Search results for: language models

Authors: Yongsheng Guo, Shuchao Li

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This study explores Chinese foreign direct investment (FDI) in Europe and the cross-cultural cooperation between Chinese and European managers. The aim of this research is to shed light on the phenomenon of investments in developed countries from an emerging market and to gain insights into the cooperation process. A grounded theory approach is adopted, and 46 semi-structured interviews were conducted with 10 case companies in Germany and 13 case companies in the UK. Grounded theory models are developed from primary data and interview quotes are used to support the themes. The interviewees perceived differences between the two parties in cultural traits, management concepts, knowledge structure and resource endowment between the two parties. Chinese and European partners can take advantage of different resources and cooperate in innovative ways to improve corporate performance. Moreover, both parties appreciate different ethical and cultural characteristics and complement each other to develop a combined organizational culture. This study proposes an ethical and cultural diversity theory in international management arguing that a team with diversified values and behaviors may be more excited and motivated. This study suggests that “resource complement” and “cross-cultural cooperation” might be an advantage for international investment. Firms are encouraged to open their minds and cooperate with partners with different resources and cultures. The authorities may review the FDI policies to reduce social and political barriers.

Keywords: cross-culture, FDI, cooperation, innovation, China, Europe

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Authors: Jennifer K. Bowerman, Rhonda L. Reich

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The purpose of this paper is to explore the concepts ACDC (Amore, Consciousness, Discipline, and Commitment) which the authors first discovered as a philosophy and framework for recruitment and organizational development in a successful start-up tech company in Brazil. This paper represents an exploration of these concepts as a potential pedagogical foundation for undergraduate business education in the classroom. It explores whether their application has potential to build emotional and practical resilience in the face of constant organizational and societal change. Derived from Holonomy this paper explains the concepts and develops a narrative around how change influences the operation of organizations. Using examples from leading edge organizational theorists, it explains why a different educational approach grounded in ACDC concepts may not only have relevance for the working world, but also for undergraduates about to enter that world. The authors propose that in the global context of constant change, it makes sense to develop an approach to education, particularly business education, beyond cognitive knowledge, models and tools, in such a way that emotional and practical resilience and creative thinking may be developed. Using the classroom as an opportunity to explore these concepts, and aligning personal passion with the necessary discipline and commitment, may provide students with a greater sense of their own worth and potential as they venture into their ever-changing futures.

Keywords: ACDC, holonomic thinking, organizational learning, organizational change, business pedagogy

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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Authors: Cameron Jones

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Emissions, produced by landfill waste from demolished obsolete buildings, have a damaging effect on both the Earth’s climate and human health. The philosophical theory of material vitalism - the potential for materials to react and emit harmful pollutants - therefore defines this construction and demolition waste (CDW) as having vitality. The European Union’s ‘Circular Economic Action Plan’ (CEAP) aims to mitigate the effects of CDW by prioritising the circularity of building materials. This dissertation examines how the philosophical theory of material vitalism can make an environmentally responsible contribution to CDW policy. The CEAP and Silvertown Quays development are used as case studies for the application of vitalism to policy revision. The study concludes that vitalism has a positive role to play in informing CDW policy, although its contribution is stronger in some areas. This is established by first appraising the aspects that relate to the obsolescence of buildings outlined in the EU’s existing CDW policies. Next, these policy directives are compared with the CE principles employed in the Silvertown Quays development. Subsequently, a keyword analysis model is used to categorise the language used in the CEAP, demonstrating how socio-political approaches to the CE and strategies to address resource scarcity could be strengthened to represent the EU’s policy aspirations more effectively. Recommendations are then made on how material vitalism could be utilised to strengthen legislation, arguing that a notable contribution can be made in most policy areas. Finally, theoretical testing of the impact of these revisions to policy on the case study development identified some practicalities for consideration in improving waste management outcomes.

Keywords: vitalism, construction waste, obsolescence, political ecology, exceptionalism

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Authors: Marziyeh Khavari

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In recent decades, climate change, global warming, and the growing population worldwide face some challenges, such as increasing food consumption and shortage of resources. Assessing how climate change could disturb crops, especially hazelnut production, seems crucial for sustainable agriculture production. For hazelnut cultivation in the mid-warm condition, such as in Iran, here we present an investigation of climate parameters and how much they are effective on fertility and nut production of hazelnut trees. Therefore, the climate change of the northern zones in Iran has investigated (1960-2017) and was reached an uptrend in temperature. Furthermore, the descriptive analysis performed on six cultivars during seven years shows how this small-scale survey could demonstrate the effects of climate change on hazelnut production and stability. Results showed that some climate parameters are more significant on nut production, such as solar radiation, soil temperature, relative humidity, and precipitation. Moreover, some cultivars have produced more stable production, for instance, Negret and Segorbe, while the Mervill de Boliver recorded the most variation during the study. Another aspect that needs to be met is training and predicting an actual model to simulate nut production through a neural network and linear regression simulation. The study developed and estimated the ANN model's generalization capability with different criteria such as RMSE, SSE, and accuracy factors for dependent and independent variables (environmental and yield traits). The models were trained and tested while the accuracy of the model is proper to predict hazelnut production under fluctuations in weather parameters.

Keywords: climate change, neural network, hazelnut, global warming

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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Authors: Sapan Tiwari, Namrata Ghosh

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In urban mass transit, crew scheduling always plays a significant role. It deals with the formulation of work timetables for its staff so that an organization can meet the demand for its products or services. The efficient schedules of a specified timetable have an enormous impact on staff demand. It implies that an urban mass transit company's financial outcomes are strongly associated with planning operations in the region. The research aims to demonstrate the state of the crew scheduling studies and its practical implementation in mass transit businesses in metropolitan areas. First, there is a short overview of past studies in the field. Subsequently, the restrictions and problems with crew scheduling and some models, which have been developed to solve the related issues with their mathematical formulation, are defined. The comments are completed by a description of the solution opportunities provided by computer-aided scheduling program systems for operational use and exposures from urban mass transit organizations. Furthermore, Bus scheduling is performed using the Hungarian technique of problem-solving tasks and mathematical modeling. Afterward, the crew scheduling problem, which consists of developing duties using predefined tasks with set start and end times and places, is resolved. Each duty has to comply with a set line of work. The objective is to minimize a mixture of fixed expenses (number of duties) and varying costs. After the optimization of cost, the outcome of the research is that the same frequency can be provided with fewer buses and less workforce.

Keywords: crew scheduling, duty, optimization of cost, urban mass transit

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Authors: Mamta Rajbhar, Sanjay K. Mohanty

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India's progress in achieving replacement level of fertility is largely contingent on fertility reduction in the state of Uttar Pradesh as it accounts 17% of India's population with a low level of development. Though the TFR in the state has declined from 5.1 in 1991 to 3.4 by 2011, it conceals large differences in fertility level across districts. Using data from multiple sources this paper tests the hypothesis that the improvement in human development significantly reduces the fertility levels in districts of Uttar Pradesh. The unit of analyses is district, and fertility estimates are derived using the reverse survival method(RSM) while human development indices(HDI) are are estimated using uniform methodology adopted by UNDP for three period. The correlation and linear regression models are used to examine the relationship of fertility change and human development indices across districts. Result show the large variation and significant change in fertility level among the districts of Uttar Pradesh. During 1991-2011, eight districts had experienced a decline of TFR by 10-20%, 30 districts by 20-30% and 32 districts had experienced decline of more than 30%. On human development aspect, 17 districts recorded increase of more than 0.170 in HDI, 18 districts in the range of 0.150-0.170, 29 districts between 0.125-0.150 and six districts in the range of 0.1-0.125 during 1991-2011. Study shows significant negative relationship between HDI and TFR. HDI alone explains 70% variation in TFR. Also, the regression coefficient of TFR and HDI has become stronger over time; from -0.524 in 1991, -0.7477 by 2001 and -0.7181 by 2010. The regression analyses indicate that 0.1 point increase in HDI value will lead to 0.78 point decline in TFR. The HDI alone explains 70% variation in TFR. Improving the HDI will certainly reduce the fertility level in the districts.

Keywords: Fertility, HDI, Uttar Pradesh

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Authors: Helen S. Ghali, Engy Serag, A. Samer Ezeldin

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In many countries, the construction industry relies heavily on outsourcing models in executing their projects and expanding their businesses to fit in the diverse market. Such extensive integration of subcontractors is becoming an influential factor in contractor’s cash flow management. Accordingly, subcontractors’ financial terms are important phenomena and pivotal components for the well-being of the contractor’s cash flow. The aim of this research is to study the contractor’s cash flow with respect to the owner and subcontractor’s payment management plans, considering variable advance payment, payment frequency, and lag and retention policies. The model is developed to provide contractors with a decision support tool that can assist in selecting the optimum subcontracting plan to minimize the contractor’s financing limits and optimize the profit values. The model is built using Microsoft Excel VBA coding, and the genetic algorithm is utilized as the optimization tool. Three objective functions are investigated, which are minimizing the highest negative overdraft value, minimizing the net present worth of overdraft, and maximizing the project net profit. The model is validated on a full-scale project which includes both self-performed and subcontracted work packages. The results show potential outputs in optimizing the contractor’s negative cash flow values and, in the meantime, assisting contractors in selecting suitable subcontractors to achieve the objective function.

Keywords: cash flow optimization, payment plan, procurement management, subcontracting plan

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Authors: K. Ö. Kartal, L. Maul, M. Hägele

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With the development of new technologies come additional opportunities for the founding of companies and new markets to be created. The barriers to entry are lowered and technology makes old business models obsolete. Incumbent companies have to be adaptable to this quickly changing environment. They have to start the process of digital maturation and they have to be able to adapt quickly to new and drastic changes that might arise. One of the biggest barriers for organizations in order to do so is their culture. This paper shows the core elements of a corporate culture that supports the process of digital maturation in incumbent organizations. Furthermore, it is explored how ideation and innovation can be used in a strategy in order to facilitate these core elements of culture that promote digital maturity. Focus areas are identified for the design of ideation strategies, with the aim to make the facilitation and incitation process more effective, short to long term. Therefore, one in-depth case study is conducted with data collection from interviews, observation, document review and surveys. The findings indicate that digital maturity is connected to cultural shift and 11 relevant elements of digital culture are identified which have to be considered. Based on these 11 core elements, five focus areas that need to be regarded in the design of a strategy that uses ideation and innovation to facilitate the cultural shift are identified. These are: Focus topics, rewards and communication, structure and frequency, regions and new online formats.

Keywords: digital transformation, innovation management, ideation strategy, creativity culture, change

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Authors: Anh T. P. Tran, Harald Von Korflesch

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Entrepreneurial intention play a major role in entrepreneurship academia and practice. The spectrum ranges from the first model of the so-called Entrepreneurial Event, then the Theory of Planned Behavior, the Theory of Planned Behavior Entrepreneurial Model, and the Social Cognitive Career Theory to some typical empirical studies with more or less diverse results. However, little is known so far about the intentions of entrepreneurs in the social areas of venture creation. It is surprising that, since social entrepreneurship is an emerging field with growing importance. Currently, all around the world, there is a big challenge with a lot of urgent soaring social and environmental problems such as poor households, people with disabilities, HIV/AIDS infected people, the lonely elderly, or neglected children, some of them even actual in the Western countries. In addition, the already existing literature on entrepreneurial intentions demonstrates a high level of theoretical diversity in general, especially the missing link to the social dimension of entrepreneurship. Seeking to fill the mentioned gaps in the social entrepreneurial intentions literature, this paper proposes a conceptual model of social entrepreneurial intentions based on the Social Cognitive Career Theory with two main factors influencing entrepreneurial intentions namely self-efficacy and outcome expectation. Moreover, motives, goals and plans do not arise from empty nothingness, but are shaped by interacting with the environment. Hence, personalities (i.e., agreeableness, conscientiousness, extraversion, neuroticism, openness) as well as contextual factors (e.g., role models, education, and perceived support) are also considered as the antecedents of social entrepreneurship intentions.

Keywords: entrepreneurial intention, social cognitive career theory, social entrepreneurial intention, social entrepreneurship

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Authors: Nureni O. Adeboye, Dawud A. Agunbiade

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This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.

Keywords: audit fee lagrange multiplier test, heteroscedasticity, lagrange multiplier test, Monte-Carlo scheme, periodicity

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Authors: Abimbola M. Enitan, J. Adeyemo

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Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (µmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (dˉ¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: brewery wastewater, methane generation model, environment, anaerobic modeling

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Authors: Dana Mohammed, Fatemah Abdullah, Hawraa Ali, Najat Al-Shaer, Rawan Al-Awadhi, , Magdy Helal

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We study the patient service performance at the emergency department of a major Kuwaiti public hospital, using discrete simulation and lean concepts. In addition to the common problems in such health care systems (over crowdedness, facilities planning and usage, scheduling and staffing, capacity planning) the emergency department suffered from several cultural and patient behavioural issues. Those contributed significantly to the system problems and constituted major obstacles in maintaining the performance in control. This led to overly long waiting times and the potential of delaying providing help to critical cases. We utilized the visual management tools to mitigate the impact of the patients’ behaviours and attitudes and improve the logistics inside the system. In addition a proposal is made to automate the date collection and communication within the department using RFID-based barcoding system. Discrete event simulation models were developed as decision support systems; to study the operational problems and assess achieved improvements. The simulation analysis resulted in cutting the patient delays to about 35% of their current values by reallocating and rescheduling the medical staff. Combined with the application of the visual management concepts, this provided the basis to improving patient service without any major investments.

Keywords: simulation, visual management, health care system, patient

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Authors: I. Salas-Menotti

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Problem-solving courts were created to assist offenders with specific needs that were not addressed properly in traditional courts. Problem-solving courts' main objective is to pursue solutions that will benefit the offender, the victim, and society as well. These courts were developed as an innovative response to deal with issues such as drug abuse, mental illness, and domestic violence. In Brooklyn, men who are charged with domestic violence related offenses for the first time are offered plea bargains that include the attendance to a domestic abuse intervention program as a condition to dismiss the most serious charges and avoid incarceration. The desired outcome is that the offender will engage in a program that will modify his behavior avoiding new incidents of domestic abuse, it requires accountability towards the victim and finally, it will hopefully bring down statistic related to domestic abuse incidents. This paper will discuss the effectiveness of the Duluth model as applied to Spanish-speaking men mandated to participate in the program by the specialized domestic violence courts in Brooklyn. A longitudinal study was conducted with 243 Spanish- speaking men who were mandated to participated in the men's program offered by EAC in Brooklyn in the years 2016 through 2018 to determine the recidivism rate of domestic violence crimes. Results show that the recidivism rate was less than 5% per year after completing the program which indicates that the intervention is effective in preventing new abuse allegations and subsequent arrests. It's recommended that comparative study with English-speaking participants is conducted to determine cultural and language variables affecting the program's efficacy.

Keywords: domestic violence, domestic abuse intervention programs, Problem solving courts, Spanish-speaking offenders

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Authors: Parnaz Boodagh, Danila Vella, Antonio Damore, Laura Modica De Mohac, Sang-Ho Ye, Garret Coyan, Gaetano Burriesci, William Wagner, Federica Cosentino

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The use of cardiac patches is among the main therapeutic solution for cardiovascular diseases, a leading mortality cause in the world with an increasing trend, responsible of 19 millions deaths in 2020. Several classes of biomaterials serve that purpose, both of synthetic origin and biological derivation, and many bioengineered treatment alternatives were proposed to satisfy two main requirements, providing structural support and promoting tissue remodeling. The objective of this paper is to compare the mechanical properties and the characterization of four cardiac patches: the Adeka, PhotoFix, CorPatch, and CardioCel patches. In vitro and in vivo tests included: biaxial, uniaxial, ball burst, suture retention for mechanical characterization; 2D surface topography, 3D volume and microstructure, and histology assessments for structure characterization; in vitro test to evaluate platelet deposition, calcium deposition, and macrophage polarization; rat right ventricular outflow tract (RVOT) models at 8- and 16-week time points to characterize the patch-host interaction. Lastly, the four patches were used to produce four stented aortic valve prosthesis, subjected to hydrodynamic assessment as well as durability testing to verify compliance with the standard ISO.

Keywords: cardiac patch, cardiovascular disease, cardiac repair, blood contact biomaterial

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Authors: Wenbo Wang, Yi-Fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state-of-the-art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study introduces a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive, and authoritative data; 2) developing a search function to automatically select relevant, new, and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graphs in Wikidata to dynamically augment the representations of claims and references without introducing too much noise, II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: fact checking, claim verification, deep learning, natural language processing

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Authors: Nashalla Gwyn Nyinda

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The ancient system of Tibetan Medicine, known as Sowa Rigpa across the Himalayan regions, is a systematic system of healing encouraging balance primarily through diet and behavior modifications. With the rise of the popularity of Tibetan Medicine, compliance is critical to successful treatment outcomes. As patients learn more about who they are as individuals and how their elemental balances or imbalances affect disorders and mental-emotional balance, they develop faith and dedication to their healing process. Specifically, regarding diet and behavior and the basic principles of the medical system, patient compliance increases dramatically in all treatment areas when they understand why a treatment or dietary prescription guidance is effective. Successful responses to Tibetan treatment rely on a buy-in from the patient. Trust between the slower process of Traditional medicine treatments, the Tibetan physician and the patient is a cornerstone of treatment. The resulting decrease in the use of allopathic medicine and better health outcomes for acute and chronic disorders are well documented. This paper addresses essential points of the Tibetan Medicine system, dialogue between doctor and patient focused on appropriate and seasonal changing dietetics. Such fluctuating treatment approaches, based on external elemental factors, dramatically increase treatment outcomes. Specifically, this work addresses why allopathic medicine models may need more trust development between practitioner and patient.

Keywords: compliancy in treatment, diet and lifestyle medicine, nature and elements as medicine, seasonal diets, Sowa Rigpa, traditional Tibetan medicine, treatment outcomes

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Authors: Annette Joseph

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Background: The construction industry is dynamic in nature owing to the increasing uncertainties in technology, budgets, and development processes making projects more complex. Thus, predicting project performance and chances of its likely success has become difficult. The goal of all parties involved in construction projects is to successfully complete it on schedule, within planned budget and with the highest quality and in the safest manner. However, the concept of project success has remained ambiguously defined in the mind of the construction professionals. Purpose: This paper aims to study the analysis of a project in terms of its performance and measure the success. Methodology: The parameters for evaluating project success and the indices to measure success/performance of a project are identified through literature study. Through questionnaire surveys aimed at the stakeholders in the projects, data is collected from two live case studies (an ongoing and completed project) on the overall performance in terms of its success/failure. Finally, with the help of SPSS tool, the data collected from the surveys are analyzed and applied on the selected performance indices. Findings: The score calculated by using the indices and models helps in assessing the overall performance of the project and interpreting it to find out whether the project will be a success or failure. This study acts as a reference for firms to carry out performance evaluation and success measurement on a regular basis helping projects to identify the areas which are performing well and those that require improvement. Originality & Value: The study signifies that by measuring project performance; a project’s deviation towards success/failure can be assessed thus helping in suggesting early remedial measures to bring it on track ensuring that a project will be completed successfully.

Keywords: project, performance, indices, success

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Authors: Carolin Lutz, Jörg Matthes, Patrick Waibel, Ulrich Precht, Krassimir Garbev, Günter Beuchle, Uwe Schweike, Peter Stemmermann, Hubert B. Keller

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Online measurement of the product quality is a challenging task in cement production, especially in the production of Celitement, a novel environmentally friendly hydraulic binder. The mineralogy and chemical composition of clinker in ordinary Portland cement production is measured by X-ray diffraction (XRD) and X ray fluorescence (XRF), where only crystalline constituents can be detected. But only a small part of the Celitement components can be measured via XRD, because most constituents have an amorphous structure. This paper describes the development of algorithms suitable for an on-line monitoring of the final processing step of Celitement based on NIR-data. For calibration intermediate products were dried at different temperatures and ground for variable durations. The products were analyzed using XRD and thermogravimetric analyses together with NIR-spectroscopy to investigate the dependency between the drying and the milling processes on one and the NIR-signal on the other side. As a result, different characteristic parameters have been defined. A short overview of the Celitement process and the challenging tasks of the online measurement and evaluation of the product quality will be presented. Subsequently, methods for systematic development of near-infrared calibration models and the determination of the final calibration model will be introduced. The application of the model on experimental data illustrates that NIR-spectroscopy allows for a quick and sufficiently exact determination of crucial process parameters.

Keywords: calibration model, celitement, cementitious material, NIR spectroscopy

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Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

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Authors: Jolanta Jonak, Sylvia Tolczyk

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Students demonstrate various learning preferences and learning styles that range from visual, auditory to kinesthetic preferences. These learning preferences are further impacted by individual cognitive make up that characterizes itself in linguistic strengths, logical- special, inter-or intra- personal, just to name a few. Students from culturally and linguistically diverse backgrounds (CLD) have an increased risk of being misunderstood by many school systems and even medical personnel. CLD students are influenced by many factors (like acculturation and experience) that may impact their achievements and functioning levels. CLD students who develop initial or basic interpersonal communication proficiency skills in the target language are even at a higher risk for being suspected of learning disability when they are underachieving academically. Research indicates that large numbers of students arenot provided the type of education and types of supports they need in order to be successful in an academicenvironment. Multiple research findings indicate that significant numbers of school staff self-reports that they do not feel adequately prepared to work with CLD students. It is extremely important for the school staff, especially school psychologists, who often are the first experts that are consulted, to be educated about overlapping symptoms and settle differences between learning difference and disability. It is equally important for medical personnel, mainly pediatricians, psychologists, and psychiatrists, to understand the subtle differences to avoid inaccurate opinions. Having the knowledge, school staff can avoid unnecessary referrals for special education evaluations and avoid inaccurate decisions about the presence of a disability. This presentation will illustrate distinctions based on research between learning differences and disabilities, how to recognize them, and how to assess for them.

Keywords: special education, learning disability, differentiation, differences

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Authors: Amir Hossein Allahdadi

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The mystical and intuitive look of Islamic artists inspired by the Koranic and mystical principles and also based on the geometry and mathematics has left unique works whose range extends across the borders of Islam. The relationship between Islamic art and music in the traditional art is of one of the concepts that can be traced back to the other arts by detection of its components. One of the links is the art of painting whose subtleties that can be applicable to both architecture and music. So, architecture and music links can be traced in other arts with a traditional foundation in order to evaluate the equivalents of traditional arts. What is the relationship between physical space of architecture and nonphysical space of music? What is musical architecture? What is the music that tends to architecture? These questions are very small samples of the questions that arise in this category, and these questions and concerns remain as long as the music is played and the architecture is made. Efforts have been made in this area, references compiled and plans drawn. As an example, we can refer to views of ‘Mansour Falamaki’ in the book of architecture and music, as well as the book transition from mud to heart by ‘Hesamodin Seraj’. The method is such that a certain melody is given to an architect and it is tried to design a specified architecture using a certain theme. This study is not to follow the architecture of a particular type of music and the formation of a volume based on a sound. In this opportunity, it is tried to briefly review the relationship between music and architecture in the Iranian original and traditional arts, using the basic definitions of arts. The musician plays, the architect designs, the actor forms his desired space and painter displays his multi-dimensional world in the form of two-dimensions. The expression language is different, but all of them can be gathered in a form, a form which has no clear boundaries. In fact, in any original art, the artist applies his art as a tool to express his insights which are nothing but achieving the world beyond this place and time.

Keywords: architecture, music, geometric proportions, mathematical proportions

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Authors: Elnaz Lalezari, Ramin Ghasemi Shaya

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The birth way is influenced by a fracture within the quiet care handle, making a brokenness of this final one. The pregnant lady has got to interface with numerous experts, both amid the pregnancy, the childbirth, and the puerperium. Be that as it may, amid the final ten a long time, there has been an expanding of the pregnancy care worked by the midwife, who is considered to be the administrator with the correct competences, who can beware of each pregnancy and may profit herself of other professionals' commitments in arrange to make strides the results of maternal and neonatal health. To confirm whether there are proofs of viability that bolster the caseload birthing assistance care show, and in case it is conceivable to apply this show within the birth way in Italy. A amendment of writing has been done utilizing a few look motor (Google, Bing) and particular databases (MEDLINE, CINAHL, Embase, Domestic - ClinicalTrials.gov). There has, too, been a discussion of the Italian directions, the national rules, and the proposals of WHO. Results: The look string, legitimately adjusted to the three databases, has given the taking after comes about: MEDLINE 64 articles, CINAHL 94 articles, Embase 88 articles. From this choice, 14 articles have been extricated: 1 orderly survey, 3 controlled arbitrary trial, 7 observational ponders, 3 subjective studies. The caseload maternity care appears to be an successful and dependable organisational/caring strategy. It reacts to the criterions of quality and security, to the requirements of ladies not as it were amid the pregnancy but moreover amid the post-partum stage. For these reasons, it appears exceptionally valuable also for the birth way within the Italian reality.

Keywords: midwifery, care, caseload, maternity

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Authors: Nuo Duan, Yi Pik Cheng

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This paper presents the data of a series of two-dimensional Discrete Element Method (DEM) simulations of a large-diameter rigid monopile subjected to cyclic loading under a high gravitational force. At present, monopile foundations are widely used to support the tall and heavy wind turbines, which are also subjected to significant from wind and wave actions. A safe design must address issues such as rotations and changes in soil stiffness subject to these loadings conditions. Design guidance on the issue is limited, so are the availability of laboratory and field test data. The interpretation of these results in sand, such as the relation between loading and displacement, relies mainly on empirical correlations to pile properties. Regarding numerical models, most data from Finite Element Method (FEM) can be found. They are not comprehensive, and most of the FEM results are sensitive to input parameters. The micro scale behaviour could change the mechanism of the soil-structure interaction. A DEM model was used in this paper to study the cyclic lateral loads behaviour. A non-dimensional framework is presented and applied to interpret the simulation results. The DEM data compares well with various set of published experimental centrifuge model test data in terms of lateral deflection. The accumulated permanent pile lateral displacements induced by the cyclic lateral loads were found to be dependent on the characteristics of the applied cyclic load, such as the extent of the loading magnitudes and directions.

Keywords: cyclic loading, DEM, numerical modelling, sands

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Authors: Achim Washington, Reece Clothier, Jose Silva

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System Safety Regulations (SSR) are a central component to the airworthiness certification of Unmanned Aircraft Systems (UAS). There is significant debate on the setting of appropriate SSR for UAS. Putting this debate aside, the challenge lies in how to apply the system safety process to UAS, which lacks the data and operational heritage of conventionally piloted aircraft. The limited knowledge and lack of operational data result in uncertainty in the system safety assessment of UAS. This uncertainty can lead to incorrect compliance findings and the potential certification and operation of UAS that do not meet minimum safety performance requirements. The existing system safety assessment and compliance processes, as used for conventional piloted aviation, do not adequately account for the uncertainty, limiting the suitability of its application to UAS. This paper discusses the challenges of undertaking system safety assessments for UAS and presents current and envisaged research towards addressing these challenges. It aims to highlight the main advantages associated with adopting a risk based framework to the System Safety Performance Requirement (SSPR) compliance process that is capable of taking the uncertainty associated with each of the outputs of the system safety assessment process into consideration. Based on this study, it is made clear that developing a framework tailored to UAS, would allow for a more rational, transparent and systematic approach to decision making. This would reduce the need for conservative assumptions and take the risk posed by each UAS into consideration while determining its state of compliance to the SSR.

Keywords: Part 1309 regulations, risk models, uncertainty, unmanned aircraft systems

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Authors: Lakhoua Najeh

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Aims of the work: After a presentation of the functionality of an example of a mechatronic system which is a paint mixer system, we present the concepts of modeling and safe operation. This paper briefly discusses how to model and protect the functioning of a mechatronic system relying mainly on functional analysis and safe operation techniques. Methods: For the study of an example of a mechatronic system, we use methods for external functional analysis that illustrate the relationships between a mechatronic system and its external environment. Thus, we present the Safe-Structured Analysis Design Technique method (Safe-SADT) which allows the representation of a mechatronic system. A model of operating safety and automation is proposed. This model enables us to use a functional analysis technique of the mechatronic system based on the GRAFCET (Graphe Fonctionnel de Commande des Etapes et Transitions: Step Transition Function Chart) method; study of the safe operation of the mechatronic system based on the Safe-SADT method; automation of the mechatronic system based on a software tool. Results: The expected results are to propose a model and safe operation of a mechatronic system. This methodology enables us to analyze the relevance of the different models based on Safe-SADT and GRAFCET in relation to the control and monitoring functions and to study the means allowing exploiting their synergy. Conclusion: In order to propose a general model of a mechatronic system, a model of analysis, safety operation and automation of a mechatronic system has been developed. This is how we propose to validate this methodology through a case study of a paint mixer system.

Keywords: mechatronic systems, system modeling, safe operation, Safe-SADT

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Authors: Ophir Nave

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In our research, we present the concept of singularly perturbed vector field (SPVF) method, and its application to thermal explosion of diesel spray combustion. Given a system of governing equations, which consist of hidden Multi-scale variables, the SPVF method transfer and decompose such system to fast and slow singularly perturbed subsystems (SPS). The SPVF method enables us to understand the complex system, and simplify the calculations. Later powerful analytical, numerical and asymptotic methods (e.g method of integral (invariant) manifold (MIM), the homotopy analysis method (HAM) etc.) can be applied to each subsystem. We compare the results obtained by the methods of integral invariant manifold and SPVF apply to spray droplets combustion model. The research deals with the development of an innovative method for extracting fast and slow variables in physical mathematical models. The method that we developed called singular perturbed vector field. This method based on a numerical algorithm applied to global quasi linearization applied to given physical model. The SPVF method applied successfully to combustion processes. Our results were compared to experimentally results. The SPVF is a general numerical and asymptotical method that reveals the hierarchy (multi-scale system) of a given system.

Keywords: polydisperse spray, model reduction, asymptotic analysis, multi-scale systems

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Authors: Gaya Bin Noon, Thoko Hanjahanja-Phiri, Laura Xavier Fadrique, Plinio Pelegrini Morita, Hélène Vaillancourt, Jennifer Teague, Tania Donovska

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Active Assisted Living (AAL) refers to systems designed to improve the quality of life, aid in independence, and create healthier lifestyles for care recipients. As the population ages, there is a pressing need for non-intrusive, continuous, adaptable, and reliable health monitoring tools to support aging in place. AAL has great potential to support these efforts with the wide variety of solutions currently available, but insufficient efforts have been made to address concerns arising from the integration of AAL into care. The purpose of this research was to (1) explore the integration of AAL technologies and data into the clinical pathway, and (2) map data access and governance for AAL technology in order to develop standards for use by policy-makers, technology manufacturers, and developers of smart communities for seniors. This was done through four successive research phases: (1) literature search to explore existing work in this area and identify lessons learned; (2) modeling of the continuum of care; (3) adapting a framework for data governance into the AAL context; and (4) interviews with stakeholders to explore the applicability of previous work. Opportunities for standards found in these research phases included a need for greater consistency in language and technology requirements, better role definition regarding who can access and who is responsible for taking action based on the gathered data, and understanding of the privacy-utility tradeoff inherent in using AAL technologies in care settings.

Keywords: active assisted living, aging in place, internet of things, standards

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Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Assigning aircrafts’ activities to appropriate gates is one the most challenging issues in airport authorities’ multiple criteria decision making. The potential financial loss due to imbalances of demand and supply in congested airports, higher occupation rates of gates, and the existing restrictions to expand facilities provide further evidence for the need for an optimal supply allocation. Passengers walking distance, towing movements, extra fuel consumption (as a result of awaiting longer to taxi when taxi conflicts happen at the apron area), etc. are the major traditional components involved in GAP models. In particular, the total cost associated with gate assignment problem highly depends on the airport terminal layout. The study herein presents a well-elaborated literature review on the topic focusing on major concerns, applicable variables and objectives, as well as proposing a three-objective mathematical model for the gate assignment problem. The model has been tested under different concourse layouts in order to check its performance in different scenarios. Results revealed that terminal layout pattern is a significant parameter in airport and that the proposed model is capable of dealing with key constraints and objectives, which supports its practical usability for future decision making tools. Potential solution techniques were also suggested in this study for future works.

Keywords: airport management, terminal layout, gate assignment problem, mathematical modeling

Procedia PDF Downloads 191