Search results for: key performance indicator (KPI)

Authors: Kamal Ray, Tapati Bhattacharya

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Private use of public office for private gain could be a tentative definition of corruption and most distasteful event of corruption is that it is not there, nor that it is pervasive, but it is socially acknowledged in the global economy, especially in the developing nations. We attempted to assess the interrelationship between the Corruption perception index (CPI) and the principal components of governance indicators as per World Bank like Control of Corruption (CC), rule of law (RL), regulatory quality (RQ) and government effectiveness (GE). Our empirical investigation concentrates upon the degree of reflection of governance indicators upon the CPI in order to single out the most powerful corruption-generating indicator in the selected countries. We have collected time series data on above governance indicators such as CC, RL, RQ and GE of the selected eleven countries from the year of 1996 to 2012 from World Bank data set. The countries are USA, UK, France, Germany, Greece, China, India, Japan, Thailand, Brazil, and South Africa. Corruption Perception Index (CPI) of the countries mentioned above for the period of 1996 to 2012is also collected. Graphical method of simple line diagram against the time series data on CPI is applied for quick view for the relative positions of different trend lines of different nations. The correlation coefficient is enough to assess primarily the degree and direction of association between the variables as we get the numerical data on governance indicators of the selected countries. The tool of Granger Causality Test (1969) is taken into account for investigating causal relationships between the variables, cause and effect to speak of. We do not need to verify stationary test as length of time series is short. Linear regression is taken as a tool for quantification of a change in explained variables due to change in explanatory variable in respect of governance vis a vis corruption. A bilateral positive causal link between CPI and CC is noticed in UK, index-value of CC increases by 1.59 units as CPI increases by one unit and CPI rises by 0.39 units as CC rises by one unit, and hence it has a multiplier effect so far as reduction in corruption is concerned in UK. GE causes strongly to the reduction of corruption in UK. In France, RQ is observed to be a most powerful indicator in reducing corruption whereas it is second most powerful indicator after GE in reducing of corruption in Japan. Governance-indicator like GE plays an important role to push down the corruption in Japan. In China and India, GE is proactive as well as influencing indicator to curb corruption. The inverse relationship between RL and CPI in Thailand indicates that ongoing machineries related to RL is not complementary to the reduction of corruption. The state machineries of CC in S. Africa are highly relevant to reduce the volume of corruption. In Greece, the variations of CPI positively influence the variations of CC and the indicator like GE is effective in controlling corruption as reflected by CPI. All the governance-indicators selected so far have failed to arrest their state level corruptions in USA, Germany and Brazil.

Keywords: corruption perception index, governance indicators, granger causality test, regression

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Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

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Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

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Authors: S. Ravichandra, D. V. L. N. Somayajulu

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Requirement of stakeholders for adding more details to the database is the main cause of the schema evolution in the relational database. Further, this schema evolution causes the instability to the database. Hence, it is aimed to define a metric suite for schema evolution of a relational database. The metric suite will calculate the metrics based on the features of the database, analyse the queries on the database and measures the coupling, cohesion and component dependencies of the schema for existing and evolved versions of the database. This metric suite will also provide an indicator for the problems related to the stability and usability of the evolved database. The degree of change in the schema of a database is presented in the forms of graphs that acts as an indicator and also provides the relations between various parameters (metrics) related to the database architecture. The acquired information is used to defend and improve the stability of database architecture. The challenges arise in incorporating these metrics with varying parameters for formulating a suitable metric suite are discussed. To validate the proposed metric suite, an experimentation has been performed on publicly available datasets.

Keywords: cohesion, coupling, entropy, metric suite, schema evolution

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Authors: P. Góes, J. Manzi

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This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.

Keywords: energy, efficiency, entropy, reactive

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Authors: Ramin Shadani

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This study introduces adaptive performance as a key organizational performance dimension and explores the relationship between the dimensions of a learning organization and adaptive performance. A survey was therefore conducted using the dimensions of the Learning Organization Questionnaire (DLOQ), followed by factor analysis and structural equation modeling in order to investigate the dynamics between learning organization practices and adaptive performance. Results confirm that adaptive performance is indeed one important dimension of organizational performance. The study also shows that perceived knowledge and adaptive performance mediate the positive relationship between the practices of a learning organization with perceived financial performance. We extend existing DLOQ research by demonstrating that adaptive performance, as a nonfinancial organizational learning outcome, has a significant impact on financial performance. Our study also provides additional validation of the measures of DLOQ's performance. Indeed, organizations need to take a glance at how the activities of learning and development can provide better overall improvement in performance, especially in enhancing adaptive capability. The study has provided requisite empirical support that activities of learning and development within organizations allow much-improved intangible performance outcomes, especially through adaptive performance.

Keywords: adaptive performance, continuous learning, financial performance, leadership style, organizational learning, organizational performance

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Authors: Henrie Yunianto, Dermawan Wibisono

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PT. XYZ is a family business (private company) in Indonesia that provide an educational program and consultation services. Since its establishment in 2011, the company has run without any strategic management system implemented. Though the company could survive until now. The management of PT. XYZ sees the business opportunity for such product is huge, even though the targeted market is very specific (niche), the volume is large (due to large population of Indonesia) and numbers of competitors are low (now). It can be said if the product life cycle is in between ‘Introduction stage’ and ‘growth’ stage. It is observed that nowadays the new entrants (competitors) are increasing, thus PT. XYZ consider reacting in facing the intense business rivalry by conducting the business in an appropriate manner. A Performance Management System is important to be implemented in accordance with the business sustainability and growth. The framework of Performance Management System chosen is Integrated Performance Management System (IPMS). IPMS framework has the advantages of its simplicity, linkage between its business variables and indicators where the company can see the connections between all factors measured. IPMS framework consists of perspectives: (1) Business Result, (2) Internal Processes, (3) Resource Availability. Variables and indicators were examined through deep analysis of the business external and internal environments, Strength-Weakness-Opportunity-Threat (SWOT) analysis, Porter’s five forces analysis. Analytical Hierarchy Process (AHP) analysis was then used to quantify the weight of each variable/indicators. AHP is needed since in this study, PT. XYZ, the data of existing performance indicator was not available. Later, where the IPMS is implemented, the real data measured can be examined to determine the weight factor of each indicators using correlation analysis (or other methods). In this study of IPMS design for PT. XYZ, the analysis shows that with current company goals, along with the AHP methodology, the critical indicators for each perspective are: (1) Business results: Customer satisfaction and Employee satisfaction, (2) Internal process: Marketing performance, Supplier quality, Production quality, Continues improvement; (3) Resources Availability: Leadership and company culture & value, Personal Competences, Productivity. Company and/or organization require performance management system to help them in achieving their vision and mission. Company strategy will be effectively defined and addressed by using performance management system. Integrated Performance Management System (IPMS) framework and AHP analysis help us in quantifying the factors which influence the business output expected.

Keywords: analytical hierarchy process, business strategy, differentiation strategy, integrated performance management system

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Authors: M. Cizmesija, N. Erjavec, V. Bahovec

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While the European Union (EU) harmonized methodology is a benchmark of worldwide used business survey (BS) methodology, the choice of variables that are components of the confidence indicators, as the leading indicators, is not strictly determined and unique. Therefore, the aim of this paper is to investigate and to quantify the relationship between all business survey variables in manufacturing industry and industrial production as a reference macroeconomic series in Croatia. The assumption is that there are variables in the business survey, that are not components of Industrial Confidence Indicator (ICI) and which can accurately (and sometimes better then ICI) predict changes in Croatian industrial production. Empirical analyses are conducted using quarterly data of BS variables in manufacturing industry and Croatian industrial production over the period from the first quarter 2005 to the first quarter 2013. Research results confirmed the assumption: three BS variables which is not components of ICI (competitive position, demand and liquidity) are the best leading indicator then ICI, in forecasting changes in Croatian industrial production instantaneously, with one, two or three quarter ahead.

Keywords: balance, business survey, confidence indicators, industrial production, forecasting

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Authors: M. Peña Aguilar Juan, Valencia Luis, Pastrana Alberto, Nava Estefany, A. Martinez, M. Vivanco, A. Castañeda

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This paper seeks to compare the innovation of Mexico from an economic and human perspective, with the seven most innovative countries according to the Global Innovation Index 2013, done by the World Intellectual Property Organization (WIPO). The above analysis suggests nine dimensions: Expenditure on R & D, intellectual property, appropriate environment to conduct business, economic stability, and triple helix for R & D, ICT Infrastructure, education, human resources and quality of life. Each dimension is represented by an indicator which is later used to construct a radial graph that compares the innovative capacity of the countries analysed. As a result, it is proposed a new indicator of innovation called The Area of Innovation. Observations are made from the results, and finally as a conclusion, those items or dimensions in which Mexico suffers lag in innovation are identify.

Keywords: dimension, measure, innovation level, economy, radar chart

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Authors: Pranav Ajmera, Amit Kharat, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Purnachandra Lamghare

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The cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR, that is, a value greater than 0.55, is often an indicator of an underlying pathological condition. The accurate prediction of an abnormal CTR from chest X-rays (CXRs) aids in the early diagnosis of clinical conditions. We propose a deep learning-based model for automatic CTR calculation that can assist the radiologist with the diagnosis of cardiomegaly and optimize the radiology flow. The study population included 1012 posteroanterior (PA) CXRs from a single institution. The Attention U-Net deep learning (DL) architecture was used for the automatic calculation of CTR. A CTR of 0.55 was used as a cut-off to categorize the condition as cardiomegaly present or absent. An observer performance test was conducted to assess the radiologist's performance in diagnosing cardiomegaly with and without artificial intelligence (AI) assistance. The Attention U-Net model was highly specific in calculating the CTR. The model exhibited a sensitivity of 0.80 [95% CI: 0.75, 0.85], precision of 0.99 [95% CI: 0.98, 1], and a F1 score of 0.88 [95% CI: 0.85, 0.91]. During the analysis, we observed that 51 out of 1012 samples were misclassified by the model when compared to annotations made by the expert radiologist. We further observed that the sensitivity of the reviewing radiologist in identifying cardiomegaly increased from 40.50% to 88.4% when aided by the AI-generated CTR. Our segmentation-based AI model demonstrated high specificity and sensitivity for CTR calculation. The performance of the radiologist on the observer performance test improved significantly with AI assistance. A DL-based segmentation model for rapid quantification of CTR can therefore have significant potential to be used in clinical workflows.

Keywords: cardiomegaly, deep learning, chest radiograph, artificial intelligence, cardiothoracic ratio

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Authors: Aliya K. Salahova

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Scientific thinking is a fundamental cognitive skill that plays a crucial role in preparing young minds for an increasingly complex world. This study explores the connection between scientific thinking and the ability to ask questions in children aged 5-9. The research aims to identify and assess how questioning ability serves as an indicator of scientific thinking development in this age group. A longitudinal investigation was conducted over a span of 240 weeks, involving 72 children from diverse backgrounds. The participants were divided into an experimental group, engaging in weekly STEM activities, and a control group with no STEM involvement. The development of scientific thinking was evaluated through a comprehensive assessment of questioning skills, hypothesis formulation, logical reasoning, and problem-solving abilities. The findings reveal a significant correlation between the ability to ask questions and the level of scientific thinking in children aged 5-9. Participants in the experimental group exhibited a remarkable improvement in their questioning ability, which positively influenced their scientific thinking growth. In contrast, the control group, devoid of STEM activities, showed minimal progress in questioning skills and subsequent scientific thinking development. This study highlights the pivotal role of questioning ability as a key indicator of scientific thinking in young children. The results provide valuable insights for educators and researchers, emphasizing the importance of fostering and nurturing questioning skills to enhance scientific thinking capabilities from an early age. The implications of these findings are crucial for designing effective educational interventions to promote scientific curiosity and critical thinking in the next generation of scientific minds.

Keywords: scientific thinking, education, STEM, intervention, psychology, pedagogy, collaborative learning, longitudinal study

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Authors: Seyedeh Belin Tavakoly Sany, H. Rosli, R. Majid, S. Aishah

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In this study, water monitoring was performed from Nov. 2012 to Oct. 2013 to assess water quality and evaluate the spatial and temporal distribution of physicochemical and biological variables in water. Water samples were collected from 10 coastal water stations of West Port. In the case of water-quality assessment, multi-metric indices and operational indicators have been proposed to classify the trophic status at different stations. The trophic level of West Port coastal water ranges from eutrophic to hypertrophic. Chl-a concentration was used to estimate the biological response of phytoplankton biomass and indicated eutrophic conditions in West Port and mesotrophic conditions at the control site. During the study period, no eutrophication events or secondary symptoms occurred, which may be related to hydrodynamic turbulence and water exchange, which prevent the development of eutrophic conditions in the West Port.

Keywords: water quality, multi-metric indices, operational indicator, Malaysia, West Port

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Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

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Sport performance analysis is a technique that is becoming every year more important for athletes of every level. Many techniques have been developed to measure and analyse efficiently the performance of athletes in some sports, but in combat sports these techniques found in many times their limits, due to the high interaction between the two opponents during the competition. In this paper the problem will be framed. Moreover the physical performance measurement problem will be analysed and three different techniques to manage it will be presented. All the techniques have been used to analyse the performance of 22 high level Judo athletes.

Keywords: sport performance, physical performance, judo, performance coefficients

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Authors: Sherly M. A., Varsha Vijaykumar, Subhankar Karmakar, Terence Chan, Christian Rau

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This study aims at proposing an indicator-based framework for assessing social vulnerability of any coastal megacity to floods. The final set of indicators of social vulnerability are chosen from a set of feasible and available indicators which are prepared using a Geographic Information System (GIS) framework on a smaller scale considering 1-km grid cell to provide an insight into the spatial variability of vulnerability. The optimal weight for each individual indicator is assigned using data envelopment analysis (DEA) as it avoids subjective weights and improves the confidence on the results obtained. In order to de-correlate and reduce the dimension of multivariate data, principal component analysis (PCA) has been applied. The proposed methodology is demonstrated on twenty four wards of Mumbai under the jurisdiction of Municipal Corporation of Greater Mumbai (MCGM). This framework of vulnerability assessment is not limited to the present study area, and may be applied to other urban damage centers.

Keywords: urban floods, vulnerability, data envelopment analysis, principal component analysis

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Authors: Fatemeh Abbasi, Sahand Daneshvar

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Productivity is one of the essential goals of companies to improve performance, which as a strategy-oriented method, determines the basis of the company's economic growth. The history of productivity goes back centuries, but most researchers defined productivity as the relationship between a product and the factors used in production in the early twentieth century. Productivity as the optimal use of available resources means that "more output using less input" can increase companies' economic growth and prosperity capacity. Also, having a quality life based on economic progress depends on productivity growth in that society. Therefore, productivity is a national priority for any developed country. There are several methods for calculating productivity growth measurements that can be divided into parametric and non-parametric methods. Parametric methods rely on the existence of a function in their hypotheses, while non-parametric methods do not require a function based on empirical evidence. One of the most popular non-parametric methods is Data Envelopment Analysis (DEA), which measures changes in productivity over time. The DEA evaluates the productivity of decision-making units (DMUs) based on mathematical models. This method uses multiple inputs and outputs to compare the productivity of similar DMUs such as banks, government agencies, companies, airports, Etc. Non-parametric methods are themselves divided into the frontier and non frontier approaches. The Malmquist productivity index (MPI) proposed by Caves, Christensen, and Diewert (1982), the Hicks–Moorsteen productivity index (HMPI) proposed by Bjurek (1996), or the Luenberger productivity indicator (LPI) proposed by Chambers (2002) are powerful tools for measuring productivity changes over time. This study will compare the Malmquist, Hicks–Moorsteen, and Luenberger indices theoretically and empirically based on DEA models and review their strengths and weaknesses.

Keywords: data envelopment analysis, Hicks–Moorsteen productivity index, Leuenberger productivity indicator, malmquist productivity index

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Authors: Günther Schuh, Christina König, Toni Drescher

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One of the key factors for the competitiveness and market success of technology-driven companies is the timely provision of information about emerging technologies, changes in existing technologies, as well as relevant related changes in the market's structures and participants. Therefore, many companies conduct technology intelligence (TI) activities to ensure an early identification of appropriate technologies and other (weak) signals. One base activity of TI is technology monitoring, which is defined as the systematic tracking of developments within a specified topic of interest as well as related trends over a long period of time. Due to the very large number of dynamically changing parameters within the technological and the market environment of a company as well as their possible interdependencies, it is necessary to focus technology monitoring on specific indicators or other criteria, which are able to point out technological developments and market changes. In addition to the execution of a literature review on existing approaches, which mainly propose patent-based indicators, it is examined in this paper whether indicator systems from other branches such as risk management or economic research could be transferred to technology monitoring in order to enable an efficient and focused technology monitoring for companies.

Keywords: technology forecasting, technology indicator, technology intelligence, technology management, technology monitoring

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Authors: Oludamilare Bode Adewuyi, Yanxia Sun, Isaiah Gbadegesin Adebayo

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Voltage stability analysis is crucial to the reliable and economic operation of power systems. The power system of developing nations is more susceptible to failures due to the continuously increasing load demand, which is not matched with generation increase and efficient transmission infrastructures. Thus, most power systems are heavily stressed, and the planning of extra generation from distributed generation sources needs to be efficiently done so as to ensure the security of the power system. Some voltage stability index-based approach for DG siting has been reported in the literature. However, most of the existing voltage stability indices, though sufficient, are found to be inaccurate, especially for overloaded power systems. In this paper, the performance of a relatively different approach using a line voltage stability margin indicator, which has proven to have better accuracy, has been presented and compared with a conventional line voltage stability index for DG siting using the Nigerian 28 bus system. Critical boundary index (CBI) for voltage stability margin estimation was deployed to identify suitable locations for DG placement, and the performance was compared with DG placement using the Novel Line Stability Index (NLSI) approach. From the simulation results, both CBI and NLSI agreed greatly on suitable locations for DG on the test system; while CBI identified bus 18 as the most suitable at system overload, NLSI identified bus 8 to be the most suitable. Considering the effect of the DG placement at the selected buses on the voltage magnitude profile, the result shows that the DG placed on bus 18 identified by CBI improved the performance of the power system better.

Keywords: voltage stability analysis, voltage collapse, voltage stability index, distributed generation

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Authors: María Victoria Alvarez Magañini, Lautaro Nahuel Rubbi

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According to different theories, the hegemonic war between the United States and the People's Republic of China seems to be imminent. However, nowadays, it is clear that China's conventional military capacity is inferior to that of the United States. Nevertheless, the conditions that in the past were considered to be an indicator of validity in asymmetrical warfare, at present, in a possible asymmetric war scenario, are no longer considered to be taken as such. The military capacity is not the only concept that represents the main indicator of victory. The organisation and the use of forces are also an essential part of it. The present paper aims to analyze the Chinese Defense Strategy in relation to the concept of asymmetric warfare in the face of a possible war with the United States. The starting point will be developed on the basis of application of the theory which corresponds to the concept aforementioned making focus on recent developments of the People’s Republic of China in the field of non-conventional defense. A comparative analysis of the conventional forces of both powers/countries will also be carried out.

Keywords: asymmetric warfare, China, United States, hegemonic warfare

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Authors: Hanee Ryu

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The former president Lee Myung-bak's administration of Korea presented “green growth” as a catchphrase from 2008. He declared “low-carbon, green growth” the nation's vision for the next decade according to United Nation Framework on Climate Change. The government designed omnidirectional policy for low-carbon and green growth with concentrating all effort of departments. The structural change was expected because this slogan is the identity of the government, which is strongly driven with the whole department. After his administration ends, the purpose of this paper is to quantify the policy effect and to compare with the value of the other OECD countries. The major target values under direct policy objectives were suggested, but it could not capture the entire landscape on which the policy makes changes. This paper figures out the policy impacts through comparing the value of ex-ante between the one of ex-post. Furthermore, each index level of Korea’s low-carbon and green growth comparing with the value of the other OECD countries. To measure the policy effect, indicators international organizations have developed are considered. Environmental Sustainable Index (ESI) and Environmental Performance Index (EPI) have been developed by Yale University’s Center for Environmental Law and Policy and Columbia University’s Center for International Earth Science Information Network in collaboration with the World Economic Forum and Joint Research Center of European Commission. It has been widely used to assess the level of natural resource endowments, pollution level, environmental management efforts and society’s capacity to improve its environmental performance over time. Recently OCED publish the Green Growth Indicator for monitoring progress towards green growth based on internationally comparable data. They build up the conceptual framework and select indicators according to well specified criteria: economic activities, natural asset base, environmental dimension of quality of life and economic opportunities and policy response. It considers the socio-economic context and reflects the characteristic of growth. Some selected indicators are used for measuring the level of changes the green growth policies have induced in this paper. As results, the CO2 productivity and energy productivity show trends of declination. It means that policy intended industry structure shift for achieving carbon emission target affects weakly in the short-term. Increasing green technologies patents might result from the investment of previous period. The increasing of official development aids which can be immediately embarked by political decision with no time lag present only in 2008-2009. It means international collaboration and investment to developing countries via ODA has not succeeded since the initial stage of his administration. The green growth framework makes the public expect structural change, but it shows sporadic effect. It needs organization to manage it in terms of the long-range perspectives. Energy, climate change and green growth are not the issue to be handled in the one period of the administration. The policy mechanism to transfer cost problem to value creation should be developed consistently.

Keywords: comparing ex-ante between ex-post indicator, green growth indicator, implication for green growth policy, measuring policy effect

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Authors: Ting (Grace) Lin, Jianhong (Cecilia) Xia, Todd Robinson

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Accessibility analysis, examining people’s ability to access facilities and destinations, is a fundamental assessment for transport planning, policy making, and social exclusion research. Dynamic accessibility which measures accessibility in real-time traffic environment has been an advanced accessibility indicator in transport research. It is also a useful indicator to help travelers to understand travel time daily variability, assists traffic engineers to monitor traffic congestions, and finally develop effective strategies in order to mitigate traffic congestions. This research involved real-time traffic information by collecting travel time data with 15-minute interval via the TomTom^® API. A framework for measuring dynamic accessibility was then developed based on the gravity theory and accessibility dichotomy theory through space and time interpolation. Finally, the dynamic accessibility can be derived at any given time and location under dynamic accessibility spatial analysis framework.

Keywords: dynamic accessibility, hot spot, transport research, TomTom® API

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Authors: Kaleeswari R. K., Seevagan L .

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Soil quality in an agroecosystem is influenced by the cropping system, water and soil fertility management. A valid soil quality index would help to assess the soil and crop management practices for desired productivity and soil health. The soil quality indices also provide an early indication of soil degradation and needy remedial and rehabilitation measures. Imbalanced fertilization and inadequate organic carbon dynamics deteriorate soil quality in an intensive cropping system. The rice soil ecosystem is different from other arable systems since rice is grown under submergence, which requires a different set of key soil attributes for enhancing soil quality and productivity. Assessment of the soil quality index involves indicator selection, indicator scoring and comprehensive score into one index. The most appropriate indicator to evaluate soil quality can be selected by establishing the minimum data set, which can be screened by linear and multiple regression factor analysis and score function. This investigation was carried out in intensive rice cultivating regions (having >1.0 lakh hectares) of Tamil Nadu viz., Thanjavur, Thiruvarur, Nagapattinam, Villupuram, Thiruvannamalai, Cuddalore and Ramanathapuram districts. In each district, intensive rice growing block was identified. In each block, two sampling grids (10 x 10 sq.km) were used with a sampling depth of 10 – 15 cm. Using GIS coordinates, and soil sampling was carried out at various locations in the study area. The number of soil sampling points were 41, 28, 28, 32, 37, 29 and 29 in Thanjavur, Thiruvarur, Nagapattinam, Cuddalore, Villupuram, Thiruvannamalai and Ramanathapuram districts, respectively. Principal Component Analysis is a data reduction tool to select some of the potential indicators. Principal Component is a linear combination of different variables that represents the maximum variance of the dataset. Principal Component that has eigenvalues equal or higher than 1.0 was taken as the minimum data set. Principal Component Analysis was used to select the representative soil quality indicators in rice soils based on factor loading values and contribution percent values. Variables having significant differences within the production system were used for the preparation of the minimum data set. Each Principal Component explained a certain amount of variation (%) in the total dataset. This percentage provided the weight for variables. The final Principal Component Analysis based soil quality equation is SQI = ∑ i=1 (W ᵢ x S ᵢ); where S- score for the subscripted variable; W-weighing factor derived from PCA. Higher index scores meant better soil quality. Soil respiration, Soil available Nitrogen and Potentially Mineralizable Nitrogen were assessed as soil quality indicators in rice soil of the Cauvery Delta zone covering Thanjavur, Thiruvavur and Nagapattinam districts. Soil available phosphorus could be used as a soil quality indicator of rice soils in the Cuddalore district. In rain-fed rice ecosystems of coastal sandy soil, DTPA – Zn could be used as an effective soil quality indicator. Among the soil parameters selected from Principal Component Analysis, Microbial Biomass Nitrogen could be used quality indicator for rice soils of the Villupuram district. Cauvery Delta zone has better SQI as compared with other intensive rice growing zone of Tamil Nadu.

Keywords: soil quality index, soil attributes, soil mapping, and rice soil

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Authors: Svetlana Pushkar, Oleg Verbitsky

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An energy-conscious design for a classroom in a hot-humid climate is reanalyzed. The hypothesis of this study is that use of photovoltaic (PV) electricity generation in building operation energy consumption will lead to re-analysis of the energy-conscious design. Therefore, the objective of this study is to reanalyze the energy-conscious design by evaluating the environmental impact of operational energy with PV electrical generation. Using the hierarchical design structure of Eco-indicator 99, the alternatives for energy-conscious variables are statistically evaluated by applying a two-stage nested (hierarchical) ANOVA. The recommendations for the preferred solutions for application of glazing types, wall insulation, roof insulation, window size, roof mass, and window shading design alternatives were changed (for example, glazing type recommendations were changed from low-emissivity glazing, green, and double- glazed windows to low-emissivity glazing only), whereas the applications for the lighting control system and infiltration are not changed. Such analysis of operational energy can be defined as environment-conscious analysis.

Keywords: ANOVA, Eco-Indicator 99, energy-conscious design, hot–humid climate, photovoltaic

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Authors: Pedro Cabrales, Scott Caroen, Tony R. Reid, Bryan Oronsky

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Introduction and Purpose RRx-001 is an NLRP3 inhibitor and Nrf2 agonist in Phase 3 trials for the treatment of cancer. The purpose of this study was to examine whether treatment with RRx-001, given itsanti-inflammatory and antioxidant properties, improvedexercise and skeletal muscle oxidative capacity in mice on the generalpremiss that better health outcomes correlatewith more activity. Material and Methods Male and female adult mice (n=6 per group) were subjected to an endurance exercise capacity (EEC)test until exhaustion on a motorized treadmill after 3 once weekly doses of either RRx-001 5 mg/kg, RRx-001 2 mg/kg, or vehicle. The EEC protocol consisted of a treadmill velocity of 30meters per min at an uphill inclination (slope of 10%) until the mice reached fatigue, which was defined as the inability of the mice to maintain the appropriate pace despitecontinuous hand stimulation for 1 min. The concentration of malondialdehyde (MDA), an indicator of lipid peroxidation, and creatine kinase (CK), an indicator of muscle damage, in the blood samples collected immediately after the acute exercise was determined with a commercial ELISA assay kit. ResultsThe exhaustive exercise times of the RRx-001 groups were significantly longer than that of the vehicle group (p<0.05) by weeks 2 and 3. In addition, MDA levels in the gastrocnemius, soleus, and extensor digitorum longus muscles were significantly lower than those of the vehicle group were (p<0.05), as were the serum CK levels(p<0.05). ConclusionsIn conclusion, this study found that RRx-001 has anti-fatigue properties, as evidenced by an increase in exercise capacity with RRx-001 treatment, and protects against strenuous exercise-induced muscle damage and lipid peroxidation. This data potentially supports the use of RRx-001 in the clinic to improve exercise performance and reduce physical fatigue.

Keywords: RRx-001, anti-fatigue, muscle protection, increased exercise tolerance, lipid peroxidation

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Authors: Gizem İntepe, Eti Mizrahi

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Investment and financing decisions are influenced by various economic features. Detailed analysis should be conducted in order to make decisions not only by companies but also by governments. Such analysis can be conducted either at the company level or on a sectoral basis to reduce risks and to maximize profits. Sectoral disaggregation caused by seasonality effects, subventions, data advantages or disadvantages may appear in sectors behaving parallel to BIST (Borsa Istanbul stock exchange) Index. Proposed logistic indices could serve market needs as a decision parameter in sectoral basis and also helps forecasting activities in import export volume changes. Also it is an indicator of logistic activity, which is also a sign of economic mobility at the national level. Publicly available data from “Ministry of Transport, Maritime Affairs and Communications” and “Turkish Statistical Institute” is utilized to obtain five logistics indices namely as; exLogistic, imLogistic, fLogistic, dLogistic and cLogistic index. Then, efficiency and reliability of these indices are tested.

Keywords: economic activity, export trade data, import trade data, logistics indices

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Authors: Homer Hermes De Dios, Dewoowoogen Baclayon

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The community assemblages of reef fishes was conducted in ten marine sanctuaries and ten non-marine sanctuary areas in Sogod Bay, Southern Leyte, Philippines from 2014-2015. A total of 223 species belonging to 39 families of reef fishes in Sogod Bay were recorded. Family Pomacentridae (e.g. damsel fishes) has the highest number of species (42), followed by Labridae or wrasses (27), Chaetodonthidae or butterfly fish (22), Scaridae or parrotfishes (17), and Acanthuridae (surgeonfishes) and Pomacanthidae (angelfishes) both with 10 species. Two of the recorded fish species were included in the IUCN Red List, wherein one is near threatened (Chlorurus bowersi) and the other is endangered species (Cheilinus undulatus). The mean total fish biomass (target + indicator + major or other fish) in MPA was significantly higher (13,468 g/500m2 or equivalent to 26.94 mt/km2) than Non-MPA with 7,408 g/500m2 or 15,216mt/km2 in Non-MPA. The mean total fish biomass in MPAs in Sogod Bay can be categorized as high (21-40 mt/km2) with minimal fishing and medium or slightly moderately fished (11-20 mt/km2) in Non-MPAs. The mean (±SE) biomass of target fishes was significantly higher in MPA than Non-MPA and differ significantly across two depths. The target fish biomass was significantly higher in Limasawa Marine Sanctuary (13,569 g/500m2) followed by Lungsodaan Marine Sanctuary in Padre Burgos (11,884 g/500m2) and the lowest was found in San Isidro (735 g/500m2). The mean total fish density (target + indicator + major or other fish) did not differ between Marine Protected area (607.912 fishes/500m2 or 1215.824 fishes/1000m2) and 525.937 fishes/500m2 in non-Marine Protected Area and can be categorized as moderate (667-2267mt/km2). The mean density of target fishes was significantly (p=0.022) higher in deeper areas (12-15m) than in shallow areas but did not differ significantly between MPAs and Non-MPA. No significant difference of the biomass and density for indicator and other fishes in MPAs and Non-MPAs.

Keywords: abundance, density, species richness, target fish, coral reef management

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Authors: Naomi Grigoryan, Alexandros Loutsioli Daskalakis, Anna Elisse Uy, Yihe Huang, Aude Laurent (Webanck)

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In response to the building and construction sectors accounting for a third of all energy demand and emissions, the European Union has placed new laws and regulations in the construction sector that emphasize material circularity, energy efficiency, biodiversity, and social impact. Existing design tools assess sustainability in early-stage design for products or buildings; however, there is no standardized methodology for measuring the circularity performance of building components. Existing assessment methods for building components focus primarily on carbon footprint but lack the comprehensive analysis required to design for circularity. The research conducted in this paper covers the parameters needed to assess sustainability in the design process of architectural products such as doors, windows, and facades. It maps a framework for a tool that assists designers with real-time sustainability metrics. Considering the life cycle of building components such as façades, windows, and doors involves the life cycle stages applied to product design and many of the methods used in the life cycle analysis of buildings. The current industry standards of sustainability assessment for metal building components follow cradle-to-grave life cycle assessment (LCA), track Global Warming Potential (GWP), and document the parameters used for an Environmental Product Declaration (EPD). Developed by the Ellen Macarthur Foundation, the Material Circularity Indicator (MCI) is a methodology utilizing the data from LCA and EPDs to rate circularity, with a "value between 0 and 1 where higher values indicate a higher circularity+". Expanding on the MCI with additional indicators such as the Water Circularity Index (WCI), the Energy Circularity Index (ECI), the Social Circularity Index (SCI), Life Cycle Economic Value (EV), and calculating biodiversity risk and uncertainty, the assessment methodology of an architectural product's impact can be targeted more specifically based on product requirements, performance, and lifespan. Broadening the scope of LCA calculation for products to incorporate aspects of building design allows product designers to account for the disassembly of architectural components. For example, the Material Circularity Indicator for architectural products such as windows and facades is typically low due to the impact of glass, as 70% of glass ends up in landfills due to damage in the disassembly process. The low MCI can be combatted by expanding beyond cradle-to-grave assessment and focusing the design process on disassembly, recycling, and repurposing with the help of real-time assessment tools. Design for Disassembly and Urban Mining has been integrated within the construction field on small scales as project-based exercises, not addressing the entire supply chain of architectural products. By adopting more comprehensive sustainability metrics and incorporating uncertainty calculations, the sustainability assessment of building components can be more accurately assessed with decarbonization and disassembly in mind, addressing the large-scale commercial markets within construction, some of the most significant contributors to climate change.

Keywords: architectural products, early-stage design, life cycle assessment, material circularity indicator

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Authors: Sina Moradi, Sanly Liu, Christopher W. K. Chow, John Van Leeuwen, David Cook, Mary Drikas, Soha Habibi, Rose Amal

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In recent years, chloramine has been widely used for both primary and secondary disinfection. However, a major concern with the use of chloramine as a secondary disinfectant is the decay of chloramine and nitrification occurrence. The management of chloramine decay and the prevention of nitrification are critical for water utilities managing chloraminated drinking water distribution systems. The detection and monitoring of nitrification episodes is usually carried out through measuring certain water quality parameters, which are commonly referred to as indicators of nitrification. The approach taken in this study was to collect water samples from different sites throughout a drinking water distribution systems, Tailem Bend – Keith (TBK) in South Australia, and analyse the samples by high performance size exclusion chromatography (HPSEC). We investigated potential association between the water qualities from HPSEC analysis with chloramine decay and/or nitrification occurrence. MATLAB 8.4 was used for data processing of HPSEC data and chloramine decay. An increase in the absorbance signal of HPSEC profiles at λ=230 nm between apparent molecular weights of 200 to 1000 Da was observed at sampling sites that experienced rapid chloramine decay and nitrification while its absorbance signal of HPSEC profiles at λ=254 nm decreased. An increase in absorbance at λ=230 nm and AMW < 500 Da was detected for Raukkan CT (R.C.T), a location that experienced nitrification and had significantly lower chloramine residual (<0.1 mg/L). This increase in absorbance was not detected in other sites that did not experience nitrification. Moreover, the UV absorbance at 254 nm of the HPSEC spectra was lower at R.C.T. than other sites. In this study, a chloramine residual index (C.R.I) was introduced as a new indicator of chloramine decay and nitrification occurrence, and is defined based on the ratio of area underneath the HPSEC spectra at two different wavelengths of 230 and 254 nm. The C.R.I index is able to indicate DS sites that experienced nitrification and rapid chloramine loss. This index could be useful for water treatment and distribution system managers to know if nitrification is occurring at a specific location in water distribution systems.

Keywords: nitrification, HPSEC, chloramine decay, chloramine residual index

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Authors: Juan Carlos Baena, Zhongxiao Peng

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Ultra-high molecular weight polyethylene (UHMWPE) is extensively used in industrial and biomedical fields. The slippery nature of UHMWPE makes this material suitable for surface bearing applications, however, the operational conditions limit the lubrication efficiency, inducing boundary and mixed lubrication in the tribological system. The lack of lubrication in a tribological system intensifies friction, contact stress and consequently, operating temperature. With temperature increase, the material’s mechanical properties are affected, and the lifespan of the component is reduced. The understanding of how mechanical properties and wear performance of UHMWPE change when the temperature is increased has not been clearly identified. The understanding of the wear and mechanical performance of UHMWPE at different temperature is important to predict and further improve the lifespan of these components. This study evaluates the effects of temperature variation in a range of 20 °C to 60 °C on the hardness and the wear resistance of UHMWPE. A reduction of the hardness and wear resistance was observed with the increase in temperature. The variation of the wear rate increased 94.8% when the temperature changed from 20 °C to 50 °C. Although hardness is regarded to be an indicator of the material wear resistance, this study found that wear resistance decreased more rapidly than hardness with the temperature increase, evidencing a low material stability of this component in a short temperature interval. The reduction of the hardness was reflected by the plastic deformation and abrasion intensity, resulting in a significant wear rate increase.

Keywords: hardness, surface bearing, tribological system, UHMWPE, wear

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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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Authors: Yu Shan Wang

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Different from other industries, the structure of the tourism industry depends to a large degree the environmental and cultural resources. The industry has to undertake social responsibilities for its commercial behaviour. This paper refers to the seven dimensions of the KLD STATS in 1991-2011 as the indicator to CSR practices. The purpose is to investigate what CSR activities create significant impacts on accounting-based financials and firm values by delving into different CSR dimensions. Meanwhile, this paper takes into consideration S&P 500 and control variables (firm sizes and financial leverage). In fact, the commercial behavior of the tourism-related industry may result in negative impacts on the economy and the society. Therefore, this paper classifies a positive set of CSR elements and a negative set of CSR elements for the tourism-related industry in order to examine their respective effects on short-term profitability and long-term firm values. This can shed light on which CSR dimensions exhibit significant impacts on CFP better than holistic CSR indicators, and hence provide more useful information to investors and corporates. This paper uses quantile regressions to avoid the impact of outliers in the data set. This helps to offer specific information so that companies can make informed decisions.

Keywords: corporate social responsibility, CSR, firm value, tourism, corporate financial performance, CFP

Procedia PDF Downloads 288

Authors: Bita Mashayekhi, Amin Jahangard, Milad Samavat, Saeid Homayoun

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In the modern competitive business environment, one cannot overstate the importance of corporate social responsibility. The controversial link between the social and financial performance of firms has become a topic of interest for scholars. Hence, this study examines the social and financial performance link by taking into account the mediating role of innovation performance. We conducted the Covariance-based Structural Equation Modeling (CB-SEM) method on an international sample of firms provided by the ASSET4 database. In this research, to explore the black box of the social and financial performance relationship, we first examined the effect of social performance separately on financial performance and innovation; then, we measured the mediation role of innovation in the social and financial performance link. While our results indicate the positive effect of social performance on financial performance and innovation, we cannot document the positive mediating role of innovation. This possibly relates to the long-term nature of benefits from investments in innovation.

Keywords: ESG, financial performance, innovation, social performance, structural equation modeling

Procedia PDF Downloads 102