H.6.3.2. Feature evaluation and selection
1. MLIFT: Enhancing Multi-label Classifier with Ensemble Feature Selection

Sh kashef; H. Nezamabadi-pour

Volume 7, Issue 3 , Summer 2019, Pages 355-365

Abstract
  Multi-label classification has gained significant attention during recent years, due to the increasing number of modern applications associated with multi-label data. Despite its short life, different approaches have been presented to solve the task of multi-label classification. LIFT is a multi-label ...  Read More

H.6.2.2. Fuzzy set
2. Identification of Cement Rotary Kiln in Noisy Condition using Takagi-Sugeno Neuro-fuzzy System

N. Moradkhani; M. Teshnehlab

Volume 7, Issue 3 , Summer 2019, Pages 367-375

Abstract
  Cement rotary kiln is the main part of cement production process that have always attracted many researchers’ attention. But this complex nonlinear system has not been modeled efficiently which can make an appropriate performance specially in noisy condition. In this paper Takagi-Sugeno neuro-fuzzy ...  Read More

D.4. Data Encryption
3. A New Method for Encryption of Color Images based on Combination of Chaotic Systems

H. Khodadadi; A. Zandvakili

Volume 7, Issue 3 , Summer 2019, Pages 377-383

Abstract
  This paper presents a new method for encryption of color images based on a combination of chaotic systems, which makes the image encryption more efficient and robust. The proposed algorithm generated three series of data, ranged between 0 and 255, using a chaotic Chen system. Another Chen system was ...  Read More

G.3.2. Logical Design
4. Fast Mux-based Adder with Low Delay and Low PDP

H. Tavakolaee; Gh. Ardeshir; Y. Baleghi

Volume 7, Issue 3 , Summer 2019, Pages 385-392

Abstract
  Adders, as one of the major components of digital computing systems, have a strong influence on their performance. There are various types of adders, each of which uses a different algorithm to do addition with a certain delay. In addition to low computational delay, minimizing power consumption is also ...  Read More

H.6.3.1. Classifier design and evaluation
5. Ensemble-based Top-k Recommender System Considering Incomplete Data

M. Moradi; J. Hamidzadeh

Volume 7, Issue 3 , Summer 2019, Pages 393-402

Abstract
  Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user-interest (Top-k recommendation problem). Demanding sufficient ...  Read More

H.7. Simulation, Modeling, and Visualization
6. A Data-driven Method for Crowd Simulation using a Holonification Model

J. Peymanfard; N. Mozayani

Volume 7, Issue 3 , Summer 2019, Pages 403-409

Abstract
  In this paper, we present a data-driven method for crowd simulation with holonification model. With this extra module, the accuracy of simulation will increase and it generates more realistic behaviors of agents. First, we show how to use the concept of holon in crowd simulation and how effective it ...  Read More

H.3. Artificial Intelligence
7. Forecasting Gold Price using Data Mining Techniques by Considering New Factors

A.R. Hatamlou; M. Deljavan

Volume 7, Issue 3 , Summer 2019, Pages 411-420

Abstract
  Gold price forecast is of great importance. Many models were presented by researchers to forecast gold price. It seems that although different models could forecast gold price under different conditions, the new factors affecting gold price forecast have a significant importance and effect on the increase ...  Read More

G.4. Information Storage and Retrieval
8. RRLUFF: Ranking function based on Reinforcement Learning using User Feedback and Web Document Features

V. Derhami; J. Paksima; H. Khajeh

Volume 7, Issue 3 , Summer 2019, Pages 421-442

Abstract
  Principal aim of a search engine is to provide the sorted results according to user’s requirements. To achieve this aim, it employs ranking methods to rank the web documents based on their significance and relevance to user query. The novelty of this paper is to provide user feedback-based ranking ...  Read More

Document and Text Processing
9. A Joint Semantic Vector Representation Model for Text Clustering and Classification

S. Momtazi; A. Rahbar; D. Salami; I. Khanijazani

Volume 7, Issue 3 , Summer 2019, Pages 443-450

Abstract
  Text clustering and classification are two main tasks of text mining. Feature selection plays the key role in the quality of the clustering and classification results. Although word-based features such as term frequency-inverse document frequency (TF-IDF) vectors have been widely used in different applications, ...  Read More

Document and Text Processing
10. External Plagiarism Detection based on Human Behaviors in Producing Paraphrases of Sentences in English and Persian Languages

A. Shojaie; F. Safi-Esfahani

Volume 7, Issue 3 , Summer 2019, Pages 451-466

Abstract
  With the advent of the internet and easy access to digital libraries, plagiarism has become a major issue. Applying search engines is one of the plagiarism detection techniques that converts plagiarism patterns to search queries. Generating suitable queries is the heart of this technique and existing ...  Read More

H.3.8. Natural Language Processing
11. Feature Engineering in Persian Dependency Parser

S. Lazemi; H. Ebrahimpour-komleh

Volume 7, Issue 3 , Summer 2019, Pages 467-474

Abstract
  Dependency parser is one of the most important fundamental tools in the natural language processing, which extracts structure of sentences and determines the relations between words based on the dependency grammar. The dependency parser is proper for free order languages, such as Persian. In this paper, ...  Read More

12. Adaptive Robust Control for Trajectory Tracking of Autonomous underwater Vehicles on Horizontal Plane

N. Zendehdel; S. J. Sadati; A. Ranjbar Noei

Volume 7, Issue 3 , Summer 2019, Pages 475-486

Abstract
  This manuscript addresses trajectory tracking problem of autonomous underwater vehicles (AUVs) on the horizontal plane. Adaptive sliding mode control is employed in order to achieve a robust behavior against some uncertainty and ocean current disturbances, assuming that disturbance and its derivative ...  Read More