Structured Reporting in Musculoskeletal Radiology

2021 ◽  
Vol 25 (05) ◽  
pp. 641-645
Author(s):  
Ajay Kohli ◽  
Samantha Castillo ◽  
Uma Thakur ◽  
Avneesh Chhabra
Keyword(s):  
Manufacturing Industry ◽  
Service Industry ◽  
Quality Standards ◽  
Structured Reporting ◽  
Learning Approaches ◽  
Musculoskeletal Radiology ◽  
Future Directions ◽  
Future Data ◽  
Service Departments ◽  
And Training

AbstractMusculoskeletal (MSK) radiologists are predominantly consultants in the service departments of health care. Unlike the manufacturing industry, quality controls are difficult to institute in a service industry and more variability is expected. Structured reporting is a unique way to institute quality standards, and by using the checklist approach with uniform terminology, it can lead to more homogeneity and consistency of reporting, concise lexicon use within and across practices, minimization of errors, enhancement of divisional and departmental branding, improvement of interdisciplinary communications, and future data mining. We share our experience from more than a decade of structured reporting in the domain of MSK radiology, our practice standards, and how reporting has evolved in our MSK practice. Further discussions include future directions aided by machine learning approaches with augmented reality and the possibility of virtual fellowship and training using consistent lexicons and structured reporting.

Machine Learning and Human Factors: Status, Applications, and Future Directions

2018 ◽  
Vol 62 (1) ◽  
pp. 135-138 ◽  
Author(s):  
Nathan Lau ◽  
Lex Fridman ◽  
Brett J. Borghetti ◽  
John D. Lee
Keyword(s):  
Machine Learning ◽  
Human Factors ◽  
Interaction Design ◽  
Intelligent Systems ◽  
Consumer Products ◽  
Learning Approaches ◽  
Future Directions ◽  
Industrial Systems ◽  
Human Factors Research ◽  
And Training

As machine learning approaches ubiquity in industrial systems and consumer products, human factors research must attend to machine learning, specifically on how intelligent systems built on machine learning are different from early generations of automated systems, and what these differences mean for human-system interaction, design, evaluation and training. This panel invites five researchers in different domains to discuss how human factors can contribute to machine learning research and applications, as well as how machine learning presents both challenges and contributions for human factors.

scholarly journals 5S APPLICATION TRAINING (SEIRI, SEITON, SEISŌ, SEIKETSU, AND SHITSUKE) TO IMPROVE THE QUALITY OF WORK ENVIRONMENT IN THE SERVICE INDUSTRY

ICCD ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 352-354
Author(s):  
Humiras Hardi Purba ◽  
Dana Santoso Saroso ◽  
Jafkat Haekal
Keyword(s):  
Work Environment ◽  
Community Service ◽  
Manufacturing Industry ◽  
Service Industry ◽  
Self Awareness ◽  
Real Economy ◽  
Medium Businesses ◽  
Small Industries ◽  
And Training

National industries already have policies that are able to strengthen industrial competitiveness, especially small and medium businesses. Business activities in the form of manufacturing Small Industries are the backbone of the real economy that encourages the welfare of the community because the numbers are very large and spread in various regions. because it is generally close to residential and business centers. National policies that can encourage competitiveness, for example, are carried out in the form of soft loans, training, incentives, tax breaks, business assistance, ease of regulation and various forms of support. But it must be understood that what is no less important is how the small manufacturing industry itself can make competitive steps both in capturing markets and in the efficient form of work operations within its organization. At present, the 5S method (Seiri, Seiton, Seisō, Seiketsu, and Shitsuke) has been widely adopted by various industries in various countries. The 5S method (Seiri, Seiton, Seisō, Seiketsu, and Shitsuke) was first introduced in Japan as a determination to conduct sorting (Seiri), structuring (Seiton), cleansing (Seisō), maintaining steady conditions (Seiketsu), and self-awareness of the habits needed to carry out work well (Shitsuke). The implementation of community service activities in the form of socialization and training on the application of 5S (Seiri, Seiton, Seisō, Seiketsu, andShitsuke) to improve the quality of the work environment in the service industry is packaged in the form of simple, easy to understand concepts planned for three months.

Conclusions and Future Directions for the Study of Accurate Personality Judgment

2020 ◽  
Author(s):  
Tera D. Letzring
Keyword(s):  
Standardized Tests ◽  
Personality Trait ◽  
Training Programs ◽  
Future Research ◽  
Research Topics ◽  
Theoretical Frameworks ◽  
Future Directions ◽  
Personality Judgment ◽  
Exciting Time ◽  
And Training

This chapter identifies several well-established findings and overarching themes within personality trait accuracy research, and highlights especially promising directions for future research. Topics include (1) theoretical frameworks for accuracy, (2) moderators of accuracy and the context or situation in which judgments are made, (3) the important consequences of accuracy, (4) interventions and training programs to increase judgmental ability and judgability, (5) the generalizability of previous findings, and (6) standardized tests of the accuracy of judging personality traits. The chapter ends by stating that it is an exciting time to be a researcher studying the accuracy of personality trait judgments.

scholarly journals Olfaction and Aging: A Review of the Current State of Research and Future Directions

i-Perception ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 204166952110203
Author(s):  
Jonas K. Olofsson ◽  
Ingrid Ekström ◽  
Maria Larsson ◽  
Steven Nordin
Keyword(s):  
Warning Signs ◽  
Future Directions ◽  
Current State ◽  
Challenging Tasks ◽  
State Of Research ◽  
To Come ◽  
Health Cognition ◽  
Olfactory Abilities ◽  
And Training

Olfaction, the sense of smell, is characterized by a notable age-dependency such that aging individuals are more likely to have poor olfactory abilities. These impairments are considered to be mostly irreversible and as having potentially profound effects on quality of life and food behavior, as well as constituting warning signs of mortality, cognitive dysfunction, and dementia. Here, we review the current state of research on aging and olfaction, focusing on five topics which we regard to be of particular relevance for the field: nutrition and health, cognition and dementia, mortality, environment and genetics, and training-based enhancement. Under each of these headlines, we provide a state-of-the-art overview and discuss gaps in our knowledge which might be filled by further research. Understanding how olfactory abilities are diminished in aging, and how they may be alleviated or recovered, involves a set of challenging tasks for researchers in the years to come.

scholarly journals A Bayesian Control Chart for Monitoring Process Variance

2021 ◽  
Vol 11 (6) ◽  
pp. 2729
Author(s):  
Chien-Hua Lin ◽  
Ming-Che Lu ◽  
Su-Fen Yang ◽  
Ming-Yung Lee
Keyword(s):  
Service Quality ◽  
Control Chart ◽  
Manufacturing Industry ◽  
Industrial Revolution ◽  
Service Industry ◽  
Service Process ◽  
Time Varying ◽  
Exponential Process ◽  
Free Process ◽  
Process Variance

Automation in the service industry is emerging as a new wave of industrial revolution. Standardization and consistency of service quality is an important part of the automation process. The quality control methods widely used in the manufacturing industry can provide service quality measurement and service process monitoring. In particular, the control chart as an online monitoring technique can be used to quickly detect whether a service process is out of control. However, the control of the service process is more difficult than that of the manufacturing process because the variability of the service process comes from widespread and complex factors. First of all, the distribution of the service process is usually non-normal or unknown. Moreover, the skewness of the process distribution can be time-varying, even if the process is in control. In this study, a Bayesian procedure is applied to construct a Phase II exponential weighted moving average (EWMA) control chart for monitoring the variance of a distribution-free process. We explore the sampling properties of the new monitoring statistic, which is suitable for monitoring the time-varying process distribution. The average run lengths (ARLs) of the proposed Bayesian EWMA variance chart are calculated, and they show that the chart performs well. The simulation studies for a normal process, exponential process, and the mixed process of normal and exponential distribution prove that our chart can quickly detect any shift of a process variance. Finally, a numerical example of bank service time is used to illustrate the application of the proposed Bayesian EWMA variance chart and confirm the performance of the process control.

scholarly journals How to train your differentiable filter

2021 ◽  
Author(s):  
Alina Kloss ◽  
Georg Martius ◽  
Jeannette Bohg
Keyword(s):  
Bayesian Filtering ◽  
Learning Approaches ◽  
Filtering Algorithms ◽  
Recursive Filtering ◽  
Process Dynamics ◽  
Noise Characteristics ◽  
Complex Models ◽  
End To End ◽  
Robotic Applications ◽  
And Training

AbstractIn many robotic applications, it is crucial to maintain a belief about the state of a system, which serves as input for planning and decision making and provides feedback during task execution. Bayesian Filtering algorithms address this state estimation problem, but they require models of process dynamics and sensory observations and the respective noise characteristics of these models. Recently, multiple works have demonstrated that these models can be learned by end-to-end training through differentiable versions of recursive filtering algorithms. In this work, we investigate the advantages of differentiable filters (DFs) over both unstructured learning approaches and manually-tuned filtering algorithms, and provide practical guidance to researchers interested in applying such differentiable filters. For this, we implement DFs with four different underlying filtering algorithms and compare them in extensive experiments. Specifically, we (i) evaluate different implementation choices and training approaches, (ii) investigate how well complex models of uncertainty can be learned in DFs, (iii) evaluate the effect of end-to-end training through DFs and (iv) compare the DFs among each other and to unstructured LSTM models.

New product and emerging business growth in Kwara State

2016 ◽  
Vol 12 (3) ◽  
pp. 207-227 ◽  
Author(s):  
Seun Oladele ◽  
Femi Oladele
Keyword(s):  
Market Share ◽  
Manufacturing Industry ◽  
Service Industry ◽  
New Product ◽  
Sales Volume ◽  
Test Results ◽  
Business Growth ◽  
Content Type ◽  
Product Service ◽  
Service Portfolio

Purpose – The purpose of this paper is to examine the effect of new product on growth of emerging businesses (EBs) through sales volume and market share. Design/methodology/approach – The study surveyed 137 EBs in Kwara State. Two hypotheses were formulated and tested using correlation and regression analyses. Findings – Results show that service industry is dominant among EBs while the manufacturing industry trails. Many EBs are aware of the complexities of new product, its development and contribution to increasing sales volume, market share and ensuring competitive advantage with apparent infrastructural deficiencies. Test results show that there is a significant positive relationship and effect on sales volume and market share. Originality/value – Encouraging EBs to step up and focus on improving product/service portfolio to transform their fortune is explored giving focus to the benefits of increasing sales volume and market share.

Future Directions in Simulation and Training

1978 ◽  
Vol 6 (4) ◽  
pp. 285-292 ◽  
Author(s):  
Robert W. Swezey
Keyword(s):  
Brain Stimulation ◽  
Social Processes ◽  
Future Directions ◽  
Simulation And Training ◽  
The Future ◽  
And Training

A discussion of potential future directions in the areas of simulation and training is presented. Advantages, disadvantages and problems associated with training-oriented simulations are discussed, and several areas including: holography, social processes, mnemonics, trance learning, and electrical and biochemical brain stimulation are presented as fertile areas for increased development in the future.

The fuzzy integrated TOPSIS economy ranking (FITER) model for manufacturing technology development in China

2021 ◽  
pp. 1-13
Author(s):  
Yang GAO ◽  
Xiang GAO
Keyword(s):  
Decision Making ◽  
Information Diffusion ◽  
Manufacturing Industry ◽  
Service Industry ◽  
Technology Development ◽  
Manufacturing Technology ◽  
Technological Advancement ◽  
Ranking Score ◽  
Expansion Level ◽  
High Level

With knowledge perspective of industrial technology, in this paper we propose fast ranking score decision making model based on Fuzzy integrated TOPSIS approach to determine economic growth rate of manufacturing industry in China. This research focuses on driving effects of China’s productive service industry on manufacturing technology innovation. The research results show that the manufacturer service industry takes a high level of information diffusion for the manufacturing industry. It transmits a large amount of diverse information through the unconstrained relationship with the manufacturing industry, thereby forming the economic network with proposed Fuzzy integrated TOPSIS economy ranking (FITER) model and improve the development level of the manufacturing industry. We evaluate the performance of proposed FITER model by comparing ranking score of different manufacturing industry with different existing decision making mode and demonstrate that proposed model represent best ranking score in comparison to existing approach. Result from data analysis motivates driving effect of production services on the technological innovation of manufacturing and sub-sectors. It is found that the innovation and technological advancement in the production industry of services takes drive the overall expansion level of the business industry, as well as make the manufacturing industry the strongest.

scholarly journals Psychology and interviewing: what direction now in our quest for reliable information?

2011 ◽  
Vol 13 (2) ◽  
pp. 135-144 ◽  
Author(s):  
Gavin E. Oxburgh ◽  
Coral J. Dando
Keyword(s):  
Empirical Research ◽  
Academic Research ◽  
Psychological Theory ◽  
Investigative Interviewing ◽  
Future Directions ◽  
Content Type ◽  
The Impact ◽  
Emergent Theory ◽  
And Training ◽  
Do So

PurposeThe purpose of this paper is to discuss two distinct but interrelated areas, namely witness/victim and suspect interviewing, and to argue that both must continue to evolve, suggest how they might do so, and that this process must be driven by emergent theory and contemporary empirical research.Design/methodology/approachThe paper outlines the impact of psychological theory and empirical research to investigative interviewing in recent decades.FindingsIt is argued that in order to stay ahead of the game, the field of investigative interviewing (suspect and witness) must continue to evolve in such a manner that not only protects and fosters the important practitioner/academic relationship, but also ensures that future directions are driven by empirical research, with recourse to emergent theory.Originality/valueThe paper outlines the impact of psychological theory and empirical research on investigative interviewing and the consequent enhancement of the interviewing of both suspected offenders and witnesses. The paper demonstrates that working closely together academic research can make a difference, and influence law, policy decisions and training guidelines in order to improve practice.

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