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Rose Plant Horticulture performs a tremendous position in the field of trading in phrases of the enterprise. An overview of art in predicting rose plant leaf diseases using machine learning was considered in this paper. It also investigated various predictive systems mastering strategies developed by the researcher to identify rose plant diseases. Moreover, the researcher's manipulation of experimental outcomes was reviewed by current device requirements. The accuracy of the present methodologies became measured using a confusion matrix to evaluate the overall performance of the study’s work became explored. In the end, the suggestion to are expecting the effective and green predictive device learning techniques to decide the rose plant using image processing was considered.

Emergence of Internet of Things (IoT) and modern digital applications such as digital financial services and deliveries make it easy to reproduce and re-distribute digital contents thus give room to so many copyright violations of illegal use of contents that need to be resolved. Researcher have been presenting the watermarking algorithms to prevent these illicit activities to a document before distribution. However, several issues have been identified for the digital transactions in the IoT. Thus, this research proposes a new text document image watermarking algorithm which emphasizes on two most important measures, visual quality, and robustness. To boost these measures, third least significant bit has been used for insertion. In addition, to further strengthen the technique, the Pascal Triangle is applied to determine the best position for embedding. Experimental results on the standard dataset have revealed that the proposed watermarking has achieved very encouraging results with PSNR and NCC averaged 54.95db and 0.98, respectively.

PurposeThe purpose of the research is to concentrate on the most important smart metropolitan applications which are smart living, smart security and smart maintainable. In that, Power management and security is a most important problem in the current metropolitan situation.Design/methodology/approachA smart metropolitan area utilizes recent innovative technologies to improve its living, security and maintainable. The aim of this study is to recognize and resolve the difficulties in metropolitan area applications.FindingsThe main aim of this study is to reduce the metropolitan foremost energy consumption, to recharge the electric vehicles and to increase the lifetime of smart street lights.Originality/valueThe hybrid renewable energy street light applies smart resolutions to substructure and facilities in rural and metropolitan areas to create them well. This study will be applying smart metropolitan solar and wind turbine street light using renewable energy for existing areas. In future, the smart street light work will be implemented everywhere else.

Media streaming is the key innovation in technology era brings high quality on-demand and live media content to the consumer on-the-go anywhere, any time. Achieving best quality-of-service and quality-of-experience (QoE) are major concerns in the current circumstances due to increasing network usage and user demand to high quality media content. Conventional streaming approaches face numerous challenges in delivering media content to the uses without degradation of quality. An adaptive HTTP streaming is emerging content delivery approach which provides real time content delivery without compromising quality and ensuring superlative QoE. The dynamic and robust bit rate selection based on the network and client key performance indices helps to achieve best class of service to the consumer. As many standards and processes emerge in the field of Adaptive HTTP Streaming, it is necessary to study and compare the performance of different approaches based on the defined metrics. In this paper, we emphasis on the comprehensive study of different emerging adaptive streaming models such as HTTP Live Streaming, Microsoft Smooth Streaming and MPEG Dynamic Adaptive Streaming over HTTP (DASH). The experiments were conducted using Gstreamer adaptive HTTP streaming client to measure delivery performance of the approaches under varying network conditions for on-demand streaming and live streaming contents. The outcome for adaptive HTTP methods were measured and analyzed using defined performance indices. The analyzed data indicates that each delivery method performs well with respect to outlined metrics. However, overall DASH gives considerably stable performance across different network settings than other streaming approaches.

Web services is software entity allows machine to machine communication, operates as standalone unit and interoperability over network using standard web technologies such as Hypertext transfer pro...

In this world, one of the major IT (Information Technology) hub is located in Bengaluru, Karnataka, in the developing country of India and hence technological effectuation is expected. Many people are availing the state bus transport facility for their day to day life activities. This research focuses on the concept of smart bus shelter under smart city mission. It promotes the idea of a bus shelter and connected buses. The former is equipped with IoT technologies like smart lights and information kiosk, for the benefit of both stakeholders and commuters. The latter deals with bus schedule information wherein the passengers are made aware of the bus schedule, thereby minimizing the waiting time in the shelter which in turn will lead to the minimization of the crowd density in shelters and as well as buses. The bus shelter is equipped with Zigbee Receiver, Raspberry Pi and other IoT modules which sends data to a cloud periodically. The data is then analysed against the bus schedule for the ease of operations in real-time. Machine learning (ML) algorithm is applied to predict the crowd density well in advance. In addition to all this, an android mobile application and a website have been developed for educating the commuters on bus information and crowd density and help them plan their travel accordingly.

Grid computing is distributed computing that coordinates and utilizes computing power, data storage, applications and network resources in dynamic and geographically dispersed organizations. Resource management and application scheduling are two major grid computing problems. Resources are heterogeneous regarding power, architecture, configuration and availability complicating task scheduling. The aim of grid scheduling is in reducing makespan. In grid applications, users should be ensured reliable transactions. Trust is multi-dimensional factor and depends on components like entity reputation, policies and opinions of the entity. A trust based scheduling approach is proposed in this study.

With standard change in the computing architecture and distributed, wide range processing approach leverage the large data to be analyzed and extract the content. The recent advancement in Web technology enables the user to produce process and ingest content of any structure. Cloud computing helps to provide computing infrastructure, centralized storage and seamless services for organizations and users. In a digital world, data is core aspect of the economy, become part of government, enterprise, social sectors and every individual in a day to day life. Data analysis is gathering of strength in both research and production communities. There are many social networking sites, web, enterprise and IoT data require being stored in secured, centralized data store. It also demands data to be stored without any predefined schema and able to retrieve in near real time. When demand goes up application needs to be scaled to sustain for the demand. Similarly, data store should support scalability to support applications demand. Cloud providers and third-party organization offers numerous data storage, database options. This article highlights various available data storage options, suitability and limitations.

In the current work, the effect of implementing a medical image data-set query application on the grid is studied. Medical imaging is extremely data intensive, because of the size of medical image scans. Grids offer immense processing power as well as a possibility for great levels of coarse grain parallelism adequate for tackling queries on medical image datasets in a comparatively shorter time period. Apart from the security issues, which are common in the domain, the possible parallelism of grids is challenging to make use of. In the current study, the max–min method, Genetic Algorithm (GA), wherein genetic material is substituted by strings of bits while natural selection is substituted by fitness functions, Particle Swarm Optimization (PSO), wherein all particles utilize their own memories and optimum solutions are discovered on the basis of the knowledge obtained by the swarm as a whole as well as a modified PSO (PSO with 2-opt algorithms) are suggested. The outcomes of experiments proved th...

Clustering has various methods for solving the different research problems in biological domain. Analysis of gene expression data in biomedical filed is very critical task, in which various algorithms are proposed under different experimental conditions. In this proposed work the gene expression data are tested with Biclustering Bimax and Biclustering Iterative Signature Algorithm (ISA) and Biclustering Coherent Column; the experimental result show the Biclustering ISA has demonstrated a coherent manifestation contour only in the surfeit of subset of microarray experiments and produced momentous result.

Grid is a collection of heterogeneous resources for solving the complex computational problems. Workflow is a collection of atomic tasks. In this article we propose an Enhanced Ant Colony System (EACS) approach to solve grid workflow scheduling problem with two QoS parameters time and cost to minimize the makespan with low cost. We design a five heuristics for EACS approach and propose an adaptive scheme that allows ants to select heuristics in a quick convergence manner for mapping of tasks to resources based on the modified pheromone updating value. The experiment is done by the simulation with different tasks in various workflow applications and we achieve QoS as well as optimized performance.