In this paper, the spurious modes and quality-factor (Q) values of the one-port dual-mode AlN lamb-wave resonators at 500-1000 MHz were studied by theoretical analysis and experimental verification. Through finite element analysis, we found that optimizing the width of the lateral reflection boundary at both ends of the resonator to reach the quarter wavelength (λ/4), which can improve its spectral purity and shift its resonant frequency. The designed resonators were micro-fabricated by using lithography processes on a 6-inch wafer. The measured results show that the spurious mode can be converted and dissipated, splitting into several longitudinal modes by optimizing the width of the lateral reflection boundary, which are consistent well with the theoretical analysis. Similarly, optimizing the interdigital transducer (IDT) width and number of IDT fingers can also suppress the resonator's spurious modes. In addition, it is found that there is no significant difference in the Qs value for the two modes of the dual-mode resonator with the narrow anchor and full anchor. The acoustic wave leaked from the anchor into the substrate produces a small displacement, and the energy is limited in the resonator. Compared to the resonator with Au IDTs, the resonator with Al IDTs can achieve a higher Q value due to its lower thermo-elastic damping loss. The measured results show the optimized dual-mode lamb-wave resonator can obtain Qs value of 2946.3 and 2881.4 at 730.6 MHz and 859.5 MHz, Qp values of 632.5 and 1407.6, effective electromechanical coupling coefficient (k2eff) of 0.73% and 0.11% respectively, and has excellent spectral purity simultaneously.

This paper presents a fully digital modulation calibration technique for channel mismatch of TIADC at any frequency. By pre-inputting a test signal in TIADC, the mismatch errors are estimated and stored, and the stored values will be extracted for compensation when the input signal is at special frequency which can be detected by a threshold judgement module, thus solving the problem that the traditional modulation calibration algorithm cannot calibrate the signal at special frequency. Then, by adjusting the operation order among the error estimation coefficient, modulation function and input signal in the calibration loop, further, the order of correlation and modulation in the error estimation module, the complexity of the proposed calibration algorithm is greatly reduced and it will not increase with the number of channels of TIADC. What's more, the hardware consumption of filters in calibration algorithm is greatly reduced by introducing a CSD (Canonical Signed Digit) coding technique based on Horner's rule and sub-expression sharing. Applied to a four-channel 14bit 560MHz TIADC system, with input signal at 75.6MHz, the FPGA verification results show that, after calibration, the spurious-free dynamic range (SFDR) improves from 33.47dB to 99.81dB and signal-to-noise distortion ratio (SNDR) increases from 30.15dB to 81.89dB.

Aiming at the problem of the deterioration of the contact performance caused by the wear debris generated during the fretting wear of the electrical connector, low-frequency fretting wear experiments were carried out on the contacts of electrical connectors, the accumulation and distribution of the wear debris were detected by the electrical capacitance tomography technology; the influence of fretting cycles, vibration direction, vibration frequency and vibration amplitude on the accumulation and distribution of wear debris were analyzed; the correlation between characteristic value of wear debris and contact resistance value was studied, and a performance degradation model based on the accumulation and distribution of wear debris was built. The results show that fretting wear and performance degradation are the most serious in axial vibration; the characteristic value of wear debris and contact resistance are positively correlated with the fretting cycles, vibration frequency and vibration amplitude; there is a strong correlation between the sum of characteristic value of wear debris and the contact resistance value; the prediction error of ABC-SVR model of fretting wear performance degradation of electrical connectors constructed by the characteristic value of wear debris is less than 6%. Therefore, the characteristic value of wear debris in contact subareas can quantitatively describe the degree of fretting wear and the process of performance degradation.

An efficient bent waveguide and an optical power splitter with a resonator constructed by a metal-dielectric-metal plasmonic waveguide have been analyzed. The method of solution is the finite difference time domain (FD-TD) method with the piecewise linear recursive convolution (PLRC) method. The resonator can be realized by utilizing impedance mismatch at the connection between a narrow waveguide and an input/output waveguide. Numerical results for the bent waveguide show that transmission bands can be controlled by adjusting the length of the narrow waveguide. We have also shown that the optical power of the power splitter is entirely distributed into the output waveguide at the resonant wavelength and its distribution ratio can be controlled.

We attempt to design and fabricate of a 4×4 Butler matrix for short-millimeter-wave frequencies by using the microfabrication process for a polytetrafluoroethylene (PTFE) substrate-integrated waveguide (SIW) by the synchrotron radiation (SR) direct etching of PTFE and the addition of a metal film by sputter deposition. First, the dimensions of the PTFE SIW using rectangular through-holes for G-band (140-220 GHz) operation are determined, and a cruciform 90 ° hybrid coupler and an intersection circuit are connected by the PTFE SIW to design the Butler matrix. Then, a trial fabrication is performed. Finally, the validity of the design result and the fabrication process is verified by measuring the radiation pattern.

This paper analyzes a blockchain network forming a directed acyclic graph (DAG), called a DAG-type blockchain, from the viewpoint of graph algorithm theory. To use a DAG-type blockchain, NP-hard graph optimization problems on the DAG are required to be solved. Although various problems for undirected and directed graphs can be efficiently solved by using the notions of graph parameters, these currently known parameters are meaningless for DAGs, which implies that it is hopeless to design efficient algorithms based on the parameters for such problems. In this work, we propose a novel graph parameter for directed graphs called a DAG-pathwidth, which represents the closeness to a directed path. This is an extension of the pathwidth, a well-known graph parameter for undirected graphs. We analyze the features of the DAG-pathwidth and prove that computing the DAG-pathwidth of a DAG (directed graph in general) is NP-complete. Finally, we propose an efficient algorithm for a variant of the maximum k-independent set problem for the DAG-type blockchain when the DAG-pathwidth of the input graph is small.

Register automaton (RA) is an extension of finite automaton by adding registers storing data values. RA has good properties such as the decidability of the membership and emptiness problems. Linear temporal logic with the freeze quantifier (LTL↓) proposed by Demri and Lazić is a counterpart of RA. However, the expressive power of LTL↓ is too high to be applied to automatic verification. In this paper, we propose a subclass of modal µ-calculus with the freeze quantifier, which has the same expressive power as RA. Since a conjunction ψ1 ∧ ψ2 in a general LTL↓ formula cannot be simulated by RA, the proposed subclass prohibits at least one of ψ1 and ψ2 from containing the freeze quantifier or a temporal operator other than X (next). Since the obtained subclass of LTL↓ does not have the ability to represent a cycle in RA, we adopt µ-calculus over the subclass of LTL↓, which allows recursive definition of temporal formulas. We provide equivalent translations from the proposed subclass of µ-calculus to RA and vice versa and prove their correctness.

Recently, we introduced a new automata model, so-called colored finite automata (CFAs) whose accepting states are multi-colored (i.e., not conventional black-and-white acceptance) in order to classify their input strings into two or more languages, and solved the specific complexity problems concerning color-unmixedness of nondeterministic CFA. That is, so-called UV, UP, and UE problems are shown to be NLOG-complete, P, and NP-complete, respectively. In this paper, we apply the concept of colored accepting mechanism to pushdown automata and show that the corresponding versions of the above-mentioned complexity problems are all undecidable. We also investigate the case of unambiguous pushdown automata and show that one of the problems turns out to be permanent true (the others remain undecidable).

Due to the limitations of cloud computing on latency, bandwidth and data confidentiality, edge computing has emerged as a novel location-aware paradigm to provide them with more processing capacity to improve the computing performance and quality of service (QoS) in several typical domains of human activity in smart society, such as social networks, medical diagnosis, telecommunications, recommendation systems, internal threat detection, transports, Internet of Things (IoT), etc. These application domains often handle a vast collection of entities with various relationships, which can be naturally represented by the graph data structure. Graph processing is a powerful tool to model and optimize complex problems in which the graph-based data is involved. In view of the relatively insufficient resource provisioning of the portable terminals, in this paper, for the first time to our knowledge, we propose an interactive and reductive graph processing library (GPL) for edge computing in smart society at low overhead. Experimental evaluation is conducted to indicate that the proposed GPL is more user-friendly and highly competitive compared with other established systems, such as igraph, NetworKit and NetworkX, based on different graph datasets over a variety of popular algorithms.

Calculation is a solitaire card game with a standard 52-card deck. Initially, cards A, 2, 3, and 4 of any suit are laid out as four foundations. The remaining 48 cards are piled up as the stock, and there are four empty tableau piles. The purpose of the game is to move all cards of the stock to foundations. The foundation starting with A is to be built up in sequence from an ace to a king. The other foundations are similarly built up, but by twos, threes, and fours from 2, 3, and 4 until a king is reached. Here, a card of rank i may be used as a card of rank i + 13j for j ∈ {0, 1, 2, 3}. During the game, the player moves (i) the top card of the stock either onto a foundation or to the top of a tableau pile, or (ii) the top card of a tableau pile onto a foundation. We prove that the generalized version of Calculation Solitaire is NP-complete.

Stereo depth estimation has become an attractive topic in the computer vision field. Although various algorithms strive to optimize the speed and the precision of estimation, the energy cost of a system is also an essential metric for an embedded system. Among these various algorithms, Semi-Global Matching (SGM) has been a popular choice for some real-world applications because of its accuracy-and-speed balance. However, its power consumption makes it difficult to be applied to an embedded system. Thus, we propose a robust stereo matching system, RT-libSGM, working on the Xilinx Field-Programmable Gate Array (FPGA) platforms. The dedicated design of each module optimizes the speed of the entire system while ensuring the flexibility of the system structure. Through an evaluation on a Zynq FPGA board called M-KUBOS, RT-libSGM achieves state-of-the-art performance with lower power consumption. Compared with the benchmark design (libSGM) working on the Tegra X2 GPU, RT-libSGM runs more than 2× faster at a much lower energy cost.

Using third-party intellectual properties (3PIP) has been a norm in IC design development process to meet the time-to-market demand and at the same time minimizing the cost. But this flow introduces a threat, such as hardware trojan, which may compromise the security and trustworthiness of underlying hardware, like disclosing confidential information, impeding normal execution and even permanent damage to the system. In years, different detections methods are explored, from just identifying if the circuit is infected with hardware trojan using conventional methods to applying machine learning where it identifies which nets are most likely are hardware trojans. But the performance is not satisfactory in terms of maximizing the detection rate and minimizing the false positive rate. In this paper, a new hardware trojan detection approach is proposed where gate-level netlist is segmented into regions first before analyzing which nets might be hardware trojans. The segmentation process depends on the nets' connectivity, more specifically by looking on each fanout points. Then, further analysis takes place by means of computing the structural similarity of each segmented region and differentiate hardware trojan nets from normal nets. Experimental results show 100% detection of hardware trojan nets inserted on each benchmark circuits and an overall average of 1.38% of false positive rates which resulted to a higher accuracy with an average of 99.31%.

The equilibrium optimizer (EO) is a novel physics-based meta-heuristic optimization algorithm that is inspired by estimating dynamics and equilibrium states in controlled volume mass balance models. As a stochastic optimization algorithm, EO inevitably produces duplicated solutions, which is wasteful of valuable evaluation opportunities. In addition, an excessive number of duplicated solutions can increase the risk of the algorithm getting trapped in local optima. In this paper, an improved EO algorithm with a bis-population-based non-revisiting (BNR) mechanism is proposed, namely BEO. It aims to eliminate duplicate solutions generated by the population during iterations, thus avoiding wasted evaluation opportunities. Furthermore, when a revisited solution is detected, the BNR mechanism activates its unique archive population learning mechanism to assist the algorithm in generating a high-quality solution using the excellent genes in the historical information, which not only improves the algorithm's population diversity but also helps the algorithm get out of the local optimum dilemma. Experimental findings with the IEEE CEC2017 benchmark demonstrate that the proposed BEO algorithm outperforms other seven representative meta-heuristic optimization techniques, including the original EO algorithm.

In this paper we propose an extension of the Attention Branch Network (ABN) by using instance segmentation for generating sharper attention maps for action recognition. Methods for visual explanation such as Grad-CAM usually generate blurry maps which are not intuitive for humans to understand, particularly in recognizing actions of people in videos. Our proposed method, Object-ABN, tackles this issue by introducing a new mask loss that makes the generated attention maps close to the instance segmentation result. Further the Prototype Conformity (PC) loss and multiple attention maps are introduced to enhance the sharpness of the maps and improve the performance of classification. Experimental results with UCF101 and SSv2 shows that the generated maps by the proposed method are much clearer qualitatively and quantitatively than those of the original ABN.

Many optimisation algorithms improve the algorithm from the perspective of population structure. However, most improvement methods simply add hierarchical structure to the original population structure, which fails to fundamentally change its structure. In this paper, we propose an umbrellalike hierarchical artificial bee colony algorithm (UHABC). For the first time, a historical information layer is added to the artificial bee colony algorithm (ABC), and this information layer is allowed to interact with other layers to generate information. To verify the effectiveness of the proposed algorithm, we compare it with the original artificial bee colony algorithm and five representative meta-heuristic algorithms on the IEEE CEC2017. The experimental results and statistical analysis show that the umbrellalike mechanism effectively improves the performance of ABC.

We characterized prion disease by comparing brain functional connectivity network (BFCN), which were constructed by 16-ch scalp-recorded electroencephalograms (EEGs). The connectivity between each pair of nodes (electrodes) were computed by synchronization likelihood (SL). The BFCN was applied to graph theory to discriminate prion disease patients from healthy elderlies and dementia groups.

A new method for hiding information in digital images is proposed. Our method differs from existing techniques in that the information is hidden in a mixture of colors carefully tuned on a specific device according to the device's signal-to-luminance (gamma) characteristics. Because these reproduction characteristics differ in general from device to device and even from model to model, the hidden information appears when the cover image is viewed on a different device, and hence the hiding property is device-dependent. To realize this, we modulated a cover image using two identically-looking checkerboard patterns and switched them locally depending on the hidden information. Reproducing these two patterns equally on a different device is difficult. A possible application of our method would be secure printing where an image is allowed to be viewed only on a screen but a warning message appears when it is printed.

This study focuses on creating arithmetical stories as a sub-task of problem posing and proposes a game named “Tri-prop scrabble” as a learning environment based on a fusion method of learning and game. The problem-posing ability has a positive relationship with mathematics achievement and understanding the mathematical structure of problems. In the proposed game, learners are expected to experience creating and concatenating various arithmetical stories by integrating simple sentences. The result of a preliminary feasibility study shows that the participants were able to pose and concatenate a variety of types of arithmetic stories and accept this game is helpful for learning arithmetic word problems.

This paper focuses on the potential value and future prospects of using virtual reality (VR) technology in online education. In detailing online education and the latest VR technology, we focus on metaverse construction and artificial intelligence (AI) for educational VR use. In particular, we describe a virtual university campus in which on-demand VR lectures are conducted in virtual lecture halls, automated evaluations of student learning and training using machine learning, and the linking of multiple digital campuses.

Quadrature voltage-controlled oscillators (VCOs) with current-weight-average and voltage-weight-average phase-adjusting architectures are studied. The phase adjusting equalizes the oscillation frequency to the LC-resonant frequency. The merits of the equalization are explained by using Leeson's phase noise equation and the impulse sensitivity function (ISF). Quadrature VCOs with the phase-adjusting architectures are fabricated using 180-nm TSMC CMOS and show low-phase-noise performances compared to a conventional differential VCO. The ISF analysis and small-signal analysis also show that the drawbacks of the current-weight-average phase-adjusting and voltage-weight-average phase-adjusting architectures are current-source noise effect and large additional capacitance, respectively. A voltage-average-adjusting circuit with a source follower at its input alleviates the capacitance increase.