Miracle-dz/UniFAR-FTUs huggingface dataset:
In-profile monitoring for cluster-correlated data in advanced manufacturing system

Abstract Nowadays advanced sensing technology enables real-time data collection of key variables during manufacturing, known as multi-channel profiles. These data facilitate in-process monitoring and anomaly detection, which have been extensively studied in recent years. However, most studies treat each profile as a whole, e.g., a high-dimensional vector or function, and construct monitoring schemes accordingly. As a result, these methods cannot be implemented until the entire profile has been obtained, leading to long detection delay especially if anomalies occur in early sensing points of the profile. In addition, they require that profiles of different samples have the same time length and feature location, yet additional time-warping operation for real misaligned samples may weaken the anomaly patterns. To address these problems, this article proposes an in-profile monitoring (INPOM) control chart, which not only gives the feasibility of detecting anomalies inside the profile, but also can handle the misalignment problem of different samples. In particular, our INPOM scheme is built upon state space model (SSM). To better describe the clustered between-profile correlation and avoid overfitting, SSM is extended to a regularized SSM (RSSM), where regularizations are imposed as prior information and expectation maximization algorithm is integrated for posterior maximization to efficiently learn the model parameters. Furthermore, a monitoring statistic based on one-step-ahead prediction error of RSSM is constructed for INPOM control chart. Thorough numerical studies and real case studies demonstrate the effectiveness and applicability of our proposed RSSM-INPOM framework.
Analysis of gravity-induced particle motion and fluid perfusion flow in the NASA-designed rotating zero-head-space tissue culture vessel

The gravity induced motions, through the culture media, is calculated of living tissue segments cultured in the NASA rotating zero head space culture vessels. This is then compared with the media perfusion speed which is independent of gravity. The results may be interpreted as a change in the physical environment which will occur by operating the NASA tissue culture systems in actual microgravity (versus unit gravity). The equations governing particle motions which induce flows at the surface of tissues contain g terms. This allows calculation of the fluid flow speed, with respect to a cultured particle, as a function of the external gravitational field strength. The analysis is approached from a flow field perspective. Flow is proportional to the shear exerted on a structure which maintains position within the field. The equations are solved for the deviation of a particle from its original position in a circular streamline as a function of time. The radial deviation is important for defining the operating limits and dimensions of the vessel because of the finite radius at which particles necessarily intercept the wall. This analysis uses a rotating reference frame concept.
Utilizing Wearable Devices To Design PersonalThermal Comfort Model

Apart from the common environmental factors such as relative humidity, radiant, and ambient temperatures, studies have confirmed that thermal comfort significantly depends on internal personal parameters such as metabolic rate, age, and health status. This is manifested as a difference in comfort levels between people residing under the same roof, and hence no general comprehensive comfort model satisfying everyone. Current and newly emerging advancements in state of the art wearable technology have made it possible to continuously acquired biometric information. This work proposes to access and exploit this data to build personal thermal comfort model. Relying on various supervised machine-learning methods, a personal thermal comfort model will be produced and compared to a general model to show its superior performance. In this work, it has been shown that the introduction of galvanic skin response (GSR) data in training the models results in more reliable and accurate private models.
Femoral Valgus Correction Angle for the Intramedullary Alignment Rod Is Strongly Associated with Femoral Lateral Bowing in Japanese Patients with Varus Knee Osteoarthritis Undergoing Total Knee Arthroplasty

Background This study aimed to investigate factors, such as differences in femoral shape, that could affect the femoral valgus correction angle (VCA) for the intramedullary alignment rod (IM rod) by using a three-dimensional (3D) measurement system in patients with varus knee osteoarthritis undergoing total knee arthroplasty (TKA). Methods A total of 305 knees in 233 Japanese patients with varus knee osteoarthritis who underwent primary TKA by using Jig Engaged 3D Pre-Operative Planning Software for the TKA operation support system was examined. We retrospectively analysed factors, such as the shape of the proximal, middle, and distal femur in the coronal plane, all of which could affect the VCA for the IM rod, by multiple linear regression analyses. Results The VCA for the IM rod was 5.9° ± 1.6° (range: 1.7° to 10.7°), and the femoral lateral bowing angle (FBA) was 3.5° ± 3.2°. Major factors independently associated with the VCA for the IM rod were the FBA (β: 0.75), femoral offset (β: 0.38), and the medial angle between the mechanical femoral axis and the line that connects the distal margins of the medial and lateral femoral condyles (β: −0.16). The model was created by stepwise multiple linear regression (F = 266.6, p < 0.001, and estimated effect size = 4.4) explained 85% of the variance in the VCA for the IM rod (R2 = 0.85). Conclusions The VCA for the IM rod was most strongly associated with femoral lateral bowing in patients with varus knee osteoarthritis undergoing TKA. Our findings suggest that preoperatively measuring the VCA for the IM rod in patients with femoral lateral bowing by using a 3D measurement system could be useful for accurate coronal alignment of the femoral component in TKA.
The value of intelligent services and intelligent destination: From the perspective of residents

Destinations are considered brands that must be properly managed to increase not only tourist arrivals but also the quality of life of residents. Brand equity plays an important role in achieving such objectives. Simultaneously, the integration of ICT in the territory has led to the concept of “smart destinations”. In this context, the aim of the paper is to develop a value model of smart destinations from the perspective of residents (key actor of destinations as they project their image and influence the tourist experience). Our model includes smart services related to safety, health, heritage, mobility and environment. Our results confirm that smart destination value is formed by recognition, image, perceived quality and loyalty. In addition, safety, environment and mobility services are the main antecedents of smart destination value.
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)

Abstract. A simple numerical solution procedure – namely the method of lines combined with an off-the-shelf ordinary differential equation (ODE) solver – was shown in previous work to provide efficient, mass-conservative solutions to the pressure-head form of Richards' equation. We implement such a solution in our model openRE. We developed a novel method to quantify the boundary fluxes that reduce water balance errors without negative impacts on model runtimes – the solver flux output method (SFOM). We compare this solution with alternatives, including the classic modified Picard iteration method and the Hydrus 1D model. We reproduce a set of benchmark solutions with all models. We find that Celia's solution has the best water balance, but it can incur significant truncation errors in the simulated boundary fluxes, depending on the time steps used. Our solution has comparable runtimes to Hydrus and better water balance performance (though both models have excellent water balance closure for all the problems we considered). Our solution can be implemented in an interpreted language, such as MATLAB or Python, making use of off-the-shelf ODE solvers. We evaluated alternative SciPy ODE solvers that are available in Python and make practical recommendations about the best way to implement them for Richards' equation. There are two advantages of our approach: (i) the code is concise, making it ideal for teaching purposes; and (ii) the method can be easily extended to represent alternative properties (e.g., novel ways to parameterize the K(ψ) relationship) and processes (e.g., it is straightforward to couple heat or solute transport), making it ideal for testing alternative hypotheses.
2D-QSAR and CoMFA Models for Antitubercular Activity of Scalarane-Type Sesterterpenes

A series of scalarane sesterterpenes were prepared using heteronemin (1) as a primary precursor. Combined with the scalarane derivatives obtained from natural sources, a total of 22 antitubercular scalaranes were used to build QSAR models based in the 2D-QSAR and CoMFA approaches. Both models indicated the influences of substitutions in the vicinity of C-12 and C-16 of the scalaranes. A 2D-QSAR model suggested the necessity of hydrophilic functionalities on the peripherals with hydrophobic cores, and the lowering steric repulsion to improve the potential energy. This was complemented by the pictorial CoMFA model, which indicated the importance of the positive electrostatic with shortened steric extension crowning over C-12 and the lengthy negative functionalities extended from C-16.
Controllability of Delayed Discret Fornasini-Marchesini Model via Quantization and Random Packet Dropouts

This research is devoted to Fornasnisi-Marchesini model (FM). More precisely, the investigation of the control problem for the second model discrete-time FM. Random packet dropouts, time delays and quantization are taken into consideration in the feedback control problem simultaneously. Measured signals are quantized before being communicated. A logarithmic quantizer is utilized and quantized signal measurements are handled by a sector bound method. The random packet dropouts are modeled as a Bernoulli process. A control law model which depends on packet dropouts and quantization is formulated. Notably, we lighten the assumptions by using the Schur complement. Besides, both a state feedback controller and an observer-based output feedback controller are designed to ensure corresponding closed-loop systems asymptotically stability. Sufficient conditions on mean square asymptotic stability in terms of LMIs have been obtained. Finally, two numerical example show the feasibility of our theoretical results.
Calibration and characterization of photomultiplier tubes of the IceCube neutrino detector

The IceCube neutrino observatory will consist of an array of 4800 Digital Optical Modules (DOMs) located in the deep ice at the South Pole, and also an IceTop air shower array of 320 DOMs in 160 ice tanks located on the surface. A 10 inch PMT is housed in each DOM for the detection of Cherenkov light. This poster describes the methods of calibration and characterization of the IceCube PMTs in the laboratory, which are germane to improving the detector resolution and reducing systematic uncertainties. Two dimensional scans on the entire photocathode to map out photon conversion efficiency have been carried out for 60 PMTs. The quantum/collection efficiency has been calibrated in an absolute manner using the Rayleigh scattered light from our newly built chamber filled with nitrogen gas. The charge response of the PMTs at temperatures below freezing has been extensibely studied and found to be well represented by the analytical model. All these results have been combined and implemented in the detector Monte Carlo simulation. Introduction
Fixed-Time Leader-Following Consensus Tracking Control for Nonliear Multi-Agent Systems under Jointly Connected Graph

This paper researches the fixed-time leader-following consensus problem for nonlinear multi-agent systems (MASs) affected by unknown disturbances under the jointly connected graph. In order to achieve control goal, this paper designs a fixed-time consensus protocol, which can offset the unknown disturbances and the nonlinear item under the jointly connected graph, simultaneously. In this paper, the states of multiple followers can converge to the state of the leader within a fixed time regardless of the initial conditions rather than just converging to a small neighborhood near the leader state. Finally, a simulation example is given to illustrate the theoretical result.
Biases and systematics in the observational derivation of galaxy properties: comparing different techniques on synthetic observations of simulated galaxies

We study the sources of biases and systematics in the derivation of galaxy properties of observational studies, focusing on stellar masses, star formation rates, gas/stellar metallicities, stellar ages and magnitudes/colors. We use hydrodynamical cosmological simulations of galaxy formation, for which the real quantities are known, and apply observational techniques to derive the observables. We also make an analysis of biases that are relevant for a proper comparison between simulations and observations. For our study, we post-process the simulation outputs to calculate the galaxies' spectral energy distributions (SEDs) using Stellar Population Synthesis models and also generating the fully-consistent far UV-submillimeter wavelength SEDs with the radiative transfer code SUNRISE. We compared the direct results of simulations with the observationally-derived quantities obtained in various ways, and found that systematic differences in all studied galaxy properties appear, which are caused by: (1) purely observational biases, (2) the use of mass-weighted/luminosity-weighted quantities, with preferential sampling of more massive/luminous regions, (3) the different ways to construct the template of models when a fit to the spectra is performed, and (4) variations due to the use of different calibrations, most notably in the cases of the gas metallicities and star formation rates. Our results show that large differences can appear depending on the technique used to derive galaxy properties. Understanding these differences is of primary importance both for simulators, to allow a better judgement on similarities/differences with observations, and for observers, to allow a proper interpretation of the data.
Prototipo de un sistema que determine el estado de madurez de un plátano utilizando Deep Learning y Visión Artificial

Las aplicaciones de Deep Learning (DL) y Visión Artificial han revolucionado la manera de como se ejecutan los procesos en las industrias de alimentos, para disminuir la pérdida de material por procesos ineficientes. Por lo tanto, este proyecto propone la creación de un modelo inteligente de clasificación industrial con asistencia robótica, enfocado inicialmente en la distinción del estado de maduración del plátano (Musa balbisiana). Se llevó a cabo con la ayuda de librerías como TensorFlow y OpenCV, las cuales permiten la utilización de redes neuronales convolucionales. Luego de probar varios modelos, se obtuvo que el que presentó mayor precisión y menor pérdida logró clasificar correctamente los tres estados de maduración del plátano, siempre y cuando las imágenes a predecir mantengan el formato establecido.
Bounded Connectivity‐Preserving Leader‐Follower Flocking Algorithms Without Acceleration Measurements

The problem of distributed connectivity‐preserving leader‐follower flocking of multiple autonomous agents with second‐order dynamics is investigated. First, a new class of bounded artificial potential fields is carefully designed which could guarantee connectivity preservation, distance stabilization and collision avoidance simultaneously as the system evolves. Furthermore, in the absence of acceleration measurements of the dynamic leader, a set of distributed and bounded leader‐follower flocking control protocols is derived for each follower with the aid of the combination of potential based gradient descent methods and the sliding mode control paradigms. It is shown that all followers achieve velocity consensus and collision avoidance with the dynamic leader, the underlying network remains connected for all time, and the desired stable flocking behavior is asymptotically achieved on the condition that the initial network is connected. Finally, nontrivial simulations and experiments are worked out to verify the effectiveness of the proposed control algorithms.
Evaluation of internal fit of press ceramic and porous structured cobalt–chromium crown fabricated by additive manufacturing

Background: The purpose of this in vitro study is to fabricate a novel metal–ceramic prosthesis with a porous structure, to compensate for the disadvantages associated with the design of existing prostheses, and to measure the internal fit of this prosthesis. Materials and Methods: In this in vitro study, the mandibular first molar was scanned from the dental computer-aided-design to design a 3 mm porous structure frame. The frame was produced using the lamination method and fired in a pressed ceramic. For comparison, pore-free specimens were fabricated by selective laser sintering (SLS) as described above, and porous specimens were fabricated by casting (total n = 30). The internal fit was then measured using a digital microscope (at 100× magnification), and the data were analyzed using one-way ANOVA (α = 0.05). Results: The total mean internal discrepancies for each group were 42.32 ± 22.50 μm for the porous structure SLS group (PS-group), 107.54 ± 38.75 μm for no-porous casting group (group), and 121.36 ± 50.19 μm for the no-porous SLS group (group), with significant differences (P < 0.05) among all groups. Conclusion: The internal discrepancies of porous structure crown fabricated by SLS were smaller than that of no-porous crown fabricated by casting and SLS. Based on these laboratory findings, further studies should be conducted to evaluate the feasibility of the newly designed porous structure and press ceramic prosthesis to determine whether they can be applied in clinical practice.
Genetic Diversity among Single, Double, And Triple Cross Hybrids in Beit Alpha Cucumber (Cucumis sativus)

Genetic variation was investigated in fifteen single, eighteen three-way, and nine double hybrid crosses and their parents along with nine elite commercial cucumber hybrids. Six lines (NS5, NS9, NS17, NS29, NS31, and NS33) were used to develop these cross hybrids. Based on AFLP and SSR analysis, the studied cucumber genotypes have a narrow genetic base. The results also showed genetic differentiation compared to commercial varieties. Out of 1352 bands produced from 12 AFLP primer pairs, only 47 were polymorphic. Similarly, out of 26 SSR primers, only one primer was polymorphic. The highest heterozygosity index (0.6044), polymorphic information content value (0.5392), and marker Index (0.6044) were observed with M-CTT_E-AAG AFLP primer combination, while the highest effective multiplex ratio (2.8246) and resolving power (4.8421) were observed with M-CTC_E-AGC AFLP primer combination. Genetic distance estimation revealed clear distinctiveness of the studied genotypes with the control varieties. The cluster analysis by UPGMA showed two main clusters covering 84% of the studied genotypes grouped. This research shows that double and three-way hybrid crosses can be used in cucumber hybrid breeding.
A New Deep Learning Restricted Boltzmann Machine for Energy Consumption Forecasting

A key issue in the desired operation and development of power networks is the knowledge of load growth and electricity demand in the coming years. Mid-term load forecasting (MTLF) has an important rule in planning and optimal use of power systems. However, MTLF is a complicated problem, and a lot of uncertain factors and variables disturb the load consumption pattern. This paper presents a practical approach for MTLF. A new deep learning restricted Boltzmann machine (RBM) is proposed for modelling and forecasting energy consumption. The contrastive divergence algorithm is presented for tuning the parameters. All parameters of RBMs, the number of input variables, the type of inputs, and also the layer and neuron numbers are optimized. A statistical approach is suggested to determine the effective input variables. In addition to the climate variables, such as temperature and humidity, the effects of other variables such as economic factors are also investigated. Finally, using simulated and real-world data examples, it is shown that for one year ahead, the mean absolute percentage error (MAPE) for the load peak is less than 5%. Moreover, for the 24-h pattern forecasting, the mean of MAPE for all days is less than 5%.
Galactic halos of self-interacting dark matter

Recent, very accurate simulations of galaxy formation have revealed that the standard cold dark matter model has great difficulty in explaining the detailed structure of galaxies. One of the major problems is that galactic halos are too centrally concentrated. Dark matter self-interactions have been proposed as a possible means of resolving this inconsistency. Here, we investigate quantitatively the effect of dark matter self interactions on formation of galactic halos. Our numerical framework is extremely simple, while still keeping the essential physics. We confirm that strongly self-interacting dark matter leads to less centrally concentrated structures. Interestingly, we find that for a range of different interaction strengths, the dark matter halos are unstable to particle ejection on a timescale comparable to the Hubble time.
MANAJEMEN BANDWIDTH MENGGUNAKAN METODE HIERARCHICAL TOKEN BUCKET (HTB) DENGAN PENAMBAHAN BUCKET SIZE USAHA AJ COMP

The internet is currently very much needed because of the increasing use of many people depending on the internet because this information technology is very fast.In this case, it has a very big impact, the need for a very efficient internet service provider is needed. One of the technologies that is becoming a trend in computer networks is wireless computer networks (wireless local area network/WLAN) This technology is the development of local computer network technology (local area network) which allows efficiency in the implementation and development of computer networks that can increase user mobility with computer network technology using cable media. Bandwidth management is a way to manage the internet network for even distribution of bandwidth usage even though many network users use it. Hierarchical token bucket (HTB) one method to do a bandwidth management in this HTB