scholarly journals Evaluating Research Trends from Journal Paper Metadata, Considering the Research Publication Latency

Mathematics ◽  
2022 ◽  
Vol 10 (2) ◽  
pp. 233
Author(s):  
Christian-Daniel Curiac ◽  
Ovidiu Banias ◽  
Mihai Micea
Keyword(s):  
Language Processing ◽  
Time Lag ◽  
Evaluation Process ◽  
Research Trends ◽  
Trend Detection ◽  
Research Trend ◽  
Research Publication ◽  
Journal Paper ◽  
One Year

Investigating the research trends within a scientific domain by analyzing semantic information extracted from scientific journals has been a topic of interest in the natural language processing (NLP) field. A research trend evaluation is generally based on the time evolution of the term occurrence or the term topic, but it neglects an important aspect—research publication latency. The average time lag between the research and its publication may vary from one month to more than one year, and it is a characteristic that may have significant impact when assessing research trends, mainly for rapidly evolving scientific areas. To cope with this problem, the present paper is the first work that explicitly considers research publication latency as a parameter in the trend evaluation process. Consequently, we provide a new trend detection methodology that mixes auto-ARIMA prediction with Mann–Kendall trend evaluations. The experimental results in an electronic design automation case study prove the viability of our approach.

EVALUASI PROGRAM/PROYEK PENGEMBANGAN KAWASAN EKONOMI KHUSUS SEI MANGKE DALAM RANGKA PELAKSANAAN KEBIJAKAN MP3EI 2011-2025 DI KORIDOR EKONOMI SUMATERA

2018 ◽  
Vol 6 (1) ◽  
Author(s):  
Firrean Firrean
Keyword(s):  
Local Government ◽  
Evaluation Process ◽  
Spatial Arrangement ◽  
Policy Program ◽  
Evaluative Research ◽  
Policy Optimization ◽  
Economic Zones ◽  
North Sumatra

Special Economic Zones (SEZ) is a region with certain limits within the jurisdiction of Indonesia which is set to perform economic functions and obtain certain facilities. One SEZ developed in North Sumatra Province and included in the National Strategic Area (KSN) Medan - Binjai - Deli Serdang - Karo is SEZ Sei Mangke. SEZ Sei Mangke is defined in PP 29 of 2012 on 27 February 2012 and is the first KEK in Indonesia which was inaugurated its operation by President Joko Widodo on January 27, 2015. KSN Mebidangro itself is an area of priority spatial arrangement because it has a very important influence nationally against state sovereignty, defense and state security, economic, social, cultural, and / or environment, including areas designated as world heritage. This research is an evaluative research intended to find out the end of a policy program in order to determine recommendation of last policy by using CIPO model which includes four stages: (1) context, (2) input, (3) process, and (4) output. The research method used is case study by applying qualitative research that aims to make an accurate interpretation of the characteristics of the object under study. Findings on the evaluation context indicate that the program is generally running well, but some aspects of synergy and policy optimization as well as financing support from central and local government need to be improved. In the input evaluation, and evaluation process some aspects need to be improved because the findings show the weakness of some aspects is the result of lack of synergy and optimization of policy and support from local government. Interesting from the evaluation of ouput is that with some weaknesses in the input and process components, it turns out the evaluation findings ouput show Seek Mangke SEZ development can still run well. The recommendation of this research is to improve the quality of policy synergy / program of SEZ Seek development by improving several aspects that are categorized in each stage of evaluation

scholarly journals Cancer Research Trend Analysis Based on Fusion Feature Representation

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 338
Author(s):  
Jingqiao Wu ◽  
Xiaoyue Feng ◽  
Renchu Guan ◽  
Yanchun Liang
Keyword(s):  
Cancer Research ◽  
Trend Analysis ◽  
Research Trends ◽  
Feature Representation ◽  
Research Trend ◽  
Good Representation ◽  
Text Representation ◽  
Classical Text ◽  
Representation Model ◽  
Text Feature

Machine learning models can automatically discover biomedical research trends and promote the dissemination of information and knowledge. Text feature representation is a critical and challenging task in natural language processing. Most methods of text feature representation are based on word representation. A good representation can capture semantic and structural information. In this paper, two fusion algorithms are proposed, namely, the Tr-W2v and Ti-W2v algorithms. They are based on the classical text feature representation model and consider the importance of words. The results show that the effectiveness of the two fusion text representation models is better than the classical text representation model, and the results based on the Tr-W2v algorithm are the best. Furthermore, based on the Tr-W2v algorithm, trend analyses of cancer research are conducted, including correlation analysis, keyword trend analysis, and improved keyword trend analysis. The discovery of the research trends and the evolution of hotspots for cancers can help doctors and biological researchers collect information and provide guidance for further research.

Treatment of Polydipsia Using a Contingency Management Procedure Incorporating a Self-Management Approach: A Single Case Study

1993 ◽  
Vol 21 (3) ◽  
pp. 275-279 ◽  
Author(s):  
John Turnbull
Keyword(s):  
Single Case ◽  
Contingency Management ◽  
Research Literature ◽  
Self Management ◽  
Pharmacological Intervention ◽  
Management Approach ◽  
Management Procedure ◽  
Management Techniques ◽  
One Year

Polydipsia is a disorder that has received little attention in the research literature. Treatment has been mainly confined to medical or pharmacological intervention. Few studies have reported the use of contingency management techniques and none have sought to encourage self-management. This study shows how such a procedure brought about a significant change in rates of water drinking in a thirty-one year old man with a mild learning disability.

Evaluating a Functional Family Therapy Intervention: Challenges and Lessons Learned

2021 ◽  
pp. 104973152098560 ◽  
Author(s):  
Katarzyna Celinska
Keyword(s):  
Family Therapy ◽  
Service Providers ◽  
Evaluation Research ◽  
Evaluation Process ◽  
Outcome Evaluation ◽  
Lessons Learned ◽  
Functional Family Therapy ◽  
Functional Family ◽  
Family Based

Purpose: This case study is the introspective account of the evaluation process of Functional Family Therapy (FFT) as implemented in Middlesex County in New Jersey between 2005 and 2011. The study presents challenges and issues in evaluation falling into three main categories. Methods: The case study is based on the recollections and documented experiences of the author who was responsible for all major aspects of the evaluation including designing the study, collecting the data, and handling daily evaluation activities. Results: The author differentiated among three main categories of challenges. In respect to research design, the relative merits of experimental versus nonexperimental designs and quantitative versus qualitative research methods are discussed. The second set of issues involves developing and exercising the social competence skills necessary to form working partnerships with service providers. The third set encompasses logistical barriers encountered during daily evaluation activities. Conclusions: The challenges and lessons learned from conducting the outcome evaluation of FFT are situated within scholarly debates on evaluation research, with the goal of providing further insights into the on-the-ground implementation and process of program evaluations. The experiences, recollections and processes illustrate challenges and solutions applicable to evaluations of other family-based violence prevention interventions.

scholarly journals Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder

2020 ◽  
Vol 20 (S11) ◽  
Author(s):  
Jacqueline Peng ◽  
Mengge Zhao ◽  
James Havrilla ◽  
Cong Liu ◽  
Chunhua Weng ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Clinical Manifestations ◽  
Predictive Performance ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Research Articles

Abstract Background Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and MetaMap are among the most widely used tools to extract biomedical concept entities. However, their performance in extracting disease-specific terminology from literature has not been compared extensively, especially for complex neuropsychiatric disorders with a diverse set of phenotypic and clinical manifestations. Methods We comparatively evaluated these NLP tools using autism spectrum disorder (ASD) as a case study. We collected 827 ASD-related terms based on previous literature as the benchmark list for performance evaluation. Then, we applied CLAMP, cTAKES, and MetaMap on 544 full-text articles and 20,408 abstracts from PubMed to extract ASD-related terms. We evaluated the predictive performance using precision, recall, and F1 score. Results We found that CLAMP has the best performance in terms of F1 score followed by cTAKES and then MetaMap. Our results show that CLAMP has much higher precision than cTAKES and MetaMap, while cTAKES and MetaMap have higher recall than CLAMP. Conclusion The analysis protocols used in this study can be applied to other neuropsychiatric or neurodevelopmental disorders that lack well-defined terminology sets to describe their phenotypic presentations.

scholarly journals A Weighted-Time-Lag Method to Detect Lag Vegetation Response to Climate Variation: A Case Study in Loess Plateau, China, 1982–2013

2021 ◽  
Vol 13 (5) ◽  
pp. 923
Author(s):  
Qianqian Sun ◽  
Chao Liu ◽  
Tianyang Chen ◽  
Anbing Zhang
Keyword(s):  
Climate Change ◽  
Loess Plateau ◽  
Time Lag ◽  
New Method ◽  
Climate Factors ◽  
The Loess Plateau ◽  
Climate Conditions ◽  
Vegetation Growth ◽  
Lag Effect

Vegetation fluctuation is sensitive to climate change, and this response exhibits a time lag. Traditionally, scholars estimated this lag effect by considering the immediate prior lag (e.g., where vegetation in the current month is impacted by the climate in a certain prior month) or the lag accumulation (e.g., where vegetation in the current month is impacted by the last several months). The essence of these two methods is that vegetation growth is impacted by climate conditions in the prior period or several consecutive previous periods, which fails to consider the different impacts coming from each of those prior periods. Therefore, this study proposed a new approach, the weighted time-lag method, in detecting the lag effect of climate conditions coming from different prior periods. Essentially, the new method is a generalized extension of the lag-accumulation method. However, the new method detects how many prior periods need to be considered and, most importantly, the differentiated climate impact on vegetation growth in each of the determined prior periods. We tested the performance of the new method in the Loess Plateau by comparing various lag detection methods by using the linear model between the climate factors and the normalized difference vegetation index (NDVI). The case study confirmed four main findings: (1) the response of vegetation growth exhibits time lag to both precipitation and temperature; (2) there are apparent differences in the time lag effect detected by various methods, but the weighted time-lag method produced the highest determination coefficient (R2) in the linear model and provided the most specific lag pattern over the determined prior periods; (3) the vegetation growth is most sensitive to climate factors in the current month and the last month in the Loess Plateau but reflects a varied of responses to other prior months; and (4) the impact of temperature on vegetation growth is higher than that of precipitation. The new method provides a much more precise detection of the lag effect of climate change on vegetation growth and makes a smart decision about soil conservation and ecological restoration after severe climate events, such as long-lasting drought or flooding.

scholarly journals Analysis Methods in Neural Language Processing: A Survey

2019 ◽  
Vol 7 ◽  
pp. 49-72 ◽  
Author(s):  
Yonatan Belinkov ◽  
James Glass
Keyword(s):  
Language Processing ◽  
Network Models ◽  
Research Trends ◽  
Neural Network Models ◽  
Fine Grained ◽  
Survey Paper ◽  
Review Analysis ◽  
Analysis Methods ◽  
New Models ◽  
Future Work

The field of natural language processing has seen impressive progress in recent years, with neural network models replacing many of the traditional systems. A plethora of new models have been proposed, many of which are thought to be opaque compared to their feature-rich counterparts. This has led researchers to analyze, interpret, and evaluate neural networks in novel and more fine-grained ways. In this survey paper, we review analysis methods in neural language processing, categorize them according to prominent research trends, highlight existing limitations, and point to potential directions for future work.

Incorporating Life Cycle Assessment (LCA) in Freight Transportation Infrastructure Project Evaluation

2017 ◽  
Author(s):  
Soumith Kumar Oduru ◽  
Pasi Lautala
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Fossil Fuels ◽  
Ghg Emissions ◽  
Freight Transportation ◽  
Evaluation Process ◽  
Planning Stage ◽  
Simplified Lca ◽  
Modal Route

Transportation industry at large is a major consumer of fossil fuels and contributes heavily to the global greenhouse gas emissions. A significant portion of these emissions come from freight transportation and decisions on mode/route may affect the overall scale of emissions from a specific movement. It is common to consider several alternatives for a new freight activity and compare the alternatives from economic perspective. However, there is a growing emphasis for adding emissions to this evaluation process. One of the approaches to do this is through Life Cycle Assessment (LCA); a method for estimating the emissions, energy consumption and environmental impacts of the project throughout its life cycle. Since modal/route selections are often investigated early in the planning stage of the project, availability of data and resources for analysis may become a challenge for completing a detailed LCA on alternatives. This research builds on such detailed LCA comparison performed on a previous case study by Kalluri et al. (2016), but it also investigates whether a simplified LCA process that only includes emissions from operations phase could be used as a less resource intensive option for the analysis while still providing relevant outcomes. The detailed LCA is performed using SimaPro software and simplified LCA is performed using GREET 2016 model. The results are obtained in terms of Kg CO2 equivalents of GHG emissions. This paper introduces both detailed and simplified methodologies and applies them to a case study of a nickel and copper mine in the Upper Peninsula of Michigan. The analysis’ are done for three modal alternatives (two truck routes and one rail route) and for multiple mine lives.

Individualized Behavioural Treatment of Severe Stuttering

1991 ◽  
Vol 19 (4) ◽  
pp. 347-357 ◽  
Author(s):  
Willi Ecker ◽  
Victor Meyer
Keyword(s):  
Oral Reading ◽  
Reading Improvement ◽  
Behavioural Treatment ◽  
Communication Situations ◽  
Cognitive Techniques ◽  
One Year

This case study illustrates the reduction of severe stuttering by an individually tailored treatment programme. Interventions are derived from a tripartite analysis (Lang, 1971) and include EMG biofeedback, regulated breathing, exposure in vivo to stressful communication situations and cognitive techniques to reduce relapse risk. The role of dysfunctional response system interactions in stuttering is emphasized. Treatment resulted in a marked reduction of stuttering and associated facial contortions during videotaped conversations with strangers and oral reading. Improvement was maintained at one-year follow-up.

A Successful Adaptation of Systematic Desensitization in the Treatment of a Phobia of Babies

1985 ◽  
Vol 2 (1) ◽  
pp. 59-64
Author(s):  
Michael Free ◽  
Margaret Beekhuis
Keyword(s):  
Young Woman ◽  
Skin Conductance ◽  
Treatment Strategy ◽  
Physiological Measures ◽  
Systematic Desensitization ◽  
Physiological Measure ◽  
One Year

A case study is presented of a young woman with an unusual phobia, a fear of babies. Barabasz's (1977) technique of systematic desensitization using psycho-physiological measures was chosen as the main treatment strategy. Difficulties arose as the client was unable to visualise scenes involving babies. Nor could she look at photographs of babies long enough for the hierarchy to be ordered using a psycho-physiological measure (skin conductance). A set of photographs was eventually used for the hierarchy, but it was ordered in terms of the length of time the client could look at the various photographs. Systematic desensitization was carried out using the set of photographs instead of imaginary scenes, together with some in vivo exposure in the latter stages of treatment. At termination the client could approach babies without discomfort. Improvement was maintained at one year follow-up.

Sign in / Sign up

Export Citation Format

Share Document