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

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

The influence of Sufism on Eric–Emmanuel Schmitt’s work

This paper attempts to investigate Eric-Emmanuel Schmitt(1960- ), as a Western dramatist and mystical writer of Eastern traditions through a detailed, qualitative and critical analysis of one of his most important work, Monsieur Ibrahim and the Flowers of Quran . In the play , Sufi framework and Archetypal Theory is used to present plainly and briefly the main concepts of mysticism and, at the same time, to situate mysticism within the play. Here, the author finds that the title character takes on the role of a Sufi master, initiating the protagonist, Moses, into the way of the Sufi and to eventually become his successor. The author concludes that Schmitt is indeed influenced by the master and disciple relationship in the initiation and journey of Sufism.Keywords: Modern drama, Emmanuel Schmitt, Sufism, Theater, play, Monsieur Ibrahim and the Flowers of the Qur’a

Higher dietary magnesium intake and higher magnesium status are associated with lower prevalence of coronary heart disease in patients with Type 2 Diabetes

In type 2 diabetes mellitus (T2D), the handling of magnesium is disturbed. Magnesium deficiency may be associated with a higher risk of coronary heart disease (CHD). We investigated the associations between (1) dietary magnesium intake; (2) 24 h urinary magnesium excretion; and (3) plasma magnesium concentration with prevalent CHD in T2D patients. This cross-sectional analysiswas performed on baseline data fromthe DIAbetes and LifEstyle Cohort Twente-1 (DIALECT-1, n = 450, age 63 � 9 years, 57%men, and diabetes duration of 11 (7–18) years). Prevalence ratios (95% CI) of CHD by sex-specific quartiles of magnesium indicators, as well as by magnesium intake per dietary source, were determined using multivariable Cox proportional hazard models. CHD was present in 100 (22%) subjects. Adjusted CHD prevalence ratios for the highest compared to the lowest quartiles were 0.40 (0.20, 0.79) for magnesium intake, 0.63 (0.32, 1.26) for 24 h urinary magnesium excretion, and 0.62 (0.32, 1.20) for plasma magnesium concentration. For every 10 mg increase of magnesium intake from vegetables, the prevalence of CHD was, statistically non-significantly, lower (0.75 (0.52, 1.08)). In this T2D cohort, higher magnesium intake, higher 24 h urinary magnesium excretion, and higher plasma magnesium concentration are associated with a lower prevalence of CHD

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

A scalable framework for cross-lingual authorship identification

This is an accepted manuscript of an article published by Elsevier in Information Sciences on 10/07/2018, available online: https://doi.org/10.1016/j.ins.2018.07.009 The accepted version of the publication may differ from the final published version.© 2018 Elsevier Inc. Cross-lingual authorship identification aims at finding the author of an anonymous document written in one language by using labeled documents written in other languages. The main challenge of cross-lingual authorship identification is that the stylistic markers (features) used in one language may not be applicable to other languages in the corpus. Existing methods overcome this challenge by using external resources such as machine translation and part-of-speech tagging. However, such solutions are not applicable to languages with poor external resources (known as low resource languages). They also fail to scale as the number of candidate authors and/or the number of languages in the corpus increases. In this investigation, we analyze different types of stylometric features and identify 10 high-performance language-independent features for cross-lingual stylometric analysis tasks. Based on these stylometric features, we propose a cross-lingual authorship identification solution that can accurately handle a large number of authors. Specifically, we partition the documents into fragments where each fragment is further decomposed into fixed size chunks. Using a multilingual corpus of 400 authors with 825 documents written in 6 different languages, we show that our method can achieve an accuracy level of 96.66%. Our solution also outperforms the best existing solution that does not rely on external resources.Published versio