In this paper, a parallel flow monitoring technique that achieves accurate measurement of end-to-end delay of networks is proposed. In network monitoring tasks, network researchers and practitioners usually monitor multiple probe flows to measure delays on multiple paths in parallel. However, when they measure an end-to-end delay on a path, information of flows except for the flow along the path is not utilized in the conventional method. Generally, paths of flows share common parts in parallel monitoring. In the proposed method, information of flows on paths that share common parts, utilizes to measure delay on a path by partially converting the observation results of a flow to those of another flow. We perform simulations to confirm that the observation results of 72 parallel flows of active measurement are appropriately converted between each other. When the 99th-percentile of the end-to-end delay for each flow are measured, the accuracy of the proposed method is doubled compared with the conventional method.

This paper proposes a low-profile unidirectional supergain antenna applicable to wireless communication devices such as mobile terminals, the Internet of Things and so on. The antennas used for such systems are required to be not only electrically low-profile but also unsusceptible to surrounding objects such as human body and/or electrical equipment. The proposed antenna achieves both requirements due to its supergain property using planar elements and a closely placed planar reflector. The primary antenna is an asymmetric dipole type, and consists of a monopole element mounted on an edge of a rectangular conducting plane. Both elements are placed on a dielectric substrate backed by the planar reflector. It is numerically and experimentally shown that the supergain property is achieved by optimizing the geometrical parameters of the antenna. It is also shown that the impedance characteristics can be successfully adjusted by changing the lengths of the ground plane element and the monopole element. Thus, no additional impedance matching circuit is necessary. Furthermore, it is shown that surrounding objects have insignificant impact on the antenna performance.

This paper analyzes the performance of single-cell massive multiple-input multiple-output (MIMO) systems with non-orthogonal pilots. Specifically, closed-form expressions of the normalized channel estimation error and achievable uplink capacity are derived for both least squares (LS) and minimum mean square error (MMSE) estimation. Then a pilot reconstruction scheme based on orthogonal Procrustes principle (OPP) is provided to reduce the total normalized mean square error (NMSE) of channel estimations. With these reconstructed pilots, a two-step pilot assignment method is formulated by considering the correlation coefficient among pilots to reduce the maximum NMSE. Based on this assignment method, a step-by-step pilot power allocation scheme is further proposed to improve the average uplink signal-to-interference and noise ratio (SINR). At last, simulation results demonstrate the superiority of the proposed approaches.

This study proposes a design and calibration method for a small-footprint, low-frequency, and low-power gate leakage timer using a differential leakage technique for IoT applications. The proposed gate leakage timer is different from conventional ones because it is composed of two leakage sources and exploits differential leakage current for the charging capacitor. This solution alleviates the inherent trade-off between small-footprint and low-frequency in the conventional gate leakage timer. Furthermore, a calibration method to suppress variations of the output frequency is proposed in this paper. To verify the effectiveness of the proposed gate leakage timer, a test chip was fabricated using 55-nm-DDC-CMOS technology. The test chip successfully demonstrates the highest figure of merit (FoM) of the product of the capacitor area (0.072µm2) and output frequency (0.11Hz), which corresponds to an improvement by a factor of 2,121 compared to the conventional one. It also demonstrates the operation with 4.5pW power consumption. The total footprint can be reduced to be 28µm2, which enables low-cost and low-power IoT edges. The scaling scenario shows that the proposed technique is conducive to technology scaling.

A number of all-optical signal processing schemes based on nonlinear optical effects have been proposed and demonstrated for use in future photonic networks. Since various modulation formats have been developed for optical communication systems, all-optical converters between different modulation formats will be a key technology to connect networks transparently and efficiently. This paper reviews our recent works on all-optical modulation format conversion technologies in order to highlight the fundamental principles and applications in variety of all-optical signal processing schemes.

In the library, recognizing the activity of the reader can better uncover the reading habit of the reader and make book management more convenient. In this study, we present the design and implementation of a reading activity recognition approach based on passive RFID tags. By collecting and analyzing the phase profiling distribution feature, our approach can trace the reader's trajectory, recognize which book is picked up, and detect the book misplacement. We give a detailed analysis of the factors that can affect phase profiling in theory and combine these factors with relevant activities. The proposed approach recognizes the activities based on the amplitude of the variation of phase profiling, so that the activities can be inferred in real time through the phase monitoring of tags. We then implement our approach with off-the-shelf RFID equipment, and the experiments show that our approach can achieve high accuracy and efficiency in activity recognition in a real-world situation. We conclude our work and further discuss the necessity of a personalized book recommendation system in future libraries.

Wireless communication security has become a hot topic in recent years. The directional modulation (DM) is a promising secure communication technique that has attracted attentions of many researchers. Several different frequency diverse arrays (FDAs) are used to obtain the direction-range-dependent DM signals in previous literatures. However, most of them are not ideal enough to obtain a nonperiodic dot-shaped secure area. In this paper, the symmetrical multi-carrier frequency diverse array with logarithmical frequency increment, named the symmetrical-multilog-FDA, is used to obtain the direction-range-dependent DM signals that are normal at the desired locations while disordered at other locations. Based on the symmetrical-multilog-FDA, we derive the closed-form expression of baseband-weighted vector using the artificial-noise-aided zero-forcing approach. Compared with previous schemes, the proposed scheme can obtain a more fine-focusing nonperiodic dot-shaped secure area at the desired location. In addition, it can achieve a point-to-multipoint secure communication for multiple cooperative receivers at different locations.

With the spread of map applications, route generation has become a familiar function. Most of route generation methods search a route from a starting point to a destination point with the shortest time or shortest length, but more enjoyable route generation is recently focused on. Particularly, cyclic-route generation for strolling requires to suggest to a user more than one route passing through several POIs (Point-of-Interests), to satisfy the user's preferences as much as possible. In this paper, we propose a multiple cyclic-route generation method with a route length constraint considering POIs. Firstly, our proposed method finds out a set of reference points based on the route length constraint. Secondly, we search a non-cyclic route from one reference point to the next one and finally generate a cyclic route by connecting these non-cyclic routes. Compared with previous methods, our proposed method generates a cyclic route closer to the route length constraint, reduces the number of the same points passing through by approximately 80%, and increases the number of POIs passed approximately 1.49 times.

Smartphone users often want to customize the positions and functions of physical buttons to accommodate their own usage patterns; however, this is unfeasible for electronic mobile devices based on COTS (Commercial Off-The-Shelf) due to high production costs and hardware design constraints. In this letter, we present the design and implementation of customized virtual buttons that are localized using only common built-in sensors of electronic mobile devices. We develop sophisticated strategies firstly to detect when a user taps one of the virtual buttons, and secondly to locate the position of the tapped virtual button. The virtual-button scheme is implemented and demonstrated in a COTS-based smartphone. The feasibility study shows that, with up to nine virtual buttons on five different sides of the smartphone, the proposed virtual buttons can operate with greater than 90% accuracy.

This paper presents a novel model in the field of image co-saliency detection. Previous works simply design low level handcrafted features or extract deep features based on image patches for co-saliency calculation, which neglect the entire object perception properties. Besides, they also neglect the problem of visual similar region's mismatching when designing co-saliency calculation model. To solve these problems, we propose a novel strategy by considering both local prediction and global refinement (LPGR). In the local prediction stage, we train a deep convolutional saliency detection network in an end-to-end manner which only use the fully convolutional layers for saliency map prediction to capture the entire object perception properties and reduce feature redundancy. In the global refinement stage, we construct a unified co-saliency refinement model by integrating global appearance similarity into a co-saliency diffusion function, realizing the propagation and optimization of local saliency values in the context of entire image group. To overcome the adverse effects of visual similar regions' mismatching, we innovatively incorporates the inter-images saliency spread constraint (ISC) term into our co-saliency calculation function. Experimental results on public datasets demonstrate consistent performance gains of the proposed model over the state-of-the-art methods.

Notes on two constructions of zero-difference balanced (ZDB) functions are made in this letter. Then ZDB functions over Ze×∏ki=0 Fqi are obtained. And it shows that all the known ZDB functions using cyclotomic cosets over Zn are special cases of a generic construction. Moreover, applications of these ZDB functions are presented.

This paper investigates the wireless information surveillance in a suspicious millimeter wave (mmWave) wireless communication system via the spoofing relay based proactive eavesdropping approach. Specifically, the legitimate monitor in the system acts as a relay to simultaneously eavesdrop and send spoofing signals to vary the source transmission rate. To maximize the effective eavesdropping rate, an optimization problem for both hybrid precoding design and power distribution is formulated. Since the problem is fractional and non-convex, we resort to the Dinkelbach method to equivalently reduce the original problem into a series of non-fractional problems, which is still coupling. Afterwards, based on the BCD-type method, the non-fractional problem is reduced to three subproblems with two introduced parameters. Then the GS-PDD-based algorithm is proposed to obtain the optimal solution by alternately optimizing the three subproblems and simultaneously updating the introduced parameters. Numerical results verify the effectiveness and superiority of our proposed scheme.

Generalized approximate message passing (GAMP) is introduced into distributed compressed sensing (DCS) to reconstruct jointly sparse signals under the mixed support-set model. A GAMP algorithm with known support-set is presented and the matching pursuit generalized approximate message passing (MPGAMP) algorithm is modified. Then, a new joint recovery algorithm, referred to as the joint MPGAMP algorithm, is proposed. It sets up the jointly shared support-set of the signal ensemble with the support exploration ability of matching pursuit and recovers the signals' amplitudes on the support-set with the good reconstruction performance of GAMP. Numerical investigation shows that the joint MPGAMP algorithm provides performance improvements in DCS reconstruction compared to joint orthogonal matching pursuit, joint look ahead orthogonal matching pursuit and regular MPGAMP.

It is known that policy gradient algorithm can not guarantee the convergence to a Nash equilibrium in mixed policies when it is applied in matrix games. To overcome this problem, we propose a novel multi-agent reinforcement learning (MARL) algorithm called a policy gradient lagging anchor (PGLA) algorithm. And we prove that the agents' policies can converge to a Nash equilibrium in mixed policies by using the PGLA algorithm in two-player two-action matrix games. By simulation, we confirm the convergence and also show that the PGLA algorithm has a better convergence than the LR-I lagging anchor algorithm.

The methods proposed in this paper enable resynchronization when a synchronization deviation occurs in a sensor node without a beacon or an ack in a wireless sensor network under ultra-limited but stable resources such as the energy generated from tiny solar cell batteries. The method for a single-hop network is straightforward; when a receiver does not receive data, it is simply placed in recovery mode, in which the receiver sets its cycle length TB to (b±γ)T, where b is non-negative integer, 0 < γ < 1, and T is its cycle length in normal mode, and in which the receiver sets its active interval WB to a value that satisfies WB ≥ W + γT, where W is its active interval in normal mode. In contrast, a sender stays in normal mode. Resynchronization methods for linear multi-hop and tree-based multi-hop sensor networks are constructed using the method for a single-hop network. All the methods proposed here are complete because they are always able to resynchronize networks. The results of simulations based on the resynchronization methods are given and those of an experiment using actual sensor nodes with wireless modules are also presented, which show that the methods are feasible.

Optical I/O core based on silicon photonics technology and optical/electrical assembly was developed as a fingertip-size optical module with high bandwidth density, low power consumption, and high temperature operation. The advantages of the optical I/O core, including hybrid integration of quantum dot laser diode and optical pin, allow us to achieve 300-m transmission at 25Gbps per channel when optical I/O core is mounted around field-programmable gate array without clock data recovery.

We propose a method for extracting multi-view images from a light field (plenoptic) camera that accurately handles the physical pixel arrangement of this camera. We use a Lytro Illum camera to obtain 4D light field data (a set of multi-viewpoint images) through a micro-lens array. The light field data are multiplexed on a single image sensor, and thus, the data is first demultiplexed into a set of multi-viewpoint (sub-aperture) images. However, the demultiplexing process usually includes interpolation of the original data such as demosaicing for a color filter array and pixel resampling for the hexagonal pixel arrangement of the original sub-aperture images. If this interpolation is performed, some information is added or lost to/from the original data. In contrast, we preserve the original data as faithfully as possible, and use them directly for the super resolution reconstruction, where the super-resolved image and the corresponding depth map are alternatively refined. We experimentally demonstrate the effectiveness of our method in resolution enhancement through comparisons with Light Field Toolbox and Lytro Desktop Application. Moreover, we also mention another type of light field cameras, a Raytrix camera, and describe how it can be handled to extract high-quality multi-view images.

In recent years we have witnessed an increasing demand to process queries on large datasets in Non-ordered Discrete Data Spaces (NDDS). In particular, one type of query in an NDDS, called box queries, is used in many emerging applications including error corrections in bioinformatics and network intrusion detection in cybersecurity. Effective indexing methods are necessary for efficiently processing queries on large datasets in disk. However, most existing NDDS indexing methods were not designed for box queries. Several recent indexing methods developed for box queries on a large NDDS dataset in disk are based on the popular data-partitioning approach. Unfortunately, a space-partitioning based indexing scheme, which is more effective for box queries in an NDDS, has not been studied before. In this paper, we propose a novel indexing method based on space-partitioning, called the BINDS-tree, for supporting efficient box queries on a large NDDS dataset in disk. A number of effective strategies such as node split based on minimum span and cross optimal balance, redundancy reduction utilizing a singleton dimension inheritance property, and a space-efficient structure for the split history are incorporated in the constructing algorithm for the BINDS-tree. Experimental results demonstrate that the proposed BINDS-tree significantly improves the box query I/O performance, comparing to that of the state-of-the-artdata-partitioning based NDDS indexing method.

We propose a method to find assembly models contained in another assembly model given as a query from a set of 3D CAD assembly models. A 3D CAD assembly model consists of multiple components and is constructed using a 3D CAD software. The proposed method distinguishes assembly models which consist of a subset of components constituting the query model and also whose components have the same layout as the subset of the components. We compute difference between the shapes and the layouts of the components from the sinograms which are constructed by the Radon transform of their projections from various angles. We evaluate the proposed method experimentally using the assembly models which we prepare as a benchmark. The proposed method can also be used to find the database models which contains a query model.

As big data attracts attention in a variety of fields, research on data exploration for analyzing large-scale scientific data has gained popularity. To support exploratory analysis of scientific data, effective summarization and visualization of the target data as well as seamless cooperation with modern data management systems are in demand. In this paper, we focus on the exploration-based analysis of scientific array data, and define a spatial V-Optimal histogram to summarize it based on the notion of histograms in the database research area. We propose histogram construction approaches based on a general hierarchical partitioning as well as a more specific one, the l-grid partitioning, for effective and efficient data visualization in scientific data analysis. In addition, we implement the proposed algorithms on the state-of-the-art array DBMS, which is appropriate to process and manage scientific data. Experiments are conducted using massive evacuation simulation data in tsunami disasters, real taxi data as well as synthetic data, to verify the effectiveness and efficiency of our methods.