ACO Research Papers - Academia.edu (original) (raw)

The process of dividing an image into multiple regions (set of pixels) is known as Image segmentation. It will make an image easy and smooth to evaluate. Image segmentation objective is to generate image more simple and meaningful. In... more

The process of dividing an image into multiple regions (set of pixels) is known as Image segmentation. It will make an image easy and smooth to evaluate. Image segmentation objective is to generate image more simple and meaningful. In this paper present a survey on image segmentation general segmentation techniques, clustering algorithms and optimization methods. Also a study of different research also been presented. The latest research in each of image segmentation methods is presented in this study. This paper presents the recent research in biologically inspired swarm optimization techniques, including ant colony optimization algorithm, particle swarm optimization algorithm, artificial bee colony algorithm and their hybridizations, which are applied in several fields.

High-cost, low-value care permeates much of the American health care system. Congress has begun attempting to address the issue by provisions in the Affordable Care Act encouraging a shift from pay-for-volume to pay-for-performance... more

High-cost, low-value care permeates much of the American health care system. Congress has begun attempting to address the issue by provisions in the Affordable Care Act encouraging a shift from pay-for-volume to pay-for-performance practices, and by funding clinical effectiveness research through the new Patient-Centered Outcomes Research Institute (PCORI). This short paper offers an overview of the background of PCORI’s formation, the politically-derived constraints within which it is required to operate, and the types of studies it is carrying out. The paper concludes that in addition to clinical effectiveness studies, well-designed cost-effectiveness studies are needed for the development of rationalized health care practices -- current congressional restrictions notwithstanding.

The edge detection in an image has become an imminent process, with the edge of an image containing the important information related to a particular image such as the pixel intensity value, minimal path deciding factors, etc. This... more

The edge detection in an image has become an imminent process, with the edge of an image containing the important information related to a particular image such as the pixel intensity value, minimal path deciding factors, etc. This requires a specific methodology to guide in the detection of the edges, assign a Critical Path with a minimal path set and their respective energy partitions. The basis for this approach is the Optimized Ant Colony Algorithm [2], guiding through the various optimized structure in the edge detection of an image. Here we have considered the scenario with respect to a Medical Image, as the information contained in the obtained medical image is of high value and requires a redundant loss in information pertaining to the medical image obtained through various modalities. A proper plan with a minimal set as Critical Path, analysis with respect to the Power partitions or the Energy partitions with the minimal set, computation of the total time taken by the algorithm to detect an edge and retrieve the data with respect to the edge of a medical image, cumulatively considering the cliques, trade-offs in the intensity and the number of iterations required to detect an edge in an image, with or without the presence of suitable noise factors in the image are the necessary aspects being addressed in this paper. This paper includes an efficient hybrid approach to address the edge detection within an image and the consideration of various other factors, including the Shortest path out of the all the paths being produced during the traversing of the ants within a medical image, evaluation of the time duration empirically produced by the ants in traversing the entire image. We also construct a hybrid mechanism called ABCP (As Built Critical Path) factor to show the deviation produced by the algorithm in covering the entire medical image, for the metrics such as the shortest paths, computation time stamps obtained eventually and the planned schedules. This paper addresses the meta-heuristic process of ant colony optimization which is self-adaptive and adds onto the parallelism with the addressing of the hard problem offering many practical ways of subduing the effect of Critical analysis aspects as such.

Wireless Sensor Network WSN is tightly constrained for resources like energy, computational power and memory. Many applications of WSN require to communicate sensitive information at sensor nodes SN to Base station BS. The basic... more

Wireless Sensor Network WSN is tightly constrained for resources like energy, computational power and memory. Many applications of WSN require to communicate sensitive information at sensor nodes SN to Base station BS. The basic performance of WSN depends upon the path length and numbers of nodes in the path by which data is forwarded to BS. In this paper we present bio-inspired Ant Colony Optimisation ACO algorithm for Optimal Path Identification OPI for packet transmission to communicate between SN to BS. Our modified algorithm OPI using ACO is base-station driven which considers the path length and the number of hops in path for data packet transmission. This modified algorithm finds optimal path OP as well as several suboptimal paths between SN & BS which are useful for effective communication.

The U.S. health care system is expensive, fragmented, poorly organized, and fails too often to deliver high quality care that is both accessible and cost efficient. In 2014, Americans spent an estimated $3.1 trillion on health care,... more

The U.S. health care system is expensive, fragmented, poorly organized, and fails too often to deliver high quality care that is both accessible and cost efficient. In 2014, Americans spent an estimated 3.1trilliononhealthcare,averaging3.1 trillion on health care, averaging 3.1trilliononhealthcare,averaging9695 per capita and accounting for 17.8% of gross domestic product (" GDP "). Over the course of the next decade, these figures are projected to increase by an average of 5.8% per year, reaching an estimated $5.4 trillion and 19.8% of GDP by 2024. In an effort to curb this unsustainable trend of rising health care costs, Congress enacted the Medicare Shared Savings Program (" MSSP ") in conjunction with the Affordable Care Act (" ACA ") in 2010. The MSSP created a Medicare framework for Accountable Care Organizations (" ACOs "), a new health care delivery model that promotes health care provider accountability, cost efficiency, and higher quality care. At the same time, the program raises serious antitrust concerns in that it facilitates horizontal integration between competitors, thus perpetuating increased concentrations of provider market power that allow providers to drive up health care prices. This Note argues that there is a need for increased vigilance on the part of Centers for Medicare and Medicaid Services in regulating ACOs participating in the MSSP to prevent the acquisition and exercise of pricing power. Antitrust enforcement alone remains an inadequate solution to the problem of provider market power and, accordingly, additional regulatory efforts are necessary to promote competition and, at the very least, mitigate and contain the anticompetitive effects of health care market consolidation under the MSSP.

The recent popularity of applications based on wireless sensor networks (WSN) provides a strong motivation for pursuing research in different dimension of WSN. Node placement is an important task in wireless sensor network and is a... more

The recent popularity of applications based on wireless sensor networks (WSN) provides a strong motivation for pursuing research in different dimension of WSN. Node placement is an important task in wireless sensor network and is a multi-objective combinatorial problem. A multi-objective ACO (Ant Colony Optimization) algorithm based framework has been proposed in this paper. The framework optimizes the operational modes of the sensor nodes along with clustering schemes and transmission signal

Bio-inspired evolutionary algorithms are probabilistic search methods that mimic natural biological evolution. They show the behavior of the biological entities interacting locally with one another or with their environment to solve... more

Bio-inspired evolutionary algorithms are probabilistic search methods that mimic natural biological evolution. They show the behavior of the biological entities interacting locally with one another or with their environment to solve complex problems. This paper aims to analyze the most predominantly used bio-inspired optimization techniques that have been used for stock market prediction and hence present a comparative study between them.

High-cost, low-value care permeates much of the American health care system. Congress has begun attempting to address the issue by provisions in the Affordable Care Act encouraging a shift from pay-for-volume to pay-for-performance... more

High-cost, low-value care permeates much of the American health care system. Congress has begun attempting to address the issue by provisions in the Affordable Care Act encouraging a shift from pay-for-volume to pay-for-performance practices, and by funding clinical effectiveness research through the new Patient-Centered Outcomes Research Institute (PCORI). This short paper offers an overview of the background of PCORI’s formation, the politically-derived constraints within which it is required to operate, and the types of studies it is carrying out. The paper concludes that in addition to clinical effectiveness studies, well-designed cost-effectiveness studies are needed for the development of rationalized health care practices -- current congressional restrictions notwithstanding.

Today, science and technology is developing, particularly the internet of things (IoT), there is an increasing demand in the sensor field to serve the requirements of individuals within modern life. Wireless sensor networks (WSNs) was... more

Today, science and technology is developing, particularly the internet of things (IoT), there is an increasing demand in the sensor field to serve the requirements of individuals within modern life. Wireless sensor networks (WSNs) was created to assist us to modernize our lives, saving labor, avoid dangers, and that bring high efficiency at work. There are many various routing protocols accustomed to increase the ability efficiency and network lifetime. However, network systems with one settled sink frequently endure from a hot spots issue since hubs close sinks take a lot of vitality to forward information amid the transmission method. In this paper, the authors proposed combining the colony optimization algorithm ant colony optimization (ACO) routing algorithm and mobile sink to deal with that drawback and extend the network life. The simulation results on MATLAB show that the proposed protocol has far better performance than studies within the same field.