Miracle-dz/UniFAR-FTUs huggingface dataset:
Power quality detection and classification using wavelet-multiresolution signal decomposition

The wavelet transform is introduced as a powerful tool for monitoring power quality problems generated due to the dynamic performance of industrial plants. The paper presents a multiresolution signal decomposition technique as an efficient method in analyzing transient events. The multiresolution signal decomposition has the ability to detect and localize transient events and furthermore classify different power quality disturbances. It can also be used to distinguish among similar disturbances.
Semantic Search and Summarization of Judgments Using Topic Modeling

Online legal document libraries, such as WorldLII, are indispensable tools for legal professionals to conduct legal research. We study how topic modeling techniques can be applied to such platforms to facilitate searching of court judgments. Specifically, we improve search effectiveness by matching judgments to queries at semantics level rather than at keyword level. Also, we design a system that summarizes a retrieved judgment by highlighting a small number of paragraphs that are semantically most relevant to the user query. This summary serves two purposes: (1) It explains to the user why the machine finds the retrieved judgment relevant to the user’s query, and (2) it helps the user quickly grasp the most salient points of the judgment, which significantly reduces the amount of time needed by the user to go through the returned search results. We further enhance our system by integrating domain knowledge provided by legal experts. The knowledge includes the features and aspects that are most important for a given category of judgments. Users can then view a judgement’s summary focusing on particular aspects only. We illustrate the effectiveness of our techniques with a user evaluation experiment on the HKLII platform. The results show that our methods are highly effective.
P‐4: Measurement and Analysis of a Novel Full‐Parallax Three Dimensional Display System

This paper provides some imaging performance measurements and analysis for a prototype‐equipment based on a novel full‐parallax 3D display system. The projection center offset and crosstalk situation are mainly analyzed. Imaging performance of this 3D display system can be improved according to the analysis with the minimum changes to the system structure.
Complementary usage of real and virtual manufacturing systems for safe PLC training

Abstract Physical models mimicking industrial plants and relevant control issues are usually considered the most interesting targets for effective PLC (Programmable Logic Controller) training. However, they introduce safety problems. Filtering bad commands from the PLC is double interesting in this scenario: it guarantees safety and guides trainees by supplying explanations when a command is filtered. However, devising the appropriate filters can be hard for complex systems. Simulation is the single safe solution in advanced PLC training. While synthetic systems are traditionally viewed as a second-class solution in PLC training, modern computer game technologies are enabling realistic and interactive virtual environments, from where a “de facto” effective and exciting training environment comes very naturally. And filters can be relaxed in virtual environments as they only intend to help trainees in finding out their mistakes whenever a (virtual) accident happens. The paper details the design and usage of filters in PLC training. The aim is to demonstrate the benefits of the complementary usage of real and virtual target systems in PLC training, which were assessed and validated with different skilled students.
Increasing Patient Adherence to Home Health-Monitoring Systems

Research indicates that behavior change interventions can assist patients’ performance with respect to their health, and empower them to take a proactive role in their well-being. The objective of this research was to identify features that make remote health-monitoring systems more effective. To that end, a persuasive design approach was used to design a prototype application that encourages patients to consult their home monitoring devices appropriately. An exploratory user study was conducted to evaluate participants’ opinions about the developed prototype, their preferences, as well as their concerns regarding the different components of the mockup. In addition to the exploratory study, a comparative study was conducted, in which a conventionally designed health application was compared with a newly designed engagement application. The results of the study showed no difference on quantitative measures but participant preferences still indicated the engagement design may have potential.
A fault location technique for rural distribution feeders

The fault location scheme presented attempts to account for the multi-phase laterals, the unbalanced conditions, and the unsymmetrical nature of distribution feeders by continually updating voltage and current vectors at set locations within the system. The updated voltage and current vectors are the estimates of the 60 Hz phasor quantities obtained using a recursive optimal estimation algorithm. The distance to the fault is then estimated using a method based on the apparent impedance approach and the updated voltage and current vectors. Another consideration is the ability to determine the fault location on a lateral. A simulation of an actual rural distribution feeder using the electromagnetic transients program (EMTP) is used to illustrate the concepts of the approach and to show the accuracy and speed of this fault location technique, even on a temporary fault that lasts only for a few cycles. <<ETX>>
Cerebellar model articulation controller proportional velocity parameters variations and learning schemes—A study on electrohydraulic servo system

Cerebellar model articulation controller neural networks is one of the computational intelligence tools that can be applied for modeling, classification, and control. Proportional velocity controller is a servo-type controller, which is commonly applied to motion control systems. This paper presents a novel combination of cerebellar model articulation controller neural networks and optimal proportional velocity controller. A simple mathematical model for applying and studying cerebellar model articulation controller is introduced, and a study of its parameters is presented individually. The effect of parameters variation on cerebellar model articulation controller performance is identified. Learning algorithms highly affect the cerebellar model articulation controller behavior even when the parameters are optimized, and proper selection of the learning scheme must be taken under consideration. Three different learning algorithms are studied for evaluating transient and steady-state cerebellar model articulation controller responses. The results showed that the change of cerebellar model articulation controller generalization size and scale of the control signal has a marked effect on the performance of cerebellar model articulation controller. Furthermore, the constant learning rate algorithm gives the best overall performance.
Power-amplifier characterization using a two-tone measurement technique

An accurate nonlinear model is necessary to optimize the tradeoff between efficiency and linearity in power amplifiers. Gain compression (AM/AM) and amplitude-phase (AM/PM) distortion are the two primary model inputs used to characterize the nonlinearity. The amplifier's AM/AM and AM/PM characteristics are typically measured statically using a vector network analyzer. Since the input is typically a modulated signal, it is desirable to characterize the amplifier dynamically. This paper describes and demonstrates a dynamic AM/AM and AM/PM measurement and modeling technique involving a spectrum analyzer and two-tone input signals. A complete analysis of the measurement technique is presented, along with the data processing needed for the identification of a new three-box model. The test configuration and procedure are presented with special precautions to minimize measurement error. Results for a solid-state amplifier are used to accurately predict intermodulation distortion, while those for a traveling-wave tube amplifier show good agreement with that obtained dynamically using a 16 quadrature-amplitude-modulation signal.
Peripheral Nerve Decline Impacts Lower Extremity Muscle Function in Older Adults

The prevalence of poor peripheral nerve function increases with age from approximately 8% at ages 40-49 to 35% after age 80 and likely contributes to declines in muscle strength, power, and mobility limitations. However, longitudinal evidence is lacking and the relationship between nerve function and muscle power has not been examined even at a cross-sectional level. This dissertation investigates the role of sensory and motor peripheral nerve function in muscle function decline and incident mobility limitation in older adults using data from two longitudinal cohort studies. Data from the Osteoporotic Fractures in Men Study (MrOS) show that poor motor and sensory nerve function are independently associated with poor muscle power and that light monofilament insensitivity is associated with greater decline in muscle power. Findings from the Health Aging and Body Composition (Health ABC) Study indicate that sensory and motor nerve function are predictive of subsequent strength and concurrent change in strength, although improvement in nerve function may not always lead to improvements in strength. We also found that sex modified the relationship between nerve function and strength, with motor and sensory nerve function being associated with strength in women and only sensory nerve function being associated with strength in men. Again using data from the Health ABC Study, we found that poor initial motor and sensory nerve function and sustained poor motor nerve function over seven years independently predicted incident mobility limitation. Understanding the role of neuromuscular parameters in the disablement process may help to identify multiple points of intervention. Our findings have important public health implications, suggesting a need for future work to examine early prevention of modifiable risk factors and secondary prevention to slow muscle function declines and prevent mobility limitation. Since our results persisted after adjustment for known risk factors for poor nerve function such as diabetes and vitamin B12 deficiency, novel risk factors should also be explored.
Intelligent Vehicle Design based on PaddlePaddle and Deep Learning

ABSTRACT.In order to visualize the applications of deep learning based intelligent vehicle in the real field vividly, especially in the unmanned cases in which it realizes the integration of various technologies such as automatic data acquisition, data model construction, automatic curve detection, traffic signs recognition, verification of the unmanned driving, etc. A M-typed Model intelligent vehicle that is embedded with a high-performance board from Baidu named Edge Board is adopted by this study. The vehicle is trained under the PaddlePaddle deep learning frame and Baidu AI Studio Develop platform. Through the autonomous control scheme design and the non-stop study on the deep learning algorithm, an intelligent vehicle model based on PaddlePaddle deep learning is here. The vehicle has the function of automatic driving on the simulated track. In addition, it can distinguish several traffic signs and make feedbacks accordingly.
A People-Oriented Designing for Pattern Carving Intelligent Control Integrated Device

Aiming at solving the problems of weak human-computer interaction, poor scalability, low system integration, and lack of information management capabilities of the original engraving equipment, a set of pattern engraving intelligence integrated management and control device has been developed. The device flexibly integrates the main processes of engraving machining, detection, sorting, etc, and realizes the automatic machining of multi-mode engraving tasks such as on-site touch screen delivery, remote machine vision collection, network PC communication, and mobile APP sending. It can identify and evaluate the characteristic parameters of engraved final products over non-contact machine vision; and use the SCARA robot for intelligent sorting and palletizing of engraved final products. In addition,its information management platform can realize real-time monitoring of production status and production data storage and statistical analysis. In general, the device realizes the intelligent upgrade and informatization transformation of traditional engraving equipment.
Triple band circularly polarized compact microstrip antenna with defected ground structure for wireless applications

Asymmetric slits loaded irregular shaped microstrip patch antenna with three different ground structures is proposed. All three antennas show triple band characteristics. First antenna with regular ground plane resonates at 1.95, 2.4, and 4.90 GHz with good radiation characteristics and shows right-hand circular polarization at 1.95 GHz. 18.75% of compactness is achieved with triple band characteristics. Further, same patch is used with different defected ground structures. Second antenna resonates at 1.85, 2.4, and 4.85 GHz with suppressed cross-polarization level and antenna shows right-hand circular polarization at 1.85 and 4.85 GHz. Compactness is further improved to the value of 22.91%. The third antenna resonates at 1.95, 2.4, and 4.85 GHz with better gain and radiation characteristics and antenna shows right-hand circular polarization at 1.95 and 2.4 GHz. The small frequency ratio f2/f1 is achieved and the value of f2/f1 is 1.29 and 1.23 for second and third configuration, respectively. Proposed structures show right-hand circularly polarized with suppressed left-hand circularly polarized radiations and suitable for fixed mobile wireless communication applications. All structures are analyzed using Ansoft HFSS v.14 based on finite element method and measured results satisfy the simulated results.
PEDOT:PSS-Modified Cotton Conductive Thread for Mass Manufacturing of Textile-Based Electrical Wearable Sensors by Computerized Embroidery

The textile industry has advanced processes that allow computerized manufacturing of garments at large volumes with precise visual patterns. The industry, however, is not able to mass fabricate clothes with seamlessly integrated wearable sensors, using its precise methods of fabrication (such as computerized embroidery). This is due to the lack of conductive threads compatible with standard manufacturing methods used in industry. In this work, we report a low-cost poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)-modified cotton conductive thread (PECOTEX) that is compatible with computerized embroidery. The PECOTEX was produced using a crosslinking reaction between PEDOT:PSS and cotton thread using divinyl sulfone as the crosslinker. We extensively characterized and optimized our formulations to create a mechanically robust conductive thread that can be produced in large quantities in a roll-to-roll fashion. Using PECOTEX and a domestic computerized embroidery machine, we produced a series of wearable electrical sensors including a facemask for monitoring breathing, a t-shirt for monitoring heart activity and textile-based gas sensors for monitoring ammonia as technology demonstrators. PECOTEX has the potential to enable mass manufacturing of new classes of low-cost wearable sensors integrated into everyday clothes.
Biological Control - Parasitoids and Predators Adventive Larval Parasitoids Reconstruct Their Close Association with Spotted-Wing Drosophila in the Invaded North American Range

Two species of larval parasitoids of the globally invasive fruit pest, Drosophila suzukii (Diptera: Drosophilidae), Leptopilina japonica and Ganaspis brasiliensis (both Hymenoptera: Figitidae), were detected in British Columbia, Canada in 2016 and 2019, respectively. Both are presumed to have been unintentionally introduced from Asia; however, the extent of their establishment across different habitats with diverse host plants used by D. suzukii was unclear. In addition, there was no knowledge of the temporal dynamics of parasitism of D. suzukii by these two parasitoids. To address these gaps, we repeatedly sampled the fruits of known host plants of D. suzukii over the entire 2020 growing season in British Columbia. We documented the presence of L. japonica and G. brasiliensis and estimated the apparent percentage of D. suzukii parasitized among host plant species. Across a large region of southwestern British Columbia, both L. japonica and G. brasiliensis were found to be very common across a variety of mostly unmanaged habitats over the entire course of the season (May–October) in the fruits of most host plants known to host D. suzukii larvae. Parasitism of D. suzukii was variable (0–66% percent parasitism) and appeared to be time-structured. Our study demonstrates that the close association between the two larval parasitoids and D. suzukii that exists in Asia has evidently been re-constructed in North America, resulting in the highest parasitism levels of D. suzukii yet recorded outside of its area of origin.
Modeling and operation of a 10 kW photovoltaic power generator using equivalent electric circuit method

The output power of a photovoltaic power generator system (PV system) changes continuously as it strongly depends on the weather condition (solar radiation and temperature). Large fluctuations of output of PV system result in fluctuation and hence of harmonics in the inverter output. The PV systems are usually connected to the power grid lines, therefore, it is necessary to simulate the effects of the PV power systems on the commercial distribution line. In this paper, the authors have modeled a 10 kW PV module using current-voltage characteristic of a PV module by estimating its equivalent electrical circuit parameters.
A predictive microfluidic model of human glioblastoma to assess trafficking of blood–brain barrier-penetrant nanoparticles

The blood-brain barrier represents a significant challenge for the treatment of high-grade gliomas, and our understanding of drug transport across this critical biointerface remains limited. To advance preclinical therapeutic development for gliomas, there is an urgent need for predictive in vitro models with realistic blood-brain barrier vasculature. Here, we report a vascularized human glioblastoma (GBM) model in a microfluidic device that accurately recapitulates brain tumor vasculature with self-assembled endothelial cells, astrocytes, and pericytes to investigate the transport of targeted nanotherapeutics across the blood-brain barrier and into GBM cells. Using modular layer-by-layer assembly, we functionalized the surface of nanoparticles with GBM-targeting motifs to improve trafficking to tumors. We directly compared nanoparticle transport in our in vitro platform with transport across mouse brain capillaries using intravital imaging, validating the ability of the platform to model in vivo blood-brain barrier transport. We investigated the therapeutic potential of functionalized nanoparticles by encapsulating cisplatin and showed improved efficacy of these GBM-targeted nanoparticles both in vitro and in an in vivo orthotopic xenograft model. Our vascularized GBM model represents a significant biomaterials advance, enabling in-depth investigation of brain tumor vasculature and accelerating the development of targeted nanotherapeutics. Significance Statement The blood-brain barrier represents a major therapeutic challenge for the treatment of glioblastoma, and there is an unmet need for in vitro models that recapitulate human biology and are predictive of in vivo response. Here we present a new microfluidic model of vascularized glioblastoma featuring a tumor spheroid in direct contact with self-assembled vascular networks comprised of human endothelial cells, astrocytes, and pericytes. This model was designed to accelerate the development of targeted nanotherapeutics, and enabled rigorous assessment of a panel of surface-functionalized nanoparticles designed to exploit a receptor overexpressed in tumor-associated vasculature. Trafficking and efficacy data in the in vitro model compared favorably to parallel in vivo data, highlighting the utility of the vascularized glioblastoma model for therapeutic development.
Ultra-thin benzocyclobutene bonding of III-V dies onto SOI substrate

The bonding of InP/InGaAsP heterostructures dies onto an SOI substrate is reported. Bonding layer thicknesses down to 200 nm were reproducibly achieved. Bonding was achieved both on unprocessed SOI substrates as on processed SOI substrates containing high index contrast waveguides.
Utilizing occupancy-detection models with museum specimen data: promise and pitfalls

Historical museum records provide potentially useful data for identifying drivers of change in species occupancy. However, because museum records are typically obtained via many collection methods, methodological developments are needed in order to enable robust inferences. Occupancy-detection models, a relatively new and powerful suite of methods, are a potentially promising avenue because they can account for changes in collection effort through space and time. Here we present a methodological road-map for using occupancy models to analyze historical museum records. We use simulated data-sets to identify how and when patterns in data and/or modelling decisions can bias inference. We focus primarily on the consequences of contrasting methodological approaches for dealing with species’ ranges and inferring species’ non-detections in both space and time. We find that not all data-sets are suitable for occupancy-detection analysis but, under the right conditions (namely, data-sets that span long durations and contain a high fraction of community-wide collections, or collection events that focus on communities of organisms), models can accurately estimate trends. Finally, we present a case-study on eastern North American odonates where we calculate long-term trends of occupancy by using our most robust workflow.
On the Varying Effectiveness of Computer/Mobile-Assisted Language Learning

Educational technology has evolved tremendously over the past fifty years. Computer-and mobile-assisted tools have enabled language learning to take place anytime and anyplace. This paper examines the effectiveness of computer/mobile-assisted language learning (C/MALL) by reviewing findings as reported in the literature and by discussing benefits as well as issues linked with using technology in second/foreign (L2) language education. Overall, despite reports that technology has enhanced language instruction and acquisition, some find that it has not been as effective as anticipated or may have even impeded learning. This paper argues that the deciding factor defining the depth and breadth of technology’s effectiveness, in and outside of the classroom, is the teacher. Good teachers must precede technology for it to be effective in language learning. To improve the likelihood of effectively employing technology, this paper outlines key questions for teachers to consider when deciding whether to include technology in language instruction.