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1.
Food Chem ; 368: 130842, 2022 Jan 30.
Artigo em Inglês | MEDLINE | ID: mdl-34419794

RESUMO

This study proposes a preliminary assessment of the homogeneity and stability through digital image acquisition of a candidate for mechanically processed pumpkin seed meal reference material, exploring the concepts of homogeneity curve and the analysis of texture characteristics by Continuous-Level Moving Block through Robust Principal Component Analysis. This innovative methodology allowed us to examine the percentage of homogeneity in a set of samples, revealing an average of 41% with only one outlier in relation to the entire sample, indicating low homogeneity. In the stability study carried out after storing samples for 12 months at different temperatures, 83% of the samples were considered regular and 17% were outlier, which means that most of them were considered stable. Therefore, this methodology is useful for screening samples for homogeneity, by textural analysis, and detected non-homogeneity can be corrected in advance for quantification by standard protocols.


Assuntos
Cucurbita , Farinha , Computadores , Farinha/análise , Análise de Componente Principal , Padrões de Referência , Sementes
2.
Appl Ergon ; 98: 103550, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34450458

RESUMO

Prior research has found that office workers may not be fully utilizing their chair's back support. This may be due in part to cognitive demands or other psychological stressors. Not using the back support may increase the muscle tension and contribute to muscle fatigue and discomfort. Historically, footrests have been advocated to address anthropometric disparities in office settings. In this laboratory study, it was hypothesized that a footrest may facilitate the use of the backrest and mediate the biomechanical demands on the back and neck muscles, especially when cognitive workload is elevated. Twenty participants performed computer tasks, which varied in their complexity levels, both with and without an angled footrest. Using a footrest increased workers' use of a chair's backrest, increased pelvic rotation towards the backrest, and had a corresponding change in spine flexion. However, no changes were found in the sampled electromyographic activities due to the footrest.


Assuntos
Fadiga Muscular , Coluna Vertebral , Computadores , Eletromiografia , Humanos , Amplitude de Movimento Articular
3.
Chemosphere ; 286(Pt 2): 131739, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34371353

RESUMO

Waste electrical and electronic equipment (WEEE) is one of the world's fastest-growing class of waste. WEEE contain a large amount of precious materials that have aroused the interest to develop new recycling technologies. Hence, effective recycling strategies are extremely necessary to promote the proper handling of these materials as well as for environmentally sound recovery of secondary raw resource. This paper reviews important existing methods and emerging technologies in WEEE management, with special emphasis in characterization, extraction and reclamation of precious materials from waste computer and mobile phones. Traditional pyrometallurgical and hydrometallurgical technologies still play a central role in the recovery of metals. More recently, emerging greener recycling technologies using microorganisms (i.e. biometallurgical), plasma arc fusion method and pretreatments (i.e. ultrasound and mechanochemical technologies) combined with other recycling methods (e.g. hydrometallurgical), and using less toxic solvents such as ionic liquids (ILs) and deep eutectic solvents (DESs) have also been attempted to recycle metals from computer and mobile phone scrap. The role of analytical method development, especially using spectroanalytical methods for chemical inspection and e-waste sorting process at industrial applications is also discussed. This confirmed that most direct sampling techniques such as laser-induced breakdown spectroscopy (LIBS) and X-ray fluorescence (XFR) have several advantages over traditional sorting methods including rapid analytical response, without use of chemical reagents or waste generation, and greater reclamation of precious and critical materials in the WEEE stream.


Assuntos
Telefone Celular , Resíduo Eletrônico , Gerenciamento de Resíduos , Computadores , Reciclagem
4.
J Contemp Dent Pract ; 22(8): 943-946, 2021 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-34753849

RESUMO

AIM: The clinical report describes how chairside intraoral scanning can be performed while a rubber dam is in place prior to fabrication of a computer-assisted design and computer-assisted manufacture (CAD/CAM) ceramic restoration. BACKGROUND: Recently, combining a chairside CAD/CAM system with rubber dam isolation in place could be used in order to both speed up the restorative process and avoid any contamination to abutment surface, which are the positive effects to patients and clinicians. Unfortunately, manufacturers do not provide guidance on how to make use of chairside CAD/CAM restorations while rubber dam isolation is in place. CASE DESCRIPTION: The chief complaint of necessitating a crown after endodontic therapy and the patient was digital restorative procedure in single visit. Intraoral scanning with rubber dam isolation in place was planned and successfully completed in order to fabricate a chairside CAD/CAM ceramic crown. The software was able to interpose the scan of the prepped tooth with rubber dam isolation into a scan made without the rubber dam from which the tooth had been erased. CONCLUSION: Chairside CAD/CAM system can be used to scan, design, and fabricate crowns while rubber dam is kept intraorally. Initial scan without rubber dam is needed in order to interpose the second scan with rubber dam in place. CLINICAL SIGNIFICANCE: Combining the advantages of intraoral scanning and rubber dam isolation in place for the fabrication of a chairside CAD/CAM ceramic crown in a single visit is feasible.


Assuntos
Planejamento de Prótese Dentária , Diques de Borracha , Cerâmica , Desenho Assistido por Computador , Computadores , Coroas , Porcelana Dentária , Humanos
5.
J Prof Nurs ; 37(5): 928-934, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34742524

RESUMO

The COVID-19 pandemic created an upheaval for nursing faculty teaching students in both didactic and clinical settings. From the intense disruption, opportunities for creative endeavors emerged. Program directors from a consortium of 12 nursing schools met remotely for problem-solving and support. Rich text from minutes of nine program director meetings were analyzed. Aims of our project included identifying challenges that nurse educators encountered during the pandemic, demonstrating benefits of a university and community college partnership model, and informing nurse educators of innovative outcomes that originated from our project. Thematic analysis of meeting minutes revealed four categories: timing and urgency; collaboration, preparation, and teaching; altruism; and what we learned. Further themes were identified from each of the categories. Innovative outcomes were identified from the text including creation of website teaching resources and development of a computer based clinical checklist. Implications for future nursing education included that computer- based simulation will continue to be embedded in nursing curricula. Also, the need for nursing faculty to remain technologically savvy to deliver trailblazing online pedagogies will prominently continue. We conclude that the synergistic collaboration of nursing program directors can have momentous outcomes for support and success of nursing programs.


Assuntos
COVID-19 , Bacharelado em Enfermagem , Educação em Enfermagem , Estudantes de Enfermagem , Computadores , Docentes de Enfermagem , Humanos , New Mexico , Pandemias , SARS-CoV-2
6.
BMC Med ; 19(1): 273, 2021 11 18.
Artigo em Inglês | MEDLINE | ID: mdl-34789257

RESUMO

BACKGROUND: Collagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients. METHODS: In this retrospective and multicenter study, we included 942 invasive breast cancer patients in both a training cohort (n = 355) and an internal validation cohort (n = 334) from one clinical center and in an external validation cohort (n = 253) from a different clinical center. TACS corresponding microscopic features (TCMFs) were firstly extracted from multiphoton images for each patient, and then least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust features to build a TCMF-score. Finally, the Cox proportional hazard regression analysis was used to evaluate the association of TCMF-score with disease-free survival (DFS). RESULTS: TCMF-score is significantly associated with DFS in univariate Cox proportional hazard regression analysis. After adjusting for clinical variables by multivariate Cox regression analysis, the TCMF-score remains an independent prognostic indicator. Remarkably, the TCMF model performs better than the clinical (CLI) model in the three cohorts and is particularly outstanding in the ER-positive and lower-risk subgroups. By contrast, the TACS model is more suitable for the ER-negative and higher-risk subgroups. When the TACS and TCMF are combined, they could complement each other and perform well in all patients. As expected, the full model (CLI+TCMF+TACS) achieves the best performance (AUC 0.905, [0.873-0.938]; 0.896, [0.860-0.931]; 0.882, [0.840-0.925] in the three cohorts). CONCLUSION: These results demonstrate that the TCMF-score is an independent prognostic factor for breast cancer, and the increased prognostic performance (TCMF+TACS-score) may help us develop more appropriate treatment protocols.


Assuntos
Neoplasias da Mama , Neoplasias da Mama/diagnóstico , Colágeno , Computadores , Feminino , Humanos , Prognóstico , Estudos Retrospectivos
7.
Artigo em Inglês | MEDLINE | ID: mdl-34769844

RESUMO

In this digital era, young children spend a considerable amount of time looking at telephone, tablet, computer and television screens. However, preventative eye health behavior education could help avoid and relieve asthenopia. The effects of parental influence on their children's eye health behavior through the preschool eye health education intervention program were examined. The Health Belief Model was used to develop parental involvement strategy and eye health curriculum. The study was conducted in a large public preschool with five branches in Beijing, China. A total of 248 parent-child pairs participated in the baseline and follow-up surveys, of which 129 were in the intervention group and 119 were in the comparison group. The generalized estimating equation analysis results indicated that parental involvement in preschool-based eye health intervention on screen uses had positive influence on parents' eye health knowledge, cues to action, and parenting efficacy. The intervention program also had positive effects on the increasing level of children's eye health knowledge, beliefs, cues to action, self-efficacy, and behaviors. The results supported the implementation of a preschool-based eye health intervention program with parental involvement, which could potentially enhance children's and parents' eye health beliefs and practices.


Assuntos
Poder Familiar , Televisão , Criança , Comportamento Infantil , Pré-Escolar , Computadores , Escolaridade , Humanos , Relações Pais-Filho
8.
Sensors (Basel) ; 21(21)2021 Oct 20.
Artigo em Inglês | MEDLINE | ID: mdl-34770277

RESUMO

Critical Infrastructures (CIs) are sensible targets. They could be physically damaged by natural or human actions, causing service disruptions, economic losses, and, in some extreme cases, harm to people. They, therefore, need a high level of protection against possible unintentional and intentional events. In this paper, we show a logical architecture that exploits information from both physical and cybersecurity systems to improve the overall security in a power plant scenario. We propose a Machine Learning (ML)-based anomaly detection approach to detect possible anomaly events by jointly correlating data related to both the physical and cyber domains. The performance evaluation showed encouraging results-obtained by different ML algorithms-which highlights how our proposed approach is able to detect possible abnormal situations that could not have been detected by using only information from either the physical or cyber domain.


Assuntos
Segurança Computacional , Sistemas de Informação , Algoritmos , Computadores , Humanos
9.
Sensors (Basel) ; 21(21)2021 Oct 21.
Artigo em Inglês | MEDLINE | ID: mdl-34770286

RESUMO

This paper proposes a cloud-based software architecture for fully automated point-of-care molecular diagnostic devices. The target system operates a cartridge consisting of an extraction body for DNA extraction and a PCR chip for amplification and fluorescence detection. To facilitate control and monitoring via the cloud, a socket server was employed for fundamental molecular diagnostic functions such as DNA extraction, amplification, and fluorescence detection. The user interface for experimental control and monitoring was constructed with the RESTful application programming interface, allowing access from the terminal device, edge, and cloud. Furthermore, it can also be accessed through any web-based user interface on smart computing devices such as smart phones or tablets. An emulator with the proposed software architecture was fabricated to validate successful operation.


Assuntos
Computação em Nuvem , Sistemas Automatizados de Assistência Junto ao Leito , Computadores , Patologia Molecular , Software
10.
Sensors (Basel) ; 21(21)2021 Oct 27.
Artigo em Inglês | MEDLINE | ID: mdl-34770444

RESUMO

Real-time image processing and computer vision systems are now in the mainstream of technologies enabling applications for cyber-physical systems, Internet of Things, augmented reality, and Industry 4.0. These applications bring the need for Smart Cameras for local real-time processing of images and videos. However, the massive amount of data to be processed within short deadlines cannot be handled by most commercial cameras. In this work, we show the design and implementation of a manycore vision processor architecture to be used in Smart Cameras. With massive parallelism exploration and application-specific characteristics, our architecture is composed of distributed processing elements and memories connected through a Network-on-Chip. The architecture was implemented as an FPGA overlay, focusing on optimized hardware utilization. The parameterized architecture was characterized by its hardware occupation, maximum operating frequency, and processing frame rate. Different configurations ranging from one to eighty-one processing elements were implemented and compared to several works from the literature. Using a System-on-Chip composed of an FPGA integrated into a general-purpose processor, we showcase the flexibility and efficiency of the hardware/software architecture. The results show that the proposed architecture successfully allies programmability and performance, being a suitable alternative for future Smart Cameras.


Assuntos
Inteligência Artificial , Processamento de Imagem Assistida por Computador , Computadores , Software
11.
Sensors (Basel) ; 21(21)2021 Oct 30.
Artigo em Inglês | MEDLINE | ID: mdl-34770535

RESUMO

The place of public key cryptography (PKC) in guaranteeing the security of wireless networks under human-centered IoT environments cannot be overemphasized. PKC uses the idea of paired keys that are mathematically dependent but independent in practice. In PKC, each communicating party needs the public key and the authorized digital certificate of the other party to achieve encryption and decryption. In this circumstance, a directory is required to store the public keys of the participating parties. However, the design of such a directory can be cost-prohibitive and time-consuming. Recently, identity-based encryption (IBE) schemes have been introduced to address the vast limitations of PKC schemes. In a typical IBE system, a third-party server can distribute the public credentials to all parties involved in the system. Thus, the private key can be harvested from the arbitrary public key. As a result, the sender could use the public key of the receiver to encrypt the message, and the receiver could use the extracted private key to decrypt the message. In order to improve systems security, new IBE schemes are solely desired. However, the complexity and cost of designing an entirely new IBE technique remain. In order to address this problem, this paper presents a provably secure IBE transformation model for PKC using conformable Chebyshev chaotic maps under the human-centered IoT environment. In particular, we offer a robust and secure IBE transformation model and provide extensive performance analysis and security proofs of the model. Finally, we demonstrate the superiority of the proposed IBE transformation model over the existing IBE schemes. Overall, results indicate that the proposed scheme posed excellent security capabilities compared to the preliminary IBE-based schemes.


Assuntos
Segurança Computacional , Confidencialidade , Algoritmos , Computadores , Humanos
12.
Sensors (Basel) ; 21(21)2021 Oct 30.
Artigo em Inglês | MEDLINE | ID: mdl-34770547

RESUMO

This paper presents a systematic and efficient design approach for the two degree-of-freedom (2-DoF) capacitive microelectromechanical systems (MEMS) accelerometer by using combined design and analysis of computer experiments (DACE) and Gaussian process (GP) modelling. Multiple output responses of the MEMS accelerometer including natural frequency, proof mass displacement, pull-in voltage, capacitance change, and Brownian noise equivalent acceleration (BNEA) are optimized simultaneously with respect to the geometric design parameters, environmental conditions, and microfabrication process constraints. The sampling design space is created using DACE based Latin hypercube sampling (LHS) technique and corresponding output responses are obtained using multiphysics coupled field electro-thermal-structural interaction based finite element method (FEM) simulations. The metamodels for the individual output responses are obtained using statistical GP analysis. The developed metamodels not only allowed to analyze the effect of individual design parameters on an output response, but to also study the interaction of the design parameters. An objective function, considering the performance requirements of the MEMS accelerometer, is defined and simultaneous multi-objective optimization of the output responses, with respect to the design parameters, is carried out by using a combined gradient descent algorithm and desirability function approach. The accuracy of the optimization prediction is validated using FEM simulations. The behavioral model of the final optimized MEMS accelerometer design is integrated with the readout electronics in the simulation environment and voltage sensitivity is obtained. The results show that the combined DACE and GP based design methodology can be an efficient technique for the design space exploration and optimization of multiphysics MEMS devices at the design phase of their development cycle.


Assuntos
Sistemas Microeletromecânicos , Aceleração , Simulação por Computador , Computadores , Distribuição Normal
13.
Sensors (Basel) ; 21(21)2021 Oct 31.
Artigo em Inglês | MEDLINE | ID: mdl-34770574

RESUMO

The speed and accuracy of phenotype detection from medical images are some of the most important qualities needed for any informed and timely response such as early detection of cancer or detection of desirable phenotypes for animal breeding. To improve both these qualities, the world is leveraging artificial intelligence and machine learning against this challenge. Most recently, deep learning has successfully been applied to the medical field to improve detection accuracies and speed for conditions including cancer and COVID-19. In this study, we applied deep neural networks, in the form of a generative adversarial network (GAN), to perform image-to-image processing steps needed for ovine phenotype analysis from CT scans of sheep. Key phenotypes such as gigot geometry and tissue distribution were determined using a computer vision (CV) pipeline. The results of the image processing using a trained GAN are strikingly similar (a similarity index of 98%) when used on unseen test images. The combined GAN-CV pipeline was able to process and determine the phenotypes at a speed of 0.11 s per medical image compared to approximately 30 min for manual processing. We hope this pipeline represents the first step towards automated phenotype extraction for ovine genetic breeding programmes.


Assuntos
Inteligência Artificial , COVID-19 , Animais , Computadores , Humanos , Processamento de Imagem Assistida por Computador , Fenótipo , SARS-CoV-2 , Ovinos
14.
Sensors (Basel) ; 21(21)2021 Nov 03.
Artigo em Inglês | MEDLINE | ID: mdl-34770615

RESUMO

Cloud computing is an emerging paradigm that offers flexible and seamless services for users based on their needs, including user budget savings. However, the involvement of a vast number of cloud users has made the scheduling of users' tasks (i.e., cloudlets) a challenging issue in selecting suitable data centres, servers (hosts), and virtual machines (VMs). Cloudlet scheduling is an NP-complete problem that can be solved using various meta-heuristic algorithms, which are quite popular due to their effectiveness. Massive user tasks and rapid growth in cloud resources have become increasingly complex challenges; therefore, an efficient algorithm is necessary for allocating cloudlets efficiently to attain better execution times, resource utilisation, and waiting times. This paper proposes a cloudlet scheduling, locust inspired algorithm to reduce the average makespan and waiting time and to boost VM and server utilisation. The CloudSim toolkit was used to evaluate our algorithm's efficiency, and the obtained results revealed that our algorithm outperforms other state-of-the-art nature-inspired algorithms, improving the average makespan, waiting time, and resource utilisation.


Assuntos
Computação em Nuvem , Gafanhotos , Algoritmos , Animais , Computadores , Heurística
15.
Sensors (Basel) ; 21(21)2021 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-34770646

RESUMO

Human Activity Recognition (HAR) has become increasingly crucial in several applications, ranging from motion-driven virtual games to automated video surveillance systems. In these applications, sensors such as smart phone cameras, web cameras or CCTV cameras are used for detecting and tracking physical activities of users. Inevitably, spoof detection in HAR is essential to prevent anomalies and false alarms. To this end, we propose a deep learning based approach that can be used to detect spoofing in various fields such as border control, institutional security and public safety by surveillance cameras. Specifically, in this work, we address the problem of detecting spoofing occurring from video replay attacks, which is more common in such applications. We present a new database containing several videos of users juggling a football, captured under different lighting conditions and using different display and capture devices. We train our models using this database and the proposed system is capable of running in parallel with the HAR algorithms in real-time. Our experimental results show that our approach precisely detects video replay spoofing attacks and generalizes well, even to other applications such as spoof detection in face biometric authentication. Results show that our approach is effective even under resizing and compression artifacts that are common in HAR applications using remote server connections.


Assuntos
Identificação Biométrica , Algoritmos , Computadores , Face , Atividades Humanas , Humanos
16.
Sensors (Basel) ; 21(21)2021 Nov 05.
Artigo em Inglês | MEDLINE | ID: mdl-34770656

RESUMO

Object detection, classification and tracking are three important computer vision techniques [...].


Assuntos
Aprendizado Profundo , Computadores
17.
Sensors (Basel) ; 21(21)2021 Nov 05.
Artigo em Inglês | MEDLINE | ID: mdl-34770675

RESUMO

Recently, artificial intelligence has been successfully used in fields, such as computer vision, voice, and big data analysis. However, various problems, such as security, privacy, and ethics, also occur owing to the development of artificial intelligence. One such problem are deepfakes. Deepfake is a compound word for deep learning and fake. It refers to a fake video created using artificial intelligence technology or the production process itself. Deepfakes can be exploited for political abuse, pornography, and fake information. This paper proposes a method to determine integrity by analyzing the computer vision features of digital content. The proposed method extracts the rate of change in the computer vision features of adjacent frames and then checks whether the video is manipulated. The test demonstrated the highest detection rate of 97% compared to the existing method or machine learning method. It also maintained the highest detection rate of 96%, even for the test that manipulates the matrix of the image to avoid the convolutional neural network detection method.


Assuntos
Inteligência Artificial , Redes Neurais de Computação , Computadores , Decepção , Aprendizado de Máquina
18.
Sensors (Basel) ; 21(21)2021 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-34770684

RESUMO

FPGA-based data acquisition and processing systems play an important role in modern high-speed, multichannel measurement systems, especially in High-Energy and Plasma Physics. Such FPGA-based systems require an extended control and diagnostics part corresponding to the complexity of the controlled system. Managing the complex structure of registers while keeping the tight coupling between hardware and software is a tedious and potentially error-prone process. Various existing solutions aimed at helping that task do not perfectly match all specific requirements of that application area. The paper presents a new solution based on the XML system description, facilitating the automated generation of the control system's HDL code and software components and enabling easy integration with the control software. The emphasis is put on reusability, ease of maintenance in the case of system modification, easy detection of mistakes, and the possibility of use in modern FPGAs. The presented system has been successfully used in data acquisition and preprocessing projects in high-energy physics experiments. It enables easy creation and modification of the control system definition and convenient access to the control and diagnostic blocks. The presented system is an open-source solution and may be adopted by the user for particular needs.


Assuntos
Computadores , Software
19.
Artigo em Inglês | MEDLINE | ID: mdl-34769758

RESUMO

Measuring muscle fatigue is one essential and standard method to quantify the ergonomic risks associated with prolonged low-load exposure. However, measuring muscle fatigue using EMG-based methods has shown conflicting results under low-load but sustained work conditions, e.g., prolonged sitting. Muscle stimulation technology provides an alternative way to estimate muscle fatigue development during such work conditions by monitoring the stimulation-evoked muscle responses, which, however, could be restricted by the accessibility and measurability of targeted muscles. This study proposes a computer vision-based method to overcome such potential restrictions by visually quantifying the muscle belly displacement caused by muscle stimulation. The results demonstrate the ability of the developed computer vision-based stimulation method to detect muscle fatigue from prolonged low-load tasks. Current results can be used as a foundation to develop a sensitive and reliable method to quantify the adverse effects of the daily low-load sustained condition in occupational and nonoccupational settings.


Assuntos
Fadiga Muscular , Músculo Esquelético , Computadores , Eletromiografia , Ergonomia
20.
Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi ; 35(11): 1492-1498, 2021 Nov 15.
Artigo em Chinês | MEDLINE | ID: mdl-34779179

RESUMO

Objective: To compare the application effects between personal specific instrumentation (PSI) and computer-assisted navigation surgery (CAS) in total knee arthroplasty (TKA). Methods: The literature comparing the application effects of PSI and CAS in TKA in recent years was widely consulted, and the difference between PSI-TKA and CAS-TKA in operation time, lower limb alignment, blood loss, and knee function were compared. Results: Compared to CAS-TKA, PSI-TKA simplifies operation procedures and shortens operation time but probably has worse lower limb alignment. It is still controversial in comparison of perioperative blood loss and knee function between two techniques. Conclusion: PSI-TKA and CAS-TKA both have advantages and disadvantages, and their differences need to be confirmed by further high-quality clinical trial.


Assuntos
Artroplastia do Joelho , Prótese do Joelho , Osteoartrite do Joelho , Cirurgia Assistida por Computador , Computadores , Humanos , Articulação do Joelho/cirurgia , Osteoartrite do Joelho/cirurgia
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