Properties of Bipolar Fuzzy Hypergraphs

In this article, we apply the concept of bipolar fuzzy sets to hypergraphs and investigate some properties of bipolar fuzzy hypergraphs. We introduce the notion of $A-$ tempered bipolar fuzzy hypergraphs and present some of their properties. We also present application examples of bipolar fuzzy hypergraphs

Fluctuations in canal water supplies: a case study

Irrigation management / Water allocation / Canals / Water distribution / Water supply / Performance evaluation / Irrigated farming / Irrigation systems / Pakistan / Chishtian Sub-Division / Fordwah Distributary

Computer simulation of the adsorption of chlorinated organics in zeolites.

Computer modelling techniques have been used to study the adsorption of three chlorinated hydrocarbons Dichloromethane, 1,2-Dichloroethane, and Trichloroethene in three different zeolite frameworks MFI, MOR and FAU. Calculations have been performed using both classical methods based on inter-atomic potentials, quantum mechanical Density Functional Theory (DFT) and combined QM/MM embedded methods. The first section of this thesis presents results of DFT calculations on purely siliceous and aluminosilicate gas-phase clusters. The results obtained are compared to experimental data and are found to differ significantly from experimental results. The reasons for this are rationalised and alternative methods suggested. The second section investigates some of these alternative approaches. Results of a Periodic DFT study and cluster calculations using a hybrid functional are presented. The QMPot embedded cluster method is then employed as an alternative to the cluster and periodic DFT approaches. The results of these different approaches are compared and rationalised. The thesis then moves on to describe atomistic simulations of the adsorption and diffusion of the molecules in the framework structures. The third section of this thesis uses the Grand Canonical Monte Carlo method to simulate adsorption isotherms and isosteric heat plots. The simulated data is found to be in good agreement to that in the literature. The final chapter describes results of a Molecular Dynamics simulation which models the diffusion of the molecules in the FAU framework at different temperatures

SGLT-2 Inhibitors: A Novel Mechanism in Targeting Glycemic Control in Type 2 Diabetes Mellitus

OBJECTIVE: To review the chemistry, pharmacology, pharmacodynamics, pharmacokinetics, clinical efficacy, tolerability, dosing, drug interactions, and administration of canagliflozin, dapagliflozin, and empagliflozin, and comparing the benefit and risk aspects of using these agents in the older adult diabetes patient population. DATA SOURCES, STUDY SELECTION, DATA EXTRACTION, AND DATA SYNTHESIS: A search of PubMed using the terms SGLT-2 inhibitors, canagliflozin, dapagliflozin, empagliflozin, efficacy, and tolerability was performed to find relevant primary literature on each of the sodium/glucose cotransporter 2 (SGLT-2) inhibitors currently approved for use in type 2 diabetes. Phase III trials for all agents were included. All English-language articles from 2010 to 2015 appearing in these searches were reviewed for relevance to this paper. In addition, related articles suggested in the PubMed search were also reviewed. The SGLT-2 inhibitors have shown a reduction in hemoglobin A1c values and fasting plasma glucose levels with a low incidence of hypoglycemia. The incidence of mycotic infections is increased in patients taking an SGLT-2 inhibitor. CONCLUSION: SGLT-2 inhibitors may be a viable treatment option for patients not controlled on other oral agents. The risk of hypoglycemia is small. However, the clinical efficacy and tolerability of these agents has not been fully elucidated in older and frail patients

FedBiometric: Image Features Based Biometric Presentation Attack Detection Using Hybrid CNNs-SVM in Federated Learning

In the past few years, biometric identification systems have become popular for personal, national, and global security. In addition to other biometric modalities, facial and fingerprint recognition have gained popularity due to their uniqueness, stability, convenience, and cost-effectiveness compared to other biometric modalities. However, the evolution of fake biometrics, such as printed materials, 2D or 3D faces, makeup, and cosmetics, has brought new challenges. As a result of these modifications, several facial and fingerprint Presentation Attack Detection methods have been proposed to distinguish between live and spoof faces or fingerprints. Federated learning can play a significant role in this problem due to its distributed learning setting and privacy-preserving advantages. This work proposes a hybrid ResNet50-SVM based federated learning model for facial Presentation Attack Detection utilizing Local Binary Pattern (LBP), or Gabor filter-based extracted image features. For fingerprint Presentation Attack Detection (PAD), this work proposes a hybrid CNN-SVM based federated learning model utilizing Local Binary Pattern (LBP), or Histograms of Oriented Gradient (HOG)-based extracted image features

Substituting Wood with Nonwood Fibers in Papermaking: A Win-Win Solution for Bangladesh

Bangladesh is facing an acute shortage of fibrous raw materials for the production of pulp and paper. On the other hand, the demand for paper and paper products is increasing day by day. This study reviews the availability and suitability of nonwood raw materials for pulp production in Bangladesh. It shows that Bangladesh has a huge amount of unused jute fiber, which is highly suitable for papermaking in Bangladesh. Other agricultural wastes like rice straw, dhaincha, golpata fronds, cotton stalks, corn stalks, and kash are also available and may be used for some pulp production. Given the different properties of these different nonwood fibers, jute pulp can be used as a reinforcing agent with other nonwood pulps for the production of high quality paper in Bangladesh.Bangladesh, natural fibers, jute, paper making, pulp

Context-Aware Personalized Activity Modeling in Concurrent Environment

Activity recognition, having endemic impact on smart homes, faces one of the biggest challenges in learning a personalized activity model completely by using a generic model especially for parallel and interleaved activities. Furthermore, inhabitant’s mistaken object interaction may entail in another spurious activity at smart homes. Identifying and removing such spurious activities is another challenging task. Knowledge driven techniques used for recognizing activity models are static in nature, lack contextual representation and may not comprehend spurious actions for parallel/interleaved activities. In this paper, a novel approach for completing the personalized model specific to each inhabitant at smart homes using generic model (incomplete) is presented that can recognize the sequential, parallel, and interleaved activities dynamically while removing the spurious activities semantically. A comprehensive set of experiments and results based upon number of correct (true positivity) or incorrect (false negativity) recognition of activities assert effectiveness of presented approach within a smart hom

Terrorism or Political Terrorism Vs Tourism: New Evidence from Developing Countries

In the 21st century, tourism emerges as a significant income generating sector as well as weapon for growth and survival for various countries[1]. Tourism is the largest global industry with continuously growing global market which will triple in size by 2020[2]. Besides, numerous natural and human-caused disasters, the threat that accompanies political turmoil, tends to frighten potential tourists more severely. Such uncertainties in an economy can impede the flow of tourism. Terrorism risk tends to intimidate the traveling public more severely—as demonstrated by the realignment of travel flows and cancellation of vacations during periods of heightened terrorist activity. The tourism industry is highly vulnerable to such disturbances—whether social or political (i.e., riots, insurgency, terrorism, crime, political upheaval, war, regional tensions). This study also aims at finding a nexus between Terrorism and tourism based on new evidence from developing nations. Moreover developing nations have been further divided into two panels i.e. Politically Free , and Politically Not Free nations. This classification has been made to see whether political environment also affects terrorism activities in nations or not. Similarly another important aspect of this study is to see whether simply terrorist’s activities or Political terrorism[3] is a hurdle for the development of an economy. For this purpose different variables related to political terror and failures have also been used. Moreover time span for the study is from 1995-2011. Both parametric and non-parametric approaches have been employed. For evaluating the impact of Terrorist activities, data has been taken from World Governance Indicators(WGI), while data for tourism is from World Tourism Organization (UNWTO). Keywords: Tourism, Economic Development, panel Data [1] E. T. Heath, “Globalization of the Tourism Industry: Future Trends and Challenges for South Africa,” South African Journal of Economic and Management Sciences, vol. 4, pp. 542-569, 2001. [2] World Tourism Organization, World Tourism Barometer. [3] E. Neumayer, “The impact of political violence on tourism: Dynamic cross-national estimation,” Journal of Conflict Resolution vol. 48(2), pp. 259-281, 200

Welfaremindedness in Trade Policy Decision Making Process: A Qualitative and Quantitative Analysis from Developing Nations

The proposition of free trade has been one of the most important tenets of economists for the past two centuries. They have been of the view that free trade will be in benefit of nations in most of the cases. But “new trade theory” and “infant industry argument” does not support this principle of trade. Therefore now economists are trying to seek out not only economic rather political determinants of protection in nations. So this study has basically tried to see how government maximizes welfare of the society in designing trade policies specifically in developing countries. Moreover the whole developing region has been divided regime wise, domestic institutional wise and  income wise. Both quantitative and qaualitative analysis has been performed. Grossman Helpman model has been employed for estimating these welfare estimates. Time span of the study is from 1995-2010. And GTAP7 has been used for extracting data for intermediate inputs. Welfare mindedness has been calculated with lobby and without lobby formation in an economy. Results are very much close to the present world scenario that more rich and democratic nations are more welfare concerned than poor and autocratic nations. More over parliamentary democracies proved more welfare oriented than presidential democracies

Review of Traffic Sign Detection and Recognition Techniques

Text, as one of the most compelling developments of humankind, has assumed a significant job in human life, so distant from antiquated occasions. The rich and exact data epitomized in content is extremely helpful in a wide scope of vision-based applications; along these lines content detection and recognition in regular scenes have turned out to be significant and dynamic research points in PC vision and report investigation. Traffic sign detection and recognition is a field of connected PC vision research worried about the programmed detection and grouping or recognition of traffic signs in scene pictures procured from a moving vehicle. Driving is an assignment dependent on visual data handling. The traffic signs characterize a visual language translated by drivers. Traffic signs convey much data important for effective driving; they portray current traffic circumstance, characterize option to proceed, preclude or grant certain headings. In this paper, talked about different detection and recognition schemes