محمد قاسم زاده
استادیار، دانشکده مهندسی برق و کامپیوتر- دانشگاه یزد- یزد- ایران
[ 1 ] - ارایه یک فیلتر ترکیبی هوشمند فازی برای حذف نویز تصاویر پزشکی
تصاویر پزشکی اهمیت ویژهای در تشخیص پزشکی دارند. در این مقاله یک روش ترکیبی هوشمند مبتنی بر یک سیستم فازی- عصبی برای حذف نویز از این گونه تصاویر ارایه میشود. چندین روش عمومی و مفید برای حذف نویز از تصاویر وجود دارند؛ بهعنوان نمونه میتوان از فیلتر میانگین، فیلتر میانه، فیلتر میانه وزن‌دار و فیلتر میانه تطبیقی نام برد. در رابطه با حذف نویز از تصاویر پزشکی به علت ویژگی خاص آنها نیاز به قابلیت...
[ 2 ] - Comparing k-means clusters on parallel Persian-English corpus
This paper compares clusters of aligned Persian and English texts obtained from k-means method. Text clustering has many applications in various fields of natural language processing. So far, much English documents clustering research has been accomplished. Now this question arises, are the results of them extendable to other languages? Since the goal of document clustering is grouping of docum...
[ 3 ] - QoS-Based web service composition based on genetic algorithm
Quality of service (QoS) is an important issue in the design and management of web service composition. QoS in web services consists of various non-functional factors, such as execution cost, execution time, availability, successful execution rate, and security. In recent years, the number of available web services has proliferated, and then offered the same services increasingly. The same web ...
[ 4 ] - An Improved Algorithm for Network Reliability Evaluation
Binary Decision Diagram (BDD) is a data structure proved to be compact in representation and efficient in manipulation of Boolean formulas. Using Binary decision diagram in network reliability analysis has already been investigated by some researchers. In this paper we show how an exact algorithm for network reliability can be improved and implemented efficiently by using CUDD - Colorado Univer...
[ 5 ] - تشخیص خودکار مدولاسیون با استفاده از برنامه نویسی ژنتیک و شبکه عصبی چند لایه پرسپترون
This paper shows how we can make advantage of using genetic programming in selection of suitable features for automatic modulation recognition. Automatic modulation recognition is one of the essential components of modern receivers. In this regard, selection of suitable features may significantly affect the performance of the process. In this research we implemented our model by using appropria...
[ 6 ] - Discovering Popular Clicks\' Pattern of Teen Users for Query Recommendation
Search engines are still the most important gates for information search in internet. In this regard, providing the best response in the shortest time possible to the user's request is still desired. Normally, search engines are designed for adults and few policies have been employed considering teen users. Teen users are more biased in clicking the results list than are adult users. This leads...
[ 7 ] - A Hybrid Machine Learning Method for Intrusion Detection
Data security is an important area of concern for every computer system owner. An intrusion detection system is a device or software application that monitors a network or systems for malicious activity or policy violations. Already various techniques of artificial intelligence have been used for intrusion detection. The main challenge in this area is the running speed of the available implemen...
[ 8 ] - Reduction of Computational Complexity in Finite State Automata Explosion of Networked System Diagnosis (RESEARCH NOTE)
This research puts forward rough finite state automata which have been represented by two variants of BDD called ROBDD and ZBDD. The proposed structures have been used in networked system diagnosis and can overcome cominatorial explosion. In implementation the CUDD - Colorado University Decision Diagrams package is used. A mathematical proof for claimed complexity are provided which shows ZBDD ...
[ 9 ] - Using Generalized Language Model for Question Matching
Question and answering service is one of the popular services in the World Wide Web. The main goal of these services is to finding the best answer for user's input question as quick as possible. In order to achieve this aim, most of these use new techniques foe question matching. . We have a lot of question and answering services in Persian web, so it seems that developing a question matching m...
[ 10 ] - A version numbering scheme for informational objects used in VM live migration
Various numbering schemes are used to track different versions and revisions of files, software packages, and documents. One major challenge in this regard is the lack of an all-purpose, adaptive, comprehensive and efficient standard. To resolve the challenge, this article presents Quadruple Adaptive Version Numbering Scheme. In the proposed scheme, the version identifier consists of four integ...
[ 11 ] - Analytical evaluation of an innovative decision-making algorithm for VM live migration
In order to achieve the virtual machines live migration, the two "pre-copy" and "post-copy" strategies are presented. Each of these strategies, depending on the operating conditions of the machine, may perform better than the other. In this article, a new algorithm is presented that automatically decides how the virtual machine live migration takes place. In this approach, the virtual machine m...
[ 12 ] - An Evolutionary Multi-objective Discretization based on Normalized Cut
Learning models and related results depend on the quality of the input data. If raw data is not properly cleaned and structured, the results are tending to be incorrect. Therefore, discretization as one of the preprocessing techniques plays an important role in learning processes. The most important challenge in the discretization process is to reduce the number of features’ values. This operat...
[ 13 ] - یک شبکۀ حافظۀ طولانی کوتاه‌مدت عمیق مبتنی بر توجه تکاملی برای پیش‌بینی سری‌های زمانی
پیش‌بینی طولانی‌مدت سری‌های زمانی یک مسئله، مهم و چالش‌برانگیز است. امروزه شبکه‌های عمیق به‌خصوص شبکه‌های حافظۀ طولانی کوتاه‌مدت (LSTM)، با موفقیت در پیش‌بینی سری‌های زمانی به کار گرفته شده‌اند. شبکه‌های LSTM وابستگی‌های طولانی‌مدت را حفظ می‌کنند؛ اما توانایی آنها در اختصاص درجه‌های مختلف توجه به ویژگی‌های زیر پنجره در چند مرحلۀ زمانی کافی نیست. همچنین، عملکرد این شبکه‌ها به‌شدت به مقادیر ابر...
[ 14 ] - Improvement of generative adversarial networks for automatic text-to-image generation
This research is related to the use of deep learning tools and image processing technology in the automatic generation of images from text. Previous researches have used one sentence to produce images. In this research, a memory-based hierarchical model is presented that uses three different descriptions that are presented in the form of sentences to produce and improve the image. The proposed ...