Title: Numerical Range of Generalized Aluthge Transformation

Abstract:Let $T=U|T|$ be the polar decomposition of an operator $T$. For $s,t\\geq0$ with $s+t=1$,\nthe $(s,t)$-Aluthge transform is defined by $\\Dst(T)=|T|^sU|T|^t$. In this paper, we shall\ndiscuss the numerical range of $\\Dst(T)$ and show that $w(\\Dst(T))\\leq w(T)$ and if $T$\nis an $n\\times n$ matrix, then $\\overline{W(\\Dst(T))}\\subset \\overline{W(T)}$. Moreover, among other things by applying the generalized Aluthge transform of operators, we establish some inequalities involving the numerical radius. Also, we establish some upper bounds for the numerical radius of $2\\times 2$ operator matrices.

Title: The Role of the Current Health Information System (HIS) Workflow Processes in mitigating Opioids Abuse in Saudi Arabia

Abstract:The incidence of opioid abuse is an alarming issue within the healthcare industry as it could cause death and could increase the healthcare cost. Monitoring of opioid intake is essential and interoperable data is highly required to reach the goal of monitoring opioid intake using the Health Information System (HIS). Therefore, this study aims to explore the current workflow of HIS to curb the incidence of opioid abused in Saudi Arabia and to determine healthcare practitionerï¿½s perception towards the role of the current HIS in mitigating the opioid abuse issues. Methods: A Case Study Research was performed at Emergency Department, King Faisal Specialist Hospital and Research Centre (KFSHRC) and Al-Amal Mental Health Complex (AAMHC) from 1st March to 20th April 2018 whereby an observation on the Health Information System (HIS) workflow process was conducted and 37 healthcare practitioners were recruited to determine their perception on the current HIS through 5 Liker-scale questionnaire. Results: Opioid abuse issue is a prevalent issue in Saudi Arabia. Although the healthcare practitioners perceived the current HIS positively in curbing the opioid abuse or misuse issue but only within their organization, the absence of interoperability in the current HIS could be observed. Hence the ultimate role of HIS to curb the opioid abuse issue might not be reached. Conclusion: In order to use the HIS in curbing the issue of opioid abuse, the current workflow of HIS in Saudi Arabia needs to be improved and the function of real-time health information exchange needs to be developed.

Title: Encrypting Communication Transmission Messages by Utilizing Multi-Layer Perception Neural Network

Abstract:Encryptions can play essential role in securely communication transmissions. It can be used to raise the reliability and security of any communication system such as satellite communication and wireless Local Area Network (LAN). Security should satisfy and reassure the data transmission arrival to a specific destination. In this paper, a well-defined and powerful encryption technique is suggested, it can be exploited for securely communication transmissions. This technique utilizes An artificial neural network (ANN) of Multi-Layer Perceptron (MLP). It is used to efficiently encrypt text information into useful codes. Significant accuracies of 100% are investigated for data encryption and decryption as well.

Title: Spotting Fake and Genuine Reviews with Hybridization of Fuzzy and Neural Networks Techniques

Abstract:Sentiment Analysis/Opinion Mining integrates the discipline of Computer Science as well as Business Management. Sentiment Analysis on Fake and Genuine Reviews spotting is based on public emotional approaches. The main aim of this work is for helping customers to identify fake reviews on social media and websites for better decision on product purchases through online. Also it is helpful for sellers and manufacturers to notify fake and genuine reviews of their products. The most emerging techniques viz Fuzzy Logic, Neural Network, Hybrid of Fuzzy Logic, and Neural Network are used to splotch fake and genuine reviews. These techniques analyze social media comments which are then classified to fake and genuine reviews separately. These proposed technique’s performance are evaluated by evaluation metrics providing 96% of Accuracy Score and F1-Score. The higher percentage of evaluation metrics proves better classification of fake and genuine reviews.

Title: Combining Convolutional Neural Network with Recursive Neural Network for Robotic Financial Guidance

Abstract:In the proposed work is discussed the design and the development of a web app platform supporting the choice of financial announcements. The platform is based on digitized information extracted from a pdf file and on automatic text mining data processing. Models integrating Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). are applied to implement a Decision Support System (DSS) based on Natural Language Processing (NLP), and to favor the choice of the announcement to follow, by guiding financial perspectives. The proposed DSS automatizes the choice process by enhancing announcement keywords, deadlines and requirements to participate to request for funds. The research is finalized to provide a dashboard suggesting automatically all the possibilities for a funding participation matching with company profiles. The paper introduces also an innovative approach based on a successive application of, CNN, LSTM-CNN, and of the combination of CNN + LSTM-CNN, thus furthermore improving text recognition performances. The combined CNN + LSTM-CNN approach provides the best Accuracy of about 95 %, and the best Loss of 0.006 for the specific case of study. The results are obtained within a framework of an industry project.

Title: Comparison of experimental and artificial neural network-estimated thermal performance parameters for a hot-box solar cooker

Abstract:A hot-box solar cooker designed for domestic applications had its thermal performance initially evaluated from experimental measurements, and then numerically using artificial neural networks (ANNs). Ambient temperature, temperature of the cooker and that of a known volume of water were measured as functions of incident solar radiation intensity and time of day. The cooker output power and efficiency, and the exergy output and efficiency computed from experimental measurements, constituted the four cooker thermal performance parameters. Experimental results show that the cooker has peak energy output of 21.3 W and peak energy efficiency of about 12 %. Peak exergy out was 1.4 %, while peak exergy efficiency was about 0.9 %. ANNs were then employed to estimate the four cooker performance parameters, for arbitrary inputs. A feed-forward neural network based on the Levenberg-Marquardt backpropagation algorithm was developed that used the five experimentally measured variables as inputs, while the four computed thermal performance parameters were the targets. Statistical parameters were used to rate the performance of ANNs in estimating the four experimental thermal performance parameters. Linear regressions were used to find relationships between ANN estimated and experimental energy/exergy outputs, and efficiencies. Results show good correlations between ANN predictions and experimentally measured cooker performance parameters. Correlation coefficients for all the four thermal parameters were very close to unity, with relatively low root-mean square errors (rmse) of only up to ±0.20. Peak mean absolute errors (mae) were about 0.10 W for cooker power, while mean absolute percentage errors (mape) were in the range of 0.57−1.25 %. High values of the correlation coefficients and relatively low error values show that the ANN model developed here successfully estimates cooker power, energy efficiency, exergy and exergy efficiencies with some good degree of accuracy.

Title: Mongolian and Tibetan medicine techniques for health screening

Abstract:Objectives: Traditional oriental medicine provides a wide range of techniques for human health screening. Some of them, such as pulse diagnostics, are currently widely used especially in Asia regions. However, the question of these techniques utility for population screening is relevant. The study describes the experience of using the Mongolian and Tibetan medicine methods.\nMethods: More than 800 participants voluntarily undertook in the study. Participants filled out questionnaires and attended medical examination with a clinician trained in Tibetan and Mongolian medicine. To analyze these experiments, we used correlation analysis methods, Student\'s t-criterion.\nResults: The results of the analysis show a correlation between the Tibetan and Mongolian medicine questionnaires. A reliable positive correlation for \"wind\" humor between the Tibetan questionnaire and the clinician\'s diagnosis was found. \nConclusion: We described an information model based on Tibetan and Mongolian medicine techniques. It is possible to use this model for population screening. However, additional experiments are required to obtain a representative sample for the whole population.

Title: Molecular detection of Eimeria acervulina isolated from broiler birds

Abstract:The present study reports the histopathological, haematological and biochemical changes in broiler chicken naturally infected with Eimeria acervulina. A polymerase chain reaction (PCR) was used to identify this species in 225 gut samples of broiler chicken from different farms in North Eastern (NE) region of India. Postmortem examination revealed greyish white transeversely elongated area on the serous surface, oedema, together with necrosis and sloughing of intestinal epithelium.Haematological changes included a decrease in haemoglobin,(Hb) and packed cell volume. The value of mean corpuscular haemoglobin concentration (MCHC), on the otherhand increased slightly. Biochemical changes showed a significant increase in the level of glucose, cholesterol, Alaninine amino transferase (ALT), Asparase amino transferase (AST) and Alkaline phosphatase. The PCR assay was based on internal transcribed spacer (ITS1) region of the ribosomal DNA ofEimeria sp which has shown interspecies variation that enables to differentiate the species. The six isolates of Eimeria acervulina obtained were sequenced and a phylogenetic tree wasprepared. The sequences of the six isolates were searched for matching with isolates available in the Gen Bank database for sequence similarity using nucleotide blast. The sequence analysis showed that the newly isolates of E. acervulina had 99% Similarity with isolate of Turkey origin.

Title: Basic core fuzzy logics and algebraic Routley--Meyer-style semantics

Abstract:Yang recently introduced algebraic Routley--Meyer-style semantics for basic substructural logics. We extend his investigation to fuzzy logics. First, we recall the basic substructural core fuzzy logic MIAL (Mianorm logic) and its axiomatic extensions, together with their algebraic semantics. Next, we introduce two kinds of ternary relational semantics, called here \nUrquhart-style and Fine-style Routley--Meyer semantics, for them as algebraic Routley--Meyer-style semantics.

Title: Compressed-Air-Driven Motor for Lighting Towards a Sustainable Electricity Supply

Abstract:In this paper study focuses on a portable compressed air-driven power mechanical generation apparatus that a green clean energy and clear air power generation apparatus driven by compressed air. This invention design approach concept can provide real-time power electricity or LED lighting requirement application. A novel approach to air kinetic energy can operate to transfer to power energy for electricity useful. Modularization experimental testing, design, and assembly are adopted in this power generation electricity source apparatus to enhance portability. The gas source can drive the micro-rotor speed is between 5,400 rpm and 32,400 rpm, which power is sufficient to have closed to 40 W LED lighting. It is a good gas dynamics output power can be converted to green clean energy.