Papers by Mahmoud Gadallah
International Journal of Intelligent Engineering and Systems, Aug 31, 2020
The capacitated vehicle routing problem is the most popular type of vehicle routing problem and i... more The capacitated vehicle routing problem is the most popular type of vehicle routing problem and is a kind of NP-hard optimization problems. The purpose of this problem is to decrease the total distance travelled by vehicles with respect to restrictions of vehicles' capacity. In this paper the capacitated vehicle routing problem solved by Chicken Swarm Optimization algorithm, Tabu Search and a new hybrid algorithm. The main idea of the proposed algorithm is to use the hieratical order of Chicken Swarm Algorithm and Tabu Search for finding best neighbourhood to find shortest path with minimum cost, after that we using the moving equations of the two algorithms on each chicken to construct the paths then we choose the shortest path which has the minimum cost. Results from a computational experiment on 10 different datasets show that the hybrid algorithm can be considered as an efficient approach and overcome the best known results in 9 datasets which means that it is 90% better than known results.
International Journal of Intelligent Engineering and Systems, Oct 31, 2020
The Capacitated Vehicle Routing Problem is the most popular type of Vehicle Routing Problem and i... more The Capacitated Vehicle Routing Problem is the most popular type of Vehicle Routing Problem and is a kind of NP-hard problems. Finding the minimum total distance travelled by vehicles to serve a group of customers with respect to capacity constrains is the aim of the Capacitated Vehicle Routing Problem. This problem will be solved by hybrid algorithm combining Chicken Swarm Optimization algorithm with Genetic Algorithm using Crossover and Mutation operation. The main idea of the proposed algorithm is to use the hieratical order of Chicken Swarm Algorithm to find paths after using the moving equations. Then we will rearrange the hieratical order according the paths cost. In an attempt to improve results for some chickens, we will use the Genetic Algorithm because it has the advantage that it searches in the neighbourhood to find the best solution then we will get the best solution which has the lowest cost. Results from a computational experiment on 10 different datasets show that the hybrid algorithm can be considered as an efficient approach and overcome the best known results in 10 datasets which means that it is 100% better than best known results which exist on NEO benchmark.
IAES International Journal of Artificial Intelligence (IJ-AI)
Social media impacts society whether these impacts are positive or negative, or even both. It has... more Social media impacts society whether these impacts are positive or negative, or even both. It has become a key component of our lives and a vital news resource. The crisis of covid-19 has impacted the lives of all people. The spread of misinformation causes confusion among individuals. So automated methods are vital to detect the wrong arguments to prevent misinformation spread. The covid-19 news can be classified into two categories: false or real. This paper provides an automated misinformation checking system for the covid-19 news. Five machine learning algorithms and deep learning models are evaluated. The proposed system uses the bidirectional encoder representations from transformers (BERT) with deep learning models. detecting fake news using BERT is a fine-tuning. BERT achieved accuracy (98.83%) as a pre-trained and a classifier on the covid-19 dataset. Better results are obtained using BERT with deep learning models (LSTM), which achieved accuracy (99.1%). The results achiev...
International Journal of Service Science, Management, Engineering, and Technology, 2020
Visual object tracking remains a challenge facing an intelligent control system. A variety of app... more Visual object tracking remains a challenge facing an intelligent control system. A variety of applications serve many purposes such as surveillance. The developed technology faces plenty of obstacles that should be addressed including occlusion. In visual tracking, online learning techniques are most common due to their efficiency for most video sequences. Many object tracking techniques have emerged. However, the drifting problem in the case of noisy updates has been a stumbling block for the majority of relevant techniques. Such a problem can now be surmounted through updating the classifiers. The proposed system is called the Occluded Object Tracking System (OOTS) It is a hybrid system constructed from two algorithms: a fast technique Circulant Structure Kernels with Color Names (CSK-CN) and an efficient algorithm occlusion-aware Real-time Object Tracking (ROT). The proposed OOTS is evaluated with standard visual tracking benchmark databases. The experimental results proved that ...
Heliyon, 2019
Nowadays, virtualization and real-time systems are increasingly relevant. Real-time virtual machi... more Nowadays, virtualization and real-time systems are increasingly relevant. Real-time virtual machines are adequate for closely-coupled computer systems, execute tasks from associated language only and re-target tasks to the new platform at runtime. Complex systems in space, avionics, and military applications usually operate with Loosely-Coupled Computer Systems in a real-time environment for years. In this paper, a new approach is introduced to support task transfer between loosely-coupled computers in a real-time environment to add more features without software upgrading. The approach is based on automatic source code transformation into a platform-independent "Structured Byte-Code" (SBC) and a real-time virtual machine (SBC-RVM). Unlike Ordinary virtual machines which virtualize a specific processor for a specific code only, SBC-RVM transforms source code from any language with a known grammar into SBC without re-targeting the new platform. SBC-RVM executes local or placed tasks and preserving real-time constraints and adequate for Loosely-coupled computer systems.
International Journal of Advanced Computer Science and Applications
The availability of a machine translation to translate from English-to-Arabic with high accuracy ... more The availability of a machine translation to translate from English-to-Arabic with high accuracy is not available because of the difficult morphology of the Arabic Language. A hybrid machine translation system between Example Based machine translation technique and Translation memory was introduced in this paper. Two datasets have been used in the experiments that were constructed by using internal medicine publications and Worldwide Arabic Medical Translation Guide Common Medical Terms sorted by Arabic. To examine the accuracy of the system constructed four experiments were made using Example Based Machine Translation system in the first, Google Translate in the second and Example Based with Google translate in the third and the fourth is the system proposed using Example Based with Translation memory. The system constructed achieved 77.17 score for the first dataset and 63.85 score for the second which were the highest score using BLEU score.
Proceedings of the 7th International Conference on Software and Information Engineering, 2018
Automatic machine translation becomes an important source of translation nowadays. It is a softwa... more Automatic machine translation becomes an important source of translation nowadays. It is a software system that translates a text from one natural language to one (many) natural language. On the web, there are many machine translation systems that give the reasonable translation, although the systems are not very good. Medical records contain complex information that must be translated correctly according to its medical meaning not its English meaning only. So, the quality of a machine translation in this domain is very important. In this paper, we present using matching stage from Example-Based Machine Translation technique to translate a medical text from English as source language to Arabic as the target language. We have used 259 medical sentences that are extracted from internal medicine publications for our system. Experimental results on BLUE metrics showed a decreased performance 0.486 comparing to GOOGLE translation which has an accuracy result about 0.536.
2018 13th International Conference on Computer Engineering and Systems (ICCES), 2018
Spreading of fake news is a social phenomenon that is pervasive at the social level between indiv... more Spreading of fake news is a social phenomenon that is pervasive at the social level between individuals, and also through social media such as Facebook and Twitter. Fake news that we are interested in is one of many kinds of deception in social media, but it’s more important one as it is created with dishonest intention to mislead people. We are concerned about this issue because we have noticed that this phenomenon has recently caused through the means of social communication to change the course of society and peoples and also their views, for example, during revolutions in some Arab countries have emerged some false news that led to the absence of truth and stirs up public opinion and also fake of news is one of the factors Trump successes in the presidential election. So we decided to face and reduce this phenomenon, which is still the main factor to choose most of our decisions. Techniques of fake news detection varied, ingenious, and often exciting. In this paper our objective is to build a classifier that can predict whether a piece of news is fake or not based only its content, thereby approaching the problem from a purely deep learning perspective by RNN technique models (vanilla, GRU) and LSTMs. We will show the difference and analysis of results by applying them to the dataset that we used called LAIR. We found that the results are close, but the GRU is the best of our results that reached (0.217) followed by LSTM (0.2166) and finally comes vanilla (0.215). Due to these results, we will seek to increase accuracy by applying a hybrid model between the GRU and CNN techniques on the same data set.
Protein 3D structure alignment process has become the key focus of interest in structural bioinfo... more Protein 3D structure alignment process has become the key focus of interest in structural bioinformatics. Yet, obtaining perfect alignment in a short execution time was not successful to this point. To overcome this problem, researchers tend to use parallel programming techniques to enhance the performance of the alignment process. In this article, we compare between two parallel programming paradigms for implementing a parallel version of the well-known pairwise alignment algorithm MatAlign. This parallel algorithm is implemented by using two common APIs for C++ parallel programming, which are OpenMP for multi-core CPUs and CUDA for multi-core GPUs. The results show that beside the significant improvement of the parallel implementation over the sequential one, it also shows that the multi-core GPU parallel programming model improves speedup over multi-core CPU programming model.
This paper presents a new testing approach for analogue circuits based on the digital signature a... more This paper presents a new testing approach for analogue circuits based on the digital signature analysis. In this paper, the efficient parametric fault detection approach for analogue circuits using the simulation environment is presented. This approach has three main parts, an analogue test pattern generator (ATPG), an analogue test response compactor (ATRC), and an analogue circuit under test (ACUT) model, build in the PSpice circuit simulator. The proper ATPG is designed to sweep the applying sinusoidal frequencies to match the frequency domain of the ACUT. The output test response of the ACUT is acquired via the analogue-to-digital converter (ADC). The ATRC accumulates digital samples of the output response from the ADC to generate a digital signature that can characterize the situation of the ACUT. The signature comparison is achieved based on signature boundaries based on the worst-case analysis. In addition, the signature curve for each component variations of the ACUT is pre...
International Journal of Intelligent Systems and Applications, 2021
Social media presence is a crucial portion of our life. It is considered one of the most importan... more Social media presence is a crucial portion of our life. It is considered one of the most important sources of information than traditional sources. Twitter has become one of the prevalent social sites for exchanging viewpoints and feelings. This work proposes a supervised machine learning system for discovering false news. One of the credibility detection problems is finding new features that are most predictive to better performance classifiers. Both features depending on new content, and features based on the user are used. The features' importance is examined, and their impact on the performance. The reasons for choosing the final feature set using the k-best method are explained. Seven supervised machine learning classifiers are used. They are Naïve Bayes (NB), Support vector machine (SVM), Knearest neighbors (KNN), Logistic Regression (LR), Random Forest (RF), Maximum entropy (ME), and conditional random forest (CRF). Training and testing models were conducted using the Phe...
Electronics ETF, 2017
In this paper, filtered back-projection algorithm is optimally implemented using low-cost Spartan... more In this paper, filtered back-projection algorithm is optimally implemented using low-cost Spartan 3A-DSP 3400 chip. The optimization enables parallel implementation. The combination of the pixel parallelism and projection parallelism is presented to significantly reduce the total reconstruction time to produce the image. The applied data is presented in fixed point format to achieve efficient implementation with maximum speed. The selection of data bus-width is optimized with very little error and good visual quality required for medical images. Before implementation, the computer tomography ( CT ) reconstruction simulator is developed to provide a testing reference for the hardware implementation. Using the combination of the pixel parallelism and projection parallelism, the presented hardware design achieves image reconstruction of a 512-by-512 pixel image from 1024 projections in 134. 8ms using 50 MHz clock cycles. It achieves the reduction of the required number of clock cycles ...
The International Conference on Electrical Engineering, 2010
Computed tomography is a technique for estimating the interior of an object from measurements of ... more Computed tomography is a technique for estimating the interior of an object from measurements of radiation collected around the object. This radiation is projected either through or emitted from the object and the projections are reconstructed to form the object image. The reconstruction quality & time depend on many factors such as: filteration domain, filter type and interpolation level. The objective of this paper is to develop an algorithm to simulate CT image reconstruction from projections (image simulated projections or raw data projections file).The developed program enables the user to investigate the effects of many factors mentioned above on the quality of the reconstructed images. The system has agraphical user interface (GUI) to facilitate changing the effictive factors and measuring the performance of the reconstruction. This system helps for studying the CT reconstruction process by introducing many factors selections for development as well as for training
The International Conference on Electrical Engineering, 2010
The traditional Electroencephalogram (EEG) visual inspection suffers from the limited accuracy of... more The traditional Electroencephalogram (EEG) visual inspection suffers from the limited accuracy of the human interpretator, and the variation of different interpretator skills. In addition, the accurate investigation of the EEG requires long time and big effort. A proposed Computerized EEG Abnormalities Detection (CEAD) system is introduced to overcome the limitations of the traditional EEG visual inspection method. This system has the ability to detect the EEG abnormalities automatically and display them to the physician both numerically and graphically. Moreover, the system can show the EEG electrodes that have the abnormal events on a graphical skull map. The proposed system saves much time and effort for the interpretator, as well as providing high accuracy in detecting the EEG abnormalities.
In this paper, we introduce an integrated human-robot interfaces system that enables users to con... more In this paper, we introduce an integrated human-robot interfaces system that enables users to control robots using some electrophysiological signals, voice commands and legacy peripheral devices (keyboard, mouse and game controller). The control may be performed locally or remotely over the internet. In previous woks, Brainwaves (Alpha-waves) were used in controlling limited movements, and also voice commands were used in both robot movements and arms. These systems limit the number of commands to the robot and/or limit the types of users that can deal with the robot. The proposal system in this paper uses multi user interfaces inputs to provide full controlling of the robot over the internet for multiple user types including handicapped users. Our results show that Electromyography (EMG), Electrooculography (EOG) and Electroencephalography (EEG) signals with voice commands can provides simpler way to control complex machines even by disabled people with 97.5% accuracy rate.
International Journal of Advanced Computer Science and Applications, 2014
In this paper, a comprehensive survey on gaming tree searching methods that can use to find the b... more In this paper, a comprehensive survey on gaming tree searching methods that can use to find the best move in two players zero-sum computer games was introduced. The purpose of this paper is to discuss, compares and analyzes various sequential and parallel algorithms of gaming tree, including some enhancement for them. Furthermore, a number of open research areas and suggestions of future work in this field are mentioned.
2014 9th International Conference on Informatics and Systems, 2014
ABSTRACT
International Journal of Computer Applications, 2014
This paper presents a new testing approach for analogue circuits based on the digital signature a... more This paper presents a new testing approach for analogue circuits based on the digital signature analysis. In this paper, the efficient parametric fault detection approach for analogue circuits using the simulation environment is presented. This approach has three main parts, an analogue test pattern generator (ATPG), an analogue test response compactor (ATRC), and an analogue circuit under test (ACUT) model, build in the PSpice circuit simulator. The proper ATPG is designed to sweep the applying sinusoidal frequencies to match the frequency domain of the ACUT. The output test response of the ACUT is acquired via the analogue-to-digital converter (ADC). The ATRC accumulates digital samples of the output response from the ADC to generate a digital signature that can characterize the situation of the ACUT. The signature comparison is achieved based on signature boundaries based on the worst-case analysis. In addition, the signature curve for each component variations of the ACUT is presented to be illustrated as image of some parameters affected in the transfer function of the ACUT. It combines effective parameters of the transfer function of the ACUT with respect to the component variations. These parameters are the band-with and the passband transmission. Using the signature curve, a parametric fault of each component of the ACUT can be detected under the sweep sinusoidal frequency of the ATPG. The presented testing approach is applied to the analogue benchmark circuit to validate the presented testing approach.
2014 IEEE International Conference on Progress in Informatics and Computing, 2014
ABSTRACT
Lasers in Dentistry XII, 2006
Laser-induced photoacoustic spectroscopy (LIPS) can be used to measure trace-element concentratio... more Laser-induced photoacoustic spectroscopy (LIPS) can be used to measure trace-element concentration in materials, down to parts-per-million. In this paper we investigate the use of laser-induced photoacoustic response in carious teeth detection. First, we found the Q-switched Nd:YAG laser of a wavelength of 1064 nm to produce detectable response in teeth. Then, we implemented two detection techniques using a piezoelectric transducer and Michelson Interferometer. The accurately detected response of a tooth sample by the piezoelectric transducer was analyzed using spectral analysis. However, in dentistry we do not necessarily mead an exact quantitative measurement; thus we designed a more physically realizable system that measures the acoustically-induced surface displacement using Michelson Interferometer. Monitoring this surface displacement we were able to determine the physical and optical properties of the tooth sample which could be used as a basis in diagnostics. The responses obtained by both detectors were equally confined to the categorization of a carious tooth from a normal one.
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Papers by Mahmoud Gadallah