Miracle-dz/UniFAR-FTUs huggingface dataset:
A LOCAL APPROACH TO IDENTIFY THE IMPACT OF SUBJECT SPECIFIC MOVEMENT STRATEGIES ON THE LOCAL FORCES DURING CUTTING MANEUVERS

During multidirectional movements the body is not aligned with the global coordinate system (CS), complicating the interpretation of forces and moments. To overcome these issues, the global ground reaction force (GRF) was transformed into the CS of each segment and the orientation of the segments relative to the global CS were expressed in Euler angles (EA). Principle component analysis (PCA) was used to discriminate the wave forms of the local GRF and the EAs. The first three PC Eigenvectors of the EA and local GRF were correlated to determine the impact of the segment’s orientation on the GRF. An upright position of the shank and thigh segment increased the force acting medially on the knee. This potentially increases the risk of a varus movement, whereas a frontal tilt increased a laterally directed force that potentially stabilized the leg axis.
Comparison of Software Licensing and Development Models Using Val IT

Today Small Medium Enterprise (SME) in Indonesia increasingly growing, along with the growth of business done, of course must be offset by existing IT in the company, due to support the performance of the company. Who originally used it daily jobs done manually will be diverted to use software to help the work. But sometimes to develop the IT application, the obstacle typically encountered is about the budget for the investment of IT itself, therefore in this paper the authors compare the advantages and disadvantages between open source software and software Proprietary using VAL IT as a framework. For the result of the Open Source Software is low cost because the the code it is free but company should spend budget for the training and for the report the company need to learn to create the reporting. While for software Proprietary is high cost but support is conducted regularly for operational and for just ask the vendor to create report.
For a hybrid vehicle drivetrain

A vehicle powertrain, comprising: a planetary gear transmission which includes an output unit, a first power source connected to the first member and a second member connected to the second power source; brake for alternately releasing output unit and the holding section to prevent rotation of the output; motor comprising drivably connected to a wheel portion of the second output; and a clutch for the opening and closing drive unit is connected between the output and the wheel.
Learning data representations for robust neighbour-based inference

Learning data representations for robust neighbour-based inference Tharindu Salinda Bandara Adikari Mudiyanselage Master of Applied Science The Edward S. Rogers Sr. Department of Electrical & Computer Engineering University of Toronto 2018 The recently proposed Boundary Trees algorithm by Mathy et al. (2015) enables fast neighbourbased classification, regression and retrieval in large datasets. While boundary trees use a Euclidean measure of similarity, the Differentiable Boundary Tree (DBT) algorithm by Zoran et al. (2017) was introduced to learn low-dimensional representations of complex input data, on which semantic similarity can be measured, to train boundary trees. The DBT approach contains a few limitations that prevents it from scaling to large datasets. In this thesis, we introduce Differentiable Boundary Sets, an algorithm that overcomes the computational issues of the DBT scheme and also improves its classification accuracy and data representability. Our algorithm is efficiently implementable with existing tools and offers a significant reduction in training time. We test and compare the proposed algorithm on the well known MNIST handwritten digits dataset and the newer Fashion-MNIST dataset by Xiao et al. (2017).
Parallel Fixed Switching Frequency CRM and DCM Boost PFC Converter With High Power Factor

Critical conduction mode (CRM) or discontinuous conduction mode (DCM) boost power factor correction (PFC) converter is widely used in low power applications for its advantages of zero-current turn-on of the switch, no reverse recovery in diode, and simple control. The input current of fixed switching frequency control CRM boost PFC converter and the input current of constant duty-cycle control DCM boost PFC converter mainly contain third harmonic. Moreover, the phase of the third harmonics is opposite. This article proposes a harmonic elimination parallel control to connect these two converters in parallel. The input current third harmonic of the parallel converter can be eliminated completely so as to improve the PF to nearly unity in the whole input voltage range. This parallel method is an interesting way to extend power, and is different from the existing method of parallel DCM boost PFC converter or parallel CRM boost PFC converter. The experimental results verify the accuracy of the theoretical analysis.
A Review on Palmprint Authentication System using various Feature Extraction and Classification Techniques

Biometric as a technology was largely limited to organisational and governmental purposes only where the purpose of usage was to Identify or to verify an user or individual in particular. The introduction of biometric authentication in regular consumer electronics such as smart phones has extrapolated the technology usage in numbers. In the recent years, the area of biometric has gained more popularity and as a result, become more attractive to many researchers. According to a recent study by Juniper Research, it is estimated that more than 770 million biometric authentication applications will get downloaded each year, by the year 2019. With an increase in number of users adopting biometric technology, the threat of data loss in the form of identity theft and its subsequent consequences (which may or may not be severe in nature) is significantly high and therefore a need of enhancement and upgradation of the technology
Ultrasound-guided thoracic paravertebral block for percutaneous kyphoplasty: A prospective non-randomized comparative study

Introduction Kyphoplasty for osteoporotic vertebral compression fractures was short but painful. The purpose of the current study was to investigate the effects and safety of ultrasound-guided thoracic paravertebral block in patients undergoing percutaneous kyphoplasty (PKP). Methods A prospective study of 195 patients with thoracic compression fracture undergoing PKP was conducted. The patients were non-randomly assigned to receive an ultrasound-guided thoracic paravertebral block (Group P, n=96) and local infiltration anesthesia (Group L, n=99), and were compared along with intraoperative parameters and anesthetic effects. Visual analog scale (VAS) of pain, systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) were measured at pre-anesthesia (T0), post-anesthesia (T1), trocar insertion (T2), balloon dilatation (T3), cement injection (T4) and post-operation (T5). Results The anesthesia time was significantly longer in group P than in group L. There were no significant differences in the epidemiological data, operation time, blood loss, hospitalization time complications and costs between the two groups. The additional analgesics rate was significantly lower in group P than in group L. The investigators’ satisfaction scores, patients’ anesthesia satisfaction scores and intention rate of re-administration anesthesia were significantly higher in group P than in group L. Intraoperative VAS score (T1-T4) was significantly lower in group P than in group L. There was no significant difference in VAS scores (T0 and T5), SBP, DBP and HR between these two groups. Conclusion Ultrasound - guided thoracic paravertebral block achieved more effective analgesia in comparison to local infiltration groups in patients undergoing percutaneous kyphoplasty.
A DNN-based Post Filter for Geometric Source Separation

In robot audition, the capability of separating or extracting the target speaker signal from the mixture is essential for the auditory information processing. As a powerful method in source separation, the geometric source separation (GSS) algorithm is widely used in many robot audition systems. However, its performance is limited in the real “cocktail party” environments, where the target source is immersed in background noise and interference. In this paper, a deep neural network (DNN)- based post filter is proposed to enhance the output of the GSS method. The proposed DNN-based post filter can suppress the residual background noise and channel leakage without making any assumption about the noise and the leakage as the conventional approach does. The experimental results show that the proposed approach outperforms the conventional method in terms of the short-time objective intelligibility (STOI) and the perceptual evaluation of speech quality (PESQ).
Climate change as a catalyst of social evolution

Anthropogenic climatic change will be a major factor shaping natural populations over the foreseeable future. The scope of this issue has spawned the integrative field of global change biology, which is chiefly concerned with identifying vulnerabilities of natural systems to climate change and integrating these into models of biodiversity loss. Meanwhile, there remains considerable latitude for investigating the multiple indirect and nuanced ways that broad-scale shifts in the abiotic environment will impact biological systems. One major unexplored category of effects is on social organisation. While climate has consistently been implicated as a major source of natural selection responsible for facilitating the evolution of complex animal societies, studies directed at testing these links on contemporary climatic time scales have thus far been limited to a select few higher-order, eusocial, taxa. Here, we present the case for how climate change, and specifically rising global temperatures, could catalyze social change at multiple stages of social evolution. We argue that these effects will manifest themselves through a range of subtle, climate-mediated pathways affecting the opportunities, nature, and context of interactions between individuals. We propose a broad conceptual framework for considering these pathways first at the individual level, and then discuss how feedbacks between bottom-up and top-down processes could mediate population-level shifts. We then implement this framework to explore the capacity for climate-mediated shifts in social evolution within three broad categories of social complexity: social group formation, social group maintenance, and social elaboration. For each category, we leverage social evolutionary theory and phylogenetic work spanning diverse systems to describe the pivotal traits that underpin transitions from each level of social complexity. In doing so, we aim to build a case for how short-term individual responses to climate could scale to impart constructive and/or destructive effects on the origins, maintenance, and diversification of animal societies.
Energy Saving by Handoff Classification in Femtocells Network

A femtocell is a radio equipment hich aims to improve the quality of the telecommunications network in customers' homes and / or in places that do not support the coverage of macro network. We focused our work on the issue of saving the energy consumed by femto-cells. In this paper, we introduce an energy efficient solution, to the cited issue, based on the removal of unwanted mobility events by classifying them according to their probabilistic importance in the context of BWA (Broadband Wireless Access) networks. We derived the analytical model of the solution. The first simulation results seem to confirm the advantage of our solution in reducing energy consumption.
Network review emotion mining based on Domain Ontology

In the era of e-commerce, network reviews have become one of the most important means for people to exchange and obtain product information. It is an urgent need for consumers and enterprises to quickly and effectively obtain consumers’ emotional attitude towards products from a large-scale network review. In order to better extract the product attributes involved in the network reviews and the emotional attitude of the consumer to the product attributes, this paper proposes a method of online comment sentiment analysis based on domain ontology. This method constructs the domain ontology, uses this ontology to extract product attributes, and constructs a domain sentiment dictionary to realize the emotional calculation of product attributes.
Important differences in cardiovascular autonomic control of hypertensive middle-aged women and men – a critical appraisal

BackgroundNormotensive women before menopause showed a vagal predominance of cardiac autonomic modulation, while age-matched men showed a sympathetic modulation predominance. However, some women develop systemic arterial hypertension (SAH) even with preserved ovarian function. Our hypothesis is that these women may have cardiovascular autonomic parameters like those of hypertensive men, even when subjected to pharmacological treatment. We aim to investigate the cardiovascular autonomic modulation balance and baroreflex sensitivity (BRS) in hypertensive women with preserved ovarian function and age-matched men.MethodsOne hundred volunteers between 18 and 45 years of age, were assigned to two groups of fifty: Hypertensive group, with a SAH history for at least 6 months (25 men and 25 women) treated with monotherapy (losartan, 25-50mg/kg) and normotensive group (25 men and 25 women). Anthropometric, hemodynamic, metabolic, and autonomic cardiovascular assessments were performed focusing: BRS, autonomic modulation of heart rate variability (HRV) and blood pressure variability (BPV). ResultsThe results showed that HRV analysis, women showed higher values ​​of HF oscillations in absolute and normalized units, and lower values ​​of LF in normalized units and LF/HF ratio compared to men. When normotensive and hypertensive groups were compared, hypertensive groups showed lower values ​​of total variance, LF and HF bands in absolute units. There were similar in BPV. However, hypertensive groups showed lower BRS values when compared to normotensive group.ConclusionThe results indicate that hypertensive groups even with blood pressure controlled through pharmacological treatment, continued to have reduced HRV than normotensive, and hypertensive women have minor cardiovascular autonomic impairment than men.
A novel approach for predicting protein functions by transferring annotation via alignment networks

One of the challenges of the post-genomic era is to provide accurate function annotations for orphan and unannotated protein sequences. With the recent availability of huge protein-protein interactions for many model species, it becomes an opportunity to computational methods to elucidate protein function based on many strategies. In this respect, most automated computational approaches integrate diverse kinds of functional interactions to deduce protein functions by transferring annotations across different species by relying on similar sequence, structure 2D/3D, amino acid motifs or phylogenetic profiles. In this work, we introduce a new approach called TANA (Transferring Annotation via Network Alignment) for inferring protein function which is based on our approach MAPPIN for GNA (Global Network Alignment). The main originality of the introduced approach stands on discovering functional modules within the PPI network by transferring annotation via network alignment. Doing so, we are able to discover the functions of proteins that could not to be easily described by sequence homology. We assess the performance of our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and highlight a sharp significant improvement over other competitive methods, in particular for predicting molecular functions.
Minimized the Complexity of Digital Circuit with GA Approach: A Review

Digital Equipments are the necessity in the current scenario. Rapid growth of digital world has taken the researchers interest in order to improve the performance of circuit. As the time increases the complexity of circuit will also increase. It also seems to be that there are number of outputs will generate by the circuit. The challenge is that which one is the best or maximum. Such output can find by the various methods. This paper is a review on various methods and the genetic approach which are used in digital circuits. It also throws light on the basic steps of genetic algorithm and its application.
Increasing Motion Fidelity in Driving Simulators Using a Fuzzy-Based Washout Filter

The motion cueing algorithm is the procedure used to regenerate vehicle motion cues by transforming translational and rotational motions of a simulated vehicle into the simulator motion such that high fidelity motions can be generated through a washout filter. Classical washout filters are widely being used in different motion simulators because of their low computational load, simplicity, and functionality. However, they have a number of disadvantages that make them unreliable in some cases. One of the main disadvantages is its parameter selecting procedure, which is based on trial-and-error and the worst case driving scenario. In addition, the washout filter parameters are kept constant during different driving scenarios, causing inflexibility of the filter design. This causes conservative platform workspace usage and as a result false motion cues. Furthermore, the mathematical model of human motion sensation plays no role in designing of the classical washout filter. Ignorance of the online information about physical limitations of the platform and the simulator driver motion sensation factors are other main drawbacks of classical washout filters. The aim of this research is to provide a fuzzy logic-based washout filter that considers the motion sensation error between the real vehicle and simulator drivers as well as the distance of the simulator platform from its physical boundaries to correct false motion cues and decrease human sensation errors. The proposed fuzzy-based washout filter also seeks to increase motion fidelity and enable the simulator to use the platform workspace more efficiently. The simulation results show the efficiency of the proposed fuzzy-based washout filter in reducing the human sensation error and enhancing efficiency of the simulator platform workspace usage.
Distributed Rendering Based on Fine-Grained and Coarse-Grained Strategy to Speed up Time and Increase Efficiency of Rendering Process

The purpose of this research was to solve several problems in the rendering process such as slow rendering time and complex calculations, which caused inefficient rendering. This research analyzed the efficiency in the rendering process. This research was an experimental study by implementing a distributed rendering system with fine-grained and coarse-grained parallel decomposition in computer laboratory. The primary data used was the rendering time obtained from the rendering process of three scenes animation. Descriptive analysis method was used to compare performance using speedup and efficiency of parallel performance metrics. The results show that the distributed rendering method succeeds in increasing the rendering speed with speedup value of 9,43. Moreover, the efficiency of processor use is 94% when it is applied to solve the problem of slow rendering time in the rendering process.
American Economic Association Universal Academic Questionnaire Summary Statistics

Published here is information from the 2005 Universal Academic Questionnaire, an annual survey of U.S. university economics departments. One survey goes to each institution, addressed to the chair of the Department of Economics. Responses apply only to that department. Economists employed in other academic units are not included in the survey. We try to maintain the confidentiality of individual institutions’ responses. The accuracy and scope of these tables depends on the cooperation of departments in completing the UAQ. For the Fall 2005 survey, the total number of usable responses was 245. The 2006 questionnaire will be mailed in October.
Implementing publisher policies that inform, support and encourage authors to share data: two case studies

Open research data is one of the key areas in the expanding open scholarship movement. Scholarly journals and publishers find themselves at the heart of the shift towards openness, with recent years seeing an increase in the number of scholarly journals with data-sharing policies aiming to increase transparency and reproducibility of research. In this article we present two case studies which examine the experiences that two leading academic publishers, Taylor & Francis and Springer Nature, have had in rolling out data-sharing policies. We illustrate some of the considerations involved in providing consistent policies across journals of many disciplines, reflecting on successes and challenges.
STRATEGIES HUMAN RESOURCE MANAGEMENT

strategies is carried out, features of implementation of policies of HRM for each of them are defined. The features of employee behavior under different types of HRM strategies are systematized. The peculiarities of the application of digital HRM strategy are analyzed, the opportunities that arise in the enterprise from the implementation of the digital-HRM approach are indicated. The relevance of further research on the analysis of theoretical approaches to strategic HRM of the enterprise is argued.
The Effects of Media Co-coverage on Investors’ Perceived Relatedness between Two Firms: Evidence from Information Transfers

This study examines the effects of media co-coverage—a phenomenon where multiple firms are simultaneously mentioned in the same news article—on investors’ perceived relatedness between the co-covered firms. Using the setting of information transfers during two co-covered firms’ earnings announcements, I find evidence consistent with co-coverage increasing the firms’ perceived relatedness. Specifically, the announcement return of an early-announcing co-covered peer negatively predicts the announcement return of the subsequently-announcing focal firm, suggesting that focal firm investors overreact to the peer’s earnings news. The negative return predictability is stronger when investors are more likely to pay attention to the article where the two firms were co-covered and when the peer’s earnings are more relevant to the focal firm’s upcoming earnings announcement. These findings shed light on an unintended consequence of journalists’ co-coverage practice on the efficiency with which equity investors use peer information.
Forecasting Kunjungan Wisatawan Dengan Long Short Term Memory (LSTM)

Bali is one of the favorite tourist attractions in Indonesia, where the number of foreign tourists visiting Bali is around 4 million over 2015 (Dispar Bali). The number of tourists visiting is spread in various regions and tourist attractions that are located in Bali. Although tourist visits to Bali can be said to be large, the visit was not evenly distributed, there were significant fluctuations in tourist visits. Forecasting or forecasting techniques can find out the pattern of tourist visits. Forecasting technique aims to predict the previous data pattern so that the next data pattern can be known. In this study using the technique of recurrent neural network in predicting the level of tourist visits. One of the techniques for a recurrent neural network (RNN) used in this study is Long Short-Term Memory (LSTM). This model is better than a simple RNN model. In this study predicting the level of tourist visits using the LSTM algorithm, the data used is data on tourist visits to one of the attractions in Bali. The results obtained using the LSTM model amounted to 15,962. The measured value is an error value, with the MAPE technique. The LSTM architecture used consists of 16 units of neuron units in the hidden layer, a learning rate of 0.01, windows size of 3, and the number of hidden layers is 1.