Neutrosophic Adaptive LSB and Deep Learning Hybrid Framework for ECG Signal Classification

This paper proposes a novel hybrid framework for ECG signal classification and privacy preservation. The framework includes two phases: the first phase uses LSTM+CNN with attention gate for ECG classification, while the second phase utilizes adaptive least signal bit with neutrosophic for hiding important data during transmission. The proposed framework converts data into three sets of degrees (true, false, and intermediate) using neutrosophic and passes them to an embedding layer. In the sender part, the framework hides important data in ECG signal as true and false degrees, using the intermediate set as a shared dynamic key between sender and receiver. The receiver can reconstruct the important data using the shared dynamic key or the intermediate set. The proposed framework is more robust against attacks compared to other methods

Effects of contact resistance and metal additives in finned-tube adsorbent beds on the performance of silica gel/water adsorption chiller

Recently interest in adsorption cooling systems has increased due to their capability to utilise low grade heat sources and environmentally friendly refrigerants. Currently, most of the commercially available adsorption cooling systems utilise granular packed adsorbent beds. Enhancing the heat transfer process inside the adsorbent bed will improve the overall efficiency of the adsorption system. Using recently developed empirical lumped analytical simulation model for a 450 kW two-bed silica gel/water adsorption chiller, this paper theoretically investigates the effects of various adsorbent bed heat transfer enhancement techniques on the adsorption system cooling capacity. Firstly, coating the first adsorbent layer to the metal part and packing the rest of adsorbent granules to eliminate the thermal contact resistance between heat exchanger metal and granules while keeping the same level of permeability. Secondly, adding metal particles to the adsorbent in order to enhance the granules thermal conductivity. The effective thermal conductivity of adsorbent/metal mixtures were determined and validated by comparing it with published experimental data. Also, the combined effect of using both techniques simultaneously was investigated. All these investigations were carried out at various adsorption bed fin spacing. Results of the combined techniques showed that the enhancement in the cooling capacity and system coefficient of performance (COP) increased with increasing the fin spacing ratio to reach maximum of 25% and 10% respectively at fin spacing ratio of 2

The homotopy theory of simplicial props

The category of (colored) props is an enhancement of the category of colored operads, and thus of the category of small categories. In this paper, the second in a series on "higher props," we show that the category of all small colored simplicial props admits a cofibrantly generated model category structure. With this model structure, the forgetful functor from props to operads is a right Quillen functor.Comment: Final version, to appear in Israel J. Mat

An Artistic Vision of Using Polyurethane Foam in Drapping Fictional Costumes Designs to Achieve Sustainable Development

One of the aspects of the modern era is leaving more room for imagination and experimentation. Costumes design in general and fictional costumes design in particular are among the areas that need a lot of experimentation, especially with new, non-traditional materials. This is what encouraged the researchers to choose the polyurethane foam as a non-traditional material to design fictional costumes in order to achieve sustainable development goals. The research aims at clarifying the characteristics of the polyurethane foam and it’s Forming instead of plastic capabilities in the field of Costumes design, and providing proposals for fictional costumes designs with this material, in addition to achieving the sustainable development goals; such as, adopting sustainable production and consumption patterns, and stimulating innovation. The research findings state the possibility of achieving new visions of using the polyurethane foam to design and create fictional costumes in order to achieve the goals of sustainable development

Questionning on oral and health behavior status of dental patients

РОТОВАЯ ПОЛОСТЬРОТОВОЙ ПОЛОСТИ СИМПТОМЫ ПРИ ПАТОЛОГИЧЕСКИХ СОСТОЯНИЯ

An efficient framework for adequacy evaluation through extraction of rare load curtailment events in composite power systems

With the growing robustness of modern power systems, the occurrence of load curtailment events is becoming lower. Hence, the simulation of these events constitutes a challenge in adequacy indices assessment. Due to the rarity of the load curtailment events, the standard Monte Carlo simulation (MCS) estimator of adequacy indices is not practical. Therefore, a framework based on the enhanced cross-entropy-based importance sampling (ECE-IS) method is introduced in this paper for computing the adequacy indices. The framework comprises two stages. Using the proposed ECE-IS method, the first stage’s purpose is to identify the samples or states of the nodal generation and load that are greatly significant to the adequacy indices estimators. In the second stage, the density of the input variables’ conditional on the load curtailment domain obtained by the first stage are used to compute the nodal and system adequacy indices. The performance of the ECE-IS method is verified through a comparison with the standard MCS method and the recent techniques of rare events simulation in literature. The results confirm that the proposed method develops an accurate estimation for the nodal and system adequacy indices (loss of load probability (LOLP), expected power not supplied (EPNS)) with appropriate convergence value and low computation time

Histopathological and immunohistochemical study of the protective effect of triptorelin on the neurocytes of the hippocampus and the cerebral cortex of male albino rats after short-term exposure to cyclophosphamide

AbstractChemotherapy treats many types of cancer effectively but it often causes side effects. Chemotherapy works on active cells, such as cancer cells, and some healthy cells. Side effects happen when chemotherapy damages these healthy cells. Today, many more drugs are available to treat side effects than in the past. Triptorelin (Decapeptyl) is a gonadotropin-releasing hormone agonist that is reported to have many therapeutic effects besides being an anti-cancer agent. In the current study, intraperitoneal cyclophosphamide (65mg/kg/day) was administered for 4 weeks to induce marked dystrophic changes in the cerebral cortex and hippocampus of male albino rats. After 4 weeks, we observed significant degeneration of neurocytes with dystrophic changes. Subcutaneous triptorelin (0.05mg/kg/day) for 4 weeks significantly improved histological signs of degeneration and apoptosis. Anti-Bcl2 staining of sections of the cerebral cortex and hippocampus showed that the apoptotic index was increased. This finding was confirmed by the anti-p53 staining, which showed a significant decrease in the apoptotic index. Ultimately, such improvements were accompanied by significant restoration of normal brain histology, as revealed by hematoxylin and eosin. In conclusion, triptorelin can reverse the apoptotic changes induced by cyclophosphamide therapy, which is more marked in the hippocampus than cerebral cortex

Ontop: answering SPARQL queries over relational databases

We present Ontop, an open-source Ontology-Based Data Access (OBDA) system that allows for querying relational data sources through a conceptual representation of the domain of interest, provided in terms of an ontology, to which the data sources are mapped. Key features of Ontop are its solid theoretical foundations, a virtual approach to OBDA, which avoids materializing triples and is implemented through the query rewriting technique, extensive optimizations exploiting all elements of the OBDA architecture, its compliance to all relevant W3C recommendations (including SPARQL queries, R2RML mappings, and OWL2QL and RDFS ontologies), and its support for all major relational databases

Breast cancer image classification using pattern-based Hyper Conceptual Sampling method

The increase in biomedical data has given rise to the need for developing data sampling techniques. With the emergence of big data and the rise of popularity of data science, sampling or reduction techniques have been assistive to significantly hasten the data analytics process. Intuitively, without sampling techniques, it would be difficult to efficiently extract useful patterns from a large dataset. However, by using sampling techniques, data analysis can effectively be performed on huge datasets, to produce a relatively small portion of data, which extracts the most representative objects from the original dataset. However, to reach effective conclusions and predictions, the samples should preserve the data behavior. In this paper, we propose a unique data sampling technique which exploits the notion of formal concept analysis. Machine learning experiments are performed on the resulting sample to evaluate quality, and the performance of our method is compared with another sampling technique proposed in the literature. The results demonstrate the effectiveness and competitiveness of the proposed approach in terms of sample size and quality, as determined by accuracy and the F1-measure. 2018This contribution was made possible by NPRP-07-794-1-145 grant from the Qatar National Research Fund (a member of Qatar foundation). The statements made herein are solely the responsibility of the authors.Scopu