Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The study included the determination of pollen grains features for 8 genera and 13 taxa of Mimosoideae subfamily grown in Baghdad/ Iraq by using each of light and scanning electron microscope. The samples of taxa were collected from various sites in Baghdad province in central Iraq located on 32 45° 0-33 45 0 N and 44 0 0- 44° 45 0 E. the results from this study revealed different pollen types as monad in each of Leucaena, Prosopis, and Neltuma, tetrad in Mimosa and polyads in Acacia, Albizia, Calliandra, Pithecellobium and Vachellia. Each taxa of these genera characterized by special palynological features as shape, size, number of polyads grain and conplateuration as well as other parameters included other dimensions, and these

I came back and made my jewelery from the first research or studies known to man, and the oldest era and confirmed the problem of searching for the links of sweets and admiration of the magnificence of the effectiveness of the search for the importance of preserving the heritage of the Iraqi civilization in its original creative aspects. Metal in Iraq, Head Costume, Neck Costume, Party Costume (Hands and Legs). The main results of the research were;

1-Contemporary folk jewelry in Iraq was characterized by design units for use.

Dependence in the feed industry in the form of laboratory mold.

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

     NS-2 is a tool to simulate networks and events that occur per packet sequentially based on time and are widely used in the research field. NS-2 comes with NAM (Network Animator) that produces a visual representation it also supports several simulation protocols. The network can be tested end-to-end. This test includes data transmission, delay, jitter, packet-loss ratio and throughput. The Performance Analysis simulates a virtual network and tests for transport layer protocols at the same time with variable data and analyzes simulation results based on the network simulator NS-2.