Miracle-dz/UniFAR-FTUs huggingface dataset:
Precise Inside-Out Electromagnetic Input Tracking

Precise Inside-Out Electromagnetic Input Tracking Farshid Salemi Parizi Chair of the Supervisory Committee: Washington Research Foundation Entrepreneurship Endowed Professor Shwetak Patel Paul G. Allen School of Computer Science and Engineering & Department of Electrical and Computer Engineering Wearable computing platforms, such as smartwatches and head-mounted mixed reality displays represent a promising direction for next-generation computing platforms. As computing platforms evolve from devices we carry with us to devices we wear on us, there is a renewed demand for input techniques that are decoupled from the display. These input devices demand precise tracking for high-fidelity interaction and must be continuously available and subtle to support various contexts of use while enabling robust and expressive interaction. In this thesis, I leverage electromagnetic tracking with data-driven approaches to enable new input devices that are more precise, subtle, and computationally simpler.
Just Noticeable Distortion Profile for Flat-Shaded 3D Mesh Surfaces

It is common that a 3D mesh undergoes some lossy operations (e.g., compression, watermarking and transmission through noisy channels), which can introduce geometric distortions as a change in vertex position. In most cases the end users of 3D meshes are human beings; therefore, it is important to evaluate the visibility of introduced vertex displacement. In this paper we present a model for computing a Just Noticeable Distortion (JND) profile for flat-shaded 3D meshes. The proposed model is based on an experimental study of the properties of the human visual system while observing a flat-shaded 3D mesh surface, in particular the contrast sensitivity function and contrast masking. We first define appropriate local perceptual properties on 3D meshes. We then detail the results of a series of psychophysical experiments where we have measured the threshold needed for a human observer to detect the change in vertex position. These results allow us to compute the JND profile for flat-shaded 3D meshes. The proposed JND model has been evaluated via a subjective experiment, and applied to guide 3D mesh simplification as well as to determine the optimal vertex coordinates quantization level for a 3D model.
Effects of Flash Glucose Monitoring on Dietary Variety, Physical Activity, and Self-Care Behaviors in Patients with Diabetes

The aim of this study was to evaluate the effects of flash glucose monitoring on dietary variety, physical activity, and self-care behavior in patients with diabetes. This study included outpatients with diabetes using insulin who presented at the Department of Diabetes and Metabolism of the Ise Red Cross Hospital. Before initiating flash glucose monitoring and 12 weeks after its initiation, blood glucose-related parameters were assessed and self-administered questionnaires were completed (Dietary Variety Score (DVS), the International Physical Activity Questionnaire (IPAQ), the Summary of Diabetes Self-Care Activities Measure (SDSCA), and the Diabetes Treatment Satisfaction Questionnaire (DTSQ)) and compared between the two time points. We analyzed 42 patients with type 1 diabetes mellitus and 48 patients with type 2 diabetes mellitus. In patients with type 2 diabetes mellitus, but not type 1 diabetes mellitus, there was an increase in moderate/high category scores for IPAQ (P < 0.001) and for treatment satisfaction reported via DTSQ. Furthermore, in patients with type 2 diabetes mellitus, the glycemic excursion index improved significantly and HbA1c decreased significantly (from 7.7 (1.2) to 7.4 (0.8), P = 0.025). Results showed that standard deviation and mean amplitude of glycemic excursions significantly decreased in patients with type 1 diabetes mellitus (from 71.2 (20.4) to 66.2 (17.5), P = 0.033 and from 124.6 (31.9) to 108.1 (28.4), P < 0.001, respectively). Flash glucose monitoring is a useful tool to improve physical activity in patients with type 2 diabetes.
Trends in aggregate employment, hours worked per worker, and the long-run labor wedge

Hours worked are fundamentally important for aggregate economic activity, yet canonical macroeconomic models fail dramatically at tracking its long-run trends. We develop an intuitive and tractable extension of the canonical model that decomposes trend hours into extensive and intensive margins via household-side employment-attainment costs and firm-side employment adjustment costs. Its predictions track very well the trend behavior of hours, and its two underlying margins, in the United States and a host of OECD countries. Our framework is relevant for analyzing the long run labor-market effects of a number of factors such as productivity growth, and tax or labor-market reforms.
Title Non-destructive method for wood identification using conventional X-ray computed tomography data

We establish an efficient and reliable method of wood identification that combines a non-destructive and non-invasive laboratory-scale tool, X-ray computed tomography (CT), with machine learning for image recognition. We selected six hardwood species used to create the Tripitaka Koreana and obtained the X-ray CT data of its woodblocks. Image recognition systems using the gray-level co-occurrence matrix (GLCM) or local binary patterns (LBP) were applied to the CT images and the prediction accuracies were evaluated. Because the gray level of the CT data is linearly related with the density, the CT images were preprocessed to calibrate the density. Although the resolution of the images is too low for the anatomical microstructures required for wood identification to be easily recognized visually, the predicted accuracies are quite high in both systems. However, the LBP system has slight advantages over the GLCM system. The results moreover show that the calibration of gray level to density improves the accuracies of the results. If the candidates for the wood species are selected properly and sufficient data for training is available, this technique will provide novel information about the properties of wooden historical objects. © 2019 Les Auteurs. Publié par Elsevier Masson SAS. Cet article est publié en Open Access sous licence CC BY (http://creativecommons.org/licenses/by/4.0/).
Ethnobotany of suweg, Amorphophallus paeoniifolius: Utilization and cultivation in West Java, Indonesia

Mutaqin AZ, Kurniadie D, Iskandar J, Nurzaman M, Partasasmita R. 2020. Ethnobotany of suweg, Amorphophallus paeoniifolius: Utilization and cultivation in West Java, Indonesia. Biodiversitas 21: 1635-1644. Amorphophallus paeoniifolius (Dennst.) Nicolson, locally known as suweg, is a bulbous plant that has many benefits, but has not been cultivated as intensively as other species from the Araceae family. Suweg grows scattered in various rural areas in Indonesia, including West Java. Some suweg plants are cultivated by villagers, while the others grow wildly in forested areas. Suweg is commonly cultivated in several types of agroecosystems, such as home gardens (pekarangan) and gardens (kebun), using traditional ecological knowledge inherited from generation to generation. This study aims to investigate the utilization and cultivation of suweg by a community in Cisoka Village, Cikijing Sub-district, Majalengka District, West Java. This study used a qualitative method using ethnobotany approach, i.e. an emic analysis of the perception and local knowledge of community on suweg, and then validated using scientific or ethical knowledge. Field data collection was done by observation and semi-structured interviews with key informants chosen purposively considered having expertise and knowledge about suweg. The results showed that suweg has long been cultivated or growing naturally in Cisoka Village. The species has been culturally utilized by the rural community as additional food sources of carbohydrates, fish feed, and traditional ceremonies. However, the use of traditional ceremonies has been lost its importance. Suweg is generally used by the elderly, with certain groups, such as rural fish farmers and some younger age groups or children who like suweg. The rural people of Cisoka Village also mentioned that suweg was not cultivated as intensively as other. This is partly because it is considered not to have a high economic value as other agricultural commodities.
Haptic rendering of hyperelastic models with friction

This paper presents an original method for interactions' haptic rendering when treating hyperelastic materials. Such simulations are known to be difficult due to the non-linear behavior of hyperelastic bodies; furthermore, haptic constraints enjoin contact forces to be refreshed at least at 1000 updates per second. To enforce the stability of simulations of generic objects of any range of stiffness, this method relies on implicit time integration. Soft tissues dynamics is simulated in real time (20 to 100 Hz) using the Multiplicative Jacobian Energy Decomposition (MJED) method. An asynchronous preconditioner, updated at low rates (1 to 10 Hz), is used to obtain a close approximation of the mechanical coupling of interactions. Finally, the contact problem is linearized and, using a specific-loop, it is updated at typical haptic rates (around 1000 Hz) allowing this way new simulations of prompt stiff-contacts and providing a continuous haptic feedback as well.
PROMINENT COGNITIVE IMPAIRMENT IN ALZHEIMER DISEASE, VASCULAR DEMENTIA AND DEMENTIA WITH LEWY BODIES

Although cognitive impairments seen in early and mild stages of Alzheimer Disease (AD), Vascular Dementia (VaD) and Lewy Bodies Dementia (LBD) might overlap, they have quite different aspects. The prominent cognitive impairments in AD are in the episodic and semantic memory. In VaD, while cognitive fl exibility, initiation, goal formulation and mood changes deteriorate, memory performance is preserved compared to these functions. On the other hand, the main impairments in LBD are cognitive fl uctuation, attention, visualspatial abilities and visual memory, whereas the verbal memory components
Title: Operational Integration of CAD Data and the Impact on Organizational Development in a Small Business

The accompanying research report is submitted to the University of Wisconsin-Stout, Graduate School in partial completion of the requirements for the Graduate Degree/ Major: MS Degree/Operations and Supply Management Research Advisor: Jim Keyes, Ph.D. Submission Term/Year: Spring/2018 Number of Pages: 56 Style Manual Used: American Psychological Association, 6th edition I have adhered to the Graduate School Research Guide and have proofread my work. I understand that this research report must be officially approved by the Graduate School. Additionally, by signing and submitting this form, I (the author(s) or copyright owner) grant the University of Wisconsin-Stout the non-exclusive right to reproduce, translate, and/or distribute this submission (including abstract) worldwide in print and electronic format and in any medium, including but not limited to audio or video. If my research includes proprietary information, an agreement has been made between myself, the company, and the University to submit a thesis that meets course-specific learning outcomes and CAN be published. There will be no exceptions to this permission. I attest that the research report is my original work (that any copyrightable materials have been used with the permission of the original authors), and as such, it is automatically protected by the laws, rules, and regulations of the U.S. Copyright Office. My research advisor has approved the content and quality of this paper. STUDENT: NAME: Rodney Vizer DATE: 4/24/2018 ADVISOR: (Committee Chair if MS Plan A or EdS Thesis or Field Project/Problem): NAME: James Keyes, Ph.D. DATE: 4/24/2018 --------------------------------------------------------------------------------------------------------------------------------This section for MS Plan A Thesis or EdS Thesis/Field Project papers only Committee members (other than your advisor who is listed in the section above)
Coexisting violence and self‐harm: Dual harm in an early‐stage male prison population

Purpose: This study examined the characteristics of men in prison who have a history of both self-harm and violence (known as dual harm) and the extent to which demographic and criminogenic factors, in-prison incidents and self-harm method could differentiate men who dual harm. Methods: Official prison sample data were examined for the period April 2010 to November 2017 (n = 965). Regression analysis of all custodial incidents, demographic and offending information, and imprisonment experience, was undertaken. Results: Self harm was associated with violence in prison, representing a 3.5-fold risk of violence compared with men who did not self-harm, after controlling for time in prison, age and index offence. 60% of men who harmed themselves also engaged in custodial violence, while 32% who were violent also had a self-harm event. After controlling for age at first incident, 11% of the sample had custodial history of dual harm and they accounted for 56% of all recorded custodial incidents. They had a high probability of property damage and fire-setting in prison and spent 40% longer in custody). Men who dual harmed used a greater variety of self-harm methods, with increased use of lethal methods. Conclusion: Dual harm is prevalent, particularly amongst those who harm themselves in prison. Men who dual harm contribute excessively to the overall incident burden in prison and demonstrate behavioural variability and risk regarding both violence and self-harm. The findings challenge the usual distinctive management responses or that self-harm or violence are solely the responsibility of health or justice; with greater integration required.
Water is the taste of life – the contribution of metacognitive guidance to drinking-related nutritional literacy

This study examined the contribution of metacognitive guidance to the development of drinking-related nutritional literacy (DNL). Metacognitive awareness promotes meaningful learning. Active involvement of students in metacognitive activities develops deep conceptual understanding. Childhood food and beverage consumption affects growth and can be a predictor of adult obesity, diabetes, and cardiovascular diseases. One of the factors that might improve food and beverage consumption is nutritional literacy. The research examined 225 students aged 9–11 and included a research and a control group. In both groups, students prepared and conducted an activity for students aged 6–8, as part of their science class. The activity sought to encourage the drinking of water and reducing the consumption of sweetened drinks. In the research group, the students received metacognitive guidance while preparing the activity. Changes in DNL in the areas of knowledge, attitudes, and behavior were tested by analysis of quantitative questionnaires. While there was no difference between the research and control groups in knowledge, the metacognitive guidance generated improvement in drinking-related attitudes and behavior. The improvement was seen both for everyday circumstances and at special occasions and emphasizes the great potential of expanding the relationship between metacognition and nutritional literacy.
An Inexpensive Way to Prevent Phishing using OCR Technology

-Phishing is one of the main thrusts of the country and world , e-commerce is also predominant in the growing mobile services abroad mainly from the growing mobile services, although many consumers are tired with phishing. Fishing is also a major part of the mainly unfortunate attacks, from URL addresses to suspicious routes. Most browser vendors predominantly adopt blacklists and heuristic based although both have limited limitations.This paper is proposed to protect against the novel method of image recognition of phishing attacks using the OCR technique of phishing attacks. Can be realistically different from the website by people reading on the website and comparing people with the website. index terms was the highest score performance to implement site URL prototype for the detection accuracy of experimental
Finding a Stable Phillips Curve Relationship: A Persistence-Dependent Regression Model

We establish that the Phillips curve is persistence-dependent: inflation responds differently to persistent versus moderately persistent (or versus transient) fluctuations in the unemployment gap. Previous work fails to model this dependence, so it finds numerous “inflation puzzles”—such as missing inflation/disinflation—noted in the literature. Our model specification eliminates these puzzles; for example, the Phillips curve has not weakened, and inflation is not “stubbornly low” at present. The model’s coefficients are stable, and it provides accurate conditional recursive forecasts through the Great Recession. The persistence-dependent relationship we uncover is interpretable as being business-cycle-phase-dependent and is thus consistent with existing theory.
A Generic and Flexible Framework for Selecting Correspondences in Matching and Alignment Problems

The Web 2.0 and the inexpensive cost of storage have pushed towards an exponential growth in the volume of collected and produced data. However, the integration of distributed and heterogeneous data sources has become the bottleneck for many applications, and it therefore still largely relies on manual tasks. One of this task, named matching or alignment, is the discovery of correspondences, i.e., semantically-equivalent elements in different data sources. Most approaches which attempt to solve this challenge face the issue of deciding whether a pair of elements is a correspondence or not, given the similarity value(s) computed for this pair. In this paper, we propose a generic and flexible framework for selecting the correspondences by relying on the discriminative similarity values for a pair. Running experiments on a public dataset has demonstrated the im-provment in terms of quality and the robustness for adding new similarity measures without user intervention for tuning.
Theoretical Framework for a Local, Agile Supply Chain to Create Innovative Product Closer to End-user: Onshore-Offshore Debate

This paper presents a conceptual model of a viable onshore, agile supply chain approach for innovative product manufacturers in the manufacturing sector. As such, this paper provides insight into the drawbacks of offshore manufacturing and an empirical investigation into the importance of the manufacturing sector. This study aims to answer the research question: how can agile supply chain management add value to the manufacturing to create innovative products closer to the end-user? A theoretical framework was developed through a qualitative methodology to demonstrate effective onshore operation and supply chain. For the first time, the combination of Dynamic Capabilities (DC) and Total Cost of Ownership (TCO) theories has been used as a lens to examine the location decision of a close geographical supply chain network – global supply chain debate. Offshore manufacturing and global sourcing do not appear to fit the DC theory in a geographically and culturally distant situation, especially when supply chains involve operations in different continents. The ‘theoretical perspective’, including DC and TCO suggests that companies should frequently integrate, build and reconfigure internal and external competences to promptly react to the changing environment and they should also wisely calculate all the indirect, hidden, lifecycle and transaction costs of an operation when considering moving production offshore. Although studies in the agile supply chain area have examined competitiveness from several perspectives, there has been little to no research focusing on the advantages of agile, nearshore operation and supply chain solutions. This research notably widens the theoretical perspective of agility and adaptability for innovative product manufacturers in the manufacturing sector, and the viability of remaining close to the market and apply agile supply chain.
Analysis of heat and mass transfer mechanism during thermal energy storage and temperature regulation

To strengthen the heat and mass transfer capacity and improve the temperature regulation rate, potential storage is taken as the research object in this research to study the heat energy storage of the battery in the low temperature environment. Lattice Boltzmann method is adopted to study the heat energy storage influence mechanism of the temperature regulation system of the low temperature phase-change materials. In addition, the influence of different physical parameters (thermal conductivity and latent heat of phase change) on the thermal insulation of the system in the process of temperature control is revealed. The results show that the mechanism of heat and mass transfer in the process of heat storage and temperature control is related to the different physical properties of phase change materials. The decrease of thermal conductivity and the increase of latent heat of phase change materials will greatly increase the effect of heat energy storage. Therefore, under the action of phase change latent heat, phase change material can effectively extend the holding time of the battery in the low temperature environment.
Data Mining for Student Performance Prediction in Education

The ability to predict the performance tendency of students is very important to improve their teaching skills. It has become a valuable knowledge that can be used for different purposes; for example, a strategic plan can be applied for the development of a quality education. This paper proposes the application of data mining techniques to predict the final grades of students based on their historical data. In the experimental studies, three well-known data mining techniques (decision tree, random forest, and naive Bayes) were employed on two educational datasets related to mathematics lesson and Portuguese language lesson. The results showed the effectiveness of data mining learning techniques when predicting the performances of students.
Quick estimation of egg number in compact ovisacs of pink hibiscus mealybug, Maconellicoccus hirsutus (Green)

Estimating the number of eggs in a mealybug ovisac (= egg sac) is not only tedious but time consuming. Here, we explain a simple method to estimate the number of eggs in a mealybug ovisac using the ovisac parameters viz., length, width, weight. When subjected to correlation analysis these parameters revealed significant association (P = 0.01) between number of eggs per ovisac with ovisac length (r=0.81) and weight (r=0.69) but not with ovisac width. Further detailed step-wise regression analyses revealed that ovisac length (cm) and ovisac weight (mg) together can predict variability in the number of eggs to the tune of 72% (-110.45 + 897.61 x1 + 28.72 x2; F =46.63; edf =36; P <0.0001). Further, ovisac length alone could predict the egg number to the tune of 66% (F = 70.42; edf = 36; P<0.0001). This method can speed up the mealybug egg estimation vis a vis population in both field as well as laboratory conditions.