This paper proposes a novel approach of constructing statistical preference models for context-aware personalized applications such as recommender systems. In constructing context-aware statistical preference models, one of the most important but difficult problems is acquiring a large amount of training data in various contexts/situations. In particular, some situations require a heavy workload to set them up or to collect subjects capable of answering the inquiries under those situations. Because of this difficulty, it is usually done to simply collect a small amount of data in a real situation, or to collect a large amount of data in a supposed situation, i.e., a situation that the subject pretends that he is in the specific situation to answer inquiries. However, both approaches have problems. As for the former approach, the performance of the constructed preference model is likely to be poor because the amount of data is small. For the latter approach, the data acquired in the supposed situation may differ from that acquired in the real situation. Nevertheless, the difference has not been taken seriously in existing researches. In this paper we propose methods of obtaining a better preference model by integrating a small amount of real situation data with a large amount of supposed situation data. The methods are evaluated using data regarding food preferences. The experimental results show that the precision of the preference model can be improved significantly.

In block transmission systems, blind channel shortening methods are known to be effective to reduce the influence of interblock interference which degrades the performance when the length of a channel impulse response is extremely long. Conventional methods assume that the transmitted signal is uncorrelated; however, this assumption is invalid in practical systems such as OFDM with null carriers and MC-CDMA. In this paper, we consider blind channel shortening methods for block transmissions when the transmitted samples within a block are correlated. First, the channel shortening ability of a conventional method is clarified. Next, a new method which exploits the fact that the transmitted samples in different blocks are uncorrelated is introduced. It is shown that the proposed method can shorten the channel properly under certain conditions. Finally, simulation results of OFDM and MC-CDMA systems are shown to verify the effectiveness of the proposed method compared with a conventional one.

This paper presents the analysis of in-band interference caused by pulse-based ultra-wideband (UWB) systems. The analysis contains both plain Impulse Radio UWB (IR-UWB) and Transmitted Reference UWB (TR-UWB) systems as a source of interference. The supposed victim is a narrowband BPSK system with a band-pass filter. The effect of pulse-based UWB systems is analyzed in terms of bit error rate. The analysis is given in terms of the specific combinations of pulse repetition frequency and center frequency of the narrowband bandpass filter. In those situations, the UWB interference cannot be modeled as a Gaussian noise. It also manifests situations in which the victim is under the severest or the slightest interference from TR-UWB. According to its result, the analysis is validated via simulation.

Exact bit error probabilities (BEP) are derived in closed-form for binary pulsed direct sequence (DS-) and hybrid direct sequence time hopping code division multiple access (DS/TH-CDMA) systems that have potential applications in ultra-wideband (UWB) communications. Flat Nakagami fading channel is considered and the characteristic function (CF) method is adopted. An exact expression of the CF is obtained through a straightforward method, which is simple and good for any arbitrary pulse shape. The CF is then used to obtain the exact BEP that requires less computational complexity than the method based on improved Gaussian approximation (IGA). It is shown under identical operating conditions that the shape of the CF, as well as, the BEP differs considerably for the two systems. While both the systems perform comparably in heavily faded channel, the hybrid system shows better BEP performance in lightly-faded channel. The CF and BEP also strongly depend on chip length and chip-duty that constitute the processing gain (PG). Different combinations of the parameters may result into the same PG and the BEP of a particular system for a constant PG, though remains nearly constant in a highly faded channel, may vary substantially in lightly-faded channel. A comparison of the results from the exact method with those from the standard Gaussian approximation (SGA) reveals that the SGA, though accurate for both the systems in highly-faded channel, becomes extremely optimistic for low-duty systems in lightly-faded channel. The SGA also fails to track several other system trade-offs.

This paper presents a method of scalable lossless image compression by means of lossy coding. A progressive decoding capability and a full decoding for the lossless rendition are equipped with the losslessly encoded bit stream. Embedded coding is applied to large-amplitude coefficients in a wavelet transform domain. The other wavelet coefficients are encoded by a context-based entropy coding. The proposed method slightly outperforms JPEG-LS in lossless compression. Its rate-distortion performance with respect to progressive decoding is close to that of JPEG2000. The spatial scalability with respect to resolution is also available.

In this letter we propose a robust detection algorithm for audio watermarking for copyright protection. The watermark is embedded in the time domain of an audio signal by the normally used spread spectrum technique. The scheme of detection is an improvement of the conventional correlation detector. A high-pass filter is applied along with the linear prediction error filter for whitening the audio signal and an adaptive threshold is chosen for decision comparing. Experimental results show that our detection algorithm outperforms the conventional one not only because it improves the robustness to normal attacks but also because it can provide the robustness to time-invariant pitch-scale modification.

Compact and planar active integrated antenna arrays with a high power multi-stage amplifier were developed with effective heat sink mechanism. By attaching an aluminum plate to the backside of the creased amplifier circuit board, effective cooling can be achieved. The nonlinear behavior of the amplifier agrees well with the simulation based on the Angelov model. The high power amplifier circuit consisted of the three-stage amplifier and operated with an output power of 4 W per each element at 5.8 GHz. The 32-element active integrated antenna array stably operated with the output power of 120 W under the effective heat sink design. With a weight of 4 kg, the weight-to-output power ratio and the volume-to-output power ratio of the antenna array are 33.3 g/W and 54.5 cm3/W, respectively. Wireless power transmission was also successfully demonstrated.

Packet delivery in Proxy Mobile IPv6 (PMIPv6) relies on an anchor node called LMA. All packets sent by a source node reach a receiver node via LMA, even though the two nodes attach to the same MAG. In some scenarios, PMIPv6 results in high delivery latency and processing costs due to this unnecessary detour. To address this issue, several PMIPv6 route optimization schemes have been proposed. However, high signaling costs and excessive delays remain when handover is performed. For this reason, we propose an enhanced PMIPv6 route optimization (EPRO) scheme. In addition, we analyze the performance of the EPRO. Analytical results indicate that the EPRO outperforms previous schemes in terms of signaling overhead and handover latency.

Even though weighted frequent pattern (WFP) mining is more effective than traditional frequent pattern mining because it can consider different semantic significances (weights) of items, existing WFP algorithms assume that each item has a fixed weight. But in real world scenarios, the weight (price or significance) of an item can vary with time. Reflecting these changes in item weight is necessary in several mining applications, such as retail market data analysis and web click stream analysis. In this paper, we introduce the concept of a dynamic weight for each item, and propose an algorithm, DWFPM (dynamic weighted frequent pattern mining), that makes use of this concept. Our algorithm can address situations where the weight (price or significance) of an item varies dynamically. It exploits a pattern growth mining technique to avoid the level-wise candidate set generation-and-test methodology. Furthermore, it requires only one database scan, so it is eligible for use in stream data mining. An extensive performance analysis shows that our algorithm is efficient and scalable for WFP mining using dynamic weights.

The basic playout scheme (BAS) is designed not to take into account network impairment information during silence periods. We propose a jitter-robust playout mechanism (RST), which uses silence description (SID) packets. The lateness loss percentages are compared between the BAS and the RST algorithms. We report that the accuracy of the playout schedule calculation in the BAS is getting worse as the previous silence interval increases and our proposed RST algorithm is more effective in removing high jitter than the BAS. Under high jitter Internet conditions, the accuracy of the estimates and therefore the resulting of VoIP playout quality can be significantly improved by using the SID packets in the playout schedule recalculation.

In video streaming applications over the Internet, TCP-friendly rate control schemes are useful for improving network stability and inter-protocol fairness. However, they do not always guarantee a smooth video streaming. To simultaneously satisfy both the network and user requirements, video streaming applications should be quality-adaptive. In this paper, we propose a new quality adaptation mechanism to adjust the quality of congestion-controlled video stream by controlling the frame rate. Based on the current network condition, it controls the frame rate of video stream and the sending rate in a TCP-friendly manner. Through a simulation, we prove that our adaptation mechanism appropriately adjusts the quality of video stream while improving network stability.

We propose a selective detection scheme based on pulse repetition considering both BER (Bit Error Rate) performance and complexity in coherent UWB (Ultra Wide Band) systems. To take system complexity into account, the proposed scheme transmits the UWB signals by pulse repetition at the transmitter, like conventional PRC (Pulse Repetition Coding). However, to effectively improve BER performance of the system, the proposed scheme performs selective detection by estimating the SNR (Signal-to-Noise Ratio) of the received pulse-repeated signal at the UWB receiver.

In an RFID search protocol, a reader uses a designated query instead of an unspecified query commonly used in RFID authentication protocols. Due to this fundamental difference, techniques used in RFID authentication protocols may not be suitable for RFID search protocols. Tan et al.'s protocol, however, is based on techniques used in previous works such as using random values. In this paper, we propose two RFID search protocols, one based on static ID and the other based on dynamic ID, both which does not require additional measures to satisfy security requirements of RFID protocols. We achieve this by using counters.

An important objective of surveillance sensor networks is to effectively monitor the environment, and detect, localize, and classify targets of interest. The optimal sensor placement enables us to minimize manpower and time, to acquire accurate information on target situation and movement, and to rapidly change tactics in the dynamic field. Most of previous researches regarding the sensor deployment have been conducted without considering practical input factors. Thus in this paper, we apply more real-world input factors such as sensor capabilities, terrain features, target identification, and direction of target movements to the sensor placement problem. We propose a novel and efficient hybrid steady-state genetic algorithm giving low computational overhead as well as optimal sensor placement for enhancing surveillance capability to monitor and locate target vehicles. The proposed algorithm introduces new two-dimensional geographic crossover and mutation. By using a new simulator adopting the proposed genetic algorithm developed in this paper, we demonstrate successful applications to the wireless real-world surveillance sensor placement problem giving very high detection and classification rates, 97.5% and 87.4%, respectively.

Broadcasting is an elementary operation in wireless multi-hop networks. Flooding is a simple broadcast protocol but it frequently causes serious redundancy, contention and collisions. Probability based methods are promising because they can reduce broadcast messages without additional hardware and control packets. In this paper, the counter-based scheme which is one of the probability based methods is focused on as a broadcast protocol, and the RAD (Random Assessment Delay) Extension is proposed to improve the original counter-based scheme. The RAD Extension can be implemented without additional hardware, so that the strength of the counter-based scheme can be preserved. In addition, we propose the additional algorithm called Hop Count Aware RAD Extension to establish shorter path from the source node. Simulation results show that both of the RAD Extension and the Hop Count Aware RAD Extension reduce the number of retransmitting nodes by about 10% compared with the original scheme. Furthermore, the Hop Count Aware RAD Extension can establish almost the same path length as the counter-based scheme.

In this article, we propose a vehicle positioning method that can estimate positions of cars even in areas where the GPS is not available. For the estimation, each car measures the relative distance to a car running in front, communicates the measurements with other cars, and uses the received measurements for estimating its position. In order to estimate the position even if the measurements are received with time-delay, we employed the time-delay tolerant Kalman filtering. For sharing the measurements, it is assumed that a car-to-car communication system is used. Then, the measurements sent from farther cars are received with larger time-delay. It follows that the accuracy of the estimates of farther cars become worse. Hence, the proposed method manages only the states of nearby cars to reduce computing effort. The authors simulated the proposed filtering method and found that the proposed method estimates the positions of nearby cars as accurate as the distributed Kalman filtering.

Amidst conflicting views about whether soft cooperative energy detection scheme (SCEDS) outperforms hard cooperative energy detection scheme (HCEDS) greatly in cognitive radio, we establish the bridge that mathematically connects SCEDS and HCEDS by closed approximations. Through this bridge, it is demonstrate that, if the number of detectors of HCEDS is 1.6 times as that of SCEDS, they have nearly the same performance which is confirmed by numerical simulations, enabling a quantitative evaluation of the relation between them and a resolution of the conflicting views.

To realize the compact ultra-wideband (UWB) bandpass filters, a novel filter prototype with two short-circuited stubs loaded at both sides of a stepped-impedance resonator (SIR) via the parallel coupled lines is proposed based on a distributed filter synthesis theory. The equivalent circuit of this filter is established, while the corresponding 7-pole Chebyshev-type transfer function is derived for filter synthesis. Then, a distributed-circuit-based technique was presented to synthesize the elements' values of this filter. As an example, a FCC UWB filter with the fractional bandwidth (FWB) @ -10 dB up to 110% was designed using the proposed prototype and then re-modeled by commercial microwave circuit simulator to verify the correctness and accuracy of the synthesis theory. Furthermore, in terms of EM simulator, the filter was further-optimized and experimentally-realized by using microstrip line. Good agreements between the measurement results and theoretical ones validate the effectiveness of our technique. In addition, compared with the conventional SIR-type UWB filter without short-circuited stubs, the new one significantly improves the selectivity and out-of-band characteristics (especially in lower one -45 dB@1-2 GHz) to satisfy the FCC's spectrum mask. The designed filter also exhibits very compact size, quite low insertion loss, steep skirts, flat group delay and the easily-fabricatable structure (the coupling gap dimension in this filter is 0.15 mm) as well. Moreover, it should be noted that, in terms of the presented design technique, the proposed filter prototype can be also used to easily realize the UWB filters with other FBW even greater than 110%.

The Letter deals with constant false alarm rate (CFAR) detection of random Gaussian target signals embedded in Gaussian clutter with unknown covariance. The proposed detector is analyzed on the assumption that clutter covariance is not known and a random target signal has low-rank property. The low-dimensional subspace-based approach leads to a robust false alarm rate (RFAR) detector. The detection performance loss and the false alarm stability loss to unknown clutter covariance have been evaluated for example scenario.

Target tracking is one of the key applications of Wireless Sensor Networks (WSNs) that forms basis for numerous other applications. The overall procedures of target tracking involve target detection, localization, and tracking. Because of the WSNs' resource constraints (especially energy), it is highly desired that target tracking should be done by involving as less number of sensor nodes as possible. Due to the uncertain behavior of the target and resulting mobility patterns, this goal becomes harder to achieve without predicting the future locations of the target. The presence of a prediction mechanism may allow the activation of only the relevant sensors along the future course, before actually the target reaches the future location. This prior activation contributes to increasing the overall sensor networks lifetime by letting non-relevant nodes sleep. In this paper, first, we introduce a Yaw rate aware sensor wAkeup Protocol (YAP) for the prediction of future target locations. Second, we present improvements on the YAP design through the incorporation of adaptability. The proposed schemes are distributive in nature, and select relevant sensors to determine the target track. The performance of YAP and A-YAP is also discussed on different mobility patterns, which confirms the efficacy of the algorithm.