cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
,
INDONESIA
International Journal of Intelligent Systems and Applications in Engineering
Published by Ismail SARITAS
ISSN : 21476799     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Intelligent Systems and Applications in Engineering (IJISAE) is an international and interdisciplinary journal for both invited and contributed peer reviewed articles that intelligent systems and applications in engineering at all levels. The journal publishes a broad range of papers covering theory and practice in order to facilitate future efforts of individuals and groups involved in the field. IJISAE, a peer-reviewed double-blind refereed journal, publishes original papers featuring innovative and practical technologies related to the design and development of intelligent systems in engineering. Its coverage also includes papers on intelligent systems applications in areas such as nanotechnology, renewable energy, medicine engineering, Aeronautics and Astronautics, mechatronics, industrial manufacturing, bioengineering, agriculture, services, intelligence based automation and appliances, medical robots and robotic rehabilitations, space exploration and etc.
Arjuna Subject : -
Articles 12 Documents
 1   2 
Search results for , issue " Vol 3, No 2 (2015)" : 12 Documents clear
Grade prediction improved by regular and maximal association rules Udristoiu, Anca Loredana; Udristoiu, Stefan
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.17210

Abstract

In this paper we propose a method of predicting student scholar performance using the power of regular and maximal association rules. Due to the large number of generated rules, traditional data mining algorithms can become difficult and inappropriate to educational systems. Thus, we use some methods to overcome this problem, discovering rules useful in educational process. These methods are applied to the e-learning system Moodle, for “Database” course.
BAT algorithm for Cryptanalysis of Feistel cryptosystems Tahar, Mekhaznia
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.82426

Abstract

Recent cryptosystems constitute an effective task for cryptanalysis algorithms due to their internal structure based on nonlinearity. This problem can be formulated as NP-Hard. It has long been subject to various attacks; available results, emerged many years ago remain insufficient when handling large instances due to resources requirement which increase with the amount of processed data.  On another side, optimization techniques inspired by swarm intelligence represents a set of approaches used to solve complex problems. This is mainly due to their fast convergence with a consumption of reduced resources. The purpose of this paper is to provide, and for a first time, a more detailed study about the performance of BAT algorithm in cryptanalysis of some variant of Data encryption standard algorithms. Experiments were performed to study the effectiveness of the used algorithm in solving the considered problem and underline the difficulties encountered.
Comparison among Feature Encoding Techniques for HIV-1 Protease Cleavage Specificity Turhal, Uğur; Gök, Murat; Durgut, Aykut
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.21005

Abstract

HIV-1 protease which is responsible for the generation of infectious viral particles by cleaving the virus polypeptides, play an indispensable role in the life cycle of HIV-1. Knowledge of the substrate specificity of HIV-1 protease will pave the way of development of efficacious HIV-1 protease inhibitors. In the prediction of HIV-1 protease cleavage site techniques, many efforts have been devoted. Last decade, several works have approached the prediction of HIV-1 protease cleavage site problem by applying a number of methods from the field of machine learning. However, it is still difficult for researchers to choose the best method due to the lack of an effective and up-to-date comparison. Here, we have made an extensive study on feature encoding techniques for the problem of HIV-1 protease specificity on diverse machine learning algorithms. Also, for the first time, we applied OEDICHO technique, which is a combination of orthonormal encoding and the binary representation of selected 10 best physicochemical properties of amino acids derived from Amino Acid index database, to predict HIV-1 protease cleavage sites.
Classification of Siirt and Long Type Pistachios (Pistacia vera L.) by Artificial Neural Networks Sabanci, Kadir; Koklu, Murat; Unlersen, Muhammed Fahri
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.74573

Abstract

Quality is one of the important factors in agricultural products marketing. Grading machines have great role in quality control systems. The most efficient method used in grading machines today is image processing. This study aims to do the grading of high valued agricultural product of our land called pistachio that has two different types namely Siirt and Long type of pistachios by image processing methods and artificial neural networks. Photos of Siirt and long type of pistachios are taken by a Webcam with CCD sensor. These photos were converted to gray scale in Matlab. Afterwards, these photos were converted to binary photo format using Otsu’s Method. Then this data was used to train multi-layered neural network to complete grading.  Matlab was used for both image processing and artificial neural networks. Successes of the grading with image processing and artificial neural networks for mixed type pistachios Siirt and Long were researched.
Fuzzy multicriterial methods for the selection of IT-professionals Jabrayilova, Zarifa Gasim
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.08607

Abstract

This paper presents the solution of issues related to selection based on evaluation of demand set forth to IT specialists, to develop appropriate decision support system. In this case problem is reduced to multicriterial task of decision making, functioning in a fuzzy environment.We propose criteria estimation method allowing regulation and selection of the best alternative according to the scenario appropriate to the requirements of the decision making person, at a current time. For realization of abovementioned task on the basis of fuzzy logic methods we propose methods of expert knowledge processing of the importance criteria and their characterizing factors.
Atmospheric and light-induced effects in nanostructured silicon deposited by capacitively and inductively-coupled plasma Saleh, Zaki Mohammad; Nogay, Gizem; Ozkol, Engin; Turan, Rasit
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.13913

Abstract

Renewable sources of energy have demonstrated the potential to replace much of the conventional sources but the cost continues to pose a challenge. Efforts to reduce cost involve highly efficient and less expensive materials as well as enhanced light management. Nanostructured materials consisting of silicon quantum dots in a matrix of amorphous silicon (a-Si) are promising for higher efficiency and better stability. Quantum confinement offers a tunable band gap, relaxes momentum conservation rule, and may permit multi exciton generation, MEG. We employ electron spin resonance (ESR), the temperature dependence of dark and photoconductivity to compare the stability of amorphous and nanostructured silicon films deposited by inductively- and capacitively-coupled plasma against atmospheric and light exposure. Distinctly different behaviors are observed for amorphous and nanostructured films suggesting that nanostructured films are more permeable to oxygen infusion but more resistant to light induced effect
About a discussion ‘‘Development a new mutation operator to solve the Traveling Salesman Problem by aid of genetic algorithms’’, by Murat Albayrak and Novruz Allahverdi, (2011). Expert System with Applications (38) (pp. 1313–1320) Allahverdi, Novruz
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the Short Communication published in “Expert Systems with Application” in volume 41 2014, (Comments on "Albayrak, M., & Allahverdi N. (2011). Development a new mutation operator to solve the Traveling Salesman Problem by aid of Genetic Algorithms. Expert Systems with Applications, 38(3), 1313-1320": A Proposal of Good Practice; E. Osaba, E. Onieva, F. Diaz, R. Carballedo, Volume: 41, Issue: 4, Pages: 1530-1531, Part: 1, MARCH 2014) the Osoba E. et al have discussed our method to solve the Traveling Salesman Problem pointing that we use our developed new algorithm to compare different versions of a classical genetic algorithm, each of one with a different mutation operator and they write that this can generate some controversy. Here we shortly analyze the comment of Osaba E. et al to show that our comparing method has a chance of existence.
Dependability Assessment of the Railway Signalling Systems Based on the Stochastic Petri Nets Analysis Boudnaya, Jaouad; Mkhida, Abdelhak; Bououlid Idrissi, Badr
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.04059

Abstract

In this article, we propose a methodology to evaluate the performances of the railway signalling systems in terms of the availability. Firstly, level crossings in Morocco are presented. Secondly, a railway signalling system ERTMS level 2 modelling is proposed .The human factor and network failures are also taken into account. Finally, this system performance evaluation is proposed in every state (nominal way of functioning, degraded mode, and failure mode).
Particle Swarm Optimization Based Approach for Location Area Planning in Cellular Networks Algebary, Mays Saad
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.24975

Abstract

Location area planning problem plays an important role in cellular networks because of the trade-off caused by paging and registration signalling (i.e., location update). Compromising between the location update and the paging costs is essential in order to improve the performance of the network. The trade-off between these two factors can be optimized in such a way that the total cost of paging and location update can be minimized along with the link cost. Due to the complexity of this problem, meta-heuristic techniques are often used for analysing and solving practical sized instances. In this paper, we propose an approach to solve the LA planning problem based on the Particle Swarm Optimization (PSO) algorithm. The performance of the approach is investigated and evaluated with respect to the solution quality on a range of problem instances. Moreover, experimental work demonstrated the performance comparison in terms of different degree of mobility, paging load, call traffic load, and TRX load. The performance of the proposed approach outperform other existing meta-heuristic based approaches for the most problem instances.
Performance Evaluation of Different Feature Extractors and Classifiers for Recognition of Human Faces with Low Resolution Images Nikan, Soodeh; Ahmadi, Majid
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 2 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.28949

Abstract

Face recognition is an effective biometric identification technique used in many applications such as law enforcement, document validation and video surveillance. In this paper the effect of low resolution images which are captured in real world applications, on the performance of different feature extraction techniques combined with a variety of classification approaches is evaluated.  Gabor features and its combination with local phase quantization histogram (GLPQH) are dimensionality reduced by principal component analysis (PCA), linear discriminant analysis (LDA), locally sensitive discriminant analysis (LSDA) and neighbourhood preserving embedding (NPE) to extract discriminant image characteristics and the class label is attributed using the extreme learning machine (ELM), sparse classifier (SC), fuzzy nearest neighbour (FNN) or regularized discriminant classifier (RDC). ORL and AR databases are utilized and the results show that ELM and RDC have better performance and stability against resolution reduction, especially on Gabor-PCA and Gabor-LDA techniques. Among the interpolation approaches that we employed to enhance the image resolution, nearest neighbour outperforms other methods.

Page 1 of 2 | Total Record : 12

 1   2 

Filter by Year

2015 2015


Reset
Filter By Issues
All Issue Vol 6, No 4 (2018) Vol 6, No 3 (2018) Vol 6, No 2 (2018) Vol 6, No 1 (2018) Vol 5, No 4 (2017) Vol 5, No 3 (2017) Vol 5, No 2 (2017) Vol 5, No 1 (2017) 2017: Special Issue Vol 4, No 4 (2016) Vol 4, No 3 (2016) Vol 4, No 2 (2016) Vol 4, No 1 (2016) 2016: Special Issue Vol 3, No 4 (2015) Vol 3, No 3 (2015) Vol 3, No 2 (2015) Vol 3, No 1 (2015) Vol 2, No 4 (2014) Vol 2, No 3 (2014) Vol 2, No 2 (2014) Vol 1, No 4 (2013) Vol 1, No 3 (2013) Vol 1, No 2 (2013) More Issue