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Security In Wireless Sensor Networks Based On Lightweight Algorithms : An Effective Survey
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At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance penalty. Due to the massive calculations required by conventional public-key and secret encryption methods, information security in this limited context calls for light encryption techniques. In many applications involving sensor networks, security is a crucial concern. On the basis of traditional cryptography, a number of security procedures are created for wireless sensor networks. Some symmetric-key encryption techniques used in sensor network setups include AES, RC5, SkipJack, and XXTEA. These algorithms do, however, have several flaws of their own, including being susceptible to chosen-plaintext assault, brute force attack, and computational complexity.

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Publication Date
Sun Dec 01 2013
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
THE FAUNISTIC SURVEY OF LADY BEETLES (COLEOPTERA, COCCINELLIDAE) IN THE MEHRIZ REGION(YAZD PROVINCE), IRAN
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  In this study the faunistic of lady beetles (Coleoptera, Coccinellidae) was studied in Mehriz region (Yazd province) during 2009-2010. The total number of specimens of coccinellid beetles were collected from 6 different localities having altitudes from 1420-2420 m. Altogether 11 species from 8 genera, 3 tribes and 3 subfamilies were collected and identified. External characters plus characteristics male and female genitalia were used in order to diagnose species. Seven species were recorded for the first time from Yazd province (marked*). Many species were predacious, preying on various species of aphids, mites and coccids. Some species were also sent to Dr. Helmut Fursch in Germany for identification or confirmation. T

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Publication Date
Wed Dec 28 2022
Journal Name
Al–bahith Al–a'alami
Effectiveness of Digital journalism in developing political awareness among Iraqi feminist activists "A survey study"
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The paper aims to reveal the effectiveness of digital journalism in developing political awareness among Iraqi feminist activists. This paper is descriptive, and it adopted the analytical descriptive survey method. A snowball sample composed of (102) respondents of Iraqi feminist activists was adopted and questionnaire was used to collect data. The research has reached the following conclusions: The rate of Iraqi Feminist Activists dependence on digital Journalism have increased; to develop their political awareness, and their preference - in this regard - (the pages of journalistic institutions to social media) in a way that exceeds other types of digital journalism. (Variety of languages) has topped the priorities of Iraqi feminist act

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Publication Date
Fri Oct 02 2026
Journal Name
Albahith Alalami
Tendencies of Scientific Research in the Specialized Journalism the Media Researcher Magazine A survey study
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Publication Date
Thu Jan 15 2009
Journal Name
Basrah Journal For Date Palm Research 8 (1), 64-71‏
Survey study of ten rare cultivars of Date Palm Phoenix dactylifera L. in Basrah city‏
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Comprehensive Review on Medical Image Steganography Based on LSB Technique and Potential Challenges
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The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in

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Publication Date
Thu Jun 23 2022
Journal Name
American Scientific Research Journal For Engineering, Technology, And Sciences
A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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Publication Date
Mon Dec 28 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
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The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks
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To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

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Publication Date
Fri Aug 01 2025
Journal Name
Journal Of Communications
Deep Reinforcement Learning for Dynamic Routing, Modulation, and Spectrum Assignment in Elastic Optical Networks
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