Sensors in your clothes: Design and development of a prototype

Wearable computing is fast advancing as a preferred approach for integrating software solutions not only in our environment, but also in our everyday garments to exploit the numerous information sources we constantly interact with. This paper explores this context further by showing the possible use of wearable sensor technology for information critical information systems, through the design and development of a proof-of-concept prototyp

Context-oriented and transaction-based service provisioning

This paper presents our approach for service provisioning in pervasive computing environments. The presented approach is based on the usage of context-aware features and transactions during the discovery and the deployment of composite services. Context ensures that the best service offers are selected to participate in a service composition. Transactions help in improving the reliability and efficiency of the composite services

Trends and directions in cloud service selection

With the growing popularity of cloud computing the number of cloud service providers and services have significantly increased. Thus selecting the best cloud services becomes a challenging task for prospective cloud users. The process of selecting cloud services involves various factors such as characteristics and models of cloud services, user requirements and knowledge, and service level agreement (SLA), to name a few. This paper investigates into the cloud service selection tools, techniques and models by taking into account the distinguishing characteristics of cloud services. It also reviews and analyses academic research as well as commercial tools in order to identify their strengths and weaknesses in the cloud services selection process. It proposes a framework in order to improve the cloud service selection by taking into account services capabilities, quality attributes, level of user's knowledge and service level agreements. The paper also envisions various directions for future research

A cloud-based energy efficient hosting model for malware detection framework

Protection strategy against malware attacks, whether in enterprise networks or on personal computers is generally divided into two main aspects; the detection rate and the resource consumption. Having a better detection rate is not the solution unless it is complimented by energy efficiency with respect to its CPU resource consumption of the host machine. This paper presents a cloud-based energy efficient hosting model for an intelligent malware detection framework, which amalgamates different components of Amazon's cloud services to develop a unique and dynamically scalable hosting model. The hosting model is then evaluated separately for its CPU utilization and in comparison with the conventional security software. The experimental results demonstrate significant energy efficiency in terms of CPU utilization by the hosting model

Priority scheduling service for E-commerce web servers

Service scheduling is one of the crucial issues in E-commerce environment. E-commerce web servers often get overloaded as they have to deal with a large number of customers’ requests—for example, browse, search, and pay, in order to make purchases or to get product information from E-commerce web sites. In this paper, we propose a new approach in order to effectively handle high traffic load and to improve web server’s performance. Our solution is to exploit networking techniques and to classify customers’ requests into different classes such that some requests are prioritised over others. We contend that such classification is financially beneficial to E-commerce services as in these services some requests are more valuable than others. For instance, the processing of “browse” request should get less priority than “payment” request as the latter is considered to be more valuable to the service provider. Our approach analyses the arrival process of distinct requests and employs a priority scheduling service at the network nodes that gives preferential treatment to high priority requests. The proposed approach is tested through various experiments which show significant decrease in the response time of high priority requests. This also reduces the probability of dropping high priority requests by a web server and thus enabling service providers to generate more revenue

Automating the Semantic Mapping between Regulatory Guidelines and Organizational Processes

The mapping of regulatory guidelines with organizational processes is an important aspect of a regulatory compliance management system. Automating this mapping process can greatly improve the overall compliance process. Currently, there is research on mapping between different entities such as ontology mapping, sentence similarity, semantic similarity and regulation-requirement mapping. However, there has not been adequate research on the automation of the mapping process between regulatory guidelines and organizational processes. In this paper, we explain how Natural Language Processing and Semantic Web technologies can be applied in this area. In particular, we explain how we can take advantage of the structures of regulation-ontology and the process-ontology in order to compute the similarity between a regulatory guideline and a process. Our methodology is validated using a case study in the Pharmaceutical industry, which has shown promising results

Antibacterial efficacy of indigenous Pakistani honey against extensively drug-resistant clinical isolates of Salmonella enterica serovar Typhi: an alternative option to combat antimicrobial resistance

Abstract Background Extensively drug-resistant (XDR) Salmonella enterica serovar Typhi (S. Typhi) poses a grave threat to public health due to increased mortality and morbidity caused by typhoid fever. Honey is a promising antibacterial agent, and we aimed to determine the antibacterial activity of honey against XDR S. Typhi. Methods We isolated 20 clinical isolates of XDR S. Typhi from pediatric septicemic patients and determined the minimum inhibitory concentrations (MICs) of diferent antibiotics against the pathogens using the VITEK 2 Compact system. Antimicrobial-resistant genes carried by the isolates were identifed using PCR. The antibacterial efcacy of fve Pakistani honeys was examined using agar well difusion assay, and their MICs and minimum bactericidal concentrations (MBCs) were determined with the broth microdilution method. Results All 20 isolates were confrmed as S. Typhi. The antibiogram phenotype was confrmed as XDR S. Typhi with resistance to ampicillin (≥32 µg/mL), ciprofoxacin (≥4 µg/mL), and ceftriaxone (≥4 µg/mL) and sensitivity to azithromycin (≤16 µg/mL) and carbapenems (≤1 µg/mL). Molecular conformation revealed the presence of blaTM-1, Sul1, qnrS, gyrA, gyrB, and blaCTX-M-15 genes in all isolates. Among the fve honeys, beri honey had the highest zone of inhibition of 7–15 mm and neem honey had a zone of inhibition of 7–12 mm. The MIC and MBC of beri honey against 3/20 (15%) XDR S. Typhi isolates were 3.125 and 6.25%, respectively, while the MIC and MBC of neem were 3.125 and 6.25%, respectively, against 3/20 (15%) isolates and 6.25 and 12.5%, respectively, against 7/20 (35%) isolates. Conclusion Indigenous honeys have an efective role in combating XDR S. Typhi. They are potential candidates for clinical trials as alternative therapeutic options against XDR S. Typhi isolates. Keywords Antimicrobial resistance, Natural antibiotics, XDR S. Typhi, MIC, Honey, Resistance gene

A fuzzy outranking approach in risk analysis of web service security

Risk analysis is considered as an important process to identify the known and potential vulnerabilities and threats in the web services security. It is quite difficult for users to collect adequate events to estimate the full vulnerabilities and probability of threats in the Web, due to the rapid change of the malicious attacks and the new computer’s vulnerabilities. In this paper, a fuzzy risk assessment model is developed in order to evaluate the risk of web services in a situation where complete information is not available. The proposed model extends Pseudo-Order Preference Model (POPM) to estimate the imprecise risk based on richness of information and to determine their ranking using a weighted additive rule. A case study of a number of web services is presented in order to test the proposed approach

MILK PRODUCTION POTENTIAL OF PURE BRED HOLSTEIN FRIESIAN AND JERSEY COWS IN SUBTROPICAL ENVIRONMENT OF PAKISTAN

The data on 575 records of 270 Holstein Friesian and 818 records of 326 Jersey cows maintained in Punjab, Pakistan were analyzed. The cows were grouped into imported Holstein Friesian, imported Jersey, Farm born Holstein Friesian and farm born Jersey cows. Lactation milk yield of farm born Holstein Friesian and Jersey cows was significantly (P<0.05) lower than that of imported Holstein Friesian and Jersey cows. Breed group, season of calving and lactation number had significant (P<0.05) effect on lactation milk yield. The highest lactation milk yield was observed in imported and farm born Holstein Friesian cows calved during autumn, while in imported Jersey cows maximum lactation milk yield was observed in cows calved during spring season. The maximum lactation milk yield was observed in the third lactation in imported Holstein Friesian, imported Jersey and farm born Holstein Friesian cows, while in farm born Jersey cows maximum lactation milk yield was observed in the fifth lactation. The milk yield in all breed groups increased with increase in lactation length and service period