Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanical impedance control in the human arm while manually transporting an open-top fluid filled dish

The present study deals with stabilizing aspects of a hand-held dish filled with liquid while walking steadily. This is an attempt to decipher the neuro-muscular strategies employed and the mechanical responses of the arm during certain tasks of manual materials handling. The experimental configuration included a cup and the test-subject's hand as an 'end-effector' of a serial three-link system representing the upper limb. These links are connected together by the wrist, elbow and shoulder joints. The tested subjects walked at constant speed on a treadmill while aiming to minimize liquid spillage from the cup. The motion of the limb and shoulder girdle served as inputs to a model to reveal the impedance adjustments during the simultaneous control of grasping and walking under ordinary conditions, and when one of the joints is affected. A regressive function used to express stiffness, included first-order dependence on angle and on angular velocity. The function used for damping included first-order dependence on angular velocity. Redundancies in the numerical solution were eliminated using multicollinearity diagnostic algorithms. The results revealed that the wrist joint was found to have constant stiffness and damping and no regulation of these coefficients was necessary during gait. Both in the elbow and shoulder joints stiffness included a constant coefficient as well as an angular velocity-dependent coefficient. Although all tested subjects demonstrated ability to prevent spillage of liquid, there was a considerable variability among the results obtained, indicating that the compensatory mechanisms employed by each subject to regulate the mechanical impedance were subjective. These results can help in the optimization of manual materials handeling tasks in industrial settings as well as future design of prosthetic arms, robotic appliances and man machine interfacing devices.
Leveraging Machine Learning to Estimate Effect Modification

Sociologists are often interested in estimating and testing whether some causal effect varies by a modifier of interest. The conventional regression estimator for effect modification is inflexible in functional form and prone to misspecification bias. Machine Learning (ML) algorithms can aid the estimation of effect modification in observational studies by controlling for confounders in a highly flexible, automated, yet principled way. Therefore, leveraging ML for effect modification helps reduce misspecification bias and enhance the credibility of causal identification. We introduce a novel estimator that estimates effect modification in a familiar regression framework after using ML algorithms to fit nuisance components of the model. We show that this estimator is more flexible than the conventional regression model while more efficient and suitable for theory-driven sociological research than other ML-based methods. We use the new estimator to study the modification in the effect of a college degree on adult family income by gender and family income in adolescence in the United States. Along these two dimensions, the benefits of a college degree are rather equally distributed.
Artificial Neural Network–Based Slip-Trip Classifier Using Smart Sensor for Construction Workplace

AbstractThis paper presents a smart artificial neural network (ANN)-based slip-trip classification method, which integrates a smart sensor and an ANN. It was trained to identify the slip and trip events that occur while a worker walks in a workplace. It encourages preventive and collective actions to reduce construction accidents by identifying the type of near miss, i.e., slip or trip, and the exact time that it occurs. The variation in the energy released by a worker is measured using a triaxial accelerometer embedded in a smart phone. This study is of value to researchers because the method measures a near miss quantitatively using acceleration. It is also of relevance to practitioners because it provides a computerized tool that records each and every moment of a near-miss event. A test was performed by collecting the three-axis acceleration streams generated by workers wearing a smart phone running the classifier as they walked around a simulated construction jobsite. It identified the type of near m.
Controlador de Tráfico Inteligente con Prelación para Vehículos de Emergencia

This paper describes the development of a traffic controller using fuzzy logic, combined with the analysis of video sequences through machine vision techniques. The controller is able to automatically manage the traffic flow in a set of intersections, giving priority to the traffic lights of roads where there are emergency vehicles waiting. The system uses a classification algorithm, which is trained in order to detect any vehicle the scene and an image processing algorithm that identifies emergency vehicles within the previously detected vehicles. Using the information of video sequences acquired with CCD cameras installed on the intersections, the system choose the sequence of actions that improves the traffic flow, so as to increase the mobility in the road where the emergency vehicle is detected. Results show that the system is able to detect vehicles in real time. Also, the system adapts in an efficient and fast way to the changes in traffic flow in order to establish a priority road for emergency vehicles.
SAIC SENTINEL acoustic counter-sniper system

An acoustic surveillance system tailored to the detection and location of sniper fire was designed and a prototype built and tested. The SENTINEL system by Science Applications International Corporation exploits 100 kHz 16- bit digitization of signals from 16 condenser microphones in two volumetric arrays to make robust determinations of bearing, range, bullet trajectory, weapon caliber, and muzzle velocity. Signal processing is accomplished on VME hardware with C40 DSPs. Solutions are displayed within three seconds of a detected event on a ruggedized full-daylight- readable color laptop console. Typical accuracies are 1 degree to 2 degrees in azimuth and 2% to 10% in range, depending on range and environmental conditions. The large bandwidth and dynamic range, and exploitation of shock waveform period and amplitude estimates, give the system good capability even in difficult geometries and highly reverberant environments. In-depth study of the phenomenology of the ballistic shock wave was undertaken during the design phase. Results of this study are summarized.
A High-Efficient Data Model of Road Network in Vehicle Navigation System

Vehicle navigation system (VNS) is a world acknowledged efficient way of solving the urban traffic problem, and road network database is one of the core component parts in the system. In order to improve performance of VNS, this paper conducts a research on data organization technique of road network, and proposes a novel data model of road network, which includes spatial index and topology structure. Firstly, some common spatial index structures, such as regular grid index, R-tree index and quad-tree index, are studied, and a novel spatial index structure based on “hierarchical quad-tree and R-tree” index of two ranks is proposed. This structure can greatly reduce the access time of map data and raise index performance. Secondly, a topology model of road network based on arc-relation is presented, which can effectively solve turn penalty problems in the conventional topology model based on vertex-relation and represent real road network. Thirdly, a real topology storage structure using adjacency list is designed and a corresponding creating algorithm is put forward. Finally, the tests on the practical system prove that the proposed model effectively support kinds of data-processing and greatly raise the performance of the system.
Dual-Mode Switched-Capacitor DC-DC Converter for Subthreshold Processors with Deep Sleep Mode

Wireless sensor networks motivate the development of ultra-low power nodes based on subthreshold processors. As such applications are highly duty cycled, subthreshold processors must support two modes of operation: active mode and sleep mode in which RAM, timer and interrupt control must nevertheless remain powered on. In this paper, we propose a dual-mode switched-capacitor DC-DC converter to power such subthreshold processors with high efficiencies in both modes. It delivers a 0.4V output voltage from a 1-1.2V input source. Simulations in 0. 13μm CMOS technology show that the efficiency reaches 74% on a 100μW load, corresponding to the processor active mode. Adaptive body biasing and adaptive internal clock generation supplied by the output voltage allow the converter to maintain an efficiency of 60% on a load as low as 100nW, corresponding to the processor sleep mode.
Have Critical Audit Matter Disclosures Indirectly Benefitted Investors by Constraining Earnings Management? Evidence from Tax Accounts

ABSTRACT: Prior research indicates that expanded audit reports, which disclose financial statement matters that involved especially challenging, subjective, or complex auditor judgment (known as “critical audit matters” (CAMs) in the U.S.), have fallen short on their objective to provide investors with useful information. In this study, we investigate whether tax-related CAM disclosures indirectly benefit investors by constraining tax-related earnings management. Such a finding would indicate that the communication of CAMs has increased auditor and/or management scrutiny of the financial statement areas that underly critical audit matter disclosures. We find that tax-related CAM disclosures are associated with (1) a lower likelihood that the audited company uses tax expense to meet analysts’ consensus forecasts, and (2) increases in the reported reserve for prior-period uncertain tax benefits (UTBs). Our findings should assist the Public Company Accounting Oversight Board (PCAOB) with their postimplementation review of the new U.S. auditor reporting requirement.
A possible instrument for measuring ethical behavior of engineering students

Ethics is one of the most important competencies required of today's engineering graduates. All attempts towards developing that competency constitute, at best, conducting scenario and active learning-based courses and, at worst, delivering passive lectures. There is little chance of developing ethics with these methods. One must follow a systemic cycle of measures to build any such competency. Further, the measurement must be based on real-life situations with real stakes, especially for ethics, which is not easy. In fact, this is one of the most difficult competencies from both measurement and development perspectives. Ethics is reflected in most of the professional decisions. A decision depends on being able to identify and acquire right information and being able to identify and execute a process based on that information. A competent and qualified engineer typically does not make mistakes in these two stages. The next step, which involves implementing the decision, is susceptible to unethical influen.
Effects of conducting defects on resistive switching characteristics of SiNx-based resistive random-access memory with MIS structure

In this work, the effects of conducting defects on resistive switching characteristics of SiNx-based resistive random-access memory (RRAM) have been investigated. Two types of RRAM devices having metal–insulator–silicon layer configuration were fabricated. One is the device with SiNx as the resistive switching layer deposited by plasma-enhanced chemical vapor deposition (PECVD), and the other has the SiNx layer prepared by low-pressure chemical vapor deposition (LPCVD). The device cell deposited by LPCVD (LP-SiNx cell afterward) demonstrated superior uniformity of switching parameters and better endurance cycles compared with the device cell deposited by PECVD (PE-SiNx cell afterward).
An Improved Algorithm on Point Cloud Optimization for Unmanned Aerial Vehicles

It is hard to keep vertical photography for Unmanned Aerial Vehicles (UAV) and there is large deflection and rotation in the UAV image, which lead to accuracy of point cloud data produced by UAV image is not high. In this paper an algorithm on UAV point cloud optimization based on Patch-based Least Squares Image Matching is proposed. By optimizing the point cloud data with Patch-based Least Squares Image Matching, and test data with images in campus of Northwestern University. The experimental results show that UAV point cloud optimization based on Patch-based Least Squares Image Matching can conspicuously improve the accuracy of the UAV image matching.
Emission frequency stability in single-mode-fibre optical feedback controlled semiconductor lasers

A newly designed semiconductor laser emitter with adjustable linewidth by controlling the coupling to a single-mode fibre is described with emphasis on thermal requirements to obtain a high-frequency stability. A stable operation has been achieved during more than 1 h using an AlGaAs laser diode with optical feedback from a 50 cm-long single-mode fibre resulting in a 50-fold reduction of the spectral linewidth.
Funcionalidades de la gamificación: Classcraft y Moodle en el marco de Octalysis

La gamificación es una técnica reciente que consiste en aplicar elementos del juego en contextos ajenos al juego. Existen marcos teóricos que sugieren un modelo para aplicar estos elementos en la implementación de soluciones concretas. En este artículo se analiza dos sistemas de gestión de aprendizaje, Classcraft y Moodle, bajo la lente del marco de Octalysis. A pesar de que las dos plataformas proporcionan varios elementos del juego, que combinados entre sí buscan aumentar la motivación de los estudiantes.
Anomaly Detection in SCADA Systems - A Network Based Approach

Supervisory Control and Data Acquisition (SCADA) networks are commonly deployed to aid the operation of large industrial facilities, such as water treatment facilities. Historically, these networks were composed by special-purpose embedded devices communicating through proprietary protocols. However, modern deployments commonly make use of commercial off-the-shelf devices and standard communication protocols, such as TCP/IP. Furthermore, these networks are becoming increasingly interconnected, allowing communication with corporate networks and even the Internet. As a result, SCADA networks become vulnerable to cyber attacks, being exposed to the same threats that plague traditional IT systems. In our view, measurements play an essential role in validating results in network research; therefore, our first objective is to understand how SCADA networks are utilized in practice. To this end, we provide the first comprehensive analysis of real-world SCADA traffic. We analyze five network packet traces collected at four different critical infrastructures: two water treatment facilities, one gas utility, and one electricity and gas utility. We show, for instance, that exiting network traffic models developed for traditional IT networks cannot be directly applied to SCADA network traffic. We also confirm two SCADA traffic characteristics: the stable connection matrix and the traffic periodicity, and propose two intrusion detection approaches that exploit them. In order to exploit the stable connection matrix, we investigate the use of whitelists at the flow level. We show that flow whitelists have a manageable size, considering the number of hosts in the network, and that it is possible to overcome the main sources of instability in the whitelists. In order to exploit the traffic periodicity, we focus our attention to connections used to retrieve data from devices in the field network. We propose PeriodAnalyzer, an approach that uses deep packet inspection to automatically identify the different messages and the frequency at which they are issued. Once such normal behavior is learned, PeriodAnalyzer can be used to detect data injection and Denial of Service attacks.
Dual reflector antenna with narrow broadside beam for omnidirectional coverage

A new type of high gain omnidirectional antenna is presented, particularly suited for higher frequencies (e.g. milllimetre waves): it is obtained with an axially symmetric dual reflector system, fed with an unconventional feed with conical pattern. The feed radiated field, after reflection on the parabolic subreflector and on the conical main reflector, is uniformly scattered in the plane perpendicular to the axis of the system, with vertical polarisation and narrow vertical beamwidth.
A Grid Based Approach for Fire and Explosion Consequence Analysis

The process area of an offshore oil and gas platform is very compact with a high degree of congestion and confinement due to space limitations and environmental conditions. Although there are safety systems installed on the platforms, the process area is never completely safe. Among the loss producing events, fires and explosions are the most frequently reported process related accidents. They have potential to cause serious injury to personnel, major damage to equipment and structure, and disruption of operations. It is therefore necessary to perform a fire and explosion hazard analysis as a basis for the implementation of appropriate mitigation measures and emergency response plans to protect personnel. In this paper, we reviewed the existing consequence models, such as source models, dispersion models, ignition models, fire and explosion models, and selected the ones most suitable for offshore conditions. These models were then used to perform a consequence assessment for an offshore platform by simulating four different scenarios. Two main revisions were incorporated: (1) a grid-based approach was adopted to enable better consequence/impact modelling and analysis of radiation and blast overpressures, and (2) an enhanced onsite ignition model was integrated in the consequence assessment process to obtain better results.
The Limits of Knowledge Management

This paper traces the impact of three knowledge management (KM) projects inside a global pharmaceuticals firm. The first was a conventional debriefing exercise; the second a major investment in an electronic repository, "Warehouse"; and the third, "Cafe", an attempt to use web technology to construct new "communities of practice". Discussions of KM have been dominated by prescriptive and managerialist approaches that ignore organisational politics and the impact of KM on the labour process. We place these issues at the centre of our account of KM. The critical weaknesses of the KM projects were: First, their reliance on the active involvement of labour. Passive resistance was sufficient to limit the impact of KM in practice. Second, the technical development of KM systems was not matched by the formation of consistent, centralised measures of social processes. Both factors severely limited the development of KM as a durable power/knowledge regime.
Effects of detuned loading on the modulation performance of widely tunable MG-Y lasers

The Detuning Loading Effect, i.e., the effects of the modulation performance on the position of the lasing mode relative to the Bragg reflection peak, is investigated in a Modulated Grating Y-branch laser. By proper adjustment of the lasing mode position, simultaneous chirp reduction and modulation bandwidth enhancement can be obtained. The lasing mode position is also crucial for side mode suppression ratio and output power.
Are suicidal behaviors more prevalent among rural-to-urban migrants than non-migrant rural and urban residents in Wuhan, China? –Evidence from a GIS/GPS-assisted probability sample

Background There is a lack of solid data on suicide among rural-to-urban migrants in China, a large and rapid growing population currently totaling 280 million. The study aims to investigate whether suicidal behaviors are more prevalent among the rural migrants than the non-migrant rural and urban residents. Methods Data from a probability sample (N=3951, 32.65% rural-to-urban migrants) were analyzed. The sample was selected in Wuhan, China using the GIS/GPS-assisted multistage probability sampling method. Suicidal ideation and attempt in the past year were measured. Prevalence rate [95% CI] was calculated using survey estimation method, considering the sampling design with sample clusters, disproportionate probabilities, and weights. Adjusted odds ratio (AOR) [95% CI] was used to compare the difference of rural migrants with rural and urban residents in suicidal behaviors controlling for covariates. Results Among rural migrants, 5.74% [4.81, 6.68] reported having suicidal ideation, compared to 4.74% [3.07, 6.42] and 3.65% [2.64, 4.65] for rural and urban residents, respectively. The migrant-urban resident difference was significant with AOR =1.93 [1.26, 2.94] while the migrant-rural resident difference was not with AOR= 0.87 [0.46, 1.67]. The prevalence rate of suicidal attempt was 5.47% [4.57, 6.36] for rural migrants, significantly higher than 1.14% [0.43, 1.85] for rural residents with AOR=2.89 [1.12, 7.43]; and 2.01% [1.21, 2.82] for urban residents with AOR =3.97 [2.15, 7.34]. Conclusions Rural migrants are at higher risks for suicide comparing to rural and urban residents. Additional research is needed to examine factors related to the increased risk of suicidal behaviors among rural migrants in China.
Organização do trabalho, subjetividade e confiabilidade na atividade de mergulho profundo

In this paper, we focus on the collective dimension of the deep-sea diving work and, specially, the subjective compounds implicated in such activity, because we consider such aspects so fundamental to think the security and the reliability of the complex social-technical systems. We took as empirical field the investigation conducted by Figueiredo (2001) concerning the conditions in which this activity is developed in the Campos Oil Fields (Northern region of the state of Rio de Janeiro), that is permanently outsourced and inserted in the offshore oil industry. Our analysis showed that when some of the so-called fundamental rules of work are not considered, such as the decisive role that these rules perform in the execution of the tasks, the way of labor organization is presented, creates serious obstacles to cohesion and to consolidation of the work collectives, mining the inner cooperation potential, with serious risks to the reliability of the analyzed system and to the mental health and security of the divers.
Development of an Adaptive Workload Management System using the Queueing Network-Model Human Processor

Drivers overloaded with information from in-vehicle systems significantly increase the chance of vehicle collisions. Developing adaptive workload management systems (AWMS) to dynamically control the rate of messages from these in-vehicle systems is one of the solutions to this problem. However, existing AWMS do not use driver models to estimate workload, and only suppress or redirect messages without changing the rate of messages from the in-vehicle systems. In this work, we propose a prototype of a new adaptive workload management system, the Queuing Network-Model Human Processor (QN-MHP) AWMS, which includes a model of driver workload based on the queueing network theory of human performance that estimates driver workload in different driving situations and a message controller that dynamically controls the rate of messages presented to drivers. Corresponding experimental studies were conducted to validate the potential effectiveness of this system in reducing driver workload and improving driver performance.