Search results for: models error comparison

Authors: Anirudh Lahiri

Abstract:

Neuromorphic computing, inspired by the intricate operations of biological neural networks, offers a revolutionary approach to overcoming the limitations of traditional computing architectures. This research proposes the integration of spintronics with neuromorphic systems, aiming to enhance computational performance, scalability, and energy efficiency. Traditional computing systems, based on the Von Neumann architecture, struggle with scalability and efficiency due to the segregation of memory and processing functions. In contrast, the human brain exemplifies high efficiency and adaptability, processing vast amounts of information with minimal energy consumption. This project explores the use of spintronics, which utilizes the electron's spin rather than its charge, to create more energy-efficient computing systems. Spintronic devices, such as magnetic tunnel junctions (MTJs) manipulated through spin-transfer torque (STT) and spin-orbit torque (SOT), offer a promising pathway to reducing power consumption and enhancing the speed of data processing. The integration of these devices within a neuromorphic framework aims to replicate the efficiency and adaptability of biological systems. The research is structured into three phases: an exhaustive literature review to build a theoretical foundation, laboratory experiments to test and optimize the theoretical models, and iterative refinements based on experimental results to finalize the system. The initial phase focuses on understanding the current state of neuromorphic and spintronic technologies. The second phase involves practical experimentation with spintronic devices and the development of neuromorphic systems that mimic synaptic plasticity and other biological processes. The final phase focuses on refining the systems based on feedback from the testing phase and preparing the findings for publication. The expected contributions of this research are twofold. Firstly, it aims to significantly reduce the energy consumption of computational systems while maintaining or increasing processing speed, addressing a critical need in the field of computing. Secondly, it seeks to enhance the learning capabilities of neuromorphic systems, allowing them to adapt more dynamically to changing environmental inputs, thus better mimicking the human brain's functionality. The integration of spintronics with neuromorphic computing could revolutionize how computational systems are designed, making them more efficient, faster, and more adaptable. This research aligns with the ongoing pursuit of energy-efficient and scalable computing solutions, marking a significant step forward in the field of computational technology.

Keywords: material science, biological engineering, mechanical engineering, neuromorphic computing, spintronics, energy efficiency, computational scalability, synaptic plasticity.

Procedia PDF Downloads 17

Authors: El Ghazi Safae, Cherkaoui Mounia

Abstract:

Within companies, emotions have been forgotten as key elements of successful management systems. Seen as factors which disturb judgment, make reckless acts or affect negatively decision-making. Since management systems were influenced by the Taylorist worker image, that made the work regular and plain, and considered employees as executing machines. However, recently, in globalized economy characterized by a variety of uncertainties, emotions are proved as useful elements, even necessary, to attend high-level management. The work of Elton Mayo and Kurt Lewin reveals the importance of emotions. Since then emotions start to attract considerable attention. These studies have shown that emotions influence, directly or indirectly, many organization processes. For example, the quality of interpersonal relationships, job satisfaction, absenteeism, stress, leadership, performance and team commitment. Emotions became fundamental and indispensable to individual yield and so on to management efficiency. The idea that a person potential is associated to Intellectual Intelligence, measured by the IQ as the main factor of social, professional and even sentimental success, was the main problematic that need to be questioned. The literature on emotional intelligence has made clear that success at work does not only depend on intellectual intelligence but also other factors. Several researches investigating emotional intelligence impact on performance showed that emotionally intelligent managers perform more, attain remarkable results, able to achieve organizational objectives, impact the mood of their subordinates and create a friendly work environment. An improvement in the emotional intelligence of managers is therefore linked to the professional development of the organization and not only to the personal development of the manager. In this context, it would be interesting to question the importance of emotional intelligence. Does it impact organizational performance? What is the importance of emotional intelligence and how it impacts organizational performance? The literature highlighted that measurement and conceptualization of emotional intelligence are difficult to define. Efforts to measure emotional intelligence have identified three models that are more prominent: the mixed model, the ability model, and the trait model. The first is considered as cognitive skill, the second relates to the mixing of emotional skills with personality-related aspects and the latter is intertwined with personality traits. But, despite strong claims about the importance of emotional intelligence in the workplace, few studies have empirically examined the impact of emotional intelligence on organizational performance, because even though the concept of performance is at the heart of all evaluation processes of companies and organizations, we observe that performance remains a multidimensional concept and many authors insist about the vagueness that surrounds the concept. Given the above, this article provides an overview of the researches related to emotional intelligence, particularly focusing on studies that investigated the impact of emotional intelligence on organizational performance to contribute to the emotional intelligence literature and highlight its importance and show how it impacts companies’ performance.

Keywords: emotions, performance, intelligence, firms

Procedia PDF Downloads 95

Authors: Prateek Goyal, Archini Paruthi, Superb K. Misra

Abstract:

Contamination of water resources has been a major concern, which has drawn attention to the need to develop new material models for treatment of effluents. Existing conventional waste water treatment methods remain ineffective sometimes and uneconomical in terms of remediating contaminants like heavy metal ions (mercury, arsenic, lead, cadmium and chromium); organic matter (dyes, chlorinated solvents) and high salt concentration, which makes water unfit for consumption. We believe that nanotechnology based strategy, where we use nanoparticles as a tool to remediate a class of pollutants would prove to be effective due to its property of high surface area to volume ratio, higher selectivity, sensitivity and affinity. In recent years, scientific advancement has been made to study the application of photocatalytic (ZnO, TiO2 etc.) nanomaterials and magnetic nanomaterials in remediating contaminants (like heavy metals and organic dyes) from water/wastewater. Our study focuses on the synthesis and monitoring remediation efficiency of ZnO, Fe3O4 and Fe3O4 coated ZnO nanoparticulate system for the removal of heavy metals and dyes simultaneously. Multitude of ZnO nanostructures (spheres, rods and flowers) using multiple routes (microwave & hydrothermal approach) offers a wide range of light active photo catalytic property. The phase purity, morphology, size distribution, zeta potential, surface area and porosity in addition to the magnetic susceptibility of the particles were characterized by XRD, TEM, CPS, DLS, BET and VSM measurements respectively. Further on, the introduction of crystalline defects into ZnO nanostructures can also assist in light activation for improved dye degradation. Band gap of a material and its absorbance is a concrete indicator for photocatalytic activity of the material. Due to high surface area, high porosity and affinity towards metal ions and availability of active surface sites, iron oxide nanoparticles show promising application in adsorption of heavy metal ions. An additional advantage of having magnetic based nanocomposite is, it offers magnetic field responsive separation and recovery of the catalyst. Therefore, we believe that ZnO linked Fe3O4 nanosystem would be efficient and reusable. Improved photocatalytic efficiency in addition to adsorption for environmental remediation has been a long standing challenge, and the nano-composite system offers the best of features which the two individual metal oxides provide for nanoremediation.

Keywords: adsorption, nanocomposite, nanoremediation, photocatalysis

Procedia PDF Downloads 232

Authors: Lachin Mikjtarnejad, Mohsen Farzaneh

Abstract:

Various microbes, such as fungi and bacteria species, are naturally found in the fruit microbiota, and some of them act as a pathogen and result in fruit rot. Among non-pathogenic microbes, yeasts (single-celled microorganisms belonging to the fungi kingdom) can colonize fruit tissues and interact with them without causing any damage to them. Although yeasts are part of the plant microbiota, there is little information about their interactions with plants in comparison with bacteria and filamentous fungi. According to several existing studies, some yeasts can colonize different plant species and have the biological control ability to suppress some of the plant pathogens. It means those specific yeast-colonized plants are more resistant to some plant pathogens. The major objective of the present investigation is to isolate yeast strains from apple fruit and screen their ability to control Penicillium expansum, the causal agent of blue mold of fruits. In the present study, psychrotrophic and epiphytic yeasts were isolated from apple fruits that were stored at low temperatures (0–1°C). Totally, 42 yeast isolates were obtained and identified by molecular analysis based on genomic sequences of the D1/D2 and ITS1/ITS4 regions of their rDNA. All isolated yeasts were primarily screened by' in vitro dual culture assay against P. expansum by measuring the fungus' relative growth inhibition after 10 days of incubation. The results showed that the mycelial growth of P. expansum was reduced between 41–53% when challenged by promising yeast strains. The isolates with the strongest antagonistic activity belonged to Metschnikowia pulcherrima A13, Rhodotorula mucilaginosa A41, Leucosporidium Scottii A26, Aureobasidium pullulans A19, Pichia guilliermondii A32, Cryptococcus flavescents A25, and Pichia kluyveri A40. The results of seven superior isolates to inhibit blue mold decay on fruit showed that isolates A. pullulans A19, L. scottii A26, and Pi. guilliermondii A32 could significantly reduce the fruit rot and decay with 26 mm, 22 mm and 20 mm zone diameter, respectively, compared to the control sample with 43 mm. Our results show Pi. guilliermondii strain A13 was the most effective yeast isolates in inhibiting P. expansum on apple fruits. In addition, various biological control mechanisms of promising biological isolates against blue mold have been evaluated to date, including competition for nutrients and space, production of volatile metabolites, reduction of spore germination, production of siderophores and production of extracellular lytic enzymes such as chitinase and β-1,3-glucanase. However, the competition for nutrients and the ability to inhibit P. expansum spore growth have been introduced as the prevailing mechanisms among them. Accordingly, in our study, isolates A13, A41, A40, A25, A32, A19 and A26 inhibited the germination of P. expansum, whereas isolates A13 and A19 were the strongest inhibitors of P. expansum mycelia growth, causing 89.13% and 81.75 % reduction in the mycelial surface, respectively. All the promising isolates produced chitinase and β-1,3-glucanase after 3, 5 and 7 days of cultivation. Finally, based on our findings, we are proposing that, Pi. guilliermondiias as an effective biocontrol agent and alternative to chemical fungicides to control the blue mold of apple fruit.

Keywords: yeast, yeast enzymes, biocontrol, post harvest diseases

Procedia PDF Downloads 111

Authors: N. Garrós, P. Bustos, N. Beirampour, R. Mohammadi, M. Mallandrich, A.C. Calpena, H. Colom

Abstract:

Atopic dermatitis (AD) is a persistent skin condition characterized by chronic inflammation caused by an autoimmune response. It is a prevalent clinical issue that requires continual treatment to enhance the patient's quality of life. Systemic therapy often involves the use of glucocorticoids or immunosuppressants to manage symptoms. Our objective was to create and assess topical liposomal formulations containing Baricitinib (BNB), a reversible inhibitor of Janus-associated kinase (JAK), which is involved in various immune responses. These formulations were intended to address flare-ups and improve treatment outcomes for AD. We created three distinct liposomal formulations by combining different amounts of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC), cholesterol (CHOL), and ceramide (CER): (i) pure POPC, (ii) POPC mixed with CHOL (at a ratio of 8:2, mol/mol), and (iii) POPC mixed with CHOL and CER (at a ratio of 3.6:2.4:4.0 mol/mol/mol). We conducted various tests to determine the formulations' skin tolerance, irritancy capacity, and their ability to cause erythema and edema on altered skin. We also assessed the transepidermal water loss (TEWL) and skin hydration of rabbits to evaluate the efficacy of the formulations. Histological analysis, the HET-CAM test, and the modified Draize test were all used in the evaluation process. The histological analysis revealed that liposome POPC and POPC:CHOL avoided any damage to the tissues structures. The HET-CAM test showed no irritation effect caused by any of the three liposomes, and the modified Draize test showed a good Draize score for erythema and edema. Liposome POPC effectively counteracted the impact of xylol on the skin, and no erythema or edema was observed during the study. TEWL values were constant for all the liposomes with similar values to the negative control (within the range 8 - 15 g/h·m2, which means a healthy value for rabbits), whereas the positive control showed a significant increase. The skin hydration values were constant and followed the trend of the negative control, while the positive control showed a steady increase during the tolerance study. In conclusion, the developed formulations containing BNB exhibited no harmful or irritating effects, they did not demonstrate any irritant potential in the HET-CAM test and liposomes POPC and POPC:CHOL did not cause any structural alteration according to the histological analysis. These positive findings suggest that additional research is necessary to evaluate the efficacy of these liposomal formulations in animal models of the disease, including mutant animals. Furthermore, before proceeding to clinical trials, biochemical investigations should be conducted to better understand the mechanisms of action involved in these formulations.

Keywords: baricitinib, HET-CAM test, histological study, JAK inhibitor, liposomes, modified draize test

Procedia PDF Downloads 82

Authors: Biao Sun, Tejas Bhatelia, Vishnu Pareek, Ranjeet Utikar, Moses Tadé

Abstract:

Additive manufacturing (AM), commonly known as 3D printing, with the continuing advances in parallel processing and computational modeling, has created a paradigm shift (with significant radical thinking) in the design and operation of chemical processing plants, especially LNG plants. With the rising energy demands, environmental pressures, and economic challenges, there is a continuing industrial need for disruptive technologies such as AM, which possess capabilities that can drastically reduce the cost of manufacturing and operations of chemical processing plants in the future. However, the continuing challenge for 3D printing is its lack of adaptability in re-designing the process plant equipment coupled with the non-existent theory or models that could assist in selecting the optimal candidates out of the countless potential fabrications that are possible using AM. One of the most common packings used in the LNG process is structured packing in the packed column (which is a unit operation) in the process. In this work, we present an example of an optimum strategy for the application of AM to this important unit operation. Packed columns use a packing material through which the gas phase passes and comes into contact with the liquid phase flowing over the packing, typically performing the necessary mass transfer to enrich the products, etc. Structured packing consists of stacks of corrugated sheets, typically inclined between 40-70° from the plane. Computational Fluid Dynamics (CFD) was used to test and model various geometries to study the governing hydrodynamic characteristics. The results demonstrate that the costly iterative experimental process can be minimized. Furthermore, they also improve the understanding of the fundamental physics of the system at the multiscale level. SpiroPak, patented by Curtin University, represents an innovative structured packing solution currently at a technology readiness level (TRL) of 5~6. This packing exhibits remarkable characteristics, offering a substantial increase in surface area while significantly enhancing hydrodynamic and mass transfer performance. Recent studies have revealed that SpiroPak can reduce pressure drop by 50~70% compared to commonly used commercial packings, and it can achieve 20~50% greater mass transfer efficiency (particularly in CO2 absorption applications). The implementation of SpiroPak has the potential to reduce the overall size of columns and decrease power consumption, resulting in cost savings for both capital expenditure (CAPEX) and operational expenditure (OPEX) when applied to retrofitting existing systems or incorporated into new processes. Furthermore, pilot to large-scale tests is currently underway to further advance and refine this technology.

Keywords: Additive Manufacturing (AM), 3D printing, Computational Fluid Dynamics (CFD, structured packing (SpiroPak)

Procedia PDF Downloads 54

Authors: Corneliu-Ioan Dimitriu, Gheorghe Frățilă

Abstract:

Romania and Bulgaria have high rates of road deaths per million inhabitants. Directive (EU) 2019/1936, known as the RISM Directive, has been transposed into national law by each Member State. The research focuses on the amendments made to Romanian legislation through Government Ordinance no. 3/2022, which aims to improve road safety management on infrastructure. The aim of the research is two-fold: to sensitize the Romanian Government and decision-making entities to develop an integrated and competitive management system and to establish a safe and proactive mobility system that ensures efficient and safe roads. The research includes a critical analysis of European and Romanian legislation, as well as subsequent normative acts related to road infrastructure safety management. Public data from European Union and national authorities, as well as data from the Romanian Road Authority-ARR and Traffic Police database, are utilized. The research methodology involves comparative analysis, criterion analysis, SWOT analysis, and the use of GANTT and WBS diagrams. The Excel tool is employed to process the road accident databases of Romania and Bulgaria. Collaboration with Bulgarian specialists is established to identify common road infrastructure safety issues. The research concludes that the legislative changes have resulted in a relaxation of road safety management in Romania, leading to decreased control over certain management procedures. The amendments to primary and secondary legislation do not meet the current safety requirements for road infrastructure. The research highlights the need for legislative changes and strengthened administrative capacity to enhance road safety. Regional cooperation and the exchange of best practices are emphasized for effective road infrastructure safety management. The research contributes to the theoretical understanding of road infrastructure safety management by analyzing legislative changes and their impact on safety measures. It highlights the importance of an integrated and proactive approach in reducing road accidents and achieving the "zero deaths" objective set by the European Union. Data collection involves accessing public data from relevant authorities and using information from the Romanian Road Authority-ARR and Traffic Police database. Analysis procedures include critical analysis of legislation, comparative analysis of transpositions, criterion analysis, and the use of various diagrams and tools such as SWOT, GANTT, WBS, and Excel. The research addresses the effectiveness of legislative changes in road infrastructure safety management in Romania and the impact on control over management procedures. It also explores the need for strengthened administrative capacity and regional cooperation in addressing road safety issues. The research concludes that the legislative changes made in Romania have not strengthened road safety management and emphasize the need for immediate action, legislative amendments, and enhanced administrative capacity. Collaboration with Bulgarian specialists and the exchange of best practices are recommended for effective road infrastructure safety management. The research contributes to the theoretical understanding of road safety management and provides valuable insights for policymakers and decision-makers in Romania.

Keywords: management, road infrastructure safety, legislation, amendments, collaboration

Procedia PDF Downloads 68

Authors: A. G. Akhundov

Abstract:

Issues of obtaining unbiased data on the status of pipeline systems of oil- and oil product transportation become especially important when laying and operating pipelines under severe nature and climatic conditions. The essential attention is paid here to researching exogenous processes and their impact on linear facilities of the pipeline system. Reliable operation of pipelines under severe nature and climatic conditions, timely planning and implementation of compensating measures are only possible if operation conditions of pipeline systems are regularly monitored, and changes of permafrost soil and hydrological operation conditions are accounted for. One of the main reasons for emergency situations to appear is the geodynamic factor. Emergency situations are proved by the experience to occur within areas characterized by certain conditions of the environment and to develop according to similar scenarios depending on active processes. The analysis of natural and technical systems of main pipelines at different stages of monitoring gives a possibility of making a forecast of the change dynamics. The integration of GIS technologies, traditional means of geotechnical monitoring (in-line inspection, geodetic methods, field observations), and remote methods (aero-visual inspection, aero photo shooting, air and ground laser scanning) provides the most efficient solution of the problem. The united environment of geo information system (GIS) is a comfortable way to implement the monitoring system on the main pipelines since it provides means to describe a complex natural and technical system and every element thereof with any set of parameters. Such GIS enables a comfortable simulation of main pipelines (both in 2D and 3D), the analysis of situations and selection of recommendations to prevent negative natural or man-made processes and to mitigate their consequences. The specifics of such systems include: a multi-dimensions simulation of facilities in the pipeline system, math modelling of the processes to be observed, and the use of efficient numeric algorithms and software packets for forecasting and analyzing. We see one of the most interesting possibilities of using the monitoring results as generating of up-to-date 3D models of a facility and the surrounding area on the basis of aero laser scanning, data of aerophotoshooting, and data of in-line inspection and instrument measurements. The resulting 3D model shall be the basis of the information system providing means to store and process data of geotechnical observations with references to the facilities of the main pipeline; to plan compensating measures, and to control their implementation. The use of GISs for geotechnical monitoring of pipeline systems is aimed at improving the reliability of their operation, reducing the probability of negative events (accidents and disasters), and at mitigation of consequences thereof if they still are to occur.

Keywords: databases, 3D GIS, geotechnical monitoring, pipelines, laser scaning

Procedia PDF Downloads 183

Authors: Shrabani Ghosh

Abstract:

Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

Procedia PDF Downloads 95

Authors: Dominik Kowitzke

Abstract:

Housing constructions have direct and indirect environmental impacts especially caused by soil sealing and gray energy consumption related to the use of construction materials. Accordingly, the German government introduced regulations limiting additional annual soil sealing. At the same time, in many regions like metropolitan areas the demand for further housing is high and of current concern in the media and politics. It is argued that meeting this demand by making better use of the existing housing supply is more sustainable than the construction of new housing units. In this context, targeting the phenomenon of so-called over the housing of empty nest households seems worthwhile to investigate for its potential to free living space and thus, reduce the need for new housing constructions and related environmental harm. Over housing occurs if no space adjustment takes place in household lifecycle stages when children move out from home and the space formerly created for the offspring is from then on under-utilized. Although in some cases the housing space consumption might actually meet households’ equilibrium preferences, frequently space-wise adjustments to the living situation doesn’t take place due to transaction or information costs, habit formation, or government intervention leading to increasing costs of relocations like real estate transfer taxes or tenant protection laws keeping tenure rents below the market price. Moreover, many detached houses are not long-term designed in a way that freed up space could be rent out. Findings of this research based on socio-economic survey data, indeed, show a significant difference between the living space of empty nest and a comparison group of households which never had children. The approach used to estimate the average difference in living space is a linear regression model regressing the response variable living space on a two-dimensional categorical variable distinguishing the two groups of household types and further controls. This difference is assumed to be the under-utilized space and is extrapolated to the total amount of empty nests in the population. Supporting this result, it is found that households that move, despite market frictions impairing the relocation, after children left their home tend to decrease the living space. In the next step, only for areas with tight housing markets in Germany and high construction activity, the total under-utilized space in empty nests is estimated. Under the assumption of full substitutability of housing space in empty nests and space in new dwellings in these locations, it is argued that in a perfect market with empty nest households consuming their equilibrium demand quantity of housing space, dwelling constructions in the amount of the excess consumption of living space could be saved. This, on the other hand, would prevent environmental harm quantified in carbon dioxide equivalence units related to average constructions of detached or multi-family houses. This study would thus provide information on the amount of under-utilized space inside dwellings which is missing in public data and further estimates the external effect of over housing in environmental terms.

Keywords: empty nests, environment, Germany, households, over housing

Procedia PDF Downloads 163

Authors: Jean Pierre Kabue, Emma Meader, Afsatou Ndama Traore, Paul R. Hunter, Natasha Potgieter

Abstract:

Norovirus is now considered the most common cause of outbreaks of nonbacterial gastroenteritis. Limited data are available for Norovirus strains in Africa, especially in rural and peri-urban areas. Despite the excessive burden of diarrhea disease in developing countries, Norovirus infections have been to date mostly reported in developed countries. There is a need to investigate intensively the role of viral agents associated with diarrhea in different settings in Africa continent. To determine the prevalence and genetic diversity of Norovirus strains circulating in the rural communities in the Limpopo Province, South Africa and investigate the genetic relationship between Norovirus strains, a cross-sectional study was performed on human stools collected from rural communities. Between July 2014 and April 2015, outpatient children under 5 years of age from rural communities of Vhembe District, South Africa, were recorded for the study. A total of 303 stool specimens were collected from those with diarrhea (n=253) and without (n=50) diarrhea. NoVs were identified using real-time one-step RT-PCR. Partial Sequence analyses were performed to genotype the strains. Phylogenetic analyses were performed to compare identified NoVs genotypes to the worldwide circulating strains. Norovirus detection rate was 41.1% (104/253) in children with diarrhea. There was no significant difference (OR=1.24; 95% CI 0.66-2.33) in Norovirus detection between symptomatic and asymptomatic children. Comparison of the median CT values for NoV in children with diarrhea and without diarrhea revealed significant statistical difference of estimated GII viral load from both groups, with a much higher viral burden in children with diarrhea. To our knowledge, this is the first study reporting on the differences in estimated viral load of GII and GI NoV positive cases and controls. GII.Pe (n=9) were the predominant genotypes followed by GII.Pe/GII.4 Sydney 2012 (n=8) suspected recombinant and GII.4 Sydney 2012 variants(n=7). Two unassigned GII.4 variants and an unusual RdRp genotype GII.P15 were found. With note, the rare GIIP15 identified in this study has a common ancestor with GIIP15 strain from Japan previously reported as GII/untypeable recombinant strain implicated in a gastroenteritis outbreak. To our knowledge, this is the first report of this unusual genotype in the African continent. Though not confirmed predictive of diarrhea disease in this study, the high detection rate of NoV is an indication of subsequent exposure of children from rural communities to enteric pathogens due to poor sanitation and hygiene practices. The results reveal that the difference between asymptomatic and symptomatic children with NoV may possibly be related to the NoV genogroups involved. The findings emphasize NoV genetic diversity and predominance of GII.Pe/GII.4 Sydney 2012, indicative of increased NoV activity. An uncommon GII.P15 and two unassigned GII.4 variants were also identified from rural settings of the Vhembe District/South Africa. NoV surveillance is required to help to inform investigations into NoV evolution, and to support vaccine development programmes in Africa.

Keywords: asymptomatic, common, outpatients, norovirus genetic diversity, sporadic gastroenteritis, South African rural communities, symptomatic

Procedia PDF Downloads 178

Authors: William Kerua

Abstract:

The PNG University of Technology (Unitech) has mandatory access to teaching, research and extension education. Given such function, the Agriculture Department has established the ‘South Pacific Institute of Sustainable Agriculture and Rural Development (SPISARD)’ in 2004. SPISARD is established as a vehicle to improve farming systems practiced in selected villages by undertaking pluralistic extension method through ‘Educational Institutional Approach’. Unlike other models, SPISARD’s educational institutional approach stresses on improving the whole farming systems practiced in a holistic manner and has a two-fold focus. The first is to understand the farming communities and improve the productivity of the farming systems in a sustainable way to increase income, improve nutrition and food security as well as livelihood enhancement trainings. The second is to enrich the Department’s curriculum through teaching, research, extension and getting inputs from farming community. SPISARD has established number of model villages in various provinces in Papua New Guinea (PNG) and with many positive outcome and success stories. Adaption of ‘educational institutional approach’ thus binds research, extension and training into one package with the use of students and academic staff through model village establishment in delivering development and extension to communities. This centre (SPISARD) coordinates the activities of the model village programs and linkages. The key to the development of the farming systems is establishing and coordinating linkages, collaboration, and developing partnerships both within and external institutions, organizations and agencies. SPISARD has a six-point step strategy for the development of sustainable agriculture and rural development. These steps are (i) establish contact and identify model villages, (ii) development of model village resource centres for research and trainings, (iii) conduct baseline surveys to identify problems/needs of model villages, (iv) development of solution strategies, (v) implementation and (vi) evaluation of impact of solution programs. SPISARD envisages that the farming systems practiced being improved if the villages can be made the centre of SPISARD activities. Therefore, SPISARD has developed a model village approach to channel rural development. The model village when established become the conduit points where teaching, training, research, and technology transfer takes place. This approach is again different and unique to the existing ones, in that, the development process take place in the farmers’ environment with immediate ‘real time’ feedback mechanisms based on the farmers’ perspective and satisfaction. So far, we have developed 14 model villages and have conducted 75 trainings in 21 different areas/topics in 8 provinces to a total of 2,832 participants of both sex. The aim of these trainings is to directly participate with farmers in the pursuit to improving their farming systems to increase productivity, income and to secure food security and nutrition, thus to improve their livelihood.

Keywords: development, educational institutional approach, livelihood improvement, sustainable agriculture

Procedia PDF Downloads 148

Authors: Z. Gharaee

Abstract:

Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

Procedia PDF Downloads 149

Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

Abstract:

The U.S. Federal Emergency Management Agency (FEMA) developed flood maps based on experts’ experience and estimates of the probability of flooding. Current flood-risk models evaluate flood risk with regional and subjective measures without impact from torrential rain and nuisance flooding at the neighborhood level. Nuisance flooding occurs in small areas in the community, where a few streets or blocks are routinely impacted. This type of flooding event occurs when torrential rainstorm combined with high tide and sea level rise temporarily exceeds a given threshold. In South Florida, this threshold is 1.7 ft above Mean Higher High Water (MHHW). The National Weather Service defines torrential rain as rain deposition at a rate greater than 0.3-inches per hour or three inches in a single day. Data from the Florida Climate Center, 1970 to 2020, shows 371 events with more than 3-inches of rain in a day in 612 months. The purpose of this research is to develop a data-driven method to determine comprehensive analytical damage-avoidance criteria that account for nuisance flood events at the single-family home level. The method developed uses the Failure Mode and Effect Analysis (FMEA) method from the American Society of Quality (ASQ) to estimate the Damage Avoidance (DA) preparation for a 1-day 100-year storm. The Consequence of Nuisance Flooding (CoNF) is estimated from community mitigation efforts to prevent nuisance flooding damage. The Probability of Nuisance Flooding (PoNF) is derived from the frequency and duration of torrential rainfall causing delays and community disruptions to daily transportation, human illnesses, and property damage. Urbanization and population changes are related to the U.S. Census Bureau's annual population estimates. Data collected by the United States Department of Agriculture (USDA) Natural Resources Conservation Service’s National Resources Inventory (NRI) and locally by the South Florida Water Management District (SFWMD) track the development and land use/land cover changes with time. The intent is to include temporal trends in population density growth and the impact on land development. Results from this investigation provide the risk of nuisance flooding as a function of CoNF and PoNF for coastal areas of South Florida. The data-based criterion provides awareness to local municipalities on their flood-risk assessment and gives insight into flood management actions and watershed development.

Keywords: flood risk, nuisance flooding, urban flooding, FMEA

Procedia PDF Downloads 80

Authors: Gautier Girard, Marion Martiny, Sebastien Mercier, Mohamad Jrad, Mohamed-Slim Bahi, Laurent Bodin, Francois Lechleiter, David Nevo, Sophie Dareys

Abstract:

Reliability of electronic devices has always been of highest interest for Aero-MIL and space applications. In any electronic device, Printed Circuit Board (PCB), providing interconnection between components, is a key for reliability. During the last decades, PCB technologies evolved to sustain and/or fulfill increased original equipment manufacturers requirements and specifications, higher densities and better performances, faster time to market and longer lifetime, newer material and mixed buildups. From the very beginning of the PCB industry up to recently, qualification, experiments and trials, and errors were the most popular methods to assess system (PCB) reliability. Nowadays OEM, PCB manufacturers and scientists are working together in a close relationship in order to develop predictive models for PCB reliability and lifetime. To achieve that goal, it is fundamental to characterize precisely base materials (laminates, electrolytic copper, …), in order to understand failure mechanisms and simulate PCB aging under environmental constraints by means of finite element method for example. The laminates are woven composites and have thus an orthotropic behaviour. The in-plane properties can be measured by combining classical uniaxial testing and digital image correlation. Nevertheless, the out-of-plane properties cannot be evaluated due to the thickness of the laminate (a few hundred of microns). It has to be noted that the knowledge of the out-of-plane properties is fundamental to investigate the lifetime of high density printed circuit boards. A homogenization method combining analytical and numerical approaches has been developed in order to obtain the complete elastic orthotropic behaviour of a woven composite from its precise 3D internal structure and its experimentally measured in-plane elastic properties. Since the mechanical properties of the resin surrounding the fibres are unknown, an inverse method is proposed to estimate it. The methodology has been applied to one laminate used in hyperfrequency spatial applications in order to get its elastic orthotropic behaviour at different temperatures in the range [-55°C; +125°C]. Next; numerical simulations of a plated through hole in a double sided PCB are performed. Results show the major importance of the out-of-plane properties and the temperature dependency of these properties on the lifetime of a printed circuit board. Acknowledgements—The support of the French ANR agency through the Labcom program ANR-14-LAB7-0003-01, support of CNES, Thales Alenia Space and Cimulec is acknowledged.

Keywords: homogenization, orthotropic behaviour, printed circuit board, woven composites

Procedia PDF Downloads 193

Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

Abstract:

Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 123

Authors: Qingxin Chen, Liben Jiang, Andrew Smith, Karim Hadjri

Abstract:

Since 2007, the Chinese food industry has undergone serious food contamination in the baby dairy industry, especially milk powder contamination. One of the milk powder products was found to contain melamine and a significant number (294,000) of babies were affected by kidney stones. Due to growing concerns among consumers about food safety and protection, and high pressure from central government, companies must take radical action to ensure food quality protection through the use of an appropriate quality management system. Previously, though researchers have investigated the health and safety aspects of food industries and products, quality issues concerning food products in China have been largely over-looked. Issues associated with baby dairy products and their quality issues have not been discussed in depth. This paper investigates the impact of quality management systems on the Chinese baby dairy product industry. A literature review was carried out to analyse the use of quality management systems within the Chinese milk power market. Moreover, quality concepts, relevant standards, laws, regulations and special issues (such as Melamine, Flavacin M1 contamination) have been analysed in detail. A qualitative research approach is employed, whereby preliminary analysis was conducted by interview, and data analysis based on interview responses from four selected Chinese baby dairy product companies was carried out. Through the analysis of literature review and data findings, it has been revealed that for quality management system that has been designed by many practitioners, many theories, models, conceptualisation, and systems are present. These standards and procedures should be followed in order to provide quality products to consumers, but the implementation is lacking in the Chinese baby dairy industry. Quality management systems have been applied by the selected companies but the implementation still needs improvement. For instance, the companies have to take measures to improve their processes and procedures with relevant standards. The government need to make more interventions and take a greater supervisory role in the production process. In general, this research presents implications for the regulatory bodies, Chinese Government and dairy food companies. There are food safety laws prevalent in China but they have not been widely practiced by companies. Regulatory bodies must take a greater role in ensuring compliance with laws and regulations. The Chinese government must also play a special role in urging companies to implement relevant quality control processes. The baby dairy companies not only have to accept the interventions from the regulatory bodies and government, they also need to ensure that production, storage, distribution and other processes will follow the relevant rules and standards.

Keywords: baby dairy product, food quality, milk powder contamination, quality management system

Procedia PDF Downloads 460

Authors: María Cárdenas Gaudry, Gonzalo Ramces Fano Miranda

Abstract:

Sediment removal is very important in the purification of water, not only for reasons of visual perception but also because of its association with odor and taste problems. The Cuchoquesera reservoir, which is in the Andean region of Ayacucho (Peru) at an altitude of 3,740 meters above sea level, visually presents suspended particles and organic impurities indicating that it contains water of dubious quality to deduce that it is suitable for direct consumption of human beings. In order to quantitatively know the degree of impurities, water quality monitoring was carried out from February to August 2018, in which four sampling stations were established in the reservoir. The selected measured parameters were electrical conductivity, total dissolved solids, pH, color, turbidity, and sludge volume. The indicators of the studied parameters exceed the permissible limits except for electrical conductivity (190 μS/cm) and total dissolved solids (255 mg/L). In this investigation, the best combination and the optimal doses of reagents were determined that allowed the removal of sediments from the waters of the Cuchoquesera reservoir, through the physicochemical process of coagulation-flocculation. In order to improve this process during the rainy season, six combinations of reagents were evaluated, made up of three coagulants (ferric chloride, ferrous sulfate, and aluminum sulfate) and two natural flocculants: prickly pear powder (Opuntia ficus-indica) and tara gum (Caesalpinia spinoza). For each combination of reagents, jar tests were developed following the central composite experimental design (CCED), where the design factors were the doses of coagulant and flocculant and the initial turbidity. The results of the jar tests were adjusted to mathematical models, obtaining that to treat the water from the Cuchoquesera reservoir, with a turbidity of 150 UTN and a color of 137 U Pt-Co, 27.9 mg/L of the coagulant aluminum sulfate with 3 mg/L of the natural tara gum flocculant to produce a purified water quality of 1.7 UTN of turbidity and 3.2 U Pt-Co of apparent color. The estimated cost of the dose of coagulant and flocculant found was 0.22 USD/m³. This is how “grey-green” technologies can be used as a combination in nature-based solutions in water treatment, in this case, to achieve potability, making it more sustainable, especially economically, if green technology is available at the site of application of the nature-based hybrid solution. This research is a demonstration of the compatibility of natural coagulants/flocculants with other treatment technologies in the integrated/hybrid treatment process, such as the possibility of hybridizing natural coagulants with other types of coagulants.

Keywords: prickly pear powder, tara gum, nature-based solutions, aluminum sulfate, jar test, turbidity, coagulation, flocculation

Procedia PDF Downloads 93

Authors: Dina C. Castro, Rossana Boyd, Eugenia Papadaki

Abstract:

Immigration within and across continents is currently a global reality. The number of people leaving their communities in search for a better life for them and their families has increased dramatically during the last twenty years. Therefore, young children of the 21st century around the World are growing up in diverse communities, exposed to many languages and cultures. One consequence of these migration movements is the increased linguistic diversity in school settings. Depending on the linguistic history and the status of languages in the communities (i.e., minority-majority; majority-majority) the instructional approaches will differ. This session will discuss how bilingualism is addressed in early education programs in both minority-majority and majority-majority language communities, analyzing experiences in three countries with very distinct societal and demographic characteristics: Peru (South America), the United States (North America), and Italy (European Union). The ultimate goal is to identify commonalities and differences across the three experiences that could lead to a discussion of bilingualism in early education from a global perspective. From Peru, we will discuss current national language and educational policies that have lead to the design and implementation of bilingual and intercultural education for children in indigenous communities. We will also discuss how those practices are being implemented in preschool programs, the progress made and challenges encountered. From the United States, we will discuss the early education of Spanish-English bilingual preschoolers, including the national policy environment, as well as variations in language of instruction approaches currently being used with these children. From Italy, we will describe early education practices in the Bilingual School of Monza, in northern Italy, a school that has 20 years promoting bilingualism and multilingualism in education. While the presentations from Peru and the United States will discuss bilingualism in a majority-minority language environment, this presentation will lead to a discussion on the opportunities and challenges of promoting bilingualism in a majority-majority language environment. It is evident that innovative models and policies are necessary to prevent inequality of opportunities for bilingual children beginning in their earliest years. The cross-cultural examination of bilingual education experiences for young children in three part of the World will allow us to learn from our success and challenges. The session will end with a discussion of the following question: To what extent are early care and education programs being effective in promoting positive development and learning among all children, including those from diverse language, ethnic and cultural backgrounds? We expect to identify, with participants to our session, a set of recommendations for policy and program development that could ensure access to high quality early education for all bilingual children.

Keywords: early education for bilingual children, global perspectives in early education, cross-cultural, language policies

Procedia PDF Downloads 291

Authors: Micael Sousa

Abstract:

Board games (BGs) are thriving as new designs emerge from the hobby community to greater audiences all around the world. Although digital games are gathering most of the attention in game studies and serious games research fields, the post-digital movement helps to explain why in the world dominated by digital technologies, the analog experiences are still unique and irreplaceable to users, allowing innovation in new hybrid environments. The BG’s new designs are part of these post-digital and hybrid movements because they result from the use of powerful digital tools that enable the production and knowledge sharing about the BGs and their face-to-face unique social experiences. These new BGs, defined as modern by many authors, are providing innovative designs and unique game mechanics that are still not yet fully explored by the main serious games (SG) approaches. Even the most established frameworks settled to address SG, as fun games implemented to achieve predefined goals need more development, especially when considering modern BGs. Despite the many anecdotic perceptions, researchers are only now starting to rediscover BGs and demonstrating their potentials. They are proving that BGs are easy to adapt and to grasp by non-expert players in experimental approaches, with the possibility of easy-going adaptation to players’ profiles and serious objectives even during gameplay. Although there are many design thinking (DT) models and practices, their relations with SG frameworks are also underdeveloped, mostly because this is a new research field, lacking theoretical development and the systematization of the experimental practices. Using BG as case studies promise to help develop these frameworks. Departing from the Design, Experience, and Play (DPE) framework and considering the Common Design Think Tools (CDST), this paper proposes a new experimental framework for the adaptation and development of modern BG design for DT: the Design, Experience, and Play for Think (DPET) experimental framework. This is done through the systematization of the DPE and CDST approaches applied in two case studies, where two different sequences of adapted BG were employed to establish a DT collaborative process. These two sessions occurred with different participants and in different contexts, also using different sequences of games for the same DT approach. The first session took place at the Faculty of Economics at the University of Coimbra in a training session of serious games for project development. The second session took place in the Casa do Impacto through The Great Village Design Jam light. Both sessions had the same duration and were designed to progressively achieve DT goals, using BGs as SGs in a collaborative process. The results from the sessions show that a sequence of BGs, when properly adapted to address the DPET framework, can generate a viable and innovative process of collaborative DT that is productive, fun, and engaging. The DPET proposed framework intents to help establish how new SG solutions could be defined for new goals through flexible DT. Applications in other areas of research and development can also benefit from these findings.

Keywords: board games, design thinking, methodology, serious games

Procedia PDF Downloads 98

Authors: Masoume Ehsani, Ning Zhu, Huu Doan, Ali Lohi, Amira Abdelrasoul

Abstract:

Membrane fouling poses severe challenges in membrane-based wastewater treatment applications. Ultrasound (US) has been considered an effective fouling remediation technique in filtration processes. Bubble cavitation in the liquid medium results from the alternating rarefaction and compression cycles during the US irradiation at sufficiently high acoustic pressure. Cavitation microbubbles generated under US irradiation can cause eddy current and turbulent flow within the medium by either oscillating or discharging energy to the system through microbubble explosion. Turbulent flow regime and shear forces created close to the membrane surface cause disturbing the cake layer and dislodging the foulants, which in turn improve the cleaning efficiency and filtration performance. Therefore, the number, size, velocity, and oscillation pattern of the microbubbles created in the liquid medium play a crucial role in foulant detachment and permeate flux recovery. The goal of the current study is to gain in depth understanding of the influence of the US power intensity and frequency on the microbubble dynamics and its characteristics generated under US irradiation. In comparison with other imaging techniques, the synchrotron in-line Phase Contrast Imaging technique at the Canadian Light Source (CLS) allows in-situ observation and real-time visualization of microbubble dynamics. At CLS biomedical imaging and therapy (BMIT) polychromatic beamline, the effective parameters were optimized to enhance the contrast gas/liquid interface for the accuracy of the qualitative and quantitative analysis of bubble cavitation within the system. With the high flux of photons and the high-speed camera, a typical high projection speed was achieved; and each projection of microbubbles in water was captured in 0.5 ms. ImageJ software was used for post-processing the raw images for the detailed quantitative analyses of microbubbles. The imaging has been performed under the US power intensity levels of 50 W, 60 W, and 100 W, in addition to the US frequency levels of 20 kHz, 28 kHz, and 40 kHz. For the duration of 2 seconds of imaging, the effect of the US power and frequency on the average number, size, and fraction of the area occupied by bubbles were analyzed. Microbubbles’ dynamics in terms of their velocity in water was also investigated. For the US power increase of 50 W to 100 W, the average bubble number and the average bubble diameter were increased from 746 to 880 and from 36.7 µm to 48.4 µm, respectively. In terms of the influence of US frequency, a fewer number of bubbles were created at 20 kHz (average of 176 bubbles rather than 808 bubbles at 40 kHz), while the average bubble size was significantly larger than that of 40 kHz (almost seven times). The majority of bubbles were captured close to the membrane surface in the filtration unit. According to the study observations, membrane cleaning efficiency is expected to be improved at higher US power and lower US frequency due to the higher energy release to the system by increasing the number of bubbles or growing their size during oscillation (optimum condition is expected to be at 20 kHz and 100 W).

Keywords: bubble dynamics, cavitational bubbles, membrane fouling, ultrasonic cleaning

Procedia PDF Downloads 135

Authors: Raptis Sotirios

Abstract:

Health and social care (HSc) services planning and scheduling are facing unprecedented challenges due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven can help to improve policies, plan and design services provision schedules using algorithms assist healthcare managers’ to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as CART, random forests (RF), and logistic regression (LGR). The significance tests Chi-Squared test and Student test are used on data over a 39 years span for which HSc services data exist for services delivered in Scotland. The demands are probabilistically associated through statistical hypotheses that assume that the target service’s demands are statistically dependent on other demands as a NULL hypothesis. This linkage can be confirmed or not by the data. Complementarily, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus groups of services. Statistical tests confirm ML couplings making the prediction also statistically meaningful and prove that a target service can be matched reliably to other services, and ML shows these indicated relationships can also be linear ones. Zero paddings were used for missing years records and illustrated better such relationships both for limited years and in the entire span offering long term data visualizations while limited years groups explained how well patients numbers can be related in short periods or can change over time as opposed to behaviors across more years. The prediction performance of the associations is measured using Receiver Operating Characteristic(ROC) AUC and ACC metrics as well as the statistical tests, Chi-Squared and Student. Co-plots and comparison tables for RF, CART, and LGR as well as p-values and Information Exchange(IE), are provided showing the specific behavior of the ML and of the statistical tests and the behavior using different learning ratios. The impact of k-NN and cross-correlation and C-Means first groupings is also studied over limited years and the entire span. It was found that CART was generally behind RF and LGR, but in some interesting cases, LGR reached an AUC=0 falling below CART, while the ACC was as high as 0.912, showing that ML methods can be confused padding or by data irregularities or outliers. On average, 3 linear predictors were sufficient, LGR was found competing RF well, and CART followed with the same performance at higher learning ratios. Services were packed only if when significance level(p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, birth weights, alcoholism, drug abuse, and emergency admissions. The work found that different HSc services can be well packed as plans of limited years, across various services sectors, learning configurations, as confirmed using statistical hypotheses.

Keywords: class, cohorts, data frames, grouping, prediction, prob-ability, services

Procedia PDF Downloads 215

Authors: Catelyn Coyle, Helena Kwakwa

Abstract:

Objective: As novel and better tolerated therapies become available, effective HCV testing and care models become increasingly necessary to not only identify individuals with active infection but also link them to HCV providers for medical evaluation and treatment. Our aim is to describe an effective HCV testing and linkage to care model piloted in a network of five community health centers located in Philadelphia, PA. Methods: In October 2012, National Nursing Centers Consortium piloted a routine opt-out HCV testing model in a network of community health centers, one of which treats HCV, HIV, and co-infected patients. Key aspects of the model were medical assistant initiated testing, the use of laboratory-based reflex test technology, and electronic medical record modifications to prompt, track, report and facilitate payment of test costs. Universal testing on all adult patients was implemented at health centers serving patients at high-risk for HCV. The other sites integrated high-risk based testing, where patients meeting one or more of the CDC testing recommendation risk factors or had a history of homelessness were eligible for HCV testing. Mid-course adjustments included the integration of dual HIV testing, development of a linkage to care coordinator position to facilitate the transition of HIV and/or HCV-positive patients from primary to specialist care, and the transition to universal HCV testing across all testing sites. Results: From October 2012 to June 2015, the health centers performed 7,730 HCV tests and identified 886 (11.5%) patients with a positive HCV-antibody test. Of those with positive HCV-antibody tests, 838 (94.6%) had an HCV-RNA confirmatory test and 590 (70.4%) progressed to current HCV infection (overall prevalence=7.6%); 524 (88.8%) received their RNA-positive test result; 429 (72.7%) were referred to an HCV care specialist and 271 (45.9%) were seen by the HCV care specialist. The best linkage to care results were seen at the test and treat the site, where of the 333 patients were current HCV infection, 175 (52.6%) were seen by an HCV care specialist. Of the patients with active HCV infection, 349 (59.2%) were unaware of their HCV-positive status at the time of diagnosis. Since the integration of dual HCV/HIV testing in September 2013, 9,506 HIV tests were performed, 85 (0.9%) patients had positive HIV tests, 81 (95.3%) received their confirmed HIV test result and 77 (90.6%) were linked to HIV care. Dual HCV/HIV testing increased the number of HCV tests performed by 362 between the 9 months preceding dual testing and first 9 months after dual testing integration, representing a 23.7% increment. Conclusion: Our HCV testing model shows that integrated routine testing and linkage to care is feasible and improved detection and linkage to care in a primary care setting. We found that prevalence of current HCV infection was higher than that seen in locally in Philadelphia and nationwide. Intensive linkage services can increase the number of patients who successfully navigate the HCV treatment cascade. The linkage to care coordinator position is an important position that acts as a trusted intermediary for patients being linked to care.

Keywords: HCV, routine testing, linkage to care, community health centers

Procedia PDF Downloads 346

Authors: Richa Sharma, Uma Nahar, Sadhna Sharma, Indu Verma

Abstract:

Counteracting the deadly pathogen Mycobacterium tuberculosis (M. tb) effectively is still a global challenge. Scrutinizing alternative weapons like antimicrobial peptides to strengthen existing tuberculosis artillery is urgently required. Considering the antimycobacterial potential of Human Beta Defensin 1 (HBD-1) along with isoniazid, the present study was designed to explore the ability of HBD-1 to act against active and dormant M. tb. HBD-1 was screened in silico using antimicrobial peptide prediction servers to identify its short antimicrobial motif. The activity of both HBD-1 and its selected motif (Pep B) was determined at different concentrations against actively growing M. tb in vitro and ex vivo in monocyte derived macrophages (MDMs). Log phase M. tb was grown along with HBD-1 and Pep B for 7 days. M. tb infected MDMs were treated with HBD-1 and Pep B for 72 hours. Thereafter, colony forming unit (CFU) enumeration was performed to determine activity of both peptides against actively growing in vitro and intracellular M. tb. The dormant M. tb models were prepared by following two approaches and treated with different concentrations of HBD-1 and Pep B. Firstly, 20-22 days old M. tbH37Rv was grown in potassium deficient Sauton media for 35 days. The presence of dormant bacilli was confirmed by Nile red staining. Dormant bacilli were further treated with rifampicin, isoniazid, HBD-1 and its motif for 7 days. The effect of both peptides on latent bacilli was assessed by colony forming units (CFU) and most probable number (MPN) enumeration. Secondly, human PBMC granuloma model was prepared by infecting PBMCs seeded on collagen matrix with M. tb(MOI 0.1) for 10 days. Histopathology was done to confirm granuloma formation. The granuloma thus formed was incubated for 72 hours with rifampicin, HBD-1 and Pep B individually. Difference in bacillary load was determined by CFU enumeration. The minimum inhibitory concentrations of HBD-1 and Pep B restricting growth of mycobacteria in vitro were 2μg/ml and 20μg/ml respectively. The intracellular mycobacterial load was reduced significantly by HBD-1 and Pep B at 1μg/ml and 5μg/ml respectively. Nile red positive bacterial population, high MPN/ low CFU count and tolerance to isoniazid, confirmed the formation of potassium deficienybaseddormancy model. HBD-1 (8μg/ml) showed 96% and 99% killing and Pep B (40μg/ml) lowered dormant bacillary load by 68.89% and 92.49% based on CFU and MPN enumeration respectively. Further, H&E stained aggregates of macrophages and lymphocytes, acid fast bacilli surrounded by cellular aggregates and rifampicin resistance, indicated the formation of human granuloma dormancy model. HBD-1 (8μg/ml) led to 81.3% reduction in CFU whereas its motif Pep B (40μg/ml) showed only 54.66% decrease in bacterial load inside granuloma. Thus, the present study indicated that HBD-1 and its motif are effective antimicrobial players against both actively growing and dormant M. tb. They should be further explored to tap their potential to design a powerful weapon for combating tuberculosis.

Keywords: antimicrobial peptides, dormant, human beta defensin 1, tuberculosis

Procedia PDF Downloads 252

Authors: Michael McCann

Abstract:

Managerial theories propose that, in joint stock companies, executives may be tempted to waste excess free cash on unprofitable projects to keep control of resources. In order to conceal their projects' poor performance, they may seek to engage in earnings management. On the one hand, managers may manipulate earnings upwards in order to post ‘good’ performances and safeguard their position. On the other, since managers pursuit of unrewarding investments are likely to lead to low long-term profitability, managers will use negative accruals to reduce current year’s earnings, smoothing earnings over time in order to conceal the negative effects. Agency models argue that boards of directors are delegated by shareholders to ensure that companies are governed properly. Part of that responsibility is ensuring the reliability of financial information. Analyses of the impact of board characteristics, particularly board independence on the misuse of free cash flow and earnings management finds conflicting evidence. However, existing characterizations of board independence do not account for such directors gaining firm-specific knowledge over time, influencing their monitoring ability. Further, there is little analysis of the influence of the relative experience of independent directors and executives on decisions surrounding the use of free cash. This paper contributes to this literature regarding the heterogeneous characteristics of boards by investigating the influence of independent director tenure on earnings management and the relative tenures of independent directors and Chief Executives. A balanced panel dataset comprising 51 companies across 11 annual periods from 2005 to 2015 is used for the analysis. In each annual period, firms were classified as conducting earnings management if they had discretionary accruals in the bottom quartile (downwards) and top quartile (upwards) of the distributed values for the sample. Logistical regressions were conducted to determine the marginal impact of independent board tenure and a number of control variables on the probability of conducting earnings management. The findings indicate that both absolute and relative measures of board independence and experience do not have a significant impact on the likelihood of earnings management. It is the level of free cash flow which is the major influence on the probability of earnings management. Higher free cash flow increases the probability of earnings management significantly. The research also investigates whether board monitoring of earnings management is contingent on the level of free cash flow. However, the results suggest that board monitoring is not amplified when free cash flow is higher. This suggests that the extent of earnings management in companies is determined by a range of company, industry and situation-specific factors.

Keywords: corporate governance, boards of directors, agency theory, earnings management

Procedia PDF Downloads 212

Authors: Éva Pintér, Péter Bagó, Nikolett Deutsch, Miklós Hetényi

Abstract:

The process of digital transformation has a profound influence on all sectors of the worldwide economy and the business environment. The influence of blockchain technology can be observed in the digital economy and e-government, rendering it an essential element of a nation's growth strategy. The banking industry is experiencing significant expansion and development of financial technology firms. Utilizing developing technologies such as artificial intelligence (AI), machine learning (ML), and big data (BD), these entrants are offering more streamlined financial solutions, promptly addressing client demands, and presenting a challenge to incumbent institutions. The advantages of digital transformation are evident in the corporate realm, and firms that resist its adoption put their survival at risk. The advent of digital technologies has revolutionized the business environment, streamlining processes and creating opportunities for enhanced communication and collaboration. Thanks to the aid of digital technologies, businesses can now swiftly and effortlessly retrieve vast quantities of information, all the while accelerating the process of creating new and improved products and services. Big data analytics is generally recognized as a transformative force in business, considered the fourth paradigm of science, and seen as the next frontier for innovation, competition, and productivity. Big data, an emerging technology that is shaping the future of the banking sector, offers numerous advantages to banks. It enables them to effectively track consumer behavior and make informed decisions, thereby enhancing their operational efficiency. Banks may embrace big data technologies to promptly and efficiently identify fraud, as well as gain insights into client preferences, which can then be leveraged to create better-tailored products and services. Moreover, the utilization of big data technology empowers banks to develop more intelligent and streamlined models for accurately recognizing and focusing on the suitable clientele with pertinent offers. There is a scarcity of research on big data analytics in the banking industry, with the majority of existing studies only examining the advantages and prospects associated with big data. Although big data technologies are crucial, there is a dearth of empirical evidence about the role of big data analytics (BDA) capabilities in bank performance. This research addresses a gap in the existing literature by introducing a model that combines the resource-based view (RBV), the technical organization environment framework (TOE), and dynamic capability theory (DC). This study investigates the influence of Big Data Analytics (BDA) utilization on the performance of market and risk management. This is supported by a comparative examination of Hungarian mobile banking services.

Keywords: big data, digital transformation, dynamic capabilities, mobile banking

Procedia PDF Downloads 41

Authors: Ikechukwu Ndu

Abstract:

This study examines the econometric modeling of the relation between discretionary accrual earnings management, International Financial Reporting Standards (IFRS), and certain corporate governance factors with regard to listed Nigerian non-financial firms. Although discretionary accrual earnings management is a well-known and global problem that has an adverse impact on users of the financial statements, its relationship with IFRS and corporate governance is neither adequately researched nor properly systematically investigated in Nigeria. The dearth of research in the relation between discretionary accrual earnings management, IFRS and corporate governance in Nigeria has made it difficult for academics, practitioners, government setting bodies, regulators and international bodies to achieve a clearer understanding of how discretionary accrual earnings management relates to IFRS and certain corporate governance characteristics. This is the first study to the author’s best knowledge to date that makes interesting research contributions that significantly add to the literature of discretionary accrual earnings management and its relation with corporate governance and IFRS pertaining to the Nigerian context. A comprehensive review is undertaken of the literature of discretionary total accrual earnings management, IFRS, and certain corporate governance characteristics as well as the data, models, methodologies, and different estimators used in the study. Secondary financial statement, IFRS, and corporate governance data are sourced from Bloomberg database and published financial statements of Nigerian non-financial firms for the period 2004 to 2016. The methodology uses both the total and working capital accrual basis. This study has a number of interesting preliminary findings. First, there is a negative relationship between the level of discretionary accrual earnings management and the adoption of IFRS. However, this relationship does not appear to be statistically significant. Second, there is a significant negative relationship between the size of the board of directors and discretionary accrual earnings management. Third, CEO Separation of roles does not constrain earnings management, indicating the need to preserve relationships, personal connections, and maintain bonded friendships between the CEO, Chairman, and executive directors. Fourth, there is a significant negative relationship between discretionary accrual earnings management and the use of a Big Four firm as an auditor. Fifth, including shareholders in the audit committee, leads to a reduction in discretionary accrual earnings management. Sixth, the debt and return on assets (ROA) variables are significant and positively related to discretionary accrual earnings management. Finally, the company size variable indicated by the log of assets is surprisingly not found to be statistically significant and indicates that all Nigerian companies irrespective of size engage in discretionary accrual management. In conclusion, this study provides key insights that enable a better understanding of the relationship between discretionary accrual earnings management, IFRS, and corporate governance in the Nigerian context. It is expected that the results of this study will be of interest to academics, practitioners, regulators, governments, international bodies and other parties involved in policy setting and economic development in areas of financial reporting, securities regulation, accounting harmonization, and corporate governance.

Keywords: discretionary accrual earnings management, earnings manipulation, IFRS, corporate governance

Procedia PDF Downloads 128

Authors: Maria De Los Angeles Ortega, Denis Bruneau, Patrick Sebastian, Jean-Pierre Nadeau, Alain Sommier, Saed Raji

Abstract:

Phase change materials (PCM) present attractive features that made them a passive solution for thermal comfort assessment in buildings during summer time. They show a large storage capacity per volume unit in comparison with other structural materials like bricks or concrete. If their use is matched with the peak load periods, they can contribute to the reduction of the primary energy consumption related to cooling applications. Despite these promising characteristics, they present some drawbacks. Commercial PCMs, as paraffines, offer a low thermal conductivity affecting the overall performance of the system. In some cases, the material can be enhanced, adding other elements that improve the conductivity, but in general, a design of the unit that optimizes the thermal performance is sought. The material selection is the departing point during the designing stage, and it does not leave plenty of room for optimization. The PCM melting point depends highly on the atmospheric characteristics of the building location. The selection must relay within the maximum, and the minimum temperature reached during the day. The geometry of the PCM container and the geometrical distribution of these containers are designing parameters, as well. They significantly affect the heat transfer, and therefore its phenomena must be studied exhaustively. During its lifetime, an air-PCM unit in a building must cool down the place during daytime, while the melting of the PCM occurs. At night, the PCM must be regenerated to be ready for next uses. When the system is not in service, a minimal amount of thermal exchanges is desired. The aforementioned functions result in the presence of sensible and latent heat storage and release. Hence different types of mechanisms drive the heat transfer phenomena. An experimental test was designed to study the heat transfer phenomena occurring in a circular tube bundle air-PCM exchanger. An in-line arrangement was selected as the geometrical distribution of the containers. With the aim of visual identification, the containers material and a section of the test bench were transparent. Some instruments were placed on the bench for measuring temperature and velocity. The PCM properties were also available through differential scanning calorimeter (DSC) tests. An evolution of the temperature during both cycles, melting and solidification were obtained. The results showed some phenomena at a local level (tubes) and on an overall level (exchanger). Conduction and convection appeared as the main heat transfer mechanisms. From these results, two approaches to analyze the heat transfer were followed. The first approach described the phenomena in a single tube as a series of thermal resistances, where a pure conduction controlled heat transfer was assumed in the PCM. For the second approach, the temperature measurements were used to find some significant dimensionless numbers and parameters as Stefan, Fourier and Rayleigh numbers, and the melting fraction. These approaches allowed us to identify the heat transfer phenomena during both cycles. The presence of natural convection during melting might have been stated from the influence of the Rayleigh number on the correlations obtained.

Keywords: phase change materials, air-PCM exchangers, convection, conduction

Procedia PDF Downloads 165

Authors: N. Naz, A. D. Domenico, M. N. Huda

Abstract:

Soft Robotics is a rapidly growing multidisciplinary field where robots are fabricated using highly deformable materials motivated by bioinspired designs. The high dexterity and adaptability to the external environments during contact make soft robots ideal for applications such as gripping delicate objects, locomotion, and biomedical devices. The actuation system of soft robots mainly includes fluidic, tendon-driven, and smart material actuation. Among them, Soft Pneumatic Actuator, also known as SPA, remains the most popular choice due to its flexibility, safety, easy implementation, and cost-effectiveness. However, at present, most of the fabrication of SPA is still based on traditional molding and casting techniques where the mold is 3d printed into which silicone rubber is cast and consolidated. This conventional method is time-consuming and involves intensive manual labour with the limitation of repeatability and accuracy in design. Recent advancements in direct 3d printing of different soft materials can significantly reduce the repetitive manual task with an ability to fabricate complex geometries and multicomponent designs in a single manufacturing step. The aim of this research work is to design and analyse the Soft Pneumatic Actuator (SPA) utilizing both conventional casting and modern direct 3d printing technologies. The mold of the SPA for traditional casting is 3d printed using fused deposition modeling (FDM) with the polylactic acid (PLA) thermoplastic wire. Hyperelastic soft materials such as Ecoflex-0030/0050 are cast into the mold and consolidated using a lab oven. The bending behaviour is observed experimentally with different pressures of air compressor to ensure uniform bending without any failure. For direct 3D-printing of SPA fused deposition modeling (FDM) with thermoplastic polyurethane (TPU) and stereolithography (SLA) with an elastic resin are used. The actuator is modeled using the finite element method (FEM) to analyse the nonlinear bending behaviour, stress concentration and strain distribution of different hyperelastic materials after pressurization. FEM analysis is carried out using Ansys Workbench software with a Yeon-2nd order hyperelastic material model. FEM includes long-shape deformation, contact between surfaces, and gravity influences. For mesh generation, quadratic tetrahedron, hybrid, and constant pressure mesh are used. SPA is connected to a baseplate that is in connection with the air compressor. A fixed boundary is applied on the baseplate, and static pressure is applied orthogonally to all surfaces of the internal chambers and channels with a closed continuum model. The simulated results from FEM are compared with the experimental results. The experiments are performed in a laboratory set-up where the developed SPA is connected to a compressed air source with a pressure gauge. A comparison study based on performance analysis is done between FDM and SLA printed SPA with the molded counterparts. Furthermore, the molded and 3d printed SPA has been used to develop a three-finger soft pneumatic gripper and has been tested for handling delicate objects.

Keywords: finite element method, fused deposition modeling, hyperelastic, soft pneumatic actuator

Procedia PDF Downloads 80

Authors: Zabihullah Mahdi, Khwaja Naweed Seddiqi

Abstract:

Afghanistan is located in a tectonically complex and dynamic area, surrounded by rocks that originated on the mother continent of Gondwanaland. The northern Afghanistan basin, which runs along the country's northern border, has the potential for petroleum generation and accumulation. The Amu Darya basin has the largest petroleum potential in the region. Sedimentation occurred in the Amu Darya basin from the Jurassic to the Eocene epochs. Kashkari oil field is located in northern Afghanistan's Amu Darya basin. The field structure consists of a narrow northeast-southwest (NE-SW) anticline with two structural highs, the northwest limb being mild and the southeast limb being steep. The first oil production well in the Kashkari oil field was drilled in 1976, and a total of ten wells were drilled in the area between 1976 and 1979. The amount of original oil in place (OOIP) in the Kashkari oil field, based on the results of surveys and calculations conducted by research institutions, is estimated to be around 140 MMbbls. The objective of this study is to increase recoverable oil reserves in the Kashkari oil field through the implementation of low-salinity water flooding (LSWF) enhanced oil recovery (EOR) technique. The LSWF involved conducting a core flooding laboratory test consisting of four sequential steps with varying salinities. The test commenced with the use of formation water (FW) as the initial salinity, which was subsequently reduced to a salinity level of 0.1%. Afterwards, the numerical simulation model of core scale oil recovery by LSWF was designed by Computer Modelling Group’s General Equation Modeler (CMG-GEM) software to evaluate the applicability of the technology to the field scale. Next, the Kahskari oil field simulation model was designed, and the LSWF method was applied to it. To obtain reasonable results, laboratory settings (temperature, pressure, rock, and oil characteristics) are designed as far as possible based on the condition of the Kashkari oil field, and several injection and production patterns are investigated. The relative permeability of oil and water in this study was obtained using Corey’s equation. In the Kashkari oilfield simulation model, three models: 1. Base model (with no water injection), 2. FW injection model, and 3. The LSW injection model were considered for the evaluation of the LSWF effect on oil recovery. Based on the results of the LSWF laboratory experiment and computer simulation analysis, the oil recovery increased rapidly after the FW was injected into the core. Subsequently, by injecting 1% salinity water, a gradual increase of 4% oil can be observed. About 6.4% of the field, is produced by the application of the LSWF technique. The results of LSWF (salinity 0.1%) on the Kashkari oil field suggest that this technology can be a successful method for developing Kashkari oil production.

Keywords: low salinity water flooding, immiscible displacement, kashkari oil field, twophase flow, numerical reservoir simulation model

Procedia PDF Downloads 18