Fault Tolerance Framework for Composite Web Services

A composite Web service combines multiple, logically interrelated services for creating more common services meeting complex requirements from users. The services participating in a composition coordinate the actions of distributed activity using Web services protocols to reach consistent agreement on the outcome of joint operation. However, as services run over unreliable protocols, there is a great chance that services fail due to the failure of protocols. However, current protocol standards provide fault-tolerance but are limited to backward recovery using expensive compensation and roll-back strategies. This paper gives an extension of the existing Web services business activity (WS-BA) protocol to deal with failures using forward recovery approach. A set of common failure types affecting the execution of component services is identified, and recovery solutions for each identified failure are also presented. The fault-handling extension of the WS-BA protocol implements recovery solutions for each of the identified failures to handle failures at runtime. Another important aspect about which the WS-BA protocol specification is unclear is reaching and notifying consistent outcome on the completion of joint work. This study extends the WS-BA protocol to notify consistent outcome reached by all participating services. The implementation and testing of the framework are performed using the model-checking and verification tool UPPAAL. A well-known application example supports the study. The key properties of the framework, like the execution of corresponding recovery actions in cases of failures and reaching a consistent agreement on the outcome of joint operation, are verified

Performance Evaluation of Java Based Object Relational Mapping Tools

Object persistency is the hot issue in the form of ORM (Object Relational Mapping) tools in industry as developers use these tools during software development. This paper presents the performance evaluation of Java based ORM tools. For this purpose, Hibernate, Ebean and TopLinkhave been selected as the ORM tools which are popular and open source. Their performance has been measured from execution point of view. The results show that ORM tools are the good option for the developers considering the system throughput in shorter setbacks and they can be used efficiently and effectively for performing mapping of the objects into the relational dominated world of database, thus creating a hope for a better and well dominated future of this technology

Increase Suicidal Mortality Rate Among Females in District Peshawar

OBJECTIVE: To study increased suicidal mortality rate among females in district Peshawar. METHODOLOGY: The bodies of women in the reproductive age who died because of fatal deliberate self-harming were examined at Forensic Medicine Department Khyber Medical College, Peshawar from January 2015 to September 2015. RESULTS: Forty-four bodies of females were autopsied. 13 (30%) were adolescents between the age of 10-18 years. 31 (70.4%) were aged between 19-48 years. 33 of the victims committed suicide due to health-related issues. 28 (64%) victims used poisons. In almost all cases (n=38) the incident happened when the victim was alone in house or left unattended. 30 (68%) victims were brought to hospitals for treatment. 13 were found to have recurrent attempt of self-harming. CONCLUSION: Females have increased tendency to commit suicide than males especially in their reproductive age. Low socioeconomic status, cultural norms, unwanted pregnancies and ill health are the major causes

Handwritten Sindhi Character Recognition Using Neural Networks

OCR (OpticalCharacter Recognition) is a technology in which text image is used to understand and write text by machines. The work on languages containing isolated characters such as German, English, French and others is at its peak. The OCR and ICR (Intelligent Character Recognition) research in Sindhi script is currently at in starting stages and not sufficient work have been cited in this area even though Sindhi language is rich in culture and history. This paper presents one of the initial steps in recognizing Sindhi handwritten characters. The isolated characters of Sindhi script written by thesubjects have been recognized. The various subjects were asked to write Sindhi characters in unconstrained form and then the written samples were collected and scanned through a flatbed scanner. The scanned documents were preprocessedwith the help of binary conversion, removing noise by pepper noise and the lines were segmented with the help of horizontal profile technique. The segmented lines were used to extract characters from scanned pages.This character segmentation was done by vertical projection. The extracted characters have been used to extract features so that the characters can be classified easily. Zoning was used for the feature extraction technique. For the classification, neural network has been used. The recognized characters converted into editable text with an average accuracy of 85%