Miracle-dz/UniFAR-FTUs huggingface dataset:
An Enhanced Fall Detection System using Android based Smart Phone

: Due to their widespread popularity, decreasing costs, built-in sensors, computing power and communication capabilities, Android-based personal devices are being seen as an appealing technology for the deployment of wearable fall detection systems. In contrast with previous solutions in the existing literature, which are based on the performance of a single element (a smart phone), this paper proposes and evaluates a fall detection system that benefits from the detection performed by two popular personal devices: a smart phone and a smart watch (both provided with an embedded accelerometer and a gyroscope). In the proposed architecture, a specific application in each component permanently tracks and analyses the patient’s movements. Diverse fall detection algorithms (commonly employed in the literature) were implemented in the developed Android apps to discriminate falls from the conventional activities of daily living of the patient. As a novelty, a fall is only assumed to have occurred if it is simultaneously and independently detected by the two Android devices (which can interact via Bluetooth communication). The system was systematically evaluated in an experimental tested with actual test subjects simulating a set of falls and conventional movements associated with activities of daily living. The tests were repeated by varying the detection algorithm as well as the pre-defined mobility patterns executed by the subjects (i.e., the typology of the falls and non-fall movements). The proposed system was compared with the cases where only one device (the smart phone or the smart-watch) is considered to recognize and discriminate the falls. The obtained results show that the joint use of the two detection devices clearly increases the system’s capability to avoid false alarms or ‘false positives’ (those conventional movements misidentified as falls) while maintaining the effectiveness of the detection decisions
A Differentiable Neural Computer for Logic Reasoning with Scalable Near-Memory Computing and Sparsity Based Enhancement

Logic reasoning represents a new class of artificial intelligence. This work presents the first hardware implementation of the Differentiable Neural Computer accelerator based on brain inspired “working memory” concept for reasoning tasks. A special near-memory computing architecture is developed achieving high scalability and over 90% utilization of computing resources. Sparsity based enhancements such as zero skipping, data compression are applied with 30% speedup of the computing latency. A 65nm test chip was fabricated with demonstrations on a variety of logic reasoning tasks showing 700X and 46X speedup compared with CPU and GPU and up to 1.28TOPS/W power efficiency.
Couplage de l'optimisation multi-objectif avec la simulation thermique dynamique pour la rénovation de parcs de bâtiments

RESUME. Cet article presente un nouvel outil pour realiser de l'optimisation multi-objectif sur les parcs de bâtiments geres par le meme le gestionnaire. Il detaille comment interfacer de l'optimisation multi-objectif avec de la simulation thermique de parcs de bâtiment sous le langage Modelica dans l'optique de trouver les strategies optimales de rehabilitation energetique pour ce parc. Les perspectives de cet outil sont l'etude de l'influence du phasage des travaux sur l'elaboration des strategies de rehabilitation et l'etude de l'influence des contraintes sur l'espace de decision. MOTS-CLES : optimisation multiobjectif, Modelica, parcs de bâtiment, rehabilitation ABSTRACT. This paper presents a new tool that enable multi-objective optimization on a building stock which common attribute is the building manager. It presents how multiobjective optimization can be connected with thermal simulation of building stock on Modelica in order to elaborate optimal strategies for energy retrofit of the building stock. This tool has been developped for further work on the study of the influence of construction phasing on the elaboration of optimal strategies and on the study of the impact on constraints of such an optimization.
Group C*-algebras without the completely bounded approximation property

It is proved that: (1) The Fourier algebra A(G) of a simple Lie group G of real rank at least 2 with finite center does not have a multiplier bounded approximate unit. (2) The reduced C*-algebra of any lattice in a non-compact simple Lie group of real rank at least 2 with finite center does not have the completely bounded approximation property. Hence, the results obtained by J. de Canniere and the author for SO(n,1), n at least 2, and by M. Cowling for SU(n,1) do not generalize to simple Lie groups of real rank at least 2.
Generalized Method of Integrated Moments for High-Frequency Data

We propose a semiparametric two-step inference procedure for a finite-dimensional parameter based on moment conditions constructed from high-frequency data. The population moment conditions take the form of temporally integrated functionals of state-variable processes that include the latent stochastic volatility process of an asset. In the first step, we nonparametrically recover the volatility path from high-frequency asset returns. The nonparametric volatility estimator is then used to form sample moment functions in the second-step GMM estimation, which requires the correction of a high-order nonlinearity bias from the first step. We show that the proposed estimator is consistent and asymptotically mixed Gaussian and propose a consistent estimator for the conditional asymptotic variance. We also construct a Bierens-type consistent specification test. These infill asymptotic results are based on a novel empirical-process-type theory for general integrated functionals of noisy semimartingale processes.
Powder Diffraction Notes for Authors

s: An abstract must accompany all articles except Letters to the Editor and contributions to International Report. The abstract should be typed double-spaced on a page separate from the rest of the manuscript. The abstract should be as informative as possible in the length allowed. It should state, in not more than 300 words, the main conclusions of the article and should include, briefly, the principal numerical results. Because an abstract is usually reprinted in its entirety in AIP and other abstract journals and on-line services, special care should be used in writing it.
Reconsidering [consonantal]

One of the fundamental claims of modern phonology is that generalisations about phonemes are based on a small, universal set of phonetically defined features. The theory of distinctive features is a very powerful idea, insofar as it predicts that sets of phonemes will act together in specific ways within and across languages, allowing the voiceless stops [p t k] to serve as a unified target or trigger class, but ruling out the possibility that [p r y a] will function as a unitary class. Much of the appeal of distinctive features lies in the fact that the rich array of segments and processes encountered in the world's languages can be understood in terms of a very small number of features. Numerous hypotheses have been advanced regarding what that set of features is – see Jakobson et al. (1952), Chomsky & Halle (1968), Sagey (1990) and Clements & Hume (1995), inter al. The ideal set of features must be rich enough to express phonemic contrasts which actually exist, and must otherwise be capable of capturing generalisations about sound structure. Equally important, a theory of features should be maximally impoverished – it should use the minimum resources necessary to describe languages.
Do lean manufacturing practices have negative impact on job satisfaction?

PurposeDue to the increasing trend of global competitiveness, lean manufacturing has received much attention in the international literature. Although previous studies have indicated the positive effects of lean manufacturing on the performance of the manufacturing firms, the impact of lean practices on two aspects of “job”, namely, characteristics and satisfaction, as of yet remains unclear. As a result, this study aims to evaluate job characteristics to understand the effects of lean manufacturing on job satisfaction.Design/methodology/approachData from a survey of 206 employees in lean manufacturing companies were gathered and analysed using the partial least squares technique.FindingsThe results indicate that customer relationship, human resources and product design practices had positive indirect effects on job satisfaction through job characteristics, whereas, process and equipment practices had a negative indirect effect.Practical implicationsThe findings of the study will be useful for the companies that implement lean manufacturing practices. Companies could either adjust their lean initiatives or make a trade-off amongst job characteristics.Originality/valueThis study contributes to the advancement of knowledge on the effects of lean manufacturing practices on job satisfaction through job characteristics.
Boundary Element Analysis of Anisotropic Thermomagnetoelectroelastic Solids with 3D Shell-Like Inclusions

Abstract The paper presents novel boundary element technique for analysis of anisotropic thermomagnetoelectroelastic solids containing cracks and thin shell-like soft inclusions. Dual boundary integral equations of heat conduction and thermomagnetoelectroelasticity are derived, which do not contain volume integrals in the absence of distributed body heat and extended body forces. Models of 3D soft thermomagnetoelectroelastic thin inclusions are adopted. The issues on the boundary element solution of obtained equations are discussed. The efficient techniques for numerical evaluation of kernels and singular and hypersingular integrals are discussed. Nonlin-ear polynomial mappings are adopted for smoothing the integrand at the inclusion’s front, which is advantageous for accurate evaluation of field intensity factors. Special shape functions are introduced, which account for a square-root singularity of extended stress and heat flux at the inclusion’s front. Numerical example is presented.
Clinical options for mandibular reconstruction: A review

This paper reviewed the different clinical options for reconstruction of segmental defects of the mandible. The options reviewed included no reconstruction; the use of prosthetic implants (alloplasts); autogenous bone grafts; combination of allopplasts with autografts; free pedicled compound grafts;combination of homografts and autografts; distraction osteogenesis; and tissue engineering. The goal, objectives, criteria for success of autogenous and alloplastic reconstructions were highlighted as well as the factors that may influence the choice of a particular method.
Extern styrning och modularisering av styrning till Bioloid robot

This thesis carried out on behalf of Cybercom and is about development of a unit which can process sound and images. Predetermined objects are going to be recognized and a user can give voice commands. The unit is made of two lesser units, a Raspberry pi 3 and a Bioloid Robot. The robot is built as a human body and can walk on an horizontal plane. These two units will be able to communicate through serial communication via a USB cable. To achieve sound and image processing the Raspberry Pi has been provided with a camera and a USB microphone. The functionalities have been divided in three different modules. One module is responsible for image processing with OpenCV and the use of the Viola-Jones method to recognize selected objects. Another one manage voice commands with help of CMU pocketsphinx. The third module deals with the serial communication. Development on the Raspberry Pi has been done in C++ while the Bioloid robot uses C code. To show the ability of the combined unit a demonstration was developed. The demo is using all of the projects resulting resources to affect the units actions. The project and demo have been developed in a way that hopefully encourage further development.
The Need for Academic Programs in Tourism, Arts & Culture, Sports, and Healthcare Management in the UAE

For several years, the UAE government has embarked upon diversifying its oiland gas-based economy. As a result, the service industry, particularly the tourism, healthcare, arts and culture, and sports and recreation service sectors have witnessed much growth. Unfortunately, as revealed in this study, the country lacks the professional human resources needed to keep pace with the tremendous growth. We make the case for the need for more professional and higher education training programs in tourism, arts and culture, sports, and healthcare by highlighting the paucity of such training programs and by reporting on the mostly favorable attitude of prospective and current college students toward studying these disciplines. Several constructs and variables, including awareness of the discipline as a choice of academic major, gender, educational background and interest relate to students’ overall attitude and preference for any of the four disciplines. These findings, we recommend, could inform the marketing and promotion strategies of existing and future institutions considering offering these programs.
Magnetic anisotropy and hyperfine interactions in Ce Fe 2 , Gd Fe 2 , and Lu Fe 2

M\"ossbauer-effect measurements on $^{57}\mathrm{Fe}$ have been carried out on the cubic Laves compounds Ce${\mathrm{Fe}}_{2}$, Gd${\mathrm{Fe}}_{2}$, and Lu${\mathrm{Fe}}_{2}$ between 80 and 300 K. The analysis of the M\"ossbauer spectra allowed the determination of the easy axes of magnetization $\stackrel{\ensuremath{\rightarrow}}{\mathrm{n}}$ in these compounds. In Ce${\mathrm{Fe}}_{2}$, $\stackrel{\ensuremath{\rightarrow}}{\mathrm{n}}$ is parallel to the [100] direction up to 150 K; it then becomes of type [$\mathrm{uuw}$] with an angle of inclination with respect to the [100] axis of 20\ifmmode^\circ\else\textdegree\fi{}. Just below the Curie temperature at 230 K, this angle increases to 30\ifmmode^\circ\else\textdegree\fi{}. In Gd${\mathrm{Fe}}_{2}$, $\stackrel{\ensuremath{\rightarrow}}{\mathrm{n}}$ is parallel to the [100] direction at 80 and 300 K. In Lu${\mathrm{Fe}}_{2}$, $\stackrel{\ensuremath{\rightarrow}}{\mathrm{n}}$ is of [$\mathrm{uuw}$] type at 80 and 300 K. In terms of the phenomenological treatment of the magnetic anisotropy, the presence of an [$\mathrm{uuw}$] type of easy axis of magnetization indicates that the bulk magnetic-anisotropy constant ${K}_{3}$ is of the same order of magnitude as ${K}_{1}$ and ${K}_{2}$. The hyperfine parameters of the three compounds are reported and discussed.
Blended vs. flipped teaching: One course - Three engineering schools

Renee M. Clark serves as research assistant professor focusing on assessment and evaluation within the University of Pittsburgh’s Swanson School of Engineering and its Engineering Education Research Center (EERC), where her interests focus on active and experiential learning. She has 25 years of experience as an engineer and analyst, having worked most recently for Walgreens and General Motors/Delphi Automotive in the areas of data analysis, IT, and manufacturing. She received her PhD in Industrial Engineering from the University of Pittsburgh and her MS in Mechanical Engineering from Case Western while working for Delphi. She completed her postdoctoral studies in engineering education at the University of Pittsburgh.
Some results on empirical processes and stochastic complexity

This thesis contains two parts. In Part I, an intuitive and simple approach is used to obtain uniform convergence and Central Limit Theorems for empirical processes indexed by families of functions, for stationary mixing sequences with not too slow a $\beta$-mixing (or $\phi$-mixing) rate. The conditions imposed are in terms of random metric entropies, and the $\beta$-mixing (or $\phi$-mixing) rate. In the case of a Vapnik-Cervonenkis class, the uniform convergence result holds for any strictly stationary sequence with $\beta$-mixing (or $\phi$-mixing) rate $\beta\sb{n}$ (or $\phi\sb{n}$) = $o$($n\sp{-d}$) for some d $>$ 0, while the Central Limit Theorem requires the rate $\beta\sb{n}$ (or $\phi\sb{n}$ = $o$($n\sp{-d}$) for some d $>$ 3. In Part II, we use a shortest code length criterion to select the bin width of a histo-gram from a string of i.i. d. observations. Under smoothness conditions on the underlying density on (0, 1), this criterion is shown to be optimal as a code selection criterion in reaching the smallest redundancy within the class of codes under consideration. Furthermore, the criterion consistently selects the underlying density when it is uniform on (0, 1). Minimax lower bounds for the redundancy over many smooth families of underlying densities are also derived. In a special case, the lower bound is shown to be achieved almost surely, and in expectation, by a predictive code based on a sequence of histograms. In the case of Sobolev balls, the minimax optimal code is described and a heuristic proof is provided.
A Review of the Fungi That Degrade Plastic

Plastic has become established over the world as an essential basic need for our daily life. Current global plastic production exceeds 300 million tons annually. Plastics have many characteristics such as low production costs, inertness, relatively low weight, and durability. The primary disadvantage of plastics is their extremely slow natural degradation. The latter results in an accumulation of plastic waste in nature. The amount of plastic waste as of 2015 was 6300 million tons worldwide, and 79% of this was placed in landfills or left in the natural environment. Moreover, recent estimates report that 12,000 million tons of plastic waste will have been accumulated on the earth by 2050. Therefore, it is necessary to develop an effective plastic biodegradation process to accelerate the natural degradation rate of plastics. More than 400 microbes have been identified as capable of plastic degradation. This is the first paper of the series on plastic-degrading fungi. This paper provides a summary of the current global production of plastic and plastic waste accumulation in nature. A list is given of all the plastic-degrading fungi recorded thus far, based on the available literature, and comments are made relating to the major fungal groups. In addition, the phylogenetic relationships of plastic-degrading fungi were analyzed using a combined ITS, LSU, SSU, TEF, RPB1, and RPB2 dataset consisting of 395 strains. Our results confirm that plastic-degrading fungi are found in eleven classes in the fungal phyla Ascomycota (Dothideomycetes, Eurotiomycetes, Leotiomycetes, Saccharomycetes, and Sordariomycetes), Basidiomycota (Agaricomycetes, Microbotryomycetes, Tremellomycetes, Tritirachiomycetes, and Ustilaginomy-cetes), and Mucoromycota (Mucoromycetes). The taxonomic placement of plastic-degrading fungal taxa is briefly discussed. The Eurotiomycetes include the largest number of plastic degraders in the kingdom Fungi. The results presented herein are expected to influence the direction of future research on similar topics in order to find effective plastic-degrading fungi that can eliminate plastic wastes. The next publication of the series on plastic-degrading fungi will be focused on major metabolites, degradation pathways, and enzyme production in plastic degradation by fungi.
An Ergonomic Customized-Tool Handle Design for Precision Tools using Additive Manufacturing: A Case Study

A study was carried out with 135 surgeons to obtain a surgical laparoscopic grasper handle design that adapts to the size of each surgeon’s hand, in a functionally appropriate way, and has the sufficient ergonomics to avoid generating the problems detected nowadays. The main conclusion of the work is the practical 3D parametric design obtained for a laparoscopic surgical graspers handle that is scalable to fit each particular surgeon's hand size. In addition, it has been possible to determine that the anthropometric measure of the surgeon's hand defined as Palm Length Measured (PLM) allows the design of the 3D parametric model of the surgical handle to be conveniently scaled. The results show that both additive manufacturing and the application of ergonomics criterion provide an efficient method for the custom design and manufacture of this type of specialised tool, with potential application in other sectors.
Electromagnetic Characterization of Biological Tissues with Particle Swarm Optimization

The objective of this research is the electromagnetic characterization of biological tissues in radiofrequency domain. In this aim, a measurement bench including a vector network analyzer and an open-end coaxial probe was introduced. The complex permittivity identification of the middle under testing is performed by solving an inverse problem. A quadratic fitness function that represents the difference between reflection coefficient measurement and reflection coefficient acquired with the normalized aperture admittance is minimized. The optimization is based on a heuristic algorithm: particle swarm. The approach is validated on well known dielectric middle and then tested on biological tissues.
Synthetic Data Augmentation using GAN for Improved Breast Cancer Classiﬁcation

The application of computer vision to biomedical imaging holds many promises, from biomedical research to clinical diagnosis. With the appropriate dataset, deep learning can in principle detect disease at rates comparable to a physician’s diagnosis if not better. However, large quantities of high quality data are often challenging to obtain in the biomedical space. In this project, we explore whether image synthesis with generative adversarial networks (GANs) can address this challenge. Speciﬁcally, we evaluate the effectiveness of deep convolutional GAN (DC-GAN) and cycle adversarial network (CCAN) in augmenting training data to improve breast cancer classiﬁcation. Additionally, we also report heuristics that improve visual similarity between generated and real images. Overall, we found DCGAN to be the most effective method to improve breast cancer classiﬁcation accuracy. Accuracy and precision improved by around 5% and 12% respectively as a result of data augmentation. However, recall decreased by nearly 15% . Our work shows that it is possible to use image synthesis with GANs to improve certain performance metrics, but also highlights the many challenges associated with this task.
Information to the development of an educational manual for women with breast cancer

Resumen This study aimed to identify the necessary information to develop an educational material to assist women in preoperative surgery to treat breast cancer. For the construction, women with the diagnosis of breast cancer and who underwent surgery for the first time in up to six months were interviewed. 51 women aged between 25 and 84 years were included, 32 had a partner, 26 had incomplete elementary school, 24 considered their occupation as “housewife”, 43.1% underwent mastectomy, and 82.4% performed axillary dissection. They responded to an instrument with socio demographic data and questions concerning the information/guidance which they received from health team about types of surgery, hospitalization, anesthesia, use of drain and complications. For the preparation of the educational material, knowing this reality and the expectations of subjects are indispensable to prioritize the needs of clients and not only therapeutic requirements.