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This article investigated the impact of immersive virtual reality (VR) content, using 360-degree videos, in undergraduate education. To improve the delivery and reality of 360-degree VR content, we filmed the video in the third person so that the viewers could feel like they were in the environment where the lecture was conducted. To verify the educational effects, 33 university students participated in our experiment. We conducted pretest learning, using 360-degree videos, and posttest learning via conventional 2-D videos for statistical analysis. A paired t-test was used to compare the means of the pretest and the posttest. In addition, learning via 360-degree videos was assessed for its effectiveness through questionnaires consisting of five measurement elements--engagement, immersion, motivation, cognitive benefits, and perceived learning effectiveness--and comparing them to the existing 2-D video method, based on e-learning. From the results, we confirmed that the teaching material delivered through 360-degree VR content allows students to be more focused, immersed, and interested than 2-D learning modes. Furthermore, the high scores of cognitive and perceived learning elements imply that VR-based 360-degree educational content can encourage more active participation than traditional lectures and can improve the ability to analyze and organize study lessons.

This study implements a highly uniform 3D vertically stack resistive random‐access memory (VRRAM) with a four‐layer contact hole structure. The fabrication process of a four‐layer VRRAM is demonstrated, and its physical and electrical properties are thoroughly examined. X‐ray photoelectron spectroscopy and transmission electron microscopy are employed to analyze the chemical distribution and physical structure of the VRRAM device. Multilevel capability, reliable endurance (>104 cycles), and retention (104 s) are successfully obtained. Synaptic memory plasticity, such as spike time‐dependent plasticity, spike rate‐dependent plasticity, excitatory post‐synaptic current, paired‐pulse facilitation, and long‐term potentiation and depression is presented. Finally, the vector‐matrix multiplication (VMM) operation is conducted on a 4 × 12 VRRAM array, according to the low resistance state ratio. It is ascertained that the accuracy drop, which can occur due to VMM error, can be limited to a decrease of less than 0.44% point. Utilizing the high‐density, multilevel, and biological characteristics of VRRAM, it is possible to implement high‐performance neuromorphic systems that require densely integrated synaptic devices. [ABSTRACT FROM AUTHOR]

Low‐cost passive reconfigurable intelligent surfaces that provide coverage expansion in wireless communication networks are facing challenges in phase shift optimization due to limitations in acquiring channel information for sub‐channels. To overcome this, a new approach that improves both the convergence speed and overall performance relative to the existing state‐of‐the‐art scheme is proposed. Experimental results in an environment with a Rician factor of 20 showed a 9.3% increase in the average sum data rate, and the probability of the sum data rate exceeding the threshold of 10 increased by 30%. [ABSTRACT FROM AUTHOR]

The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model‐based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data‐driven methods perform slightly worse than model‐based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning‐based method by improving a state‐of‐the‐art data‐driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error‐propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model‐based methods in perfect CSI environments and the best performance in imperfect CSI environments. [ABSTRACT FROM AUTHOR]

This paper presents a physical space design method for mixed reality-based immersive environments by improving the color rendering of optically visible head-mounted displays. In OST-HMD, the phenomenon that the light of the external environment is combined with the enhanced image occurs, which reduces the visibility of the content. Moreover, previous studies to solve this problem required additional optical components or performed only simple verification. Proposed physical space was designed using black curtains, blinds, low-reflection structures, and adjustable lighting. The physical space can be adapted to the intended use of the physical space through physical transitions for multiple users without additional optics. To verify the usefulness of this environment, we measured the color gamut and intensity spectrum in three experimental environments. Also, we analyzed the factors that change the color gamut according to the components and the surrounding environment. As a result, the color gamut improved by up to 4.7 times from 19.92% to 93.53% based on the environment and improved by up to 4.1 times from 21% to 86.29% depending on the location. The experimental results revealed that the presented method could reduce the factors that degrade the color gamut within all measurement locations and significantly improve the color gamut. [ABSTRACT FROM AUTHOR]

In recent years, research on ferroelectric materials based on hafnium oxide has increased because of promising advantages such as fast operating speeds and CMOS process compatibility. In the case of Al-doped HfO2 (HAO), the remnant polarization (Pr), switching endurance, and high ON/OFF ratio can induce better ferroelectricity. In this work, three metal–ferroelectric–(insulator)–semiconductor MF(I)S devices with TiN/HAO/n+ Si and 1 nm and 2 nm thick SiO2 insulators inserted between the ferroelectric layer and the semiconductor have been studied. Doping Al2O3 results in enhanced ferroelectric properties such as switching voltage and higher polarization compared to that of undoped HfO2. It is because the stabilization of tetragonal phases results in a high dielectric constant. The MFIS (1 nm) device's high remnant polarization value of 37.8 μC cm−2 was measured using polarization-switching PUND (positive-up–negative-down). Additionally, with DC dual sweeping, I–V characteristics exhibited a wide memory window and a large tunneling electro-resistance (TER) ratio. Furthermore, it has shown improvement in current and energy performance because of the stronger bond between the ferroelectric layer and the bottom electrical material and high charge transfer efficiency. Finally, we have successfully demonstrated the properties of the interfacial SiO2 layer and found the thickness of the optimal interlayer for the MFIS structure. Various experiments were conducted to study the synaptic characteristics of FTJ devices, including the long-term potentiation and depression, paired-pulse facilitation (PPF), spike-timing-dependent plasticity (STDP), and the recognition and prediction ability of the device using reservoir computing (RC) technology. Through these experiments, the fabricated device is suitable as an ideal device for implementing energy-efficient and high-speed artificial neural network applications. [ABSTRACT FROM AUTHOR]

The beamforming technique has attracted considerable attention in wireless communication due to its various advantages such as interference reduction and improved wireless resource efficiency. However, the beam alignment between transmitting and receiving devices, which is fundamentally required for the beamforming, poses a significant challenge due to the continuous variability of the wireless channel. Recently, a deep learning-based technique has been proposed to predict narrow beam indices by measuring wide beams. However, there is room for improvement in the performance of the neural network architecture employed in this technique. Therefore, we suggest a novel deep learning model architecture that incorporates a channel attention module for beam training. The simulation results show a significant enhancement in performance with our scheme compared to both a state-of-the-art approach and other existing methods across all scenarios. Particularly, we confirm that even when reducing the number of wide beams used for measurement by approximately 50 % , our proposed approach achieves a performance close to that of the state-of-the-art scheme. [ABSTRACT FROM AUTHOR]

HfO2-based ferroelectric tunnel junctions (FTJs) are promising nonvolatile memory types for neural network applications because of their speed, low power, and excellent complementary metal-oxide semiconductor compatibility. Specifically, HfAlOx (HAO) has led to extensive research efforts owing to its outstanding ferroelectric performance. This is a result of the fact that the atomic radius of Al is smaller than that of Hf. In this study, we investigate the metal–ferroelectric–semiconductor device with an Al doping concentration of 2% that was annealed at 900 °C. A high-remnant polarization (Pr) value of 39.85 µC/cm2 and endurance were achieved by using the polarization switching positive-up-negative-down measurement method at this annealing condition. Our device shows long-term potentiation and depression properties, including high linearity and multiple conductance states for neuromorphic applications. Moreover, paired-pulse facilitation was implemented to mimic human synaptic functions. The construction of 16 states comprising four bits was achieved by employing reservoir computing with the FTJ device functioning as a physical reservoir. Finally, the results obtained from the experiment show promising outcomes for the ferroelectric memory characteristics and synaptic properties of the manufactured HAO device. [ABSTRACT FROM AUTHOR]

Since HfOx‐based ferroelectric tunnel junctions (FTJs) are attractive compared to perovskite‐based FTJs and other emerging memory devices, they are being actively studied recently. They have advantages such as a simple metal–insulator–metal structure, complementary metal oxide semiconductor (CMOS) compatibility, non‐destructive operation, and low power consumption. Moreover, doped HfOx‐based FTJs are in the spotlight in terms of neuromorphic engineering as a way of advancing from the von Neumann structure. In particular, Al dopant is effective for inducing ferroelectric properties due to its smaller radius than that of Hf. The optimal concentration of Al varies depending on the device materials and the annealing conditions during deposition. Therefore, in‐depth research is required for neuromorphic applications. Herein, the properties of FTJ devices according to Al doping concentrations are analyzed. Subsequently, using the device with the highest remanent polarization, neuromorphic applications are implemented, including spike‐timing‐dependent plasticity (STDP), paired‐pulse facilitation (PPF), long‐term potentiation, and depression. The characteristics in different frequency regions are also studied to satisfy the demand for fast switching. Finally, the FTJ device is used as a physical reservoir in reservoir computing for efficient processing of time‐dependent inputs. [ABSTRACT FROM AUTHOR]

In this work, we fabricated an ITO/WOX/TaN memristor device by reactive sputtering to investigate resistive switching and conduct analog resistive switching to implement artificial synaptic devices. The device showed good pulse endurance (104 cycles), a high on/off ratio (>10), and long retention (>104 s) at room temperature. The conduction mechanism could be explained by Schottky emission conduction. Further, the resistive switching characteristics were performed by additional pulse-signal-based experiments for more practical operation. Lastly, the potentiation/depression characteristics were examined for 10 cycles. The results thus indicate that the WOX-based devices are appropriate candidates for synaptic devices as well as next-generation nonvolatile memory. [ABSTRACT FROM AUTHOR]

The ferroelectric characteristics of a metal-ferroelectric-metal (MFM) ferroelectric tunneling junction (FTJ) capacitor device are investigated herein. The device consists of an aluminum-doped hafnium oxide (HAO) insulator sandwiched between tungsten (W) and titanium nitride (TiN) metal electrodes. Rapid thermal annealing (RTA) is performed for 20 s under a nitrogen atmosphere at temperatures of 750 °C, 800 °C, and 850 °C to find that ferroelectricity with a large remanent polarization (Pr) of 41.28 μC cm−2 can be obtained at the optimum annealing temperature of 800 °C. The presence of ferroelectricity is confirmed by polarization-switching positive-up–negative-down (PUND) measurements and by the hysteric polarization–voltage (P–V) loop. All devices exhibit excellent reliability, with an endurance of up to ∼106 cycles and long retention characteristics. In addition, the interfacial paraelectric capacitance (Ci) values of the three HAO FTJs are investigated via pulse-switching measurements. The results indicate that the HAO film annealed at 800 °C for 20 s exhibits an excellent tunneling electro-resistance (TER) ratio of 186% and this is attributed to the extra paraelectric layer formed between the ferroelectric layer and the bottom electrode. The detailed findings of this study are expected to assist in the development of hafnium oxide-based ferroelectric non-volatile memory applications. [ABSTRACT FROM AUTHOR]

This study proposed a virtual reality (VR) course that addresses the overall understanding and application of VR technology. After investigating previous studies, we found that two technologies must be applied to design a VR course that fits the latest trends. One is hardware technology dealing with the technical background, while the other is software utilization and development using the merits of VR technology. To accommodate these needs, we designed a VR course consisting of three steps: VR-related theory, TA-led content creation training, and team projects. Through this course, students will improve their ability to develop applications that apply to their research fields after studying the technical background and courses of VR. We conducted a semester-long study with nine students to verify the proposed method and then evaluated them through an in-depth interview and a questionnaire with a five-point Likert scale consisting of nine items. Considering this feedback, we have added several steps to improve the educational effect among students. [ABSTRACT FROM AUTHOR]

In this work, we evaluate the resistive switching (RS) and synaptic characteristics of a fully transparent resistive random-access memory (T-RRAM) device based on indium-tin-oxide (ITO) electrodes. Here, we fabricated ITO/WOX/ITO capacitor structure and incorporated DC-sputtered WOX as the switching layer between the two ITO electrodes. The device shows approximately 77% (including the glass substrate) of optical transmittance in visible light and exhibits reliable bipolar switching behavior. The current-voltage (I–V) curve is divided into two types: partial and full curves affected by the magnitude of the positive voltage during the reset process. In the partial curve, we confirmed that the retention could be maintained for more than 104 s and the endurance for more than 300 cycles could be stably secured. The switching mechanism based on the formation/rupture of the filament is further explained through the extra oxygen vacancies provided by the ITO electrodes. Finally, we examined the responsive potentiation and depression to check the synaptic characteristics of the device. We believe that the transparent WOX-based RRAM could be a milestone for neuromorphic devices as well as future non-volatile transparent memory. [ABSTRACT FROM AUTHOR]

Resistive random–access memory (RRAM) for neuromorphic systems has received significant attention because of its advantages, such as low power consumption, high–density structure, and high–speed switching. However, variability occurs because of the stochastic nature of conductive filaments (CFs), producing inaccurate results in neuromorphic systems. In this article, we fabricated nitrogen–doped tantalum oxide (TaOx:N)–based resistive switching (RS) memory. The TaOx:N–based device significantly enhanced the RS characteristics compared with a TaOx–based device in terms of resistance variability. It achieved lower device–to–device variability in both low-resistance state (LRS) and high–resistance state (HRS), 8.7% and 48.3% rather than undoped device of 35% and 60.7%. Furthermore, the N–doped device showed a centralized set distribution with a 9.4% variability, while the undoped device exhibited a wider distribution with a 17.2% variability. Concerning pulse endurance, nitrogen doping prevented durability from being degraded. Finally, for synaptic properties, the potentiation and depression of the TaOx:N–based device exhibited a more stable cycle–to–cycle variability of 4.9%, compared with only 13.7% for the TaOx–based device. The proposed nitrogen–doped device is more suitable for neuromorphic systems because, unlike the undoped device, uniformity of conductance can be obtained. [ABSTRACT FROM AUTHOR]

This paper presents an optical see-through head-mounted display (OST-HMD) that can provide a highly immersive augmented reality (AR) environment. Because visibility of objects is degraded by external light and because projection optics cannot represent black color, the reality of AR content is reduced. To solve this problem, we adopted an additional transparent display to adjust the transmittance of exterior light. This adjustment is achieved using a guest–host liquid crystal (GHLC) to provide transparency in the initial state and opacity when voltage is applied. To verify the display's usefulness, we measured ambient contrast ratio (ACR) and color gamut under various ambient light conditions after attaching the GHLC panel to the existing OST-HMD (Microsoft HoloLens). Under typical office illumination, use of the GHLC panel increased the ACR by 4.67 times, and the color gamut by 2.87 times compared to the OST-HMD without it. Under high illumination the panel increased the ACR by 1.54 times and the color gamut by 16.16 times. The proposed method significantly improved the ambient contrast ratio and color expression, and yielded a flexible way to customize existing OST-HMDs by adding a detachable display. [ABSTRACT FROM AUTHOR]

Concrete cracks can threaten the usability of structures and degrade the aesthetics of buildings. Furthermore, minor cracks can develop into large-scale cracks that may lead to structural failure when exposed to excessive external loads. In addition, the concrete crack width and depth should be precisely measured to investigate the effects of concrete cracks on the stability of structures. Thus, a nondestructive and noncontact testing method was introduced for detecting concrete crack depth using thermal images and machine learning. The thermal images of the cracked specimens were obtained using a constant test setup for several months under daylight conditions, which provided sufficient heat for measuring the temperature distributions of the specimens, with recording parameters such as air temperature, humidity, and illuminance. From the thermal images, the crack and surface temperatures were obtained depending on the crack widths and depths using the parameters. Four machine-learning algorithms (decision tree, extremely randomized tree, gradient boosting, and AdaBoost) were selected, and the results of crack depth prediction were compared to identify the best algorithm. In addition, data bias analysis using principal component analysis, singular value decomposition, and independent component analysis were conducted to evaluate the efficiency of machine learning. [ABSTRACT FROM AUTHOR]

This paper presents a channel estimation scheme using a new jammed pilot detection algorithm for orthogonal frequency-division multiplexing (OFDM) systems under narrow-band jamming (NBJ). The jammed pilot subcarrier can be detected and excised by using the proposed algorithm after least squares estimation. The average mean square error (mse) on one OFDM symbol both under a jammed and a removed pilot subcarrier are derived analytically. Moreover, the symbol error rate (SER) performance for the channel estimation scheme using the proposed algorithm is evaluated by simulation. From the results, we can show that the channel estimator with the proposed algorithm improves the mse and SER performances at a low signal-to-jamming ratio. Index Terms--Channel estimation, least squares (LS), linear interpolation, narrow-band jamming (NBJ), orthogonal frequency-division multiplexing (OFDM) systems.

In time-varying fading channels, orthogonal frequency division multiplexing systems suffer severe performance degradation caused by interchannel interference (ICI). We utilize this ICI as a source of diversity by using a new ICI-cancellation algorithm and Wiener filter. The proposed algorithm can support joint Doppler-frequency diversity gain. In addition, both the computational complexity and total detection time are reduced. Index Terms--Hybrid interference cancellation (HIC), joint Doppler-frequency diversity, orthogonal frequency division multiplexing (OFDM), parallel interference cancellation (PIC), successive interference cancellation, Wiener filter (WF).

Leucine‐rich repeat kinase 2 (LRRK2) is considered a promising therapeutic target for Parkinson's disease, Crohn's disease, and cancer. Despite considerable research, none of these inhibitors are available for clinical application. Herein, we designed and synthesized novel thienopyrimidine derivatives by a bioisosteric replacement and investigated their structure–activity relationships. Thieno[3,2‐d]pyrimidine derivative 22 showed the most potent inhibitory activity and inhibited both wild‐type and G2019S mutant LRRK2 with IC50 values of 30 and 14 nM, respectively. [ABSTRACT FROM AUTHOR]

This article investigated the impact of immersive virtual reality (VR) content, using 360-degree videos, in undergraduate education. To improve the delivery and reality of 360-degree VR content, we filmed the video in the third person so that the viewers could feel like they were in the environment where the lecture was conducted. To verify the educational effects, 33 university students participated in our experiment. We conducted pretest learning, using 360-degree videos, and posttest learning via conventional 2-D videos for statistical analysis. A paired t-test was used to compare the means of the pretest and the posttest. In addition, learning via 360-degree videos was assessed for its effectiveness through questionnaires consisting of five measurement elements—engagement, immersion, motivation, cognitive benefits, and perceived learning effectiveness—and comparing them to the existing 2-D video method, based on e-learning. From the results, we confirmed that the teaching material delivered through 360-degree VR content allows students to be more focused, immersed, and interested than 2-D learning modes. Furthermore, the high scores of cognitive and perceived learning elements imply that VR-based 360-degree educational content can encourage more active participation than traditional lectures and can improve the ability to analyze and organize study lessons. [ABSTRACT FROM AUTHOR]

This paper discusses how to optimize the weighting of individual subarrays to derive the low sidelobe level (SLL) based on quadratic programming (QP) and how to derive QP parameters to ensure that the objective function is composed of the quadratic function form, with the actual number identical to the standard objective function of QP. Next, in order to analyze the SLL, a 24 × 24 phased array antenna was compared with 96 transmit–receive modules (TRMs) attached only to the subarray stage and a phased array antenna with 576 TRMs attached to all radiating elements without a subarray. Optimized weighting was applied to the array antennas with a subarray, and Taylor weighting was applied to the array antennas without a subarray. The number of TRMs used in the phased array antenna with the optimized weighting was reduced by 83.3% compared to the phased array antenna in which TRMs were attached to all radiating elements. The SLL and the half-power beamwidths (HPBWs) of the two antennas were practically identical in a narrow beam-scanning environment. Finally, an array pattern (AP) in which mutual coupling between the radiating elements was considered was calculated to verify the optimized weighting. Moreover, the optimized weighting was applied to CST Microwave Studio (an EM full-wave simulation) to compare the results from the AP calculation and a simulation. It was confirmed that the two results above are largely indistinguishable. The analysis found that the HPBW is 3.6 ∘ × 3.6 ∘ and the SLL is −26.18 dB from AP calculations in the boresight direction. When each 5 ∘ beam was scanned at the azimuth and elevation, the corresponding HPBW values were 3.7 ∘ × 3.7 ∘ and 3.7 ∘ × 3.7 ∘ and the SLLs were −22.70 dB and −24.44 dB according to the AP calculations. [ABSTRACT FROM AUTHOR]

Radiation from a cavity-backed circular aperture array antenna enclosed by a frequency selective surface (FSS) radome is studied using the hybrid analysis method, by combining the mode matching method, the ray tracing technique, and Huygens's principle. The equivalent magnetic surface currents on the apertures are derived from the aperture electromagnetic fields, which are calculated based on the mode matching method. The rays are generated from the equivalent magnetic surface currents and used to analyze the FSS radome based on the ray tracing technique. After being obtained from both the mode matching method and the ray tracing technique, electromagnetic fields on an outermost radome are transformed into the equivalent electric and magnetic surface currents using Huygens's principle. The radiated fields are computed from the equivalent surface currents and compared with the measured data. [ABSTRACT FROM AUTHOR]

Recently, the 3rd Generation Partnership Project has developed vehicle-to-everything communication to manage and advance future traffic safety and mobility. In this study, we propose a position-based resource allocation scheme for vehicle-to-vehicle communication. The proposed scheme allocates a different frequency and time resources based on vehicle speed, density, direction, and position. Our performance analysis is based on urban and freeway cases involving periodic message transmission. Simulation results show that the proposed scheme can improve the cumulative distribution function of packet reception ratio (PRR) and average PRR. [ABSTRACT FROM AUTHOR]