Miracle-dz/UniFAR-FTUs huggingface dataset:
A Simulation Technique for Radiation Properties of Time-Varying Media Based on Frequency-Domain Solvers

A novel simulation technique is proposed for the radiation properties of time-varying media. This method divides the time-variation process into finite discrete time steps. The radiation field of the media at each instant in time is simulated by using commercially available frequency-domain solvers, and then these results are processed and synthesized to obtain the radiation field of the time-varying media. In other words, by using this technique, the radiation field of the time-varying media can be obtained based on the frequency-domain simulation results. The proposed technique is introduced with a time-varying grating, and the scattered wave and radiation pattern are illustrated. Moreover, an analytical model of the time-varying grating is also introduced to further explore the proposed technique. This simulation technique can be used to analyze many applications such as the radiation properties of time-modulated media, especially space-time-modulated metamaterials. It fills the gap of existing simulation methods and provides a new way for direct EM simulation of time-varying structures.
Clamped-Resonant Interleaved Boost Converter: Analysis and Design

This paper investigates a DC-DC converter topology called Clamped-Resonant Interleaved Boost converter (CRIB), suitable for high-frequency operation. The use of a resonant L-C tank connected between the switch drain terminals ensures zero-voltage and zero current commutations of all devices, independently of the load current, as well as a reduced dv/dt across the switches. Moreover, no-load operation was demonstrated whenever the minimum voltage gain is higher than a limit value.The theoretical predictions have been confirmed by an experimental setup based on a 42 − 54 V to 400 V – 300 W prototype, showing an efficiency above 96% at the nominal power in the whole input voltage range.
Dynamic User Grouping-Based NOMA Over Rayleigh Fading Channels

With the development of wireless communications and internet of things (IoT), non-orthogonal multiple access (NOMA) has been considered as one of effective schemes to meet the rapidly growing user access requirements. Two types of NOMA, i.e., NOMA-2000 and power-domain NOMA (PD-NOMA), have been proposed in recent years. The first one is a superposition of a set of orthogonal frequency division multiple access (OFDMA) signals and a set of spread-spectrum multicarrier-code division multiple access (MC-CDMA) signals while the second one is a direct superposition of a MC-CDMA signal and an OFDMA signal. This paper proposes a dynamic user grouping method for classifying users and then compares the performance between NOMA-2000 and PD-NOMA over Rayleigh fading channels. Simulation results show that the PD-NOMA can always exhibit lower bit error rate (BER) than the NOMA-2000 under different signal-to-noise ratios. Under the Rayleigh fading environment, the performance of the PD-NOMA after user grouping is better than that of NOMA-2000.
Performance of the Population Bioequivalence (PBE) Statistical Test with Impactor Sized Mass Data

This article extends previous work studying performance characteristics of the population bioequivalence (PBE) statistical test recommended by the US Food and Drug Administration (FDA) for orally inhaled and nasal drug products. Based on analysis of a metered dose inhaler database for impactor sized mass, a simulation study was designed to compare performance of the recommended PBE approach with several modified or alternative approaches. These included an extended PBE that separately modeled within-batch (can) and between-batch (batch) variability and average bioequivalence (ABE) tests that modeled with or without between-batch variability and with or without log-transformation. This work showed that separately modeling within- and between-batch variability while increasing the number of sampled batches addressed previously identified issues of the PBE approach when between-batch variability was present, namely, (a) increased risk for falsely concluding equivalence and (b) low probability of correctly concluding equivalence. The same modifications were also required of the ABE to achieve expected performance. However, these modifications did not successfully address the issue of equivalence conclusions that depended on the direction of product mean differences (asymmetric performance). This work highlights the importance of understanding decision-making error rates in developing regulatory recommendations to standardize bioequivalence outcomes across products.
Fine-Grained TDMA MAC Design toward Ultra-Reliable Broadcast for Autonomous Driving

In the autonomous driving era, V2X communication is essential since it enables rapid message dissemination via periodical beacon exchange (broadcast communication), which contributes to better situation awareness and maneuvering cooperation. However, designing a MAC protocol for reliable V2X broadcasting is challenging, as minimal beacon delivery delay and collision avoidance should be achieved simultaneously. In this article, we design a fine-grained TDMA-based MAC protocol to support ultra-reliable broadcast for autonomous vehicles. Specifically, three critical issues are first identified: mobility-caused time slot collision, time slot shortage, and stiff beacon rate limitation. Accordingly, three fine-grained solutions are provided to tackle those issues: mobility-aware time slot assignment, beacon rate adaption with safety awareness, and flexible beacon rates support. Moreover, a case study on mobility-aware time slot assignment based on road topology and lane distribution is presented, with simulation results' verification. Finally, we elaborate the steps to implement the fine-grained MAC protocol in autonomous driving environments.
The Influence of Public Engaging Intention on Value Co-Creation of E-Government Services

The wide acceptability of ICTs and social media enriches the delivery platform of e-government (E-gov) services. The public can explore problems, provide ideas, and design solutions to improve E-gov services (EGS) in a convenient and timely manner. The role of the public transforms from passive users to active, informed partners or co-creators of EGS innovations and problem solving. However, value co-creation is an interactive process, and service value can only be created through joint efforts of all participants. This study builds an influence factor model of public engaging intention towards EGS value co-creation, based on technology acceptance theory, trust theory, and motivation theory, to explore the impact factors and impact paths. Comprehensive validation is further conducted through path analysis using structural equation modeling (SEM) methods. Path analysis interprets how the public will accept and adopt value co-creation behavior for EGS. The results presented in this study might be helpful for government policymakers or IT managers seeking to enhance EGS value creation through designing more effective incentive mechanisms. This study also introduces a comprehensive picture of the potential paradigm of public service value creation in an era of increasing user dominance.
Soft-Event-Upset and Soft-Event-Transient Tolerant CMOS Circuit Design for Low-Voltage Low-Power Wireless IoT Applications

In the wireless IoT applications, low power is a critical criteria, and low-voltage is a direct way to meet such demand. However, low-voltage criteria in advanced CMOS VLSI designs will lead to critical design challenges in dealing with soft-error interference, especial while the cascade transistor number is limited under low-voltage operations. Some possible low-voltage SEU-tolerant and SET-tolerant circuit design methods are discussed in this paper, such as robust C-element, Error-Correction with Duplication, dual interlocked storage cell (DICE) latch, and such as feedback redundant SEU-tolerant (FERST) latch designs.
Analytical Model and Experiments of Phase Noise in Oven-Controlled Mems Resonators

We develop an analytical model of phase noise in an oven-controlled MEMS resonator, which behaves like 1/f. The model reveals that the 1/f like phase noise is up-converted of the self-heating noise of the spring constant. Though the self-heating voltage is white noise, the temperature fluctuation of the spring constant is 1/f like due to the thermal diffusion. When the supporting beam is infinite long, the power of the temperature fluctuation of the resonator are inversely proportional to f. The temperature fluctuation of the real resonator can be simulated by an equivalent circuit model. The temperature fluctuation is further modulated by the relaxation process of resonator damping. The power of the 1/f like phase noise in mechanical resonators is approximately proportional to Q2 when f approaches 0, Q being the quality factor of the resonator. The model matches the experiments qualitatively.
A Memory-Reinforced Tabu Search Algorithm With Critical Path Awareness for HW/SW Partitioning on Reconfigurable MPSoCs

Hardware/software (HW/SW) partitioning and scheduling are the crucial steps in HW/SW co-design. They have a strong effect on performance, area, power and the system itself. In this paper, a memory-reinforced tabu search algorithm with critical path awareness (MTSP) is proposed for solving the HW/SW partitioning problem. First, the critical path (CP) algorithm can locate the critical task queues and output a reduced task graph. Second, the solution to a heuristic algorithm (HA) is used as the initial solution. Third, by introducing hash technology, adding dual memory tables improves the search strength and effectiveness of the tabu search, and the experiment is completed by priority scheduling. MTSP especially has good performance in large task graphs, while it can greatly improve system performance, especially in the case of generating a large communication penalty. The experimental results show that the average improvement over the latest efficient hybrid algorithm is up to 5%. The improvement in algorithm searching time is 66% in comparison to the popular algorithms cited in this paper.
Cycling renaissance: The VR potential in exploring static and moving environment elements

Although cycling attracts increasing attention being an active and healthy way of transport, understanding the determinants of cycling experience is still a challenge. The current study addressed this challenge by exploring how various parameters (i.e. static and moving elements) of the environment influence cycling experience in a simulated Virtual Reality (VR) world. Different scenarios were created mirroring the streetscape of a real Dutch city. The scenarios were designed in such a way that we have a full crossing of the manipulated factors, namely, static (bicycle path presence, crossroad presence) and moving elements (cars, pedestrians, other cyclists intensity). After having a bike ride, participants had to provide their evaluation on the just experienced environment, in terms of safety and enjoyment perception. Naturalness, presence, engagement and liking of the VR environment were also addressed.The results are clear in showing that safety perception depends on whether bicycle path and crossroads are present. Enjoyment however did not show statistical differences in respect to the above factors. Concerning moving elements, car intensity influenced both, safety and enjoyment perception. Current results are discussed in line with the existing theories on cycling experience. We further focus attention at how well-known VR applications might enhance experience and thus opening avenues to appropriately investigate everyday context scenarios, outside research laboratories and specialist environments.
Examination of factors influencing students and faculty behavior towards m-learning acceptance

Purpose Mobile learning is a unique form of learning which uses the distinct features of mobile devices. The purpose of this paper is to investigate the present state of student and faculty perception towards m-learning at open and distance educational institutes in Pakistan. Design/methodology/approach The paper presents a conceptual model based on TAM, which explains factors influencing student and faculty perception towards m-learning acceptance. M-learning acceptance mainly depends on personal attitude, so this study focusses on individual context. Primary data from students and faculty including tutors (n=612, students =448, faculty/tutors=162) was collected through a properly designed questionnaire by using purposive convenient sampling technique during Autumn 2015 semester. Structural equation modelling was used to analyse the collected data. Findings The results indicate that student and faculty skill readiness and self-efficacy influence perceived ease of use and perceived usefulness, where these two factors along with prior experience positively influence behavioural intension (BI) to accept mobile learning. Furthermore study results specifically provide factors which positively influence BI either directly or indirectly. Research limitations/implications The study was limited to AIOU. Originality/value The study specifically provides factors which influence BI either directly or indirectly.
Fault Isolation in the DC Distribution Grid Using Current Signature Analysis

The dc distribution grid based on power electronics is a promising solution for flexible power management and dc integration. However, the protection techniques that fit in this application are still immature. This study develops a fault isolation method tailored for the dc distribution grid on the basis of local measurement only. After studying the characteristic behaviors of the dc distribution grid during short circuit faults, we then extract the current signatures of the dc distribution grid using wavelet transform. Subsequently, the influences of system and fault parameters on this fault isolation method are discussed in this context This study offers a new insight into the fault isolation in the dc distribution grid.
Meta-Learning via Weighted Gradient Update

Despite deep reinforcement learning has attained performance beyond human beings in many domains, including games, dialogue systems and robotics, sample inefficient is still a limitation in the application of deep reinforcement learning. This paper develops a novel and simple gradient-based meta learning method suitable for improving learning efficiency of deep reinforcement learning methods. Rather than designing complex network or adding excessive fine tuning parameters, the proposed method is simple and does not introduce any learned parameters for meta learning. Specifically, according to the characteristic of different trajectories, this paper proposes to weight every trajectory in model-agnostic meta-learning for meta updating gradient effectively. The key idea underlying this method is to take advantage of the relationship between different trajectories and the direction of parameter update. Additionally, an end-to-end training approach is also introduced so that the proposed model can attain good results with a small amount of training data on new tasks. The statistical results of the experiments indicate that the proposed algorithm delivers state-of-the-art performance on both discrete and continuous control tasks.
Mapping Human Settlements with Multi-seasonal Sentinel-2 Imagery and Attention-based ResNeXt

This paper explores the potential of multi-spectral Sentinel-2 imagery for human settlement mapping, using deep learning based methods. We show first results of a study area in central Europe, with an attention-based ResNeXt to better exploit the spectral information. Reasonable mapping accuracy has been achieved, compared to the state-of-the-art products. Based on the results and comparison with the existing products, we discuss two interesting questions: how can human settlement mapping be made consistent with or complementary to the existing human settlement maps and how can further improvement in human settlement mapping be achieved by exploring deep learning-based approachesƒ
Smart and Efficient Energy Saving System Using PDLC Glass

As identified by environmental scientists on energy consumption statistical projection, energy shortage is among one of the most prominent current global issues. Thus, energy saving solutions are becoming more and more relevant, since they are beneficial ecologically, financially, and personally. Therefore, there are more scientific research studies being conducted in increasing energy efficiency at a reduced rate in order to gain continuity of energy availability while lessening harmful negative environmental impacts (e.g., thermal pollution, glass house global warming effects). Working towards this crucial goal, this paper shares a new method of designing smart and efficient energy saving system using PDLC glass. It is capable of automatically turning into the user’s shades of choice gradually from a remote control. This capability is dependent on the building’s sun movement or sunlight exposure throughout the day from any angle of the building, which is detectable by a programmable Arduino light sensor. This is especially beneficial for areas with stable weather patterns and can also serve as a replacement for traditional curtains or blinds. When considering the initial cost of the product and the time spent installing and maintaining them, curtains or blinds cost more while only having similar results on decreasing or increasing the solar illumination, sunlight exposure, and temperature control according to the weather. An added benefit is that it can also turn the thermal pollution factor into a regenerative renewable storable solar energy by eliminating the sunlight reflection over the building when the glass absorbs it. Tests on the invented prototype validate its feasibility, offering an economical yet efficient option as a choice for smart energy saving systems.
Research on Identification of Freeway Black Spots and Accident Induced Factors

In order to improve the objectivity and fairness of identifying black spots and elements, three correlative methodologies are developed. Firstly, an approach for segment division based on dynamic clustering algorithm is proposed, which can be used to separate a highway into a series of subsections according to the appearance of accidents. Then, a self-organizing neural network model is established to identify the black spots from these subsections. Lastly, a methodology based on discrete multi-variable algorithm combined with rough set theory is presented to determine the accident induced factors of these black spots. The results show that (1) the segment division based on dynamic clustering algorithm can describe objectively the concentration and dispersion of accidents, (2) the neural network model can quickly identify the black spots and the corresponding results are reasonable, and (3) the methodology to identify the prominent accident causes can be used to establish a set of evaluation criteria and then to determine the accident induced factors of a black spot.
VATT Working Papers 128

This study exploits a large-scale natural experiment in Finnish conscription to study how exposure to peers from different family backgrounds affects education, earnings, employment, and hourly wage. Our research design is based on the alphabetic rule in assigning conscripts to dorms, which induces credible exogenous variation in peer family backgrounds. Being exposed to a dormmate from a highincome family has a positive long-term effect on earnings. The effects are the largest for individuals who come from high-income families. Exposure to peers with one standard deviation higher average parent income raises their earnings at age 28-42 by 2.6%. The results suggest beneficial labor market networks as a key mechanism. Exposure to peers from high-income families has little impact on earnings and hourly wages of individuals who come from low-income families, but it increases their educational attainment in the long run. The findings imply that social stratification reinforces economic and educational inequality between rich and poor families.
The development and testing of an audit for the pedestrian environment 3

10 Recognizing the need for consistent, reliable, and efficient methods to collect information about the walking environment, the authors have developed and tested a complete environmental audit methodology—the Pedestrian Environmental Data Scan (PEDS). In this paper, the development of the audit methodology is presented, including the design of the instrument, the creation of training and supporting materials, administration, and integration with handheld technology. Various tests of interand intra-rater reliability of our instrument have been conducted, including i a i 11
Anthropogenic disturbance along the Kinabatangan River in Borneo , Malaysia and the distribution and abundance of the saltwater crocodile ( Crocodylus porosus )

Anthropogenic disturbances on wildlife populations are a growing problem worldwide and populations of large carnivores are often subject to human wildlife conflicts. Some disturbances are well documented, for example habitat destruction or poaching. Non-lethal disturbances, for instance boat-traffic, are less widely recognized. The order Crocodilia are characterised as large, semiaquatic carnivores living in freshwater habitats in the tropical and warm temperate regions of the world. Response to disturbances such as boat-traffic can directly affect the survival of aquatic animals. This study investigates the effect of non-lethal human disturbances on the abundance and distribution of saltwater crocodiles (Crocodylus porosus) in the Kinabatangan River, Borneo. The results indicated that these disturbances have a small effect on the distribution and number of crocodiles. It also indicated that larger crocodiles are more sensitive and wary regarding boat traffic and fishing. Although, it is likely that these studied disturbance factors are far from the only factors affecting crocodile abundance and distribution.
Reaction Time in Grade 5: Data Collection within the Practice of Statistics.

This study reports on a classroom activity for Grade 5 students investigating their reaction times. The investigation was part of a 3-year research project introducing students to informal inference and giving them experience carrying out the practice of statistics. For this activity the focus within the practice of statistics was on introducing two different ways of collecting data to answer a statistical question, in this case, "What is the typical reaction time of Grade 5 students? " Workbook entries were used to assess students’ capacities to engage in the investigation. Results indicated that although the students were proficient with the procedures and measures introduced, they were less able to explain and apply the underlying concepts. The activity provides a suggestion and benchmarks for others wishing to follow student development of concepts related to the practice of statistics.