Before introducing systems to an activity in a business or in daily life, the effects of these systems should first be carefully examined by analysts. Thus, methods for examining such effects are required at the early stage of requirements analysis. In this study, we propose and evaluate an analysis method using a modeling notation for this purpose, called goal dependency modeling and analysis (GDMA). In an activity, an actor, such as a person or a system, expects a goal to be achieved. The actor or another actor will achieve this goal. We focus herein on such a goal and the two different roles played by the actors. In GDMA, the dependencies in the roles of the two actors about a goal are mainly represented. GDMA enables analysts to observe the change of actors, their expectations, and abilities by using metrics. Each metric is defined on the basis of the GDMA meta-model. Therefore, GDMA enables them to decide whether the change is good or bad both quantitatively and qualitatively for the people. We evaluate GDMA by describing models of the actual system introduction written in the literatures and explain the effects caused by this introduction. In addition, CASE tools are crucial in efficiently and accurately performing GDMA. Hence, we develop its tools by extending an existing UML modeling tool.

Reliability is an important figure of merit of the system and it must be satisfied in safety-critical applications. This paper considers parallel applications on heterogeneous embedded systems and proposes a two-phase algorithm framework to minimize energy consumption for satisfying applications’ reliability requirement. The first phase is for initial assignment and the second phase is for either satisfying the reliability requirement or improving energy efficiency. Specifically, when the application’s reliability requirement cannot be achieved via the initial assignment, an algorithm for enhancing the reliability of tasks is designed to satisfy the application’s reliability requirement. Considering that the reliability of initial assignment may exceed the application’s reliability requirement, an algorithm for reducing the execution frequency of tasks is designed to improve energy efficiency. The proposed algorithms are compared with existing algorithms by using real parallel applications. Experimental results demonstrate that the proposed algorithms consume less energy while satisfying the application’s reliability requirements.

A double step attenuation measurement technique using a non-isolating gauge block attenuator (GBA) has been proposed for accurate measurements of radio frequency and microwave high attenuation. For fixed attenuator as a device under test (DUT), a medium value (≤ 60 dB) attenuator is used as the GBA which connected directly between the test ports, then high attenuation of the DUT is measured in two setups as follows. 1) Thru and GBA with normal power level and 2) GBA and DUT with higher power level. This approach removes the need to isolate the GBA, therefore, accurate measurements of high attenuation can be obtained simply over a broad frequency range. For variable or step attenuator as a DUT, one of the attenuation sections of the DUT is applied as the GBA. Detailed analyses and those verification measurements are carried out both for fixed attenuator, as well as for variable attenuator and show good agreement.

This paper proposes a novel configuration for a wideband single-carrier transmitter using a sub-terahertz frequency. For wideband single-carrier transmission over a bandwidth of several gigahertz, the frequency response non-flatness derived from transmitter components in an operating band seriously deteriorates the transmission quality due to inter-symbol interference. A promising approach to address this problem is equalizing the frequency response non-flatness at the transmitter. The proposed novel configuration has a feedback route for calculating the inverse frequency response and multiplying it with a transmission signal spectrum in the frequency domain. Moreover, we verify that employing the proposed transmitter configuration simplifies the receiver configuration by lowering the calculation complexity to minimize the inter-symbol interference to meet the signal-to-interference-and-noise ratio requirements. To confirm the feasibility of the proposed configuration, the transmission quality obtained using the proposed configuration is measured and evaluated. Experimental results confirm that the proposed configuration improves the error vector magnitude value to over 5 dB for a 10 Gbaud transmission and the transmission data rate of 25 Gbps.

The load-independent zero-voltage switching class-E inverter has garnered considerable interest as an essential component in wireless power transfer systems. This inverter achieves high efficiency across a broad spectrum of load conditions by incorporating a load adjustment circuit (LAC) subsequent to the resonant filter. Nevertheless, the presence of the LAC influences the output impedance of the inverter, thereby inducing a divergence between the targeted and observed output power, even in ideal lossless simulations. Consequently, iterative adjustments to component values are required via an LC element implementation. We introduce a novel design methodology that incorporates an external quality factor on the side of the resonant filter, inclusive of the LAC. Thus, the optimized circuit achieves the intended output power without necessitating alterations in component values.

Recently, trace representation of a class of balanced quaternary sequences of period p from the classical cyclotomic classes was given by Yang et al. (Cryptogr. Commun.,15 (2023): 921-940). In this letter, based on the generalized cyclotomic classes, we define a class of balanced quaternary sequences of period pn, where p = ef + 1 is an odd prime number and satisfies e ≡ 0 (mod 4). Furthermore, we calculate the defining polynomial of these sequences and obtain the formula for determining their trace representations over ℤ4, by which the linear complexity of these sequences over ℤ4 can be determined.

To address the challenge of target signals being completely submerged by ionospheric clutter during typhoon passages, this letter proposes a chaotic detection method for target signals in the background of ionospheric noise under typhoon excitation. Experimental results demonstrate the effectiveness of the proposed method in detecting target signals with harmonic characteristics from strong ionospheric clutter during typhoon passages.

We consider the problem of finding the best subset of sensors in wireless sensor networks where linear Bayesian parameter estimation is conducted from the selected measurements corrupted by correlated noise. We aim to directly minimize the estimation error which is manipulated by using the QR and LU factorizations. We derive an analytic result which expedites the sensor selection in a greedy manner. We also provide the complexity of the proposed algorithm in comparison with previous selection methods. We evaluate the performance through numerical experiments using random measurements under correlated noise and demonstrate a competitive estimation accuracy of the proposed algorithm with a reasonable increase in complexity as compared with the previous selection methods.

Unmanned Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) can provide mobile users (MU) with additional computing services and a wide range of connectivity. This paper investigates the joint optimization strategy of task offloading and resource allocation for UAV-assisted MEC systems in complex scenarios with the goal of reducing the total system cost, consisting of task execution latency and energy consumption. We adopt a game theoretic approach to model the interaction process between the MEC server and the MU Stackelberg bilayer game model. Then, the original problem with complex multi-constraints is transformed into a duality problem using the Lagrangian duality method. Furthermore, we prove that the modeled Stackelberg bilayer game has a unique Nash equilibrium solution. In order to obtain an approximate optimal solution to the proposed problem, we propose a two-stage alternating iteration (TASR) algorithm based on the subgradient method and the marginal revenue optimization method. We evaluate the effective performance of the proposed algorithm through detailed simulation experiments. The simulation results show that the proposed algorithm is superior and robust compared to other benchmark methods and can effectively reduce the task execution latency and total system cost in different scenarios.

A novel temporal convolution network-gated recurrent unit (NTCN-GRU) algorithm is proposed for the greatest of constant false alarm rate (GO-CFAR) frequency hopping (FH) prediction, integrating GRU and Bayesian optimization (BO). GRU efficiently captures the semantic associations among long FH sequences, and mitigates the phenomenon of gradient vanishing or explosion. BO improves extracting data features by optimizing hyperparameters besides. Simulations demonstrate that the proposed algorithm effectively reduces the loss in the training process, greatly improves the FH prediction effect, and outperforms the existing FH sequence prediction model. The model runtime is also reduced by three-quarters compared with others FH sequence prediction models.

This paper reports a spatial extrapolation of the sound field with a physics-informed neural network. We investigate the spatial extrapolation of the room impulse responses with physics-informed SIREN architecture. Furthermore, we proposed a noise-robust extrapolation method by introducing a tolerance term to the loss function.

Latin squares are a classical and well-studied topic of discrete mathematics, and recently Takeuti and Adachi (IACR ePrint, 2023) proposed (2, n)-threshold secret sharing based on mutually orthogonal Latin squares (MOLS). Hence efficient constructions of as large sets of MOLS as possible are also important from practical viewpoints. In this letter, we determine the maximum number of MOLS among a known class of Latin squares defined by weighted sums. We also mention some known property of Latin squares interpreted via the relation to secret sharing and a connection of Takeuti-Adachi’s scheme to Shamir’s secret sharing scheme.

The development of energy-efficient neural network hardware using magnetic tunnel junction (MTJ) devices has been widely investigated. One of the issues in the use of MTJ devices is large write energy. Since MTJ devices show stochastic behaviors, a large write current with enough time length is required to guarantee the certainty of the information held in MTJ devices. This paper demonstrates that quantized neural networks (QNNs) exhibit high tolerance to bit errors in weights and an output feature map. Since probabilistic switching errors in MTJ devices do not have always a serious effect on the performance of QNNs, large write energy is not required for reliable switching operations of MTJ devices. Based on the evaluation results, we achieve about 80% write-energy reduction on buffer memory compared to the conventional method. In addition, it is demonstrated that binary representation exhibits higher bit-error tolerance than the other data representations in the range of large error rates.

Neural networks (NNs) fail to perform well or make excessive predictions when predicting out-of-distribution or unseen datasets. In contrast, Bayesian neural networks (BNNs) can quantify the uncertainty of their inference to solve this problem. Nevertheless, BNNs have not been widely adopted owing to their increased memory and computational cost. In this study, we propose a novel approach to extend binary neural networks by introducing a probabilistic interpretation of binary weights, effectively converting them into BNNs. The proposed approach can reduce the number of weights by half compared to the conventional method. A comprehensive comparative analysis with established methods like Monte Carlo dropout and Bayes by backprop was performed to assess the performance and capabilities of our proposed technique in terms of accuracy and capturing uncertainty. Through this analysis, we aim to provide insights into the advantages of this Bayesian extension.

With the advent of gated quantum computers and the regular structures for qubit layout, methods for placement, routing, noise estimation, and logic to hardware mapping become imminently required. In this paper, we propose a method for quantum circuit layout that is intended to solve such problems when mapping a quantum circuit to a gated quantum computer. The proposed methodology starts by building a Circuit Interaction Graph (CIG) that represents the ideal hardware layout minimizing the distance and path length between the individual qubits. The CIG is also used to introduce a qubit noise model. Once constructed, the CIG is iteratively reduced to a given architecture (qubit coupling model) specifying the neighborhood, qubits, priority, and qubits noise. The introduced constraints allow us to additionally reduce the graph according to preferred weights of desired properties. We propose two different methods of reducing the CIG: iterative reduction or the iterative isomorphism search algorithm. The proposed method is verified and tested on a set of standard benchmarks with results showing improvement on certain functions while in average improving the cost of the implementation over the current state of the art methods.

This paper proposes a scatterer information estimation method using numerical data for the response waveform of a backward transient scattering field for both E- and H-polarizations when a two-dimensional (2-D) coated metal cylinder is selected as a scatterer. It is assumed that a line source and an observation point are placed at different locations. The four types of scatterer information covered in this paper are the relative permittivity of a surrounding medium, the relative permittivity of a coating medium layer and its thickness, and the radius of a coated metal cylinder. Specifically, a time-domain saddle-point technique (TD-SPT) is used to derive scatterer information estimation formulae from the amplitude intensity ratios (AIRs) of adjacent backward transient scattering field components. The estimates are obtained by substituting the numerical data of the response waveforms of the backward transient scattering field components into the estimation formulae and performing iterative calculations. Furthermore, a minimum thickness of a coating medium layer for which the estimation method is valid is derived, and two kinds of applicable conditions for the estimation method are proposed. The effectiveness of the scatterer information estimation method is verified by comparing the estimates with the set values. The noise tolerance and convergence characteristics of the estimation method and the method of controlling the estimation accuracy are also discussed.

In underwater acoustic communication systems based on orthogonal frequency division multiplexing (OFDM), taking clipping to reduce the peak-to-average power ratio leads to nonlinear distortion of the signal, making the receiver unable to recover the faded signal accurately. In this letter, an Aquila optimizer-based convolutional attention block stacked network (AO-CABNet) is proposed to replace the receiver to improve the ability to recover the original signal. Simulation results show that the AO method has better optimization capability to quickly obtain the optimal parameters of the network model, and the proposed AO-CABNet structure outperforms existing schemes.

Point cloud video contains not only color information but also spatial position information and usually has large volume of data. Typical rate distortion optimization algorithms based on Human Visual System only consider the color information, which limit the coding performance. In this paper, a Coding Tree Unit (CTU) level quantization parameter (QP) adjustment algorithm based on JND and spatial complexity is proposed to improve the subjective and objective quality of Video-Based Point Cloud Compression (V-PCC). Firstly, it is found that the JND model is degraded at CTU level for attribute video due to the pixel filling strategy of V-PCC, and an improved JND model is designed using the occupancy map. Secondly, a spatial complexity detection metric is designed to measure the visual importance of each CTU. Finally, a CTU-level QP adjustment scheme based on both JND levels and visual importance is proposed for geometry and attribute video. The experimental results show that, compared with the latest V-PCC (TMC2-18.0) anchors, the BD-rate is reduced by -2.8% and -3.2% for D1 and D2 metrics, respectively, and the subjective quality is improved significantly.

Mutually unbiased bases (MUBs) are widely used in quantum information processing and play an important role in quantum cryptography, quantum state tomography and communications. It’s difficult to construct MUBs and remains unknown whether complete MUBs exist for any non prime power. Therefore, researchers have proposed the solution to construct approximately mutually unbiased bases (AMUBs) by weakening the inner product conditions. This paper constructs q AMUBs of ℂq, (q + 1) AMUBs of ℂq-1 and q AMUBs of ℂq-1 by using character sums over Galois rings and finite fields, where q is a power of a prime. The first construction of q AMUBs of ℂq is new which illustrates K AMUBs of ℂK can be achieved. The second and third constructions in this paper include the partial results about AMUBs constructed by W. Wang et al. in [9].

High Frequency Surface Wave Radar holds significant potential in sea detection. However, the target signals are often surpassed by substantial sea clutter and ionospheric clutter, making it crucial to address clutter suppression and extract weak target signals amidst the strong noise background.This study proposes a novel method for separating weak harmonic target signals based on local tangent space, leveraging the chaotic feature of ionospheric clutter.The effectiveness of this approach is demonstrated through the analysis of measured data, thereby validating its practicality and potential for real-world applications.