Information2014, 5(4), 652-660; doi:10.3390/info5040652 - published 3 December 2014 Show/Hide Abstract
Abstract: Conventional fluorescent light sources, as well as incandescent light sources are gradually being replaced by Light Emitting Diodes (LEDs) for reducing power consumption in the image display area for multimedia application. An LED light source requires a controller with a low-power operation. In this paper, a low-power technique using adiabatic operation is applied for the implementation of LED controller with a stable constant-current, a low-power and low-heat function. From the simulation result, the power consumption of the proposed LED controller using adiabatic operation was reduced to about 87% in comparison with conventional operation with a constant VDD. The proposed circuit is expected to be an alternative LED controller which is sensitive to external conditions such as heat.
Information2014, 5(4), 634-651; doi:10.3390/info5040634 - published 1 December 2014 Show/Hide Abstract
Abstract: To surface the Deep Web, one crucial task is to predict whether a given web page has a search interface (searchable HyperText Markup Language (HTML) form) or not. Previous studies have focused on supervised classification with labeled examples. However, labeled data are scarce, hard to get and requires tediousmanual work, while unlabeled HTML forms are abundant and easy to obtain. In this research, we consider the plausibility of using both labeled and unlabeled data to train better models to identify search interfaces more effectively. We present a semi-supervised co-training ensemble learning approach using both neural networks and decision trees to deal with the search interface identification problem. We show that the proposed model outperforms previous methods using only labeled data. We also show that adding unlabeled data improves the effectiveness of the proposed model.
Information2014, 5(4), 622-633; doi:10.3390/info5040622 - published 1 December 2014 Show/Hide Abstract
Abstract: Communications, Navigation, Surveillance/Air Traffic Management (CNS/ATM) systems utilize digital technologies, satellite systems, and various levels of automation to facilitate seamless global air traffic management. Automatic Dependent Surveillance-Broadcast (ADS-B), the core component of CNS/ATM, broadcasts important monitoring information, such as the location, altitude, and direction of aircraft, to the ground. However, ADS-B data are transmitted in an unencrypted (or unprotected) communication channel between ADS-B sensors and Air Traffic Control (ATC). Consequently, these data are vulnerable to security threats, such as spoofing, eavesdropping, and data modification. In this paper, we propose a method that protects the ADS-B data transmitted between ADS-B sensors and ATC using Simple Public Key Infrastructure (SPKI) certificates and symmetric cryptography. The SPKI certificates are used to grant transmission authorization to the ADS-B sensors, while symmetric cryptography is used to encrypt/decrypt the ADS-B data transmitted between the ADS-B sensors and ATC. The proposed security framework comprises an ADS-B sensor authentication module, an encrypted data processing module, and an ADS-B sensor information management module. We believe that application of the proposed security framework to CNS/ATM will enable it to effectively obviate security threats, such as ground station flood denial, ground station target ghost injection, and ADS-B data modification.
Information2014, 5(4), 612-621; doi:10.3390/info5040612 - published 14 November 2014 Show/Hide Abstract
Abstract: In recent years, a large portion of smartphone applications (Apps) has targeted context-aware services. They aim to perceive users’ real-time context like his/her location, actions, or even emotion, and to provide various customized services based on the inferred context. However, context-awareness in mobile environments has some challenging issues due to limitations of devices themselves. Limited power is regarded as the most critical problem in context-awareness on smartphones. Many studies have tried to develop low-power methods, but most of them have focused on the power consumption of H/W modules of smartphones such as CPU and LCD. Only a few research papers have recently started to present some S/W-based approaches to improve the power consumption. That is, previous works did not consider energy consumed by context-awareness of Apps. Therefore, in this paper, we focus on the power consumption of context-aware Apps. We analyze the characteristics of context-aware Apps in a perspective of the power consumption, and then define two main factors which significantly influence the power consumption: a sort of context that context-aware Apps require for their services and a type of ways that a user uses them. The experimental result shows the reasonability and the possibility to develop low-power methods based on our analysis. That is, our analysis presented in this paper will be a foundation for energy-efficient context-aware services in mobile environments.
Information2014, 5(4), 602-611; doi:10.3390/info5040602 - published 12 November 2014 Show/Hide Abstract
Abstract: This paper describes the design of a high-efficiency vehicular roof-mounted antenna for wireless access for vehicular environment (WAVE) communication systems used for ubiquitous intelligent systems. The main objective of the ubiquitous intelligent system’s automotive IT technology is to enhance the connectivity among vehicles to ensure seamless communication and to reduce the initial access time using high-performance antenna systems. The efficiency of WAVE communication systems used for ubiquitous intelligent systems depends on the antenna efficiency. The proposed vehicular antenna for WAVE communication systems shows an improvement of approximately 4.77 dB in the return loss, as compared with a conventional antenna system.
Information2014, 5(4), 587-601; doi:10.3390/info5040587 - published 11 November 2014 Show/Hide Abstract
Abstract: In this paper, firstly, a new intuitionistic fuzzy (IF) entropy has been put forward, which considered both the uncertainty and the hesitancy degree of IF sets. Through comparing with other entropy measures, the advantage of the new entropy measure is obvious. Secondly, based on the new entropy measure, a new decision making method of a multi-attribute decision making problem was subsequently put forward, in which attribute values are expressed with IF values. In the cases of attribute weights, completely unknown and attribute weights are partially known. Two methods were constructed to determine them. One method is an extension of the ordinary entropy weight method, and the other method is a construction the optimal model according to the minimum entropy principle. Finally, two practical examples are given to illustrate the effectiveness and practicability of the proposed method.