Product return is a critical but controversial issue. To deal with such a vague return problem, businesses must improve their information transparency in order to administrate the product return behaviour of their end users. This study proposes an intelligent return administration expert system (iRAES) to provide product return forecasting and decision support for returned product administration. The iRAES consists of two intelligent agents that adopt a hybrid data mining algorithm. The return diagnosis agent generates different alarms for certain types of product return, based on forecasts of the return possibility. The return recommender agent is implemented on the basis of case-based reasoning, and provides the return centre clerk with a recommendation for returned product administration. We present a 3C-iShop scenario to demonstrate the feasibility and efficiency of the iRAES architecture. Our experiments identify a particularly interesting return, for which iRAES generates a recommendation for returned product administration. On average, iRAES decreases the effort required to generate a recommendation by 70% compared to previous return administration systems, and improves performance via return decision support by 37%. iRAES is designed to accelerate product return administration, and improve the performance of product return knowledge management.

Entity is an important information carrier in Web pages. Users would like to directly get a list of relevant entities instead of a list of documents when they submit a query to the search engine. So the research of related entity finding (REF) is a meaningful work. In this paper we investigate the most important task of REF: Entity Ranking. The wrong-type entities which don't belong to the target-entity type will pollute the ranking result. We propose a novel method to filter wrong-type entities. We focus on the acquisition of seed entities and automatically extracting the common Wikipedia categories of target-entity type. Also we demonstrate how to filter wrong-type entities using the proposed model. The experimental results show our method can filter wrong-type entities effectively and improve the results of entity ranking.

The present paper introduces a prototype design and experimental results for a multi-user MIMO linear precoding system. A base station and two mobile stations are implemented by taking full advantage of the software-defined radio. The base station consists of general purpose signal analyzers and signal generators controlled by a personal computer. Universal software radio peripherals are used as mobile stations. Linear spatial precoding and a simple two-way channel estimation technique are adopted in this experimental system. In-lab and field transmission experiments are carried out, and the bit error rate performance is evaluated. The impact of the channel estimation error under average channel gain discrepancy between two mobile stations is analyzed through computer simulations. Channel estimation error is shown to have a greater influence on the mobile station with the greater average channel gain.

In this letter, we propose a innovative threshold receiver for MIMO-OFDM system. The proposed scheme calculates the channel condition number and then selects either combined V algorithm and CLLL or combined QRD-M and DFE detection scheme according to channel information. The complexity of the proposed scheme is about 33.3% of the QRD-M for 44 MIMO-OFDM system.

The Generalized Feistel Structure (GFS) generally uses the sub-block-wise cyclic shift in the permutation layer, the layer between the two F function layers. For Type 2 GFS, at FSE 2010, Suzaki and Minematsu showed that a better diffusion property can be obtained if one uses some other sub-block-wise permutation. In this paper, we consider Type 1, Type 3, Source-Heavy (SH), and Target-Heavy (TH) GFSs, and study if their diffusion properties can be improved by changing the sub-block-wise cyclic shift. For Type 1 GFS and Type 3 GFS, we show that better permutations in terms of diffusion exist. For SH and TH GFSs, we show that the diffusion property does not change even if we change the sub-block-wise cyclic shift. We also experimentally derive optimum permutations in terms of diffusion, and evaluate the security of the resulting schemes against saturation, impossible differential, differential, and linear attacks.

In OFDM systems, residual inter-block interference can be suppressed by a time-domain equalizer that blindly shortens the effective length of a channel impulse response. To further improve the performance of blind equalizers, we propose a channel shortening method that attempts to maximize the minimum FFT output power over data subcarriers. Simulation results indicate that the max-min strategy has performance improvement over a conventional channel shortening method.

In this paper, we derive a fast polynomial basis multiplier for GF(2m) defined by pentanomials xm+xk3+xk2+xk1+1 with 1 ≤ k1 < k2 < k3 ≤ m/2 using the presented method by Park and Chang. The proposed multiplier has the time delay TA+(2+⌈log2(m-1)⌉) TX or TA+(3+⌈log2(m-1)⌉) TX which is the lowest one compared with known multipliers for pentanomials except for special types, where TA and TX denote the delays of one AND gate and one XOR gate, respectively. On the other hand, its space complexity is very slightly greater than the best known results.

Network devices, such as routers or L3 switches, have a feature called packet-filtering for network security. They determine whether or not to pass arriving packets by applying filtering rules to them. If the number of comparisons of packets with rules increases, the time required for a determination will increase, which will result in greater communication delay. Various algorithms for optimizing filtering tables to minimize the load of packet filtering, which directly impacts the communication delay, have been proposed. In this paper, first we introduce an adaptive packet filter based on an algorithm that reconstructs the filtering table according to the frequency distribution of arrival packets. Next, we propose a new reconstruction algorithm based on grouping of dependent rules. Grouping dependent rules makes it possible to sort the rules in the table by the frequency of matching. Finally, we show the effectiveness of our algorithm by comparing it against previously reported algorithms.

This paper proposes a dynamic bandwidth allocation algorithm that improves the network performance and bandwidth sharing efficiency in the upstream channels of a hybrid passive optical network (PON) that combines a fiber-to-the-home (FTTH) access network and wireless sensor networks (WSNs). The algorithm is called the adaptive limited dynamic bandwidth allocation (ALDBA) algorithm. Unlike existing algorithms, the ALDBA algorithm is not limited to controlling just FTTH access networks, it also supports WSNs. For the proposed algorithm, we investigate the difference in the lengths of generated data packets between the FTTH terminals and sensor nodes of WSN to effectively evaluate the end-to-end average packet delay, bandwidth utilization, time jitter, and upstream efficiency. Two variants of the proposed algorithm and a limited service (LS) scheme, which is an existing well-known algorithm, are compared under non-uniform traffic conditions without taking into consideration priority scheduling. We demonstrate the proposed scheme through simulation by generating a realistic network traffic model, called self-similar network traffic. We conducted a detailed simulation using several performance parameters to validate the effectiveness of the proposed scheme. The results of the simulation showed that both ALDBA variants outperformed the existing LS scheme in terms of average packet delay, bandwidth utilization, jitter, and upstream efficiency for both low and high traffic loads.

In this letter, we propose a non-cooperative limited feedback precoding and subchannel selection scheme for non-reciprocal multiple-input multiple-output (MIMO) interference channels. At each iteration of the proposed scheme, each user updates its precoder selection for each subchannel and then chooses the predetermined number of subchannels in a distributed and non-cooperative way. We present simulation results to verify the performance of the proposed scheme.

This letter presents a framework, including two constructions, for yielding several types of sequences with optimal autocorrelation properties. Only by simply choosing proper coefficients in constructions and optimal known sequences, two constructions transform the chosen sequences into optimally required ones with two or four times periods as long as the original sequences', respectively. These two constructions result in binary and quaternary sequences with optimal autocorrelation values (OAVs), perfect QPSK+ sequences, and multilevel perfect sequences, depending on choices of the known sequences employed. In addition, Construction 2 is a generalization of Construction B in [5] so that the number of distinct sequences from the former is larger than the one from the latter.

Testbeds play a key role in the advancement of network science and the exploration of new network architectures. Because the scale and scope of any individual testbed is necessarily limited, federation is a useful technique for constructing testbeds that serve a wide range of experimenter needs. In a federated testbed, individual facilities maintain local autonomy while cooperating to provide a unified set of abstractions and interfaces to users. Forming an international federation is particularly challenging, because issues of trust, user access policy, and local laws and regulations are of greater concern that they are for federations within a single country. In this paper, we describe an architecture, based on the US National Science Foundation's GENI project, that is capable of supporting the needs of an international federation.

This paper proposes a Reduced Explicitly Parallel Instruction Computing Processor (REPICP) which is an independently designed, 64-bit, general-purpose microprocessor. The REPICP based on EPIC architecture overcomes the disadvantages of hardware-based superscalar and software-based Very Long Instruction Word (VLIW) and utilizes the cooperation of compiler and hardware to enhance Instruction-Level Parallelism (ILP). In REPICP, we propose the Optimized Lock-Step execution Model (OLSM) and instruction control pipeline method. We also propose reduced innovative methods to optimize the design. The REPICP is fabricated in Artisan 0.13 µm Nominal 1P8M process with 57 M transistors. The die size of the REPICP is 100 mm2 (1010), and consumes only 12 W power when running at 300 MHz.

Clock network synthesis is one of the most important and limiting factors in VLSI designs. Hence, the clock skew variation reduction is one of the most important objectives in clock distribution methodology. Cross-link insertion is proposed in [1], however, it is based on empirical methods and does not use variation information for link insertion location choice. [17] considers the delay variation, but it is slow even for small clock trees. In this paper, we propose a fast link insertion algorithm that considers the delay variation information directly during link selection process. Experimental results show that our algorithm is very fast and achieves better skew variability reduction while utilizing considerably lesser routing resources compared with existing methods.

Dynamic Programming (DP) based Track-Before-Detect (TBD) algorithm is effective in detecting low signal-to-noise ratio (SNR) targets. However, its complexity increases exponentially as the dimension of the target state space increases, so the exact implementation of DP-TBD will become computationally prohibitive if the state dimension is more than two or three, which greatly prevents its applications to many realistic problems. In order to improve the computational efficiency of DP-TBD, a thresholding process based DP-TBD (TP-DP-TBD) is proposed in this paper. In TP-DP-TBD, a low threshold is first used to eliminate the noise-like (with low-amplitude) measurements. Then the DP integration process is modified to only focuses on the thresholded higher-amplitude measurements, thus huge amounts of computation devoted to the less meaningful low-amplitude measurements are saved. Additionally, a merit function transfer process is integrated into DP recursion to guarantee the inheritance and utilization of the target merits. The performance of TP-DP-TBD is investigated under both optical style Cartesian model and surveillance radar model. The results show that substantial computation reduction is achieved with limited performance loss, consequently TP-DP-TBD provides a cost-efficient tradeoff between computational cost and performance. The effect of the merit function transfer on performance is also studied.

This letter proposes a multiple symbol differential detection (MSDD) with majority decision method for differentially coded quadrature phase-shift keying (DQPSK) in Rician fading channels. The proposed method shows better BER performance than the conventional MSDD. Simulation results show that the proposed MSDD with a majority decision method improves the system's BER performance for DQPSK signals under the AWGN channel and it approaches asymptotically the theoretical BER performance of coherent detection. Furthermore, the proposed method shows better BER performance under the Rician fading channel with large frequency offsets especially for the range of C/M > 12 dB in comparison with the conventional MSDD.

As the number of new malware has increased explosively, traditional malware detection approaches based on pattern matching have been less effective. Therefore, it is important to develop a detection method which relies on not signatures but characteristic behaviors of malware. Recently, malware authors have been embedding functions for countermeasure against malware analyses and detections into malware. Accordingly, modern malware often changes their runtime behaviors in each execution to tolerate against malware analyses and detections. For example, when malware copies itself on a file system, it can randomly determine its file name for avoiding the detections. Another example is that when malware tries to connect its command and control server, it randomly chooses a domain name from a hard-coded domain name list to avoid being blocked by a static blacklist of malicious domain names. We assume that such evasive behaviors are unnecessary for benign software. Therefore the behaviors can be the clues to distinguish malware from benign software. In this paper, we propose a novel behavior-based malware detection method which focuses attention on such characteristics. Our proposed method conducts dynamic analysis on an executable file multiple times in same sandbox environment so as to obtain plural lists of API call sequences and plural traffic logs, and then compares the lists and the logs to find the difference between the multiple executions. In the experiments with 5,697 malware samples and 819 benign software samples, we can detect about 70% malware samples and the false positive rate is about 1%. In addition, we can detect about 50% malware samples which were not detected by each Anti-Virus Software engine. Therefore we confirm the possibility the proposed method may be able to improve the accuracy of malware detection utilizing in combination with other existing methods.

The paper presents capability of signal detection for realizing coexistence between broadband wireless access (BWA) systems and ultra wideband (UWB) devices. The capability is experimentally evaluated for baseband signals of downlink (DL) in both mobile WiMAX and 3GPP LTE. An UWB receiver based on fast Fourier transform (FFT) compliant with MB-OFDM standard is implemented as a detector of the BWA signals. The capability is evaluated in terms of elapsed time required to achieve signal detection with probability of 99% by the implemented FFT-based UWB receiver at different conditions of the receiver. Decisions on the signal detection are made by the simplest method which is by setting a threshold which is determined by noise floor of the receiver as reference. The experiments have been conducted though baseband signals for both AWGN and multipath fading channels without any synchronization between the DL signals and UWB receiver. In AWGN environment, results show that the elapsed time depends on the duty ratio of the DL signal to be detected, however, the correlation between the required time and duty ratio is not linear since their envelopes of the DL signals are not constant. In multipath fading environments based on channel models commonly employed as mobile radio environments, the required time for the signal detection becomes as 17 times longer than that in AWGN due to its signal attenuation. For robust signal detection in multipath fading environments, it has been revealed that the number of quantization bits at ADC is crucial through the experiments.

This paper deals with a characteristic of the so-called effective boundary condition for a plane wave scattering from periodic surfaces with perfect conductivity. The perturbation solution with all orders is explicitly given under the effective boundary condition. It is newly found that such a perturbation solution satisfies the optical theorem under the exact boundary condition. A comparison between such a perturbation solution and a reference solution for the exact boundary condition by other methods is performed. Then, the validity of such a perturbation solution is concretely discussed.

Dynamic virtual network allocation is a promising traffic control model for cloud resident data center which offers virtual data centers for customers from the provider's substrate cloud. Unfortunately, dynamic virtual network allocation designed in the past was aimed to the Internet so it needs distributed control methods to scale with such a large network. The price for the scalability of the completely distributed control method at both virtual layer and substrate layer is the slow convergence of algorithm and the less stability of traffic. In this paper, we argue that the distributed controls in both virtual and substrate networks are not necessary for the cloud resident data center environment, because cloud resident data center uses centralized controller as the way to give network control features to customers. In fact, we can use the centralized algorithm in each virtual data center which is not very large network and the distributed algorithm is only needed in substrate network. Based on the specific properties of this model, we have used optimization theory to re-design the substrate algorithm for periodically re-adjusting virtual link capacity. Results from theoretical analysis, simulations, and experiments show that our algorithm has faster convergence time, simpler calculation and can make better use of the feedback information from virtual networks than the previous algorithm.