A number of parallel applications run on a high-performance computing (HPC) system simultaneously. Job mapping and scheduling become crucial to improve system utilization, because fragmentation prevents an incoming job from being assigned even if there are enough compute nodes unused. Wireless supercomputers and datacenters with free-space optical (FSO) terminals have been proposed to replace the conventional wired interconnection so that a diverse application workload can be better supported by changing their network topologies. In this study we firstly present an efficient job mapping by swapping the endpoints of FSO links in a wireless HPC system. Our evaluation shows that an FSO-equipped wireless HPC system can achieve shorter average queuing length and queuing time for all the dispatched user jobs. Secondly, we consider the use of a more complicated and enhanced scheduling algorithm, which can further improve the system utilization over different host networks, as well as the average response time for all the dispatched user jobs. Finally, we present the performance advantages of the proposed wireless HPC system under more practical assumptions such as different cabinet capacities and diverse subtopology packings.

Linear feedback shift register (LFSR) reseeding is an effective method for test data reduction. However, the test patterns generated by LFSR reseeding generally have high toggle rate and thus cause high test power. Therefore, it is feasible to fill X bits in deterministic test cubes with 0 or 1 properly before encoding the seed to reduce toggle rate. However, X-filling will increase the number of specified bits, thus increase the difficulty of seed encoding, what's more, the size of LFSR will increase as well. This paper presents a test frame which takes into consideration both compression ratio and power consumption simultaneously. In the first stage, the proposed reseeding-oriented X-filling proceeds for shift power (shift filling) and capture power (capture filling) reduction. Then, encode the filled test cubes using the proposed Compatible Block Code (CBC). The CBC can X-ize specified bits, namely turning specified bits into X bits, and can resolve the conflict between low-power filling and seed encoding. Experiments performed on ISCAS'89 benchmark circuits show that our scheme attains a compression ratio of 94.1% and reduces capture power by at least 15% and scan-in power by more than 79.5%.

Established in self-organized mode between mobile terminals (MT), mobile Ad Hoc networks are characterized by a fast change of network topology, limited power dissipation of network node, limited network bandwidth and poor security of the network. Therefore, this paper proposes an efficient one round certificateless authenticated group key agreement (OR-CLAGKA) protocol to satisfy the security demand of mobile Ad Hoc networks. Based on elliptic curve public key cryptography (ECC), OR-CLAGKA protocol utilizes the assumption of elliptic curve discrete logarithm problems (ECDLP) to guarantee its security. In contrast with those certificateless authenticated group key agreement (GKA) protocols, OR-CLAGKA protocol can reduce protocol data interaction between group users and it is based on efficient ECC public key infrastructure without calculating bilinear pairings, which involves negligible computational overhead. Thus, it is particularly suitable to deploy OR-CLAGKA protocol on MT devices because of its limited computation capacity and power consumption. Also, under the premise of keeping the forward and backward security, OR-CLAGKA protocol has achieved appropriate optimization to improve the performance of Ad Hoc networks in terms of frequent communication interrupt and reconnection. In addition, it has reduced executive overheads of key agreement protocol to make the protocol more suitable for mobile Ad Hoc network applications.

The segmentation of Mycobacterium tuberculosis images forms the basis for the computer-aided diagnosis of tuberculosis. The segmented objects are often broken due to the low-contrast objects and the limits of segmentation method. This will result in decreasing the accuracy of segmentation and recognition. A simple and effective post-processing method is proposed to connect the broken objects. The broken objects in the segmented binary images are connected based on the information obtained from their skeletons. Experimental results demonstrate the effectiveness of our proposed method.

This paper proposes an on-line rigid object tracking framework via discriminative object appearance modeling and learning. Strong classifiers are combined with 2D scale-rotation invariant local features to treat tracking as a keypoint matching problem. For on-line boosting, we correspond a Gaussian mixture model (GMM) to each weak classifier and propose a GMM-based classifying mechanism. Meanwhile, self-organizing theory is applied to perform automatic clustering for sequential updating. Benefiting from the invariance of the SURF feature and the proposed on-line classifying technique, we can easily find reliable matching pairs and thus perform accurate and stable tracking. Experiments show that the proposed method achieves better performance than previously reported trackers.

In this paper, we aim to investigate the potential usefulness of machine learning in image quality assessment (IQA). Most previous studies have focused on designing effective image quality metrics (IQMs), and significant advances have been made in the development of IQMs over the last decade. Here, our goal is to improve prediction outcomes of “any” given image quality metric. We call this the “IQM's Outcome Improvement” problem, in order to distinguish the proposed approach from the existing IQA approaches. We propose a method that focuses on the underlying IQM and improves its prediction results by using machine learning techniques. Extensive experiments have been conducted on three different publicly available image databases. Particularly, through both 1) in-database and 2) cross-database validations, the generality and technological feasibility (in real-world applications) of our machine-learning-based algorithm have been evaluated. Our results demonstrate that the proposed framework improves prediction outcomes of various existing commonly used IQMs (e.g., MSE, PSNR, SSIM-based IQMs, etc.) in terms of not only prediction accuracy, but also prediction monotonicity.

In this paper, a new scheme for personalized web page recommendation using multi-user search engine query information is proposed. Our contribution is a scheme that improves the accuracy of personalization for various types of contents (e.g., documents, images and music) without increasing user burden. The proposed scheme combines “preference footprints” for browsed pages with collaborative filtering. We acquire user interest using words that are relevant to queries submitted by users, attach all user interests to a page as a footprint when it is browsed, and evaluate the relevance of web pages in relation to words in footprints. The performance of the scheme is evaluated experimentally. The results indicate that the proposed scheme improves the precision and recall of previous schemes by 1%-24% and 80%-107%, respectively.

Network intelligence is a discipline that builds on the capabilities of network systems to act intelligently by the usage of network resources for delivering high-quality services in a changing environment. Wide area network intelligence is a class of network intelligence in wide area network which covers the core and the edge of Internet. In this paper, we propose a system based on machine learning for wide area network intelligence. The whole system consists of a core machine for pre-training and many terminal machines to accomplish faster responses. Each machine is one of dual-hemisphere models which are made of left and right hemispheres. The left hemisphere is used to improve latency by terminal response and the right hemisphere is used to improve communication by data generation. In an application on multimedia service, the proposed model is superior to the latest deep feed forward neural network in the data center with respect to the accuracy, latency and communication. Evaluation shows scalable improvement with regard to the number of terminal machines. Evaluation also shows the cost of improvement is longer learning time.

In this paper, a new MIMO antenna for ultra-wide band (UWB) applications is designed and proposed. The proposed MIMO antenna consists of two single UWB antenna elements, one acts as a magnetic dipole while the other as an electric one, to reduce mutual coupling. In order to reduce further the mutual coupling, a copper stub is used to isolate the two antenna elements. The designed MIMO UWB antenna provides a broad operating bandwidth from 3.1GHz to 10.6GHz, while achieving low mutual coupling and VSWR ≤ 2. Various performance characteristics of the antenna such as radiation patterns, VSWR, and the maximal gain are thoroughly investigated by simulations and experiments.

Microwave heating is expected to increase the yield of product, to decrease the reaction time, and to discover the new reaction system. The Rolling Circle Amplification (RCA) is an enzymatic synthesis method of deoxyribonucleic acid (DNA) strands with repeated sequence of a circulate template-DNA. In previous study, controlled microwave heating accelerated the maximum 4-fold compared with the conventional condition. Further, we indicated that the selectively heat of some buffer components by microwave irradiation induced the acceleration of RCA. The purpose of this research is to clarify the relationship between the microwave heating and buffer components. The understanding of role of ion-containing buffer components under microwave will be able to control the microwave-assisted enzymatic reaction. We studied the relation between the microwave power loss and RCA components via dielectric measurements, cavity resonator feature measurement, and electromagnetic simulation. Electromagnetic simulation of the TM010 cavity showed that the sample tube was heated only by an electric field. The buffer containing ions of the RCA components was selectively heated via microwave irradiation in the TM010 cavity resonator.

This paper proposes an efficient lossless coding scheme for color video in RGB 4:4:4 format. For the R signal that is encoded before the other signals at each frame, we employ a block-adaptive prediction technique originally developed for monochrome video. The prediction technique used for the remaining G and B signals is extended to exploit inter-color correlations as well as inter- and intra-frame ones. In both cases, multiple predictors are adaptively selected on a block-by-block basis. For the purpose of designing a set of predictors well suited to the local properties of video signals, we also explore an appropriate setting for the spatiotemporal partitioning of a video volume.

In this work, a novel formulation of crosstalk (XT) is developed, in which the perturbation/loading effect that the generator circuit exerts on the passive part of the receptor circuit is elucidated. Practical conditions (i.e., weak coupling and matching/mismatching of the generator circuit) under which this effect can be neglected are then discussed and exploited to develop an alternative radiated susceptibility (RS) test procedure, which resorts to crosstalk to induce at the terminations of a cable harness the same disturbance that would be induced by an external uniform plane-wave field. The proposed procedure, here developed with reference to typical RS setups foreseen by Standards of the aerospace sector, assures equivalence with field coupling without a priori knowledge and/or specific assumptions on the units connected to the terminations of the cable harness. Accuracy of the proposed scheme of equivalence is assessed by virtual experiments carried out in a full-wave simulation environment.

In this letter, we propose a novel framework to estimate the joint distribution of multiple Local Binary Patterns (LBPs). Multiple LBPs extracted from the same central pixel are first encoded using handcrafted encoding schemes to achieve rotation invariance, and the outputs are further encoded through a pre-trained Restricted Boltzmann Machine (RBM) to reduce the dimension of features. RBM has been successfully used as binary feature detectors and the binary-valued units of RBM seamlessly adapt to LBP. The proposed feature is called RBM-LBP. Experiments on the CUReT and Outex databases show that RBM-LBP is superior to conventional handcrafted encodings and more powerful in estimating the joint distribution of multiple LBPs.

Automatic detection of immunoreactive areas in fluorescence microscopic images is becoming a key technique in the field of biology including neuroscience, although it is still challenging because of several reasons such as low signal-to-noise ratio and contrast variation within an image. In this study, we developed a new algorithm that exhaustively detects co-localized areas in multi-channel fluorescence images, where shapes of target objects may differ among channels. Different adaptive binarization thresholds for different local regions in different channels are introduced and the condition of each segment is assessed to recognize the target objects. The proposed method was applied to detect immunoreactive spots that labeled membrane receptors on dendritic spines of mouse cerebellar Purkinje cells. Our method achieved the best detection performance over five pre-existing methods.

Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization problems involving many variables. However, physicists noted that in a network, a node variable (such as the amount of resources of the nodes) is connected to a set of link variables (such as the flow connecting the node), and similarly each link variable is connected to a number of (usually two) node variables. This enables one to break the problem into local components, often arriving at distributive algorithms to solve the problems. Compared with centralized algorithms, distributed algorithms have the advantages of lower computational complexity, and lower communication overhead. Since they have a faster response to local changes of the environment, they are especially useful for networks with evolving conditions. This review will cover message-passing algorithms in applications such as resource allocation, transportation networks, facility location, traffic routing, and stability of power grids.

To efficiently utilize storage resources, the in-network caching system of Information-Centric Networking has to deal with the popularity of huge content chunks which could cause large memory consumption. This paper presents a Popularity Monitoring based Gain-aware caching scheme, called PMG, which is an integrated design of cache placement and popularity monitoring. In PMG, by taking into account both the chunk popularity and the consumption saving of single cache hit, the cache placement process is transformed into a weighted popularity comparison, while the chunks with high cache gain are placed on the node closer to the content consumer. A Bloom Filter based sliding window algorithm, which is self-adaptive to the dynamic request rate, is proposed to capture the chunks with higher caching gain by Inter-Reference Gap (IRG) detection. Analysis shows that PMG can drastically reduce the memory consumption of popularity monitoring, and the simulation results confirm that our scheme can achieve popularity based cache placement and get better performance in terms of bandwidth saving and cache hit ratio when content popularity changes dynamically.

Extending the very popular tori interconnection networks[1]-[3], Torus-Connected Cycles (TCC) have been proposed as a novel network topology for massively parallel systems [5]. Here, the set-to-set disjoint paths routing problem in a TCC is solved. In a TCC(k,n), it is proved that paths of lengths at most kn2+2n can be selected in O(kn2) time.

In this paper, a built-in test circuit for an electrical interconnect test method is proposed to detect an open defect occurring at an interconnect between an IC and a printed circuit board. The test method is based on measuring the supply current of an inverter gate in the test circuit. A time-varying signal is provided to an interconnect as a test signal by the built-in test circuit. In this paper, the test circuit is evaluated by SPICE simulation and by experiments with a prototyping IC. The experimental results reveal that a hard open defect is detectable by the test method in addition to a resistive open defect and a capacitive open one at a test speed of 400 kHz.

In this paper, we propose and analyze the opportunistic amplify-and-forward (AF) relaying scheme using antenna selection in conjunction with different adaptive transmission techniques over Rayleigh fading channels. In this scheme, the best antenna of a source and the best relay are selected for communication between the source and destination. Closed-form expressions for the outage probability and average symbol error rate (SER) are derived to confirm that increasing the number of antennas is the best option as compared with increasing the number of relays. We also obtain closed-form expressions for the average channel capacity under three different adaptive transmission techniques: 1) optimal power and rate adaptation; 2) constant power with optimal rate adaptation; and 3) channel inversion with a fixed rate. The channel capacity performance of the considered adaptive transmission techniques is evaluated and compared with a different number of relays and various antennas configurations for each adaptive technique. Our derived analytical results are verified through extensive Monte Carlo simulations.

A continuous flow reactor equipped with a low-loss flow channel and a microwave cavity was developed for synthesizing nanophosphors. A continuous solution synthesis of YVO4:Eu,Bi nanophosphor was succeeded through the rapid hydrothermal method using this equipment. Internal quantum efficiency of YVO4:Eu,Bi nanophosphor obtained by 20 minutes microwave heating is about 30% at 320 nm as high as that obtained by 6 hours hydrothermal treatment in autoclave.