Volume-5 Issue-6

ijsab.com logo

The Impact of Test Case Generation Methods on the Software Performance: A Review Dathar A. Hasan, Bzar Kh. Hussan, Subhi R. M. Zeebaree, Dindar M. Ahmed, Omar S. Kareem & Mohammed A. M. Sadeeq

Editor

The Impact of Test Case Generation Methods on the Software Performance: A Review

Author (s)

Dathar A. Hasan, Bzar Kh. Hussan, Subhi R. M. Zeebaree, Dindar M. Ahmed, Omar S. Kareem & Mohammed A. M. Sadeeq

Abstract

­

The software development in different fields leads to increase the requirements for effective, efficient and complicated software. Due to the huge amounts of software requirements, it is possible some errors to occur in the certain part of the programs and this means a real challenge for the software producer. The need for an effective test system is necessary for designing reliable programs and avoiding the errors that may appear during the software product. In this review, many techniques are discussed for the process of generating test cases which are a group of conditions that determine whether the designed programs are able to satisfy the user’s requirements or not. Fuzzy logic utilizes an operational profile in the process of allocating test case to improve the software quality, as well as the design of fault propagation path to predicts the software defects during the test operation, also the automatic generation for PLC test cases that produce a new track through the program code in order to minimize the test cases needed for large size program.

 Keywords: Software test, test case, program evaluation, reliable software system, test suite.

 

Download PDF

Title: The Impact of Test Case Generation Methods on the Software Performance: A Review
Author: Dathar A. Hasan, Bzar Kh. Hussan, Subhi R. M. Zeebaree, Dindar M. Ahmed, Omar S. Kareem & Mohammed A. M. Sadeeq
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4623940
Media: Online
Volume: 5
Issue: 6
Acceptance Date: 13/03/2021
Date of Publication: 19/02/2021
PDF URL: https://ijsab.com/wp-content/uploads/744.pdf
Free download: Available
Page: 33-44
First Page: 33
Last Page: 44
Paper Type: Literature review
Current Status: Published

 

Cite This Article:

Dathar A. Hasan, Bzar Kh. Hussan, Subhi R. M. Zeebaree , Dindar M. Ahmed, Omar S. Kareem & Mohammed A. M. Sadeeq (2021). The Impact of Test Case Generation Methods on The Software Performance: A Review. International Journal of Science and Business, 5(6), 33-44. doi: https://doi.org/10.5281/zenodo.4623940

Retrieved from https://ijsab.com/wp-content/uploads/744.pdf

 

About Author (s)

Dathar A. Hasan (corresponding author), Duhok Polytechnic University, Shekhan Technical Institute, Kurdistan Region, Duhok, Iraq. Email: dathar.hasan@dpu.edu.krd

Bzar Kh. Hussan, Erbil Polytechnic University, Kurdistan Region, Iraq.

Subhi R. M. Zeebaree, Duhok Polytechnic University, Kurdistan Region, Duhok, Iraq.

Dindar M. Ahmed, Duhok Polytechnic University, Kurdistan Region, Duhok, Iraq.

Omar S. Kareem, Duhok Polytechnic University, Kurdistan Region, Duhok, Iraq.

Mohammed A. M.Sadeeq, Duhok Polytechnic University, Kurdistan Region, Duhok, Iraq.

Download PDF

DOI: https://doi.org/10.5281/zenodo.4623940

Total Download of This Article : 24
ijsab.com logo

A Comparative Study of Detect Brain Tumor Based on K-Means and Fuzzy C-Means Algorithms Noor Salah Hassan & Nawzat Sadiq Ahmed

Editor

A Comparative Study of Detect Brain Tumor Based on K-Means and Fuzzy C-Means Algorithms

Author (s)

Noor Salah Hassan & Nawzat Sadiq Ahmed

Abstract

­

The detection of the tumor region in medical images such as (MRI, CT, X-Ray) a boring and time-consuming task is by radiologists or experts. So, in this review the accuracy is needed for detection the tumor. The area of medical imaging is also reducing complexity and improving diagnostic precision with the growth of information technology. This review paper makes a comparison between the k-mean, and fuzzy c-mean algorithms to display the results and accuracy of them to detection the brain tumor. The execution of the k-mean algorithm is based on centroid, size, split process, threshold, epoch, characteristics, and number of iterations, while Fuzzy C-mean is executed on the basis of the fuzziness value and the termination condition in medical images. In comparing the efficiency parameters with the state-of-the-art processes, the experimental outcomes demonstrate the importance of medical images (MRI, CT and X-Ray) and the accuracy of each algorithm that have been discussed.

 Keywords: Brain Tumor, Medical Images, Pre-processing, Segmentation, Feature Extraction, K- means.

 

Download PDF

Title: A Comparative Study of Detect Brain Tumor Based on K-Means and Fuzzy C-Means Algorithms
Author: Noor Salah Hassan & Nawzat Sadiq Ahmed
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4596362
Media: Online
Volume: 5
Issue: 6
Acceptance Date: 07/03/2021
Date of Publication: 11/02/2021
PDF URL: https://ijsab.com/wp-content/uploads/743.pdf
Free download: Available
Page: 21-32
First Page: 21
Last Page: 32
Paper Type: Literature review
Current Status: Published

 

Cite This Article:

Noor Salah Hassan & Nawzat Sadiq Ahmed (2021). A Comparative Study of Detect Brain Tumor Based on K-Means and Fuzzy C-Means Algorithms. International Journal of Science and Business, 5(6), 21-32. doi: https://doi.org/10.5281/zenodo.4596362

Retrieved from https://ijsab.com/wp-content/uploads/743.pdf

 

About Author (s)

Noor Salah Hassan (corresponding author), Department of Information Technology, Akre Technical Collage, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. Email:  noor.salah.hassan6@gmail.com

Nawzat Sadiq Ahmed, Department of Information Technology, Technical Collage of Administration, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. Email:  nawzat.ahmed@dpu.edu.krd.

 

Download PDF

DOI: https://doi.org/10.5281/zenodo.4596362

Total Download of This Article : 11
ijsab.com logo

A comparison study: Classification brain tumor based on Support Vector Machine and K-Nearest Neighbors Shler Farhad Khorshid & Nawzat Sadiq Ahmed

Editor

A comparison study: Classification brain tumor based on Support Vector Machine and K-Nearest Neighbors

Author (s)

Shler Farhad Khorshid & Nawzat Sadiq Ahmed

Abstract

­

Brain tumor is one of the commonest tumors. For the diagnosis of this disease, automated detection and classification are crucial. Magnetic resonance imaging (MRI) is a unique sort of imaging which is utilized for detecting these tumors and categorizing them as benign or malignant using special algorithms such as of K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM). The classification of brain tumors through imaging can be divided into four phases: pre-processing, extraction, segmentation and classification. This paper reviews some recent studies that highlight the efficacy of K-NN and SVM accuracies in classifying brain MRI images as normal or abnormal, benign or malignant.

 Keywords: brain tumor, Magnetic resonance imaging (MRI), classification, SVM, K-NN.

 

Download PDF

Title: A comparison study: Classification brain tumor based on Support Vector Machine and K-Nearest Neighbors
Author: Shler Farhad Khorshid & Nawzat Sadiq Ahmed
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4590054
Media: Online
Volume: 5
Issue: 6
Acceptance Date: 05/03/2021
Date of Publication: 09/02/2021
PDF URL: https://ijsab.com/wp-content/uploads/742.pdf
Free download: Available
Page: 12-20
First Page: 12
Last Page: 20
Paper Type: Literature review
Current Status: Published

 

Cite This Article:

Shler Farhad Khorshid & Nawzat Sadiq Ahmed (2021). A comparison study: Classification brain tumor based on Support Vector Machine and K-Nearest Neighbors. International Journal of Science and Business, 5(6), 12-20. doi: https://doi.org/10.5281/zenodo.4590054

Retrieved from https://ijsab.com/wp-content/uploads/742.pdf

 

About Author (s)

Shler Farhad Khorshid (corresponding author), Information Technology Department, Akre Technical College of Informatics, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. E-mail: Shler.sulayvani@gmail.com

Nawzat Sadiq Ahmed, Information Technology Management, Technical College of Administration, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. Email: nawzat.ahmed@dpu.edu.krd

 

Download PDF

DOI: https://doi.org/10.5281/zenodo.4590054

Total Download of This Article : 19
ijsab.com logo

Evaluating Students Feedback Towards Teachers Performance on E-learning Sarbast H. Ali, Sardar Omar Salih, Arman Ismael Mohammed & Omer Mohammed Salih Hassan

Editor

Evaluating Students Feedback Towards Teachers Performance on E-learning

Author (s)

Sarbast H. Ali, Sardar Omar Salih, Arman Ismael Mohammed & Omer Mohammed Salih Hassan

Abstract

­

Internet use in the Kurdistan region of Iraq has grown dramatically and has become an essential element of our daily lives, with hundred ISPs on hand and constantly increasing number of users by using e-learning platforms. The need for feedback is deeply linked to student participation and peer evaluation. It is also an issue of evaluation quality; how many feedbacks is made available, how they are given to students, how they are accepted by students, and to how much they are integrated into future instruction and learning. In this paper, three instruments, documentation, interviews and questionnaires were carried out to collect the data. Documentation was used to know the experiences of the students during classroom teaching and learning. The data were collected from the system application on our website. The data were called documentation. A survey is conducted comparing the feedback received from students on e-learning courses at the Duhok Polytechnic University (DPU), with the results of analyzed 100 teachers’ e-learning courses in the Covid-19 period in 2020. Eighteen questions have been asked to 7709 students in 14 technical faculties (6 colleges and 8 institutes) at DPU. The students’ responses were classified to the questions related to teachers’ experiences on preparing courses, students’ interactions, using available e-learning tools and methods. A review has been made on (100) teachers’ courses in the Moodle platform as LMS (learning management systems) to reveal their course preparation, experiences on using available technologies. Our results showed 34.92% of participant students satisfied with e-learning, this means that 65.08% of students preferred face-to-face learning (in class), regarding the trustiness of feedback, reviewed courses and students’ responses which were significantly mismatched. This means that student feedback is not entirely reliable in the learning process.

 Keywords: E-learning, feedback, questionnaires, teacher experiences, survey.

 

Download PDF

Title: Evaluating Students Feedback Towards Teachers Performance on E-learning
Author: Sarbast H. Ali, Sardar Omar Salih, Arman Ismael Mohammed & Omer Mohammed Salih Hassan
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4588538
Media: Online
Volume: 5
Issue: 6
Acceptance Date: 03/03/2021
Date of Publication: 08/02/2021
PDF URL: https://ijsab.com/wp-content/uploads/741.pdf
Free download: Available
Page: 1-11
First Page: 1
Last Page: 11
Paper Type: Research Paper
Current Status: Published

 

Cite This Article:

Sarbast H. Ali, Sardar Omar Salih, Arman Ismael Mohammed & Omer Mohammed Salih Hassan (2021). Evaluating Students Feedback Towards Teachers Performance on E-learning. International Journal of Science and Business, 5(6), 1-11. doi: https://doi.org/10.5281/zenodo.4588538

Retrieved from https://ijsab.com/wp-content/uploads/741.pdf

 

About Author (s)

Sarbast H. Ali (corresponding author), Information Technology Department, Duhok Polytechnic University (DPU), Duhok, Iraq.  Email: sarbast.ali@dpu.edu.krd

Sardar Omar Salih, Information Technology Department, Duhok Technical Institute, Duhok Polytechnic University (DPU), Duhok, Iraq.

Arman Ismael Mohammed, Information Technology Department, Duhok Polytechnic University (DPU), Duhok, Iraq.

Omer Mohammed Salih Hassan, Information Technology Department, Duhok Polytechnic University (DPU), Duhok, Iraq.

 

Download PDF

DOI: https://doi.org/10.5281/zenodo.4588538

Total Download of This Article : 20