Electronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our s

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controll

Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

In the present paper, an eco-epidemiological model consisting of diseased prey consumed by a predator with fear cost, and hunting cooperation property is formulated and studied. It is assumed that the predator doesn’t distinguish between the healthy prey and sick prey and hence it consumed both. The solution’s properties such as existence, uniqueness, positivity, and bounded are discussed. The existence and stability conditions of all possible equilibrium points are studied. The persistence requirements of the proposed system are established. The bifurcation analysis near the non-hyperbolic equilibrium points is investigated. Numerically, some simulations are carried out to validate the main findings and obtain the critical values of th

The purpose of this study is to underline the progression and development of research regarding oxygen-containing heterocycles as well as the contribution that some oxygen-containing heterocycles have made as anticancer medicines. A series of publications about the antitumor effects of derivatives of heterocyclic compounds containing an oxygen atom, such as furan, benzofuran, oxazole, benzoxazole, and oxadiazole, were evaluated, and their anticancer activities showed encouraging results when compared to those of established standard treatments.

Detection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200

   The Financial systems can be classified into two types. The first is the market–oriented, which is applied in United States and United Kingdom. While the second is bank-oriented as in Japan and Germany.

   This study tries to explain the reasons which make some countries adopt the first one instead of the second, and the contrary. So the study consists of three sections. The first deals with the concept of financial system and it are functions. The second displays the indicators which are used to classify the financial systems, while the third one is devoted to the factors that determine the type of financial system .These sections followed by some conclusions.

Due to the continuous development in society and the multiplicity of customers' desires and their keeping pace with this development and their search for the quality and durability of the commodity that provides them with the best performance and that meets their needs and desires, all this has led to the consideration of quality as one of the competitive advantages that many industrial companies compete for and which are of interest to customers and are looking for. The research problem showed that the Diyala State Company for Electrical Industries relies on some simple methods and personal experience to monitor the quality of products and does not adopt scientific methods and modern programs. The aim of this research is to desi

Cement is a major component in oil and gas drilling operations that is used to maintain the integrity of boreholes by preventing the movement of formation fluids through the annular space and outside the casing. In 2019, Iraq National Oil Company ordered all international oil and gas companies which are working in Iraq to use Iraqi cement (made in Iraq) in all Iraqi oil fields; however, the X-ray fluorescence (XRF) and compressive strength results in this study show that this cement is not matching with American Petroleum Institute (API) standards.

During this study, barolift was used to improve the properties of Iraqi cement used in oil wells at high pressure and high temperature (HPHT). Barolift (1 g) was added to cement admixt