A new cooperative MAC protocol called the busy tone cooperative medium access control (BT-COMAC) protocol is proposed to overcome the drawbacks and maximize the advantages of existing schemes. This scheme uses a new metric called decibel power to decide an appropriate helper node. Using received power strength is more efficient in selecting an appropriate helper node, especially in a densely populated network, than the effective transmission rates used in conventional schemes. All communication nodes in a communication service area are assumed to move independently. Two performance metrics are used: System throughput and channel access delay. A performance evaluation of the BT-COMAC protocol is conducted using a computer simulation over a slow fading wireless channel, and its performance results are compared with those of four existing schemes. The numerical results show that the BT-COMAC protocol improves the system throughput by approximately 15% as compared to the best existing scheme.

In this paper, in order to solve the problems of a narrow viewing angle and the flip effect in a three-dimensional (3D) integral imaging display, we propose an improved system by using an eye tracking method based on the Kinect sensor. In the proposed method, we introduce two types of calibration processes. First process is to perform the calibration between two cameras within Kinect sensor to collect specific 3D information. Second process is to use a space calibration for the coordinate conversion between the Kinect sensor and the coordinate system of the display panel. Our calibration processes can provide the improved performance of estimation for 3D position of the observer's eyes and generate elemental images in real-time speed based on the estimated position. To show the usefulness of the proposed method, we implement an integral imaging display system using the eye tracking process based on our calibration processes and carry out the preliminary experiments by measuring the viewing angle and flipping effect for the reconstructed 3D images. The experimental results reveal that the proposed method extended the viewing angles and removed the flipping images compared with the conventional system.

We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

In this paper, we analyze the effect of the coherence bandwidth of wireless channels on leakage suppression methods for discrete Fourier transform (DFT)-based channel estimation in orthogonal frequency division multiplexing (OFDM) systems. Virtual carriers in an OFDM symbol cause orthogonality loss in DFT-based channel estimation, which is referred to as the leakage problem. In order to solve the leakage problem, optimal and suboptimal methods have already been proposed. However, according to our analysis, the performance of these methods highly depends on the coherence bandwidth of wireless channels. If some of the estimated channel frequency responses are placed outside the coherence bandwidth, a channel estimation error occurs and the entire performance worsens in spite of a high signal-to-noise ratio.

One of major purposes of these standard technologies is to ensure interoperability between entities from different vendors and enable interworking between various technologies. As interoperability and interworking are essential for machine-to-machine communications (M2M) and Internet of Things (IoT) for them to achieve their ultimate goal, i.e., things to be connected each other, multiple standards organizations are now working on development M2M/IoT related specifications. This paper reviews the current activities of some of the most relevant standardization bodies in the area of M2M and IoT: third-generation partnership project (3GPP) core and radio network aspects, broadband forum, and oneM2M. The major features and issues being focused upon in these standards bodies are summarized. Finally, some key common trends among the different bodies are identified: a common service layer platform, new technologies mitigating an explosive growth of network traffic, and considerations and efforts related to the development of device management technologies.

In this study, software-based countermeasures against a side-channel cryptanalysis of the Rabbit stream cipher were developed using Moteiv's Tmote Sky, a popular wireless sensor mote based on the Berkeley TelosB, as the target platform. The countermeasures build upon previous work by improving mask generation, masking and hiding other components of the algorithm, and introducing a key refreshment scheme. Our contribution brings improvements to previous countermeasures making the implementation resistant to higher-order attacks. Four functional metrics, namely resiliency, robustness, resistance, and scalability, were used for the assessment. Finally, performance costs were measured using memory usage and execution time. In this work, it was demonstrated that although attacks can be feasibly carried out on unprotected systems, the proposed countermeasures can also be feasibly developed and deployed on resource-constrained devices, such as wireless sensors.

The recent rise of the three-dimensional television (3DTV) industry has led to a wide exploitation of the dual-lens stereoscopic camera. However, when the zoom-in function is used, it is possible that a camera object is magnified only with a fixed convergence point, thereby leading to visual discomfort. In this paper, we propose several methods based on which a convergence point can be adjusted to prevent visual discomfort during zoom-in for a dual-lens stereoscopic camera. Further, we produce 3D contents by applying the proposed methods to certain cases and at certain distances and conduct a subjective evaluation. On the subjective evaluation, 48 subjects watch the 3D contents created by the proposed methods and score the stages of the visual comfort. The result of the subjective evaluation shows that some of the proposed methods are more efficient than the others. We hope that these proposed high-efficiency methods can be applied to produce a dual-lens stereoscopic camera that allows convenient stereoscopic photography.

Traditional block cipher Advanced Encryption Standard (AES) is widely used in the field of network security, but it has high overhead on each operation. In the 15th international workshop on information security applications, a novel lightweight and low-power encryption algorithm named low-power encryption algorithm (LEA) was released. This algorithm has certain useful features for hardware and software implementations, that is, simple addition, rotation, exclusive-or (ARX) operations, non-Substitute-BOX architecture, and 32-bit word size. In this study, we further improve the LEA encryptions for cloud computing. The Web-based implementations include JavaScript and assembly codes. Unlike normal implementation, JavaScript does not support unsigned integer and rotation operations; therefore, we present several techniques for resolving this issue. Furthermore, the proposed method yields a speed-optimized result and shows high performance enhancements. Each implementation is tested using various Web browsers, such as Google Chrome, Internet Explorer, and Mozilla Firefox, and on various devices including personal computers and mobile devices. These results extend the use of LEA encryption to any circumstance.

Meta-analysis is a statistical integration method that delivers an opportunity to overview the entire result by integrating and analyzing many quantitative research results. This study will find meaningful mediator variables for criterion variables that affect purchase and repurchase intentions in e-commerce, on the basis of the results of a meta-analysis. We reviewed a total of 114 e-commerce studies published in Korean journals between 2000 and 2014, where a cause and effect relationship is established between variables that are specified in the conceptual model of this study. In this meta-analysis, the path between trust and purchase intention showed the biggest effect size. The second biggest effect size was found in the path between commitment and purchase intention, while the smallest one was obtained with perceived. Thus, we present the theoretical and practical implications of these results and discuss the differences among these results through a comparative analysis with previous studies.

Corner detection and feature extraction are essential aspects of computer vision problems such as object recognition and tracking. Feature detectors such as Scale Invariant Feature Transform (SIFT) yields high quality features but computationally intensive for use in real-time applications. The Features from Accelerated Segment Test (FAST) detector provides faster feature computation by extracting only corner information in recognising an object. In this paper we have analyzed the efficient object detection algorithms with respect to efficiency, quality and robustness by comparing characteristics of image detectors for corner detector and feature extractors. The simulated result shows that compared to conventional SIFT algorithm, the object recognition system based on the FAST corner detector yields increased speed and low performance degradation. The average time to find keypoints in SIFT method is about 0.116 seconds for extracting 2169 keypoints. Similarly the average time to find corner points was 0.651 seconds for detecting 1714 keypoints in FAST methods at threshold 30. Thus the FAST method detects corner points faster with better quality images for object recognition.