Journal of University of Babylon

The system of Home Automation consider nowadays as a promise technology for living a comfortable life and minimizing the cost of the user homeowner. The system might be accomplished by controlling the heating, ventilation, air conditioning, shading, and lightening. The energy consumed efficiency is get better also the protection system is exists. In this work, a Home Automation System is proposed, so that it performs automatically controlling to some of the appliances in the home. In addition, the proposed system will discover any undesirable movement or fire when the person is out of his home by taking a suitable decision instead of homeowner.
The control unit uses a Smart Phone (Android Mobile). In this work, to gather readings of movements, heating, and lightening, a number of nodes are used (three nodes). Also a Microcontroller uses especial sensors to collect this information, after that sends them wirelessly through WIFI to the Smart Phone for manipulation and taking a convenience decision. Delta Neural Network Learning Rule is use for the first time as the intelligent algorithm to give the decisions for all the readings of sensors, so that it learned after 113259 which take 2280 seconds. In addition, it turns out the automated system to be further smart such that if there is fire or movement into the house, the application will distinguish if this movement for example dangerous or not. The mobile (through the application) then gives a command to send a message (GSM) to the homeowner (Police, or fire station) telling the new situation. Furthermore, the controlling of all convenient appliances at the home automatically for each state.
JAVA Program is use for manipulation process, and then by employing Eclipse Juno IDE program it turn into to an android application that installed into the Mobile. The Microcontroller is Arduino with WIFI shield and Xbee.

In this paper a new approach of rough set features selection has been proposed. Feature selection has been used for several reasons a) decrease time of prediction b) feature possibly is not found c) present of feature case bad prediction. Rough set has been used to select most significant features. The proposed rough set has been applied on heart diseases data sets. The main problem is how to predict patient has heart disease or not depend on given features. The problem is challenge, because it cannot determine decision directly .Rough set has been modified to get attributes for prediction by ignored unnecessary and bad features. Bayes net has been used for classified method. 10-fold cross validation is used for evaluation. The Correct Classified Instances were 82.17, 83.49, and 74.58 when use full, 12, 7 length of attributes respectively. Traditional rough set has been applied, the minimum Correct Classified Instances were 58.41 and 81.51 when use 2 length of attributes respectively.

The system of Home Automation consider nowadays as a promise technology for living a comfortable life and minimizing the cost of the user homeowner. The system might be accomplished by controlling the heating, ventilation, air conditioning, shading, and lightening. The energy consumed efficiency is get better also the protection system is exists. In this work, a Home Automation System is proposed, so that it performs automatically controlling to some of the appliances in the home. In addition, the proposed system will discover any undesirable movement or fire when the person is out of his home by taking a suitable decision instead of homeowner.
The control unit uses a Smart Phone (Android Mobile). In this work, to gather readings of movements, heating, and lightening, a number of nodes are used (three nodes). Also a Microcontroller uses especial sensors to collect this information, after that sends them wirelessly through WIFI to the Smart Phone for manipulation and taking a convenience decision. Delta Neural Network Learning Rule is use for the first time as the intelligent algorithm to give the decisions for all the readings of sensors, so that it learned after 113259 which take 2280 seconds. In addition, it turns out the automated system to be further smart such that if there is fire or movement into the house, the application will distinguish if this movement for example dangerous or not. The mobile (through the application) then gives a command to send a message (GSM) to the homeowner (Police, or fire station) telling the new situation. Furthermore, the controlling of all convenient appliances at the home automatically for each state.
JAVA Program is use for manipulation process, and then by employing Eclipse Juno IDE program it turn into to an android application that installed into the Mobile. The Microcontroller is Arduino with WIFI shield and Xbee.

Nowadays cloud computing had become is an integral part of IT industry, cloud computing provides Working environment allow a user of environmental to share data and resources over the internet. Where cloud computing its virtual grouping of resources offered over the internet, this lead to different matters related to the security and privacy in cloud computing. And therefore, create intrusion detection very important to detect outsider and insider intruders of cloud computing with high detection rate and low false positive alarm in the cloud environment. This work proposed network intrusion detection module using fuzzy c mean algorithm. The kdd99 dataset used for experiments .the proposed system characterized by a high detection rate with low false positive alarm.

The proposed research Provides an approach for hiding an encrypted text in side a digital image. Where the text is encrypted in a complex manner used method of PlayFair to encrypt clear text and to increase security put lettering ciphertext on the geometric shape clockwise and then we write the ciphertext output in the form of lines, taken new ciphertext and converted to Ascii code and then to binary and hidden text in bits least importance in the picture. The results were good by PNSR scale.

Intelligent Hypothermia Care System (IHCS) is an intelligence system uses set of methodologies, algorithms, architectures and processes to determine where patients in a postoperative recovery area must be sent. Hypothermia is a significant concern after surgery. This paper utilizes the classification task in data mining to propose an intelligent technique to predict where to send a patient after surgery: intensive care unit, general floor or home. To achieve this goal, this paper evaluates the performance of decision tree algorithm, exemplifying the deterministic approach, against the AntMiner algorithm, exemplifying the heuristic approach, to choose the best approach in detecting the patient’s status. Results show the outperformance of the heuristic approach. The implication of this proposal will be twofold: in hypothermia treatment and in the application of ant colony optimization.

Intelligent Hypothermia Care System (IHCS) is an intelligence system uses set of methodologies, algorithms, architectures and processes to determine where patients in a postoperative recovery area must be sent. Hypothermia is a significant concern after surgery. This paper utilizes the classification task in data mining to propose an intelligent technique to predict where to send a patient after surgery: intensive care unit, general floor or home. To achieve this goal, this paper evaluates the performance of decision tree algorithm, exemplifying the deterministic approach, against the AntMiner algorithm, exemplifying the heuristic approach, to choose the best approach in detecting the patient’s status. Results show the outperformance of the heuristic approach. The implication of this proposal will be twofold: in hypothermia treatment and in the application of ant colony optimization.

Investigation of medical images have major consequence in the field of treatment.in this work ,MR images have been used to distinguish the normal brain from brain with Alzheimer disease .Texture is an native property of all surfaces it contains important facts about the structural organization of the surfaces and their connections neighboring area. In direction to classify texture must be segmented into a number of section that has the similar properties, for this purpose we used k- means algorithm with GLCM for feature extraction ,finally we used k-nearest neighbor algorithm to distinguish between normal and abnormal brain.

Maintaining the confidentiality of the data of the very important areas in computer applications , Where many researchers work in the fields of concealment and encryption . So in this research we are working on the combining of the two methods , where confidential data is encrypted by using a proposed method , Then the cover is encrypted (regular image) by LCG algorithm (which generates a series of random numbers) to generate the encrypted cover (irregular image) , After that ,we hide the encrypted data in encrypted cover by depending on the LSB technique, then we convert the irregular image into regular image and thereby getting hidden data in random locations in the cover image , This method is characterized by flexibility in terms of the possibility of hiding the different types of confidential data in different types of media , and durability as that data be hidden in random locations and this what distinguishes the proposed algorithm , and the results showed high security, because the data is hidden in random locations in encrypted image then convert to the original regular image For clarification of the proposed algorithm , it has been applied on a digital image of the gray type using MATLAB language by using the efficiency scales PSNR and MSE .

In this research, we introduced the exponentiated transmuted exponential (ETE) distribution. This distribution is more flexible than some distributions so we investigate some of its properties. As well as studying the maximum likelihood estimation of this distribution

To identify diagnostic utilities of Anti citrullinated protein (ACCP) and Rheumatoid factor (RF) are autoantibodies (Abs directly against an self-individual antigens), Analytical study. The questioner reported for 50 patients with RA were collected from Department of Rheumatology¸ AL˗Sader Teaching Hospital. Serum levels of RF & (ACCP) Abs were determinated by enzyme ˗ linked immunosorbent assay”, while the level of erythrocyte sedimentation rate (ESR) was determined by westergreen method. Distribution of RA occur in females more than males which reached (80%) & (20%) respectively according to the patients group. The patients divided according to the age into three groups (<30)¸ (30˗50) & (>50). The percent for these groups were (16%)¸ (52%) & (32%). Among the 50 patients with RA¸ CCP and ESR 49 patients (98%) tested positive for (ACCP) antibodies¸ and 22 patients (44%) tested positive for RF. and 37 patients(74% ) tested increasing levels of ESR in RA patients. The mean value of (ACCP) & ESR shows highly significance (P<0∙05), while the RF serum levels increase significantly. Demonstrate the (ACCP) antibodies assay is a useful test for diagnosing RA. However, the use of RF and (ACCP)auto- antibodies in combination further elevated the diagnostic value for RA.

The present study was aimed to assess the effects of antiandrogen flutamide on some histological and morphometric cerebrum and cerebellum tissue for white albino rats, Twenty five male rats were divided into five groups each group contains 5 animals, the first and second group regarded as positive and negative control, respectively, while the other groups was treated with flutamide drug orally for 28 days at concentrations of (8, 12, 25 mg/kg/day). Histopathological results revealed that there is a significant increase in cell number of outer granular layers in cerebrum of the groups treated with 25 mg/kg/day compared to positive and negative control group as well as with other treated groups cerebrum, also the results of histopathological pointed that there were no significant differences in cerebellum tissue in all treated groups .
The morphometric results showed that there were no significant differences in thickness of cerebellar layers among different groups , therefore antiandrogen flutamide can be considered as a testosterone modulator. To determine more precise effect of flutamide on the brain, further studies are needed.

The present study was aimed to assess the effects of antiandrogen flutamide on some histological and morphometric cerebrum and cerebellum tissue for white albino rats, Twenty five male rats were divided into five groups each group contains 5 animals, the first and second group regarded as positive and negative control, respectively, while the other groups was treated with flutamide drug orally for 28 days at concentrations of (8, 12, 25 mg/kg/day). Histopathological results revealed that there is a significant increase in cell number of outer granular layers in cerebrum of the groups treated with 25 mg/kg/day compared to positive and negative control group as well as with other treated groups cerebrum, also the results of histopathological pointed that there were no significant differences in cerebellum tissue in all treated groups .
The morphometric results showed that there were no significant differences in thickness of cerebellar layers among different groups , therefore antiandrogen flutamide can be considered as a testosterone modulator. To determine more precise effect of flutamide on the brain, further studies are needed.

Infection with Helicobacter pylori is associated with the development of different gastric disorders. Clinical outcome of H. pylori infection related to virulence factors that encoded by genes of this bacteria that can be used in a molecular detection such as the housekeeping genes; ureA and ureC. 16S rRNA is also used in bacterial diagnosis.
Seventy-five patients with dyspeptic symptoms sent to esophago- gastroduodenal scope (OGD) unit at Merjan Hospital in Babylon Province. They were diagnosed by specialist physicians and selected in the current study and were classified 43 patients had gastritis, 23 patients had peptic ulcer disease(PUD), 3 had growth like mass non cancer and 6 were normal as negative control.
The results of multiplex PCR and monoplex PCR revealed that a total of 49 (65.3%) cases were found positive for H. pylori by 16S rRNA and ureA, whereas ureC primer is less sensitive for bacterial detection.