With the development of network technology, next-generation networks must satisfy many new requirements for network functions and performance. The processing of overlong packet fields is one of the requirements and is also the basis for ID-based routing and content lookup, and packet field addition/deletion mechanisms. The current SDN switches do not provide good support for the processing of overlong fields. In this paper, we propose a series of optimization mechanisms for protocol-oblivious instructions, in which we address the problem of insufficient support for overlong data in existing SDN switches by extending the bit width of instructions and accelerating them using SIMD instruction sets. We also provide an intermediate representation of the protocol-oblivious instruction set to improve the efficiency of storing and reading instruction blocks, and further reduce the execution time of instruction blocks by preprocessing them. The experiments show that our approach improves the performance of overlong data processing by 56%. For instructions involving packet field addition and deletion, the improvement in performance reaches 455%. In normal forwarding scenarios, our solution reduces the packet forwarding latency by around 30%.

Reducing the number of link crossings in a network drawn on the plane such as a wiring board is a well-known problem, and especially the calculation of the minimum number of such crossings: this is the crossing number problem. It has been shown that finding a general solution to the crossing number problem is NP-hard. So, this problem is addressed for particular classes of graphs and this is also our approach in this paper. More precisely, we focus hereinafter on the torus topology. First, we discuss an upper bound on cr(T(2, k)) the number of crossings in a 2-dimensional k-ary torus T(2, k) where k ≥ 2: the result cr(T(2, k)) ≤ k(k - 2) and the given constructive proof lay foundations for the rest of the paper. Second, we extend this discussion to derive an upper bound on the crossing number of a 3-dimensional k-ary torus: cr(T(3, k)) ≤ 2k4 - k3 - 4k2 - 2⌈k/2⌉⌊k/2⌋(k - (k mod 2)) is obtained. Third, an upper bound on the crossing number of an n-dimensional k-ary torus is derived from the previously established results, with the order of this upper bound additionally established for more clarity: cr(T(n, k)) is O(n2k2n-2) when n ≥ k and O(nk2n-1) otherwise.

Network Function Virtualization (NFV) enables the embedding of Virtualized Network Function (VNF) into commodity servers. A sequence of VNFs can be chained in a particular order to form a service chain (SC). This paper considers placing multiple SCs in a geo-distributed edge system owned by multiple service providers (SPs). For a pair of SC and SP, minimizing the placement cost while meeting a latency constraint is formulated as an integer programming problem. As SC clients and SPs are self-interested, we study the matching between SCs and SPs that respects individual's interests yet maximizes social welfare. The proposed matching approach excludes any blocking individual and block pair which may jeopardize the stability of the result. Simulation results show that the proposed approach performs well in terms of social welfare but is suboptimal concerning the number of placed SCs.

In this study, a computational method is proposed for acoustic field analysis tasks that require lengthy observation times. The acoustic fields at a given observation time are obtained using a fast inverse Laplace transform with a finite-difference complex-frequency-domain. The transient acoustic field can be evaluated at arbitrary sampling intervals by obtaining the instantaneous acoustic field at the desired observation time using the proposed method.

The phenomenon known as social polarization, in which a social group splits into two or more groups, can cause division of the society by causing the radicalization of opinions and the spread of misinformation, is particularly significant in online communities. To develop technologies to mitigate the effects of polarization in online social networks, it is necessary to understand the mechanism driving its occurrence. There are some models of social polarization in which network structure and users' opinions change, based on the quantified opinions held by the users of online social networks. However, they are based on the interaction between users connected by online social networks. Current recommendation systems offer information from unknown users who are deemed to have similar interests. We can interpret this situation as being yielded non-local effects brought on by the network system, it is not based on local interactions between users. In this paper, based on the spectral graph theory, which can describe non-local effects in online social networks mathematically, we propose a model of polarization that user behavior and network structure change while influencing each other including non-local effects. We investigate the characteristics of the proposed model. Simultaneously, we propose an index to evaluate the degree of network polarization quantitatively, which is needed for our investigations.

Inspired by the framework of algorithm unrolling, we propose a scalable network architecture that computes layer patterns for light field displays, enabling control of the trade-off between the display quality and the computational cost on a single pre-trained network.

Low-temperature deposition of Y2O3 at 80°C is studied using an yttrium precursor of tris(butylcyclopentadienyl)yttrium (Y(BuCp)3) and plasma exited humidified argon oxidizer. The deposition is demonstrated using an atomic-layer-deposition sequence; the Y(BuCp)3 and the oxidizing gases are time separately introduced to the reaction chamber and these injections are repeated. To determine the gas introduction conditions, surface reactions of Y(BuCp)3 adsorption and its oxidization are observed by an in-situ IR absorption spectroscopy. The deposited film is confirmed as fully oxidized Y2O3 by X-ray photoelectron spectroscopy. The present deposition is applicable for the deposition of Y2O3 film on flexible polyethylene terephthalate films.

The low temperature deposition of AlN at 160 °C is examined by using trimethyl aluminum (TMA) and NH radicals from plasma excited Ar diluted ammonia. For the deposition, a plasma tube separated from the reaction chamber is used to introduce the neutral NH radicals on the growing surface without the direct impacts of high-speed species and UV photons, which might be effective in suppressing the plasma damage to the sample surfaces. To maximize the NH radical generation, the NH3 and Ar mixing ratio is optimized by plasma optical emission spectroscopy. To determine the saturated condition of TMA and NH radical irradiations, an in-situ surface observation of IR absorption spectroscopy (IRAS) with a multiple internal reflection geometry is utilized. The low temperature AlN deposition is performed with the TMA and NH radical exposures whose conditions are determined by the IRAS experiment. The spectroscopic ellipsometry indicates the all-round surface deposition in which the growth per cycles measured from front and backside surfaces of the Si sample are of the same range from 0.39∼0.41nm/cycle. It is confirmed that the deposited film contains impurities of C, O, N although we discuss the method to decrease them. X-ray diffraction suggests the AlN polycrystal deposition with crystal phases of AlN (100), (002) and (101). From the saturation curves of TMA adsorption and its nitridation, their chemical reactions are discussed in this paper. In the present paper, we discuss the possibility of the low temperature AlN deposition.

We fabricated Fe-silicide nanodots (NDs) on an ultrathin SiO2 layer and evaluated changes in electron transport properties with and without magnetic field application. High-density NDs with an areal density as high as ∼1011cm-2 were formed on thermally grown SiO2 by exposing ultrathin Fe/Si-NDs structures to a remote H2 plasma without external heating. In electron transport properties related to current-time characteristics for a diode with Fe electrode and charging energy to NDs, clear changes in current levels through NDs and electron injection modulation of NDs depending on intensity of magnetic fields were observed.

When BJTs are irradiated by gamma rays, interface trapped charges and positive oxide trapped charges are formed by ionization at the Si-SiO2 interface and SiO2 regions, respectively. These trapped charges affect the movement of carriers depending on the type of BJT. This paper presents experimental results regarding operating characteristics of gamma irradiated pnp Si BJTs.

Couplers in a film-type capacitive wireless power charging (CWC) system for an implantable medical device were designed and analyzed in this work. Due to the high conductivity of the human body, two paths contribute to the power transmission, namely a high-frequency current and an electric field. This was confirmed by an equivalent circuit of the system. During analysis of the system, we used pig skin with subcutaneous fat, which has a high affinity with the human body, to search for a highly efficient electrode shape. Subsequently, we fabricated the designed coupler and measured ηmax. An ηmax of 56.6% was obtained for a half-circular coupler with a radius of 20 mm and a distance of 10 mm between adjacent couplers. This study will contribute to the realization of implantable devices that can be recharged during breaks or while sleeping at home and is expected to significantly reduce the burden on patients.

This paper studies generalized variants of the MAXIMUM INDEPENDENT SET problem, called the MAXIMUM DISTANCE-d INDEPENDENT SET problem (MaxDdIS for short). For an integer d≥2, a distance-d independent set of an unweighted graph G=(V, E) is a subset S⊆V of vertices such that for any pair of vertices u, v∈S, the number of edges in any path between u and v is at least d in G. Given an unweighted graph G, the goal of MaxDdIS is to find a maximum-cardinality distance-d independent set of G. In this paper, we analyze the (in)approximability of the problem on r-regular graphs (r≥3) and planar graphs, as follows: (1) For every fixed integers d≥3 and r≥3, MaxDdIS on r-regular graphs is APX-hard. (2) We design polynomial-time O(rd-1)-approximation and O(rd-2/d)-approximation algorithms for MaxDdIS on r-regular graphs. (3) We sharpen the above O(rd-2/d)-approximation algorithms when restricted to d=r=3, and give a polynomial-time 2-approximation algorithm for MaxD3IS on cubic graphs. (4) Finally, we show that MaxDdIS admits a polynomial-time approximation scheme (PTAS) for planar graphs.

A grid drawing of a plane graph G is a drawing of G on the plane so that all vertices of G are put on plane grid points and all edges are drawn as straight line segments between their endpoints without any edge-intersection. In this paper we give a linear-time algorithm to find a grid drawing of any given 5-connected plane graph G with five or more vertices on the outer face. The size of the drawing satisfies W + H≤n - 2, where n is the number of vertices in G, W is the width and H is the height of the grid drawing.

Noninvasive recognition is an important trend in diabetes recognition. Unfortunately, the accuracy obtained from the conventional noninvasive recognition methods is low. This paper proposes a novel Diabetes Noninvasive Recognition method via the plantar pressure image and improved Capsule Network (DNR-CapsNet). The input of the proposed method is a plantar pressure image, and the output is the recognition result: healthy or possibly diabetes. The ResNet18 is used as the backbone of the convolutional layers to convert pixel intensities to local features in the proposed DNR-CapsNet. Then, the PrimaryCaps layer, SecondaryCaps layer, and DiabetesCaps layer are developed to achieve the diabetes recognition. The semantic fusion and locality-constrained dynamic routing are also developed to further improve the recognition accuracy in our method. The experimental results indicate that the proposed method has a better performance on diabetes noninvasive recognition than the state-of-the-art methods.

This paper details the design of a plate that controls the beam direction in an aperture array excited by a waveguide 2-plane hybrid coupler. The beam direction can be controlled in the range of ±15-32deg. in the quasi H-plane, and ±26-54deg. in the quasi E-plane at the design frequency of 66.425GHz. Inductive irises are introduced into tapered waveguides in the plate and the reflection is suppressed by narrow apertures. A plate that has a larger tilt angle in the quasi E-plane and another plate with conventional rectangular waveguide ports as a reference are fabricated and measured. The measured values agree well with the simulation results.

In recent years, there has been an increasing trend of applying artificial intelligence in many different fields, which has a profound and direct impact on human life. Consequently, this raises the need to understand the principles of model making predictions. Since most current high-precision models are black boxes, neither the AI scientist nor the end-user profoundly understands what is happening inside these models. Therefore, many algorithms are studied to explain AI models, especially those in the image classification problem in computer vision such as LIME, CAM, GradCAM. However, these algorithms still have limitations, such as LIME's long execution time and CAM's confusing interpretation of concreteness and clarity. Therefore, in this paper, we will propose a new method called Segmentation - Class Activation Mapping (SeCAM)/ This method combines the advantages of these algorithms above while at simultaneously overcoming their disadvantages. We tested this algorithm with various models, including ResNet50, InceptionV3, and VGG16 from ImageNet Large Scale Visual Recognition Challenge (ILSVRC) data set. Outstanding results were achieved when the algorithm has met all the requirements for a specific explanation in a remarkably short space of time.

The increasing amount of fake news is a growing problem that will progressively worsen in our interconnected world. Machine learning, particularly deep learning, is being used to detect misinformation; however, the models employed are essentially black boxes, and thus are uninterpretable. This paper presents an overview of explainable fake news detection models. Specifically, we first review the existing models, datasets, evaluation techniques, and visualization processes. Subsequently, possible improvements in this field are identified and discussed.

At present, the application of different types of memristors in electronics is being deeply studied. Given the nonlinearity characterizing memristors, a circuit with memristors cannot be treated by classical circuit analysis. In this paper, memristor is equivalent to a nonlinear dynamic system composed of linear dynamic system and nonlinear static system by Volterra series. The nonlinear transfer function of memristor is derived. In the complex frequency domain, the n-order complex frequency response of memristor is established by multiple Laplace transform, and the response of MLC parallel circuit is taken as an example to verify. Theoretical analysis shows that the complex frequency domain analysis method of memristor transforms the problem of solving nonlinear circuit in time domain into n times complex frequency domain analysis of linear circuit, which provides an idea for nonlinear dynamic system analysis.

This paper presents improvement of port-to-port isolation characteristics of a linearly dual-polarized dual-band and wideband multi-ring microstrip antenna (MR-MSA) fed by two L-probes. The linearly dual-polarized dual-band and wideband MR-MSA consists of two circular ring patches and two L-probes arranged in a multi-layered dielectric substrate. By using a thick substrate for the L-probe and arranging two ring patches as radiation elements, the proposed antenna operates wideband and dual-band characteristics. Furthermore, by arranging two L-probes at the orthogonal positions, the proposed antenna can radiate dual linear polarizations. In this paper, for improving port-to-port isolation characteristics of the linearly dual-polarized dual-band and wideband MR-MSA fed by two L-probes, a via connected to the ground plane at the center of the radiation elements is arranged. The fractional bandwidths below -10dB reflection obtained by the simulation of the MR-MSA with the via were 17.0% and 14.4%. Furthermore, the simulated isolation characteristics were more than 21.0dB and 17.0dB in the two bands. Improvement of the isolation characteristics between two ports as well as the dual-band and wideband performance of the proposed MR-MSA with the via were confirmed by the simulation and the measurement.

In this paper, we propose a new training framework named the INmfCA algorithm for nonparallel voice conversion (VC) systems. To train conversion models, traditional VC frameworks require parallel corpora, in which source and target speakers utter the same linguistic contents. Although the frameworks have achieved high-quality VC, they are not applicable in situations where parallel corpora are unavailable. To acquire conversion models without parallel corpora, nonparallel methods are widely studied. Although the frameworks achieve VC under nonparallel conditions, they tend to require huge background knowledge or many training utterances. This is because of difficulty in disentangling linguistic and speaker information without a large amount of data. In this work, we tackle this problem by exploiting NMF, which can factorize acoustic features into time-variant and time-invariant components in an unsupervised manner. The method acquires alignment between the acoustic features of a source speaker's utterances and a target dictionary and uses the obtained alignment as activation of NMF to train the source speaker's dictionary without parallel corpora. The acquisition method is based on the INCA algorithm, which obtains the alignment of nonparallel corpora. In contrast to the INCA algorithm, the alignment is not restricted to observed samples, and thus the proposed method can efficiently utilize small nonparallel corpora. The results of subjective experiments show that the combination of the proposed algorithm and the INCA algorithm outperformed not only an INCA-based nonparallel framework but also CycleGAN-VC, which performs nonparallel VC without any additional training data. The results also indicate that a one-shot VC framework, which does not need to train source speakers, can be constructed on the basis of the proposed method.