Specifying and Verifying Contract-driven Composite Web Services: a Model Checking Approach

As a promising computing paradigm in the new era of cross-enterprise e-applications, web services technology works as plugin mode to provide a value-added to applications using Service-Oriented Computing (SOC) and Service-Oriented Architecture (SOA). Verification is an important issue in this paradigm, which focuses on abstract business contracts and where services’ behaviors are generally classified in terms of compliance with / violation of their contracts. However, proposed approaches fail to describe in details both compliance and violation behaviors, how the system can distinguish between them, and how the system reacts after each violation. In this context, specifying and automatically generating verification properties are challenging key issues. This thesis proposes a novel approach towards verifying the compliance with contracts regulating the composition of web services. In this approach, properties against which the system is verified are generated automatically from the composition’s implementation. First, Business Process Execution Language (BPEL)that specifies actions within business processes with web services is extended to create custom activities, called labels. Those labels are used as means to represent the specifications and mark the points the developer aims to verify. A significant advantage of this labeling is the ability to target specific points in the design to be verified, which makes this verification very focused. Second, new translation rules from the extended BPEL into ISPL, the input language of the MCMAS model checker, are provided so that model checking the behavior of our contract-driven compositions is possible. The verification properties are expressed in the CTLC logic, which provides a powerful representation for modeling composition contracts using commitment-based multiagent interactions. A detailed case study with experimental results are also reported ins the thesis

Monetizing Personal Data: A Two-Sided Market Approach

© 2016 The Authors. Mobile phone-based sensing is a new paradigm that aims at using smartpohnes to answer sensing requests and collect useful data. Nowadays, a wide variety of domains ranging from health-care applications to pollution monitoring are benefiting from such collected data. However, despite its increasing popularity and the huge amount of data provided by users, there is no platform where mobile phone owners can effectively sell their data. In this paper, we propose the idea of a data monetization platform using two-sided market theory. In this platform, the data is viewed as an economic good and the data sharing activity is considered as an economic transaction. The proposed platform considers the case of abundant data. An experimental analysis is conducted to compare our approach against the peer-to-peer model using a real case study from the health care domain. We show that our proposed platform has the potential to generate higher profit for both data providers and data consumers

Effects of acute caffeine on muscle damage biomarkers and time to exhaustion after a single session of resistance exercises followed by exhaustive incremental test in long-distance runners

The present study was designed to investigate the acute effect of caffeine on muscle damage biomarkers (creatine kinase, lactate dehydrogenase, creatine kinase MB, and myoglobin) measured before, immediately after, and 24 h after a single session of resistance exercises followed by exhaustive incremental test. In addition, the effect of caffeine intake on time to exhaustion during exhaustive incremental test was determined. Fifteen male long-distance runners (30.67 ± 3.40 yrs.) performed two consecutive trials (7 days apart). Athletes were assigned randomly either to ingest caffeine (6 mg/kg) 1 h prior to exercise or placebo using a double-blind crossover design. Each trial consisted of 5 resistance exercises followed by exhaustive incremental test. Blood samples were collected before, immediately, and 24 h after each trial. The independent t test of data showed no significant differences in biomarkers of muscle damage at all time points between trials (p > .05). Using paired sample t test, data revealed that caffeine increased the time to exhaustion (45.78 ± 2.42 min) during exhaustive incremental test compared to the placebo (43.83 ± 2.21 min) (p = .001). In conclusion, 6 mg/kg of caffeine 1 hour prior to resistance exercises followed by exhaustive incremental test had no effect on muscle damage biomarkers in long-distance runners probably due to mechanical stress precisely affected fast twitch fibres rather than slow twitch fibres. However, the increased time to exhaustion due to caffeine consume may attributed to dampened pain sensation

The Effectiveness of an Educational Program for Developing Tolerance Values and Resistance to Intellectual Extremism at Secondary Level in Jordan

This study aimed to establish an effective educational program based on the rights of non-Muslims in Islamic principles of the development of religious tolerance values and the intellectual resistance of extremism among high school students in Jordan. The study was conducted on a sample of 48 students in 11th grade from Al-Arqam Islamic School, during the second semester of the academic year 2017-2018. A descriptive method was used for gathering the principles of rights for non-Muslims. A semi-empirical method was also used to measure the effectiveness of the educational program on two dependent variables (religious tolerance values, resistance of intellectual extremism), measured with two tools prepared by the researchers: the measure of religious tolerance values, and the measure of resistance to intellectual extremism. The results showed a statistically significant difference between the average performance of both the experimental and control groups in the measures for religious tolerance and resistance to intellectual extremism due to the experimental method of teaching designed for this study

Verifix: Verified Repair of Programming Assignments

Automated feedback generation for introductory programming assignments is useful for programming education. Most works try to generate feedback to correct a student program by comparing its behavior with an instructor's reference program on selected tests. In this work, our aim is to generate verifiably correct program repairs as student feedback. The student assignment is aligned and composed with a reference solution in terms of control flow, and differences in data variables are automatically summarized via predicates to relate the variable names. Failed verification attempts for the equivalence of the two programs are exploited to obtain a collection of maxSMT queries, whose solutions point to repairs of the student assignment. We have conducted experiments on student assignments curated from a widely deployed intelligent tutoring system. Our results indicate that we can generate verified feedback in up to 58% of the assignments. More importantly, our system indicates when it is able to generate a verified feedback, which is then usable by novice students with high confidence

A review on factors affected marital adjustment among parents of autistic children and gender effects

We aimed to systematically review studies that examine factors affecting marital adjustment among parents of children with disabilities, especially the autistic children. Besides, we emphasized the effects of gender on marital adjustments among the parents. There were at least 20 articles reviewed. The related journal articles on factor affecting marital adjustments were downloaded with cut off limit from 1992 to 2012. The articles were then analyzed and organized according to the definitions of marital adjustments and various factor affecting marital adjustments. We found there was no conclusive evidence regarding the factors affecting the marital among parents of autistics children. There was conclusive evidence from the reviewed literature regarding gender effect, yet the number of article supporting it was small. Mothers of autistics children were more affected in the marital adjustments as compared to fathers. Finally, with conclusion we then suggest for future interventional study

Low Resistance Polycrystalline Diamond Thin Films Deposited by Hot Filament Chemical Vapour Deposition

Polycrystalline diamond thin films with outgrowing diamond (OGD) grains were deposited onto silicon wafers using a hydrocarbon gas (CH4) highly diluted with H2 at low pressure in a hot filament chemical vapour deposition (HFCVD) reactor with a range of gas flow rates. X-ray diffraction (XRD) and SEM showed polycrystalline diamond structure with a random orientation. Polycrystalline diamond films with various textures were grown and (111) facets were dominant with sharp grain boundaries. Outgrowth was observed in flowerish character at high gas flow rates. Isolated single crystals with little openings appeared at various stages at low gas flow rates. Thus, changing gas flow rates had a beneficial influence on the grain size, growth rate and electrical resistivity. CVD diamond films gave an excellent performance for medium film thickness with relatively low electrical resistivity and making them potentially useful in many industrial applications

Analysis of SARS-CoV-2 viral loads in stool samples and nasopharyngeal swabs from COVID-19 patients in the United Arab Emirates

Coronavirus disease 2019 (COVID-19) was first identified in respiratory samples and was found to commonly cause cough and pneumonia. However, non-respiratory symptoms including gastrointestinal disorders are also present and a big proportion of patients test positive for the virus in stools for a prolonged period. In this cross-sectional study, we investigated viral load trends in stools and nasopharyngeal swabs and their correlation with multiple demographic and clinical factors. The study included 211 laboratory-confirmed cases suffering from a mild form of the disease and completing their isolation period at a non-hospital center in the United Arab Emirates. Demographic and clinical information was collected by standardized questionnaire and from the medical records of the patient. Of the 211 participants, 25 % tested negative in both sample types at the time of this study and 53 % of the remaining patients had detectable viral RNA in their stools. A positive fecal viral test was associated with male gender, diarrhea as a symptom, and hospitalization during infection. A positive correlation was also observed between a delayed onset of symptoms and a positive stool test. Viral load in stools positively correlated with, being overweight, exercising, taking antibiotics in the last 3 months and blood type O. The viral load in nasopharyngeal swabs, on the other hand, was higher for blood type A, and rhesus positive (Rh factor). Regression analysis showed no correlation between the viral loads measured in stool and nasopharyngeal samples in any given patient. The results of this work highlight the factors associated with a higher viral count in each sample. It also shows the importance of stool sample analysis for the follow-up and diagnosis of recovering COVID-19 patients

A novel privacy preserving user identification approach for network traffic

The prevalence of the Internet and cloud-based applications, alongside the technological evolution of smartphones, tablets and smartwatches, has resulted in users relying upon network connectivity more than ever before. This results in an increasingly voluminous footprint with respect to the network traffic that is created as a consequence. For network forensic examiners, this traffic represents a vital source of independent evidence in an environment where anti-forensics is increasingly challenging the validity of computer-based forensics. Performing network forensics today largely focuses upon an analysis based upon the Internet Protocol (IP) address – as this is the only characteristic available. More typically, however, investigators are not actually interested in the IP address but rather the associated user (whose account might have been compromised). However, given the range of devices (e.g., laptop, mobile, and tablet) that a user might be using and the widespread use of DHCP, IP is not a reliable and consistent means of understanding the traffic from a user. This paper presents a novel approach to the identification of users from network traffic using only the meta-data of the traffic (i.e. rather than payload) and the creation of application-level user interactions, which are proven to provide a far richer discriminatory feature set to enable more reliable identity verification. A study involving data collected from 46 users over a two-month period generated over 112 GBs of meta-data traffic was undertaken to examine the novel user-interaction based feature extraction algorithm. On an individual application basis, the approach can achieve recognition rates of 90%, with some users experiencing recognition performance of 100%. The consequence of this recognition is an enormous reduction in the volume of traffic an investigator has to analyse, allowing them to focus upon a particular suspect or enabling them to disregard traffic and focus upon what is left

Search for narrow resonances in dilepton mass spectra in proton-proton collisions at root s=13 TeV and combination with 8 TeV data

Peer reviewe