A MEDICAL X-RAY IMAGE CLASSIFICATION AND RETRIEVAL SYSTEM

Medical image retrieval systems have gained high interest in the scientific community due to the advances in medical imaging technologies. The semantic gap is one of the biggest challenges in retrieval from large medical databases. This paper presents a retrieval system that aims at addressing this challenge by learning the main concept of every image in the medical database. The proposed system contains two modules: a classification/annotation and a retrieval module. The first module aims at classifying and subsequently annotating all medical images automatically. SIFT (Scale Invariant Feature Transform) and LBP (Local Binary Patterns) are two descriptors used in this process. Image-based and patch-based features are used as approaches to build a bag of words (BoW) using these descriptors. The impact on the classification performance is also evaluated. The results show that the classification accuracy obtained incorporating image-based integration techniques is higher than the accuracy obtained by other techniques. The retrieval module enables the search based on text, visual and multimodal queries. The text-based query supports retrieval of medical images based on categories, as it is carried out via the category that the images were annotated with, within the classification module. The multimodal query applies a late fusion technique on the retrieval results obtained from text-based and image-based queries. This fusion is used to enhance the retrieval performance by incorporating the advantages of both text-based and content-based image retrieval

The Ceremony of Tasua and Ashura as a Tourism Attractions in Iran (Case Study: Taft City)

Today, tourism as a global and social phenomenon has special implication of its own. The mechanism behind the phenomenon intertwines and takes different forms in different times and places and completely different effects on the human beings (de freitas, 2003:47). There are many types of tourism. One of the most important tourism forms is religious tourism. Religious tourism is a combination of travel and religion. Most writers are taking into account religious tourism as a part of cultural tourism. Of course, both are quite different, but these two are tied together, and religion is a part of culture. Religious Cultural Festival is an event that causes tourism to travel to a foreign country for looking for religion and heritage experience. Hence the Muharram ceremonies (Ashura and Tasua) as a religious event can be raised as an event that can familiarize domestic and foreign tourists with part of Iranian religious and culture society. Iran is an old and historical country and its present religious is Islam, most of the people are Shia? The ceremonies of Tasua and Ashura in most part of this country with different showings are done. One of those is in Taft city located in Yazd province. This research is with aims to optimize utilization of the Ashura and Tasua religious festival in order to develop Taft city and to remove barriers on the way of Taft religious tourism using the SWOT model. This evaluation model (that evaluated strengths, weaknesses, opportunities and threats) is considered one of the best strategies for tourism planning. Methods of data collection and analysis of required data is more documentaries, analytical and Survey research. The results indicate that proximity to population centers and urban centers, such as the city of Yazd and distinctive funeral\u27s style from other parts of Province, are the best strengths for this city\u27s religious tourism. Short duration of tourists stay in the cities and Lack of tourists\u27 economic outputs in the city are the weaknesses. Finally, considering to strengths, weaknesses, threats and opportunities were presented competitive - aggressive, variation, revision and defensive strategies

EVALUATING MANAGERS LEADERSHIP STYLE, CAREER SELF-EFFICACY AND BURNOUT AMONG NURSES

Introduction: The present study examined the relation between managers leadership style and burnout through career self-efficacy in the framework of a scientific model. Methodology: The study participants included 240 nurses (205 women, 35 men) from Shiraz city hospitals who were selected based on random multistage cluster sampling method. The participants completed three questionnaires of leadership style inventory, career self-efficacy and burnout. The model was analyzed using multiple regression method in simultaneous style based on Baron & Kenni stages. Results & Conclusion: The results showed that: a) managers leadership style is predictive of burnout dimensions, b) managers leadership style is predictive of career self -efficacy dimensions. Totally, the present study findings and Sobel test results showed that career self-efficacy has a moderate role between managers leadership style and burnout

The Effect of Mitomycin-C on Corneal Endothelial Cells after Photorefractive Keratectomy

Purpose: To evaluate short-term changes in central corneal endothelial cell density and morphology after photorefractive keratectomy (PRK) with mitomycin-C (MMC) 0.02% in patients with moderate myopia. Methods: In this prospective interventional case series, patients with moderate myopia (spherical equivalent refractive error from ‑4.0 to ‑8.0 D) underwent PRK with a single intraoperative application of MMC 0.02% for 40 seconds. Specular microscopy was performed preoperatively and repeated 6 months after surgery to determine changes in central corneal endothelial cell density (ECD), mean cell area (MCA) and coefficient of variation in cell size (CV). Results: Overall, 42 eyes of 21 participants with mean age of 26.2±6.3 years underwent surgery. Mean preoperative spherical equivalent refractive error was ‑5.2}1.2 D which was reduced to ‑0.4}0.5 D postoperatively (P < 0.001). Mean ECD was reduced insignificantly from 2,920±363 cells/mm2 preoperatively to 2,802±339 cells/mm2 postoperatively (P = 0.59). Similarly, there was no significant change in MCA or CV at six months (P = 0.76 and 0.52, respectively). Conclusion: Application of MMC 0.02% for 40 seconds during PRK in patients with moderate myopia did not significantly affect central corneal endothelial cell density and morphology after a 6 month follow up period

EVALUATING MANAGERS LEADERSHIP STYLE, CAREER SELF-EFFICACY AND BURNOUT AMONG NURSES

Introduction: The present study examined the relation between managers leadership style and burnout through career self-efficacy in the framework of a scientific model.&nbsp;Methodology: The study participants included 240 nurses (205 women, 35 men) from Shiraz city hospitals who were selected based on random multistage cluster sampling method. The participants completed three questionnaires of leadership style inventory, career self-efficacy and burnout. The model was analyzed using multiple regression method in simultaneous style based on Baron &amp; Kenni stages.&nbsp;Results &amp; Conclusion: The results showed that: a) managers leadership style is predictive of burnout dimensions, b) managers leadership style is predictive of career self -efficacy dimensions. Totally, the present study findings and Sobel test results showed that career self-efficacy has a moderate role between managers leadership style and burnout

A Framework For Privacy Diagnosis And Preservation In Data Publishing

Privacy preservation in data publishing aims at the publication of data with protecting private information. Although removing direct identifier of individuals seems to protect their anonymity at first glance, private information may be revealed by joining the data to other external data. Privacy preservation addresses this privacy issue by introducing k-anonymity and l-diversity principles. Accordingly, privacy preservation techniques, namely k-anonymization and l-diversification algorithms, transform data (for example by generalization, suppression or fragmentation) to protect identity and sensitive information of individuals respectively

Towards a Privacy Diagnosis Centre : Measuring k-anonymity

Most of the recent efforts addressing the issue of privacy have focused on devising algorithms for the anonymization and diversification of data

A Rule Based Classification Model to Predict Colon Cancer Survival

Introduction: Colon cancer is the second most common cancer in the world and fourth most common cancer in both sexes in Iran, whose % 8.12 of all cancers in the covers. Predict the outcome of cancer and basic clinical data about it is very important. Data mining techniques can be used to predict cancer outcome. In our country, data mining studies on colon cancer, not covered as lung or breast cancers. It seems can be with identify factors influencing on survival and modify them, increased survival of colon cancer patients. Then according to high rates of colon cancer and the benefits of data mining to predict survival, in this study examined factors influencing on the survival of these patients. Materials and Methods: We use a dataset with four attributes that include the records of 570 patients in which 327 Patients (57.4%) and 243 (42.6%) patients were males and females respectively. Trees Random Forest (TRF), AdaBoost (AD), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of colon cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Results: Out of 570 patients, 338 patients and 232 patients were alive and dead respectively. In this Study, at first sight it seems that among this techniques, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (AD, RBFN and MLP). The accuracy, sensitivity, specificity and the area under ROC curve of TRF are 0.76, 0.808, 0.70 and 0.83, respectively. Conclusions: In this study seems that Trees Random Forest model (TRF) which is a rule based classification model was the best model with the highest level of accuracy. Therefore, this model is recommended as a useful tool for colon cancer survival prediction as well as medical decision making

Z-headspring based on Fuzzy Dialectics to Linked Energy Resources

Background: The proposed work focused on a fuzzy logic controller using Zheadspring inverter. The wind and photovoltaic energy are the most significant of the energy sources today, because of their abundance of sustainability to generate electricity. Based on wind by using power conditioner the converter acts a significant key as a ingredients. While presenting the low voltage, the demanded output voltage impressively can generate in the proposed system. The Z headspring has recently considered for alternative power conversion as both voltage and capabilities. The conventional ones cannot be obtained to improve the voltage and properties from a network utilizes however, this research looking forward for finding new way to improve it. It has single power convention, received AC voltage should be low sinusoidal but this information cannot be provide due to the harmonic content. It just because of highly presented of harmonic content. Higher order harmonics are removed by using of filters. The Fuzzy logic controller for Z headspring inverter is covered in this research