Plurality voter is one of the commonest voting methods for decision making in highly-reliable applications in which the reliability and safety of the system is critical. To resolve the problem associated with sequential plurality voter in dealing with large number of inputs, this paper introduces a new generation of plurality voter based on parallel algorithms. Since parallel algorithms normally have high processing speed and are especially appropriate for large scale systems, they are therefore used to achieve a new parallel plurality voting algorithm by using (n/log n) processors on EREW shared-memory PRAM. The asymptotic analysis of the new proposed algorithm has demonstrated that it has a time complexity of O(log n) which is less than time complexity of sequential plurality algorithm, i.e. O (n log n).
Breast cancer is the most common form of cancer among women worldwide. Early detection of breast cancer can increase treatment options and patients' survivability. Mammography is the gold standard for breast imaging and cancer detection. However, due to some limitations of this modality such as low sensitivity especially in dense breasts, other modalities like ultrasound and magnetic resonance imaging are often suggested to achieve additional information. Recently, computer-aided detection or diagnosis (CAD) systems have been developed to help radiologists in order to increase diagnosis accuracy. Generally, a CAD system consists of four stages: (a) preprocessing, (b) segmentation of regions of interest, (c) feature extraction and selection, and finally (d) classification. This paper presents the approaches which are applied to develop CAD systems on mammography and ultrasound images. The performance evaluation metrics of CAD systems are also reviewed.
Breast cancer is the most prevalent cancer that affects women all over the world. Early detection and treatment of breast cancer could decline the mortality rate. Some issues such as technical reasons, which related to imaging quality and human error, increase misdiagnosis of breast cancer by radiologists. Computer-aided detection systems (CADs) are developed to overcome these restrictions and have been studied in many imaging modalities for breast cancer detection in recent years. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist. In this study, the recent CAD systems for breast cancer detection on different modalities such as mammography, ultrasound, MRI, and biopsy histopathological images are introduced. The foundation of CAD systems generally consist of four stages: Pre-processing, Segmentation, Feature extraction, and Classification. The approaches which applied to design different stages of CAD system are summarised. Advantages and disadvantages of different segmentation, feature extraction and classification techniques are listed. In addition, the impact of imbalanced datasets in classification outcomes and appropriate methods to solve these issues are discussed. As well as, performance evaluation metrics for various stages of breast cancer detection CAD systems are reviewed.
Obesity and diabetes both mediate their effects through insulin resistance and frequently co-exist. Insulin resistance is one of the key factors in the development of the metabolic syndrome. Adult females tend to develop obesity more frequently than males. One of the factors causing this difference is the pattern of changes that occur as females age from pre-menopausal to the post-menopausal stage, causing a change in the pattern of accumulation of fats. Several studies have explored and described the association between obesity and metabolic syndrome and their effect on type II diabetes. We conducted our literature search using PubMed and Google Scholar as our primary databases. We selected a total of 49 articles for review after applying the inclusion and exclusion criteria and removing the duplicate articles. We chose the full-text articles that were published in the English language only. The selected studies were randomized controlled trials and review papers. The reviewed articles showed that visceral fat, central obesity, and fasting blood sugar of post-menopausal is higher than in pre-menopausal women and needs adequate management. More studies are needed in the future to explore the patterns of the metabolic changes in obese females to provide early and better management of diabetes and prevent related complications.
In this study, collagen/alginate/hydroxyapatite beads having different proportions were prepared as bone fillers for the restoration of osteological defects. Ionic liquid was used to dissolve the collagen and subsequently the solution was mixed with sodium alginate solution. Hydroxyapatite was added in different proportions, with the rationale to enhance mechanical as well as biological properties. The prepared solutions were given characteristic bead shapes by dropwise addition into calcium chloride solution. The prepared beads were characterized using FTIR, XRD, TGA and SEM analysis. Microhardness testing was used to evaluate the mechanical properties. The prepared beads were investigated for water adsorption behavior to ascertain its ability for body fluid uptake and adjusted accordingly to the bone cavity. Drug loading and subsequently the antibacterial activity was investigated for the prepared beads. The biocompatibility was assessed using the hemolysis testing and cell proliferation assay. The prepared collagen-alginate-HA beads, having biocompatibility and good mechanical properties, have showed an option of promising biologically active bone fillers for bone regeneration.