We describe a cell-based connected component labeling algorithm to calculate the 0th and 1st moment features as the attributes for labeled regions. These can be used to indicate their sizes and positions for multi-object extraction. Based on the additivity in moment features, the cell-based labeling algorithm can label divided cells of a certain size in an image by scanning the image only once to obtain the moment features of the labeled regions with remarkably reduced computational complexity and memory consumption for labeling. Our algorithm is a simple-one-time-scan cell-based labeling algorithm, which is suitable for hardware and parallel implementation. We also compared it with conventional labeling algorithms. The experimental results showed that our algorithm is faster than conventional raster-scan labeling algorithms.

In this paper, we propose a duplicate document detection model recognizing both partial duplicates and near duplicates. The proposed model can detect partial duplicates as well as exact duplicates by splitting a large document into many small sentence fingerprints. Furthermore, the proposed model can detect even near duplicates, the result of trivial revisions, by filtering the common words and reordering the word sequence.

We propose an adaptive coding algorithm for digital hologram transmission based on server-client interaction. A client can visualize various images of 3D objects from a digital hologram, which are reconstructed on different depth planes. The client's requests for reconstruction depths are sent to the server. The server adaptively encodes and transmits the same object image as the client's reconstructed image. When the client changes the reconstruction depth, only the prediction error of the new image is transmitted. Experimental results show that, in some cases, the proposed algorithm reduces more than half of the distortion at the same bitrate compared with the conventional coding technique.

Obtaining a compact representation of a large-size feature map built by mapper robots is a critical issue in recent mobile robotics. This “map compression” problem is explored from a novel perspective of dictionary-based data compression techniques in the paper. The primary contribution of the paper is the proposal of the dictionary-based map compression approach. A map compression system is presented by employing RANSAC map matching and sparse coding as building blocks. The effectiveness levels of the proposed techniques is investigated in terms of map compression ratio, compression speed, the retrieval performance of compressed/decompressed maps, as well as applications to the Kolmogorov complexity.

The IEEE 802.15.4 protocol is considered a promising technology for low-cost low-power wireless personal area networks. Researchers have discussed the feasibility of voice communications over IEEE 802.15.4 networks. To this end, the personal area network (PAN) coordinator allocates guaranteed time slots (GTSs) for voice communications in the beacon-enabled mode of IEEE 802.15.4. Although IEEE 802.15.4 is capable of supporting voice communications by GTS allocation, it is impossible to accommodate voice transmission beyond two hops due to the excessive transmission delay. In this paper, we propose a GTS allocation scheme for bidirectional voice traffic in IEEE 802.15.4 multihop networks. The goal of our proposed scheme is to achieve low end-to-end delay and packet drop ratio without a complex allocation algorithm. Thus, the proposed scheme allocates GTSs to devices for successful completion of voice transmission in a superframe duration. The proposed scheme also considers transceiver switching delay. This is relatively large compared to a time slot due to the low-cost and low-gain antenna designs. We analyze and validate the proposed scheme in terms of average end-to-end delay and packet drop ratio. Our scheme has lower end-to-end delay and packet drop ratio than the basic IEEE 802.15.4 GTS allocation scheme.

A key technical challenge in heterogeneous wireless networks (HWNs) is the support of vertical handoff. It allows mobile users to switch connections among networks. In this paper, we propose and evaluate the application of VIKOR for vertical handoff. VIKOR is a Multiple Attribute Decision Making (MADM) method which makes decisions based on an aggregating function representing closeness to the ideal solution. We conducted simulation experiments to compare the performance of VIKOR for vertical handoff with other decision schemes such as SAW, TOPSIS, and WMC. We considered voice, data, and cost-constrained connections. Our results show that VIKOR is able to obtain satisfactory to excellent performance in the four different types of connections being considered.

Packet classification is essential for supporting advanced network services such as firewalls, quality-of-service (QoS), virtual private networks (VPN), and policy-based routing. The rules that routers use to classify packets are called packet filters. If two or more filters overlap, a conflict occurs and leads to ambiguity in packet classification. This study proposes an algorithm that can efficiently detect and resolve filter conflicts using tuple based search. The time complexity of the proposed algorithm is O(nW +s), and the space complexity is O(nW), where n is the number of filters, W is the number of bits in a header field, and s is the number of conflicts. This study uses the synthetic filter databases generated by Class-Bench to evaluate the proposed algorithm. Simulation results show that the proposed algorithm can achieve better performance than existing conflict detection algorithms both in time and space, particularly for databases with large numbers of conflicts.

In next-generation networks, ultra-high speed transfer capability will become necessary to support a variety of advanced multimedia services. The Optical Wavelength Division Multiplexing (WDM) network is seen as one of promising networks. To deal with various multimedia services, the network should support not only unicast transmission but also multicast transmission. However, IP multicast has several problems, for example, all routers must have multicast functions. IP multicast needs routers with high overheads and excessive energy consumption. Hence, optical multicasting in optical WDM networks is a promising solution for future internet services. A tree-shared multicasting concept has been proposed to support multicast transmissions in optical WDM networks. This method assembles multiple multicast traffic streams into one burst and the burst is delivered using a shared-tree. However, this method can not be applied to dynamic multicasting. This paper proposes a novel WDM multicast design method for dynamic traffic demand using multiple shared-trees, which includes shared-tree generation/selection and wavelength assignment, for the purpose of simplifying the routing process and receiving multicast traffic efficiently. We evaluate its performance from the viewpoints of the burst loss probability and the number of redundant and useless transfers whose data is discarded at the egress edge nodes.

We developed advanced techniques for the growth of self-assembled quantum dots (QDs) for fabricating a broadband light source that can be applied to optical coherence tomography (OCT). Four QD ensembles and strain reducing layers (SRLs) were grown in selective areas on a wafer by the use of a 90° rotational metal mask. The SRL thickness was varied to achieve appropriate shifts in the peak wavelength of the QD emission spectrum of up to 120 nm. The four-color QD ensembles were expected to have a broad bandwidth of more than 160 nm due to the combination of excited state emissions when introduced in a current-induced broadband light source such as a superluminescent diode (SLD). Furthermore, a desired shape of the SLD spectrum can be obtained by controlling the injection current applied to each QD ensemble. The broadband and spectrum shape controlled light source is promising for high-resolution and low-noise OCT systems.

This letter proposes a practical algorithm for video transmission of the scalable extension of H.264/AVC (SVC) over limited bit-rate and varying channel signal-to-noise ratio (SNR). The proposal consists of SVC source-layer dropping and layered FEC using LDPC codes to maximize the video quality. The experimental results show that the proposed method realizes better video quality than the compared unequal error protection (UEP) without source-layer dropping. This implies that the dropping of a certain number of source-layers and using the resultant bit-budget for channel coding is more effective than the other UEP case which uses all possible source-layers.

A Mur type analytical absorbing boundary condition (A-ABC), which is based on the one-dimensional one-way wave equation, is proposed for multidimensional wave analysis by introducing the directional splitting technique. This new absorbing boundary condition is expansion of the first-order Mur. The absorbing ability, required memory, and calculation speed of the Mur type A-ABC are evaluated by comparison with those of conventional ABCs. The result indicated that absorbing ability of the proposed ABC is higher than the first-order Mur and lower than the second-order Mur at large incident angle. While, our proposed ABC has advantage in both required memory and calculation speed by comparison with the second-order Mur. Thus, effectivity of the proposed Mur type A-ABC is shown.

This letter focuses on the performance analysis on the Adaptive Sidelobe Blanker (ASB) detection algorithm in homogeneous environments, and provides closed summation expressions for Probability of Detection (PD) and Probability of False Alarm (PFA) rate in terms of hypergeometric function. The derived results are more powerful and effective than previous integral ones. Moreover, the framework can be modified to solve the the performance analysis problem involving in F or/and beta distributions. Several numerical evaluations of the convergence rate and computation time are provided and discussed.

We propose a motion detection model, which is suitable for higher speed operation than the video rate, inspired by the neuronal propagation in the hippocampus in the brain. The model detects motion of edges, which are extracted from monocular image sequences, on specified 2D maps without image matching. We introduce gating units into a CA3-CA1 model, where CA3 and CA1 are the names of hippocampal regions. We use the function of gating units to reduce mismatching for applying our model in complicated situations. We also propose a map-division method to achieve accurate detection. We have evaluated the performance of the proposed model by using artificial and real image sequences. The results show that the proposed model can run up to 1.0 ms/frame if using a resolution of 6460 units division of 320240 pixels image. The detection rate of moving edges is achieved about 99% under a complicated situation. We have also verified that the proposed model can achieve accurate detection of approaching objects at high frame rate (>100 fps), which is better than conventional models, provided we can obtain accurate positions of image features and filter out the origins of false positive results in the post-processing.

To assess the performance of maximum-likelihood (ML) based Nakagami m parameter estimators, current methods rely on Monte Carlo simulation. In order to enable the analytical performance evaluation of ML-based m parameter estimators, we study the statistical properties of a parameter Δ, which is defined as the log-ratio of the arithmetic mean to the geometric mean for Nakagami-m fading power. Closed-form expressions are derived for the probability density function (PDF) of Δ. It is found that for large sample size, the PDF of Δ can be well approximated by a two-parameter Gamma PDF.

We consider secure wireless communications, where a source is communicating to a destination in the presence of K (K > 1) eavesdroppers. The source and destination both are equipped with multiple antennas, while each eavesdropper has a single antenna. The source aims to maximize the communication rate to the destination, while concealing the message from all the eavesdroppers. Combined with selective diversity, we propose a heuristic secrecy transmission scheme where the multiple-input-multiple-output (MIMO) secrecy channel is simplified into a multiple-input-single-output (MISO) one with the highest orthogonality to the eavesdropper channels. Then convex optimization is applied to obtain the optimal transmit covariance matrix for this selected MISO secrecy channel. Numerical results are provided to illustrate the efficacy of the proposed scheme.

This paper proposes a utility function-based scheduling algorithm for integrated real-time and non-real-time services in long-term evolution systems. The proposed utility function satisfies the target dropping ratio of real-time users; it uses the delay constraint and increases the throughput of non-real-time users by scheduling real-time users together with non-real-time users. Simulation results show that the proposed scheduling algorithm significantly improves the throughput of non-real-time users without sacrificing the quality of service of real-time users.

In this paper, we analyze the best relay selection scheme for the soft-decision-and-forward (SDF) cooperative networks with multiple relays. The term `best relay selection' implies that the relay having the largest end-to-end signal-to-noise ratio is selected to transmit in the second phase transmission. The approximate performances in terms of pairwise error probability (PEP) and bit error rate (BER) are analyzed and compared with the conventional multiple-relay transmission scheme where all the relays participate in the second phase transmission. Using the asymptotics of the Fox's H-function, the diversity orders of the best relay selection and conventional relay scheme for the SDF cooperative networks are derived. It is shown that both have the same full diversity order. The numerical results show that the best relay selection scheme outperforms the conventional one in terms of bit error rate.

This paper proposes a diversity scheme for Multi-Input Multi-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) based on Radio Frequency (RF) signal processing. Although a 22 MIMO-OFDM system can double the capacity without expanding the occupied frequency bandwidth, we cannot get additional diversity gain using the linear MIMO decomposition method. The proposed method improves the bit error rate (BER) performance by making efficient use of RF signal processing. Computer simulation results show that the proposed scheme gives additional diversity gain.

The explosive growth of Internet usage has caused problems for the current Internet in terms of traffic congestion within networks and performance degradation of end-to-end flows. Therefore, a reconsideration of the current Internet has begun and is being actively discussed worldwide with the goals of enabling efficient share of limited network resources (i.e., the link bandwidth) and improved performance. To directly address the inefficiency of TCP's congestion mitigation solely on the end-to-end basis, in this paper we propose an adaptive split connection scheme on advanced relay nodes; this scheme dynamically splits end-to-end TCP connections on the basis of congestion status in output links. Through simulation evaluations, we examine the effectiveness and potential of the proposed scheme.

This paper presents a method for comparing and detecting clones of Java programs by analyzing program stack flows. A stack flow denotes an operational behavior of a program by describing individual instructions and stack movements for performing specific operations. We analyze stack flows by simulating the operand stack movements during execution of a Java program. Two programs for detection of clones of Java programs are compared by matching similar pairs of stack flows in the programs. Experiments were performed on the proposed method and compared with the earlier approaches of comparing Java programs, the Tamada, k-gram, and stack pattern based methods. Their performance was evaluated with real-world Java programs in several categories collected from the Internet. The experimental results show that the proposed method is more effective than earlier methods of comparing and detecting clones of Java programs.