Miracle-dz/UniFAR-FTUs huggingface dataset:
Autonomous Machine Learning Framework for Detecting People Aliveness

Determining the aliveness of people is essential for various people safety systems. While the accuracy of the aliveness determination is a key concern, there exist technical challenges in the aliveness determination with high accuracy. Our approach to the challenges is to incorporate a set of effective design tactics into a software framework. We employ machine learning models in the detection process and apply the continuous optimization of the aliveness model using autonomous computing principles. This paper presents a comprehensive framework which consists of design and implementation. Our extensive experiments show that the accuracy of aliveness determination with this framework outperforms at least 30% of conventional approaches.
Efficient Rendering of Large-Scale CAD Models on a GPU Virtualization Architecture with Model Geometry Metrics

Visualization of 3D models based on cloud computing environments has been widely recognized and used. However, real-time visualization of full-size 3D models of complex industrial products (such as detailed airplane CAD models) is still inefficient. Therefore, massive dataset preprocessing and and rendering algorithms need to be optimized in conjunction with cloud computing environments. In this paper, a geometry metric method is proposed based on minimum bounding box and multi-view projections, which is able to accurately identify narrow and irregular small parts in the model. Then, combining with a GPU-based visibility culling algorithm, the real-time rendering rate of massive CAD models is highly improved. Moreover, a sort-first parallel rendering with a cluster of virtual machines is implemented on a virtual GPU (vGPU) architecture for the sake of accelerating rendering speed by exploiting high computing capability of vGPU. A prototype software system is developed to render large-scale CAD models with the proposed architecture and algorithms. The experimental results show that users can explore CAD dataset with hundreds of millions of triangles in interactive frame rate with our technique.
Subspace Based Sequence Discriminative Training of LSTM Acoustic Models with Feed-Forward Layers

State-of-the-art automatic speech recognition (ASR) systems use sequence discriminative training for improved performance over frame-level cross-entropy (CE) criterion. Even though sequence discriminative training improves long short-term memory (LSTM) recurrent neural network (RNN) acoustic models (AMs), it is not clear whether these systems achieve the optimal performance due to overfitting. This paper investigates the effect of state-level minimum Bayes risk (sMBR) training on LSTM AMs and shows that the conventional way of performing sMBR by updating all LSTM parameters is not optimal. We investigate two methods to improve the performance of sequence discriminative training of LSTM AMs. First more feed-forward (FF) layers are included between the last LSTM layer and the output layer so those additional FF layers may benefit more from sMBR training. Second, a subspace is estimated as an interpolation of rank-1 matrices when performing sMBR for the LSTM layers of the AM. Our methods are evaluated in benchmark AMI single distance microphone (SDM) task. We find that the proposed approaches provide 1.6% absolute improvement over a strong sMBR trained LSTM baseline.
MRI Atlas of the Human Deep Brain

Mastering detailed anatomy of the human deep brain in clinical neurosciences is challenging. Although numerous pioneering works have gathered a large dataset of structural and topographic information, it is still difficult to transfer this knowledge into practice, even with advanced magnetic resonance imaging techniques. Thus, classical histological atlases continue to be used to identify structures for stereotactic targeting in functional neurosurgery. Physicians mainly use these atlases as a template co-registered with the patient's brain. However, it is possible to directly identify stereotactic targets on MRI scans, enabling personalized targeting. In order to help clinicians directly identify deep brain structures relevant to present and future medical applications, we built a volumetric MRI atlas of the deep brain (MDBA) on a large scale (infra millimetric). Twelve hypothalamic, 39 subthalamic, 36 telencephalic, and 32 thalamic structures were identified, contoured, and labeled. Nineteen coronal, 18 axial, and 15 sagittal MRI plates were created. Although primarily designed for direct labeling, the anatomic space was also subdivided in twelfths of AC-PC distance, leading to proportional scaling in the coronal, axial, and sagittal planes. This extensive work is now available to clinicians and neuroscientists, offering another representation of the human deep brain ([https://hal.archives-ouvertes.fr/] [hal-02116633]). The atlas may also be used by computer scientists who are interested in deciphering the topography of this complex region.
A Fast Hyperspectral Classification Method by Integrating Rotational Invariant Linear Discriminant Analysis and Nearest Regularized Subspace

Although feature extraction methods can improve hyperspectral image (HSI) classification speed, how to improve the effectiveness of HSI classification is also still a big challenge due to its high spectral dimensionality. The classical feature extraction methods increase the speed of classification at the cost of accuracy lost. By analyzing the correlation and differences between classes in the training samples, a new hyperspectral classification method called RILDA-NRS based on rotational invariant linear discriminant analysis theory (RILDA) and nearest regularized subspace (NRS) theory was proposed in this paper. RILDA was first used in the proposed method to extract the useful spectral features from hyperspectral images, in which not only the dimensionality of HSI is reduced, but also the discriminability between samples is enhanced. Then, the feature extraction results are embedded into the NRS classification model to classify HSI. The experimental results have demonstrated that the proposed method has obvious advantages in terms of classification accuracy and speed.
Anatomical variations of maxillary sinus: a cone-beam computed tomography study

The goal of current project was to evaluate the maxillary sinus dimensions using cone-beam computed tomography (CBCT) to assess anatomical variations. A total of 86 CBCT examinations were retrospectively performed in this regard. In this study, the Promax 3D CBCT unit was used for the dimension determination in para-axial, occlusal and panoramic views. In para-axial view, sinus height and width were 31.7 mm and 23.2 mm, in panoramic view (frontal plan) 29.9mm and 27.9 respectively and in occlusal view mean sinus length and width were 33.9 mm and 23.1 mm respectively. The dome-shaped maxillary sinus cyst was observed in 27% of patients. Sinus septum was determined in 29 % of patients (the mean height =8.1 mm). Other results were included the distances from the anterior wall of maxillary sinus to the midline mean distance (31.4 mm, SD= 8.3) and the mean distance from the lower border of the maxillary sinus to the alveolar crest of the maxilla (11.0 mm, SD= 4.4). Anatomical variations of maxillary sinus can change some vital surgery planning. The cone-beam computed tomography (CBCT) can be applied for an accurate assessment and additional validation of maxillary septum existence and avoid unnecessary surgical examinations.
ARE THERE CHANGES IN ORGANOPHOSPHORUS POISONING TRENDS OVER A 10 YEARS PERIOD?

Organophosphates poisoning represents a challenge for the emergency medical specialist, the first who comes into contact with intoxicated patients and who should promptly manage this pathology. Our study aims to determine whether there are any significant changes after a 10 years period regarding some characteristics of the patients with acute organophosphorus compounds poisoning. The study was retrospective, observational, descriptive, non-randomized and took place at the Bucharest Emergency Clinical Hospital during 1st of January 1995 – 31st of December 1997 and 1st of January 2014 – 31st of December 2016 respectively. Our study was based on the comparative assessment of two groups of patients as follows: patients admitted during 1995-1997 (292 patients) and patients admitted during 2014-2016 (161 patients). The percentage of suicidal attempts through organophosphorus compounds decreased over the course of 10 years from 84.78% in 1996 to 63.63% in 2016. A psychiatric pathology was identified in 39.31% of the suicidal attempts and in 15.68% of accidental contact cases. Regarding the distribution of exposure type per year, we observed an increase in cases where the penetration pathway occurred through skin and inhalation from 9.57% in 1995 to 18.33% in 2015, with a proportional decrease in the digestive exposure. In the analyzed groups, 36 deaths were identified, with an equal distribution in the two studied periods, of about 8-10%. Although there was a 10-year interval between the two patient lots during which intensive care techniques have significantly progressed, we observed from the statistical data that the death rate did not decrease significantly in the 2014-2016 lot compared to the 1994-1996 lot. We believe that this is partly due to the gravity of these patients and to the time elapsed from the presentation of the patients to the physician and appropriate treatment initiation.
Science And Human Behavior

Thank you very much for reading science and human behavior. As you may know, people have look numerous times for their chosen readings like this science and human behavior, but end up in malicious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they juggled with some infectious bugs inside their computer. science and human behavior is available in our digital library an online access to it is set as public so you can get it instantly. Our book servers hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the science and human behavior is universally compatible with any devices to read.
Utilizing Cognitive Resources in User Interface Designs

This chapter focuses on multiple representations and cognitive perspective about presenting information via different modes in user interface design. Research studies indicate that providing accurate representations increases users’ recognition of information. Moreover, presentation of one concept in multiple modes improves concept acquisition. Developing an understanding of how concept acquisition occurs requires knowledge about cognitive information processing and brain functioning. Scientific studies related to brain functioning will enlighten the path in front of cognitive psychology while the cognitive psychology research will advance the knowledge base on information processing.
Secure Configuration Scheme for Internet of Things using NFC as OOB Channel

The PSK (Pre-shared Secret Key) based method is appropriate for the IoT environment consisting of lightweight devices since this method requires less computing time and energy than the method to configure the session key based on the public key algorithm. A fundamental prerequisite for the PSK based method is that PSK should have been configured between the communication entities safely in advance. However, in case of a small sensor or actuator, no input and output interface such as keyboard and monitor required for configuration exists, so it is more difficult to configure PSK for such lightweight devices safely in the IoT environment than the previous Internet devices. Especially, normal users lack expertise in security so they face difficulty in configuration. Therefore, the default value configured at the time of manufacturing at factories is used or the device installer configures PSK in most cases. In such case, it is a matter for consideration whether all installers and manufacturers can be trusted or not. In order to solve such problem, this paper proposes a secure bootstrapping scheme, which utilizes the NFC (Near Field Communication) as an OOB (Out-Of-Band) channel, for lightweight devices with limited resources.
A Method of Using Genetic Algorithm in Image Stitching

Image stitching is an important part of computer vision, and how to do it more efficiently with high quality is a heated topic. In this paper, the authors propose a new method called TMGA for image stitching to get an improved performance in calculating Transform Matrix by using Genetic Algorithm. The proposed TMGA not only counts the number of interior points, but also takes standard error and degree of dispersion into consideration compared the traditional methods. The results demonstrate that the proposed algorithm can gain a high-quality transform matrix and improves the result of the stitching.
A TOF Laser Radar Receiver with 100dB-Level Dynamic Range and mm-Level Accuracy

This paper presents an integrated receiver with 100dB-level dynamic range and mm-level accuracy for a time-of-flight (TOF) laser radar system. In this receiver, the differential current signals generated by the photodiode are fed into a trans-impedance amplifier (TIA) and a low-impedance amplifier (LIA) separately to achieve a wide single-shot measurement dynamic range. A timing discrimination scheme based on converting the incoming unipolar pulses into bipolar ones is adopted to reduce the walk errors. Simulation results show that the proposed receiver achieves a dynamic range of more than 1:200000 (106dB) while keeping the walk error less than ±42ps (±6.3mm in distance) without any need for complicated gain control techniques or troublesome calibration methods.
Sketching Islands for a Game Environment

We present a simple interface for sketching height- maps of islands. This interface is close to the ideal of a modeless single-tool interface, with all of its major operations being controlled by a single device (pen or single-button mouse). As such is easy to use even for novice users and requires no technical knowledge. (10 pages)
Necessity and proper way of intermediate kissing balloon dilation for culotte stenting: further insights from bench testing

Objective: The aim of this study was to investigate whether intermediate kissing balloon dilation (IKBD) is necessary during mini-culotte stenting (MCS) and how it can be properly conducted. Methods: MCS was emulated in a bifurcation model with a branch diameter difference (BDD) in three-step sizes of 0.50, 0.75 and 1.00 mm, and with intermediate balloon dilation (IBD) in three treatments of routine intermediate solo balloon dilation (rISBD), concurrent IKBD (cIKBD) or sequential IKBD. Microcomputed tomography was performed to assess stent under-expansion (SUE) around the polygon of confluence (POC), residual ostial stenosis (ROS) at the ostial side-branch (SB) and main-branch (MB) and stent cell distortion (SCD) in the bifurcation segments. Results: There were both main and interactive effects of IBD and BDD on ROS at the ostial SB and SCD in the ostial SB, but there were only main effects of IBD or BDD on SUE around the POC, ROS at the ostial MB and SCD in the ostial MB. Analysis of the main effects showed that SUE around the POC or ROS at the ostial SB was significantly different between sIKBD and rISBD and between cIKBD and rISBD. There was also a significant difference in SCD in the ostial SB between sIKBD and rISBD and between sIKBD and cIKBD. Analysis of the interactive effects showed that ROS at the ostial SB or SCD in the ostial SB was affected by all IBD treatments in all BDD step-sizes. Moreover, increasing the BDD step-sizes significantly increased ROS at the ostial SB as treated by rISBD and SCD in the ostial SB as treated by rISBD or cIKBD. Conclusions: SIKBD was shown to be essential and superior to rISBD or cIKBD, resulting in better bifurcated stent expansion and coverage when using MCS.
Attack Graph Generation and Analysis Techniques

As computer networks are emerging in everyday life, network security has become an important issue. Simultaneously, attacks are becoming more sophisticated, making the defense of computer networks increasingly difficult. Attack graph is a modeling tool used in the assessment of security of enterprise networks. Since its introduction a considerable amount of research effort has been spent in the development of theory and practices around the idea of attack graph. This paper presents a consolidated view of major attack graph generation and analysis techniques.
Predicting the Next Process Event Using Convolutional Neural Networks

Adding the feature of business process event prediction to information systems increases its productivity in the long run, enhances the quality of the taken decisions, and eliminates inconsistencies. Inspired by the previous works of employing deep learning approaches to predicting the next process event based on files of logged events, we propose the use of one-dimensional convolutional neural networks (1D CNN) to address the same problem. In the proposed approach we used a five-layer 1D CNN method to predict the next process event based on the previous instances. This paper compared the proposed approach with other approaches that used recurrent neural networks (RNN) with Long Short-Term Memory (LSTM) neural networks, and others on eight datasets. The proposed approach outperformed all the previous studies of the state-of-the-art in this domain on all the provided datasets.
OCCURRENCE OF HIV AND SYPHILIS IN THE PRENATAL CARE OF PRIMARY HEALTH CARE

Objective: To identify in the literature the factors related to the occurrence of HIV and syphilis cases in pregnant women in primary health care. Method: Integrative review, carried out in Latin American and Caribbean databases on Health Sciences (LILACS), Scientific Electronic Library Online (SCIELO), CAPES portal and MEDLINE were selected to search for primary studies. Results: From a thorough reading of the selected studies in full, the ordering and investigation of the themes was carried out, with the purpose of describing and classifying the results, demonstrating the knowledge acquired with the presented theme. Thus, 11 researches in full, established sampling for denote results of the convenient guiding question. Conclusion: several factors favor the increase of cases of these infections in pregnant women, from the inefficiency of the programs of capture of this woman, lack of professional action in the face of this problem until the lack of resources to subsidize the work of the health team.
Cloud-Based Computing Architectures for Solving Hot Issues in Structural Bioinformatics

Bioinformatics as a scientific domain develops tools that enable understanding the wealth of information hidden in huge volumes of biological data. However, there are several problems in bioinformatics that, although already solved or at least equipped with promising algorithms, still require huge computing power in order to be completed in a reasonable time. Cloud computing responds to these demands. This chapter shows several cloud-based computing architectures for solving hot issues in structural bioinformatics, such as protein structure similarity searching or 3D protein structure prediction. Presented architectures have been implemented in Microsoft Azure public cloud and tested in several projects developed by Cloud4Proteins research group.
Analysis & Design of Control Systems using MATLAB

KEY FEATURES:-Step by step explanations guide through the complex material involving a diverse variety of concepts. -Proper allocation and extensive use and application of MATLAB. -Detailed illustrations of solution methods save a lot of time and effort in understanding problems and theoretical concepts. ABOUT THE BOOK: The book Analysis and Design of Control Systems using MATLAB, is designed as a supplement to an introductory course in feedback control systems for undergraduate or graduate engineering students of all disciplines. Feedback control systems engineering is a multidisciplinary subject and presents a control engineering methodology based on mathematical fundamentals and stresses physical system modeling. This book includes the coverage of classical methods of control systems engineering: introduction to control systems, matrix analysis, Laplace transforms, mathematical modeling of dynamic systems, control system representation, performance and stability of feedback systems, analysis and design of feedback control systems, state space analysis and design, MATLAB basics and MATLAB tutorial. The numerous worked examples offer detailed explanations, and guide the students through each set of problems to enable them to save a great deal of time and effort in arriving at an understanding of problems in this subject. Extensive references to guide the students to further sources of information on control systems and MATLAB is provided. In addition to students, practising engineers will also find this book immensely useful. ABOUT THE AUTHOR(S): Dr Rao V Dukkipati Ph.D., PE is Professor, Chair and Graduate Program Director of the Mechanical Engineering Department at Fairfield University, Connecticut, USA. He also serves as an adjunct professor in the Mechanical Engineering Department at Concordia University, Montreal, Canada. He took his Doctorate degree from Oklahoma State University, Stillwater, USA in 1973. His specialized areas of teaching and research include mechanical design, mechanics, vibrations, control systems, economy and reliability, quality control improvement and management, vehicle dynamics and accident reconstruction. He has to his credit over 300 technical papers and 38 books. He is fellow member of ASME and CSME and holds professional membership of seven national and international associations.
Antioxidant Properties of Thai Traditional Herbal Teas

Recipes for Thai traditional herbal teas have been formulated based on Thai traditional medicine, which tries to achieve a balance of the body’s elements (fire, water, wind and earth) in each season. This study aims to assess the benefits of Thai traditional herbal teas through evaluating their antioxidant properties and measuring the satisfaction levels of healthy volunteers. Antioxidant activity tests performed on 11 tea recipes and on green tea (positive control) included 2,2-diphenyl-1-picrylhydrazyl (DPPH), a radical scavenging assay and a 2,2’-azino-bis-(3-ethylbenzothiazoline)-6-sulfonic acid (ABTS) assay. In addition, total phenolic contents were determined using a Folin-Ciocalteu assay. Tests of satisfaction were performed on volunteer subjects aged between 18 and 30 years old, using the criteria of color, flavor, taste and overall satisfaction. Among the 11 tea recipes tested, the summer recipe 1 containing Aegle marmelos (L.) Correa, Stevia rebaudiana (Bert.) Bertoni, Pandanus amaryllifolius Roxb. and Morus alba L. demonstrated the most promising antioxidant properties (p > 0.05) and a phenolic content (p > 0.05), which was comparable to green tea. Furthermore, it got the highest satisfaction scores in every assessed category. Therefore, this study shows that Thai traditional herbal teas, developed based on the concepts of Thai traditional medicine, could be a good choice for people looking for health-promoting beverages.