Miracle-dz/UniFAR-FTUs huggingface dataset:
Operational rate-distortion shape coding with dual error regularization

Existing operational rate-distortion shape coding aims at finding a polygon which can be encoded with the lowest bit rate under a given upper bound on the edge error. However, this upper bound may cause noticeable errors. Therefore, we add an ℓ2-norm error regularization term to the objective function, and seek the globally optimal solution using a shortest path algorithm for a weighted directed acyclic graph. Experiments confirm the accuracy and robustness of our method.
Unsupervised feature learning from finite data by message passing: discontinuous versus continuous phase transition

Unsupervised neural network learning extracts hidden features from unlabeled training data. This is used as a pretraining step for further supervised learning in deep networks. Hence, understanding unsupervised learning is of fundamental importance. Here, we study the unsupervised learning from a finite number of data, based on the restricted Boltzmann machine where only one hidden neuron is considered. Our study inspires an efficient message-passing algorithm to infer the hidden feature and estimate the entropy of candidate features consistent with the data. Our analysis reveals that the learning requires only a few data if the feature is salient and extensively many if the feature is weak. Moreover, the entropy of candidate features monotonically decreases with data size and becomes negative (i.e., entropy crisis) before the message passing becomes unstable, suggesting a discontinuous phase transition. In terms of convergence time of the message-passing algorithm, the unsupervised learning exhibits an easy-hard-easy phenomenon as the training data size increases. All these properties are reproduced in an approximate Hopfield model, with an exception that the entropy crisis is absent, and only continuous phase transition is observed. This key difference is also confirmed in a handwritten digits dataset. This study deepens our understanding of unsupervised learning from a finite number of data and may provide insights into its role in training deep networks.
Theoretical Modeling and Experimental Verification of the Scattering From a Ferromagnetic Microwire

This paper presents a theoretical modeling of the scattering of ferromagnetic microwires in free space and inside a rectangular waveguide, providing both an analytical solution and a physical interpretation of the problem. Special attention is devoted to the impact of the microwire radius and its magnetic properties. Theoretical results have been experimentally verified measuring the reflection, absorption, and transmission coefficients of a ferromagnetic microwire inside a rectangular waveguide.
ctile identification of objects using Bayesian exploration

In order to endow robots with human-like tactile sensory abilities, they must be provided with tactile sensors and intelligent algorithms to select and control useful exploratory movements and interpret data from all available sensors. Current robotic systems do not possess such sensors or algorithms. In this study we integrate multimodal tactile sensing (force, vibration and temperature) from the BioTac® with a Shadow Dexterous Hand and program the robot to make exploratory movements similar to those humans make when identifying objects by their compliance, texture, and thermal properties. Signal processing strategies were developed to provide measures of these perceptual properties. When identifying an object, exploratory movements are intelligently selected using a process we have previously developed called Bayesian exploration [1], whereby exploratory movements that provide the most disambiguation between likely candidates of objects are automatically selected. The exploration algorithm was augmented with reinforcement learning whereby its internal representations of objects evolved according to its cumulative experience with them. This allowed the algorithm to compensate for drift in the performance of the anthropomorphic robot hand and the ambient conditions of testing, improving accuracy while reducing the number of exploratory movements required to identify an object. The robot correctly identified 10 different objects on 99 out of 100 presentations.
Book Review of "Multipliers: How the Best Leaders Make Everyone Smarter"

“Most organizations have far more intelligence than meets the eye. They are filled with latent capabilities and intelligence that wants to be used. We’ve all had experience with two dramatically different types of leaders. The first type drains intelligence, energy, and capability from those around them and always needs to be the smartest one in the room. These are the idea killers, the energy sappers, the diminishers of talent and commitment.
Assessment of past, present and future health-cost externalities of air pollution in Europe and the contribution from international ship traffic using the EVA model system

Abstract. An integrated model system, EVA (Economic Valuation of Air pollution), based on the impact-pathway chain has been developed to assess the health-related economic externalities of air pollution resulting from specific emission sources or sectors. The model system can be used to support policy-making with respect to emission control. In this study, we apply the EVA system to Europe, and perform a more detailed assessment of past, present, and future health-cost externalities of the total air pollution levels in Europe (including both natural and anthropogenic sources), represented by the years 2000, 2007, 2011, and 2020. We also assess the contribution to the health-related external costs from international ship traffic with special attention to the international ship traffic in the Baltic and North seas, since special regulatory actions on sulfur emissions, called SECA (sulfur emission control area), have been introduced in these areas. We conclude that, despite efficient regulatory actions in Europe in recent decades, air pollution still constitutes a serious problem for human health. Hence the related external costs are considerable. The total health-related external costs for the whole of Europe are estimated at 803 bn euros yr −1 for the year 2000, decreasing to 537 bn euros yr −1 in the year 2020. We estimate the total number of premature deaths in Europe in the year 2000 due to air pollution to be around 680 000 yr −1 , decreasing to approximately 450 000 in the year 2020. The contribution from international ship traffic in the Northern Hemisphere was estimated to 7% of the total health-related external costs in Europe in the year 2000, increasing to 12% in the year 2020. In contrast, the contribution from international ship traffic in the Baltic Sea and the North Sea decreases 36% due to the regulatory efforts of reducing sulfur emissions from ship traffic in SECA. Introducing this regulatory instrument for all international ship traffic in the Northern Hemisphere, or at least in areas close to Europe, would have a significant positive impact on human health in Europe.
Coupled multipath congestion control at receiver in content-centric networking

Content-Centric Networking (CCN), a recent innovative architecture, has brought about a great number of challenges for researchers whose ambition is to design such network with highly advanced ability to respond quickly to increasing demands from users. This receiver-driven content paradigm creates a different perspective of network. In this paper, we propose a coupled multipath congestion control at receiver in CCN which helps to enhance its capability of balancing congestion and network efficiency while remaining fair share among single-path user. The simulation results have shown that it can ameliorate the existing multipath algorithm for CCN.
TraCI: an interface for coupling road traffic and network simulators

Vehicular Ad-Hoc Networks (VANETs) enable communication among vehicles as well as between vehicles and roadside infrastructures. Currently available software tools for VANET research still lack the ability to asses the usability of vehicular applications. In this article, we present <u>Tra</u>ffic <u>C</u>ontrol <u>I</u>nterface (TraCI) a technique for interlinking road traffic and network simulators. It permits us to control the behavior of vehicles during simulation runtime, and consequently to better understand the influence of VANET applications on traffic patterns. In contrast to the existing approaches, i.e., generating mobility traces that are fed to a network simulator as static input files, the online coupling allows the adaptation of drivers' behavior during simulation runtime. This technique is not limited to a special traffic simulator or to a special network simulator. We introduce a general framework for controlling the mobility which is adaptable towards other research areas. We describe the basic concept, design decisions and the message format of this open-source architecture. Additionally, we provide implementations for non-commercial traffic and network simulators namely SUMO and ns2, respectively. This coupling enables for the first time systematic evaluations of VANET applications in realistic settings.
Social capital for LGBTQ+ student leaders of LGBTQ+ identity-based student groups

Michael Coomes, Advisor The purpose of this qualitative, interview-based study was to use the framework of social capital to explore how 15 LGBTQ+ student leaders of LGBTQ+ identity-based student groups described the impact of serving in those leadership roles on their sense of engagement and belonging with their university community. Using a constructivist paradigm, I sought a better understanding of how participants understood their own social capital within the university community and how they constructed the meaning of those relationships. I used a constructivist design and analyzed interviews, observations, and documents related to the topic. Participants identified as part of the LGBTQ+ community, all had at least one semester of positional leadership experience in an LGBTQ+ student group, and all were either currently enrolled undergraduate students at the research site or within one year of graduation. I used a semistructured interview protocol and conducted one interview, lasting between 45minutes and two hours, with each participant. I gained an understanding of the participants’ described experience as LGBTQ+ student leaders of LGBTQ+ identity-based student groups and how they interacted with their campus community. Four major themes emerged: (1) gaining social capital; (2) being a visible leader; (3) experiencing changing relationships; and (4) participating in the interactive campus. Through serving in these leadership positions, student leaders gained social capital granted to them by their institution and created by their positional leadership role; they gained capital within their own organization; and they joined two larger social networks of people working for
Amenity or Nuisance? Understanding and Managing Human–Panther Conflicts in Exurban Southwest Florida

ABSTRACT Golden Gate Estates (GGE), an exurban development in southwest Florida, is the site of the highest recorded number of conflicts between people and the Florida panther. We used qualitative data provided by 157 GGE residents and 19 nonresident stakeholders to investigate attitudes toward the panther, and appropriate measures to mitigate human–panther conflicts. Although a subset of GGE residents expressed some concerns about human safety risks associated with living with the panther, a higher share of residents viewed the panther positively. Residents and nonresident stakeholders agreed that GGE residents are responsible for securing their livestock against panthers. This point of agreement may improve adoption of appropriate practices to prevent human–panther conflicts. Outreach and education programs should reinforce expectations within the GGE community that residents are responsible for securing livestock against predators and adopting other conflict mitigation practices, as well as encouraging positive attitudes toward the panther.
Normal Adult Aging and the Contextual Influences Affecting Speech and Meaningful Sound Perception

It is widely accepted that hearing loss increases markedly with age, beginning in the fourth decade ISO 7029 (2000). Age-related hearing loss is typified by high-frequency threshold elevation and associated reductions in speech perception because speech sounds, especially consonants, become inaudible. Nevertheless, older adults often report additional and progressive difficulties in the perception and comprehension of speech, often highlighted in adverse listening conditions that exceed those reported by younger adults with a similar degree of high-frequency hearing loss (Dubno, Dirks, & Morgan) leading to communication difficulties and social isolation (Weinstein & Ventry). Some of the age-related decline in speech perception can be accounted for by peripheral sensory problems but cognitive aging can also be a contributing factor. In this article, we review findings from the psycholinguistic literature predominantly over the last four years and present a pilot study illustrating how normal age-related changes in cognition and the linguistic context can influence speech-processing difficulties in older adults. For significant progress in understanding and improving the auditory performance of aging listeners to be made, we discuss how future research will have to be much more specific not only about which interactions between auditory and cognitive abilities are critical but also how they are modulated in the brain.
PREVIOUS STUDIES ON THE EFFECTS OF GLOSSING ON READING COMPREHENSION OF ESL / EFL LEARNERS

The present study reviews the findings of the previous studies on reading comprehension of ESL/EFL learners chronologically. The results were divided into two groups as follows: the first group of studies reported that there was difference between the effects of textual glosses on reading comprehension and the second group of studies confirmed that there was no difference between the effects of different glosses on reading comprehension. This study reviewed the previous studies from a new perspective that can be used as a fundamental review research for future studies on the effects of glossing on reading comprehension of ESL/EFL learners.
Strategy for improving the reliability in the facial identification

This paper presents a simple, robust and novel for errors detection in biometric system which is applied to the Olivetti Research Laboratory (ORL) face database (400 images). We have used as parameterisation different transformed dominions (Travieso et al., 2004; Faundez, 2003), and a support vector machine (SVM) (Burges, 1998; Cristianini and Shawe-Taylor, 2000) as classifier. This system has been adjusted with our experiments for obtaining a false identification rate (FIR) of 0%, with a success rate of 90.8% a rejected samples rate of 9.2%.
Studies of Scientific Discovery: Complementary Approaches and Convergent Findings

This review integrates 4 major approaches to the study of science—histo rical accounts of scientific discoveries, psychological experiments with nonscientists working on tasks related to scientific discoveries, direct observation of ongoing scientific laboratories, and computational modeling of scientific discovery processes—by viewing them through the lens of the theory of human problem solving. The authors provide a brief justification for the study of scientific discovery, a summary of the major approaches, and criteria for comparing and contrasting them. Then, they apply these criteria to the different approaches and indicate their complementarities. Finally, they provide several examples of convergent principles of the process of scientific discovery. The central thesis of this article is that although research on scientific discovery has taken many different paths, these paths show remarkable convergence on key aspects of the discovery processes, allowing one to aspire to a general theory of scientific discovery. This convergence is often obscured by the disparate cultures, research methodologies, and theoretical foundations of the various disciplines that study scientific discovery, including history and sociology as well as those within the cognitive sciences (e.g., psychology, philosophy, and artificial intelligence). Despite these disciplinary differences, common concepts and terminology can express the central ideas and findings about scientific discovery from the various disciplines, treating discovery as a particular species of human problem solving. Moreover, we may be able to use these concepts and this vocabulary over an even broader domain to converge toward a common account of discovery in many areas of human endeavor: practical, scientific, and artistic, occurring both in everyday life and in specialized technical and professional domains. The doing of science has long attracted the attention of philosophers, historians, anthropologists, and sociologists. More recently, psychologists also have begun to turn their attention to the phenomena of scientific thinking, and there is now a large and rapidly growing literature on the psychology of science. (A good description of the field in its infancy can be found in Tweney, Doherty, & Mynatt, 1981, and a recent summary of topics and findings from investigations of the developmental, personality, cognitive, and social psychology of science can be found in Feist & Gorman, 1998). Our review links four major approaches to the study of science—historical accounts of scientific discoveries, laboratory experiments with nonscientists working on tasks related to scientific discoveries, direct observation of ongoing scientific laboratories, and computational modeling of scientific discovery processes—by
Global Cell Proteome Profiling, Phospho-signaling and Quantitative  Proteomics for Identification of New Biomarkers in Acute Myeloid  Leukemia Patients

The identification of protein biomarkers for acute myeloid leukemia (AML) that could find applications in AML diagnosis and prognosis, treatment and the selection for bone marrow transplant requires substantial comparative analyses of the proteomes from AML patients. In the past years, several studies have suggested some biomarkers for AML diagnosis or AML classification using methods for sample preparation with low proteome coverage and low resolution mass spectrometers. However, most of the studies did not follow up, confirm or validate their candidates with more patient samples. Current proteomics methods, new high resolution and fast mass spectrometers allow the identification and quantification of several thousands of proteins obtained from few tens of μg of AML cell lysate. Enrichment methods for posttranslational modifications (PTM), such as phosphorylation, can isolate several thousands of site-specific phosphorylated peptides from AML patient samples, which subsequently can be quantified with high confidence in new mass spectrometers. While recent reports aiming to propose proteomic or phosphoproteomic biomarkers on the studied AML patient samples have taken advantage of the technological progress, the access to large cohorts of AML patients to sample from and the availability of appropriate control samples still remain challenging.
American sign language-based finger-spelling recognition using k-Nearest Neighbors classifier

This paper presents finger-spelling recognition method for American Sign Language (ASL) Alphabet using k-Nearest Neighbours (k-NN) Classifier. This research also examines the effect of PCA for dimensional reduction to k-NN performance. The empiric results show that k-NN classifier achieves the highest accuracy (99.8 percent) for k=3 when the pattern is represented by full dimensional feature. However, k-NN classifier only achieves 28.6 percent accuracy (for k=5) when the pattern is represented by PCAreduced dimensional feature. This low accuracy is due to several factors, among others, is the presence of high numbers of redundant or highly correlated features among ASL alphabet that makes PCA unable to separate data. Although kNN classifier accuracy is higher than the proposed classifier in [7], recognition time of k-NN classifier is longer than that of the method proposed in [7]. Therefore, k-NN classifier is suitable for early child education-based application such as self-assessment system for special need student who learns ASL alphabet finger-spelling.
Load-aware scheduling for heterogeneous multi-core systems

Heterogeneous multi-core systems are becoming more and more common today. To be used to their full potential, the operating system has to be adapted to the new system environment. This is especially true for the scheduler as it is crucial to the overall system performance. In this paper, we present a scheduling approach for heterogeneous systems with two different kinds of cores. One that is very power efficient, but shows only a limited computing power, and the other one that has a very high performance and is very power consuming at the same time. We consider such heterogeneity for a centralized scheduler architecture. In our approach, we introduce a new load metric in order to classify tasks whether or not they are suited to be executed on a high-performance core. Based on this metric, we present a task state model for scheduling tasks according to their performance classification. We implemented the scheduling approach by extending the Brain Fuck Scheduler (BFS) and evaluated it on an eight core heterogeneous architecture with four low performance and four high-performance cores. The evaluation covers system responsiveness and high load behaviour compared to the vanilla BFS and the decentralized Completely Fair Scheduler (CFS). Even though our approach takes the heterogeneity into account, the results show that it scales better than the vanilla BFS while nearly maintaining its superior responsiveness.
Individual and organizational support: Does it affect red tape, stress and work outcomes of police officers in the USA?

Purpose The purpose of this paper is to examine whether management supports police officers adequately, or whether police have to rely on their individual attributes, specifically psychological capital (PsyCap), to cope with red tape and stress. Work outcomes/consequences examined were discretionary power, affective commitment and turnover intentions. Design/methodology/approach A cross-sectional design using a survey-based, self-report strategy was used to collect data from 588 police officers from USA, who are most engaged with the public. The data were analysed using AMOS and a structural model to undertake structural equation modelling. Findings Two significant paths were identified Path 1: management support to red tape to discretionary power to affective commitment and turnover intentions; and Path 2: supervisor relationships to PsyCap to stress to affective commitment and turnover intentions. Further, management support predicted PsyCap, red tape and police stressors. Red tape increased police stressors and turnover intentions. Research limitations/implications The use of self-report surveys is a limitation, causing common methods bias. Using Harmon’s one-factor post hoc test, the authors were able to provide some assurance that common method bias was of no major concern. Originality/value As far as is known, this study is the first to examine, for police officers, how PsyCap impacts upon negative factors (stress and red tape) and enhances positive drivers for employees. Examining the impact of an individual attribute – PsyCap – provides an important piece of the organizational puzzle in explaining the commitment and turnover intentions of police officers. By examining the impact of both organizational and individual factors, there is now more knowledge about the antecedents of police outcomes.