Search results for: impact measurement

Authors: Sandani Muthukumarana, Malith Shehan Keraminiyage, Pavithra Rathnasiri

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Climate change is one of the most pressing issues facing our generation. However, it also presents an opportunity to grow the economy using biotechnology. Biotechnology offers a variety of solutions that can help mitigate the effects of global warming. Despite this, there is a lack of research on the potential and challenges associated with the further use of biotechnology to combat the impacts of climate change. To address this gap, it is essential to investigate the current context surrounding the use of biotechnology for climate change mitigation, including potential applications, current practices, and existing challenges. By reviewing the existing literature on these perspectives, this paper aims to provide a comprehensive understanding of the potential for biotechnology to mitigate the hazards of climate change. The use of biotechnology to mitigate the effects of climate change will be made easier as a result, and this will lay the groundwork for further study and actual initiatives in this field. Biotechnology can play a crucial role in mitigating the impacts of climate change. It offers a range of solutions, such as genetically modified crops, bioremediation, and bioenergy, that can help reduce greenhouse gas emissions, enhance carbon sequestration, and increase climate resilience. By utilizing biotechnology, we can reduce the negative impacts of climate change and create a more sustainable future. According to this knowledge, researchers can harness the potential of biotechnology to fight climate change and build a more sustainable future for future generations.

Keywords: biotechnology, impact, solutions, climate changes

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Authors: Sara Rankohi, Lloyd Waugh

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Construction sites are information saturated. Digitalization is hitting construction sites to meet the incredible demand of knowledge sharing and information documentations. From flying drones, 3D Lasers scanners, pocket mobile applications, to augmented reality glasses and smart helmet, visualization technologies help real-time information imposed straight onto construction professional’s field of vision. Although these technologies are very applicable and can have the direct impact on project cost and productivity, experience shows that only a minority of construction professionals quickly adapt themselves to benefit from them in practice. The majority of construction managers still tend to apply traditional construction management methods. This paper investigates a) current applications of visualization technologies in construction projects management, b) the direct effect of these technologies on productivity improvement and cost saving of a multi-residential building project via a case study on Mac Taggart Senior Care project located in Edmonton, Alberta. The research shows the imaged based technologies have a direct impact on improving project productivity and cost savings.

Keywords: image-based technologies, project management, cost, productivity improvement

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Authors: Jing (Claire) LI

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More than two decades from 2000 to 2020 of economic reforms have brought China unprecedented economic growth. There is an urgent call of research towards corporate social responsibility (CSR) in the context of China because while China continues to develop into a global trading market, it suffers from various serious problems relating to CSR. This study analyses the factors affecting the adoption of CSR practices by Chinese listed companies. The author proposes a new framework of factors of CSR adoption. Following common organisational factors and external factors in the literature (including organisational support, company size, shareholder pressures, and government support), this study introduces two additional factors, dynamic capability and regional culture. A survey questionnaire was conducted on the CSR adoption of Chinese listed companies in Shen Zhen and Shang Hai index from December 2019 to March 2020. The survey was conducted to collect data on the factors that affect the adoption of CSR. After collection of data, this study performed factor analysis to reduce the number of measurement items to several main factors. This procedure is to confirm the proposed framework and ensure the significant factors. Through analysis, this study identifies four grouped factors as determinants of the CSR adoption. The first factor loading includes dynamic capability and organisational support. The study finds that they are positively related to the first factor, so the first factor mainly reflects the capabilities of companies, which is one component in internal factors. In the second factor, measurement items of stakeholder pressures mainly are from regulatory bodies, customer and supplier, employees and community, and shareholders. In sum, they are positively related to the second factor and they reflect stakeholder pressures, which is one component of external factors. The third factor reflects organisational characteristics. Variables include company size and cultural score. Among these variables, company size is negatively related to the third factor. The resulted factor loading of the third factor implies that organisational factor is an important determinant of CSR adoption. Cultural consistency, the variable in the fourth factor, is positively related to the factor. It represents the difference between perception of managers and actual culture of the organisations in terms of cultural dimensions, which is one component in internal factors. It implies that regional culture is an important factor of CSR adoption. Overall, the results are consistent with previous literature. This study is of significance from both theoretical and empirical perspectives. First, from the significance of theoretical perspective, this research combines stakeholder theory, dynamic capability view of a firm, and neo-institutional theory in CSR research. Based on association of these three theories, this study introduces two new factors (dynamic capability and regional culture) to have a better framework for CSR adoption. Second, this study contributes to empirical literature of CSR in the context of China. Extant Chinese companies lack recognition of the importance of CSR practices adoption. This study built a framework and may help companies to design resource allocation strategies and evaluate future CSR and management practices in an early stage.

Keywords: China, corporate social responsibility, CSR adoption, dynamic capability, regional culture

Procedia PDF Downloads 134

Authors: Swatantra

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Hinglish, a blended version of Hindi and English, emerged due to the lack of the competence and command of the speakers over the foreign language, i., e., English. But, amazingly, the trend has gained wide acceptance. In India, this acceptance has gone up to the extent that popular news anchors at the prime time shows are frequently using it. At the moment, instead of being considered a flaw of their presentation Hinglish is emerging as a trendy genre. Its pervasive usage and extensive acceptance is motivating youngsters to opt for the similar kind of patterns. The current study is an endeavour to assess the impact of this trend on the new language learners. With the help of semi-structured interviews, the researcher has tried to gauge the level of comfort and desire to be at par with the other fluent English speakers. The results clearly depict a substantiated boost in the confidence level of learners because they are able to use the vocabulary and sentence patterns of their own choice and convenience. The prevalence and acceptance of the trend in the main stream media have really served as a catalyst and the desire to be at par with the other fluent speakers is also fading away. The users of Hinglish find this trend to be closer to their heart as in the earlier times in the absence of exact translation they had to compromise with the meaning or spirit of the word/phrase / sentence. But now enhanced flexibility is leaving them more comfortable and confident.

Keywords: Hinglish, language learners, linguistic trends, media

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Authors: Aribisala Oluwadamilare Olufolarin

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The objective of this research was to examine how corporate governance and ethical business values impact both the performance of the organization and its employees, as it is essential for any organization to uphold good ethics and corporate governance. The study was conducted at Unilag Holdings Limited (UniHOLDs) to demonstrate that organizations may experience losses if they do not have proper corporate governance and business ethical values in place. The employees' perception of corporate governance and ethics is crucial for the organization. The research indicated a connection between corporate governance and business ethics values, and therefore, correlation analysis was utilized, making it statistically reliable. The results of the test show a strong positive correlation (r=.812, N=94, P<.01) between corporate governance and business ethical values. A questionnaire was distributed to employees at Unilag Holdings Limited (UniHOLDs), with 94 out of 130 completed and returned. The findings indicate that ethical values contribute to employee productivity, and productive employees have a beneficial impact on the organization's performance. Additionally, the study revealed that employees tend to adhere to rules regardless of their ethical nature. To address this, the organization should ensure that top-level managers do not assign unethical tasks to their subordinates. The study recommends that the organization should consistently practice corporate governance and business ethics. The company needs to make sure that its stakeholders continue to support its way of doing things.

Keywords: business ethics, business ethical values, corporate governance, organization

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Authors: Sofía Luna, Carla González Salamanca

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The 2008 economic crisis had huge implications in Europe. In this continent, the repercussions of the crisis were not only economic but also political and institutional. The economic stress has generated changes in the perception of the citizens, their attitude and the confidence placed in the political organizations. The lost of confidence is not only present in the debtor countries but it is also present in the European economic powers like Germany and France. This research explains how the economic crisis had an impact in the identity, population’s attitude and how this generated the rise of extreme right parties. In addition, it defines the different types of attitudes and support that exist towards these political and economic institutions. The results of this investigation show that the depression beside of its economic implications, it caused institutional, social and political difficulties for the Union. Moreover, the support and attitudes of the population were severely strained because the confidence in the political organization decreased. Furthermore, a rise in the otherness sentiment was shown. In other words, the distinction between “us” and “them” increased causing repercussions in the collective European identity. Additionally, there was a spread in national identities that caused the rise of the extreme right wing parties. In conclusion, the 2008 economic crisis caused not only economic stress but also it generated a political, social and institutional crisis in Europe.

Keywords: Europe, identity, economic crisis, otherness sentiment

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Authors: Martin Gascón Hove, Ralph Vermeltfoort, Alessandro Fiorini, Erwan Dulaurent, Henning von Perbandt

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Introduction: The outbreak of the COVID-19 pandemic has completely changed the global health situation, with more than 400 million cases published and over 5 million deaths. European Air Transport Command (EATC) is integrated by seven nations, and among its capabilities is that of aeromedical evacuation (AM). Material and methods: Impact of novel coronavirus was analysed based on the number and characteristics of patients and executed missions within EATC and, particularly by Spain, during the biennium 2020-2021. Results: One thousand sixty patients were transported in 186 missions. Neither death nor disease contagion was reported during AM performances. Military cases transferred were 986, mostly routine priority (91,4%), and 74 were civilians, who were transported in 17 missions, and 81,1% of which were categorized as urgent. Niger led the list of original countries, with 191 evacuated patients. 76,1% of requests came from Italy and Germany. Airbus A310 was the most used aircraft (32,2%). Germany transported 222 patients of another nationality, while Spain executed eight missions and repatriated 68 cases, 58 of which were from Mali. Conclusions: COVID-19 has led to a surged number of evacuated patients inside EATC, which has proven to be a safe and effective means of transportation, even in critical cases. Spain has gained prominence since its annexation in 2015.

Keywords: COVID-19, SARS-CoV-2, pandemic, aviation, Spain

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Authors: Matúš Mihalik, Martin Vavra, Kornel Csach, Marián Mihalik

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GdMnO₃ belongs to orthorhombically distorted, GdFeO₃-type family of perovskite compounds. These compounds are naturally vacant and the amount of vacancies depend on the sample preparation conditions. Our GdMnO₃ samples were prepared by float zone method and the vacancies were controlled using an air, Ar and O₂ preparation atmosphere. The highest amount of vacancies was found for sample prepared in Ar atmosphere, while the sample prepared in O₂ was observed to be almost vacancy-free. The magnetic measurements indicate that the preparation atmosphere has no impact on Néel temperature (TN ~ 42 K), however, it has strong impact on the incommensurate antiferromagnetic (IC) to canted A-type weak ferromagnetic (AWF) phase transition at T1: T1 = 23.4 K; 18 K and 6.7 K for samples prepared in Ar; air and O₂ atmosphere; respectively. The hysteresis loop measured at 2 K has a butterfly-type shape with the remnant magnetization (Mr) of 0.6 µB/f.u. for Ar and air sample, while Mr = 0.3 µB/f.u. for O₂ sample. The shape of the hysteresis loop depends on the preparation atmosphere in magnetic fields up to 1.5 T, but is independent for higher magnetic fields. The coercive field of less than 0.06 T and the maximum magnetic moment of 6 µB/f.u. at magnetic field µ0H = 7 T do not depend on the preparation atmosphere. All these findings indicate that only AWF phase of GdMnO₃ compound is directly affected by the vacancies in the system, while IC phase and the field induced ferroelectric phase are not affected.

Keywords: magnetism, perovskites, sample preparation, magnetic phase transition

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Authors: Narvada Ramdhany, Reena Bhattu Babajee

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The 2007-2008 Global Financial Crisis which initiated in the US had a global outreach, impacting the financial and banking sectors of several economies; such as European countries, developing and emerging countries in Asia, Latin America and Africa. European countries represent one of the main sources of export earnings for Mauritius and given that Europe has been quite profoundly affected by the crisis, the Mauritian economy also could have been negatively affected. This study is being undertaken to see if the crisis had a spill-over effect on the Mauritian banking system. It will also enable to determine if the measures put in place to counteract the crisis by regulatory authorities have been effective. The study will be carried out on 17 banks and data will be collected over a time frame of seven years; with a pre-crisis period from 2005 to 2007 and a post-crisis period from 2009 to 2011. The impact of the crisis as such will be measured through the financial performance of the banks, using financial ratios and regression analysis. The results show that during the period concerned Mauritian banks have remained solvent and relatively stable. One of the main explanations put forward to explain the resilience of the banking sector to the crisis is that foreign exposure was relatively low. Another explanation put forward is that Mauritian banks normally transact mainly with prime borrowers unlike most the banks which were affected by the financial crisis.  

Keywords: global financial crisis, banking sector, financial performance, Mauritian banks

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Authors: Yufei Peng, Zhen Qin, Jianbe Li, Jidong Long

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The thermal cathode is widely used in accelerators, FELs and kinds of vacuum electronics. However, emission nonuniformity exists due to surface profile, material distribution, temperature variation, crystal orientation, etc., which will cause intrinsic emittance growth, brightness decline, envelope size augment, device performance deterioration or even failure. To understand how emittance is manipulated by emission nonuniformity, an intrinsic emittance model consisting of contributions from macro and micro surface nonuniformity is developed analytically based on general thermal emission model at temperature limited regime according to a real 3mm cathode. The model shows relative emittance increased about 50% due to temperature variation, and less than 5% from several kinds of micro surface nonuniformity which is much smaller than other research. Otherwise, we also calculated emittance growth combining with Monte Carlo method and PIC simulation, experiments of emission uniformity and emittance measurement are going to be carried out separately.

Keywords: thermal cathode, electron emission fluctuation, intrinsic emittance, surface nonuniformity, cathode lifetime

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Authors: Maatoug Hassine, Mourad Hrizi

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In this paper, we consider a geometric inverse source problem for the heat equation with Dirichlet and Neumann boundary data. We will reconstruct the exact form of the unknown source term from additional boundary conditions. Our motivation is to detect the location, the size and the shape of source support. We present a one-shot algorithm based on the Kohn-Vogelius formulation and the topological gradient method. The geometric inverse source problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a source function. Then, we present a non-iterative numerical method for the geometric reconstruction of the source term with unknown support using a level curve of the topological gradient. Finally, we give several examples to show the viability of our presented method.

Keywords: geometric inverse source problem, heat equation, topological optimization, topological sensitivity, Kohn-Vogelius formulation

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Authors: Hala Abdulhafiz, Steffi Robak

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Introduction: Refugees often arrive in Germany with traumatic experiences, leading to psy-chosocial challenges. According to the World Health Organization's definition, psychosocial life skills help individuals effectively cope with everyday challenges and enhance their overall health and well-being. This study explores life skills acquired in integration courses and their impact on the integration of Syrian migrants. Methods: Qualitative expert interviews identified crucial life skills for successful integration, followed by a qualitative content analysis of integration course textbooks. Additionally, written interviews with former participants of integration courses were conducted. Results: Expert interviews highlighted the significance of communication skills and problem-solving abilities in promoting integration. Emotional and stress management, however, ranked lower in the hierarchy of essential life skills. While many highlighted life skills were addressed and encouraged in textbooks, there was a deficiency in opportunities to strengthen empathy, creativity, emotions, and stress management. The participant survey revealed that respondents possessed some of the defined life skills positively affecting their integration. However, there was a need for enhancing self-esteem, and many struggled with handling emotions and stress situations. Conclusion: The analyzed life skills should be further developed through educational programs and initiatives, with increased emphasis on textbooks.

Keywords: life skills, integration, migration, integration course

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Authors: Lucy Novianti

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The purpose of this study is to determine the effect of corporate governance, ownership structure, and cash holdings on firm value, either direct or indirect through profitability as an intervening variable for non-financial companies listed on the Indonesia Stock Exchange during 2006 to 2014. Samples of 176 firms are chosen based on purposive sampling method. The results of this study conclude that profitability, the size of Audit Committee, audit quality, and cash flow have positive effects on firm value. This study also shows that the meeting frequency of the Board of Directors and free cash flow have negative effects on firm value. In addition, this study finds that the size of the Board of Directors, Independent Commissioner, and ownership structure do not have significant effects on firm value. In this study, the function of profitability as an intervening variable can only be done on the impact of the meeting frequency of the Board of Directors and cash flow on firm value. This study provides a reference for management in decision making concerning the application of corporate governance, cash holdings, and financial performance. Moreover, it can be used as additional information for investors in assessing the feasibility of an investment. Finally, it provides a suggestion for the government regarding the regulation of corporate governance.

Keywords: cash holdings, corporate governance, firm value, ownership structure, profitability

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Surapol Raadnui

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This particular work describes an experimental investigation on gear wear in which wear and pitting were intentionally allowed to occur, namely, moisture corrosion pitting, acid-induced corrosion pitting, hard contaminant-related pitting and mechanical induced wear. A back to back spur gear test rig and a grease lubricated worm gear rig were used. The tests samples of wear debris were collected and assessed through the utilization of an optical microscope in order to correlate and compare the debris morphology to pitting and wear degradation of the worn gears. In addition, weight loss from all test gear pairs were assessed with utilization of statistical design of experiment. It can be deduced that wear debris characteristics from both cases exhibited a direct relationship with different pitting and wear modes. Thus, it should be possible to detect and diagnose gear pitting and wear utilization of worn surfaces, generated wear debris and quantitative measurement such as weight loss.

Keywords: predictive maintenance, worm gear, spur gear, wear debris analysis, problem diagnostic

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Authors: Lukman Andi Priyatna, Vivi Fauzia, Ferry Anggoro Ardy Nugroho

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Zinc oxide (ZnO) based nanostructures are ubiquitous in applications due to their favourable physicochemical properties and ease of fabrication. One widely accessible route to synthesize ZnO nanorods, which show promising performance in e.g. photoelectrochemical water splitting, is hydrothermal growth of ZnO seeds, obtained via an atomic nebulizer. Despite its popularity, study on the impact of the synthesis parameters in atomic nebulizer on the performance of the synthesized ZnO nanostructures is lacking. This study presents an investigation on the impact of the distance between substrates and atomic nebulizer nozzle on the photoelectrochemical water splitting performance of ZnO nanorods. Adjusting such a distance reveals an optimum separation which results in nanostructures with highest absorbance. Such high absorbance translates into improved photoelectrochemistry, as evaluated by higher photocurrent density, from 0.11 mA/cm² to 0.14 mA/cm² and higher Applied Bias Photon-to-Current Efficiency (ABPE) from 0.12% to 0.14%. These results underscore the importance of understanding and optimizing the experimental parameters during ZnO nanostructure synthesis. In a broader context, it advertises the need to carefully assess the corresponding fabrication parameters to optimize the performance of the obtained nanostructures.

Keywords: atomic nebulizer, photocurrent density, photoelectrochemical water splitting, ZnO nanorods

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Authors: Lojain Suliman, Xinrong Liu, Xiaohan Zhou

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Since most tunnels are built in crowded metropolitan settings, the excavation process must take place in highly condensed locations, including high-density cities. In this way, the tunnels are typically located close together, which leads to more interaction between the parallel existing tunnels, and this, in turn, leads to more settlement. This research presents an examination of the impact of a large-scale tunnel excavation on two forms of settlement: surface settlement and settlement surrounding the tunnel. Additionally, research has been done on the properties of interactions between two and three parallel tunnels. The settlement has been evaluated using three primary techniques: theoretical modeling, numerical simulation, and data monitoring. Additionally, a parametric investigation on how distance affects the settlement characteristic for parallel tunnels with short distances has been completed. Additionally, it has been observed that the sequence of excavation has an impact on the behavior of settlements. Nevertheless, a comparison of the model test and numerical simulation yields significant agreement in terms of settlement trend and value. Additionally, when compared to the FEM study, the suggested analytical solution exhibits reduced sensitivity in the settlement prediction. For example, the settlement of the small tunnel diameter does not appear clearly on the settlement curve, while it is notable in the FEM analysis. It is advised, however, that additional studies be conducted in the future employing analytical solutions for settlement prediction for parallel tunnels.

Keywords: settlement, FEM, analytical solution, parallel tunnels

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Authors: Lahcene Boukelkoul

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The influence of finite ground conductivity is of great importance in calculating the induced voltages from the radiated electromagnetic fields due to lightning. In this paper, we try to give a comprehensive approach to calculate the impact of the ground on the radiated electromagnetic fields to lightning. The vertical component of lightning electric field is calculated with a reasonable approximation assuming a perfectly conducting ground in case the observation point does not exceed a few kilometres from the lightning channel. However, for distant observation points the radiated vertical component of lightning electric field is attenuated due finitely conducting ground. The attenuation is calculated using the expression elaborated for both low and high frequencies. The horizontal component of the electric field, however, is more affected by a finite conductivity of a ground. Besides, the contribution of the horizontal component of the electric field, to induced voltages on an overhead transmission line, is greater than that of the vertical component. Therefore, the calculation of the horizontal electric field is great concern for the simulation of lightning-induced voltages. For field to transmission lines coupling the ground impedance is calculated for early time behaviour and for low frequency range.

Keywords: power engineering, radiated electromagnetic fields, lightning-induced voltages, lightning electric field

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Authors: Jawad Taheri

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This paper investigates the impact of foreign aid-funded development projects on corruption perception in Afghanistan, utilizing instrumental variable (IV) approaches in regression analysis setting. Seven sub-categories of development projects are examined in order to have a glance over comparative usefulness of each project. The study incorporates natural disaster indicators as exogenous variables to mitigate endogeneity concerns and control variables. The findings reveal significant associations between certain types of projects and corruption perception. Road and bridge construction, irrigation, and agriculture projects are found to decrease corruption perception, fostering optimism and trust within affected communities. Mosque construction and healthcare initiatives aligned with religious beliefs also contribute to reduced corruption perception. However, drinking water projects are associated with increased corruption perception, highlighting potential challenges in their implementation. The study emphasizes the importance of well-implemented projects, cultural contexts, and effective governance in mitigating corruption and fostering trust within communities. These findings contribute to a refined understanding of the relationship between development projects and corruption perception in Afghanistan.

Keywords: foreign aid, development projects, corruption perception, Afghanistan, instrumental variable analysis, survey of Afghan people (SAP), natural disasters, exogenous variation

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Authors: Aribisala Oluwadamilare Olufolarin

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The objective of this research was to examine how corporate governance and ethical business values impact both the performance of the organization and its employees, as it is essential for any organization to uphold good ethics and corporate governance. The study was conducted at Unilag Holdings Limited (UniHOLDs) to demonstrate that organizations may experience losses if they do not have proper corporate governance and business ethical values in place. The employees' perception of corporate governance and ethics is crucial for the organization. The research indicated a connection between corporate governance and business ethics values, and therefore, correlation analysis was utilized, making it statistically reliable. The results of the test show a strong positive correlation (r=.812, N=94, P<.01) between corporate governance and business ethical values. A questionnaire was distributed to employees at Unilag Holdings Limited (UniHOLDs), with 94 out of 130 completed and returned. The findings indicate that ethical values contribute to employee productivity, and productive employees have a beneficial impact on the organization's performance. Additionally, the study revealed that employees tend to adhere to rules regardless of their ethical nature. To address this, the organization should ensure that top-level managers do not assign unethical tasks to their subordinates. The study recommends that the organization should consistently practice corporate governance and business ethics. The company needs to make sure that its stakeholders continue to support its way of doing things.

Keywords: business ethics, business ethical values, corporate governance and organization, corporate governance

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Authors: Obaidullah Molakhail, R. Reshmi

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Objective: This study explains the impact of talent management on employee loyalty in the IT sector in Kerala, India. Methods: A descriptive investigation was conducted within the confines of this paper to gain insight into the ramifications of talent management on enhancing employee allegiance to the organization. A quantitative study was conducted by distributing questionnaires to respondents in three IT companies. One hundred and seventy questionnaires were distributed, with `150 being utilized and the remainder being discarded. Data was collected from various departments within the companies, and the selection of respondents was conducted randomly. statistical software SPSS (version 26) was used to analyze the data and determine the outcomes. Results: The objective was examined through Pearson correlation to find the relation, and linear regression was used to find the strength of variables as talent management is independent and employee loyalty is the dependent variable. The results reveal that talent management is essential to employee loyalty. If there is a high-level implementation of talent management practices, there will be low turnover rate, it reflected employee loyalty towards the organization. Conclusion: Strategic planners ought to devote their attention to the realm of talent management due to the existence of a correlation between talent management and the loyalty exhibited by employees. The results of this study suggest that there is a favorable correlation between talent management and employee loyalty.

Keywords: talent management, employee loyalty, IT sector, quantitative study

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Authors: Chun-Wei Liu, Feng-Tsai Weng

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People faced pollution threaten in modern age although the standard of exhaust gas of vehicles has been established. The goal of this study is to investigate the effect of water atomizer in a vehicle emission system. Diluted 20% ammonia water was used in spraying system. Micro particles produced by exhausted gas from engine of vehicle which were cumulated through atomized spray in a self-development collector. In experiments, a self-designed atomization model plate and a gas tank controlled by the micro-processor using Pulse Width Modulation (PWM) logic was prepared for exhaust test. The gas from gasoline-engine of vehicle was purified with the model panel collector. A soft well named ANSYS was utilized for analyzing the distribution condition of rejected gas. Micro substance and percentage of CO, HC, CO2, NOx in exhausted gas were investigated at different engine speed, and atomizer vibration frequency. Exceptional results in the vehicle engine emissions measurement were obtained. The temperature of exhausted gas can be decreased 3oC. Micro substances PM10 can be decreased and the percentage of CO can be decreased more than 55% at 2500RPM by proposed system. Value of CO, HC, CO2 and NOX was all decreased when atomizers were used with water.

Keywords: atomizer, CO, HC, NOx, PM2.5

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Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar

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Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.

Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE

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Authors: Leila Ben Haj Said, Sihem Bellagha, Karim Allaf

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The present study deals with the dehydrofreezing assisted by instant controlled pressure drop (DIC) treatment of apple fruits. Samples previously dehydrated until different water contents (200, 100, and 30% dry basis (db)) and DIC treated were frozen at two different freezing velocities (V+ and V-), depending on the thermal resistance established between the freezing airflow and the sample surface. The effects of sample water content (W) and freezing velocity (V) on freezing curves and characteristics, exudate water (EW) and texture variation were examined. Lower sample water content implied higher freezing rates, lower initial freezing points (IFP), lower practical freezing time (PFT), and lower specific freezing time (SFT). EW (expressed in g exudate water/100 g water in the product) of 200% and 100% db apple samples was approximately 3%, at low freezing velocity (V-). Whereas, it was lower than 0.5% for apple samples with 30% db water content. Moreover, the impact of freezing velocity on EW was significant and very important only for high water content samples. For samples whose water content was lower than 100% db, firmness (maximum puncture force) was as higher as the water content was lower, without any insignificant impact of freezing velocity.

Keywords: dehydrofreezing, instant controlled pressure drop DIC, freezing time, texture

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Authors: Valerie Habbel, Magdalena Orth, Johanna Richter, Steffen Schimko

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Cooperation between development actors and the private sector is becoming increasingly important, as it is expected to mobilize additional resources to achieve the Sustainable Development Goals (SDGs), among other things. However, whether the goals of cooperation are achieved has so far only been explored in evaluations and studies of individual projects and instruments. The evaluation synthesis attempts to close this gap by systematically analyzing existing evidence (evaluations and academic studies) from national and international development cooperation on private sector engagement. Overall, the evaluations and studies considered report mainly positive effects on investors and donors, intermediaries, partner countries, and target groups. However, various analyses, including on the quality of the evaluations, point to a positive bias in the results. The evaluation synthesis makes recommendations on the definition of indicators, the measurement and evaluation of impacts and additionality, knowledge management, and the consideration of transaction costs in cooperation with private actors.

Keywords: evaluation synthesis, private sector engagement, international development, sustainable development

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Authors: Luis Rodrigo Valencia Perez, Francisco Flores Aguero, Gibran Aguilar Rangel

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Artificial Intelligence (AI) is rapidly transforming diverse sectors, and higher education in Latin America is no exception. This article explores the impact of AI on higher education institutions in the region, highlighting the imperative need for well-trained teachers in emerging technologies and a cultural shift towards the adoption and efficient use of these tools. AI offers significant opportunities to improve learning personalization, optimize administrative processes, and promote more inclusive and accessible education. However, the effectiveness of its implementation depends largely on the preparation and willingness of teachers to integrate these technologies into their pedagogical practices. Furthermore, it is essential that Latin American countries develop and implement public policies that encourage the adoption of AI in the education sector, thus ensuring that institutions can compete globally. Policies should focus on the continuous training of educators, investment in technological infrastructure, and the creation of regulatory frameworks that promote innovation and the ethical use of AI. Only through a comprehensive and collaborative approach will it be possible to fully harness the potential of AI to transform higher education in Latin America, thereby boosting the region's development and competitiveness on the global stage.

Keywords: artificial intelligence (AI), higher education, teacher training, public policies, latin america, global competitiveness

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Sultan Ayoub Meo

Abstract:

Environmental pollution is a highly challenging global concern of the 21st century and is a major cause of various communicable and non-communicable diseases. We investigate the impact of air pollution on "lung function, fractional exhaled nitric oxide, and cognitive function"in a group of one hundred young students studying in a traffic-polluted school. The students wereselected based on their age, gender, height, weight, and ethnicity. After the clinical history, one hundred students were recruited from the schoolnear and away from the polluted areas. The lung and cognitive functions were recorded. The results revealed that lung and cognitive function parameters were reduced in groups of students studying in a school located in a traffic-polluted area compared to thosestudying in a schoolsituated away from the traffic-polluted area. Environmental pollution impairs students' lung and cognitive functions studying in schools located within traffic-polluted areas. The health officials and policymakers establish strategies to minimize environmental pollution and its allied health hazards. Prof. Sultan Ayoub Meo, MD, Ph.D Professor, Department of Physiology, College of Medicine, King Saud University, Saudi Arabia Email. [email protected] / [email protected]

Keywords: environmental pOllution, lung physiology, cognitive functions, air pollution

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Authors: Margaret K. Spoo-Chupka

Abstract:

The Metropolitan Water District of Southern California (MWDSC) manages surface water reservoirs that are a source of drinking water for more than 19 million people in Southern California. These reservoirs experience periodic planktonic cyanobacteria blooms that can impact water quality. MWDSC imports water from two sources – the Colorado River (CR) and the State Water Project (SWP). The SWP brings supplies from the Sacramento-San Joaquin Delta that are characterized as having higher nutrients than CR water. Above average precipitation in 2017 after five years of drought allowed the majority of the reservoirs to fill. Phytoplankton was analyzed during the drought and after the drought at three reservoirs: Diamond Valley Lake (DVL), which receives SWP water exclusively, Lake Skinner, which can receive a blend of SWP and CR water, and Lake Mathews, which generally receives only CR water. DVL experienced a significant increase in water elevation in 2017 due to large SWP inflows, and there were no significant changes to total phytoplankton biomass, Shannon-Wiener diversity of the phytoplankton, or cyanobacteria biomass in 2017 compared to previous drought years despite the higher nutrient loads. The biomass of cyanobacteria that could potentially impact DVL water quality (Microcystis spp., Aphanizomenon flos-aquae, Dolichospermum spp., and Limnoraphis birgei) did not differ significantly between the heavy precipitation year and drought years. Compared to the other reservoirs, DVL generally has the highest concentration of cyanobacteria due to the water supply having greater nutrients. Lake Mathews’ water levels were similar in drought and wet years due to a reliable supply of CR water and there were no significant changes in the total phytoplankton biomass, phytoplankton diversity, or cyanobacteria biomass in 2017 compared to previous drought years. The biomass of cyanobacteria that could potentially impact water quality at Lake Mathews (L. birgei and Microcystis spp.) did not differ significantly between 2017 and previous drought years. Lake Mathews generally had the lowest cyanobacteria biomass due to the water supply having lower nutrients. The CR supplied most of the water to Lake Skinner during drought years, while the SWP was the primary source during 2017. This change in water source resulted in a significant increase in phytoplankton biomass in 2017, no significant change in diversity, and a significant increase in cyanobacteria biomass. Cyanobacteria that could potentially impact water quality at Skinner included: Microcystis spp., Dolichospermum spp., and A.flos-aquae. There was no significant difference in Microcystis spp. biomass in 2017 compared to previous drought years, but biomass of Dolichospermum spp. and A.flos-aquae were significantly greater in 2017 compared to previous drought years. Dolichospermum sp. and A. flos-aquae are two cyanobacteria that are more sensitive to nutrients than Microcystis spp., which are more sensitive to temperature. Patterns in problem cyanobacteria abundance among Southern California reservoirs as a result of above-average precipitation after more than five years of drought were most closely related to nutrient loading.

Keywords: drought, reservoirs, cyanobacteria, and phytoplankton ecology

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