Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on Reliability of YCW Series Light Jack

By means of virtual prototyping technology and its support for the UG and the ADMAS software,has established the YCW250B hydraulic jack model.Study on dynamic simulation under rated load of the model,have obtained YCW250B hydraulic jack characteristic data of working state,and provided a valuable basis for commissioning of this hydraulic jack.
CONCEPTUAL AND MECHANICAL DESIGN OF AN ANTHROPOMETRIC-SCALED BIPED ROBOT FOR REPRODUCING NORMAL AND PATHOLOGICAL HUMAN GAIT

This paper presents some preliminary results concerning the conceptual and mechanical design, as well as the primary hardware and software development, of a biped robot able to reproduce human gait patterns as recorded from a gait analysis laboratory. Robot dimensions followed the same mean proportions between the segments observed in human subjects. In this way, geometrical and kinematical similarity between the robot and humans were sought, although the kinetical parameters of the robot (weight and moment of inertia) were kept as light as possible, minimizing the nominal torque requirements of the servo-actuators. The robot was designed and built using 10 PWM-controlled servo-actuators. For the ankle and hip joints, parallel three-dimensional mechanical linkages were used, with the advantage of almost doubling the nominal torque-generation capacity of the servoacutators, as the two servos are employed in the generation of the movements. However, this linkage has a complex kinematics, and it was necessary to derive a mathematical model to find the servo input angles that generates the desired joint angles for the gait cycle. The control of the robot is performed by MS-Windows dedicated software, that controls the PWM (Pulse Width Modulation) signals to the servo actuators. Keyworks. biped robot, biomechanics, control, human gait
Application of the Regression Algorithm Based on Sample-Self-Selection in BOF Steelmaking

As a static control algorithm of BOF steelmaking,general regression algorithm chooses a few last smelting data as the sample without appropriate screening,and the accuracy of prediction was not high.To solve this problem,the regression algorithm based on sample-self-selection was proposed.The algorithm selected a certain number of appropriate samples from the actual production data automatically to build a regression model,implementing the predictions of oxygen consumption,coolant consumption,end-point temperature and end-point carbon content.Through comparing operational data and the prediction effects among general regression algorithm,BP neural network algorithm and the regression algorithm based on sample-self-selection for 120t converter,the results show that this algorithm has the advantage of high accuracy and effective comprehensive prediction.
Electronically Scanned Coherent CO2 Laser Radar Techniques

An electronically, scanned laser radar has been designed and is currently being developed which has unprecedented agility and speed. The agile scanning of both the transmitter and receiver is controlled by the variable reflectance of a V02 film on a cathode ray tube (CRT) faceplate. Electron beam heating is used to create reflecting spots on the VO2 film which, in turn, control the transmitter laser beam direction. Components for the laser radar are currently being developed and tested. Experimental results are in complete agreement with predicted analytical results.
Interpreting Leamer

It is easy for a professional philosopher who reads Learner's essay “Let's Take the Con Out of Econometrics” to find a great deal in it that seems contentious, cavalier, or objectionable. Philosophers may even be puzzled as to what the fuss is all about. My guess is that the sorts of complaints philosophical readers are likely to make about Learner's paper are more the result of style than substance. The substance is very important.
Fabric Quality Issues Related to Apparel Merchandising

The objectives of this study are to develop an understanding of fabric quality related issues and research gaps relevant to apparel manufacturing and merchandising within the South African context. The specific focus is on fabric objective measurement (FOM), a relatively new and highly advanced technology which involves a new generation of instrumentally measured parameters that provide a more complete picture of fabric quality, tailorability and clothing performance, and which has found wide application internationally. The research involves a questionnaire survey of major clothing and retail companies in South Africa and interviews with them, with a specific focus on apparel and garment manufacturing and retailing in South Africa. The data and information so captured are graphically presented, statistically analyzed and interpreted. The main finding is that although manufacturers and retailers carry out most of the important fabric and garment testing, they lag behind the world in adopting highly advanced and integrated FOM systems, such as FAST and Kawabata, which are widely used to improve and ensure the quality of apparel fabric and garments.
Optimization of electric field intensity on 550 kV insulator surface

This paper applied the two-dimension electric field theory and finite element method to optimize the electric field along 550 kV insulator surface. Through the optimization, the even degree of the electric field along the insulator surface and the electric field near the tube was improved a lot. The partial charge of the busbar was decreased as well.
Movie Recommendation System using Naive Bayes Algorithm with Collaborative Filtering

: In recent years, the movie industry is getting more and more prosperous. There are hundreds of movies released every year. However, it is difficult to notice the releasing of every movie, not to mention actually seeing it. Therefore, movie recommendation system has become more and more popular as a research topic. Until today so many numbers of recommendation algorithms have been proposed, where collaborative filtering and content-based filtering are the two most famous and adopted recommendation techniques. Collaborative filtering recommendation systems recommend items by identifying other users with similar taste and use their opinions for recommendation whereas content-based recommendation systems recommend items based on the content information of the items. However, these systems suffer from scalability, data sparsity, overspecialization and cold-start problems resulting in poor quality recommendations and reduced coverage. Hybrid recommendation system combines the individual system to avoid certain mentioned limitations of these systems. In this project, we propose a Movie Recommendation System by combining the Naive Bayes Algorithm with Collaborative filtering.
Classification of Aircraft in Remote Sensing Images Based on Deep Convolutional Neural Networks

Convolutional Neural Network (CNN) is a component of Deep Learning(DL) recently exploited in different fifields. In this work, we improve the performance of multi-label classifification based on CNN for remote sensing images of aircraft types. Intensive preprocessing limits the classifification rate in previous studies. In order to avoid under-fifitting and over-fifitting problems, we optimized the architecture and Network parameters. To validate our method the recent public image dataset called Multi-Type Aircraft Remote Sensing Images (MTARSI) is used. Extensive experiments prove the effectiveness of the proposed method in terms of classifification rate.
Key technologies for the construction of manufacturing cloud

The construction process of"manufacturing cloud"in a Cloud Manufacturing(CMfg)system was investigated,as well as several key technologies involved in the construction process.Related illustration about manufacturing cloud and cloud service were described,and CMfg resources were classified in detail.Several key issues such as resources aware,virtual accessing,and deployment of cloud services were studied.A meta-model for describing manufacturing capability was put forward,which can support efficient and intelligent running of CMfg systems.A prototype of cloud service platform for complex product design and simulation was developed according to the proposed method.
Making shipping greener: comparative study between organic fluids and water for Rankine cycle waste heat recovery

The largest source of energy loss in ships is found in the propulsion system. This study focuses on the concept of managing waste heat energy from the exhaust gases of the main engine. Using waste heat recovery systems (WHRSs) to make shipping more efficient represents a good area of opportunity for achieving the shipping industry's green objectives. Organic Rankine cycles have been applied in land-based systems before, showing improvements in performance when compared with the traditional Rankine cycle. As marine environmental rules requiring greener vessels and engine thermal efficiency continue to increase, thus reducing the available energy in the exhaust, organic Rankine cycle WHRSs become a more attractive option.The proposed WHRS was modelled using MATLAB for a typical ship installation with a slow speed diesel engine and a WHRS installed after the steam boiler in the exhaust gas system. The energy recovered from the exhaust gas flow is transformed via the thermodynamic cycle – coupled with a generator – into electricity, which helps to cover the ship's demand. The MATLAB code found the highest electric power output, hence the maximum fuel and CO2 emission savings possible, by v varying the WHRS HP. Water and four organic fluids were considered and their performance was compared over a range of different engine operating conditions. A representative ship operating profile and a typical marine generator were used to measure CO2 emission reductions. The implications of having flammable organic fluids on board are also briefly discussed. This work demonstrates that a simple organic Rankine cycle can be more effective than a steam cycle for the same engine operating conditions.
An Adaptive Rear-End Collision Warning System for Drivers That Estimates Driving Phase and Selects Training Data

The paper proposes a rear-end collision warning system for drivers, where the collision risk is adaptively set from driving signals. The system employs the inverse of the time-to-collision with a constant relative acceleration as the risk and the one-class support vector machine as the anomaly detector. The system also utilizes brake sequences for outliers detection. When a brake sequence has a low likelihood with respect to trained hidden Markov models, the driving data during the sequence are removed from the training dataset. This data selection is confirmed to increase the robustness of the system by computer simulations.
Digital displacement hydraulic piston pump

The digital displacment hydraulic piston pump is a hybrid device which combines a microprocessor with an established form of high-pressure pump to create a highly integrated machine which can produce a variable highpower output directly from an electronic command. The actively controlled inlet poppet-valve in each cylinder can be held open against the discharging flow in order to disable it during a single cycle. Cylinders can be disabled in this manner, following a maximally smooth sequence, allowing a controlled output flow to be achieved. A compliant device located near the pump, such as an accumulator, provides time-averaging of the flow pulsations in order to minimise the effects of the quantisation error caused by cylinder disabling. The advantages of this approach over the conventional variable-swash axial piston pump lie with both the response speed. and the inherent energy efficiency of real-time cylinder selection. Disabling cylinders in this way restricts parasitic losses to very low levels since unused cylinders are not pressurised nor do they incur loads on their associated bearings. The response time of the pump is related to shaft speed, with the pump able to attain either full or zero output from any starting condition, in less than a single shaft revolution. At induction motor speeds this allows largesignal response times of the same order as those achieved by commercial proportional valves. The thesis chronicles the development of the Digital Displacement pump. It begins with the formulation of a simulation model which is able to predict the behaviour of the machine in both flow and pressure control modes. The valve control possibilities are then explored and the design of active valve latches using finite-element analysis described. The flow forces on the disabled poppet are evaluated through a large range of experiments and the results condensed into parametric equations useful for predicting the valve latching requirements of most machines. The mechanical and electronic hardware design, leading to the construction of the prototype, is then discussed. The study concludes by comparing the performance of the actual pump against that of the predictive model developed at the beginning. The ability of the pump to recover following large disturbances in flow demand, both ramping and harmonic, is investigated.
TRAUMATIC STRESS IN THE SPANISH POPULATION IN THE LOCKDOWN AND PANDEMIC OF COVID-19 RESILIENCIA, BIENESTAR Y ESTRÉS POSTRAUMÁTICO EN POBLACIÓN ESPAÑOLA ANTE EL CONFINAMIENTO Y PANDEMIA DEL COVID-19

The COVID-19 pandemic and social distancing measures have had a negative impact on mental health. The main objective is to study the role of resilience as a protective factor, against the impact of the pandemic and the confinement of COVID-19. The sample consisted of 179 participants with a mean age of 40.85 years (SD = 13.7). The analyzes indicate that resilience is highly predictive of psychological well-being and mood and is a protective factor against post-traumatic stress. Also for the ease of carrying the pandemic, which may be mediated by other factors. The effects of the pandemic and confinement appear to have significantly increased post-traumatic stress symptoms. Women have more post-traumatic stress and less psychological well-being. The age group most affected is that of young people (18-25 years).
Exploring Mental Models of Construction Managers

Experience is a critical component of expertise for construction managers. Time allows them to inductively construct and organize knowledge about the construction management domain that often cannot be easily formalized. The goal of this study was to investigate the nature of expertise in construction managers. Both experts and novices represent and organize experientially gained knowledge as abstractions that we refer to as mental models. We investigated expertise by exploring mental models of construction managers. In this study we explored experimentally the existence of a difference in the mental models among construction managers. A group of construction managers with varying levels of experience were asked to respond to a construction management crisis scenario. Using the ConProFac software to calculate an index i indicative of the structuredness of the responses we found a significant correlation between i and the number of years of experience of the respondent. A better understanding of the mental models of experienced construction managers will help in developing a better theoretical understanding of the CM domain, while also enriching the construction management educational experience.
REFINED PLASTIC HINGE ANALYSIS OF SPATIAL STEEL FRAMES

Method for computing the element restoring force, rather than the stiffness matrix, is the most important factor that determines the accuracy of a geometric nonlinear finite element problem. The formulation of a spatial beam-column element with shear deformation for the purpose of refined plastic hinge analysis of 3-D steel frames is presented. Second-order effects are captured through stability functions. Material nonlinearity is modeled using refined plastic hinge method, which can account for the gradual yielding of the section and the reduction of the element stiffness due to distributed plasticity resulting from residual stresses. The coupling terms between the axial, lateral and torsional displacements are included in element stiffness matrix. Using the User Programmable Features (UPFs) of ANSYS program, the element routines have been developed and successfully incorporated into ANSYS program. The results of numerical examples show that only one proposed element, in contrast to three or four BEAM189 elements of ANSYS program, is necessary to model a column of spatial frames with excellent accuracy. The analysis results also indicate that shear deformation of members must be considered in the analysis of multi-storey frame structures.
713. The relation between the chemical composition of milk and the stability of the caseinate complex: II. Coagulation by ethanol

1. The variation in the stability of milk protein to ethanol and the relationship between milk composition and ethanol stability were examined. 2. Samples of herd bulk milk were very similar in stability to ethanol; the range of aqueous ethanol solutions required to coagulate the caseinate complex in an equal volume of milk was only 80–84% (v/v) ethanol. Samples from individual cows showed a wide variation in stability; coagulation was caused by ethanol solutions ranging in strength from 66 to 90% (v/v) ethanol. 3. Colostrum was very unstable to ethanol but stability rapidly increased during the post-colostrum period to higher levels in mid-lactation. Late lactation and subclinical mastitis milk showed no definite bias towards stability or instability. 4. The strength of ethanol required to coagulate the caseinate complex in an equal volume of milk was inversely related to the concentration of ionized calcium in the milk. The correlation coefficient was –0·76 (significant at 0·001 level) indicating that approximately 60% of the variation in stability was accounted for by the variation in the concentration of ionized calcium. 5. The relationships between the concentrations of other milk constituents and stability to ethanol could be attributed to the interrelations of the concentrations of these constituents and the concentration of ionized calcium.
An integrated usage of circuit simulation and spreadsheet for an enhancement of circuit design and semiconductor device instruction

The circuit simulation construct is a network of nodes interconnected by component devices that are responsive to the voltage and current stimuli applied as sources and signals. The component devices may be simple linear form or they may be non-linear devices, in which case they are usually of semiconductor origin. Each different type device owns a set of specific parameters that define its operation. The circuit simulator decomposes the circuit and ascertains the electrical facts of the circuit in the form of node voltages and branch currents, outcomes which are peculiar to the physical effects represented by the strengths of these device parameters and therefore of critical concern to a circuit designer. Semiconductor devices are generally devolved in the classroom by their device physics and the principles of operation that control the flow of electrons and holes. Basic first-order concepts lend themselves to mathematics that is reasonably tractable and can be readily developed by the versatility of the spreadsheet environment. However, for sub-micron devices, where the field effects are very intense, much of the first-order physics loses ground to second-order effects, most of which are abstract and often impenetrable to the circuit designer. And often any exposition of these second-order effects is a time-consuming burden to the instructor, whether for circuit design or for device physics. This paper identifies a technique that is invaluable to the circuit designer and/or semiconductor devices instructor by which the circuit simulations and the spreadsheet environments are integrated to resolve devices and/or circuit design questions. The environment can also be used for an empirical cross-coupling of device theory and circuit design. The student version of Cadence/ORCAD/pSPICE, which is the most common classroom circuit simulation platform, is the principal operational utility, with the Excel platform as the complementary spreadsheet utility.
Experimental Hose Pump and Its Experimental Design

The hose in the hose pump is easy worn, replacing the hose costs inflation and affects the working efficiency. According to the academic research, designing experimental hose pump and experimental project, we can reach the primary factor which causes the hose invalid in this experiment. Then optimizes the structure of the hose pump, increases the using time, enhances the working efficiency, reduces the running cost.
Finite Element Analysis on Temperature Field of CFST Members under Solar Radiation

A finite element method to calculate the temperature field of Concrete Filled Steel Tubular(CFST) members under solar radiation was presented.The convection heat flux between the surface and the air,the heat flux caused by solar radiation and the heat flux absorbed from the sun were taken as the heat flux of CFST members under solar radiation.The solar radiation was simulated by the third boundary condition which was expressed by Newton's convection law when considering the solar radiation.The CFST member surface was divided into four areas to realize the calculation of solar radiation,for the vertically placed member,the surface of member can be divided into face of east,west,south and north;and for the horizontally placed member,the surface of member can be divided into the face of east,west,horizontal surface,and the face where only heat convention happens.Case study shows that the calculating results agree well with the test results and can be a reference for further research and application for engineering.It is necessary to carry out secondary development of general program in the future to simplify the complicated solar radiation calculation.
Breathing Carbon Dioxide (4% for 1-Hour) Slows Response Selection, Not Stimulus Encoding

This experiment sought to determine whether breathing carbon dioxide (CO2), a toxic environmental stressor known to impair reaction time, slows human information processing in the stimulus encoding or response selection stage, or both, and whether this effect is influenced by time-on-task and exposure duration. In a 2 X 2 X 2 X 4 (Gas X Degradation X Compatibility X Time-on-Task) within-participants design, six highly practiced (more than 10,000 trials) healthy young male participants performed a serial choice reaction time (SCRT) task while breathing either 4% CO2 (with 50% O2) or room air (0.03% CO2 and 21% O2) for 60 minutes. Task variables manipulated were stimulus degradation (intact vs. degraded) and stimulus-response compatibility (high vs. low). Data from each 20-min SCRT test were subdivided into 5-min and 2-min intervals to determine the effects of time-on-task (and exposure duration). There were significant increases in SCRT from breathing carbon dioxide (p =.004), degrading the stimulus (p <.001), lowering compatibility (p =.004), and increasing time-on-task (p =.020). Lowering compatibility served to exaggerate the impairment produced by carbon dioxide inhalation (p =.038). Time-on-task (and exposure duration), however, did not interact with gas, degradation, or compatibility. Thus, SCRT, analyzed according to the Additive Factors Method (Sternberg, 1969, 1998), (1) was sensitive to the degrading effects of breathing CO2 at an undetectable concentration that did not produce clinical symptoms, (2) determined the locus of this effect was associated with the response selection stage of processing, (3) demonstrated that the progressive deterioration in performance due to increases in time-on-task (and exposure duration) affects both the stimulus encoding and response selection stages in a similar manner, and (4) ruled out alternative explanations by showing the results did not vary with distribution analyses, data trimming, error analyses, and analyses for tradeoffs of speed-accuracy, SCRT-DT, and other performance operating characteristics.