We propose efficient algorithms for Sorting k-Sets in Bins. The Sorting k-Sets in Bins problem can be described as follows. We are given numbered n bins with k balls in each bin. Balls in the i-th bin are numbered n-i+1. We can only swap balls between adjacent bins. Our task is to move all of the balls to the same numbered bins. For this problem, we give an efficient greedy algorithm with $rac{k+1}{4}n^2+O(k+n)$ swaps and provide a detailed analysis for k=3. In addition, we give a more efficient recursive algorithm using $rac{15}{16}n^2+O(n)$ swaps for k=3.

In this paper, we study on an availability analysis for a multibase system with lateral resupply of spare items between bases. We construct a basic model that a spare item of a base is transported for operation to another base without spare upon occurrence of failure, and simultaneously, the base that supplies the spare item receives the failed item of the other base for repair. We propose an approximation method to obtain the availability of the system and show the accuracy of the solution through numerical experiments. Also, two modified models are constructed to show the efficiency of the basic model. The two models modify the assumption on the lateral resupply of spare items between bases in the basic model. We numerically illustrate that the basic model can increase the availability of the system compared with the two modified models through Monte Carlo simulation.

In our previous work [12], [13], we introduced generalized feed-forward shift registers (GF2SR, for short) to apply them to secure and testable scan design, where we considered the security problem from the viewpoint of the complexity of identifying the structure of GF2SRs. Although the proposed scan design is secure in the sense that the structure of a GF2SR cannot be identified only from the primary input/output relation, it may not be secure if part of the contents of the circuit leak out. In this paper, we introduce a more secure concept called strong security such that no internal state of strongly secure circuits leaks out, and present how to design such strongly secure GF2SRs.

Routing is a challenging issue in mobile social networks (MSNs) because of time-varying links and intermittent connectivity. In order to enable nodes to make right decisions while forwarding messages, exploiting social relationship has become an important method for designing efficient routing protocols in MSNs. In this paper, we first use the temporal evolution graph model to accurately capture the dynamic topology of the MSN. Based on the model, we introduce the social relationship metric for detecting the quality of human social relationship from contact history records. Utilizing this metric, we propose social relationship based betweenness centrality metric to identify influential nodes to ensure messages forwarded by the nodes with stronger social relationship and higher likelihood of contacting other nodes. Then, we present SRBet, a novel social-based forwarding algorithm, which utilizes the aforementioned metric to enhance routing performance. Simulations have been conducted on two real world data sets and results demonstrate that the proposed forwarding algorithm achieves better performances than the existing algorithms.

Most of the current voice conversion methods are conducted based on parallel speech, which is not easily obtained in practice. In this letter, a novel iterative speaker model alignment (ISMA) method is proposed to address this problem. First, the source and target speaker models are each trained from the background model by adopting maximum a posteriori (MAP) algorithm. Then, a novel ISMA method is presented for alignment and transformation of spectral features. Finally, the proposed ISMA approach is further combined with a Gaussian mixture model (GMM) to improve the conversion performance. A series of objective and subjective experiments are carried out on CMU ARCTIC dataset, and the results demonstrate that the proposed method significantly outperforms the state-of-the-art approach.

Sparse Matrix-Vector Multiplication (SpMxV) is widely used in many high-performance computing applications, including information retrieval, medical imaging, and economic modeling. To eliminate the overhead of zero padding in SpMxV, prior works have focused on partitioning a sparse matrix into row vectors sets (RVS's) or sub-matrices. However, performance was still degraded due to the sparsity pattern of a sparse matrix. In this letter, we propose a heuristics, called recursive merging, which uses a greedy approach to recursively merge those row vectors of nonzeros in a matrix into the RVS's, such that each set included is ensured a local optimal solution. For ten uneven benchmark matrices from the University of Florida Sparse Matrix Collection, our proposed partitioning algorithm is always identified as the method with the highest mean density (over 96%), but with the lowest average relative difference (below 0.07%) over computing powers.

Although the use of software-defined networking (SDN) enables routes of packets to be controlled with finer granularity (down to the individual flow level) by using traffic engineering (TE) and thereby enables better balancing of the link loads, the corresponding increase in the number of states that need to be managed at routers and controller is problematic in large-scale networks. Aggregating flows into macro flows and assigning routes by macro flow should be an effective approach to solving this problem. However, when macro flows are constructed as TE targets, variations of traffic rates in each macro flow should be minimized to improve route stability. We propose two methods for generating macro flows: one is based on a greedy algorithm that minimizes the variation in rates, and the other clusters micro flows with similar traffic variation patterns into groups and optimizes the traffic ratio of extracted from each cluster to aggregate into each macro flow. Evaluation using traffic demand matrixes for 48 hours of Internet2 traffic demonstrated that the proposed methods can reduce the number of TE targets to about 1/50 ∼ 1/400 without degrading the link-load balancing effect of TE.

Real-time high-quality reverberation simulation plays an important role in many modern applications, such as computer games and virtual reality. Traditional physically and perceptually-based reverberation simulation techniques, however, suffer from the high computational cost and lack of the specific characteristics of the enclosure. In this paper, a hybrid reverberation simulation approach is proposed in which early reflections are reproduced by convolving with the impulse response modeled by the image-source method and late reverberation is reproduced by the feedback delay network. A parametric predictor of energy decay relief is presented for the modeled early reflections and then exploited to compute the parameters of the feedback delay network. This ensures the smooth transition in the time-frequency domain from early to late reflections. Numerical simulation and listening tests validate the effectiveness of this proposed hybrid reverberation simulation approach.

Two-track squeeze and adjacent track interference (ATI) are major barriers to increasing track density in hard disk drives (HDD). These depend on skew angles made by a magnetic head and circumferential direction on a magnetic disk. This paper describes relationships between the skew angle and the magnetic core width (MCW) which affects two-track squeeze and ATI performance. We propose a design concept of a track pitch profile at different skew angles considering MCW. Equivalent robustness of ATI performance on different skew angle conditions is obtained with the optimized track pitch.

Radio channel modeling is fundamental for designing wireless communication systems. In millimeter or sub-millimeter wave short range communication, shadowing effect by electrically-large objects is one of the most important factors determining the field strength and thus the coverage. Unfortunately, numerical methods like MoM, FDTD, FEM are unable to compute the field scattered by large objects due to their excessive time and memory requirements. Ray theory like geometrical theory of diffraction (GTD) by Keller is an effective and popular solution but suffers various kinds of singularities at geometrical boundaries such as incidence shadow boundary (ISB) or reflection shadow boundary (RSB). Modified edge representation (MER) equivalent edge current (EEC) is an accurate and a fast high frequency diffraction technique which expresses the fields in terms of line integration. It adopts classical Keller-type knife-edge diffraction coefficients and still provides uniform and highly accurate fields everywhere including geometrical boundaries. MER is used here to compute the millimeter-wave field distribution in compact range communication systems where shadowing effects rather than multi-path ones dominate the radio environments. For further simplicity, trigonometric functions in Keller's diffraction coefficients are replaced by the path lengths of source to the observer via the edge point of integration of the scatterers in the form of Fresnel zone number (FZN). Complexity, Computation time and the memory were reduced drastically without degrading the accuracy. The dipole wave scattering from flat rectangular plates is discussed with numerical examples.

This paper studies a cascade system of dynamic binary neural networks. The system is characterized by signum activation function, ternary connection parameters, and integer threshold parameters. As a fundamental learning problem, we consider storage and stabilization of one desired binary periodic orbit that corresponds to control signals of switching circuits. For the storage, we present a simple method based on the correlation learning. For the stabilization, we present a sparsification method based on the mutation operation in the genetic algorithm. Using the Gray-code-based return map, the storage and stability can be investigated. Performing numerical experiments, effectiveness of the learning method is confirmed.

To improve the BER performance of the conventional cooperative communication, this letter proposes an efficient method for the reliability, and it uses hierarchical modulation that has both the high priority (HP) layer and the low priority (LP) layer. To compensate more reliable transmission, the proposed method uses the error correction capability of Reed-Solomon (RS) codes additionally. The simulation results show that the proposed method can transmit data more reliably than the basic RS coded decode-and-forward (DF) method.

Copper arc runners are fixed on silver electrical contacts. Break arcs are generated between the contacts in a DC resistive circuit. Circuit current when contacts are closed is 10A. Supply voltage is changed from 200V to 450V. The following results are shown. Cathode spots stay on the cathode surface but anode spots run on the runner when the supply voltage is 250V and over. In cases of the supply voltage is greater than 250V, the break arcs run on the runner when the arcs are successfully extinguished, and stays on the runner in cases of the failure of arc extinction. The arc lengths just before arc extinction with or without the runners are also investigated. The arc lengths are the same with or without the runners for each supply voltage.

Break operations of DC inductive (L=20mH) load currents up to about 5A with 14V were conducted in air with AgSnO2 contact pairs under different contact opening speeds, first up to 20mm/s and then to 200mm/s. Average break arc duration at each current level was calculated under the respective opening speeds. While break arc durations became shorter with increases in the opening speeds at larger current levels, such reduction tendencies were less significant with an increase of the contact opening speed from 20mm/s to 200mm/s, even when operated to break a load current of 5A. Both load current levels and contact opening speed levels seem to exhibit certain roles for realizing arc shortening effects.

In this paper, we propose an utilization-aware hybrid beacon scheduling method for a large-scale IEEE 802.15.4 cluster-tree ZigBee network. The proposed method aims to enhance schedulability of a target network by better utilizing transmission medium, while avoiding inter-cluster collisions at the same time. To achieve this goal, the proposed scheduling method partially allows beacon overlaps, if appropriate. In particular, this paper answers for the following questions: 1) on which condition clusters can send overlapped beacons, 2) how to select clusters to overlap with minimizing utilization, and 3) how to adjust beacon parameters for grouped clusters. Also, we quantitatively evaluate the proposed method compared to previous works — i.e., non-beacon scheduling and a serialized beacon scheduling algorithm — from several aspects including total duty cycles, packet drop rate, and end-to-end delay.

A salient feature extraction algorithm is proposed to improve the recognition rate of the speech emotion. Firstly, the spectrogram of the emotional speech is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Each map is normalized and down-sampled to form the low resolution feature matrix. Then, each feature matrix is converted to the row vector and the principal component analysis (PCA) is used to reduce features redundancy to make the subsequent classification algorithm more practical. Finally, the speech emotion is classified with the support vector machine. Compared with the tradition features, the improved recognition rate reaches 15%.

A key issue in Peer-to-Peer (P2P) live streaming systems is that several participant peers tend to leave within a short time period. For example, such a phenomenon is common at the half time of football games and at the end of the performance of famous artists. Such selfish behavior of the participants causes several problems in P2P networks such as the disconnection of the overlay, the departure of backup peers and the occurrence of cyclic reference to backup peers. In this paper, we propose several techniques for tree-structured P2P live streaming systems to enhance their resilience to the simultaneous departure of some participants. As the baseline of the discussion, we will focus on mTreebone which is a typical churn-resilient P2P live streaming system based on the notion of peer stability. The performance of the proposed techniques is evaluated by simulation. The simulation result indicates that even under high churn rates, the proposed techniques significantly reduce the number of attempts needed to connect to backup peers and the recovery time after a fail.

This paper presents an automatic method to track soccer players in soccer video recorded from a single camera where the occurrence of pan-tilt-zoom can take place. The automatic object tracking is intended to support texture extraction in a free viewpoint video authoring application for soccer video. To ensure that the identity of the tracked object can be correctly obtained, background segmentation is performed and automatically removes commercial billboards whenever it overlaps with the soccer player. Next, object tracking is performed by an attribute matching algorithm for all objects in the temporal domain to find and maintain the correlation of the detected objects. The attribute matching process finds the best match between two objects in different frames according to their pre-determined attributes: position, size, dominant color and motion information. Utilizing these attributes, the experimental results show that the tracking process can handle occlusion problems such as occlusion involving more than three objects and occluded objects with similar color and moving direction, as well as correctly identify objects in the presence of camera movements.

The iterative random subdivision of rectangles is used as a generation model of networks in physics, computer science, and urban planning. However, these researches were independent. We consider some relations in them, and derive fundamental properties for the average lifetime depending on birth-time and the balanced distribution of rectangle faces.

At present, wireless local area networks (WLANs) based on IEEE802.11 are widely deployed in both private premises and public areas. In a public environment offering several access points (APs), a station (STA) needs to choose which AP to associate with. In this paper, we propose a distributed association control scheme with user guidance to increase users' utility based on uplink and downlink throughputs of individual stations. As part of the scheme, we also present a simple throughput estimation method that considers physical data rate, traffic demand, and frame length in both uplink and downlink. Basically, in the proposed scheme, an AP selects a user and suggests that the user moves to another AP if certain conditions are met. The user then decides whether to accept the suggestion or not in a self-interested manner or in a voluntary manner for the benefit of all users including the user's own self. Through simulations under this condition, we confirm that our distributed association control scheme can improve user utility and fairness even though the channel quality of the new AP is unknown in advance.