Showing 1–12 of 498 results
“IMPORTANCE OF HADOOP IN THE MODERN ERA”- PERFORMANCE AND ITS PORTABILITY
Hadoop is a flexibleرایگان!
Hadoop is a flexible and open source implementation for analyzing large datasets using Map Reduce. The file
system is developed in java that encourages portability around multiple heterogeneous software and hardware
3D Action Recognition from Novel Viewpoints
We propose a human pرایگان!
We propose a human pose representation model that transfers human poses acquired from different unknown views to a view-invariant high-level space. The model is a deep convolutional neural network and requires a large corpus of multiview training data which is very expensive to acquire. Therefore, we propose a method to generate this data by fitting synthetic 3D human models to real motion capture data and rendering the human poses from numerous viewpoints. While learning the CNN model, we do not use action labels but only the pose labels after clustering all training poses into k clusters. The proposed model is able to generalize to real depth images of unseen poses without theneed for re-training or fine-tuning. Real depth videos are passed through the model frame-wise to extract viewinvariant features. For spatio-temporal representation, we propose group sparse Fourier Temporal Pyramid which robustly encodes the action specific most discriminative output features of the proposed human pose model. Experiments on two multiview and three single-view benchmark datasets show that the proposed method dramatically outperforms existing state-of-the-art in action recognition
A big data analytics framework for scientific data management
The Ophidia projectرایگان!
The Ophidia project is a research effort addressing big data analytics requirements, issues, and challenges for eScience. We present here the Ophidia analytics framework, which is responsible for atomically processing, transforming and manipulating array-based data. This framework provides a common way to run on large clusters analytics tasks applied to big datasets. The paper highlights the design principles, algorithm, and most relevant implementation aspects of the Ophidia analytics framework. Some experimental results, related to a couple of data analytics operators in a real cluster environment, are also presented.
A Bluetooth Routing Protocol Using Evolving Fuzzy Neural Networks
In this paper, a rouرایگان!
In this paper, a routing protocol which utilizes the characteristics of Bluetooth technology is proposed for Bluetooth-based mobile ad hoc networks. The routing tables are maintained in the master devices and the routing zone radius for each table is adjusted dynamically by using evolving fuzzy neural networks. Observing there exists some useless routing packets which are helpless to build the routing path and increase the network loads in the existing ad hoc routing protocols, we selectively use multiple unicasts or one broadcast when the destination device is out of the routing zone radius coverage of the routing table. The simulation results show that the dynamic adjustment of the routing table size in each master device results in much less reply time of routing request, fewer request packets and useless packets compared with two representative protocols, Zone Routing Protocol and Dynamic Source Routing
A Bluetooth Routing Protocol Using Evolving Fuzzy Neural Networks
In this paper, a rouرایگان!
In this paper, a routing protocol which utilizes the characteristics of Bluetooth technology is proposed for Bluetooth-based mobile ad hoc networks. The routing tables are maintained in the master devices and the routing zone radius for each table is adjusted dynamically by
using evolving fuzzy neural networks
A Case-based Data Warehousing Courseware
Data warehousing isرایگان!
Data warehousing is one of the important approaches for data integration and data preprocessing. The objective of this project is to develop a web-based interactive courseware to help beginner data warehouse designers to reinforce the key concepts of data warehousing using a case study approach. The case study is to build a data warehouse for a university student enrollment prediction data mining system. This data warehouse is able to generate summary reports as input data files for a data mining system to predict future student enrollment. The data sources include: (1) the enrollment data from California State University, Sacramento and (2) the related public data of California. The ourseware is designed to build the data warehouse systematically using a set of 4 demonstrations covering the following data warehousing topics: fundamentals, design principle, building an enterprise data warehouse using incremental approach, and aggregation.
A cloud based and Android supported scalable home automation system
In this paper, an Anرایگان!
In this paper, an Android based home automation system that allows multiple users to control the appliances by an Android application or through a web site is presented. The system has three hardware components: a local device to transfer signals to home appliances, a web server to store customer records and support services to the other components, and a mobile smart device running Android application. Distributed cloud platforms and Google services are used to support messaging between the components .The prototype implementation of the proposed system is evaluated based on the criteria considered after the requirement analysis for an adequate home automation system. The paper presents the outcomes of a survey carried out regarding the properties of home automation systems, and also the evaluation results of the experimental tests conducted with volunteers on running prototype.
A cloud computing framework on demand side management game in smart energy hubs
The presence of enerرایگان!
The presence of energy hubs in the future vision of energy networks creates an opportunity for electrical engineers to move toward more efficient energy systems. At the same time, it is envisioned that smart grid can cover the natural gas network in the near future. This paper modifies the classic Energy Hub model to present an upgraded model in the smart environment entitling ‘‘Smart Energy Hub’’. Supporting real time, two-way communication between utility companies and smart energy hubs, and allowing intelligent infrastructures at both ends to manage power consumption necessitates large-scale real-time computing capabilities to handle the communication and the storage of huge transferable data. To manage communications to large numbers of endpoints in a secure, scalable and highly-available environment, in this paper we provide a cloud computing framework for a group of smart energy hubs. Then, we use game theory to model the demand side management among the smart energy hubs. Simulation results confirm that at the Nash equilibrium, peak to average ratio of the total electricity demand reduces significantly and at the same time the hubs will pay less considerably for their energy bill.
A Cluster Based Multi-Radio Multi-Channel Assignment Approach in Wireless Mesh Networks
Wireless mesh networرایگان!
Wireless mesh networks (WMNs) are receiving increasing attention as an effective means to provide broadband internet. Throughput is a major QoS in WMNs keeping in view of their perceived application areas and others being connectivity and reliability. WMNs use multiple radios and orthogonal communication channels to reduce interference and increase throughput and at the same time providing path redundancy, reliability and connectivity. In our work we propose a cluster based channel assignment scheme for WMNs and assume that the wireless radio interfaces are equipped with IEEE 802.11 network interface cards (NICs). We have extensively simulated our work using ns-2 network simulator and compared it against well-known channel assignment techniques and our result exhibits a significant increase in throughput.
A collaborative methodology for tacit knowledge management: Application to scientific research
Tacit knowledge, whiرایگان!
Tacit knowledge, which refers to the know-how, is critical to understand and reuse since it is located in the human heads. It represents the foremost element for human and team evaluation. Seeking for tacit knowledge is achieved only by communicating with the concerned persons, which makes losing it axiomatic if people leave their work without documenting their know-how. Thus, providing a collaborative environment based on a common conceptualization of the domain to formalize the experts’ knowledge and to share their outcomes is required. However, some barriers pertaining to cultural and social factors such as personality traits impede capturing the conceptual model. To cope with these issues, we have proposed a generic two-step methodology that copes with human barriers when capturing the domain experts’ tacit knowledge, their skills, and seeds terms in order to converge to a common knowledge representation. Considering the scientific research management as a use case, we followed the proposed methodology to formalize our scientific research knowledge in the context of network and communication research field. Based on the generated ontology, we have developed a semantic web platform that allows collaboratively annotating experts’ knowledge in a computer interpretable format that can be shared and reused by human and machines. Our evaluation is based on end users’ quality of experience and feedbacks.
A Comparison of Approaches to Large-Scale Data Analysis
There is currently cرایگان!
There is currently considerable enthusiasm around the MapReduce(MR) paradigm for large-scale data analysis . Although the basic control flow of this framework has existed in parallel SQL database management systems (DBMS) for over 20 years, some have called MR a dramatically new computing model [8, 17].
A comparison of neural network models, fuzzy logic, and multiple linear regression for prediction of hatchability
Application of approرایگان!
Application of appropriate models to approximate the performance function warrants more precise prediction and helps to make the best decisions in the poultry industry. This study reevaluated the factors affecting hatchability in laying hens from 29 to 56 wk of age