Search

This paper provides a systematic review of research works on deterministic scheduling of diffusion furnaces (D-SDF) in the semiconductor manufacturing industry. After our screening process, we have identified 72 research articles published during the period 1992 to 2021 in various journals, conference proceedings, etc. This study proposes various classification schemes to systematically organise all the identified studies and to get micro-level details of D-SDF research. Further, various simple meta-analyses in the form of summary counts and percentages are carried out w.r.t (a) proposed classification schemes, and (b) various parameters such as data source, the maximum number of jobs in the instances, benchmark procedure considered, number of articles published, number of contributed authors over the years, top researchers in terms of number of publications, highly cited articles, publication outlets and publishers. From the detailed review analyses, this study suggests/shows future research opportunities/unexplored research problems considering problem configuration/objective(s)/solution methodologies in D-SDF research. Further, mapping of all references of 72 papers on D-SDF w.r.t. proposed classifications schemes would ease new researchers in D-SDF, in multiple perspectives. Finally, meta-analyses presented based on proposed classification schemes and various parameters, considered related to D-SDF problem, provide many important inferences to related researchers. [ABSTRACT FROM AUTHOR]

This paper investigates whether and how a national level general classification scheme expresses or reflects its creators' government's political stances and priorities. The following two national level general classification schemes were studied and compared: Chinese Library Classification, created by the People's Republic of China (PRC), and the New Classification Scheme for Chinese Libraries, created by the Republic of China (ROC). It is found that a nation's or region's political stances and priorities are expressed or reflected in a national level comprehensive classification through the following four venues: (1) prioritizing classes that indicate a nation's, region's, or party's ideology, governance theory, or long-term policies and goals; (2) prioritizing classes of one's leading political party and/or leaders; putting rivalrous political parties and/or leaders in a lower-level class or making them invisible; (3) putting the territory or history of a rivalrous political entity under one's own political entity to show one is a part of the other and; (4) using terms that express the government's or political party's strong political stances (such as anti-, con-, pro-), or neutralizing political terms to soften one's political stances. In (3) and (4), the classification reflects the political stances of the creator's government. [ABSTRACT FROM AUTHOR]

The recognition of facial expression in images is one of the motional states in the observing forms and is one of the most frequent non-verbal routes in which a person transfers his inner emotional expressions on faces. The recognition of facial expressions in a wide range of fields including psychological and legal studies, animation, robotics, lip-reading, image and video conferencing, communications, telecommunications, and security protection whilst counterterrorism is used to identify individuals as well as human-machine confrontation. The general solution to this problem includes three general steps: images preprocessing, features extraction, and expression classification algorithms. A series of pre-processing steps must be performed to process the area on the face and then detect the expression, that is, a square in the face must be localized while the rest of the image must be removed. Then, Features extraction is used to classify. Each facial expression to a specific category. We divide our data, including images from different expressions, into two parts: training and testing. Different categories have been learned to specify different features that tested thereafter. In recent years, a number of researches has been performed on a facial expression analysis. Even though much progress has been made in this field since the recognition of facial expression with a high accuracy rate is difficult to achieve due to the complexity and variability. In this research article, we noticed that most of researchers are used JAFFE and CK+ databases due the diversification and high accuracy. Nevertheless most of researchers are used PSO, PCA, and LBP features as well as HOG that presented high accuracy. We also noticed that SVM and CNN classification algorithms have been used mostly due to high accuracy and response latency with few errors. [ABSTRACT FROM AUTHOR]

The purpose of this research is to identify and examine documentary series related to demographic issues in the Ecclesiastical Archives of Mérida-Badajoz. To do so, and after contextualizing the concepts related to historical demography, the related series are identified in the different documentary collections (diocesan, cathedral, parish, and military orders). Additionally, a brief guide for the interested researcher will be provided. [ABSTRACT FROM AUTHOR]

A survey focused on 34 specific attributes of service quality in fitness centres was applied to 657 fitness centre clients in the city of Rio de Janeiro, following a stratified sampling process. The article aims to identify the most relevant attributes of service quality, from clients' perspective, necessary for potential future excellence-based classification schemes of fitness centres in Rio de Janeiro. A quartile analysis determined that the most critical attributes, i.e., with greatest average relevance, are related to the following aspects: (i) fitness centre environment, (ii) location and access, (iii) instructors' qualifications and (iv) results of training plans, while the items considered less relevant on average concern the following aspects: (i) additional services provided by the fitness centre, (ii) social interaction promoted by the centre and (iii) administrative employees. There is no similar research on the evaluation of service quality, from users' perspective, in fitness centers in Rio de Janeiro, and there is still no consensus in literature concerning instruments for such purpose and concerning what are the most relevant attributes to customers, when assessing service quality. In accordance, this research is relevant through providing data which are necessary to construct a hierarchical classification of fitness centres in relation to the quality of services provided.

A survey focused on 34 specific attributes of service quality in fitness centres was applied to 657 fitness centre clients in the city of Rio de Janeiro, following a stratified sampling process. The article aims to identify the most relevant attributes of service quality, from clients' perspective, necessary for potential future excellencebased classification schemes of fitness centres in Rio de Janeiro. A quartile analysis determined that the most critical attributes, i.e., with greatest average relevance, are related to the following aspects: (i) fitness centre environment, (ii) location and access, (iii) instructors' qualifications and (iv) results of training plans, while the items considered less relevant on average concern the following aspects: (i) additional services provided by the fitness centre, (ii) social interaction promoted by the centre and (iii) administrative employees. There is no similar research on the evaluation of service quality, from users' perspective, in fitness centers in Rio de Janeiro, and there is still no consensus in literature concerning instruments for such purpose and concerning what are the most relevant attributes to customers, when assessing service quality. In accordance, this research is relevant through providing data which are necessary to construct a hierarchical classification of fitness centres in relation to the quality of services provided. [ABSTRACT FROM AUTHOR]

Copyright of Revista General de Información y Documentación is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract The rock mass deformation modulus, Erm, is an input parameter for most numerical modeling to verify the deformation behavior of rocks due to rock engineering activities within/on it. Among the most common methodologies used for estimating this parameter, empirical correlations based on rock mass classification schemes (e.g., RQD, RMR, GSI, and Q) stand out the most, principally because of their low cost when compared to the other methods. Herein, the main correlations used in practice are evaluated and comparted for 48 different rock quality scenarios, previously characterized and classified according to rock mass classification systems. The results obtained by each of the empirical correlations demonstrated that normalized correlations, that is, based on the ratio of the rock mass and intact rock modulus, Erm/Ei, underestimate the Erm values when compared to those results obtained from not-normalized correlations in the scenarios of better quality rock masses. For poor quality rock mass scenarios, both non-normalized and normalized correlation presented similar results. The correlations proposed by Hoek and Diederichs (2006) and Galera et al. (2007) estimated more central Erm values when compared to the other correlations, for all quality scenarios, while the Mitri et al. (1994) and Sonmez et al. (2006) methods estimated most high and low values of Erm, respectively.

Fundamental knowledge in activity recognition of individuals with motor disorders such as Parkinson's disease (PD) has been primarily limited to detection of steady-state/static tasks (e.g., sitting, standing, walking). To date, identification of non-steady-state locomotion on uneven terrains (stairs, ramps) has not received much attention. Furthermore, previous research has mainly relied on data from a large number of body locations which could adversely affect user convenience and system performance. Here, individuals with mild stages of PD and healthy subjects performed non-steady-state circuit trials comprising stairs, ramp, and changes of direction. An offline analysis using a linear discriminant analysis (LDA) classifier and a Long-Short Term Memory (LSTM) neural network was performed for task recognition. The performance of accelerographic and gyroscopic information from varied lower/upper-body segments were tested across a set of user-independent and user-dependent training paradigms. Comparing the F1 score of a given signal across classifiers showed improved performance using LSTM compared to LDA. Using LSTM, even a subset of information (e.g., feet data) in subject-independent training appeared to provide F1 score > 0.8. However, employing LDA was shown to be at the expense of being limited to using a subject-dependent training and/or biomechanical data from multiple body locations. The findings could inform a number of applications in the field of healthcare monitoring and developing advanced lower-limb assistive devices by providing insights into classification schemes capable of handling non-steady-state and unstructured locomotion in individuals with mild Parkinson's disease. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has posed a significant global health threat since January 2020. Policies to reduce human mobility have been recognized to effectively control the spread of COVID-19; although the relationship between mobility, policy implementation, and virus spread remains contentious, with no clear pattern for how countries classify each other, and determine the destinations to- and from which to restrict travel. In this rapid review, we identified country classification schemes for high-risk COVID-19 areas and associated policies which mirrored the dynamic situation in 2020, with the aim of identifying any patterns that could indicate the effectiveness of such policies. We searched academic databases, including PubMed, Scopus, medRxiv, Google Scholar, and EMBASE. We also consulted web pages of the relevant government institutions in all countries. This rapid review's searches were conducted between October 2020 and December 2021. Web scraping of policy documents yielded additional 43 country reports on high-risk area classification schemes. In 43 countries from which relevant reports were identified, six issued domestic classification schemes. International classification schemes were issued by the remaining 38 countries, and these mainly used case incidence per 100,000 inhabitants as key indicator. The case incidence cut-off also varied across the countries, ranging from 20 cases per 100,000 inhabitants in the past 7 days to more than 100 cases per 100,000 inhabitants in the past 28 days. The criteria used for defining high-risk areas varied across countries, including case count, positivity rate, composite risk scores, community transmission and satisfactory laboratory testing. Countries either used case incidence in the past 7, 14 or 28 days. The resulting policies included restrictions on internal movement and international travel. The quarantine policies can be summarized into three categories: (1) 14 days self-isolation, (2) 10 days self-isolation and (3) 14 days compulsory isolation.

Research Aims: The Freemium business model is becoming increasingly prominent in the current digital economy. In the mobile game market, total revenue from free to download apps is overtaking those from paid apps. The purpose of this article is to propose a taxonomy that examines and categorises the various types of Freemium business models. Design/methodology/approach: This study uses the qualitative approach of logical partitioning to generate a Freemium business model's taxonomy through systematic observation of the existing business models. Research Findings: The findings identify advertisement and microtransaction as two primary revenue sources for Freemium business models. The taxonomy also reveals different types of in-app purchases, the most dominant Freemium business model in the mobile game market. Further discussion connects the taxonomy to related issues such as user archetypes and 'user flows'. Theoretical Contribution/Originality: This paper conceptualises a novel taxonomy of business model integrating various research streams and differentiating types of freemium business model. This paper also extends the existing archetypes of Freemium users by adding new categories, namely Remoras and Barnacles, to differentiate free users. Finally, this paper proposes a framework of user flows between the free and the paying state, arguing for a nonlinear flow. Research limitation/Implications: The taxonomy addresses freemium business models in the mobile game market. Application of the taxonomy in a broader context will require further study. [ABSTRACT FROM AUTHOR]

The site conditions play an important role on ground motion indicated by observed data of strong earthquakes and seismic investigation. Currently it is well recognized around the world for classifying sites according to site conditions and stipulating design ground motion parameters for different sites regarding seismic design code from the perception of engineering seismology, as well as an important research content of earthquake geotechnical engineering. It is reviewed and summarized in the paper for the research process of site classification of the seismic code home and abroad. Meanwhile, analysis and comment are performed for the site classification indexes. In addition, it is launched to review and compare the site classification schemes of different countries by taking the representative ones as China, the United States, Europe, Japan, Turkey, Chile, Nepal, Iran, South Korea, Australia and New Zealand. The keynote is to focus on the problems of site classification in the current seismic design code of China based on this, and proposed several key issues that need to be studied on site classification in the future. The results of these analyses will bring some added value for the reference of researchers who are interested in site classification. [ABSTRACT FROM AUTHOR]

Copyright of Geologia USP: Série Científica is the property of Geologia USP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fundamental knowledge in activity recognition of individuals with motor disorders such as Parkinson’s disease (PD) has been primarily limited to detection of steady-state/static tasks (e.g., sitting, standing, walking). To date, identification of non-steady-state locomotion on uneven terrains (stairs, ramps) has not received much attention. Furthermore, previous research has mainly relied on data from a large number of body locations which could adversely affect user convenience and system performance. Here, individuals with mild stages of PD and healthy subjects performed non-steady-state circuit trials comprising stairs, ramp, and changes of direction. An offline analysis using a linear discriminant analysis (LDA) classifier and a Long-Short Term Memory (LSTM) neural network was performed for task recognition. The performance of accelerographic and gyroscopic information from varied lower/upper-body segments were tested across a set of user-independent and user-dependent training paradigms. Comparing the F1 score of a given signal across classifiers showed improved performance using LSTM compared to LDA. Using LSTM, even a subset of information (e.g., feet data) in subject-independent training appeared to provide F1 score > 0.8. However, employing LDA was shown to be at the expense of being limited to using a subject-dependent training and/or biomechanical data from multiple body locations. The findings could inform a number of applications in the field of healthcare monitoring and developing advanced lower-limb assistive devices by providing insights into classification schemes capable of handling non-steady-state and unstructured locomotion in individuals with mild Parkinson’s disease.

The rock mass deformation modulus, Erm, is an input parameter for most numerical modeling to verify the deformation behavior of rocks due to rock engineering activities within/on it. Among the most common methodologies used for estimating this parameter, empirical correlations based on rock mass classification schemes (e.g., RQD, RMR, GSI, and Q) stand out the most, principally because of their low cost when compared to the other methods. Herein, the main correlations used in practice are evaluated and comparted for 48 different rock quality scenarios, previously characterized and classified according to rock mass classification systems. The results obtained by each of the empirical correlations demonstrated that normalized correlations, that is, based on the ratio of the rock mass and intact rock modulus, Erm/Ei, underestimate the Erm values when compared to those results obtained from notnormalized correlations in the scenarios of better quality rock masses. For poor quality rock mass scenarios, both non-normalized and normalized correlation presented similar results. The correlations proposed by Hoek and Diederichs (2006) and Galera et al. (2007) estimated more central Erm values when compared to the other correlations, for all quality scenarios, while the Mitri et al. (1994) and Sonmez et al. (2006) methods estimated most high and low values of Erm, respectively. [ABSTRACT FROM AUTHOR]

Throughout the history of science, different knowledge areas have collaborated to overcome major research challenges. The task of associating a researcher with such areas makes a series of tasks feasible such as the organization of digital repositories, expertise recommendation and the formation of research groups for complex problems. In this article, we propose a simple yet effective automatic classification model that is capable of categorizing research expertise according to a knowledge area classification scheme. Our proposal relies on discriminatory evidence provided by the title of academic works, which is the minimum information capable of relating a researcher to its knowledge area. Our experiments show that using supervised machine learning methods trained with manually labeled information, it is possible to produce effective classification models. [ABSTRACT FROM AUTHOR]

Abstract Background As implementation science advances, the number of interventions to promote the translation of evidence into healthcare, health systems, or health policy is growing. Accordingly, classification schemes for these knowledge translation (KT) interventions have emerged. A recent scoping review identified 51 classification schemes of KT interventions to integrate evidence into healthcare practice; however, the review did not evaluate the quality of the classification schemes or provide detailed information to assist researchers in selecting a scheme for their context and purpose. This study aimed to further examine and assess the quality of these classification schemes of KT interventions, and provide information to aid researchers when selecting a classification scheme. Methods We abstracted the following information from each of the original 51 classification scheme articles: authors’ objectives; purpose of the scheme and field of application; socioecologic level (individual, organizational, community, system); adaptability (broad versus specific); target group (patients, providers, policy-makers), intent (policy, education, practice), and purpose (dissemination versus implementation). Two reviewers independently evaluated the methodological quality of the development of each classification scheme using an adapted version of the AGREE II tool. Based on these assessments, two independent reviewers reached consensus about whether to recommend each scheme for researcher use, or not. Results Of the 51 original classification schemes, we excluded seven that were not specific classification schemes, not accessible or duplicates. Of the remaining 44 classification schemes, nine were not recommended. Of the 35 recommended classification schemes, ten focused on behaviour change and six focused on population health. Many schemes (n = 29) addressed practice considerations. Fewer schemes addressed educational or policy objectives. Twenty-five classification schemes had broad applicability, six were specific, and four had elements of both. Twenty-three schemes targeted health providers, nine targeted both patients and providers and one targeted policy-makers. Most classification schemes were intended for implementation rather than dissemination. Conclusions Thirty-five classification schemes of KT interventions were developed and reported with sufficient rigour to be recommended for use by researchers interested in KT in healthcare. Our additional categorization and quality analysis will aid in selecting suitable classification schemes for research initiatives in the field of implementation science.

Background Practices in somatic variant interpretation and classification vary between Canadian clinical molecular diagnostic laboratories, and understanding of current practices and perspectives is limited. To define gaps and future directions, including consensus guideline development, the Somatic Curation and Interpretation Across Laboratories (social) project examined the present state of somatic variant interpretation in Canadian molecular laboratories, including testing volumes and methods, data sources and evidence criteria, and application of published classification guidelines. Methods: Individuals who perform somatic variant interpretation in Canadian centres were invited to participate in an online survey. Invitees included laboratory directors (certified as Fellows of the Canadian College of Medical Geneticists or the American College of Medical Geneticists), md or md and phd molecular pathologists, and other phd experts, including phd specialists in variant annotation or bioinformatics. Current testing methods, volumes, and platforms in next-generation sequencing, use of variant annotation resources and evidence criteria, and preference for variant classification schemes were evaluated. Results: Responses were received from 37 participants in 8 provinces. A somatic variant classification scheme jointly supported by the Association for Molecular Pathology (amp), the American Society of Clinical Oncology (asco), and the College of American Pathologists (cap) was used by 47% of respondents; an alternative guideline or a combination of published guidelines was used by 35% of respondents. The remaining 18% did not use a published scheme. Only 41% of respondents used a published scheme without alteration. Although all respondents indicated that there is a need for Canadian laboratories to adopt a somatic variant classification guideline, only 38% of respondents felt that it should be mandatory to adopt the amp/asco/cap-endorsed guideline. Conclusions: Data from the social project identified high variability in current practice, yet strong support for standardization of solid-tumour somatic variant interpretation across Canadian institutions. Aligning classification methods will reduce variation in cross-institutional classification and reporting practices, aiding in consistent practice nationwide. [ABSTRACT FROM AUTHOR]

MXenes are a class of 2D materials that include layered transition metal carbides, nitrides, and carbonitrides. Since their inception in 2011, they have garnered significant attention due to their diverse compositions, unique structures, and extraordinary properties, such as high specific surface areas and excellent electrical conductivity. This versatility has opened up immense potential in various fields, catalyzing a surge in MXene research and leading to note worthy advancements. This review offers an in-depth overview of the evolution of MXenes over the past 5 years, with an emphasis on synthetic strategies, structure-property relationships, and technological prospects. A classification scheme for MXene structures based on entropy is presented and an updated summary of the elemental constituents of the MXene family is provided, as documented in recent literature. Delving into the microscopic structure and synthesis routes, the intricate structure-property relationships are explored at the nano/micro level that dictate the macroscopic applications of MXenes. Through an extensive review of the latest representative works, the utilization of MXenes in energy, environmental, electronic, and biomedical fields is showcased, offering a glimpse into the current technological bottlenecks, such asstability, scalability, and device integration. Moreover, potential pathways for advancing MXenes toward next-generation technologies are highlighted., (© 2023 Wiley-VCH GmbH.)

Three-year (2020−2022) raindrop size distribution (DSD) measurements from a second-generation PARSIVEL disdrometer deployed at Zhaosu, which is located in the Tianshan Mountains of China, are analyzed to investigate the seasonal variability of microphysical characteristics of two types of rainfall. Rainfall at Zhaosu is classified as stratiform rainfall and convective rainfall in the normalized intercept parameter–median volume diameter (log 10 N w – D 0) and log 10 N w –mass-weighted mean diameter (log 10 N w – D m) spaces, respectively. Both stratiform rainfall and convective rainfall samples in the log 10 N w – D 0 space are more than three times those in the log 10 N w – D m space, accompanied by smaller mean rainfall rate (R). Rainfall in summer (spring) has the lowest (highest) concentration of small-size raindrops, while rainfall in fall (summer) has the lowest (highest) concentration of mid- and large-size raindrops, accompanied by the largest (smallest) mean D m and D 0 values and the smallest (largest) mean log 10 N w values in summer (spring). Convective rainfall exhibits more significant seasonal variation in microphysical parameters and DSD than stratiform rainfall, whether in the log 10 N w – D 0 space or the log 10 N w – D m space. The convective rainfall in spring is more like maritime cluster, whereas that in summer is more like continental cluster in the log 10 N w – D m space. Furthermore, in the log 10 N w – D 0 and log 10 N w – D m spaces, localized relationships of radar reflectivity factor – R (Z–R) and shape parameter – slope parameter (μ– ∧) are derived across seasons for different rainfall types. The results indicate that there are significant seasonal variations in the microphysical characteristics of rainfall in the Tianshan Mountains of China for the two rainfall types. This study further emphasizes that different classification schemes for rainfall types can lead to significant differences in the characteristics of DSD, Z–R , and μ– ∧ relationships for different rainfall types. • This work concentrated on seasonal variation of microphysical characteristics for different rainfall types in the Tianshan Mountains of China. • Different classification schemes for rainfall types can lead to significant differences in the characteristics of DSD, Z–R , and μ– ∧ relationships for different rainfall types. • An appropriate classification scheme for rainfall types is crucial. [ABSTRACT FROM AUTHOR]

Background: As implementation science advances, the number of interventions to promote the translation of evidence into healthcare, health systems, or health policy is growing. Accordingly, classification schemes for these knowledge translation (KT) interventions have emerged. A recent scoping review identified 51 classification schemes of KT interventions to integrate evidence into healthcare practice; however, the review did not evaluate the quality of the classification schemes or provide detailed information to assist researchers in selecting a scheme for their context and purpose. This study aimed to further examine and assess the quality of these classification schemes of KT interventions, and provide information to aid researchers when selecting a classification scheme.Methods: We abstracted the following information from each of the original 51 classification scheme articles: authors' objectives; purpose of the scheme and field of application; socioecologic level (individual, organizational, community, system); adaptability (broad versus specific); target group (patients, providers, policy-makers), intent (policy, education, practice), and purpose (dissemination versus implementation). Two reviewers independently evaluated the methodological quality of the development of each classification scheme using an adapted version of the AGREE II tool. Based on these assessments, two independent reviewers reached consensus about whether to recommend each scheme for researcher use, or not.Results: Of the 51 original classification schemes, we excluded seven that were not specific classification schemes, not accessible or duplicates. Of the remaining 44 classification schemes, nine were not recommended. Of the 35 recommended classification schemes, ten focused on behaviour change and six focused on population health. Many schemes (n = 29) addressed practice considerations. Fewer schemes addressed educational or policy objectives. Twenty-five classification schemes had broad applicability, six were specific, and four had elements of both. Twenty-three schemes targeted health providers, nine targeted both patients and providers and one targeted policy-makers. Most classification schemes were intended for implementation rather than dissemination.Conclusions: Thirty-five classification schemes of KT interventions were developed and reported with sufficient rigour to be recommended for use by researchers interested in KT in healthcare. Our additional categorization and quality analysis will aid in selecting suitable classification schemes for research initiatives in the field of implementation science. [ABSTRACT FROM AUTHOR]

This article aims to enhance fundamental conceptualisation in performance measurement through the development of a standard conceptual typology of the field. Performance measurement is a common phenomenon in the worldwide public sector, and one that has attracted substantial academic attention. However, analysis has been hindered by confusing and inconsistent terminology, and a lack of clear and explicit classification schemes. The proposed typology is based on five explicit design considerations and threefundamenta divisionis. The typology produced has fourelements: levels;measures;targets; andactuals. Theseelementsrelate to the nature, specific aspect and state of performance phenomena. It is likely that a standard conceptual approach will have benefits for academic analysis, by clarifying language and conceptual definitions. It is also likely to have beneficial practical implications. [ABSTRACT FROM AUTHOR]