On the Cluster Validity Test (s) in Unsupervised Machine Learning TDA Approach for Atmospheric River Patterns on Flood Detection in Nigeria

Abstract TDA (i.e., Topological Data Analysis) has recently been a reliable and current research area in Statistics for extracting shape (information) from data. In this study, the researchers proposed an automated method that uses TDA & ML in identifying floods (ARs) in big data. Our process gives vital details on time series trends, which help mitigate the negative effect of ARs, such as flooding. The spatial data (between 1970 - 2018) from Nigeria Hydrological Services Agency (NIHSA) on four weather parameters were used. The daily datasets were converted to monthly datasets before the proposed method was applied. Python Software is used to develop code in the implementation of our process. Mostly, the outcome facts studied will drastically reduce disasters due to extreme events like floods and achieve some SDG goals related to the flood. The second objective is to identify potential flooding and no flooding in each zone. The work successfully used a real dataset and four variables that other studies have not used to fill a gap. After our model's training process, we obtained the best group at k = 2, where we have the highest Silhouette coefficient in each of the seven states. We have found a reasonable structure in the study considering the total average range (0.3 - 0.8). That gives an efficiency outcome of approximately 80%. Summary of clustered feature pattern shows the potential flood zone and no flood zone. We conducted cluster validity of our results using R software codes and, the test validated the best group at the same cluster k = 2. The Gap statistic shows efficiency ranging between 65% to 80% in the seven states. We found from figure 11 that only the Silhouette plot obtained optimal values at exactly k = 2; The researchers got the extent of the spread from the centroid using Excel software.

Download Full-text

Amidst Covid-19 Pandemic: An Adaptive Disaster Governance in Yogyakarta, Indonesia

Social Sciences ◽

10.3390/socsci10030092 ◽

2021 ◽

Vol 10 (3) ◽

pp. 92

Author(s):

Dyah Rahmawati Hizbaron ◽

Dina Ruslanjari ◽

Djati Mardiatno

Keyword(s):

Spatial Data ◽

Online Survey ◽

Local Development ◽

Development Planning ◽

Research Area ◽

Primary Data ◽

Adaptive Governance ◽

First Case ◽

The Government ◽

Information Conflict

Since Indonesia reported its first case of COVID-19 in the capital, Jakarta, in early March of 2020, the pandemic has affected 102,051,000 lives. In the second week of the month, the government mandated all sectors to take necessary actions to curb the spread. The research set out to evaluate how the disaster emergency response was carried out amid the COVID-19 pandemic in the Special Region of Yogyakarta (SRY). The research employs qualitative observation of adaptive governance variables, i.e., infrastructure availability, information, conflict mechanism, regulation, and adaptation. The research analyzed primary data collected from focus group discussions with key persons at the Local Disaster Management Agency, Local Development Planning Agency, and Disaster Risk Reduction Platform responsible for the crisis and included an online survey to validate data. The research revealed that the SRY had exhibited adaptive governance to the COVID-19 pandemic, as apparent by, among others, open-access spatial and non-spatial data, extensive combined uses of both types of data, and prompt active engagement of communities in the enforcement of new rules and regulations mandated by national and provincial governments. Furthermore, during emergency responses to COVID-19, the stakeholders provided infrastructure and information, dealt with conflicts in multiple spatial units, encouraged adaptations, and formulated emergent rules and regulations. For further research, we encourage qualitative analysis to confront other types of natural disaster for the research area.

Download Full-text

Estimating productivity of earthmoving operations using spatial technologies1This paper is one of a selection of papers in this Special Issue on Construction Engineering and Management.

Canadian Journal of Civil Engineering ◽

10.1139/l2012-059 ◽

2012 ◽

Vol 39 (9) ◽

pp. 1072-1082 ◽

Cited By ~ 9

Author(s):

Ali Montaser ◽

Ibrahim Bakry ◽

Adel Alshibani ◽

Osama Moselhi

Keyword(s):

Real Time ◽

Spatial Data ◽

Data Fitting ◽

Google Earth ◽

Simulation Software ◽

Distribution Functions ◽

Automated Classification ◽

Cycle Times ◽

Automated Method ◽

Spreadsheet Application

This paper presents an automated method for estimating productivity of earthmoving operations in near-real-time. The developed method utilizes Global Positioning System (GPS) and Google Earth to extract the data needed to perform the estimation process. A GPS device is mounted on a hauling unit to capture the spatial data along designated hauling roads for the project. The variations in the captured cycle times were used to model the uncertainty associated with the operation involved. This was carried out by automated classification, data fitting, and computer simulation. The automated classification is applied through a spreadsheet application that classifies GPS data and identifies, accordingly, durations of different activities in each cycle using spatial coordinates and directions captured by GPS and recorded on its receiver. The data fitting was carried out using commercially available software to generate the probability distribution functions used in the simulation software “Extend V.6”. The simulation was utilized to balance the production of an excavator with that of the hauling units. A spreadsheet application was developed to perform the calculations. An example of an actual project was analyzed to demonstrate the use of the developed method and illustrates its essential features. The analyzed case study demonstrates how the proposed method can assist project managers in taking corrective actions based on the near-real-time actual data captured and processed to estimate productivity of the operations involved.

Download Full-text

Effects of gap size, gap age, and bamboo Fargesia denudata on Abies faxoniana recruitment in South-western China

Forest Systems ◽

10.5424/fs/2015242-06682 ◽

2015 ◽

Vol 24 (2) ◽

pp. e025 ◽

Cited By ~ 1

Author(s):

Wen Kang ◽

Cheng Tian ◽

Dongwei Kang ◽

Mengjun Wang ◽

Yunxi Li ◽

...

Keyword(s):

Natural Regeneration ◽

Research Area ◽

Western China ◽

Coniferous Forests ◽

Gap Size ◽

Abies Faxoniana ◽

Age Gap ◽

Natural Reserve ◽

Negative Effect ◽

Fargesia Denudata

Aim of study: to study the effects of gap size, gap age and bamboo Fargesia denudata on natural regeneration of Abies faxoniana, both of which are the ubiquitous dominants in our research area.Area of study: subalpine coniferous forests in Wanglang Natural Reserve in Southwestern China.Material and Methods: 10 transect belts were randomly established, and a total of 97 gaps were recorded and used.Main results: (1) the number of bamboos with coverage of <17% significantly increased with increases of gap size and age, but the latter had little influence on the numbers of F. denudata with coverage of >17%. (2) F. denudata strongly inhibited A. faxoniana seedlings and saplings in small, young and old gaps, where the amount of A. faxoniana recruitment was relatively abundant, than in other types of gap. (3) The numbers of A. faxoniana seedlings in A-gaps, significantly decreased with the increases in gap size. However, in gaps where F. denudate was also present, A. faxoniana seedlings and saplings were insensitive to gap size or age. Research highlights: thick F. denudata would not be influenced by gap size or age. Because of the low occurrences of A. faxoniana seedlings and saplings, the negative effect of gap size, gap age and F. denudata on A. faxoniana recruitment was unclear.Key words: Abies faxoniana; Fargesia denudata; gap age; gap size; regeneration.

Download Full-text

PLCA

Advances in Geospatial Technologies - Qualitative Spatio-Temporal Representation and Reasoning ◽

10.4018/978-1-61692-868-1.ch002 ◽

2012 ◽

pp. 63-96 ◽

Cited By ~ 3

Author(s):

Kazuko Takahashi

Keyword(s):

Graph Theory ◽

Computational Geometry ◽

Spatial Data ◽

Qualitative Data ◽

Spatial Reasoning ◽

Research Area ◽

Qualitative Spatial Reasoning ◽

Research Areas ◽

Fruitful Research ◽

Topology Graph

This chapter describes a framework called PLCA for Qualitative Spatial Reasoning (QSR) based on the connection patterns of regions. The goal of this chapter is to provide a simple but expressive and feasible representation for qualitative data with sufficient reasoning ability. PLCA provides a symbolic representation for spatial data using simple objects. The authors of this chapter define its expression and operations on it, and show the correspondance between the expression and a figure. PLCA also provides semantical reasoning incorporated with spatial reasoning. Moreover, it can be extended to handle shapes of regions. Throughout the study, the authors discovered many topics that relate QSR to other research areas such as topology, graph theory, and computational geometry, while achieving the research goals. This indicates that QSR is a very fruitful research area.

Download Full-text

Citizens’ Spatial Footprint on Twitter—Anomaly, Trend and Bias Investigation in Istanbul

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9040222 ◽

2020 ◽

Vol 9 (4) ◽

pp. 222 ◽

Cited By ~ 2

Author(s):

Ayse Giz Gulnerman ◽

Himmet Karaman ◽

Direnc Pekaslan ◽

Serdar Bilgi

Keyword(s):

Social Media ◽

Spatial Data ◽

Central Area ◽

Research Area ◽

Time Of Day ◽

Activity Levels ◽

Social Media Data ◽

Time Space ◽

The City ◽

Media Data

Social media (SM) can be an invaluable resource in terms of understanding and managing the effects of catastrophic disasters. In order to use SM platforms for public participatory (PP) mapping of emergency management activities, a bias investigation should be undertaken with regard to the data related to the study area (urban, regional or national, etc.) to determine the spatial data dynamics. Thus, such determinations can be made on how SM can be used and interpreted in terms of PP. In this study, the city of Istanbul was chosen for social media data research area, as it is one of the most crowded cities in the world and expecting a major earthquake. The methodology for the data investigation is: 1. Obtain data and engage sampling, 2. Identify the representation and temporal biases in the data and normalize it in response to representation bias, 3. Identify general anomalies and spatial anomalies, 4. Manipulate the trend of the dataset with the discretization of anomalies and 5. Examine the spatiotemporal bias. Using this bias investigation methodology, citizen footprint dynamics in the city were determined and reference maps (most likely regional anomaly maps, representation maps, time-space bias maps, etc.) were produced. The outcomes of the study can be summarized in four steps. First, highly active users generate the majority of the data and removing this data as a general approach within a pseudo-cleaning process means concealing a large amount of data. Second, data normalization in terms of activity levels, changes the anomaly outcome resulting from diverse representation levels of users. Third, spatiotemporally normalized data present strong spatial anomaly tendency in some parts of the central area. Fourth, trend data is dense in the central area and the spatiotemporal bias assessments show the data density varies in terms of the time of day, day of week and season of the year. The methodology proposed in this study can be used to extract the unbiased daily routines of the social media data of the regions for the normal days and this can be referred for the emergency or unexpected event cases to detect the change or impacts.

Download Full-text

An Empirical Investigation into the Influence of Knowledge Sharing Barriers on Knowledge Sharing and Individual Innovation Behaviour

International Journal of Knowledge Management ◽

10.4018/jkm.2013040103 ◽

2013 ◽

Vol 9 (2) ◽

pp. 38-61 ◽

Cited By ~ 22

Author(s):

Salih Yeşil ◽

Bengü Hırlak

Keyword(s):

Higher Education ◽

Knowledge Sharing ◽

Empirical Investigation ◽

Academic Staff ◽

Education Institution ◽

Research Area ◽

Innovation Research ◽

Individual Knowledge ◽

Negative Effect ◽

Further Development

Knowledge sharing barriers reduce the propensity of individuals to share knowledge and produce innovation behaviour. Thus, identifying barriers and their impact on knowledge sharing and individual innovation behaviour is a potential research area to study. Considering lack of studies in the literature, this study provides further evidence regarding the implications of knowledge sharing barriers in the workplace. Data was collected from eighty three academic staff in a higher education institution and analysed with Smart PLS. The results showed that organisation related knowledge sharing barriers are negatively related to knowledge collecting and knowledge donating. The result also indicates that individual knowledge sharing barriers have negative effect on individual innovation behaviours. There was no link found in this study between knowledge sharing and individual innovation behaviour. These findings provide empirical evidence to the further development of knowledge management and innovation research, and insights regarding how to better implement knowledge sharing and foster innovation behaviour in organisations.

Download Full-text

GeoHAB, a Data Sharing, Spatial Web 2.0 Application for Habitat Types and Land Cover

International Journal of Applied Geospatial Research ◽

10.4018/ijagr.2019070103 ◽

2019 ◽

Vol 10 (3) ◽

pp. 46-58

Author(s):

Konstandinos Panitsidis ◽

Zacharoula Andreopoulou ◽

Rosa Misso

Keyword(s):

Land Cover ◽

Programming Languages ◽

Data Sharing ◽

Spatial Data ◽

Environmental Science ◽

System Development ◽

Research Area ◽

Environmental Information ◽

Environmental Technologies ◽

Data Layers

This article, which is based on the science of informatics and environmental technologies, deals with the implementation of informatics in environmental science and practice. It focuses on web-based GIS spatial data sharing application system design and its development, which records and represents specific environmental information with emphasis on habitats and land cover. The system development was made by using JavaScript, PHP as programming languages and Google Maps API. The application provides centralized environmental information with habitats and land cover. It addresses ordinary users and scientists, that not only have the willing to expand their knowledge in the field but also they have the privilege to explore the research area over the map. The users can render the overlay information of spatial habitat and land cover data layers, execute zooming, panning, and information querying functions. Its aim is to offer, to any interested citizen, scientist or organization, direct and reliable environmental information.

Download Full-text

A subassembly identification method for truss structures manufacturing based on community detection

Assembly Automation ◽

10.1108/aa-02-2015-011 ◽

2015 ◽

Vol 35 (3) ◽

pp. 249-258 ◽

Cited By ~ 6

Author(s):

Hao Cao ◽

Rong Mo ◽

Neng Wan ◽

Fang Shang ◽

Chunlei Li ◽

...

Keyword(s):

Research Area ◽

Truss Structures ◽

Assembly Planning ◽

Human Errors ◽

Planning Time ◽

Content Type ◽

Automated Method ◽

Assembly Sequences ◽

Bounding Boxes ◽

Oriented Bounding Boxes

Purpose – The purpose of this paper is to present an automated method for complicated truss structure subassembly identification. Design/methodology/approach – A community-detecting algorithm is introduced and adapted to reach the target. The ratio between oriented bounding boxes of parts is used as the weight to reflect the compact degree of assembly relationships. The authors also propose a method to merge nodes together at cut-vertex in model, by which the solving process could be accelerated. Findings – This method could identify the subassemblies of complex truss structures according to the specific requirements. Research limitations/implications – This research area is limited to truss structures. This research offers a new method in assembly sequences planning area. It could identify subassemblies in complex truss structures, with which the existing method is not adequate to deal. Practical implications – This method could facilitate the complex truss structures assembly planning, lower the human errors and reduce the planning time. Social implications – The method could inspire general assembly analysis planning. Originality/value – All authors of this paper confirm that this manuscript is original and has not been submitted or published elsewhere.

Download Full-text

Faktor yang Mempengaruhi Pendapatan Keluarga Miskin di Kecamatan Maesan Kabupaten Bondowoso

e-Journal Ekonomi Bisnis dan Akuntansi ◽

10.19184/ejeba.v4i2.5795 ◽

2017 ◽

Vol 4 (2) ◽

pp. 182

Author(s):

Moehammad Fathorrazi ◽

Dewa Murti ◽

Fivien Muslihatinningsih

Keyword(s):

Cross Section ◽

Research Area ◽

Variable Number ◽

Primary Data ◽

Poor Families ◽

Negative Effect ◽

Independent Variable ◽

Questionnaire Method ◽

Educational Variables ◽

Positive Effect

This study aims to determine the factors that affect the income of the poorest families in the district Maesan the regency by using the method of analysis Regression (Regression Model Multiplier). Data used in this study are primary data derived from interviews, questionnaire method, the method of observation (cross section) with a research area in District Maesan regency. The regression results obtained from this study indicate that education (X1) and age (X2) has positive effect on revenues. The number of dependents (X3) and the type of work (X4) negative effect on revenue. The probability value of each independent variable is education (X1) of 0.0000, age (X2) of 0.0000, the number of dependents (X3) at 0.0000 and the type of work (X4) of 0.7765. This shows that in the study of factors that affect the income of poor families in the District Maesan Bondowoso,variables that influence the educational variables, variables of age, and a variable number of dependents who have significant influence on the income variable. Variable type of work does not significantly influence the income variable. Keywords: income, education, age, total family dependents and The job type

Download Full-text

Analisis Tingkat Kerawanan Banjir di Kabupaten Semarang Menggunakan Overlay dan Skoring Memanfaatkan SIG

JAGAT (Jurnal Geografi Aplikasi dan Teknologi) ◽

10.33772/jagat.v5i1.14816 ◽

2021 ◽

Vol 5 (1) ◽

pp. 1

Author(s):

Dawa Rysqyqa Ramadhan ◽

Hanna Prillysca Chernovita

Keyword(s):

Information System ◽

Geographic Information System ◽

Spatial Data ◽

Secondary Data ◽

Research Area ◽

Flood Vulnerability ◽

Water Flows ◽

Flood Disasters ◽

Overlay Method ◽

Low Levels

Abstrak: Bencana banjir merupakan bencana yang sering terjadi di wilayah iklim tropis khususnya daerah yang letaknya dikelilingi oleh aliran air atau genangan air seperti danau. Banjir di Indonesia dipengaruhi oleh pergantian musim yang tidak menentu yang menyebabkan bencana banjir. Penelitian ini bertujuan untuk memetakan wilayah yang rawan terhadap banjir dan mengetahui sebarapa besar tingkat kerawananan banjir yang dapat terjadi di studi area penelitian pada wilayah Kabupaten Semarang. Penelitian ini menggunakan metode overlay dengan tumpang susun layer, berdasarkan hasil perhitungan total scoring dari nilai dan bobot dari tiap parameter. Pengumpulan data dilakukan dengan mengumpulkan data sekunder berupa data spasial dan non spasial dari lembaga resmi Negara Indonesia, yang dipakai untuk mendukung analisis yang dilakukan. Dari hasil analisis yang dilakukan pada studi area penelitian di wilayah Kabupaten Semarang, diketahui terdapat 159 desa pada daerah dengan tingkat kerawanan yang rendah, serta 109 desa pada daerah dengan tingkat kerawanan sedang, sisanya 20 desa berada pada tingkat kerawanan tinggi. Dari analisis yang dilakukan, dapat ditarik kesimpulan bahwa wilayah Kabupaten Semarang khususnya pada daerah studi area penelitian menghasilkan informasi dari empat kecamatan yang ada, memiliki tingkat kerentanan yang didominasi oleh tingkat tidak rawan dan cukup rawan. Kata kunci: Bencana Banjir, Overlay, Scoring, Sistem Informasi Geografi.Abstract: Disaster flood disasters that occur in climatic areas, especially areas associated with water flows or puddles such as lakes. Floods in Indonesia are inspired by the changing seasons that are disastrous floods. This study aims to map the areas that are prone to flooding and how much danger is the level of flood vulnerability that can occur in the study area of Semarang Regency. This study uses an overlay method with overlapping layers, based on the calculation of the total score of the values and weights of each parameter. Data collection was carried out by collecting secondary data in the form of spatial data and non-official Indonesian institutions, which were used to support the analysis carried out. From the results of the analysis carried out in the study area of research in Semarang Regency, it is known that there are 159 villages in areas with low levels of vulnerability, as well as 109 villages in areas with moderate levels of vulnerability, the remaining 20 villages are at high levels of vulnerability. From the analysis carried out, it can be concluded that the Semarang Regency area, especially in the study area the research area produces information from the four existing sub-districts, has a level of vulnerability which is dominated by a level of vulnerability which is not vulnerable and quite vulnerable. Keywords: Flood Disaster, Overlay, Scoring, Geographic Information System.

Download Full-text