Miracle-dz/UniFAR-FTUs huggingface dataset:
RFCMOS Unit Width Optimization Technique

In this paper, we demonstrate a unit width ( Wf) optimization technique based on their unity short-circuit current gain frequency (fT) unilateral power gain frequency (fMAX)? and high-frequency (HF) noise for RFCMOS transistors. Our results show that the trend for the above figures-of-merit (FOMs) with respect to the Wf change is different; hence, some tradeoff is required to obtain the optimum Wf value. During the HF noise analysis, a new FOM is proposed to study the Wf effect on the HF noise performance. In our experiment, the flicker noise of the transistor is also measured and the result shows that the change in Wf does not affect the noise spectral density at the low-frequency range. This technique enables RF engineers to optimize the transistor's layout and helps to select the optimum Wf for transistors used in specific circuit design such as the low-noise amplifier, voltage-controlled oscillator, and mixer. Furthermore, by using layout optimized transistors in the RF circuit, the optimal circuit's performance can be easily achieved and, thus, greatly reduced the circuit development time. In the aspect of RF device modeling, by knowing the optimum Wf for a particular process or technology, the number of transistors to model is reduced and, hence, greatly shortens the RF modeling development time for existing and future technologies.
Measuring the Political Salience of Supreme Court Cases

While Supreme Court cases are generally salient or important, some are many degrees more important than others. A wide range of theoretical and empirical work throughout the study of judicial politics implicates this varying salience. Some work considers salience a variable to be explained, perhaps with judicial behavior the explanatory factor. The currently dominant measure of salience is the existence of newspaper coverage of a decision, but decisions themselves are an act of judicial politics. Because this coverage measure is affected only after a decision is announced, using it limits the types of inferences we can draw about salience. We develop a measure of latent salience, one that builds on existing work, but that also explicitly incorporates and models predecision information. This measure has the potential to ameliorate concerns of causal inference, put research findings on sounder footing, and add to our understanding of judicial behavior.
Modelling selectional preferences in a lexical hierarchy

This paper describes Bayesian selectional preference models that incorporate knowledge from a lexical hierarchy such as WordNet. Inspired by previous work on modelling with WordNet, these approaches are based either on "cutting" the hierarchy at an appropriate level of generalisation or on a "walking" model that selects a path from the root to a leaf. In an evaluation comparing against human plausibility judgements, we show that the models presented here outperform previously proposed comparable WordNet-based models, are competitive with state-of-the-art selectional preference models and are particularly well-suited to estimating plausibility for items that were not seen in training.
A supervised evaluation method based on region shape descriptor for image segmentation algorithm

In this paper we present a new supervised evaluation method for measuring the accuracy of image segmentation algorithms. This method calculates the extent of similarity between segmented images against ground truth. Feature vectors are computed based on the shape descriptor for each region in segmented image and then compared with the feature vectors of ground truth image. The proposed method can be used for any type of grayscale and color images with any number of regions. It also limits under-segmentation and over-segmentation problems. We compare the efficiency of the proposed method with extended version of four different supervised evaluation measures such as, global consistency error (GCE), local consistency error (LCE), object-level consistency error (OCE using Dice's coefficient) and the Jaccard index. Analysis of the experimental results on a large variety of test images from the Berkeley segmentation dataset demonstrates the efficiency of the proposed method.
Characterization of tobacco withdrawal: physiological and subjective effects.

In total, our studies show that changes which occur reliably and consistently in chronic smokers after tobacco deprivation include: decreased heart rate, increased caloric intake/eating, increased number of awakenings during sleep, increased craving for tobacco, and increased confusion, as measured by the POMS. Other changes that were found to occur after tobacco deprivation in some but not all of our studies include decreased orthostatic heart rate, increased irritability, and decreased vigor score on the POMS. Previous investigators have found a consistent effect of tobacco deprivation on heart rate (Gilbert and Pope 1982; Knapp et al. 1963; Parsons and Hamme 1975; Weybrew and Stark 1967; Glauser et al. 1970; Myrsten et al. 1977; Murphee and Schultz 1968). Although decreased blood pressure (Knapp et al. 1963; Murphee and Schultz 1968) and changes in other vital signs such as temperature (Gilbert and Pope 1982; Myrsten et al. 1977; Ague 1974) have been reported, our present studies and studies by others (Weybrew and Stark 1967; Glauser et al. 1970) failed to find a significant deprivation effect on these measures. Perhaps the contradictory findings are a function of the reliability of the measures themselves or of the population tested. Caloric intake has been found to increase in both animals and humans after nicotine or smoking cessation (Gruneberg 1982; Myrsten et al. 1977; Wack and Rodin 1982). These results are consistent with studies which have found that smoking cessation causes an increase in body weight (Wack and Rodin 1982). However, previous studies disagree on how smoking cessation causes weight gain. Our inpatient study is believed to be the first to simultaneously measure changes in caloric intake, fluid retention, and physical activity after tobacco deprivation. In the study, caloric intake increased but fluid retention and physical activity did not change. The increases in weight may not be accounted for solely by increases in caloric intake. There may be other factors such as decreased basal metabolic rate which cause the increase in weight. Other studies have also reported sleep disturbance or insomnia among tobacco-deprived smokers (Larson et al. 1961; Weybrew and Stark 1967). Studies directly monitoring sleep have found a decrease in duration awake (Soldatos et al. 1980), increased REM sleep (Soldatos et al. 1980; Kales et al. 1970; Parsons et al. 1975), and increased Stage IV (greater than 50% delta waves) sleep (Parson et al. 1975; Parsons and Hamme 1975). Thus, objective data indicate that after tobacco deprivation smokers actually sleep longer, which contradicts subjective reports of insomnia. (ABSTRACT TRUNCATED AT 400 WORDS)
Encontros e desencontros entre a saúde do homem, a promoção da paternidade participativa e a saúde sexual e reprodutiva na atenção básica

Resumo Neste artigo, objetivamos problematizar tres acoes desenvolvidas em unidades basicas de saude de tres municipios de regioes brasileiras distintas, voltadas para a saude do homem, a promocao da paternidade participativa comprometida com o cuidado e a saude sexual e reprodutiva. Trata-se de uma pesquisa qualitativa em que os dados foram construidos atraves de observacoes e de entrevistas com 17 homens, usuarios do sistema de saude e envolvidos nessas acoes. Na analise dos dados, foram trazidos de forma especial os conceitos de genero, masculinidades e integralidade; como metodologia de analise, lancamos mao da perspectiva hermeneutica-dialetica. Dentre outros aspectos, concluimos que os homens percebem que as questoes de genero ainda sao impeditivos para essa insercao, assim como a organizacao do proprio sistema; e que as acoes analisadas se organizam de forma estanque e fragmentada, atuando sobre aspectos isolados da saude masculina, nao contemplando o principio da integralidade e dificultando a promocao do vinculo desses homens ao sistema pela atencao primaria.
Ambient Activity Technologies for Managing Responsive Behaviours in Dementia

Many people living with dementia are under-stimulated and socially isolated. While there has been an increase in activities and programming based on recreational therapy and music therapy, such programs can cover only a fraction of the day for people with dementia and are resource demanding to execute. The result is that many people with dementia, who are institutionalized, are staying most of the day either in their rooms, sitting in communal areas, or wandering the hallways. A related problem is that people with dementia often have difficulty with social interactions and may become anxious or aggressive around people they do not recognize, or in situations they do not understand. Resulting responsive behaviours (e.g., hitting, screaming) may lead to overmedication and poor quality of life. Ambient Activity Technology (AAT) is a wall-mounted interactive tool designed for people with dementia. The AAT unit is available in the environment for easy access, and have been designed to augment existing programming and activities by providing self-accessed, engaging and personalized interactions at any time (24-hours per day, 7 days/week). AATs have been designed to reduce distress, in residents and caregivers, by substituting responsive behaviours and purposelessness with active and meaningful activities, distractions, and appropriate interventions. This paper describes the motivation behind the design and development of the AAT. The paper ends with a description of our summative evaluation research, which is currently in progress at several long-term care facilities in Ontario, Canada.
Electrical-SNR-optimized detection threshold for OOK IM/DD optical wireless communications

We first revisit the problem of on-off keying demodulation with fixed detection thresholds over atmospheric turbulence channels. The resulting error floors are derived for a variety of turbulence channel models. To eliminate the irreducible error floors, we propose a detection system based on the electrical signal-to-noise ratio. Such a system offers performance compromise between the optimum system with time-varying detection threshold and the suboptimal system with fixed detection threshold.
Teachers' Motivational Strategies Used in Indonesian EFL Islamic University Students

Captivating EFL learners’ attention in a learning process is challenging for every teachers. The teachers must employ appropriate treatment and have motivational strategies to maintain students’ enthusiasm in learning. Ample research has been conducted to explore teachers’ motivational strategies in teaching English of primary and secondary schools. However, little study has been conducted in university level of students. Therefore, this study is aimed to investigate the use of motivational strategies by teachers in one of the Islamic universities in Indonesia. There were three different teachers as the participants of this research. A qualitative research design was employed to collect the data. Three different groups of students were involved for class observation. The data were collected from teachers by conducting classroom observation, interviews and video recording activity. The finding of the research revealed that each teacher has unique motivational strategies to teach EFL university students. Besides, in the context of Islamic-based university, students get more excited to learn English when the teachers were able to make a connection on English materials, the Islamic values and implication in the real life. Keywords—teachers, motivational strategies, EFL Islamic
Bilingual Software Requirements Tracing using Vector Space Model

In the software engineering world, creating and maintaining relationships between byproducts generated during the software lifecycle is crucial. A typical relation is the one that exists between an item in the requirements document and a block in the subsequent system design, i.e. class in the source code. In many software engineering projects, the requirement documentation is prepared in the language of the developers, whereas developers prefer to use the English language in the software development process. In this paper, we use the vector space model to extract traceability links between the requirements written in one language (Turkish) and the implementations of classes in another language (English). The experiments show that, by using a generic translator such as Google translate, we can obtain promising results, which can also be improved by using comment info in the source code.
Improving Named Entity Extraction Accuracy using Unlabeled Data and Several Extractors (pp. 29-38)

This paper proposes feature augmentation methods using unlabeled data and several Named Entity (NE) extractors. We collect NE-related information of each word (which we call NE-related labels) from unlabeled data by using NE extractors. NE-related labels which we collect include candidate NE class labels of each word and NE class labels of co-occurring words. To accurately collect the NE-related labels from unlabeled data, we consider methods to collect NE-related labels by using outputs of several NE extractors. We use NE-related labels as additional features for creating new NE extractors. We apply our NE extraction methods using the NE-related labels to IREX Japanese NE extraction task. The experimental results show better accuracy than the previous results obtained with NE extractors using handcrafted resources.
SAIL: Summation-bAsed Incremental Learning for Information-Theoretic Text Clustering

Information-theoretic clustering aims to exploit information-theoretic measures as the clustering criteria. A common practice on this topic is the so-called Info-Kmeans, which performs K-means clustering with KL-divergence as the proximity function. While expert efforts on Info-Kmeans have shown promising results, a remaining challenge is to deal with high-dimensional sparse data such as text corpora. Indeed, it is possible that the centroids contain many zero-value features for high-dimensional text vectors, which leads to infinite KL-divergence values and creates a dilemma in assigning objects to centroids during the iteration process of Info-Kmeans. To meet this challenge, in this paper, we propose a Summation-bAsed Incremental Learning (SAIL) algorithm for Info-Kmeans clustering. Specifically, by using an equivalent objective function, SAIL replaces the computation of KL-divergence by the incremental computation of Shannon entropy. This can avoid the zero-feature dilemma caused by the use of KL-divergence. To improve the clustering quality, we further introduce the variable neighborhood search scheme and propose the V-SAIL algorithm, which is then accelerated by a multithreaded scheme in PV-SAIL. Our experimental results on various real-world text collections have shown that, with SAIL as a booster, the clustering performance of Info-Kmeans can be significantly improved. Also, V-SAIL and PV-SAIL indeed help improve the clustering quality at a lower cost of computation.
Dual-Band Superconducting Spiral Filters Including Narrow Bandstop Notches

Dual-band filters designed as bandpass filters containing bandstop notches are described. The design formulation is simplified by considering the resonators in pairs. Two microstrip superconducting spiral filters are presented with 400-MHz center frequency, 15%-16% overall bandwidth, and notches of 1% and 0.1%, respectively. Internal dimensions of the enclosures are only 32 mm times 30 mm times6 mm. Suitable spiral shapes and orientations enable the required wide range of coupling coefficients to be implemented, and also reduce unwanted coupling without using partitions. The remaining low level of unwanted coupling is cancelled using capacitive bridges. A qualitative understanding of spurious interactions between spirals is obtained via electromagnetic simulations.
Resilient key establishment for mobile sensor networks

Wireless Sensor Networks (WSN) are self-organizing and resource-constrained networks composed of battery-powered small devices called sensor nodes. WSNs are typically deployed in unattended areas. In order to secure WSNs, firstly cryptographic keys must be distributed in a secure and robust way. Key distribution problem is extensively studied for static WSNs, but has not been studied widely for mobile WSNs (MWSN) in the literature. In this paper we propose a key distribution mechanism for MWSNs in which both sensor nodes and the BS are mobile. In our scheme BS acts as a mobile key distribution center which distributes pairwise keys to sensor nodes in a single hop. Our performance evaluations show that the proposed scheme outperforms mobile versions of two existing schemes in the literature. Moreover, our scheme has perfect resilience against node capture attacks.
Traffic signal control enhancements under vehicle infrastructure integration systems.

i Executive Summary 1 PART I: Introduction 2 1. Background of Traffic Control 2 1.1 Traffic Responsive Closed-Loop Systems 2 1.2 Adaptive Control Algorithms 3 2. The Paradigm Shift in Traffic Control 4 PART II: Fundamental Research on Typical Driver Behavior 5 1. An Agent-based Framework for Modeling Driver Left-turn Gap Acceptance Behavior at Signalized Intersections 5 1.
Warning: Sex Offenders Need to be Supervised in the Community

MANY HAVE PROBABLY read the seemingly unnecessary instructions that accompany different products. The instructions manual for a hair dryer, for example, states, "Do not use in shower. " A packet of peanuts given to airline passengers wisely advises: "Open packet. Eat peanuts. " Those purchasing a certain brand of plumbing draining liquid are told, "Do not reuse the bottle to store beverages. " If one were to develop an analogous instruction manual for probation or parole officers supervising sex offenders, the contents of the manual might tell probation and parole officers to "Watch sex offenders closely. " Such an instruction would likely be received with wonderment about why one would feel the need to state the obvious. Nevertheless, not enough guidance in the form of training has been offered to probation and parole officers supervising sex offenders.
Spectral corrections for a class of eigenvalue problems

Consider eigenvalue problems of the form Dλy = 0, x ∈ [a, b], (1) La[y;λ] = Lb[y;λ] = 0, (2) where Dλ is a second order linear differential operator and {La, Lb} are linear functionals defining the boundary conditions at a and b. Solutions to problem (1)-(2) consist of finding values for λ, called eigenvalues, and their corresponding nontrivial solutions y(λ;x) which are called eigenfunctions. There is a wide class of numerical methods that approximate the eigenvalues of (1)(2). Once an approximation λ̃ for the exact eigenvalue λ is computed with a certain method, a natural question that arises is how much does λ̃ deviate from the (unknown) λ. In the present work we are concerned with deriving a practical formula that allows to measure the difference δ := λ−λ̃ when λ̃ is obtained with an exponentially fitted version of Legendre Gauss tau method. To achieve this we construct first an approximate eigenfunction ỹ that satisfies condition La[ỹ;λ] = 0, and then, using a new approach developed in [7] , we introduce the miss-distance function F (λ) := Lb[y;λ]−Lb[ỹ; λ̃] that measures the extent to which the second boundary condition Lb[y;λ] = 0 is satisfied. Considering the Taylor’s series expansions of F (λ) near λ̃,
USING DEEP FEATURES FOR AUDIO CLASSIFICATION

This extended abstracts describes our system for audio classification and tag classification submitted to MIREX 2010. Our system uses features learned with a deep belief network (DBN) and uses support vector machines (SVMs) classifiers on these features. 1. OVERVIEW In this paper, we describe our system for audio classification and tag classification submitted to MIREX 2010. This system relies on a deep belief network to extract features. The system is explained in more details in [2]. We describe how we use this network in section 2. In section 3, we describe the classification module. We conclude in section 4.
FIMD: Fine-grained Device-free Motion Detection

Device-free passive (Dfp) motion detection seeks to monitor the position change of entities without actively carrying any physical devices. Recently, WLAN with a rich set of installed wireless infrastructures enables motion detection in the area of interest. WLAN-enabled DfP motion detection rely on received signal strength (RSS) is verified to be able to provide acceptable high accuracy. Although RSS can be easily measured with commercial equipments, it is suspectable to measurement itself due to multipath effect in indoor environment. In this paper, we present an Indoor device-free Motion Detection system (FIMD) to overcome the preceding RSS-based limitation. FIMD explores properties of Channel State Information (CSI) from PHY layer in OFDM system. FIMD is designed based on the insight that CSI maintains temporal stability in static environment, while exhibits burst patterns when motion takes place. Motivated by this observation, FIMD uses a novel feature extracted from CSI to leverage its temporal stability and frequency diversity. The motion detection is conducted with outliers identification from normal features in continuous monitoring using density-based DBSCAN algorithm. Moreover, we leverage two schemes including false alert filter and data fusion to enhance the detection accuracy. We implement FIMD system with commercial IEEE 802.11n NICs and evaluate its performance in two typical indoor scenarios. Experiment results show that FIMD can achieve high detection rate. Moreover, comparing with RSSI, the feature extracted from CSI enables better detection performance in accuracy and robustness to narrowband interference.
The impact of leadership involvement in enhancing high school climate and reducing bullying: An exploratory study

ABSTRACT Bullying in secondary schools is a serious concern for educators and parents. The relationship between bullying and school climate has been identified and strategies to improve school climate are available. The importance of leadership in shaping school climate has been well documented. This exploratory study explores the role of leadership in implementing an approach to school climate change (positive behavior intervention and supports) in comprehensive Southwestern high schools participating in a federal school safety grant. Leadership involvement in the change process appears to be a key component leading to student-reported behavior change. Our findings suggest that although changes in school climate should lead to changes in bullying behaviors, the opposite is the case. Implications for practice and further research are discussed.
Optimal Representation of MultiView Video

Multi-view video acquisition is widely used for reconstruction and free-viewpoint rendering of dynamic scenes by directly resampling from the captured images. This paper addresses the problem of optimally resampling and representing multi-view video to obtain a compact representation without loss of the view-dependent dynamic surface appearance. Spatio-temporal optimisation of the multi-view resampling is introduced to extract a coherent multi-layer texture map video. This resampling is combined with a surface-based optical flow alignment between views to correct for errors in geometric reconstruction and camera calibration which result in blurring and ghosting artefacts. The multi-view alignment and optimised resampling results in a compact representation with minimal loss of information allowing high-quality free-viewpoint rendering. Evaluation is performed on multi-view datasets for dynamic sequences of cloth, faces and people. The representation achieves >90% compression without significant loss of visual quality.