Search results for: optimal scheme

Authors: Mindaye Teshome, Evaldo Muñoz Braz, Carlos M. M. Eleto Torres, Patricia Mattos

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Sustainable forest management planning requires up-to-date information on the structure, standing volume, biomass, and growth rate of trees from a given forest. This kind of information is lacking in many forests in Ethiopia. The objective of this study was to quantify the population structure, diameter growth rate, and standing volume of wood from Juniperus procera trees in the Chilimo forest. A total of 163 sample plots were set up in the forest to collect the relevant vegetation data. Growth ring measurements were conducted on stem disc samples collected from 12 J. procera trees. Diameter and height measurements were recorded from a total of 1399 individual trees with dbh ≥ 2 cm. The growth rate, maximum current and mean annual increments, minimum logging diameter, and cutting cycle were estimated, and alternative cutting cycles were established. Using these data, the harvestable volume of wood was projected by alternating four minimum logging diameters and five cutting cycles following the stand table projection method. The results show that J. procera trees have an average density of 183 stems ha⁻¹, a total basal area of 12.1 m² ha⁻¹, and a standing volume of 98.9 m³ ha⁻¹. The mean annual diameter growth ranges between 0.50 and 0.65 cm year⁻¹ with an overall mean of 0.59 cm year⁻¹. The population of J. procera tree followed a reverse J-shape diameter distribution pattern. The maximum current annual increment in volume (CAI) occurred at around 49 years when trees reached 30 cm in diameter. Trees showed the maximum mean annual increment in volume (MAI) around 91 years, with a diameter size of 50 cm. The simulation analysis revealed that 40 cm MLD and a 15-year cutting cycle are the best minimum logging diameter and cutting cycle. This combination showed the largest harvestable volume of wood potential, volume increments, and a 35% recovery of the initially harvested volume. It is concluded that the forest is well stocked and has a large amount of harvestable volume of wood from J. procera trees. This will enable the country to partly meet the national wood demand through domestic wood production. The use of the current population structure and diameter growth data from tree ring analysis enables the exact prediction of the harvestable volume of wood. The developed model supplied an idea about the productivity of the J. procera tree population and enables policymakers to develop specific management criteria for wood harvesting.

Keywords: logging, growth model, cutting cycle, minimum logging diameter

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Authors: Grace Adebo

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Rural Farmers-herdsmen conflicts have resulted in a large number of causalities in many parts of Nigeria. Herds of cattle have died, while farmers recorded inestimable losses of their crops and harvests. The overall consequences have impacted negatively on food security across the country. There are divided opinions by scholars, agricultural experts and conflict analysts on the root causes of the conflicts and why traditional institutional interventions are ineffective in resolving the crisis. The study, therefore, aims to investigate the fundamentality of the conflicts’ causes in Southwest Nigeria and the correlates between traditional institutional authorities’ intervention and farmers-herdsmen conflicts in Southwest Nigeria. A structured interview schedule and focus group discussion were employed to elicit information from 180 farmers and 48 herdsmen selected through a multistage sampling procedure from the conflict zones in Southwest Nigeria. Collected data were analyzed using frequency counts, percentages, means and the Relative Importance Index (RII). The study found that climate change effects, farmland encroachment, crop damage, theft, and competition for land and water resources and pollution were the root causes of the violent herders-rural farmer’s clashes. The quest for wealth acquisition by some traditional rulers and some notable individuals in the conflict neighborhoods, occasioned tribal-mix herds possession and, thus undermining local institutional interventions and perverting justice through weak conflict resolution strategies, therefore, fueling further conflicts. Most farmers in the conflict zones have abandoned their farms for fear of death. This coupled with physical, social, economic and psychological consequences have deepened food insecurity and impaired the economic conditions of the herdsmen and the farmers. Currently, there are no mutually established mediation mechanisms as most states are opposed to the enactment of grazing laws to protect territorial encroachments of lands and subsequent multiplication of the herdsmen. It is suggested that government and Non-Governmental Organisation (NGOs) should encourage a functional stakeholder's forum for sustainable conflict resolution and establish a compensation scheme for losses incurred while extension agents are equipped with knowledge on conflict management strategies for peace attainment with the envisioned goal of achieving sustainable livelihoods and food security in Southwest Nigeria.

Keywords: conflict resolution, food security, herdsmen-farmers conflict, sustainable livelihoods, traditional institutions

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Authors: S. AliReza Mirghasemi, Zameer Hussain, Mohammad Saleh Sadeghi, Narges Rahimi Gabaran, Mohamadreza Baghaban Eslaminejad

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Background: Despite promising results have shown by osteogenic cell-based demineralized bone matrix composites, they need to be optimized for grafts that act as structural frameworks in load-bearing defects. The purpose of this experiment is to determine the effect of bone-marrow-mesenchymal-stem-cells seeding on partially demineralized laser-perforated structural allografts that have been implanted in critical femoral defects. Materials and Methods: P3 stem cells were used for graft seeding. Laser perforation in four rows of three holes was achieved. Cell-seeded grafts were incubated for one hour until they were planted into the defect. We used four types of grafts: partially demineralized only (Donly), partially demineralized stem cell seeded (DST), partially demineralized laser-perforated (DLP), and partially demineralized laser-perforated stem cell seeded (DLPST). histologic and histomorphometric analysis were performed at 12 weeks. Results: Partially demineralized laser-perforated had the highest woven bone formation within graft limits, stem cell seeded demineralized laser-perforated remained intact, and the difference between partially demineralized only and partially demineralized stem cell seeded was insignificant. At interface, partially demineralized laser-perforated and partially demineralized only had comparable osteogenesis, but partially demineralized stem cell seeded was inferior. The interface in stem cell seeded demineralized laser-perforated was almost replaced by distinct endochondral osteogenesis with higher angiogenesis in the vicinity. Partially demineralized stem cell seeded and stem cell seeded demineralized laser-perforated graft surfaces had extra vessel-ingrowth-like porosities, a sign of delayed resorption. Conclusion: This demonstrates that simple cell-based composites are not optimal and necessitates the supplementation of synergistic stipulations and surface changes.

Keywords: structural bone allograft, partial demineralization, laser perforation, mesenchymal stem cell

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Authors: Dicle Aydın, Süheyla Büyükşahin Sıramkaya

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Conservation concept gained importance especially in 19th century, it found value with the change and developments lived globally. Basic values in the essence of the concept are important in the continuity of historical and cultural fabrics which have character special to them. Reuse of settlements and spaces carrying historical and cultural values in the frame of socio-cultural and socio-economic conditions is related with functional value. Functional dimension of reuse signifies interrogation of the usage potential of the building with a different aim other than its determined aim. If a building carrying historical and cultural values cannot be used with its own function because of environmental, economical, structural and functional reasons, it is advantageous to maintain its reuse from the point of environmental ecology. By giving a new function both a requirement of the society is fulfilled and a culture entity is conserved because of its functional value. In this study, functional dimension of reuse is exemplified in Antalya Kaleiçi where has a special location and importance with its natural, cultural and historical heritage characteristics. Antayla Kaleiçi settlement preserves its liveliness as a touristic urban fabric with its almost fifty thousand years of past, traditional urban form, civil architectural examples of 18th–19th century reflecting the life style of the region and monumental buildings. The civil architectural examples in the fabric have a special character formed according to Mediterranean climate with their outer sofa (open or closed), one, two or three storey, courtyards and oriels. In the study reuse of five civil architectural examples as boutique hotel by forming a whole with their environmental arrangements is investigated, it is analyzed how the spatial requirements of a boutique hotel are fulfilled in traditional dwellings. Usage of a cultural entity as a boutique hotel is evaluated under the headlines of i.functional requirement, ii.satisfactoriness of spatial dimensions, iii.functional organization. There are closed and open restaurant, kitchen, pub, lobby, administrative offices in the hotel with 70 bed capacity and 28 rooms in total. There are expansions to urban areas on second and third floors by the means of oriels in the hotel surrounded by narrow streets in three directions. This boutique hotel, formed by unique five different dwellings having similar plan scheme in traditional fabric, is different with its structure opened to outside and connected to each other by the means of courtyards, and its outside spaces which gained mobility because of the elevation differences in courtyards.

Keywords: reuse, adaptive reuse, functional dimension of reuse, traditional dwellings

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Authors: Sarra Kitanou

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Water recycling and reuse is an effective measure to solve the water stress problem. The sustainable use of water resource has become a national development strategy in Morocco. A key aspect of improving overall sustainability is the potential for direct wastewater effluent reuse. However, the hybrid technology membrane bioreactors (MBR) have been identified as an attractive option for producing high quality and nutrient-rich effluents for wastewater treatment. It is based on complex interactions between biological processes, filtration process and rheological properties of the liquid to be treated. Currently, with the evolution of wastewater treatment projects in Morocco, the MBR technology can be used as a technology treating different types of wastewaters and to produce effluent with suitable quality for reuse. However, the energetic consumption of this process is a great concern, which can limit the development and implementation of this technology. In this investigation, the electric energy consumption of an ultrafiltration membrane bioreactor process in domestic wastewater treatment is evaluated and compared to some MBR installations based on literature review. Energy requirements of the MBR are linked to operational parameters and reactor performance. The analysis of energy consumption shows that the biological aeration and membrane filtration are more energy consuming than the other components listed as feed and recirculation pumps. Biological aeration needs 53% of the overall energetic consumption and the specific energy consumption for membrane filtration is about 25%. However, aeration is a major energy consumer, often exceeding 50% share of total energy consumption. The optimal results obtained on the MBR process (pressure p = 1.15 bar), hydraulic retention time (15 h) showed removal efficiencies up to 90% in terms of organic compounds removal, 100% in terms of suspended solids presence and up to 80% reduction of total nitrogen and total phosphorus. The effluent from this MBR system could be considered as qualified for irrigation reuse, showing its potential application in the future.

Keywords: hybrid process, membrane bioreactor, wastewater treatment, reuse

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Authors: Alokananda Nath

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Land is an important issue anywhere in the world as it is one of the fundamental elements in human settlements. Since the urban areas are considered to be the drivers of economy for any country across the world and the phenomenon of ‘urbanization’ happening everywhere, there is always a greater pressure on urban land and its management. Many states in India have realized the importance of land as a valuable resource and have implemented certain framework for managing and developing land. But in West Bengal no such statutory framework has been formulated till now and a very out dated model of land acquisition for public purpose is practiced. Due to the lop-sided character of urban growth in the entire eastern region of India, the city of Kolkata continues to bear the burden of excessive growth of population and consequent urbanization of the adjoining areas at a rapid pace. This research tries to look into these conflicts with respect to the present pattern of development in the context of Kolkata and suggest a system for land management in order to implement the planning processes. For this purpose, five case study areas were taken up within the Kolkata Metropolitan Area and subsequent analysis of their present land management and development techniques was done. The findings reveal that there is a lack of political will as well as administrative inefficiency on part of both the development authority and the local bodies. Mostly the local bodies lack the financial resources and technical expertise to work out any kind of land management framework or work out any kind of model in order to manage the development that is happening. All these place undue strain on city infrastructure systems and reduce the potential of cities to contribute as engines of economic growth. The focus of reforms, therefore, ought to be on streamlining the urban planning process, judicious and optimal land use, efficient plan implementation mechanisms, improvement of titling and registration processes.

Keywords: urbanization, land management framework, land development, policy reforms, land-use planning processes

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Authors: Omran Al Balushi, Haitham Al Rawahi

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Enterprise Asset Management (eAM) has been implemented across different Generation, Transmission and Distribution subsidiaries in Nama Group companies. As part of Nama group, Oman Electricity Transmission Company (OETC) was the first company to implement this system. It was very important for OETC to implement and maintain such a system to achieve its business objectives and for effective operations, which will also support the delivery of the asset management strategy. Enterprise Asset Management (eAM) addresses the comprehensive asset maintenance requirements of Oman Electricity Transmission Company (OETC). OETC needs to optimize capacity and increase utilization, while lowering unit production. E-AM will enable OETC to adopt this strategy. Implementation of e-AM has improved operation performance with preventive and scheduled maintenance as well as it increased safety. Implementation of e-AM will also enable OETC to create optimal asset management strategy which will increase revenue and decrease cost by effectively monitoring operational data such as maintenance history and operation conditions. CMMS (Computerised Maintenance Management System) is the main software and the back-bone of e-AM system. It is used to provide an improved working practice to properly establish information and data flow related to maintenance activities. Implementation of e-AM system was one of the factors that supported OETC to achieve ISO55001 Certificate on fourth quarter of 2016. Also, full implementation of e-AM system will result in strong integration between CMMS and Geographical Information Systems (GIS) application and it will improve OETC to build a reliable maintenance strategy for all asset classes in its Transmission network. In this paper we will share our experience and knowledge of implementing such a system and how it supported OETC’s management to make decisions. Also we would highlight the challenges and difficulties that we encountered during the implementation of e-AM. Also, we will list some features and advantages of e-AM in asset management, preventive maintenance and maintenance cost management.

Keywords: CMMS, Maintenance Management, Asset Management, Maintenance Strategy

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Authors: Tesfaye Walle Mekonnen

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Maize is one of the most important staple food crops for most low-income households in the Sub-Saharan (SSA). Combined heat and drought stress is the major production threats that reduce the yield potential of biofortified maize and restrain various macro and micronutrient deficiencies highly prevalent in low-income people who rely solely on maize-based diets, SSA. This problem can be alleviated by crossing the biofortified inbred lines with different nutritional attributes, Fe, Zn, Protein, and Provitamin A, and developing agronomically superior and stable multi-nutrient maize of various genetic backgrounds. This aimed to understand the correlation between biofortified inbred lines per se and hybrid performance under combined heat and drought stress conditions (CSC). The experiment was conducted at CIMMYT, Zimbabwe, using α-lattice design with three replications. The hybrid effect was highly significant for zein fractions (α-, β-, γ- and δ-zein) zinc, (Zn), and iron (Fe) provitamin A, phytic acid, and grain yield. Under CSC, Fe, Zn concentration, provitamin A in grain and grain yield of hybrids were significantly decreased, however, the zein fraction content and phytic acid content increases in grain were increased under CSC. The phenotypic correlation between grain yield with Zn, Fe concentration, and Provitamin A in grain was strongly positive and higher under CSC than in well-watered conditions. The present investigation confirmed that under CSC, Fe, and Zn-enhanced hybrids could be forecasted to a certain scope based on the performance of and scientifically selected for desirable grain yield and related traits with CSC tolerance during hybrid development programs. In conclusion, the development of high-yielding and micronutrient-dense maize variety is possible under CSC, which could reduce the highly prevalent micronutrient in SSA.

Keywords: drought, Fe, heat, maize, protein, zein fractions, Zn

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Mohammad Aminnia, Mahmood Hosseini

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Environmental and functional conditions sometimes necessitate the architectural plan of the building to be asymmetric, and this result in an asymmetric structure. In such cases, finding an optimal pattern for locating the components of the lateral load bearing system, including shear walls, in the building’s plan is desired. In case of shear walls, in addition to the location, the shape of the wall cross-section is also an effective factor. Various types of shear wall and their proper layout might come effective in better stiffness distribution and more appropriate seismic response of the building. Several studies have been conducted in the context of analysis and design of shear walls; however, few studies have been performed on making decisions for the location and form of shear walls in multi-story buildings, especially those with irregular plan. In this study, an attempt has been made to obtain the most reliable seismic behavior of multi-story reinforced concrete vertically chamfered buildings by using more appropriate shear walls form and arrangement in 7-, 10-, 12-, and 15-story buildings. The considered forms and arrangements include common rectangular walls and L-, T-, U- and Z-shaped plan, located as the core or in the outer frames of the building structure. Comparison of seismic behaviors of the buildings, including maximum roof displacement, and particularly the formation of plastic hinges and their distribution in the buildings’ structures, have been done based on the results of a series of nonlinear time history analyses by using a set of selected earthquake records. Results show that shear walls with U-shaped cross-section, placed as the building central core, and also walls with Z-shaped cross-section, placed at the corners give the building more reliable seismic behavior.

Keywords: vertically chamfered buildings, non-linear time history analyses, l-, t-, u- and z-shaped plan walls

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Authors: Harveen Kaur Tatla, Parisa Niknejad, Rajender Gupta, Bipro Ranjan Dhar, Mohd. Adana Khan

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Sewage sludge management presents a pressing challenge in the realm of wastewater treatment, calling for sustainable and efficient solutions. This study explores the integration of Hydrothermal Liquefaction (HTL) and Anaerobic Digestion (AD) as a promising approach to address the complexities associated with sewage sludge treatment. The integration of these two processes offers a complementary and synergistic framework, allowing for the mitigation of inherent limitations, thereby enhancing overall efficiency, product quality, and the comprehensive utilization of sewage sludge. In this research, we investigate the optimal sequencing of HTL and AD within the treatment framework, aiming to discern which sequence, whether HTL followed by AD or AD followed by HTL, yields superior results. We explore a range of HTL working temperatures, including 250°C, 300°C, and 350°C, coupled with residence times of 30 and 60 minutes. To evaluate the effectiveness of each sequence, a battery of tests is conducted on the resultant products, encompassing Total Ammonia Nitrogen (TAN), Chemical Oxygen Demand (COD), and Volatile Fatty Acids (VFA). Additionally, elemental analysis is employed to determine which sequence maximizes energy recovery. Our findings illuminate the intricate dynamics of HTL and AD integration for sewage sludge management, shedding light on the temperature-residence time interplay and its impact on treatment efficiency. This study not only contributes to the optimization of sewage sludge treatment but also underscores the potential of integrated processes in sustainable waste management strategies. The insights gleaned from this research hold promise for advancing the field of wastewater treatment and resource recovery, addressing critical environmental and energy challenges.

Keywords: Anaerobic Digestion (AD), aqueous phase, energy recovery, Hydrothermal Liquefaction (HTL), sewage sludge management, sustainability.

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Authors: Hugo Badia

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This research answers which is the most suitable transit network structure to serve specific demand requirements in an increasing urban dispersion process. Two main approaches of network design are found in the literature. On the one hand, a traditional answer, widespread in our cities, that develops a high number of lines to connect most of origin-destination pairs by direct trips; an approach based on the idea that users averse to transfers. On the other hand, some authors advocate an alternative design characterized by simple networks where transfer is essential to complete most of trips. To answer which of them is the best option, we use a two-step methodology. First, by means of an analytical model, three basic network structures are compared: a radial scheme, starting point for the other two structures, a direct trip-based network, and a transfer-based one, which represent the two alternative transit network designs. The model optimizes the network configuration with regard to the total cost for each structure. For a scenario of dispersion, the best alternative is the structure with the minimum cost. This dispersion degree is defined in a simple way considering that only a central area attracts all trips. If this area is small, we have a high concentrated mobility pattern; if this area is too large, the city is highly decentralized. In this first step, we can determine the area of applicability for each structure in function to that urban dispersion degree. The analytical results show that a radial structure is suitable when the demand is so centralized, however, when this demand starts to scatter, new transit lines should be implemented to avoid transfers. If the urban dispersion advances, the introduction of more lines is no longer a good alternative, in this case, the best solution is a change of structure, from direct trips to a network based on transfers. The area of applicability of each network strategy is not constant, it depends on the characteristics of demand, city and transport technology. In the second step, we translate analytical results to a real case study by the relationship between the parameters of dispersion of the model and direct measures of dispersion in a real city. Two dimensions of the urban sprawl process are considered: concentration, defined by Gini coefficient, and centralization by area based centralization index. Once it is estimated the real dispersion degree, we are able to identify in which area of applicability the city is located. In summary, from a strategic point of view, we can obtain with this methodology which is the best network design approach for a city, comparing the theoretical results with the real dispersion degree.

Keywords: analytical network design model, network structure, public transport, urban dispersion

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Authors: Harris Niavis, Dimitra Politaki

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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

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Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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Authors: Ilma Robo, Saimir Heta, Nedja Hysi, Vera Ostreni

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Introduction: Marginal gingivitis is a disease with considerable frequency among patients who present routinely for periodontal control and treatment. In fact, this disease may not have alarming symptoms in patients and may go unnoticed by themselves when personal hygiene conditions are optimal. The aim of this study was to collect retrograde data on the prevalence of marginal gingiva in the respective group of patients, evaluated according to specific periodontal diagnostic tools. Materials and methods: The study was conducted in two patient groups. The first group was with 34 patients, during December 2019-January 2020, and the second group was with 64 patients during 2010-2018 (each year in the mentioned monthly period). Bacterial plaque index, hemorrhage index, amount of gingival fluid, presence of xerostomia and candidiasis were recorded in patients. Results: Analysis of the collected data showed that susceptibility to marginal gingivitis shows higher values according to retrograde data, compared to cross-sectional ones. Susceptibility to candidiasis and the occurrence of xerostomia, even in the combination of both pathologies, as risk factors for the occurrence of marginal gingivitis, show higher values ​​according to retrograde data. The female are presented with a reduced bacterial plaque index than the males, but more importantly, this index in the females is also associated with a reduced index of gingival hemorrhage, in contrast to the males. Conclusions: Cross-sectional data show that the prevalence of marginal gingivitis is more reduced, compared to retrograde data, based on the hemorrhage index and the bacterial plaque index together. Changes in production in the amount of gingival fluid show a higher prevalence of marginal gingivitis in cross-sectional data than in retrograde data; this is based on the sophistication of the way data are recorded, which evolves over time and also based on professional sensitivity to this phenomenon.

Keywords: marginal gingivitis, cross-sectional, retrograde, prevalence

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Authors: Francois Defay, Martim Calao, Jean Francois Dassieu, Laurent Salvetat

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Electrical vehicles are a solution for reducing the pollution using green energy. The shell Eco-Marathon provides rules in order to minimize the battery use for the race. The use of solar panel combined with efficient motor control and race strategy allow driving a 60kg vehicle with one pilot using only the solar energy in the best case. This paper presents a complete modelization of a solar vehicle used for the shell eco-marathon. This project called Helios is cooperation between non-graduated students, academic institutes, and industrials. The prototype is an ultra-energy-efficient vehicle based on one-meter square solar panel and an own-made brushless controller to optimize the electrical part. The vehicle is equipped with sensors and embedded system to provide all the data in real time in order to evaluate the best strategy for the course. A complete modelization with Matlab/Simulink is used to test the optimal strategy to increase the global endurance. Experimental results are presented to validate the different parts of the model: mechanical, aerodynamics, electrical, solar panel. The major finding of this study is to provide solutions to identify the model parameters (Rolling Resistance Coefficient, drag coefficient, motor torque coefficient, etc.) by means of experimental results combined with identification techniques. One time the coefficients are validated, the strategy to optimize the consumption and the average speed can be tested first in simulation before to be implanted for the race. The paper describes all the simulation and experimental parts and provides results in order to optimize the global efficiency of the vehicle. This works have been started four years ago and evolved many students for the experimental and theoretical parts and allow to increase the knowledge on electrical self-efficient vehicle.

Keywords: electrical vehicle, endurance, optimization, shell eco-marathon

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Authors: Maryam Firouzmandi, Moosa Miri

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Smile is considered to be one of the most effective methods of influencing people. Increasing numbers of patients are requesting cosmetic dental procedures to achieve the perfect smile. Based on the patient’s age, oral and facial characteristics, and the dentist’s expertise, different concepts of treatment would be available. Orthodontics is the most conservative and the ideal treatment alternative for crowded anterior teeth; however, it may be rejected by patients due to occupational limitations of time, physical discomfort including pain and functional limitations, psychological discomfort, and appearance during treatment. In addition, orthodontic treatment will not resolve deficits of contour and color of the anterior teeth. In consequence, patients may demand restorative techniques to resolve their anterior mal-alignment instead, often called "instant orthodontics". Following its introduction, however, adhesive dentistry has suffered at times from overuse. Creating short-term attractive smiles at the expense of long-term dental health and optimal tooth biomechanics by using cosmetic techniques should not be considered an ethical approach. The objective of this narrative review was to investigate the literature for guidelines with regard to decision making and treatment planning for anterior tooth mal-alignment. In this regard, indications of orthodontic, restorative, combination of both treatments, and adjunctive periodontal surgery were discussed in clinical cases to achieve a proportional smile. Restorative modalities would include disking, cosmetic contouring, veneers, and crowns and were compared with limited or comprehensive orthodontic options. A rapid review was also presented on pros and cons of snap on smile to mask malalignments. Diagnostic tools such as mock up, wax up, and digital smile design were also considered to achieve more conservative and functional treatments with respect to biologic factors.

Keywords: crowding, misalignment, veneer, crown, orthodontics

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Authors: Manon Ghislain, Timothée Bonnet, Olivier Gimenez, Olivier Dehorter, Pierre-Yves Henry

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Climatic fluctuations affect the demography of animal populations, generating changes in population size, phenology, distribution and community assemblages. However, very few studies have identified the underlying demographic processes. For short-lived species, like common passerine birds, are these changes generated by changes in adult survival or in fecundity and recruitment? This study tests for an effect of annual climatic conditions (spring and winter) on annual, local adult survival at very large spatial (a country, 252 sites), temporal (25 years) and biological (25 species) scales. The Constant Effort Site ringing has allowed the collection of capture - mark - recapture data for 100 000 adult individuals since 1989, over metropolitan France, thus documenting annual, local survival rates of the most common passerine birds. We specifically developed a set of multi-year, multi-species, multi-site Bayesian models describing variations in local survival and recapture probabilities. This method allows for a statistically powerful hierarchical assessment (global versus species-specific) of the effects of climate variables on survival. A major part of between-year variations in survival rate was common to all species (74% of between-year variance), whereas only 26% of temporal variation was species-specific. Although changing spring climate is commonly invoked as a cause of population size fluctuations, spring climatic anomalies (mean precipitation or temperature for March-August) do not impact adult survival: only 1% of between-year variation of species survival is explained by spring climatic anomalies. However, for sedentary birds, winter climatic anomalies (North Atlantic Oscillation) had a significant, quadratic effect on adult survival, birds surviving less during intermediate years than during more extreme years. For migratory birds, we do not detect an effect of winter climatic anomalies (Sahel Rainfall). We will analyze the life history traits (migration, habitat, thermal range) that could explain a different sensitivity of species to winter climate anomalies. Overall, we conclude that changes in population sizes for passerine birds are unlikely to be the consequences of climate-driven mortality (or emigration) in spring but could be induced by other demographic parameters, like fecundity.

Keywords: Bayesian approach, capture-recapture, climate anomaly, constant effort sites scheme, passerine, seasons, survival

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Authors: Jae-Il Jeong, Hoon-Jae Park, Jung-Woo Cho, Yang-Gon Kim, Jin-Young Park, Joo-Young Oh, Si-Geun Choi, Seock-Sam Kim, Young Tae Cho, Chan Gyu Kim, Jong-Hyoung Kim

Abstract:

Bearing component has strongly required to decrease vibration and wear to achieve high durability and life time. In the industry field, bearing durability is improved by surface treatment on the bearing surface by centrifugal casting or gravity casting production method. However, this manufacturing method has caused problems such as long processing time, defect rate, and health harmful effect. To solve this problem, there is a laser cladding deposition treatment, which provides fast processing and food adhesion. Therefore, optimum conditions of white metal laser deposition should be studied to minimize bearing contact axis wear using laser cladding techniques. In this study, we deposit a soft white metal layer on SCM440, which is mainly used for shaft and bolt. On laser deposition process, the laser power and powder feed rate and laser head speed factors are controlled to find out the optimal conditions. We also measure hardness using micro Vickers, analyze FE-SEM (Field Emission Scanning Electron Microscope) and EDS (Energy Dispersive Spectroscopy) to study the mechanical properties and surface characteristics with various parameters change. Furthermore, this paper suggests the optimum condition of laser cladding deposition to apply in industrial fields. This work was supported by the Industrial Innovation Project of the Korea Evaluation Institute of Industrial Technology (KEIT) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (Research no. 10051653).

Keywords: laser deposition, bearing, white metal, mechanical properties

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Authors: Anika Chebrolu

Abstract:

Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

Abstract:

Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Sandra Cecilia Muhirirwe, Bart Van Der Bruggen, Violet Kisakye

Abstract:

Economic analysis of Rainwater harvesting (RWH) systems is vital in search of a cost-effective solution to water unreliability, especially in low-income countries. There is little literature focusing on the financial aspects of RWH for dairy farmers. The main purpose was to assess the economic viability of rainwater harvesting for diary framers in the Rwenzori region. The study focused on the use of rainwater harvesting systems from the rooftop and collection in above surface tanks. Daily rainfall time series for 12 years was obtained across nine gauging stations. The daily water balance equation was used for optimal sizing of the tank. Economic analysis of the investment was carried out based on the life cycle costs and the accruing benefits for the period of 15 years. Roof areas were varied from 75m2 as the minimum required area to 500m2 while maintaining the same number of cattle and keeping the daily water demand constant. The results show that the required rainwater tank sizes are very large and may be impractical to install due to the strongly varying terrain and the initial cost of investment. In all districts, there is a significant reduction of the volume of the required tank with an increasing collection area. The results further show that increasing the collection area has a minor effect on reducing the required tank size. Generally, for all rainfall areas, the reliability increases with an increase in the roof area. The results indicate that 100% reliability can only be realized with very large collection areas that are impractical to install. The estimated benefits outweigh the cost of investment. The Present Net Value shows that the investment is economically viable and investment with a short payback of a maximum of 3 years for all the time series in the study area.

Keywords: dairy cattle, optimisation, rainwater harvesting, economic analysis

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Authors: Vytautas Galvanauskas, Rimvydas Simutis, Donatas Levisauskas, Vykantas Grincas, Renaldas Urniezius

Abstract:

The paper deals with model-based development and implementation of efficient control strategies for recombinant protein synthesis in fed-batch E.coli cultivation processes. Based on experimental data, a kinetic dynamic model for cultivation process was developed. This model was used to determine substrate feeding strategies during the cultivation. The proposed feeding strategy consists of two phases – biomass growth phase and recombinant protein production phase. In the first process phase, substrate-limited process is recommended when the specific growth rate of biomass is about 90-95% of its maximum value. This ensures reduction of glucose concentration in the medium, improves process repeatability, reduces the development of secondary metabolites and other unwanted by-products. The substrate limitation can be enhanced to satisfy restriction on maximum oxygen transfer rate in the bioreactor and to guarantee necessary dissolved carbon dioxide concentration in culture media. In the recombinant protein production phase, the level of substrate limitation and specific growth rate are selected within the range to enable optimal target protein synthesis rate. To account for complex process dynamics, to efficiently exploit the oxygen transfer capability of the bioreactor, and to maintain the required dissolved oxygen concentration, adaptive control algorithms for dissolved oxygen control have been proposed. The developed model-based control strategies are useful in scale-up of cultivation processes and accelerate implementation of innovative biotechnological processes for industrial applications.

Keywords: adaptive algorithms, model-based control, recombinant E. coli, scale-up of bioprocesses

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Authors: Khanyisile Mnguni, Muthukrishnavellaisamy Kumarasamy, Jeff C. Smithers

Abstract:

Umgeni Water is a water board that supplies most parts of KwaZulu Natal with bulk portable water. Currently, Umgeni Water is running its distribution system based on required reservoir levels and demands and does not consider the energy cost at different times of the day, number of pump switches, and background leakages. Including these constraints can reduce operational cost, energy usage, leakages, and increase performance. Optimising pump schedules can reduce energy usage and costs while adhering to hydraulic and operational constraints. Umgeni Water has installed an online hydraulic software, WaterNet Advisor, that allows running different operational scenarios prior to implementation in order to optimise the distribution system. This study will investigate operation scenarios using optimisation techniques and WaterNet Advisor for a local water distribution system. Based on studies reported in the literature, introducing pump scheduling optimisation can reduce energy usage by approximately 30% without any change in infrastructure. Including tariff structures in an optimisation problem can reduce pumping costs by 15%, while including leakages decreases cost by 10%, and pressure drop in the system can be up to 12 m. Genetical optimisation algorithms are widely used due to their ability to solve nonlinear, non-convex, and mixed-integer problems. Other methods such as branch and bound linear programming have also been successfully used. A suitable optimisation method will be chosen based on its efficiency. The objective of the study is to reduce energy usage, operational cost, and leakages, and the feasibility of optimal solution will be checked using the Waternet Advisor. This study will provide an overview of the optimisation of hydraulic networks and progress made to date in multi-objective optimisation for a selected sub-system operated by Umgeni Water.

Keywords: energy usage, pump scheduling, WaterNet Advisor, leakages

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Authors: Rolland Epafras Fanggidae

Abstract:

The impact of climate change such as natural disasters, crop failures, increasing crop pests, bad gisi on children and other impacts, will indirectly affect education, health, food safety, as well as the economy. The impact of climate change has put a man in a situation of vulnerability, which was powerless to meet the minimum requirements, it is in close contact with poverty. When talking about poverty, the most plausible is female. The role of women in Indonesia, particularly in East Nusa Tenggara in Domestic aktifity very central and dominant. This makes Indonesian woman can say "outstanding actor in the face of climate change mitigation and adaptation and applying local knowledge", but still ignored when women based on gender division of work entrusted role in domestic activities. Similarly, in public activity is an extension of the Domestic example, trading activity in the market lele / mama. Although men are also affected by climate change, but most feel is female. From the above problems, it can be said that Indonesia's commitment has not been followed by optimal empowerment of women's role in addressing climate change, it is necessary to learn to know how the role of women in the face of climate change impacts that hit on her role as a woman, a housewife or head of the family and will be input in order to determine how women find a solution to tackle the problem of climate change. This study focuses on the efforts made by women cope with the impacts of climate change, efforts by the government, empowerment model used in Playing the impact of climate change. The container with the formulation of the title "The Role of Women in Climate Change Impact in Kupang district". Where the assessment in use types Research mix Methods combination of quantitative research and qualitative research. While the location of the research conducted in Kupang regency, East Nusa Tenggara, namely: District of East Kupang is a district granary in Kupang district. Subdistrict West Kupang, especially Tablolong Village is the center of seaweed cultivation in Kupang district.

Keywords: climate change, women, women's roles, gender, family

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Authors: Vongsathorn Ngampuak, Yutachai Chookaew, Wipawee Dejtisakdi

Abstract:

Dunaliella salina has great potential as a system for generating commercially valuable products, including beta-carotene, pharmaceuticals, and biofuels. Our goal is to improve this potential by enhancing growth rate and other properties of D. salina under optimal growth conditions. We used ethyl methane sulfonate (EMS) to generate random mutants in D. salina KU11, a strain classified in Thailand. In a preliminary experiment, we first treated D. salina cells with 0%, 0.8%, 1.0%, 1.2%, 1.44% and 1.66% EMS to generate a killing curve. After that, we randomly picked 30 candidates from approximately 300 isolated survivor colonies from the 1.44% EMS treatment (which permitted 30% survival) as an initial test of the mutant screen. Among the 30 survivor lines, we found that 2 strains (mutant #17 and #24) had significantly improved growth rates and cell number accumulation at stationary phase approximately up to 1.8 and 1.45 fold, respectively, 2 strains (mutant #6 and #23) had significantly decreased growth rates and cell number accumulation at stationary phase approximately down to 1.4 and 1.35 fold, respectively, while 26 of 30 lines had similar growth rates compared with the wild type control. We also analyzed cell size for each strain and found there was no significant difference comparing all mutants with the wild type. In addition, mutant #24 had shown an increase of biomass accumulation approximately 1.65 fold compared with the wild type strain on day 5 that was entering early stationary phase. From these preliminary results, it could be feasible to identify D. salina mutants with significant improved growth rate, cell accumulation and biomass production compared to the wild type for the further study; this makes it possible to improve this microorganism as a platform for biotechnology application.

Keywords: Dunaliella salina, ethyl methyl sulfonate, growth rate, biomass

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Authors: Chao-Ton Su, Li-Fei Chen

Abstract:

The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

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Authors: I. Kade Wiratama

Abstract:

As a result of the significant growth of wind turbines in size, blade load control has become the main challenge for large wind turbines. Many advanced techniques have been investigated aiming at developing control devices to ease blade loading. Amongst them, trailing edge flaps have been proven as effective devices for load alleviation. The present study aims at investigating the potential benefits of flaps in enhancing the energy capture capabilities rather than blade load alleviation. A software tool is especially developed for the aerodynamic simulation of wind turbines utilising blades equipped with flaps. As part of the aerodynamic simulation of these wind turbines, the control system must be also simulated. The simulation of the control system is carried out via solving an optimisation problem which gives the best value for the controlling parameter at each wind turbine run condition. Developing a genetic algorithm optimisation tool which is especially designed for wind turbine blades and integrating it with the aerodynamic performance evaluator, a design optimisation tool for blades equipped with flaps is constructed. The design optimisation tool is employed to carry out design case studies. The results of design case studies on wind turbine AWT 27 reveal that, as expected, the location of flap is a key parameter influencing the amount of improvement in the power extraction. The best location for placing a flap is at about 70% of the blade span from the root of the blade. The size of the flap has also significant effect on the amount of enhancement in the average power. This effect, however, reduces dramatically as the size increases. For constant speed rotors, adding flaps without re-designing the topology of the blade can improve the power extraction capability as high as of about 5%. However, with re-designing the blade pretwist the overall improvement can be reached as high as 12%.

Keywords: flaps, design blade, optimisation, simulation, genetic algorithm, WTAero

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Authors: Mohamed Aboelghar, Ayman Abou Hadid, Usama Albehairy, Asmaa Khater

Abstract:

Sustainable agricultural development of the desert areas of Egypt under the pressure of irrigation water scarcity is a significant national challenge. Existing water harvesting techniques on the northwest coast of Egypt do not ensure the optimal use of rainfall for agricultural purposes. Basin-scale hydrology potentialities were studied to investigate how available annual rainfall could be used to increase agricultural production. All data related to agricultural production included in the form of geospatial layers. Thematic classification of Sentinal-2 imagery was carried out to produce the land cover and crop maps following the (FAO) system of land cover classification. Contour lines and spot height points were used to create a digital elevation model (DEM). Then, DEM was used to delineate basins, sub-basins, and water outlet points using the Soil and Water Assessment Tool (Arc SWAT). Main soil units of the study area identified from Land Master Plan maps. Climatic data collected from existing official sources. The amount of precipitation, surface water runoff, potential, and actual evapotranspiration for the years (2004 to 2017) shown as results of (Arc SWAT). The land cover map showed that the two tree crops (olive and fig) cover 195.8 km2 when herbaceous crops (barley and wheat) cover 154 km2. The maximum elevation was 250 meters above sea level when the lowest one was 3 meters below sea level. The study area receives a massive variable amount of precipitation; however, water harvesting methods are inappropriate to store water for purposes.

Keywords: water catchements, remote sensing, GIS, sustainable agricultural development

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Authors: Muhammad Umer, Aishwariya Giri, Umaiyma Rakha

Abstract:

Mimicked from the humpback whale flippers, the application of tubercle technology is seen to be particularly advantageous at high angles of attack. This particular advantage is of paramount importance when it comes to structures producing lift at high angles of attack. This characteristic of the technology makes it ideal for horizontal stabilizers and selecting the same as the subject of study to identify and exploit the advantage highlighted by researchers on airfoils, this project aims in establishing a foundation for the application of the bio-mimicked technology on an existing aircraft. Using a baseline and 2 tubercle configuration integrated models, the project targets to achieve the twin aim of highlighting the possibility and merits over the base model and also choosing the right configuration in providing the best characteristic suitable for high angles of attack. To facilitate this study, the required models are generated using Solidworks followed by trials in a virtual aerodynamic environment using Fluent in Ansys for resolving the project objectives. Following a structured plan, the aim is to initially identify the advantages mathematically and then selecting the optimal configuration, simulate the end configuration at angles mimicking the actual operation envelope for the particular structure. Upon simulating the baseline configuration at various angles of attack, the stall angle was determined to be 22 degrees. Thus, the tubercle configurations will be simulated and compared at 4 different angles of attacks: 0, 10, 20, and 24. Further, after providing the optimum configuration of horizontal stabilizers, this study aims at the integration of aircraft structure so that the results better imply the end deliverables of real life application. This draws the project scope closer at this point into longitudinal static stability considerations and improvements in the manoeuvrability characteristics. The objective of the study is to achieve a complete overview ready for real life application with marked benefits obtainable from bio morphing of the tubercle technology.

Keywords: flow simulation, horizontal stabilizer, stability enhancement, tubercle

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