Iraqi Journal of Information and communication technology

n this paper a new blind energy detection spectrum- sensing method based on Discreet Wavelet Transform (DWT) is proposed. The method utilizes the DWT sub-band to collect the received energy. The proposed method recognizes the Primary User (PU) signal from noise only signal by using the differences in the collected energy in first and last sub-bands of one DWT level. The simulation results show that in the AWGN channel, the proposed method improves detection probability by a factor of 40% at Signal to Noise Ratio (SNR) equals -13dB compared to Conventional Energy Detector (CED). Furthermore, the proposed method reduces the number of sensed samples to 50% on what in the traditional method. Thus, the proposed method achieves shorter sensing time and consumes lower Energy which makes it suitable for Cognitive Radio ( CR) applications where only limited energy like device battery is available

Cardiovascular Diseases (CVDs) are consider main cause of death today a according to World Health Organization (WHO). Because ECG signal is very important tool in monitoring and diagnosis of these disease ,different automatic methods are proposed based on this signal. The manual analysis of ECG signals is suffered different challenges such as differeculty of detecting and classify waveform of this signal, So, many machine learning methods are explored to describe the anomalies ECG signal accurately . Deep learning (DL) can be used in ECG classification, it can improve the quality of the automatic classification system. In this paper , We have proposed a deep learning classification system using different layers of convolution, rectifier and pooling operations that can be used to increase feature extraction of ECG signal. We have proposed two models, one is used 1-D signal , in which we designed model for classification csv type of data for ECG signal, while in the second proposed system, we used model for 2-D signal after convert it from its csv type . 2-D signal (ECG image) is used in order to augment the two dimensional signal with different methods to increase the accuracy of the model by training it with geometric transformation of the original input images such as rotation, shearing etc. The results are compared with Alex Net and other models based on different metrics, which are used to measure performance of proposed work, the result show that, proposed models improves efficiency of the classification in the two systems

The growth of information technology lead to increasing number of users for various types of electronic equipment that resulted in the rise of cybercrime. Increasing cybercrime lead to increasing volume of digital evidence handled by the investigators; that mean more documentation, complexity of management and complexity to keep its integrity. So that, a significant procedure in handling of evidence and investigation is called as a chain of custody(CoC) , which a concept and process designed to ensure the integrity of evidence including digital evidence (DE)and to document the digital evidence from the time it collected to the time where the evidence actually presented at the court. Without a chain of custody, the evidence is valueless so that it played a vital role in the digital forensic investigation process. The solution offered in this paper is to build a Digital chain of custody application software in order to ensure the integrity and originality of digital evidence also to document these evidences from various types of digital evidence file such as network packet capture files, disk image files, extracted document files, multimedia files and more. The application is constructed through four approaches to keep the integrity of evidence: applying Hash function for each evidence and save the information in XML file, watermarking, extract metadata for each evidence and specify a geolocation for each evidence. Also, there is a privilege for users to access the application, no one can access the application without admin permission. There are two types of the chain of custody information, which are the information entered by the user and information extracted from the metadata of digital evidence file. The output from a chain of custody application is a form in the .pdf document format

Smart city deals with the developments of many services related to energy, environmental, and health care. It is also continuously providing new services to all citizens. This paper is concerned with the design and implementation of smart meter system as the core for smart grid in smart city. A system is proposed where the electricity supply is monitored by measuring its related parameters such as voltage, current, power, energy consumption, and consumption bill. Short Message Service (SMS) representing such parameters are issued by the system for notification and control. The designed system used PZEM- 004T, Arduino Mega, Raspberry Pi and Node-Red platforms to implement smart meter system. The data related to the measured parameters are successfully transmitted to the data center using Message Queuing Telemetry Transport (MQTT) protocol, stored in MySQL data base using core python program, and displayed on Node- Red platform. The test and verification of the system are performed using different scenarios showing that successful and accurate operation of the system components are achieved. The implemented system is successfully measured the related parameters (voltage, current, power and energy consumption) and these are sent to data center using MQTT protocol together with SMS containing the monthly bill to the subscribers