In this research, we propose to use two local search methods (LSM's); Particle Swarm Optimization (PSO) and the Bees Algorithm (BA) to solve Multi-Criteria Travelling Salesman Problem (MCTSP) to obtain the best efficient solutions. The generating process of the population of the proposed LSM's may be randomly obtained or by adding some initial solutions obtained from some efficient heuristic methods. The obtained solutions of the PSO and BA are compared with the solutions of the exact methods (complete enumeration and branch and bound methods) and some heuristic methods. The results proved the efficiency of PSO and BA methods for a large number of nodes ( ). The proposed LSM's give the best efficient solutions for the MCTSP for

   To deduct the childhood status in Iraq, it was important manner to use statistical tools and approaches concerned with interpreting the causal relationships and their attitudes and use classification method for the important effects (variables) to draw an obvious picture of the phenomena under study in order to make it useful through investing, updating and improving it in by demographic studies in the future. Two statistical methods had been used in the field of analyzing data of multivariate analysis namely, Cluster Analysis and Factor Analysis.  

The present study focuses on four fundamental axes .The nutrition axis, health axis, Educational axis, and the social axis. The study has ca

     One major problem facing some environments, such as insurance companies and government institutions, is when a massive amount of documents has to be processed every day. Thus, an automatic stamp recognition system is necessary. The extraction and recognition of a general stamp is not a simple task because it may have various shapes, sizes, backgrounds, patterns, and colors. Moreover, the stamp can be printed on documents with bad quality and rotation with various angles. Our proposed method presents a new approach for the preprocessing and recognition of color stamp images. It consists of four stages, which are stamp extraction, preprocessing, feature extraction, and matching. Stamp extraction is achieved to isol

Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p

The present work is an attempt to develop design data for an Iraqi roof and wall constructions using the latest ASHRAE Radiant Time Series (RTS) cooling load calculation method. The work involves calculation of cooling load theoretically by introducing the design data for Iraq, and verifies the results experimentally by field measurements. Technical specifications of Iraqi construction materials are used to derive the conduction time factors that needed in RTS method calculations. Special software published by Oklahoma state university is used to extract the conduction factors according to the technical specifications of Iraqi construction materials.  Good agreement between the average theoretical and measured cooli

               In this research, the semiparametric Bayesian method is compared with the classical  method to  estimate reliability function of three  systems :  k-out of-n system, series system, and parallel system. Each system consists of three components, the first one represents the composite parametric in which failure times distributed as exponential, whereas the second and the third components are nonparametric ones in which reliability estimations depend on Kernel method using two methods to estimate bandwidth parameter h method and Kaplan-Meier method. To indicate a better method for system reliability function estimation, it has be

This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward