High data rate at high mobile speed will still be an essential requirement for the future 5G cellular system. frequency bands above 6 GHz are particularly promising system because of large signal bandwidths such frequencies can offer. By using gain beamforming antennas, problem propagation loss overcome. However, use antennas requires a significant change in design In particular, it key functions as cell search, random access, measurement beams fast beam adaptation, and various physical...

With the growing penetration of renewable energy sources, ensuring stability and reliability Medium-Voltage Direct Current (MVDC) systems has become more critical than ever. A single fault in MVDC can cause significant disturbances, necessitating rapid precise diagnostics to prevent equipment damage maintain continuous power supply. In this work, we present a Bidirectional Gated Recurrent Unit (Bi-GRU) model that both classifies locates faults. By capturing temporal behavior voltage signals,...

This paper presents an area-efficient algorithm for the pipelined processing of fast Fourier transform (FFT). The proposed is to decompose a discrete (DFT) into two balanced sub-DFTs in order minimize total number twiddle factors be stored tables. radix decomposition adaptively changed according remaining length make lengths resulting from as close possible. An 8192-point FFT processor designed digital video broadcasting-terrestrial (DVB-T) systems saves 33% general multipliers and 23% size...

In this paper, we propose methods for the diagnosis of down conductor cables installed inside blades reliable operation wind turbines. Utilizing two synchronized drones equipped with X-ray devices to take images blades, deep learning based on images. The first method is unsupervised deblurring blurry that are generated by drones. key idea proposed apply an image sharpening process latent space trained model using only Through experiments show makes outline cable clearer. As second method,...

For better deep learning forecasting systems for photovoltaic systems, confidence information about a point forecast is necessary in practical cases where uncertainties are unavoidable. In this study, using Bayesian learning, the authors introduce confidence‐aware system that provides as well forecast. Through experiments real‐world data, they first solve three main issues caused by when applied to of daily solar irradiance weather forecast: selection neural network model, validation data be...

In this paper, we propose a technique to increase the precision of solar power generation data prediction by using time-series-based transformer deep learning model. By partially modifying model, which is widely used for language translation, use it changing input and output model in form predicting future data. Finally, through comparison with other models, was confirmed that proposed showed very good performance.

This paper proposes an efficient method to deliver multi-view 3D video in a synchronous manner for nodes that frequently switch views by employing application layer multicast (ALM) trees. The proposed attempts bound inter-view delay variation managing ALM trees with and constraints. resulting view-switching between selected of different can thus provide synchronized view videos improve the immersive experience end users.

A multimode RF amplitude modulator and a digitally controlled variable attenuator (VATT) are presented. comprehensive analysis of nonlinear distortion in current source modulated is studied this paper. To improve the dynamic range reduce local oscillator leakage, dual power modes cascode transistor for modulation employed modulator. The consists switching with modulating source, which allows low consumption linear modulation. VATT designed level control. Five II stages cascaded to attain...

High data rate at high mobile speed will still be an essential requirement for the future 5G cellular system. frequency bands above 6 GHz are particularly promising system because of large signal bandwidths such frequencies can offer. And it was shown that by using gain beamforming antennas, problem propagation loss could compensated almost completely. But, achieving communications with antennas a is daunting task and has not been demonstrated until now. In this paper, we describe testbed...

Intrinsic problems for legged robots are `low energy efficiency' and `slow speed'. In this paper, we introduce a possible solution achieved through biological observations developed robotic leg applying the proposed method. The leg, AiDIN-IV Leg (Artificial DIgitigrade Natural environment version IV) has high torque density actuators(τ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">peak</sub> = 152Nm, 127rpm), fidelity force/torque...

A CMOS power amplifier for Multi-mode LINC operation is implemented in 0.18-¿m process. The architecture except signal separator was integrated and with two-chip solution. used to increase the maximum linear output saturation range of PAs. designed PA operates at 1950 MHz 26 dBm 20% PAE WCDMA signal. improvement 2 dB 8% efficiency can be obtained by using multi-mode operation.

For the speed-up in routing table lookup software routers, we introduce a new data structure called, sTable that achieves space efficiency while causing low processing overhead without hardware parallelism. Using hash table-like approach, stores only next hop information to handle most packets within on-chip fast memory some accesses off-chip slow errors. Routing experiments using Click show that, less and smaller number of errors than Bloom filter, reduces average time by 44% (i.e., from...

For stable and successful use of grid-connected PV (photovoltaic) plants, it is quite necessary to know the expected power from plants in advance. However, forecasting output accurately difficult practical cases where uncertainties are unavoidable. In this paper, we propose a confidence-aware system that produces point forecast together with its confidence information. Our classifies outputs into confident forecasts non-confident using Then, used directly replaced by lower bound, which...

A forecast interval is effective for handling the uncertainty in solar photovoltaic systems. In estimating interval, most available approaches apply an identical policy to all point forecasts. This results inefficient (e.g. unnecessarily wide accurate forecast). They also adopt a complex model and even require modification of deterministic forecasting model, which may adversely affect their application. To overcome these limitations, authors introduce uncertainty‐aware interval. calculate...

Abstract A reliable forecasting model is required for photovoltaic (PV) power output because solar energy highly volatile. Another driver the need of a concept drift, which means that statistical properties data change over time. In this paper, an online method to handle drift proposed. First, problem in batch learning transformed into setting. Then, algorithm applied, good handling drift. Through experiments using real‐world data, it shown noticeably improves performance compared case where...

Demand response (DR) is a voluntary program that encourages related stakeholders, in this case electricity consumers, to cut down on usage during periods of high load. One key fully exploiting DR encourage residential customers join the program. Unlike programs for commercial and industrial customers, successful operation program, several issues have be addressed, one which provide group-level incentive participating customers. In particular, issue comes up when calculated group not equal...

One way for improving the tuple space search-based table lookup in software system (e.g., flow matching process of Open vSwitch) is to reduce number spaces be examined. For this purpose, we discuss two approaches based on space-efficient data structures, Bloom filter and simTable proposed paper. Click-based experiments show that noticeably examined (i.e., 1 most cases even with 121 spaces). However, different results terms time. without hardware parallelism causes noticeable processing...

Reducing the computational budget of inference in deep neural network while achieving high accuracy is important for time-sensitive applications. In this paper, unlike other approaches that try to compress a large with smaller number parameters, we complete image classification as early possible. Adding middle output layer, at layer when Top1 confidence exceeds predefined threshold. We prove feasibility proposed approach based on experiment using Inception-v3 TensorFlow.

The electron density profile was measured using a microwave amplitude modulation (AM) reflectometer in Heliotron J plasmas, where plasma performance improved supersonic molecular beam injection (SMBI) as fueling method. Immediately after the SMBI pulse, for case which penetrates deeply, rapidly peaks, and increases both core edge regions. Afterward, while line-averaged is monotonically increasing, becomes more peaked. In this phase, by Langmuir probe decreases peaking factor of SX profiles...

High data rate at high mobile speed will still be an essential requirement for the future 5G cellular system. frequency bands above 6 GHz are particularly promising system because of large signal bandwidths such frequencies can offer. And it was shown that by using gain beamforming antennas, problem propagation loss could compensated almost completely. But, achieving communications with antennas a is daunting task and has not been demonstrated until now. In this paper, we describe testbed...

This paper presents a fast and low-power decoding scheme for Reed-Solomon Product-Code (RS-PC). To increase error correction capability of RS-PC, we need to repeat (RS) several times rows columns. As the number RS decodings increases, execution time energy consumption also as well. In order reduce unnecessary operations memory accesses, added two small memories store data on whether row or column is updated not. next iteration, only columns are recalculated instead whole Based proposed...

In realizing unsupervised pixel-precise anomaly localization by utilizing a generative model, reference image must be generated (for comparison with an input image) transforming abnormal patterns of image, if any, into normal patterns. this study, patch-level operation adaptive patch control is proposed to improve generating better image. As way exploit we divide non-overlapped patches the same size, generate images, and stitch images single We then conduct comparing stitched, reconstructed...