Search results for: automatic linear modeling

Authors: Bishnupriya Sahoo, Prasad K. Bhaskaran

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Tropical cyclone is one among the worst natural hazards that results in a trail of destruction causing enormous damage to life, property, and coastal infrastructures. In a global perspective, the Indian Ocean is considered as one of the cyclone prone basins in the world. Specifically, the frequency of cyclogenesis in the Bay of Bengal is higher compared to the Arabian Sea. Out of the four maritime states in the East coast of India, Odisha is highly susceptible to tropical cyclone landfall. Historical records clearly decipher the fact that the frequency of cyclones have reduced in this basin. However, in the recent decades, the intensity and size of tropical cyclones have increased. This is a matter of concern as the risk and vulnerability level of Odisha coast exposed to high wind speed and gusts during cyclone landfall have increased. In this context, there is a need to assess and evaluate the severity of coastal risk, area of exposure under risk, and associated vulnerability with a higher dimension in a multi-risk perspective. Changing climate can result in the emergence of a new hazard and vulnerability over a region with differential spatial and socio-economic impact. Hence there is a need to have coastal vulnerability projections in a changing climate scenario. With this motivation, the present study attempts to estimate the destructiveness of tropical cyclones based on Power Dissipation Index (PDI) for those cyclones that made landfall along Odisha coast that exhibits an increasing trend based on historical data. The study also covers the futuristic scenarios of integral coastal vulnerability based on the trends in PDI for the Odisha coast. This study considers 11 essential and important parameters; the cyclone intensity, storm surge, onshore inundation, mean tidal range, continental shelf slope, topo-graphic elevation onshore, rate of shoreline change, maximum wave height, relative sea level rise, rainfall distribution, and coastal geomorphology. The study signifies that over a decadal scale, the coastal vulnerability index (CVI) depends largely on the incremental change in variables such as cyclone intensity, storm surge, and associated inundation. In addition, the study also performs a critical analysis on the modulation of PDI on storm surge and inundation characteristics for the entire coastal belt of Odisha State. Interestingly, the study brings to light that a linear correlation exists between the storm-tide with PDI. The trend analysis of PDI and its projection for coastal Odisha have direct practical applications in effective coastal zone management and vulnerability assessment.

Keywords: Bay of Bengal, coastal vulnerability index, power dissipation index, tropical cyclone

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Authors: T. Lazzarini, M. Imbiki, P. E. Sutter, G. Borragan

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While several strategies, such as the development of more efficient appliances, the financing of insulation programs or the rolling out of smart meters represent promising tools to reduce future energy consumption, their implementation relies on people’s decisions-actions. Likewise, engaging with consumers to reshape their behavior has shown to be another important way to reduce energy usage. For these reasons, integrating the human factor in the energy transition has become a major objective for researchers and policymakers. Digital education programs based on tangible and gamified user interfaces have become a new tool with potential effects to reduce energy consumption4. The B2020 program, developed by the firm “Économie d’Énergie SAS”, proposes a digital platform to encourage pro-environmental behavior change among employees and citizens. The platform integrates 160 eco-behaviors to help saving energy and water and reducing waste and CO2 emissions. A total of 13,146 citizens have used the tool so far to declare the range of eco-behaviors they adopt in their daily lives. The present work seeks to build on this database to identify the potential impact of adopted energy-saving behaviors (n=62) to reduce the use of energy in buildings. To this end, behaviors were classified into three categories regarding the nature of its implementation (Eco-habits: e.g., turning-off the light, Eco-actions: e.g., installing low carbon technology such as led light-bulbs and Home-Refurbishments: e.g., such as wall-insulation or double-glazed energy efficient windows). General Linear Models (GLM) disclosed the existence of a significantly higher frequency of Eco-habits when compared to the number of home-refurbishments realized by the platform users. While this might be explained in part by the high financial costs that are associated with home renovation works, it also contrasts with the up to three times larger energy-savings that can be accomplished by these means. Furthermore, multiple regression models failed to disclose the expected relationship between energy-savings and frequency of adopted eco behaviors, suggesting that energy-related practices are not necessarily driven by the correspondent energy-savings. Finally, our results also suggested that people adopting more Eco-habits and Eco-actions were more likely to engage in Home-Refurbishments. Altogether, these results fit well with a growing body of scientific research, showing that energy-related practices do not necessarily maximize utility, as postulated by traditional economic models, and suggest that other variables might be triggering them. Promoting home refurbishments could benefit from the adoption of complementary energy-saving habits and actions.

Keywords: energy-saving behavior, human performance, behavioral change, energy efficiency

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Authors: Maria De Albuquerque Bercot, Caio Gustavo Mesquita Angelo, Daniela Maria Moreira Siqueira, Augusto Assucena De Vasconcellos, Rodrigo Studart Correa

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Mining is an important socioeconomic activity in Brazil although it negatively impacts the environment. Mineral operations cause irreversible changes in topography, removal of vegetation and topsoil, habitat destruction, displacement of fauna, loss of biodiversity, soil erosion, siltation of watercourses and have potential to enhance climate change. Due to the impacts and its pollution potential, mining activity in Brazil is legally subjected to environmental licensing. Unlicensed mining operations or operations that not abide to the terms of an obtained license are taken as environmental crimes in the country. This work reports a case analyzed in the Forensic Institute of the Brazilian Federal District Civil Police. The case consisted of detecting illegal aspects of sand exploitation from a licensed mine in Federal District, nearby Brasilia city. The fieldwork covered an area of roughly 6 ha, which was surveyed with an unmanned aerial vehicle (UAV) (PHANTOM 3 ADVANCED). The overflight with UAV took about 20 min, with maximum flight height of 100 m. 592 UAV georeferenced images were obtained and processed in a photogrammetric software (AGISOFT PHOTOSCAN 1.1.4), which generated a mosaic of geo-referenced images and a 3D model in less than six working hours. The 3D model was analyzed in a forensic software for accurate modeling and volumetric analysis. (MAPTEK I-SITE FORENSIC 2.2). To ensure the 3D model was a true representation of the mine site, coordinates of ten control points and reference measures were taken during fieldwork and compared to respective spatial data in the model. Finally, these spatial data were used for measuring mining area, excavation depth and volume of exploited sand. Results showed that mine holder had not complied with some terms and conditions stated in the granted license, such as sand exploration beyond authorized extension, depth and volume. Easiness, the accuracy and expedition of procedures used in this case highlight the employment of UAV imagery and computational photogrammetry as efficient tools for outdoor forensic exams, especially on environmental issues.

Keywords: computational photogrammetry, environmental monitoring, mining, UAV

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Authors: M. Shukry

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According to the United Nations Declaration of Human Rights in 1948, every human being is entitled to rights in life that should be respected by others and protected by the state and community. Such rights are inherent regardless of colour, ethnicity, gender, religion or otherwise, and it is expected that all humans alike have the right to live without discrimination of any sort. However, that has not been the case with Aborigines in Australia. Over a long period of time, the governments of the State and the Territories and the Australian Commonwealth denied the Aboriginal and Indigenous inhabitants of the Torres Strait Islands such rights. Past Australian governments set policies and laws that enabled them to forcefully remove Indigenous children from their parents, which resulted in creating lost generations living the trauma of the loss of cultural identity, alienation and even their own selfhood. Intending to reduce that population of natives and their Aboriginal culture while, on the other hand, assimilate them into mainstream society, they gave themselves the right to remove them from their families with no hope of return. That practice has led to tragic consequences due to the trauma that has affected those children, an experience that is depicted by Jane Harrison in her play Stolen. The drama is the outcome of a six-year project on lost children and which was first performed in 1997 in Melbourne. Five actors only appear on the stage, playing the role of all the different characters, whether the main protagonists or the remaining cast, present or non-present ones as voices. The play outlines the life of five children who have been taken from their parents at an early age, entailing a disastrous negative impact that differs from one to the other. Unknown to each other, what connects between them is being put in a children’s home. The purpose of this paper is to analyse the play’s text in light of the 1948 Declaration of Human Rights, using it as a lens that reflects the atrocities practiced against the Aborigines. It highlights how such practices formed an outrageous violation of those natives’ rights as human beings. Harrison’s dramatic technique in conveying the children’s experiences is through a non-linear structure, fluctuating between past and present that are linked together within each of the five characters, reflecting their suffering and pain to create an emotional link between them and the audience. Her dramatic handling of the issue by fusing tragedy with humour as well as symbolism is a successful technique in revealing the traumatic memory of those children and their present life. The play has made a difference in commencing to address the problem of the right of all children to be with their families, which renders the real meaning of having a home and an identity as people.

Keywords: aboriginal, audience, Australia, children, culture, drama, home, human rights, identity, Indigenous, Jane Harrison, memory, scenic effects, setting, stage, stage directions, Stolen, trauma

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Authors: Siva K. Bathina, Sudheer Siddapureddy

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Pool fires are formed when the flammable liquid accidentally spills on the ground or water and ignites. Pool fire is a kind of buoyancy-driven and diffusion flame. There have been many pool fire accidents caused during processing, handling and storing of liquid fuels in chemical and oil industries. Such kind of accidents causes enormous damage to property as well as the loss of lives. Pool fires are complex in nature due to the strong interaction among the combustion, heat and mass transfers and pyrolysis at the fuel surface. Moreover, the experimental study of such large complex fires involves fire safety issues and difficulties in performing experiments. In the present work, large eddy simulations are performed to study such complex fire scenarios using fire dynamic simulator. A 1 m diesel pool fire is considered for the studied cases, and diesel is chosen as it is most commonly involved fuel in fire accidents. Fire simulations are performed by specifying two different boundary conditions: one the fuel is in liquid state and pyrolysis model is invoked, and the other by assuming the fuel is initially in a vapor state and thereby prescribing the mass loss rate. A domain of size 11.2 m × 11.2 m × 7.28 m with uniform structured grid is chosen for the numerical simulations. Grid sensitivity analysis is performed, and a non-dimensional grid size of 12 corresponding to 8 cm grid size is considered. Flame properties like mass burning rate, irradiance, and time-averaged axial flame temperature profile are predicted. The predicted steady-state mass burning rate is 40 g/s and is within the uncertainty limits of the previously reported experimental data (39.4 g/s). Though the profile of the irradiance at a distance from the fire along the height is somewhat in line with the experimental data and the location of the maximum value of irradiance is shifted to a higher location. This may be due to the lack of sophisticated models for the species transportation along with combustion and radiation in the continuous zone. Furthermore, the axial temperatures are not predicted well (for any of the boundary conditions) in any of the zones. The present study shows that the existing models are not sufficient enough for modeling blended fuels like diesel. The predictions are strongly dependent on the experimental values of the soot yield. Future experiments are necessary for generalizing the soot yield for different fires.

Keywords: burning rate, fire accidents, fire dynamic simulator, pyrolysis

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Authors: Evgeny A. Ermakov, Lyudmila P. Smirnova, Valentina N. Buneva

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Schizophrenia associated with dysregulation of neurotransmitter processes in the central nervous system and disturbances in the humoral immune system resulting in the formation of antibodies (Abs) to the various components of the nervous tissue. Abs to different neuronal receptors and DNA were detected in the blood of patients with schizophrenia. Abs hydrolyzing DNA were detected in pool of polyclonal autoantibodies in autoimmune and infectious diseases, such catalytic Abs were named abzymes. It is believed that DNA-hydrolyzing abzymes are cytotoxic, cause nuclear DNA fragmentation and induce cell death by apoptosis. Abzymes with DNAase activity are interesting because of the mechanism of formation and the possibility of use as diagnostic markers. Therefore, in our work we have set following goals: to determine the level anti-DNA Abs in the serum of patients with schizophrenia and to study DNA-hydrolyzing activity of IgG of patients with schizophrenia. Materials and methods: In our study there were included 41 patients with a verified diagnosis of paranoid or simple schizophrenia and 24 healthy donors. Electrophoretically and immunologically homogeneous IgGs were obtained by sequential affinity chromatography of the serum proteins on protein G-Sepharose and gel filtration. The levels of anti-DNA Abs were determined using ELISA. DNA-hydrolyzing activity was detected as the level of supercoiled pBluescript DNA transition in circular and linear forms, the hydrolysis products were analyzed by agarose electrophoresis followed by ethidium bromide stain. To correspond the registered catalytic activity directly to the antibodies we carried out a number of strict criteria: electrophoretic homogeneity of the antibodies, gel filtration (acid shock analysis) and in situ activity. Statistical analysis was performed in ‘Statistica 9.0’ using the non-parametric Mann-Whitney test. Results: The sera of approximately 30% of schizophrenia patients displayed a higher level of Abs interacting with single-stranded (ssDNA) and double-stranded DNA (dsDNA) compared with healthy donors. The average level of Abs interacting with ssDNA was only 1.1-fold lower than that for interacting with dsDNA. IgG of patient with schizophrenia were shown to possess DNA hydrolyzing activity. Using affinity chromatography, electrophoretic analysis of isolated IgG homogeneity, gel filtration in acid shock conditions and in situ DNAse activity analysis we proved that the observed activity is intrinsic property of studied antibodies. We have shown that the relative DNAase activity of IgG in patients with schizophrenia averaged 55.4±32.5%, IgG of healthy donors showed much lower activity (average of 9.1±6.5%). It should be noted that DNAase activity of IgG in patients with schizophrenia with a negative symptoms was significantly higher (73.3±23.8%), than in patients with positive symptoms (43.3±33.1%). Conclusion: Anti-DNA Abs of patients with schizophrenia not only bind DNA, but quite efficiently hydrolyze the substrate. The data show a correlation with the level of DNase activity and leading symptoms of patients with schizophrenia.

Keywords: anti-DNA antibodies, abzymes, DNA hydrolysis, schizophrenia

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Authors: Vinay Kumar Vanjakula, Frank Adam, Nils Goseberg, Christian Windt

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When a structure is installed on a seabed, the presence of the structure will influence the flow field around it. The changes in the flow field include, formation of vortices, turbulence generation, waves or currents flow breaking and pressure differentials around the seabed sediment. These changes allow the local seabed sediment to be carried off and results in Scour (erosion). These are a threat to the structure's stability. In recent decades, rapid developments of research work and the knowledge of scour On fixed structures (bridges and Monopiles) in rivers and oceans has been carried out, and very limited research work on scour and liquefaction for gravity anchors, particularly for floating Tension Leg Platform (TLP) substructures. Due to its importance and need for enhancement of knowledge in scour and liquefaction around marine structures, the MarTERA funded a three-year (2020-2023) research program called NuLIMAS (Numerical Modeling of Liquefaction Around Marine Structures). It’s a group consists of European institutions (Universities, laboratories, and consulting companies). The objective of this study is to build a numerical model that replicates the reality, which indeed helps to simulate (predict) underwater flow conditions and to study different marine scour and Liquefication situations. It helps to design a heavyweight anchor for the TLP substructure and to minimize the time and expenditure on experiments. And also, the achieved results and the numerical model will be a basis for the development of other design and concepts For marine structures. The Computational Fluid Dynamics (CFD) numerical model will build in OpenFOAM. A conceptual design of heavyweight anchor for TLP substructure is designed through taking considerations of available state-of-the-art knowledge on scour and Liquefication concepts and references to Previous existing designs. These conceptual designs are validated with the available similar experimental benchmark data and also with the CFD numerical benchmark standards (CFD quality assurance study). CFD optimization model/tool is designed as to minimize the effect of fluid flow, scour, and Liquefication. A parameterized model is also developed to automate the calculation process to reduce user interactions. The parameters such as anchor Lowering Process, flow optimized outer contours, seabed interaction study, and FSSI (Fluid-Structure-Seabed Interactions) are investigated and used to carve the model as to build an optimized anchor.

Keywords: gravity anchor, liquefaction, scour, computational fluid dynamics

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Authors: Lenon M. Pereira, Helen J. Khoury, Marcos E. A. Andrade, Dean L. Cutajar, Vinicius S. M. Barros, Anatoly B. Rozenfeld

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With the increase of beam widths and the advent of multiple-slice and helical scanners, concerns related to the current dose measurement protocols and instrumentation in computed tomography (CT) have arisen. The current methodology of dose evaluation, which is based on the measurement of the integral of a single slice dose profile using a 100 mm long cylinder ionization chamber (Ca,100 and CPPMA, 100), has been shown to be inadequate for wide beams as it does not collect enough of the scatter-tails to make an accurate measurement. In addition, a long ionization chamber does not offer a good representation of the dose profile when tube current modulation is used. An alternative approach has been suggested by translating smaller detectors through the beam plane and assessing the accumulated dose trough the integral of the dose profile, which can be done for any arbitrary length in phantoms or in the air. For this purpose, a MOSFET dosimeter of small dosimetric volume was used. One of its recently designed versions is known as the MOSkin, which is developed by the Centre for Medical Radiation Physics at the University of Wollongong, and measures the radiation dose at a water equivalent depth of 0.07 mm, allowing the evaluation of skin dose when placed at the surface, or internal point doses when placed within a phantom. Thus, the aim of this research was to characterize the response of the MOSkin dosimeter for X-ray CT beams and to evaluate its application for the accumulated dose assessment. Initially, tests using an industrial x-ray unit were carried out at the Laboratory of Ionization Radiation Metrology (LMRI) of Federal University of Pernambuco, in order to investigate the sensitivity, energy dependence, angular dependence, and reproducibility of the dose response for the device for the standard radiation qualities RQT 8, RQT 9 and RQT 10. Finally, the MOSkin was used for the accumulated dose evaluation of scans using a Philips Brilliance 6 CT unit, with comparisons made between the CPPMA,100 value assessed with a pencil ionization chamber (PTW Freiburg TW 30009). Both dosimeters were placed in the center of a PMMA head phantom (diameter of 16 cm) and exposed in the axial mode with collimation of 9 mm, 250 mAs and 120 kV. The results have shown that the MOSkin response was linear with doses in the CT range and reproducible (98.52%). The sensitivity for a single MOSkin in mV/cGy was as follows: 9.208, 7.691 and 6.723 for the RQT 8, RQT 9 and RQT 10 beams qualities respectively. The energy dependence varied up to a factor of ±1.19 among those energies and angular dependence was not greater than 7.78% within the angle range from 0 to 90 degrees. The accumulated dose and the CPMMA, 100 value were 3,97 and 3,79 cGy respectively, which were statistically equivalent within the 95% confidence level. The MOSkin was shown to be a good alternative for CT dose profile measurements and more than adequate to provide accumulated dose assessments for CT procedures.

Keywords: computed tomography dosimetry, MOSFET, MOSkin, semiconductor dosimetry

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Authors: Umair Shoukat Ali, Rashna Hoshang Sukhia, Mubassar Fida

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Introduction: The objective of the study was to compare outcomes in terms of Bleeding index (BI), Gingival Index (GI), and Orthodontic Plaque Index (OPI) with video graphics and plaque disclosing tablets (PDT) versus verbal instructions in adult orthodontic patients undergoing fixed appliance treatment (FAT). Materials and Methods: Adult orthodontic patients have recruited from outpatient orthodontic clinics who fulfilled the inclusion criteria and were randomly allocated to three groups i.e., video, PDT, and verbal groups. We included patients undergoing FAT for six months of both genders with all teeth bonded mesial to first molars having no co-morbid conditions such as rheumatic fever and diabetes mellitus. Subjects who had gingivitis as assessed by Bleeding Index (BI), Gingival Index (GI), and Orthodontic Plaque Index (OPI) were recruited. We excluded subjects having > 2 mm of clinical attachment loss, pregnant and lactating females, any history of periodontal therapy within the last six months, and any consumption of antibiotics or anti-inflammatory drugs within the last one month. Pre- and post-interventional measurements were taken at two intervals only for BI, GI, and OPI. The primary outcome of this trial was to evaluate the mean change in the BI, GI, and OPI in the three study groups. A computer-generated randomization list was used to allocate subjects to one of the three study groups using a random permuted block sampling of 6 and 9 to randomize the samples. No blinding of the investigator or the participants was performed. Results: A total of 99 subjects were assessed for eligibility, out of which 96 participants were randomized as three of the participants declined to be part of this trial. This resulted in an equal number of participants (32) that were analyzed in all three groups. The mean change in the oral hygiene indices score was assessed, and we found no statistically significant difference among the three interventional groups. Pre- and post-interventional results showed statistically significant improvement in the oral hygiene indices for the video and PDT groups. No statistically significant difference for age, gender, and education level on oral hygiene indices were found. Simple linear regression showed that the video group produced significantly higher mean OPI change as compared to other groups. No harm was observed during the trial. Conclusions: Visual aids performed better as compared to the verbal group. Gender, age, and education level had no statistically significant impact on the oral hygiene indices. Longer follow-ups will be required to see the long-term effects of these interventions. Trial Registration: NCT04386421 Funding: Aga Khan University and Hospital (URC 183022)

Keywords: oral hygiene, orthodontic treatment, adults, randomized clinical trial

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Authors: Kibrom Hadush

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Countries like Ethiopia, whose economy is mainly rain-fed dependent agriculture, are highly vulnerable to climate variability and weather extremes. Sub-seasonal (monthly) and dekadal forecasts are hence critical for crop production and water resource management. Therefore, this paper was conducted to study the predictability and variability of Kiremt rainfall over the northern half of Ethiopia on monthly and dekadal time scales in association with global Sea Surface Temperature (SST) at different lag time. Trends in rainfall have been analyzed on annual, seasonal (Kiremt), monthly, and dekadal (June–September) time scales based on rainfall records of 36 meteorological stations distributed across four homogenous zones of the northern half of Ethiopia for the period 1992–2017. The results from the progressive Mann–Kendall trend test and the Sen’s slope method shows that there is no significant trend in the annual, Kiremt, monthly and dekadal rainfall total at most of the station's studies. Moreover, the rainfall in the study area varies spatially and temporally, and the distribution of the rainfall pattern increases from the northeast rift valley to northwest highlands. Methods of analysis include graphical correlation and multiple linear regression model are employed to investigate the association between the global SSTs and Kiremt rainfall over the homogeneous rainfall zones and to predict monthly and dekadal (June-September) rainfall using SST predictors. The results of this study show that in general, SST in the equatorial Pacific Ocean is the main source of the predictive skill of the Kiremt rainfall variability over the northern half of Ethiopia. The regional SSTs in the Atlantic and the Indian Ocean as well contribute to the Kiremt rainfall variability over the study area. Moreover, the result of the correlation analysis showed that the decline of monthly and dekadal Kiremt rainfall over most of the homogeneous zones of the study area are caused by the corresponding persistent warming of the SST in the eastern and central equatorial Pacific Ocean during the period 1992 - 2017. It is also found that the monthly and dekadal Kiremt rainfall over the northern, northwestern highlands and northeastern lowlands of Ethiopia are positively correlated with the SST in the western equatorial Pacific, eastern and tropical northern the Atlantic Ocean. Furthermore, the SSTs in the western equatorial Pacific and Indian Oceans are positively correlated to the Kiremt season rainfall in the northeastern highlands. Overall, the results showed that the prediction models using combined SSTs at various ocean regions (equatorial and tropical) performed reasonably well in the prediction (With R2 ranging from 30% to 65%) of monthly and dekadal rainfall and recommends it can be used for efficient prediction of Kiremt rainfall over the study area to aid with systematic and informed decision making within the agricultural sector.

Keywords: dekadal, Kiremt rainfall, monthly, Northern Ethiopia, sea surface temperature

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Authors: M. I. Ribah, M. Jibir, Y. A. Bashar, S. S. Manga

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Food safety is a significant and growing public health problem in the world and Nigeria as a developing country, since food-borne diseases are important contributors to the huge burden of sickness and death of humans. In Nigeria, traditional ready-to-eat meat products (RTE-MPs) like balangu, tsire, guru and dried meat products like kilishi, dambun nama, banda, were reported to be highly appreciated because of their eating qualities. The consumption of these products was considered as safe due to the treatments that are usually involved during their production process. However, during processing and handling, the products could be contaminated by pathogens that could cause food poisoning. Therefore, a hazard identification for pathogenic bacteria on some traditional RTE-MPs was conducted in Kebbi and Sokoto States, Nigeria. A total of 116 RTE-MPs (balangu-38, kilishi-39 and tsire-39) samples were obtained from retail outlets and analyzed using standard cultural microbiological procedures in general and selective enrichment media to isolate the target pathogens. A six-fold serial dilution was prepared and using the pour plating method, colonies were counted. Serial dilutions were selected based on the prepared pre-labeled Petri dishes for each sample. A volume of 10-12 ml of molten Nutrient agar cooled to 42-45°C was poured into each Petri dish and 1 ml each from dilutions of 102, 104 and 106 for every sample was respectively poured on a pre-labeled Petri plate after which colonies were counted. The isolated pathogens were identified and confirmed after series of biochemical tests. Frequencies and percentages were used to describe the presence of pathogens. The General Linear Model was used to analyze data on pathogen presence according to RTE-MPs and means were separated using the Tukey test at 0.05 confidence level. Of the 116 RTE-MPs samples collected, 35 (30.17%) samples were found to be contaminated with some tested pathogens. Prevalence results showed that Escherichia coli, salmonella and Staphylococcus aureus were present in the samples. Mean total bacterial count was 23.82×106 cfu/g. The frequency of individual pathogens isolated was; Staphylococcus aureus 18 (15.51%), Escherichia coli 12 (10.34%) and Salmonella 5 (4.31%). Also, among the RTE-MPs tested, the total bacterial counts were found to differ significantly (P < 0.05), with 1.81, 2.41 and 2.9×104 cfu/g for tsire, kilishi, and balangu, respectively. The study concluded that the presence of pathogenic bacteria in balangu could pose grave health risks to consumers, and hence, recommended good manufacturing practices in the production of balangu to improve the products’ safety.

Keywords: ready-to-eat meat products, retail outlets, public health, safety assessment

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Authors: Aderonke Olaitan Adesina

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Background: The paradigm shift to knowledge, as the key to organizational innovation and competitive advantage, has made the management of knowledge resources in organizations a mandate. A key component of the knowledge management (KM) cycle is knowledge creation, which is researched to be the result of the interaction between explicit and tacit knowledge. An effective knowledge creation process requires the use of the right model. The SECI (Socialisation, Externalisation, Combination, and Internalisation) model, proposed in 1995, is attested to be a preferred model of choice for knowledge creation activities. The model has, however, been criticized by researchers, who raise their concern, especially about its sequential nature. Therefore, this paper reviews extant literature on the practical application of each mode of the SECI model, from 1995 to date, with a view to ascertaining the relevance in modern-day KM practice. The study will establish the trends of use, with regards to the location and industry of use, and the interconnectedness of the modes. The main research question is, for organizational knowledge creation activities, is the SECI model indeed linear and sequential? In other words, does the model need to be reviewed in today’s KM practice? The review will generate a compendium of the usage of the SECI modes and propose a framework of use, based on the strength weaknesses opportunities and threats (SWOT) findings of the study. Method: This study will employ the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to investigate the usage and SWOT of the modes, in order to ascertain the success, or otherwise, of the sequential application of the modes in practice from 1995 to 2019. To achieve the purpose, four databases will be explored to search for open access, peer-reviewed articles from 1995 to 2019. The year 1995 is chosen as the baseline because it was the year the first paper on the SECI model was published. The study will appraise relevant peer-reviewed articles under the search terms: SECI (or its synonym, knowledge creation theory), socialization, externalization, combination, and internalization in the title, abstract, or keywords list. This review will include only empirical studies of knowledge management initiatives in which the SECI model and its modes were used. Findings: It is expected that the study will highlight the practical relevance of each mode of the SECI model, the linearity or not of the model, the SWOT in each mode. Concluding Statement: Organisations can, from the analysis, determine the modes of emphasis for their knowledge creation activities. It is expected that the study will support decision making in the choice of the SECI model as a strategy for the management of organizational knowledge resources, and in appropriating the SECI model, or its remodeled version, as a theoretical framework in future KM research.

Keywords: combination, externalisation, internalisation, knowledge management, SECI model, socialisation

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Authors: Anita Richter

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Innovation is one of the key foundations of competitive advantage, generating growth and welfare worldwide. Consequently, all firms should innovate to bring new ideas to the market. Innovation is a vital growth driver, particularly for transition countries to move towards knowledge-based, high-income economies. However, numerous barriers, such as financial, regulatory or infrastructural constraints prevent, in particular, new and small firms in transition countries from innovating. Thus SMEs’ innovation output may benefit substantially from government support. This research paper aims to assess the effect of government interventions on innovation activities in SMEs in emerging countries. Until now academic research related to the innovation policies focused either on single country and/or high-income countries assessments and less on cross-country and/or low and middle-income countries. Therefore the paper seeks to close the research gap by providing empirical evidence from 8,500 firms in 15 transition countries (Eastern Europe, South Caucasus, South East Europe, Middle East and North Africa). Using firm-level data from the Business Environment and Enterprise Performance Survey of the World Bank and EBRD and policy data from the SME Policy Index of the OECD, the paper investigates how government interventions affect SME’s likelihood of investing in any technological and non-technological innovation. Using the Standard Linear Regression, the impact of government interventions on SMEs’ innovation output and R&D activities is measured. The empirical analysis suggests that a firm’s decision to invest into innovative activities is sensitive to government interventions. A firm’s likelihood to invest into innovative activities increases by 3% to 8%, if the innovation eco-system noticeably improves (measured by an increase of 1 level in the SME Policy Index). At the same time, a better eco-system encourages SMEs to invest more in R&D. Government reforms in establishing a dedicated policy framework (IP legislation), institutional infrastructure (science and technology parks, incubators) and financial support (public R&D grants, innovation vouchers) are particularly relevant to stimulate innovation performance in SMEs. Particular segments of the SME population, namely micro and manufacturing firms, are more likely to benefit from an increased innovation framework conditions. The marginal effects are particularly strong on product innovation, process innovation, and marketing innovation, but less on management innovation. In conclusion, government interventions supporting innovation will likely lead to higher innovation performance of SMEs. They increase productivity at both firm and country level, which is a vital step in transitioning towards knowledge-based market economies.

Keywords: innovation, research and development, government interventions, economic development, small and medium-sized enterprises, transition countries

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Authors: A. G. Akhundov

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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 176

Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat

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This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.

Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

Procedia PDF Downloads 85

Authors: Faezeh Mosallat, Eric L. Bibeau, Tarek El Mekkawy

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Availability of a wide variety of renewable resources, such as large reserves of hydro, biomass, solar and wind in Canada provides significant potential to improve the sustainability of energy uses. As buildings represent a considerable portion of energy use in Canada, application of distributed solar energy systems for heating and cooling may increase the amount of renewable energy use. Parabolic solar trough systems have seen limited deployments in cold northern climates as they are more suitable for electricity production in southern latitudes. Heat production by concentrating solar rays using parabolic troughs can overcome the poor efficiencies of flat panels and evacuated tubes in cold climates. A numerical dynamic model is developed to simulate an installed parabolic solar trough facility in Winnipeg. The results of the numerical model are validated using the experimental data obtained from this system. The model is developed in Simulink and will be utilized to simulate a tri-generation system for heating, cooling and electricity generation in remote northern communities. The main objective of this simulation is to obtain operational data of solar troughs in cold climates as this is lacking in the literature. In this paper, the validated Simulink model is applied to simulate a solar assisted absorption cooling system along with electricity generation using organic Rankine cycle (ORC) and thermal storage. A control strategy is employed to distribute the heated oil from solar collectors among the above three systems considering the temperature requirements. This modeling provides dynamic performance results using real time minutely meteorological data which are collected at the same location the solar system is installed. This is a big step ahead of the current models by accurately calculating the available solar energy at each time step considering the solar radiation fluctuations due to passing clouds. The solar absorption cooling is modeled to use the generated heat from the solar trough system and provide cooling in summer for a greenhouse which is located next to the solar field. A natural gas water heater provides the required excess heat for the absorption cooling at low or no solar radiation periods. The results of the simulation are presented for a summer month in Winnipeg which includes the amount of generated electric power from ORC and contribution of solar energy in the cooling load provision

Keywords: absorption cooling, parabolic solar trough, remote community, validated model

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Authors: Stefan Peters, Phillip Roetman

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The global loss of biodiversity is threatening the benefits nature provides to human populations and has become a more pressing issue than climate change and requires immediate attention. While there have been successful global agreements for environmental protection, such as the Montreal Protocol, these are rare, and we cannot rely on them solely. Thus, it is crucial to take national and local actions to support biodiversity. Australia is one of the 17 countries in the world with a high level of biodiversity, and its cities are vital habitats for endangered species, with more of them found in urban areas than in non-urban ones. However, the protection of biodiversity in metropolitan Adelaide has been inadequate, with over 130 species disappearing since European colonization in 1836. In this research project we conceptualized, developed and implemented a framework for wildlife Habitat Hotspots and Habitat Corridor modelling in an urban context using geographic data and GIS modelling and analysis. We used detailed topographic and other geographic data provided by a local council, including spatial and attributive properties of trees, parcels, water features, vegetated areas, roads, verges, traffic, and census data. Weighted factors considered in our raster-based Habitat Hotspot model include parcel size, parcel shape, population density, canopy cover, habitat quality and proximity to habitats and water features. Weighted factors considered in our raster-based Habitat Corridor model include habitat potential (resulting from the Habitat Hotspot model), verge size, road hierarchy, road widths, human density, and presence of remnant indigenous vegetation species. We developed a GIS model, using Python scripting and ArcGIS-Pro Model-Builder, to establish an automated reproducible and adjustable geoprocessing workflow, adaptable to any study area of interest. Our habitat hotspot and corridor modelling framework allow to determine and map existing habitat hotspots and wildlife habitat corridors. Our research had been applied to the study case of Burnside, a local council in Adelaide, Australia, which encompass an area of 30 km2. We applied end-user expertise-based category weightings to refine our models and optimize the use of our habitat map outputs towards informing local strategic decision-making.

Keywords: biodiversity, GIS modeling, habitat hotspot, wildlife corridor

Procedia PDF Downloads 92

Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices.

Keywords: Industry 4.0., mass customization, production networks, virtual process-chain

Procedia PDF Downloads 258

Authors: Marita Pigłowska, Beata Kurc, Paweł Daszkiewicz

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Railway vehicles are divided into two groups: traction (powered) vehicles and wagons. The traction vehicles include locomotives (line and shunting), railcars (sometimes referred to as railbuses), and multiple units (electric and diesel), consisting of several or a dozen carriages. In vehicles with diesel traction, fuel energy (petrol, diesel, or compressed gas) is converted into mechanical energy directly in the internal combustion engine or via electricity. In the latter case, the combustion engine generator produces electricity that is then used to drive the vehicle (diesel-electric drive or electric transmission). In Poland, such a solution dominates both in heavy linear and shunting locomotives. The classic diesel drive is available for the lightest shunting locomotives, railcars, and passenger diesel multiple units. Vehicles with electric traction do not have their own source of energy -they use pantographs to obtain electricity from the traction network. To determine the competitiveness of the hydrogen propulsion system, it is essential to understand how it works. The basic elements of the construction of a railway vehicle drive system that uses hydrogen as a source of traction force are fuel cells, batteries, fuel tanks, traction motors as well as main and auxiliary converters. The compressed hydrogen is stored in tanks usually located on the roof of the vehicle. This resource is supplemented with the use of specialized infrastructure while the vehicle is stationary. Hydrogen is supplied to the fuel cell, where it oxidizes. The effect of this chemical reaction is electricity and water (in two forms -liquid and water vapor). Electricity is stored in batteries (so far, lithium-ion batteries are used). Electricity stored in this way is used to drive traction motors and supply onboard equipment. The current generated by the fuel cell passes through the main converter, whose task is to adjust it to the values required by the consumers, i.e., batteries and the traction motor. The work will attempt to construct a fuel cell with unique electrodes. This research is a trend that connects industry with science. The first goal will be to obtain hydrogen on a large scale in tube furnaces, to thoroughly analyze the obtained structures (IR), and to apply the method in fuel cells. The second goal is to create low-energy energy storage and distribution station for hydrogen and electric vehicles. The scope of the research includes obtaining a carbon variety and obtaining oxide systems on a large scale using a tubular furnace and then supplying vehicles. Acknowledgments: This work is supported by the Polish Ministry of Science and Education, project "The best of the best! 4.0", number 0911/MNSW/4968 – M.P. and grant 0911/SBAD/2102—B.K.

Keywords: railway, hydrogen, fuel cells, hybrid vehicles

Procedia PDF Downloads 168

Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

Procedia PDF Downloads 156

Authors: Sarah J. C. Slabbert

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The uptake of research as part of the diffusion or adoption of innovation by practitioners, whether individuals or organisations, has been a popular topic in agricultural development studies for many decades. In the classical, linear model of innovation theory, the innovation originates from an expert source such as a state-supported research organisation or academic institution. The changing context of agriculture led to the development of the agricultural innovation systems model, which recognizes innovation as a complex interaction between individuals and organisations, which include private industry and collective action organisations. In terms of this model, an innovation can be developed and adopted without any input or intervention from a state or parastatal research organisation. This evolution in the diffusion of agricultural innovation has put forward new challenges for state or parastatal research organisations, which have to demonstrate the impact of their research to the legislature or a regulatory authority: Unless the organisation and the research it produces cross the knowledge paths of the intended audience, there will be no awareness, no uptake and certainly no impact. It is therefore critical for such a research organisation to base its communication strategy on a thorough understanding of the knowledge needs, information sources and knowledge networks of the intended target audience. In 2016, the South African Water Research Commission (WRC) commissioned a study to investigate the knowledge needs, information sources and knowledge networks of Water User Associations and commercial irrigators with the aim of improving uptake of its research on efficient water use in irrigation. The first phase of the study comprised face-to-face interviews with the CEOs and Board Chairs of four Water User Associations along the Orange River in South Africa, and 36 commercial irrigation farmers from the same four irrigation schemes. Intermediaries who act as knowledge conduits to the Water User Associations and the irrigators were identified and 20 of them were subsequently interviewed telephonically. The study found that irrigators interact regularly with grower organisations such as SATI (South African Table Grape Industry) and SAPPA (South African Pecan Nut Association) and that they perceive these organisations as credible, trustworthy and reliable, within their limitations. State and parastatal research institutions, on the other hand, are associated with a range of negative attributes. As a result, the awareness of, and interest in, the WRC and its research on water use efficiency in irrigated agriculture are low. The findings suggest that a communication strategy that involves collaboration with these grower organisations would empower the WRC to participate much more efficiently and with greater impact in agricultural innovation networks. The paper will elaborate on the findings and discuss partnering frameworks and opportunities to manage perceptions and uptake.

Keywords: agricultural innovation systems, communication strategy, diffusion of innovation, irrigated agriculture, knowledge paths, research organisations, target audiences, water use efficiency

Procedia PDF Downloads 97

Authors: Pamela R. Jackson, Andrea Hawkins-Daarud, Cassandra R. Rickertsen, Kamala Clark-Swanson, Scott A. Whitmire, Kristin R. Swanson

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Glioblastoma Multiforme (GBM), the most common primary brain tumor, often presents with hyperintensity on T2-weighted or T2-weighted fluid attenuated inversion recovery (T2/FLAIR) magnetic resonance imaging (MRI). This hyperintensity corresponds with vasogenic edema, however there are likely many infiltrating tumor cells within the hyperintensity as well. While MRIs do not directly indicate tumor cells, MRIs do reflect the microenvironmental water abnormalities caused by the presence of tumor cells and edema. The inherent heterogeneity and resulting MRI features of GBMs complicate assessing disease response. To understand how hyperintensity on T2/FLAIR MRI may correlate with edema in the extracellular space (ECS), a multi-compartmental MRI signal equation which takes into account tissue compartments and their associated volumes with input coming from a mathematical model of glioma growth that incorporates edema formation was explored. The reasonableness of two possible extracellular space schema was evaluated by varying the T2 of the edema compartment and calculating the possible resulting T2s in tumor and peripheral edema. In the mathematical model, gliomas were comprised of vasculature and three tumor cellular phenotypes: normoxic, hypoxic, and necrotic. Edema was characterized as fluid leaking from abnormal tumor vessels. Spatial maps of tumor cell density and edema for virtual tumors were simulated with different rates of proliferation and invasion and various ECS expansion schemes. These spatial maps were then passed into a multi-compartmental MRI signal model for generating simulated T2/FLAIR MR images. Individual compartments’ T2 values in the signal equation were either from literature or estimated and the T2 for edema specifically was varied over a wide range (200 ms – 9200 ms). T2 maps were calculated from simulated images. T2 values based on simulated images were evaluated for regions of interest (ROIs) in normal appearing white matter, tumor, and peripheral edema. The ROI T2 values were compared to T2 values reported in literature. The expanding scheme of extracellular space is had T2 values similar to the literature calculated values. The static scheme of extracellular space had a much lower T2 values and no matter what T2 was associated with edema, the intensities did not come close to literature values. Expanding the extracellular space is necessary to achieve simulated edema intensities commiserate with acquired MRIs.

Keywords: extracellular space, glioblastoma multiforme, magnetic resonance imaging, mathematical modeling

Procedia PDF Downloads 221

Authors: Rasha Waheeb, Bjorn Andersen, Rafa Shakir

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Purpose The purpose of this study is to avoid delays that occur in emergency reconstruction projects especially in post disaster circumstances whether if they were natural or manmade due to their particular national and humanitarian importance. We presented a theoretical and practical concepts for projects management in the field of construction industry that deal with a range of global and local trails. This study aimed to identify the factors of effective delay in construction projects in Iraq that affect the time and the specific quality cost, and find the best solutions to address delays and solve the problem by setting parameters to restore balance in this study. 30 projects were selected in different areas of construction were selected as a sample for this study. Design/methodology/approach This study discusses the reconstruction strategies and delay in time and cost caused by different delay factors in some selected projects in Iraq (Baghdad as a case study).A case study approach was adopted, with thirty construction projects selected from the Baghdad region, of different types and sizes. Project participants from the case projects provided data about the projects through a data collection instrument distributed through a survey. Mixed approach and methods were applied in this study. Mathematical data analysis was used to construct models to predict delay in time and cost of projects before they started. The artificial neural networks analysis was selected as a mathematical approach. These models were mainly to help decision makers in construction project to find solutions to these delays before they cause any inefficiency in the project being implemented and to strike the obstacles thoroughly to develop this industry in Iraq. This approach was practiced using the data collected through survey and questionnaire data collection as information form. Findings The most important delay factors identified leading to schedule overruns were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. Some of these are quite in line with findings from similar studies in other countries/regions, but some are unique to the Iraqi project sample, such as security issues and low-price bid selection. Originality/value we selected ANN’s analysis first because ANN’s was rarely used in project management , and never been used in Iraq to finding solutions for problems in construction industry. Also, this methodology can be used in complicated problems when there is no interpretation or solution for a problem. In some cases statistical analysis was conducted and in some cases the problem is not following a linear equation or there was a weak correlation, thus we suggested using the ANN’s because it is used for nonlinear problems to find the relationship between input and output data and that was really supportive.

Keywords: construction projects, delay factors, emergency reconstruction, innovation ANN, post disasters, project management

Procedia PDF Downloads 149

Authors: Aron Witkowski, Andrzej Wodecki

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Purpose: This study aims to explore the feasibility and effectiveness of utilizing Generative Artificial Intelligence (GenAI) agents as product managers within the manufacturing sector. It seeks to evaluate whether current GenAI capabilities can fulfill the complex requirements of product management and deliver comparable outcomes to human counterparts. Study Design/Methodology/Approach: This research involved the creation of a support application for product managers, utilizing high-quality sources on product management and generative AI technologies. The application was designed to assist in various aspects of product management tasks. To evaluate its effectiveness, a study was conducted involving 10 experienced product managers from the manufacturing sector. These professionals were tasked with using the application and providing feedback on the tool's responses to common questions and challenges they encounter in their daily work. The study employed a mixed-methods approach, combining quantitative assessments of the tool's performance with qualitative interviews to gather detailed insights into the user experience and perceived value of the application. Findings: The findings reveal that GenAI-based product management agents exhibit significant potential in handling routine tasks, data analysis, and predictive modeling. However, there are notable limitations in areas requiring nuanced decision-making, creativity, and complex stakeholder interactions. The case study demonstrates that while GenAI can augment human capabilities, it is not yet fully equipped to independently manage the holistic responsibilities of a product manager in the manufacturing sector. Originality/Value: This research provides an analysis of GenAI's role in product management within the manufacturing industry, contributing to the limited body of literature on the application of GenAI agents in this domain. It offers practical insights into the current capabilities and limitations of GenAI, helping organizations make informed decisions about integrating AI into their product management strategies. Implications for Academic and Practical Fields: For academia, the study suggests new avenues for research in AI-human collaboration and the development of advanced AI systems capable of higher-level managerial functions. Practically, it provides industry professionals with a nuanced understanding of how GenAI can be leveraged to enhance product management, guiding investments in AI technologies and training programs to bridge identified gaps.

Keywords: generative artificial intelligence, GenAI, NPD, new product development, product management, manufacturing

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Authors: Danilo F. Rodrigues, Hérida Regina N. Salgado

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Introduction: The emergence of resistant microorganisms to a large number of clinically approved antimicrobials has been increasing, which restrict the options for the treatment of bacterial infections. As a strategy, drugs with high antimicrobial activities are in evidence. Stands out a class of antimicrobial, the cephalosporins, having as fourth generation cefepime (CEF) a semi-synthetic product which has activity against various Gram-positive bacteria (e.g. oxacillin resistant Staphylococcus aureus) and Gram-negative (e.g. Pseudomonas aeruginosa) aerobic. There are few studies in the literature regarding the development of microbiological methodologies for the analysis of this antimicrobial, so researches in this area are highly relevant to optimize the analysis of this drug in the industry and ensure the quality of the marketed product. The development of microbiological methods for the analysis of antimicrobials has gained strength in recent years and has been highlighted in relation to physicochemical methods, especially because they make possible to determine the bioactivity of the drug against a microorganism. In this context, the aim of this work was the development and validation of a microbiological method for quantitative analysis of CEF in powder lyophilized for injectable solution by turbidimetric assay. Method: For performing the method, Staphylococcus aureus ATCC 6538 IAL 2082 was used as the test microorganism and the culture medium chosen was the Casoy broth. The test was performed using temperature control (35.0 °C ± 2.0 °C) and incubated for 4 hours in shaker. The readings of the results were made at a wavelength of 530 nm through a spectrophotometer. The turbidimetric microbiological method was validated by determining the following parameters: linearity, precision (repeatability and intermediate precision), accuracy and robustness, according to ICH guidelines. Results and discussion: Among the parameters evaluated for method validation, the linearity showed results suitable for both statistical analyses as the correlation coefficients (r) that went 0.9990 for CEF reference standard and 0.9997 for CEF sample. The precision presented the following values 1.86% (intraday), 0.84% (interday) and 0.71% (between analyst). The accuracy of the method has been proven through the recovery test where the mean value obtained was 99.92%. The robustness was verified by the parameters changing volume of culture medium, brand of culture medium, incubation time in shaker and wavelength. The potency of CEF present in the samples of lyophilized powder for injectable solution was 102.46%. Conclusion: The turbidimetric microbiological method proposed for quantification of CEF in lyophilized powder for solution for injectable showed being fast, linear, precise, accurate and robust, being in accordance with all the requirements, which can be used in routine analysis of quality control in the pharmaceutical industry as an option for microbiological analysis.

Keywords: cefepime hydrochloride, quality control, turbidimetric assay, validation

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Authors: B. Yaman, G. Acikbas, N. Calis Acikbas

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Epoxy based materials have advantages in tribological applications due to their unique properties such as light weight, self-lubrication capacity and wear resistance. On the other hand, their usage is often limited by their low load bearing capacity and low thermal conductivity values. In this study, it is aimed to improve tribological and also mechanical properties of epoxy by reinforcing with ceramic based porcelain waste. It is well-known that the reuse or recycling of waste materials leads to reduction in production costs, ease of manufacturing, saving energy, etc. From this perspective, epoxy and epoxy matrix composites containing 60wt% porcelain waste with different particle size in the range of below 90µm and 150-250µm were fabricated, and the effect of filler particle size on the mechanical and tribological properties was investigated. The microstructural characterization was carried out by scanning electron microscopy (SEM), and phase analysis was determined by X-ray diffraction (XRD). The Archimedes principle was used to measure the density and porosity of the samples. The hardness values were measured using Shore-D hardness, and bending tests were performed. Microstructural investigations indicated that porcelain particles were homogeneously distributed and no agglomerations were encountered in the epoxy resin. Mechanical test results showed that the hardness and bending strength were increased with increasing particle size related to low porosity content and well embedding to the matrix. Tribological behavior of these composites was evaluated in terms of friction, wear rates and wear mechanisms by ball-on-disk contact with dry and rotational sliding at room temperature against WC ball with a diameter of 3mm. Wear tests were carried out at room temperature (23–25°C) with a humidity of 40 ± 5% under dry-sliding conditions. The contact radius of cycles was set to 5 mm at linear speed of 30 cm/s for the geometry used in this study. In all the experiments, 3N of constant test load was applied at a frequency of 8 Hz and prolonged to 400m wear distance. The friction coefficient of samples was recorded online by the variation in the tangential force. The steady-state CoFs were changed in between 0,29-0,32. The dimensions of the wear tracks (depth and width) were measured as two-dimensional profiles by a stylus profilometer. The wear volumes were calculated by integrating these 2D surface areas over the diameter. Specific wear rates were computed by dividing the wear volume by the applied load and sliding distance. According to the experimental results, the use of porcelain waste in the fabrication of epoxy resin composites can be suggested to be potential materials due to allowing improved mechanical and tribological properties and also providing reduction in production cost.

Keywords: epoxy composites, mechanical properties, porcelain waste, tribological properties

Procedia PDF Downloads 183

Authors: Sihem Bazid, Meriem El Kolli, Aicha Medjahed

Abstract:

Proteins and polysaccharides are the two types of biopolymers most frequently used in the food industry to control the mechanical properties and structural stability and organoleptic properties of the products. The textural and structural properties of these two types of blend polymers depend on their interaction and their ability to form organized structures. From an industrial point of view, a better understanding of mixtures protein / polysaccharide is an important issue since they are already heavily involved in processed food. It is in this context that we have chosen to work on a model system composed of a fibrous protein mixture (gelatin)/anionic polysaccharide (sodium carboxymethylcellulose). Gelatin, one of the most popular biopolymers, is widely used in food, pharmaceutical, cosmetic and photographic applications, because of its unique functional and technological properties. Sodium Carboxymethylcellulose (NaCMC) is an anionic linear polysaccharide derived from cellulose. It is an important industrial polymer with a wide range of applications. The functional properties of this anionic polysaccharide can be modified by the presence of proteins with which it might interact. Another factor may also manage the interaction of protein-polysaccharide mixtures is the triple helix of the gelatin. Its complex synthesis method results in an extracellular assembly containing several levels. Collagen can be in a soluble state or associate into fibrils, which can associate in fiber. Each level corresponds to an organization recognized by the cellular and metabolic system. Gelatin allows this approach, the formation of gelatin gel has triple helical folding of denatured collagen chains, this gel has been the subject of numerous studies, and it is now known that the properties depend only on the rate of triple helices forming the network. Chemical modification of this system is quite controlled. Observe the dynamics of the triple helix may be relevant in understanding the interactions involved in protein-polysaccharides mixtures. Gelatin is central to any industrial process, understand and analyze the molecular dynamics induced by the triple helix in the transitions gelatin, can have great economic importance in all fields and especially the food. The goal is to understand the possible mechanisms involved depending on the nature of the mixtures obtained. From a fundamental point of view, it is clear that the protective effect of NaCMC on gelatin and conformational changes of the α helix are strongly influenced by the nature of the medium. Our goal is to minimize the maximum the α helix structure changes to maintain more stable gelatin and protect against denaturation that occurs during such conversion processes in the food industry. In order to study the nature of interactions and assess the properties of mixtures, polarimetry was used to monitor the optical parameters and to assess the rate of helicity gelatin.

Keywords: gelatin, sodium carboxymethylcellulose, interaction gelatin-NaCMC, the rate of helicity, polarimetry

Procedia PDF Downloads 293

Authors: Hemant Upadhyay, Tarun Kumar Kundu

Abstract:

It is utmost important for a blast furnace operator to understand the mechanisms governing the liquid flow, accumulation, drainage and heat transfer between various phases in blast furnace hearth for a stable and efficient blast furnace operation. Abnormal drainage behavior may lead to high liquid build up in the hearth. Operational problems such as pressurization, low wind intake, and lower material descent rates, normally be encountered if the liquid levels in the hearth exceed a critical limit when Hearth coke and Deadman start to float. Similarly, hot metal temperature is an important parameter to be controlled in the BF operation; it should be kept at an optimal level to obtain desired product quality and a stable BF performance. It is not possible to carry out any direct measurement of above due to the hostile conditions in the hearth with chemically aggressive hot liquids. The objective here is to develop a mathematical model to simulate the variation in hot metal / slag accumulation and temperature during the tapping of the blast furnace based on the computed drainage rate, production rate, mass balance, heat transfer between metal and slag, metal and solids, slag and solids as well as among the various zones of metal and slag itself. For modeling purpose, the BF hearth is considered as a pressurized vessel, filled with solid coke particles. Liquids trickle down in hearth from top and accumulate in voids between the coke particles which are assumed thermally saturated. A set of generic mass balance equations gives the amount of metal and slag intake in hearth. A small drainage (tap hole) is situated at the bottom of the hearth and flow rate of liquids from tap hole is computed taking in account the amount of both the phases accumulated their level in hearth, pressure from gases in the furnace and erosion behaviors of tap hole itself. Heat transfer equations provide the exchange of heat between various layers of liquid metal and slag, and heat loss to cooling system through refractories. Based on all that information a dynamic simulation is carried out which provides real time information of liquids accumulation in hearth before and during tapping, drainage rate and its variation, predicts critical event timings during tapping and expected tapping temperature of metal and slag on preset time intervals. The model is in use at JSPL, India BF-II and its output is regularly cross-checked with actual tapping data, which are in good agreement.

Keywords: blast furnace, hearth, deadman, hotmetal

Procedia PDF Downloads 172

Authors: Corinna Zeli, Silvia Calati, Marco Simeoni, Chiara Comastri

Abstract:

Developmental stuttering affects about 10% of preschool children; although the high percentage of natural recovery, a quarter of them will become an adult who stutters. An effective early intervention should help those children with high persistence risk for the future. The Psicodizione method for early stuttering is an Italian behavior indirect treatment for preschool children who stutter in which method parents act as good guides for communication, modeling their own fluency. In this study, we give a preliminary measure to evaluate the long-term effectiveness of Psicodizione method on stuttering preschool children with a high persistence risk. Among all Italian children treated with the Psicodizione method between 2018 and 2019, we selected 8 kids with at least 3 high risk persistence factors from the Illinois Prediction Criteria proposed by Yairi and Seery. The factors chosen for the selection were: one parent who stutters (1pt mother; 1.5pt father), male gender, ≥ 4 years old at onset; ≥ 12 months from onset of symptoms before treatment. For this study, the families were contacted after an average period of time of 14,7 months (range 3 - 26 months). Parental reports were gathered with a standard online questionnaire in order to obtain data reflecting fluency from a wide range of the children’s life situations. The minimum worthwhile outcome was set at "mild evidence" in a 5 point Likert scale (1 mild evidence- 5 high severity evidence). A second group of 6 children, among those treated with the Piscodizione method, was selected as high potential for spontaneous remission (low persistence risk). The children in this group had to fulfill all the following criteria: female gender, symptoms for less than 12 months (before treatment), age of onset <4 years old, none of the parents with persistent stuttering. At the time of this follow-up, the children were aged 6–9 years, with a mean of 15 months post-treatment. Among the children in the high persistence risk group, 2 (25%) hadn’t had stutter anymore, and 3 (37,5%) had mild stutter based on parental reports. In the low persistency risk group, the children were aged 4–6 years, with a mean of 14 months post-treatment, and 5 (84%) hadn’t had stutter anymore (for the past 16 months on average).62,5% of children at high risk of persistence after Psicodizione treatment showed mild evidence of stutter at most. 75% of parents confirmed a better fluency than before the treatment. The low persistence risk group seemed to be representative of spontaneous recovery. This study’s design could help to better evaluate the success of the proposed interventions for stuttering preschool children and provides a preliminary measure of the effectiveness of the Psicodizione method on high persistence risk children.

Keywords: early treatment, fluency, preschool children, stuttering

Procedia PDF Downloads 194