Search results for: pre-trained language models

Authors: J. O. Idoko, C. N. Michael, T. O. Fasuan

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This study investigated the effects of cooking time, seed-to-water ratio and soaking time on proximate and functional properties of African walnut seed using Box-Behnken design and Response Surface Methodology (BBD-RSM) with a view to increase its utilization in the food industry. African walnut seeds were sorted washed, soaked, cooked, dehulled, sliced, dried and milled. Proximate analysis and functional properties of the samples were evaluated using standard procedures. Data obtained were analyzed using descriptive and inferential statistics. Quadratic models were obtained to predict the proximate and functional qualities as a function of cooking time, seed-to-water ratio and soaking time. The results showed that the crude protein ranged between 11.80% and 23.50%, moisture content ranged between 1.00% and 4.66%, ash content ranged between 3.35% and 5.25%, crude fibre ranged from 0.10% to 7.25% and carbohydrate ranged from 1.22% to 29.35%. The functional properties showed that soluble protein ranged from 16.26% to 42.96%, viscosity ranged from 23.43 mPas to 57 mPas, emulsifying capacity ranged from 17.14% to 39.43% and water absorption capacity ranged from 232% to 297%. An increase in the volume of water used during cooking resulted in loss of water soluble protein through leaching, the length of soaking time and the moisture content of the dried product are inversely related, ash content is inversely related to the cooking time and amount of water used, extraction of fat is enhanced by increase in soaking time while increase in cooking and soaking times result into decrease in fibre content. The results obtained indicated that African walnut could be used in several food formulations as protein supplement and binder.

Keywords: African walnut, functional properties, proximate analysis, response surface methodology

Procedia PDF Downloads 396

Authors: Nguyen Quynh Trang, Nguyễn Thị Hông Nhung

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The study aimed to identify the effectiveness of using the mind map technique to enhance students’ medical vocabulary retention among a group of students at a higher education institution - Thai Nguyen University of Medicine and Pharmacy during the first semester of the school year 2022-2023. The research employed a quasi-experimental method, exploring primary sources such as questionnaires and the analyzed results of pre-and-post tests. Almost teachers and students showed high preferences for the implementation of the mind map technique in language teaching and learning. Furthermore, results from the pre-and-post tests between the experimental group and control one pointed out that this technique brought back positive academic performance in teaching and learning English. The research findings revealed that there should be more supportive policies to evoke the use of the mind map technique in a pedagogical context. Aim of the Study: The purpose of this research was to investigate whether using mind mapping can help students to enhance nursing students’ medical vocabulary retention and to assess the students’ attitudes toward using mind mapping as a tool to improve their vocabulary. The methodology of the study: The research employed a quasi-experimental method, exploring primary sources such as questionnaires and the analyzed results of pre-and-post tests. The contribution of the study: The research contributed to the innovation of teaching vocabulary methods for English teachers at a higher education institution. Moreover, the research helped the English teachers and the administrators at a university evoke and maintain the motivation of students not only in English classes but also in other subjects. The findings of this research were beneficial to teachers, students, and researchers interested in using mind mapping to teach and learn English vocabulary. The research explored and proved the effectiveness of applying mind mapping in teaching and learning English vocabulary. Therefore, teaching and learning activities were conducted more and more effectively and helped students overcome challenges in remembering vocabulary and creating motivation to learn English vocabulary.

Keywords: medical vocabulary retention, mind map technique, nursing students, medical vocabulary

Procedia PDF Downloads 76

Authors: Rai Sachindra Prasad

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Thought is physical force. This has been well recognized but hardly translated visually or otherwise in the sense of its transfer from one individual to another. In the present world of chaos and disorder with yawning gaps between right and wrong thinking individuals, if it is possible to transfer the right thoughts to replace the wrong ones it would indeed be a great achievement in the present situation of the world which is torn with violence with dangerous thoughts of individuals. Moreover, such a possibility would completely remove the barrier of language between two persons, which at times proves to be a great obstacle in realizing a desired purpose. If a proper instrumentation scheme containing appropriate transducers and electronics is designed and implemented to realize this thought ransfer phenomenon, this would prove to be extremely useful when properly used. Considering the advancements already made in recording the nerve impulses in the brain, which are electrical events of very short durations that move along the axon, it is conceivable that this may be used to good effect in implementing the scheme. In such a proposition one shoud consider the roles played by pineal body, pituitary gland and ‘association’ areas. Pioneer students of brain have thought that associations or connections between sensory input and motor output were made in these areas. It is currently believed that rather than being regions of simple sensory-motor connections, the association areas process and integrate sensory information relayed to them from the primary sensory areas of the cortex and from the thalamus, after the information has been processed, it may be sent to motor areas to be acted upon. Again, even though the role played by pineal body is not known fully to neurologists its interconnection with pituitary gland is a matter of great significance to the ‘Rishis’ and; Seers’ s described in Vedas and Puranas- the ancient Holy books of Hindus. If the pineal body is activated through meditation it would control the pituitary gland thereby the individual’s thoughts and acts. Thus, if thoughts can be picked up by special transducers, these can be connected to suitable electronics circuitry to amplify the signals. These signals in the form of electromagnetic waves can then be transmitted using modems for long distance transmission and eventually received by or passed on to a subject of interest through another set of electronics circuit and devices.

Keywords: modems, pituitary gland, pineal body, thought transfer

Procedia PDF Downloads 372

Authors: Smart E. Amanfo

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Although the exact functional relationship between energy consumption and economic growth and development remains a complex social science, there is a sustained growing of agreement among energy economists and the likes on direct or indirect role of energy use in the development process, and as sustenance for many of societal achieved socio-economic and environmental developments in any economy. According to OECD, the world economy will double by 2050 in which the two members of BRICS (Brazil, Russia, India, China and South Africa) countries: China and India lead. There is a global apprehension that if countries constituting the epicenter of the present and future economic growth follow the same trajectory as during and after Industrial Revolution, involving higher energy throughputs, especially fossil fuels, the already known and models predicted threats of climate change and global warming could be exacerbated, especially in the developing economies. The international community’s challenge is how to address the trilemma of economic growth, social development, poverty eradication and stability of the ecological systems. This paper aims at providing the estimates of economic growth, energy consumption, and carbon dioxide emissions using BRICS members’ panel data from 1980 to 2017. The preliminary results based on fixed effect econometric model show positive significant relationship between energy consumption and economic growth. The paper further identified a strong relationship between economic growth and CO2 emissions which suggests that the global agenda of low-carbon-led growth and development is not a straight forward achievable The study therefore highlights the need for BRICS member states to intensify low-emissions-based production and consumption policies, increase renewables in order to avoid further deterioration of climate change impacts.

Keywords: BRICS, sustainability, sustainable development, energy consumption, economic growth

Procedia PDF Downloads 95

Authors: Mandeep Saini

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The rapid advancement of Artificial Intelligence (AI) is transforming various fields, including intellectual property law. This paper explores the emerging role of AI in interpreting patent claims, a critical and highly specialized area within intellectual property rights. Patent claims define the scope of legal protection granted to an invention, and their precise interpretation is crucial in determining the boundaries of the patent holder's rights. Traditionally, this interpretation has relied heavily on the expertise of patent examiners, legal professionals, and judges. However, the increasing complexity of modern inventions, especially in fields like biotechnology, software, and electronics, poses significant challenges to human interpretation. Introducing AI into patent claim interpretation raises several legal and ethical concerns. This paper addresses critical issues such as the reliability of AI-driven interpretations, the potential for algorithmic bias, and the lack of transparency in AI decision-making processes. It considers the legal implications of relying on AI, particularly regarding accountability for errors and the potential challenges to AI interpretations in court. The paper includes a comparative study of AI-driven patent claim interpretations versus human interpretations across different jurisdictions to provide a comprehensive analysis. This comparison highlights the variations in legal standards and practices, offering insights into how AI could impact the harmonization of international patent laws. The paper proposes policy recommendations for the responsible use of AI in patent law. It suggests legal frameworks that ensure AI tools complement, rather than replace, human expertise in patent claim interpretation. These recommendations aim to balance the benefits of AI with the need for maintaining trust, transparency, and fairness in the legal process. By addressing these critical issues, this research contributes to the ongoing discourse on integrating AI into the legal field, specifically within intellectual property rights. It provides a forward-looking perspective on how AI could reshape patent law, offering both opportunities for innovation and challenges that must be carefully managed to protect the integrity of the legal system.

Keywords: artificial intelligence (ai), patent claim interpretation, intellectual property rights, algorithmic bias, natural language processing, patent law harmonization, legal ethics

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio

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We develop a data-driven agent based model (ABM) for the Italian economy. We calibrate the model for the initial condition and parameters. As a preliminary step, we replicate the Monte-Carlo simulation for the Austrian economy. Then, we evaluate the dynamic properties of the model: the long-run equilibrium and the allocative efficiency in terms of disequilibrium patterns arising in the search and matching process for final goods, capital, intermediate goods, and credit markets. In this perspective, we use a randomized initial condition approach. We perform a robustness analysis perturbing the system for different parameter setups. We explore the empirical properties of the model using a rolling window forecast exercise from 2010 to 2022 to observe the model’s forecasting ability in the wake of the COVID-19 pandemic. We perform an analysis of the properties of the model with a different number of agents, that is, with different scales of the model compared to the real economy. The model generally displays transient dynamics that properly fit macroeconomic data regarding forecasting ability. We stress the model with a large set of shocks, namely interest policy, fiscal policy, and exogenous factors, such as external foreign demand for export. In this way, we can explore the most exposed sectors of the economy. Finally, we modify the technology mix of the various sectors and, consequently, the underlying input-output sectoral interdependence to stress the economy and observe the long-run projections. In this way, we can include in the model the generation of endogenous crisis due to the implied structural change, technological unemployment, and potential lack of aggregate demand creating the condition for cyclical endogenous crises reproduced in this artificial economy.

Keywords: agent-based models, behavioral macro, macroeconomic forecasting, micro data

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Authors: Kazuki Kamada, Haruka Yamashita

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In Japan, taxi is one of the popular transportations and taxi industry is one of the big businesses. However, in recent years, there has been a difficult problem of reducing the number of taxi drivers. In the taxi business, mainly three passenger catching methods are applied. One style is "cruising" that drivers catches passengers while driving on a road. Second is "waiting" that waits passengers near by the places with many requirements for taxies such as entrances of hospitals, train stations. The third one is "dispatching" that is allocated based on the contact from the taxi company. Above all, the cruising taxi drivers need the experience and intuition for finding passengers, and it is difficult to decide "the destination for cruising". The strong recommendation system for the cruising taxies supports the new drivers to find passengers, and it can be the solution for the decreasing the number of drivers in the taxi industry. In this research, we propose a method of recommending a destination for cruising taxi drivers. On the other hand, as a machine learning technique, the embedding models that embed the high dimensional data to a low dimensional space is widely used for the data analysis, in order to represent the relationship of the meaning between the data clearly. Taxi drivers have their favorite courses based on their experiences, and the courses are different for each driver. We assume that the course of cruising taxies has meaning such as the course for finding business man passengers (go around the business area of the city of go to main stations) and course for finding traveler passengers (go around the sightseeing places or big hotels), and extract the meaning of their destinations. We analyze the cruising history data of taxis based on the embedding model and propose the recommendation system for passengers. Finally, we demonstrate the recommendation of destinations for cruising taxi drivers based on the real-world data analysis using proposing method.

Keywords: taxi industry, decision making, recommendation system, embedding model

Procedia PDF Downloads 138

Authors: Felix Eyben, Simon Schaffrath, Markus Feldmann

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A building should maximize the potential for use through its design. Therefore, flexible use is always important when designing a steel structure. To create flexibility, steel beams with web openings are increasingly used, because these offer the advantage that cables, pipes and other technical equipment can easily be routed through without detours, allowing for more space-saving and aesthetically pleasing construction. This can also significantly reduce the height of ceiling systems. Until now, beams with web openings were not explicitly considered in the European standard. However, this is to be done with the new EN 1993-1-13, in which design rules for different opening forms are defined. In order to further develop the design concepts, beams with web openings under bending are therefore to be investigated in terms of damage mechanics as part of a German national research project aiming to optimize the verifications for steel structures based on a wider database and a validated damage prediction. For this purpose, first, fundamental factors influencing the load-bearing behavior of girders with web openings under bending load were investigated numerically without taking material damage into account. Various parameter studies were carried out for this purpose. For example, the factors under study were the opening shape, size and position as well as structural aspects as the span length, arrangement of stiffeners and loading situation. The load-bearing behavior is evaluated using resulting load-deformation curves. These results are compared with the design rules and critically analyzed. Experimental tests are also planned based on these results. Moreover, the implementation of damage mechanics in the form of the modified Bai-Wierzbicki model was examined. After the experimental tests will have been carried out, the numerical models are validated and further influencing factors will be investigated on the basis of parametric studies.

Keywords: damage mechanics, finite element, steel structures, web openings

Procedia PDF Downloads 174

Authors: Rony Reátegui, Cesar Chácara, Benjamin Castañeda, Rafael Aguilar

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Nowadays, heritage building information modeling (HBIM) is considered an efficient tool to represent and manage information of cultural heritage (CH). The basis of this tool relies on a 3D model generally obtained from a cloud-to-BIM procedure. There are different methods to create an HBIM model that goes from manual modeling based on the point cloud to the automatic detection of shapes and the creation of objects. The selection of these methods depends on the desired level of development (LOD), level of information (LOI), grade of generation (GOG), as well as on the availability of commercial software. This paper presents the 3D modeling of a stone masonry chapel using Recap Pro, Revit, and Dynamo interface following a three-step methodology. The first step consists of the manual modeling of simple structural (e.g., regular walls, columns, floors, wall openings, etc.) and architectural (e.g., cornices, moldings, and other minor details) elements using the point cloud as reference. Then, Dynamo is used for generative modeling of complex structural elements such as vaults, infills, and domes. Finally, semantic information (e.g., materials, typology, state of conservation, etc.) and pathologies are added within the HBIM model as text parameters and generic models families, respectively. The application of this methodology allows the documentation of CH following a relatively simple to apply process that ensures adequate LOD, LOI, and GOG levels. In addition, the easy implementation of the method as well as the fact of using only one BIM software with its respective plugin for the scan-to-BIM modeling process means that this methodology can be adopted by a larger number of users with intermediate knowledge and limited resources since the BIM software used has a free student license.

Keywords: cloud-to-BIM, cultural heritage, generative modeling, HBIM, parametric modeling, Revit

Procedia PDF Downloads 144

Authors: Elvis Munyoka

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While the number of African refugees settling in Australia has significantly increased since the mid-1990s, the marginalisation and exclusion of young people from refugee backgrounds in employment remain a critical challenge. Unemployment or underemployment can negatively impact refugees in multiple areas, such as income, housing, life satisfaction, and social status. Higher rates of unemployment among refugees are linked in part to the intersection of pre-migration and daily challenges like trauma, racism, gender identity, and English language competency, all of which generate multiple employability disadvantages. However, the intersection of gender, race, social class, and age in impacting African refugee youth’s access to employment has received less attention. Using a qualitative case study approach, the presentation will explore how gender, race, social class, and age influence African refugee youth graduates’ access to employment in South Australia. The intersectionality theory and capability approach to social justice is used to explore intersecting factors impacting African refugee youth’s access to employment in South Australia. Participants were 16 African refugee graduates aged 18-30 living in South Australia who took part in the study for one year. Based on the trends in the data, the results suggest that long-term unemployment and underemployment, coupled with ongoing racism and marginalisation, have the potential to make refugees more vulnerable to several mental disorders such as depression, hopelessness, and suicidal thoughts. The analysis also reveals that resettlement challenges may limit refugees’ ability to recover from pre-migration trauma. The impact of resettlement challenges on refugee mental health highlights the need for comprehensive policy interventions to address the barriers refugees face in finding employment in resettlement communities. With African refugees constituting such an important part of Australian society, they should have equal access to meaningful employment, as decent work promotes good mental health, successful resettlement, hope, and self-sufficiency.

Keywords: African refugees, employment, mental health, Australia, underemployment

Procedia PDF Downloads 102

Authors: Panagiotis Platanitis

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Purpose: This research paper seeks to review the empirical studies in the field of expatriate adjustment in East Asia in order to produce a thematic understanding of the current adjustment challenges, thus enabling practitioners to enrich their knowledge. Background: Learning to live, work, and function in a country and culture vastly different from that of one’s upbringing can pose some unique challenges in terms of adaptation and adjustment. This has led to a growing body of research about the adjustment of expatriate workers. Adjustment itself has been posited as a three-dimensional construct; work adjustment, interaction adjustment and general or cultural adjustment. Methodology: This qualitative systematic review has been conducted on all identified peer-reviewed empirical studies related to expatriate adjustment in East Asia. Five electronic databases (PsychInfo, Emerald, Scopus, EBSCO and JSTOR) were searched to December 2015. Out of 625 identified records, thorough evaluation for eligibility resulted in 15 relevant studies being subjected to data analysis. The quality of the identified research was assessed according to the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields. The data were analysed by means of thematic synthesis for systematic reviews of qualitative research. Findings: Data analysis revealed five key themes. The themes developed were: (1) personality traits (2) types of adjustment, (3) language, (4) culture and (5) coping strategies. Types of adjustment included subthemes such as: Interaction, general, work, psychological, sociocultural and cross-cultural adjustment. Conclusion: The present review supported previous literature on the different themes of adjustment and it takes the focus from work and general adjustment to the psychological challenges and it introduces the psychological adjustment. It also gives a different perspective about the use of cross-cultural training and the coping strategies expatriates use when they are abroad. This review helps counselling psychologists to understand the importance of a multicultural approach when working with expatriates and also to be aware of what expatriates might face when working and living in East Asia.

Keywords: adjustment, counselling psychology, East Asia, expatriates

Procedia PDF Downloads 266

Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

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Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

Procedia PDF Downloads 142

Authors: Bahareh Yousefian, Laurel Smith Stvan

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Linguistic structures have two facades: form and meaning. These structures could have either literal meaning or figurative meaning (although it could also depend on the context in which that structure appears). The literal meaning is understandable more easily, but for the figurative meaning, a word or concept is understood from a different word or concept. In linguistic structures with a figurative meaning, it’s more difficult to relate their forms to the meanings than structures with literal meaning. In these cases, the relationship between form and figurative meaning could be studied from different perspectives. Various linguists have been curious about what happens in someone’s mind to understand figurative meaning through the forms; they have used different perspectives and theories to explain this process. It has been studied through cognitive linguistics as well, in which mind and mental activities are really important. In this viewpoint, meaning (in other words, conceptualization) is considered a mental process. In this descriptive-analytic study, 20 Persian compound nouns with figurative meanings have been collected from the Persian-language Moeen Encyclopedic Dictionary and other sources. Examples include [“Sofreh Xaneh”] (traditional restaurant) and [“Dast Yar”] (Assistant). These were studied in a cognitive semantics framework using “Conceptual Blending Theory” which hasn’t been tested on Persian compound nouns before. It was noted that “Conceptual Blending Theory” could lead to the process of understanding the figurative meanings of Persian compound nouns. Many cognitive linguists believe that “Conceptual Blending” is not only a linguistic theory but it’s also a basic human cognitive ability that plays important roles in thought, imagination, and even everyday life as well (though unconsciously). The ability to use mental spaces and conceptual blending (which is exclusive to humankind) is such a basic but unconscious ability that we are unaware of its existence and importance. What differentiates Conceptual Blending Theory from other ways of understanding figurative meaning, are arising new semantic aspects (emergent structure) that lead to a more comprehensive and precise meaning. In this study, it was found that Conceptual Blending Theory could explain reaching the figurative meanings of Persian compound nouns from their forms, such as [talkative for compound word of “Bolbol + Zabani” (nightingale + tongue)] and [wage for compound word of “Dast + Ranj” (hand + suffering)].

Keywords: cognitive linguistics, conceptual blending, figurative meaning, Persian compound nouns

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Authors: J. H. Park, R. H. Hwang, K. B. Yi

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Carbon Capture and Storage (CCS) is one of the important technology to reduce the CO₂ emission from large stationary sources such as a power plant. Among the carbon technologies for power plants, chemical looping combustion (CLC) has attracted much attention due to a higher thermal efficiency and a lower cost of electricity. A CLC process is consists of a fuel reactor and an air reactor which are interconnected fluidized bed reactor. In the fuel reactor, an oxygen carrier (OC) is reduced by fuel gas such as CH₄, H₂, CO. And the OC is send to air reactor and oxidized by air or O₂ gas. The oxidation and reduction reaction of OC occurs between the two reactors repeatedly. In the CLC system, high concentration of CO₂ can be easily obtained by steam condensation only from the fuel reactor. It is very important to understand the oxidation and reduction characteristics of oxygen carrier in the CLC system to determine the solids circulation rate between the air and fuel reactors, and the amount of solid bed materials. In this study, we have conducted the experiment and interpreted oxidation and reduction reaction characteristics via observing weight change of Ni-based oxygen carrier using the TGA with varying as concentration and temperature. Characterizations of the oxygen carrier were carried out with BET, SEM. The reaction rate increased with increasing the temperature and increasing the inlet gas concentration. We also compared experimental results and adapted basic reaction kinetic model (JMA model). JAM model is one of the nucleation and nuclei growth models, and this model can explain the delay time at the early part of reaction. As a result, the model data and experimental data agree over the arranged conversion and time with overall variance (R²) greater than 98%. Also, we calculated activation energy, pre-exponential factor, and reaction order through the Arrhenius plot and compared with previous Ni-based oxygen carriers.

Keywords: chemical looping combustion, kinetic, nickel-based, oxygen carrier, spray drying method

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Authors: Fatmah Almathkour

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Managing and controlling the construction supply chain (CSC) are very important components of effective construction project execution. The goals of managing the CSC are to reduce uncertainty and optimize the performance of a construction project by improving efficiency and reducing project costs. The heart of much SC activity is addressing risk, and the CSC is no different. The delivery and consumption of construction materials is highly variable due to the complexity of construction operations, rapidly changing demand for certain components, lead time variability from suppliers, transportation time variability, and disruptions at the job site. Current notions of managing and controlling CSC, involve focusing on one project at a time with a push-based material ordering system based on the initial construction schedule and, then, holding a tremendous amount of inventory. A two-stage methodology was proposed to coordinate the feed-forward control of advanced order placement with a supplier to a feedback local control in the form of adding the ability to transship materials between projects to improve efficiency and reduce costs. It focused on the single supplier integrated production and transshipment problem with multiple products. The methodology is used as a design tool for the CSC because it includes an external storage site not associated with one of the projects. The idea is to add this feature to a highly constrained environment to explore its effectiveness in buffering the impact of variability and maintaining project schedule at low cost. The methodology uses deterministic optimization models with objectives that minimizing the total cost of the CSC. To illustrate how this methodology can be used in practice and the types of information that can be gleaned, it is tested on a number of cases based on the real example of multiple construction projects in Kuwait.

Keywords: construction supply chain, inventory control supply chain, transshipment

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Authors: Wenli Tsou, Jessica Wu

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Courses of English for specific academic purposes (ESAP) have become popular for higher education in Taiwan; however, no standardized tests have been developed for evaluating learners’ English proficiency in individual designated fields. Assuming a learner’s proficiency in a specific academic area is built up with one’s general proficiency in English with specific knowledge and vocabulary in the content areas, an adequate ESAP proficiency test may be constructed by some selected test items related to the designated academic areas. In this study, through collaboration between a language testing institution and a university in Taiwan, three sets of ESAP tests, covering three disciplinary areas of business and the workplace, science and engineering, and health and medicine majors, were developed and administered to sophomore students (N=1704) who were enrolled in ESAP courses at a university in southern Taiwan. For this study, the courses were grouped into the above-mentioned three disciplines, and students took the specialized proficiency test based on the ESAP course they were taking. Because students were free to select which ESAP course to take, each course had both major and non-major students. Toward the end of the one-semester course, ending in January, 2015, each student took two tests, one of general English (General English Proficiency Test, or GEPT) and the other ESAP. Following each test, students filled out a survey, reporting their test taking experiences. After comparing students’ two test scores, it was found that business majors and health and medical students performed better in ESAP than the non-majors in the class, whereas science and engineering majors did about the same as their non-major counterparts. In addition, test takers with CERF B2 (upper intermediate) level or above performed well in both tests, while students who are below B2 did slightly better in ESAP. The findings suggest that students’ test performance have been enhanced by their specialist content and vocabulary knowledge. Furthermore, results of the survey show that the difficulty levels reported by students are consistent with their test performances. Based on the item analysis, the findings can be used to develop proficiency tests for specific disciplines and to identify ability indicators for college students in their designated fields.

Keywords: english for specific academic purposes (ESAP), general english proficiency test (GEPT), higher education, proficiency test

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

Procedia PDF Downloads 297

Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: dynamic modeling, missing data, mobility, multiple imputation

Procedia PDF Downloads 164

Authors: Elvis Munyoka

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While the number of African refugees settling in Australia has significantly increased since the mid-1990s, the marginalisation and exclusion of young people from refugee backgrounds in employment remain a critical challenge. Unemployment or underemployment can negatively impact refugees in multiple areas, such as income, housing, life satisfaction, and social status. Higher rates of unemployment among refugees are linked in part to the intersection of pre-migration and daily challenges like trauma, racism, gender identity, and English language competency, all of which generate multiple employability disadvantages. However, the intersection of gender, race, social class, and age in impacting African refugee youth’s access to employment has received less attention. Using a qualitative case study approach, the paper will explore how gender, race, social class, and age influence African refugee youth graduates’ access to employment in South Australia. The intersectionality theory and capability approach to social justice is used to explore intersecting factors impacting African refugee youth’s access to employment in South Australia. Participants were 16 African refugee graduates aged 18-30 living in South Australia who took part in the study for one year. Based on the trends in the data, the results suggest that long-term unemployment and underemployment, coupled with ongoing racism and marginalisation, have the potential to make refugees more vulnerable to several mental disorders such as depression, hopelessness, and suicidal thoughts. The analysis also reveals that resettlement challenges may limit refugees’ ability to recover from pre-migration trauma. The impact of resettlement challenges on refugee mental health highlights the need for comprehensive policy interventions to address the barriers refugees face in finding employment in resettlement communities. With African refugees constituting such an important part of Australian society, they should have equal access to meaningful employment, as decent work promotes good mental health, successful resettlement, hope, and self-sufficiency.

Keywords: African refugee youth, mental health, employment, resettlement, racism

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Authors: Muhd. Barzani Gasim, Mohd. Ekhwan Toriman, Mohd. Khairul Amri Kamarudin, Azman Azid, Siti Humaira Haron, Muhammad Hafiz Md. Saad

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Malaysia is a country in Southeast Asia that constantly exposed to flooding and landslide. The disaster has caused some troubles such loss of property, loss of life and discomfort of people involved. This problem occurs as a result of climate change leading to increased stream flow rate as a result of disruption to regional hydrological cycles. The aim of the study is to determine hydrologic processes in the east coasts of Peninsular Malaysia, especially in Kelantan Basin. Parameterized to account for the spatial and temporal variability of basin characteristics and their responses to climate variability. For hydrological modeling of the basin, the Soil and Water Assessment Tool (SWAT) model such as relief, soil type, and its use, and historical daily time series of climate and river flow rates are studied. The interpretation of Landsat map/land uses will be applied in this study. The combined of SWAT and climate models, the system will be predicted an increase in future scenario climate precipitation, increase in surface runoff, increase in recharge and increase in the total water yield. As a result, this model has successfully developed the basin analysis by demonstrating analyzing hydrographs visually, good estimates of minimum and maximum flows and severe floods observed during calibration and validation periods.

Keywords: east coasts of Peninsular Malaysia, Kelantan river basin, minimum and maximum flows, severe floods, SWAT model

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Authors: Morteza Malek Yarand, Hadi Saebi Monfared

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This study aimed at designing and developing a mechanical force gauge for the square watermelon mold for the first time. It also tried to introduce the square watermelon characteristics and its production limitations. The mechanical force gauge performance and the product itself were also described. There are three main designable gauge models: a. hydraulic gauge, b. strain gauge, and c. mechanical gauge. The advantage of the hydraulic model is that it instantly displays the pressure and thus the force exerted by the melon. However, considering the inability to measure forces at all directions, complicated development, high cost, possible hydraulic fluid leak into the fruit chamber and the possible influence of increased ambient temperature on the fluid pressure, the development of this gauge was overruled. The second choice was to calculate pressure using the direct force a strain gauge. The main advantage of these strain gauges over spring types is their high precision in measurements; but with regard to the lack of conformity of strain gauge working range with water melon growth, calculations were faced with problems. Finally the mechanical pressure gauge has advantages, including the ability to measured forces and pressures on the mold surface during melon growth; the ability to display the peak forces; the ability to produce melon growth graph thanks to its continuous force measurements; the conformity of its manufacturing materials with the required physical conditions of melon growth; high air conditioning capability; the ability to permit sunlight reaches the melon rind (no yellowish skin and quality loss); fast and straightforward calibration; no damages to the product during assembling and disassembling; visual check capability of the product within the mold; applicable to all growth environments (field, greenhouses, etc.); simple process; low costs and so forth.

Keywords: mechanical force gauge, mold, reshaped fruit, square watermelon

Procedia PDF Downloads 273

Authors: Kaisy Xinhong Ye, Su Lin Lim, Jialiang Li, Lei Feng

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background: Multiple healthful dietary patterns have been linked with dementia, but limited studies have looked at the role of diet in cognitive health in Asians whose eating habits are very different from their counterparts in the west. This study aimed to derive a dietary pattern that is associated with the risk of cognitive impairment (CI) in the Singaporean population. Method: The analysis was based on 719 community older adults aged 60 and above. Dietary intake was measured using a validated semi-quantitative food-frequency questionnaire (FFQ). Reduced rank regression (RRR) was used to extract dietary pattern from 45 food groups, specifying sugar, dietary fiber, vitamin A, calcium, and the ratio of polyunsaturated fat to saturated fat intake (P:S ratio) as response variables. The RRR-derived dietary patterns were subsequently investigated using multivariate logistic regression models to look for associations with the risk of CI. Results: A dietary pattern characterized by greater intakes of green leafy vegetables, red-orange vegetables, wholegrains, tofu, nuts, and lower intakes of biscuits, pastries, local sweets, coffee, poultry with skin, sugar added to beverages, malt beverages, roti, butter, and fast food was associated with reduced risk of CI [multivariable-adjusted OR comparing extreme quintiles, 0.29 (95% CI: 0.11, 0.77); P-trend =0.03]. This pattern was positively correlated with P:S ratio, vitamin A, and dietary fiber and negatively correlated with sugar. Conclusion: A dietary pattern providing high P:S ratio, vitamin A and dietary fiber, and a low level of sugar may reduce the risk of cognitive impairment in old age. The findings have significance in guiding local Singaporeans to dementia prevention through food-based dietary approaches.

Keywords: dementia, cognitive impairment, diet, nutrient, elderly

Procedia PDF Downloads 82

Authors: Naz Najma, Grace T. M. Dal Sasso, Maria de Lourdes de Souza

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The development of information and communication technologies and the accessibility of mobile devices has increased the possibilities of the teaching and learning process anywhere and anytime. Mobile and web application allows the production of constructive teaching and learning models in various educational settings, showing the potential for active learning in nursing. The objective of this study was to present the development of an educational technology (Savinglife®, an app) for learning cardiopulmonary resuscitation and advanced cardiovascular life support training. Savinglife® is a technological production, based on the concept of virtual learning and problem-based learning approach. The study was developed from January 2016 to November 2016, using five phases (analyze, design, develop, implement, evaluate) of the instructional systems development process. The technology presented 10 scenarios and 12 simulations, covering different aspects of basic and advanced cardiac life support. The contents can be accessed in a non-linear way leaving the students free to build their knowledge based on their previous experience. Each scenario is presented through interactive tools such as scenario description, assessment, diagnose, intervention and reevaluation. Animated ECG rhythms, text documents, images and videos are provided to support procedural and active learning considering real life situation. Accessible equally on small to large devices with or without an internet connection, Savinglife® offers a dynamic, interactive and flexible tool, placing students at the center of the learning process. Savinglife® can contribute to the student’s learning in the assessment and management of basic and advanced cardiac life support in a safe and ethical way.

Keywords: problem-based learning, cardiopulmonary resuscitation, nursing education, advanced cardiac life support, educational technology

Procedia PDF Downloads 305

Authors: Nesreddine Djafar Henni, Akram Khelaifia, Salah Guettala, Rachid Chebili

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Reinforced concrete shear walls and vertical plate-like elements play a pivotal role in efficiently managing a building's response to seismic forces. This study investigates how the performance of reinforced concrete buildings equipped with shear walls featuring different shear wall-to-frame stiffness ratios aligns with the requirements stipulated in the Algerian seismic code RPA99v2003, particularly in high-seismicity regions. Seven distinct 3D finite element models are developed and evaluated through nonlinear static analysis. Engineering Demand Parameters (EDPs) such as lateral displacement, inter-story drift ratio, shear force, and bending moment along the building height are analyzed. The findings reveal two predominant categories of induced responses: force-based and displacement-based EDPs. Furthermore, as the shear wall-to-frame ratio increases, there is a concurrent increase in force-based EDPs and a decrease in displacement-based ones. Examining the distribution of shear walls from both force and displacement perspectives, model G with the highest stiffness ratio, concentrating stiffness at the building's center, intensifies induced forces. This configuration necessitates additional reinforcements, leading to a conservative design approach. Conversely, model C, with the lowest stiffness ratio, distributes stiffness towards the periphery, resulting in minimized induced shear forces and bending moments, representing an optimal scenario with maximal performance and minimal strength requirements.

Keywords: dual RC buildings, RC shear walls, modeling, static nonlinear pushover analysis, optimization, seismic performance

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Authors: E. Faizan, Wahab Abdul Ghafar, Tao Zhong

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Steel plate shear walls (SPSWs) are a robust lateral load resistance structure because of their high flexibility and efficient energy dissipation when subjected to seismic loads. This research investigates the seismic performance of an innovative infill web strip (IWS-SPSW) and a typical unstiffened steel plate shear wall (USPSW). As a result, two 1:3 scale specimens of an IWS-SPSW and USPSW with a single story and a single bay were built and subjected to a cyclic lateral loading methodology. In the prototype, the beam-to-column connections were accomplished with the assistance of semi-rigid end-plate connectors. IWS-SPSW demonstrated exceptional ductility and shear load-bearing capacity during the testing process, with no cracks or other damage occurring. In addition, the IWS-SPSW could effectively dissipate energy without causing a significant amount of beam-column connection distortion. The shear load-bearing capacity of the USPSW was exceptional. However, it exhibited low ductility, severe infill plate corner ripping, and huge infill web plate cracks. The FE models were created and then confirmed using the experimental data. It has been demonstrated that the infill web strips of an SPSW system can affect the system's high performance and total energy dissipation. In addition, a parametric analysis was carried out to evaluate the material qualities of the IWS, which can considerably improve the system's seismic performances. These properties include the steel's strength as well as its thickness.

Keywords: steel shear walls, seismic performance, failure mode, hysteresis response, nonlinear finite element analysis, parametric study

Procedia PDF Downloads 75

Authors: Nadia Naadu Nartey, Esther A.O.G. Tetteh

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Male negotiator representations and the appreciation of masculine traits in negotiation contexts dominate negotiation research in the field of conflict management and resolution. This study switched focus to pay attention to rarely examined gendered criteria and social contexts in negotiation research by investigating how intuition has been used in negotiations by female leaders toward conflict transformation in Ghanaian social contexts. Using the theoretical lenses of Klein’s Recognition-Primed Decisions (RPD) and Unconscious Information Processing (UIP) models, this study employs narrative inquiry in qualitative research. Semi-structured interviews of five (5) female leaders of Ghanaian social contexts in the United States (US) revealed that the use of intuition is necessary for effective negotiation outcomes due to its primal focus on relationship-building toward transforming conflicts. The knowledge added to the body of research by this study is summed up in the study’s conceptual framework. Female leaders, in negotiation situations where there are conflicting parties, prioritize the greater need for stronger relationships and win-win outcomes. The participant female leaders in negotiation contexts utilize their intuition as a bonding mechanism by effectively timing their actions, using an appropriate communication tone, emphasizing relationship building, and drawing from experience to make sound situational judgments (as in assessing a situation in the RPD model). Female leaders’ use of intuition in negotiations then translates to creating a force that bridges the gap between the conflicting parties. That force is noticed as conflict transformation that manifests as a reduction in anger and a promotion of trust and mutual understanding toward strengthening relationships. Future studies can expand the scope of the findings of this research by conducting a comparative analysis between male and female leaders on their use of intuition in negotiations in Ghanaian contexts.

Keywords: intuition, negotiation, conflict transformation, female leaders, ghanaian social contexts

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Authors: Eunyup Yeom

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The roles of male and female in context of cuisine have developed into stereotypes throughout history. However¬— with Korea’s fast advancement in politics, technology, society and social standards¬— gender stereotypes have become blurred. This is not to say that such stereotypes no longer exist for they still remain present in media and advertisements embedding ‘idealistic’ ideas into the unconscious state of minds of viewers. Many media outlets, especially commercials, portray males expressing pleasure of food [that they are advertising] through audible qualities generally considered ‘rude’ and ‘unmannered’ in the Korean society. Females, on the other hand, express such pleasures only verbally. This happenstance of a stereotype is displayed bluntly in instant noodle, namely ramen, commercials. This research explores the cultural significance of a type of audible gesture that can be found in Korean speech in which is termed the Fricative Voice Gesture (FVG). There are two forms of FVGs: the reactive and the prosodic. The reactive FVG is a legitimate form of expression while the prosodic FVG works as a speech intensifier. So, in order to understand this stereotype of who is authorized to express sensorial pleasure as a reactive FVG as opposed to a prosodic FVG, information has been extracted from interviews and dissected numerous ramen/instant noodle commercials and its appearances in other mediums of media. The commercials were tediously analyzed in all aspects of dialogue, featured contents, background music, actors and/or actresses selling the product, body language, and voice gestures. To effectively understand the exact impact these commercials have on the audience, each commercial was viewed with an interviewee. In this research, there were main informants whom were all Korean students residing in South Korea. All three interviewees were able to attend interview and commercial viewing sessions via Skype. This research, overall, focuses and concludes on Harkness’s statement of how the reactive FVG is a recognizable index of the privileging of males for Korean culture norms and, in parallel, food commercials are still conforming to male ideals and fantasies.

Keywords: advertisement, food politics, fricative voice gestures, gender politics

Procedia PDF Downloads 226

Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: J. DeBoard, R. Dietrich, J. Hughes, K. Yurko, G. Harms

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Alzheimer’s disease (AD) is a predominant type of dementia and is likely a major cause of neural network impairment. The pathogenesis of this neurodegenerative disorder has yet to be fully elucidated. There are currently no known cures for the disease, and the best hope is to be able to detect it early enough to impede its progress. Beyond age and genetics, another prevalent risk factor for AD might be traumatic brain injury (TBI), which has similar neurodegenerative hallmarks. Our research focuses on obtaining information and methods to be able to predict when neurodegenerative effects might occur at a clinical level by observation of events at a cellular and molecular level in model mice. First, we wish to introduce our evidence that brain damage can be observed via brain imaging prior to the noticeable loss of neuromuscular control in model mice of AD. We then show our evidence that some blood biomarkers might be able to be early predictors of AD in the same model mice. Thus, we were interested to see if we might be able to predict which mice might show long-term neurodegenerative effects due to differing degrees of TBI and what level of TBI causes further damage and earlier death to the AD model mice. Upon application of TBIs via an apparatus to effectively induce extremely mild to mild TBIs, wild-type (WT) mice and AD mouse models were tested for cognition, neuromuscular control, olfactory ability, blood biomarkers, and brain imaging. Experiments are currently still in process, and more results are therefore forthcoming. Preliminary data suggest that neuromotor control diminishes as well as olfactory function for both AD and WT mice after the administration of five consecutive mild TBIs. Also, seizure activity increases significantly for both AD and WT after the administration of the five TBI treatment. If future data supports these findings, important implications about the effect of TBI on those at risk for AD might be possible.

Keywords: Alzheimer's disease, blood biomarker, neurodegeneration, neuromuscular control, olfaction, traumatic brain injury

Procedia PDF Downloads 141