Miracle-dz/UniFAR-FTUs huggingface dataset:
Visually Equivalent Light Field 3-D for Portable Displays

Highly realistic 3-D displays that can reproduce object images to look like physical objects are utilized for natural and correct remote operation in industrial scenes. Therefore, we developed a visually equivalent light field 3-D (VELF3D) display that can produce highly realistic, accurate images with a high resolution and a smooth, accurate motion parallax. However, the observation distance is slightly long, and users cannot reach the displayed images. Therefore, we aim to develop a tablet-computer-type VELF3D display that enables users to touch the displayed objects. The display viewpoint density has been increased to achieve a shorter observation distance, while maintaining the display depth range. Because higher resolutions are required for a close observation distance and increased display viewpoints, we aimed to improve the effective resolution using almost the same pixel pitch display panel. Therefore, we built a prototype that combines a vertical red, green, blue stripe display panel and a parallax barrier with subpixel width slits. We confirmed effective resolution improvement by tiny subjective tests. This method also helps increase the depth range of the display when it is observed from a normal distance.
Investigation of inoculation effect on cream cheese fermentation through models

Cream cheese, a popular condiment, is widely used in people’s daily diet and dessert making. The cream cheese fermentation starts from inoculation. Understanding the relationship between inoculation time and subsequent fermentation will help plant engineers optimise the batch scheduling of multiple fermenters. In this paper, the inoculation time effect on cream cheese fermentation will be investigated through models which comprise a kinetic model followed by an Artificial Neural Network type model for pH predictions.
Optimal control for An Active Phase Change Material System Using Reinforcement Learning

Optimal control of buildings equipped with active phase change material (PCM) systems is challenging due to the rigorous models involved. Besides the nonlinear models, binary variables appear in the optimal control formulation in this work. Deep Q-learning network (DQN) reinforcement learning was adopted to address the complexity of the optimal control formulation. DQN includes deep neural networks which can map binary actions to continuous states. The DQN was trained and tested through simulation using a validated model of the whole system. Using the electricity price, hut dynamics and ambient conditions information as states, the proposed new control strategy can achieve an optimal balance between thermal comfort and energy cost saving.
PIFE: Permutation Invariant Feature Extractor for Danmaku Games

Dealing with unstructured complex patterns provides a challenge to existing reinforcement patterns. In this research, we propose a new model to overcome the difficulty in challenging danmaku games. Touhou Project is one of the bestknown games in the bullet hell genre also known as danmaku, where a player has to dodge complex patterns of bullets on the screen. Furthermore, the agent needs to react to the environment in real-time, which made existing methods having difficulties processing the high-volume data of objects; bullets, enemies, etc. We introduce an environment for the Touhou Project game‘東方花映塚~Phantasmagoria of Flower View. ’ which manipulates the memory of the running game and enables to control the character. However, the game state information consists of unstructured and unordered data not amenable for training existing reinforcement learning models, as they are not invariant to order changes in the input. To overcome this issue, we propose a new pooling-based reinforcement learning approach that is able to handle permutation invariant inputs by extracting abstract values and merging them in an order-independent way. Experimental results corroborate the effectiveness of our approach which shows significantly increased scores compared to existing baseline approaches.
Planar and Compact Ferrite Isolator in Ku- band

This paper presents the design and fabrication of a compact, planar ferrite isolator in Ku-band. A completely filled Rectangular Wave Guide (RWG) isolator using an inset-fed micro strip transmission line is demonstrated. Size of the isolator is ~ 9mm x 9mm x 0.5mm (length x width x thickness). Method of feeding has considerably reduced the size of the isolator. The bias is applied transverse to the ferrite substrate. Isolation band from 16 GHz to 18.8 GHz is obtained. A maximum peak Isolation of around 40 dB is measured at 18.6 GHz. The device along with bias mechanism weights less than 20 gms. All the measurements are verified by simulations using a full wave 3D-electromagnetic solver. (CST MicroWave Studio(CST MWS)).
Efficient Uncertainty Quantification of Stripline Pulse Response using Singular Value Decomposition and Delay Extraction

This paper demonstrates the use of data post-processing methods with stochastic collocation, an efficient alternative to Monte Carlo sampling, for transient response parametrization in electronic design. This method is applied to find the statistics of the broadband voltage response of a 50Ω terminated stripline with uncertain width, length, and per-mittivity. Collocation results with post-processing are compared against that of Monte Carlo showing greater accuracy for a low computational budget.
Planar Ultra-Wideband Modular Transmitarray

A planar ultra-wideband transmitarray of tightly-coupled dipoles based on a novel modular unit-cell is proposed. Specifically, modularity is achieved by using capacitive coupling to connect the dipoles with the true-time-delay lines. Therefore, this modular design does not require physical connection between the receive/transmit dipole-layers and the true-time-delay lines, thereby enabling the realization of the first (to our knowledge) planar ultra-wideband transmitarray. Also, our design reduces significantly the fabrication cost of ultra-wideband transmitar-rays. As a proof-of-concept, a 12×12 element transmitarray is designed for broadside operation, and provides a 5:1 frequency bandwidth with an active VSWR < 3 from 3 to 15 GHz.
Performance Evaluation of Lead-Free Cs2CuSbCl6 Perovskite Solar Cells for > 21.67% Efficiency

This work investigates the performance of Cs<inf>2</inf>CuSbCl<inf>6</inf>-based lead-free perovskite solar cells for photovoltaic applications. Cs<inf>2</inf>CuSbCl<inf>6</inf> has a bandgap of 1.7eV and it is a durable and non-toxic material. Cs<inf>2</inf>CuSbCl<inf>6</inf> can absorb more photons and thus obtain high efficiency. This work has been performed using SCAPS-1D software with the focus on optimizing the absorber layer thickness in terms of solar cell performance metrics such as efficiency (η), fill-factor (FF), open-circuit voltage (V<inf>oc</inf>), and short-circuit current density (J<inf>sc</inf>). The highest efficiency of 21.67% has been obtained for the optimized value of the absorber layer thickness of 900 nm, with values of 1.22 V, 21.19 mA/cm<sup>2</sup>, and 83.19% for V<inf>oc</inf>, J<inf>sc</inf>, and FF respectively. Thus, Cs<inf>2</inf>CuSbCl<inf>6</inf> -based solar cell paves as the safe alternative to lead-based solar cells for photovoltaic applications.
Reinforcement Learning and Optimal Setpoint Tracking Control of Linear Systems With External Disturbances

In order to deal with optimal setpoint tracking (OST) problems, a discounted cost function has been introduced in the existing work. However, the optimal tracking controllers developed according to the discounted cost function may not ensure asymptotic tracking and the stability of the closed-loop systems. To overcome these limitations, in this article, we propose a novel adaptive optimal control method to minimize a cost function without a discount factor. The proposed method starts from a reformulation of the infinite-horizon OST problem for linear discrete-time systems with external disturbances. We derive an algebraic Riccati equation for solving the OST problem, whose solution is uniquely determined under mild conditions. It is proved that the obtained controller accommodates the disturbance and realizes the output tracking with zero steady-state error. In the framework of reinforcement learning, a $Q$-learning algorithm is devised to learn the suboptimal control policy by using measured data. The present learning algorithm does not require that the disturbance is measurable and can be implemented completely model-free. Finally, two examples on dc motor system and F-16 aircraft plant are provided to corroborate our design methodology.
Multiphysics Joint Inversion Using Successive Deep Perceptual Constraints

Using joint inversion to reveal subsurface structures has drawn considerable research attention to reduce inversion uncertainties and improve resolution. In this abstract, a novel joint inversion workflow is proposed by using the deep neural network (DNN) combined with the traditional separated inversion process to improve the result for multi-physics data. Deep perceptual constraints are added when training the networks to enforce the structural similarity. The whole workflow is executed in an iterative way to guarantee the reliability of inversion results. Numerical examples demonstrate our method can achieve more accurate inverted property values and better structural features compared to traditional separate inversions and cross gradient-based joint inversion.
Limiting Co-location Effects of Antennas using Engineered Electromagnetic Structures

An application of engineered materials to control electromagnetic waves and shield devices to maintain antenna parameters in a highly scattering multiple-antenna environment is shown. In a multiple-antenna environment, where each antenna operates at different frequencies, the scattering effects can be significantly reduced by enclosing an individual antenna with an engineered electromagnetic structure operating at a wavelength higher than the source. Numerical simulations are performed in COMSOL Multiphysics to demonstrate the success of the proposed shielding technique involving two 2D line-dipole antennas and a cylindrical enclosure of engineered EM materials at microwave frequencies.
2.4/5 GHz Dual-Band Multilayer Slot Array Antenna

This paper presents a novel antenna design to realize high antenna gain in dual bands (2.4/5 GHz) by arraying slot antenna elements and a multilayer structure. A 5 GHz slot array antenna is placed on the top metal, and the floating metal is attached on the backside to realize the one-sided directional radiation. A 2.4 GHz slot array antenna is placed on the upper side of the 5 GHz antenna. The RF signal is fed into each antenna element with the same power and phase branched coplanar waveguides (CPW). The antenna was fabricated on FR-4 substrate with top and bottom metals. The final dual-band antenna size was 161 mm x 116 mm x 28.2 mm. The measured +z-axis directional gain was 11.1 dBi at 2.50 GHz and 12.8 dBi at 5.57 GHz.
A Dual-Polarized Traveling-Wave Slot Array for X-Band Applications

In this paper, based on a single-ridged waveguide (SRWG) and a rectangular waveguide (RWG), a 16 ×56 slotted waveguide antenna array with dual-polarization, high gain and low side-lobe level is designed and simulated at X-band to validate the slot antenna design for the traveling wave. In this array, the longitudinal slot etched on the broad sidewall of the SRWG is employed for vertical polarization (VP) radiation, while the inclined slot cut in the narrow wall of the RWG is employed for horizontal polarization (HP) radiation. From the simulated results, the bandwidth of the designed antenna for voltage standing wave ratio (VSWR) < 1.5 is 0.8GHz at the center frequency of 9.4 GHz. The realized gain at 9.4 GHz is 31dBi with antenna efficiencies better than 83%. The side-lobe level is controlled lower than -31dB over the entire bandwidth. The beam width is 1.6 degrees and the beam direction is 4.5 degrees at 9.4 GHz. The realized gain, beam width, beam pointing and side-lobe of the two polarization modes are almost the same at 9.0GHz, 9.4 GHz and 9.8 GHz. Due to its high gain, compact size, low side-lobe level and easy manufacturing, this array can be combined with the edge-slotted waveguide array to build a two-dimensional dual-polarization antenna array for the applications of sea based X-band radar, satellite communication station, etc.
On the Design of PDMS Based Miniaturized Ultra-Wideband Antenna for Compact Flexible Electronics

A miniaturized UWB antenna for compact size devices is presented in this article. The antenna is designed using on PDMS substrate, well known for flexible nature. The antenna offers a wide impedance bandwidth covering UWB spectrum along with small overall size of 10 × 15 × 1.524 mm3. CPW fed antenna was modified using slots and stubs to achieve a compact size flexible antenna having simple geometrical configuration. Presented studies are carried out using Electromagnetic Solver, High Frequency Structure Simulator (HFSS).
Silicon-Based Plasmonic Nanoantennas at mid-infrared for Gas Sensing Applications

Advanced nanotechnology especially CMOS technology-enables us to re-design the classic antenna in the nanoscale, which can convert propagating optical wavelengths instead of radio and microwave wavelengths into localized energy and vice versa. As a result, sensors may be designed to make sensing molecules with their characteristic vibrational transitions easier. Bowtie silicon nanoantennas are investigated in this work. When silicon with high excess carrier concentrations is used as the material of choice, the enhancement occurs in the mid-IR (MIR) spectral range, which is red-shifted when compared to the enhancement produced when gold or silver is used. Varying the substrate material and associated resonance wavelength influences the localized electric field.
Multi-Objective Control Strategy for Power Quality Improvement in Wind-Solar Distributed Generation System Under Harmonically Distorted Grid

Grid-interactive wind-solar distributed generation system (DGS) experiences substantial power quality (PQ) challenges pertaining to incessant voltage distortions in the utility grid and nonlinear loads at the point of common intersection. Such system non-idealities cause distortions in grid currents and infuse ripples in grid active and reactive powers. The effect of harmonically distorted voltages on DGS is further intensified in case of wind generation by means of a doubly-fed induction generator (DFIG), as its stator is directly coupled to the grid. Significant performance degradation with regard to distortions in DFIG currents, and ripples in stator power as well as DFIG torque, are observed. In this context, a control strategy, based on multiresonant higher order generalized integrator for harmonic estimation (MRHGI-HE) and a ϵ-normalized sign regressor least mean fourth (ϵ-NSRLMF) algorithm, for DGS employing solar photovoltaic array and DFIG-based wind generator, is presented in this article. Based on selected objective, the control approach puts-forth a feasible solution for alleviating the aforementioned PQ challenges. The MRHGI-HE provides improved harmonics estimation and superior disturbance rejection, than its conventional counterpart. Besides, ϵ-NSRLMF algorithm exhibits enhanced system dynamics, as compared with least mean fourth algorithm. The multiobjective control strategy is corroborated through extensive simulation and experimental studies, and results demonstrate the PQ improvements in the DGS.
Influence of Terminal Dimensions on Bandwidth and Efficiency Bounds of Small Printed IFA Antennas

This paper presents a study of the influence of the terminal dimensions on the bandwidth and efficiency bounds of small antennas suitable for IoT or 5G applications. The antenna considered in this study is a printed Inverted-F Antenna (IFA). The obtained results clearly show that the dimensions of the terminal have a strong impact on the maximum total efficiency that can be achieved, whereas the bandwidth bound is less impacted.
Radiation of Female Phase Gradient Metasurface

The female phase gradient metasurface (FPGM) is proposed based on Babinet's principle. It is the complementary form of conventional PGM and has similar cross-polarization reflection characteristics taking account into the unit cells. And the property of pattern scan with frequency is also verified by one periodic structure consisted of three cells with 1200 phase difference.
Research on the Distributed Transaction of Weakly Centralized Massive Flexible Resources

With the integration of massive distributed resources into the grid, more and more traditional electricity consumers are becoming prosumers with dual identity of producer and consumer. It is of great significance to study the Peer to Peer (P2P) transaction between the prosumers. In this study, a weakly centralized prosumer P2P transaction model considering optimization of distribution network is established. Firstly, we constructed a prosumer P2P transaction model and used ADMM algorithm to solve it. The impact of optimization of distribution network on the model is then taken into consideration based on which we have the two-layer optimization model for prosumer P2P transaction considering the optimization of distribution network. Finally, the model is solved through iteration to minimize the transaction cost of prosumers and the operation cost of the distribution network, thus realizing the P2P transaction between multiple prosumers under the constraints of the distribution network.
Application of Isotonic Regression in Predicting Corrosion Depth of the Oil Refinery Pipelines

This paper presents a powerful machine learning (ML) model called isotonic regression to predict the corrosion growth process in the oil and gas pipelines. The paper mainly aims to show the powerfulness of this model in predicting corrosion depth in the pipeline. The isotonic regression model is selected in this study because it is a non-parametric model that can be freely shaped without assuming any shape oftarget function to overcome the highly stochastic nature of the corrosion growth mechanism. The other reason, the isotonic regression model is also designed to predict the monotonic increasing degradation mechanisms such as corrosion. The paper also evaluates three machine learning models used in regression analysis: linear regression, isotonic regression, and power regression based on the actual corrosion depth data collected from five sensors attached to the studied pipeline. Jupyter notebook is used in the evaluation process of each ML model performance. Four types of prediction accuracy metrics are used to calculate the prediction performance of each ML model, such as mean absolute error (MAE), mean squared error (MSE), root mean square error (RMSE), and R-squared (R2).
Efficient Implementation of Lossy Media using Improved 3-D HIE-FDTD Method

This paper presents an efficient lossy media implementation using the improved hybrid implicit–explicit finite-difference time-domain (HIE-FDTD) method. Various schemes, including a forward-backward scheme, are formulated for the proposed implementation. The efficiency of formulated schemes are validated through numerical results and compared to the efficient alternating-direction-implicit (ADI)-FDTD and the conventional FDTD methods.
Multi-Agent Reinforcement Learning System for Multiloop Control of Chemical Processes

Reinforcement Learning (RL) provide a model-free method of controlling processes. Recent advancements in Deep Reinforcement Learning have developed RL agents that can potentially control multivariate processes. Multi-Agent Reinforcement Learning (MARL) is a subfield of RL where multiple agents are trained in a shared environment. In this study, a MARL control system comprising multiple Twin-Delayed Deep Deterministic Policy Gradient (TD3) agents is trained to control a multiloop CSTR process. The MARL system achieves stable closed-loop response and good disturbance rejection.
Preparation of 3D interconnected porous carbon foam with rich electrochemical active site for improved electrochemical performance

In the manuscript, one highly controllable method for synthesis of porous carbon foam (PCF) through a hard-temple polymer coating approach is displayed, and the final product is directly used as the electrode material of micro-supercapacitor and secondary zinc battery. The PCF exhibits plentiful pore structure, easier ion-diffusion reactions, and richer electrochemical active sites. Due to the unique adjustable pore structure, the as-prepared PCF exhibits better cycle performance and higher specific capacity, which is concluded from serial electrochemical tests of as-assembled micro-supercapacitor and zinc-ion battery. When used as the electrode material of flexible quasi-solid-state symmetric micro-supercapacitor, the PCF exhibits a high capacity and could maintain the initial capacity after relatively long cycles. When working as the cathode of zinc-ion battery, the PCF displays an enhanced cycle stability compared to commercial active carbon.
A Reflectarray Element with Low Reflection Loss and Excellent Amplitude Stability

In this paper, a reflectarray element that is capable of continuously tuning the phase of reflected wave is proposed. It consists a single dielectric layer with metallic structures on both sides. The upper metallic layer includes one meandering-line ring and a square ring with open slots. The lower metallic layer acts as the ground plane. The varactor diodes are placed between the square ring and the meandering-line patches. The phase of reflected wave can be continuously tuned by varying the capacitance of the diodes while a low reflection loss and excellent amplitude stability are achieved during this process. Full-wave simulation results demonstrate an overall phase tuning range of 258 degrees and low reflection loss below -0.35 dB.
Excitation of Traveling Wave on Metal Casing Using Folded Dipole Antenna

Multiple antennas have been installed on mobile devices, and miniaturization of antennas is required. In addition, high-frequency bands are used with the development of communication technology, and the size of the platform becomes relatively larger than a wavelength. It becomes difficult in antenna design to approach from the standing wave on the platform which resonates such as a half-wavelength dipole. This paper proposes the traveling wave antenna with a platform on which the surface wave propagates and radiates. The proposed antenna is expected that the radiation can be changed by changing the characteristics of the platform surface where the surface waves propagate.