Miracle-dz/UniFAR-FTUs huggingface dataset:
A demonstration-based approach for domain-specific modeling language creation

Model-Driven Engineering (MDE) is a promising approach for addressing the issues of complex and large software system development that enables software engineers to develop software systems with high-level abstract models. In MDE, models are first-class entities of software system development and can improve the understanding of problem domains. In addition, models are used to predict the quality and performance of software systems. Within the context of MDE, Domain-Specific Modeling Languages (DSMLs) are developed to describe notions of a specific domain using either textual or graphical syntax. DSMLs provide a language that has abstractions and notations, as well as precise and concise modeling constructs, for specific domains (e.g., automotive, avionics, finance, and etc). DSMLs assist domain experts in describing their problems closer to the problem domain when compared to General-Purpose Modeling Languages (GPMLs), such as Unified Modeling Language (UML) or programming languages. DSMLs have been shown in the literature to provide several benefits, such as productivity improvement, quality improvement, and reduction of miscommunication. However, development of new DSMLs can be challenging and requires much time and effort. In addition, the current state of DSML is still in its infancy compared to the tools and resources available for creation of programming language environments. This dissertation investigates a new approach for DSML creation that allows domain experts to have a more prominent role in describing the languages that they use. The core contributions of the dissertation are focused on three aspects related to domain-specific modeling language creation: 1) enable the creation of DSMLs in a demonstration-based approach by recording and analyzing the operational behavior exhibited by a domain expert as they model notions of their domain, 2) enable domain expert verification of the inferred language by exploring the model space, and 3) enable domain expert verification of the inferred language by exploring the model space. The objectives and contributions of the research will be explained in detail in this dissertation, combined with case studies from several domain modeling languages to demonstrate how a domain expert can build their own DSMLs in practice.
Implementation of Microwave Measurements Using Novel Calibration Techniques

ADITYA P. GOSWAMI. Implementation of Microwave Measurements using Novel Calibration Techniques. (Under the direction of Dr. Michael Steer.) NetA (Network Analysis) tools for calibration of microwave measurements has been implemented. NetA contains calibration and de–embedding procedures as data analysis MATLAB routines. The Through Line method for calibration of two ports has been used and the NetA process flow has also been explained. Complex characteristic impedance of the micro-strip transmission line has been calculated using the ETRL (Enhanced TRL) technique. Results have been simulated using NetA tools. A LabVIEW Implementation of NetA has also been implemented so as to enhance the usability of NetA and also provide the capability of Real–time microwave calibration and de–embedding.
Frequency support from photovoltaic power plants using offline maximum power point tracking and variable droop control

With higher penetration of converter-connected renewable energy sources (RES) into power systems, the successful operation of the system is challenged by significant reductions in system inertia. Presently, given the dominant share of the conventional synchronous power plant, RES power plants are not demanded to provide ancillary services. However, as RES connections increase, RES power plants will play a major role in power system operation, contributing to frequency control. This study demonstrates that photovoltaic power plants (PVPPs) can provide effectively different types of frequency support based on a power reserve and an offline maximum power point tracking (MPPT) technique. An innovative method to de-load the PVPP without significantly increasing the MPPT complexity is proposed. Results from different PVPP frequency support methods, under varying levels of photovoltaic penetration, are presented which demonstrate their capability to provide inertia support comparable to that of synchronous generators. A new variable droop control method, which releases maximum power during the inertial response and returns to fixed droop gain value after a specified time is also presented. The results from using the variable droop show that the frequency nadir and the rate-of-change-of-frequency can be significantly reduced and some power reserve still maintained after a frequency event.
Ultracompact two‐way and four‐way SIW/HMSIW power dividers loaded by complementary split‐ring resonators

In this paper, two ultracompact power dividers based on the substrate integrated waveguide (SIW) and half‐mode SIW (HMSIW) technologies loaded by complementary split‐ring resonators (CSRRs) are presented. The presented structures are designed based on the theory of evanescent mode propagation. To obtain a size reduction, the CSRR unit cells are etched on the metallic surface of the SIW and HMSIW structures. First, a two‐way HMSIW power divider is reported. In this circuit, the concept of HMSIW is utilized aiming at a further size reduction in addition to the size reduction by the CSRR unit cells. Then, a four‐way SIW power divider is designed so that the direct coaxial feed is used for the input port and microstrip transmission lines are used for the output ports. Both two‐way and four‐way SIW/HMSIW power dividers at 5.8 GHz covering WLAN are designed, fabricated, and measured. They respectively have 0.18 × 0.21 λg2 and 0.38 × 0.21 λg2 total size. A fair agreement between simulated and measured results is achieved. The measured insertion losses are 0.5 ± 0.5 and 0.6 ± 0.5 dB for the two‐way and four‐way SIW/HMSIW power dividers, respectively, in the operating band of interest.
Anti-bias track-to-track association algorithm based on distance detection

To address multi-sensor real-time track-to-track association problem of aircraft platforms in a complex environment, where sensor biases are time-varied, targets are distributed closely and different sensors report different targets, an anti-bias track-to-track association algorithm based on distance detection is proposed according to the statistical characteristics of Gaussian random vectors. First, a distance vector between homologous tracks is derived and its feature is analysed; second, the rough association based on minimum average and the refined association based on χ 2 distribution are illustrated according to the features of distance vectors. Adaptability experiments are established based on three factors including different target densities, random errors, and sensor biases. Monte Carlo simulations demonstrate the proposed algorithm has significant improvements of association accuracy and complex condition adaptability compared with the classical reference topology feature algorithm.
Intensity-Modulated PM-PCF Sagnac Loop in a DWDM Setup for Strain Measurement

A novel intensity-modulated Sagnac loop sensor based on polarization-maintaining photonic crystal fiber (PM-PCF) in a setup with a dense wavelength division multiplexer (DWDM) for strain measurement is presented. The sensor head is made of PM-PCF spliced to single-mode fibers. The interferometer spectrum shifts in response to the longitudinal strain experienced by the PM-PCF. After passing the Sagnac loop, light is transmitted by a selected DWDM channel, resulting in a change in the output optical power due to the elongation of PM-PCF. Hence, appropriate adjustment of spectral characteristics of the DWDM channel and the PM-PCF Sagnac interferometer is required. However, the proposed setup utilizes an optical power measurement scheme, simultaneously omitting expensive and complex optical spectrum analyzers. An additional feature is the possibility of multiplexing of the PM-PCF Sagnac loop in order to create a fiber optic sensor network.
A Portable system for data sonification

ACKNOWLEDGMENTS I wish to thank my research advisor, Dan Reed, for all of his guidance and assistance, and especially the innnite patient revisions and criticisms of all my text. This work would have been impossible without his unwavering encouragement and trust in my ideas. I am also extremely grateful to Tom Birkett, who wrote the rst version of the sound software for the SPARC audio device, for his help and inspiration. I also owe a great deal to Brian Totty for building a serial to MIDI interface and bringing in his own synthesizer, convincing everyone of the potential of MIDI for soniication and playing Christmas carols. I am indebted to Joan Francioni and Jay Jackson for showing me their auralization work, which made me think about sound in a very diierent way. Thanks to all the members of the Picasso group, past and present, for their assistance and friendship. In particular, thanks to Mustaazur Rahman for working so hard to provide traces from the Choices operating system. Thanks to Ruth Aydt, for (among other things) saving me from certain eviction from my rst apartment. Thanks to Lawrence Rauchwerger and his army of guardian angels for a sympathetic ear and some of the best advice I have ever received. Thanks to Dave Jensen for constantly coming to my rescue with L a T E X help and thesis tips. Thanks to Chris Elford, Dave Kohr, Bradley Schwartz and Keith Shields for putting up with all my obsessions and complaints. My friend David Zimmerman gets credit for the part of East Coast Voice, although it is unlikely to earn him his big break. And nally, I thank my family for their constant love and support. And in particular, my parents, for believing in me unconditionally.
Analyzing predictors of children’s formative engineering identity development

This study examines elementary school students’ formative engineering identity development before and after studentsengage in engineering design-based science instruction over the course of one academic year. Over 200 students in gradesthree through six completed the Engineering Identity Development Scale (EIDS) on three occasions. Results indicatedstudents’ growth in conceptual understandings of engineering and increased career aspirations over time. Third and sixgraders demonstrated greater career aspirations in engineering than fourth and fifth graders. No interaction effects forgender were found. Implications for studying the impact of the integration of engineering practices on children’s identityformation are suggested.
Numerical Investigation on the Performance of a Regenerative Flow Turbine for Small-Scale Organic Rankine Cycle Systems

In this study, the performance characteristics of a regenerative flow turbine (RFT) prototype have been investigated by means of a computational fluid dynamics (CFD) study. The prototype has been initially designed to be used in gas pipelines replacing expansion valves but, because of the intrinsic characteristics of this kind of expander, its use can be extended to other applications like the expansion process in small-scale organic Rankine cycle (ORC) plants. In the first part of this work, the numerical results of the CFD analysis have been validated with the experimental data reported in literature for the same turbine prototype. After the validation of the model, a detailed study has been carried out in order to evaluate specific features of the turbine, focusing the attention on the typical operating conditions of small-scale low-temperature ORC systems. Results have shown that the considered RFT prototype operates with higher isentropic efficiencies (about 32% at 6000 rpm) at lower mass flow rates, while the power output is penalized compared to other operating points. The numerical analysis has also pointed out the high impact of the losses in the leakage flow in the gap between the blade tips and the stripper walls. Therefore, the CFD analysis carried out has provided a thoughtful understanding of the performance of the expander at varying operating conditions and useful insights for the future redesign of this kind of machine for the application in small-scale ORCs.
3D LiDAR-Based Global Localization Using Siamese Neural Network

Global localization in 3D point clouds is a challenging task for mobile vehicles in outdoor scenarios, which requires the vehicle to localize itself correctly in a given map without prior knowledge of its pose. This is a critical component of autonomous vehicles or robots on the road for handling localization failures. In this paper, based on reduced dimension scan representations learned from neural networks, a solution to global localization is proposed by achieving place recognition first and then metric pose estimation in the global prior map. Specifically, we present a semi-handcrafted feature learning method for 3D Light detection and ranging (LiDAR) point clouds using artificial statistics and siamese network, which transforms the place recognition problem into a similarity modeling problem. Additionally, the sensor data using dimension reduced representations require less storage space and make the searching easier. With the learned representations by networks and the global poses, a prior map is built and used in the localization framework. In the localization step, position only observations obtained by place recognition are used in a particle filter algorithm to achieve precise pose estimation. To demonstrate the effectiveness of our place recognition and localization approach, KITTI benchmark and our multi-session datasets are employed for comparison with other geometric-based algorithms. The results show that our system can achieve both high accuracy and efficiency for long-term autonomy.
Microgrid planning considering the resilience against contingencies

Increasing the redundancy of distribution lines and increasing the penetration of distributed energy resources (DERs) both help microgrids ride through contingencies. However, it remains a challenging problem for how to coordinate these two measures for minimising the deployment cost while guaranteeing a pre-specified degree of resilience in case of contingencies. Accordingly, this study proposes a novel microgrid planning model to site and size candidate sets of DERs and distribution lines in close coordination, which is mathematically equivalent to a two-stage robust optimisation problem. In particular, the resilience level of microgrid operations is quantified and maintained such that the load loss is constrained within a given bound under any realisation of N – k contingencies. The proposed model also incorporates a practical strategy to maintain the radial topology of islanding network sections in any N – k contingency. Finally, numerical experiments based on two microgrid test systems are performed. The results show that the system resilience is adaptively enhanced through optimally placing DERs and distribution lines compared with the conventional economics based model. Moreover, the employed robust method is at least ten times faster than the reliability-based method in identifying the worst contingency.
Applying the cognitive apprenticeship theory to examine graduate and postdoctoral researchers’ mentoring practices in undergraduate research settings

Graduate and postdoctoral researchers regularly mentor undergraduate research (UR) students, yet the literatureexamining the mentoring practices of these researchers in UR settings is scarce. This study explored the mentoringpractices of 17 experienced and highly valued graduate and postdoctoral researchers by conducting semi-structuredinterviews and analyzing the responses using cognitive apprenticeship (CA) theory. The mentoring practices used duringdifferent UR periods (i.e., teaching a literature review process, teaching technical content, training in lab skills orexperimental techniques, assisting with data analysis, assisting in creating presentation slides or a poster, and assisting inwriting a final report) were identified and classified according to CA principles. The study findings can assist graduate andpostdoctoral researchers who are mentoring UR students and can contribute to the development of training programs onmentoring UR students.
Palmprint Verification System Based on Mobile Device

Aiming at the application of palmprint recognition in mobile devices,this paper proposes a palmprint recognition algorithm and successfully embeds it into Lenovo ET980 mobile phone. The mobile-based system captures and pre-processes palmprint image in a new style. An optimal Gabor wavelets based discriminant subspace method is applied for feature extraction to give an effective and compact presentation of palmprint image. The system achieves the recognition rate of EER=3.89% and takes 1 s to verify a palmprint image,which satisfies the requirement of a real-time verification system.
Mendeley Impact on Scientific Writing: Thematic Analysis

The quality of scientific writing is based on its impact on knowledge development. This study aims at exposing the Mendeley impact on scientific writing. The thematic analysis was applied in this study to transcribe the recordings and translate as well as analyze the transcripts through NVivo 8 software. This study reveals that the identified themes appeared in this study are avoiding plagiarism, backup file, change citation style, personal library, and social network. This study recommends that due to the plagiarism deterrent is problematic in scientific writing; students are required to be educated on this issue. This study also reveals that research collaboration in internet connection could be the basis of building the real network by creating research community and organizing conference for knowledge sharing among the researchers.
Algorithms for Scheduling and Routing Problems

Optimization has been a central topic in most scientific disciplines for centuries. Continuous optimization has long benefited from well-established techniques of calculus. Discrete optimization, on the other hand, has risen to prominence quite recently. Advances in combinatorial optimization and integer programming in the past few decades, together with the improvement of computer hardware have enabled computer scientists to approach the problems in this area both theoretically and computationally. However, obtaining the exact solution for many discrete optimization problems remains is still a challenging task, mainly because most of these problems are NP-hard. Under the widespread assumption that P 6= NP, these problems are intractable from a computational complexity standpoint. Therefore, we should settle for near-optimal solutions. In this thesis, we develop techniques to obtain solutions that are provably close to the optimal for different indivisible resource allocation problems. Indivisible resource allocation encompasses a large class of problems in discrete optimization which can appear in disguise in various theoretical or applied settings. Specifically, we consider two indivisible resource allocation problems. The first one is a variant of the vehicle routing problem known as Skill Vehicle Routing problem, in which the aim is to obtain optimal tours for a fleet of vehicles that provides service to a set of customers. Each of the vehicles possesses a particular set of skills suitable for a subset of the tasks. Each customer, based on the type of service he requires, can only be served by a subset of vehicles. We study this problem computationally and find either the optimal solution or a relatively tight bound on the optimal solution on fairly large problem instances. The second problem involves approximation algorithms for two versions of the classic scheduling problem, the restricted R | |Cmax and the restricted Santa Claus problem. The objective is to design a polynomial time approximation scheme (PTAS) for ordered instances of the two problems. Finally, we consider the class of precedence hierarchies in which the neighborhoods of the processors form Laminar families. We show similar results for a generalization of this model.
System Architecture Design of 3PL Enterprise Data Exchange Platform

Third Party logistics enterprises urgently need a unified platform for a large number of customers and administrative units,research and development of this platform have great significance.Design ideas about the general framework of the third party logistics enterprise data exchange platform,docking,communication methods presented,as well as data exchange on the processing logic,and makes the experiment.
Event‐triggered distributed fault detection over sensor networks in finite‐frequency domain

In this study, the event-triggered distributed fault detection problem is investigated for a class of discrete-time uncertain systems in the finite frequency domain. A sensor network is utilised to collect the information of interest, and an event-triggered communication scheme is adopted to alleviate the communication burden. For the addressed problem, a distributed fault detection filter is designed based on the measurement information from its neighbouring nodes and itself by the given topology. In addition, a fashionable index, named as H - /H ∞ performance, is employed in order to simultaneously achieve the residual sensitivity to faults and the robustness against disturbances. By resorting to Euler's formula combined with Lyapunov stability theory, some sufficient conditions are established to satisfy the desired performance over a given finite-frequency domain, and the distributed fault detection filter gains are explicitly characterised by solving a series of linear matrix inequalities. A simulation example is conducted to illustrate the feasibility of the proposed filter design technique.
Active Charge Equalizer of Li-Ion Battery Cells Using Double Energy Carriers

In this work, a new active balancing circuit is proposed. This circuit consists of a cell-access network and an energy-transfer network. The cell-access network requires 2n + 6 switches, where n is the number of cells, and creates an energy-transfer path between unbalanced cells and the energy-transfer network. The energy-transfer network has double energy carriers and simultaneously implements cell-to-pack and pack-to-cell balancing operations without overlapping. As a result, a high power rate and fast balancing operation can be achieved by using two energy carriers in a single balancing circuit. The prototype of a proposed balancing circuit was built for six cells and then tested under various conditions; all cells in the state of charge (SOC) region of 70% to 80% were equalized after 93 min, and one charging/discharging period in the SOC region of 10% to 90% was increased by 8.58% compared to the non-balancing operation. These results show that the proposed circuit is a good way to balance charges among batteries in a battery pack.