Saad Subair - Academia.edu (original) (raw)

Papers by Saad Subair

Journal of Engineering and Computer Science, Jun 1, 2015

Researchers in the field of protein secondary structure prediction use typical three states of se... more Researchers in the field of protein secondary structure prediction use typical three states of secondary structures, namely: alpha helices (H) beta strands (E), and coils (C). The series of amino acids polymers linked together into adjacent chains are known as proteins. Protein secondary structure prediction is a fundamental step in determining the final structure and functions of a protein. In this work we developed a prediction machine for protein secondary structure. By investigating the amino acids benchmark data sets, it was observed that the data is grouped into two distinct states or groups almost 50% each. In this scheme, researchers classify any state which is not classified as helix or strands as coils. Hence, in this work a new way of looking to the data set is adopted. For this type of data, the Receiver Operating Characteristic (ROC) analysis is considered for analysing and interpreting the results of assessing the protein secondary structure classifier. The results revealed that ROC analysis showed similar results to that obtained using other non ROC classification methods. The ROC curves were able to discriminate the coil states from non-coil states by 72% prediction accuracy with very small standard error.

International Journal of Emerging Multidisciplinaries: Computer Science & Artificial Intelligence

Cyber crime is becoming more frequent in our daily life since computers are everywhere now and he... more Cyber crime is becoming more frequent in our daily life since computers are everywhere now and hence the term cyberspace is becoming our ordinary life. Digital forensics or computer forensics which the process of securing digital evidence against the crime is becoming inevitable. Digital evidence is the foundation for any digital forensic investigation that can be collected by several means using technologies and scientific crime scene investigation. Modifications with crime scene data may possibly change the evidences that may lead to different investigation results. Several models and frameworks to help investigating cybercrimes have been proposed. In this paper we are proposing a frame work that to suit the Sudanese judiciary system. The framework suggested studied several models and frameworks in the globe to come out with a suitable framework model that can help the Sudanese courts taking their decisions concerning cybercrime. The conventional chain of custody is our main plat...

Journal of Data Analysis and Information Processing, 2019

This research aims to study various Symmetrical Algorithms, while the main objective of this stud... more This research aims to study various Symmetrical Algorithms, while the main objective of this study is to find out a suitable algorithm for the encryption of any specific size of text file where the experiment of each algorithm is based on encryption of different sizes of the text files, which are in "10 KB to 5 MB", and also to calculate the time duration that each algorithm takes to encrypt or to decrypt the particular size of each text file. There are many types of encryption algorithm, which can be used to encrypt the computerized information in different Organizations, whose all algorithms can encrypt and decrypt any size of text file, but the time duration of each Algorithm during the encryption or decryption process of specific file size is not fixed. Some of the algorithms are suitable for encryption of specific ranges of the file size, or some of algorithms are functional while encryption small size of files, and others algorithms are functional for encryption of big size of text files, based on the time duration disparity among symmetric algorithms during encryption of text files. In this study five symmetrical algorithms are merged in one program using classes and concept of inheritance in the form that if encryption is needed, the program will select the file and it checks the size of the text file. After this process the program automatically will select the suitable encryption algorithm to encrypt the specific text file according to the range of the file size. Knowing that the file size before or after encryption will not change or is stable, in this case of the decryption algorithm will apply the same process of encryption while decrypting files, the program of encryption and decryption code will write using visual Studio 2013. The result will be analyzed with R program (R software), the cipher text will appear in the format of UTF8 which means Unicode Transformation Format, "8" Means "8" bits to represent a character, the size format that will apply in the program will be in format of KB (kilo Byte).

Studies in Computational Intelligence, 2020

This book provides step-by-step explanations of successful implementations and practical applicat... more This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The book’s GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data mining; and data discovery. Numerous state-of-the-art machine

Journal of Data Analysis and Information Processing, 2016

The usability of an interface is a fundamental issue to elucidate. Many researchers argued that m... more The usability of an interface is a fundamental issue to elucidate. Many researchers argued that many usability results and recommendations lack empirical and experimental data. In this research, the usability of the web pages is evaluated using several carefully selected statistical models. Universities web pages are chosen as subjects for this work for ease of comparison and ease of collecting data. A series of experiments has been conducted to investigate into the usability and design of the universities web pages. Prototype web pages have been developed according to the structured methodologies of web pages design and usability. Universities web pages were evaluated together with the prototype web pages using a questionnaire which was designed according to the Human Computer Interactions (HCI) heuristics. Nine (users) respondents' variables and 14 web pages variables (items) were studied. Stringent statistical analysis was adopted to extract the required information to form the data acquired, and augmented interpretation of the statistical results was followed. The results showed that the analysis of variance (ANOVA) procedure showed there were significant differences among the universities web pages regarding most of the 23 items studied. Duncan Multiple Range Test (DMRT) showed that the prototype usability performed significantly better regarding most of the items. The correlation analysis showed significant positive and negative correlations between many items. The regression analysis revealed that the most significant factors (items) that contributed to the best model of the universities web pages design and usability were: multimedia in the web pages, the web pages icons (alone) organisation and design, and graphics attractiveness. The results showed some of the limitations of some heuristics used in conventional interface systems design and proposed some additional heuristics in web pages design and usability.

Artificial Intelligence for Data Science in Theory and Practice

Artificial Intelligence for Data Science in Theory and Practice, 2022

Information Technology Journal, 2005

Microarray technology has been advancing rapidly during the last decade. The development of power... more Microarray technology has been advancing rapidly during the last decade. The development of powerful robot machines for DNA microarray experiments, new hybridization techniques, and increasing genome-sequencing data sets made it possible to improve the quality and accuracy of microarray experiments. Powerful computers and hardware help in analyzing and classifying microarray huge data. Microarray analysis may provide significant information on diseases mechanisms, resistance to certain drugs, and response to cells interactions. As far as cancer is concerned, microarray analysis may lead to improved early diagnosis and creative treatments to this disease.

Abstract-Microarray technology has been advancing rapidly during the last decade. The development... more Abstract-Microarray technology has been advancing rapidly during the last decade. The development of powerful robot machines for DNA microarray experiments, new hybridization techniques, and increasing genome-sequencing data sets made it possible to improve the quality and accuracy of microarray experiments. Powerful computers and hardware help in analyzing and classifying microarray huge data. Microarray analysis may provide significant information on diseases mechanisms, resistance to certain drugs, and response to cells interactions. As far as cancer is concerned, microarray analysis may lead to improved early diagnosis and creative treatments to this disease.

The usability of an interface is how easy to use this interface. Researchers debated that many us... more The usability of an interface is how easy to use this interface. Researchers debated that many usability results and recommendations lack empirical and experimental data. In this paper, the usability of the web pages is evaluated using the analysis of variance (ANOVA) and Duncan Multiple Range Test (DMRT) procedures. Universities web pages are chosen as subjects for this work. Series of experiments have been conducted to investigate into the usability and design of the universities web pages. Prototype web pages have been developed according to the structured methodologies of web pages design and usability. Universities web pages were evaluated together with the prototype web pages using a questionnaire which was designed according to the Human Computer Interactions (HCI) heuristics. Respondents (users) variables and web pages variables (items) were studied. The results showed that the ANOVA procedure showed there were significant differences among the universities web pages regardi...

Journal of Science and Technology, 2015

Predicting protein secondary structure is a key step in determining the 3D structure of a protein... more Predicting protein secondary structure is a key step in determining the 3D structure of a protein that determines its function. The Dictionary of Secondary Structure of Proteins (DSSP) uses eight classes to describe a protein. The DSSP database is a database of secondary structure assignments for all protein entries in the Protein Data Bank (PDB) with an algorithm designed to standardize these secondary structure assignments. Five methods that reduce theses eight classes into the adopted three classes: alpha helices (H) beta strands (E), and coils (C) are implemented in this research. A protein secondary structure classifier (NN-GORV-II) has been used to evaluate the five reduction methods under the same hardware, platforms, and environment to allow stringent and reliable comparison of these methods and then arrive at a clear conclusion. This paper explains and discusses the effect of these reduction methods on the prediction accuracy and quality.

A classifier for predicting protein secondary structure from amino acid sequences has been propos... more A classifier for predicting protein secondary structure from amino acid sequences has been proposed and implemented in a previous experiment. NN-GORV-II classifier utilizes the power of Artificial Neural Network and GOR method of protein secondary structure prediction. The Critical Assessment of techniques for Structure Prediction of proteins (CASP) experiments aim at establishing the current state of the art in protein structure prediction. The NN-GORV-II classifier is tested using CASP targets proteins. This test is based on testing a new protein classifier with proteins targets (amino acids) that were never used by the classifier at any prior training or testing stages, hence it's known as blind test. This type of prediction was described as true prediction. The performance of the NN-GORV-II method on the CASP targets: (Q3) is 76.9% with 7.5% standard deviation while the quality of the prediction (SOV3) of the method reached 75.4% with 9.8% standard deviation. The Correlation...

PCT No. PCT/US79/00449 Sec. 371 Date Jun. 26, 1979 Sec. 102(e) Date Jun. 26, 1979 PCT Filed Jun. ... more PCT No. PCT/US79/00449 Sec. 371 Date Jun. 26, 1979 Sec. 102(e) Date Jun. 26, 1979 PCT Filed Jun. 26, 1979 An apparatus and method is provided for heat tacking of elongate material or cables (32) to a tire carcass (15) on both peripheral sides of a core opening (20), spreading the elongate material or cables (32) lying over the core opening (20) so as to position the elongate material or cables (32) on either circumferential side of the core opening (20), and heat tacking the spread elongate material or cables (32) to the tire carcass (15). The apparatus includes a frame (40) having locating pads (72,102) for positioning the heat-tacking and elongate material or cable-spreading subassembly (110) with respect to the core opening (20). The tacking members (120,125,120) are preheated to a tacking temperature so that when the frame (40) is clamped onto the carcass (15), and the elongate material or cables (32) are spread, the spread elongate material or cables (32) are tacked to the carc...

International Journal in It Engineering, 2014

A classifier for predicting protein secondary structure from amino acid sequences has been propos... more A classifier for predicting protein secondary structure from amino acid sequences has been proposed and implemented in a previous experiment. NN-GORV-II classifier utilizes the power of Artificial Neural Network and GOR method of protein secondary structure prediction. The Critical Assessment of techniques for Structure Prediction of proteins (CASP) experiments aim at establishing the current state of the art in protein structure prediction. The NN-GORV-II classifier is tested using CASP targets proteins. This test is based on testing a new protein classifier with proteins targets (amino acids) that were never used by the classifier at any prior training or testing stages, hence it's known as blind test. This type of prediction was described as true prediction. The performance of the NN-GORV-II method on the CASP targets: (Q 3) is 76.9% with 7.5% standard deviation while the quality of the prediction (SOV 3) of the method reached 75.4% with 9.8% standard deviation. The Correlation Coefficients are 0.68, 0.63, and 0.62 for helices, strands, and coils, respectively, indicating strong relationship between predicted and observed secondary structures states.

Journal of Engineering and Computer Science, Jun 1, 2015

International Journal of Emerging Multidisciplinaries: Computer Science & Artificial Intelligence

Journal of Data Analysis and Information Processing, 2019

Studies in Computational Intelligence, 2020

Journal of Data Analysis and Information Processing, 2016

Artificial Intelligence for Data Science in Theory and Practice

Artificial Intelligence for Data Science in Theory and Practice, 2022

Information Technology Journal, 2005

Journal of Science and Technology, 2015

International Journal in It Engineering, 2014

A classifier for predicting protein secondary structure from amino acid sequences has been propos... more A classifier for predicting protein secondary structure from amino acid sequences has been proposed and implemented in a previous experiment. NN-GORV-II classifier utilizes the power of Artificial Neural Network and GOR method of protein secondary structure prediction. The Critical Assessment of techniques for Structure Prediction of proteins (CASP) experiments aim at establishing the current state of the art in protein structure prediction. The NN-GORV-II classifier is tested using CASP targets proteins. This test is based on testing a new protein classifier with proteins targets (amino acids) that were never used by the classifier at any prior training or testing stages, hence it's known as blind test. This type of prediction was described as true prediction. The performance of the NN-GORV-II method on the CASP targets: (Q 3) is 76.9% with 7.5% standard deviation while the quality of the prediction (SOV 3) of the method reached 75.4% with 9.8% standard deviation. The Correlation Coefficients are 0.68, 0.63, and 0.62 for helices, strands, and coils, respectively, indicating strong relationship between predicted and observed secondary structures states.

Implementations and Applications of Machine Learning, 2020