Search results for: accelerated online learning

Authors: Nicole Scott, Emily Dwyer, Cara Patrissy, Samantha Bonventre, Lina Begdache

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Across North America, the use and abuse of Attention Deficit Hyperactivity Disorder (ADHD) medication, cannabis, nicotine, and other psychoactive substances across college campuses have become an increasingly prevalent problem. Students frequently use these substances to aid their studying or deal with their mental health issues. However, it is still unknown what psychoactive substances are likely to be abused when college students illicitly use ADHD medication. In addition, it is not clear which psychoactive substance is associated with mental distress. Thus, the purpose of this study is to fill these gaps by assessing the use of different psychoactive substances when illicit ADHD medication is used; and how this association relates to mental stress. A total of 702 undergraduate students from different college campuses in the U.S. completed an anonymous survey distributed online. Data were self-reported on demographics, the use of ADHD medications, cannabis, nicotine, other psychoactive drugs, and mental distress, and feelings and opinions on the use of illicit study drugs were all included in the survey. Mental distress was assessed using the Kessler Psychological Distress 6 Scale. Data were analyzed in SPSS, Version 25.0, using Pearson’s Correlation Coefficient. Our results show that use of ADHD medication, cannabis use (non-frequent and very frequent), and nicotine use (non-frequent and very frequent), there were both statistically significant positive and negative correlations to specific psychoactive substances and their corresponding frequencies. Along the same lines, ADHD medication, cannabis use (non-frequent and very frequent), and nicotine use (non-frequent and very frequent) had statistically significant positive and negative correlations to specific mental distress experiences. As these findings are combined, a vicious loop can initiate a cycle where individuals who abuse psychoactive substances may or may not be inclined to use other psychoactive substances. This may later inhibit brain functions in those main areas of the brain stem, amygdala, and prefrontal cortex where this vicious cycle may or may not impact their mental distress. Addressing the impact of study drug abuse and its potential to be associated with further substance abuse may provide an educational framework and support proactive approaches to promote awareness among college students.

Keywords: stimulant, depressant, nicotine, ADHD medication, psychoactive substances, mental health, illicit, ecstasy, adrenochrome

Procedia PDF Downloads 63

Authors: Francesca Maria Melucci, Marco Panettieri, Rocco Roma

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Cities are at the forefront of achieving the sustainable development goals set out in the Sustainable Development Goals of Agenda 2030. For these reasons, increasing attention has been given to the creation of resilient, sustainable, inclusive and green cities and finding solutions to these problems is one of the greatest challenges faced by researchers today. In particular urban green infrastructures, including green roofs, play a key role in tackling environmental, social and economic problems. The starting point was an extensive literature review on 1. research developments on the benefits (environmental, economic and social) and implications of green roofs; 2. sustainability assessment and applied methodologies; 3. specific indicators to measure impacts on urban sustainability. Through this review, the appropriate qualitative and quantitative characteristics that are part of the complex 'green roof' system were identified, as studies that holistically capture its multifunctional nature are still lacking. So, this paper aims to find a method to improve community participation in green roof initiatives and support local governance processes in developing efficient proposals to achieve better sustainability and resilience of cities. To this aim, the multidimensional indicator-based framework, presented by Tapia in 2021, has been tested for the first time in the case of a green roof in the city of Madrid. The framework's set of indicators was implemented with other indicators such as those of waste management and circularity (OECD Inventory of Circular Economy indicators) and sustainability performance. The specific indicators to be used in the case study were decided after a consultation phase with relevant stakeholders. Data on the community's willingness to participate in green roof implementation initiatives were collected through interviews and online surveys with a heterogeneous sample of citizens. The results of the application of the framework suggest how the different aspects of sustainability influence the choice of a green roof and provide input on the main mechanisms involved in citizens' willingness to participate in such initiatives.

Keywords: urban agriculture, green roof, urban sustainability, indicators, multi-criteria analysis

Procedia PDF Downloads 72

Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

Procedia PDF Downloads 112

Authors: Samia Dahmani

Abstract:

The research investigated the process and outcomes of an ongoing project “Den Grønne Rute”: a network of recreational rooms to be implemented throughout a former vulnerable neighborhood: Trekanten in the city of Holstebro in Denmark. The aim of the project is to better integrate Trekanten in the city and which initiated reflections upon the (dis)connection and the integration in relation to urban planning and city management, as well as the extent to which the project considers diversity since Holstebro is a growing multicultural city. With this research, it was first verified if Trekanten is splintered from Holstebro city, and secondly if planning for diversity, by engaging people in the process via place-making approaches, can help redress the disconnection between the neighborhood and the rest of the city. More specifically, the paper aims at exploring the role of place-making “Den Grønne Rute” in Trekanten in promoting planning for diversity and reassembling the splintering in the city. The theoretical and conceptual framework served to analyze the relationship between the splintering urbanism concept and the community involvement’s role in an inclusive process. The field study examines the detachment between Trekanten and Holstebro and the extent to which the project can overcome the disconnection. Methodologically a mix-methods approach was adopted where two semi-structured interviews, a focus group, and an online survey were conducted. Contrary to prior assumptions, the results showed that not only is Trekanten splintered from the city, but also the city is greatly disconnected from Trekanten, and hence Holstebro is a splintered city. The surprise was that Trekanten is moreover inner-splintered. The splintering urbanism accordingly has different dimensions. Even though the project’s design seemed to incorporate diverse ages and groups of people, its process lacks an understanding of the diversity’s relevance in promoting inclusiveness. In fact, the analysis revealed socio-cultural and psychological splintering. Since place-making, as a collaborative approach in planning, is itself an expression of diversity (since it brings differences into play), reconsidering diversity within the process by engaging people at the early stages of planning was recommended. Another suggestion was not to limit the project to a destination but more as an experience to remember and a story to tell. Only by bringing people together in re-imagining the place can Trekanten reassemble with Holstebro and vice versa. The aim of the research was to add a new perspective to the splintering urbanism and planning for diversity so to advance place-making as an approach in promoting the latter and redressing the former.

Keywords: the splintering urbanism, place-making, planning for diversity, Den Grønne Rute, Trekanten, Holstebro

Procedia PDF Downloads 123

Authors: Yu Cheng-Yu

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‘Heterotopia’, ‘Visual Cultural Art Education’ and ‘New Media’ of these three subjects seemingly are irrelevant. In fact, there are synchronicity and intertextuality inside. In addition to visual culture, art education inspires students the ability to reflect on popular culture image through visual culture teaching strategies in school. We should get involved in the community to construct the learning environment that conveys visual culture art. This thesis attempts to probe the heterogeneity of space and value from Michel Foucault and to research sustainable development strategy in ‘New Media Art Village’ heterogeneity from Jean Baudrillard, Marshall McLuhan's media culture theory and social construction ideology. It is possible to find a new media group that can convey ‘Visual Culture Art Education’ around the National Taipei University of Technology in this commercial district that combines intelligent technology, fashion, media, entertainment, art education, and marketing network. Let the imagination and innovation of ‘New Media Art Village’ become ‘implementable’ and new media Heterotopia of inter-subjectivity with the engagement of big data and digital media. Visual culture art education will also bring aesthetics into the community by New Media Art Village.

Keywords: social construction, heterogeneity, new media, big data, visual culture art education

Procedia PDF Downloads 248

Authors: Danying Gu, Xiaoyan Li, Yuanlei He

Abstract:

As a knowledge-intensive industry, nuclear industry highly values the importance of safety and quality. The life cycle of a NPP (Nuclear Power Plant) can last 100 years from the initial research and design to its decommissioning. How to implement the high-quality knowledge management and how to contribute to a more safe, advanced and economic NPP (Nuclear Power Plant) is the most important issue and responsibility for knowledge management. As the lead of nuclear industry, nuclear research and design institute has competitive advantages of its advanced technology, knowledge and information, DKM (Design Knowledge Management) of nuclear research and design institute is the core of the knowledge management in the whole nuclear industry. In this paper, the study and practice on DKM and knowledge transfer across the life cycle of a new-built NPP in China is introduced. For this digital intelligent NPP, the whole design process is based on a digital design platform which includes NPP engineering and design dynamic analyzer, visualization engineering verification platform, digital operation maintenance support platform and digital equipment design, manufacture integrated collaborative platform. In order to make all the design data and information transfer across design, construction, commissioning and operation, the overall architecture of new-built digital NPP should become a modern knowledge management system. So a digital information transfer model across the NPP life cycle is proposed in this paper. The challenges related to design knowledge transfer is also discussed, such as digital information handover, data center and data sorting, unified data coding system. On the other hand, effective delivery of design information during the construction and operation phase will contribute to the comprehensive understanding of design ideas and components and systems for the construction contractor and operation unit, largely increasing the safety, quality and economic benefits during the life cycle. The operation and maintenance records generated from the NPP operation process have great significance for maintaining the operating state of NPP, especially the comprehensiveness, validity and traceability of the records. So the requirements of an online monitoring and smart diagnosis system of NPP is also proposed, to help utility-owners to improve the safety and efficiency.

Keywords: design knowledge management, digital nuclear power plant, knowledge transfer, life cycle

Procedia PDF Downloads 273

Authors: Christian Louis Kühner, Florian Pfeffel, Valentin Nickolai

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Taking care of children, dependents, or pets can be a difficult and time-consuming task. Especially for part- and full-time employees, it can feel exhausting and overwhelming to meet these obligations besides working a job. Thus, working mostly at home and not having to drive to the company can save valuable time and stress. This study aims to show the influence that the working model has on the job satisfaction of employees with care responsibilities in comparison to employees who do not have such obligations. Using structural equation modeling (SEM), the three work models, “work from home”, “working remotely”, and a hybrid model, have been analyzed based on 13 influencing constructs on job satisfaction. These 13 factors have been further summarized into three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, an online survey was conducted with n = 684 employees from the service sector. Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. In addition, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that among the employees with care responsibilities, the higher the proportion of working from home in comparison to working from the office, the more satisfied the employees are with their job. Since the work models that meet the requirements of comprehensive care led to higher job satisfaction amongst employees with such obligations, adapting as a company to such private obligations by employees can be crucial to sustained success. Conversely, the satisfaction level of the working model where employees work at the office is higher for workers without caregiving responsibilities.

Keywords: care responsibilities, home office, job satisfaction, structural equation modeling

Procedia PDF Downloads 83

Authors: Sagir M. Yusuf, Chris Baber

Abstract:

We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 155

Authors: Yosra Mefteh Rekik

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A computational agent-based model of financial markets stresses interactions and dynamics among a very diverse set of traders. The growing body of research in this area relies heavily on computational tools which by-pass the restrictions of an analytical method. The main goal of this research is to understand how the stock market operates and behaves how to invest in the stock market and to study traders’ behavior within the context of the artificial stock markets populated by heterogeneous agents. All agents are characterized by adaptive learning behavior represented by the Artificial Neuron Networks. By using agent-based simulations on artificial market, we show that the existence of heterogeneous agents can explain the price dynamics in the financial market. We investigate the relation between market diversity and market efficiency. Our empirical findings demonstrate that greater market heterogeneity play key roles in market efficiency.

Keywords: agent-based modeling, artificial stock market, heterogeneous expectations, financial stylized facts, computational finance

Procedia PDF Downloads 438

Authors: Samia Dahmani

Abstract:

The research investigated the process and outcomes of an ongoing project, “Den Grønne Rute”: a network of recreational rooms to be implemented throughout a former vulnerable neighborhood: Trekanten, in the city of Holstebro in Denmark. The aim of the project is to better integrate Trekanten in the city and which initiated reflections upon the (dis)connection and the integration in relation to urban planning and city management, as well as the extent to which the project considers diversity since Holstebro is a growing multicultural city. With this research, it was first verified if Trekanten is splintered from Holstebro city, and secondly if planning for diversity, by engaging people in the process via place-making approaches, can help redress the disconnection between the neighborhood and the rest of the city. More specifically, the paper aims at exploring the role of place-making “Den Grønne Rute” in Trekanten in promoting planning for diversity and reassembling the splintering in the city. The theoretical and conceptual framework served to analyze the relationship between the splintering urbanism concept and the community involvement’s role for an inclusive process. The field study examines the detachment between Trekanten and Holstebro and the extent to which the project can overcome the disconnection. Methodologically a mix-methods approach was adopted where two semi-structured interviews, a focus group, and an online survey were conducted. Contrary to prior assumptions, the results showed that not only is Trekanten splintered from the city, but also the city is greatly disconnected from Trekanten, and hence Holstebro is a splintered city. The surprise was that Trekanten is moreover inner-splintered. The splintering urbanism accordingly has different dimensions. Even though the project’s design seemed to incorporate diverse ages and groups of people, its process lacks an understanding of the diversity’s relevance in promoting inclusiveness. In fact, the analysis revealed socio-cultural and psychological splintering. Since place-making, as a collaborative approach in planning, is itself an expression of diversity (since it brings differences into play), reconsidering diversity within the process by engaging people at the early sages of planning was recommended. Another suggestion was not to limit the project to a destination but more as an experience to remember and a story to tell. Only by bringing people together in re-imagining the place, can Trekanten reassemble with Holstebro and vice versa. The aim with the research was to add a new perspective to the splintering urbanism and planning for diversity so to advance place-making as an approach in promoting the latter and redressing the former.

Keywords: the splintering urbanism, placemaking, planning for diversity, den grønne rute, trekanten, holstebro

Procedia PDF Downloads 104

Authors: Kevin. S. Badni

Abstract:

Due to the rapid advances in the use of information technology and students’ familiarity with technology, learning styles in higher education are being reshaped. One of the technology developments that has gained considerable attention in recent years is Augmented Reality (AR), where technology is used to combine overlays of digital data on physical real-world settings. While AR is being heavily promoted for entertainment by mobile phone manufacturers, it has had little adoption in higher education due to the required upfront investment that an instructor needs to undertake in creating relevant AR applications. This paper discusses a case study that uses a low upfront development approach and examines the impact on generation-Z students’ motivation whilst studying design history over a four-semester period. Even though the upfront investment in creating the AR support was minimal, the results showed a noticeable increase in student motivation. The approach used in this paper can be easily transferred to other disciplines and other areas of design education.

Keywords: augmented reality, history, motivation, technology

Procedia PDF Downloads 166

Authors: Zhizhong Yuan, Lili Wang, Chenya Zheng, Wuqi Yang

Abstract:

How to encourage and support peer-to-peer (P2P) network lending, and effectively monitor the risk of P2P network lending, has become the focus of the Chinese government departments, industrialists, experts and scholars in recent years. The reason is that this convenient online micro-credit service brings a series of credit risks and other issues. Avoiding the risks brought by the P2P network lending model, it can better play a benign role and help China's small and medium-sized private enterprises with vigorous development to solve the capital needs; otherwise, it will bring confusion to the normal financial order. As a form of financial services, P2P network lending has injected new blood into China's non-government finance in the past ten years, and has found a way out for idle funds and made up for the shortage of traditional financial services in China. However, it lacks feasible measures in credit evaluation and government supervision. This paper collects a large amount of data about P2P network lending of China. The data collection comes from the official media of the Chinese government, the public achievements of existing researchers and the analysis and collation of correlation data by the authors. The research content of this paper includes literature review; the current situation of China's P2P network lending development; the risk analysis of P2P network lending in China; the risk prevention strategy of P2P network lending in China. The focus of this paper is to try to find a specific program to strengthen supervision and avoid risks from the perspective of government regulators, operators of P2P network lending platform, investors and users of funds. These main measures include: China needs to develop self-discipline organization of P2P network lending industry and formulate self-discipline norms as soon as possible; establish a regular information disclosure system of P2P network lending platform; establish censorship of credit rating of borrowers; rectify the P2P network lending platform in compliance through the implementation of bank deposition. The results and solutions will benefit all the P2P network lending platforms, creditors, debtors, bankers, independent auditors and government agencies of China and other countries.

Keywords: peer-to-peer(P2P), regulation, risk prevention, supervision

Procedia PDF Downloads 166

Authors: Manuela Caciula, Luis Torres, Simion Tomoiaga

Abstract:

Introduction: The SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), more commonly referred to as COVID-19, has wreaked havoc on all facets of higher education since its inception in late 2019. College students, in particular, significantly reduced their daily energy expenditure and increased the time spent sitting to listen to online classes and complete their studies from home. This change, in combination with the associated COVID-19 lockdown, presumably decreased physical activity levels, increased mental health symptoms, and led to the promotion of unhealthy eating habits. Objectives: The main objective of this study was to determine the current self-reported physical activity levels, mental health symptoms, and body composition of college students after the COVID-19 lockdown in order to develop future interventions for the overall improvement of health. Methods: All participants completed pre-existing, well-validated surveys for both physical activity (International Physical Activity Questionnaire - long form) and mental health (Hospital Anxiety and Depression Scale). Body composition was assessed in person with the use of an Inbody 570 device. Results: Of the 90 American college students (M age = 22.52 ± 4.54, 50 females) who participated in this study, depressive and anxious symptom scores consistent with 58% (N = 52) heightened symptomatology, 17% (N = 15) moderate borderline symptomatology, and 25% (N = 23) asymptomatology were reported. In regard to physical activity, 79% (N = 71) of the students were highly physically active, 18% (N = 16) were moderately active, and 3% (N = 3) reported low levels of physical activity. Additionally, 46% (N = 41) of the students maintained an unhealthy body fat percentage based on World Health Organization recommendations. Strong, significant relationships were found between anxiety and depression symptomatology and body fat percentage (P = .003) and skeletal muscle mass (P = .015), with said symptomatology increasing with added body fat and decreasing with added skeletal muscle mass. Conclusions: Future health interventions for American college students should be focused on strategies to reduce stress, anxiety, and depressive characteristics, as well as nutritional information on healthy eating, regardless of self-reported physical activity levels.

Keywords: physical activity, mental health, body composition, COVID-19

Procedia PDF Downloads 98

Authors: Lillian M. Seo, Curtis L. Petersen, Ryan J. Halter, David Kotz, John A. Batsis

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Background: Resistance-based exercises effectively enhance muscle strength, which is especially important in older populations as it reduces the risk of disability. Our group developed a Bluetooth-enabled handle for resistance exercise bands that wirelessly transmits relative force data through low-energy Bluetooth to a local smartphone or similar device. The system has the potential to measure home-based exercise interventions, allowing health professionals to monitor compliance. Its feasibility has already been demonstrated in both clinical and field-based settings, but it remained unclear whether the system’s usability persisted upon repeated use. The current study sought to assess the usability of this system and its users’ satisfaction with repeated use by deploying the device among younger adults to gather formative information that can ultimately improve the device’s design for older adults. Methods: A usability study was conducted in which 32 participants used the above system. Participants executed 10 repetitions of four commonly performed exercises: bicep flexion, shoulder abduction, elbow extension, and triceps extension. Each completed three exercise sessions, separated by at least 24 hours to minimize muscle fatigue. At its conclusion, subjects completed an adapted version of the usefulness, satisfaction, and ease (USE) questionnaire – assessing the system across four domains: usability, satisfaction, ease of use, and ease of learning. The 20-item questionnaire examined how strongly a participant agrees with positive statements about the device on a seven-point Likert scale, with one representing ‘strongly disagree’ and seven representing ‘strongly agree.’ Participants’ data were aggregated to calculate mean response values for each question and domain, effectively assessing the device’s performance across different facets of the user experience. Summary force data were visualized using a custom web application. Finally, an optional prompt at the end of the questionnaire allowed for written comments and feedback from participants to elicit qualitative indicators of usability. Results: Of the n=32 participants, 13 (41%) were female; their mean age was 32.4 ± 11.8 years, and no participants had a physical impairment. No usability questions received a mean score < 5 of seven. The four domains’ mean scores were: usefulness 5.66 ± 0.35; satisfaction 6.23 ± 0.06; ease of use 6.25 ± 0.43; and ease of learning 6.50 ± 0.19. Representative quotes of the open-ended feedback include: ‘A non-rigid strap-style handle might be useful for some exercises,’ and, ‘Would need different bands for each exercise as they use different muscle groups with different strength levels.’ General impressions were favorable, supporting the expectation that the device would be a useful tool in exercise interventions. Conclusions: A simple usability assessment of a Bluetooth-enabled resistance exercise band supports a consistent and positive user experience among young adults. This study provides adequate formative data, assuring the next steps can be taken to continue testing and development for the target population of older adults.

Keywords: Bluetooth, exercise, mobile health, mHealth, usability

Procedia PDF Downloads 117

Authors: A. Drelick, T. Sondergeld, M. Decarlo-Tecce, K. McGinley

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In 1975, a free, appropriate public education (FAPE) was granted for all students in the United States regardless of their disabilities. As a result, the special education landscape has been reshaped through new policies and legislation. Progress monitoring, a specific component of an Individual Education Program (IEP) calls, for the use of data collection to determine the appropriateness of services provided to students with disabilities. The recent US Supreme Court ruling in Endrew F. v. Douglas County warrants giving increased attention to student progress, specifically pertaining to improving functional, or non-academic, skills that are addressed outside the general education curriculum. While using technology to enhance data collection has become a common practice for measuring academic growth, its application for non-academic IEP goals is uncertain. A mixed-methods study examined current practices and rationales for implementing technology-based progress monitoring focused on non-academic IEP goals. Fifty-seven participants responded to an online survey regarding their progress monitoring programs for non-academic goals. After isolated analysis and interpretation of quantitative and qualitative results, data were synthesized to produce meta-inferences that drew broader conclusions on the topic. For the purpose of this paper, specific focus will be placed on the perceived barriers and benefits of implementing technology-based progress monitoring protocols for non-academic IEP goals. The findings of this study highlight facts impacting the use of technology-based progress monitoring. Perceived barriers to implementation include: (1) lack of training, (2) access to technology, (3) outdated or inoperable technology, (4) reluctance to change, (5) cost, (6) lack of individualization within technology-based programs, and (7) legal issues in special education; while perceived benefits include: (1) overall ease of use, (2) accessibility, (3) organization, (4) potential for improved presentation of data, (5) streamlining the progress-monitoring process, and (6) legal issues in special education. Based on these conclusions, recommendations are made to IEP teams, school districts, and software developers to improve the progress-monitoring process for functional skills.

Keywords: special education, progress monitoring, functional skills, technology

Procedia PDF Downloads 247

Authors: Sujay Kotwale, Ramasubba Reddy M.

Abstract:

Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

Procedia PDF Downloads 119

Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

Procedia PDF Downloads 89

Authors: Marianne Simons, Sinan Kurt, Marjolein Stefens, Kai Karos, Johan Lataster

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As cultural diversity within older populations in European countries increases, the role of cultural background should be taken account of in aging studies. Bonding social capital (BSC), containing someone’s socio-emotional resources, is recognised as an important ingredient for wellbeing in old age and found to be associated with someone’s cultural background. The current study examined the association between BSC, loneliness and wellbeing in a sample including older Turkish migrants with a collectivistic cultural background and native Dutch older adults, both living in the Netherlands, characterised by an individualistic culture. A sample of 119 Turkish migrants (64.7% male; age 65-87, M(SD)=71.13(5.04) and 124 native Dutch adults (32.3% male, age 65-94, M(SD)= 71.9(5.32) filled out either an online or printed questionnaire measuring BSC, psychological, social and emotional well-being, loneliness and relevant demographic covariates. Regression analysis - including confounders age, gender, level of education, physical health and relationship - showed positive associations between BSC and respectively emotional, social and psychological well-being and a negative association with loneliness in both samples. Moderation analyses showed that these associations were significantly stronger for the Turkish older migrants than for their native peers. Measurement invariance analysis indicated partial metric invariance for the measurement of BSC and loneliness and non-invariance for wellbeing, calling for caution comparing means between samples. The results stress the importance of BSC for wellbeing of older migrants from collectivistic cultures living in individualistic countries. Previous research, shows a trend of older migrants displaying lower levels of BSC as well as associated variables, such as education, physical health, and financial income. This calls for more research of the interplay between demographic and psychosocial factors restraining mental wellbeing of older migrant populations. Measurement invariance analyses further emphasize the importance of taking cultural background into account in positive aging studies.

Keywords: positive aging, cultural background, wellbeing, social capital, loneliness

Procedia PDF Downloads 90

Authors: Zhao Kuo, Chen Liang, Zhang Zhongbing, Ruan Jinlu. He Shiyi, Xu Mengxuan

Abstract:

Stilbene, C₁₄H₁₂, is well known as one of the most useful organic scintillators for pulse shape discrimination (PSD) technique for its good scintillation properties. An on-line acquisition system and an off-line acquisition system were developed with several CAMAC standard plug-ins, NIM plug-ins, neutron/γ discriminating plug-in named 2160A and a digital oscilloscope with high sampling rate respectively for which stilbene crystals and photomultiplier tube detectors (PMT) as detector for accelerator neutron sources measurement carried out in China Institute of Atomic Energy. Pulse amplitude spectrums and charge amplitude spectrums were real-time recorded after good neutron/γ discrimination whose best PSD figure-of-merits (FoMs) are 1.756 for D-D accelerator neutron source and 1.393 for D-T accelerator neutron source. The probability of neutron events in total events was 80%, and neutron detection efficiency was 5.21% for D-D accelerator neutron sources, which were 50% and 1.44% for D-T accelerator neutron sources after subtracting the background of scattering observed by the on-line acquisition system. Pulse waveform signals were acquired by the off-line acquisition system randomly while the on-line acquisition system working. The PSD FoMs obtained by the off-line acquisition system were 2.158 for D-D accelerator neutron sources and 1.802 for D-T accelerator neutron sources after waveform digitization off-line processing named charge integration method for just 1000 pulses. In addition, the probabilities of neutron events in total events obtained by the off-line acquisition system matched very well with the probabilities of the on-line acquisition system. The pulse information recorded by the off-line acquisition system could be repetitively used to adjust the parameters or methods of PSD research and obtain neutron charge amplitude spectrums or pulse amplitude spectrums after digital analysis with a limited number of pulses. The off-line acquisition system showed equivalent or better measurement effects compared with the online system with a limited number of pulses which indicated a feasible method based on stilbene crystals detectors for the measurement of prompt neutrons neutron sources like prompt accelerator neutron sources emit a number of neutrons in a short time.

Keywords: stilbene crystal, accelerator neutron source, neutron / γ discrimination, figure-of-merits, CAMAC, waveform digitization

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Authors: N. Schneider, M. Bruchhage, M. Hartweg, G. Mutungi, J. O Regan, S. Deoni

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Observational neuroimaging studies suggest differences between breast-fed and formula-fed infants in developmental myelination, a key brain process for learning and cognitive development. However, the possible effects of a nutrient formulation on myelin development in healthy term infants in an intervention study have not been investigated. Objective was, therefore, to investigate the efficacy of a nutrient formulation with higher levels of myelin-relevant nutrients as compared to a control formulation with lower levels of the same nutrients on brain myelination and cognitive development in the first 6 months of life. The study is an ongoing randomized, controlled, double-blind, two-center, parallel-group clinical trial with a nonrandomized, non-blinded arm of exclusively breastfed infants. The current findings result from a staged statistical analysis at 6 months; the recruitment and intervention period has been completed for all participants. Follow-up visits at 12, 18 and 24 months are still ongoing. N= 81 enrolled full term, neurotypical infants of both sexes were randomized into either the investigational (N= 42) or the control group (N= 39), and N= 108 children in the breast-fed arm served as a natural reference group. The effect of a blend of docosahexaenoic acid, arachidonic acid, iron, vitamin B12, folic acid as well as sphingomyelin from a uniquely proceed whey protein concentrate enriched in alpha-lactalbumin and phospholipids in an infant nutrition product matrix was investigated. The main outcomes for the staged statistical analyses at 6 months included brain myelination measures derived from MRI. Additional outcomes were brain volume, cognitive development and safety. The full analyses set at 6 months comprised N= 66 infants. Higher levels of myelin-relevant nutrients compared to lower levels resulted in significant differences in myelin structure, volume, and rate of myelination as early as 3 and 6 months of life. The cross-sectional change of means between groups for whole-brain myelin volume was 8.4% for investigational versus control formulation (3.5% versus the breastfeeding reference) group at 3 months and increased to 36.4% for investigational versus control formulation (14.1% versus breastfeeding reference) at 6 months. No statistically significant differences were detected for early cognition scores. Safety findings were largely similar across groups. This is the first pediatric nutritional neuroimaging study demonstrating the efficacy of a myelin nutrient blend on developmental myelination in well-nourished term infants. Myelination is a critical process in learning and development. The effects were demonstrated across the brain, particularly in temporal and parietal regions, known to be functionally involved in sensory, motor and language skills. These first results add to the field of nutritional neuroscience by demonstrating early life nutrition benefits for brain architecture which may be foundational for later cognitive and behavioral outcomes. ClinicalTrials.gov Identifier: NCT03111927 (Infant Nutrition and Brain Development - Full-Text View - ClinicalTrials.gov).

Keywords: brain development, infant nutrition, MRI, myelination

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Authors: Gueidi Afef, Gharsellaoui Hamza, Ben Ahmed Samir

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This paper deals with the secret of the continual progression data that new data management solutions have been emerged: The NoSQL databases. They crossed several areas like personalization, profile management, big data in real-time, content management, catalog, view of customers, mobile applications, internet of things, digital communication and fraud detection. Nowadays, these database management systems are increasing. These systems store data very well and with the trend of big data, a new challenge’s store demands new structures and methods for managing enterprise data. The new intelligent machine in the e-learning sector, thrives on more data, so smart machines can learn more and faster. The robotics are our use case to focus on our test. The implementation of NoSQL for Robotics wrestle all the data they acquire into usable form because with the ordinary type of robotics; we are facing very big limits to manage and find the exact information in real-time. Our original proposed approach was demonstrated by experimental studies and running example used as a use case.

Keywords: NoSQL databases, database management systems, robotics, big data

Procedia PDF Downloads 355

Authors: Nattamon Srithammee, Ratchanikorn Chonchaiya

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This study explores the impact of Augmented Reality (AR) technology on mathematics education, focusing on Area and Volume concepts at Phra Dabos School in Thailand. We developed a mobile augmented reality application to present these mathematical concepts innovatively. Using a mixed-methods approach, we assessed the knowledge of 79 students before and after using the application. The results showed a significant improvement in students' understanding of Area and Volume, with average test scores increasing from 3.70 to 9.04 (p < 0.001, Cohen's d = 2.05). Students also reported increased engagement and satisfaction. Our findings suggest that augmented reality technology can be a valuable tool in mathematics education, particularly for enhancing the understanding of abstract concepts like Area and Volume. This study contributes to research on educational technology in STEM education and provides insights for educators and educational technology developers.

Keywords: augmented reality, mathematics education, area and volume, educational technology, STEM education

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Authors: Bernabeo R. Alberto

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With the tremendous improvements in the processing power of computers, the possibilities of artificial intelligence will increasingly be used in aviation and make autonomous flights, preventive maintenance, ATM (Air Traffic Management) optimization, pilots, cabin crew, ground staff, and airport staff training possible in a cost-saving, less time-consuming and less polluting way. Through the use of artificial intelligence, we foresee an interviewing scenario where the interviewee will interact with the artificial intelligence tool to contextualize the character and the necessary information in a way that aligns reasonably with the character and the scenario. We are creating simulated scenarios connected with either an aviation incident or accident to enhance also the training of future accident/incident investigators integrating artificial intelligence and augmented reality tools. The project's goal is to improve the learning and teaching scenario through academic and professional expertise in aviation and in the artificial intelligence field. Thus, we intend to contribute to the needed high innovation capacity, skills, and training development and management of artificial intelligence, supported by appropriate regulations and attention to ethical problems.

Keywords: artificial intelligence, aviation accident, aviation incident, risk, safety

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Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

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Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

Procedia PDF Downloads 137

Authors: Thomas Ogilegwu Orohu

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This paper presents agricultural education as a vocational study, an impetus for youths, economic empowerment. The survival of Nigeria’s agriculture rests squarely on the youth who are the farmers and leaders of tomorrow. Hitherto, the teaching and learning of agriculture has proceeded in such a manner that graduates of such programs have failed to make the successful launch into the world of agricultural enterprises (entrepreneurship). Major constraints that predisposed this anomalous situation were identified to include poor policy framework, socio-economic pressures, undue parental and peer influences, improper value orientation and of course, the nature of curricula. In response to the situation, some programs and/or initiatives aimed at inculcating entrepreneurial skills were proposed by this paper with identified target beneficiaries. The initiatives bordered on curricular reorientation that integrate entrepreneurship/enterprise education, retraining of graduates, financial support system among others.

Keywords: Program initiatives. vocational agriculture, youths’ empowerment, introduction

Procedia PDF Downloads 310

Authors: Philippe Judlin, Olivier Morel

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Background: In France, the resident curriculum (RC) in Obstetrics and Gynecology (OBGYN) takes five years. In the course of the last 15 years, this RC has undergone major changes, characterized mainly by successive reductions of work hours. The program used to comprise long and frequent shifts, huge workload, poor supervision and erratic theoretical teaching. A decade ago, the French Ministry of Heath recommended a limitation of shift duration up to 24 hours and a minimum of 11 hours off duty between shifts. Last year, in order to comply with European Union directives, new recommendations have further limited residents’ work hours to 48 hours per week. Methods: Assessment of the residency program adjustments recently made to accommodate the recommendations while improving the training quality in resorting to new methods. Results: The challenge facing program directors was to provide an all-encompassing curriculum to OBGYN residents despite fewer work hours. Program has been dramatically redesigned, and several measures have been put in place: -The resident rotation system has been redesigned. Residents used to make 6-month rotations between 10-12 Departments of OBGYN or Surgery. Fewer Departments, those providing the best teaching, have been kept in the new RC. -Extensive inhouse supervision has been implemented for all kinds of clinical activities. Effectual supervision of residents has proved to be an effective tool to improve the quality of training. -The tutorship system, with academic members individually overseeing residents during their curriculum, has been perfected. It allows a better follow-up of residents’ progresses during the 5-year program. -The set up of an extensive program of lectures encompassing all maters in Obstetrics & Gynecology. These mandatory lectures are available online in a dedicated website. Therefore, face-to-face lectures have been limited in order to fit in the 48-hour limit. -The use of simulation has been significantly increased in obstetrics, materno-fetal medicine and surgery (stressing especially laparoscopic training). -Residents’ feedback has been taken into account in the setup of the new RC. Conclusion: This extensive overhaul of the Obstetrics and Gynecology RC has been in place since last year only. Nevertheless, the new program seems to adequately take into account the new recommendations while providing a better and more consistent teaching to the OBGYN residents.

Keywords: education, laparoscopy, residency, simulation

Procedia PDF Downloads 186

Authors: Sandra So, Mohd Roslan Ismail, Safurah Jaafar

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With the rapid proliferation of data in healthcare has provided an opportune platform creation of Artificial Intelligence (AI). AI has brought a paradigm shift for healthcare professionals, promising improvement in delivery and quality. This study aims to determine the perception of healthcare personnel on perceived ease of use, perceived usefulness, and subjective norm toward attitude for artificial intelligence acceptance. A cross-sectional single institutional study of employees’ perception of adopting AI in the hospital was conducted. The survey was conducted using a questionnaire adapted from Technology Acceptance Model and a four-point Likert scale was used. There were 96 or 75.5% of the total population responded. This study has shown the significant relationship and the importance of ease of use, perceived usefulness, and subjective norm to the acceptance of AI. In the study results, it concluded that the determining factor to the strong acceptance of AI in their practices is mostly those respondents with the most interaction with the patients and clinical management.

Keywords: artificial intelligence, machine learning, perceived ease of use, perceived usefulness, subjective norm

Procedia PDF Downloads 226

Authors: S. Kawther, C. Marshall

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Educational neuroscience has the intention of transforming research findings of the underpinning neural processes of learning to educational practices. A main criticism of the field, hitherto, is that less focus has been put on studying the in-progress practical application of these findings. Therefore, this study aims to gain a better understanding of teachers’ perceptions of the practical application and utilization of brain knowledge. This was approached by investigating the answer to 'What are the facilitators and barriers for bringing research from neuroscience to bear on education?'. Following a qualitative design, semi-structured interviews were conducted with 12 teachers who had a proficient course in educational neuroscience. Thematic analysis was performed on the transcribed data applying Braun & Clark’s steps. Findings emerged with four main themes: time, knowledge, teacher’s involvement, and system. These themes revealed that some effective brain-based practices are being engaged in by the teachers. However, the lack of guidance and challenges regarding this implementation were also found. This study discusses findings in light of the development of educational neuroscience implementation.

Keywords: brain-based, educational neuroscience, neuroeducation, neuroscience-informed

Procedia PDF Downloads 168

Authors: Alina M. Udall, Judith de Groot, Simon de Jong, Avi Shankar

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There are many ways in which environmentally significant behavior can be explained. Dominant psychological theories, namely, the theory of planned behavior, the norm-activation theory, its extension, the value-belief-norm theory, and the theory of habit do not explain large parts of environmentally significant behaviors. A new and rapidly growing approach is to focus on how consumer’s identities predict environmentally significant behavior. Identity may be relevant because consumers have many identities that are assumed to guide their behavior. Therefore, we assume that many identities will guide environmentally significant behavior. Many identities can be relevant for environmentally significant behavior. In reviewing the literature, over 200 identities have been studied making it difficult to establish the key identities for explaining environmentally significant behavior. Therefore, this paper first aims to establish the key identities previously used for explaining environmentally significant behavior. Second, the aim is to test which key identities explain environmentally significant behavior. To address the aims, an online survey study (n = 578) is conducted. First, the exploratory factor analysis reveals 15 identity factors. The identity factors are namely, environmentally concerned identity, anti-environmental self-identity, environmental place identity, connectedness with nature identity, green space visitor identity, active ethical identity, carbon off-setter identity, thoughtful self-identity, close community identity, anti-carbon off-setter identity, environmental group member identity, national identity, identification with developed countries, cyclist identity, and thoughtful organisation identity. Furthermore, to help researchers understand and operationalize the identities, the article provides theoretical definitions for each of the identities, in line with identity theory, social identity theory, and place identity theory. Second, the hierarchical regression shows only 10 factors significantly uniquely explain the variance in environmentally significant behavior. In order of predictive power the identities are namely, environmentally concerned identity, anti-environmental self-identity, thoughtful self-identity, environmental group member identity, anti-carbon off-setter identity, carbon off-setter identity, connectedness with nature identity, national identity, and green space visitor identity. The identities explain over 60% of the variance in environmentally significant behavior, a large effect size. Based on this finding, the article reveals a new, theoretical framework showing the key identities explaining environmentally significant behavior, to help improve and align the field.

Keywords: environmentally significant behavior, factor analysis, place identity, social identity

Procedia PDF Downloads 451

Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

Procedia PDF Downloads 105