Search results for: hybrid working models

Authors: Mohamed Abdalla Saleem

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Around one hundred wells were drilled in the Cyrenaica platform north-east Libya, and almost all of them were dry. Although the drilled samples reveal good oil shows and good source rock maturity. Most of the upper Cretaceous age and the above deposit successions are outcrops in different places. We have a thorough understanding and mapping of the structures related to the Cretaceous and above Cenozoic Era. But the subsurface beneath these outcrops still needs more investigation and delineation. This study aims to give answers to some questions about the tectonic history and the types of structures that are distributed in the area using gravity, magnetic, and well data. According to the information that has been obtained from groups of wells drilled in concessions 31, 35, and 37, one can note that the depositional sections become ticker and deeper southward. The topography map of the study area shows that the area is highly elevated at the north, about 300 m above the sea level, while the minimum elevation (16–18 m) exists nearly in the middle (lat. 30°). South to this latitude, the area is started elevated again (more than 100 m). The third-order residual gravity map, which was constructed from the Bouguer gravity map, reveals that the area is dominated by a large negative anomaly working as a sub-basin (245 km x 220 km), which means a very thick depositional section, and the basement is very deep. The mentioned depocenter is surrounded by four high gravity anomalies (12-37 mGal), which means a shallow basement and a relative thinner succession of sediments. The highest gravity values are located beside the coast line. The total horizontal gradient (THG) map reveals various systems of structures, the first system where the structures are oriented NE-SW, which is crosscut by the second regime extending NW-SE. This second system is distributed through the whole area, but it is very strong and shallow near the coast line and at the south part, while it is relatively deep at the middle depocenter area.

Keywords: cyrenaica platform, gravity, structures, basement, tectonic history

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Authors: Manuel Alejandro Taborda Ceballos, Martin Sommerfeld

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Transport phenomena and dispersion of non-spherical particle in turbulent flows are found everywhere in industrial application and processes. Powder handling, pollution control, pneumatic transport, particle separation are just some examples where the particle encountered are not only spherical. These types of multiphase flows are wall bounded and mostly highly turbulent. The particles found in these processes are rarely spherical but may have various shapes (e.g., fibers, and rods). Although research related to the behavior of regular non-spherical particles in turbulent flows has been carried out for many years, it is still necessary to refine models, especially near walls where the interaction fiber-wall changes completely its behavior. Imaging-based experimental studies on dispersed particle-laden flows have been applied for many decades for a detailed experimental analysis. These techniques have the advantages that they provide field information in two or three dimensions, but have a lower temporal resolution compared to point-wise techniques such as PDA (phase-Doppler anemometry) and derivations therefrom. The applied imaging techniques in dispersed two-phase flows are extensions from classical PIV (particle image velocimetry) and PTV (particle tracking velocimetry) and the main emphasis was simultaneous measurement of the velocity fields of both phases. In a similar way, such data should also provide adequate information for validating the proposed models. Available experimental studies on the behavior of non-spherical particles are uncommon and mostly based on planar light-sheet measurements. Especially for elongated non-spherical particles, however, three-dimensional measurements are needed to fully describe their motion and to provide sufficient information for validation of numerical computations. For further providing detailed experimental results allowing a validation of numerical calculations of non-spherical particle dispersion in turbulent flows, a water channel test facility was built around a horizontal closed water channel. Into this horizontal main flow, a small cross-jet laden with fiber-like particles was injected, which was also solely driven by gravity. The dispersion of the fibers was measured by applying imaging techniques based on a LED array for backlighting and high-speed cameras. For obtaining the fluid velocity fields, almost neutrally buoyant tracer was used. The discrimination between tracer and fibers was done based on image size which was also the basis to determine fiber orientation with respect to the inertial coordinate system. The synchronous measurement of fluid velocity and fiber properties also allow the collection of statistics of fiber orientation, velocity fields of tracer and fibers, the angular velocity of the fibers and the orientation between fiber and instantaneous relative velocity. Consequently, an experimental study the behavior of elongated non-spherical particles in wall bounded turbulent flows was achieved. The development of a comprehensive analysis was succeeded, especially near the wall region, where exists hydrodynamic wall interaction effects (e.g., collision or lubrication) and abrupt changes of particle rotational velocity. This allowed us to predict numerically afterwards the behavior of non-spherical particles within the frame of the Euler/Lagrange approach, where the particles are therein treated as “point-particles”.

Keywords: crossflow, non-spherical particles, particle tracking velocimetry, PIV

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Authors: Dzmitry Misiulia, Sergiy Antonyuk

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Small-scale cyclone separators are widely used in aerosol sampling. The flow field in a cyclone sampler is very complex, especially the vortex behavior. Most of the existing models for calculating cyclone efficiency use the same stable vortex structure while the vortex demonstrates dynamic variations rather than the steady-state picture. It can spontaneously ‘end’ at some point within the body of the separator. Natural vortex length is one of the most critical issues when designing and operating gas cyclones and is crucial to proper cyclone performance. The particle transport along the wall to the grid pot is not effective beyond this point. The flow field and vortex behavior inside the aerosol sampler have been investigated for a wide range of Reynolds numbers using Large Eddy Simulations. Two characteristics types of vortex behavior have been found with simulations. At low flow rates the vortex created in the cyclone dissipates in free space (without attaching to a surface) while at higher flow rates it attaches to the cyclone wall. The effects of the Reynolds number on the natural vortex length and the rotation frequency of the end of the vortex have been revealed.

Keywords: cyclone, flow field, natural vortex length, pressure drop

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Authors: Alex B. Cusick

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The objective of this study is to improve upon the current ²³⁸PuO₂ fuel technology for space and defense applications. Modern RTGs (radioisotope thermoelectric generators) utilize the heat generated from the radioactive decay of ²³⁸Pu to create heat and electricity for long term and remote missions. Application of RTG technology is limited by the scarcity and expense of producing the isotope, as well as the power output which is limited to only a few hundred watts. The scarcity and expense make the efficient use of ²³⁸Pu absolutely necessary. By utilizing the decay of ²³⁸Pu, not only to produce heat directly but to also indirectly induce fission in ²³⁹Pu (which is already present within currently used fuel), it is possible to see large increases in temperature which allows for a more efficient conversion to electricity and a higher power-to-weight ratio. This concept can reduce the quantity of ²³⁸Pu necessary for these missions, potentially saving millions on investment, while yielding higher power output. Current work investigating radioisotope power systems have focused on improving efficiency of the thermoelectric components and replacing systems which produce heat by virtue of natural decay with fission reactors. The technical feasibility of utilizing (α,n) reactions to induce fission within current radioisotopic fuels has not been investigated in any appreciable detail, and our study aims to thoroughly investigate the performance of many such designs, develop those with highest capabilities, and facilitate experimental testing of these designs. In order to determine the specific design parameters that maximize power output and the efficient use of ²³⁸Pu for future RTG units, MCNP6 simulations have been used to characterize the effects of modifying fuel composition, geometry, and porosity, as well as introducing neutron moderating, reflecting, and shielding materials to the system. Although this project is currently in the preliminary stages, the final deliverables will include sophisticated designs and simulation models that define all characteristics of multiple novel RTG fuels, detailed enough to allow immediate fabrication and testing. Preliminary work has consisted of developing a benchmark model to accurately represent the ²³⁸PuO₂ pellets currently in use by NASA; this model utilizes the alpha transport capabilities of MCNP6 and agrees well with experimental data. In addition, several models have been developed by varying specific parameters to investigate their effect on (α,n) and (n,fi ssion) reaction rates. Current practices in fuel processing are to exchange out the small portion of naturally occurring ¹⁸O and ¹⁷O to limit (α,n) reactions and avoid unnecessary neutron production. However, we have shown that enriching the oxide in ¹⁸O introduces a sufficient (α,n) reaction rate to support significant fission rates. For example, subcritical fission rates above 10⁸ f/cm³-s are easily achievable in cylindrical ²³⁸PuO₂ fuel pellets with a ¹⁸O enrichment of 100%, given an increase in size and a ⁹Be clad. Many viable designs exist and our intent is to discuss current results and future endeavors on this project.

Keywords: radioisotope thermoelectric generators (RTG), Pu-238, subcritical reactors, (alpha, n) reactions

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Authors: Van Diem Thi, Mourad Khelifa, Mohammed El Ganaoui, Yann Rogaume

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An efficient numerical method has been developed to incorporate the effects of heat transfer in timber panels on partition walls exposed to real building fires. The procedure has been added to the software package Abaqus/Standard as a user-defined subroutine (UMATHT) and has been verified using both time-and spatially dependent heat fluxes in two- and three-dimensional problems. The aim is to contribute to the development of simulation tools needed to assist structural engineers and fire testing laboratories in technical assessment exercises. The presented method can also be used under the developmental stages of building components to optimize performance in real fire conditions. The accuracy of the used thermal properties and the finite element models was validated by comparing the predicted results with three different available fire tests in literature. It was found that the model calibrated to results from standard fire conditions provided reasonable predictions of temperatures within assemblies exposed to real building fire.

Keywords: Timber panels, heat transfer, thermal properties, standard fire tests

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Authors: Vishwesh Kulkarni, Nikhil Bellarykar

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Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.

Keywords: synthetic gene network, network identification, optimization, nonlinear modeling

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Authors: Kelsi Matwick, Keri Matwick

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This presentation focuses on national campaigns as a government tactic of social behavior and order. Focusing on one of Singapore’s first national campaigns, Keep Singapore Clean (1968), particularly its iterations of public hygiene in recent years: Keep the Toilets Clean (2012-2019) and UnLittering with Mary Chongo (2019), the study examines how humor and the use of multimodality reflect contemporary practices in political practice. A critical social semiotic analysis involving the textual (linguistic and visual design) and material (print cartoons and videos) is undertaken to show how these messages are communicated. Incongruity and parody are humorous mechanisms used to project the government as likeable, effectively capture the public attention, and instill individual responsibility for the greater community. In focusing on public hygiene national campaigns, the study further illustrates how humor offers a polite way to address crude behavior while providing models of exemplary behavior.

Keywords: communication strategies, critical social semiotics, humor, national campaigns

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Authors: D. Kumar, S. Kumar, A. G. Memon, R. A. Memon, K. Harijan

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A considerable amount of energy is usually lost due to compression of insulation in Heating, ventilation, and air conditioning (HVAC) duct. In this paper, the economic impact of compression of insulation is estimated. Relevant mathematical models were used to estimate the optimal thickness at the points of compression. Furthermore, the payback period is calculated for the optimal thickness at the critical parts of supply air duct (SAD) and return air duct (RAD) considering natural gas (NG) and liquefied petroleum gas (LPG) as fuels for chillier operation. The mathematical model is developed using preliminary data obtained for an HVAC system of a pharmaceutical company. The higher heat gain and cooling loss, due to compression of thermal insulation, is estimated using relevant heat transfer equations. The results reveal that maximum energy savings (ES) in SAD is 34.5 and 40%, while in RAD is 22.9% and 29% for NG and LPG, respectively. Moreover, the minimum payback period (PP) for SAD is 2 and 1.6years, while in RAD is 4.3 and 2.7years for NG and LPG, respectively. The optimum insulation thickness (OIT) corresponding to maximum ES and minimum PP is estimated to be 35 and 42mm for SAD, while 30 and 38mm for RAD in case of NG and LPG, respectively.

Keywords: optimum insulation thickness, life cycle cost analysis, payback period, HVAC system

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Authors: Sharifa Alshahrani

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Comics is a multimodal text wherein meaning is created by taking in all modes of expression at once. It uses two different semiotic modes, the verbal and the visual modes, together to make meaning and these different semiotic modes can be socially and culturally shaped to give meaning. Therefore, comics translation cannot treat comics as a monomodal text by translating only the verbal mode inside or outside the speech balloons as the cultural differences are encoded in the visual mode as well. Due to the development of the internet and editing software, comics translation is not anymore confined to the publishing houses and official translation as scanlation, or the fan translation took the initiative in translating comics for being emotionally attracted to the culture and genre. Scanlation is carried out by volunteering fans who translate out of passion. However, quality is one of the debatable issues relating to scanlation and fan translation. This study will investigate how the dynamic multimodal relationship in comics is exploited and interpreted in the translation by exploring the translation strategies and procedures adopted by the publishing houses and scanlation in interpreting comics into Arabic using three analytical frameworks; cultural references model, multimodal relation model and translation strategies and procedures models.

Keywords: comics, multimodality, translation, scanlation

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Authors: Benoit Rougier, Alexandre Lefrancois, Herve Aubert

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Microwave interrogation in the range 10-100 GHz is identified as an advanced technique to investigate simultaneously shock and particle velocity measurements. However, it requires the understanding of electromagnetic wave propagation in a multi-layered moving media. The existing models limit their approach to wave guides or evaluate the velocities with a fitting method, restricting therefore the domain of validity and the precision of the results. Moreover, few data of permittivity on high explosives at these frequencies under dynamic compression have been reported. In this paper, shock and particle velocities are computed concurrently for steady and unsteady shocks for various inert and reactive materials, via a propagation model based on Doppler shifts and signal amplitude. Refractive index of the material under compression is also calculated. From experimental data processing, it is demonstrated that Hugoniot curve can be evaluated. The comparison with published results proves the accuracy of the proposed method. This microwave interrogation technique seems promising for shock and detonation waves studies.

Keywords: electromagnetic propagation, experimental setup, Hugoniot measurement, shock propagation

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Authors: Hamed Ouattara, Pierre Duthon, Frédéric Bernardin, Omar Ait Aider, Pascal Salmane

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In this article, we present three neural network architectures for real-time classification of weather conditions (sunny, rainy, snowy, foggy) from images. Inspired by recent advances in style transfer, two of these architectures -Truncated ResNet50 and Truncated ResNet50 with Gram Matrix and Attention- surpass the state of the art and demonstrate re-markable generalization capability on several public databases, including Kaggle (2000 images), Kaggle 850 images, MWI (1996 images) [1], and Image2Weather [2]. Although developed for weather detection, these architectures are also suitable for other appearance-based classification tasks, such as animal species recognition, texture classification, disease detection in medical images, and industrial defect identification. We illustrate these applications in the section “Applications of Our Models to Other Tasks” with the “SIIM-ISIC Melanoma Classification Challenge 2020” [3].

Keywords: weather simulation, weather measurement, weather classification, weather detection, style transfer, Pix2Pix, CycleGAN, CUT, neural style transfer

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Authors: Jianxin Zhu, Na Liu

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Entry strategies play a vital role in the development of new enterprises in the catering industry. Different entry strategies will have different effects on the development of new enterprise. Based on the research of scholars at home and abroad, and combining the characteristics of the catering industry, the entry strategies are divided into low-price entry strategies and high-quality entry strategies. Facing the entry of new enterprise, the strategies of incumbent enterprises are divided into response strategies and non-response strategies. This paper uses evolutionary game theory to study the strategic interaction mechanism between incumbent companies and new enterprises. When different initial values and parameter values are set, which strategy will the two-game subjects choose, respectively? Using matlab2016 for numerical simulation, the results show that the choice of strategies for new enterprise and incumbent enterprise is influenced by more than one factor, and the system has different evolution trends under different circumstances. When the parameters were set, the choice of two subjects' strategies mainly depends on the net profit between the strategies.

Keywords: catering industry, entry strategy, evolutionary game, strategic interaction mechanism

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Authors: Charles Sikwanda

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The use of geosynthetic materials in geotechnical engineering projects has rapidly increased over the past several years. These materials have resulted in improved performance and cost reduction of geotechnical structures as compared to the use of conventional materials. However, working with geosynthetics requires knowledge of interface parameters for design. These parameters are typically determined by the large direct shear device in accordance with ASTM-D5321 and ASTM-D6243 standards. Although these laboratory tests are standardized, the quality of the results can be largely affected by several factors that include; the shearing rate, applied normal stress, gripping mechanism, and type of the geosynthetic specimens tested. Amongst these factors, poor surface gripping of a specimen is the major source of the discrepancy. If the specimen is inadequately secured to the shearing blocks, it experiences progressive failure and shear strength that deviates from the true field performance of the tested material. This leads to inaccurate, unsafe, and cost ineffective designs of projects. Currently, the ASTM-D5321 and ASTM-D6243 standards do not provide a standardized gripping system for geosynthetic shear strength testing. Over the years, researchers have come up with different gripping systems that can be used such as; glue, metal textured surface, sandblasting, and sandpaper. However, these gripping systems are regularly not adequate to sufficiently secure the tested specimens to the shearing device. This has led to large variability in test results and difficulties in results interpretation. Therefore, this study was aimed at determining the effects of gripping systems in geosynthetic interface shear strength testing using a 300 x 300 mm direct shear box. The results of the research will contribute to easy data interpretation and increase result accuracy and reproducibility.

Keywords: geosynthetics, shear strength parameters, gripping systems, gripping

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester

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This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.

Keywords: CFD, electronic discharge, ignition, spark plug

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Authors: Saeb Ahmadi, Mohsen Vafaie Sefti, Mohammad Mahdi Shadman, Ebrahim Tangestani

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Carbon nanotube has shown great potential for the removal of various inorganic and organic components due to properties such as large surface area and high adsorption capacity. Central composite design is widely used method for determining optimal conditions. Also due to the economic reasons and wide application, the rare earth elements are important components. The analyses of cerium (Ce(III)) adsorption as one of the Rare Earth Elements (REEs) adsorption on Multiwall Carbon Nanotubes (MWCNTs) have been studied. The optimization process was performed using Response Surface Methodology (RSM). The optimum amount conditions were pH of 4.5, initial Ce (III) concentration of 90 mg/l and MWCNTs dosage of 80 mg. Under this condition, the optimum adsorption percentage of Ce (III) was obtained about 96%. Next, at the obtained optimum conditions the kinetic and isotherm studied and result showed the pseudo-second order and Langmuir isotherm are more fitted with experimental data than other models.

Keywords: cerium, rare earth element, MWCNTs, adsorption, optimization

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Authors: Mark Salisbury

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The arrival of artificially intelligent avatars and the automation they bring is worrying many of us, not only for our livelihood but for the jobs that may be lost to our kids. We worry about what our place will be as human beings in this new economy where much of it will be conducted online in the metaverse – in a network of 3D virtual worlds – working with intelligent machines. The Future of Leadership was written to address these fears and show what our place will be – the right place – in this new economy of AI avatars, automation, and 3D virtual worlds. But to be successful in this new economy, our job will be to bring wisdom to our workplace and the marketplace. And we will use AI avatars and 3D virtual worlds to do it. However, this book is about more than AI and the avatars that we will work with in the metaverse. It’s about building Organizational intelligence (OI) -- the capability of an organization to comprehend and create knowledge relevant to its purpose; in other words, it is the intellectual capacity of the entire organization. To increase organizational intelligence requires a new kind of knowledge worker, a wisdom worker, that requires a new kind of leadership. This book begins your story for how to become a leader of wisdom workers and be successful in the emerging wisdom economy. After this presentation, conference participants will be able to do the following: Recognize the characteristics of the new generation of wisdom workers and how they differ from their predecessors. Recognize that new leadership methods and techniques are needed to lead this new generation of wisdom workers. Apply personal and professional values – personal integrity, belief in something larger than yourself, and keeping the best interest of others in mind – to improve your work performance and lead others. Exhibit an attitude of confidence, courage, and reciprocity of sharing knowledge to increase your productivity and influence others. Leverage artificial intelligence to accelerate your ability to learn, augment your decision-making, and influence others.Utilize new technologies to communicate with human colleagues and intelligent machines to develop better solutions more quickly.

Keywords: metaverse, generative artificial intelligence, automation, leadership, organizational intelligence, wisdom worker

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Authors: E. D. Paul, O. F. Paul, J. E. Toryila, A. J. Salifu, C. E. Gimba

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Adsorption of Cd2+ ions from aqueous solution by Chitosan, a natural polymer, obtained from a mixture of the exoskeletons of Littorina littorea (Periwinkle) and Achatinoidea (Snail) was studied at varying adsorbent dose, contact time, metal ion concentrations, temperature and pH using batch adsorption method. The equilibrium adsorption isotherms were determined between 298 K and 345 K. The adsorption data were adjusted to Langmuir, Freundlich and the pseudo second order kinetic models. It was found that the Langmuir isotherm model most fitted the experimental data, with a maximum monolayer adsorption of 35.1 mgkg⁻¹ at 308 K. The entropy and enthalpy of adsorption were -0.1121 kJmol⁻¹K⁻¹ and -11.43 kJmol⁻¹ respectively. The Freundlich adsorption model, gave Kf and n values consistent with good adsorption. The pseudo-second order reaction model gave a straight line plot with rate constant of 1.291x 10⁻³ kgmg⁻¹ min⁻¹. The qe value was 21.98 mgkg⁻¹, indicating that the adsorption of Cadmium ion by the chitosan composite followed the pseudo-second order kinetic model.

Keywords: adsorption, chitosan, littorina littorea, achatinoidea, natural polymer

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Authors: Tadewos Awugchew Wudineh

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Health and safety issues have always been a major problem and concern in the building construction industry. The health and safety regulations are stated to eliminate the potential hazards and to reduce the consequential risks. However, the importance of the regulations seems to be overlooked in building construction sites of Hawassa City. Accordingly, many companies don’t follow the regulations as construction workers are more likely to be injured and killed by construction accident than any other type of employment. This paper aimed to identify factors that affect the implementation of construction health and safety regulations, their effects and mitigation measures in building construction project sites of Hawassa City. To reach this objective, a review of literature as well as the Ethiopian construction health and safety regulations have been undertaken. Mainly a five-point Likert scale questionnaire was distributed, and statistical analysis was used to summarize, interpret the data, and to find the significances of the responses. In addition, interviews were carried out. Accordingly, the findings indicate that the top factors which affect the implementation of CHS regulations are, availability and development of a clear health and safety policy, health and safety inspections by top management, conducting health and safety training and orientation, provision of healthy and safe working environment and employment of trained safety officers. The study revealed that implementation or non-implementation of CHS regulations have effects on the worker’s productivity, job satisfaction, rate of accidents, and cost greatly. Thus, the suggestion to minimize the impact on worker’s job performance are, developing of a clear health and safety policy, management commitment towards implementation of health and safety regulations, health and safety education and training and conducting regular health and safety inspections. It was concluded from the study that good implementation of health and safety regulations are the results from administrative and management commitment which calls for more attention to be paid to improve the implementation of CHS regulations in building construction sites of Hawassa City.

Keywords: construction health and safety regulations, effects, factors, mitigation

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Petra Buzkova, Milos Kopa

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Reliability of the credit default swap market had been questioned repeatedly during the EMU debt crisis. The article examines whether this development influenced sovereign EMU CDS prices in general. We regress the CDS market price on a model risk neutral CDS price obtained from an adopted reduced form valuation model in the 2009-2013 period. We look for a break point in the single-equation and multi-equation econometric models in order to show the changes in relations between CDS market and model prices. Our results differ according to the risk profile of a country. We find that in the case of riskier countries, the relationship between the market and model price changed when market participants started to question the ability of CDS contracts to protect their buyers. Specifically, it weakened after the change. In the case of less risky countries, the change happened earlier and the effect of a weakened relationship is not observed.

Keywords: chow stability test, credit default swap, debt crisis, reduced form valuation model, seemingly unrelated regression

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Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

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Authors: Suparman Suparman

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A white noise in autoregressive (AR) model is often assumed to be normally distributed. In application, the white noise usually do not follows a normal distribution. This paper aims to estimate a parameter of AR model that has a exponential white noise. A Bayesian method is adopted. A prior distribution of the parameter of AR model is selected and then this prior distribution is combined with a likelihood function of data to get a posterior distribution. Based on this posterior distribution, a Bayesian estimator for the parameter of AR model is estimated. Because the order of AR model is considered a parameter, this Bayesian estimator cannot be explicitly calculated. To resolve this problem, a method of reversible jump Markov Chain Monte Carlo (MCMC) is adopted. A result is a estimation of the parameter AR model can be simultaneously calculated.

Keywords: autoregressive (AR) model, exponential white Noise, bayesian, reversible jump Markov Chain Monte Carlo (MCMC)

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Authors: Aura Alejandra Burbano Patino, Mariela Agotegaray, Veronica Lassalle, Fernanda Horst

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Water pollution is of worldwide concern due to its importance as an essential resource for life. Industrial and urbanistic growth are anthropogenic activities that have caused an increase of undesirable compounds in water. In the last decade, emerging pollutants have become of great interest since, at very low concentrations (µg/L and ng/L), they exhibit a hazardous effect on wildlife, aquatic ecosystems, and human organisms. One group of emerging pollutants that are a matter of study are pharmaceuticals. Their high consumption rate and their inappropriate disposal have led to their detection in wastewater treatment plant influent, effluent, surface water, and drinking water. In consequence, numerous technologies have been developed to efficiently treat these pollutants. Adsorption appears like an easy and cost-effective technology. One of the most used adsorbents of emerging pollutants removal is carbon-based materials such as hydrochars. This study aims to use a magnetic hydrochar nanocomposite to be employed as an adsorbent for diclofenac removal. Kinetics models and the adsorption efficiency in real water samples were analyzed. For this purpose, a magnetic hydrochar nanocomposite was synthesized through the hydrothermal carbonization (HTC) technique hybridized to co-precipitation to add the magnetic component into the hydrochar, based on iron oxide nanoparticles. The hydrochar was obtained from sunflower husk residue as the precursor. TEM, TGA, FTIR, Zeta potential as a function of pH, DLS, BET technique, and elemental analysis were employed to characterize the material in terms of composition and chemical structure. Adsorption kinetics were carried out in distilled water and real water at room temperature, pH of 5.5 for distilled water and natural pH for real water samples, 1:1 adsorbent: adsorbate dosage ratio, contact times from 10-120 minutes, and 50% dosage concentration of DCF. Results have demonstrated that magnetic hydrochar presents superparamagnetic properties with a saturation magnetization value of 55.28 emu/g. Besides, it is mesoporous with a surface area of 55.52 m²/g. It is composed of magnetite nanoparticles incorporated into the hydrochar matrix, as can be proven by TEM micrographs, FTIR spectra, and zeta potential. On the other hand, kinetic studies were carried out using DCF models, finding percent removal efficiencies up to 85.34% after 80 minutes of contact time. In addition, after 120 minutes of contact time, desorption of emerging pollutants from active sites took place, which indicated that the material got saturated after that t time. In real water samples, percent removal efficiencies decrease up to 57.39%, ascribable to a possible mechanism of competitive adsorption of organic or inorganic compounds, ions for active sites of the magnetic hydrochar. The main suggested adsorption mechanism between the magnetic hydrochar and diclofenac include hydrophobic and electrostatic interactions as well as hydrogen bonds. It can be concluded that the magnetic hydrochar nanocomposite could be valorized into a by-product which appears as an efficient adsorbent for DCF removal as a model emerging pollutant. These results are being complemented by modifying experimental variables such as pollutant’s initial concentration, adsorbent: adsorbate dosage ratio, and temperature. Currently, adsorption assays of other emerging pollutants are being been carried out.

Keywords: environmental remediation, emerging pollutants, hydrochar, magnetite nanoparticles

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Authors: Liang Wang, Wei Zhang

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Nowadays, sustainable development has increasingly become an important research topic of engineering education. Existing research on Engineering Education for Sustainable Development (EESD) has highlighted the importance of perceptions for ethical responsibility to address sustainable development in practice. However, whether and how the professional engineering experience affects those perceptions has not been proved, especially in a Chinese context. Our study fills this gap by investigating the perceptions bias of EESD between experienced engineers and engineering students. We specifically examined what EESD means for experienced engineers and engineering students using a triple-dimensional model to understand if there are obvious differences between the two groups. Our goal is to make the benefits of these experiences more accessible in school context. The data (n=438) came from a questionnaire created and adapted from previously published studies containing 288 students from mechanical or civil engineering and 150 civil engineers with rich working experience, and the questionnaire was distributed during Fall 2020. T-test was used to find the difference in different dimensions between the two groups. The statistical results show that there is a significant difference in the perceptions of EESD between experienced engineers and inexperienced engineering students in China. Experienced engineers tend to consider sustainable development from ecological, economic, and social perspectives, while engineering students' answers focus more on ecology and ignore economic and social dimensions to some extend. The findings provide empirical evidence that professional experience is helpful to cultivate the cognition and ability of sustainable development in engineering education. The results of this work indicate that more practical content should be added to engineering education to promote sustainable development. In addition, for the design of engineering courses and professional practice systems for sustainable development, we should not only pay attention to the ecological aspects but also emphasize the coordination of ecological, economic, and socially sustainable development (e.g., engineer's ethical responsibility).

Keywords: engineering education, sustainable development, experienced engineers, engineering students

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Authors: Irena Balaban Cakirpaloglu, Karla Hrbackova

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This paper focuses on the issue of intercultural competencies of university students who are preparing to work in assisting professions. In recent years, the Czech Republic has become a major destination for many people from different cultural environments, and there is a growing need for workers in assisting professions to be able to respond flexibly and adequately to the changing living conditions of multicultural coexistence. The main objective of this study is to analyse the preparedness of students in assisting professions in relation to intercultural competencies. Intercultural competences include several essential skills for working successfully with diversity. Taking into account the main objective of this research, a pilot study was conducted among students of Social Pedagogy at the Faculty of Humanities at Tomas Bata University in Zlin in the academic year 2017/2018. The research sample consisted of 116 students. To obtain the data, we used the Cross-Cultural Adaptability Inventory (CCAI) by Kelley and Meyers. The inventory maps strengths and weaknesses in 4 skill areas: Emotional Resilience, Flexibility/Openness, Perceptual Acuity and Personal Autonomy. This inventory also examines individual ability to succeed in intercultural interaction and communication. The results obtained from the survey were statistically processed and analysed using the relevant statistical methods. The results of the survey point to the fact that students of social pedagogy achieve average to below average results in individual skill areas. At the same time, significant differences have been detected among the students with work experience in multicultural environment and those with no experience.

Keywords: cross–cultural adaptability inventory, diversity, intercultural competences, students of social pedagogy

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Authors: Salma A. El-Marasy, Reham M. Abd-Elsalam, Omar A. Ahmed-Farid

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Dementia is characterized by impairments in memory and other cognitive abilities. This study aims to elucidate the possible ameliorative effect of silymarin on scopolamine-induced dementia using the object recognition test (ORT). The study was extended to demonstrate the role of cholinergic activity, oxidative stress, neuroinflammation, brain neurotransmitters and histopathological changes in the anti-amnestic effect of silymarin in demented rats. Wistar rats were pretreated with silymarin (200, 400, 800 mg/kg) or donepezil (10 mg/kg) orally for 14 consecutive days. Dementia was induced after the last drug administration by a single intraperitoneal dose of scopolamine (16 mg/kg). Then behavioral, biochemical, histopathological, and immunohistochemical analyses were then performed. Rats pretreated with silymarin counteracted scopolamine-induced non-spatial working memory impairment in the ORT and decreased acetylcholinesterase (AChE) activity, reduced malondialdehyde (MDA), elevated reduced glutathione (GSH), restored gamma-aminobutyric acid (GABA) and dopamine (DA) contents in the cortical and hippocampal brain homogenates. Silymarin dose-dependently reversed scopolamine-induced histopathological changes. Immunohistochemical analysis showed that silymarin dose-dependently mitigated protein expression of a glial fibrillary acidic protein (GFAP) and nuclear factor kappa-B (NF-κB) in the brain cortex and hippocampus. All these effects of silymarin were similar to that of the standard anti-amnestic drug, donepezil. This study reveals that the ameliorative effect of silymarin on scopolamine-induced dementia in rats using the ORT maybe in part mediated by, enhancement of cholinergic activity, anti-oxidant and anti-inflammatory activities as well as mitigation in brain neurotransmitters and histopathological changes.

Keywords: dementia, donepezil, object recognition test, rats, silymarin, scopolamine

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Authors: Maulita Sari Hani, Abraham B. Sianipar, Jamaluddin Jompa, Natsir Nessa, Alan T. White

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Manta ray is an icon for tourism in Raja Ampat. The tourist volume has been increased for the past ten years which up to approximately 23,000 tourists in 2017. Since 2013, Conservation International Indonesia deployed satellite and acoustic tags on manta ray in Dampier strait to track the species and identify the aggregation areas. These findings encourage the government and the local community to boost conservation through the management of marine protected areas for tourism purposes. Community in Dampier strait including the village of Arborek, Kurkapa, Kapisawar, and Sawingray involved in variety of small scale tourism business including homestay, dive shop, tour operator, and crafts. Working groups of related local businesses were established to support the local community and to ensure the sustainability of the economic viability and environmental sustainability. In order to analyze the economic benefits of manta ray tourism, this study was conducted to identify the number of local business in Dampier Strait and the economic impacts in terms of local finance security, social, humanity, individual, and physical assets. The results of this study identify 30 homestays, 2 dive shops, 10 tour operators, 30 women involved in crafts, and about 50 villagers worked for dive resorts. In addition to community assets, we confirmed the welfare of community has been improved in terms of food security, households, education for children, savings, and health insurance.

Keywords: marine wildlife tourism, elasmobranch, conservation, ecotourism, co-management, economic viability, environmental sustainability

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Authors: Carolina Cuéllar, Paz González

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Research has shown that school leadership has a significant indirect effect on students’ achievements. In Chile, evidence has also revealed that this impact is stronger in vulnerable schools. With the aim of strengthening school leadership, public policy has taken up the challenge of enhancing capabilities of novice principals through the implementation of induction programs, which include a mentoring component, entrusting the task of delivering these programs to universities. The importance of using mentoring or coaching models in the preparation of novice school leaders has been emphasized in the international literature. Thus, it can be affirmed that building leadership capacity through partnership is crucial to facilitate cognitive and affective support required in the initial phase of the principal career, gain role clarification and socialization in context, stimulate reflective leadership practice, among others. In Chile, mentoring is a recent phenomenon in the field of school leadership and it is even more new in the preparation of new principals who work in public schools. This study, funded by the Chilean Ministry of Education, sought to explore the challenges and lessons arising from the design and implementation of mentoring processes which are part of the induction programs, according to the perception of the different actors involved: ministerial agents, university coordinators, mentors and novice principals. The investigation used a qualitative design, based on a study of three cases (three induction programs). The sources of information were 46 semi-structured interviews, applied in two moments (at the beginning and end of mentoring). Content analysis technique was employed. Data focused on the uniqueness of each case and the commonalities within the cases. Five main challenges and lessons emerged in the design and implementation of mentoring within the induction programs for new principals from Chilean public schools. They comprised the need of (i) developing a shared conceptual framework on mentoring among the institutions and actors involved, which helps align the expectations for the mentoring component within the induction programs, along with assisting in establishing a theory of action of mentoring that is relevant to the public school context; (ii) recognizing trough actions and decisions at different levels that the role of a mentor differs from the role of a principal, which challenge the idea that an effective principal will always be an effective mentor; iii) improving mentors’ selection and preparation processes trough the definition of common guiding criteria to ensure that a mentor takes responsibility for developing critical judgment of novice principals, which implies not limiting the mentor’s actions to assist in the compliance of prescriptive practices and standards; (iv) generating common evaluative models with goals, instruments and indicators consistent with the characteristics of mentoring processes, which helps to assess expected results and impact; and (v) including the design of a mentoring structure as an outcome of the induction programs, which helps sustain mentoring within schools as a collective professional development practice. Results showcased interwoven elements that entail continuous negotiations at different levels. Taking action will contribute to policy efforts aimed at professionalizing the leadership role in public schools.

Keywords: induction programs, mentoring, novice principals, school leadership preparation

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Authors: Svanik Garg

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Static Test Pads are stationary mechanisms that hold a solid rocket motor, measuring the different parameters of its operation including thrust and temperature to better calibrate it for launch. This paper outlines a specific STP designed to test high powered rocket motors with a thrust upwards of 4000N and limited to 6500N. The design includes a specific portable mechanism with cost an integral part of the design process to make it accessible to small scale rocket developers with limited resources. Using curved surfaces and an ergonomic design, the STP has a delicately engineered façade/case with a focus on stability and axial calibration of thrust. This paper describes the design, operation and working of the STP and its widescale uses given the growing market of aviation enthusiasts. Simulations on the CAD model in Fusion 360 provided promising results with a safety factor of 2 established and stress limited along with the load coefficient A PCB was also designed as part of the test pad design process to help obtain results, with visual output and various virtual terminals to collect data of different parameters. The circuitry was simulated using ‘proteus’ and a special virtual interface with auditory commands was also created for accessibility and wide-scale implementation. Along with this description of the design, the paper also emphasizes the design principle behind the STP including a description of its vertical orientation to maximize thrust accuracy along with a stable base to prevent micromovements. Given the rise of students and professionals alike building high powered rockets, the STP described in this paper is an appropriate option, with limited cost, portability, accuracy, and versatility. There are two types of STP’s vertical or horizontal, the one discussed in this paper is vertical to utilize the axial component of thrust.

Keywords: static test pad, rocket motor, thrust, load, circuit, avionics, drag

Procedia PDF Downloads 381