Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Super Cut-off Transistors for Ultralow Power Digital Logic Circuits

Super cut-off devices with sub-60mV/decade subthreshold swings have recently been demonstrated and being extensively studied. This paper presents a feasibility analysis of such tunneling devices for ultralow power subthreshold logic. Analysis shows that this device can deliver 800times higher performance (@iso-IOFF) compared to a MOSFET. The possible use of this device as a sleep transistor in conjunction with the regular Si MOSFET shows 2000times average improvement in leakage power compared to Si MOSFETs
A Proposal of New Autonomous Decentralized Structure Formation Based on Huygens' Principle and Renormalization

—This paper proposes an autonomous distributed algorithm that can construct spatial structures for clustering in MANETs. Since the topology of a MANET changes frequently, a fast, light-weight, and autonomous clustering mechanism is required. However, existing autonomous clustering mechanisms are based on differential equations and thus demand a lot of calculations for generating the spatial structures that yield clustering. This paper proposes an autonomous clustering algo-rithm that is based on Huygens’ principle. The most remarkable characteristics of our proposal are calculation simplicity and fast convergence on the cluster structures. We verify the basic characteristics of the proposed algorithm.
Association of Antioxidants With Allergic Rhinitis in Children From Seoul

Purpose The prevalence of allergic diseases has risen over the last few decades. Many factors, including environmental factors such as those related to diet, have been considered. Among dietary factors, intake of antioxidant-related nutrients has been associated with the risk of allergic disease. We investigated the association of antioxidant nutritional status with allergic rhinitis (AR) in Korean schoolchildren aged 6-12 years. Methods Subjects were 4,554 children in Seoul, Korea. The risk of allergic disease was measured using the Korean version of the International Study of Asthma and Allergies in Childhood, and dietary intake was measured by a semi-quantitative food frequency questionnaire. Intake of vitamins A (including retinol and β-carotene), C, and E was used in the analysis. Results Vitamin C intake was negatively associated with an increased risk of current symptoms (adjusted odds ratio, 0.886; 95% confidence interval, 0.806-0.973). There was no association between AR and intake of vitamin A, retinol, β-carotene, or vitamin E. Total serum IgE level and sensitization to allergen did not differ according to nutrient intake. Conclusions The group of children with increased vitamin C consumption had fewer AR symptoms, despite the lack of a difference in total serum IgE level or allergen sensitization. These findings suggest that nutrient intake, especially that of vitamin C, influences AR symptoms.
Contrasting Automated and Human Scoring of Essays

Essay scoring has traditionally relied on human raters, who understand both the content and the quality of writing. However, the increasing use of constructedresponse items, and the large number of students that will be exposed to such items in assessments based on the Common Core State Standards (CCSS), raise questions about the viability of relying on human scoring alone. This scoring method is expensive, requires extensive logistical efforts, and depends on less-than-perfect human judgment. Testing programs are therefore tapping into the power of computers to score constructed-response items efficiently. The interest in automated scoring of essays is not new and has recently received additional attention from two federally supported consortia, PARCC and Smarter Balanced, which intend to incorporate automated scoring into their common core state assessments planned for 2014. Nonetheless, human labor cannot simply be replaced with machines, since human scoring and automated scoring have different strengths and limitations. In this essay, the two scoring methods are compared from measurement and logistical perspectives. Conclusions are drawn from research literature, including ETS research, to summarize the current state of automated essay scoring technology. The published research has few in-depth comparisons of the advantages and limitations of automated and human scoring. There are also debates in academia, the media, and among the general public concerning the use of automated scoring of essays in standardized tests and in electronic learning environments used in and outside of classrooms. It is important for test developers, policymakers, and educators to have sufficient knowledge about the strengths and weaknesses of each scoring method in order to prevent misuse in a testing program. The purpose of this essay is to contrast significant characteristics of the two scoring methods, elucidate their differences, and discuss their practical implications for testing programs.
Physiological Effects of a Simple Adaptive Ankle Exoskeleton

A major problem in exoskeleton design is the unnatural movement that comes from a poor human machine interface. Innovative controller designs are a primary focus in making the interface between man and machine more fluid and intuitive. One controls approach is to detect the user’s intent to move and then command the exoskeleton’s actuators to act appropriately. These types of controllers rely on intrinsic mechanical measurements such as angles, forces/torques, or accelerations to sense the user’s intent. Once the controller has detected intent, it then commands actuators to move in parallel with the user to assist them through predefined motions [1]. These control schemes commonly lag behind the user because the intrinsic mechanical measurements are only sensed once the user has already begun movement [2]. Additionally, many of these controllers are constraining the user to move in a particular predefined manner, one that may not be to the user’s preference.
Adaptive feedforward and feedback control schemes for sliding mode controlled power converters

A major disadvantage of applying sliding mode control to dc/dc converters is that the steady-state switching frequency is affected by line and load variations. This is undesirable as it complicates the design of the input and output filters. To reduce switching frequency deviation in the events of line and load variations, an adaptive feedforward control scheme that varies the hysteresis band according to the change of line input voltage and an adaptive feedback control scheme that varies the control parameter (i.e., sliding coefficient) according to the change of the output load are proposed. This paper presents a thorough investigation into the problem and the effectiveness of the proposed solutions. In addition, methods of implementing the proposed adaptive control strategies are discussed. Experimental results confirm that the adaptive control schemes are capable of reducing the switching frequency variations caused by both line and load variations.
Brecha digital, uso frecuente y aprovechamiento de Internet en México

El abordaje de la brecha digital en el contexto de los usuarios frecuentes de Internet constituye un acercamiento poco usual, a pesar de la necesidad de validar los supuestos socioterritoriales que pretenden participar en la construcción de su teoría. Con base en ello, este artículo tiene el objetivo de averiguar la validez de un modelo de accesibilidad moderado por el tamaño de las localidades donde habitan los usuarios mexicanos. La investigación se sustenta en microdatos de la Encuesta Nacional sobre Disponibilidad y Uso de las Tecnologías de la Información en los Hogares (Inegi, 2016a) y recurre a la modelación con ecuaciones estructurales para la validación de las hipótesis planteadas. Los resultados de la investigación dejan entrever una multidimensionalidad en el modelo socioterritorial, la cual es estructurada alrededor de diferencias significativas entre grupos locales y un uso frecuente que no parece asociado en todos los casos con habilidades y un aprovechamiento de Internet.
Probabilistic Metrics for Soft-Clustering and Topic Model Validation

In this paper the problem of performing external validation of the semantic coherence of topic models is considered. The Fowlkes-Mallows index, a known clustering validation metric, is generalized for the case of overlapping partitions and multi-labeled collections, thus making it suitable for validating topic modeling algorithms. In addition, we propose new probabilistic metrics inspired by the concepts of recall and precision. The proposed metrics also have clear probabilistic interpretations and can be applied to validate and compare other soft and overlapping clustering algorithms. The approach is exemplified by using the Reuters-21578 multi-labeled collection to validate LDA models, then using Monte Carlo simulations to show the convergence to the predicted results. Additional statistical evidence is provided to better understand the relation of the metrics presented.
Accurate statistical soft error rate (SSER) analysis using a quasi-Monte Carlo framework with quality cell models

For CMOS designs in sub 90nm technologies, statistical methods are necessary to accurately estimate circuit SER considering process variations. However, due to the lack of quality statistical models, current statistical SER (SSER) frameworks have not yet achieved satisfactory accuracy. In this work, we present accurate table-based cell models, based on which a Monte Carlo SSER analysis framework is built. We further propose a heuristic to customize the use of quasirandom sequences, which successfully speeds up the convergence of simulation error and hence shortens the runtime. Experimental results show that this framework is capable of more precisely estimating circuit SSERs with reasonable speed.
Design measurement: some lessons learned

The author extracts from several measurement projects some of the important lessons he has learned about measurement in general and design measurement in particular. He synthesizes from these lessons a design-measurement framework in an attempt to communicate his personal measurement experience to other software engineers. The lessons he has learned fall into three areas: (1) how measurement must be applied in individual experiments or case studies; (2) how measurement can help continuously improve an organization's state of the practice; and (3) why measurement requires automated support. <<ETX>>
Fault detection of networked control systems with disturbance

Fault detection problem of networked control systems with network-induced delay, data packets dropout and disturbance in sensor-to-controller link is discussed. First, we design an observer-based residual generator, and model the residual dynamics to be a discrete-time markovian jump linear system in this paper. By using H∞ optimization theory and linear matrix in-equation approach, the solution of alarm threshold is proposed. Then we introduce a new index to design a fault detection filter, which improves the performance of dynamic system, the sensitivity of the detection system to the fault. The approach of solving suitable observer gain matrix is proposed. At last, a numerical example is given to verify the effect of the method presented in this paper.
Introduction to This Special Issue: The Role of Morphology in Learning to Read

Reading involves the decoding of written forms into language forms that represent phonological, morphological, and word level units. Thus, orthographies convey not only phonological but also morphological information-the word roots, syntactic inflections, and derivational relations that constitute the minimal semantic and grammatical units of a language. There are many psycholinguistic issues brought to light by the facts about morphology. However, the central one has focused on decomposition-whether and how language users, including readers, decompose morphologically complex words into their constituent morphemes.
ScholarWorks@BGSU ScholarWorks@BGSU

: This study critically analyzed the current body of published research on microblogging in education (MIE) to build a deep and comprehensive understanding of this increasingly popular phenomenon. Twenty-one studies on MIE in 2008-2011 were selected based on the selection criteria and analyzed to answer the following questions: (a) What types of research have been published on MIE? (b) How was microblogging used for teaching and learning in these studies? (c) What educational benefits did microblogging have on teaching and learning? and (d) What suggestions and implications did the current research have for future MIE research and practices? The analysis suggested that microblogging has a potential to encourage participation, engagement, reflective thinking as well as collaborative learning under different learning settings. The quality of research, however, varies greatly, suggesting a need for rigorous research on MIE. The analysis has implications for MIE practices as well as research and development efforts.
Confounding issues related to determining sample size in qualitative research

ABSTRACT The debate on determining sample size in qualitative research is confounded by four fundamental methodological issues: the exclusive focus on theme analysis; the diverse and imprecise use of ‘qualitative’; a reliance on only two logics of inquiry, induction and deduction, and the occasional confusion of abduction with induction; and a general lack of recognition of the importance of differences in ontological assumptions. Embedded in these issues is an unwarranted acceptance of limited associations between certain assumptions, logics, forms of data, and methods of data collection/generation and analysis. What is required is a reformulation of the problem and its discussion with reference to ontological assumptions and logics of inquiry.
PTP1B in Calpain Dependent Feedback Regulation of VEGFR2 in Endothelial Cells: Implication in VEGF‐Dependent Angiogenesis and Diabetic Wound Healing

The VEGF/VEGFR2/Akt/eNOS/NO pathway is essential to VEGF‐induced angiogenesis. We have previously discovered a novel role of calpain in mediating VEGF‐induced PI3K/AMPK/Akt/eNOS activation through Ezrin. Here, we sought to identify possible feedback regulation of VEGFR2 by calpain via cleavage and activation of its substrate protein phosphotyrosine phosphatase 1B (PTP1B), and the relevance of this pathway to VEGF‐induced angiogenesis, especially in diabetic wound healing. Over‐expression of PTP1B inhibited VEGF‐induced VEGFR2 and Akt phosphorylation in bovine aortic endothelial cells (BAECs), while PTP1B siRNA increased both VEGFR2 and Akt phosphorylation in response to VEGF stimulation. Calpain inhibitor induced VEGFR2 activation can be completely blocked by PTP1B over‐expression. These data implicate calpain/PTP1B feedback regulation of VEGFR2. We next examined a potential role of PTP1B in VEGF‐induced angiogenesis. Endothelial cells transfected with PTP1B siRNA showed faster wound closure in response to VEGF. Aortic discs isolated from PTP1B siRNA transfected mice also had augmented endothelial outgrowth. To further define the role of PTP1B in physiological angiogenesis in vivo, wound healing assay in diabetic mice was carried out. Furthermore, we found that PTP1B over‐expression or calpain inhibition significantly deteriorated wound healing in STZ‐induced diabetic mice. In conclusion, our data for the first time demonstrate a calpain/PTP1B/VEGFR2 negative feedback loop. A critical role of PTP1B as a negative regulator in VEGF‐induced angiogenesis is revealed. Modulation of local calpain and PTP1B activities may prove beneficial in the treatment of defective wound healing in diabetes.
Filled Pauses in Spontaneous Speech Filled Pauses in Spontaneous Speech

Das diesem Bericht zugrundeliegende Forschungsvorhaben wurde mit Mitteln des Bundesministers f ur Bildung, Wissenschaft, Forschung und Technologie unter dem F orderkennzeichen 01 IV 102 F/4 und 01 IV 102 H/0 gef ordert. Die Verantwortung f ur den Inhalt dieser Arbeit liegt bei den Autoren. ABSTRACT Filled pauses as, e.g., uh, eh, signal dis-uencies, i.e. hesitations or repairs. They do normally not occur in read speech and were therefore up to now rather seldom investigated; they must, however, be accounted for in the (automatic) processing of spontaneous speech. We present descriptive statistics and the results of an automatic classiication of lled pauses in the database of the VERBMOBIL project and discuss the relevancy of diierent prosodic features for the marking of diierent types.
Generalized adaptive comb filter with improved accuracy and robustness properties

Generalized adaptive comb filters can be used to identify/track parameters of quasi-periodically varying systems. In a special, signal case they reduce down to adaptive comb filters, applied to elimination or extraction of nonstationary multi-harmonic signals buried in noise. We propose a new algorithm which combines, in an adaptive way, results yielded by several, simultaneously working generalized adaptive comb filters. Due to its highly parallel estimation structure, the new algorithm is more accurate and more robust than the currently available algorithms.
Multivariate relationships between instrumental attributes, microstructure, sensory profiles and consumer preference in roasted peanuts (Arachis spp)

The objective of this research was to determine how raw material and process technology selection can affect the organoleptic characteristics of roasted peanuts, and further identify which of those characteristics drive liking with European consumers. Twelve different raw peanuts of various market types, origins and grades were treated by eleven different process (maceration in water, aqueous glucose and at different pH followed by frying or baking), resulting in 134 unique samples, which were profiled by a sensory panel (SPECTRUM, DSA) and analysed for colour (CIELAB), fatty acid composition (FAMEs-GC-MS), headspace volatile composition (DHS-GC-MS, SPME-GC-MS, and GC-MS-O), sugar profile (ion chromatography), and textural characteristics (large deformation compression). Principal Component Analysis, Canonical Variate Analysis and General Linear Model regressions were used to identify differences in sensory attributes, fatty acid and headspace volatile profiles, and to relate them to raw materials and process conditions. Process selection had a large impact on the final sensory characteristics. Specifically, baking reduced ‘roasted peanut’ and ‘dark roast’ and increased ‘raw bean’ aromas compared to frying. Maceration significantly increased ‘roasted peanut’ and ‘dark roast’, and reduced ‘sweet’, ‘raw bean’ aromas, and sweetness. ‘Crispy’, ‘crunchy’ and ‘hardness’ attributes were significantly rated higher in the presence of glucose in the medium, while the effect of pH was minor. The microstructure was further probed with confocal microscopy and X-ray tomography. The degree of alveolation was similar in differently processed macerated peanuts, even though sensory attributes were significantly different. Quantitative data on alveolation showed that microstructure disruption through steam generation cannot explain all the texture differences among processed peanuts. Correlations between sensory and instrumental attributes were also explored using Partial Least Squares Regression. Several headspace volatile compounds which positively or negatively correlated to ‘roasted peanut’, ‘raw bean’, ‘dark roast’ and ‘sweet’ attributes were identified. It was also determined that sensory texture attributes can be predicted from instrumental measurements, but a multivariate approach using both hardness and toughness data from different probe geometries was necessary. 26 of the most varied samples were hedonically rated by consumers in The Netherlands, Spain and Turkey (n>200 each). Preference map models revealed that the drivers of liking are similar across the three countries. Sweet taste, ‘roasted peanut’, ‘dark roast’ and ‘sweet’ aromas and the colour b* value were related to increased liking, and ‘raw bean’ aroma and bitter taste with decreased liking. The colour coordinates, sucrose content, several pyrroles and low levels of hexanal and 2-heptanone were strong predictors of both preference and perceived freshness.
Line hand feature-based palm-print identification system using learning vector quantization

Palm print identification has become one of the most active research areas of image processing, computer vision, graphics, and visualization. The palm print identification problems which are due to affectedness, illumination, impediment, shadow, and blur are undertaken using various methods such as hierarchal feature-based, template matching, graphical record matching, and artificial neural network approach. We propose a line hand feature-based palm print identification system with GLCM feature extraction (including 5 differentiators-Angular Second Moment/Energy, Contrast, Homogeneity/Inverse Difference Moment, Entropy, Correlation) and Learning Vector Quantization (LVQ) artificial neural network as a classifier. The motivation of using this palm print identification is because of its unique solution to the stability-malleability dilemma, where it is the ability to preserve antecedently learnt knowledge (stability), and potency to accommodate new patterns indefinitely (malleability). Another motivation is also used for biometric authentication of a person's identity because of its profusion, where it not only has the information available on the fingerprint, but also it has a far more amount of details in terms of principal lines and wrinkles. Yet compared with the other biometric characteristics, palm print identification has several advantages : low-cost capturing device, low-resolution imaging, and low-officiousness. The experiments show a promising result by using the proposed method that obtained an identification rate of 98.75%.