Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of On-Body Communication Channel and Energy Efficient Topology Design for Wireless Body Area Networks

Wireless body area networks (WBANs) offer many promising new applications in the area of remote health monitoring. An important element in the development of a WBAN is the characterization of the physical layer of the network, including an estimation of the delay spread and the path loss between two nodes on the body. This paper discusses the propagation channel between two half-wavelength dipoles at 2.45 GHz, placed near a human body and presents an application for cross-layer design in order to optimize the energy consumption of different topologies. Propagation measurements are performed on real humans in a multipath environment, considering different parts of the body separately. In addition, path loss has been numerically investigated with an anatomically correct model of the human body in free space using a 3-D electromagnetic solver. Path loss parameters and time-domain channel characteristics are extracted from the measurement and simulation data. A semi-empirical path loss model is presented for an antenna height above the body of 5 mm and antenna separations from 5 cm up to 40 cm. A time-domain analysis is performed and models are presented for the mean excess delay and the delay spread. As a cross-layer application, the proposed path loss models are used to evaluate the energy efficiency of single-hop and multihop network topologies.
DALMATIAN: An Algorithm for Automatic Cell Detection and Counting in 3D

Current 3D imaging methods, including optical projection tomography, light-sheet microscopy, block-face imaging, and serial two photon tomography enable visualization of large samples of biological tissue. Large volumes of data obtained at high resolution require development of automatic image processing techniques, such as algorithms for automatic cell detection or, more generally, point-like object detection. Current approaches to automated cell detection suffer from difficulties originating from detection of particular cell types, cell populations of different brightness, non-uniformly stained, and overlapping cells. In this study, we present a set of algorithms for robust automatic cell detection in 3D. Our algorithms are suitable for, but not limited to, whole brain regions and individual brain sections. We used watershed procedure to split regional maxima representing overlapping cells. We developed a bootstrap Gaussian fit procedure to evaluate the statistical significance of detected cells. We compared cell detection quality of our algorithm and other software using 42 samples, representing 6 staining and imaging techniques. The results provided by our algorithm matched manual expert quantification with signal-to-noise dependent confidence, including samples with cells of different brightness, non-uniformly stained, and overlapping cells for whole brain regions and individual tissue sections. Our algorithm provided the best cell detection quality among tested free and commercial software.
Object-Based Unsupervised Classification of VHR Panchromatic Satellite Images by Combining the HDP and IBP on Multiple Scenes

We present a nonparametric Bayesian hierarchical model (HDP_IBPs) to classify very high resolution panchromatic satellite images in an unsupervised way, in which the hierarchical Dirichlet process (HDP) and Indian buffet process (IBP) are combined on multiple scenes. The main contribution of this paper is a novel application framework to solve the problems of traditional probabilistic topic models and achieve the effective unsupervised classification of very high resolution (VHR) panchromatic satellite images. In this framework, a VHR satellite image is first oversegmented into basic processing units and divided into a set of subimages. We use the Chinese restaurant franchise process as a construct method of the HDP to capture the latent semantic structures (i.e., classes) and the class proportion (i.e., co-occurrence of topics) for each subimage. Meanwhile, the subimages are grouped into different scenes based on the class proportion. Finally, the IBP is employed to select the most appropriate classes for each subimage from all of the classes based on different scenes in turn. The hierarchical structure of our model transmits the spatial information from the original image to the scene layer implicitly and provides useful cues of classification. The experimental results show that HDP_IBPs outperforms state-of-the-art models in terms of both qualitative and quantitative evaluations.
Clustering of laser measurements via the Dirichlet process mixture model for object tracking

In this paper, the Dirichlet process mixture model is used to describe the distribution of the whole laser measurements in a given scan. Then the number of clusters is inferred from the measurements by the Gibbs sampler. We focus on the automotive application which usually has a more complex environment. Due to the variant shapes and sizes of the real traffic objects, the multi-class DP-based clustering model, which is incorporated with a mixture prior distribution, is proposed to cluster the measurements more properly. The clustering results of the proposed method are compared with those of several existing clustering methods both in an expressway case and in an urban road case. The corresponding tracking performances are also analyzed and the improvements of the proposed method are presented.
The Development of Metropolitan Languages in Post-Colonial Contexts: Language Contact and Language Change and the Case of Portuguese in Maputo

This article explores briefly some phenomena of potential indigenization of the Portuguese spoken in Mozambique. Data for the study has been taken from work that is currently underway in Maputo, Mozambique, that was originally initiated to investigate contact varieties of Portuguese and to probe their educational implications. Speech samples comprise formal interviews and non-formal encounters from a socio-demographically representative sample of informants. The article first provides an inventory of some non-standard European Portuguese variants that are found in this data, and subsequently focusses upon a discussion of what contribution different linguistic processes make to indigenization, specifically the role played by processes of second language acquisition in a context of massive and diffuse language contact and change. Special attention is also paid to the social contexts in which different manifestations of language contact are found, and the importance of linguistic ideology for the form that language contact takes in particular cases is explored. The article concludes with the suggestion that the salient characteristics of types of non-native speech community such as Maputo require a reconceptualization of models and methods of contact linguistics and second language acquisition, and that this in turn carries implications for the terms of reference and analysis to which indigenization need be related.
Multi-expert evolving system for objective psychophysiological monitoring and fast discovery of effective personalized therapies

Diagnostics and monitoring in applied and clinical psychology is often based on subjective patient's questionnaires and observations. Lack of objective quantitative approaches could lead to biased conclusions and selection of sub-optimal therapies. However, established methods of modern psychophysiology indicate possibility of objective physiological measurement of certain psychological states and their dynamics. Nevertheless treatment personalization and optimization is very difficult task even in medicine, where many objective diagnostic tools are available. Previously we have proposed generic quantitative framework capable of discovering optimal combination of physiological indicators for early detection of emerging pathologies and efficient multi-expert characterization of complex and rare states. Ability of implicit encoding of great variety of patterns and regimes in training phase makes our system evolving in nature and capable of robust novelty detection without any formal online learning algorithms. Here we argue that the same approach could be also applicable to objective psychophysiological monitoring and fast discovery of effective personalized therapies in applied and clinical psychology. The web-based version of our system will be made available for researchers and psychology practitioners.
David Ingram, Phonological disability in children . London: Edward Arnold, 1976. Pp. xvii + 167.

recently experienced by the child. Verbal identification of such referents is not obligatory. In such contexts, mothers sometimes identify these referents with an indefinite expression, but at other times they refer immediately with a definite expression (Warden, in preparation). Faced with such conflicting data, children will find it hard to acquire the identifying function of a. In conclusion, a number of methodological criticisms may be made. A speaker's decision to identify a specific referent with an indefinite expression, assuming he recognizes this function of a, rests on his estimation of whether or not the referent is already specified for his listener. The experimental contexts utilized by Maratsos were such that the children's audience was always an adult experimenter who introduced the experimental tasks and generally provided the verbal and non-verbal context for their utterances. Conceivably, some of the children, for example in the 4-low group, may have assumed that the experimenter was familiar with the referents of their referring expressions, and therefore tended to use the definite article. In similar situations, even adults sometimes fail to use indefinite expressions (Warden 1976). It would seem essential, therefore, to explore children's use of the articles in conversation with a variety of listeners, particularly with other children to whom they could not attribute prior knowledge. And the emphasis should be on the word CONVERSATION, because another weakness in Maratsos' work is the degree to which the experimenter controlled the verbal context, and constrained the children's contributions to ' article + noun' responses. In none of the studies were the children allowed to initiate the verbal context for their referring expressions. It seems possible that, by asking his subjects for a name in response to a question, Maratsos may have biased their responses in favour of the nominative indefinite article. Such a limited use of referring expressions does not seem the best test of children's capacity to use the articles.
Submodularity in Input Node Selection for Networked Systems

Networked systems are systems of interconnected components, in which the dynamics of each component are influenced by the behavior of neighboring components. Examples of networked systems include biological networks, critical infrastructures such as power grids, transportation systems, and the Internet, and social networks. The growing importance of such systems has led to an interest in control of networks to ensure performance, stability, robustness, and resilience. A widely-studied method for controlling networked systems is to directly control a subset of input nodes, which then steer the remaining nodes to their desired states. This article presents submodular optimization approaches for input node selection in networked systems. Submodularity is a property of set functions that enables the development of computationally tractable algorithms with provable optimality bounds. For a variety of physically relevant systems, the physical dynamics have submodular structures that can be exploited to develop efficient input selection algorithms. This article will describe these structures and the resulting algorithms, as well as discuss open problems.
POLISH EMOTIONAL SPEECH RECOGNITION USING ARTIFICAL NEURAL NETWORK

The article presents the issue of emotion recognition based on polish emotional speech analysis. The Polish database of emotional speech, prepared and shared by the Medical Electronics Division of the Lodz University of Technology, has been used for research. The following parameters extracted from sampled and normalised speech signal has been used for the analysis: energy of signal, speaker’s sex, average value of speech signal and both the minimum and maximum sample value for a given signal. As an emotional state a classifier fof our layers of artificial neural network has been used. The achieved results reach 50% of accuracy. Conducted researches focused on six emotional states: a neutral state, sadness, joy, anger, fear and boredom.
Progression in physical education teachers’ career-long professional learning

This paper considers the issue of learning ‘progression’ in pedagogy for physical education (PE) teachers in their career-long professional development (CPD). This issue arose from an analysis of findings from three research projects in which the authors were involved. The projects were undertaken in different national contexts (Ireland, Greece, England), but all used similar methods to investigate questions about effective/ineffective PE-CPD. The findings identified numerous barriers that teachers and pre-service teachers encountered in accessing effective professional development. Of particular interest, however, was the realization that taken together, the findings raised concerns about teachers’ learning progression, including progression over time, across learning contexts and in specific areas of interest. This issue has rarely been discussed in the existing literature and is poorly theorized. Indeed, there would appear to be little agreement in the profession about how to conceptualize ‘good’ or ‘adequate’ learning progression in pedagogy across a career. This paper, therefore, seeks to open a new line of enquiry.
Decentralized broadcast-based scheduling for dense multi-hop TSCH networks

Wireless Sensor Networks (WSNs) are becoming more and more popular to support a wide range of Internet of Things (IoT) applications. Time-Slotted Channel Hopping (TSCH) is a technique to enable ultra reliable and ultra low-power wireless multi-hop networks. TSCH consist of a channel hopping scheme for sending link-layer frames in different time slots and frequencies in order to efficiently combat external interference and multi-path fading. The keystone of TSCH is the scheduling algorithm, which determines for every node at which opportunity (a combination of time slots and channels) it is allowed to send. However, current scheduling algorithms are not suited for dense deployments and have important scalability limitations. In this paper, we investigate TSCH's scheduling performance in dense deployments and show how the scheduling can be improved for such environments. We performed an extensive analysis of the scalability for different scheduling approaches showing the performance drops as the number of nodes increases. Moreover, we propose a novel Decentralized Broadcast-based Scheduling algorithm called DeBraS, based on selective broadcasting to inform nodes about each other's schedule. Through extensive simulations, we show that DeBraS is highly more scalable than centralized solutions and that it outperforms the current decentralized 6Tisch algorithms in up to 88.5% in terms of throughput for large network sizes.
Consistency Orientation and Models of Social Behavior: Is It Not Time for West to Meet East

The study examined the cultural differences in inconsistency-reducing behaviors by testing the reactions of 110 Japanese and 169 American college students to the inconsistencies arising from a difference of opinion with a significant other on ego-involving issues. It was predicted that (1) the Japanese sample would show more inconsistency support than will an American sample; (2) The American sample will show more preference for active inconsistency-reducing responses than will the Japanese sample; (3) on the hypothesis that contemporary social psychology's models of humans is based upon the American stereotype of the “typical American,” the first two predictions will be more strongly confirmed by comparing the American subjects' stereotype of the “typical American” than by comparing their own reported choices. The findings generally supported the first two predictions and strongly supported the third one.
Naturally Occurring Retirement Communities

Naturally occurring retirement communities (NORCs) are defined as housing developments that are not planned or designed for older people, but which over time come to house largely older people. NORCs are of interest because they differ from the stereotypical retirement community (RC) and yet are probably the most common form of RC in the U.S. An analysis of NORCs is presented by examining their evolution and comparing them to planned RCs and community-based housing. A supportive neighborhood emerges as the common denominator in each living arrangement.
Retinol , a-Tocopherol , Lycopene , and aand f 3-CaroteneSimultaneously Determinedin Plasmaby IsocraticLiquidChromatography

Retinol, a-tocopherol, Iycopene, and aand /3-carotene can be simultaneously determined in human plasma by reversedphase liquid chromatography. Plasma-0.5 mL plus added internal standard, retinyl acetate-is deproteinized with 0.5 mL of ethanol, then extracted with 1.0 mL of petroleum ether. The organic layer is removed and evaporated, the residue is redissolved in 0.25 mL of ethanol, and 8-4 samples are injected into a 60 x 4.6 mm column of Hypersil ODS 3-. tm particles at 35 #{176}C. An isocratic methanol mobile phase, flow rate 0.9 mLimin, is used for the 9-mm run. Retinol and retinyl acetate are monitored at 305 nm, the tocopherols at 292 nm, and the carotenoids at 460 nm. Between-run CVs were 3.1, 6.9, 6.1, and 6.5% for retinol, a-tocopherol, lycopene, and (3-carotene, respectively. Small sample requirement, simplicity of extraction, short run time, and good reproducibility make this procedure ideal for clinical or research use.
A Taxonomy of Collaboration in Online Information Seeking

People can help other people find information in networked information seeking environments. Recently, many such systems and algorithms have proliferated in industry and in academia. Unfortunately, it is difficult to compare the systems in meaningful ways because they often define collaboration in different ways. In this paper, we propose a model of possible kinds of collaboration, and illustrate it with examples from literature. The model contains four dimensions: intent, depth, concurrency and location. This model can be used to classify existing systems and to suggest possible opportunities for design in this space.
Effects of Similar and Diversified Modeling on African American Women's Efficacy Expectations and Intentions to Perform Breast Self-Examination

This experiment tested the impact of similar and diversified modeling on African American women's self-efficacy beliefs, perceptions of model appropriateness, and intentions to perform breast self-examination. Perceptions of physician source credibility also were assessed. Subjects in the similar-modeling condition viewed a videotape that used an African American female physician to impart information about breast cancer and breast self-examination and an African American model to demonstrate how to perform breast self-examination. Subjects in the diversified-modeling condition were exposed to a videotape that used a White male physician and multirace models for this purpose. Control condition subjects watched a tape that contained no modeling or efficacy information. Overall, efficacy expectations, physician credibility, and model appropriateness were greater for the similar-modeling condition than for the diversified-modeling and control conditions. Recommendations for breast self-examination campaigns .
Title of deliverable : ASSESSING OUTCOMES OF ASSISTIVE TECHNOLOGY PRODUCTS AND SERVICES : THE EATS INSTRUMENTS

Workpackage WP03 of the EATS project developed two new measures of effectiveness and utility of assistive technology, respectively 1) the IPPA (Individually Prioritised Problems Assessment), intended to describe the outcomes generated by the provision of AT&S (Assistive Technology products and Services) in terms of solution to pre-identified problems and 2) EATS 6-D (EATS 6 dimensions), intended to describes changes in autonomy in daily life resulting from the adoption of such AT&S. Both instruments are user-centred, being designed to collect data from the direct real-life experience of the user of AT&S: in the first case (IPPA) through interview sessions carried out by trained interviewers, in the second case (EATS 6-D) by a self-administered questionnaire. The first chapter of this document clarifies the objectives and the boundaries of the study. It also addresses the remaining open issues, that means those aspects needing further research in order to achieve a more comprehensive and thorough understanding of AT outcomes. The second and third chapters present and describe respectively the effectiveness (IPPA) and the utility (EATS 6-D) instruments, in terms of their rationale, structure, items explanation, validity and reliability issues and administration technique. This document presents the findings of Workpackage 3 of the EATS project. It covers the scope and the contents of deliverables D03.1 (effectiveness instrument) and D03.2 (utility instrument) as defined by the Project Programme. Since a number of issues were found to be common to both instruments, and these are likely to be used in parallel, the solution of merging the two deliverables into a single manual was adopted as the most handy and usable for the readers. The intended audience of the document are mainly researchers, rehabilitation professionals and user groups who will use the instruments for trials. The overall objective of EATS is the development of a methodology for comprehensive assessment of assistive technology products and services, aimed at supporting decision at policy and provision level. As a step towards such objective, the mission of this workpackage was to establish measurement instruments able to generate the data that are needed for carrying out such an assessment. In particular, a set of two new measures was developed: • the IPPA (Individually Prioritised Problems Assessment), intended as an effectiveness measure that describes the outcomes generated by the provision of Assistive Technology products and services (AT&S) in terms of solution to pre-identified problems • the EATS 6-D (EATS 6 dimensions), intended as a …
Symmetry-Aided Particle Filter for Vehicle Tracking

Symmetry is an important characteristic of vehicle and has been used for detection tasks by many researchers. However, existing results of vehicle tracking seldom used this feature. In this paper, we combine the color histogram and the symmetry measurements to design a hierarchical-like particle filter for vehicle tracking. Experimental results show that the use of symmetry information will obtain better tracking performance than the conventional color histogram-based particle filters and effectively avoid some "hijack" problems.
Recursive least squares with forgetting for online estimation of vehicle mass and road grade: theory and experiments

Good estimates of vehicle mass and road grade are important in automation of heavy duty vehicles, vehicle following manoeuvres or traditional powertrain control schemes. Recursive least square (RLS) with multiple forgetting factors accounts for different rates of change for different parameters and thus, enables simultaneous estimation of the time-varying grade and the piece-wise constant mass. An ad hoc modification of the update law for the gain in the RLS scheme is proposed and used in simulation and experiments. We demonstrate that the proposed scheme estimates mass within 5% of its actual value and tracks grade with good accuracy provided that inputs are persistently exciting. The experimental setups, signals, their source and their accuracy are discussed. Issues like lack of persistent excitations in certain parts of the run or difficulties of parameter tracking during gear shift are explained and suggestions to bypass these problems are made.