Big data usually running in large-scale and centralized key management systems. However, the centralized key management systems are increasing the problems such as single point of failure, exchanging a secret key over insecure channels, third-party query, and key escrow problem. To avoid these problems, we propose an improved certificate-based encryption scheme that ensures data confidentiality by combining symmetric and asymmetric cryptography schemes. The combination can be implemented by using the Advanced Encryption Standard (AES) and Elliptic Curve Diffie-Hellman (ECDH). The proposed scheme is an enhanced version of the Certificate-Based Encryption (CBE) scheme and preserves all its advantages. However, the key generation process in our scheme has been done without any intervention from the certificate issuer and avoiding the risk of compromised CA. The Elliptic Curve Digital Signature Algorithm (ECDSA) has been used with the ECDH to handle the authentication of the key exchange. The proposed scheme is demonstrated on a big dataset of social networks. The scheme is analyzed based on security criteria that have been compared with the previous schemes to evaluate its performance.
Background: DVT is a very common problem with a very serious complications like pulmonary embolism (PE) which carries a high mortality,and many other chronic and annoying complications ( like chronic DVT, post-phlebitic syndrome, and chronic venous insufficiency) ,and it has many risk factors that affect its course, severity ,and response to treatment. Objectives: Most of those risk factors are modifiable, and a better understanding of the relationships between them can be beneficial for better assessment for liable pfatients , prevention of disease, and the effectiveness of our treatment modalities. Male to female ratio was nearly equal , so we didn’t discuss the gender among other risk factors. Type of the study:A cross- secti
This work presents an approach to deal with modelling a decision support system framework to introduce an application for decisions in medical knowledge system analysis. First aid is extremely important worldwide and, hence, a decision support framework, know as First Aid Decision Support System (FADSS), was designed and implemented to access experimental cases exerting danger to the general population, offering advanced conditions for testing abilities in research and arranging an emergency treatment through the graphical user interface (UI). The design of first aid treatment in FADSS depends on the general cases in first aid. We presented a strategy to manage first aid treatment by modelling an application (FADSS) that assists pe
... Show MoreThe cadastral map is very important because it has technical and materialist
specification of the property borders and these maps which are land registration
based on it in Iraq, the problem is an ancient maps and unfit for use, despite its
importance, Therefor the updating and digitize the cadastral map is very pivotal, this
is what we have done in the present work.
In the present work, we have an old cadastral map (as a paper) was made in 1932
with modern satellite image (Quick Bird ) 2006, which has 61 cm resolution for the
same area after. Geometric correction technique has been applied by using image-toimage
method or (image registration ) and after that we get new agricultural cadaster
map and connect the
Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.
World statistics declare that aging has direct correlations with more and more health problems with comorbid conditions. As healthcare communities evolve with a massive amount of data at a faster pace, it is essential to predict, assist, and prevent diseases at the right time, especially for elders. Similarly, many researchers have discussed that elders suffer extensively due to chronic health conditions. This work was performed to review literature studies on prediction systems for various chronic illnesses of elderly people. Most of the reviewed papers proposed machine learning prediction models combined with, or without, other related intelligence techniques for chronic disease detection of elderly patie
... Show MoreIn recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
... Show MoreThe production of fission products during reactor operation has a very important effect on reactor reactivity .Results of neutron cross section evaluations are presented for the main product nuclides considered as being the most important for reactor calculation and burn-up consideration . Data from the main international libraries considered as containing the most up-to-date nuclear data and the latest experimental measurements are considered in the evaluation processes, we describe the evaluated cross sections of the fission product nuclides by making inter comparison of the data and point out the discrepancies among libraries.
This paper proposed a new method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA)) for measureing the closeness between curves. Root Mean Square Errors is used for the implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when the cov
... Show MoreMachine learning-based techniques are used widely for the classification of images into various categories. The advancement of Convolutional Neural Network (CNN) affects the field of computer vision on a large scale. It has been applied to classify and localize objects in images. Among the fields of applications of CNN, it has been applied to understand huge unstructured astronomical data being collected every second. Galaxies have diverse and complex shapes and their morphology carries fundamental information about the whole universe. Studying these galaxies has been a tremendous task for the researchers around the world. Researchers have already applied some basic CNN models to predict the morphological classes
... Show MoreThe intellectual property of digital documents has been protected by using many methods of digital watermarking. Digital documents have been so much of advantages over print documents. Digital documents are less expensive and easy to store, transport, and searched compared to traditional print documents. But it has its owner limitation too. A simple image editor can be used to modify and make a forged document. Digital documents can be tampered easily. In order to utilize the whole benefits of digital document, these limitations have to overcome these limitations by embedding some text, logo sequence that identifies the owner of the document..
In this research LSB technique has been used
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