Miracle-dz/UniFAR-FTUs huggingface dataset:
Room and Cryogenic Temperature Behaviour of Magnetic Sensors Based on Gan/Si Single Saw Resonators

This work analyzes resonance frequency shift vs. the applied magnetic field strength for GHz operating GaN/Si SAW single resonators. Magnetostrictive elements (Ni and CoFeB) were deposited in the proximity of the interdigitated transducers (IDTs) of the resonators (A-type structures) and also over the IDTs, after covering them with a BCB layer to avoid short circuits with IDTs metal (B-type structures). This work targets emerging applications of SAW resonators in driving spin wave pumping and in coupling of surface acoustic waves (SAW) with superconducting Q-bits. Magnetic sensitivity of the SAWs was analyzed at room temperature (RT) and at cryogenic temperatures, obtaining high magnetic sensitivities at 16 K. According to our knowledge, GaN based SAWs are first time used in magnetic applications; also, cryogenic behavior of magnetic SAW sensors is first time analyzed.
A Novel Loop Closure Detection Method Using Line Features

Loop closure detection is a significant requirement for simultaneous localization and mapping (SLAM) to recognize revisited place. This paper presents a novel line-based loop closure detection method for vision-based SLAM that allows reliable loop closure detections, especial under structural environment. The performance of coping with perceptual aliasing conditions is more competitive than point based methods. The bag of words model is extended in this work which uses only line features. A variant of TF-IDF (term frequency & inverse document frequency) scoring scheme is proposed by adding a discrimination coefficient to improve the discrimination of image similarity scores, further to reinforce the similarity evaluation of two images. LBD (Line Band Descriptor) and binary LBD features are extracted to build visual vocabularies. Temporal consistency and spatial continuity checks enhance detection reliability. The performance of proposed scoring scheme was compared with original TF-IDF, results show that our proposed scheme has competitive discrimination ability. We also compared the query performance of our vocabularies with ORB-based, MSLD (mean standard-deviation line descriptor)-based, and PL (Point-and-Line)-based vocabularies, results indicate that our vocabularies obtain the highest successful retrieval rate. The performance of the whole loop closure detection algorithm was also evaluated in terms of precision, recall and efficiency, which were compared with ORB, MSLD, PL-based methods, and also with CNN-based method, results demonstrate that our method is superior to others with satisfactory precision and efficiency.
Spatial relations of slums: size of slum clusters

More than half of the world’s population currently lives in cities. In many parts of the world, slums are part of the urban landscape. Despite different history, cultures and continents, slums share common properties. This allows for abstraction and modelling. In this context, the objective of this paper is, to gain insight into the intraurban pattern of slums. Therefore spatial relations, i.e. the cluster tendency of slums, in Dhaka (Bangladesh) and Rio de Janeiro (Brasil) are analysed on different length scales and compared. It is found that the length scale of the analysis has a huge influence on the form of the spatial relationship. On the city scale slums are clustered, while on smaller scales there is a relatively large variation in spatial relationships with predominantly random distribution. It is observed that there is a scale where the large variations of the spatial relationships vanish in a sharp transition. This scale is interpreted as a characteristic size of slum clusters, which has implications for understanding the emergence of slums and urban modelling.
Development of Teaching Material Using an Android

The purpose of this study was to develop Android-based teaching materials, which have qualities (valid, practical and effective) that can help to improve the quality of student learning outcomes and to motivate students to learn. The process of developing this material used the Plomp development model, which consists of a preliminary investigation phase, a design phase, a realisation/construction phase, a test, evaluation and revision phase and an implementation phase. To assess the quality of the learning device, the validity of the validator of experts was, then, tested in order to ensure that the teaching material is valid, practical and effective.
Lean internationalisation of high-tech firms

This study examines the internationalisation of high-tech start-up firms (HSFs) from small and open economies (SMOPECs). It explores how HSFs may differ in their speed of internationalisation relying on information collected via interviews with the CEOs or founders of 32 HSFs that operate internationally. It uses a comparative cross-national multiple-case study research design to answer the research questions. The findings provide the basis for developing propositions for further comparative analyses of the early and fast internationalisation of HSFs based in emerging and developed markets. The study contributes to the literature on networks, internationalisation and international entrepreneurship.
Detailed Balance Efficiency of 1310 nm Multijunction Photonic Power Converters

We present modeled detailed balance efficiency of multijunction photonic power converters operating at 1310 nm at a laser intensity of 5.88× 105 W/m2, corresponding to our test laser power and cell size, in two scenarios: (1) with an absorbing substrate and (2) with a perfect specular back reflector. We show that, in the radiative limit, efficiency increases as a function of number of junctions in the case of an absorbing substrate. In this case, efficiency can reach as high as 69% with 15 junctions. In the case of a perfect specular back reflector, efficiency reaches more than 75% and is not sensitive to the number of junctions. This insensitivity allows freedom in future device design.
Thermal behavior and its seasonal and diurnal variability of urban green infrastructure in a mid-latitude city - Berlin

Land surface temperature (LST) is a key variable in characterizing the surface energy and water balance at the land surface-atmosphere interface [1], [2]. Vegetation reduces the LST by providing shade and absorbing radiation energy via transpiration and photosynthesis [3], [4]. A review of research on urban green spaces recommended that future research should incorporate functional, structural, and configurational parameters of urban vegetation in order to more fully assess the thermal effect of green spaces [5]. This study aims to fill this research gap by considering satellite-derived LST (Landsat 8), biotope types and 3D vegetation data in a study of LST across diurnal and seasonal temporal scales in a mid-latitude city (Berlin). Four cloud-free Landsat 8 scenes representing each season were analyzed. Day and night summer scenes with comparable air temperatures were used to assess the day/ night difference in LST. Kruskall-Wallis tests and Dunn’s post-hoc tests were applied to assess the significance of difference between LST of biotope classes and subclasses. Overall, LST varied significantly between the majority of biotope classes and subclasses. The relative coolness of each biotope class differed based on the season. The lowest and highest day/night LST variation could be noted for water biotope classes and dwarf shrub heaths, respectively. Vegetation height was significantly negatively correlated with LST (p-value<0.001) for all day scenes. Our results contribute to an enhanced understanding of how biotope types influence LST in an urban environment, which will be vital to urban planning in light of climate change.
The dual-process theory and understanding of stocks and flows

Recent evidence suggests that using the analytic mode of thinking (System 2) can improve people's performance in stock–flow (SF) tasks. In this paper, we further investigate the effects by implementing several different interventions in two studies. First, we replicate a previous finding that answering analytical questions before the SF task approximately doubles the likelihood of answering the stock questions correctly. We also investigate effects of three other interventions that can potentially prime participants to use their System 2. Specifically, the first group is asked to justify their response to the SF task; the second group is warned about the difficulty of the SF task; and the third group is offered information about cognitive biases and the role of the analytic mode of thinking. We find that the second group showed a statistically significant improvement in their performance. We claim that there are simple interventions that can modestly improve people's response in SF tasks. Copyright © 2017 System Dynamics Society.
Low Frequency Sound Pressure Level Improvement of Piezoelectric Mems Microspeaker Using Novel Spiral Spring with Dual Electrode

Extending the approach in the previous work [1], this study presents a piezoelectric actuation MEMS microspeaker with novel spring design to achieve high sound pressure level (SPL) at low frequencies for in-ear applications. The soft PZT/Si unimorph springs enable larger out-of-plane displacement to enhance SPL. With the proposed spiral-spring design, longer spring length (compared with [1]) and lower resonant frequency are achieved to improve SPL at low frequencies. Moreover, the spiral spring has simple stress distribution during actuation to ease electrical routings and also increase the net driving output for piezoelectric films, thus the dual driving electrodes to increases diaphragm out-of-plane displacement and SPL is achieved. Measurements demonstrate 79.5dB SPL (72.6dB SPL for [1]) with only 2Vpp driving voltage and 1mm2 diaphragm area at 1kHz in a 3cm long canal. Furthermore, 106.8dB SPL is observed with 15Vpp at 1.85kHz without any structure damage.
Hand Gesture Recognition for Sign Language Transcription

Sign Language is a language which allows mute people to communicate. The ease of communication offered by this language, however, disappears when one of the interlocutors, who may or not be mute, does not know Sign Language and a conversation starts using that language. In this document, I discuss research efforts that resulted in a system that takes advantage of Convolutional Neural Networks to recognize hand letter and number gestures from American Sign Language based on depth images captured by the Kinect camera. As a byproduct of these research efforts, I created a new dataset which consists of depth images of American Sign Language letters and numbers, I conducted an empirical assessment and I compared the presented method for image recognition against a similar dataset but for Vietnamese Sign Language. Finally, I present how this work supports my ideas for the future work on a complete system for Sign Language transcription.
Performance Analysis and Operating Limits of a Dual-Inverter Open-Winding IPMSM Drive

Operating capabilities of a dual-inverter open-winding interior permanent magnet synchronous motor (IPMSM) drive are investigated and compared with those of a conventional single-inverter drive in maximum torque per ampere (MTPA) and field-weakening (FW) regions. To predict the performance and operating limits of the drive systems with improved accuracy, the impact of saturation on inductances and permanent magnet (PM) flux linkage values are taken into account, and core, copper, friction and windage, and solid losses are considered in a wide speed range. Performance prediction is conducted using machine's electromagnetic parameters and losses that are obtained via finite element analysis, coupled with an optimization algorithm to find optimal operating points in MTPA and FW regions. The analytical findings are further validated against experimental results obtained from a 1-kW dual-inverter IPMSM motor drive.
Evaluating the use of augmented reality in learning portfolios for different team roles

Increasingly augmented reality becomes an integrated component of modern learning environments. This paper builds on previous work to focus on the evaluation of how augmented reality and in particular the use of an Optical Head Mounted Display (OHMD) for the creation of learning portfolios. Emphasis is given on the evaluation of the use of such tools for different learning activities. The paper provides an in depth analysis of how the technology is evaluated by using Belbin’s team role theory for classifying participants’ responses. The paper’s final contribution is in the form of a discussion of a range of issues associated with privacy and security of personal information collected with the use of OHMD in learning environments.
Preparation, Optimization, and Evaluation of Hyaluronic Acid-Based Hydrogel Loaded with Miconazole Self-Nanoemulsion for the Treatment of Oral Thrush

Miconazole nitrate (MZ) is a BCS class II antifungal poorly water-soluble drug with limited dissolution properties and gastrointestinal side effects. Self-nanoemulsifying delivery system-based gel of MZ can improve both solubility and oral mucosal absorption with enhanced antifungal activity. The study aims to formulate MZ self-nanoemulsion (MZ-NE) and combine it within hyaluronic acid-based gel. MZ solubility in various oils, surfactants, and cosurfactant used in NE formulations were evaluated. Mixture design was implemented to optimize the levels of NE components as a formulation variable to study their effects on the mean globule size and antifungal inhibition zones. Further, the optimized MZ-NE was loaded into a hyaluronic acid gel base. Rheological behavior of the prepared gel was assessed. Ex vivo permeability of optimized formulation across buccal mucous of sheep and inhibition against Candida albicans were examined. Mixture design was used to optimize the composition of MZ-NE formulation as 22, 67, and 10% for clove oil, Labrasol, and propylene glycol, respectively. The optimized formulation indicated globule size of 113 nm with 29 mm inhibition zone. Pseudoplastic flow with thixotropic behavior was observed, which is desirable for oral gels. The optimized formulation exhibited higher ex vivo skin permeability and enhanced antifungal activity by 1.85 and 2.179, respectively, compared to MZ-SNEDDS, and by 1.52 and 1.72 folds, respectively, compared to marketed gel. Optimized MZ-NE hyaluronic acid-based oral gel demonstrated better antifungal activity, indicating its potential in oral thrush pharmacotherapy.
Region-Based Nonparametric Model for Interactive Image Segmentation

In this paper, we present a novel framework for interactive segmentation problems. It integrates a nonparametric model into the Conditional Random Field (CRF) framework, which can effectively combine high-level features with low-level features to represent image information. In the nonparametric model, multiple region layers are used to estimate data likelihood terms to overcome the bad regions generated by unsupervised methods. The likelihood values of each layer are calculated separately to reduce the computational cost. In addition, we analyze that the pixel layer has little effect on data estimation, so we remove it to further reduce the complexity of the algorithm. We employ the label consistency between pixels and their corresponding regions in smooth term estimation, which can be regard as a higher order potential for pixels. The data term and the smooth term are then performed together in Conditional Random Fields (CRFs) as a fine-tuning of the results. Experimental results show that the proposed method can segment images efficiently and accurately with fewer user inputs.
How Student Information System Influence Students’ Trust and Satisfaction Towards the University?: An Empirical Study in a Multicultural Environment

The Student Information System (SIS) has increasingly gained popularity among universities for various reasons. However, evaluating student’s trust and satisfaction of the system are not fully investigated. In this research, a sample of 634 students participated in the study from Cyprus International University, Cyprus. The Structural Equation Modelling (SEM) technique was employed with AMOS 23 software to identify the trust and satisfaction of students’ SIS usage. The study model, which include subjective norm, image, output quality, result demonstrability, perceived usefulness, perceived ease of use, trust and satisfaction, was developed based on extended Technology Acceptance Model (TAM II). Results obtained from the analysis indicated that image, output quality, result demonstrability and perceived ease of use had a significant impact on perceived usefulness. Trust was found to be significantly correlated with satisfaction; however, subjective norm, Perceived usefulness and perceived ease of use did not have a significant influence on satisfaction. Furthermore, the finding confirmed that several constructs in the TAM II that were important in previous studies were not significant in the SIS. The students’ behavior aspects are essential for the effective use of the system. It provides valuable information for university management in understanding the challenges of student’s trust and satisfaction about SIS usage.
Comparison of Current Control Strategies Based on FCS-MPC and D-PI-PWM Control for Actively Damped VSCs With LCL-Filters

This paper presents a comparative study of the proportional-integral-based (PI-based) synchronous current control strategy with derivative-feedback-based active damping and the finite-control-set model-predictive-control-based (FCS-MPC-based) synchronous current control strategy with cost-function-based active damping. For a fair comparison, the sensor requirement and the average switching frequency of FCS-MPC are made equivalent to that of the pulse-width-modulation-based counterpart through internal model estimation and control sampling frequency adjustment. The comparative study considers gain/weighting-factor tuning, delay compensation, switching harmonics, and active damping performance at the critical frequency operating point. The overall performance of both schemes is validated through the same experimental setup and test scenarios. The results conclude that the emerging FCS-MPC has the potential to produce similar results as the classical PI-based counterpart while carrying some practical features. These include being intuitive in active damping design and tuning, guaranteeing fast dynamics, and being sufficiently robust to grid impedance shifting. These findings essentially justify the potential of model predictive control being a viable alternative for this area of application.
Prototyping and Load Balancing the Service Based Architecture of 5G Core Using NFV

3GPP has chosen Service Based Architecture (SBA) for 5G Core (5GC). In this work, we build a prototype of SBA of 5GC from scratch using open source tools in Network Functions Virtualization (NFV) environment. In SBA, Network Functions (NFs) are designed to expose capabilities to consumers with interfaces, called Service Based Interface (SBI). To reduce the latency and the load on NFs, we use gRPC, a modern open-source Remote Procedure Call (RPC) framework, instead of REST for implementing SBI. We present a distributed service registration and discovery framework for 5GC using a software solution named Consul. We then propose usage of a Look Aside Load Balancer (LALB) for load balancing multiple NFs of 5GC. The control plane latency is reduced by routing traffic across multiple instances of Access and Mobility Management Function (AMF) via an LALB. Experimental results suggest that carefully chosen load balancing algorithms can significantly lessen the control plane latency when compared to simple random or round-robin schemes.
Patient Radiation Risks during CT Brain procedure in Moroccan hospitals

Computed Tomography (CT) of Brain is a diagnostic device used to create detailed pictures of the skull, brain, paranasal sinuses, and eye sockets; however, patients are exposed to great radiation doses and the likelihood of a cancer occurrence and other biological effects is increased. The objectives of this study were to measure the patient radiation dose during a brain CT procedure and to assess the radiation dose and biological effects.The study was conducted in six radiology departments equipped with various CT machines calibrated according to international protocols. A total of 180 patients underwent brain examinations. The effective radiation dose, cancer and biological risks were estimated using the International Commission on Radiological Protection (ICRP) conversion factors.The effective dose for Brain CT procedure in Moroccan hospital varied between (0,80± 0,12) and (5,47± 1,51) mSv with an average value of (2,96± 0,67) mSv. The cancer risk per Brain procedure ranged between 44 and 301 with an average value of 163 per 1 million procedures. The hereditary risk per Brain procedure ranged between 2 and 11 with an average value of 6 per 1 million procedures. The effective dose and risk factors for brain CT scan examination are higher than the national averages for one third of our hospitals.The cancer and hereditary risks are significant during multiple image acquisition. The study revealed that 66% of the procedures with normal findings. However, staff should optimize the radiation dose during Brain procedures.
Impact of Autonomous Vehicles in Cities: User Perception

Autonomous driving is a very important topic aiming on changing mobility in smart cities. A lot of research has been dedicated to development of vehicles without drivers and quite many tests and real world demonstrations have been reported especially in the last years. The first expectations were very optimistic. Researchers as well as general public expected high positive influence in the congestions, travel time and other mobility aspects. However, the latest research questions these purely positive expectations and suggest that autonomous driving might have positive or negative effect based on city policies in place.In order to gain a better understanding about the current expectations of general public about the impact of autonomous driving, a survey has been conducted as part of a European project MAVEN. This paper provides a short description of the survey design and then summarizes the main findings and results of this survey. The results can get us a better way to understand the feeling of citizens about autonomous vehicles and the transition to full automated cities.The results confirmed the general trends and at the same time gave us more insight into the special questions related to MAVEN use cases. These findings will be further validated in simulation experiments.
Learning geometric soft constraints for multi-view instance matching across street-level panoramas

We present a new approach for matching tree instances across multiple street-view panorama images for the ultimate goal of city-scale street-tree mapping with high positioning accuracy. What makes this task challenging is the strong change in view-point, different lighting conditions, high similarity of neighboring trees, and variability in scale. We propose to turn (tree) instance matching into a learning task, where image-appearance and geometric relationships between views fruitfully interact. Our approach constructs a Siamese convolutional neural network that learns to match two views of the same tree given many candidate tree image cut-outs and geographic information of the two panorama images. In addition to image features, we propose utilizing location information about the camera and the tree. Our method is compared to existing patch matching methods to prove its edge over state-of-the-art. This takes us one step closer to the ultimate goal of city-wide tree mapping based solely on panorama imagery to benefit city administration.