September 2022 - ScienceFather

Association of artificial intelligence use and the retention of elderly caregivers: A cross-sectional study based on empowerment theory

Posted on 30/09/2022 by ScienceFatherLeave a Comment

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Aim:

The purpose of this study is to investigate how the use of artificial intelligence (AI) is associated with the retention of elderly caregivers.

Background:

The turnover of elderly caregivers is high and increasing. Elderly care institutions are beginning to use artificial intelligence (AI) to support caregivers in their work, and the use of technology is critical to staff retention. Empowerment of elderly caregivers has been neglected by managers and researchers.

Methods:

This cross-sectional study involved 511 elderly caregivers in 25 elderly institutions. Six validated standardized scales were used for data collection, and the softwares SPSS and SmartPLS were used for data analysis.

Results:

The quality of artificial intelligence (AI) has a significant positive effect on empowerment. artificial intelligence (AI) psychological empowerment (β = 0.355, p < 0.001) and artificial intelligence (AI) structural empowerment (β = 0.375, p < 0.001) both had positive effects on retention intention, and the jointly explained variance (R² ) was 42.6%.

Conclusions:

The results show that a significant relationship exists between artificial intelligence (AI) empowerment and retention intention. Elderly caregivers with more structural empowerment have higher retention intention.

Implications for nursing management:

artificial intelligence (AI) suppliers need to pay attention to the role of product quality in elderly care services, continuously improve artificial intelligence (AI) quality, and strengthen the application and routine maintenance of artificial intelligence (AI) technology. Elderly care institution managers should pay special attention to artificial intelligence (AI) structural empowerment (such as AI-related education and training, learning and development opportunities, and resource support).

Keywords:

artificial intelligence; empowerment; psychological empowerment; retention; structural empowerment.

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CNN Multi-Position Wearable Sensor Human Activity Recognition Used in Basketball Training

Posted on 29/09/2022 by ScienceFatherLeave a Comment

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. 2022 Sep 19;2022:9918143.

doi: 10.1155/2022/9918143.

eCollection 2022.

Affiliations

Item in Clipboard

Biao Tang et al.

Comput Intell Neurosci.

2022.

Abstract

With the development trend of artificial intelligence technology and the popularization of wearable sensors, human activity recognition based on sensor data information has received widespread attention and has great application value. In order to better optimize the network structure and reduce the total number of main training parameters in the convolutional layer, a convolutional network entity model based on shared resources of main parameters is clearly proposed. We analyzed the CNN multi-position wearable sensor human activity recognition used in basketball training. According to the entity model of the main parameters of shared resources, the effectiveness of the entity model is verified from both the total number of sensors and the accuracy of single-class recognition. In addition to maintaining the actual effect of recognition, the main training parameters are also reduced. The simulation results verify the actual effect of the SVM algorithm and motion simulation of the convolutional network entity model. On this basis, scientific research physical exercise methods are selected to reasonably ensure the smooth progress of appropriate physical exercise at a certain level, improve the quality of training and the actual effect.

Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

**Figure 1**

Convolution structure based on multi-channel time series data.

**Figure 2**

Multi-position three-axis sensor input construction method.

**Figure 3**

Two-dimensional convolution model network structure M.2DCNN based on multi-position hybrid sensor.

**Figure 4**

Two-dimensional convolution calculation process.

**Algorithm 1**

Two dimensional input algorithm of moving image based on multi position hybrid sensor.

References

1. Alcalá D. H., García C. G., Garijo A. H. Combat versus team sports: the effects of gender in a climate of peer-motivation, and levels of fun and violence in physical education students. Ido Movement for Culture . 2017;17(3):11–20.
1. Chen Y. Study on neural network model-based senior high school Men’s basketball training strategy and approach. Journal of Computational and Theoretical Nanoscience . 2016;13(12):10059–10063. doi: 10.1166/jctn.2016.6210.
  
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  DOI
1. Kirkup J. A., Rowlands D. D., Thiel D. V. Team Player tracking using sensors and signal strength for indoor basketball. IEEE Sensors Journal . 2016;16(11):4622–4630. doi: 10.1109/jsen.2016.2542359.
  
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  DOI
1. Vaquera A., Mielgo-Ayuso J., Calleja-González J., Leicht A. S. Match intensity and heart rate predictors in top level basketball referees during men’s Eurobasket. The Journal of Sports Medicine and Physical Fitness . 2016;56(9):1034–1040.
  
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1. Huang Q., Ko K. T., Iversen V. B. An approximation method for multiservice loss performance in hierarchical networks. Proceedings of the Managing Traffic Performance in Converged Networks; May 2007; Berlin, Heidelberg. Springer; pp. 901–912.
  
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Multimodal ultrasound imaging: A method to improve the accuracy of diagnosing thyroid TI-RADS 4 nodules

Posted on 28/09/2022 by ScienceFatherLeave a Comment

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Review

doi: 10.1002/jcu.23352.

Online ahead of print.

Affiliations

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Review

Zhengyang Han et al.

J Clin Ultrasound.

2022.

Abstract

Thyroid nodule is a common and frequently occurring disease in the neck in recent years, and ultrasound has become the preferred imaging diagnosis method for thyroid nodule due to its advantages of noninvasive, nonradiation, real-time, and repeatable. The thyroid imaging, reporting and data system (TI-RADS) classification standard scores suspicious nodules that are difficult to determine benign and malignant as grade 4, and further pathological puncture is recommended clinically, which may lead to a large number of unnecessary biopsies and operations. Including conventional ultrasound, ACR TI-RADS, shear wave elastography, super microvascular imaging, contrast enhanced ultrasound, “firefly,” artificial intelligence, and multimodal ultrasound imaging used in combination. In order to identify the most clinically significant malignant tumors when reducing invasive operations. This article reviews the application and research progress of multimodal ultrasound imaging in the diagnosis of TI-RADS 4 thyroid nodules.

Keywords:

ACR TI-RADS; contrast enhanced ultrasound; multimodal ultrasound imaging; shear wave elastography; thyroid nodule; ultramicro vascular imaging.

References

REFERENCES

1. Horvath E, Majlis S, Rossi R, et al. An ultrasonogram reporting system for thyroid nodules stratifying cancer risk for clinical management. J Clin Endocrinol Metab. 2009;94(5):1748-1751.
1. Cancela E, Penna G, Costa CT, Pires MC, Nunes TA. Are the anatomical, clinical, and ultrasound characteristics of thyroid nodules with Bethesda III or IV cytology and ACR TI-RADS 3, 4, or 5 able to refine the indications for molecular diagnostic tests? Arch Endocrinol Metab. 2021;65(5):625-631.
1. Wang Y, Dong T, Nie F, Wang G, Liu T, Niu Q. Contrast-enhanced ultrasound in the differential diagnosis and risk stratification of ACR TI-RADS category 4 and 5 thyroid nodules with non-hypovascular. Front Oncol. 2021;11:662273.
1. Huang K, Bai Z, Bian D, Yang P, Li X, Liu Y. Diagnostic accuracy of contrast-enhanced ultrasonography in papillary thyroid microcarcinoma stratified by size. Ultrasound Med Biol. 2020;46(2):269-274.
1. Junior RA, Falsarella PM, Rocha RD, et al. Correlation of thyroid imaging reporting and data system [TI-RADS] and fine needle aspiration: experience in 1,000 nodules. Einstein (Sao Paulo). 2016;14(2):119-123.

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Effects of human-machine interaction on employee’s learning: A contingent perspective

Posted on 26/09/2022 by ScienceFatherLeave a Comment

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doi: 10.3389/fpsyg.2022.876933.

eCollection 2022.

Affiliations

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Wang Sen et al.

Front Psychol.

2022.

doi: 10.3389/fpsyg.2022.876933.

eCollection 2022.

Affiliations

¹ Department of Business Administration, School of Management, Beijing Union University, Beijing, China.
² Department of Business Administration, School of Business Administration, Nanjing University of Finance and Economics, Nanjing, China.

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Abstract

The popularization of intelligent machines such as service robot and industrial robot will make human-machine interaction, an essential work mode. This requires employees to adapt to the new work content through learning. However, the research involved human-machine interaction that how influences the employee’s learning is still rarely. This paper was to reveal the relationship between human-machine interaction and employee’s learning from the perspective of job characteristics and competence perception of employees. We sent questionnaire to 500 employees from 100 artificial intelligence companies in China and received 319 valid and complete responses. Then, we adopted a hierarchical regression for the test. Empirical results show that human-machine interaction has a U-shaped curvilinear relationship with employee learning, and employee’s vitality mediates the curvilinear relationship. In addition, job characteristics (skill variety and job autonomy) moderate the U-shaped curvilinear relationship between human-machine interaction and employee’s vitality, especially the results of moderating effects varying with employee’s competence perception. Exploring the mechanism of the effect of human-machine interaction on employee’s learning enriches the socially embedded model. Moreover, it provides managerial implications how to enhance individual adaptability with the introduction of AI into firms. However, our research focuses more on the impact of human-machine interaction on employees at the initial stage of AI development, and the level of machine intelligence in various industries will reach a high degree of autonomy in the future. The future research can explore the impact of human-machine interaction on individual’s behavior at different stages, and the results may vary depending on the technologies mastered by different individuals. The study has theoretical and practical significance to human-machine interaction literature by underscoring the important of individual’s behavior among individuals with different skills.

Keywords:

competence perception; employee learning; employee vitality; human–machine interaction; job characteristics.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Saudi artificial intelligence summit attracts global talents

Posted on 26/09/2022 by ScienceFatherLeave a Comment

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Prince Mohammed bin Khalid Al-Abdullah Al-Faisal, chairman of stc, and Olayan bin Mohammed Alwetaid, chief executive of stc Group, congratulated King Salman, Crown Prince Mohammed bin Salman and the Saudi people, on the occasion of the 92nd National Day.

The stc chairman said: “The 92nd National Day anniversary comes as we continue the march toward progress and development, moving forward to achieve the ambitions and goals set by our wise leadership under Vision 2030.”

He added: “The great and diverse achievements we see today across different areas in the Kingdom of Saudi Arabia are the absolute proof that the march started by the Kingdom’s Vision 2030 is steadily moving forward toward building our great nation with the help of Saudi hands.

“The huge digital leaps reflect the Kingdom’s accomplishments and have given the Kingdom a solid digital infrastructure that has enabled it to face crises and ensure business continuity across various fields. These changes resulted in an increasing demand for digital services, which helped accelerate digital transformation as one of the pillars of the Kingdom’s Vision 2030 and a key driver of development in the digital economy.

“The core of stc’s mission is constantly focused on innovation and development of digital solutions to establish its local and regional leadership as well as its global reputation, in addition to playing a pivotal role as one of the leading digital enablers in the Kingdom and the region.”

Prince Mohammed bin Khalid expressed appreciation for the wise leadership for their support and interest in uplifting the ICT sector while enhancing the digital transformation process and consolidating the position of the Kingdom as the largest and fastest growing digital economy in the Middle East and North Africa.

Meanwhile, stc Group CEO Alwetaid said: “The ICT sector contributes to the growth of the digital economy in the Kingdom at an unprecedented pace. During H1 of 2022, stc Group investments reached SR5 billion ($1.3 billion). This helped establish the Kingdom’s position as one of the world’s largest economies.”

He said that the stc Group will continue its strategy to expand and grow in nontraditional ways by building strategic partnerships, establishing specialized technology companies and making acquisitions as part of its efforts to achieve its vision of growth, while relying on the group’s modern infrastructure and technologies.

“During this year, we have concluded several partnerships with a number of international companies, including an agreement to localize data centers and train Saudi talents with Huawei, an agreement to enhance 5G networks with Ericsson, develop areas of innovation with Microsoft and other agreements aimed at developing technological fields in the Kingdom. We also launched the Saudi Cloud Computing Company in partnership with Alibaba Cloud and established Saudi Arabia’s SITE and SCAI.”

Furthermore, we announced an IoT company in partnership with the Public Investment Fund and launched an initiative to establish a major digital center — MENA Hub — for the Middle East and North Africa region. Moreover, our investments in submarine cables, adopted initiatives, had a sustainable impact on society, the economy and the environment. The InspireU incubator supports entrepreneurs in their technology startups, reaching 75 projects till date, with a market value today exceeding hundreds of millions in addition to 15 new projects in the ninth batch,” Alwetaid said.

“We are pleased with our achievements as a culmination of our ongoing contributions to the growth and prosperity of the ICT sector,” he said.

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Revisiting the Design Strategies for Metasurfaces: Fundamental Physics, Optimization, and Beyond

Posted on 25/09/2022 by ScienceFatherLeave a Comment

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Review

doi: 10.1002/adma.202206399.

Online ahead of print.

Affiliations

¹ Graduate School of Physics, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
² Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
³ Samsung Advanced Institute of Technology, Suwon, 16678, Republic of Korea.
⁴ Department of Chemical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
⁵ POSCO-POSTECH-RIST Convergence Research Center for Flat Optics and Metaphotonics, Pohang, 37673, Republic of Korea.

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Review

Sunae So et al.

Adv Mater.

2022.

doi: 10.1002/adma.202206399.

Online ahead of print.

Affiliations

¹ Graduate School of Physics, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
² Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
³ Samsung Advanced Institute of Technology, Suwon, 16678, Republic of Korea.
⁴ Department of Chemical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
⁵ POSCO-POSTECH-RIST Convergence Research Center for Flat Optics and Metaphotonics, Pohang, 37673, Republic of Korea.

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Abstract

Over the last two decades, the capabilities of metasurfaces in light modulation with subwavelength thickness have been proven, and metasurfaces are expected to miniaturize conventional optical components and add various functionalities. In this review article, various metasurface design strategies are reviewed thoroughly. First, we revisit the scalar diffraction theory to provide the basic principle of light propagation. Then, we discuss widely used design methods based on the unit-cell approach. The methods include a set of simplified steps, including the phase map retrieval and meta-atom unit-cell design. Then, we introduce recently emerging metasurfaces that may not be accurately designed using unit-cell approach. We examine unconventional metasurfaces where the conventional design methods fail and finally discuss potential design methods for such metasurfaces. This article is protected by copyright. All rights reserved.

Keywords:

design and optimization; diffraction theory; flat optics; meta-atom; metasurface.

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Updated review of advances in microRNAs and complex diseases: towards systematic evaluation of computational models

Posted on 24/09/2022 by ScienceFatherLeave a Comment

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doi: 10.1093/bib/bbac407.

Online ahead of print.

Affiliations

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Li Huang et al.

Brief Bioinform.

2022.

doi: 10.1093/bib/bbac407.

Online ahead of print.

Affiliations

¹ Academy of Arts and Design, Tsinghua University, Beijing, 10084, China.
² The Future Laboratory, Tsinghua University, Beijing, 10084, China.
³ School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China.
⁴ Physics Research Institute, China University of Mining and Technology, Xuzhou, 221116, China.

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Abstract

Currently, there exist no generally accepted strategies of evaluating computational models for microRNA-disease associations (MDAs). Though K-fold cross validations and case studies seem to be must-have procedures, the value of K, the evaluation metrics, and the choice of query diseases as well as the inclusion of other procedures (such as parameter sensitivity tests, ablation studies and computational cost reports) are all determined on a case-by-case basis and depending on the researchers’ choices. In the current review, we include a comprehensive analysis on how 29 state-of-the-art models for predicting MDAs were evaluated. Based on the analytical results, we recommend a feasible evaluation workflow that would suit any future model to facilitate fair and systematic assessment of predictive performance.

Keywords:

association prediction; complex diseases; computational model; microRNA; performance evaluation.

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Clinical evaluation of deep learning and atlas-based auto-segmentation for critical organs at risk in radiation therapy

Posted on 23/09/2022 by ScienceFatherLeave a Comment

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Introduction:

Contouring organs at risk (OARs) is a time-intensive task that is a critical part of radiation therapy. Atlas-based automatic segmentation has shown some success at reducing this time burden on practitioners; however, this method often requires significant manual editing to reach a clinically accurate standard. Deep learning (DL) auto-segmentation has recently emerged as a promising solution. This study compares the accuracy of DL and atlas-based auto-segmentation in relation to clinical ‘gold standard’ reference contours.

Methods:

Ninety CT datasets (30 head and neck, 30 thoracic, 30 pelvic) were automatically contoured using both atlas and DL segmentation techniques. Sixteen critical OARs were then quantitatively measured for accuracy using the Dice similarity coefficient (DSC) and Hausdorff distance (HD). Qualitative analysis was performed to visually classify the accuracy of each structure into one of four explicitly defined categories. Additionally, the time to edit atlas and DL contours to a clinically acceptable level was recorded for a subset of 9 OARs.

Results:

Of the 16 OARs analysed, DL delivered statistically significant improvements over atlas segmentation in 13 OARs measured with DSC, 12 OARs measured with HD, and 12 OARs measured qualitatively. The mean editing time for the subset of DL contours was 50%, 23% and 61% faster (all P < 0.05) than that of atlas segmentation for the head and neck, thorax, and pelvis respectively.

Conclusions:

Deep learning segmentation comprehensively outperformed atlas-based contouring for the majority of evaluated OARs. Improvements were observed in geometric accuracy and visual acceptability, while editing time was reduced leading to increased workflow efficiency.

Keywords:

artificial intelligence; atlas contouring; auto-segmentation; deep learning; organs at risk.

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Training Ultrasound Image Classification Deep-Learning Algorithms for Pneumothorax Detection Using a Synthetic Tissue Phantom Apparatus

Posted on 22/09/2022 by ScienceFatherLeave a Comment

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doi: 10.3390/jimaging8090249.

Affiliations

¹ U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
² Trauma & Combat Medicine Branch, Surgeon General’s Headquarters, Israel Defense Forces, Ramat-Gan 52620, Israel.
³ Division of Anesthesia, Intensive Care & Pain Management, Tel-Aviv Sourasky Medical Center, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv 64239, Israel.

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Emily N Boice et al.

J Imaging.

2022.

doi: 10.3390/jimaging8090249.

Affiliations

¹ U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
² Trauma & Combat Medicine Branch, Surgeon General’s Headquarters, Israel Defense Forces, Ramat-Gan 52620, Israel.
³ Division of Anesthesia, Intensive Care & Pain Management, Tel-Aviv Sourasky Medical Center, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv 64239, Israel.

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Abstract

Ultrasound (US) imaging is a critical tool in emergency and military medicine because of its portability and immediate nature. However, proper image interpretation requires skill, limiting its utility in remote applications for conditions such as pneumothorax (PTX) which requires rapid intervention. Artificial intelligence has the potential to automate ultrasound image analysis for various pathophysiological conditions. Training models require large data sets and a means of troubleshooting in real-time for ultrasound integration deployment, and they also require large animal models or clinical testing. Here, we detail the development of a dynamic synthetic tissue phantom model for PTX and its use in training image classification algorithms. The model comprises a synthetic gelatin phantom cast in a custom 3D-printed rib mold and a lung mimicking phantom. When compared to PTX images acquired in swine, images from the phantom were similar in both PTX negative and positive mimicking scenarios. We then used a deep learning image classification algorithm, which we previously developed for shrapnel detection, to accurately predict the presence of PTX in swine images by only training on phantom image sets, highlighting the utility for a tissue phantom for AI applications.

Keywords:

artificial intelligence; automation; deep learning; human; model development; pneumothorax; porcine; tissue phantom; ultrasound.

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Algorithms and the future of work

Posted on 21/09/2022 by ScienceFatherLeave a Comment

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doi: 10.1002/ajim.23429.

Online ahead of print.

Affiliations

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John Howard.

Am J Ind Med.

2022.

Abstract

An algorithm refers to a series of stepwise instructions used by a machine to perform a mathematical operation. In 1955, the term artificial intelligence (AI) was coined to indicate that a machine could be programmed to duplicate human intelligence. Even though that goal has not yet been reached, the use of sophisticated machine learning algorithms has moved us closer to that goal. While algorithm-enabled systems and devices will bring many benefits to occupational safety and health, this Commentary focuses on new sources of worker risk that algorithms present in the use of worker management systems, advanced sensor technologies, and robotic devices. A new “digital Taylorism” may erode worker autonomy, and lead to work intensification and psychosocial stress. The presence of large amounts of information on workers within algorithmic-enabled systems presents security and privacy risks. Reliance on indiscriminate data mining may reproduce forms of discrimination and lead to inequalities in hiring, retention, and termination. Workers interfacing with robots may face work intensification and job displacement, while injury in the course of employment by a robotic device is also possible. Algorithm governance strategies are discussed such as risk management practices, national and international laws and regulations, and emerging legal accountability proposals. Determining if an algorithm is safe for workplace use is rapidly becoming a challenge for manufacturers, programmers, employers, workers, and occupational safety and health practitioners. To achieve the benefits that algorithm-enabled systems and devices promise in the future of work, now is the time to study how to effectively manage their risks.

Keywords:

algorithm; artificial intelligence; robotics; sensors.

References

REFERENCES

1. Knuth DE. Ancient Babylonian algorithms. Commun ACM. 1972;15(7):671-677. doi:10.1145/361454.361514
1. Chabert J-L. Introduction. In: Chabert J-L, ed. A history of algorithms: from the pebble to the microchip. Springer Science and Business Media; 1999:1-6.
1. Oaks JA, Alkhateeb HM. Simplifying equations in Arabic algebra. Hist Math. 2007; 34:45-61
1. Brezina C, Al-Khwarizimi. The Inventor of Algebra. Rosen Publishing Group; 2006.
1. Louridas P. Algorithms. The MIT Press; 2020.

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