Miracle-dz/UniFAR-FTUs huggingface dataset:
Photonic crystal based interferometric design for label-free all-optical sensing applications.

Optical sensing devices has a great potential in both industrial and biomedical applications for the detection of biochemicals, toxic substances or hazardous gases thanks to their sustainability and high-selectivity characteristics. Among different kinds of optical sensors based on such as fibers, surface plasmons and resonators; photonic crystal (PC) based optical sensors enable the realization of more compact and highly efficient on-chip sensing platforms due to their intriguing dispersive relations. Interferometric devices based on PCs render possible the creation of biochemical sensors with high sensitivity since a slight change of sensor path length caused by the captured biochemicals could be detected at the output of the interferometer via the interferences of separated beams. In this study, a new type of Mach-Zehnder Interferometer (MZI) using low-symmetric Si PCs is proposed, which is compatible with available CMOS technology. Intended optical path difference between the two MZI channels is provided by the periodic alignments of symmetry-reduced PC unit cells in the MZI arms. Unlike the conventional symmetrical PC based MZIs, Fano resonances exist for the proposed MZI design, i.e. transmission dips and peaks appear in the output spectrum, and the location of dip and peak frequencies in transmission spectra can be efficiently controlled by utilizing interference phenomenon. Exploiting this effect, any refractive index change at the surrounding medium could be distinctly observed at the transmission spectra. In the view of such results, it is convenient to say that the proposed MZI configuration is suitable for efficient optical sensing of toxic gases as well as liquids. The designed all-dielectric MZI system is numerically investigated in both spectral and spatial domains to analyze its interferometric tunability: an optical sensitivity of about 300 nm/RIU is calculated for gaseous analytes whereas that sensitivity value is around 263.2 nm/RIU in the case of liquid analytes. Furthermore, high quality factor of Q > 45000 is obtained at Fano resonances with Figure-of-Merit (FoM) value of FoM ∼ 8950 RIU-1(7690 RIU-1) in the case of gas analytes (liquid analytes), which is the indication of enhanced optical sensing performance of the proposed MZI design. Considering all the above-mentioned advantages, the proposed interferometric configurations based on low-symmetric PCs could be utilized for efficient photonic sensor applications that require controllable output power or sensing of gaseous and liquid substances.
D-ViNE: Dynamic Virtual Network Embedding in Non-Terrestrial Networks

In this paper, we address the virtual network embedding (VNE) problem in non-terrestrial networks (NTNs) enabling dynamic changes in the virtual network function (VNF) deployment to maximize the service acceptance rate and service revenue. NTNs such as satellite networks involve highly dynamic topology and limited resources in terms of rate and power. VNE in NTNs is a challenge because a static strategy under-performs when new service requests arrive or the network topology changes unexpectedly due to failures or other events. Existing solutions do not consider the power constraint of satellites and rate limitation of inter-satellite links (ISLs) which are essential parameters for dynamic adjustment of existing VNE strategy in NTNs. In this work, we propose a dynamic VNE algorithm that selects a suitable VNE strategy for new and existing services considering the time-varying network topology. The proposed scheme, D-ViNE, increases the service acceptance ratio by 8.51% compared to the benchmark scheme TS-MAPSCH.
High temperature phase transitions in NaNbO3 epitaxial films grown under tensile lattice strain

We have investigated high temperature phase transitions in NaNbO3 thin films epitaxially grown under tensile lattice strain on (110) DyScO3 substrates using metal-organic vapor phase epitaxy. At room temperature, a very regular stripe domain pattern consisting of the monoclinic a1a2 ferroelectric phase was observed. Temperature-dependent studies of the refractive index and the optical bandgap as well as in situ high-resolution x-ray diffraction measurements prove a ferroelectric–ferroelectric phase transition in the range between 250 and 300 °C. The experimental results strongly suggest that the high-temperature phase exhibits a distorted orthorhombic a1/a2 crystal symmetry, with the electric polarization vector lying exclusively in the plane. A second phase transition was observed at about 500 °C, which presumably signifies the transition to the paraelectric phase. Both phase transitions show a pronounced temperature-dependent hysteresis, indicating first-order phase transitions.
Weather Radar Echo Extrapolation Method Based on Deep Learning

In order to forecast some high intensity and rapidly changing phenomena, such as thunderstorms, heavy rain, and hail within 2 h, and reduce the influence brought by destructive weathers, this paper proposes a weather radar echo extrapolation method based on deep learning. The proposed method includes the design and combination of the data preprocessing, convolutional long short-term memory (Conv-LSTM) neuron and encoder–decoder model. We collect eleven thousand weather radar echo data in high spatiotemporal resolution, these data are then preprocessed before they enter the neural network for training to improve the data’s quality and make the training better. Next, the neuron integrates the structure and the advantages of convolutional neural network (CNN) and long short-term memory (LSTM), called Conv-LSTM, is applied to solve the problem that the full-connection LSTM (FC-LSTM) cannot extract the spatial information of input data. This operation replaced the full-connection structure in the input-to-state and state-to-state parts so that the Conv-LSTM can extract the information from other dimensions. Meanwhile, the encoder–decoder model is adopted due to the size difference of the input and output data to combine with the Conv-LSTM neuron. In the neural network training, mean square error (MSE) loss function weighted according to the rate of rainfall is added. Finally, the matrix “point-to-point” test method, including the probability of detection (POD), critical success index (CSI), false alarm ratio (FAR) and spatial test method contiguous rain areas (CRA), is used to examine the radar echo extrapolation’s results. Under the threshold of 30 dBZ, at the time of 1 h, we achieved 0.60 (POD), 0.42 (CSI) and 0.51 (FAR), compared with 0.42, 0.28 and 0.58 for the CTREC algorithm, and 0.30, 0.24 and 0.71 for the TITAN algorithm. Meanwhile, at the time of 1 h, we achieved 1.35 (total MSE ) compared with 3.26 for the CTREC algorithm and 3.05 for the TITAN algorithm. The results demonstrate that the radar echo extrapolation method based on deep learning is obviously more accurate and stable than traditional radar echo extrapolation methods in near weather forecasting.
An Integrated Programmable Wide-range PLL for Switching Synchronization in Isolated DC-DC Converters

An Integrated Programmable Wide-range PLL for Switching Synchronization in Isolated DC-DC Converters Miad Fard Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2016 In this thesis, two Phase-Locked-Loop (PLL) based synchronization schemes are introduced and applied to a bi-directional Dual-Active-Bridge (DAB) dc-dc converter with an input voltage up to 80 V switching in the range of 250 kHz to 1 MHz. The two schemes synchronize gating signals across an isolated boundary without the need for an isolator per transistor. The Power Transformer Sensing (PTS) method utilizes the DAB power transformer to indirectly sense switching on the secondary side of the boundary, while the Digital Isolator Sensing (DIS) method utilizes a miniature transformer for synchronization and communication at up to 100 MHz. The PLL is implemented on-chip, and is used to control an external DAB power-stage. This work will lead to lower cost, high-frequency isolated dc-dc converters needed for a wide variety of emerging low power applications where isolator cost is relatively high and there is a demand for the reduction of parts.
Psychological tests for expectant parents and young children in the Nordic countries: A review of the evidence

ABSTRACT The aim of this article is to review the psychometric properties of the psychological tests that are being used in the Nordic countries during pregnancy and the child’s first two years of life. A systematic literature search was performed for 33 identified tests routinely used in health care, using specific review databases as well as PsycInfo, Embase and Medline. The trained authors conducted an overall assessment of quality for each test which was then verified by the editors. A total of 12% of the tests were rated at Level 1 ‘Low level of quality’, 61% at Level 2 ‘Some evidence of Quality’, 15% at level 3 ‘Good level of Quality’ and 12% at Level 4 ‘High level of quality’. This indicates that the evidence for the psychometric properties is insufficient for many tests used in the Nordic countries for this purpose
A MATHEMATICAL MODEL FOR THINNING RATE PREDICTION OF SHEET DOUBLE HYDRO-FORMING

Double sheet blank hydro-forming (DSBH) is a technology for forming hollow parts with complex shapes. The pair of workpieces is deformed and shaped by the high-pressure liquid inside. The material is thinned after hydraulic forming, which significantly affects the quality of the product, especially the fields with high requirements, such as the automotive and aerospace industry. The goal of optimizing input process parameters to ensure that the level of thinning into a product is within the allowable limit is posed by this study. This study considered blank holder force, forming fluid pressure, and relative thickness as candidate factors for optimization using Response Surface Method (RSM). The spherical parts were formed by the DSBH method of welding blank pairs of DC04 carbon steel material based on theoretical analysis, experiment solution, and experiment to verify the results. Experiments were performed with different combinations of parameters using the Box-Behnken design. This paper presented a mathematical model that helps determine material thinning rate according to these three process parameters in the hydro-forming of spherical parts from welded sheet metal pairs. The research results can be applied to control the input parameters in the DSBH to achieve the wall thickness of the spherical part as desired by the manufacturer.
Resolving spin currents and spin densities generated by charge-spin interconversion in systems with reduced crystal symmetry

The ability to control the generation of spins in arbitrary directions is a long-sought goal in spintronics. Charge to spin interconversion (CSI) phenomena depend strongly on symmetry. Systems with reduced crystal symmetry allow anisotropic CSI with unconventional components, where charge and spin currents and the spin polarization are not mutually perpendicular to each other. Here, we demonstrate experimentally that the CSI in graphene-WTe2 induces spins with components in all three spatial directions. By performing multi-terminal nonlocal spin precession experiments, with specific magnetic fields orientations, we discuss how to disentangle the CSI from the spin Hall and inverse spin galvanic effects.
Active Power Coordination Control for Wind and Energy Storage System

Wind turbines are the one of the important steps to reach carbon zero target for countries. Therefore, there have been huge investment for wind turbines for an onshore and offshore. Due to wind fluctuations, wind turbines are still defined as an intermittent power sources in literature. In order to improve the wind turbine penetration, mitigating negative effects and increasing benefits makes important contribution to support from grid operator and market players. In addition to this, energy storage integration to wind turbine can provide further support to mitigate the negative effects such as unforeseen wind speed as well as intermittency. This positive support increases the control of active power output. In this paper, the research on the energy storage integration to wind turbine system are conducted. As a case study, 4.2 MW output power wind turbine model is used with real time measured wind speed data which is gathered from in Turkey. Li-ion energy storage system (ESS) and its technical data from one real product is chosen in this study. All necessary operation is carried out on Python.
Ring-based forwarder selection to improve packet delivery in ultra-dense networks

This paper proposes a novel protocol-agnostic approach to optimize the performance of routing protocols in ultra-dense networks through a careful selection of the forwarders in a multi-hop transmission. In an ultra-dense wireless network, nodes have hundreds of neighbours, and existing routing protocols which require neighbourhood information are unable to operate efficiently. Using our method, each node wanting to transmit first selects forwarders that fall in a ring near the border of the communication range of the transmitting node, which makes up a subset of all the node's neighbours. This significantly reduces the number of nodes contending for the wireless channel yet ensures that there are sufficient forwarders to deliver packets successfully. We validate our approach using two routing schemes, one flooding and one unicast, augmented with our forwarder selection method and applied to an electromagnetic nanonetwork scenario as a novel incarnation of ultra-dense networks. Simulations using an enhanced propagation model show that our forwarder selection method drastically reduces the number of forwarders while still allowing packets to reach the intended destinations.
Toward redressing inequities through partnership: A critical assessment of an equity-focused partnership initiative

There is growing recognition of the potential for student-faculty/staff partnerships to attend to and redress inequities within postsecondary education. As a result, there are an increasing number of partnership initiatives and programs that foreground principles of equity and justice in their design and delivery. This article reports findings from research that assessed an equity-focused partnership initiative, piloted in 2019, at a research-intensive Canadian institution. We describe the distinctive features of the pilot, including our efforts to enhance equity in and through recruitment and support for student and faculty participants during the pilot, and report findings pertaining to outcomes, process indicators, and positionality and social location. The findings suggest tentatively positive outcomes for participants and contribute to existing scholarship by raising important complexities and limitations relating to issues of access, support, and scale of equity-focused partnerships.
Data Protection in Palmprint Recognition via Dynamic Random Invisible Watermark Embedding

Palmprint recognition is one of the most popular biometric technologies. Recent researches mainly focus on the recognition performance, while pay less attention to the data protection issues. In this paper, we propose an active biometric data protection model for securing palmprint images in transmission or storage scenarios, called Dynamic Random Invisible Watermark Embedding (DRIWE) model. The DRIWE model implicitly embeds a watermark in each original palmprint ROI image, and then separates the embedded watermark from the watermarked image before identification. If the separated watermark is consistent with the original watermark, it indicates that the image is trustworthy and can be used in the subsequent recognition process. Otherwise, it proves that the image has been illegally tampered with. Furthermore, a two-dimensional image information entropy loss is proposed to enhance the generalization of the model to different watermarks. It ensures that the model can always assign enough information to the host image (i.e., original palmprint image) when different watermarks are applied. Thus, it enables the separator to extract the complete watermark from the watermarked image. This greatly enhances the dynamics and randomness of the watermark embedding process and further improves the ability to secure the data. Adequate experiments are conducted on two benchmark palmprint databases. The results show that the proposed DRIWE model has satisfactory attack resistance and strong generalization ability: even if only one watermark is used in training stage, it can be generalized to a dozen of other new watermark images in the testing stage. In addition, the optimal accuracy of the watermarked data is only reduced by 0.07% compared with the original data.
A Phase Field Approach for a Modified Mumford-Shah Functional Based on Fractional Derivatives

Recovering the true image, or true signal, from a corrupted one is by no means a trivial task, and we will in this paper study some approaches to finding good approximations to this unknown true image. The main focus will be on a minimization method based on wavelet decompositions of images and finding a solution which is sparse with respect to the wavelet basis. We then argue that knowledge of the position of edges between objects in the image could be utilized with the aim to improve the edge preserving capabilities of the method. Therefore, we present an edge detection approach and a subsequent edge dependent weighting of the coefficients in the minimization method. If this method does in fact improve the appearance of the solution, we shall seek a more sophisticated and efficient approach. Borrowing a phase field approach used by Ambrosio and Tortorelli to approximate a solution to the Mumford–Shah functional, we construct a modified functional where the edge dependent weighting is found based on the phase field. After developing an alternating minimization method, we test the different approaches on a blurred image, and study the differences in the results.
Extending the theory of planned behaviour with application to renewable energy investment: the moderating effect of tax incentives

Purpose The purpose of this study is to deploy and expand the theory of planned behaviour (TPB) model with application to renewable energy investment by incorporating the component of tax incentives (TIN). This will serve as an additional measure in understanding the conventional energy stakeholders’ investment intention into renewable energy in Nigeria. Design/methodology/approach Data was collected from 357 individual key conventional energy stakeholders in Nigeria using survey questionnaires. The research model was tested using structural equation modelling. Findings The results from the study revealed the applicability of the TPB in predicting the conventional energy stakeholders’ investment intention into renewable energy. The result indicates that attitude and subjective norm are significantly associated with investment intentions. Research limitations/implications The outcome implies that the integration of tax incentives can improve the predictive power of the model as the introduced variable demonstrates a significant impact on the conventional energy stakeholders’ investment intention into renewable energy. Practical implications This study extends on the well-established TPB model by integrating tax incentives in understanding investment intentions and the outcome implies a significant association of tax incentives with investment intention and moderated the influence of attitude and subjective norm over the conventional energy stakeholders’ investment intention. Originality/value TPB has been widely deployed and even extended to predict intention in numerous fields of study. Available literature presents the lack of such empirical research that focuses on investment in Nigeria and specifically regarding energy investment. The outcome highlighted the significant influence of tax incentives, thus the need for policymakers to suggest and implement various tax incentives to attract private investment into renewable energy for electricity generation that will consequently assist in achieving SDG-7 and mitigate climate change.
The Application of Social Media into Moodle for Teaching Writing Skills to Non-English Major Students at Dong Nai Technology University

Social media tools are a new type of media with a variety of properties and characteristics. Today, the use of social media is increasing at an alarming rate. Students can digitally meet up with their peers and teachers in this realm. They are able to discuss important topics that are connected to their learning process. This study aimed to see how social media tools in Moodle affected English writing skills in narrative paragraphs and whether social media tools in Moodle may help enhance English writing skills in the narrative paragraph. The current study used a mixed-method strategy that included quantitative and qualitative methodologies such as interviews and questionnaires, as well as an experimental research method. To investigate the impact of using social media platforms on boosting students’ writing, pre-and post-tests were used to assess students’ performance before and after the experiment. The three instruments, the questionnaire, the interview, and the quasi-experiment (pre-post-test), revealed how Moodle’s social media facilities affect students’ English writing skills. Using social media features in Moodle helped students improve their writing skills and enhanced their motivation when creating recount narratives. As a result of this research, it is recommended that social media be integrated into Dong Nai Technology University to increase the students’ other skills dramatically.
Ceramic Additive Manufactured Monolithic X-Shaped TM Dual-Mode Filter

This paper presents a monolithic 3D-printed ceramic X-shaped dual-mode microwave filter. The filter is manufactured utilizing a lithography-based ceramic manufacturing (LCM) process, allowing the realization of the resonator as well as the housing in one single piece. Therefore, contact as well as alignment problems, usually arising between a ceramic in $TM$ mode operation and a metallic enclosure, can conveniently be avoided. A fourth order dual-mode filter with a designed center frequency of 6 GHz and a bandwidth of 279 MHz is realized in alumina material. Practical design rules to be considered in the filter layout process as well as limitations imposed by the LCM approach are discussed. The outer surface of the ceramic cavity is subsequently metallized using a silver spray-coating. Advantageously, the metallization is only a few micrometers thick, wherefore the weight of the component can be reduced. The measurement results are compared to the simulation and reveal good agreement. A temperature stability measurement shows a center frequency downward shift of 0.22%.