Flash flood is a natural disaster that often occurs after heavy rain, and it is getting more common nowadays. The flood early warning and response system (FEWRS) can be installed to minimize the level of damage and the number of casualties due to flood by providing accurate and reliable flood data. Unfortunately, the existing number of studies detailing on the factors affecting the efficiency of FEWRS in flood disaster is quite limited. The above issue is addressed in the current work, which involves conducting a comprehensive literature review on the factors that drive the effectiveness of information systems (IS) in FEWRS. The current analysis was based on the Wymer and Regan's standards. From the 66 factors identified from the previous studies on IS adoption, the most significant factors affecting the effectiveness of FEWRS are: system quality, information quality, user satisfaction, service quality, use, perceived usefulness, intention to use,net benefits, perceived ease of use,compatibility, user experience, relative advantage, complexity, perceivedrisks, educational quality, and confirmation, these factors can be constructed to the success model to address the effectiveness of FEWRS in disaster management.
PAPERS20 April 2013 ■ Project Management Jou.docxdanhaley45372
P
A
P
E
R
S
20 April 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj
INTRODUCTION ■
U
ncertainty is both a reality and great challenge for most projects
(Chapman & Ward, 2003; Hillson, 2010). The presence of risk creates
surprises throughout the project life cycle, affecting everything
from technical feasibility to cost, market timing, financial perform-
ance, and strategic objectives (Hillson, 1999; Loch, Solt, & Bailey, 2008;
Thieme, Song, & Shin, 2003). Yet, to succeed in today’s ultracompetitive envi-
ronment, management must deal with these risks effectively despite these
difficulties (Buchanan & O’Connell, 2006; Patil, Grantham, & Steele, 2012;
Shenhar, 2001; Shenhar, Milosevic, Dvir, & Thamhain, 2007; Srivannaboon &
Milosevic, 2006). This concerns executives, and it is not surprising that lead-
ers in virtually all organizations, from commerce to government, spend
much of their time and effort dealing with risk-related issues. Examples trace
back to ancient times that include huge infrastructure projects and military
campaigns. Writings by Sun Tzu articulated specific risks and suggested
mitigation methods 2,500 years ago (Hanzhang & Wilkinson, 1998). Risk
management is not a new idea. However, in today’s globally connected, fast-
changing business world with broad access to resources anywhere, and pres-
sures for quicker, cheaper, and smarter solutions, projects have become
highly complex and intricate. Many companies try to leverage their
resources and accelerate their schedules by forming alliances, consortia, and
partnerships with other firms, universities, and government agencies that
range from simple cooperative agreements to “open innovation,” a concept
of scouting for new product and service ideas anywhere in the world. In such
an increasingly complex and dynamic business environment, risks lurk in
many areas, not only associated with the technical part of the work, but also
including social, cultural, organizational, and technological dimensions. In
fact, research studies have suggested that much of the root cause of project-
related risks can be traced to the organizational dynamics and multidiscipli-
nary nature that characterizes today’s business environment, especially for
technology-based developments (R. Cooper, Edgett, & Kleinschmidt, 2001;
Torok, Nordman, & Lin, 2011). The involvement of many people, processes,
and technologies spanning different organizations, support groups, subcon-
tractors, vendors, government agencies, and customer communities com-
pounds the level of uncertainty and distributes risk over a wide area of the
enterprise and its partners (Thamhain, 2004; Thamhain & Wilemon, 1999),
often creating surprises with potentially devastating consequences. This
paradigm shift leads to changing criteria for risk management. To be effec-
tive in dealing with the broad spectrum of risk factors, project leaders must
go beyond the mechanics of analyzing the work a.
What affects digitalization process in developing economies? An evidence from...journalBEEI
The main objective of this paper is to investigate the SMEs’ leader perspective about the basic factors influencing the transformation into digitalization by SMEs they lead, using technological, organizational, and environmental (TOE) Model. The data were collected from 61 SMEs leaders in Oman, to achieve the study objective TOE model has been adopted. Internal consistency and data normality, and factor analysis were implemented. Structural equation modeling (SEM) used to test the proposed hypotheses. The outcomes of SEM indicate that TOE factors are significantly affects the ability of SMEs to digitalize their business process. The study findings come in the context of Omani definition of SMEs. More, no control was made for industry type to which SMEs participants are belong. Leaders of SMEs should frame strategies to simplify the digital transformation of their enterprises and attempt to provide organizational and technological facilities that will smooth their digitalization which will improve SMEs capabilities, as well as, increasing the international competitiveness of the SMEs. To the best of the authors' knowledge, this study is one of the first that investigated the digital transformation among SMEs from the leaders’ perspective in Oman.
PAPERS20 April 2013 ■ Project Management Jou.docxdanhaley45372
P
A
P
E
R
S
20 April 2013 ■ Project Management Journal ■ DOI: 10.1002/pmj
INTRODUCTION ■
U
ncertainty is both a reality and great challenge for most projects
(Chapman & Ward, 2003; Hillson, 2010). The presence of risk creates
surprises throughout the project life cycle, affecting everything
from technical feasibility to cost, market timing, financial perform-
ance, and strategic objectives (Hillson, 1999; Loch, Solt, & Bailey, 2008;
Thieme, Song, & Shin, 2003). Yet, to succeed in today’s ultracompetitive envi-
ronment, management must deal with these risks effectively despite these
difficulties (Buchanan & O’Connell, 2006; Patil, Grantham, & Steele, 2012;
Shenhar, 2001; Shenhar, Milosevic, Dvir, & Thamhain, 2007; Srivannaboon &
Milosevic, 2006). This concerns executives, and it is not surprising that lead-
ers in virtually all organizations, from commerce to government, spend
much of their time and effort dealing with risk-related issues. Examples trace
back to ancient times that include huge infrastructure projects and military
campaigns. Writings by Sun Tzu articulated specific risks and suggested
mitigation methods 2,500 years ago (Hanzhang & Wilkinson, 1998). Risk
management is not a new idea. However, in today’s globally connected, fast-
changing business world with broad access to resources anywhere, and pres-
sures for quicker, cheaper, and smarter solutions, projects have become
highly complex and intricate. Many companies try to leverage their
resources and accelerate their schedules by forming alliances, consortia, and
partnerships with other firms, universities, and government agencies that
range from simple cooperative agreements to “open innovation,” a concept
of scouting for new product and service ideas anywhere in the world. In such
an increasingly complex and dynamic business environment, risks lurk in
many areas, not only associated with the technical part of the work, but also
including social, cultural, organizational, and technological dimensions. In
fact, research studies have suggested that much of the root cause of project-
related risks can be traced to the organizational dynamics and multidiscipli-
nary nature that characterizes today’s business environment, especially for
technology-based developments (R. Cooper, Edgett, & Kleinschmidt, 2001;
Torok, Nordman, & Lin, 2011). The involvement of many people, processes,
and technologies spanning different organizations, support groups, subcon-
tractors, vendors, government agencies, and customer communities com-
pounds the level of uncertainty and distributes risk over a wide area of the
enterprise and its partners (Thamhain, 2004; Thamhain & Wilemon, 1999),
often creating surprises with potentially devastating consequences. This
paradigm shift leads to changing criteria for risk management. To be effec-
tive in dealing with the broad spectrum of risk factors, project leaders must
go beyond the mechanics of analyzing the work a.
What affects digitalization process in developing economies? An evidence from...journalBEEI
The main objective of this paper is to investigate the SMEs’ leader perspective about the basic factors influencing the transformation into digitalization by SMEs they lead, using technological, organizational, and environmental (TOE) Model. The data were collected from 61 SMEs leaders in Oman, to achieve the study objective TOE model has been adopted. Internal consistency and data normality, and factor analysis were implemented. Structural equation modeling (SEM) used to test the proposed hypotheses. The outcomes of SEM indicate that TOE factors are significantly affects the ability of SMEs to digitalize their business process. The study findings come in the context of Omani definition of SMEs. More, no control was made for industry type to which SMEs participants are belong. Leaders of SMEs should frame strategies to simplify the digital transformation of their enterprises and attempt to provide organizational and technological facilities that will smooth their digitalization which will improve SMEs capabilities, as well as, increasing the international competitiveness of the SMEs. To the best of the authors' knowledge, this study is one of the first that investigated the digital transformation among SMEs from the leaders’ perspective in Oman.
effective disaster management by efficient usage of resourcesINFOGAIN PUBLICATION
Disaster Management can be merely defined as the organization and management of resources and responsibilities for dealing with all humanitarian aspects of crises, in specific preparedness, rejoinder and recapture in order to diminish the influence of disasters. But the affects of the disaster increases only when the information about the disaster is unknown and when the resources for the disaster management is not correctly used. Now there are several methods for forecast the disaster, But there are no any effective methods for handling the resources needed for both managing the disaster and also for rehabilitation purpose. Thus this paper proposes an application used for managing the disaster and handling the rehabilitation process. This application which deals with almost all the resources those are required for the management of disaster. This proposed application which is based on java programming language. This project also has a great scope of enhancement in future.
EFFECTS OF RISK MANAGEMENT METHODS ON PROJECT PERFORMANCE IN RWANDAN CONSTRUC...Sibo Kanyambari Aimable
Risks are very common in construction sector. Risk is the Possibility of suffering loss and the impact on the involved parties. According to APM (2006), all projects are inherently risky because they are unique, constrained, complex, based on assumptions, and performed by people. As a result, project risk management methods must be built into the management of projects and should be used throughout the project lifecycle.
Many construction projects fail because organizations assume that all the projects would succeed and they therefore do not identify, analyze, and provide mitigation or contingencies for the risk elements involved in the project.
Society desires that all projects should be performing and has become less tolerant of failure (Edwards and Bowen, 2005). Pressure is exerted on project managers to minimize the chance of project failure. This increasing pressure for performance which suggests that it is prudent for anyone involved in a project to be concerned about the associated risks and how they can be effectively managed.
Traditionally, performance of a project is analyzed on the criteria of quality, budget and time of completion. Two more criteria to determine the performance of a project were added by Kerzner (2001). Firstly, the project would effectively and efficiently manage risks and, secondly, it should be accepted by the customer.
It is known that the cause of the projects failure can be directly related to the extent of risk management methods undertaken. Besides, the level of risk management methods undertaken during project lifecycle impacts directly on the performance or otherwise of the project. Furthermore, using risk management methods effectively to manage risk should be continuously undertaken throughout the project lifecycle to enhance project performance. Risk management methods are thus an important tool to cope with such substantial risks in projects performance.
The main objective of the enquiry work that underpins this research is to investigate the effect of risk management methods on project performance. In this paper, a case study of RSSB multi-storey already executed project is considered.
Prediction of Corporate Bankruptcy using Machine Learning Techniques Shantanu Deshpande
Aim is to build a classification model to predict whether company will become bankrupt or not using financial ratios of Polish companies. Applied various machine learning models like Random Forest, KNN, AdaBoost & Decision Tree with pre-processing techniques like SMOTE-ENN (to deal with class imbalance) & feature selection (for identifying ) and trained on Polish Bankruptcy dataset with prediction accuracy of 89%.
Effect or Risk Management Methods on project performance in Rwandan Construct...Sibo Kanyambari Aimable
Risks are very common in construction sector. Risk is the Possibility of suffering loss and the impact on the involved parties. According to APM (2006), all projects are inherently risky because they are unique, constrained, complex, based on assumptions, and performed by people. As a result, project risk management methods must be built into the management of projects and should be used throughout the project lifecycle.
Many construction projects fail because organizations assume that all the projects would succeed and they therefore do not identify, analyze, and provide mitigation or contingencies for the risk elements involved in the project.
Society desires that all projects should be performing and has become less tolerant of failure (Edwards and Bowen, 2005). Pressure is exerted on project managers to minimize the chance of project failure. This increasing pressure for performance which suggests that it is prudent for anyone involved in a project to be concerned about the associated risks and how they can be effectively managed.
Traditionally, performance of a project is analyzed on the criteria of quality, budget and time of completion. Two more criteria to determine the performance of a project were added by Kerzner (2001). Firstly, the project would effectively and efficiently manage risks and, secondly, it should be accepted by the customer.
It is known that the cause of the projects failure can be directly related to the extent of risk management methods undertaken. Besides, the level of risk management methods undertaken during project lifecycle impacts directly on the performance or otherwise of the project. Furthermore, using risk management methods effectively to manage risk should be continuously undertaken throughout the project lifecycle to enhance project performance. Risk management methods are thus an important tool to cope with such substantial risks in projects performance.
The main objective of the enquiry work that underpins this research is to investigate the effect of risk management methods on project performance. In this paper, a case study of RSSB multi-storey already executed project is considered.
Next generation architecture examination for Mass Notification System(MNS) co...IJERA Editor
The abstract should summarize the content of the paper. Try to keep the abstract below 200 words. Do not make references nor display equations in the abstract. The journal will be printed from the same-sized copy prepared by you. Your manuscript should be printed on A4 paper (21.0 cm x 29.7 cm). It is imperative that the margins and style described below be adhered to carefully. This will enable us to keep uniformity in the final printed copies of the Journal. Please keep in mind that the manuscript you prepare will be photographed and printed as it is received. Readability of copy is of paramount importance.
Risk assessment of information production using extended risk matrix approachTELKOMNIKA JOURNAL
In many cases poor information quality appears mainly due to in-effectiveness of information management including information production and delivery. Where this situation poses a certain risk. A holistic information risk management model has been previously proposed. But the model has some limitations especially on risk calculation and risk priority ranking as the model does not consider existing control effectiveness. In this paper, a new risk assessment method is proposed in order to improve the model of total impact of risks and to improve the accuracy of risk priority ranking by modifying the extended risk matrix approach (RMA) where we take into account the existing control effectiveness. Using our approach by adding a new dimension on extended RMA. We are able to improve the accuracy (7.15%) and reduced the ambiguity (1.34) of assessment results on real cases illustration.
Net impact implementation application development life-cycle management in ba...CSITiaesprime
Digital transformation in the banking sector creates a lot of demand for application development, either new development or application enhancement. Continuous demand for reimagining, revamping, and running applications reliably needs to be supported by collaboration tools. Several big banks in Indonesia use Atlassian products, including Jira, Confluence, Bamboo, Bitbucket, and Crowd, to support strategic company projects. We need to measure the net impact of application development life-cycle management (ADLM) as a collaboration tool. Using the deLone and McLean model, process questionnaire data from banks in Indonesia that use ADLM. Processing data using structural equation modeling (SEM), multiple variables are analyzed statistically to establish, estimate, and test the causation model. The conclusions highlight that system quality strongly affected only User Satisfaction (p=0.049 and β=0.39). Information quality strongly affected use (p=0.001 and β=0.84) and strongly affected user satisfaction (p=0.169 and β=0.28). Service quality strongly affected only use (p=0.127 and β=0.31). Conclusion research verifies the information system's achievement approach described by DeLone and McLean. Importantly, it was discovered that system usability and quality were key indicators of ADLM success. To fulfill their objective, ADLM must be developed in a way that is simple to use, adaptable, and functional.
Use of information Systems in Yemeni Universities Future Vision EECJOURNAL
This research examines the use of computed information systems in Yemeni universities through the use of intermediate variable technology to test the indirect impact of the information systems structure on the relationship between information technology, and the final performance in the computed information systems in Yemeni universities. The applied situation was exemplified by the selection of four universities where the data on the study were collected through special friendly questionnaire, and the number of respondent (224) persons had been used. Many statistical means, percentages, arithmetic mean, standard deviation, and intermediate deviation have been used for the description of the study sample, and for the study variables, as for hypothesis testing, the intermediate variant method was used and the end result was to prove that there was a relationship An incomplete mediation attributed to the structure of information systems that has an indirect impact on the resulting relationship between information technology and the final performance of information systems.
In this study, machine learning is examined in relation to commercial machine learning's resilience to the COVID-19 pandemic-related crisis. Two approaches are used to assess the pandemic's impact on machine learning risk, as well as a method to prioritize sectors according to the crisis's potential negative consequences. I conducted the study to determine Santander machine learning's resilience. The data mining area offers prospects for COVID-19's future. A total of 13 machine learning demos were selected for its organization. The Hellweg strategy and the technique for order preference by similarity to ideal solution (TOPSIS) technique were utilized as direct request strategies. Parametric assessment of machine learning versatility in business was based on capital sufficiency, liquidity proportion, market benefits, and share in an arrangement of openings with a perceived disability, and affectability of machine learning's credit portfolio to monetary hazard. As a result of the COVID-19 pandemic, these enterprises were ranked according to their threat. Based on the findings of the research, machine learning worked the best for the pandemic. Meanwhile, machine learning suffered the most during the downturn. It can be seen, for example, in conversations about the impact of the pandemic on developing business sector soundness and managing financial framework solidity risk.
In Indian scenario of infrastructure industry, there is a colossal vocation of peril analysis knacks and tools available for the management of affliction. In dogma, each peril analysis knack has its strengths and weaknesses. Knacks such as Probability Theory, Certainty Factors and Dempster-Shaffer theory of evidence are discussed with regard to their application to peril analysis in road projects. Suggestions on the most appropriate tools associated with the knacks are also presented. The mighty and emaciation of each knack are highlighted and discussed. This paper inferred the peril to be determined in project.
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
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effective disaster management by efficient usage of resourcesINFOGAIN PUBLICATION
Disaster Management can be merely defined as the organization and management of resources and responsibilities for dealing with all humanitarian aspects of crises, in specific preparedness, rejoinder and recapture in order to diminish the influence of disasters. But the affects of the disaster increases only when the information about the disaster is unknown and when the resources for the disaster management is not correctly used. Now there are several methods for forecast the disaster, But there are no any effective methods for handling the resources needed for both managing the disaster and also for rehabilitation purpose. Thus this paper proposes an application used for managing the disaster and handling the rehabilitation process. This application which deals with almost all the resources those are required for the management of disaster. This proposed application which is based on java programming language. This project also has a great scope of enhancement in future.
EFFECTS OF RISK MANAGEMENT METHODS ON PROJECT PERFORMANCE IN RWANDAN CONSTRUC...Sibo Kanyambari Aimable
Risks are very common in construction sector. Risk is the Possibility of suffering loss and the impact on the involved parties. According to APM (2006), all projects are inherently risky because they are unique, constrained, complex, based on assumptions, and performed by people. As a result, project risk management methods must be built into the management of projects and should be used throughout the project lifecycle.
Many construction projects fail because organizations assume that all the projects would succeed and they therefore do not identify, analyze, and provide mitigation or contingencies for the risk elements involved in the project.
Society desires that all projects should be performing and has become less tolerant of failure (Edwards and Bowen, 2005). Pressure is exerted on project managers to minimize the chance of project failure. This increasing pressure for performance which suggests that it is prudent for anyone involved in a project to be concerned about the associated risks and how they can be effectively managed.
Traditionally, performance of a project is analyzed on the criteria of quality, budget and time of completion. Two more criteria to determine the performance of a project were added by Kerzner (2001). Firstly, the project would effectively and efficiently manage risks and, secondly, it should be accepted by the customer.
It is known that the cause of the projects failure can be directly related to the extent of risk management methods undertaken. Besides, the level of risk management methods undertaken during project lifecycle impacts directly on the performance or otherwise of the project. Furthermore, using risk management methods effectively to manage risk should be continuously undertaken throughout the project lifecycle to enhance project performance. Risk management methods are thus an important tool to cope with such substantial risks in projects performance.
The main objective of the enquiry work that underpins this research is to investigate the effect of risk management methods on project performance. In this paper, a case study of RSSB multi-storey already executed project is considered.
Prediction of Corporate Bankruptcy using Machine Learning Techniques Shantanu Deshpande
Aim is to build a classification model to predict whether company will become bankrupt or not using financial ratios of Polish companies. Applied various machine learning models like Random Forest, KNN, AdaBoost & Decision Tree with pre-processing techniques like SMOTE-ENN (to deal with class imbalance) & feature selection (for identifying ) and trained on Polish Bankruptcy dataset with prediction accuracy of 89%.
Effect or Risk Management Methods on project performance in Rwandan Construct...Sibo Kanyambari Aimable
Risks are very common in construction sector. Risk is the Possibility of suffering loss and the impact on the involved parties. According to APM (2006), all projects are inherently risky because they are unique, constrained, complex, based on assumptions, and performed by people. As a result, project risk management methods must be built into the management of projects and should be used throughout the project lifecycle.
Many construction projects fail because organizations assume that all the projects would succeed and they therefore do not identify, analyze, and provide mitigation or contingencies for the risk elements involved in the project.
Society desires that all projects should be performing and has become less tolerant of failure (Edwards and Bowen, 2005). Pressure is exerted on project managers to minimize the chance of project failure. This increasing pressure for performance which suggests that it is prudent for anyone involved in a project to be concerned about the associated risks and how they can be effectively managed.
Traditionally, performance of a project is analyzed on the criteria of quality, budget and time of completion. Two more criteria to determine the performance of a project were added by Kerzner (2001). Firstly, the project would effectively and efficiently manage risks and, secondly, it should be accepted by the customer.
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Next generation architecture examination for Mass Notification System(MNS) co...IJERA Editor
The abstract should summarize the content of the paper. Try to keep the abstract below 200 words. Do not make references nor display equations in the abstract. The journal will be printed from the same-sized copy prepared by you. Your manuscript should be printed on A4 paper (21.0 cm x 29.7 cm). It is imperative that the margins and style described below be adhered to carefully. This will enable us to keep uniformity in the final printed copies of the Journal. Please keep in mind that the manuscript you prepare will be photographed and printed as it is received. Readability of copy is of paramount importance.
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In many cases poor information quality appears mainly due to in-effectiveness of information management including information production and delivery. Where this situation poses a certain risk. A holistic information risk management model has been previously proposed. But the model has some limitations especially on risk calculation and risk priority ranking as the model does not consider existing control effectiveness. In this paper, a new risk assessment method is proposed in order to improve the model of total impact of risks and to improve the accuracy of risk priority ranking by modifying the extended risk matrix approach (RMA) where we take into account the existing control effectiveness. Using our approach by adding a new dimension on extended RMA. We are able to improve the accuracy (7.15%) and reduced the ambiguity (1.34) of assessment results on real cases illustration.
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In this study, machine learning is examined in relation to commercial machine learning's resilience to the COVID-19 pandemic-related crisis. Two approaches are used to assess the pandemic's impact on machine learning risk, as well as a method to prioritize sectors according to the crisis's potential negative consequences. I conducted the study to determine Santander machine learning's resilience. The data mining area offers prospects for COVID-19's future. A total of 13 machine learning demos were selected for its organization. The Hellweg strategy and the technique for order preference by similarity to ideal solution (TOPSIS) technique were utilized as direct request strategies. Parametric assessment of machine learning versatility in business was based on capital sufficiency, liquidity proportion, market benefits, and share in an arrangement of openings with a perceived disability, and affectability of machine learning's credit portfolio to monetary hazard. As a result of the COVID-19 pandemic, these enterprises were ranked according to their threat. Based on the findings of the research, machine learning worked the best for the pandemic. Meanwhile, machine learning suffered the most during the downturn. It can be seen, for example, in conversations about the impact of the pandemic on developing business sector soundness and managing financial framework solidity risk.
In Indian scenario of infrastructure industry, there is a colossal vocation of peril analysis knacks and tools available for the management of affliction. In dogma, each peril analysis knack has its strengths and weaknesses. Knacks such as Probability Theory, Certainty Factors and Dempster-Shaffer theory of evidence are discussed with regard to their application to peril analysis in road projects. Suggestions on the most appropriate tools associated with the knacks are also presented. The mighty and emaciation of each knack are highlighted and discussed. This paper inferred the peril to be determined in project.
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In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
In this paper, snake optimization algorithm (SOA) is used to find the optimal gains of an enhanced controller for controlling congestion problem in computer networks. M-file and Simulink platform is adopted to evaluate the response of the active queue management (AQM) system, a comparison with two classical controllers is done, all tuned gains of controllers are obtained using SOA method and the fitness function chose to monitor the system performance is the integral time absolute error (ITAE). Transient analysis and robust analysis is used to show the proposed controller performance, two robustness tests are applied to the AQM system, one is done by varying the size of queue value in different period and the other test is done by changing the number of transmission control protocol (TCP) sessions with a value of ± 20% from its original value. The simulation results reflect a stable and robust behavior and best performance is appeared clearly to achieve the desired queue size without any noise or any transmission problems.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Water Industry Process Automation and Control Monthly - May 2024.pdf
Factors influencing the success of information systems in flood early warning and response systems context
1. TELKOMNIKA Telecommunication, Computing, Electronics and Control
Vol. 18, No. 6, December 2020, pp. 2956~2961
ISSN: 1693-6930, accredited First Grade by Kemenristekdikti, Decree No: 21/E/KPT/2018
DOI: 10.12928/TELKOMNIKA.v18i6.14666 2956
Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA
Factors influencing the success of information systems in flood
early warning and response systems context
Waleed A. Hammood1
, Salwana Mohamad @Asmara2
, Ruzaini A Arshah3
, Omar A. Hammood4
,
Hussam Al Halbusi5
, Mohammed Abdullah Al-Sharafi6
1,2,3,4,6
Faculty of Computing, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Malaysia
5
Department of Business Strategy and Policy, Faculty of Business and Accountancy, University of Malaya, Malaysia
Article Info ABSTRACT
Article history:
Received Nov 24, 2019
Revised Jul 6, 2020
Accepted Jul 29, 2020
Flash flood is a natural disaster that often occurs after heavy rain, and it is
getting more common nowadays. The flood early warning and response
system (FEWRS) can be installed to minimize the level of damage and the
number of casualties due to flood by providing accurate and reliable flood data.
Unfortunately, the existing number of studies detailing on the factors affecting
the efficiency of FEWRS in flood disaster is quite limited. The above issue is
addressed in the current work, which involves conducting a comprehensive
literature review on the factors that drive the effectiveness of information
systems (IS) in FEWRS. The current analysis was based on the Wymer and
Regan's standards. From the 66 factors identified from the previous studies on
IS adoption, the most significant factors affecting the effectiveness of FEWRS
are: system quality, information quality, user satisfaction, service quality, use,
perceived usefulness, intention to use, net benefits, perceived ease of use,
compatibility, user experience, relative advantage, complexity, perceived
risks, educational quality, and confirmation, these factors can be constructed
to the success model to address the effectiveness of FEWRS in disaster
management.
Keywords:
Disaster management
Flood
Flood early warning and
response system
Information systems success
Technology adoption
This is an open access article under the CC BY-SA license.
Corresponding Author:
Waleed A. Hammood,
Faculty of Computing, College of Computing and Applied Sciences,
Universiti Malaysia Pahang,
Lebuhraya Tun Razak, 26300 Gambang, Kuantan, Pahang, Malaysia.
Email: engwaleed54@yahoo.com
1. INTRODUCTION
Flood is a natural phenomenon caused by earthquakes, tsunamis, hurricanes, etc. [1, 2]. The rising
number of flash floods has endangered the lives of villagers along the river bank due to urban modernization.
Over the last two decades, flash floods have become more frequent and damaging [3], due to the climate change
(greenhouse effect) [4]. It is estimated that a global loss in major coastal cities due to flood alone could exceed
$1 trillion per annum by 2050 due to flood alone 2050 [3], building dike can mitigate the amount of flood
damage; however, construction work can be expensive. The level of risk due to flooding is currently more
severe now than that of other weather-related disasters [5], as more casualties are anticipated in
the former. Previous studies have shown that structural engineering strategy alone cannot overcome flood
hazard completely. Annually, the number of victims due to floods is increased. Hence, the significance of
the flood early warning and response system (FEWRS) is a crucial in-flood risk. In this context of the study, it
is necessary to address the factors that contribute to the success of FEWRS in the system to improve the
2. TELKOMNIKA Telecommun Comput El Control
Factors influencing the success of information system in flood early warning ... (Waleed A. Hammod)
2957
efficiency and effectiveness of the system [6]. Although the FEWRS has been established in which its
reliability is guided by the quality of information, degree of knowledge-sharing culture, and efficacy of
communication but still not dramatically efficient to those in danger. This non-structural method is assumed to
help reduce the expense of flood control and the number of casualties [7]. In developing countries including
those in Asia, the population level is comparatively high in the area of flood-prone rivers. Unfortunately in
these countries, the potential for FEWRS is very small. Undoubtedly, the precise forecast of water movement
dynamics of flood-prone areas is essential to the creation of a successful flood alarm and flood control plan.
Over the last 3 decades [8, 9], Many mitigation measures (i.e programs designed to inform people about
potential hazards, disaster preparedness plans, and legislation designed to limit risk by building standards) have
elements of local public goods in that they provide benefits to a community as a whole. In fact, local
governments play an important role in the mitigation flood risk as
The FEWRS is essentially a part of information system (IS) that can be used to minimize the risk due
to flood [10]. FEWRS is used to provide instant flood information using the signal transmitted by early warning
centers. According to Sättele et al. [11], there are three stages of flood disaster, i.e. pre-disaster, during-disaster,
and post-disaster. These stages should be considered in the design of FEWRS. Of course, advance warning and
pre-planning measures can be included in FEWRS to further reduce the level of damage due to flood. The
advantage of IS that can deploy on the model of FEWRS will provide information on the factors affecting the
success of the FEWRS. According to Baudoin et al. and Meyer [8, 12], information-based disaster tool such
as FEWRS can be adopted to forecast and to provide recommendation to decision makers on natural disasters
based on factors that contribute to the success of FEWRS [8, 13, 14]. Hence, information-based disaster tools
should be able to predict the likelihood of a disaster and to provide ample time for evacuation purpose. In fact,
existing FEWRSs are unable to provide information on natural disasters effectively [7, 15], and they are
ineffective in mitigating flood disasters during pre-disaster, during-disaster, and post-disaster stages [16, 17].
To this end, IS academicians such as Baudoin et al. [8] argued that information system is useful for improving
the efficiency and the effectiveness of disaster-handling activities. IS success becoming a significant problem
in the IS sector. Many experiments have sought to clarify whether an organization succeeds, but what is most
important for us is to consider how an IS influences organizational success. Therefore, factors affecting the
effectiveness of FEWRS should be properly studied; however, the factors on this area is rather limited. A model
should be developed to address the factors affecting the system’s effectiveness and to evaluate the effectiveness
of FEWRS [3]. The current systems are ineffective in reducing the impact of flood disaster [2, 18], mainly due
to the lack of information on the factors that contribute to the success of these systems [19-25].
In this paper, the success factors affecting the FEWRS has been addressing since there are limited
study focuses on this issue, the success factors help the disaster management to evaluate the system of FEWRS
easily and the weak of the design of the system. Many IS models have been developed to predicting and
explaining the user behavior in IS field. As such, these factors can be constructed to the success model to
address the effectiveness of FEWRS in disaster management. For instance, the popular IS success model is
the one proposed by DeLon & McLean (D&M) [26]. The D&M model is built by assuming that the overall
system use is an indication of IS success [27], which is supported by other researchers. In such a study the issue
of how we assess success is important. In 1992 William H. DeLone and Ephraim R. McLean [26] developed
their first IS success model to be able to recognize and measure IS success in an e-commerce context.
Centered on a taxonomy that incorporates all the multiple metrics used to determine IS success in
the IS literature, their model aims to explain how each of the suggested dimensions of IS success is linked to
each other. Assume that the e-commerce environment is a specific setting for analyzing the success of DeLone
and McLean's IS model, as the system itself is important for the market, without it there will be no
company-customer relationship. The system is therefore not unique to the organization; it serves the client in
its main application, not corporate workers. Finally, the website's features are standard, easy to interpret, and
match the various dimensions of the DeLone and McLean models. Their model offers a point of starting from
which to develop and improve all the further work. Researchers have shown strong interest in this model, as
cited in over 300 publications aimed at explaining IS success [26, 28]. This study has been selected 16 factors
form the previous study which in an IS success field to help the researchers in selecting the most relevant
factors to apply in the FEWRS model [29].
2. RESEARCH METHOD
The primary aim of this study is to incorporate the most crucial factors affecting the effectiveness of
IS in context of FEWRS model. In order to meet this objective, literature review on IS success adoption is
conducted. The factors affecting the effectiveness of IS are taken from Hong and Kim [30]. The first step is to
identify all the relevant factors. From the literature review (40 papers), there are 66 factors as shown in
Table 1 reported to date. The exclusion/inclusion criteria have been developed for the selection process. Only
articles published from 2014-2019 are included in the search criter
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The second step is to reorganize and alphabetize the factor, consolidate them and eliminate those
repeating factors defined with different terminology. Then, the collection of unified factors was defined. This
will subsequently map to the data of all authors who examined those variable and excluded the factors
contained in the list at the individual level. Finally, a total of 16 factors are classified based on the frequency
appeared in the literature and the relative importance of the research findings are subsequently reported.
Table 1. Factors extracted from the literature
Factors Sources F* Factors Sources F*
System Quality [19, 21-23, 27, 31-53] 29 Focused Immersion [48] 1
Information Quality [21-23, 27, 31-54] 28 Knowledge of Data Science [47] 1
User Satisfaction [19, 21-23, 27, 31, 33-40,
42-44, 48, 51, 53, 55-57]
26 Social Norms [47] 1
Service Quality [19, 21, 23, 27, 31-43, 46,
50, 51, 55, 57]
23 Stickiness Intention [34] 1
Use [19, 21-23, 33, 37, 40, 44,
45, 48, 50, 51, 57]
13 Behavioral Control [47] 1
Perceived Usefulness [19, 27, 33, 36, 37, 39, 45,
48, 49, 55, 56]
12 Computer Web Skills [55] 1
Intention to Use [19, 27, 31-33, 35, 38, 41,
42, 46, 47, 55]
12 Habit [23] 1
Net Benefits [22, 31, 33, 36, 38, 39, 44,
47]
8 Referent Network Size [45] 1
Perceived Ease of Use [19, 35, 48, 49, 55] 7 Flow [45] 1
User Experience [35, 36, 50] 3 IS Project Success [40] 1
Compatibility [52, 53, 58] 3 IS Utilization [54] 1
Perceived Risks [23, 55] 2 Perceived KMS Output Quality [56] 1
Relative Advantage [52, 53] 2 Goals [54] 1
Complexity [52, 58] 2 Challenges [54] 1
Educational Quality [19, 35] 2 Extrinsic Rewards [56] 1
Confirmation [23, 48] 2 Organizational Trust [56] 1
Transformational Leadership [21] 1 Attitude [42] 1
Performance Impact [21] 1 Management Support [43] 1
Decision Making Process [32] 1 Compatibility [43] 1
Trust in Sellers [57] 1 Perceived Behavioral Control [43] 1
Trust in Website [57] 1 Complexity [43] 1
Reputation of Sellers [57] 1 Individual Impact [43] 1
Reputation of Website [57] 1 Organizational Impact [43] 1
Perceived Size of Sellers [57] 1 managerial IT Capability [59] 1
Perceived Size of Website [57] 1 Technical IT Capability [59] 1
Perceived Value [34] 1 Relational IT Capability [59] 1
Effort Expectancy [27] 1 Cloud Success [59] 1
Trust Government [36] 1 RL Cost Effectiveness [54] 1
Temporal dissociation [48] 1 Social Influence [33] 1
Relationship Commitment [34] 1 Trust in E-government Website [36] 1
Organizational Results [51] 1 Firm Performance [59] 1
Perceived Complementarity [45] 1
Adoption Intention [49] 1
Focused Immersion [48] 1
F* Frequency
3. RESULTS AND ANALYSIS
In this This section presents the findings of this study. Many decision makers are unable to get
the best return from FEWRS due to the lack of comprehensive understanding of factors affecting
the effectiveness of IS in meeting the requirement of FEWRS. The most crucial factors affecting
the effectiveness of IS in disaster management are sought in this research. As stated earlier, a total of 66 factors
have been extracted. Table 2 shows the most popular factors. As seen, there are sixteen popular factors affecting
IS adoption [6, 19, 21-23, 27, 31-43, 46, 50-53, 55, 57].
From Table 2, the information quality and the system quality are the most important factors. These
factors determine the successful adoption of IS in both individual and organization levels. In literature, different
terminologies are used to address the same factor. For instance, terms such as net benefits [51], success of
IS [21], and technology characteristics [60, 61] have been used to describe the system quality along information
quality. Also, the term compatibility has been used to describe the compatibility of human characteristics in
using IS [60].
Table 2. Most popular success factors
Factors Sources Factors Sources
System Quality [19, 21-23, 27, 31-53] Perceived Ease of Use [19, 35, 48, 49, 55]
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Information Quality [21-23, 27, 31-54] Compatibility [52, 53, 58]
User Satisfaction [19, 21-23, 27, 31, 33-40, 42-44, 48, 51, 53, 55-57] User Experience [35, 36, 50]
Service Quality [19, 21, 23, 27, 31-43, 46, 50-53, 55, 57] Relative Advantage [52, 53]
Use [19, 21-23, 33, 37, 40, 44, 45, 48, 50, 51, 57] Complexity [52, 58]
Perceived Usefulness [19, 27, 33, 36, 37, 39, 45, 48, 49, 55, 56] Perceived Risks [23, 55]
Intention to Use [19, 27, 31-33, 35, 38, 41, 42, 46, 47, 55] Educational Quality [19, 35]
Net Benefits [22, 31, 33, 36, 38, 39, 44, 47] Confirmation [23, 48]
4. CONCLUSION
The flood hazard mitigation technique mainly involves the use of an engineering approach which
could be costly and challenging. For example, it is difficult to find suitable areas for constructing dikes.
Apparently, the risk due to flood is more severe than those due to other types of natural disasters, as excessive
urbanization has led to global climate change inevitably. The FEWRS is one of the non-structural examples
introduced to reduce the risk of flood hazards. The main aim of FEWRS is to save lives and to reduce the level
of flood damage. However, due to information lacking, the implementation of FEWRS is still unsuccessful. To
address this gap, factors affecting the success of FEWRS are identified. Information system success is one of
the most crucial creations in the history of IS [26]. In most cases, organizations using FEWRS find that it is
challenging to evaluate the effectiveness of these systems, as practical understanding on how quality factors
are related to the use of information within the systems is rather limited. Factors such as quality, information,
service, and use are commonly evaluated [23]. The goal of any information system is to improve job
performance, in which improvement is only visible when a proper IT system is used.
This paper has comprehensively reviewed the existing IS success adoptions, which can
help researchers to identify relevant adoption factors in the context of FEWRS. The findings of this study
should have a significant effect on researchers dealing with IS. This research may be expanded by
identifying the conditions most commonly followed by scientific analysts and practitioners to influence
the success of the FEWRS. Such chosen factors will then be used to formulate a computational model for
tablethe performance of FEWRS.
ACKNOWLEDGEMENTS
The authors would like to sincerely thank Faculty of Computing, Universiti Malaysia Pahang as this
research has been supported by RACER 2019-1 Grant Vote: RDU192606.
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