Abstract A descriptive study using evaluation technique was carried at the health organizations concerning STIs/HIV/AIDS, mainly the AIDS Researches and Studies Center in Baghdad and many of the AIDS sections in the Health Directorates in the Governorates throughout the period of May 15th , 2003 through September 30th, 2003( to describe the surveillance system for the period 1993 through 2002). The study aimed to describe the STIs/HIV/AIDS surveillance system in Iraq. System evaluation questionnaire was adopted from WHO and developed for the purpose of this study. Content validity of questionnaire was established through a panel of 12 experts. Interobservor reliability method was carried out by two researchers to establish the reliability of the instrument and Cronbach’s alpha coefficient was computed for such reliability as (0.93). Data were collected through two ways, firstly from the documented information which was available in the health organizations concerning STIs/HIV/AIDS surveillance activities and secondly from the direct interview that was carried out with the health workers who are involved in the surveillance system. The data were analyzed through the application of descriptive statistical analysis (frequency and percentage). The study reveals that the activities of the surveillance system are covering all over the country through its distributed health facilities. The surveillance system is focusing on capture, control and prevent transmission of Syphilis, HIV and AIDS as a health events of devastating consequences on the patient and community. Also it succeeds in identification and coverage of the risk groups. National regulation notification of new HIV+ve case is very rapid to control the case and to protect the community . Control measures are so effective in preventing the transmission of these diseases. Three levels (Peripheral , Intermediate and Central) are identified to conduct the surveillance activities all over the country, through which special schedule of time is depending in reporting the information . Feedback among these levels is taking the forms of sessions, seminars for the staff involved in the surveillance, the community and field visits to the sentinel sites. The study recommended that high technical communication means may be depended in reporting . Lastly, surveillance is to be included as a subject in the curriculum of the Community Health Nursing as well as for Community Medicine for undergraduate and post-graduate students.
Solar tracking systems used are to increase the efficiency of the solar cells have attracted the attention of researchers recently due to the fact that the attention has been directed to the renewable energy sources. Solar tracking systems are of two types, Maximum Power Point Tracking (MPPT) and sun path tracking. Both types are studied briefly in this paper and a simple low cost sun path tracking system is designed using simple commercially available component. Measurements have been made for comparison between fixed and tracking system. The results have shown that the trackin
In this paper we deal with the problem of ciphering and useful from group isomorphism for construct public key cipher system, Where construction 1-EL- Gamal Algorithm. 2- key- exchange Algorithm
A security system can be defined as a method of providing a form of protection to any type of data. A sequential process must be performed in most of the security systems in order to achieve good protection. Authentication can be defined as a part of such sequential processes, which is utilized in order to verify the user permission to entree and utilize the system. There are several kinds of methods utilized, including knowledge, and biometric features. The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field. EEG has five major wave patterns, which are Delta, Theta, Alpha, Beta and Gamma. Every wave has five features which are amplitude, wavelength, period, speed and frequency. The linear
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
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One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,
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Worldwide, shipping documents are still primarily created and handled in the traditional paper manner. Processes taking place in shipping ports as a result are time-consuming and heavily dependent on paper. Shipping documents are particularly susceptible to paperwork fraud because they involve numerous parties with competing interests. With the aid of smart contracts, a distributed, shared, and append-only ledger provided by blockchain technology allows for the addition of new records. In order to increase maritime transport and port efficiency and promote economic development, this paper examines current maritime sector developments in Iraq and offers a paradigm to secure the management system based on a hyper-ledger fabric blockchain p
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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