UML-SOA-Sec and Saleem’s MDS Services Composition Framework for Secure Business Process Modelling of Services Oriented Applications

In Service Oriented Architecture (SOA) environment, a software application is a composition of services, which are scattered across enterprises and architectures. Security plays a vital role during the design, development and operation of SOA applications. However, analysis of today’s software development approaches reveals that the engineering of security into the system design is often neglected. Security is incorporated in an ad-hoc manner or integrated during the applications development phase or administration phase or out sourced. SOA security is cross-domain and all of the required information is not available at downstream phases. The post-hoc, low-level integration of security has a negative impact on the resulting SOA applications. General purpose modeling languages like Unified Modeling Language (UML) are used for designing the software system; however, these languages lack the knowledge of the specific domain and “security” is one of the essential domains. A Domain Specific Language (DSL), named the “UML-SOA-Sec” is proposed to facilitate the modeling of security objectives along the business process modeling of SOA applications. Furthermore, Saleem’s MDS (Model Driven Security) services composition framework is proposed for the development of a secure web service composition

Economic Freedom Indicators and Higher Education Reforms: Evaluation and Planning Internationalization Process

This study contributes to the body of knowledge by measuring the effects of economic freedom indicators on higher education reforms in selected SAARC countries over a period of 1995-2012. The results show a strong linkage between economic freedom indicators and higher education,which support the internationalization policies of higher education institutions in the region. The results indicate that “freedom from corruption” increases higher education expenditures and literacy rate in Bangladesh, while trade freedom, financial development, property rights, and government spending have a positive impact on higher education expenditures and per capita GDP in India, Nepal, Pakistan, and Sri Lanka. Property rights increases the higher education enrollment, higher education spending per student, and R&D expenditures in Pakistan, while government spending in Sri Lanka has a positive relationship with the literacy rate and R&D expenditures.  The results of panel fixed effect regression model confirm the importance of economic freedom indicators in higher education reforms in selected SAARC countries. The study concludes that economic freedom indicators enforce the need of higher education reforms, which is prerequisite for internationalization process across the globe. Keywords: Higher Education; Economic freedom indicators; Internationalization of Universities; SAARC countries; Panel Fixed Effect Regression JEL Classifications: C23, I2

Агрессивная форма ювенильной макромастии

ПОДРОСТКИМОЛОЧНЫЕ ЖЕЛЕЗЫ ЧЕЛОВЕКА /АНОМАЛБОЛЕЗНИ РЕДКИЕМАКРОМАСТИЯГИПЕРТРОФИЯМОЛОЧНОЙ ЖЕЛЕЗЫ ПЛАСТИКАХИРУРГИЧЕСКИЕ ОПЕРАЦИИ ВОССТАНОВИТЕЛЬНЫЕМОЛОЧНОЙ ЖЕЛЕЗЫ БОЛЕЗНИ /ТЕР /ХИ

Helium Assisted Sand Casting of Aluminum Alloys

Sand casting is the most widely used casting process for both ferrous and non-ferrous alloys; however, the process is marred by large grain size structures and long solidification times. The coarser microstructure has a negative effect on the mechanical properties of the cast components and the long processing time affects the overall productivity of the process. The research reported herein addresses these problems for aluminum sand castings by enhancing the rate of heat extraction from the casting by replacing air, which is typically present in the pores of the sand mold and has a relatively low thermal conductivity by helium which has a thermal conductivity that is at least five times that of air in the temperature range of interest. The effect of (1) the flow rate of helium, (2) the way in which it is introduced into the mold, and (3) the mold design on (a) the average grain size, (b) the secondary dendrite arm spacing, and (c) the room temperature tensile properties of castings is investigated and compared to their counterparts produced in a typical sand casting process. In addition, a cost analysis of the helium-assisted sand casting process is performed and an optimum set of parameters are identified. It is found that when the helium-assisted sand casting process is performed with close to the optimum parameters it produces castings that exhibit a 22 percent increase in ultimate tensile strength and a 34 percent increase in yield strength with no significant loss of ductility, no degradation in the quality of the as-cast surfaces, and no significant increase in the overall cost

Efficient distributed path computation on RDF knowledge graphs using partial evaluation

International audienceA key property of Linked Data is the representation and publication of data as interconnected labelled graphs where different resources linked to each other form a network of meaningful information. Searching these important relationships between resources – within single or distributed graphs – can be reduced to a pathfinding or navigation problem, i.e., looking for chains of intermediate nodes. SPARQL1.1, the current standard query language for RDF-based Linked Data defines a construct – called Property Paths (PPs) – to navigate between entities within a single graph. Since Linked Data technologies are naturally aimed at decentralised scenarios, there are many cases where centralising this data is not feasible or even not possible for querying purposes. To address these problems, we propose a SPARQL PP-based graph processing approach – dubbed DpcLD – where users can execute SPARQL PP queries and find paths distributed across multiple, connected graphs exposed as SPARQL endpoints. To execute the distributed path queries we implemented an index-free, cache-based query engine that communicates with a shared algorithm running on each remote endpoint, and computes the distributed paths. In this paper, we highlight the way in which this approach exploits and aggregates partial paths, within a distributed environment, to produce complete results. We perform extensive experiments to demonstrate the performance of our approach on two datasets: One representing 10 million triples from the DBPedia SPARQL benchmark, and another full benchmark dataset corresponding to 124 million triples. We also perform a scalability test of our approach using real-world genomics datasets distributed across multiple endpoints. We compare our distributed approach with other distributed and centralized pathfinding approaches, showing that it outperforms other distributed approaches by orders of magnitude, and provides a good trade-off for cases when the data cannot be centralised

Performance Optimization of Electrical Discharge Machining (Die Sinker) for Al-6061 via Taguchi Approach

This paper parametrically optimizes the EDM (Electrical Discharge Machining) process in die sinking mode for material removal rate, surface roughness and edge quality of aluminum alloy Al-6061. The effect of eight parameters namely discharge current, pulse on-time, pulse off-time, auxiliary current, working time, jump time distance, servo speed and work piece hardness are investigated. Taguchi's orthogonal array L18 is employed herein for experimentation. ANOVA (Analysis of Variance) with F-ratio criterion at 95% confidence level is used for identification of significant parameters whereas SNR (Signal to Noise Ratio) is used for determination of optimum levels. Optimization obtained for Al-6061 with parametric combination investigated herein is validated by the confirmation run

SAFE: SPARQL federation over RDF data cubes with access control

Several query federation engines have been proposed for accessing public Linked Open Data sources. However, in many domains, resources are sensitive and access to these resources is tightly controlled by stakeholders; consequently, privacy is a major concern when federating queries over such datasets. In the Healthcare and Life Sciences (HCLS) domain real-world datasets contain sensitive statistical information: strict ownership is granted to individuals working in hospitals, research labs, clinical trial organisers, etc. Therefore, the legal and ethical concerns on (i) preserving the anonymity of patients (or clinical subjects); and (ii) respecting data ownership through access control; are key challenges faced by the data analytics community working within the HCLS domain. Likewise statistical data play a key role in the domain, where the RDF Data Cube Vocabulary has been proposed as a standard format to enable the exchange of such data. However, to the best of our knowledge, no existing approach has looked to optimise federated queries over such statistical data.This publication has emanated from research supported in part by the research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289, EU FP7 project Linked2Safety (contract number 288328), EU FP7 project GeoKnow (contract number 318159), the Millennium Nucleus Center for Semantic Web Research under Grant NC120004, and Fondecyt Grant No. 11140900.peer-reviewe

Helical Milling of CFRP/Ti6Al4V Stacks Using Nano Fluid Based Minimum Quantity Lubrication (NF-MQL): Investigations on Process Performance and Hole Integrity

The structural components in the aeronautical industry require CFRP/Ti6Al4V stacks to be processed together, which results in poor hole integrity due to the thermal properties of the materials and challenges related to processability. These challenges include quality variation of the machined holes because of the limitations in process properties. Therefore, a novel solution through helical milling is investigated in the study using nano fluid based minimum quantity lubrication (NF-MQL). The analysis of variance shows, for Ti6Al4V, eccentricity (PCR = 28.56%), spindle speed (Ti) (PCR = 42.84%), and tangential feed (PCR = 8.61%), and for CFRP, tangential feed (PCR = 40.16%), spindle speed (PCR = 28.75%), and eccentricity (PCR = 8.41%) are the most significant parameters for diametric error. Further on, the rise in the circularity error is observed because of prolonged tool engagement at a higher value of tangential feed. Moreover, the surface roughness of Ti was reduced with an increasing percentage of MoS2 in the lubricant. The spindle speed (37.37%) and lubricant (45.76%) have a potential influence on the processing temperature, as evident in the analysis of variance. Similarly, spindle speed Ti (61.16%), tangential feed (23.37%), and lubrication (11.32%) controlled flank wear, which is critical to tool life. Moreover, the concentration of MoS2 decreased edge wear from ~105 µm (0.5% concentration) to ~70 µm (1% concentration). Thorough analyses on process performance in terms of hole accuracy, surface roughness, processing temperature, and tool wear are carried out based on the physical science of the process for cleaner production. The NF-MQL has significantly improved process performance and hole integrity

Vehicle Remote Health Monitoring and Prognostic Maintenance System

In many industries inclusive of automotive vehicle industry, predictive maintenance has become more important. It is hard to diagnose failure in advance in the vehicle industry because of the limited availability of sensors and some of the designing exertions. However with the great development in automotive industry, it looks feasible today to analyze sensor’s data along with machine learning techniques for failure prediction. In this article, an approach is presented for fault prediction of four main subsystems of vehicle, fuel system, ignition system, exhaust system, and cooling system. Sensor is collected when vehicle is on the move, both in faulty condition (when any failure in specific system has occurred) and in normal condition. The data is transmitted to the server which analyzes the data. Interesting patterns are learned using four classifiers, Decision Tree, Support Vector Machine, K Nearest Neighbor, and Random Forest. These patterns are later used to detect future failures in other vehicles which show the similar behavior. The approach is produced with the end goal of expanding vehicle up-time and was demonstrated on 70 vehicles of Toyota Corolla type. Accuracy comparison of all classifiers is performed on the basis of Receiver Operating Characteristics (ROC) curves