Search results for: causal factor analysis system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 40959

Search results for: causal factor analysis system

40779 Analysis of Building Response from Vertical Ground Motions

Authors: George C. Yao, Chao-Yu Tu, Wei-Chung Chen, Fung-Wen Kuo, Yu-Shan Chang

Abstract:

Building structures are subjected to both horizontal and vertical ground motions during earthquakes, but only the horizontal ground motion has been extensively studied and considered in design. Most of the prevailing seismic codes assume the vertical component to be 1/2 to 2/3 of the horizontal one. In order to understand the building responses from vertical ground motions, many earthquakes records are studied in this paper. System identification methods (ARX Model) are used to analyze the strong motions and to find out the characteristics of the vertical amplification factors and the natural frequencies of buildings. Analysis results show that the vertical amplification factors for high-rise buildings and low-rise building are 1.78 and 2.52 respectively, and the average vertical amplification factor of all buildings is about 2. The relationship between the vertical natural frequency and building height was regressed to a suggested formula in this study. The result points out an important message; the taller the building is, the greater chance of resonance of vertical vibration on the building will be.

Keywords: vertical ground motion, vertical amplification factor, natural frequency, component

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40778 Two-Level Graph Causality to Detect and Predict Random Cyber-Attacks

Authors: Van Trieu, Shouhuai Xu, Yusheng Feng

Abstract:

Tracking attack trajectories can be difficult, with limited information about the nature of the attack. Even more difficult as attack information is collected by Intrusion Detection Systems (IDSs) due to the current IDSs having some limitations in identifying malicious and anomalous traffic. Moreover, IDSs only point out the suspicious events but do not show how the events relate to each other or which event possibly cause the other event to happen. Because of this, it is important to investigate new methods capable of performing the tracking of attack trajectories task quickly with less attack information and dependency on IDSs, in order to prioritize actions during incident responses. This paper proposes a two-level graph causality framework for tracking attack trajectories in internet networks by leveraging observable malicious behaviors to detect what is the most probable attack events that can cause another event to occur in the system. Technically, given the time series of malicious events, the framework extracts events with useful features, such as attack time and port number, to apply to the conditional independent tests to detect the relationship between attack events. Using the academic datasets collected by IDSs, experimental results show that the framework can quickly detect the causal pairs that offer meaningful insights into the nature of the internet network, given only reasonable restrictions on network size and structure. Without the framework’s guidance, these insights would not be able to discover by the existing tools, such as IDSs. It would cost expert human analysts a significant time if possible. The computational results from the proposed two-level graph network model reveal the obvious pattern and trends. In fact, more than 85% of causal pairs have the average time difference between the causal and effect events in both computed and observed data within 5 minutes. This result can be used as a preventive measure against future attacks. Although the forecast may be short, from 0.24 seconds to 5 minutes, it is long enough to be used to design a prevention protocol to block those attacks.

Keywords: causality, multilevel graph, cyber-attacks, prediction

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40777 Effects of a Cooler on the Sampling Process in a Continuous Emission Monitoring System

Authors: J. W. Ahn, I. Y. Choi, T. V. Dinh, J. C. Kim

Abstract:

A cooler has been widely employed in the extractive system of the continuous emission monitoring system (CEMS) to remove water vapor in the gas stream. The effect of the cooler on analytical target gases was investigated in this research. A commercial cooler for the CEMS operated at 4 C was used. Several gases emitted from a coal power plant (i.e. CO2, SO2, NO, NO2 and CO) were mixed with humid air, and then introduced into the cooler to observe its effect. Concentrations of SO2, NO, NO2 and CO were made as 200 ppm. The CO2 concentration was 8%. The inlet absolute humidity was produced as 12.5% at 100 C using a bubbling method. It was found that the reduction rate of SO2 was the highest (~21%), followed by NO2 (~17%), CO2 (~11%) and CO (~10%). In contrast, the cooler was not affected by NO gas. The result indicated that the cooler caused a significant effect on the water soluble gases due to condensate water in the cooler. To overcome this problem, a correction factor may be applied. However, water vapor might be different, and emissions of target gases are also various. Therefore, the correction factor is not only a solution, but also a better available method should be employed.

Keywords: cooler, CEMS, monitoring, reproductive, sampling

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40776 Detecting Memory-Related Gene Modules in sc/snRNA-seq Data by Deep-Learning

Authors: Yong Chen

Abstract:

To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

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40775 Developing a Multidimensional Adjustment Scale

Authors: Nadereh Sohrabi Shegefti, Siamak Samani

Abstract:

Level of adjustment is the first index to check mental health. The aim of this study was developing a valid and reliable Multidimensional Adjustment Scale (MAS). The sample consisted of 150 college students. Multidimensional adjustment scale and Depression, Anxiety, and stress scale (DASS) were used in this study. Principle factor analysis, Pearson correlation coefficient, and Cornbach's Alpha were used to check the validity and reliability of the MAS. Principle component factor analysis showed a 5 factor solution for the MAS. Alpha coefficients for the MAS sub scales were ranged between .69 to .83. Test-retest reliability for MAS was .88 and the mean of sub scales- total score correlation was .88. All these indexes revealed an acceptable reliability and validity for the MAS. The MAS is a short assessment instrument with good acceptable psychometric properties to use in clinical filed.

Keywords: psychological adjustment, psychometric properties, validity, Pearson correlation

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40774 Sync Consensus Algorithm: Trying to Reach an Agreement at Full Speed

Authors: Yuri Zinchenko

Abstract:

Recently, distributed storage systems have been used more and more in various aspects of everyday life. They provide such necessary properties as Scalability, Fault Tolerance, Durability, and others. At the same time, not only reliable but also fast data storage remains one of the most pressing issues in this area. That brings us to the consensus algorithm as one of the most important components that has a great impact on the functionality of a distributed system. This paper is the result of an analysis of several well-known consensus algorithms, such as Paxos and Raft. The algorithm it offers, called Sync, promotes, but does not insist on simultaneous writing to the nodes (which positively affects the overall writing speed) and tries to minimize the system's inactive time. This allows nodes to reach agreement on the system state in a shorter period, which is a critical factor for distributed systems. Also when developing Sync, a lot of attention was paid to such criteria as simplicity and intuitiveness, the importance of which is difficult to overestimate.

Keywords: sync, consensus algorithm, distributed system, leader-based, synchronization.

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40773 Collaborative Governance in Dutch Flood Risk Management: An Historical Analysis

Authors: Emma Avoyan

Abstract:

The safety standards for flood protection in the Netherlands have been revised recently. It is expected that all major flood-protection structures will have to be reinforced to meet the new standards. The Dutch Flood Protection Programme aims at accomplishing this task through innovative integrated projects such as construction of multi-functional flood defenses. In these projects, flood safety purposes will be combined with spatial planning, nature development, emergency management or other sectoral objectives. Therefore, implementation of dike reinforcement projects requires early involvement and collaboration between public and private sectors, different governmental actors and agencies. The development and implementation of such integrated projects has been an issue in Dutch flood risk management since long. Therefore, this article analyses how cross-sector collaboration within flood risk governance in the Netherlands has evolved over time, and how this development can be explained. The integrative framework for collaborative governance is applied as an analytical tool to map external factors framing possibilities as well as constraints for cross-sector collaboration in Dutch flood risk domain. Supported by an extensive document and literature analysis, the paper offers insights on how the system context and different drivers changing over time either promoted or hindered cross-sector collaboration between flood protection sector, urban development, nature conservation or any other sector involved in flood risk governance. The system context refers to the multi-layered and interrelated suite of conditions that influence the formation and performance of complex governance systems, such as collaborative governance regimes, whereas the drivers initiate and enable the overall process of collaboration. In addition, by applying a method of process tracing we identify a causal and chronological chain of events shaping cross-sectoral interaction in Dutch flood risk management. Our results indicate that in order to evaluate the performance of complex governance systems, it is important to firstly study the system context that shapes it. Clear understanding of the system conditions and drivers for collaboration gives insight into the possibilities of and constraints for effective performance of complex governance systems. The performance of the governance system is affected by the system conditions, while at the same time the governance system can also change the system conditions. Our results show that the sequence of changes within the system conditions and drivers over time affect how cross-sector interaction in Dutch flood risk governance system happens now. Moreover, we have traced the potential of this governance system to shape and change the system context.

Keywords: collaborative governance, cross-sector interaction, flood risk management, the Netherlands

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40772 Application of Subversion Analysis in the Search for the Causes of Cracking in a Marine Engine Injector Nozzle

Authors: Leszek Chybowski, Artur Bejger, Katarzyna Gawdzińska

Abstract:

Subversion analysis is a tool used in the TRIZ (Theory of Inventive Problem Solving) methodology. This article introduces the history and describes the process of subversion analysis, as well as function analysis and analysis of the resources, used at the design stage when generating possible undesirable situations. The article charts the course of subversion analysis when applied to a fuel injection nozzle of a marine engine. The work describes the fuel injector nozzle as a technological system and presents principles of analysis for the causes of a cracked tip of the nozzle body. The system is modelled with functional analysis. A search for potential causes of the damage is undertaken and a cause-and-effect analysis for various hypotheses concerning the damage is drawn up. The importance of particular hypotheses is evaluated and the most likely causes of damage identified.

Keywords: complex technical system, fuel injector, function analysis, importance analysis, resource analysis, sabotage analysis, subversion analysis, TRIZ (Theory of Inventive Problem Solving)

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40771 The Study of Genetic Diversity in Canola Cultivars of Kashmar-Iran Region

Authors: Seyed Habib Shojaei, Reza Eivazi, Mir Sajad Shojaei, Alireza Akbari, Pooria Mazloom, Seyede Mitra Sadati, Mir Zeinalabedin Shojaei, Farnaz Farbakhsh

Abstract:

To study the genetic diversity in rapeseeds and agronomic traits, an experiment was conducted using multivariate statistical methods at Agricultural Research Station of Kashmar in 2012-2013.In this experiment, ten genotypes of rapeseed in a Randomized Complete Block designs with three replications were evaluated. The following traits were studied: seed yield, number of days to the fifty percent of flowering, plant height, number of pods on main stem, length of the pod, seed yield per plant, number of seed in pod, harvest index, weight of 100 seeds, number of pods on lateral branch, number of lateral branches. In analyzing the variance, differences between cultivars were significant. The average comparative revealed that the most valuable variety was Licord regarding to the traits while the least valuable variety was Opera. In stepwise regression, harvest index, grain yield per plant and number of pods per lateral branches were entering to model. Correlation analysis showed that the grain yield with the number of pods per lateral branches and seed yield per plant have positive and significant correlation. In the factor analysis, the first five components explained more than 83% of the variance in the data. In the first factor, seed yield and the number of pods per lateral branches were of the highest importance. The traits, seed yield per plant, and pod per main stem were of a great significance in the second factor. Moreover, in the third factor, plant height and the number of lateral branches were more important. In the fourth factor, plant height and one hundred seeds weight were of the highest variance. Finally, days to fifty percent of flowering and one hundred seeds weight were more important in fifth factor.

Keywords: rapeseed, variance analysis, regression, factor analysis

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40770 Causality between Stock Indices and Cryptocurrencies during the Russia-Ukraine War

Authors: Nidhal Mgadmi, Abdelhafidh Othmani

Abstract:

This article examines the causal relationship between stock indices and cryptocurrencies during the current war between Russia and Ukraine. The econometric investigation runs from February 24, 2022, to April 12, 2023, focusing on seven stock market indices (S&P500, DAX, CAC40, Nikkei, TSX, MOEX, and PFTS) and seven cryptocurrencies (Bitcoin, Ethereum, Litcoin, Dash, Ripple, DigiByte and XEM). In this article, we try to understand how investors react to fluctuations in financial assets to seek safe havens in cryptocurrencies. We used dynamic causality to detect a possible causal relationship in the short term and seven models to estimate the long-term relationship between cryptocurrencies and financial assets. The causal relationship between financial market indexes and cryptocurrency coins in the short run indicates that three famous cryptocurrencies (BITCOIN, ETHEREUM, RIPPLE) and the two digital assets with minor popularity (XEM, Digibyte) are impacted by the German, Russian, and Ukrainian stock markets. In the long run, we found a positive and significate effect of the American, Canadian, French, and Ukrainian stock market indexes on Bitcoin. Thus, the stability of the traditional financial markets during the current war period can be explained on the one hand by investors’ fears of an unstable business climate, and on the other hand, by speculators’ sentiment towards new electronic products, which are perceived as hedging instruments and a safe haven in the face of the conflict between Ukraine and Russia.

Keywords: causality, stock indices, cryptocurrency, war, Russia, Ukraine

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40769 Developing a Toolkit of Undergraduate Nursing Student’ Desirable Characteristics (TNDC) : An application Item Response Theory

Authors: Parinyaporn Thanaboonpuang, Siridej Sujiva, Shotiga Pasiphul

Abstract:

The higher education reform that integration of nursing programmes into the higher education system. Learning outcomes represent one of the essential building blocks for transparency within higher education systems and qualifications. The purpose of this study is to develop a toolkit of undergraduate nursing student’desirable characteristics assessment on Thai Qualifications Framework for Higher education and to test psychometric property for this instrument. This toolkit seeks to improve on the Computer Multimedia test. There are three skills to be examined: Cognitive skill, Responsibility and Interpersonal Skill, and Information Technology Skill. The study was conduct in 4 phases. In Phase 1. Based on developed a measurement model and Computer Multimedia test. Phase 2 two round focus group were conducted, to determine the content validity of measurement model and the toolkit. In Phase 3, data were collected using a multistage random sampling of 1,156 senior undergraduate nursing student were recruited to test psychometric property. In Phase 4 data analysis was conducted by descriptive statistics, item analysis, inter-rater reliability, exploratory factor analysis and confirmatory factor analysis. The resulting TNDC consists of 74 items across the following four domains: Cognitive skill, Interpersonal Skill, Responsibility and Information Technology Skill. The value of Cronbach’ s alpha for the four domains were .781, 807, .831, and .865, respectively. The final model in confirmatory factor analysis fit quite well with empirical data. The TNDC was found to be appropriate, both theoretically and statistically. Due to these results, it is recommended that the toolkit could be used in future studies for Nursing Program in Thailand.

Keywords: toolkit, nursing student’ desirable characteristics, Thai qualifications framework

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40768 Potential of Landslides Based On Maximum Monthly Rainfall in Sumber Sari Village Watershed Tirtomoyo Wonogiri Indonesia

Authors: Heny Pratiwi, Niken Silmi Surjandari, Noegroho Djarwanti

Abstract:

This study was conducted to determine the potential for landslides as a result of monthly rainfall in a watershed. Rainfall data that will be used is rainfall from years 2007-2011. Research methods created by modeling the slope on some variation of angle in a row 30◦, 45◦, and 60◦ with a homogeneous layer of soil. Slope Stability Analysis using Method Fellenius. The results of the slope stability analysis without rain on slope 30◦, 45◦, and 60◦ respectively 1.3846, 1.0115, and 0.7284. Results in the absence of rain showed that the slope on the slope 45◦ are in critical condition and on a slope with a slope 60◦ already avalanche with safety factor value <1. The results in the rainy conditions shows slopes 30◦ are in critical condition with a value factor <1 due to the intensity of monthly rainfall> 250 mm/month.

Keywords: slope stability, monthly rainfall, infiltration, safety factor, Fellenius method

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40767 Designing an Effective Accountability Model for Islamic Azad University Using the Qualitative Approach of Grounded Theory

Authors: Davoud Maleki, Neda Zamani

Abstract:

The present study aims at exploring the effective accountability model of Islamic Azad University using a qualitative approach of grounded theory. The data of this study were obtained from semi-structured interviews with 25 professors and scholars in Islamic Azad University of Tehran who were selected by theoretical sampling method. In the data analysis, the stepwise method and Strauss and Corbin analytical methods (1992) were used. After identification of the main component (balanced response to stakeholders’ needs) and using it to bring the categories together, expressions and ideas representing the relationships between the main and subcomponents, and finally, the revealed components were categorized into six dimensions of the paradigm model, with the relationships among them, including causal conditions (7 components), main component (balanced response to stakeholders’ needs), strategies (5 components), environmental conditions (5 components), intervention features (4 components), and consequences (3 components). Research findings show an exploratory model for describing the relationships between causal conditions, main components, accountability strategies, environmental conditions, university environmental features, and that consequences.

Keywords: accountability, effectiveness, Islamic Azad University, grounded theory

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40766 Overview of Constructed Wetlands System for Greywater Treatment: Challenges, Advantages, and Sustainable Analysis

Authors: Iga Maliga

Abstract:

As developing country, Indonesia, retreatment for greywater is an important factor that guaranteeing water sustainability? But, its still not familiar in Indonesian society. Because they still use their old habit for wasting the water without retreatment. Differently, with industry wastewater, effect of domestic wastewater is not directly looked with naked eyes. Domestic wastewater that not gets treatment directly can affect pollution in water body or river. Its affected by accumulation many pollutants that include on water. This paper is trying to analyze the challenges and advantages on greywater treatment system based on Constructed Wetlands (CWs) system in Bandung, one of the biggest cities in Indonesia. Aside that, this paper also is trying to analyze sustainability aspects. There is economic, social and of course environment with two methods. The first, study literature is used to see the advantages and challenges that faced by Indonesia when CWs are applied. Secondly, quantitative method is used to get the society perception about retreatment of greywater. Then, it will get a conclusion that this technique not only good in theoretically but also practically.

Keywords: greywater, constructed wetlands, advantages, challenges, Bandung, sustainability analysis

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40765 The Employees' Classification Method in the Space of Their Job Satisfaction, Loyalty and Involvement

Authors: Svetlana Ignatjeva, Jelena Slesareva

Abstract:

The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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40764 Adaptive Auth - Adaptive Authentication Based on User Attributes for Web Application

Authors: Senthuran Manoharan, Rathesan Sivagananalingam

Abstract:

One of the main issues in system security is Authentication. Authentication can be defined as the process of recognizing the user's identity and it is the most important step in the access control process to safeguard data/resources from being accessed by unauthorized users. The static method of authentication cannot ensure the genuineness of the user. Due to this reason, more innovative authentication mechanisms came into play. At first two factor authentication was introduced and later, multi-factor authentication was introduced to enhance the security of the system. It also had some issues and later, adaptive authentication was introduced. In this research paper, the design of an adaptive authentication engine was put forward. The user risk profile was calculated based on the user parameters and then the user was challenged with a suitable authentication method.

Keywords: authentication, adaptive authentication, machine learning, security

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40763 Validity and Reliability of the Iranian Version of the Self-Expansion Questionnaire

Authors: Mehravar Javid, James Sexton, Farzaneh Amani, Kainaz Patravala

Abstract:

Self-expansion is a procedure through which people expand the dimensions of their self-concept by incorporating novel content into their sense and experience of identity. Greater self-expansion predicts positive consequences for individuals and romantic relationships. The self-expansion questionnaire (SEQ) originally developed by Lewandowski & Aron (2002) assumes that self-expansion is constituted of key components from the self-expansion model. This study aimed to confirm the factor structure of SEQ and adapt the questions of the scale to the Iranian culture. The sample included 190 participants who responded to 14 items and were selected by simple random sampling. Using Amos-21 and SPSS-21, descriptive statistics, Pearson correlation and Confirmatory Factor Analysis (CFA) were calculated. Cronbach’s alpha coefficient for total SEQ items was 0.92. Results of CFA supported the factor structure SEQ [RMSEA=0.08, GFI=0.88 and CFI=0.92] that showed the model has a good fit and also all the items of SEQ, have a high correlation and have a direct and significant relationship. So, the SEQ demonstrated acceptable psychometric properties in Tehran University students. Looking forward, it would be interesting and exciting to see the implications of the scale as applied to romantic relationships.

Keywords: validity, reliability, confirmatory factor analysis, self-expansion questionnaire

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40762 Reaching New Levels: Using Systems Thinking to Analyse a Major Incident Investigation

Authors: Matthew J. I. Woolley, Gemma J. M. Read, Paul M. Salmon, Natassia Goode

Abstract:

The significance of high consequence, workplace failures within construction continues to resonate with a combined average of 12 fatal incidents occurring daily throughout Australia, the United Kingdom, and the United States. Within the Australian construction domain, more than 35 serious, compensable injury incidents are reported daily. These alarming figures, in conjunction with the continued occurrence of fatal and serious, occupational injury incidents globally suggest existing approaches to incident analysis may not be achieving required injury prevention outcomes. One reason may be that, incident analysis methods used in construction have not kept pace with advances in the field of safety science and are not uncovering the full range system-wide contributory factors that are required to achieve optimal levels of construction safety performance. Another reason underpinning this global issue may also be the absence of information surrounding the construction operating and project delivery system. For example, it is not clear who shares the responsibility for construction safety in different contexts. To respond to this issue, to the author’s best knowledge, a first of its kind, control structure model of the construction industry is presented and then used to analyse a fatal construction incident. The model was developed by applying and extending the Systems Theoretic and Incident Model and Process method to hierarchically represent the actors, constraints, feedback mechanisms, and relationships that are involved in managing construction safety performance. The Causal Analysis based on Systems Theory (CAST) method was then used to identify the control and feedback failures involved in the fatal incident. The conclusions from the Coronial investigation into the event are compared with the findings stemming from the CAST analysis. The CAST analysis highlighted additional issues across the construction system that were not identified in the coroner’s recommendations, suggested there is a potential benefit in applying a systems theory approach to incident analysis in construction. The findings demonstrate the utility applying systems theory-based methods to the analysis of construction incidents. Specifically, this study shows the utility of the construction control structure and the potential benefits for project leaders, construction entities, regulators, and construction clients in controlling construction performance.

Keywords: construction project management, construction performance, incident analysis, systems thinking

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40761 Web 2.0 Enabling Knowledge-Sharing Practices among Students of IIUM: An Exploration of the Determinants

Authors: Shuaibu Hassan Usman, Ishaq Oyebisi Oyefolahan

Abstract:

This study was aimed to explore the latent factors in the web 2.0 enabled knowledge sharing practices instrument. Seven latent factors were identified through a factor analysis with orthogonal rotation and interpreted based on simple structure convergence, item loadings, and analytical statistics. The number of factors retains was based on the analysis of Kaiser Normalization criteria and Scree plot. The reliability tests revealed a satisfactory reliability scores on each of the seven latent factors of the web 2.0 enabled knowledge sharing practices. Limitation, conclusion, and future work of this study were also discussed.

Keywords: factor analysis, latent factors, knowledge sharing practices, students, web 2.0 enabled

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40760 Developing the Principal Change Leadership Non-Technical Competencies Scale: An Exploratory Factor Analysis

Authors: Tai Mei Kin, Omar Abdull Kareem

Abstract:

In light of globalization, educational reform has become a top priority for many countries. However, the task of leading change effectively requires a multidimensional set of competencies. Over the past two decades, technical competencies of principal change leadership have been extensively analysed and discussed. Comparatively, little research has been conducted in Malaysian education context on non-technical competencies or popularly known as emotional intelligence, which is equally crucial for the success of change. This article provides a validation of the Principal Change Leadership Non-Technical Competencies (PCLnTC) Scale, a tool that practitioners can easily use to assess school principals’ level of change leadership non-technical competencies that facilitate change and maximize change effectiveness. The overall coherence of the PCLnTC model was constructed by incorporating three theories: a)the change leadership theory whereby leading change is the fundamental role of a leader; b)competency theory in which leadership can be taught and learned; and c)the concept of emotional intelligence whereby it can be developed, fostered and taught. An exploratory factor analysis (EFA) was used to determine the underlying factor structure of PCLnTC model. Before conducting EFA, five important pilot test approaches were conducted to ensure the validity and reliability of the instrument: a)reviewed by academic colleagues; b)verification and comments from panel; c)evaluation on questionnaire format, syntax, design, and completion time; d)evaluation of item clarity; and e)assessment of internal consistency reliability. A total of 335 teachers from 12 High Performing Secondary School in Malaysia completed the survey. The PCLnTCS with six points Liker-type scale were subjected to Principal Components Analysis. The analysis yielded a three-factor solution namely, a)Interpersonal Sensitivity; b)Flexibility; and c)Motivation, explaining a total 74.326 per cent of the variance. Based on the results, implications for instrument revisions are discussed and specifications for future confirmatory factor analysis are delineated.

Keywords: exploratory factor analysis, principal change leadership non-technical competencies (PCLnTC), interpersonal sensitivity, flexibility, motivation

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40759 Land Suitability Scaling and Modeling for Assessing Crop Suitability in Some New Reclaimed Areas, Egypt

Authors: W. A. M. Abdel Kawy, Kh. M. Darwish

Abstract:

Adequate land use selection is an essential step towards achieving sustainable development. The main object of this study is to develop a new scale for land suitability system, which can be compatible with the local conditions. Furthermore, it aims to adapt the conventional land suitability systems to match the actual environmental status in term of soil types, climate and other conditions to evaluate land suitability for newly reclaimed areas. The new system suggests calculation of land suitability considering 20 factors affecting crop selection grouping into five categories; crop-agronomic, land management, development, environmental conditions and socio – economic status. Each factor is summed by each other to calculate the total points. The highest rating for each factor indicates the highest preference for the evaluated crop. The highest rated crops for each group are those with the highest points for the actual suitability. This study was conducted to assess the application efficiency of the new land suitability scale in recently reclaimed sites in Egypt. Moreover, 35 representative soil profiles were examined, and soil samples were subjected to some physical and chemical analysis. Actual and potential suitabilities were calculated by using the new land suitability scale. Finally, the obtained results confirmed the applicability of a new land suitability system to recommend the most promising crop rotation that can be applied in the study areas. The outputs of this research revealed that the integration of different aspects for modeling and adapting a proposed model provides an effective and flexible technique, which contribute to improve land suitability assessment for several crops to be more accurate and reliable.

Keywords: analytic hierarchy process, land suitability, multi-criteria analysis, new reclaimed areas, soil parameters

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40758 Adolescent Obesity Leading to Adulthood Cardiovascular Diseases among Punjabi Population

Authors: Manpreet Kaur, Badaruddoza, Sandeep Kaur Brar

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The increasing prevalence of adolescent obesity is one of the major causes to be hypertensive in adulthood. Various statistical methods have been applied to examine the performance of anthropometric indices for the identification of adverse cardiovascular risk profile. The present work was undertaken to determine the significant traditional risk factors through principal component factor analysis (PCFA) among population based Punjabi adolescents aged 10-18 years. Data was collected among adolescent children from different schools situated in urban areas of Punjab, India. Principal component factor analysis (PCFA) was applied to extract orthogonal components from anthropometric and physiometric variables. Association between components were explained by factor loadings. The PCFA extracted four factors, which explained 84.21%, 84.06% and 83.15% of the total variance of the 14 original quantitative traits among boys, girls and combined subjects respectively. Factor 1 has high loading of the traits that reflect adiposity such as waist circumference, BMI and skinfolds among both sexes. However, waist circumference and body mass index are the indicator of abdominal obesity which increases the risk of cardiovascular diseases. The loadings of these two traits have found maximum in girls adolescents (WC=0.924; BMI=0.905). Therefore, factor 1 is the strong indicator of atherosclerosis in adolescents. Factor 2 is predominantly loaded with blood pressures and related traits (SBP, DBP, MBP and pulse rate) which reflect the risk of essential hypertension in adolescent girls and combined subjects, whereas, factor 2 loaded with obesity related traits in boys (weight and hip circumferences). Comparably, factor 3 is loaded with blood pressures in boys and with height and WHR in girls, while factor 4 contains high loading of pulse pressure among boys, girls and combined group of adolescents.

Keywords: adolescent obesity, cvd, hypertension, punjabi population

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40757 Factor Analysis Based on Semantic Differential of the Public Perception of Public Art: A Case Study of the Malaysia National Monument

Authors: Yuhanis Ibrahim, Sung-Pil Lee

Abstract:

This study attempts to address factors that contribute to outline public art factors assessment, memorial monument specifically. Memorial monuments hold significant and rich message whether the intention of the art is to mark and commemorate important event or to inform younger generation about the past. Public monument should relate to the public and raise awareness about the significant issue. Therefore, by investigating the impact of the existing public memorial art will hopefully shed some lights to the upcoming public art projects’ stakeholders to ensure the lucid memorial message is delivered to the public directly. Public is the main actor as public is the fundamental purpose that the art was created. Perception is framed as one of the reliable evaluation tools to assess the public art impact factors. The Malaysia National Monument was selected to be the case study for the investigation. The public’s perceptions were gathered using a questionnaire that involved (n-115) participants to attain keywords, and next Semantical Differential Methodology (SDM) was adopted to evaluate the perceptions about the memorial monument. These perceptions were then measured with Reliability Factor and then were factorised using Factor Analysis of Principal Component Analysis (PCA) method to acquire concise factors for the monument assessment. The result revealed that there are four factors that influence public’s perception on the monument which are aesthetic, audience, topology, and public reception. The study concludes by proposing the factors for public memorial art assessment for the next future public memorial projects especially in Malaysia.

Keywords: factor analysis, public art, public perception, semantical differential methodology

Procedia PDF Downloads 478
40756 A Sociocybernetics Data Analysis Using Causality in Tourism Networks

Authors: M. Lloret-Climent, J. Nescolarde-Selva

Abstract:

The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: attractor, invariant set, tourist flows, orbits, social responsibility, tourism, tourist variables

Procedia PDF Downloads 483
40755 On the Design of a Secure Two-Party Authentication Scheme for Internet of Things Using Cancelable Biometrics and Physically Unclonable Functions

Authors: Behnam Zahednejad, Saeed Kosari

Abstract:

Widespread deployment of Internet of Things (IoT) has raised security and privacy issues in this environment. Designing a secure two-factor authentication scheme between the user and server is still a challenging task. In this paper, we focus on Cancelable Biometric (CB) as an authentication factor in IoT. We show that previous CB-based scheme fail to provide real two-factor security, Perfect Forward Secrecy (PFS) and suffer database attacks and traceability of the user. Then we propose our improved scheme based on CB and Physically Unclonable Functions (PUF), which can provide real two-factor security, PFS, user’s unlinkability, and resistance to database attack. In addition, Key Compromise Impersonation (KCI) resilience is achieved in our scheme. We also prove the security of our proposed scheme formally using both Real-Or-Random (RoR) model and the ProVerif analysis tool. For the usability of our scheme, we conducted a performance analysis and showed that our scheme has the least communication cost compared to the previous CB-based scheme. The computational cost of our scheme is also acceptable for the IoT environment.

Keywords: IoT, two-factor security, cancelable biometric, key compromise impersonation resilience, perfect forward secrecy, database attack, real-or-random model, ProVerif

Procedia PDF Downloads 75
40754 Multivalued Behavior for a Two-Level System Using Homotopy Analysis Method

Authors: Angelo I. Aquino, Luis Ma. T. Bo-ot

Abstract:

We use the Homotopy Analysis Method (HAM) to solve the system of equations modeling the two-level system and extract results which will pinpoint to turbulent behavior. We look at multi-valued solutions as indicative of turbulence or turbulent-like behavior. We take di erent speci c cases which result in multi-valued velocities. The solutions are in series form and application of HAM ensures convergence in some region.

Keywords: multivalued solutions, homotopy analysis method, two-level system, equation

Procedia PDF Downloads 570
40753 Analysis and Design of Simultaneous Dual Band Harvesting System with Enhanced Efficiency

Authors: Zina Saheb, Ezz El-Masry, Jean-François Bousquet

Abstract:

This paper presents an enhanced efficiency simultaneous dual band energy harvesting system for wireless body area network. A bulk biasing is used to enhance the efficiency of the adapted rectifier design to reduce Vth of MOSFET. The presented circuit harvests the radio frequency (RF) energy from two frequency bands: 1 GHz and 2.4 GHz. It is designed with TSMC 65-nm CMOS technology and high quality factor dual matching network to boost the input voltage. Full circuit analysis and modeling is demonstrated. The simulation results demonstrate a harvester with an efficiency of 23% at 1 GHz and 46% at 2.4 GHz at an input power as low as -30 dBm.

Keywords: energy harvester, simultaneous, dual band, CMOS, differential rectifier, voltage boosting, TSMC 65nm

Procedia PDF Downloads 377
40752 Expectation-Confirmation Model of Information System Continuance: A Meta-Analysis

Authors: Hui-Min Lai, Chin-Pin Chen, Yung-Fu Chang

Abstract:

The expectation-confirmation model (ECM) is one of the most widely used models for evaluating information system continuance, and this model has been extended to other study backgrounds, or expanded with other theoretical perspectives. However, combining ECM with other theories or investigating the background problem may produce some disparities, thus generating inaccurate conclusions. Habit is considered to be an important factor that influences the user’s continuance behavior. This paper thus critically examines seven pairs of relationships from the original ECM and the habit variable. A meta-analysis was used to tackle the development of ECM research over the last 10 years from a range of journals and conference papers published in 2005–2014. Forty-six journal articles and 19 conference papers were selected for analysis. The results confirm our prediction that a high effect size for the seven pairs of relationships was obtained (ranging from r=0.386 to r=0.588). Furthermore, a meta-analytic structural equation modeling was performed to simultaneously test all relationships. The results show that habit had a significant positive effect on continuance intention at p<=0.05 and that the six other pairs of relationships were significant at p<0.10. Based on the findings, we refined our original research model and an alternative model was proposed for understanding and predicting information system continuance. Some theoretical implications are also discussed.

Keywords: Expectation-confirmation theory, Expectation-confirmation model, Meta-analysis, meta-analytic structural equation modeling.

Procedia PDF Downloads 245
40751 Evaluating Factors Influencing Information Quality in Large Firms

Authors: B. E. Narkhede, S. K. Mahajan, B. T. Patil, R. D. Raut

Abstract:

Information quality is a major performance measure for an Enterprise Resource Planning (ERP) system of any firm. This study identifies various critical success factors of information quality. The effect of various critical success factors like project management, reengineering efforts and interdepartmental communications on information quality is analyzed using a multiple regression model. Here quantitative data are collected from respondents from various firms through structured questionnaire for assessment of the information quality, project management, reengineering efforts and interdepartmental communications. The validity and reliability of the data are ensured using techniques like factor analysis, computing of Cronbach’s alpha. This study gives relative importance of each of the critical success factors. The findings suggest that among the various factors influencing information quality careful reengineering efforts are the most influencing factor. This paper gives clear insight to managers and practitioners regarding the relative importance of critical success factors influencing information quality so that they can formulate a strategy at the beginning of ERP system implementation.

Keywords: Enterprise Resource Planning (ERP), information systems (IS), multiple regression, information quality

Procedia PDF Downloads 300
40750 Power System Stability Enhancement Using Self Tuning Fuzzy PI Controller for TCSC

Authors: Salman Hameed

Abstract:

In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

Procedia PDF Downloads 394