Literature based study on Health Systems

Health system has been defined with a reductionist perspective. Some authors have developed arguments to expand the concept of health systems, indicating additional  dimensions that should be considered: Health systems should not be expressed in terms of their components only, but also of their interrelationships; Health systems should include not only the institutional or supply side of the health system but also the population; Health systems must be seen in terms of their goals, which include not only health improvement, but also equity, responsiveness to legitimate expectations, respect of dignity, and fair financing, among others; Health systems must also be defined in terms of their functions, including the direct provision of services, whether they are medical or public health services, but also "other enabling functions, such as stewardship, financing, and resource generation, including what is probably the most complex of all challenges, the health workforce." This paper is a review based study on existing literature.

A Review Study On Role Of AI In Healthcare

Artificial intelligence in healthcare is an overarching term used to describe the use of machine-learning algorithms and software, or artificial intelligence (AI), to mimic human cognition in the analysis, presentation, and comprehension of complex medical and health care data. Specifically, AI is the ability of computer algorithms to approximate conclusions based solely on input data. This paper presents a review study on role of AI in healthcare in short.

FACE RECOGNITION USING DISCRIMINATIVE APPROACH AND LOCAL BINARY PATTERN

Estimating human age automatically via facial image analysis has lots of potential real-world applications, such as human computer interaction and multimedia communication. However, it is still a challenging problem for the existing computer vision systems to automatically and effectively estimate human ages. In this research project, we study the problem by designing and evaluating discriminative approaches. First, we find that the gradient orientation (GO), after discarding magnitude information, provides a simple but effective representation for this problem. When combined with a support vector machine (SVM). Our experiments are conducted on the Morph dataset and two large passport datasets, one of them being the largest ever reported for recognition tasks. Second, taking advantage of these datasets, we empirically study how age gaps and related issues (including image quality, spectacles, and facial hair) affect recognition algorithms. We found surprisingly that the added difficulty of verification produced by age gaps becomes saturated after the gap is larger than four years, for gaps of up to ten years. The face boundary can be differ from different age groups. Identify the age groups of a human based on the edges and stored in the database. Compare the input image and the existing database image. The input will be coming from any sensor devices like camera, robotics, GPS (global positioning system). Discriminative methods defines the input image appears in which clusters in the pattern space

INDEXING THE DISTANCE – AN INCISIVE APPROACH FOR QUERY PROCESSING

Given two spatial datasets P (e.g., facilities) and Q (queries), a nearest neighbor  (NN) query retrieves the point(s) of P with the smallest group distance(s) to points in Q. Assuming, for example, n users at locations q1, . . . qn, a NN query outputs the facility p ε P that minimizes the sum of distances |pqi | for 1 ≤ i ≤ n that the users have to travel in order to meet there. Similarly, another NN query may report the point p ε P that minimizes the maximum distance that any user has to travel, or the minimum distance from some user to his/her closest facility. If Q fits in memory and P is indexed by an R-tree, we develop algorithms for nearest neighbors that capture several versions of the problem, including weighted queries and incremental reporting of results

ENCOURAGING SOFT QUERIES FOR INDEPENDENT E-BUSINESS WEB DATABASES

To deal with the fast expansion of the World Wide Web has made a huge number of E-Business Web databases like used vehicles, houses databases etc. to become accessible to ordinary web users. These users do not have definite query intent loosening ions when searching the E-Business Web databases and may not know how to formulate correct queries that will provide satisfactory answers. This paper proposes a unique approach of the soft query and results ranking by using query loosening mechanism in order to present ranked appropriate answers to the web users. Depending upon on the user asked query, we hypothesize how much the user concern about each attribute and assign a corresponding value to it. Then, each tuple in the asked query results is loosened according to the attribute value and is acted as a loosen query to get the likeness tuples from the database. The loosening sequence of all attributes and the loosened level on each attribute are varied with respect to the corresponding attribute values.  The appropriate answers, they are finally ranked according to their likeliness to the asked query. The performance of our approach is also determined by experimental resul

ON GENERALIZED REUSABLE VERIFICATION ENVIRONMENT BASED TESTING

Testing can be subdivided into defining or generating test inputs and test scenarios, specifying test oracles to judge testing results, and executing test cases. In this paper we introduce different techniques to tackle these problems, taking into account agent's properties and investigate automated ways to generating test inputs that can produce enormous number of different and challenging situations to exercise the agents under test. The automated generation to some extent helps dealing with the dynamic nature of the environments where the agents under test operate. In this paper we employ, three approaches to evaluate behaviours of software agents. As agents are autonomous, saying if an agent exhibits a correct behaviour or not is not as straightforward as traditional programs. A test evaluation, i.e. to evaluate test results in the first place as feedbacks from test results give important insights to guide the automated test input generation. Then, introduce monitoring as a way to collect data about test execution. The monitoring technique can deal with the distributed and asynchronous property of agent-based systems and provide a global view during test execution. Finally, we present different test generation methodologies to reveal the faults