Achieving Accuracy in Early Stage Tumor Identification Systems based on Image Segmentation and 3D Structure Analysis

Cancer is a disease which can be removed if early stage tumor identification systems efficiently and accurately work at cancer hospitals. As the accuracy in detection of tumor means to detect exact size of the tumor. Because the best way to beat cancer is early stage tumor diagnosis and quality treatment. In this research article an accuracy module is proposed for computer aided tumor diagnosis system. The ultimate proposed CAD gets image of tumor infected lung and breast images from different state of the art early stage tumor detection methodologies as micrographic and mammographic based imaging systems. For accuracy in detection of early stage tumor, image enhancement and segmentation techniques are applied according to the imaging problems at input image. Also for accurate estimation of tumor the 3D image construction and 3D structure analysis are tried to realized. The realization of the proposed CAD proves that the accuracy module can assist well the computer aided tumor diagnosis systems with almost near to 100% accuracy in early stage tumor detection and size estimation for breast and lung cancer. Keywords: Computer Aided Tumor Detection, Accurate identificatio

Distributed Virtual Disk Storage System

Distributed Virtual Disk Storage System (DVDSS) is a reliable and fully decentralized storage system which is based on the concept of Distributed Storage and Virtual Disk. It is Client / Server architecture and utilizes all free space of desktop machines of a LAN for storage purposes. DVDSS converts all storage of computers on the LAN into a large disk, create a virtual disk and provide this disk to all users of the system. Users can store their data files and folders on this disk and they can retrieve their data whenever they need. DVDSS provides a transparent and reliable access to data. It also provides data consistency and data security. The recovery of data when a node fails is also provided by DVDSS. The objective of system is to combine the all storage space of a LAN and utilize it for storage of user's data in transparent and reliable manner. Keywords: Distributed Storage, Virtual Disk, Space Utilization, data recovery, data consistency

Comparison of Residual based Cointegration Tests: Evidence from Monte Carlo

In this article ten cointegration tests based on residuals of cointegrating equation are compared on basis of stringency criterion: a robust technique for comparison of tests using Monte Carlo simulations. Two tests i.e. Phillips and Ouliaris’ Pu and Choi Durbin-Hausman statistic are the leading performers and are recommended for any sample size. The remaining eight tests are recommended for only large sample sizes of 200 or greater. The use of all these ten tests is not recommended when presence of both intercept and linear time trend is assumed in cointegrating equation unless the sample size is very large i.e. greater than 200

Comparison of Residual based Cointegration Tests: Evidence from Monte Carlo

In this article ten cointegration tests based on residuals of cointegrating equation are compared on basis of stringency criterion: a robust technique for comparison of tests using Monte Carlo simulations. Two tests i.e. Phillips and Ouliaris’ Pu and Choi Durbin-Hausman statistic are the leading performers and are recommended for any sample size. The remaining eight tests are recommended for only large sample sizes of 200 or greater. The use of all these ten tests is not recommended when presence of both intercept and linear time trend is assumed in cointegrating equation unless the sample size is very large i.e. greater than 200

Sub-Holistic Hidden Markov Model for Face Recognition

Abstract In this paper, a face recognition technique " Sub-Holistic Hidden Markov Model" ha

The Impact of Colorectal Conditions on Psychosocial Well Being of Caregivers and Patients Presenting to A Tertiary Care Hospital

Colorectal conditions such as Hirschsprung disease, anorectal malformation, fecal incontinence and spinal condition cause a significant stress among patients and their caregivers. Managing such disorders requires not only a one-time definitive surgery but a significant number of follow up visits, dietary modifications and long-term medication. The aim of this study was to estimate the psychosocial wellbeing of caregivers and patients suffering from these conditions

Artificial Intelligence (AI) in Pharmacy: An Overview of Innovations

Artificial Intelligence (AI) emerged as an intervention for data and number-related problems. This breakthrough has led to several technological advancements in virtually all fields from engineering to architecture, education, accounting, business, health, and so on. AI has come a long way in healthcare, having played significant roles in data and information storage and management – such as patient medical histories, medicine stocks, sale records, and so on; automated machines; software and computer applications like diagnostic tools such as MRI radiation technology, CT diagnosis and many more have all been created to aid and simplify healthcare measures. Inarguably, AI has revolutionized healthcare to be more effective and efficient and the pharmacy sector is not left out. During the past few years, a considerable amount of increasing interest in the uses of AI technology has been identified for analyzing as well as interpreting some important fields of pharmacy like drug discovery, dosage form designing, polypharmacology, and hospital pharmacy. Given the growing importance of AI, we wanted to create a comprehensive report which helps every practicing pharmacist understand the biggest breakthroughs which are assisted by the deployment of this field

Who is the bigger culprit? Studying impacts of traffic and land use on noise levels in CBD area of Karachi, Pakistan

The trend of urbanization has attracted increased attention towards urban areas around the world. Central business districts (CBDs) serve as the core of commercial activities of urban areas and are often associated with high-density population. Noise pollution in urban areas, especially CBDs, is considered as an important issue for planners and policy makers especially with regard to human health. Noise prediction models for CBD area of Karachi, Pakistan, have been developed in this study using land use and traffic parameters. These models show that traffic and built-up space (especially residential land use) contribute positively and vacant space contributes negatively to the noise levels. However, it was found that traffic volume has higher impact, than land use, in terms of on noise levels in CBD area. The models of this research are anticipated to be used for planning of urban CBD areas in other cities where noise levels do not meet international health standards. In addition, they would be useful in calculating the rate of traffic volume associated with residential land use