The collection of images in the web are growing larger and becoming more diverse. Retrieving images from such large collections is a challenging problem. The research communities study about image retrieval from different angles, one being text-based and the other visual-based. The text-based Image retrieval applies traditional text retrieval techniques to image annotations. The content-based Image retrieval apply image processing techniques to first extract image features and then retrieve relevant images based on the match of these features.
The two leading vendors in the BI space, Tableau and Qlik have emphasized visualization which caused other vendors to move towards visual approach in their software. Virtually all BI softwares has strong data visualization functionalities. Data visualization tools have played an important role in democratizing data and analytics and making data-driven insights available to workers throughout an organization. They are easier to operate than traditional statistical analysis software, leading to a rise in data visualization tools. Data visualization software also plays an important role in big data and advanced analytics projects.
Even though fiber optics is very efficient and better technology others. But it also has some disadvantages as well. One of them is system reconfiguration. In order to update any work area with fiber optics can take a lot more money and time because every hardware and software has to update according to the needs of fiber optics. Sometimes it’s really fine to send high speed data out from serial coaction than parallel.
Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Previously, a number of statistical algorithms had been applied to perform clustering to the data including the text documents. There are recent endeavors to enhance the performance of the clustering with the optimization based algorithms such as the evolutionary algorithms. Thus, document clustering with evolutionary algorithms became an emerging topic that gained more attention in the recent years. This paper presents an up-to-date review fully devoted to evolutionary algorithms designed for document clustering.
Using research and engaging in practice, agents can also enhance the utility of research by making the evidence more usable by improving the capacity of management and policy decision makers to use it. One such example is they develop translation tools to improve communication between research and practice. Research is an exhaustive process: there are lots words, numbers, graphs, and models, but change agents can dissect what is in... ... middle of paper ... ...ention. Web. .
Information provided by Tobii eye-tracker can provide researchers with significant information abo... ... middle of paper ... ...nments and physical products. In other words, it brings new branding measurements for the eMarkteing research, that will help marketers to improve format, layout, placement, electronic messages and etc. to induce action and increase effectiveness of the electronic sources (Tobii Technology, 2011). Overall, Tobii Eye Tracking system is bringing a completely new tool for collecting the unique information that opens a gate to the new important area of study and research for the eMarketing. Works Cited Grundberg, S. (2012, March 16).
I. INTRODUCTION Content-based image retrieval is a technique, which uses visual contents to search images from large scale image databases according to users' interests and it has been an active and fast advancing research area since the 1990s. A necessity for developing a successful CBIR system is the extraction of discriminant features to describe the images in the database. As such, the development of feature extraction algorithms has dominated the literature in the field, where the ultimate goal is to retrieve visually similar images. In this paper, retrieval is done for natural and geographic images using SIFT, GLCM and moment invariant techniques .In similar to this, GLCM and Gabor techniques are adopted for medical images.
Data Compression I. Introduction In the modern era known as the “Information Age,” forms of electronic information are steadily becoming more important. Unfortunately, maintenance of data requires valuable resources in storage and transmission, as even the presence of information in storage re-quires some power. However, some of the largest files are those that are in formats re-plete with repetition, and thus are larger than they need to be. The study of data compres-sion is the science which attempts to advance toward methods that can be applied to data in order to make it take up less space.
They also found that region based methods are also time consuming and not give effective segmentation. They proposed a new region based method based on Least Square method in order to detect objects sharply. They used a weight matrix for region based method which also takes the local information into account and also the usage of Least Square method provides optimal and fast segmentation. Comparison of their method is conducted with Otsu method and Chan-Vese method using Lena image. Their method can extract the features more accurately than other methods.
Second, larger files is the trend today and should be managed effectively. Third, read operations are performed many times so they should consider sorting the small reads to enhance performance. Fourth, the trend now is writing large files that are usually not modified but appended so they consider appending operation instead of updating or overwriting. Fifth, since multiple clients could read from the same file at the same time, there should be defined semantics for that. Sixth, they considered that high stable bandwidth is more importa... ... middle of paper ... ...the primary master is not working.