Earticle

This paper considers the problem of sampling frequency offset (SFO) estimation for orthogonal frequency division multiplexing (OFDM) based digital radio mondiale (DRM) systems. In this study, the mean square error (MSE) expression for conventional SFO estimators is derived and their low-complexity variants are reported. The theoretical MSE analysis for different algorithms are validated by Monte-Carlo simulations and proven accurate.

This paper proposes a new framework for semantically interpreting and processing information of various types of sensors in heterogeneous sensor network environments. The ideal ubiquitous computing environment allows any devices interpret and use information from any sensors on mixed sensor networks. However, existing systems consider only the restricted environment where semantics of sensor information used by devices are predefined. To resolve this issue, various approaches have been studied, but there still remain several problems to realize the ubiquitous computing environment. This paper proposes a novel framework for achieving the seamless semantic interoperability. The proposed framework registers and manages information of heterogeneous sensors as well as their data. The concept of proposed framework is inherited from ISO/IEC 11179 - Metadata Registry. This paper also shows a prototype system and accomplishes a comparative evaluation against the previous approaches. The proposed framework is capable of the instant sensor data processing and enables sensor devices to use precise context information. It also supports semantic information extensibility by providing a dynamic semantic management facility.

This paper proposes an efficient full-duplex multiple input multiple output (MIMO) relay in wireless multihop networks. The proposed relay consists of a minimum mean square error (MMSE) filter, a decode-and-forward protocol processor, and a modified Alamouti encoder. In consideration of the tradeoff between performance and complexity, the MMSE filtering is presented to suppress the spatial loop interference, and the modified Alamouti encoding is simply added to improve the performance of the destination by intimately collaborating with the relay. Simulation results confirm that the proposed method outperforms the conventional methods at the expense of a reasonable increase in complexity.

Wireless video transmission suffers from degrading the quality of video service due to dynamic change of the wireless network environment. Packet-level forward error correction (FEC) enables video to be transmitted robustly as adding the redundant packets. This paper proposes two cross-layer strategies to improve the quality of video using the adaptive packet-level FEC over IEEE 802.11 networks. These strategies adaptively produce redundant packets according to the types of video frames encoded by H.264. Among the frame types, I frame (Intra frame) is the most important because it is referenced by other frames as well as decoded by itself without the prediction of any other frames. One approach, named AFEC_PI (Adaptive FEC with Priority to Intra frames), generates FEC packets only for Intra frames. The other, named AFEC_BI (Adaptive FEC with Both Intra and Inter frames), makes FEC packets for all frames, but applies differential level according to the types of frames. By using the two approaches, the received video quality is estimated based on the various error rates in wireless networks. Experimental results show that AFEC_PI improves video quality as generating fewer FEC packets than the traditional packet-level FEC and AFEC_BI increases PSNR more than AFEC_PI at a low error rate.

Thanks to the rapid development of information technology and the growth of the Internet through high speed networks, network environments have even been changed from office oriented environments based on business industries and public institutions to the interconnection of digital electronics in home networks. Home network based applications are very diverse and the remote monitoring and control areas have been studied. Recently, ZigBee has become one of the most promising technologies for home networks. ZigBee is a specification for a suite of networking, security and application software layers using small, low-power, low data rate communication technology based on IEEE 802.15.4 standard for personal area networks. Moreover, owing to the rapid growth of mobile technology, high-performance smartphones are widespread and in increasing cases are utilized as a terminal device. In this paper, we propose the design and implementation of a remote monitoring and controlling system using ZigBee networks. This system targets a home network. Web services and a smartphone are used for the client system to monitor and control the home.

In this paper, we propose a new method of image deformation. The unequal grids, which are based on the density of edges, were used for the dividing criteria in the MLS (Moving Least Squares) approximation [1] in image deformation. Depending on the importance of the image, we place the size of the grid differently and minimize the distortion that can occur when transforming the image. In this method, we introduce the image partition method using the quad tree for densely placing the small mesh in complex part with lots of edge in the image. By using this method, we can improve the quality of the images and increase the processing speed of image deformation. The validity of this method will be shown by the presentation of the results of deformed images with unequal grids.

With the increase in vehicle production and world population, more and more parking spaces and facilities are required. In this paper a new parking system called Smart Parking System (SPS) is proposed to assist drivers to find vacant spaces in a car park in a shorter time. The new system uses ultrasonic (ultrasound) sensors to detect either car park occupancy or improper parking actions. Different detection technologies are reviewed and compared to determine the best technology for developing SPS. Features of SPS include vacant parking space detection, detection of improper parking, display of available parking spaces, and directional indicators toward vacant parking spaces, payment facilities and different types of parking spaces (vacant, occupied, reserved and handicapped) through the use of specific LEDs. This paper also describes the use of an SPS system from the entrance into a parking lot until the finding of a vacant parking space. The system is designed for a four-level parking lot with 100 parking spaces and five aisles on each floor. The system architecture defines the essential design features such as location of sensors, required number of sensors and LEDs for each level, and indoor and outdoor display boards.

This paper is proposed a cell-specific reference signals (RSs)-based residual frequency offset (RFO) estimation scheme for 3GPP long term evolution (LTE) downlink in time-varying channels. For the computational efficiency and alleviate the effects of noise, two consecutive OFDM symbols which have same subcarrier index of cell-specific RSs are used. An analytical closed-form expression of the mean square error (MSE) of the post-FFT based RFO synchronization scheme is presented in terms of time-variant fading channels. In this paper, our analysis is compared to simulation results for demonstrate. Simulations are carried out within the LTE frequency division duplex (FDD) downlink systems.

In this paper, a low-complexity integer frequency offset (IFO) estimation scheme is proposed for an orthogonal frequency division multiplexing (OFDM) based digital radio mondiale plus (DRM+) system. In order to reduce the complexity of the IFO estimation, this paper addresses a grouping of time reference cell (TRC) pilot subcarriers in DRM+ system. The grouping method of TRCs is using the characteristics of phase rotation between TRC subcarriers. The performance of the proposed IFO estimator is compared with the conventional IFO estimator. The simulation results show that the proposed scheme can effectively achieve similar estimation errors in the IFO estimation as well as can be implemented with reduced computational complexity.

Recently launched a communication standard, communication architecture for network protocol design technique, defined by International Electrotechnical Commission(IEC), the need is to implement communication interconnection network architecture with logical devices, it’s a challenging task. The choice of logical device is to attain the critical time requirement of data transmission for Protective Relaying of 3ms without complicating the real-time implementation, processing power and data interconnection requirement. We are confirmed that the speed is only depends on the interconnection architecture design so as to prove the effectiveness of network design.

We applied simulated annealing algorithm and decision tree to find set of single nucleotide polymorphisms relevant to a disease and build a risk prediction model. For time complexity problem of simulated annealing caused by initial set and candidate generation, we constructed an initial set of the variants by fast heuristic algorithm and proposed a transition rules based on contribution of available variants. The experiment results show that we can obtain new set of variants with the reduced number of variants and the improved prediction performance compared to others by traditional feature selection algorithms.

In Wireless Sensor Networks (WSNs) due to unfavorable environmental conditions that sensor nodes are placed into and some other reasons, power limitation of sensor nodes is the main challenge. Emerging in-network aggregation techniques are increasingly being sought to overcome this limitation and to save energy. Data aggregation methods can be facilitated by cluster based communication model. One application of WSN is in measuring the generated signal from the object. In order to achieve full coverage, this application requires spatially dense deployment of sensor nodes and sensors observations have spatial correlation. Rate-Distortion (RD) theory as an aggregation technique can use spatial correlation to reduce the network load with the help of cluster based communication model. In this paper we introduce a more realistic spatial correlation analysis that makes the RD theory based aggregation model to be more effective. Numerical test results show the effectiveness of this analysis for data aggregation of moving object using RD theory.

Even by using the data mining, many weaknesses still existed in childhood obesity prediction and it is still far from achieving perfect prediction. This paper studies previous steps involved in childhood obesity prediction using different data mining techniques and proposed hybrid approaches to improve the accuracy of the prediction. The steps taken in this study were a review of childhood obesity, data collections, data cleaning and preprocessing, implementation of the hybrid approach, and evaluation of the proposed approach. The hybrid approach consists of the classification and regression tree, Naïve Bayes, mean value identification and Euclidean distances classification. The results from the evaluation have shown that the proposed approach has 60% sensitivity for childhood obesity prediction and 95% sensitivity for childhood overweight prediction.

Emerging technology drives technological development and innovation in diverse fields of technology. Emerging technology forecasting can predict the possible areas of emerging technology. However, it is difficult to forecast the emerging technology because most technology forecasting tasks depend on the subjective experience of experts. Patent analysis is an objective method to recognize the trends in technological development. Many patent analysis methods have been researched; these methods apply text mining techniques to analyze the text data of patent documents such as the title and abstract. This approach has some limitations, namely the computing cost and information loss associated with the preprocessing step of text mining. Therefore, we propose a new patent information analysis to overcome these problems. Using the International Patent Classification codes from the patent documents of a target technology, we construct an emerging technology forecasting model. This research combines statistical inference and neural networks to construct our model for new patent information analysis. We perform a case study to verify how our research can be practically applied, using nanotechnology as the target technology. Therefore, we contribute this research to R&D planning.

In this paper, we propose a synchronization method for Digital Radio Mondiale (DRM) receivers. In order to satisfy the advanced synchronization requirement of DRM receivers, the proposed method eliminates the initial sampling frequency synchronization (SFO) process in conventional synchronization methods. In the proposed method, sampling frequency tracking is performed after integer frequency synchronization and frame synchronization. Different correlation algorithms are applied to detect the first frame of the Orthogonal Frequency Division Multiplexing (OFDM) demodulation symbol with SFO. A frame detection algorithm that is robust to SFO is selected based on the performance analysis and simulation. Simulation results show that the proposed method reduces the time spent for initial SFO even if SFO is present in the DRM signal. In addition, it is verified that inter-cell differential correlation used between reference cells is robust to the effect of initial SFO.

Information repositories containing text data of different languages are abundant on the World Wide Web. Digital corpora of sacred text of Islam related to Quran containing Arabic language are also publicly available. The availability of these corpora and intelligent application to analyze them are vital to better comprehend the religious text of Islam. In this paper I propose a method of representing the Quranic text corpus as a graph, and apply a frequent sub-path mining algorithm on it to generate frequent patterns. I have explained how the resulting frequent patterns can be used for subjective indexing and clustering similar verses of Quran.

Holes are generated due to limited precision of deployment, and thus bypassing holes is one important issue of Wireless Sensor Networks (WSNs). In existing routing schemes using an optimal path, intermediate nodes in the path may deplete their energy quickly, which results in expansion of holes. The Ant Colony Optimization (ACO) algorithm solves this problem by balancing the traffic of data transmitted in the optimal path with transition probability. Ant Colony optimization based Location aware Routing (ACLR) is a hole detour scheme that uses nodes residual energy in transition probability to route data packets in a more energy-efficient way. The problem of ACLR is that it causes unbalanced energy consumption when local minimums occur because a packet may be retransmitted many times by one sensor node. In addition, ACLR also limits the number of nodes used for routing data. In this paper, we propose an algorithm that uses the node’s virtual position, calculated by neighbor nodes coordinates, when computing distances between sensor nodes. By using a node’s virtual positions, a routing scheme using Probability based on Virtual Position (PViP) reduces the number of backoff processes and has more neighbor nodes compared to ACLR. This will enhance the delay performance. As a result, it can balance energy consumption among nodes, improve the network lifetime by up to 7.3%, and the transmission delay by up to 2.7%.