Preferred Language
Articles
/
0xZUpYsBVTCNdQwCbtUW
Cryptography Using Artificial Neural Network
...Show More Authors

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

Preview PDF
Quick Preview PDF
Publication Date
Sat Mar 01 2025
Journal Name
Coed
Engaging High School Teachers with Artificial Intelligence Concepts, Applications, and Developments
...Show More Authors

This work analyzes the effectiveness of an artificial intelligence (AI) community- building workshop designed for high school teachers and it focuses on contemporary issues related to AI concepts and applications. A group of high school teachers from local education districts attended a one-day AI hands-on workshop at our university. The workshop included several AI-related topics and hands-on examples and exercises aiming to introduce AI concepts and tools relevant to pre-college education. The participating teachers were expected to become a part of a collaborative network created to design, develop, and implement novel AI learning modules for high school students. Initial and a post-training surveys have been used to measure the

... Show More
View Publication
Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Lecture Notes In Electrical Engineering
Handling Mobility with Network Virtualization in IoT WAVE Context
...Show More Authors

Realizing robust interconnectivity in a rapidly changing network topology is a challenging issue. This problem is escalating with the existence of constrained devices in a vehicular environment. Several standards have been developed to support reliable communication between vehicular nodes as the IEEE 1609 WAVE stack. Mitigating the impact of security/mobility protocols on limited capability nodes is a crucial aspect. This paper examines the burden of maintaining authenticity service that associated with each handover process in a vehicular network. Accordingly, a network virtualization-based infrastructure is proposed which tackles the overhead of IEEE 1906 WAVE standard on constrained devices existed in vehicular network. The virtualized

... Show More
View Publication
Scopus Crossref
Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
...Show More Authors

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

... Show More
View Publication Preview PDF
Scopus Clarivate Crossref
Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Design and Analysis WIMAX Network Based on Coverage Planning
...Show More Authors

In this paper, wireless network is planned; the network is predicated on the IEEE 802.16e standardization by WIMAX. The targets of this paper are coverage maximizing, service and low operational fees. WIMAX is planning through three approaches. In approach one; the WIMAX network coverage is major for extension of cell coverage, the best sites (with Band Width (BW) of 5MHz, 20MHZ per sector and four sectors per each cell). In approach two, Interference analysis in CNIR mode. In approach three of the planning, Quality of Services (QoS) is tested and evaluated. ATDI ICS software (Interference Cancellation System) using to perform styling. it shows results in planning area covered 90.49% of the Baghdad City and used 1000 mob

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Apr 01 2013
Journal Name
International Journal Of Electrical, Electronics And Telecommunication Engineering
Performance Analysis of xPON Network for Different Queuing Models
...Show More Authors

Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay

... Show More
View Publication Preview PDF
Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Classification of Rural Road Network in Al-Najaf Governorate
...Show More Authors

This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

... Show More
View Publication Preview PDF
Publication Date
Mon Jan 01 2024
Journal Name
Ieee Transactions On Emerging Topics In Computational Intelligence
Reservoir Network With Structural Plasticity for Human Activity Recognition
...Show More Authors

View Publication
Scopus (1)
Crossref (3)
Scopus Clarivate Crossref
Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Design of Hybrid Neural Fuzzy Controller for Human Robotic Leg System
...Show More Authors

 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Jan 13 2016
Journal Name
University Of Baghdad
Employ Mathematical Model and Neural Networks for Determining Rate Environmental Contamination
...Show More Authors

Preview PDF
Publication Date
Mon Jun 30 2008
Journal Name
Iraqi Journal Of Science
On the Greedy Ridge Function Neural Networks for Approximation Multidimensional Functions
...Show More Authors

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

Preview PDF