Recognizing cars is a highly difficult task due to the wide variety in the appearance of cars from the same car manufacturer. Therefore, the car logo is the most prominent indicator of the car manufacturer. The captured logo image suffers from several problems, such as a complex background, differences in size and shape, the appearance of noise, and lighting circumstances. To solve these problems, this paper presents an effective technique for extracting and recognizing a logo that identifies a car. Our proposed method includes four stages: First, we apply the k-medoids clustering method to extract the logo and remove the background and noise. Secondly, the logo image is converted to grayscale and also converted to a binary imag

    With the explosive growth of data, it has become very difficult for a person to process the data and find the right information from it. So, to discover the right information from the colossal amount of data that is available online, we need information filtering systems. Recommendation systems (RS) help users find the most interesting information among the options that are available. Ratings given by the users play a vital role in determining the purposes of recommendations. Earlier, researchers used a user’s rating history to predict unknown ratings, but recently a user’s review has gained a lot of attention as it contains a lot of relevant information about a user’s decision. The proposed system makes an attempt to deal w

In this work, we introduce an intuitionistic fuzzy ideal on a KU-semigroup as a generalization of the fuzzy ideal of a KU-semigroup. An intuitionistic fuzzy k-ideal and some related properties are studied. Also, a number of characteristics of the intuitionistic fuzzy k-ideals are discussed. Next, we introduce the concept of intuitionistic fuzzy k-ideals under homomorphism along with the Cartesian products.

In this work, watershed transform method was implemented to detect and extract tumors and abnormalities in MRI brain skull stripped images. An adaptive technique has been proposed to improve the performance of this method.Watershed transform algorithm based on clustering techniques: K-Means and FCM were implemented to reduce the oversegmentation problem. The K-Means and FCM clustered images were utilized as input images to the watershed algorithm as well as of the original image. The relative surface area of the extracted tumor region was calculated for each application. The results showed that watershed trnsform algorithm succeedeed to detect and extract the brain tumor regions very well according to the consult of a specialist doctor a

Data mining is one of the most popular analysis methods in medical research. It involves finding patterns and correlations in previously unknown datasets. Data mining encompasses various areas of biomedical research, including data collection, clinical decision support, illness or safety monitoring, public health, and inquiry research. Health analytics frequently uses computational methods for data mining, such as clustering, classification, and regression. Studies of large numbers of diverse heterogeneous documents, including biological and electronic information, provided extensive material to medical and health studies.

One of the challenging and active research topics in the recent years is Facial Expression. This paper presents the method to extract the features from the facial expressions from still images. Feature extraction is very important for classification and recognition process. This paper involve three stages which contain capture the images, pre-processing and feature extractions. This method is very efficient in feature extraction by applying haar wavelet and Karhunen-Loève Transform (KL-T). The database used in this research is from Cohen-Kanade which used six expressions of anger, sadness fear, happiness, disgust and surprise. Features that have been extracted from the image of facial expressions were used as inputs to the neural networ

     Heart disease is a non-communicable disease and the number 1 cause of death in Indonesia. According to WHO predictions, heart disease will cause 11 million deaths in 2020. Bad lifestyle and unhealthy consumption patterns of modern society are the causes of this disease experienced by many people. Lack of knowledge about heart conditions and the potential dangers cause heart disease attacks before any preventive measures are taken. This study aims to produce a system for Predicting Heart Disease, which benefits to prevent and reduce the number of deaths caused by heart disease. The use of technology in the health sector has been widely practiced in various places and one of the advanced technologies is machine lea

E-mail is an efficient and reliable data exchange service. Spams are undesired e-mail messages which are randomly sent in bulk usually for commercial aims. Obfuscated image spamming is one of the new tricks to bypass text-based and Optical Character Recognition (OCR)-based spam filters. Image spam detection based on image visual features has the advantage of efficiency in terms of reducing the computational cost and improving the performance. In this paper, an image spam detection schema is presented. Suitable image processing techniques were used to capture the image features that can differentiate spam images from non-spam ones. Weighted k-nearest neighbor, which is a simple, yet powerful, machine learning algorithm, was used as a clas

The current study aimed to investigate the viability of biofilm formation klebsilla pneumoniae and Staphylococcus aureus. 440 urine samples were collected from patients suffering from urinary tract infection (UTI) from those who were admitted and visitors to Al-Ramadi Teaching Hospital, Al-Yarmouk Teaching Hospital, Al-Ramadi Teaching Hospital for women and children and , Teaching Laboratories in the Medical City for both genders for a period extended from 5 July, 2017 to 10 October, 2017. Samples were diagnosed by culturing them on a selective media and by biochemical testes , also, diagnosis was ensured by using VITEK-2 compact system. Results showed that K.pneumoniae isolation ratio was 17.1%(68) and S.aureus ratio was 13.1%(52). Thei

Two hundred and ten specimens include urine, blood and ear swab were collected from different hospitals in Baghdad city; 85 (40%) isolates were diagnosed as Proteus spp. with (82%), (11.7%) and (5.8%) represented in urine, blood and ear swab specimens respectively. PCR technique was shown 30 (35.3%) isolates were positive for specific Urease C gene that used in rapid detection of Proteus vulgaris. The ability for chondritinase production was checked invetro and invevo, 24 (80%) isolates of P. vulgaris were showed ablity to chondritinase production and the isolate (p17) has higher enzyme activity value to (175.2U/ml). The Chondroitinase was purified by three short steps only included precipitate with 60% saturated of ammonium sulfate, dia