Here active and reactive power on load bus of the system considered has been determined under different fault conditions. UPFC has been connected to the system and its effects on power flow and voltage profile of test system has been determined with various line data and bus data for six buses, three lines power system and simulation model by using simulation toolbox has been developed. In this work a versatile model is presented for UPFC inherent order to improve the transient stability and damp oscillation. Index Terms – Unified Power Flow Controller (UPFC), Control, simulation, transients, line to ground fault (L-G), double line to ground fault (L-L-G), double line fault (L-L

Effect of enrichment material on the shelf life and field efficiency of bioformulation of Rhizobium sp. and P-solubilizing Pseudomonas fluorescens

ABSTRACT In the present investigation seven carriers -talc, saw dust, fuller&apos;s earth, rice husk, sugarcane bagasse, charcoal and wheat bran were evaluated for the production of bioformulation. The bacteria used for bioformulation development were root nodulating Rhizobium sp. RASH6 Chl+Kan+ and phosphate solubilizing Pseudomonas fluorescens PB6 Amp+Str+ . Both bacterial strains were inoculated in all the carriers separately and in combination with each other (coinoculants). The bacterial population was determined in each carrier up to six month storage. Sawdust proved to be the best carrier in both water holding capacity (350 %) and also in maintaining the bacterial population for both individual and co-inoculation. Saw dust based formulation was separately amended with CMC, sucrose, molasses and gum. Enrichment of saw dust with molasses brought maximum increment in population both in mono and coinoculants. Finally the impact of six month-stored enrichment inoculants on plant productivity was determined taking chickpea as a test crop. The co-inoculants proved much better in enhancing the seedling biomass and the nodule number. Molasses enriched saw dust based formulation showed 48.43 %, 52.02 % and 57.41 % enhancement in dry weight with RASH6, PB6 and their co-inoculant respectively after 60 days of sowing. Results showed that enrichment of carrier is expected to permit the retention of cell viability thus increasing the effectiveness of the active material

Werner Syndrome Protein Expression in Breast Cancer

IntroductionWerner protein (WRN) plays an important role in DNA repair, replication, transcription, and consequently genomic stability via its DNA-helicase and exonuclease activity. Loss of function of WRN is associated with Werner syndrome (WS), which is characterized by premature aging and cancer predisposition. Malignancies that are commonly linked to WS are thyroid carcinoma, melanoma, breast cancer, meningioma, and soft tissue and bone sarcomas. Currently, the clinicopathologic significance of WRN in breast cancer is largely unknown.Patients and MethodsWe investigated the clinicopathologic and prognostic significance of WRN protein expression in a cohort of clinically annotated series of sporadic (n = 1650) and BRCA-mutated (n = 75) invasive breast cancers. We correlated WRN protein expression to clinicopathologic characteristics, DNA repair protein expression, and survival outcomes.ResultsThere is strong evidence of association between low nuclear and cytoplasmic WRN co-expression and low levels of KU70/KU80, DNA-PK, DNA Pol-B, CKD18, cytoplasmic RECQL4, and nuclear BLM protein expression (adjusted P-values < .05). Tumors with low nuclear or cytoplasmic WRN expression have worse overall breast cancer-specific survival (BCSS) (adjusted P-values < .05). In topoisomerase I overexpressed tumors, low WRN nuclear expression was associated with poor BCSS (P-value < .05). In BRCA-mutated tumors, low WRN cytoplasmic expression conferred shortest BCSS (P < .05).ConclusionsLow WRN protein expression is associated with poor BCSS in patients with breast cancer. This can be used to optimize the risk stratification for personalized treatment

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations