Processing structures required in sensing are designed to convert real-world information into useful information, and there are various restrictions and performance goals depending on physical restrictions and the target applications. On the other hand, network technologies are mainly designed for data exchange in the information world, as is seen in packet communications, and do not go well with sensing structures from the viewpoints of real-time properties, spatial continuity, etc. This indicates the need for understanding the architectures and restrictions of sensor technologies and network technologies when aiming to fuse these technologies. This paper clarifies the differences between these processing structures, proposes some issues to be addressed in order to achieve real fusion of them, and presents future directions toward real fusion of sensor technologies and network technologies.

Ambient light sensors have been used to reduce power consumption of Active Matrix Liquid Crystal Displays (AMLCD) adjusting display brightness depending on ambient illumination. Discrete sensors have been commonly used for this purpose. They make module design complex. Therefore it has been required to integrate the sensors on the display panels for solving the issue. So far, many kinds of integrated sensors have been developed using Amorphous Silicon (a-Si) technology or Low Temperature Polycrystalline Silicon (LTPS) technology. These conventional integrated sensors have two problems. One is that LTPS sensors have less dynamic range due to the less photosensitivity of LTPS photodiodes. The other is that both the LTPS and a-Si sensors are susceptible to display driving noises. In this paper, we introduce a novel integrated sensor using both LTPS and a-Si technologies, which can solve these problems. It consists of vertical a-Si Schottky photodiodes and an LTPS differential converter circuit. The a-Si photodiodes have much higher photosensitivity than LTPS ones, and this contributes to wide dynamic range and high accuracy. The LTPS differential converter circuit converts photocurrent of the photodiodes to a robust digital signal. In addition it has a function of canceling the influences of the display driving noises. With the circuit, the sensor can stably and accurately work even under the noises. The performance of the sensor introduced in this paper was measured to verify the advantages of the novel design. The measurement result showed that it worked in a wide ambient illuminance range of 5-55,000 lux with small errors of below 5%. It was also verified that it stably and accurately worked even under the display driving noise. Thus the sensor introduced in this paper achieved the wide dynamic range and noise robustness.

A novel method for single image super resolution without any training samples is presented in the paper. By sparse representation, the method attempts to recover at each pixel its best possible resolution increase based on the self similarity of the image patches across different scale and rotation transforms. The experiments indicate that the proposed method can produce robust and competitive results.

This paper proposes a cross layer wireless VoIP service which integrates an Adaptive QoS Playout (AQP) algorithm, E-model, Stream Control Transmission Protocol (SCTP), IEEE 802.21 Media Independent Handover (MIH) middleware and two user motion detection services. The proposed AQP algorithm integrates the effect of playout control and lost packet retransmission based on the E-model. Besides, by using the partial reliable transmission service from SCTP and the handoff notification from MIH services in a cross layer manner, AQP can reduce the lateness loss rate and improve speech quality under high frame error rates. In the simulations, the performance of AQP is compared with a fixed playout algorithm and four adaptive playout strategies. The simulation results show that the lateness loss rate of AQP is 2% lower than that of existing playout algorithms and the R-factor is 16% higher than the compared algorithms when a network has 50 ms wired propagation delay and 2.5% frame error rate.

Fractional sampling (FS) and Doppler diversity equalization in OFDM receivers can achieve two types of diversity (path diversity and frequency diversity) simultaneously on time-varying multipath channels. However FS with a higher sampling rate requires the large amount of complexity in demodulation. In this paper, a novel sampling point selection (SPS) scheme with MMSE equalization in FS-OFDM receivers is proposed. On fast time-varying multipath channels, the proposed scheme selects the appropriate samples from the fractionally sampled signals. Through the computer simulation, it is demonstrated that with the proposed scheme, both path diversity gain and Doppler diversity gain can increase as compared to a conventional non-SPS scheme.

The logistic map is a chaotic mapping. Although several studies have examined logistic maps over real domains with infinite/finite precisions, there has been little analysis of the logistic map over integers. Focusing on differences between the logistic map over the real domain with infinite precision and the logistic map over integers with finite precision, we herein show the characteristic properties of the logistic map over integers and discuss the sequences generated by the map.

A novel approach for fast traffic classification for the high speed networks is proposed, which bases on the protocol behavior statistical features. The packet size and a new parameter named "Estimated Protocol Processing Time" are collected from the real data flows. Then a set of joint probability distributions is obtained to describe the protocol behaviors and classify the traffic. Comparing the parameters of an unknown flow with the pre-obtained joint distributions, we can judge which application protocol the unknown flow belongs to. Distinct from other methods based on traditional inter-arrival time, we use the "Estimated Protocol Processing Time" to reduce the location dependence and time dependence and obtain better results than traditional traffic classification method. Since there is no need for character string searching and parallel feature for hardware implementation with pipeline-mode data processing, the proposed approach can be easily deployed in the hardware for real-time classification in the high speed networks.

The authors focus on the improvement of Visible Light Communication Identification (VLID) system that provides positioning information via LED light bulb, which is a part of Visible Light Communication (VLC) system. The conventional VLID system provides very low positioning estimation accuracy at room level. In our approach, neither additional infrastructure nor modification is required on the transmitter side. On the receiver side, 6-axis sensor is embedded to provide 3-axis of Azimuth and 3-axis of Tilt angulations information to perform positioning estimation. We verify the proposed system characteristics by making both empirical and numerical analysis, to confirm the effectiveness of proposed system. We define two words to justify the characteristic of the proposed system, which are Field-of-View (FOV: ψc) Limit and Sensitivity (RXS) Limit. Both FOV and Sensitivity Limits have crucial impact on positioning estimation accuracy. Intuitively, higher positioning accuracy can be achieved with smaller FOV configuration in any system that has FOV. Conversely, based on system characteristics of VLID, we propose a positioning estimation scheme, namely Switching Estimated Receiver Position (SwERP) yields high accuracy even with wide FOV configuration. Cumulative Distribution Function (CDF) of error distance and Root Mean Square of Error Distance (RMSED) between experimental positions and estimated receiver positions are used to indicate the system performance. We collected 440 samples from 3 receivers' FOV configurations altogether 1320 samples within the experimental area of 1200 mm5000 mm2050 mm. The results show that with the proposed scheme, the achievable RMSEDs are in the range of 298 and 463 mm under different FOV configurations, which attained the maximum accuracy improvement over 80% comparing to the one without positioning estimation scheme. The proposed system's achievable accuracy does not depend on transmitters' orientation; only one transmitter is required to perform positioning estimation.

Let T be a tree with n nodes, in which each edge is associated with a length and a weight. The density-constrained longest (heaviest) path problem is to find a path of T with maximum path length (weight) whose path density is bounded by an upper bound and a lower bound. The path density is the path weight divided by the path length. We show that both problems can be solved in optimal O(n log n) time.

A structured codebook with various codeword configurations is proposed to overcome the sum capacity limitation in a region with finite number of users. Specifically, based on multi-user MIMO platform with a codebook of multiple orthonormal sets, called as per user unitary rate control (PU2RC), we diversify the codeword configuration of each orthonormal set and expand the corresponding codeword configuration. Numerical experiments with respect to several system parameters, such as user density and received signal to noise ratio, show that the proposed codebook offers throughput gains over the conventional system in a small to moderate number of user region.

We propose an "estimation of distribution algorithm" incorporating switching. The algorithm enables switching from the standard estimation of distribution algorithm (EDA) to the genetic algorithm (GA), or vice versa, on the basis of switching criteria. The algorithm shows better performance than GA and EDA in deceptive problems.

Ubiquitous technologies such as sensor network and RFID have enabled companies to realize more rapid and agile manufacturing and service systems. In this paper, we addresses how the huge amount of real-time events coming from these devices can be filtered and integrated to business process such as manufacturing, logistics, and supply chain process. In particular, we focus on complex event processing of sensor and RFID events in order to integrate them to business rules in business activities. We also illustrate a ubiquitous event processing system, named ueFilter, which helps to filter and aggregate sensor event, to detect event patterns from sensors and RFID by means of event pattern languages (EPL), and trigger event-condition-action (ECA) in logistics processes.

In this letter, we propose a novel frequency-domain equalization (FDE) scheme for single-carrier multiple-input multiple-output (MIMO) systems over time-varying channels. Based on frequency-domain decision-feedback equalization (FD-DFE), we design a feedforward filter with constraint such that the equalization can be easily realized segment-by-segment with the help of the overlap-save (OLS) method. Since the segment length and block length can be designed independently, our proposal sets relatively short segment length to obtain good performance in time-varying environments, and very long block length to achieve high spectral efficiency. Furthermore, we present two scenarios in the design of filters for MIMO systems.

Vision sensors provide rich sources of information, but sensing images and processing them in real time would be a challenging task. This paper introduces a vision system using SoCBase platform and presents heuristic designs of SAD correlation algorithm as a component of the vision system. Simulation results show that the vision system is suitable for real-time applications and that the heuristic designs of SAD algorithm are worth utilizing since they save a considerable amount of space with little sacrificing in quality.

This paper describes a nonlinear filter that can extract the image feature from noise corrupted image labeled self-quotient ε-filter (SQEF). SQEF is an improved self-quotient filter (SQF) to extract the image feature from noise corrupted image. Although SQF is a simple approach for feature extraction from the images, it is difficult to extract the feature when the image includes noise. On the other hand, SQEF can extract the image feature not only from clear images but also from noise corrupted images with uniform noise, Gaussian noise and impulse noise. We show the algorithm of SQEF and describe its feature when it is applied to uniform noise corrupted image, Gaussian noise corrupted image and impulse noise corrupted image. Experimental results are also shown to confirm the effectiveness of the proposed method.

The need for efficient movement and precise location of robots in intelligent robot control systems within complex buildings is becoming increasingly important. This paper proposes an indoor positioning and communication platform using Fluorescent Light Communication (FLC) employing a newly developed nine-channel receiver, and discusses a new location estimation method using FLC, that involves a simulation model and coordinate calculation formulae. A series of experiments is performed. Distance errors of less than 25 cm are achieved. The enhanced FLC system yields benefits such as greater precision and ease of use.

We propose an opportunistic spectrum access scheme for unslotted secondary users exploiting spectrum opportunities in unslotted primary networks. An analytical model is developed to investigate the performance of the proposed scheme, and numerical results are presented to evaluate the performance in unslotted primary networks.

In 2006, Yeh and Tsai proposed a mobile commerce security mechanism. However, in 2008, Yum et al. pointed out that Yeh-Tsai security mechanism is not secure against malicious WAP gateways and then proposed a simple countermeasure against the attack is to use a cryptographic hash function instead of the addition operation. Nevertheless, this paper shows that both Yeh-Tsai's and Yum et al.'s security mechanisms still do not provide perfect forward secrecy and are susceptible to an off-line guessing attack and Denning-Sacco attack. In addition, we propose a new security mechanism to overcome the weaknesses of the previous related security mechanisms.

The distribution of streaming multicast and real time audio/video applications in the Internet has been quickly increased in the Internet. Commonly, these applications rarely use congestion control and do not fairly share provided network capacity with TCP-based applications such as HTTP, FTP and emails. Therefore, Internet communities will be threatened by the increase of non-TCP-based applications that likely cause a significant increase of traffics congestion and starvation. This paper proposes a set of mechanisms, such as providing various data rates, background traffics, and various scenarios, to act friendly with TCP when sending multicast traffics. By using 8 scenarios of simulations, we use 6 layered multicast transmissions with background traffic Pareto with the shape factor 1.5 to evaluate performance metrics such as throughput, delay/latency, jitter, TCP friendliness, packet loss ratio, and convergence time. Our study shows that non TCP traffics behave fairly and respectful of the co-existent TCP-based applications that run on shared link transmissions even with background traffic. Another result shows that the simulation has low values on throughput, vary in jitter (0-10 ms), and packet loss ratio > 3%. It was also difficult to reach convergence time quickly when involving only non TCP traffics.

The unification problem for term rewriting systems (TRSs) is the problem of deciding, for a TRS R and two terms s and t, whether s and t are unifiable modulo R. We have shown that the problem is decidable for confluent simple TRSs. Here, a simple TRS means one where the right-hand side of every rewrite rule is a ground term or a variable. In this paper, we extend this result and show that the unification problem for confluent semi-constructor TRSs is decidable. Here, a semi-constructor TRS means one where all defined symbols appearing in the right-hand side of each rewrite rule occur only in its ground subterms.