Miracle-dz/UniFAR-FTUs huggingface dataset:
Tensor structures arising from affine Lie algebras. III

This paper is a part of the series [KL]; however, it can be read independently of the first two parts. In [D3], Drinfeld proved the existence of an equivalence between a tensor category of representations of a quantum group over C[[w]] and a tensor category of representations of an undeformed enveloping algebra over C[[w ]]], in which the associativity constraints are given by the Knizhnik-Zamolodchikov equations. However, Drinfeld's proof was nonconstructive, in the sense that he showed that the set of equivalences between the two tensor categories was nonempty, without describing an equivalence explicitly. Our main result is an explicit construction of an equivalence between the tensor categories above. Its main virtue is, as we will show in Part IV, that it "extends analytically" to the case where w is no longer a formal variable
Artificial Intelligence Applications in Reservoir Engineering: A Status Check

This article provides a comprehensive review of the state-of-art in the area of artificial intelligence applications to solve reservoir engineering problems. Research works including proxy model development, artificial-intelligence-assisted history-matching, project design, and optimization, etc. are presented to demonstrate the robustness of the intelligence systems. The successes of the developments prove the advantages of the AI approaches in terms of high computational efficacy and strong learning capabilities. Thus, the implementation of intelligence models enables reservoir engineers to accomplish many challenging and time-intensive works more effectively. However, it is not yet astute to completely replace the conventional reservoir engineering models with intelligent systems, since the defects of the technology cannot be ignored. The trend of research and industrial practices of reservoir engineering area would be establishing a hand-shaking protocol between the conventional modeling and the intelligent systems. Taking advantages of both methods, more robust solutions could be obtained with significantly less computational overheads.
Thermal and flicker phase noise analysis in rotary traveling‐wave oscillator

This paper analyzes the thermally induced phase noise and the up‐conversion of flicker noise into phase noise of rotary traveling‐wave oscillator (RTWO). Based on the analyses, this paper extracts the closed‐form formulas for the thermal and flicker phase noise of the RTWO. This paper compares the theoretical results with appropriate simulations to evaluate the accuracy of the derived closed‐form formulas. Comparisons confirm the accuracy of the extracted phase noise formulas. By using the presented straightforward approach along with accurate phase noise formulas, the designers can understand the RTWO's design tradeoffs. Also, they can design the RTWO for a specific phase noise without needing lengthy simulations.
Evaluation of Deep Neural Network and Alternating Decision Tree for Kiwifruit Detection

Robotic kiwifruit harvesting systems are currently being introduced to improve the reliability and farming yields of kiwifruit harvesting operations. Machine learning is widely used to carry out the visual detection tasks required of such systems. This paper specifically compares two types of machine learning algorithms: the multivariate alternating decision tree and deep learning based kiwifruit classifiers. The purpose of the study is to investigate the cost of implementation against the classification performance. Thus, discussion is centred around computational cost and its impacts on the overall system architecture. We found that the traditional decision tree classifiers can achieve comparable classification performance at a fraction of the cost and complexity, providing robust and cost-effective instrument design.
Fault-Tolerant Fixed-Time Trajectory Tracking Control of Autonomous Surface Vessels With Specified Accuracy

This article investigates the trajectory tracking control problem for a family of underactuated autonomous surface vessels under the condition of model uncertainties, actuator faults, and environmental disturbances. The emphasis or difficulty is how to ensure the trajectory tracking with specified accuracy in the fixed-time settings. A new-type fault-tolerant tracking control strategy is developed based on the marriage of a novel bounding function and a method of handling constraints. Compared with the existing results it can be noted that: first, the position error enters into a preassigned residual set in a priori designate time and remains there; second, no adaptive mechanisms, disturbance observers, or command filters are involved, leading to a simplicity control attribute. Results from a comparative simulation on the CyberShip II further illustrate the above theoretical findings.
Investigation on the design and application of 3-dimensional wide-band piezoelectric energy harvester for low amplitude vibration sources

In order to realize 3-dimensional, wide-band vibration energy harvesting in low-frequency and low-amplitude environments, a multi-layer Z-type beam piezoelectric harvester structure is proposed. Nonlinear mass and instabilities of horizontal and longitudinal are introduced by the multi-layer Z-type beam structure. Simulation and experiment results show that when the number of beam layer is 7 and excitation intensity is 0.8 g, there are more than 4 voltage peaks within 5–40 Hz, the maximum voltage is above 16 V, the maximum output power can reach 180 μW, which greatly widens harvesting frequency band. When exciting in horizontal and vertical directions, the maximum voltages peaks are all above 10 V, the number of voltage peaks are all above 5, maximum output powers can reach 108 μW and 53 μW respectively, by which 3-dimensional energy harvesting is verified. Next, the performances of arrays are studied. When the arrays number is 12, excitation intensity reduces to 0.2 g, nearly 90% of the voltage response amplitudes for parallel arrays within 15–40 Hz are above 4 V, almost all the voltage response amplitudes for series arrays are above 5 V within 17–40 Hz, even response amplitudes are all above 10 V within 23–33 Hz. The maximum output power generated by parallel arrays is up to 864.5 μW. So, wide-band 3-dimensional vibration energy harvesting for low amplitude environment is realized by multi-layer Z-type vibration energy harvester. Finally, the feasibility that wireless switch could be powered by the multi-layer Z-type vibration energy harvester parallel arrays from low-frequency and low-amplitude environment is verified.
Monopole‐like and semi‐directional reconfigurable pattern antenna for wireless body area network applications

A simple, low profile and pattern reconfigurable antenna with a full‐ground plane is presented for use in wireless body area networks at 5.8 GHz ISM band. The antenna consists of a probe‐fed circular patch, and a parasitic ring surrounding it. The ring is loaded with a rectangular slot on each side of the patch, and two PIN diodes are added in the center of each slot. With all the diodes in on‐state, the antenna presents monopole‐like radiation patterns with the gain of 4.2 dBi for maximum coverage on the body, whereas the pattern of the antenna can be directed to ±15° with an increased gain of 2.9 dBi, by turning off each diode for the semi‐directional patterns states. Measured results of the fabricated prototype antenna show good agreement with numerical results obtained using Ansys HFSS.
Near-term Applications of Quantum Computers Based on Parametric Modulation of Superconducting Circuits

Over the last several years a number of near-term applications of quantum computers have emerged, including simulation of complex molecules, combinatorial optimization, and machine learning. These near term applications use the quantum device as a small but powerful subroutine in a traditional (classical) optimization loop, and are therefore called hybrid algorithms. We describe our quantum computational gate architecture — based on the parametric modulation of superconducting circuits — which is particularly well suited for such applications, and also describe several aspects of our quantum cloud services that are optimized for fast execution of hybrid algorithms in general. Keywords—quantum computing; transmon; hybrid algorithm; parametric gates
Social Network Analysis using Cultural Algorithms and its Variants

Finding relationships between social entities and discovering the underlying structures of networks are fundamental tasks for analyzing social networks. In recent years, various methods have been suggested to study these networks efficiently, however, due to the dynamic and complex nature that these networks have, a lot of open problems still exist in the field. The aim of this research is to propose an integrated computational model to study the structure and behavior of the complex social network. The focus of this research work is on two major classic problems in the field which are called community detection and link prediction. Moreover, a problem of population adaptation through knowledge migration in real-life social systems has been identified to model and study through the proposed method. To the best of our knowledge, this is the first work in the field which is exploring this concept through this approach. In this research, a new adaptive knowledge-based evolutionary framework is defined to investigate the structure of social networks by adopting a multi-population cultural algorithm. The core of the model is designed based on a unique community-oriented approach to estimate the existence of a relationship between social entities in the network. In each evolutionary cycle, the normative knowledge is shaped through the extraction of the topological knowledge from the structure of the network. This source of knowledge is utilized for the various network analysis tasks such as estimating the quality of relation between social entities, related studies regarding the link prediction, population adaption, and knowledge formation. The main contributions of this work can be summarized in introducing a novel method to define, extract and represent different sources of knowledge from a snapshot of a given network to determine the range of the optimal solution, and building a probability matrix to show the quality of relations between pairs of actors in the system. Introducing a new similarity metric, utilizing the prior knowledge in dynamic social network analysis and study the co-evolution of societies in a case of individual migra-
An automation framework design for secure software development

Business process modeling (BPM) is procedural‐oriented advanced activity for representing process models with domain knowledge. It consists of all the functional requirements given by the users to build the software. However, nonfunctional requirements such as cost, time, performance, and security are used to evaluate the performance of a system. Among these requirements, security is the vital attribute to be taken care at the early stage of any software development. For example, even governing bodies are heavily dependents on the data system due to security exposures. So automation on model transformation from non‐secured metamodel to secured metamodels improves the overall execution of the software evolution process. In this paper, the authors propose an Auto Secure Business Process (AutoSBP) system to automate security to the existing software models. The activity model of existing system is dismantled into attributes and actions to extract its business need. Based on the interpretation from business data, security implications are applied to the existing software models. To fine tune the security implications, ID3 decision learning algorithm is applied. The effect of the system‐generated model assures the quality by its complexity metrics.
Computer-Assisted Instruction in Elementary Classrooms: Student-Teacher Relationships and Teacher Role Through the Implementation of Computer-Adaptive Instruction Programs

iii Acknowledgements . v Dedication . vii List of Figures . xi Chapter One: Introduction . 1 Purpose Statement . 5 Significance. 6 Rationale . 8 Theoretical Framework . 9 Summary . 14 Chapter Two: Review of the Literature . 16 Effects of Education Technology on Student Achievement . 17 Students as Technology Users . 21 Human-Robot Interaction . 24 Classroom Environment. 26 Technology Enhanced Personalized Learning . 28 Computer-Adaptive Instruction . 30 Student-Teacher Relationships . 39 Student-Teacher Relationship Measurement . 46 ix Teacher Role . 49 Summary . 54 Chapter Three: Methodology . 57 Research Questions . 57 Rationale for Methodology . 58 Participants and Setting. 60 Computer-Adaptive Programs Used . 66 Design and Procedure . 69 Ethical Considerations . 76 Role of the Researcher . 76 Trustworthiness . 77 Summary . 79 Chapter Four: Results . 80 Data Sources . 82 Teacher Experiences . 83 RQ1: How is teacher role impacted through the implementation of computer-adaptive instruction programs? 107 RQ2: How do teachers perceive their student-teacher relationships through the implementation of computer-adaptive instruction programs? 116 Summary . 126 Chapter Five: Discussion . 127
Measurement method for characterizing a millimeter-wave traveling-wave power combiner using in-situ test accessories

Abstract This paper presents a novel assessment method that minimizes test-fixture-induced errors in non-coaxial power combiner measurement by extending the port reduction method. This method involves terminating certain ports to acquire the scattering matrix of an N-port network from the scattering matrix measured at a reduced port order. The entire DUT scattering matrix is obtained from multiple scanning measurements, which are taken from partial coaxial accessible ports, based on a set of configurable terminating states. This advantage is leveraged to exclude a major portion of coaxial launch structures that would otherwise be incorporated in the conventional multiport test fixture. An analogous concept here is applied to measure a waveguide traveling-wave power combiner. A sandwiched twin structure, containing a divider/combiner pair with certain auxiliary through-type components cushioned between them, is utilized to assess the combiner characteristics. A theoretical framework of the proposed method was established to test its potential precision. Thereafter, an in-situ implementation was conducted to test its practical application on a traveling-wave combined amplifier prototype operating at the Q-band (33–39 GHz).
NIDM-Results: Standardized reporting of mass univariate neuroimaging results in SPM, FSL and AFNI

Results of a neuroimaging study are usually shared through the publication of a scientific paper describing the experiment and analysis outcome. While hundreds of gigabytes of data are usually generated as part of an fMRI experiment, in the literature the authors typically report their results as a list of significant local maxima, i.e. locations in the brain defined in a standard space (e.g. MNI) that pass rigorous statistical testing. This practice is unsatisfactory in terms of data re-use as it does not allow for the automatic extraction of acquisition or processing information and it provides only sparse information about the location of the brain activity. While databases have been built to provide manually curated (such as BrainMap ​ [1]​) or automatically-extracted (e.g. NeuroSynth ​ [2]​) meta-data associated with published papers, ideally, these meta-data should be made available by the authors themselves at the time of the publication.
Visualization and Characterization of Cerebrospinal Fluid Motion Based on Magnetic Resonance Imaging

the Abstract Purpose : To characterize cardiac- and respiratory-driven cerebrospinal fluid (CSF) motions in intracranial space noninvasively, four-dimensional velocity mapping (4D-VM), correlation mapping, and power and frequency mapping with cardiac-gated and/or asynchronous magnetic resonance (MR) phase contrast (PC) techniques were conducted. Methods : Cardiac-gated PC in three spatial directions was applied to young, healthy, elderly, healthy, and idiopathic normal pressure hydrocephalus patient groups. 4D-VM was created from time-resolved 3D velocity distribution represented as vector and color coding. The curl and pressure gradient were calculated. Correlation mapping provides propagation delay and correlation of CSF motion at arbitrary points regarding a reference point. In addition, asynchronous PC technique was conducted for healthy volunteers with respiratory instruc-tion as constant rhythm. Cardiac- and respiratory-driven velocities were separated by fre- quency analysis. Power and frequency mapping present both the energy and dominant frequency of cardiac or respiratory CSF motion. Results : 4D-VM, curl, pressure gradient images, and correlation mapping by cardiac- gated PC demonstrated cardiac-driven CSF motion and its propagation properties. Power and frequency mapping, correlation mapping, and displacement analysis exhibited that the cardiac-driven CSF velocity was higher than the respiratory, although the cardiac-driven displacement was smaller. Conclusion : Visualization and characterization techniques based on PC imaging can capture the properties of CSF motion in intracranial space.
An Improved Method for Estimating Renal Dimensions; Implications for Management of Kidney Disease

Changes in renal dimensions, including total kidney volume, not only inform ongoing renal disease but also disease progression. Determination of renal dimensions can inform drug efficacy, is important for matching recipients with potential donors, and to inform debulking of renal tumors. Imaging of kidney and application of the ellipse-based formula has become standard for estimating renal dimensions. Nevertheless, the existing ellipse-based formula underestimates renal dimensions including total kidney volume, regardless of the imaging modality used. Based on a model of murine kidney disease, this laboratory has previously proposed a modification to this formula which exhibits better estimation of renal dimensions. The present study sought to determine whether this modified formula is applicable to additional models of kidney disease. Kidneys were sourced from etiologically distinct murine and rat models of renal scarring. In each case, renal dimensions calculated using the existing ellipse-based formula was significantly lesser than the measured dimensions. By contrast, there was no difference between the measured dimensions and those calculated using the modified formula. In a model of polycystic kidney disease, total kidney volume calculated using the existing formula significantly underestimated measured kidney volume whereas use of the modified formula yielded a calculated kidney volume in excellent agreement with the measured volume. Use of this modified formula provides a better estimate of renal dimensions across a number of disease models.
Designing Collaborative Research: The Exploration of Common Purposes to Foster the Generation of Cross-Disciplinary Projects

Despite the increasing demand to develop cross-disciplinary research projects, designing collaborative research still prove to be difficult due to both scientific specialization and organizational issues. In this paper, we explore how innovative design dynamics can be developed between researchers to collectively build research projects that could become common purposes for collaboration. This work relies on a case study led with the newly formed Eco&Phy research team, who applied an innovative design process to initiate collaboration and design its scientific agenda for the next 5 years. This process was built based on both KCP and matching-building methodologies: it included an initialization phase, during which the team strategically chose topics to be explored, and exploration phases, during which researchers collectively developed new knowledge and concepts to build cross-disciplinary projects. At the end of the design process, the team had developed two new research lines that were integrated in its official agenda. In conclusion, the article discusses the relevance of design approaches to develop original collaborative research through dedicated innovation processes.
3D Magnetic Imaging With GMR Sensors

This paper reports on the development of spin electronics based probes for 3D magnetic imaging. We have demonstrated the feasibility of using four orientations of magnetoresistive sensors (GMR) for the reconstruction of three dimensional components of magnetic field at the same measurement point. The use of different GMR sensor structures makes it possible to adapt the sensitivity and field range to the signal to detect for a specific application. Their characteristics and field reconstruction steps are also shown. Different examples of magnetic imaging are presented.
Application of Wideband Differential Phase Shifters With Wide Phase Range in Chipless RFID Readers

Eliminating the strong self-interference signal in chipless radio frequency identification (RFID) readers is key for enabling a reliable and long range reading in chipless RFID readers. The suggested method is to add a compensation signal to cancel the leakage signal vectorially before the first stage of the receiver front-end. An ultra-wideband (UWB) polyphase power divider (PPPD) generates the vector compensation signal of any arbitrary amplitude and phase. Unfortunately, the reported PPPD cannot meet the requirements for the realization of a UWB compensation unit (CU). A microstrip wideband differential phase shifter capable of producing a wide range of phase shifts is presented in this paper. The delay lines, including transmission line (TL) segments loaded with shorted stubs (SSs), generate prescribed phase shift values with respect to the universal reference line. It is shown that an arbitrary phase shift (up to 360°) with an in-band return loss (RL) better than 15 dB within an octave bandwidth is obtainable. Its full-range phase shift capability alongside the universal reference line and simple structure ensure its suitability for polyphase applications. To verify the proposed structure, a set of C-band phase shifters ranging from 60° to 300° is designed and fabricated, and a phase deviation from ±1° to ±9° is obtained. Finally, based on the proposed differential phase shifter, a four-phase power divider is implemented and utilized in the CU of a chipless RFID reader. Excessive isolation of better than 35 dB over 4–8-GHz frequency band is attained.
Feedback Control of Multiphase Induction Machines With Backstepping Technique

This article presents the control possibility of five-phase induction machines. In the proposed solution, the machine model vector form is not transformed to the (<italic>dq</italic>)-coordinate system, that is connected to the rotor flux vector, but utilizes the stationary system (α<italic>β</italic>). Moreover, the nonlinear model linearization is based on demonstrated nonlinear variables transformation for <italic>i</italic>-orthogonal <inline-formula><tex-math notation="LaTeX">$(\alpha \beta)_{(n)}$</tex-math></inline-formula> planes. By introducing the backstepping approach, the independent stabilization of electromagnetic torque and rotor flux in each plane is obtained. A practical stability analysis of the proposed controller for a multiphase machine is illustrated as well. Finally, experimental test results are demonstrated for a specific speed sensorless five-phase induction motor test setup.