Introduction: Content Based Image Retrieval (CBIR) is a method of image searching and retrieval in a database. In medical applications, CBIR is a tool used by physicians to compare the previous and current medical images associated with patients pathological conditions. As the volume of pictorial information stored in medical image databases is in progress, efficient image indexing and retrieval is increasingly becoming a necessity.Materials and Methods: This paper presents a new content based radiographic image retrieval approach based on HISTOGRAM of PATTERN ORIENTATIONs, namely PATTERN ORIENTATION HISTOGRAM (POH). POH represents the spatial distribution of five different PATTERN ORIENTATIONs: vertical, horizontal, diagonal down/left, diagonal down/right and non-ORIENTATION. In this method, a given image is first divided into image-blocks and the frequency of each type of PATTERN is determined in each image-block. Then, local PATTERN HISTOGRAMs for each of these image-blocks are computed.Results: The method was compared to two well known texture-based image retrieval methods: Tamura and Edge HISTOGRAM Descriptors (EHD) in MPEG-7 standard. Experimental results based on 10000 IRMA radiography image dataset, demonstrate that POH provides better precision and recall rates compared to Tamura and EHD. For some images, the recall and precision rates obtained by POH are, respectively, 48% and 18% better than the best of the two above mentioned methods.Discussion and Conclusion: Since we exploit the absolute location of the PATTERN in the image as well as its global composition, the proposed matching method can retrieve semantically similar medical images.

Face recognition is a challenging problem due to different illuminations, poses, facial expressions, and occlusions. In this paper, a new robust face recognition method is proposed based on the color and edge ORIENTATION difference HISTOGRAM. Firstly, the color and edge ORIENTATION difference HISTOGRAM is extracted using color, color difference, edge ORIENTATION, and edge ORIENTATION difference of the face image. Then the backward feature selection is employed in order to reduce the number of features. Finally, the Canberra measure is used to assess the similarity between the images. The color and edge ORIENTATION difference HISTOGRAM shows the color and edge ORIENTATION difference between two neighboring pixels. This HISTOGRAM is effective for face recognition due to the different skin colors and different edge ORIENTATIONs of the face image, which leads to a different light reflection. The proposed method is evaluated on the Yale and ORL face datasets. These datasets consist of gray-scale face images under different illuminations, poses, facial expressions, and occlusions. The recognition rate over the Yale and ORL datasets is achieved to be 100% and 98. 75%, respectively. The experimental results demonstrate that the proposed method outperforms the existing methods in face recognition.

Content-based image retrieval is one of the interesting subjects in image processing and machine vision. In image retrieval systems, the query image is compared with images in the database to retrieve images containing similar content. Image comparison is done using features extracted from the query and database images. In this paper, the features are extracted based on the human visual system. Since the human visual system considers the texture and the edge ORIENTATION in images for comparison, the colour difference HISTOGRAM associated with the image’ s texture and edge ORIENTATION is extracted as a feature. In this paper, the features are selected using the Shannon entropy criterion. The proposed method is tested using the Corel-5K and Corel-10K databases. The precision and recall criteria were used to evaluate the proposed system. The experimental results show the ability of the proposed system for more accurate retrieval rather than recently content-based image retrieval systems.

In recent years, subjects concerning Brand and brand ORIENTATION has attracted consideration of some specialists of management field especially marketing. In this research, brand ORIENTATION empowerment components, artists and craftsperson of small craft enterprises has been recognized and selected and by examining the manner of communication and their effects, a model as a process recognized and has been tested in Zanjan Province. All craftsperson employing in active handicrafts enterprises in Zanjan province in spring 1392 forms statistical society of research. By judgment sampling, 197 craftsperson from 400 handicrafts enterprises were selected. Research data was collected through questioner and secondary information. Research hypothesis were tested by using structural equations model and correlation analysis and soft wares like SPSS13, LESREL 8/5. Finally, after analysis, all suggested elements of research were approved. Based on direction analysis in process, only two sub-hypothesis was not accepted.

An Internet of Things-based security system and OpenCV technology have been developed to improve the efficiency and ease of monitoring video footage from CCTV. The face detection process is carried out using the Haar Cascade method, while facial recognition is carried out using the Local Binary PATTERN HISTOGRAM algorithm. The test results show that light intensity has a significant influence on system accuracy, but this system provides convenience in monitoring CCTV video in real-time through a webserver and improves security, especially in rooms by utilizing Internet of Things technology. The current facial recognition success rate is 72%. Therefore, for the subsequent development of the system, it is recommended to increase the success rate of facial recognition and also implement the File Transfer Protocol to ensure better and better system performance.

Introduction: Academic faculty members need to emphasize ethical principles in order to improve higher education, with the understanding of this importance, the current research was conducted with the aim of designing the ethical model of academic faculty members in Iran's higher education. Material & Methods: This research is a type of qualitative study that uses foundational data theory. The participants, including experts and faculty members of the country's public universities, who were responsible for the promotion of academic members, were selected as key informants through a targeted sampling method of 45 people. Data were collected through semi-structured interviews. The reliability and validity of the data were obtained from the two methods of reviewing the participants and recoding by experts. Data were analyzed by open, central and selective coding. Results: The results showed that the moral model of faculty members in Iran's higher education is explained in 10 main categories and 27 subcategories. Major and core categories in the form of 6 dimensions of causal conditions including (individual factors, organizational factors), core (cultural-educational, educational ethics, research ethics, scientific-executive), background conditions (higher education policies, moral activism), intervening conditions (environmental factors), strategies (micro level-university, macro level-higher education) and consequences (individual and organizational) were elevated to a higher abstract level and finally the research paradigm model was presented. Conclusion: The regulations for the promotion of academic staff members in Iran require a detailed revision of the content with an ethical and qualitative approach in order to make the indicators of the promotion regulations efficient and effective.

Background: Entrococci is a clinically important pathogenic bacterium in UTIs. CHROMagar ORIENTATION is a recently method for rapid, easy and economic isolation and identification of entrococci. This study compares the chromogenic media with traditional methods for presumptive identification of entrococci from urine specimen. Materials and Methods: We evaluated 240 gram positive cocci from urine specimens. These isolated microorganisms were inoculated on CHROMagar ORIENTATION and were presumptively identified according to manufacturer instruction. The identity of all isolated microorganisms was then confirmed by conventional identification tests and compared with the results obtained from CHROMagar ORIENTATION. Results: In this study, the sensitivity and specificity of CHROMagar ORIENTATION to identify entrococci, solely, were 100% and 40.8%, respectively. Conclusion: Although CHROMagar ORIENTATION was rapid and sensitive method for identification of entrococci in urine culture, CHROMagar ORIENTATION alone appeared not to be very specific for entrococci and needed to be combined with other tests for greater exclusivity. So, CHROMagar ORIENTATION media is not recommended for routine usages in medical laboratories in Iran.