Search results for: multi cloud storage

Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

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This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

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Authors: Jon Ajuria, Edurne Redondo, Roman Mysyk, Eider Goikolea

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Hybrid capacitor configurations are now of increasing interest to overcome the current energy limitations of supercapacitors entirely based on non-Faradaic charge storage. Among them, Li-ion capacitors including a negative battery-type lithium intercalation electrode and a positive capacitor-type electrode have achieved tremendous progress and have gone up to commercialization. Inexpensive electrode materials from renewable sources have recently received increased attention since cost is a persistently major criterion to make supercapacitors a more viable energy solution, with electrode materials being a major contributor to supercapacitor cost. Additionally, Na-ion battery chemistries are currently under development as less expensive and accessible alternative to Li-ion based battery electrodes. In this work, we are presenting both lithium and sodium ion capacitor (LIC & NIC) entirely based on electrodes prepared from carbon materials derived from recycled olive pits. Yearly, around 1 million ton of olive pit waste is generated worldwide, of which a third originates in the Spanish olive oil industry. On the one hand, olive pits were pyrolized at different temperatures to obtain a low specific surface area semigraphitic hard carbon to be used as the Li/Na ion intercalation (battery-type) negative electrode. The best hard carbon delivers a total capacity of 270mAh/g vs Na/Na+ in 1M NaPF6 and 350mAh/g vs Li/Li+ in 1M LiPF6. On the other hand, the same hard carbon is chemically activated with KOH to obtain high specific surface area -about 2000 m2g-1- activated carbon that is further used as the ion-adsorption (capacitor-type) positive electrode. In a voltage window of 1.5-4.2V, activated carbon delivers a specific capacity of 80 mAh/g vs. Na/Na+ and 95 mAh/g vs. Li/Li+ at 0.1A /g. Both electrodes were assembled in the same hybrid cell to build a LIC/NIC. For comparison purposes, a symmetric EDLC supercapacitor cell using the same activated carbon in 1.5M Et4NBF4 electrolyte was also built. Both LIC & NIC demonstrates considerable improvements in the energy density over its EDLC counterpart, delivering a maximum energy density of 110Wh/Kg at a power density of 30W/kg AM and a maximum power density of 6200W/Kg at an energy density of 27 Wh/Kg in the case of NIC and a maximum energy density of 110Wh/Kg at a power density of 30W/kg and a maximum power density of 18000W/Kg at an energy density of 22 Wh/Kg in the case of LIC. In conclusion, our work demonstrates that the same biomass waste can be adapted to offer a hybrid capacitor/battery storage device overcoming the limited energy density of corresponding double layer capacitors.

Keywords: hybrid supercapacitor, Na-Ion capacitor, supercapacitor, Li-Ion capacitor, EDLC

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Authors: Dieter Veldsman, Theo Heyns Veldsman

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The knowledge economy demands an organisation that is flexible, adaptable and able to navigate the ever-changing environment. This fast-paced environment has however resulted in an organizational landscape that battles to engage employees, retain top talent and create meaningful work for its members. In the knowledge economy, the concept of organizational identity has become an important consideration as organisations aim to create a compelling and inviting narrative for all stakeholders across the business value chain. Values are often seen as the behavioural framework that informs organisational culture, yet often values are perceived to be inauthentic and misaligned with the true character or identity of the organisation and how it is perceived by different role players. This paper focuses on exploring the relationship between organisational identity and value systems by focusing on a case study within a multi-national organisation within South Africa. The paper evaluates the implementation of mixed methods OD approach that gathered collaborative inputs of more than 4500 employees who participated in crafting the newly established values system post a retrenchment process. The paper will evaluate the relationship between the newly crafted value system and the identity of the organisation as described by various internal and external stakeholders in order to explore potential alignment, dissonance and key insights into understanding the relationship between organisational identity and values. The case study will be reported from the perspective of an OD consultant who supported the transformation process over a period of 8 months and aims to provide key insights into values and identity alignment within knowledge economy organisations. From a practical perspective, the paper provides insights into how values are created, perceived and lived within organisations and the impact on employee engagement and culture.

Keywords: culture, organisational development, organisational identity, values

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Authors: Khadidja Belbachir, Hafida Belbachir

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subsequently the expansion of the physical supports storage and the needs ceaseless to accumulate several data, the sequential algorithms of associations’ rules research proved to be ineffective. Thus the introduction of the new parallel versions is imperative. We propose in this paper, a parallel version of a sequential algorithm “Partition”. This last is fundamentally different from the other sequential algorithms, because it scans the data base only twice to generate the significant association rules. By consequence, the parallel approach does not require much communication between the sites. The proposed approach was implemented for an experimental study. The obtained results, shows a great reduction in execution time compared to the sequential version and Count Distributed algorithm.

Keywords: association rules, distributed data mining, partition, parallel algorithms

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Authors: Dahia Chibouti, Benoit Trouette, Eric Chenier

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With the development of micro-electro-mechanical systems (MEMS), understanding fluid flow and heat transfer at the micrometer scale is crucial. In the case where the flow characteristic length scale is narrowed to around ten times the mean free path of gas molecules, the classical fluid mechanics and energy equations are still valid in the bulk flow, but particular attention must be paid to the gas/solid interface boundary conditions. Indeed, in the vicinity of the wall, on a thickness of about the mean free path of the molecules, called the Knudsen layer, the gas molecules are no longer in local thermodynamic equilibrium. Therefore, macroscopic models based on the continuity of velocity, temperature and heat flux jump conditions must be applied at the fluid/solid interface to take this non-equilibrium into account. Although these macroscopic models are widely used, the assumptions on which they depend are not necessarily verified in realistic cases. In order to get rid of these assumptions, simulations at the molecular scale are carried out to study how molecule interaction with walls can change the fluid flow and heat transfers at the vicinity of the walls. The developed approach is based on a kind of heterogeneous multi-scale method: micro-domains overlap the continuous domain, and coupling is carried out through exchanges of information between both the molecular and the continuum approaches. In practice, molecular dynamics describes the fluid flow and heat transfers in micro-domains while the Navier-Stokes and energy equations are used at larger scales. In this framework, two kinds of micro-simulation are performed: i) in bulk, to obtain the thermo-physical properties (viscosity, conductivity, ...) as well as the equation of state of the fluid, ii) close to the walls to identify the relationships between the slip velocity and the shear stress or between the temperature jump and the normal temperature gradient. The coupling strategy relies on an implicit formulation of the quantities extracted from micro-domains. Indeed, using the results of the molecular simulations, a Bayesian regression is performed in order to build continuous laws giving both the behavior of the physical properties, the equation of state and the slip relationships, as well as their uncertainties. These latter allow to set up a learning strategy to optimize the number of micro simulations. In the present contribution, the first results regarding this coupling associated with the learning strategy are illustrated through parametric studies of convergence criteria, choice of basis functions and noise of input data. Anisothermic flows of a Lennard Jones fluid in micro-channels are finally presented.

Keywords: multi-scale, microfluidics, micro-channel, hybrid approach, coupling

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Authors: Reza Sadeghi

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Carbon dioxide treatment is one of the new methods for storage pest control. It can be used to replace chemical approaches. In the present study, the mortalities of Oryzaephilus mercator as the key pest of stored products, especially nuts, were studied after being exposed to different CO2 pressures (0.1, 0.2, 0.3, 0.4 and 0.5 bar) within 24 hours. The mortality percentages of O. mercator increased with an increase in CO2 pressure. The results obtained from experiments on the qualitative characteristics of the studied dates through the sensory test revealed that CO2 pressures did not affect their aroma, color, crispness, firmness, and overall acceptance. Therefore, it could be concluded that the atmospheric CO2 gas provided a cost-effective and environmentally friendly method for controlling the insect pests of pumpkin seed, besides preserving their sensory and quality properties.

Keywords: carbon dioxide, control, seed, qualitative characteristics

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Authors: Kadir Gök

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In this study, a vacuum system was developed for orthopedic drilling processes, and the most efficient processing parameters were determined using statistical analysis of temperature rise. A reverse engineering technique was used to obtain a 3D model of the chip vacuum system, and the obtained point cloud data was transferred to Solidworks software in STL format. An experimental design method was performed by selecting different parameters and their levels, such as RPM, feed rate, and drill bit diameter, to determine the most efficient processing parameters in temperature rise using ANOVA. Additionally, the bone chip-vacuum device was developed and performed successfully to collect the whole chips and fragments in the bone drilling experimental tests, and the chip-collecting device was found to be useful in removing overheating from the drilling zone. The effects of processing parameters on the temperature levels during the chip-vacuuming were determined, and it was found that bone chips and fractures can be used as autograft and allograft for tissue engineering. Overall, this study provides significant insights into the development of a vacuum system for orthopedic drilling processes and the use of bone chips and fractures in tissue engineering applications.

Keywords: vacuum system, orthopedic drilling, temperature rise, bone chips

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Authors: Ammar Nimer Natsheh

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Chaos control is used to design a controller that is able to eliminate the chaotic behaviour of nonlinear dynamic systems that experience such phenomena. The paper describes the control of the bifurcation behaviour of a parallel-connected DC-DC buck-boost converter used to provide an interface between energy storage batteries and photovoltaic (PV) arrays as renewable energy sources. The paper presents a delayed feedback control scheme in a module converter comprises two identical buck-boost circuits and operates in the continuous-current conduction mode (CCM). MATLAB/SIMULINK simulation results show the effectiveness and robustness of the scheme.

Keywords: chaos, bifurcation, DC-DC Buck-Boost Converter, Delayed Feedback Control

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Authors: Chevonne Reynolds, Robert J. Fletcher, Jr, Celine M. Carneiro, Nicole Jennings, Alison Ke, Michael C. LaScaleia, Mbhekeni B. Lukhele, Mnqobi L. Mamba, Muzi D. Sibiya, James D. Austin, Cebisile N. Magagula, Themba’alilahlwa Mahlaba, Ara Monadjem, Samantha M. Wisely, Robert A. McCleery

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A key challenge for the developing world is reconciling biodiversity conservation with the growing demand for food. In these regions, agriculture is typically interspersed among other land-uses creating heterogeneous landscapes. A primary hypothesis for promoting biodiversity in agricultural landscapes is the habitat heterogeneity hypothesis. While there is evidence that landscape heterogeneity positively influences biodiversity, the application of this hypothesis is hindered by a need to determine which components of landscape heterogeneity drive these effects and at what spatial scale(s). Additionally, whether diverse taxonomic groups are similarly affected is central for determining the applicability of this hypothesis as a general conservation strategy in agricultural mosaics. Two major components of landscape heterogeneity are compositional and configurational heterogeneity. Disentangling the roles of each component is important for biodiversity conservation because each represents different mechanisms underpinning variation in biodiversity. We identified a priori independent gradients of compositional and configurational landscape heterogeneity within an extensive agricultural mosaic in north-eastern Swaziland. We then tested how bird, dung beetle, ant and meso-carnivore diversity responded to compositional and configurational heterogeneity across six different spatial scales. To determine if a general trend could be observed across multiple taxa, we also tested which component and spatial scale was most influential across all taxonomic groups combined, Compositional, not configurational, heterogeneity explained diversity in each taxonomic group, with the exception of meso-carnivores. Bird and ant diversity was positively correlated with compositional heterogeneity at fine spatial scales < 1000 m, whilst dung beetle diversity was negatively correlated to compositional heterogeneity at broader spatial scales > 1500 m. Importantly, because of these contrasting effects across taxa, there was no effect of either component of heterogeneity on the combined taxonomic diversity at any spatial scale. The contrasting responses across taxonomic groups exemplify the difficulty in implementing effective conservation strategies that meet the requirements of diverse taxa. To promote diverse communities across a range of taxa, conservation strategies must be multi-scaled and may involve different strategies at varying scales to offset the contrasting influences of compositional heterogeneity. A diversity of strategies are likely key to conserving biodiversity in agricultural mosaics, and we have demonstrated that a landscape management strategy that only manages for heterogeneity at one particular scale will likely fall short of management objectives.

Keywords: agriculture, biodiversity, composition, configuration, heterogeneity

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Authors: Carolyn Hatch, Laurent Simon

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Urban mobility and the transportation industry are undergoing a transformation, shifting from an auto production-consumption model that has dominated since the early 20th century towards new forms of personal and shared multi-modality [1]. This is shaped by key forces such as climate change, which has induced a shift in production and consumption patterns and efforts to decarbonize and improve transport services through, for instance, the integration of vehicle automation, electrification and mobility sharing [2]. Advanced innovation practices and platforms for experimentation and validation of new mobility products and services that are increasingly complex and multi-stakeholder-oriented are shaping this new world of mobility. Transportation hubs – such as airports - are emblematic of these disruptive forces playing out in the mobility industry. Airports are emerging as the core of innovation ecosystems on and around contemporary mobility issues, and increasingly recognized as complex public/private nodes operating in many societal dimensions [3,4]. These include urban development, sustainability transitions, digital experimentation, customer experience, infrastructure development and data exploitation (for instance, airports generate massive and often untapped data flows, with significant potential for use, commercialization and social benefit). Yet airport innovation practices have not been well documented in the innovation literature. This paper addresses this gap by proposing a model of airport innovation that aims to equip airport stakeholders to respond to these new and complex innovation needs in practice. The methodology involves: 1 – a literature review bringing together key research and theory on airport innovation management, open innovation and innovation ecosystems in order to evaluate airport practices through an innovation lens; 2 – an international benchmarking of leading airports and their innovation practices, including such examples as Aéroports de Paris, Schipol in Amsterdam, Changi in Singapore, and others; and 3 – semi-structured interviews with airport managers on key aspects of organizational practice, facilitated through a close partnership with the Airport Council International (ACI), a major stakeholder in this research project. Preliminary results find that the most successful airports are those that have shifted to a multi-stakeholder, platform ecosystem model of innovation. The recent entrance of new actors in airports (Google, Amazon, Accor, Vinci, Airbnb and others) have forced the opening of organizational boundaries to share and exchange knowledge with a broader set of ecosystem players. This has also led to new forms of governance and intermediation by airport actors to connect complex, highly distributed knowledge, along with new kinds of inter-organizational collaboration, co-creation and collective ideation processes. Leading airports in the case study have demonstrated a unique capacity to force traditionally siloed activities to “think together”, “explore together” and “act together”, to share data, contribute expertise and pioneer new governance approaches and collaborative practices. In so doing, they have successfully integrated these many disruptive change pathways and forced their implementation and coordination towards innovative mobility outcomes, with positive societal, environmental and economic impacts. This research has implications for: 1 - innovation theory, 2 - urban and transport policy, and 3 - organizational practice - within the mobility industry and across the economy.

Keywords: airport management, ecosystem, innovation, mobility, platform, transport hubs

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Authors: N. V. Kazmiruk, Y. R. Nartsissov

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Phosphate activated glutaminase (GA, E.C. 3.5.1.2) plays a key role in glutamine/glutamate homeostasis in mammalian brain, catalyzing the hydrolytic deamidation of glutamine to glutamate and ammonium ions. GA is mainly localized in mitochondria, where it has the catalytically active form on the inner mitochondrial membrane (IMM) and the other soluble form, which is supposed to be dormant. At present time, the exact localization of the membrane glutaminase active site remains a controversial and an unresolved issue. The first hypothesis called c-side localization suggests that the catalytic site of GA faces the inter-membrane space and products of the deamidation reaction have immediate access to cytosolic metabolism. According to the alternative m-side localization hypothesis, GA orients to the matrix, making glutamate and ammonium available for the tricarboxylic acid cycle metabolism in mitochondria directly. In our study, we used a multi-compartment kinetic approach to simulate metabolism of glutamate and glutamine in the astrocytic cytosol and mitochondria. We used physiologically important ratio between the concentrations of glutamine inside the matrix of mitochondria [Glnₘᵢₜ] and glutamine in the cytosol [Glncyt] as a marker for precise functioning of the system. Since this ratio directly depends on the mitochondrial glutamine carrier (MGC) flow parameters, key observation was to investigate the dependence of the [Glnmit]/[Glncyt] ratio on the maximal velocity of MGC at different initial concentrations of mitochondrial glutamate. Another important task was to observe the similar dependence at different inhibition constants of the soluble GA. The simulation results confirmed the experimental c-side localization hypothesis, in which the glutaminase active site faces the outer surface of the IMM. Moreover, in the case of such localization of the enzyme, a 3-fold decrease in ammonium production was predicted.

Keywords: glutamate metabolism, glutaminase, kinetic approach, mitochondrial membrane, multi-compartment modeling

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Authors: John Ahluwalia

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As an affluent first-world nation, Canada took swift and comprehensive action during the outbreak of the SARS-CoV-2 (COVID-19) pandemic compared to other countries in the same socio-economic cohort. The United States has stumbled to overcome obstacles most developed nations have faced, which has led to significantly more per capita cases and deaths. The initial outbreaks of COVID-19 occurred in the US and Canada within days of each other and posed similar potentially catastrophic threats to public health, the economy, and governmental stability. On a macro level, events that take place in the US have a direct impact on Canada. For example, both countries tend to enter and exit economic recessions at approximately the same time, they are each other’s largest trading partners, and their currencies are inexorably linked. Variables intrinsic to Canada’s national infrastructure have been instrumental in the country’s efforts to flatten the curve of COVID-19 cases and deaths. Canada’s coordinated multi-level governmental effort has allowed it to create and enforce policies related to COVID-19 at both the national and provincial levels. Canada’s policy of universal health care is another variable. Health care and public health measures are enforced on a provincial level, and it is within each province’s jurisdiction to dictate standards for public safety based on scientific evidence. Rather than introducing confusion and the possibility of competition for resources such as PPE and vaccines, Canada’s multi-level chain of government authority has provided consistent policies supporting national public health and local delivery of medical care. This paper will demonstrate that the coordinated efforts on provincial and federal levels have been the linchpin in Canada’s relative success in containing the deadly spread of the COVID-19 virus.

Keywords: COVID-19, canada, GIS, geospatial analysis

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

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We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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Authors: Anukul K. Thakur, Ram Bilash Choudhary, Mandira Majumder

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In this technologically driven world, it is requisite to develop better, faster and smaller electronic devices for various applications to keep pace with fast developing modern life. In addition, it is also required to develop sustainable and clean sources of energy in this era where the environment is being threatened by pollution and its severe consequences. Supercapacitor has gained tremendous attention in the recent years because of its various attractive properties such as it is essentially maintenance-free, high specific power, high power density, excellent pulse charge/discharge characteristics, exhibiting a long cycle-life, require a very simple charging circuit and safe operation. Binary and ternary composites of conducting polymers with carbon and other layered transition metal dichalcogenides have shown tremendous progress in the last few decades. Compared with bulk conducting polymer, these days conducting polymers have gained more attention because of their high electrical conductivity, large surface area, short length for the ion transport and superior electrochemical activity. These properties make them very suitable for several energy storage applications. On the other hand, carbon materials have also been studied intensively, owing to its rich specific surface area, very light weight, excellent chemical-mechanical property and a wide range of the operating temperature. These have been extensively employed in the fabrication of carbon-based energy storage devices and also as an electrode material in supercapacitors. Incorporation of carbon materials into the polymers increases the electrical conductivity of the polymeric composite so formed due to high electrical conductivity, high surface area and interconnectivity of the carbon. Further, polymeric composites based on layered transition metal dichalcogenides such as molybdenum disulfide (MoS2) are also considered important because they are thin indirect band gap semiconductors with a band gap around 1.2 to 1.9eV. Amongst the various 2D materials, MoS2 has received much attention because of its unique structure consisting of a graphene-like hexagonal arrangement of Mo and S atoms stacked layer by layer to give S-Mo-S sandwiches with weak Van-der-Waal forces between them. It shows higher intrinsic fast ionic conductivity than oxides and higher theoretical capacitance than the graphite.

Keywords: supercapacitor, layered transition-metal dichalcogenide, conducting polymer, ternary, carbon

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Authors: Loong Qing Zhe, Foo Jing Heng

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A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.

Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)

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Authors: Usman Asif, Klaus Schmidt

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In recent years, the development of alternate fuel vehicles has helped to reduce carbon emissions worldwide. As the number of vehicles will continue to increase in the future, the energy demand will also increase. Therefore, we must consider automotive technologies that are efficient and less harmful to the environment in the long run. Battery Electric Vehicles (BEVs) have gained popularity in recent years because of their lower maintenance, lower fuel costs, and lower carbon emissions. Nevertheless, BEVs show several disadvantages, such as slow charging times and lower range than traditional combustion-powered vehicles. These factors keep many people from switching to BEVs. The authors of this research believe that these limitations can be overcome by using fuel cell technology. Fuel cell technology converts chemical energy into electrical energy from hydrogen power and therefore serves as fuel to power the motor and thus replacing heavy lithium batteries that are expensive and hard to recycle. Also, in contrast to battery-powered electric vehicle technology, Fuel Cell Electric Vehicles (FCEVs) offer higher ranges and lower fuel-up times and therefore are more competitive with electric vehicles. However, FCEVs have not gained the same popularity as electric vehicles due to stringent legal frameworks, underdeveloped infrastructure, high fuel transport, and storage costs plus the expense of fuel cell technology itself. This research will focus on the legal frameworks for hydrogen-powered vehicles, and how a change in these policies may affect and improve hydrogen fueling infrastructure and lower hydrogen transport and storage costs. These policies may also facilitate reductions in fuel cell technology costs. In order to attain a better framework, a number of countries have developed conceptual roadmaps. These roadmaps have set out a series of objectives to increase the access of FCEVs to their respective markets. This research will specifically focus on policies in Japan, Europe, and the USA in their attempt to shape the automotive industry of the future. The researchers also suggest additional policies that may help to accelerate the advancement of FCEVs to mass-markets. The approach was to provide a solid literature review using resources from around the globe. After a subsequent analysis and synthesis of this review, the authors concluded that in spite of existing legal challenges that have hindered the advancement of fuel-cell technology in the automobile industry in the past, new initiatives that enhance and advance the very same technology in the future are underway.

Keywords: fuel cell electric vehicles, fuel cell technology, legal frameworks, policies and regulations

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Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

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Authors: Abderrahmane Diaf, Assia Cherfa, Lamia Karadaniz

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Multiple tray solar distillation offers an interesting alternative for small-scale desalination and production high quality distilled water at a competitive cost using solar energy. In this work, we present indoor/outdoor trial performance data of our multiple tray solar distillation as well as the results of cost estimation analysis.

Keywords: solar desalination, tray distillation, multi-étages solaire, solar distillation

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Authors: Un Hwa Choe, Jong Hyon Choe, Yong Jun Kim

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The aim of this study was to effectively remove Fe2+ by using ozone microbubbles in bottled mineral water to prevent sediment from occurring during storage and increase shelf life. By considering the characteristics of mineral water with low solubility of ozone and high CO2 content, a suitable ozone injection step was chosen and a new mineral water treatment method using microbubbles was proposed. As a result of the treatment of the bottled mineral water with ozone microbubbles, the iron ion concentration was reduced from 0.14 mg/L to 0.01 mg/L, and the shelf life increased to 360 days. During the treatment, the concentrations of K+ and Na+ were almost unchanged, and the deposition time was reduced to one-third compared to the natural oxidation.

Keywords: CO₂-rich mineral water, ozone-micro bubble, shelf life, bottled mineral water, water treatment

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Authors: G. Kermarrec, J. Hartmann

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Spline surfaces are a major representation of freeform surfaces in the computer-aided graphic industry and were recently introduced in the field of geodesy for processing point clouds from terrestrial laser scanner (TLS). The surface fitting consists of approximating a trustworthy mathematical surface to a large numbered 3D point cloud. The standard B-spline surfaces lack of local refinement due to the tensor-product construction. The consequences are oscillating geometry, particularly in the transition from low-to-high curvature parts for scattered point clouds with missing data. More economic alternatives in terms of parameters on how to handle point clouds with a huge amount of observations are the recently introduced T-splines. As long as the partition of unity is guaranteed, their computational complexity is low, and they are flexible. T-splines are implemented in a commercial package called Rhino, a 3D modeler which is widely used in computer aided design to create and animate NURBS objects. We have applied T-splines surface fitting to terrestrial laser scanner point clouds from a bridge under load and a sheet pile wall with noisy observations. We will highlight their potential for modelling details with high trustworthiness, paving the way for further applications in terms of deformation analysis.

Keywords: deformation analysis, surface modelling, terrestrial laser scanner, T-splines

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Authors: S. Periyadharshini, K. Ramkumar, S. Jayalalitha, M. GuruPrasath, R. Manikandan

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This paper presents a formulation and solution for industrial load management and product grade problem. The formulation is created using linear programming technique thereby optimizing the electricity cost by scheduling the loads satisfying the process, storage, time zone and production constraints which will create an impact of reducing maximum demand and thereby reducing the electricity cost. Product grade problem is formulated using integer linear programming technique of optimization using lingo software and the results show that overall increase in profit margin. In this paper, time of use tariff is utilized and this technique will provide significant reductions in peak electricity consumption.

Keywords: cement industries, integer programming, optimal formulation, objective function, constraints

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Authors: Adam N. Bell, Sarina J. Ergas, Michael Nystrom, Nathan P. Brennan, Kevan L. Main

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Integrated Multi-Trophic Aquaculture systems (IMTA) have the potential to improve the sustainability of seafood production, generate organic fertilizer and feed, remove waste discharges and reduce energy use. IMTA can include periphyton biofilters where algae and microbes grow on surfaces, along with caught detritus and amphipods. Periphyton biofilters provide many advantages: nitrification, denitrification, primary production and ecological diversity. The goal of this study was to determine how biofilter hydraulic residence time (τ) effects periphyton biomass production, dissolved oxygen (DO) and nutrient removal. A pilot scale recirculating aquaculture system (RAS) was designed, constructed and operated at different hydraulic residence times (τ= 1, 2, 4, 6, 8 hours per tank). For each τ, a conservative tracer study was conducted to investigate system hydrodynamics. Data on periphyton weights, pH, nitrogen species, phosphorus, temperature and DO were collected. The tracer study for τ =1 hour revealed that the normalized time < τ, indicating short-circuiting. Periphyton biomass production rate was relatively unaffected by τ (R_e<1 for all τ). Average ammonia nitrogen removal was > 75% for all trials. Nitrate and nitrite did not accumulate in the RAS for τ≥4 hours due to enhanced denitrification in anoxic zones. For τ≥4 hours DO concentration was at a maximum of 4 mg L-1 after 14:00, and decreased to 0 mg L-1 during nighttime. At τ=1 hour, the RAS stayed > 2 mg L-1 and DO was more evenly distributed. For the validation trial, the culture tank was stocked with Centropomus undecimalis (common snook) and the system was operated at τ= 1 hr. Preliminary results showed that a RAS with an integrated periphyton biofilter could support fish health with low nutrient concentrations DO > 6 mg L-1.

Keywords: sustainable aquaculture, resource recovery, nitrogen, microalgae, hydrodynamics, integrated multi-trophic aquaculture

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Authors: Yalçın Kılıç, İbrahim Kani

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In recent years, interest in the synthesis of coordination compounds has greatly increased due to various application areas (such as catalysis, gas storage, luminescence). Dicarboxylic acids are often used in the synthesis of metal complexes. Bis-thiosalicylate derivative ligands contribute to the synthesis of structures of crystal engineering interest, as they can have both rigid and flexible properties. In addition, these ligands have great potential in terms of catalytic applications with the sulfur and oxygen donor atoms in their structures. In this study, we synthesized a Cu(II) complex [Cu(tsaxyl)(phen)2]•CH3OH (where tsaxyl = 2,2'-(1,2-phylenebis(methylene))bis(sulfanedyl)dibenzoate, phen = 1,10-phenantroline) and characterized through X-ray crystallography. The catalytic activities of Cu(II) complex on oxidation of ethylbenzene, cyclohexane, diphenylmethane, p-xylene were performed in acetonitrile with t-BuOOH as the source of oxygen.

Keywords: complex, crystallography, catalysis, oxidation

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Authors: Roman Knizek, Denisa Karhankova, Ludmila Fridrichova

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For their exceptional properties nanofibers, respectively, nanofiber layers are achieving an increasingly wider range of uses. Nowadays nanofibers are used mainly in the field of air filtration where they are removing submicron particles, bacteria, and viruses. Their efficiency is not changed in time, and the power consumption is much lower than that of electrically charged filters. Nanofibers are primarily used for converting and storage of energy in both air and liquid filtration, in food and packaging, protecting the environment, but also in health care which is made possible by their newly discovered properties. However, a major problem of the nanofiber layer is practically zero abrasion resistance; it is, therefore, necessary to laminate the nanofiber layer with another suitable material. Unfortunately, lamination of nanofiber layers is a major problem since the nanofiber layer contains small pores through which it is very difficult for adhesion to pass through. Therefore, there is still only a small percentage of products with these unique fibers 5.

Keywords: nanofiber layer, nanomembrane, lamination, electrospinning

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Authors: Sam Weber, Deepak Mishra, Susan Wilde, Elizabeth Kramer

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The frequency and severity of cyanobacteria harmful blooms (CyanoHABs) have been increasing over time, with point and non-point source eutrophication and shifting climate paradigms being blamed as the primary culprits. Excessive nutrients, warm temperatures, quiescent water, and heavy and less regular rainfall create more conducive environments for CyanoHABs. CyanoHABs have the potential to produce a spectrum of toxins that cause gastrointestinal stress, organ failure, and even death in humans and animals. To promote enhanced, proactive CyanoHAB management, risk modeling using geospatial tools can act as predictive mechanisms to supplement current CyanoHAB monitoring, management and mitigation efforts. The risk maps would empower water managers to focus their efforts on high risk water bodies in an attempt to prevent CyanoHABs before they occur, and/or more diligently observe those waterbodies. For this research, exploratory spatial data analysis techniques were used to identify the strongest predicators for CyanoHAB blooms based on remote sensing-derived cyanobacteria cell density values for 771 waterbodies in the Georgia Piedmont and landscape characteristics of their watersheds. In-situ datasets for cyanobacteria cell density, nutrients, temperature, and rainfall patterns are not widely available, so free gridded geospatial datasets were used as proxy variables for assessing CyanoHAB risk. For example, the percent of a watershed that is agriculture was used as a proxy for nutrient loading, and the summer precipitation within a watershed was used as a proxy for water quiescence. Cyanobacteria cell density values were calculated using atmospherically corrected images from the European Space Agency’s Sentinel-2A satellite and multispectral instrument sensor at a 10-meter ground resolution. Seventeen explanatory variables were calculated for each watershed utilizing the multi-petabyte geospatial catalogs available within the Google Earth Engine cloud computing interface. The seventeen variables were then used in a multiple linear regression model, and the strongest predictors of cyanobacteria cell density were selected for the final regression model. The seventeen explanatory variables included land cover composition, winter and summer temperature and precipitation data, topographic derivatives, vegetation index anomalies, and soil characteristics. Watershed maximum summer temperature, percent agriculture, percent forest, percent impervious, and waterbody area emerged as the strongest predictors of cyanobacteria cell density with an adjusted R-squared value of 0.31 and a p-value ~ 0. The final regression equation was used to make a normalized cyanobacteria cell density index, and a Jenks Natural Break classification was used to assign waterbodies designations of low, medium, or high risk. Of the 771 waterbodies, 24.38% were low risk, 37.35% were medium risk, and 38.26% were high risk. This study showed that there are significant relationships between free geospatial datasets representing summer maximum temperatures, nutrient loading associated with land use and land cover, and the area of a waterbody with cyanobacteria cell density. This data analytics approach to CyanoHAB risk assessment corroborated the literature-established environmental triggers for CyanoHABs, and presents a novel approach for CyanoHAB risk mapping in waterbodies across the greater southeastern United States.

Keywords: cyanobacteria, land use/land cover, remote sensing, risk mapping

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Authors: Yu-Hsuan Chang, Jian-Hao Su, Chen-Yu Chen, Wei-Mon Yan

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In this work, the experimental measurement was applied to examine the membrane type and flow field design on the performance of a planar membrane humidifier. The performance indexes were used to evaluate the planar membrane humidifier. The performance indexes of the membrane humidifier include the dew point approach temperature (DPAT), water recovery ratio (WRR), water flux (J) and pressure loss (P). The experiments contain mainly three parts. In the first part, a single membrane humidifier was tested using different flow field under different dry-inlet temperatures. The measured results show that the dew point approach temperature decreases with increasing the depth of flow channel at the same width of flow channel. However, the WRR and J reduce with an increase in the dry air-inlet temperature. The pressure loss tests indicate that pressure loss decreases with increasing the hydraulic diameter of flow channel, resulting from an increase in Darcy friction. Owing to the comparison of humidifier performances and pressure losses, the flow channel of width W=1 and height H=1.5 was selected as the channel design of the multi-membrane humidifier in the second part of experiment. In the second part, the multi-membrane humidifier was used to evaluate the humidification performance under different relative humidity and flow rates. The measurement results indicate that the humidifier at both lower temperature and relative humidity of inlet dry air have higher DPAT but lower J and WRR. In addition, the counter flow approach has better mass and heat transfer performance than the parallel flow approach. Moreover, the effects of dry air temperature, relative humidity and humidification approach are not significant to the pressure loss in the planar membrane humidifier. For the third part, different membranes were tested in this work in order to find out which kind membrane is appropriate for humidifier.

Keywords: water management, planar membrane humidifier, heat and mass transfer, pressure loss, PEM fuel cell

Procedia PDF Downloads 199

Authors: Eiko Takaoka, Yoshiyuki Fukushima, Koichiro Hirose, Tadashi Hasegawa

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Although all high school students in Japan are required to learn informatics, many of them do not learn this topic sufficiently. In response to this situation, we propose a support package for high school informatics classes. To examine what students learned and if they sufficiently understood the context of the lessons, a questionnaire survey was distributed to 186 students. We analyzed the results of the questionnaire and determined the weakest units, which were “basic computer configuration” and “memory and secondary storage”. We then developed a package for teaching these units. We propose that our package be applied in high school classrooms.

Keywords: computer science unplugged, computer science outreach, high school curriculum, experimental evaluation

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Authors: C. Busuioc, S. Jinga, E. Pavel

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Optical lithography is a key technique in the development of sub-5 nm patterns for the semiconductor industry. We have already reported that the best results obtained with respect to direct laser writing process on active media, such as glass-ceramics, are achieved only when the energy of the laser radiation is absorbed in discrete quantities. Further, we need to clarify the role of active centers concentration in silver nanocrystals natural generation, as well as in fluorescent rare-earth nanostructures formation. As a consequence, samples with different compositions were prepared. SEM, AFM, TEM and STEM investigations were employed in order to demonstrate that few nm width lines can be written on fluorescent photosensitive glass-ceramics, these being efficient absorbers. Moreover, we believe that the experimental data will lead to the best choice in terms of active centers amount, laser power and glass-ceramic matrix.

Keywords: glass-ceramics, 3D laser writing, optical disks, data storage

Procedia PDF Downloads 290

Authors: Bryan M. Baltazar, Marjorie V. Remolador, Klathea H. Sevilla, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Biomass energy is a traditional source of sustainable energy, which has been widely used in developing countries. The Philippines, specifically Central Luzon, has an abundant source of biomass. Hence, it could supply abundant agricultural residues (rice husks), as feedstock in a biomass power plant. However, locating a potential site for biomass development is a complex process which involves different factors, such as physical, environmental, socio-economic, and risks that are usually diverse and conflicting. Moreover, biomass distribution is highly dispersed geographically. Thus, this study develops an integrated method combining Geographical Information Systems (GIS) and methods for energy planning; Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP), for locating suitable site for biomass power plant development in Central Luzon, Philippines by considering different constraints and factors. Using MCDA, a three level hierarchy of factors and constraints was produced, with corresponding weights determined by experts by using AHP. Applying the results, a suitability map for Biomass power plant development in Central Luzon was generated. It showed that the central part of the region has the highest potential for biomass power plant development. It is because of the characteristics of the area such as the abundance of rice fields, with generally flat land surfaces, accessible roads and grid networks, and low risks to flooding and landslide. This study recommends the use of higher accuracy resource maps, and further analysis in selecting the optimum site for biomass power plant development that would account for the cost and transportation of biomass residues.

Keywords: analytic hierarchy process, biomass energy, GIS, multi-criteria decision analysis, site suitability analysis

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Authors: Mina Malak Zakaria Henin

Abstract:

The finite detail evaluation of magnetic fields in electromagnetic devices shows that the machine cores revel in extraordinary flux patterns consisting of alternating and rotating fields. The rotating fields are generated in different configurations variety, among circular and elliptical, with distinctive ratios between the fundamental and minor axes of the flux locus. Experimental measurements on electrical metal uncovered one-of-a-kind flux patterns that divulge distinctive magnetic losses in the samples below the test. Therefore, electric machines require unique interest throughout the core loss calculation technique to bear in mind the flux styles. In this look, a circular rotational unmarried sheet tester is employed to measure the middle losses in the electric-powered metallic pattern of M36G29. The sample becomes exposed to alternating fields, circular areas, and elliptical fields with axis ratios of zero.2, zero. Four, 0.6 and 0.8. The measured statistics changed into applied on 6-4 switched reluctance motors at 3 distinctive frequencies of interest to the industry 60 Hz, 400 Hz, and 1 kHz. The effects reveal an excessive margin of error, which can arise at some point in the loss calculations if the flux pattern difficulty is overlooked. The mistake in exceptional components of the gadget associated with considering the flux styles may be around 50%, 10%, and a couple of at 60Hz, 400Hz, and 1 kHz, respectively. The future paintings will focus on the optimization of gadget geometrical shape, which has a primary effect on the flux sample on the way to decrease the magnetic losses in system cores.

Keywords: converters, electric machines, MEA (more electric aircraft), PES (power electronics systems) synchronous machine, vector control Multi-machine/ Multi-inverter, matrix inverter, Railway tractionalternating core losses, finite element analysis, rotational core losses

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