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M A Modified Similarity Measure for Improving Accuracy of User-Based Collaborative Filtering: Nadia Fadhil
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Production sites suffer from idle in marketing of their products because of the lack in the efficient systems that analyze and track the evaluation of customers to products; therefore some products remain untargeted despite their good quality. This research aims to build a modest model intended to take two aspects into considerations. The first aspect is diagnosing dependable users on the site depending on the number of products evaluated and the user's positive impact on rating. The second aspect is diagnosing products with low weights (unknown) to be generated and recommended to users depending on logarithm equation and the number of co-rated users. Collaborative filtering is one of the most knowledge discovery techniques used positively in recommendation system. Similarity measures are the core operations in collaborative filtering; however, there is a certain deviance through using traditional similarity measures, which decreases the recommendation accuracy. Thus, the proposed model consists of a combination of measures: constraint Pearson correlation, jaccard distance measure and inverse user frequency (IUF).

     The experimental results implemented on movielens data set using MATLAB show a comparison between the results of the proposed model and some of the traditional similarity measures. The outcome results of the comparison show that the proposed model can be used as a parameter in the prediction process to achieve accurate prediction results during recommendation process.

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Machine Learning Based Crop Yield Prediction Model in Rajasthan Region of India
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     The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mea

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Publication Date
Wed Jul 01 2020
Journal Name
2020 42nd Annual International Conference Of The Ieee Engineering In Medicine & Biology Society (embc)
Recurrent Fusion of Time-Domain Descriptors Improves EMG-based Hand Movement Recognition
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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Proposed Hybrid Technique in Cryptanalysis of Cryptosystem Based on PSO and SA
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     Modern ciphers are one of the more difficult to break cipher systems because these ciphers high security, high speed, non - propagation error and difficulty in breaking it. One of the most important weaknesses of stream cipher is a matching or correlation between the output key-stream and the output of shift registers.

     This work considers new investigation methods for cryptanalysis stream cipher using ciphertext only attack depending on Particle Swarm Optimization (PSO) for the automatic extraction for the key. It also introduces a cryptanalysis system based on PSO with suggestion for enhancement of the performance of PSO, by using Simulated Annealing (SA). Additionally, it presents a comparison for the cryptanal

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Proposed Hybrid Cryptosystems Based on Modifications of Playfair Cipher and RSA Cryptosystem
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Cipher security is becoming an important step when transmitting important information through networks. The algorithms of cryptography play major roles in providing security and avoiding hacker attacks. In this work two hybrid cryptosystems have been proposed, that combine a modification of the symmetric cryptosystem Playfair cipher called the modified Playfair cipher and two modifications of the asymmetric cryptosystem RSA called the square of RSA technique and the square RSA with Chinese remainder theorem technique. The proposed hybrid cryptosystems have two layers of encryption and decryption. In the first layer the plaintext is encrypted using modified Playfair to get the cipher text, this cipher text will be encrypted using squared

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
Diagnosis and Classification of Type II Diabetes based on Multilayer Neural Network
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     Diabetes is considered by the World Health Organization (WHO) as a main health problem globally. In recent years, the incidence of Type II diabetes mellitus was increased significantly due to metabolic disorders caused by malfunction in insulin secretion. It might result in various diseases, such as kidney failure, stroke, heart attacks, nerve damage, and damage in eye retina. Therefore, early diagnosis and classification of Type II diabetes is significant to help physician assessments.

The proposed model is based on Multilayer Neural Network using a dataset of Iraqi diabetes patients obtained from the Specialized Center for Endocrine Glands and Diabetes Diseases. The investigation includes 282 samples, o

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Generating Streams of Random Key Based on Image Chaos and Genetic Algorithm
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    Today the Genetic Algorithm (GA) tops all the standard algorithms in solving complex nonlinear equations based on the laws of nature. However, permute convergence is considered one of the most significant drawbacks of GA, which is known as increasing the number of iterations needed to achieve a global optimum. To address this shortcoming, this paper proposes a new GA based on chaotic systems. In GA processes, we use the logistic map and the Linear Feedback Shift Register (LFSR) to generate chaotic values to use instead of each step requiring random values. The Chaos Genetic Algorithm (CGA) avoids local convergence more frequently than the traditional GA due to its diversity. The concept is using chaotic sequences with LFSR to gene

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Publication Date
Mon Sep 03 2012
Journal Name
The International Archives Of The Photogrammetry, Remote Sensing And Spatial Information Sciences
CALIBRATION OF FULL-WAVEFORM ALS DATA BASED ON ROBUST INCIDENCE ANGLE ESTIMATION
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Abstract. Full-waveform airborne laser scanning data has shown its potential to enhance available segmentation and classification approaches through the additional information it can provide. However, this additional information is unable to directly provide a valid physical representation of surface features due to many variables affecting the backscattered energy during travel between the sensor and the target. Effectively, this delivers a mis-match between signals from overlapping flightlines. Therefore direct use of this information is not recommended without the adoption of a comprehensive radiometric calibration strategy that accounts for all these effects. This paper presents a practical and reliable radiometric calibration r

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Investigation of Optimum Heat Flux Profile Based on the Boiling Safety Factor
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An experimental study is conducted to investigate the effect of heat flux distribution on the boiling safety factor of its cooling channel. The water is allowed to flow in a horizontal circular pipe whose outlet surface is subjected to different heat flux profiles. Four types of heat flux distribution profiles are used during experiments: (constant distribution profile, type a, triangle distribution profile with its maximum in channel center, type b, triangle distribution profile with its maximum in the channel inlet, type c, and triangle distribution profile with its maximum in the channel outlet, type d). The study is conducted using heat sources of (1000 and 2665W), water flow rates of (5, 7 and 9 lit/min). The water

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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
BER Performance Improvement of Dual Chaotic Maps Based on STBC Communication System
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Sensitive information of any multimedia must be encrypted before transmission. The dual chaotic algorithm is a good option to encrypt sensitive information by using different parameters and different initial conditions for two chaotic maps. A dual chaotic framework creates a complex chaotic trajectory to prevent the illegal use of information from eavesdroppers. Limited precisions of a single chaotic map cause a degradation in the dynamical behavior of the communication system. To overcome this degradation issue in, a novel form of dual chaos map algorithm is analyzed. To maintain the stability of the dynamical system, the Lyapunov Exponent (LE) is determined for the single and dual maps. In this paper, the LE of the single and dual maps

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of The College Of Languages (jcl)
Negation marker in Standard Persian : a typological analysis based on Givon’s functional model: عامل نفی در زبان فارسی معیار: بررسی رده‌شناختی براساس مدل نقش‌ گرایی گیون
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 Abstract:

Typological analysis about  the negation marker  in different languages is one of the fields of research that has attracted much attention.  In Persian language, this constituent has been analysed from different aspects. This study aimed to analyse  different aspects of negation marker  in  the adjectives,  the noun phrases and  the verb phrases based on typological analysis.  Many studies have been revealed that  the negation in adjectives has shown lexically and morphologically. In the noun phrases, /hich/  has used as a negative marker necessarily marking the verb phrase as negative too. In the verb phrases, negation occurs morphologically by the addition of the prefix /n

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