MapReduce is considered as the de facto framework for storing and processing massive data due to its fascinating features: simplicity, flexibility, fault tolerance and scalability. However, since the MapReduce framework does not provide an efficient access method to data (i.e., an index), whole data should be retrieved even though a user wants to access a small portion of data. Thus, in this paper, we devise an efficient algorithm constructing quadtrees with MapReduce. Our proposed algorithms reduce the index construction time by utilizing a sampling technique to partition a data set. To improve the query performance, we extend the quadtree construction algorithm in which the adjacent nodes of a quadtree are integrated when the number of points located in the nodes is less than the predefined threshold. Furthermore, we present an effective algorithm for incremental update. Our experimental results show the efficiency of our proposed algorithms in diverse environments.

The orthogonal array is an important object in combinatorial design theory, and it is applied to many fields, such as computer science, coding theory and cryptography etc. This paper mainly studies the existence of the mixed orthogonal arrays of strength two with seven factors and presents some new constructions. Consequently, a few new mixed orthogonal arrays are obtained.

In this correspondence, a method of constructing optimal zero correlation zone (ZCZ) sequence sets over the 16-QAM+ constellation is presented. Based on 16-QAM orthogonal matrices and perfect ternary sequences, 16-QAM+ ZCZ sequence sets are obtained. The resulting ZCZ sequence sets are optimal with respect to the Tang-Fan-Matsufuji bound. Moreover, methods for transforming binary or quaternary orthogonal matrices into 16-QAM orthogonal matrices are proposed. The proposed 16-QAM+ ZCZ sequence sets can be potentially applied to communication systems using a 16-QAM constellation to remove the multiple access interference (MAI) and multi-path interference (MPI).

With the development of silicon-based Nano-photonics, Optical Network on Chip (ONoC) is, due to its high bandwidth and low latency, becoming an important choice for future multi-core networks. As a key ONoC technology, the arbitration scheme should provide differential arbitration service with high throughput and low latency for various types and priorities of traffic in CMPs. In this work, we propose a fast hierarchical arbitration scheme based on multi-level priority QoS. First, given multi-priority data buffer queue, arbiters provide differential transmissions with fair service for all nodes and guarantee the max-transmit-delay and min-communication-bandwidth for all queues. Second, arbiter adopts the transmit bound resource reservation scheme to reserve time slots for all nodes fairly, thereby achieving a throughput of 100%. Third, we propose fast arbitration with a layout of fast optical arbitration channels (FOACs) to reduce the arbitration period, thereby reducing packet transmitting delay. Simulation results show that with our hierarchical arbitration scheme, all nodes are allocated almost equal service access probability under various traffic patterns; thus, the min-communication-bandwidth and max-transmit-delay is guaranteed to be 5% and 80 cycles, respectively, under the overload demands. This scheme improves throughput by 17% compared to FeatherWeight under a self-similar traffic pattern and decreases arbitration delay by 15% compare to 2-pass arbitration, incurring a total power overhead of 5%.

This paper proposes a novel object tracking method via online boosting. The on-line boosting technique is combined with local features to treat tracking as a keypoint matching problem. First, We improve matching reliability by exploiting the statistical repeatability of local features. In addition, we propose 2D scale-rotation invariant quasi-keypoint matching to further improve matching efficiency. Benefiting from SURF feature's statistical repeatability and the complementary quasi-keypoint matching technique, we can easily find reliable matching pairs and thus perform accurate and stable tracking. Experimental results show that the proposed method achieves better performance compared with previously reported trackers.

These days, the Web contains a huge volume of (semi-)structured data, called Linked Data (LD). However, LD suffer in data quality, and this poor data quality brings the need to identify erroneous data. Because manual erroneous data checking is impractical, automatic erroneous data detection is necessary. According to the data publishing guidelines of LD, data should use (already defined) ontology which populates type-annotated LD. Usually, the data type annotation helps in understanding the data. However, in our observation, the data type annotation could be used to identify erroneous data. Therefore, to automatically identify possible erroneous data over the type-annotated LD, we propose a framework that uses a novel nearest-neighbor based error detection technique. We conduct experiments of our framework on DBpedia, a type-annotated LD dataset, and found that our framework shows better performance of error detection in comparison with state-of-the-art framework.

The rapid development of a global navigation satellite system (GNSS) has raised the demand for spacecraft navigation, particularly for lunar spacecraft (LS). First, instead of the traditional approach of combining the united X-band system (UXB) with very-long-baseline interferometry (VLBI) by a terrestrial-based observing station in Chinese deep-space exploration, the spacecraft navigation based on inter-satellite link (ISL) is proposed because the spatial coverage of the GNSS downstream signals is too narrow to be used for LS navigation. Second, the feasibility of LS navigation by using ISL wide beam signals has been analyzed with the following receiving parameters: the geometrical dilution of precision (GDOP) and the carrier-to-noise ratio (C/N0) for satellites autonomously navigation of ISL and LS respectively; the weighting distance root-mean-square (wdrms) for the combination of both navigation modes. Third, to be different from all existing spacecraft ISL and GNSS navigation methods, an ISL annular beam transmitting antenna has been simulated to minimize the wdrms (1.138m) to obtain the optimal beam coverage: 16°-47° on elevation angle. Theoretical calculations and simulations have demonstrated that both ISL autonomous navigation and LS navigation can be satisfied at the same time. Furthermore, an onboard annular wide beam ISL antenna with optimized parameters has been designed to provide a larger channel capacity with a simpler structure than that of the existing GPS ISL spot beam antenna, a better anti-jamming performance than that of the former GPS ISL UHF-band wide band antenna, and a wider effectively operating area than the traditional terrestrial-based measurement. Lastly, the possibility and availability of applying an ISL receiver with an annular wide beam antenna on the Chinese Chang'E-5T (CE-5T) reentry experiment for autonomous navigation are analyzed and verified by simulating and comparing the ISL receiver with the practiced GNSS receiver.

The recent cyber-attacks utilize various malware as a means of attacks for the attacker's malicious purposes. They are aimed to steal confidential information or seize control over major facilities after infiltrating the network of a target organization. Attackers generally create new malware or many different types of malware by using an automatic malware creation tool which enables remote control over a target system easily and disturbs trace-back of these attacks. The paper proposes a generation method of malware behavior patterns as well as the detection techniques in order to detect the known and even unknown malware efficiently. The behavior patterns of malware are generated with Multiple Sequence Alignment (MSA) of API call sequences of malware. Consequently, we defined these behavior patterns as a “feature-chain” of malware for the analytical purpose. The initial generation of the feature-chain consists of extracting API call sequences with API hooking library, classifying malware samples by the similar behavior, and making the representative sequences from the MSA results. The detection mechanism of numerous malware is performed by measuring similarity between API call sequence of a target process (suspicious executables) and feature-chain of malware. By comparing with other existing methods, we proved the effectiveness of our proposed method based on Longest Common Subsequence (LCS) algorithm. Also we evaluated that our method outperforms other antivirus systems with 2.55 times in detection rate and 1.33 times in accuracy rate for malware detection.

In this paper, we consider solving the all-pairs regular path problem on large graphs efficiently. Let G be a graph and r be a regular path query, and consider finding the answers of r on G. If G is so small that it fits in main memory, it suffices to load entire G into main memory and traverse G to find paths matching r. However, if G is too large and cannot fit in main memory, we need another approach. In this paper, we propose a novel approach based on external memory algorithm. Our algorithm finds the answers matching r by scanning the node list of G sequentially. We made a small experiment, which suggests that our algorithm can solve the problem efficiently.

Web Service Composition (WSC) has been well recognized as a convenient and flexible way of service sharing and integration in service-oriented application fields. WSC aims at selecting and composing a set of initial services with respect to the Quality of Service (QoS) values of their attributes (e.g., price), in order to complete a complex task and meet user requirements. A major research challenge of the QoS-aware WSC problem is to select a proper set of services to maximize the QoS of the composite service meeting several QoS constraints upon various attributes, e.g. total price or runtime. In this article, a fast algorithm based on QoS-aware sampling (FAQS) is proposed, which can efficiently find the near-optimal composition result from sampled services. FAQS consists of five steps as follows. 1) QoS normalization is performed to unify different metrics for QoS attributes. 2) The normalized services are sampled and categorized by guaranteeing similar number of services in each class. 3) The frequencies of the sampled services are calculated to guarantee the composed services are the most frequent ones. This process ensures that the sampled services cover as many as possible initial services. 4) The sampled services are composed by solving a linear programming problem. 5) The initial composition results are further optimized by solving a modified multi-choice multi-dimensional knapsack problem (MMKP). Experimental results indicate that FAQS is much faster than existing algorithms and could obtain stable near-optimal result.

Some networks, such as wireless sensor networks, vehicle networks, etc., are often disconnected and thus fail to provide an end-to-end route for transmission. As a result, a new kind self-organized wireless network, i.e., Delay Tolerant Network (DTN) is proposed to transmit messages using a store-carry-forward method. To efficiently process aggregation queries, this paper proposes a subscription aggregation query processing method that combines query processing and transfer protocols. The basic idea is reducing the number of redundant copy transmissions, increasing the message delivery rate and reducing the transmission delay by matrix summation. Theoretical and experimental results show that the method can attain a good performance in the delay tolerant networks.

An on-chip monitoring circuit using a sub-sampling scheme, which consists of a 6-bit flash analog-to-digital converter (ADC) and a 51-phase phase-locked loop (PLL)-based frequency synthesizer, is proposed to analyze the signal integrity of a single-ended 8-Gb/s octal data rate (ODR) chip-to-chip interface with a source synchronous clocking scheme.

In this letter, several new families of binary sequence pairs with period N=np, where p is a prime and gcd(n,p)=1, and optimal correlation values 1 and -3 are constructed. These classes of binary sequence pairs are based on Chinese remainder theorem. The constructed sequence pairs have optimum balance among 0's and 1's.

One of the main research tasks in community question answering (cQA) is finding the most relevant questions for a given new query, thereby providing useful knowledge for users. The straightforward approach is to capitalize on textual features, or a bag-of-words (BoW) representation, to conduct the matching process between queries and questions. However, these approaches have a lexical gap issue which means that, if lexicon matching fails, they cannot model the semantic meaning. In addition, latent semantic models, like latent semantic analysis (LSA), attempt to map queries to its corresponding semantically similar questions through a lower dimension representation. But alas, LSA is a shallow and linear model that cannot model highly non-linear correlations in cQA. Moreover, both BoW and semantic oriented solutions utilize a single dictionary to represent the query, question, and answer in the same feature space. However, the correlations between them, as we observe from data, imply that they lie in entirely different feature spaces. In light of these observations, this paper proposes a tri-modal deep belief network (tri-DBN) to extract a unified representation for the query, question, and answer, with the hypothesis that they locate in three different feature spaces. Besides, we compare the unified representation extracted by our model with other representations using the Yahoo! Answers queries on the dataset. Finally, Experimental results reveal that the proposed model captures semantic meaning both within and between queries, questions, and answers. In addition, the results also suggest that the joint representation extracted via the proposed method can improve the performance of cQA archives searching.

In this study, our recent research activities on nanophotonic devices with semiconductor quantum nanostructures are reviewed. We have developed a technique for nanofabricating of high-quality and high-density semiconductor quantum dots (QDs). On the basis of this core technology, we have studied next-generation nanophotonic devices fabricated using high-quality QDs, including (1) a high-performance QD laser for long-wavelength optical communications, (2) high-efficiency compound-type solar cell structures, and (3) single-QD devices for future applications related to quantum information. These devices are expected to be used in high-speed optical communication systems, high-performance renewable energy systems, and future high-security quantum computation and communication systems.

Quantum efficiency (QE) evolution by several negative electron affinity (NEA) activation process for p-doped GaAs(100) specimen has been studied. We have carried out the surface pretreatment at 580°C or 480°C and the successive NEA activation process at room temperature (R.T.). When the NEA surface was degraded, the surface was refreshed by above pretreatment and activation process, and approximately 0.10 of QE was repeatedly obtained. It was found that the higher QE of 0.13 was achieved with the reduced pretreatment temperature at 480°C with the specific experimental conditions. This is probably caused by the residual Cs-related compounds playing an important role of the electron emission. In addition, after the multiple pretreatment and activation sequence, surface morphology of GaAs remarkably changed.

This paper presents novel reconfigurable semi-systolic array architecture for the Smith-Waterman with an affine gap penalty algorithm to align protein sequences optimized for shorter database sequences. This architecture has been modified to enable hardware reuse rather than replicating processing elements of the semi-systolic array in multiple FPGAs. The proposed hardware architecture and the previously published conventional one are described at the Register Transfer Level (RTL) using VHDL language and implemented using the FPGA technology. The results show that the proposed design has significant higher normalized speedup (up to 125%) over the conventional one for query sequence lengths less than 512 residues. According to the UniProtKB/TrEMBL protein database (release 2015_05) statistics, the largest number of sequences (about 80%) have sequence length less than 512 residues that makes the proposed design outperforms the conventional one in terms of speed and area in this sequence lengths range.

The alternating direction implicit (ADI) method is proposed for low-rank solution of projected generalized continuous-time algebraic Lyapunov equations. The low-rank solution is expressed by Cholesky factor that is similar to that of Cholesky factorization for linear system of equations. The Cholesky factor is represented in a real form so that it is useful for balanced truncation of sparsely connected RLC networks. Moreover, we show how to determine the shift parameters which are required for the ADI iterations, where Krylov subspace method is used for finding the shift parameters that reduce the residual error quickly. In the illustrative examples, we confirm that the real Cholesky factor certainly provides low-rank solution of projected generalized continuous-time algebraic Lyapunov equations. Effectiveness of the shift parameters determined by Krylov subspace method is also demonstrated.

Many selected mapping (SLM) schemes have been proposed to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signal sequences. In this paper, an efficient selection (ES) method of the OFDM signal sequence with minimum PAPR among many alternative OFDM signal sequences is proposed; it supports various SLM schemes. Utilizing the fact that OFDM signal components can be sequentially generated in many SLM schemes, the generation and PAPR observation of the OFDM signal sequence are processed concurrently. While the u-th alternative OFDM signal components are being generated, by applying the proposed ES method, the generation of that alternative OFDM signal components can be interrupted (or stopped) according to the selection criteria of the best OFDM signal sequence in the considered SLM scheme. Such interruption substantially reduces the average computational complexity of SLM schemes without degradation of PAPR reduction performance, which is confirmed by analytical and numerical results. Note that the proposed method is not an isolated SLM scheme but a subsidiary method which can be easily adopted in many SLM schemes in order to further reduce the computational complexity of considered SLM schemes.

In this paper we propose an adaptive bitrate (ABR) algorithm that selects the video rates by observing and controlling the playback buffer. In a Hypertext Transfer Protocol (HTTP) adaptive streaming session, buffer dynamics largely depend on the chunk sizes. First, we present the algorithm that selects the next video rates based on the current buffer level, while considering the upcoming chunk sizes. We aim to exploit the variation of chunk sizes of a variable bitrate (VBR) encoded video to optimize the tradeoff between the video rate and buffer underflow events while keeping a low frequency of video rate changes. To evaluate the performance of the proposed algorithm, we consider three scenarios: (i) the video flow does not compete with any cross traffic, (ii) the video flow shares the bottleneck link with competing TCP traffic, and (iii) two HTTP clients share the bottleneck. We show that the proposed algorithm selects a high playback video rate and avoids unnecessary rebuffering while keeping a low frequency of video rate changes. Furthermore, we show that the proposed algorithm changes the video quality gradually to guarantee the user's viewing experience.