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1 |
Data Driven Robust Optimization for Handling Uncertainty in Supply Chain Planning Models
بهینه سازی قوی مبتنی بر داده ها برای مدیریت عدم قطعیت در مدل های برنامه ریزی زنجیره تامین-2021 While addressing supply chain planning under uncertainty, Robust Optimization (RO) is regarded as an efficient and tractable method. As RO involves calculation of several statistical moments or maximum / minimum values involving the objective functions under realizations of these uncertain parameters, the accuracy of this method significantly depends on the efficient techniques to sample the uncertainty parameter space with limited amount of data. Conventional sampling techniques, e.g. box/budget/ellipsoidal, work by sampling the uncertain parameter space inefficiently, often leading to inaccuracies in such estimations. This paper proposes a methodology to amalgamate machine learning and data analytics with RO, thereby making it data-driven. A novel neuro fuzzy clustering mechanism is implemented to cluster the uncertain space such that the exact regions of uncertainty are optimally identified. Subsequently, local density based boundary point detection and Delaunay triangulation based boundary construction enable intelligent Sobol based sampling to sample the uncertain parameter space more accurately. The proposed technique is utilized to explore the merits of RO towards addressing the uncertainty issues of product demand, machine uptime and production cost associated with a multiproduct, and multisite supply chain planning model. The uncertainty in supply chain model is thoroughly analysed by carefully constructing examples and its case studies leading to large scale mixed integer linear and nonlinear programming problems which were efficiently solved in GAMS framework. Demonstration of efficacy of the proposed method over the box, budget and ellipsoidal sampling method through comprehensive analysis adds to other highlights of the current work. Keywords: Uncertainty Modelling | Supply chain Management | Data driven Robust Optimization | Neuro Fuzzy Clustering | Multi-Layered Perceptron |
مقاله انگلیسی |
2 |
Automated Vision-Based Microsurgical Skill Analysis in Neurosurgery Using Deep Learning: Development and Preclinical Validation
تجزیه و تحلیل خودکار مهارتهای میکروجراحی مبتنی بر بینایی در جراحی مغز و اعصاب با استفاده از یادگیری عمیق: توسعه و اعتبار پیش بالینی-2021 - BACKGROUND/OBJECTIVE: Technical skill acquisition
is an essential component of neurosurgical training.
Educational theory suggests that optimal learning and
improvement in performance depends on the provision of
objective feedback. Therefore, the aim of this study was to
develop a vision-based framework based on a novel representation of surgical tool motion and interactions
capable of automated and objective assessment of microsurgical skill.
- METHODS: Videos were obtained from 1 expert, 6 intermediate, and 12 novice surgeons performing arachnoid dissection in a validated clinical model using a standard operating microscope. A mask region convolutional neural network framework was used to segment the tools present within the operative field in a recorded video frame. Tool motion analysis was achieved using novel triangulation metrics. Performance of the framework in classifying skill levels was evaluated using the area under the curve and accuracy. Objective measures of classifying the surgeons skill level were also compared using the ManneWhitney U test, and a value of P < 0.05 was considered statistically significant. - RESULTS: The area under the curve was 0.977 and the accuracy was 84.21%. A number of differences were found, which included experts having a lower median dissector velocity (P [ 0.0004; 190.38 mse1 vs. 116.38 mse1), and a smaller inter-tool tip distance (median 46.78 vs. 75.92; P [ 0.0002) compared with novices. - CONCLUSIONS: Automated and objective analysis of microsurgery is feasible using a mask region convolutional neural network, and a novel tool motion and interaction representation. This may support technical skills training and assessment in neurosurgery. Key words: Artificial intelligence | Computer vision | Convolutional neural network | Mask RCNN | Microsurgery | Motion-analysis | Neurosurgery |
مقاله انگلیسی |
3 |
Combining conventional and participatory approaches to identify and prioritise management and health-related constraints to smallholder pig production in San Simon, Pampanga, Philippines
تلفیق رویکردهای مرسوم و مشارکتی برای شناسایی و اولویت بندی مدیریت و محدودیتهای مرتبط با سلامتی در تولید خوک های خرده فروش در سن سیمون ، پامبانگا ، فیلیپین-2020 Pork is the main meat produced and consumed in the Philippines. The majority of pigs are raised by smallholders
who experience a range of constraints to their pig production. This study presents the findings of the first part of
an overarching project that used an Ecohealth approach and aimed to improve the production and competitiveness
of the smallholder pig system in an area of the Philippines. A participatory approach was embraced,
combining conventional and participatory epidemiology methods followed by a stakeholder discussion. The first
aim was to identify management and health-related constraints to pig production among smallholder famers in
San Simon, Pampanga, Philippines. The second aim was for the project team and stakeholders to jointly
prioritise activities for the immediate future to address these constraints. Key management and health-related
constraints identified included inadequate water supply to pigs, particularly lactating and gestating sows, and a
range of feeding-related issues. Diarrhoea was recognised as the disease syndrome of highest priority and limited
record keeping meant that farmers were unable to assess the productivity and profitability of their pig farming
enterprises. Actions jointly prioritised by stakeholders and the project team were: the appointment of a project
coordinator within each barangay; conduct two sets of seminars, the first covering water and nutrition and the
second piglet management and diarrhoea, to be delivered by technical experts but with farmer “trusted sources”
also sharing their experiences; development of easily understandable leaflets and posters covering key technical
information; promotion of nipple drinkers attached to five-gallon water containers and creep boxes for piglets,
and conduct of a record keeping workshop with a small group of innovative farmers to develop a useful and
usable tool for record keeping. The use of multiple approaches to data-gathering enabled triangulation of study
findings. Without any one of these components the understanding of the pig production system would have been
less complete and it is possible that the proposed actions would not have been as well-tailored to the needs of the
farmers. The participatory approach, in particular the stakeholder discussion, provided the opportunity to
embrace the “deciding together” and “acting together” stances of participation rather than the lower “information
giving” stance, thereby giving stakeholders greater ownership of the future activities of the overarching
project and beyond. Keywords: Philippines | Pig | Smallholder | Constraints | Participatory epidemiology | Ecohealth |
مقاله انگلیسی |
4 |
Gotong Royong as social capital to overcome micro and small enterprises capital difficulties
Gotong Royong به عنوان سرمایه اجتماعی برای غلبه بر مشکلات سرمایه ای خرد و کوچک-2020 One of the micro and small enterprises (MSEs) main problem is business capital. Cash flow shortage often in- terrupts business development. This difficulty is due to the limited ability in meeting the requirements to access sources of capital. The development of micro and small enterprises using the culture of the local community is a way to overcome this issue. Asians generally have the perception of Gotong Royong (which means mutual aid in English) as a form of collectivism. This study comes from the gap whether Gotong Royong serves as social capital to overcome the difficulties of micro and small enterprises’ capital. Therefore, the purpose of this study is to find out the perception of owners of MSEs toward the application of Gotong Royong culture, which suggests how to overcome the business capital difficulties in reality. The qualitative method was applied to investigate the in- formants with triangulation process to validate the result accuracy. The results of this study show that MSEs owners build their businesses with the family culture, which upholds a Gotong Royong character. Small: based on the field data processing, the second result reveals that the social capital of the community in the form of Gotong Royong culture could overcome capital constraints in micro and small enterprises. Similarly, the Gotong Royong culture applied in business could reduce the capital requirement that should be prepared by micro and small entrepreneurs. The contribution of this research is for business owners so that they do not lose the character of mutual cooperation and to provide input for the government to support family businesses that still rely on these characters by giving light funding assistance. However, this research must be developed further in a broader business scale with different informant profiles so that the results will be more comprehensive. Keywords: Social capital | Gotong Royong | MSEs | Capital | Sustainable business | Management | Research and development | Social networks | Social policy |
مقاله انگلیسی |
5 |
Incentivizing green entrepreneurship: A proposed policy prescription (a study of entrepreneurial insights from an emerging economy perspective)
تحریک کارآفرینی سبز: نسخه پیشنهادی سیاست (مطالعه بینش کارآفرینی از منظر اقتصاد نوظهور)-2020 This study undertakes an in-depth analysis of green and traditional entrepreneurs’ experiences using a multiple case study research methodology along with triangulation and coding techniques, identifying the specific drivers of ecopreneurship given the constraints and challenges faced by them. This study maps this analysis to Resource Based View’s (RBV) theoretical construct and argues that ecopreneurs navigate and negotiate their enterprise development constraints through combinations of personal at- tributes and innovative mechanisms rendering tangible and intangible economic, environmental and social gains. It further proposes a policy framework to incentivise, assist and accelerate ecopreneurs’ efforts in achieving scalability in an uncertain external ecosystem. This proposed framework would also address the conflict between monetisation of innovations and environmental concerns.© 2020 Elsevier Ltd. All rights reserved. Keywords: Green | Entrepreneurship | Ecopreneurship | Environment | Resource based view theory |
مقاله انگلیسی |
6 |
An Expert System Gap Analysis and Empirical Triangulation of Individual Differences, Interventions, and Information Technology Applications in Alertness of Railroad Workers
تجزیه و تحلیل شکاف سیستم خبره و مثلث تجربی تفاوت های فردی ، مداخلات و کاربردهای فناوری اطلاعات در هوشیاری کارگران راهآهن-2019 In this abstract we would like to provide some exciting concrete information including the
article’s main impact and significance on expert and intelligent systems. The main impact is that
the PTC expert intelligent system fills in the gaps between the human and software decision
making processes. This gap analysis is analyzed via empirical triangulation of rail worker data
collected from its groups, individuals and the rail industry itself. We utilize an expert intelligent
system PTC information technology application to both measure and to improve the alertness of
the groups and workers in order to improve the overall safety of the railways through reduced
human errors and failures to prevent accidents. Many individual differences in alertness among
military, railroad, and other industry workers stem from a lack of sufficient sleep. This continues
to be a concern in the railroad industry, even with the implementation of positive train control
(PTC) expert system technology. Information technology aids such as PTC cannot prevent all
accidents, and errors and failures with PTC may occur. Furthermore, drug interventions are a
short-term solution for improving alertness. This study investigated the effect of sleep
deprivation on the alertness of railroad signalmen at work, individual differences in alertness,
and the information technology available to improve alertness. We investigated various
information and communication technology control systems that can be used to maintain
operational safety in the railroad industry in the face of incompatible circadian rhythms due to
irregular hours, weekend work, and night operations. To fully explain individual differences after
the adoption of technology, our approach posits the necessary parameters that one must consider
for reason-oriented action, sequential updating, feedback, and technology acceptance in a unified
model. This triangulation can help manage workers by efficiently increasing their productivity
and improving their health. In our analysis we used R statistical software and Tableau. To test
our theory, we issued an Apple watch to a locomotive engineer. The perceived usefulness,
perceived ease of use, and actual use he reported led to an analysis of his sleep patterns that
eventually ended in his adoption of a sleep apnea device and an improvement in his alertness and
effectiveness. His adoption of the technology also resulted in a decrease in his use of chemical
interventions to increase his alertness. Our model shows that the alertness of signalmen can be
predicted. Therefore, we recommend that the alertness of all railroad workers be predicted given
the safety limitations of PTC. Keywords : Sleep Deprivation | Fatigue | Stress | Expert System | Alertness | Empirical Analysis |
مقاله انگلیسی |
7 |
A generalizable deep learning framework for localizing and characterizing acoustic emission sources in riveted metallic panels
یک چارچوب یادگیری عمیق قابل تعمیم برای بومی سازی و توصیف منابع انتشار صوتی در صفحه های فلزی پرچین-2019 This paper introduces a deep learning-based framework to localize and characterize acoustic
emission (AE) sources in plate-like structures that have complex geometric features,
such as doublers and rivet connections. Specifically, stacked autoencoders are
pre-trained and utilized in a two-step approach that first localizes AE sources and then
characterizes them. To achieve these tasks with only one AE sensor, the paper leverages
the reverberation patterns, multimodal characteristics, and dispersive behavior of AE
waveforms. The considered waveforms include AE sources near rivet connections, on the
surface of the plate-like structure, and on its edges. After identifying AE sources that occur
near rivet connections, the proposed framework classifies them into four source-to-rivet
distance categories. In addition, the paper investigates the sensitivity of localization results
to the number of sensors and compares their localization accuracy with the triangulation
method as well as machine learning algorithms, including support vector machine (SVM)
and shallow neural network. Moreover, the generalization of the deep learning approach
is evaluated for typical scenarios in which the training and testing conditions are not identical.
To train and test the performance of the proposed approach, Hsu-Nielsen pencil lead
break tests were carried out on two identical aluminum panels with a riveted stiffener. The
results demonstrate the effectiveness of the deep learning-based framework for singlesensor,
AE-based structural health monitoring of plate-like structures Keywords: Acoustic emission | Deep learning | Edge reflection | Reverberation patterns | Plate-like structures | Pattern recognition | Stacked autoencoders | uided ultrasonic waves | Machine learning | Structural health monitoring |
مقاله انگلیسی |
8 |
Blockchain: How shipping industry is dealing with the ultimate technological leap
بلاکچین : چگونه صنعت حمل و نقل با جهش نهایی فناوری روبرو است-2019 Despite its historical resilience to innovation, several novel technologies (e.g. IoT, AIS data, and automation) have recently been introduced in the maritime sector: the majority of them represents incremental changes in respect to current practice. Nevertheless, a few of these novel solutions could represent radical game changers for the whole shipping business. Among the latter category, blockchain registers a particular role, given the possibility for smoothening administrative problems, providing new ways to achieve secure and frictionless transactions at a global level. Despite the importance of such innovation, most of the published studies have just focused on technical aspects, while the adoption and implementation processes are far to be clarified since there is not a clear understanding on the potential effects of blockchain on shipping and logistics actors, especially at local level. The proposed study aims at filling this gap, providing insights that might help to better understand: i) which are the actors that impact the most on the blockchain implementation (and related potential frictions), and ii) the difference among alternative initiatives currently present on the market. In order to achieve these twofold aim, the study uses a triangulation approach, mixing literature and media reports research with both web-based research on main initiative characteristics and expert opinions. The proposed study defines that regulators and public authorities might potentially represent the main barrier to the full implementation of the block chain technology, especially due to a missing market standard. |
مقاله انگلیسی |
9 |
A generalizable deep learning framework for localizing and characterizing acoustic emission sources in riveted metallic panels
یک چارچوب یادگیری عمیق قابل تعمیم برای محلی سازی و توصیف منابع انتشار صوتی در پانل های فلزی پرچین-2019 This paper introduces a deep learning-based framework to localize and characterize acoustic
emission (AE) sources in plate-like structures that have complex geometric features,
such as doublers and rivet connections. Specifically, stacked autoencoders are
pre-trained and utilized in a two-step approach that first localizes AE sources and then
characterizes them. To achieve these tasks with only one AE sensor, the paper leverages
the reverberation patterns, multimodal characteristics, and dispersive behavior of AE
waveforms. The considered waveforms include AE sources near rivet connections, on the
surface of the plate-like structure, and on its edges. After identifying AE sources that occur
near rivet connections, the proposed framework classifies them into four source-to-rivet
distance categories. In addition, the paper investigates the sensitivity of localization results
to the number of sensors and compares their localization accuracy with the triangulation
method as well as machine learning algorithms, including support vector machine (SVM)
and shallow neural network. Moreover, the generalization of the deep learning approach
is evaluated for typical scenarios in which the training and testing conditions are not identical.
To train and test the performance of the proposed approach, Hsu-Nielsen pencil lead
break tests were carried out on two identical aluminum panels with a riveted stiffener. The
results demonstrate the effectiveness of the deep learning-based framework for singlesensor,
AE-based structural health monitoring of plate-like structures. Keywords: Acoustic emission | Deep learning | Edge reflection | Reverberation patterns | Plate-like structures | Pattern recognition | Stacked autoencoders | Guided ultrasonic waves | Machine learning | Structural health monitoring |
مقاله انگلیسی |
10 |
Strengthening stakeholder buy-in and engagement for successful exploration and installation: A case study of the development of an area-wide, evidence-based prevention and early intervention strategy
استحکام بخشیدن به خرید و مشغولیت ذی نفع برای بررسی و راه اندازی موفق: یک مطالعه موردی روی توسعه یک جلوگیری گسترده و مبتنی بر شواهد و راهبرد مداخله قبلی-2018 Background
The implementation of evidence-based programmes (EBPs) designed to improve outcomes for children and young people and prevent disadvantage is an increasingly important international policy imperative. However, the integration of EBPs into existing service settings and systems is a complex and multifaceted undertaking.
Methods
A process evaluation was conducted to appraise the design and development of a large-scale, area-based, prevention and early intervention initiative. This initiative, called Youngballymun, consisted of five service strategies comprising a range of EBPs (e.g. the Incredible Years Programme, Highscope) targeted at children and young people and their families (from birth to 20 years). The initiative was designed to promote the development, adoption and implementation of EBPs within routine children and youth services in a disadvantaged urban area in the Republic of Ireland. The analytical approach involved the systematic analysis and triangulation of data obtained from relevant documentation (e.g. programme manuals, meeting minutes), as well as a series of one-to-one interviews (n = 27) and six group discussions with key stakeholders (n = 29).
Results
Adopting aspects of an implementation stages framework (Fixsen, Naoom, Blase, & Friedman, 2005), we examined the key implementation stages of exploration and installation. Data gathering and needs assessment and strategic organisational development played an important role in implementation. However, resistance to innovation amongst local service providers emerged as a major challenge to implementation. Factors identified as crucial to overcoming this challenge and promoting stakeholder buy-in for innovation included: encouraging and supporting stakeholder engagement; and adopting a flexible approach to implementation planning.
Conclusion
Generating buy-in amongst stakeholders is central to ensuring a fit between innovative programmes and practices and the systems in which they are to be embedded. Some key lessons, such as the need for the active involvement of community-based service providers in the planning process at the earliest stages of implementation, are identified. The kinds of implementation strategies that may be used to address challenges to practice change and innovation, particularly stakeholder responsiveness to, and perceived compatibility of, EBPs, are discussed.
keywords: Implementation |Implementation stages |Intervention appropriateness |Implementation strategies |Stakeholder buy-in |Evidence-based programmes |
مقاله انگلیسی |