Left-weight sequences (LW-sequences for short) are in common currency for encoding binary trees. In [16], Wu et al. proposed an algorithm associated with tree rotations for listing all binary trees in diverse representations including LW-sequences. In particular, such a list of LW-sequences is generated in Gray-code order. In this paper, based on this ordering, we present efficient ranking and unranking algorithms. For binary trees with n internal nodes, the time complexity and the space requirement in each of our ranking and unranking algorithms are O(n2) and O(n), respectively.

The purpose of this paper is to present a case study of the development, implementation and performance analysis of an autonomous flight control strategy for a 1-meter small-sized unmanned aerial vehicle. Firstly, a learning algorithm based open-loop control is proposed by simulating a skilled human operator's manipulation of the aircraft. This is aimed to generate a set of command data inputs and investigate the multi-channel control characteristics with the open-loop control. Secondly, a feedforward plus a proportional and derivative (PD) feedback control is employed to control the vehicle in following the command data to complete the loitering flight. The PD control gains are tuned automatically according to the attitude of the vehicle using the fuzzy logic theory. Thirdly, autonomous flight experiments conducted on a 1-meter small-sized aerial vehicle demonstrated the effectiveness of the proposed method.

In this paper, we introduce a concise representation, called right-distance sequences (or RD-sequences for short), to describe all t-ary trees with n internal nodes. A result reveals that there exists a close relationship between the representation and the well-formed sequences suggested by Zaks [Lexicographic generation of ordered trees, Theoretical Computer Science 10 (1980) 63-82]. Using a coding tree and its concomitant tables, a systematical way can help us to investigate the structural representation of t-ary trees. Consequently, we develop efficient algorithms for determining the rank of a given t-ary tree in lexicographic order (i.e., a ranking algorithm), and for converting a positive integer to its corresponding RD-sequence (i.e., an unranking algorithm). Both the ranking and unranking algorithms can be run in O(tn) time and without computing all the entries of the coefficient table.

A conical area evolutionary algorithm (CAEA) is presented to further improve computational efficiencies of evolutionary algorithms for bi-objective optimization. CAEA partitions the objective space into a number of conical subregions and then solves a scalar subproblem in each subregion that uses a conical area indicator as its scalar objective. The local Pareto optimality of the solution with the minimal conical area in each subregion is proved. Experimental results on bi-objective problems have shown that CAEA offers a significantly higher computational efficiency than the multi-objective evolutionary algorithm based on decomposition (MOEA/D) while CAEA competes well with MOEA/D in terms of solution quality.

A new design methodology is proposed and analyzed for the design of ternary logic systems. In the new ternary logic systems, no conversions among radices are required and only the two-state ternary literals associated with the ternary signals are transmitted in the whole system. With the new design methodology, the ternary systems can be realized by the dynamic CMOS logic circuits which are simple and fully compatible with those of the conventional binary logic circuits in process, power supply, and logic levels. A new dynamic differential logic called the CMOS Redundant Differential Logic (CRDL) is also developed to increase the logic flexibility and the circuit performance. Using the new design methodology and the CRDL circuits, the multiplier with redundant binary addition tree is designed in both non-pipelined and pipelined systems. The experimental chip has been fabricated and measured, which successfully verifies the correctness of the logic functions and the speed performance of the designed circuits.

A non-regular tree T with a prescribed branching sequence (s1,s2,...,sn) is a rooted and ordered tree such that its internal nodes are numbered from 1 to n in preorder and every internal node i in T has si children. Recently, Wu et al. (2010) introduced a concise representation called RD-sequences to represent all non-regular trees and proposed a loopless algorithm for generating all non-regular trees in a Gray-code order. In this paper, based on such a Gray-code order, we present efficient ranking and unranking algorithms of non-regular trees with n internal nodes. Moreover, we show that the ranking algorithm and the unranking algorithm can be run in O(n2) time and O(n2+nSn-1) time, respectively, provided a preprocessing takes O(n2Sn-1) time and space in advance, where .

Unstructured overlay networks are widely adopted in large-scale and heterogeneous peer-to-peer (P2P) systems for their scalability and flexibility. A distinct feature of such systems is that they randomly route messages e.g., by flooding or random walk. In such systems, the number of messages and tasks carrying by those messages each peer receives is greatly affected by the number of the peer's incoming links. The objective of this paper is to build controllable degree-weighted networks in which the expected number of incoming links of each peer is proportional to its weight which is a local parameter. In such a network, a peer can control the number of those randomly disseminated messages and tasks it receives by adjust it weight. In addition, in order to bound the construction overhead for highly biased networks, we restrict all peers to have the same number of outgoing links. The objective network is constructed by local topology transformations that peers periodically exchange outgoing links with each other. A framework, which includes 81 different protocols by combination of exchange rules, is presented and evaluated by simulation. The simulation result shows that two of them can generate the networks having similar properties with the objective network. This work first achieves the weight-proportional degree control under the out-regular network model.

Resource search is a fundamental problem in large-scale and highly dynamic Peer-to-Peer (P2P) systems. Unstructured search approaches are widely used because of their flexibility and robustness. However, such approaches incur high communication cost. The index-dissemination-based search is a kind of efficient unstructured search approach. We investigate such approaches with respect to minimize the system communication cost. Based on a dynamic system model that peers continuously leave and join, we solve two problems. One problem is how to efficiently disseminate and maintain a given number of indices. Another is to determine the optimal number of indices for each resource object of a given popularity. Finally, we propose an optimized index dissemination scheme which is fully decentralized and self-adaptive. A remarkable advantage is that the scheme yields no additional communication cost to achieve the self-adaptive feature.

A low-power K-band CMOS current-mode up-conversion mixer is proposed. The proposed mixer is realized using four analog current-squaring circuits. This current-mode up-conversion mixer is fabricated in 0.13-µm 1P8M triple-well CMOS process, and has the measured power conversion gain of -5 dB. The fabricated CMOS up-conversion mixer dissipates only 3.1 mW from a 1-V supply voltage. The VCO can be tuned from 20.8 GHz to 22.7 GHz. Its phase noise is -108 dBc/Hz at 10-MHz offset frequency. It is shown that the proposed mixer has great potential for low-voltage and low-power CMOS transmitter front-ends in advanced nano-CMOS technologies.

Heat map is an important tool for eye tracking data analysis and visualization. It is very intuitive to express the area watched by observer, but ignores saccade information that expresses gaze shift. Based on conventional heat map generation method, this paper presents a novel heat map generation method for eye tracking data. The proposed method introduces a mixed data structure of fixation points and saccades, and considers heat map deformation for saccade type data. The proposed method has advantages on indicating gaze transition direction while visualizing gaze region.

A 0.8-V CMOS Phase-Locked Loop (PLL) has been designed and fabricated by using a 0.13-µm 1p8m CMOS process. In the proposed PLL, the double-positive-feedbacks voltage-controlled oscillator (DPF-VCO) is used to generate current signals for the coupling current-mode injection-locked frequency divider (CCMILFD) and current-injection current-mode logic (CICML) divider. A short-pulsed-reset phase frequency detector (SPR-PFD) with the reduced pulse width of reset signal to improve the linear range of the PFD and a complementary-type charge pump to eliminate the current path delay are also adopted in the proposed PLL. The measured in-band phase noise of the fabricated PLL is -98 dBc/Hz. The locking range of the PLL is from 22.6 GHz to 23.3 GHz and the reference spur level is -69 dBm that is 54 dB bellow the carrier. The power consumption is 9.2 mW under a 0.8-V power supply. The proposed PLL has the advantages of low phase noise, low reference spur, and low power dissipation at low voltage operation.

The conical area evolutionary algorithm (CAEA) has a very high run-time efficiency for bi-objective optimization, but it can not tackle problems with more than two objectives. In this letter, a conical hypervolume evolutionary algorithm (CHEA) is proposed to extend the CAEA to a higher dimensional objective space. CHEA partitions objective spaces into a series of conical subregions and retains only one elitist individual for every subregion within a compact elitist archive. Additionally, each offspring needs to be compared only with the elitist individual in the same subregion in terms of the local hypervolume scalar indicator. Experimental results on 5-objective test problems have revealed that CHEA can obtain the satisfactory overall performance on both run-time efficiency and solution quality.

In this letter, a path dynamics assessment asynchronous advantage actor-critic scheduling algorithm (PDAA3C) is proposed to solve the MPTCP scheduling problem by using deep reinforcement learning Actor-Critic framework. The algorithm picks out the optimal transmitting path faster by multi-core asynchronous updating and also guarantee the network fairness. Compared with the existing algorithms, the proposed algorithm achieves 8.6% throughput gain over RLDS algorithm, and approaches the theoretic upper bound in the NS3 simulation.

A direct-conversion receiver integrated with the CMOS subharmonic frequency tripler (SFT) for V-band applications is designed, fabricated and measured using 0.13-µm CMOS technology. The receiver consists of a low-noise amplifier, a down-conversion mixer, an output buffer, and an SFT. A fully differential SFT is introduced to relax the requirements on the design of the frequency synthesizer. Thus, the operational frequency of the frequency synthesizer in the proposed receiver is only 20 GHz. The fabricated receiver has a maximum conversion gain of 19.4 dB, a minimum single-side band noise figure of 10.2 dB, the input-referred 1-dB compression point of -20 dBm and the input third order inter-modulation intercept point of -8.3 dB. It draws only 15.8 mA from a 1.2-V power supply with a total chip area of 0.794 mm0.794 mm. As a result, it is feasible to apply the proposed receiver in low-power wireless transceiver in the V-band applications.

A partitioning parallelization of the multi-objective evolutionary algorithm based on decomposition, pMOEA/D, is proposed in this letter to achieve significant time reductions for expensive bi-objective optimization problems (BOPs) on message-passing clusters. Each sub-population of pMOEA/D resides on a separate processor in a cluster and consists of a non-overlapping partition and some extra overlapping individuals for updating neighbors. Additionally, sub-populations cooperate across separate processors by the hybrid migration of elitist individuals and utopian points. Experimental results on two benchmark BOPs and the wireless sensor network layout problem indicate that pMOEA/D achieves satisfactory performance in terms of speedup and quality of solutions on message-passing clusters.

In this letter, the k-out-of-n rule for cooperative sensing is considered. For a given n, we derive the optimal value of k that minimizes the total sensing error probability subject to the sensing accuracy, considering both the effective of sensing errors and the primary activities. According to the optimal k, we analyze the performance and compare with other schemes, which illustrate the effectiveness of the proposed scheme.

A queue layout of a graph G consists of a linear order of its vertices, and a partition of its edges into queues, such that no two edges in the same queue are nested. The queuenumber qn(G) is the minimum number of queues required in a queue layout of G. The Cartesian product of two graphs G1 = (V1,E1) and G2 = (V2,E2), denoted by G1 × G2, is the graph with {:v1 ∈ V1 and v2 ∈ V2} as its vertex set and an edge (,) belongs to G1×G2 if and only if either (u1,v1) ∈ E1 and u2 = v2 or (u2,v2) ∈ E2 and u1 = v1. Let Tk1,k2,...,kn denote the n-dimensional toroidal grid defined by the Cartesian product of n cycles with varied lengths, i.e., Tk1,k2,...,kn = Ck1 × Ck2 × … × Ckn, where Cki is a cycle of length ki ≥ 3. If k1 = k2 = … = kn = k, the graph is also called the k-ary n-cube and is denoted by Qnk. In this paper, we deal with queue layouts of toroidal grids and show the following bound: qn(Tk1,k2,...,kn) ≤ 2n-2 if n ≥ 2 and ki ≥ 3 for all i = 1,2,...,n. In particular, for n = 2 and k1,k2 ≥ 3, we acquire qn(Tk1,k2) = 2. Recently, Pai et al. (Inform. Process. Lett. 110 (2009) pp.50-56) showed that qn(Qnk) ≤ 2n-1 if n ≥1 and k ≥9. Thus, our result improves the bound of qn(Qnk) when n ≥2 and k ≥9.

An n-dimensional folded hypercube, denoted by FQn, is an enhanced n-dimensional hypercube with one extra link between nodes that have the furthest Hamming distance. Let FFv (respectively, FFe) denote the set of faulty nodes (respectively, faulty links) in FQn. Under the assumption that every fault-free node in FQn is incident to at least two fault-free links, Hsieh et al. (Inform. Process. Lett. 110 (2009) pp.41-53) showed that if |FFv|+|FFe| ≤ 2n-4 for n ≥ 3, then FQn-FFv-FFe contains a fault-free cycle of length at least 2n-2|FFv|. In this paper, we show that, under the same conditional fault model, FQn with n ≥ 5 can tolerate more faulty elements and provides the same lower bound of the length of a longest fault-free cycle, i.e., FQn-FFv-FFe contains a fault-free cycle of length at least 2n-2|FFv| if |FFv|+|FFe| ≤ 2n-3 for n ≥ 5.

Real-time matting is a challenging research in deep learning. Conventional CNN (Convolutional Neural Networks) approaches are easy to misjudge the foreground and background semantic and have blurry matting edges, which result from CNN’s limited concentration on global context due to receptive field. We propose a real-time matting approach called RMViT (Real-time matting with Vision Transformer) with Transformer structure, attention and content-aware guidance to solve issues above. The semantic accuracy improves a lot due to the establishment of global context and long-range pixel information. The experiments show our approach exceeds a 30% reduction in error metrics compared with existing real-time matting approaches.