Microcalcification detection is a very important issue in early diagnosis of breast cancer. Generally physicians use mammogram images for this task; however, sometimes analyzing these images become a hard task because of problems in images such as high brightness values, dense tissues, noise, and insufficient contrast level. In this paper, we present a novel technique for the task of microcalcification detection. This technique consists of three steps. The first step is focused on removing pectoral muscle and unnecessary parts from the mammogram images by using cellular neural networks (CNNs), which makes this a novel process. In the second step, we present a novel image enhancement technique focused on enhancing lesion intensities called the automated lesion intensity enhancer (ALIE). In the third step, we use a special CNN structure, named multistable CNNs. After applying the combination of these methods on the MIAS database, we achieve 82.0% accuracy, 90.9% sensitivity, and 52.2% specificity values.
Travel time plays a major role in handling the traffic rate. Bluetooth technology is one of the approaches this time observable. Traffic tracking, vehicle determination on a certain route, and travel time information can be obtaine dusing the bluetooth data gathered using this tool. The Bluetooth technology will be used to analyze certain features affecting travel time results. Highway travel time can be used as a new and efficient data collection tool through the bluetooth sensors which are widely used today. The central control software system consists of a comprehensive system for storing and organizing data at a central location, processing data in vehicles and displaying it to drivers. The central system architecture can be used to display congested road data to the driver, including scenarios, text messages and visuals, identified by traffic information message signs (VMS), which are also linked to the system on the particular highway via a data fusion process in line with data from a variety of sources, for example sensors. Providing information about travel time distribution, both average and variance, will play a more effective role in drivers' high likelihood of arriving on time and in selecting efficient routes. In order to determine the travel time flow, an inhomogeneous data fusion tracking is performed by combining the scattered collected data with distance detectors. With this method preferred in the research, road travel time flows are determined with the help of sensors. The travel time of the roads without sensors is obtained from the data of GPSbased service providers. In addition to the travel time flow, the Dempster-Shafer theory is combined with the travel time results from the distance sensors. Based on the travel time results obtained, the method of improvement in travel time flow has been developed.
Solution of linear algebra systems may come out with "ill-condition" or "well-condition" based on input information and solution methods. The aim of this study is to determine and correction of problems that may come out from the solution of matrix equations by computers and to calculate. A x f linear algebra.
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