It is well known that orientation-selective cells in the striate cortex are organized as a spatial structure in the area V1 of the visual cortex, and stimulus-selective cells in the area IT only respond to simple geometrical patterns. However, the neural network structure and its learning principle between the area V1 and the area IT have not been studied sufficiently. This paper presents a hierarchical neural network model between the area V1 and the area IT as well as its learning principle based on Kohonen’s self-organizing model. Experimental results show that the hierarchical neural network organizes orientation-selective cells in the area V1 and stimulus-selective cells responding to simple geometrical patterns in the area IT.

A new integrated feature distribution-based color textured image segmentation algorithm has been proposed. Two novel histogram-based inherent color texture feature extraction methods have been presented. From the histogram features, mean color texture histogram is calculated. Instead of concatenating the feature channels, a multichannel nonparametric Bayesean clustering is employed for primary segmentation. A region homogeneity-based merging algorithm is used for final segmentation. The proposed feature extraction techniques inherently combine color texture features rather then explicitly extracting it. Use of nonparametric Bayesean clustering makes the segmentation framework fully unsupervised where no a priori knowledge about the number of color texture regions is required. The feasibility and effectiveness of the proposed method have been demonstrated by various experiments using color textured and natural images. The experimental results reveal that superior segmentation results can be obtained through the proposed unsupervised segmentation framework.

This paper introduces a hidden topic-based framework for processing short and sparse documents (e.g., search result snippets, product descriptions, book/movie summaries, and advertising messages) on the Web. The framework focuses on solving two main challenges posed by these kinds of documents: 1) data sparseness and 2) synonyms/homonyms. The former leads to the lack of shared words and contexts among documents while the latter are big linguistic obstacles in natural language processing (NLP) and information retrieval (IR). The underlying idea of the framework is that common hidden topics discovered from large external data sets (universal data sets), when included, can make short documents less sparse and more topic-oriented. Furthermore, hidden topics from universal data sets help handle unseen data better. The proposed framework can also be applied for different natural languages and data domains. We carefully evaluated the framework by carrying out two experiments for two important online applications (Web search result classification and matching/ranking for contextual advertising) with large-scale universal data sets and we achieved significant results.

lung cancer (NSCLC), to stratify potential differences in long-term survival outcomes. Methods: We established a multi-institutional registry for 4138 patients with NSCLC who underwent lobectomy between January, 2000, and December, 2007, from eight institutions in China. Age, gender, histological type, and tumour staging, based on the latest TNM classification, were entered into a non-parsimonious multivariable logistic-regression model. The predicted probability derived from the logistic equation was used as the propensity score for each individual. Based on similar propensity scores, we matched 1356 of the 1584 patients who underwent VATS lobectomy with 1356 of the 2554 patients who underwent open lobectomy, and compared their long-term survival outcomes. Findings: The mean age of the 2712 matched patients was 59 years (SD 11). After propensity matching, VATS and open lobectomy were similar with regard to important prognostic variables. In multivariate analysis, four prognostic factors were independently associated with improved survival: gender (p = 0.001), histological type (p < 0.001), pathological staging (p < 0.001), and surgery type (lobectomy/sleeve resection vs. pneumonectomy (p = 0.044). Patients who underwent VATS versus open lobectomy had similar long-term survival (p = 0.101). Interpretation: The current propensity-score analysis suggests that well-matched patients with NSCLC who underwent VATS lobectomy did not have inferior long-term survival outcomes compared with those who underwent open lobectomy. Funding: National Natural Science Foundation of China, Guangdong Province Science and Technology Planning Programme, Guangdong Province Science and Technology Key Programme, and Guangzhou City Science and Technology Planning Programme. The authors declared no conflicts of interest.

Energy conserving design is the research focus to prolong the lifetime of wireless sensor networks. A simple and effective way to save energy is to place sensor nodes in sleep mode periodically. However, sleep mode corresponds to low power consumption as well as to reduced network capacity and increased latency. This paper develops an analytical framework to study the interaction between random sleep scheme and network performance. Our framework consists of the queueing model for sensor node and performance model for the whole network. We derived the network throughput, power consumption and packet delivery delay. Our analytical models shed light on the guidelines to design random sleep scheme and enable us to explore the trade-offs existing between sensor sleep/active dynamics and those performance measures.

The trade-off between resource efficiency and Quality of Service (QoS) is always a vital issue for communication networks, and link overbooking is a common technique used to improve resource efficiency. How to properly overbook a link and analytically determine its overbooking factor under QoS constraints are still problems, especially when achieving advanced QoS by per-flow queueing, as urged by the emerging mobilized applications in the access networks. This paper first proposes an Opportunistic Link Overbooking (OLO) scheme for an edge gateway to improve its link efficiency, and then develops an integrated analytical framework for determining the suitable link overbooking factor with service guarantee on flow level. In our scheme, once the idle time of a high priority flow's quasi-dedicated link is larger than a specified threshold, the link is temporarily overbooked to a low priority flow; and then when the high priority flow's subsequent packets start arriving, the link can be recovered at the expense of a setup delay. To explore the balance between link efficiency and the flow's QoS in the proposed scheme, we develop the corresponding queueing model under either bounded packet delay (relevant to delaysensitive flow) or finite buffer size (relevant to loss-sensitive flow). Our queueing analysis reveals the inherent trade-offs among the link overbooking factor, packet loss rate and delay/jitter under different traffic patterns.

Network coding has the potential to greatly improve the throughput of wireless networks. In the current proposals for wireless network coding, network nodes transmit packets at a fixed transmission rate. It is notable, however, that by dynamically selecting the rate, we can effectively improve the node transmission efficiency. In this paper, we study the application of a rate-adaptive transmission mechanism in network-coding-based multihop wireless networks. In such networks, whether a coding solution is satisfactory or not depends not only on the number of involved native packets but on the packet loss probabilities of its intended next hops and its transmission time as well, both of which depend on the transmission rate. Therefore, we aim to jointly design the coding operation and rate selection to maximize the transmission efficiency. Specifically, we first describe and mathematically formulate the optimal packet coding and rate-selection problem. Then, we prove the NP-completeness of this optimization problem. Finally, we propose an efficient algorithm for finding good combinations of the coding solution and the transmission rate. Simulation results demonstrate that compared with the rate-fixed transmission, the rate-adaptive transmission based on our algorithm can significantly improve the node transmission efficiency.

This paper presents a proposal of an expected-credibility-based job scheduling method for volunteer computing (VC) systems with malicious participants who return erroneous results. Credibility-based voting is a promising approach to guaranteeing the computational correctness of VC systems. However, it relies on a simple round-robin job scheduling method that does not consider the jobs' order of execution, thereby resulting in numerous unnecessary job allocations and performance degradation of VC systems. To improve the performance of VC systems, the proposed job scheduling method selects a job to be executed prior to others dynamically based on two novel metrics: expected credibility and the expected number of results for each job. Simulation of VCs shows that the proposed method can improve the VC system performance up to 11%; It always outperforms the original round-robin method irrespective of the value of unknown parameters such as population and behavior of saboteurs.

Recently, network coding has been applied to the loss recovery of reliable multicast in wireless networks [19], where multiple lost packets are XOR-ed together as one packet and forwarded via single retransmission, resulting in a significant reduction of bandwidth consumption. In this paper, we first prove that maximizing the number of lost packets for XOR-ing, which is the key part of the available network coding-based reliable multicast schemes, is actually a complex NP-complete problem. To address this limitation, we then propose an efficient heuristic algorithm for finding an approximately optimal solution of this optimization problem. Furthermore, we show that the packet coding principle of maximizing the number of lost packets for XOR-ing sometimes cannot fully exploit the potential coding opportunities, and we then further propose new heuristic-based schemes with a new coding principle. Simulation results demonstrate that the heuristic-based schemes have very low computational complexity and can achieve almost the same transmission efficiency as the current coding-based high-complexity schemes. Furthermore, the heuristic-based schemes with the new coding principle not only have very low complexity, but also slightly outperform the current high-complexity ones.

This paper proposes and evaluates an approach for defect isolation of DNA self-assembled networks made of a large number of processing nodes. The complexity of DNA self-assembled networks makes impractical to add a large amount of redundancy and employ inefficient and unscalable defect tolerant schemes. A previous framework based on a broadcast algorithm isolates defective nodes without incorporating redundancy for nodes. However, its disadvantage is the limited scalability, thus making it unsuitable for extremely large scale networks built by DNA self-assembly. The proposed framework improves upon the previous framework by involving three algorithmic tiers; namely, 1-hop wave expansion, efficient via placement, and unsafe node detection. The performance of the proposed framework is evaluated and compared with the original framework by considering large scale networks (up to 2,000 × 2,000 nodes), and a novel gross defect model (as well as a conventional random defect model as assumed in previous works). Simulation results indicate that the proposed framework outperforms the original framework in broadcast latency and efficiency and shows excellent scalability for DNA self-assembled nano-scale networks.

The complexity of an interconnection network often determines the size of the parallel computer and thus the attainable performance of a parallel computer is limited by the characteristics of the interconnection network. Pruning technique reduces the complexity and hence increases the performance. In this paper, we apply the pruning technique on Hierarchical Torus Network (HTN) and study the architectural details of the pruned HTN. We have explored the network diameter, average distance, bisection width, peak number of vertical links, and VLSI layout area of different HTN. It is shown that the pruned HTN possesses several attractive features including small diameter, small average distance, small number of wires, a particularly small number of vertical links, and economic layout area as compared to its non-pruned counterpart.

This paper presents a proposal of a collusion-resistant sabotage-tolerance mechanism against malicious sabotage attempts in volunteer computing (VC) systems. While VC systems reach the most powerful computing platforms, they are vulnerable to mischief because volunteers can output erroneous results, for various reasons ranging from hardware failure to intentional sabotage. To protect the integrity of data and validate the computation results, most VC systems rely on the replication-based sabotage-tolerance mechanisms such as the m-first voting. However, these mechanisms are powerless against malicious volunteers (saboteurs) that have intention and use some form of collusion. To face this collusion threat, this paper proposes a spot-checking-based mechanism, which estimates the frequency of malicious attempts and dynamically eliminates erroneous results from the system. Simulation of VCs shows that the proposed method can improve the performance of VC systems up to 30 percent, while guaranteeing the same level of computational correctness.

Interconnection networks play a crucial role in the performance of massively parallel computers. Hierarchical interconnection networks provide high performance at low cost by exploring the locality that exists in the communication patterns of massively parallel computer systems. The Tori-connected mESH (TESH) Network is a 2D-torus network of multiple basic modules, in which the basic modules are 2D-mesh networks that are hierarchically interconnected for higher level networks. In this paper, we present a deadlock-free routing algorithm for the TESH network using 2 virtual channels - 2 being the minimum number for dimension-order routing - and evaluate the network's dynamic communication performance under various nonuniform traffic patterns, using the proposed routing algorithm. We evaluate the dynamic communication performance of TESH, mesh, and torus networks by computer simulation. It is shown that the dynamic communication performance of the TESH network is better than that of the mesh and torus networks.

The lack of optical buffer is still one of the main problems that hinder the development of all optical network. The current works on this topic mainly focus on the emulation of optical buffers by using bufferless switch fabric and fiber delay line (SDL). Recent advances have shown the feasibility of emulating many kinds of optical buffers, such as First In First Out (FIFO) buffer, priority buffer etc. The Last In First Out (LIFO) buffer is another important network component that can be used for congestion control and providing quality of service guarantee in the network. In [1] Huang et al. introduced a recursive construction of LIFO buffer with buffer size B by using no less than 9 log B delay lines. In this paper, we explore a more effective construction of optical LIFO buffer from SDL and the feedback switch architecture. Based on such an architecture, a scheduling algorithm is proposed to emulate the LIFO buffer of size B with 2 log B delay lines.

Recently, a promising packet forwarding architecture COPE was proposed to essentially improve the throughput of multihop wireless networks, where each network node can intelligently encode multiple packets together and forward them in a single transmission. However, COPE is still in its infancy and has the following limitations: (1) COPE adopts the FIFO packet scheduling and thus does not provide different priorities for different types of packets. (1) COPE simply classifies all packets destined to the same nexthop into small-size or large-size virtual queues solutions. Such a queuing structure will lose some potential coding opportunities, because among packets destined to the same nexthop at most two packets (the head packets of small-size and large-size queues) will be examined in the coding process, regardless of the number of flows. (3) The coding algorithm adopted in COPE is fast but cannot always find good solutions. In order to address the above limitations, in this paper we first present a new queuing structure for COPE, which can provide more potential coding opportunities, and then propose a new packet scheduling algorithm for this queuing structure to assign different priorities to different types of packets. Finally, we propose an efficient coding algorithm to find appropriate packets for coding. Simulation results demonstrate that this new COPE architecture can further greatly improve the node transmission efficiency.

Constructing 2D mesh topology network on chips (NoCs) without using virtual channels becomes attractive approach to building future massive multi-core computer systems because of its large amount of bandwidths, less design complexity, and less space consumption of routers. Dead lock problem on NoC is critical because it makes data transmission between nodes unreachable, and inevitable failures in hardware make mesh topology irregular. Although several fault-tolerant techniques are available, deadlock-free routing control algorithm for irregular mesh topology is promising approach to utilize large amount of bandwidths of NoC. The main drawback of available routing control algorithms is that many healthy nodes are deactivated to guarantee deadlock-freeness, and a number of deactivated nodes lead to traffic congestion. In this paper, we propose new fault-tolerant routing algorithm on 2D mesh topology NoC constructed without using virtual channels. The proposed algorithm is fully analyzed its dead lock-freeness, and the experimental result shows that the proposed algorithm can achieve both less number of deactivated nodes and higher throughput.