Iraqi Journal of Intelligent Computing and Informatics

Data protection and security is one of the important issues at the present time. Because of the development of methods of data penetration and manipulation, it is necessary to find alternative ways to protect sensitive data from these violationsand storedin a secure manner. A complete system has been provided for the purpose of enhanced security for storingIraqi national cards that issues to the citizens based on the blockchain technology. This study aims to protect the sensitive data of the government from violations by using blockchain technique. The proposed method detects fraud and data alteration and protect the transmitted data between the nodes and the serverby encryption the data using Schnorr Digital Signature to guarntie the confidentiality, besides detection of any alter in data stored in nodes by using hash function (SHA 256) to guarantie the integrity of data. The method is evaluation using Scyther to test the security of the traditional method and the proposed method. As a result the proposed method provide high security

As it is known, making a successful decisions is not an easy task, because these decisions affect by many circumstances and depend on set of factors. It is necessary that the decision-making in colleges must be subject to the voting of the members of the college council. The traditional way for issuance the decision can be computed through counting the voters. There are three options for voting: agree, disagree, or conservative. This kind of voting ignores various degrees of opinions and preferences. Some situations that require decision making are difficult because they have uncertain and fuzzy environments. This paper aims to use a new method for making the decision in the college, depending on a fuzzy decision scheme. This work uses data from four colleges to evaluate the projects that will be implemented. Data collection was accomplished by using a table of preferences and presenting it to the College Council members to give their opinions. The preferences table provides various degrees of opinions instead of the traditional method. Exploiting the Multi-Criteria Decision Making (MCDM) in a fuzzy method requires using different mechanisms for ranking the alternatives according to their importance. Evaluation of the results will determine which one of the alternatives or the criteria has more importance comparing with the others. The results prove that Fuzzy Linguist Preferences can solve many real problems.This work gives the total process about howto solve multiple alternatives decision making problems using analytic hierarchical process in fuzzy and builds a fuzzy evaluating scheme which prioritized the relative weights of the alternatives.

Wireless Sensor Networks (WSNs) are crucial in various applications, including smart homes, military surveillance, health monitoring, and environmental sensing. These networks consist of distributed sensor nodes that collect and transmit environmental data to a central location for processing. However, WSNs face challenges such as limited energy resources, scalability, complexity, security, fault tolerance, and quality of service. Researchers have proposed different routing protocols tailored to WSN characteristics to address these issues. This article comprehensively overviews WSN design issues, focusing on routing protocol classification and comparative analysis. Among the hierarchical protocols, LEACH (Low-Energy Adaptive Clustering Hierarchy) is highlighted as a prominent clustering-based protocol that reduces energy consumption by forming clusters and utilizing cluster heads for data aggregation. Each addresses specific challenges and enhances network performance.The comparative analysis evaluates the protocols based on energy efficiency, network lifetime, data delivery, scalability, and security. The findings help researchers, practitioners, and network designers select appropriate routing protocols for their specific WSN applications. This article offers valuable insights into WSN design issues and presents a comprehensive classification and comparison of routing protocols. By understanding the strengths and limitations of different protocols.

Encryption is regarded as essential within the safety measures used to protect data via unsafe transport methods. Elliptic Curve encryption (ECC), one of the several asymmetric encryption algorithms currently in use, has become popular because of its high level of security and small key sizes. In contrast to Rivest, Shamir and Adleman (RSA), for instance, ECC can keep security levels at a certain level with a smaller key. The primary purpose of ECC is elliptic curve point multiply (ECPM), which also has the largest hardware cost. Numerous hardware applications have been made to accelerate the calculus of the ECPM. This paper discusses the idea behind the cryptography of elliptic curves (ECC's) and the benefits it quicker, moreover believed way of encoding as compared to the RSA public_key encryption techniques that are currently used as standards. ECC's specifications encompass all relevant asymmetry cryptography elements, including electronic signatures & key negotiation processes. The scalar multiplication Key Point (K.P)function, which is the fundamental operation of ECCs, is utilized to accomplish this objective. Where P is a value and k represents an integer and is exists on an elliptic curve. This article explains how ECC contributes to system safety and applications of it in the field of security

Service institutions are considered one of the most important institutions in our time, and they have become a great place in our lives The health institutions are considered the most important, because they provide many types of necessary health services And related to the safety of the health of individuals, and through cooperation between the academic study and the health sector, which was represented by Khanaqeen General Hospital, where this research paper presented a proposal hospital management system project is primarily focused on managing medical-related records within a hospital. More precisely, this system helps track medical reports. The system also displays all available employees and patients. In additionally, the system can aggregate inventory and pharmacy records, this system consists of two major sections: databasestructure, and GUI (Graphical User Interface) frames (created in environments utilizing PHP, HTML, and CSS).The database constructed with MYSQL and the GUI frame make it easier for novice users to utilize the suggested system.at the latest this paper describes a hospital management system that can be used to manage and analyze hospital information related to patients, treatments, and sales. The practical implications of this system are:It can help hospitals to manage their operations more efficiently by providing a centralized system for managing patient information, treatment records, The system can be of assistance hospital administrators to make data-driven decisions by providing them with real-time information about hospital operations, and improve patient care by providing doctors and nurses with easy access to patient information and treatment records, The system can be beneficial to reduce errors and improve accuracy by automating many of the manual processes involved in managing hospital information.Overall, the HMS described in this paper has the ability to increase efficiency,accuracy, and quality of hospital operations, which can ultimately lead to better patient outcomes

Accurate assessment of mosquito population density is crucial for the efficient management of mosquito-borne diseases such as malaria and dengue in areas affected by these vectors. Nevertheless, the traditional approach of manually counting and classifying mosquitoes through the use of traps is both laborious and expensive. This research paper presents a proposed pipeline for the identification and categorization of mosquitoes from photographs, specifically designed for low-cost Internet of Things (IoT) sensors. The pipeline aims to achieve a balance between accuracy and efficiency. Through the process of fine-tuning conventional machine learning models such as VGG16, RESNET50, and Convolutional Neural Network (CNN), a notable level of accuracy of 98% is attained. The present study highlights the potential of integrating a highly effective mosquito detection device with a convolutional neural network to offer a viable balance between precision and efficiency in the realm of mosquito identification, categorization, and quantification. Consequently, this approach has promise for improving the control and prevention of mosquito-borne illnesses.

Iraq is considered one of the first countries in the world to export Dates of all kinds. This sector at present needs support and serious work to improve sales to provide the country's economy with more revenues. This study proposes building an integrated artificial intelligence model that predicts the quantities of Dates that Iraq will produce in the coming years based on previous data and based on two main points: The first point is to make a comparison between three different food datasets with a different correlation between their features, as the first dataset is of high correlation, the second is of medium correlation, and the third is of weak correlation. The second point is to apply twelve Machine Learning algorithms and evaluate their results to obtain the best three algorithms. The model was applied to predict the quantities of Dates that Iraq will produce for the next five years. The proposed three algorithms were used and gave the following results: (Gradient Boosting: 99.51, Random Forest: 97.05, and Bagging Regressor: 98.54). This study constitutes a starting point for future studies in terms of the process of choosing the datasets, as well as the machine learning technique.

Technological development develops every second increasing text data, especially the Arabic texts on the internet. These Arabic data are massive but it is not useful for use because it is unstructured data and it can’t be used for natural language processing (NLP) and its applications. The increase of Arabic language texts on the Internet has led to an increase in Arabic lexicon web pages but it is not ready for use by NLP applications because it is semi-structured or even unstructured lexicons. The method used in this study is web scraping for scrap data from the internet and converting data from unstructured to structured data. This study aims to build an automatic structured Arabic lexicon ready for NLP and its applications using web scraping. which increases the opportunity to use the Arabic language more widely, which is of great importance in natural language processing applications