Miracle-dz/UniFAR-FTUs huggingface dataset:
SYNTHESIS OF WIDEBAND RECONFIGURABLE ARRAY ANTENNAS FOR MONOPULSE RADAR APPLICATIONS

A new approach to the bandwidth maximization of reconfigurable antenna arrays for monopulse radar applications is proposed and tested. The provided radiating systems allow switching the radiation behavior from sum to difference patterns (and vice versa) while sharing the excitation amplitudes of a user-decided set of radiating elements. Furthermore, the proposed design procedure guarantees the maximum possible bandwidth performance once the overall antenna size, the desired beamwidth, sidelobe level, and slope in the target direction of the generated power patterns are fixed. The synthesis problem is cast and solved as a sequence of convex programming optimizations, and hence the maximization of performances is attained with advantages in terms of computational times as well as convergence to the global optimum. The given theory is supported by numerical experiments including arrays with ultra-wideband performances.
Parent-child nonverbal engagement during read versus sung book-sharing in preschoolers with and without ASD

Providing natural opportunities that scaffold interpersonal engagement is important for supporting social interactions for young children with autism spectrum disorder (ASD). Musical activities are often motivating, familiar, and predictable, and may support both children and their interaction partners by providing opportunities for shared social engagement. We assessed multiple facets of nonverbal social engagement—child and caregiver visual attention and interpersonal movement coordination—during musical (song) and non-musical (picture) book-sharing contexts in caregiver–child dyads of preschoolers with (n = 13) and without (n = 16) ASD. Overall, children with ASD demonstrated reduced visual attention during the book sharing activity, as well as reduced movement coordination with their caregivers, compared to children with typical development. Children in both diagnostic groups, as well as caregivers, demonstrated greater visual attention (gaze toward the activity and/or social partner) during song books compared to picture books. Visual attention behavior was correlated between children and caregivers in the ASD group but only in the song book condition. Findings highlight the importance of considering how musical contexts impact the behavior of both partners in the interaction. Musical activities may support social engagement by modulating the behavior of both children and caregivers.
Variation in cone, seed, and kernel nutritional components traits of Pinus koraiensis

Abstract Pinus koraiensis Sieb. et Zucc. (Korean pine) is an evergreen coniferous tree species with significant therapeutic and nutritional value in northeastern China. To assess variation and select highly productive and nutritionally valuable materials, 25 cone, seed, and kernel nutritional components traits were measured and analyzed. Coefficients of variation for phenotypic traits ranged from 6.32 % to 161.51 %, and the coefficients of most traits were approximately 10 %. Most traits showed significant or extremely significant differences among clones or groups, especially for amino acid content. Cone numbers were under moderate genetic control, and their repeated ability ranged from 0.42 to 0.53. Most other traits were under high genetic control, and their repeated ability was higher than 0.70. Despite the weak correlation with seed traits, cone number had strong correlations with other characters. Four principal components were obtained with a cumulative variance contribution of 93.51 %. The selected elite material will provide a theoretical basis for selection and breeding of P. koraiensis.
DECLARATION OF THESIS / UNDERGRADUATE PROJECT PAPER AND COPYRIGHT

This research presents an educational software interface tool for undergraduate level in microwave field. The CAD, particularly for the planar waveguides are developed using Agilent VEE software and built-in MATLAB commands. It allows the visualization of electromagnetic propagation phenomena for various types of planar waveguides. The interface allow student to define the parameters associated with a study and to run real-time simulations on the computer. The simulations will give real time graphs for properties of the waveguides. The simulation results are compared with the available literature data.
Integrative Comparison of Burrows-Wheeler Transform-Based Mapping Algorithm with de Bruijn Graph for Identification of Lung/Liver Cancer-Specific Gene

Cancers of the lung and liver are the top 10 leading causes of cancer death worldwide. Thus, it is essential to identify the genes specifically expressed in these two cancer types to develop new therapeutics. Although many messenger RNA (mRNA) sequencing data related to these cancer cells are available due to the advancement of next-generation sequencing (NGS) technologies, optimized data processing methods need to be developed to identify the novel cancer-specific genes. Here, we conducted an analytical comparison between Bowtie2, a Burrows-Wheeler transform-based alignment tool, and Kallisto, which adopts pseudo alignment based on a transcriptome de Bruijn graph using mRNA sequencing data on normal cells and lung/liver cancer tissues. Before using cancer data, simulated mRNA sequencing reads were generated, and the high Transcripts Per Million (TPM) values were compared. mRNA sequencing reads data on lung/liver cancer cells were also extracted and quantified. While Kallisto could directly give the output in TPM values, Bowtie2 provided the counts. Thus, TPM values were calculated by processing the Sequence Alignment Map (SAM) file in R using package Rsubread and subsequently in python. The analysis of the simulated sequencing data revealed that Kallisto could detect more transcripts and had a higher overlap over Bowtie2. The evaluation of these two data processing methods using the known lung cancer biomarkers concludes that in standard settings without any dedicated quality control, Kallisto is more effective at producing faster and more accurate results than Bowtie2. Such conclusions were also drawn and confirmed with the known biomarkers specific to liver cancer.
Integrating Domain Knowledge into Deep Learning for Skin Lesion Risk Prioritization to Assist Teledermatology Referral

Teledermatology has developed rapidly in recent years and is nowadays an essential tool for early diagnosis. In this work, we aim to improve existing Teledermatology processes for skin lesion diagnosis by developing a deep learning approach for risk prioritization with a dataset of retrospective data from referral requests of the Portuguese National Health System. Given the high complexity of this task, we propose a new prioritization pipeline guided and inspired by domain knowledge. We explored automatic lesion segmentation and tested different learning schemes, namely hierarchical classification and curriculum learning approaches, optionally including additional patient metadata. The final priority level prediction can then be obtained by combining predicted diagnosis and a baseline priority level accounting for explicit expert knowledge. In both the differential diagnosis and prioritization branches, lesion segmentation with 30% tolerance for contextual information was shown to improve classification when compared with a flat baseline model trained on original images; furthermore, the addition of patient information was not beneficial for most experiments. Curriculum learning delivered better results than a flat or hierarchical approach. The combination of diagnosis information and a knowledge map, created in collaboration with dermatologists, together with the priority achieved interesting results (best macro F1 of 43.93% for a validated test set), paving the way for new data-centric and knowledge-driven approaches.
Nanomaterial by Sol-Gel Method: Synthesis and Application

The sol-gel process is a more chemical method (wet chemical method) for the synthesis of various nanostructures, especially metal oxide nanoparticles. In this method, the molecular precursor (usually metal alkoxide) is dissolved in water or alcohol and converted to gel by heating and stirring by hydrolysis/alcoholysis. Since the gel obtained from the hydrolysis/alcoholysis process is wet or damp, it should be dried using appropriate methods depending on the desired properties and application of the gel. For example, if it is an alcoholic solution, the drying process is done by burning alcohol. After the drying stage, the produced gels are powdered and then calcined. The sol-gel method is a cost-effective method and due to the low reaction temperature there is good control over the chemical composition of the products. The sol-gel method can be used in the process of making ceramics as a molding material and can be used as an intermediate between thin films of metal oxides in various applications. The materials obtained from the sol-gel method are used in various optical, electronic, energy, surface engineering, biosensors, and pharmaceutical and separation technologies (such as chromatography). The sol-gel method is a conventional and industrial method for the synthesis of nanoparticles with different chemical composition. The basis of the sol-gel method is the production of a homogeneous sol from the precursors and its conversion into a gel. The solvent in the gel is then removed from the gel structure and the remaining gel is dried. The properties of the dried gel depend significantly on the drying method. In other words, the “removing solvent method” is selected according to the application in which the gel will be used. Dried gels in various ways are used in industries such as surface coating, building insulation, and the production of special clothing. It is worth mentioning that, by grinding the gel by special mills, it is possible to achieve nanoparticles.
Understanding the Importance of Sexual Consent among University Students

The knowledge about how young people understand sexual consent remains scant. This study aimed to understand how the university students perceived sexual consent and the importance of consent before engaging in sexual related activities with a partner. Using explanatory sequential mixed method approach, an in-depth interview was conducted to five participants following administration of survey questionnaire to obtain a general view on the issues around sexual consent. 102 active university students at the age between 18-25 years old participated in this study. The result of the questionnaire-survey was analysed with descriptive analysis and the in-depth interview data were transcribed and were analysed using the Interpretative Phenomenology Analysis (IPA). Integration of data was done to find pattern and relation between quantitative and qualitative data. Findings from this study suggest that young people, both young men and women, perceived sexual consent as important and, therefore, should be obtained before engaging in any sexual contact. While gesture and direct communication were the common techniques on communicating consent between genders, there were still difficulties in conveying the message of consent because of the subjective feeling and norms of the society.
Differential Private Motion Sensor and Wasted Energy in Building Energy Management System

Building energy management system (BEMS) uses various sensors and smart meters to detect power consumption and user movement within buildings. By applying data integration, raw BEMS data can be employed for multiple purposes. For example, power consumption data can be matched with motion sensor data and electric appliance details in any staff room to calculate wasted energy and continually predict an individual electric appliance status. Therefore, disclosing these data severely violates local electricity users’ privacy. To resolve data privacy concerns using differential privacy, the traditional Laplacian mechanism cannot be used to detect overloads and the standard coin-flipping algorithm gives a high percentage error of wasted energy calculation. Thus, this paper proposes a modified truncated Laplacian noise addition and random motion state processes to hide the actual electrical use and movement patterns. Based on a 30-day sample period of actual BEMS, both privacy and usability of the proposed processes have been compared with the traditional methods in terms of the privacy loss parameter, the reported error of energy consumption, the correctness of overload detection, and the error of the wasted energy calculation. Based on the obtainable effectiveness, these proposed processes are recommended for further extension to implement at BEMS data gateways in real-time.
Micro-electromechanical systems-based microspectrometers covering wavelengths from 1500nm to 5000nm

There is an increasing need for infrared spectroscopic instrumentation that is low-cost and extremely robust for applications in agriculture, environmental monitoring, food science and medicine. This paper describes a MEMS-based tunable Fabry-Perot filter that can be directly integrated on a detector. The fabrication process is detector independent, and has been demonstrated on Si as well as one of the most unforgiving detector material systems, HgCdTe. Results are presented that show that the technology is applicable for coverage of a wide spectral range, with examples of tuning from ~1600nm to ~2300nm and ~3800nm to ~4800nm using voltages <20V with line widths < 100nm and tuning speeds of 50kHz. Modeling shows that the device should be stable to shocks up to 250G. Line widths and tuning speeds can be significantly improved using different actuator designs and removal of squeezed-film damping effects. The process uses a maximum process temperature of 125°C, and is therefore compatible with a wide range of detector materials including Si, Ge, InGaAs, InSb, as well as more specialized detector materials such as InAs quantum dots and InAs/GaSb superlattices. Work is currently underway to demonstrate application of microspectrometers fabricated using this technology in real-time testing of soils for agricultural applications.
A novel signal restoration method in the frequency domain to enhance spatial resolution in distributed Brillouin sensing

This article demonstrates how spatial resolution of distributed Brillouin sensing systems can be significantly enhanced by measuring the spatially resolved Brillouin gain spectra of an optical fiber in the frequency domain. We employ a novel signal processing method to overcome the known problem of spectral broadening that occurs at centimeter-range spatial resolutions. The method is based on an analytical description of stimulated Brillouin scattering in optical fibers for the case of harmonically modulated optical signals. From this analysis, the artifacts that degrade the measurement resolution were modeled; for the first time to our knowledge, undegraded gain spectra could be restored by means of deconvolution techniques adopted from digital image processing.
Can a mat sensor algorithm identify mobility challenges in older adults getting out of bed

Falls are a major source of morbidity and mortality in older adults. Reducing their frequency could lead to significant improvements in quality of life of older adults, and reduce health care expenditures. The TAFETA (Technology Assisted Friendly Environment for the Third Age) program of research has been using a pressure sensitive mat to develop an unobtrusive home monitoring system to analyse the quality of transfers in older adults. In this study, the goal was to assess whether the mat could help differentiate between older adults with normal mobility versus those with mobility challenges.
The dielectric properties of the diamond-like films grown by ion-plasma method

Diamond-like films was deposited by ion-plasma method in impulse mode. The dielectric properties of the diamond-like films in the frequency of 10−1 – 106 Hz at room temperature were studied. The dispersion of the dielectric parameters indicates the existence of non-Debye relaxation mechanism correlates with structural changes. The charge transfer is temperature activated hopping process.
Range Finding and Fault Locating with Chaotic Signal

In this paper, we review our recent works on range finding and fault locating in optical network and wire with chaotic signal. Using a distributed-feedback semiconductor laser with optical feedback as chaotic source, we developed a prototype chaotic optical time domain reflectometer which can achieve a range- independent resolution of 4cm and measurable distance of about 70km. We further present the measurement of faults in the wavelength-division-multiplexing passive optical network (WDM-PON) by using a wavelength-tunable chaotic laser. Moreover, we also demonstrate the location of wire faults or impedance discontinuities with chaotic signal. Our results show that the fault location using wideband chaotic signal is a promising method of precise diagnoses for WDM-PON and electric cables.
Optimal control of a single-basin tidal power scheme in various operating modes

Abstract Operation of a tidal power scheme in ebb generation and double generation modes with or without pumping is described. Dynamic programming is used to formulate the control of the scheme to maximize its energy output when operated in any of these modes: in the formulation hydrodynamic effects within the scheme are neglected but real turbine characteristics are used. Optimal control was found to be unnecessary for ebb generation, but it is essential if the scheme is to be operated in any other mode.
Rescheduling with controllable processing times for number of disrupted jobs and manufacturing cost objectives

We consider a machine rescheduling problem that arises when a disruption such as machine breakdown occurs to a given schedule. Machine unavailability due to a breakdown requires repairing the schedule as the original schedule becomes infeasible. When repairing a disrupted schedule a desirable goal is to complete each disrupted job on time, i.e. not later than the planned completion time in the original schedule. We consider the case where processing times of jobs are controllable and compressing the processing time of a job requires extra processing cost. Usually, there exists a nonlinear relation between the processing time and manufacturing cost. We solve a bicriteria rescheduling problem that trades off the number of on-time jobs and manufacturing cost objectives. We give a mixed-integer second-order cone programming formulation for the problem. We develop a heuristic search algorithm to generate efficient solutions for the problem. Heuristic algorithm searches solution space by moving and swapping jobs among machines. We develop cost change estimates for job moves and swaps so that the heuristic implements only promising moves and hence generates a set of efficient solutions in reasonably short CPU times.
Real‐time automated segmentation of breast lesions using CNN‐based deep learning paradigm: Investigation on mammogram and ultrasound

The existing studies involving single imaging modalities (i.e., mammogram (MG) or ultrasound (US)) to detect breast lesions have demonstrated limited clinical application because radiologists rarely interpret an MG without a corresponding US and vice‐versa. Thus, this article aims to develop a Computer Aided Segmentation (CAS) system for detecting breast lesions in both MG and US. A customized convolutional neural network (CNN) is adopted for this purpose. A new real‐time bi‐modal database of MG and US is used for dual‐modality evaluation. Twelve performance measures, five shape measurements, area under receiver operating characteristics (ROC), and paired T‐test are used to assess the performance of proposed CAS system. A Dice Similarity Coefficient (DSC) of 0.64 (for MG) and 0.77 (for US) and Jaccard Index (JI) of 0.53 (for MG) and 0.64 (for US) indicate that the US can be used as an adjunct technique to MG in the segmenting breast lesions.
The architecture of teamwork: examining relationships between teaching, assessment, student learning and satisfaction with creative design outcomes

Student satisfaction with teamwork experiences is important for two interrelated reasons. First, students learn about teamwork more effectively when they view their teamwork learning experience more positively. Second, their satisfaction with prior teamwork learning has an impact on future teamwork learning – because team effectiveness is influenced by attitudes and motivations to teamwork shaped by past experience. This paper draws on data collected from almost 196 students at 4 Australian universities. It considers the relationships between architecture students' satisfaction with two dimensions of teamwork – its processes and its outcomes – and five pedagogic factors that teachers can control: team size, assessment, team formation, the teaching of teamwork skills and knowledge, and feedback on teamwork skills and processes. The results indicated that a student's perception of whether assessment was fair was the greatest predictor of satisfaction. Through an understanding of the factors that contribute to positive learning experiences for students in teams, suggestions are given on how design educators might better support student learning in teamwork assignments and student learning of how to design in teams.
POWER REQUIREMENTS FOR TRAVERSING UNEVEN ROADWAYS

Vehicles which travel on uneven roadways or rough surfaces require power beyond that associated with air drag, rolling resistance or other sources of friction even though kinetic and potential energy may be conserved on the average. This is true because damped relative motions within the vehicle dissipate energy, and, even for nearly rigid vehicles, energy is lost at impact with the ground whenever the vehicle loses contact with the ground surface due to the finite downward acceleration of gravity. Using elementary vehicle models, the nature and magnitude of the component of propulsive force associated with these energy loss mechanisms is estimated. In certain speed ranges, this force is found to vary dramatically with speed for several types of periodic roadway profiles studied. While the force due to unevenness may be small compared to other forces for high-speed vehicles operating on smooth surfaces, it can be the major source of required power for off-road vehicles operating on very rough terrain. /Author/TRRL/
Vehicle Access Intelligent Monitoring and Network Management System Based on RFID Technology

Now, Internal and external vehicles are artificially queried and identified by a specially-assigned person in most of schools and enterprises, so the workload of vehicle management is very heavy, what’s more the vehicles information can not be effectively preserved. So it is not convenient for vehicles access query in the furture. Using RFID intelligent sensor network technology, the intelligent monitoring and identifing of vehicles access was realized and vehicles access was better controlled. The system can provide real-time effective data for enterprises management. Through the unit LAN system, the remote transmission and perservation of the vehicle information and photos were completed, so the network management was realized and the information can be conveniently queried in the future.