A Calculus of Mobility and Communication for Ubiquitous Computing

We propose a Calculus of Mobility and Communication (CMC) for the modelling of mobility, communication and context-awareness in the setting of ubiquitous computing. CMC is an ambient calculus with the in and out capabilities of Cardelli and Gordon's Mobile Ambients. The calculus has a new form of global communication similar to that in Milner's CCS. In CMC an ambient is tagged with a set of ports that agents executing inside the ambient are allowed to communicate on. It also has a new context-awareness feature that allows ambients to query their location. We present reduction semantics and labelled transition system semantics of CMC and prove that the semantics coincide. A new notion of behavioural equivalence is given by defining capability barbed bisimulation and congruence which is proved to coincide with barbed bisimulation congruence. The expressiveness of the calculus is illustrated by two case studies.Comment: In Proceedings WWV 2015, arXiv:1508.0338

FORMULATION AND EVALUATION OF GLIBENCLAMIDE GEL FOR TRANSDERMAL DRUG DELIVERY

Objective: The purpose of the recent study was to formulate glibenclamide gels for transdermal drug release, and to evaluate the oleic acid effect on the release of the preparations. Methods: Oleic acid was used at a range of concentrations in the gel formulations and its effects observed in Glibenclamide gel using In vitro release of drug was done in Franz diffusion cells, whereas pH 7.4 Phosphate buffer was used for release studies. Formulations were characterized by clarity, pH, homogeneity, viscosity, spreadabilty, skin irritation, drug content, stability studies. Scanning calroimetry analysis (SCA) and XRD studies were performed to assess the physical and chemical interactions. Results: Release profiles in vitro were observed. The released quantity of drug recovered from the glibenclamide gel after the addition of 1% oleic acid, increased with increasing concentration of the enhancer that is oleic acid. Whereas drug quantity recovered in the receptor solvent was 69.999% of Glibenclamide gel having 3% oleic acid. All the formulation were physicochemically stable. The data was statistically analyzed by using SPSS and DD solver. Conclusion: The drug is released and the oleic acid does enhance the release of the drug with the increase in its concentration

Optimal trees selection for classification via out-of-bag assessment and sub-bagging

The effect of training data size on machine learning methods has been well investigated over the past two decades. The predictive performance of tree based machine learning methods, in general, improves with a decreasing rate as the size of training data increases. We investigate this in optimal trees ensemble (OTE) where the method fails to learn from some of the training observations due to internal validation. Modified tree selection methods are thus proposed for OTE to cater for the loss of training observations in internal validation. In the first method, corresponding out-of-bag (OOB) observations are used in both individual and collective performance assessment for each tree. Trees are ranked based on their individual performance on the OOB observations. A certain number of top ranked trees is selected and starting from the most accurate tree, subsequent trees are added one by one and their impact is recorded by using the OOB observations left out from the bootstrap sample taken for the tree being added. A tree is selected if it improves predictive accuracy of the ensemble. In the second approach, trees are grown on random subsets, taken without replacement-known as sub-bagging, of the training data instead of bootstrap samples (taken with replacement). The remaining observations from each sample are used in both individual and collective assessments for each corresponding tree similar to the first method. Analysis on 21 benchmark datasets and simulations studies show improved performance of the modified methods in comparison to OTE and other state-of-the-art methods

Genotypes of GSTM1 and GSTT1: Useful determinants for clinical outcome of bladder cancer in Pakistani population

Background: Incidence of bladder cancer has increased rapidly worldwide in the past few years. Environmental as well as genetic factors are involved in the etiology of bladder cancer. Glutathione S transferase mu 1 (GSTM1) and glutathione S transferase theta 1 (GSTT1) genes are two xenobiotic metabolizing genes in phase II of detoxification process. Aim: The current study was aimed to find out the association of different environmental factors and GSTM1 and GSTT1 gene polymorphisms with susceptibility to bladder cancer in Pakistani population. Method: Bladder cancer cases (236) and control blood samples (270) were screened using phenol chloroform method of DNA extraction followed by multiplex PCR. Results: With respect to age; bladder cancer was more prevalent in age >60 years and low grade tumors were more frequent than high grade tumors. Smokers had a significantly higher incidence rate of cancer; also family history of cancer was found to be strongly associated (P < 0.05) with bladder cancer. Commonly reported symptoms by the patients of bladder cancer were hematuria, lower urinary tract symptoms (LUTS) and flank pain. A larger number of patients had undergone surgery, chemotherapy and radiotherapy. Similarly GSTM1 (OR 2.24; CI 1.5–3.2; P = 0.0001) and GSTT1 (OR 2.9; CI 1.4–6.1; P = 0.002) gene deletion showed a highly significant association with bladder cancer. Simultaneous deletions of both GSTM1 and GSTT1 genes also showed highly significant association (OR 5.3; CI 2.1–13.1; P = 0.0001) with cancer risk. No association was found when both of the two genes deletion was compared with bladder cancer among smokers. Conclusion: This study suggests that GSTM1 and GSTT1 gene polymorphisms may be associated with increased susceptibility toward bladder cancer in Pakistani population

Rough bipolar fuzzy ideals in semigroups

Abstract Fuzzy set (FS) theory and rough sets (RSs) are constructed to accommodate the data uncertainty. In contrast, the bipolar FS (BFS) theory can tackle the uncertainty and the bipolarity of the data in different circumstances. This article aims to introduce the idea of rough bipolar fuzzy ideals in semigroup (SG), which is a generalization of the concept of rough BFSs (RBFSs) in an SG. We also investigate the roughness in the bipolar fuzzy subsemigroup (BF-SSG) with the help of congruence relation (cng-R) defined on the SG and studied some relevant structural properties. Moreover, the idea is extended to the rough bipolar fuzzy left ideal, rough bipolar fuzzy right ideal, rough bipolar fuzzy two-sided ideal, rough bipolar fuzzy interior ideal, and rough bipolar fuzzy bi-ideal in SGs. Further, it is seen that cng-Rs and complete cng-Rs play vital roles in the construction of rough approximations of bipolar fuzzy ideals. Consequently, their associated properties are explored by using cng-Rs and complete cng-Rs

Secure Reversible Data Hiding in Images Based on Linear Prediction and Bit-Plane Slicing

Reversible Data Hiding (RDH) should be secured as per requirements to protect content in open environments such as the cloud and internet. Integrity and undetectability of steganographic images are amongst the main concerns in any RDH scheme. As steganographic encryption using linear prediction over bit-planes is challenging, so the security and embedding capacity of the existing RDH techniques could not be adequate. Therefore, a new steganographic technique is proposed which provides better security, higher embedding capacity and visual quality to the RDH scheme. In this technique, the cover image is divided into n-bit planes (nBPs) and linear prediction is applied to it. Next, the histogram of the residual nBPs image is taken, and secret data bits are encrypted using the RC4 cryptographic algorithm. To embed the encrypted secret data bits, the histogram shifting process is applied. This is achieved by using peak and zero pairs of residual nBPs images. This scheme provides security to the cover image and hidden data. The proposed RDH scheme is capable of extracting the embedded secret data accurately and recovering the original cover or residual nBPs image

Redesign and validation of a computer programming course using Inductive Teaching Method.

Inductive Teaching Method (ITM) promotes effective learning in technological education (Felder & Silverman, 1988). Students prefer ITM more as it makes the subject easily understandable (Goltermann, 2011). The ITM motivates the students to actively participate in class activities and therefore could be considered a better approach to teach computer programming. There has been little research on implementing ITM in computer science courses despite its potential to improve effective learning. In this research, an existing computer programming lab course is taught using a traditional Deductive Teaching Method (DTM). The course is redesigned and taught by adopting the ITM instead. Furthermore, a comprehensive plan has been devised to deliver the course content in computer labs. The course was evaluated in an experiment consisting of 81 undergraduate students. The students in the Experimental Group (EG) (N = 45) were taught using the redesigned ITM course, whereas the students in the Control Group (CG) (N = 36) were taught using the DTM course. The performance of both groups was compared in terms of the marks obtained by them. A pre-test conducted to compare pre-course mathematical and analytical abilities showed that CG was better in analytical reasoning with no significant differences in mathematical abilities. Three post-tests were used to evaluate the groups theoretical and practical competence in programming and showed EG improved performance with large, medium, and small effect sizes as compared to CG. The results of this research could help computer programming educators to implement inductive strategies that could improve the learning of the computer programming

Valorization of the phytochemical profile, nutritional composition, and therapeutic potentials of garlic peel: a concurrent review

ABSTRACTGarlic (Allium sativum) is an ingredient that is frequently utilized in food for its therapeutic properties. Even though garlic peel accounts for 25% of production overall, unfortunately, it is discarded by the industry. Garlic peel is a valuable source of phytochemicals and medicinal substances. Throughout history, various civilizations have recognized the potential benefits of using garlic peel for illness prevention and treatment. This review emphasizes that garlic peel contains a variety of chemicals that are believed to offer health benefits for high blood sugar levels, lower the risk of cardiovascular illnesses, and have anti-tumor, anti-viral, anti-inflammatory, and anti-microbial properties. Additionally, we discuss the main bioactive substances in garlic peel, namely total phenolics, total flavonoids, and their derivatives. We may infer from our understanding that garlic peel is a useful agricultural waste because it contains a range of biologically active components. As a result, it can be employed as an ingredient to control health, especially in the biomedical and pharmaceutical fields