Localization is an essential issue in pervasive computing application. FM performs worse in some indoor environment when its structure is same to some extent the outdoor environment like shopping mall. Furthermore, FM signal are less varied over time, low power consumption and less effected by human and small object presence when it compared to Wi-Fi. Consequently, this paper focuses on FM radio signal technique and its characteristics that make it suitable to be used for indoor localization, its benefits, areas of applications and limitations.

A new technique for embedding image data into another BMP image data is presented. The image data to be embedded is referred to as signature image, while the image into which the signature image is embedded is referred as host image. The host and the signature images are first partitioned into 8x8 blocks, discrete cosine transformed “DCT”, only significant coefficients are retained, the retained coefficients then inserted in the transformed block in a forward and backward zigzag scan direction. The result then inversely transformed and presented as a BMP image file. The peak signal-to-noise ratio (PSNR) is exploited to evaluate the objective visual quality of the host image compared with the original image.

In this research we will present the signature as a key to the biometric authentication technique. I shall use moment invariants as a tool to make a decision about any signature which is belonging to the certain person or not. Eighteen voluntaries give 108 signatures as a sample to test the proposed system, six samples belong to each person were taken. Moment invariants are used to build a feature vector stored in this system. Euclidean distance measure used to compute the distance between the specific signatures of persons saved in this system and with new sample acquired to same persons for making decision about the new signature. Each signature is acquired by scanner in jpg format with 300DPI. Matlab used to implement this system.

Background: Congenital adrenal hyperplasia is a family of autosomal recessive disorders of cortisol biosynthesis. Depending on the enzymatic step that is deficient, there may be signs, symptoms, and laboratory findings of mineralocorticoid deficiency or excess; incomplete virilization or premature puberty in affected males; and virilization or sexual infantilism in affected females. The most frequent is 21-hydroxylase enzyme deficiency, accounting for more than 90% of cases.
Objectives: to review cases of congenital adrenal hyperplasia registered in children welfare teaching hospital- medical city- Baghdad.
Patients and method: This study included all patients who were presented and registered in the e

Background: Lymphoblastic lymphomas (LBL) are neoplasms of precursor T cells and B cells, or lymphoblasts. The term lymphoblastic lymphoma has been used to describe predominantly lymph node– based disease; however, clinical distinction between LBL and acute lymphoblastic leukemia (ALL) has been arbitrary and has varied among different studies and institutions
Objectives: To determine the frequency of LBL among all Non-Hodgkin’s lymphoma (NHL) patients in children and to study the clinical and pathological features of LBL and assess the treatment outcome.
Methods: A retrospective study included 28 children with newly diagnosed LBL (based on morphology) below the age of 14 years over 8 years period from J

Coumarins have been recognized as anticancer competitors. HDACis are one of the interesting issues in the field of antitumor research. In order to achieve an increased anticancer efficacy, a series of hybrid compounds bearing coumarin scaffolds have been designed and synthesized as novel HDACis, In this review we present a series of novel HDAC inhibitors comprising coumarin as a core e of cap group of HDAC inhibitors that have been designed, synthesized and assessed for their enzyme inhibitory activity as well as antiproliferative activity. Most of them exhibited potent HDAC inhibitory activity and significant cytotoxicity

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Background: Periodontitis is a long-standing infection that destroys the gums, periodontal ligaments, and the alveolar bone that supports the teeth. Inflammation of the gums and chronic periodontitis are both caused by the bacteria in the dental plaque and the herpes viruses, especially types 1 and 2 of the herpes simplex virus.

Objectives: To compare the ELISA and real-time PCR as ways to detect the herpes simplex virus in breast cancer pat