scholarly journals Use of a text mining method for classifying citizen report data and analyzing the occurrence trend of local problems

2019 ◽  
Vol 8 (2) ◽  
pp. 1
Author(s):  
Eiji Kano ◽  
Kazuhiko Tsuda
Keyword(s):  
Text Mining ◽  
Traffic Safety ◽  
Living Environment ◽  
Mining Method ◽  
Local Problems ◽  
Problem Detection ◽  
Report System ◽  
Report Data ◽  
Maintenance And Inspection ◽  
The Relationship

An important task of any municipality is the maintenance and improvement of the street-related living environment and traffic safety for citizens.  For this, their department of street maintenance is expected to efficiently perform the maintenance and inspection of streets according to priority with limited human and budgetary resources.  Recently, municipalities in various countries are adopting “the citizen report system,” which is a system of reporting problems of streets, such as damaged streets, by citizens to their municipality, for citizens to perform part of street maintenance and inspection.  It is possible that the data obtained by municipalities through the citizen report system can be utilized not only for early problem detection but also for prioritizing administrative measures by using it for analyzing the occurrence trend of problems.  Problems reported by citizens, however, are classified by different methods from municipality to municipality, and thus the collection and comparative analysis of such data across municipalities is difficult.  This study presents a method of commonly classifying such data, regardless of different classification standards, by analyzing the contents of citizen reports by using text mining.  We then analyze the relationship between the trend of citizen reports and the occurrence trend of problems concerning the living environment and traffic safety, using the citizen report data of three large municipalities classified by this method, and infer the occurrence trend of problems.  This study has confirmed that citizen report data possibly contributes to municipalities’ prioritization of the maintenance and improvement of the living environment and traffic safety.

Analyzing the Relationship between Citizen Report and Local Crime Occurrence Tendency Using Broken Windows Theory

2021 ◽  
Vol 12 (2) ◽  
pp. 31-35
Author(s):  
Eiji Kano ◽  
◽  
Kazuhiko Tsuda
Keyword(s):  
Financial Constraints ◽  
Broken Windows ◽  
Broken Windows Theory ◽  
Local Problems ◽  
Important Challenge ◽  
Report System ◽  
Report Data ◽  
Using Data ◽  
A Minor ◽  
The Relationship

Municipalities are required to prioritize and solve local problems effectively under human and financial constraints. Preventing local crime is an important challenge among them. One of the major theories of crime prevention is the “broken windows theory,” which states that if a minor crime or a rule infringement is left unaddressed, it may lead to more serious crimes. This theory affected police administrations in some areas, but it was not widely accepted due to problems such as difficulty in verifying its validity and identifying effective measures. There is a possibility that these limitations can be overcome by using data obtained from the citizen report system, which was introduced in municipalities in recent years. This study examines the relationship between local problems and local crimes based on the broken windows theory using citizen report data.

The Study of Classification Analysis on Oil Exploration Research Trends and Digging Technology Based on Properties of Biochemical Materials (2012-2013)

2013 ◽  
Vol 859 ◽  
pp. 280-283
Author(s):  
Shiang Hau Wu ◽  
Jiann Jong Guo
Keyword(s):  
Text Mining ◽  
Random Forests ◽  
Research Trends ◽  
Oil Exploration ◽  
Mining Method ◽  
Research Papers ◽  
Classification Analysis ◽  
Relationship Of ◽  
The Relationship ◽  
Random Forests Model

The study aimed at analyzing the keywords of the oil exploration research papers abstracts in 2012 and 2013 and using the random forests model to make the classification analysis in order to find the importance and similarities of 2012 and 2013 research trends. The contribution of the study included the following two points. First, the study used the text mining method in order to explore the content of oil exploration research paper abstracts. Second, the study applied the AdaBoost classification analysis to explore the relationship of the keywords between the two years’ keywords.

THE IMPACT OF THE PHYSICAL ENVIRONMENT ON RESIDENTS’ SELF-RATED HEALTH: A CASE STUDY IN PENANG, MALAYSIA

2020 ◽  
Vol 6 (1) ◽  
pp. 109
Author(s):  
Massoomeh Hedayati ◽  
Aldrin Abdullah ◽  
Mohammad Javad Maghsoodi Tilaki
Keyword(s):  
Physical Environment ◽  
Fear Of Crime ◽  
Structural Equation ◽  
Well Being ◽  
Living Environment ◽  
Housing Quality ◽  
Self Rated Health ◽  
Environment And Health ◽  
The Impact ◽  
The Relationship

There is continuous debate on the impact of house quality on residents’ health and well-being. Good living environment improves health, and fear of crime is recognised as a mediator in the relationship between physical environment and health. Since minimal studies have investigated the relationship, this study aims to examine the impact of the house quality on fear of crime and health. A total of 230 households from a residential neighbourhood in Malaysia participated in the study. Using structural equation modelling, the findings indicate that housing quality and fear of crime can account for a proportion of the variance in residents’ self-rated health. However, there is no significant relationship between housing quality and fear of crime. Results also show that fear of crime does not mediate the relationship between housing quality and health. This study suggests that the environment-fear relationship should be re-examined theoretically.  

Investigating Diseases and Chemicals in COVID-19 Literature with Text Mining (Preprint)

2020 ◽  
Author(s):  
Amir Karami ◽  
Brandon Bookstaver ◽  
Melissa Nolan
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Topic Modeling ◽  
Large Scale ◽  
Clinical Manifestations ◽  
International Health ◽  
Research Papers ◽  
Strategic Plans ◽  
Funding Agencies ◽  
The Relationship

BACKGROUND The COVID-19 pandemic has impacted nearly all aspects of life and has posed significant threats to international health and the economy. Given the rapidly unfolding nature of the current pandemic, there is an urgent need to streamline literature synthesis of the growing scientific research to elucidate targeted solutions. While traditional systematic literature review studies provide valuable insights, these studies have restrictions, including analyzing a limited number of papers, having various biases, being time-consuming and labor-intensive, focusing on a few topics, incapable of trend analysis, and lack of data-driven tools. OBJECTIVE This study fills the mentioned restrictions in the literature and practice by analyzing two biomedical concepts, clinical manifestations of disease and therapeutic chemical compounds, with text mining methods in a corpus containing COVID-19 research papers and find associations between the two biomedical concepts. METHODS This research has collected papers representing COVID-19 pre-prints and peer-reviewed research published in 2020. We used frequency analysis to find highly frequent manifestations and therapeutic chemicals, representing the importance of the two biomedical concepts. This study also applied topic modeling to find the relationship between the two biomedical concepts. RESULTS We analyzed 9,298 research papers published through May 5, 2020 and found 3,645 disease-related and 2,434 chemical-related articles. The most frequent clinical manifestations of disease terminology included COVID-19, SARS, cancer, pneumonia, fever, and cough. The most frequent chemical-related terminology included Lopinavir, Ritonavir, Oxygen, Chloroquine, Remdesivir, and water. Topic modeling provided 25 categories showing relationships between our two overarching categories. These categories represent statistically significant associations between multiple aspects of each category, some connections of which were novel and not previously identified by the scientific community. CONCLUSIONS Appreciation of this context is vital due to the lack of a systematic large-scale literature review survey and the importance of fast literature review during the current COVID-19 pandemic for developing treatments. This study is beneficial to researchers for obtaining a macro-level picture of literature, to educators for knowing the scope of literature, to journals for exploring most discussed disease symptoms and pharmaceutical targets, and to policymakers and funding agencies for creating scientific strategic plans regarding COVID-19.

Relating Household Consumption Expenditures to Road Traffic Fatalities: A Rural–Urban Study

2021 ◽  
pp. 036119812110332
Author(s):  
Ruchika Agarwala ◽  
Vinod Vasudevan
Keyword(s):  
Developing Countries ◽  
Traffic Safety ◽  
Rural Areas ◽  
Urban Areas ◽  
Household Consumption ◽  
Household Expenditure ◽  
Traffic Fatality ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
The Relationship

Research shows that traffic fatality risk is generally higher in rural areas than in urban areas. In developing countries, vehicle ownership and investments in public transportation typically increase with economic growth. These two factors together increase the vehicle population, which in turn affects traffic safety. This paper presents a study focused on the relationship of various factors—including household consumption expenditure data—with traffic fatality in rural and urban areas and thereby aims to fill some of the gaps in the literature. One such gap is the impacts of personal and non-personal modes of travel on traffic safety in rural versus urban areas in developing countries which remains unexplored. An exhaustive panel data modeling approach is adopted. One important finding of this study is that evidence exists of a contrasting relationship between household expenditure and traffic fatality in rural and urban areas. The relationship between household expenditure and traffic fatality is observed to be positive in rural areas and a negative in urban areas. Increases in most expenditure variables, such as fuel, non-personal modes of travel, and two-wheeler expenditures, are found to be associated with an increase in traffic fatality in rural areas.

scholarly journals Perceived Neighborhood Environment and Park Use as Mediators of the Effect of Area Socio-Economic Status on Walking Behaviors

2010 ◽  
Vol 7 (6) ◽  
pp. 802-810 ◽  
Author(s):  
Evie Leslie ◽  
Ester Cerin ◽  
Peter Kremer
Keyword(s):  
Traffic Safety ◽  
Economic Status ◽  
Neighborhood Environment ◽  
Self Report ◽  
Low Ses ◽  
Neighborhood Socioeconomic Status ◽  
Park Use ◽  
Recreational Walking ◽  
Report Data ◽  
Self Report Data

Background:Access to local parks can affect walking levels. Neighborhood environment and park use may influence relationships between neighborhood socioeconomic status (SES) and walking.Methods:Self-report data on perceived park features, neighborhood environment, park use, neighborhood walking and sociodemographics were obtained from a sample of Australian adults, living in high/low SES areas. Surveys were mailed to 250 randomly selected households within 500m of 12 matched parks. Mediating effects of perceived environment attributes and park use on relationships between area-SES and walking were examined.Results:Mean frequency of local park use was higher for high-SES residents (4.36 vs 3.16 times/wk, P < .01), who also reported higher levels of park safety, maintenance, attractiveness, opportunities for socialization, and neighborhood crime safety, aesthetics, and traffic safety. Safety and opportunity for socialization were independently positively related to monthly frequency of visits to a local park which, in turn, was positively associated with walking for recreation and total walking. Residents of higher SES areas reported an average 22% (95% CI: 5%, 37%) more weekly minutes of recreational walking than their low SES counterparts.Conclusion:Residents of high-SES areas live in environments that promote park use, which positively contributes to their weekly amounts of overall and recreational walking.

Analysis on the Anti-Glare Plate Setting Distance on Horizontal Curve Sections of Expressway

2014 ◽  
Vol 587-589 ◽  
pp. 2156-2159 ◽  
Author(s):  
Tian Xiao ◽  
Ji Shu Sun ◽  
Can Zhang Jin
Keyword(s):  
Traffic Safety ◽  
Calculation Formula ◽  
Horizontal Curve ◽  
Distance Calculation ◽  
Element Simulation ◽  
Curved Section ◽  
Curve Radius ◽  
The Relationship ◽  
Plate Distance ◽  
Glare Effect

Glare is one of the most important factors threating expressway traffic safety an night. The most commonly way to prevent glaring night is to set anti-glare plate. Different from the straight sections of expressway, the relationship between the front light of vehicles and the distance of anti-glare plate on the horizontal curved section has some-what changed. Through a lot of tests and finite element simulation, the relationship between the distance of anti-glare plate, horizontal curve radius and anti-glare effect were analyzed systematically. Distance calculation formula of anti-glare plate in horizontal curve sections was revised in this paper. The anti-glare plate distance requirement under different expressway alignment design indexes and its calculation formula was proposed. The achievement was beneficial to confirm the anti-glare effect and improve traffic safety. It can provide us with a reference and a supplement of the specification.

scholarly journals Demystifying Learning Analytics in Personalised Learning

2018 ◽  
Vol 7 (3) ◽  
pp. 1124 ◽  
Author(s):  
Andino Maseleno ◽  
Noraisikin Sabani ◽  
Miftachul Huda ◽  
Roslee Ahmad ◽  
Kamarul Azmi Jasmi ◽  
...  
Keyword(s):  
Learning Environment ◽  
Learning Process ◽  
Learning Analytics ◽  
Educational Institutions ◽  
Learning Resources ◽  
Personalised Learning ◽  
Report Data ◽  
Overall Performance ◽  
The Relationship ◽  
Specific Learning

This paper presents learning analytics as a mean to improve students’ learning. Most learning analytics tools are developed by in-house individual educational institutions to meet the specific needs of their students. Learning analytics is defined as a way to measure, collect, analyse and report data about learners and their context, for the purpose of understanding and optimizing learning. The paper concludes by highlighting framework of learning analytics in order to improve personalised learning. In addition, it is an endeavour to define the characterising features that represents the relationship between learning analytics and personalised learning environment. The paper proposes that learning analytics is dependent on personalised approach for both educators and students. From a learning perspective, students can be supported with specific learning process and reflection visualisation that compares their respective performances to the overall performance of a course. Furthermore, the learners may be provided with personalised recommendations for suitable learning resources, learning paths, or peer students through recommending system. The paper’s contribution to knowledge is in considering personalised learning within the context framework of learning analytics. 

Complaint management model of manufacturing products using text mining and potential failure identification

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ririn Diar Astanti ◽  
Ivana Carissa Sutanto ◽  
The Jin Ai
Keyword(s):  
Quality Management ◽  
Text Mining ◽  
Failure Mode ◽  
Management System ◽  
Main Part ◽  
Mining Method ◽  
Content Type ◽  
Complaint Management ◽  
Potential Failure ◽  
Failure Identification

PurposeThis paper aims to propose a framework on complaint management system for quality management by applying the text mining method and potential failure identification that can support organization learning (OL). Customer complaints in the form of email text is the input of the framework, while the most frequent complaints are visualized using a Pareto diagram. The company can learn from this Pareto diagram and take action to improve their process.Design/methodology/approachThe first main part of the framework is creating a defect database from potential failure identification, which is the initial part of the failure mode and effect analysis technique. The second main part is the text mining of customer email complaints. The last part of the framework is matching the result of text mining with the defect database and presenting in the form of a Pareto diagram. After the framework is proposed, a case study is conducted to illustrate the applicability of the proposed method.FindingsBy using the defect database, the framework can interpret the customer email complaints into the list of most defect complained by customer using a Pareto diagram. The results of the Pareto diagram, based on the results of text mining of consumer complaints via email, can be used by a company to learn from complaint and to analyze the potential failure mode. This analysis helps company to take anticipatory action for avoiding potential failure mode happening in the future.Originality/valueThe framework on complaint management system for quality management by applying the text mining method and potential failure identification is proposed for the first time in this paper.

scholarly journals Objective measurement of physical activity in Macaca fascicularis

1982 ◽  
Vol 16 (3) ◽  
pp. 240-243
Author(s):  
Wayne T. Corbett ◽  
Harry M. Schey ◽  
A. W. Green
Keyword(s):  
Physical Activity ◽  
Standard Deviation ◽  
Macaca Fascicularis ◽  
Living Environment ◽  
Activity Levels ◽  
Free Living ◽  
Activity Measurements ◽  
Active Intermediate ◽  
The Mean ◽  
The Relationship

The mean and standard deviation over 24 h for 3 groups of animals - active, intermediate and inactive - in physical activity units were 10948 ± 3360, 2611 ± 1973 and 484 ± 316 respectively. The differences were significant ( P = 0·004), demonstrating the ability of the method to distinguish between groups that can be visibly differentiated. The small within-animal physical activity standard deviation (18·85 PAU) obtained in another group, suggests that it also yields reliable physical activity measurements for non-human primates. The monitoring device used can discriminate between individual nonhuman primate physical activity levels in a free-living environment and does not alter daily behaviour. This makes possible the study of the relationship between physical activity and atherosclerosis in nonhuman primates.

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