Search results for: process performance index

Authors: Mimi Hafizah Abdullah, Hanani Farhah Harun, Nik Ruzni Nik Idris

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With the implied volatility as an important factor in financial decision-making, in particular in option pricing valuation, and also the given fact that the pricing biases of Leland option pricing models and the implied volatility structure for the options are related, this study considers examining the implied adjusted volatility smile patterns and term structures in the S&P/ASX 200 index options using the different Leland option pricing models. The examination of the implied adjusted volatility smiles and term structures in the Australian index options market covers the global financial crisis in the mid-2007. The implied adjusted volatility was found to escalate approximately triple the rate prior the crisis.

Keywords: implied adjusted volatility, financial crisis, Leland option pricing models, Australian index options

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Authors: Yasaman Ashrafi, Stephen Kajewski, Annastiina Silvennoinen, Madhav Nepal

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Mega projects either in construction, urban development or energy sectors are one of the key drivers that build the foundation of wealth and modern civilizations in regions and nations. Such projects require economic justification and substantial capital investment, often derived from individual and corporate investors as well as governments. Cost overruns and time delays in these mega projects demands a new approach to more accurately predict project costs and establish realistic financial plans. The significance of this paper is that the cost efficiency of megaprojects will improve and decrease cost overruns. This research will assist Project Managers (PMs) to make timely and appropriate decisions about both cost and outcomes of ongoing projects. This research, therefore, examines the oil and gas industry where most mega projects apply the classic methods of Cost Performance Index (CPI) and Schedule Performance Index (SPI) and rely on project data to forecast cost and time. Because these projects are always overrun in cost and time even at the early phase of the project, the probabilistic methods of Monte Carlo Simulation (MCS) and Bayesian Adaptive Forecasting method were used to predict project cost at completion of projects. The current theoretical and mathematical models which forecast the total expected cost and project completion date, during the execution phase of an ongoing project will be evaluated. Earned Value Management (EVM) method is unable to predict cost at completion of a project accurately due to the lack of enough detailed project information especially in the early phase of the project. During the project execution phase, the Bayesian adaptive forecasting method incorporates predictions into the actual performance data from earned value management and revises pre-project cost estimates, making full use of the available information. The outcome of this research is to improve the accuracy of both cost prediction and final duration. This research will provide a warning method to identify when current project performance deviates from planned performance and crates an unacceptable gap between preliminary planning and actual performance. This warning method will support project managers to take corrective actions on time.

Keywords: cost forecasting, earned value management, project control, project management, risk analysis, simulation

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Authors: Zimasa Siyasanga Gysman

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This paper assesses the history of electronic music and its performance to illustrate that machines and technology have largely influenced how humans perform electronic music. The history of electronic music mainly focuses on the composition and production of electronic music with little to no attention paid to its performance by the majority of scholars in this field. Therefore, establishing a history of performance involves investigating what compositions of electronic music called for in the production of electronic music performance. This investigation into seminal works in the history of electronic music, therefore, illustrates the aesthetics of electronic music performance and the aesthetics established in the very beginnings of electronic music performance demonstrate the aesthetics of electronic music which are still prevalent today. The key aesthetics are the repurposing of technology and the hybridisation of technology. Performers take familiar technology (technology that society has become accustomed to using in daily life), not necessarily related to music or performance and use it as an instrument in their performances, such as a rotary dial telephone. Likewise, since the beginnings of electronic music, producers have always experimented with the latest technologies available to them in their compositions and performances. The spirit of performers of electronic music, therefore, revolves around repurposing familiar technologies and using them in new ways, whilst similarly experimenting with new technologies in their performances. This process of hybridisation plays a key role in the production and performance of electronic music in the twentieth century. Through various interviews with performers of electronic music, it is shown that these aesthetics are driving performance practices in the twenty-first century.

Keywords: body, hybridisation, performance, sound

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Authors: Kim Sang Hyuck, Y. Park Sung

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The outbreak of national disasters stimulates the decrease of the both internal and domestic tourism demands, causing bad effects on the hospitality industry. The effective and efficient risk management regarding national disasters are being increasingly required from the hospitality industry practitioners and the tourism policymakers. To establish the effective and efficient risk management strategy on national disasters, the most essential prerequisite condition is the correct estimation of national disasters’ effects in terms of the size and duration of the damages occurred from national disaster on hospitality industry. More specifically, the national disasters are twofold: natural disaster and social disaster. In addition, the hospitality industry has consisted of several types of business, such as hotel, restaurant, travel agency, etc. As reasons of the above, it is important to consider how each type of national disasters differently influences on the performance of each type of hospitality industry. Therefore, the purpose of this study is examining the effects of national disaster on hospitality industry in Korea based on the types of national disasters as well as the types of hospitality business. The monthly data was collected from Jan. 2000 to Dec. 2016. The indexes of industrial production for each hospitality industry in Korea were used with the proxy variable for the performance of each hospitality industry. Two national disaster variables (natural disaster and social disaster) were treated as dummy variables. In addition, the exchange rate, industrial production index, and consumer price index were used as control variables in the research model. The impulse response analysis was used to examine the size and duration of the damages occurred from each type of national disaster on each type of hospitality industries. The results of this study show that the natural disaster and the social disaster differently influenced on each type of hospitality industry. More specifically, the performance of airline industry is negatively influenced by the natural disaster at the time of 3 months later from the incidence. However, the negative impacts of social disaster on airline industry occurred not significantly over the time periods. For the hotel industry, both natural disaster and social disaster negatively influence the performance of hotel industry at the time of 5 months and 6 months later, respectively. Also, the negative impact of natural disaster on the performance of restaurant industry occurred at the time of 5 months later, as well as for both 3 months and 6 months later for the social disaster. Finally, both natural disaster and social disaster negatively influence the performance of travel agency at the time of 3 months and 4 months later, respectively. In conclusion, the types of national disasters differently influence the performance of each type of hospitality industry in Korea. These results would provide an important information to establish the effective and efficient risk management strategy for the national disasters.

Keywords: impulse response analysis, Korea, national disaster, performance of hospitality industry

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Authors: S. Kumchoo

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The result of suggestion for low energy diet (1,000-1,200 kcal) in obese women to the effect on body weight, waist circumference and body mass index (BMI) in this experiment. Quisi experimental research was used for this study and it is a One-group pretest-posttest designs measurement method. The aim of this study was body weight, waist circumference and body mass index (BMI) reduction by using low energy diet (1,000-1,200 kcal) in obese women, the result found that in 15 of obese women that contained their body mass index (BMI) ≥ 30, after they obtained low energy diet (1,000-1,200 kcal) within 2 weeks. The data were collected before and after of testing the results showed that the average of body weight decrease 3.4 kilogram, waist circumference value decrease 6.1 centimeter and the body mass index (BMI) decrease 1.3 kg.m2 from their previous body weight, waist circumference and body mass index (BMI) before experiment started. After this study, the volunteers got healthy and they can choose or select some food for themselves. For this study, the research can be improved for data development for forward study in the future.

Keywords: body weight, waist circumference, BMI, low energy diet

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Authors: Abbas Al-Refaie, Ruba Najdawi, Nour Bata, Mohammad D. AL-Tahat

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The pharmaceutical industry is an important component of health care systems throughout the world. Measurement of a production unit-performance is crucial in determining whether it has achieved its objectives or not. This paper applies data envelopment (DEA) window analysis to assess the efficiencies of two packaging lines; Allfill (new) and DP6, in the Penicillin plant in a Jordanian Medical Company in 2010. The CCR and BCC models are used to estimate the technical efficiency, pure technical efficiency, and scale efficiency. Further, the Malmquist productivity index is computed to measure then employed to assess productivity growth relative to a reference technology. Two primary issues are addressed in computation of Malmquist indices of productivity growth. The first issue is the measurement of productivity change over the period, while the second is to decompose changes in productivity into what are generally referred to as a ‘catching-up’ effect (efficiency change) and a ‘frontier shift’ effect (technological change). Results showed that DP6 line outperforms the Allfill in technical and pure technical efficiency. However, the Allfill line outperforms DP6 line in scale efficiency. The obtained efficiency values can guide production managers in taking effective decisions related to operation, management, and plant size. Moreover, both machines exhibit a clear fluctuations in technological change, which is the main reason for the positive total factor productivity change. That is, installing a new Allfill production line can be of great benefit to increasing productivity. In conclusions, the DEA window analysis combined with the Malmquist index are supportive measures in assessing efficiency and productivity in pharmaceutical industry.

Keywords: window analysis, malmquist index, efficiency, productivity

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Authors: Anahita Farhang Ghahfarokhi, Alessandro Berti, Wil M.P. van der Aalst

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Process mining provides ways to analyze business processes. Common process mining techniques consider the process as a whole. However, in real-life business processes, different behaviors exist that make the overall process too complex to interpret. Process comparison is a branch of process mining that isolates different behaviors of the process from each other by using process cubes. Process cubes organize event data using different dimensions. Each cell contains a set of events that can be used as an input to apply process mining techniques. Existing work on process cubes assume single case notions. However, in real processes, several case notions (e.g., order, item, package, etc.) are intertwined. Object-centric process mining is a new branch of process mining addressing multiple case notions in a process. To make a bridge between object-centric process mining and process comparison, we propose a process cube framework, which supports process cube operations such as slice and dice on object-centric event logs. To facilitate the comparison, the framework is integrated with several object-centric process discovery approaches.

Keywords: multidimensional process mining, mMulti-perspective business processes, OLAP, process cubes, process discovery, process mining

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Authors: Xuan Li, Weian Huang, Jinsheng Sun, Fuhao Zhao, Zhiyuan Wang, Jintang Wang

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Natural gas hydrates (NGHs) as promising alternative energy sources have gained increasing attention. Hydrate-bearing formation in marine areas is highly unconsolidated formation and is fragile, which is composed of weakly cemented sand-clay and silty sediments. During the drilling process, the invasion of drilling fluid can easily lead to excessive water content in the formation. It will change the soil liquid plastic limit index, which significantly affects the formation quality, leading to wellbore instability due to the metastable character of hydrate-bearing sediments. Therefore, controlling the filtrate loss into the formation in the drilling process has to be highly regarded for protecting the stability of the wellbore. In this study, the temperature-sensitive nanogel of P(NIPAM-co-AMPS-co-tBA) was prepared by soap-free emulsion polymerization, and the temperature-sensitive behavior was employed to achieve self-adaptive plugging in hydrate sediments. First, the effects of additional amounts of AMPS, tBA, and cross-linker MBA on the microgel synthesis process and temperature-sensitive behaviors were investigated. Results showed that, as a reactive emulsifier, AMPS can not only participate in the polymerization reaction but also act as an emulsifier to stabilize micelles and enhance the stability of nanoparticles. The volume phase transition temperature (VPTT) of nanogels gradually decreased with the increase of the contents of hydrophobic monomer tBA. An increase in the content of the cross-linking agent MBA can lead to a rise in the coagulum content and instability of the emulsion. The plugging performance of nanogel was evaluated in a core sample with a pore size distribution range of 100-1000nm. The temperature-sensitive nanogel can effectively improve the microfiltration performance of drilling fluid. Since a combination of a series of nanogels could have a wide particle size distribution at any temperature, around 200nm to 800nm, the self-adaptive plugging capacity of nanogels for the hydrate sediments was revealed. Thermosensitive nanogel is a potential intelligent plugging material for drilling operations in natural gas hydrate-bearing sediments.

Keywords: temperature-sensitive nanogel, NIPAM, self-adaptive plugging performance, drilling operations, hydrate-bearing sediments

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Authors: Silvija ŠIljeg, Ante ŠIljeg, Ivan Marić

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Measuring housing quality is being done on objective and subjective level using different indicators. During the research 5 urban and housing indicators formed according to 58 variables from different housing, domains were used. The aims of the research were to measure housing quality based on GIS approach and to detect critical points of housing in the example of Croatian coastal Town Zadar. The purposes of GIS in the research are to generate models of housing quality indexes by standardisation and aggregation of variables and to examine accuracy model of housing quality index. Analysis of accuracy has been done on the example of variable referring to educational objects availability. By defining weighted coefficients and using different GIS methods high, middle and low housing quality zones were determined. Obtained results can be of use to town planners, spatial planners and town authorities in the process of generating decisions, guidelines, and spatial interventions.

Keywords: housing quality, GIS, housing quality index, indicators, models of housing quality

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Authors: Amritee Bora, B. S. Mipun

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Land degradation is often used to describe the land environmental phenomena that reduce land’s original productivity both qualitatively and quantitatively. The study of land degradation vulnerability primarily deals with “Environmentally Sensitive Areas” (ESA) and the amount of topsoil loss due to erosion. In many studies, it is observed that the assessment of the existing status of land degradation is used to represent the vulnerability. Moreover, it is also noticed that in most studies, the primary emphasis of land degradation vulnerability is to assess its sensitivity to soil erosion only. However, the concept of land degradation vulnerability can have different objectives depending upon the perspective of the study. It shows the extent to which changes in land use land cover can imprint their effect on the land. In other words, it represents the susceptibility of a piece of land to degrade its productive quality permanently or in the long run. It is also important to mention that the vulnerability of land degradation is not a single factor outcome. It is a probability assessment to evaluate the status of land degradation and needs to consider both biophysical and human induce parameters. To avoid the complexity of the previous models in this regard, the present study has emphasized on to generate a simplified model to assess the land degradation vulnerability in terms of its current human population pressure, land use practices, and existing biophysical conditions. It is a “Mixed-Method” termed as the land degradation vulnerability index (LDVi). It was originally inspired by the MEDALUS model (Mediterranean Desertification and Land Use), 1999, and Farazadeh’s 2007 revised version of it. It has followed the guidelines of Space Application Center, Ahmedabad / Indian Space Research Organization for land degradation vulnerability. The model integrates the climatic index (Ci), vegetation index (Vi), erosion index (Ei), land utilization index (Li), population pressure index (Pi), and cover management index (CMi) by giving equal weightage to each parameter. The final result shows that the very high vulnerable zone primarily indicates three (3) prominent circumstances; land under continuous population pressure, high concentration of human settlement, and high amount of topsoil loss due to surface runoff within the study sites. As all the parameters of the model are amalgamated with equal weightage further with the help of regression analysis, the LDVi model also provides a strong grasp of each parameter and how far they are competent to trigger the land degradation process.

Keywords: population pressure, land utilization, soil erosion, land degradation vulnerability

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Authors: Ahmed Mohammed Mohagir, Ahmat-Charfadine Mahamat, Nde Divine Bup, Richard Kamga, César Kapseu

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In this investigation, kinetics studies of adsorption of colour material of shea butter showed a peak at the wavelength 440 nm and the equilibrium time was found to be 30 min. Response surface methodology applying Doehlert experimental design was used to investigate decolourisation parameters of crude shea butter. The decolourisation process was significantly influenced by three independent parameters: contact time, decolourisation temperature and adsorbent dose. The responses of the process were oil loss, acid value, peroxide value and colour index. Response surface plots were successfully made to visualise the effect of the independent parameters on the responses of the process.

Keywords: decolourisation, doehlert experimental design, physicochemical characterisation, RSM, shea butter

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone

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Authors: Jing Jiang, Yuguang Gao, Yang Yu

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Facing increasingly challenging insurance payment pressures, the Chinese healthcare system is undergoing significant transformations, akin to the implementation of DRG payment models by the United States' Medicare. Consequently, there is a pressing need for Chinese hospitals to establish optimizations in departmental operations tailored to the ongoing healthcare payment reforms. This abstract delineates the meticulous construction of a scientifically rigorous and comprehensive index system at the departmental level in China strategically aligned with the evolving landscape of healthcare payment reforms. Methodologically, it integrates key process areas and maturity assessment theories, synthesizing relevant literature and industry standards to construct a robust framework and indicator pool. Employing the Delphi method, consultations with 21 experts were conducted, revealing a collective demonstration of high enthusiasm, authority, and coordination in designing the index system. The resulting model comprises four primary indicators -technical capabilities, cost-effectiveness, operational efficiency, and disciplinary potential- supported by 14 secondary indicators and 23 tertiary indicators with varied coefficient adjustment for department types (platform or surgical). The application of this evaluation system in a Chinese hospital within the northeastern region yielded results aligning seamlessly with the actual operational scenario. In conclusion, the index system comprehensively considers the integrity and effectiveness of structural, process, and outcome indicators and stands as a comprehensive reflection of the collective expertise of the engaged experts, manifesting in a model designed to elevate the operational management of hospital departments. Its strategic alignment with healthcare payment reforms holds practical significance in guiding departmental development positioning, brand cultivation, and talent development.

Keywords: Chinese healthcare system, Delphi method, departmental management, evaluation indicators, hospital operations, weight coefficients

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Levent Basayigit, Mert Dedeoglu, Fadime Ozogul

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In this study, an application was carried out to determine the Volcanic Soils by using remote sensing.  The study area was located on the Golcuk formation in Isparta-Turkey. The thermal bands of Landsat 7 image were used for processing. The implementation of the climate model that was based on the water index was used in ERDAS Imagine software together with pixel based image classification. Soil Moisture Index (SMI) was modeled by using the surface temperature (Ts) which was obtained from thermal bands and vegetation index (NDVI) derived from Landsat 7. Surface moisture values were grouped and classified by using scoring system. Thematic layers were compared together with the field studies. Consequently, different moisture levels for volcanic soils were indicator for determination and separation. Those thermal wavelengths are preferable bands for separation of volcanic soils using moisture and temperature models.

Keywords: Landsat 7, soil moisture index, temperature models, volcanic soils

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Authors: Felipe Bedoya Maya, Agustina Calatayud, Vileydy Gonzalez Mejia

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Encompassing inventory, warehousing, and transportation management, logistics is a crucial predictor of firm performance. This has been extensively proven by extant literature in business and operations management. Logistics is also a fundamental determinant of a country's ability to access international markets. Available studies in international and transport economics have shown that limited transport infrastructure and underperforming transport services can severely affect international competitiveness. However, the evidence lacks the overall impact of logistics performance-encompassing all inventory, warehousing, and transport components- on global trade. In order to fill this knowledge gap, the paper uses a gravitational trade model with 155 countries from all geographical regions between 2007 and 2018. Data on logistics performance is obtained from the World Bank's Logistics Performance Index (LPI). First, the relationship between logistics performance and a country’s total trade is estimated, followed by a breakdown by the economic sector. Then, the analysis is disaggregated according to the level of technological intensity of traded goods. Finally, after evaluating the intensive margin of trade, the relevance of logistics infrastructure and services for the extensive trade margin is assessed. Results suggest that: (i) improvements in both logistics infrastructure and services are associated with export growth; (ii) manufactured goods can significantly benefit from these improvements, especially when both exporting and importing countries increase their logistics performance; (iii) the quality of logistics infrastructure and services becomes more important as traded goods are technology-intensive; and (iv) improving the exporting country's logistics performance is essential in the intensive margin of trade while enhancing the importing country's logistics performance is more relevant in the extensive margin.

Keywords: gravity models, infrastructure, international trade, logistics

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Authors: Nokwethaba Makhanya, Babatunde J. Abiodun, Piotr Wolski

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Climate change possibly intensifies hydrological droughts and reduces water availability in river basins. Despite this, most research on climate change effects in southern Africa has focused exclusively on meteorological droughts. This thesis projects the potential impact of climate change on the future characteristics of hydrological droughts in the Limpopo River Basin (LRB). The study uses regional climate model (RCM) measurements (from the Coordinated Regional Climate Downscaling Experiment, CORDEX) and a combination of hydrological simulations (using the Soil and Water Assessment Tool Plus model, SWAT+) to predict the impacts at four global warming levels (GWLs: 1.5℃, 2.0℃, 2.5℃, and 3.0℃) under the RCP8.5 future climate scenario. The SWAT+ model was calibrated and validated with a streamflow dataset observed over the basin, and the sensitivity of model parameters was investigated. The performance of the SWAT+LRB model was verified using the Nash-Sutcliffe efficiency (NSE), Percent Bias (PBIAS), Root Mean Square Error (RMSE), and coefficient of determination (R²). The Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) have been used to detect meteorological droughts. The Soil Water Index (SSI) has been used to define agricultural drought, while the Water Yield Drought Index (WYLDI), the Surface Run-off Index (SRI), and the Streamflow Index (SFI) have been used to characterise hydrological drought. The performance of the SWAT+ model simulations over LRB is sensitive to the parameters CN2 (initial SCS runoff curve number for moisture condition II) and ESCO (soil evaporation compensation factor). The best simulation generally performed better during the calibration period than the validation period. In calibration and validation periods, NSE is ≤ 0.8, while PBIAS is ≥ ﹣80.3%, RMSE ≥ 11.2 m³/s, and R² ≤ 0.9. The simulations project a future increase in temperature and potential evapotranspiration over the basin, but they do not project a significant future trend in precipitation and hydrological variables. However, the spatial distribution of precipitation reveals a projected increase in precipitation in the southern part of the basin and a decline in the northern part of the basin, with the region of reduced precipitation projected to increase with GWLs. A decrease in all hydrological variables is projected over most parts of the basin, especially over the eastern part of the basin. The simulations predict meteorological droughts (i.e., SPEI and SPI), agricultural droughts (i.e., SSI), and hydrological droughts (i.e., WYLDI, SRI) would become more intense and severe across the basin. SPEI-drought has a greater magnitude of increase than SPI-drought, and agricultural and hydrological droughts have a magnitude of increase between the two. As a result, this research suggests that future hydrological droughts over the LRB could be more severe than the SPI-drought projection predicts but less severe than the SPEI-drought projection. This research can be used to mitigate the effects of potential climate change on basin hydrological drought.

Keywords: climate change, CORDEX, drought, hydrological modelling, Limpopo River Basin

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Authors: Ilias A. Makris

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In this work, we attempt to analyse the contribution of innovative activities to firm performance and growth. We examine economic data from some of the economies that were heavily affected by current economic crisis: the countries of southern Europe (Portugal, Italy, Greece, and Spain) and Ireland. Following literature, an appropriate econometric model is developed and several indicators are tested in order to disclose possible relation with innovative activity. Findings confirm the crucial effect of innovative process in economic activity, in firm and country level.

Keywords: Eurozone periphery, firm performance, innovative activity, R&D

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Authors: Ting-YuLiu, Yi-Feng Lin

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Porous Prussian Blue (PB) nanoparticles were successfully incorporated into chitosan (CS) membranes to form PB/CS mixed-matrix membranes (MMMs) and the as-prepared PB/CS MMMs were used to dehydration of ethanol at 25 oC in the pervaporation process. The effect of PB loading in CS matrix on pervaporation performance was investigated. The FESEM, EDS, FTIR and XRD measurements were also used for the characterization of the PB/CS MMMs. The PB/CS membranes with 30 wt% PB loading show the best performance with the permeate flux of 614 g/m2h and the separation factor of 1472. The pervaporation using the PB/CS membranes exhibits outstanding performance as compared with the previously reported CS based membranes and MMMs. The present work demonstrates good pervaporation performance of the PB/CS MMMs for the separation of 90wt% ethanol aqueous solution, moreover, it has an opportunity for dehydration of bioethanol in this system of pervaporation.

Keywords: pervaporation, chitosan, Prussian blue, mixed-matrix membrane

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Authors: Ikram Kamal, Mohamed Blaghen

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Petroleum hydrocarbons are serious problems and global pollutants in the environment due to their toxicity, carcinogenicity and persistent organic pollutant properties. One of the approaches to enhance biodegradation of petroleum hydrocarbons is to use biosurfactant. Biosurfactants are amphiphilic biomolecules produced as metabolic by-products from microorganisms they received considerable attention in the field of environmental remediation processes such as bioremediation. Biosurfactants have been considered as a desirable alternative to synthetic surfactants in various applications particularly in the environmental field. In comparison with their synthetic counterparts, biosurfactants have been reported to be less toxic, biodegradable and persistent. In this study we have investigated the potential of bacterial strains collected aseptically from the lagoon Marchika (water and soil) in Nador, Morocco; for the production of biosurfactants. This study also aimed to optimize the biosurfactant production process by changing the variables that influence the type and amount of biosurfactant produced by these microorganisms such as: carbon sources and also other physical and chemical parameters such as temperature and pH. Emulsification index, methylene blue test and thin layer chromatography (TLC) revealed the ability of strains used in this study to produce compounds that could emulsify gasoline. In addition, a HPLC/MS was used to separate and identify different biosurfactants purified.

Keywords: petroleum hydrocarbons, biosurfactants, biodegradation, lagoon marchika, emulsification index

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Authors: Nazlı Çetindağ, Pelin Yılmaz Çetiner, Metin Mert İlgün, Emine Birci, Gizemnur Yıldız Uysal, Özcan Hatipoğlu, Ehsan Tuzcuoğlu, Gökhan Sır

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Stressing the importance of water conservation, emphasizing the need for efficient management of household water, and underlining the significance of alternative solutions are important. In this context, advanced solutions based on technologies such as the advanced oxidation process have emerged as promising methods for treating household wastewater. Evaluating household water usage holds critical importance for the sustainability of water resources. Researchers and experts are examining various technological approaches to effectively treat and reclaim water for reuse. In this framework, the advanced oxidation process has proven to be an effective method for the removal of various organic and inorganic pollutants in the treatment of household wastewater. In this study, performance will be evaluated by comparing it with the reference case. This international criterion simulates the washing of home textile products, determining various performance parameters. The specially designed stain strips, including sebum, carbon black, blood, cocoa, and red wine, used in experiments, represent various household stains. These stain types were carefully selected to represent challenging stain scenarios, ensuring a realistic assessment of washing performance. Experiments conducted under different temperatures and program conditions successfully demonstrate the practical applicability of the advanced oxidation process for treating household wastewater. It is important to note that both adherence to standards and the use of real-life stain types contribute to the broad applicability of the findings. In conclusion, this study strongly supports the effectiveness of treating household wastewater with the advanced oxidation process in terms of washing performance under both standard and practical application conditions. The study underlines the importance of alternative solutions for sustainable water resource management and highlights the potential of the advanced oxidation process in the treatment of household water, contributing significantly to optimizing water usage and developing sustainable water management solutions.

Keywords: advanced oxidation process, household water usage, household appliance waste water, modelling, water reuse

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Authors: Pratap Chandra Pati, Prabina Rajib, Parama Barai

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The traditional finance theory neglects the role of sentiment factor in asset pricing. However, the behavioral approach to asset-pricing based on noise trader model and limit to arbitrage includes investor sentiment as a priced risk factor in the assist pricing model. Investor sentiment affects stock more that are vulnerable to speculation, hard to value and risky to arbitrage. It includes small stocks, high volatility stocks, growth stocks, distressed stocks, young stocks and non-dividend-paying stocks. Since the introduction of Chicago Board Options Exchange (CBOE) volatility index (VIX) in 1993, it is used as a measure of future volatility in the stock market and also as a measure of investor sentiment. CBOE VIX index, in particular, is often referred to as the ‘investors’ fear gauge’ by public media and prior literature. The upward spikes in the volatility index are associated with bouts of market turmoil and uncertainty. High levels of the volatility index indicate fear, anxiety and pessimistic expectations of investors about the stock market. On the contrary, low levels of the volatility index reflect confident and optimistic attitude of investors. Based on the above discussions, we investigate whether market-wide fear levels measured volatility index is priced factor in the standard asset pricing model for the Indian stock market. First, we investigate the performance and validity of Fama and French three-factor model and Carhart four-factor model in the Indian stock market. Second, we explore whether India volatility index as a proxy for fearful market-based sentiment indicators affect the cross section of stock returns after controlling for well-established risk factors such as market excess return, size, book-to-market, and momentum. Asset pricing tests are performed using monthly data on CNX 500 index constituent stocks listed on the National stock exchange of India Limited (NSE) over the sample period that extends from January 2008 to March 2017. To examine whether India volatility index, as an indicator of fear sentiment, is a priced risk factor, changes in India VIX is included as an explanatory variable in the Fama-French three-factor model as well as Carhart four-factor model. For the empirical testing, we use three different sets of test portfolios used as the dependent variable in the in asset pricing regressions. The first portfolio set is the 4x4 sorts on the size and B/M ratio. The second portfolio set is the 4x4 sort on the size and sensitivity beta of change in IVIX. The third portfolio set is the 2x3x2 independent triple-sorting on size, B/M and sensitivity beta of change in IVIX. We find evidence that size, value and momentum factors continue to exist in Indian stock market. However, VIX index does not constitute a priced risk factor in the cross-section of returns. The inseparability of volatility and jump risk in the VIX is a possible explanation of the current findings in the study.

Keywords: India VIX, Fama-French model, Carhart four-factor model, asset pricing

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Authors: Sara Muhammad Elqudah, Vigh László Gergely

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Catastrophic events, such as earthquakes, are sudden, short, and devastating, threatening lives, demolishing futures, and causing huge economic losses. Current seismic analyses and design standards are based on life safety levels where only some residual strength and stiffness are left in the structure leaving it beyond economical repair. Consequently, it has become necessary to introduce and implement the concept of resilient design. Resilient design is about designing for ductility over time by resisting, absorbing, and recovering from the effects of a hazard in an appropriate and efficient time manner while maintaining the functionality of the structure in the aftermath of the incident. Resilient analysis is mainly based on the fragility, vulnerability, and functionality curves where eventually a resilience index is generated from these curves, and the higher this index is, the better is the performance of the structure. In this paper, seismic performances of a simple two story reinforced concrete building, located in a moderate seismic region, has been evaluated using the conventional seismic analyses methods, which are the linear static analysis, the response spectrum analysis, and the pushover analysis, and the generated results of these analyses methods are compared to those of the resilient analysis. Results highlight that the resilience analysis was the most convenient method in generating a more ductile and functional structure from a socio-economic perspective, in comparison to the standard seismic analysis methods.

Keywords: conventional analysis methods, functionality, resilient analysis, seismic performance

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Authors: Agnieszka Dudzik

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The problem of correlation between random variables in the structural reliability analysis has been extensively discussed in literature on the subject. The cases taken under consideration were usually related to correlation between random variables from one side of ultimate limit state: correlation between particular loads applied on structure or correlation between resistance of particular members of a structure as a system. It has been proved that positive correlation between these random variables reduces the reliability of structure and increases the probability of failure. In the paper, the problem of correlation between random variables from both side of the limit state equation will be taken under consideration. The simplest case where these random variables are of the normal distributions will be concerned. The case when a degree of that correlation is described by the covariance or the coefficient of correlation will be used. Special attention will be paid on questions: how much that correlation changes the reliability level and can it be ignored. In reliability analysis will be used well-known methods for assessment of the failure probability: based on the Hasofer-Lind reliability index and Monte Carlo method adapted to the problem of correlation. The main purpose of this work will be a presentation how correlation of random variables influence on reliability index of steel bar structures. Structural design parameters will be defined as deterministic values and random variables. The latter will be correlated. The criterion of structural failure will be expressed by limit functions related to the ultimate and serviceability limit state. In the description of random variables will be used only for the normal distribution. Sensitivity of reliability index to the random variables will be defined. If the reliability index sensitivity due to the random variable X will be low when compared with other variables, it can be stated that the impact of this variable on failure probability is small. Therefore, in successive computations, it can be treated as a deterministic parameter. Sensitivity analysis leads to simplify the description of the mathematical model, determine the new limit functions and values of the Hasofer-Lind reliability index. In the examples, the NUMPRESS software will be used in the reliability analysis.

Keywords: correlation of random variables, reliability index, sensitivity of reliability index, steel structure

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Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

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Authors: Kemkanit Sanyanunthana

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The purpose of this research is to study the management system of information technology which supports the education of five private universities in Thailand, according to the case studies which have been developing their qualities and standards of management and education by service provision of information technology to support the excellence performance. The concept to connect information technology with a suitable system has been created by information technology administrators for development, as a system that can be used throughout the organizations to help reach the utmost benefits of using all resources. Hence, the researcher as a person who has been performing these duties within higher education is interested to do this research by selecting the Control Objective for Information and Related Technology 5 (COBIT 5) for the Malcolm Baldrige National Quality Award (MBNQA) of America, or the National Award which applies the concept of Total Quality Management (TQM) to the organization evaluation. Such evaluation is called the Education Criteria for Performance Excellence (EdPEx) focuses on studying and comparing education quality development for excellent performance using COBIT 5 in terms of information technology to study the problems and obstacles of the investigation process for an information technology system, which is considered as an instrument to drive all organizations to reach the excellence performance of the information technology, and to be the model of evaluation and analysis of the process to be in accordance with the strategic plans of the information technology in the universities. This research is conducted in the form of descriptive and survey research according to the case studies. The data collection were carried out by using questionnaires through the administrators working related to the information technology field, and the research documents related to the change management as the main study. The research can be concluded that the performance based on the APO domain process (ALIGN, PLAN AND ORGANISE) of the COBIT 5 standard frame, which emphasizes concordant governance and management of strategic plans for the organizations, could reach only 95%. This might be because of some restrictions such as organizational cultures; therefore, the researcher has studied and analyzed the management of information technology in universities as a whole, under the organizational structures, to reach the performance in accordance with the overall APO domain which would affect the determined strategic plans to be able to develop based on the excellence performance of information technology, and to apply the risk management system at the organizational level into every performance process which would develop the work effectiveness for the resources management of information technology to reach the utmost benefits. 

Keywords: COBIT5, APO, EdPEx Criteria, MBNQA

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Authors: Lynmar M. Didal, Ramises G. Manzano Jr., Jacque Bon-Isaac C. Aboy

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This study analyzes the performance of global minimum variance and naive portfolios across different economic periods, using monthly stock returns from the Philippine Stock Exchange Index (PSEI), S&P 500, and Dow Jones Industrial Average (DOW). The performance is evaluated through the Sharpe ratio, Sortino ratio, Jensen’s Alpha, Treynor ratio, and Information ratio. Additionally, the study investigates the impact of short selling on portfolio performance. Six-time periods are defined for analysis, encompassing events such as the global financial crisis and the COVID-19 pandemic. Findings indicate that the Naive portfolio generally outperforms the GMV portfolio in the S&P 500, signifying higher returns with increased volatility. Conversely, in the PSEI and DOW, the GMV portfolio shows more efficient risk-adjusted returns. Short selling significantly impacts the GMV portfolio during mid-GFC and mid-COVID periods. The study offers insights for investors, suggesting the Naive portfolio for higher risk tolerance and the GMV portfolio as a conservative alternative.

Keywords: portfolio performance, global minimum variance, naïve portfolio, risk-adjusted metrics, short-selling

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Authors: Mohamed El-Khateeb

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Encompassing inventory, warehousing, and transportation management, logistics is a crucial predictor of firm performance. This has been extensively proven by extant literature in business and operations management. Logistics is also a fundamental determinant of a country's ability to access international markets. Available studies in international and transport economics have shown that limited transport infrastructure and underperforming transport services can severely affect international competitiveness. However, the evidence lacks the overall impact of logistics performance-encompassing all inventory, warehousing, and transport components- on global trade. In order to fill this knowledge gap, the paper uses a gravitational trade model with 155 countries from all geographical regions between 2007 and 2018. Data on logistics performance is obtained from the World Bank's Logistics Performance Index (LPI). First, the relationship between logistics performance and a country’s total trade is estimated, followed by a breakdown by the economic sector. Then, the analysis is disaggregated according to the level of technological intensity of traded goods. Finally, after evaluating the intensive margin of trade, the relevance of logistics infrastructure and services for the extensive trade margin is assessed. Results suggest that: (i) improvements in both logistics infrastructure and services are associated with export growth; (ii) manufactured goods can significantly benefit from these improvements, especially when both exporting and importing countries increase their logistics performance; (iii) the quality of logistics infrastructure and services becomes more important as traded goods are technology-intensive; and (iv) improving the exporting country's logistics performance is essential in the intensive margin of trade while enhancing the importing country's logistics performance is more relevant in the extensive margin.

Keywords: low-cost, recycling, reuse, solid waste, wastewater treatment

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Authors: Tohid Eskandarzadeh, Nader Bahlouli, Turaj Behnam, Azra Jafarzadeh

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The purpose of the study reported in this paper was to propose an optimal pattern to evaluate the staff management performance of the water and sewage organization. The performance prism-model was used to evaluate the following significant dimensions of performance: organizational strategies, organizational processes, organization capabilities, stakeholders’ partnership and satisfaction. In the present study, a standard, valid and reliable questionnaire was used to obtain data about the five dimensions of the performance prism model. 169 sample respondents were used for responding the questionnaire who were selected from the staff of water and waste-water organization in western Azerbaijan, Iran. Also, Alpha coefficient was used to check the reliability of the data-collection instrument which was measured to be beyond 0.7. The obtained data were statistically analyzed by means of SPSS version 18. The results obtained from the data analysis indicated that the performance of the staff management of the water and waste-water organization in western Azerbaijan was acceptable in terms of organizational strategies, organizational process, stakeholders’ partnership and satisfaction. Nevertheless, it was found that the performance of the staff management with respect to organizational abilities was average. Indeed, the researchers drew the conclusion that the current performance of the staff management in this organization in western Azerbaijan was less than ideal performance.

Keywords: performance evaluation, performance prism model, water, waste-water organization

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Authors: Mehul Srivastava, Sharma Tushar Ravikant, Mridul Krishn Mishra

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In structural design, the evaluation of safety and probability failure of structure is of significant importance, mainly when the variables are random. On real structures, structural reliability can be evaluated obtaining an implicit limit state function. The structural reliability limit state function is obtained depending upon the statistically independent variables. In the analysis of reliability, we considered the statistically independent random variables to be the load intensity applied and the depth or height of the beam member considered. There are many approaches for structural reliability problems. In this paper Extreme Learning Machine technique and First Order Second Moment Method is used to determine the reliability indices for the same set of variables. The reliability index obtained using ELM is compared with the reliability index obtained using FOSM. Higher the reliability index, more feasible is the method to determine the reliability.

Keywords: reliability, reliability index, statistically independent, extreme learning machine

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