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Open Access Article
1 - A new method based on texture analysis for the classification of automatic detection of breast microcalcifications of mammography images
Zahra Maghsoodzadeh Sarvestani Jasem Jamali mhdi taghizadeh Mohammad h FatehiMammography is a diagnostic technology used in screening programs to find breast cancer early. By using two techniques for image enhancement and highlighting breast tissue microcalcifications for the desired areas by regional ROI based on fuzzy system and also Gabor fil MoreMammography is a diagnostic technology used in screening programs to find breast cancer early. By using two techniques for image enhancement and highlighting breast tissue microcalcifications for the desired areas by regional ROI based on fuzzy system and also Gabor filtering method, the study's objective was to assess the viability of automatic separation of images of breast tissue microcalcifications and to assess its accuracy. The decision tree classification algorithm is used to categorize the clusters of breast tissue microcalcifications after the clusters have been identified. The samples that are thought to have microcalcification are next highlighted and masked for segmentation, and in the last step, tissue properties are extracted. Then, it was possible to distinguish between benign and malignant forms of segmented ROI clusters with the aid of an artificial neural network (ANN). The results of this work show a high accuracy of 93% and an improvement of sensitivity of 95%, which shows that the presented solution can be reliably applied to detect breast cancer.. Manuscript profile -
Open Access Article
2 - Investigating the possibility of biasing recommendation algorithms from users' rating behavior in online social networks
Mehdi Safarpour Seyed Hadi Yaghobian Karamollah BagheriFard razieh malekhoseini Samad NejatianAs online social networks become more widely used, there is a growing focus on the role of recommender algorithms within these platforms. It is important to assess the accuracy of these algorithms in providing suitable recommendations. Our research demonstrates that the MoreAs online social networks become more widely used, there is a growing focus on the role of recommender algorithms within these platforms. It is important to assess the accuracy of these algorithms in providing suitable recommendations. Our research demonstrates that the presence of individuals and acquaintances within social networks influences user behavior in ways that are largely psychological. Many user actions on a post are influenced by their respect or closeness to the post's owner. This article explores how the predictability of user behavior towards posts from friends and acquaintances highlights the impact of emotional connections stemming from stable social relationships on post acceptance. It also raises concerns about the potential for incorrect recommendations in algorithms based on collaborative filtering due to data bias caused by these factors. Manuscript profile -
Open Access Article
3 - A New Shuffled Sub-swarm Particle Swarm Optimization Algorithm for Speech Enhancement
Masoud Geravanchizadeh Sina Ghalami Osgouei -
Open Access Article
4 - comparative study of dynamic performance of investment according to method (garch)and kalman filter
Javad Yousefi Brahman JAVAD ramezani Mehdi KhalilpourThe importance of investing for economic growth and development is enough to make it a strong incentive to reach development; one that investors care about is the information that comes from the coming part of the company.In spite of an efficient construction of the mar MoreThe importance of investing for economic growth and development is enough to make it a strong incentive to reach development; one that investors care about is the information that comes from the coming part of the company.In spite of an efficient construction of the market, it is possible to identify companies and projects. one of the main parts of the capital market is the stock exchange. and efficiency is the main and most important feature of the stock exchange. according to the significant effect of efficiency on the trade and investment level, the main purpose of this study is to compare the dynamic performance of investment according to the garch and kalman filter method.in this research , by using kalman filter , the beta - kalman filter is applied to the firms listed in tehran stock exchange ( tse ) . then beta values for these shares are estimated using garch method and the efficiency of these two methods is compared .tthe results are obtained and based on the mean square error of each method , it can be stated that kalman filter method outperforms the garch method and therefore outperforms the garch model . Manuscript profile -
Open Access Article
5 - Enhancing the Quality of Satellite Images Enhancing through Combination of Feature and Pixel Level Image Fusion
Mahnaz zarei Mansour Esmaeilpour -
Open Access Article
6 - Comparison between Recursive Least Squares and Optimal Design Methods for Audio Enhancement
Teimour Tajdari -
Open Access Article
7 - Presenting a novel method based on collaborative filtering for nearest neighbor detection in recommender systems
Mahdi Bazargani Zeinab HomayounpourRecommendation systems propose specific items to users based on their interests by analysis the user data. The main goal of this analysis is extraction of each user pattern to predict the interested items. One of the main well-known methods in recommender systems is col MoreRecommendation systems propose specific items to users based on their interests by analysis the user data. The main goal of this analysis is extraction of each user pattern to predict the interested items. One of the main well-known methods in recommender systems is collaborative filtering in which similarity measures are utilized to detect similar users to a new user. The challenging issues related to collaborative filtering are similarity and neighborhood detection. In this paper, nearest neighbor (NN) algorithm is used to detect similar neighbors to a new user. The proposed model, which is inspired by user-item method, the score of items is calculated based on a distance metric and the nearest neighbor is selected. In the presented work, we detect similar users using user-item matrix and the Euclidean distance. The proposed method is evaluated on Movielens dataset which includes 1682 items and evaluation metrics such as Accuracy, Precision, Recall, F1-measure, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) are measured. MAE of the proposed method is 0.7351 which is less than Pearson and Cosine similarities, which demonstrates the superior performance of the proposed method in similarity detection and prediction. Manuscript profile -
Open Access Article
8 - An algorithm for clustering of insurance products and users in a collaborative filtering-based insurance recommender system and evaluating its performance based on the insurance recommendation
Marzieh Amini Shirkoohi Mohammadreza YamaghaniIntroduction There are many improvements in insurance industries in these decades. So Many people refer to public and private insurance companies to get insurance services. They usually face to some challenges and issues for selecting the best and suitable insurance be MoreIntroduction There are many improvements in insurance industries in these decades. So Many people refer to public and private insurance companies to get insurance services. They usually face to some challenges and issues for selecting the best and suitable insurance because of various type of insurance and lack of enough information of insurance service. Choosing the proper insurance service always related to people personal and social features Method Prediction of customer’s insurance selection according to people personal and social property especially thier financial condition play vital role. On one hand Prediction of insurance type can help people who want to utilize insurance service. On the other hand this prediction can facilitate process of insurance for Insurers too. There are multiple important mechanisms and factors like customers clustring, analyze each class feature, detection of popular insurance in each class and using Collaborative filtering technique to offer best insurance that can influence on process of decision and selection the suitable insurance. Results The total precision value of the proposed method is 89.98% for joint insurances of similar users. Also, the total value of the F-measure of the proposed method for joint insurances between similar customers is 87.13%. Discussion Customer behavior can be predicted by available data of people’s personal and social features and type of insurance that they are chosen and rate of their satisfactions. K-means clustring algorithm and recommender systems Techniques like Collaborative filtering are two significant mechanisms to implement prediction of customer’s behaviors. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Manuscript profile -
Open Access Article
9 - Optimized computational Afin image algorithm using combination of update coefficients and wavelet packet conversion
jhila mohammadiyan Jafae Rasi -
Open Access Article
10 - A New Similarity Measure Based on Item Proximity and Closeness for Collaborative Filtering Recommendation
Sama Jamalzehi Mohammad Bagher Menhaj -
Open Access Article
11 - Design and Simulation of a Dual-Band Filtering Power Divider Using Stepped Impedance Resonators and present a novel method for generation of transmission zeros
Mojtaba Mirzaei Mohammad Amin HonarvarIn this article, a compact power divider with dual-band frequency response, designed and simulated using dual-mode stepped impedance resonators (SIRs) for WLAN application. The resonant frequencies of the proposed stepped impedance resonator are investigated using even- MoreIn this article, a compact power divider with dual-band frequency response, designed and simulated using dual-mode stepped impedance resonators (SIRs) for WLAN application. The resonant frequencies of the proposed stepped impedance resonator are investigated using even- and odd-mode analysis for frequency of 2.4 GHz and 5.2 GHz. A new method is presented for feeding the stepped impedance resonators that using the wave cancellation theory to create transmission zeros near the pass bands. Finally, four transmission zeros are generated around the both pass bands to improve the selectivity and out of band isolation. To reducing the circuit size and possibility of the feeding method implementation, two spiral stepped impedance resonators are used to design the filtering power divider. the designed power divider is simulated by HFSS software. The proposed filtering power divider has a miniature size (0.14 λg × 0.15 λg), good isolation between the output ports as well as appropriate operation at the pass bands. Manuscript profile -
Open Access Article
12 - Provide a video recommendation system using collaborative filtering and data mining methods
Reza Molaee Fard -
Open Access Article
13 - An Optimal Similarity Measure for Collaborative Filtering Using Firefly Algorithm
Fatemeh Shomalnasab Mehdi Sadeghzadeh Mansour Esmaeilpour -
Open Access Article
14 - Using an Automatic Weighted Keywords Dictionary for Intelligent Web Content Filtering
Najibeh Farzi Veijouyeh Jamshid Bagherzadeh -
Open Access Article
15 - A New Multi-Stage Feature Selection and Classification Approach: Bank Customer Credit Risk Scoring
Farshid Abdi -
Open Access Article
16 - Development of an evolutionary fuzzy expert system for estimating future behavior of stock price
Azam Goodarzi Amirhossein Amiri Shervin Asadzadeh Farhad Mehmanpazir Shahrokh Asadi -
Open Access Article
17 - Modeling and Comparative Study of the Behavior of Consumption, Production and Investment Sectors in the Money and Capital Markets of Iran
Fatemeh Masoumi Soureh Mohammadreza Nahidi Amirkhiz AliReza Bafandeh Zendeh Yousof HajiAsghariExtended Abstract With the view of the existence of different types of markets in every economy and according to the macroeconomic structure of every country, we can mention money and capital markets as the most basic financial markets. In the money market, resources MoreExtended Abstract With the view of the existence of different types of markets in every economy and according to the macroeconomic structure of every country, we can mention money and capital markets as the most basic financial markets. In the money market, resources are lent for a short period, and the most important task of this market is to create facilities for economic units and improve their liquidity. By definition, the money market is a market for trading money and other financial assets that are close substitutes for money that have a maturity of less than one year. In other words, the money market is known as the market of short-term financial instruments with the characteristics of low non-payment risk, liquidity, and high nominal value. The capital market is a market where longer-term bonds (with a maturity of one year or more) and company stocks are traded. Securities that are traded in the capital market (such as stocks and long-term bonds) are more interested in financial intermediaries. Considering that these institutions have a long-term investment horizon and prefer to invest in such long-term bonds. Several variables such as economic growth, investment growth in the production sector, investment growth in the housing sector, consumer price index, people's purchasing power, income and savings changes, employment, liquidity, inflation, exchange rate fluctuations, imports, exports, profit fluctuations, and bank interest. and... can be counted among the internal factors influencing the markets and consequently economic growth and development. One of the most basic goals of economic development is to increase the wealth and welfare of the people of the society. In the meantime, among the issues that can have a fundamental and significant role in the markets, is the behavior of economic variables, whose changes and fluctuations can affect the indices of those markets. Purpose In this research, an attempt has been made to investigate consumption behavior, production and investment, producer index and investor behavior in the years 1357 to 1397, using the Hodrick-Press filter method Methodology For this purpose, in this research, an attempt has been made to investigate the behavior of the consumption, production, and investment sectors in the money and capital markets of Iran. To achieve this goal, the annual data of variables of consumer price index, producer price index, private sector investment in new buildings in urban areas, inflation uncertainty, value of stock transactions and money supply have been used and after examining the behavior of each variable in the form of behavior Consumer consumption, producer production behavior and investor behavior for the years 1357 to 1397 have been investigated using Hodrick-Prescott filtering method, autoregression with distributed lag (ARDL) and vector autoregression (VAR) model. The price index of consumer goods and services is one of the types of price indices that shows the price changes of goods and services that are consumed by households in a period. This variable is expected to affect money and capital markets; Therefore, in this research, the consumer price index was used to evaluate the consumer's consumption behavior, and the producer price index was used to evaluate the producer's production behavior. The producer price index includes all productions (goods and services) in the country in question. The weight of each item is the sales volume (producer's sales) of that item to the total sales volume of items and the change in the price of items is the price of each item in each month compared to the price of the same item in the previous month. In the housing sector, it is expected that an expansionary monetary policy will increase the demand for housing by increasing the amount of money in the asset portfolio. Of course, this depends on various issues. For example, suppose the amount of money increases as a result of an expansionary monetary policy, people will try to buy other assets, such as housing, currency, and stocks, to use the amount of money more. If in that economy, the yield of the housing sector is higher than other assets, or if people in that society are more willing to make long-term investments. In that case, the demand for housing will increase and investors will replace housing with other assets, including stocks and currency. To investigate the behavior of these variables, the Hedrick-Prescott filter provides the unobservable time trend for the time series variable. This filter is used to separate permanent and temporary fluctuations in a time series. The working principle of this filter is based on the separation of fluctuations into permanent fluctuations (supply) and short-term fluctuations (demand). Finding After examining the behavior of the aforementioned variables using Hedrick-Prescott filtering, the results of the ARDL method with a distribution break for the money market showed that in the short term, the variables of consumer consumption behavior, producer production behavior, and investor behavior, and in the long term, all variables with money supply have a relationship But the results of the same method for the capital market show that there is no significant relationship between any of the variables with the value of stock market transactions, both in the short term and in the long term. The results of the VAR model for the money market showed that there is a significant positive relationship between the money supply and the consumer's consumption behavior and the investor's behavior of a previous period, and there is a negative significant relationship between the money supply and the producer's production behavior of a previous period, and the output resulting from this The method for the capital market indicates the existence of a significant negative relationship between the consumption behavior of the consumer, the production behavior of the producer and the behavior of the investor with the value of the stock transactions of a previous period. Conclusion The results of the ARDL method showed that in the long term in the money market, all the considered variables were related to the money supply, which indicates the confirmation of all the considered hypotheses for the money market, but none of the mentioned variables were related to the value of market transactions. Stocks were not related and it shows the rejection of all the hypotheses considered for the capital market. Manuscript profile -
Open Access Article
18 - Data mining of Iranian stock market by modeling complex network filtering based on MST
Hadi Esmaeilpour MoghadamAbstract One of the most important problems in modern finance is finding efficient ways to summarize and visualize stock market data. Modeling the filtering of complex networks in the stock market allows this to be achieved by reducing the market size, obtaining reliab MoreAbstract One of the most important problems in modern finance is finding efficient ways to summarize and visualize stock market data. Modeling the filtering of complex networks in the stock market allows this to be achieved by reducing the market size, obtaining reliable information with less disturbance. Since stock price changes are not independent of each other, the study of the correlation between stock price changes provides a better understanding of market performance for investors. Stock market analysis based on complex networks allows studying the correlation of stock prices. In this paper, using the stock market data in the Tehran Stock Exchange, the Iranian stock market network is created by the threshold method, and then the network filtering is based on MST. The results show that the filtration modeling of Iran's stock market network based on the MST can form a subset of the stock market that follows the performance of the entire market with a significant reduction in size and has a similar degree of diversification with the entire market. These analyzes provide a more in-depth insight into the structure of the stock market while reducing the size. Manuscript profile -
Open Access Article
19 - A Total Ratio of Vegetation Index (TRVI) for Shrubs Sparse Cover Delineating in Open Woodland
Hadi Fadaei -
Open Access Article
20 - A Novel Clustering Algorithm Based upon Learning Automata for Collaborative Filtering
Sara Taghipour Javad Akbari Torkestani Sara Nazari -
Open Access Article
21 - User Classification in a Personalized Recommender System using Learning Automata
Mansoureh Ghiasabadi Farahani Akbar Torkestani Mohsen Rahmani -
Open Access Article
22 - Designing a Two-Band Micro-Strip Filtering Antenna for Use in Wi-Max Telecommunication Systems and the Fifth Generation Mobile Cellular Communication Networks
Elnaz Ghanadian Mohammad Amin Honarvar -
Open Access Article
23 - One-way and two-way risk filtering using generalized dynamic factor model in Tehran Stock Exchange
amir sarabadani Ali Baghani Mohsen Hamidian Ghodratollah Emamverdi Norooz NoorolahzadeaAbstractAccording to statistics, risk estimation makes unusual predictions without focusing on the relevant factors and only focusing on a set of equations. In this study, we used a spreadsheet data set of time series and a new method for risk estimation. This estimatio MoreAbstractAccording to statistics, risk estimation makes unusual predictions without focusing on the relevant factors and only focusing on a set of equations. In this study, we used a spreadsheet data set of time series and a new method for risk estimation. This estimation was based on a generalized dynamic factor model (GDFM) and daily data series obtained from different measures of Tehran Stock Exchange over a 10-year period during 2008 to 2018. we first utilized a generalized dynamic factor model proposed by Forni et al in order to determine statistic and dynamic factors. In the second step, by using MATLAB, we estimated the joint component of the study series as Tehran Stock Exchange risk. Next, using the generalized least squares (GLS) method, we examined the impact of each of the filtered risks on the index returns. The results showed that although both risks estimated through one-side and two-side filtering substantially and significantly explain the changes in the performance of the studied indices, but the risk estimated through two-side filtering using GDFM can explain the returns changes much better and more accurate than the one-side filter using the same model. Manuscript profile -
Open Access Article
24 - To Examine Dimensions of Social Networks’ Filtering Regulations in Iran’s law
Alireza Milani Mahdi Farahnaki