Search results for: Global Accuracy Indicator (GAI)

Authors: Bhogendra Mishra, Andy Nelson, Mirco Boschetti, Lorenzo Busetto, Alice Laborte

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Rice is grown on over 100 million hectares in almost every country of Asia. It is the most important staple crop for food security and has high economic and cultural importance in Asian societies. The combination of genetic diversity and management options, coupled with the large geographic extent means that there is a large variation in seasonality (when it is grown) and cropping intensity (how often it is grown per year on the same plot of land), even over relatively small distances. Seasonality and intensity can and do change over time depending on climatic, environmental and economic factors. Detecting where and when these changes happen can provide information to better understand trends in regional and even global rice production. Remote sensing offers a unique opportunity to estimate these trends. We apply the recently published PhenoRice algorithm to 14 years of moderate resolution remote sensing (MODIS) data (utilizing 250m resolution 16 day composites from Terra and Aqua) to estimate seasonality and cropping intensity per year and changes over time. We compare the results to the surveyed data collected by International Rice Research Institute (IRRI). The study results in a unique and validated dataset on the extent and change of extent, the seasonality and change in seasonality and the cropping intensity and change in cropping intensity between 2003 and 2016 for the Philippines. Observed trends and their implications for food security and trade policies are also discussed.

Keywords: rice, cropping intensity, moderate resolution remote sensing (MODIS), phenology, seasonality

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Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

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Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, material recycling, optimization modeling

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Jalal Eddine Benmansour, Khouane Boulanoir, Nacera Bekhadda, Elhassen Benfriha

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This paper introduces a novel composite control approach that addresses the challenge of stabilizing the three-axis attitude of a flexible satellite in the presence of vibrations caused by flexible appendages. The key contribution of this research lies in the development of a disturbance observer, which effectively observes and estimates the unwanted torques induced by the vibrations. By utilizing the estimated disturbance, the proposed approach enables efficient compensation for the detrimental effects of vibrations on the satellite system. To govern the attitude angles of the spacecraft, a proportional derivative controller (PD) is specifically designed and proposed. The PD controller ensures precise control over all attitude angles, facilitating stable and accurate spacecraft maneuvering. In order to demonstrate the global stability of the system, the Lyapunov method, a well-established technique in control theory, is employed. Through rigorous analysis, the Lyapunov method verifies the convergence of system dynamics, providing strong evidence of system stability. To evaluate the performance and efficacy of the proposed control algorithm, extensive simulations are conducted. The simulation results validate the effectiveness of the combined approach, showcasing significant improvements in the stabilization and control of the satellite's attitude, even in the presence of disruptive vibrations from flexible appendages. This novel composite control approach presented in this paper contributes to the advancement of satellite attitude control techniques, offering a promising solution for achieving enhanced stability and precision in challenging operational environments.

Keywords: attitude control, flexible satellite, vibration control, disturbance observer

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Authors: Mohammed A. Elhaj, Jamal S. Yassin

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In the present time, energy crises are considered a severe problem across the world. For the protection of global environment and maintain ecological balance, energy saving is considered one of the most vital issues from the view point of fuel consumption. As the industrial sectors everywhere continue efforts to improve their energy efficiency, recovering waste heat losses provides an attractive opportunity for an emission free and less costly energy resource. In the other hand the using of solar energy has become more insistent particularly after the high gross of prices and running off the conventional energy sources. Therefore, it is essential that we should endeavor for waste heat recovery as well as solar energy by making significant and concrete efforts. For these reasons this investigation is carried out to study and analyze the performance of a power plant working by a combined cycle in which Heat Recovery System Generator (HRSG) gets its energy from the waste heat of a gas turbine unit. Evaluation of the performance of the plant is based on different thermal efficiencies of the main components in addition to the second law analysis considering the exergy destructions for the whole components. The contribution factors including the solar as well as the wasted energy are considered in the calculations. The final results have shown that there is significant exergy destruction in solar concentrator and the combustion chamber of the gas turbine unit. Other components such as compressor, gas turbine, steam turbine and heat exchangers having insignificant exergy destruction. Also, solar energy can contribute by about 27% of the input energy to the plant while the energy lost with exhaust gases can contribute by about 64% at maximum cases.

Keywords: solar energy, environment, efficiency, waste heat, steam generator, performance, exergy destruction

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Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

Abstract:

Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, life cycle assessment, material recycling

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Authors: Maliheh Rezaei

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Peace education has been introduced into many higher educational contexts by designing different programs, expecting to result in constructive changes, specifically in post-conflict countries. Teachers are the potential agents of positive change who play a major role in fostering the culture of peace in their classes. The purpose of this literature review was thus to evaluate the implementation of peace pedagogies by teachers in the context of higher education. More specifically, it addressed a) the role and characteristics of teachers and b) the pedagogies that they used to construct the culture of peace. The systematic literature review was used and several inclusion criteria were applied. Only papers published in English, which contained the keywords of university, higher education, peace, peace education, and similar derivatives such as ‘peacebuilding’ in their title and/or abstract, were included in this review. Moreover, only papers that dealt with the actual implementation of peace education theories were investigated. Findings highlighted that most teachers relied on pedagogies adopted from social justice, global citizenship, and positive psychology practices aiming to foster positive human traits such as resilience, empathy and reflection that were also believed to play an important role in peacebuilding efforts. Nevertheless, the incorporation of peace remained peripheral. The main challenge to incorporate the tenets of peace education was the shortage of teachers who were skilled and qualified enough to incorporate and promote the culture of peace in their classes. This literature review presents the body of research that has linked peace education to Higher Education. Therefore, it informs teachers about the potential roles they have in creating a peaceful and sustainable future. It also presents them with more effective pedagogies and practices to successfully integrate peace-related activities in Higher Education.

Keywords: culture of peace, higher education, teacher, pedogogy

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Authors: Faith Eweluegim Enahoro-Ofagbe

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Worldwide, every nation is experiencing the effects of global warming. In developing countries, due to the heavy reliance on agriculture for socioeconomic growth and security, among other things, these countries are more affected by climate change, particularly with the availability of water. Floods, droughts, rising temperatures, saltwater intrusion, groundwater depletion, and other severe environmental alterations are all brought on by climatic change. Life depends on water, a vital resource; these ecological changes affect all water use, including agriculture and household water use. Therefore adequate and adaptive water usage strategies for sustainability are essential in developing countries. Therefore, this paper investigates Nigeria's challenges due to climate change and adaptive techniques that have evolved in response to such issues to ensure water management and sustainability for irrigation and provide quality water to residents. Questionnaires were distributed to respondents in the study area, central Nigeria, for quantitative evaluation of sustainable water resource management techniques. Physicochemical analysis was done, collecting soil and water samples from several locations under investigation. Findings show that farmers use different methods, ranging from intelligent technologies to traditional strategies for water resource management. Also, farmers need to learn better water resource management techniques for sustainability. Since more residents obtain their water from privately held sources, the government should enforce legislation to ensure that private borehole construction businesses treat water sources of poor quality before the general public uses them.

Keywords: developing countries, irrigation, strategies, sustainability, water resource management, water usage

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Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

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Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

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Authors: Homa Hedayat

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In the dynamic urban landscape of Toronto, the concept of belonging assumes paramount importance. As global challenges—such as the pandemic, financial instability, and geopolitical shifts—reshape our world, understanding how different generations of immigrants establish connections within this multicultural metropolis becomes increasingly vital. Our research delves into forming a sense of belonging in urban spaces, specifically focusing on the experiences of Iranian immigrants residing in Toronto. By examining their perceptions of public places, attachment to residential neighborhoods, and the impact of the urban environment, we contribute to a more holistic understanding of social sustainability and community well-being. We unravel the intricate interplay between individual characteristics, housing context, and neighborhood dynamics through qualitative interviews and a quantitative survey. This research presents a study of the perception of public places and sense of belonging in residential neighbourhoods by younger and older Iranian immigrants living in the Toronto metropolitan area. Few works in the existing literature have investigated the relationship immigrants develop with the shared spaces of the city and their residential environment and how that relationship can impact the development of a ‘sense of belonging’ in the city. Ultimately, our findings pave the way for inclusive and cohesive urban environments, fostering connections across generations and enhancing Toronto’s resilience and harmony. As Toronto continues to evolve, nurturing a sense of belonging becomes paramount. Our research emphasizes the importance of social cohesion and community well-being. By fostering connections across generations, we pave the way for a more resilient and harmonious city.

Keywords: sense of belonging, multigenerational, urban spaces, social sustainability

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Reza Ehsani, Hawa Ze Jaffar, Ishak Aris

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Ripeness estimation of oil palm fresh fruit is important processes that affect the profitableness and salability of oil palm fruits. The adulthood or ripeness of the oil palm fruits influences the quality of oil palm. Conventional procedure includes physical grading of Fresh Fruit Bunches (FFB) maturity by calculating the number of loose fruits per bunch. This physical classification of oil palm FFB is costly, time consuming and the results may have human error. Hence, many researchers try to develop the methods for ascertaining the maturity of oil palm fruits and thereby, deviously the oil content of distinct palm fruits without the need for exhausting oil extraction and analysis. This research investigates the potential of infrared images (Thermal Images) as a predictor to classify the oil palm FFB ripeness. A total of 270 oil palm fresh fruit bunches from most common cultivar of oil palm bunches Nigresens according to three maturity categories: under ripe, ripe and over ripe were collected. Each sample was scanned by the thermal imaging cameras FLIR E60 and FLIR T440. The average temperature of each bunches were calculated by using image processing in FLIR Tools and FLIR ThermaCAM researcher pro 2.10 environment software. The results show that temperature content decreased from immature to over mature oil palm FFBs. An overall analysis-of-variance (ANOVA) test was proved that this predictor gave significant difference between underripe, ripe and overripe maturity categories. This shows that the temperature as predictors can be good indicators to classify oil palm FFB. Classification analysis was performed by using the temperature of the FFB as predictors through Linear Discriminant Analysis (LDA), Mahalanobis Discriminant Analysis (MDA), Artificial Neural Network (ANN) and K- Nearest Neighbor (KNN) methods. The highest overall classification accuracy was 88.2% by using Artificial Neural Network. This research proves that thermal imaging and neural network method can be used as predictors of oil palm maturity classification.

Keywords: artificial neural network, maturity classification, oil palm FFB, thermal imaging

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Authors: Flavio Gazzani

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Nitrogen is an important agricultural input that is critical for the production. However, the introduction of large amounts of nitrogen into the environment has a number of undesirable impacts such as: the loss of biodiversity, eutrophication of waters and soils, drinking water pollution, acidification, greenhouse gas emissions, human health risks. It is a challenge to sustain or increase food production and at the same time reduce losses of reactive nitrogen to the environment, but there are many potential benefits associated with improving nitrogen use efficiency. Reducing nutrient losses from agriculture is crucial to the successful implementation of agricultural policy. Traditional regulatory instruments applied to implement environmental policies to reduce environmental impacts from nitrogen fertilizers, despite some successes, failed to address many environmental challenges and imposed high costs on the society to achieve environmental quality objectives. As a result, economic instruments started to be recognized for their flexibility and cost-effectiveness. The objective of the research project is to analyze the potential for increased use of market-based instruments in nitrogen control policy. The report reviews existing knowledge, bringing different studies together to assess the global nitrogen situation and the most relevant environmental management policy that aims to reduce pollution in a sustainable way without affect negatively agriculture production and food price. This analysis provides some guidance on how different market based instruments might be orchestrated in an overall policy framework to the development and assessment of sustainable nitrogen management from the economics, environmental and food security point of view.

Keywords: nitrogen emissions, chemical fertilizers, eutrophication, non-point of source pollution, dairy farm

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Authors: Seungchul Lee, Minjeong Kim, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo

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It is hard to maintain the effluent quality of the wastewater treatment plants (WWTPs) under with fixed types of operational control because of continuously changed influent flow rate and pollutant load. The aims of this study is development of multi-loop multi-objective control (ML-MOC) strategy in plant-wide scope targeting four objectives: 1) maximization of nutrient removal efficiency, 2) minimization of operational cost, 3) maximization of CH4 production in anaerobic digestion (AD) for CH4 reuse as a heat source and energy source, and 4) minimization of N2O gas emission to cope with global warming. First, benchmark simulation mode is modified to describe N2O dynamic in biological process, namely benchmark simulation model for greenhouse gases (BSM2G). Then, three types of single-loop proportional-integral (PI) controllers for DO controller, NO3 controller, and CH4 controller are implemented. Their optimal set-points of the controllers are found by using multi-objective genetic algorithm (MOGA). Finally, multi loop-MOC in BSM2G is implemented and evaluated in BSM2G. Compared with the reference case, the ML-MOC with the optimal set-points showed best control performances than references with improved performances of 34%, 5% and 79% of effluent quality, CH4 productivity, and N2O emission respectively, with the decrease of 65% in operational cost.

Keywords: Benchmark simulation model for greenhouse gas, multi-loop multi-objective controller, multi-objective genetic algorithm, wastewater treatment plant

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Authors: Francisco Dos Santos, Diogo Fonseca-Pereira, Sílvia Arroz-Madeira, Henrique Veiga-Fernandes

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Haematopoiesis is a developmental process that generates all blood cell lineages in health and disease. This relies on quiescent haematopoietic stem cells (HSCs) that are able to differentiate, self renew and expand upon physiological demand. HSCs have great interest in regenerative medicine, including haematological malignancies, immunodeficiencies and metabolic disorders. However, the limited yield from existing HSC sources drives the global need for reliable techniques to expand harvested HSCs at high quality and sufficient quantities. With the extensive use of cord blood progenitors for clinical applications, there is a demand for a safe and efficient expansion protocol that is able to overcome the limitations of the cord blood as a source of HSC. StemCell2MAXTM developed a technology that enhances the survival, proliferation and transplantation efficiency of HSC, leading the way to a more widespread use of HSC for research and clinical purposes. StemCell2MAXTM MIX is a solution that improves HSC expansion up to 20x, while preserving stemness, when compared to state-of-the-art. In a recent study by a leading cord blood bank, StemCell2MAX MIX was shown to support a selective 100-fold expansion of CD34+ Hematopoietic Stem and Progenitor Cells (when compared to a 10-fold expansion of Total Nucleated Cells), while maintaining their multipotent differentiative potential as assessed by CFU assays. The technology developed by StemCell2MAXTM opens new horizons for the usage of expanded hematopoietic progenitors for both research purposes (including quality and functional assays in Cord Blood Banks) and clinical applications.

Keywords: cord blood, expansion, hematopoietic stem cell, transplantation

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Authors: Luis Alvarado, Victor Poblete, Isaac Gonzalez, Yetzabeth Gonzalez

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In MIREX 2016 (http://www.music-ir.org/mirex), the deep neural network (DNN)-Deep Chroma Extractor, proposed by Korzeniowski and Wiedmer, reached the highest score in an audio chord recognition task. In the present paper, this tool is assessed under acoustic reverberant environments and distinct source-microphone distances. The evaluation dataset comprises The Beatles and Queen datasets. These datasets are sequentially re-recorded with a single microphone in a real reverberant chamber at four reverberation times (0 -anechoic-, 1, 2, and 3 s, approximately), as well as four source-microphone distances (32, 64, 128, and 256 cm). It is expected that the performance of the trained DNN will dramatically decrease under these acoustic conditions with signals degraded by room reverberation and distance to the source. Recently, the effect of the bio-inspired Locally-Normalized Cepstral Coefficients (LNCC), has been assessed in a text independent speaker verification task using speech signals degraded by additive noise at different signal-to-noise ratios with variations of recording distance, and it has also been assessed under reverberant conditions with variations of recording distance. LNCC showed a performance so high as the state-of-the-art Mel Frequency Cepstral Coefficient filters. Based on these results, this paper proposes a variation of locally-normalized triangular filters called Locally-Normalized Quarter Tone (LNQT) filters. By using the LNQT spectrogram, robustness improvements of the trained Deep Chroma Extractor are expected, compared with classical triangular filters, and thus compensating the music signal degradation improving the accuracy of the chord recognition system.

Keywords: chord recognition, deep neural networks, feature extraction, music information retrieval

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Authors: Gabriel Sunday Ayayia

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Food waste has reached alarming levels worldwide, contributing to food insecurity, resource depletion, and environmental degradation. While numerous strategies exist to mitigate this issue, the role of traditional practices and indigenous knowledge remains underexplored. There is a need to investigate how these age-old practices can contribute to sustainable food waste reduction, particularly in the African context. This study explores the potential of traditional practices and indigenous knowledge in Africa to address this challenge sustainably. The study examines traditional African food management practices and indigenous knowledge related to food preservation and utilization; assess the impact of traditional practices on reducing food waste and its broader implications for sustainable development, and identify key factors influencing the continued use and effectiveness of traditional practices in contemporary African societies. Thus, the study argues that traditional practices and indigenous knowledge in Africa offer valuable insights and strategies for sustainable food waste reduction that can be adapted and integrated into global initiatives This research will employ a mixed-methods approach, combining qualitative and quantitative research techniques. Data collection will involve in-depth interviews, surveys, and participant observations in selected African communities. Moreover, a comprehensive review of literature on traditional food management practices and their impact on food waste reduction will be conducted. The significance of this study lies in its potential to bridge the gap between traditional knowledge and modern sustainability efforts. By uncovering the value of traditional practices in reducing food waste, this research can inform policies, interventions, and awareness campaigns aimed at achieving sustainable food systems worldwide.

Keywords: traditional practices, indigenous knowledge, food waste reduction, sustainability

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Authors: Abid Kousay

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Appeared and developed essentially in large companies and multinationals, Talent Management (TM) in Small and Medium-Sized Enterprises (SMEs) has remained an under-explored subject till today. Although the literature on TM in the Anglo-Saxon context is developing, it remains monopolized in non-European contexts, especially in France. Therefore, this article aims to address these shortcomings through contributing to TM issues, by adopting a multilevel approach holding the goal of reaching a global holistic vision of interactions between various levels, while applying TM. A qualitative research study carried out within 12 SMEs in France, built on the methodological perspective of grounded theory, will be used in order to go beyond description, to generate or discover a theory or even a unified theoretical explanation. Our theoretical contributions are the results of the grounded theory, the fruit of context considerations and the dynamic of the multilevel approach. We aim firstly to determine the perception of talent and TM in SMEs. Secondly, we formalize TM in SME through the empowerment of all 3 levels in the organization (individual, collective, and organizational). And we generate a multilevel dynamic system model, highlighting the institutionalization dimension in SMEs and the managerial conviction characterized by the domination of the leader's role. Thirdly, this first study shed the light on the importance of rigorous implementation of TM in SMEs in France by directing CEO and HR and TM managers to focus on elements that upstream TM implementation and influence the system internally. Indeed, our systematic multilevel approach policy reminds them of the importance of the strategic alignment while translating TM policy into strategies and practices in SMEs.

Keywords: French context, institutionalization, talent, multilevel approach, talent management system

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Authors: Mohamed El-Khateeb

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

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

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Authors: Zelda Jansen Van Rensburg

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Purpose: This study investigates the perceived disparities between Quantity Surveying and Commercial Management in the construction industry, questioning if these differences are substantive or merely semantic. It aims to challenge the conventional notion of Commercial Managers’ superiority by critically evaluating QS and CM roles, exploring CM integration possibilities, examining qualifications for aspiring Commercial Managers, assessing regulatory frameworks, and considering terminology redefinition for global QS professional enhancement. Design: Utilizing mixed methods like literature reviews, surveys, interviews, and document analyses, this research examines the QS-CM relationship. Insights from industry professionals, academics, and regulatory bodies inform the investigation into changing QS roles. Findings: Empirical data highlight evolving roles, showcasing areas of convergence and divergence between QSs and CM. Potential CM integration into QS practice and qualifications for aspiring Commercial Managers are identified. Limitations/Implications: Limitations include potential bias in self-reported data and findings. Nevertheless, the research informs future practices and educational approaches in QS and CM, reflecting the changing roles and responsibilities of Quantity Surveyors. Practical Implications: Findings inform industry practitioners, educators, and regulators, stressing the need to adapt to changing QS roles and integrate CM principles where applicable. Value to the Conference Theme: Aligned with ‘Evolving roles and responsibilities of Quantity Surveyors,’ this research offers insights crucial for understanding the changing dynamics within the QS profession and informs strategies to navigate these shifts effectively.

Keywords: quantity surveying, commercial management, cost engineering, quantity survey

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Authors: Irsa Ejaz, Siyang He, Wei Li, Naiyue Hu, Chaochen Tang, Songbo Li, Meng Li, Boubacar Diallo, Guanghui Xie, Kang Yu

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Background: Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. Previously reported NIR model calibrations using the whole grain spectra had moderate accuracy. Improved predictions are achievable by using the spectra of whole grains, when compared with the use of spectra collected from the flour samples. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Objectives: To evaluate the feasibility of using NIRS and the influence of four sample types (whole grains, flours, hulled grain flours, and hull-less grain flours) on the prediction of chemical components to improve the grain sorting efficiency for human food, animal feed, and biofuel. Methods: NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. Results: The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. Conclusion: The established PLSR models could enable food, feed, and fuel producers to efficiently evaluate a large number of samples by predicting the required biochemical components in sorghum grains without destruction.

Keywords: FT-NIR, sorghum grains, biochemical composition, food, feed, fuel, PLSR

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Authors: Ismaila Olabisi Ogundiji, Hakeem Mayowa Olujide, Qasim Usamot

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The main reasons for site-specific management for agricultural inputs are to increase the profitability of crop production, to protect the environment and to improve products’ quality. Information about the variability of different soil attributes within a field is highly essential for the decision-making process. Lack of fast and accurate acquisition of soil characteristics remains one of the biggest limitations of precision agriculture due to being expensive and time-consuming. Adaptive sampling has been proven as an accurate and affordable sampling technique for planning within a field for site-specific management of agricultural inputs. This study employed spatial uncertainty of soil apparent electrical conductivity (ECa) estimates to identify adaptive re-survey areas in the field. The original dataset was grouped into validation and calibration groups where the calibration group was sub-grouped into three sets of different measurements pass intervals. A conditional simulation was performed on the field ECa to evaluate the ECa spatial uncertainty estimates by the use of the geostatistical technique. The grouping of high-uncertainty areas for each set was done using image segmentation in MATLAB, then, high and low area value-separate was identified. Finally, an adaptive re-survey was carried out on those areas of high-uncertainty. Adding adaptive re-surveying significantly minimized the time required for resampling whole field and resulted in ECa with minimal error. For the most spacious transect, the root mean square error (RMSE) yielded from an initial crude sampling survey was minimized after an adaptive re-survey, which was close to that value of the ECa yielded with an all-field re-survey. The estimated sampling time for the adaptive re-survey was found to be 45% lesser than that of all-field re-survey. The results indicate that designing adaptive sampling through spatial uncertainty models significantly mitigates sampling cost, and there was still conformity in the accuracy of the observations.

Keywords: soil electrical conductivity, adaptive sampling, conditional simulation, spatial uncertainty, site-specific management

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Authors: Ranojoy Dutta, Adam Barker

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Multifamily residential buildings are increasingly being built with large glazed areas to provide tenants with greater daylight and outdoor views. However, traditional double-glazed window assemblies can lead to significant thermal discomfort from high radiant temperatures as well as increased cooling energy use to address solar gains. Dynamic glazing provides an effective solution by actively controlling solar transmission to maintain indoor thermal comfort, without compromising the visual connection to outdoors. This study uses thermal simulations across three Canadian cities (Toronto, Vancouver and Montreal) to verify if dynamic glazing along with operable windows and ceiling fans can maintain the indoor operative temperature of a prototype southwest facing high-rise apartment unit within the ASHRAE 55 adaptive comfort range for a majority of the year, without any mechanical cooling. Since this study proposes the use of natural ventilation for cooling and the typical building life cycle is 30-40 years, the typical weather files have been modified based on accepted global warming projections for increased air temperatures by 2050. Results for the prototype apartment confirm that thermal discomfort with dynamic glazing occurs only for less than 0.7% of the year. However, in the baseline scenario with low-E glass there are up to 7% annual hours of discomfort despite natural ventilation with operable windows and improved air movement with ceiling fans.

Keywords: electrochromic glazing, multi-family housing, passive cooling, thermal comfort, natural ventilation

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Authors: Lili Yang, Jirui Gong, Qinpu Luo, Min Liu, Bo Yang, Zihe Zhang

Abstract:

Anthropogenic activities have increased nitrogen (N) inputs to grassland ecosystems. Knowledge of the impact of N addition on litter decomposition is critical to understand ecosystem carbon cycling and their responses to global climate change. The aim of this study was to investigate the effects of N addition and litter types on litter decomposition of a semi-arid temperate grassland during growing and non-growing seasons in Inner Mongolia, northern China, and to identify the relation between litter decomposition and C: N: P stoichiometry in the litter-soil continuum. Six levels of N addition were conducted: CK, N1 (0 g Nm−2 yr−1), N2 (2 g Nm−2 yr−1), N3 (5 g Nm−2 yr−1), N4 (10 g Nm−2 yr−1) and N5 (25 g Nm−2 yr−1). Litter decomposition rates and nutrient release differed greatly among N addition gradients and litter types. N addition promoted litter decomposition of S. grandis, but exhibited no significant influence on L. chinensis litter, indicating that the S. grandis litter decomposition was more sensitive to N addition than L. chinensis. The critical threshold for N addition to promote mixed litter decomposition was 10 -25g Nm−2 yr−1. N addition altered the balance of C: N: P stoichiometry between litter, soil and microbial biomass. During decomposition progress, the L. chinensis litter N: P was higher in N2-N4 plots compared to CK, while the S. grandis litter C: N was lower in N3 and N4 plots, indicating that litter N or P content doesn’t satisfy microbial decomposers with the increasing of N addition. As a result, S. grandis litter exhibited net N immobilization, while L. chinensis litter net P immobilization. Mixed litter C: N: P stoichiometry satisfied the demand of microbial decomposers, showed net mineralization during the decomposition process. With the increasing N deposition in the future, mixed litter would potentially promote C and nutrient cycling in grassland ecosystem by increasing litter decomposition and nutrient release.

Keywords: C: N: P stoichiometry, litter decomposition, nitrogen addition, nutrient release

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Authors: Ghadeer A.Al-Jabaree, Husam Aldeen Al-Khadash, M. Nassar

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This study aimed at investigating the effect of well-designed corporate governance system on the financial stability of insurance companies listed in ASE. Further, this study provides a comprehensive model for evaluating and analyzing insurance companies' financial position and prospective for comparing the degree of corporate governance application provisions among Jordanian insurance companies. In order to achieve the goals of the study, a whole population that consist of (27) listed insurance companies was introduced through the variables of (board of director, audit committee, internal and external auditor, board and management ownership and block holder's identities). Statistical methods were used with alternative techniques by (SPSS); where descriptive statistical techniques such as means, standard deviations were used to describe the variables, while (F) test and ANOVA analysis of variance were used to test the hypotheses of the study. The study revealed the existence of significant effect of corporate governance variables except local companies that are not listed in ASE on financial stability within control variables especially debt ratio (leverage),where it's also showed that concentration in motor third party doesn't have significant effect on insurance companies' financial stability during study period. Moreover, the study concludes that Global financial crisis affect the investment side of insurance companies with insignificant effect on the technical side. Finally, some recommendations were presented such as enhancing the laws and regulation that help the appropriate application of corporate governance, and work on activating the transparency in the disclosures of the financial statements and focusing on supporting the technical provisions for the companies, rather than focusing only on profit side.

Keywords: corporate governance, financial stability and solvency margin, insurance companies, Jordan

Procedia PDF Downloads 477

Authors: Onur Kaya, Halit Bayer

Abstract:

Global grocery and supermarket sales are among the largest markets in the world and perishable products such as fresh produce, dairy and meat constitute the biggest section of these markets. Due to their deterioration over time, the demand for these products depends highly on their freshness. They become totally obsolete after a certain amount of time causing a high amount of wastage and decreases in grocery profits. In addition, customers are asking for higher product variety in perishable product categories, leading to less predictable demand per product and to more out-dating. Effective management of these perishable products is an important issue since it is observed that billions of dollars’ worth of food is expired and wasted every month. We consider coordinated inventory and pricing decisions for perishable products with a time and price dependent random demand function. We use stochastic dynamic programming to model this system for both periodically-reviewed and continuously-reviewed inventory systems and prove certain structural characteristics of the optimal solution. We prove that the optimal ordering decision scenario has a monotone structure and the optimal price value decreases by time. However, the optimal price changes in a non-monotonic structure with respect to inventory size. We also analyze the effect of 1 different parameters on the optimal solution through numerical experiments. In addition, we analyze simple-to-implement heuristics, investigate their effectiveness and extract managerial insights. This study gives valuable insights about the management of perishable products in order to decrease wastage and increase profits.

Keywords: age-dependent demand, dynamic programming, perishable inventory, pricing

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Authors: Girma Y. Iyassu Menelik

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“The world is now like a global village!” so goes the saying that shows that due to development and technology the countries of the world are now closely linked. In the field of Human rights there is a close relationship in the way that rights are recognised and enforced. This paper will show that human rights have evolved from ancient times through important landmarks such as the Magna Carta, the French Declaration of Rights of Man and of the Citizen and the American Bill of Rights. The formation of the United Nations after the Second World War resulted in the need to codify and protect human rights. There are some rights which are so fundamental that they are found in international and continental instruments, national constitutions and domestic legislation. In the civil and political sphere they include the right to vote, to freedom of association, speech and assembly, right to life, privacy and fair trial. In the economic and social sphere you have the right to work, protection of the family, social security and rights to education, health and shelter. In some instance some rights can be suspended in times of public emergency but such derogations shall be circumscribed by the law and in most constitutions such limitations are subject to judicial review. However, some rights are so crucial that they cannot be derogated from under any circumstances and these include the right to life, recognition before the law, freedom from torture and slavery and of thought, conscience and religion. International jurisprudence has been developed to protect fundamental rights and avoid discrimination on the grounds of race, colour, sex, language or social origin. The elaborate protection system go to show that these rights have become part of the international order and they have universal application. We have now got to a stage where UDHR, ICCPR and ICESCR and have come to be regarded as part of an international bill of rights with horizontal and vertical enforcement mechanisms involving state parties, NGO’s , international bodies and other organs.

Keywords: rights, international, constitutional, state, judiciary

Procedia PDF Downloads 434

Authors: Peiming Li

Abstract:

This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

Procedia PDF Downloads 43

Authors: Clementina Ebere Okoro, Olumuyiwa Adeyemi Owolabi, Doris Bola James, Aloysius Nwabugo Maduforo, Andrew Lingililani Mbewe, Christopher Osaruwanmwen Isokpunwu

Abstract:

Poor dietary practices and malnutrition, including severe acute malnutrition among under-five children in Nigeria has remained a great public health concern. This study assessed infant and young child feeding practices and nutritional status of under-five children to determine the prevalence of malnutrition of under-five children in Kuje area council, Abuja. The study was a cross-sectional study. Multi-stage sampling techniques was used in selecting the population that was studied. Probability proportion by size was applied in choosing 30 clusters for the survey using ENA for SMART software 2011 version. Questionnaires were used to obtain information from the population, while appropriate equipment was used for measurements of anthropometric parameters. The data was also subjected to statistical analysis. Results were presented in tables and figures. The result showed that 96.7% of the children were breastfed, 30.6% had early initiation to breastfeeding within first hour of birth and 22.4% were breastfed exclusively up to 6 months, 69.8% fed infants’ colostrum, while 30.2% discarded colostrum. About half of the respondents (49.1%) introduced complementary feeding before six months and 23.2% introduced it after six months while 27.7% had age appropriate timely introduction of complementary feeding. The anthropometric result showed that the prevalence of global acute malnutrition (GAM) was 12.8%, severe wasting prevalence was 5.4%, moderate wasting was 7.4%, underweight was 24.4%, stunting was 40.3% and overweight was 7.0%. The result showed that there is a high prevalence of malnutrition among under-five children in Kuje

Keywords: malnutrition, under five children, breastfeeding, complementary feeding

Procedia PDF Downloads 243

Authors: Kelly F. Delgado-De Agrela, Sonia E. Ruiz, Marco A. Santos-Santiago

Abstract:

An approach is proposed for the design of regular buildings equipped with non-linear viscous dissipating devices. The approach is based on a direct-displacement seismic design method which satisfies seismic performance objectives. The global system involved is formed by structural regular moment frames capable of supporting gravity and lateral loads with elastic response behavior plus a set of non-linear viscous dissipating devices which reduce the structural seismic response. The dampers are characterized by two design parameters: (1) a positive real exponent α which represents the non-linearity of the damper, and (2) the damping coefficient C of the device, whose constitutive force-velocity law is given by F=Cvᵃ, where v is the velocity between the ends of the damper. The procedure is carried out using a substitute structure. Two limits states are verified: serviceability and near collapse. The reduction of the spectral ordinates by the additional damping assumed in the design process and introduced to the structure by the viscous non-linear dampers is performed according to a damping reduction factor. For the design of the non-linear damper system, the real velocity is considered instead of the pseudo-velocity. The proposed design methodology is applied to an 8-story steel moment frame building equipped with non-linear viscous dampers, located in intermediate soil zone of Mexico City, with a dominant period Tₛ = 1s. In order to validate the approach, nonlinear static analyses and nonlinear time history analyses are performed.

Keywords: based design, direct-displacement based design, non-linear viscous dampers, performance design

Procedia PDF Downloads 182

Authors: Wan Liu, Haibo Wang, Cathy Huang, Zhiwu Tan, Zhiwei Chen

Abstract:

The tremendous diversity of HIV-1 has been a major challenge for an effective AIDS vaccine development. Mosaic approach presents the potential for vaccine design aiming for global protection. The mosaic antigen of HIV-1 Gag allows antigenic breadth for vaccine-elicited immune response against a wider spectrum of viral strains. However, the enhancement of immune response using vaccines is dependent on the strategy used. Heterologous prime/boost regimen has been shown to elicit high levels of immune responses. Here, we investigated whether priming using plasmid DNA with electroporation followed by boosting with the live replication-competent modified vaccinia virus vector TianTan (MVTT) combined with the mosaic antigenic sequence could elicit a greater and broader antigen-specific response against HIV-1 Gag in mice. When compared to DNA or MVTT alone, or MVTT/MVTT group, DNA/MVTT group resulted in coincidentally high frequencies of broadly reactive, Gag-specific, polyfunctional, long-lived, and cytotoxic CD8+ T cells and increased anti-Gag antibody titer. Meanwhile, the vaccination could upregulate PD-1+, and Tim-3+ CD8+ T cell, myeloid-derived suppressive cells and Treg cells to balance the stronger immune response induced. Importantly, the prime/boost vaccination could help control the EcoHIV and mesothelioma AB1-gag challenge. The stronger protective Gag-specific immunity induced by a Mosaic DNA/MVTT vaccine corroborate the promise of the mosaic approach, and the potential of two acceptably safe vectors to enhance anti-HIV immunity and cancer prevention.

Keywords: DNA/MVTT vaccine, EcoHIV, mosaic antigen, mesothelioma AB1-gag

Procedia PDF Downloads 224