Prof Mo Saraee's Outputs (81)

Defining a New Measure for Synchronization of Multi-Channel Epileptic Depth-EEG Signals based on Identification of Parameters of a Computational Model (2011)
Presentation / Conference
Shayegh, F., Amirfattahi, R., Sadri, S., Ansari-Asl, K., & Saraee, M. (2011, July). Defining a New Measure for Synchronization of Multi-Channel Epileptic Depth-EEG Signals based on Identification of Parameters of a Computational Model. Presented at Intelligent Systems and Control / 742: Computational Bioscience (ISC 2011), Cambridge, United Kingdom

There are various methods to measure the value of synchronization of signals. These methods usually do not consider the sources of the signals. Therefore, these methods usually underestimate the coupling phenomena of the sources of the system that ge... Read More about Defining a New Measure for Synchronization of Multi-Channel Epileptic Depth-EEG Signals based on Identification of Parameters of a Computational Model.

Defining a new measure for synchronization of multi-channel epileptic depth-EEG signals based on identification of parameters of a computational model (2011)
Presentation / Conference
Shayegh, F., Amirfattahi, R., Sadri, S., Ansari-Asl, K., & Saraee, M. (2011, July). Defining a new measure for synchronization of multi-channel epileptic depth-EEG signals based on identification of parameters of a computational model. Presented at Intelligent Systems and Control / 742 : Computational Bioscience (ISC 2011), Cambridge, UK

There are various methods to measure the value of synchronization of signals. These methods usually do not consider the sources of the signals. Therefore, these methods usually underestimate the coupling phenomena of the sources of the system that ge... Read More about Defining a new measure for synchronization of multi-channel epileptic depth-EEG signals based on identification of parameters of a computational model.

A new framework for online rule threshold adjustment in intrusion detection (2011)
Presentation / Conference
Moghimi, M., & Saraee, M. (2011, June). A new framework for online rule threshold adjustment in intrusion detection. Presented at 2011 CSI International Symposium on Computer Science and Software Engineering (CSSE), Tehran

Generally, rule-based systems work to make sense of a large volume of alerts generated by the intrusion detection systems (IDSs) every minute. Hence, it is very significant to verify that these systems are error-free and that the rules are suitable f... Read More about A new framework for online rule threshold adjustment in intrusion detection.

Toward a functional ontology of reputation for e-commerce (2011)
Presentation / Conference
Ehghaghi Kakoli, Z., Nematbakhsh, M., & Saraee, M. (2011, March). Toward a functional ontology of reputation for e-commerce. Presented at e-Society 2011, 9th International Conference IADIS, Avila, Spain

In recent years, the expansion of the internet has influenced all aspect of our lives. Trust is an important factor making business transactions possible. In a conventional setting this trust is based on all involved parties knowing each other. Howev... Read More about Toward a functional ontology of reputation for e-commerce.

A fuzzy recommender system for dynamic prediction of user's behavior (2010)
Presentation / Conference
Nadi, S., Saraee, M., & Davarpanah Jazi, M. (2010, November). A fuzzy recommender system for dynamic prediction of user's behavior. Presented at 2010 International Conference for Internet Technology and Secured Transactions (ICITST), Issue Date: 8-11 Nov. 2010, London

Analyzing and predicting navigational behavior of Web users can lead to more user friendly and efficient websites which is an important issue in Electronic Commerce. Web personalization is a common way for adapting the content of a website to the nee... Read More about A fuzzy recommender system for dynamic prediction of user's behavior.

A new path planner for autonomous mobile robots based on genetic algorithm (2010)
Presentation / Conference
Shamsinejad, P., Saraee, M., & Sheikholeslam, F. (2010, July). A new path planner for autonomous mobile robots based on genetic algorithm. Presented at he 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), Chengdu, China

One of the most important issues for autonomous mobile robots is finding paths in their environment. A local path planner must be able to design the path immediately and if possible with high accuracy and efficiency. In this p... Read More about A new path planner for autonomous mobile robots based on genetic algorithm.

Data mining approaches on discovering knowledge for decision makers: towards sustainable groundwater resources management (2010)
Presentation / Conference
Taheri, H., Safavi, H., Saraee, M., & Afghari, N. (2010, July). Data mining approaches on discovering knowledge for decision makers: towards sustainable groundwater resources management. Presented at 2010 IEEE International Conference on Advanced Management Science (ICAMS), Chengdu, China

Rapid population growth, increased irrigation, and industrial development, dramatically increased risk of vulnerability in water resources especially groundwater resources all over the world. Because of the complexity of water resources management, t... Read More about Data mining approaches on discovering knowledge for decision makers: towards sustainable groundwater resources management.

Mining time series data : case of predicting consumption patterns in steel industry (2010)
Presentation / Conference
Fazel, A., Saraee, M., & Shamsinejad, P. (2010, June). Mining time series data : case of predicting consumption patterns in steel industry. Presented at The 2nd International Conference on Software Engineering and Data Mining, Chengdu, China

Analyzing and predicting with Time series is a method which used in different fields, including consumption pattern analyzing and predicting. In this paper, required amount of inventory items have been predicted with time series. At first, desired da... Read More about Mining time series data : case of predicting consumption patterns in steel industry.

The use of genetic algorithm for feature selection in video concept detection (2010)
Presentation / Conference
Momtazpour, M., Saraee, M., & Palhang, M. (2010, May). The use of genetic algorithm for feature selection in video concept detection. Presented at The 18th Iranian Conference on Electrical Engineering (ICEE), 2010, Isfahan Iran

Video semantic concept detection is considered as an important research problem by the multimedia industry in recent years. Classification is the most accepted method used for concept detection, where, the output of the classification system is inter... Read More about The use of genetic algorithm for feature selection in video concept detection.

Application of data mining in traffic management: case of city of Isfahan (2010)
Presentation / Conference
Zamani, Z., Pourmand, M., & Saraee, M. (2010, May). Application of data mining in traffic management: case of city of Isfahan. Presented at 2010 International Conference on Electronic Computer Technology (ICECT), Kuala Lumpur, Malaysia

This paper describes the work investigating the application of data mining tools to aid in the development of traffic signal timing plans. A case study was conducted to illustrate that the use of hierarchical cluster analysis. This approach can be us... Read More about Application of data mining in traffic management: case of city of Isfahan.

Application of data mining in predicting cell phones subscribers behavior employing the contact pattern (2010)
Presentation / Conference
Mansouri, R., Saraee, M., & Amirfattahi, R. (2010, February). Application of data mining in predicting cell phones subscribers behavior employing the contact pattern. Presented at DSDE, Bangalore, India

As telecommunication services becoming competitive, client contract management in this sector has become importance as well. In regards to the fact that a huge volume of telecommunication data especially details of the cell phone conversations exist... Read More about Application of data mining in predicting cell phones subscribers behavior employing the contact pattern.

Better classifiers for credit scoring : a comparison study between self organizing maps (SOM) and support vector machine (SVM) (2009)
Presentation / Conference
Shahlaii Moghadam, A., Shalbafzadeh, A., & Saraee, M. (2009, December). Better classifiers for credit scoring : a comparison study between self organizing maps (SOM) and support vector machine (SVM). Presented at 3rd International Conference on Communications and information technology, Vouliagmeni, Athens, Greece

Credit scoring has become an increasingly important area for financial institutions. Self Organizing Maps and Support Vector Machine are two techniques of data mining which are used in different applications of businesses. In this paper, we use descr... Read More about Better classifiers for credit scoring : a comparison study between self organizing maps (SOM) and support vector machine (SVM).

Better classifiers for credit scoring: a comparison study between self organizing maps (SOM) and support vector machine (SVM) (2009)
Presentation / Conference
Shahlaii Moghada, A., Shalbafzadeh, A., & Saraee, M. (2009, December). Better classifiers for credit scoring: a comparison study between self organizing maps (SOM) and support vector machine (SVM). Presented at 3rd International Conference on Communications and Information Technology, Vouliagmeni, Athens, Greece

Credit scoring has become an increasingly important area for financial institutions. Self Organizing Maps (SOM) and Support Vector Machine(SVM) are two techniques of data mining which are being used in different applications of businesses. In this p... Read More about Better classifiers for credit scoring: a comparison study between self organizing maps (SOM) and support vector machine (SVM).

Extracting temporal rules from medical data (2009)
Presentation / Conference
Meamarzadeh, H., Khayyambashi, M., & Saraee, M. (2009, November). Extracting temporal rules from medical data. Presented at The 2009 International Conference on Computer Technology and Development, Kota, Kinabalu, Malaysia

Trauma is the main leading cause of death in children;
we need a tool to prevent and predict the outcome in these
patients. Data mining is the science of extracting the useful information from a large amount of data sets or databases that leads to... Read More about Extracting temporal rules from medical data.

Data mining cardiovascular risk factors (2009)
Presentation / Conference
Kajabadi, A., Saraee, M., & Asgari, S. (2009, October). Data mining cardiovascular risk factors. Presented at International Conference on Application of Information and Communication Technologies, 2009. AICT 2009., Baku, Azerbaija

Nowadays, medical centers collect various data in different diseases. Investigating these data and obtaining useful results and patterns with respect to the diseases are the aims of using these data. Great amount of these data and confusions results... Read More about Data mining cardiovascular risk factors.

Web search personalization: A fuzzy adaptive approach (2009)
Presentation / Conference
Norouzzadeh, M., Bagheri, A., & Saraee, M. (2009, August). Web search personalization: A fuzzy adaptive approach. Presented at 2nd IEEE International Conference on Computer Science and Information Technology, 2009. ICCSIT 2009, Beijing, China,

Today the growing rate of Web data has become so large and this is the reason for turning search engines into the major decision support systems for the Internet. In this paper, a novel and simple approach is proposed to improve Web search. The appro... Read More about Web search personalization: A fuzzy adaptive approach.

Application of self-organizing map to model a machining process (2009)
Presentation / Conference
Saraee, M., Moosavi, S., & Rezapoor, S. (2009, July). Application of self-organizing map to model a machining process. Presented at The 4th European Conference on Intelligent Management Systems in Operations, Salford, UK

Protein contact map prediction based on an ensemble learning method (2009)
Presentation / Conference
Habibi, N., & Saraee, M. (2009, January). Protein contact map prediction based on an ensemble learning method. Presented at International Conference on Computer Engineering and Technology (ICCET 2009),, Singapore

Contact map is the simplified, 2D representation of protein spatial structure. Contact map prediction is an intermediate step to predict protein 3D structure. Ensemble learning-based model is a collection of learners that is more accurate than a sing... Read More about Protein contact map prediction based on an ensemble learning method.

Optimizing classification techniques using genetic programming approach (2008)
Presentation / Conference
Saraee, M., & Sadjady, R. (2008, December). Optimizing classification techniques using genetic programming approach. Presented at 12th IEEE International Multitopic Conference, Conquering the Horizons of Future Technology (IEEE INMIC 2008), Karachi, Pakistan

Genetic Programming (GP) is a branch of Genetic
Algorithms (GA) that searches for the best operation or
computer program in search space of operations. At the same
time classification is a data mining technique used to build model of data classes... Read More about Optimizing classification techniques using genetic programming approach.

Applying data mining in medical data with focus on mortality related to accident in children (2008)
Presentation / Conference
Saraee, M., Ehghaghi, Z., Meamarzadeh, H., & Zibanezhad, B. (2008, December). Applying data mining in medical data with focus on mortality related to accident in children. Presented at IEEE International Multitopic Conference, Karachi, Pakistan

Trauma is the main leading cause of death in children; we need a tool to prevent and predict the outcome in these patients. Data mining is the science of extracting the useful information from a large amount of data sets or databases that leads to st... Read More about Applying data mining in medical data with focus on mortality related to accident in children.