Search results for: cluster model approach

Authors: Yasin Tadayonrad

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

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Authors: Priyanshu Sharma

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Urban development mechanism has evolved over the years in India, and various planning models and tools have been adopted by different states. Large cities have been able to make and implement plans with the varied degree. However, it has been observed these mechanisms face challenges to gain the momentum in small and medium towns. Gujarat has a very robust legislation that empowers planning authorities to prepare development plans (DP) and town planning scheme (TPS). The DP- TPS planning methods are quite popular for large cities in Gujarat. However, it has been observed that in the smaller towns these methods of plan preparation are facing severe agitations. Recently, development authorities of many small towns like Himmatnagar, Nadiad, and Junagadh, etc. have faced serious protest from local residents. This is because of the large amount of land deduction under the provisions of DP and TPS. And this number of opposition has been increasing since 2012 in Gujarat. This study aims to understand in detail the reasons for agitation against the plans prepared by smaller towns. It will further try to see whether the current framework of urban planning (DP and TPS) are really suitable for these towns. After understanding the development concerns and background, the aim and objectives of the study were outlined: Aim: To evaluate the suitability and acceptability of the current urban development mechanism for the small and medium towns. Objectives: (i) To review the GTPUD Act and identify the provision related to small and medium towns (ii) To understand preparation process of development plan and town planning scheme and issues related to it (iii) To understand the issues raised by the different stakeholder w.r.t plan because of which the plan and authority was agitated (iv) To find out the possible option through which these plans can be made suitable and acceptable to the stakeholder. The approach of this study is more qualitative based with the intention to understand the time frame process of preparation of development plan and town planning scheme and issues related to it. On the basis of literature study, the three towns were selected, and the detailed questionnaire was prepared for the stakeholders (development authorities and local residents) which include the time process taken in the preparation of DP and TPS and what were issues faced during the process and who all were involved. Lastly, the study looks into aspects of the land value of original plots and readjusted plots by concluding the argument whether this TP scheme model really worked in small and medium towns. Because the land deduction under TP scheme is allowed up to 50% as per the act and there is no distinct provision for small and medium towns under the act, so how this could be justified to smaller towns where the market value have not changed over the years. After analyzing the issues and reason behind the agitation against the DP and TPS in these small and medium towns. The broader recommendation has been given which can make these plans acceptable and suitable for the stakeholder.

Keywords: development plans, medium towns, small towns, town planning schemes

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Authors: Derradji Chebli, Abdallah Bouguettoucha, Abdelbaki Reffas Khalil Guediri, Abdeltif Amrane

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The removal of Methyl Green dye (MG) from aqueous solutions using modified P-brutia cones (PBH and PBN), has been investigated work. The physical parameters such as pH, temperature, initial MG concentration, ionic strength are examined in batch experiments on the sorption of the dye. Adsorption removal of MG was conducted at natural pH 4.5 because the dye is only stable in the range of pH 3.8 to 5. It was observed in experiments that the P-brutia cones treated with NaOH (PBN) exhibited high affinity and adsorption capacity compared to the MG P-brutia cones treated with HCl (PBH) and biosorption capacity of modified P-brutia cones (PBN and PBH) was enhanced by increasing the temperature. This is confirmed by the thermodynamic parameters (ΔG° and ΔH°) which show that the adsorption of MG was spontaneous and endothermic in nature. The positive values of ΔS° suggested an irregular increase in the randomness for both adsorbent (PBN and PBH) during the adsorption process. The kinetic model pseudo-first order, pseudo-second order, and intraparticle diffusion coefficient were examined to analyze the sorption process; they showed that the pseudo-second-order model is the one that best describes the adsorption process (MG) on PBN and PBH with a correlation coefficient R²> 0.999. The ionic strength has shown that it has a negative impact on the adsorption of MG on two supports. A reduction of 68.5% of the adsorption capacity for a value Ce=30 mg/L was found for the PBH, while the PBN did not show a significant influence of the ionic strength on adsorption especially in the presence of NaCl. Among the tested isotherm models, the Langmuir isotherm was found to be the most relevant to describe MG sorption onto modified P-brutia cones with a correlation factor R²>0.999. The capacity adsorption of P-brutia cones, was confirmed for the removal of a dye, MG, from aqueous solution. We note also that P-brutia cones is a material very available in the forest and low-cost biomaterial

Keywords: adsorption, p-brutia cones, forest wastes, dyes, isotherm

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Authors: Sebastian van Delden, Matthew Anuszkiewicz, Jayse White, Scott Stolarski

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Industrial robotic manipulators have been commonplace in the manufacturing world since the early 1960s, and unmanned aerial vehicles (drones) have only begun to realize their full potential in the service industry and the military. The omnipresence of these technologies in their respective fields will only become more potent in coming years. While these technologies have greatly evolved over the years, the typical approach to human interaction with these robots has not. In the industrial robotics realm, a manipulator is typically jogged around using a teach pendant and programmed using a networked computer or the teach pendant itself via a proprietary software development platform. Drones are typically controlled using a two-handed controller equipped with throttles, buttons, and sticks, an app that can be downloaded to one’s mobile device, or a combination of both. This application-oriented work offers a novel approach to human interaction with both unmanned aerial vehicles and industrial robotic manipulators via hand gestures and movements. Two systems have been implemented, both of which use a Myo™ armband to control either a drone (DJI Spark™) or a robotic arm (Stäubli™ TX40). The methodologies developed by this work present a mapping of armband gestures (fist, finger spread, swing hand in, swing hand out, swing arm left/up/down/right, etc.) to either drone or robot arm movements. The findings of this study present the efficacy and limitations (precision and ergonomic) of hand gesture control of two distinct types of robotic technology. All source code associated with this project will be open sourced and placed on GitHub. In conclusion, this study offers a framework that maps hand and arm gestures to drone and robot arm control. The system has been implemented using current ubiquitous technologies, and these software artifacts will be open sourced for future researchers or practitioners to use in their work.

Keywords: human robot interaction, drones, gestures, robotics

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Authors: Hanan F. Aly, Fateheya M. Metwally, Hanaa H. Ahmed

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The current study is undertaken to elucidate a possible neuroprotective role of dehydroepiandrosterone (DHEA) against the development of Alzheimer’s disease in experimental rat model. Alzheimer’s disease was produced in young female ovariectomized rats by intraperitoneal administration of AlCl3 (4.2 mg/kg body weight) daily for 12 weeks. Half of these animals also received orally DHEA (250 mg/kg body weight, three times weekly) for 18 weeks. Control groups of animals received either DHAE alone, or no DHEA, or were not ovariectomized. After such treatment the animals were analyzed for oxidative stress biomarkers such as hydrogen peroxide, nitric oxide and malondialdehyde, total antioxidant capacity, reduced glutathione, glutathione peroxidase, glutathione reductase, superoxide dismutase and catalase activities, antiapoptotic marker Bcl-2 and brain derived neurotrophic factor. Also, brain cholinergic markers (acetylcholinesterase and acetylcholine) were determined. The results revealed significant increase in oxidative stress parameters associated with significant decrease in the antioxidant enzyme activities in Al-intoxicated ovariectomized rats. Significant depletion in brain Bcl-2 and brain-derived neurotrophic factor levels were also detected. Moreover, significant elevations in brain acetylcholinesterase activity accompanied with significant reduction in acetylcholine level were recorded. Significant amelioration in all investigated parameters was detected as a result of treatment of Al-intoxicated ovariectomized rats with DHEA. These results were confirmed by histological examination of brain sections. These results clearly indicate a neuroprotective effect of DHEA against Alzheimer’s disease.

Keywords: Alzheimer’s disease, oxidative stress, apoptosis, dehydroepiandrosterone

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Authors: Tytus Tulwin, Ksenia Siadkowska, Rafał Sochaczewski

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A high power radial reciprocating engine is characterized by a large displacement volume of a combustion chamber. Choosing the right moment for ignition is important for a high performance or high reliability and ignition certainty. This work shows methods of simulating ignition process and its impact on engine parameters. For given conditions a flame speed is limited when a deflagration combustion takes place. Therefore, a larger length scale of the combustion chamber compared to a standard size automotive engine makes combustion take longer time to propagate. In order to speed up the mixture burn-up time the second spark is introduced. The transient Computational Fluid Dynamics model capable of simulating multicycle engine processes was developed. The CFD model consists of ECFM-3Z combustion and species transport models. A relative ignition timing difference for the both spark sources is constant. The temperature distribution on engine walls was calculated in the separate conjugate heat transfer simulation. The in-cylinder pressure validation was performed for take-off power flight conditions. The influence of ignition timing on parameters like in-cylinder temperature or rate of heat release was analyzed. The most advantageous spark timing for the highest power output was chosen. The conditions around the spark plug locations for the pre-ignition period were analyzed. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: CFD, combustion, ignition, simulation, timing

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Authors: Dirson Santos De Campos, Deller James Ferreira, Anderson Cavalcante Gonçalves, Uyara Ferreira Silva

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Rubrics to learning research provide many evaluation criteria and expected performance standards linked to defined student activity for learning and pedagogical objectives. Despite the rubric being used in education at all levels, academic literature on rubrics as a tool to support research in SQL Education is quite rare. There is a large class of SQL queries is syntactically correct, but certainly, not all are semantically correct. Detecting and correcting errors is a recurring problem in SQL education. In this paper, we usthe Rubric Abstract Framework (RAF), which consists of steps, that allows us to map the information to measure student performance guided by didactic objectives defined by the teacher as long as it is contextualized domain modeling by rubric. An empirical study was done that demonstrates how rubrics can mitigate student difficulties in finding logical errors and easing teacher workload in SQL education. Detecting and correcting logical errors is an important skill for students. Researchers have proposed several ways to improve SQL education because understanding this paradigm skills are crucial in software engineering and computer science. The RAF instantiation was using in an empirical study developed during the COVID-19 pandemic in database course. The pandemic transformed face-to-face and remote education, without presential classes. The lab activities were conducted remotely, which hinders the teaching-learning process, in particular for this research, in verifying the evidence or statements of knowledge, skills, and abilities (KSAs) of students. Various research in academia and industry involved databases. The innovation proposed in this paper is the approach used where the results obtained when using rubrics to map logical errors in query formulation have been analyzed with gains obtained by students empirically verified. The research approach can be used in the post-pandemic period in both classroom and distance learning.

Keywords: rubric, logical error, structured query language (SQL), empirical study, SQL education

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Authors: M. Rafiur Rahman, M. Mezbah Uddin, Mohammad Irfan Uddin, M. Moinul Islam

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With a rapid development of offshore renewable energy industry, the research activities in regards of harnessing power from offshore wind and wave energy are increasing day by day. Integration of wind turbines and wave energy converters into one combined semi-submersible platform might be a cost-economy and beneficial option. In this paper, the coupled integrated dynamic analysis in the time domain (TD) of a simplified semi-submersible flap type concept (SFC) is accomplished via state-of-the-art numerical code referred as Simo-Riflex-Aerodyn (SRA). This concept is a combined platform consisting of a semi-submersible floater supporting a 5 MW horizontal axis wind turbine (WT) and three elliptical shaped flap type wave energy converters (WECs) on three pontoons. The main focus is to validate the numerical model of SFC with experimental results and perform the frequency domain (FD) and TD response analysis. The numerical analysis is performed using potential flow theory for hydrodynamics and blade element momentum (BEM) theory for aerodynamics. A variety of environmental conditions encompassing the functional & survival conditions for short-term sea (1-hour simulation) are tested to evaluate the sustainability of the SFC. The numerical analysis is performed in full scale. Finally, the time domain analysis of heave, pitch & surge motions is performed numerically using SRA and compared with the experimental results. Due to the simplification of the model, there are some discrepancies which are discussed in brief.

Keywords: coupled integrated dynamic analysis, SFC, time domain analysis, wave energy converters

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Authors: Elnaz Kanani-Kuchesfehani, Andrea Schiffauerova

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Due to the novelty of the nanotechnology science, its highly knowledge intensive content, and its invaluable application in almost all technological fields, the close interaction between university and industry is essential. A possible gap between academic strengths to generate good nanotechnology ideas and industrial capacity to receive them can thus have far-reaching consequences. In order to be able to enhance the collaboration between the two parties, a better understanding of knowledge transfer within the university-industry relationship is needed. The objective of this research is to investigate the research collaboration between academia and industry in Canadian nanotechnology and to propose the best cooperative strategy to maximize the quality of the produced knowledge. First, a network of all Canadian academic and industrial nanotechnology inventors is constructed using the patent data from the USPTO (United States Patent and Trademark Office), and it is analyzed with social network analysis software. The actual level of university-industry collaboration in Canadian nanotechnology is determined and the significance of each group of actors in the network (academic vs. industrial inventors) is assessed. Second, a novel methodology is proposed, in which the network of nanotechnology inventors is assessed from a game theoretic perspective. It involves studying a cooperative game with n players each having at most n-1 decisions to choose from. The equilibrium leads to a strategy for all the players to choose their co-worker in the next period in order to maximize the correlated payoff of the game. The payoffs of the game represent the quality of the produced knowledge based on the citations of the patents. The best suggestion for the next collaborative relationship is provided for each actor from a game theoretic point of view in order to maximize the quality of the produced knowledge. One of the major contributions of this work is the novel approach which combines game theory and social network analysis for the case of large networks. This approach can serve as a powerful tool in the analysis of the strategic interactions of the network actors within the innovation systems and other large scale networks.

Keywords: cooperative strategy, game theory, industry-university collaboration, knowledge production, social network analysis

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Authors: Maelle Noir

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International Human rights norms prescribe the obligation to protect refugee women against violence which requires, inter alia, state provision of justiciable, accessible, affordable and non-discriminatory access to justice. However, the interpretation and application of the law still lack gender sensitivity, intersectionality and a trauma-informed approach. Consequently, many refugee survivors face important structural obstacles preventing access to justice and often experience secondary traumatisation when navigating the legal system. This paper argues that the unique nature of the experiences of refugees with gender-based violence against women exacerbated throughout the migration journey calls for a tailored practice of the law to ensure adequate access to justice. The argument developed here is that the obligation to provide survivors with justiciable, accessible, affordable and non-discriminatory access to justice implies radically transforming the practice of the law altogether. This paper, therefore, proposes feminist lawyering as an alternative approach to the practice of the law when addressing gender-based violence against women refugees. First, this paper discusses the specific nature of gender-based violence against refugees with a particular focus on two aspects of the power-violence nexus: the analysis of the shift in gender roles and expectations following displacement as one of the causes of gender-based violence against women refugees and the argument that the asylum situation itself constitutes a form of state-sponsored and institutional violence. Second, the re-traumatising and re-victimising nature of the legal system is explored with the objective to demonstrate States’ failure to comply with their legal obligation to provide refugee women with effective access to justice. Third, this paper discusses some key practical strategies that have been proposed and implemented to transform the practice of the law when dealing with gender-based violence outside of the refugee context. Lastly, this analysis is applied to the specificities of the experiences of refugee survivors of gender-based violence.

Keywords: feminist lawyering, feminist legal theory, gender-based violence, human rights law, intersectionality, refugee protection

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Authors: Simona Lucakova, Irena Branyikova

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Eutrophication, a condition when water becomes over-enriched with nutrients (P, N), can lead to undesirable excessive growth of phytoplankton, so-called algal bloom. This process results in the accumulation of toxin-producing cyanobacteria and oxygen depletion, both possibly leading to the collapse of the whole ecosystem. In real conditions, the limiting nutrient, which determines the possible growth of harmful algal bloom, is usually phosphorus. Algicides or flocculants have been applied in the eutrophicated waterbody in order to reduce the phytoplankton growth, which leads to the introduction of toxic chemicals into the water. In our laboratory, the idea of the prevention of harmful phytoplankton growth by the intentional cultivation of non-toxic cyanobacteria Tolypothrix tenuis in semi-open floating photobioreactors directly on the surface of phosphorus-rich waterbody is examined. During the process of cultivation, redundant phosphorus is incorporated into cyanobacterial biomass, which can be subsequently used for the production of biofuels, cosmetics, pharmaceuticals, or biostimulants for agricultural use. To determine the ability of phosphorus incorporation, batch-cultivation of Tolypothrix biomass in media simulating eutrophic water (10% BG medium) and in effluent from municipal wastewater treatment plant, both with the initial phosphorus concentration in the range 0.5-1.0 mgP/L was performed in laboratory-scale models of floating photobioreactors. After few hours of cultivation, the phosphorus content was decreased below the target limit of 0.035 mgP/L, which was given as a borderline for the algal bloom formation. Under laboratory conditions, the effect of several parameters on the rate of phosphorus decrease was tested (illumination, temperature, stirring speed/aeration gas flow, biomass to medium ratio). Based on the obtained results, a bench-scale floating photobioreactor was designed and will be tested for Tolypothrix growth in real conditions. It was proved that intentional cultivation of cyanobacteria Tolypothrix could be a suitable approach for extracting redundant phosphorus from eutrophic waters as prevention of algal bloom formation.

Keywords: cyanobacteria, eutrophication, floating photobioreactor, Tolypothrix

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Authors: I. Nitoi, P. Oancea, M. Raileanu, M. Crisan, L. Constantin, I. Cristea

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Hazardous organic compounds like nitroaromatics are frequently found in chemical and petroleum industries discharged effluents. Due to their bio-refractory character and high chemical stability cannot be efficiently removed by classical biological or physical-chemical treatment processes. In the past decades, semiconductor photocatalysis has been frequently applied for the advanced degradation of toxic pollutants. Among various semiconductors titania was a widely studied photocatalyst, due to its chemical inertness, low cost, photostability and nontoxicity. In order to improve optical absorption and photocatalytic activity of TiO2 many attempts have been made, one feasible approach consists of doping oxide semiconductor with metal. The degradation of dinitrobenzene (DNB) and dinitrotoluene (DNT) from aqueous solution under UVA-VIS irradiation using heavy metal (0.5% Fe, 1%Co, 1%Ni ) doped titania was investigated. The photodegradation experiments were carried out using a Heraeus laboratory scale UV-VIS reactor equipped with a medium-pressure mercury lamp which emits in the range: 320-500 nm. Solutions with (0.34-3.14) x 10-4 M pollutant content were photo-oxidized in the following working conditions: pH = 5-9; photocatalyst dose = 200 mg/L; irradiation time = 30 – 240 minutes. Prior to irradiation, the photocatalyst powder was added to the samples, and solutions were bubbled with air (50 L/hour), in the dark, for 30 min. Dopant type, pH, structure and initial pollutant concentration influence on the degradation efficiency were evaluated in order to set up the optimal working conditions which assure substrate advanced degradation. The kinetics of nitroaromatics degradation and organic nitrogen mineralization was assessed and pseudo-first order rate constants were calculated. Fe doped photocatalyst with lowest metal content (0.5 wt.%) showed a considerable better behaviour in respect to pollutant degradation than Co and Ni (1wt.%) doped titania catalysts. For the same working conditions, degradation efficiency was higher for DNT than DNB in accordance with their calculated adsobance constants (Kad), taking into account that degradation process occurs on catalyst surface following a Langmuir-Hinshalwood model. The presence of methyl group in the structure of DNT allows its degradation by oxidative and reductive pathways, while DNB is converted only by reductive route, which also explain the highest DNT degradation efficiency. For highest pollutant concentration tested (3 x 10-4 M), optimum working conditions (0.5 wt.% Fe doped –TiO2 loading of 200 mg/L, pH=7 and 240 min. irradiation time) assures advanced nitroaromatics degradation (ηDNB=89%, ηDNT=94%) and organic nitrogen mineralization (ηDNB=44%, ηDNT=47%).

Keywords: hazardous organic compounds, irradiation, nitroaromatics, photocatalysis

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Authors: Milica Lilic, Marina Rosales Martínez

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Academic research cannot be oblivious to social problems and needs, so projects that have the capacity for transformation and impact should have the opportunity to go beyond the University circles and bring benefit to society. Apart from patents and R&D research contracts, this opportunity can be achieved through entrepreneurship as one of the most direct tools to turn knowledge into a tangible product. Thus, as an example of good practices, it is intended to analyze the case of an institutional entrepreneurship program carried out at the University of Seville, aimed at researchers interested in assessing the business opportunity of their research and expanding their knowledge on procedures for the commercialization of technologies used at academic projects. The program is based on three pillars: training, teamwork sessions and networking. The training includes aspects such as product-client fit, technical-scientific and economic-financial feasibility of a spin-off, institutional organization and decision making, public and private fundraising, and making the spin-off visible in the business world (social networks, key contacts, corporate image and ethical principles). On the other hand, the teamwork sessions are guided by a mentor and aimed at identifying research results with potential, clarifying financial needs and procedures to obtain the necessary resources for the consolidation of the spin-off. This part of the program is considered to be crucial in order for the participants to convert their academic findings into a business model. Finally, the networking part is oriented to workshops about the digital transformation of a project, the accurate communication of the product or service a spin-off offers to society and the development of transferable skills necessary for managing a business. This blended program results in the final stage where each team, through an elevator pitch format, presents their research turned into a business model to an experienced jury. The awarded teams get a starting capital for their enterprise and enjoy the opportunity of formally consolidating their spin-off company at the University. Studying the results of the program, it has been shown that many researchers have basic or no knowledge of entrepreneurship skills and different ways to turn their research results into a business model with a direct impact on society. Therefore, the described program has been used as an example to highlight the importance of knowledge transfer at the University and the role that this institution should have in providing the tools to promote entrepreneurship within it. Keeping in mind that the University is defined by three main activities (teaching, research and knowledge transfer), it is safe to conclude that the latter, and the entrepreneurship as an expression of it, is crucial in order for the other two to comply with their purpose.

Keywords: good practice, knowledge transfer, a spin-off company, university

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Authors: Olivia A. Wilson, Hannah E. Power, Murray Kendall

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Sydney Harbour is an iconic location with a dense population and low-lying development. On the east coast of Australia, facing the Pacific Ocean, it is exposed to several tsunamigenic trenches. This paper presents a component of the most detailed assessment of the potential for earthquake-generated tsunami impact on Sydney Harbour to date. Models in this study use dynamic tides to account for tide-tsunami interaction. Sydney Harbour’s tidal range is 1.5 m, and the spring tides from January 2015 that are used in the modelling for this study are close to the full tidal range. The tsunami wave trains modelled include hypothetical tsunami generated from earthquakes of magnitude 7.5, 8.0, 8.5, and 9.0 M_W from the Puysegur and New Hebrides trenches as well as representations of the historical 1960 Chilean and 2011 Tohoku events. All wave trains are modelled for the peak wave to coincide with both a low tide and a high tide. A single wave train, representing a 9.0 M_W earthquake at the Puysegur trench, is modelled for peak waves to coincide with every hour across a 12-hour tidal phase. Using the hydrodynamic model ANUGA, results are compared according to the impact parameters of inundation area, depth variation and current speeds. Results show that both maximum inundation area and depth variation are tide dependent. Maximum inundation area increases when coincident with a higher tide, however, hazardous inundation is only observed for the larger waves modelled: NH90high and P90high. The maximum and minimum depths are deeper on higher tides and shallower on lower tides. The difference between maximum and minimum depths varies across different tidal phases although the differences are slight. Maximum current speeds are shown to be a significant hazard for Sydney Harbour; however, they do not show consistent patterns according to tide-tsunami phasing. The maximum current speed hazard is shown to be greater in specific locations such as Spit Bridge, a narrow channel with extensive marine infrastructure. The results presented for Sydney Harbour are novel, and the conclusions are consistent with previous modelling efforts in the greater area. It is shown that tide must be a consideration for both tsunami modelling and emergency management planning. Modelling with peak tsunami waves coinciding with a high tide would be a conservative approach; however, it must be considered that maximum current speeds may be higher on other tides.

Keywords: emergency management, sydney, tide-tsunami interaction, tsunami impact

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Authors: Asma Mosbah, Hanane Khither, Kamelia Mosbah, Noreddine Kacem Chaouche, Mustapha Benboubetra

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In the present investigation, total oil (TO) and its neutral lipid fraction (NLF) extracted from the seed of the well know studied medicinal plant Nigella sativa were tested for their therapeutically effect on alcohol-induced liver injury in rat model. Male Albino rats were divided into five groups of eight animals each and fed a Lieber–DeCarli liquid diet containing 5% ethanol for experimental groups and dextran for control group, for a period of six weeks. Afterwards, rats received, orally, treatments with Nigella sativa extracts (TO, NLF) and N- acetylcysteine (NAC) as a positive control for four weeks. Activities of antioxidant enzymes; superoxide dismutase (SOD) and catalase (CAT), as well as malondialdehyde (MDA) and reduced glutathione (GSH). Biochemical parameters for kidney and liver functions, in treated and non treated rats, were evaluated throughout the time course of an experiment. Liver histological changes were taken into account. Enzymatic activities of both SOD and CAT increased significantly in rats treated with NLF and TO. While MDA level decreased in TO and NLF treated rats, GSH level increased significantly in TO and NLF treated rats. We noted equally a decrease in liver enzymes AST, ALT, and ALP. Microscopic observation of slides from the liver of ethanol treated rats showed a severe hepatotoxicity with lesions. Treatment with fractions leads to an improvement in liver lesions and a marked reduction in necrosis and infiltration. As a conclusion, both extracts of Nigella sativa seeds, TO and NLF, possess an important therapeutic protective potential against ethanol-induced hepatotoxicity in rats.

Keywords: alcohol-induced hepatotoxicity, antioxidant enzymes, Nigella sativa seeds, oil fractions

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Authors: Tommy Krieger, Klaus Gruendler

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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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Authors: Sombol Mokhles

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This paper tries to show the prospects of utilising (big)data for enabling just the transition of diverse cities. Our key purpose is to offer a framework of applications and implications of utlising (big) data in comparing sustainability transitions across different cities. Relying on the cosmopolitan comparison, this paper explains the potential application of (big) data but also its limitations. The paper calls for adopting a data-driven and just perspective in including different cities around the world. Having a just and inclusive approach at the front and centre ensures a just transition with synergistic effects that leave nobody behind.

Keywords: big data, just sustainable transition, cosmopolitan city comparison, cities

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Authors: Hongjian Jia

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A finite-length cylindrical shell with a spherical cap is a typical engineering approximation model of actual underwater targets. The research on the omni-directional acoustic scattering characteristics of this target model can provide a favorable basis for the detection and identification of actual underwater targets. The elastic resonance characteristics of the target are the results of the comprehensive effect of the target length, shell-thickness ratio and materials. Under the conditions of different materials and geometric dimensions, the coincidence resonance characteristics of the target have obvious differences. Aiming at this problem, this paper obtains the omni-directional acoustic scattering field of the underwater hemispherical cylindrical shell by numerical calculation and studies the influence of target geometric parameters (length, shell-thickness ratio) and material parameters on the coincidence resonance characteristics of the target in turn. The study found that the formant interval is not a stable value and changes with the incident angle. Among them, the formant interval is less affected by the target length and shell-thickness ratio and is significantly affected by the material properties, which is an effective feature for classifying and identifying targets of different materials. The quadratic polynomial is utilized to fully fit the change relationship between the formant interval and the angle. The results show that the three fitting coefficients of the stainless steel and aluminum targets are significantly different, which can be used as an effective feature parameter to characterize the target materials.

Keywords: hemispherical cylindrical shell;, fine echo characteristics;, geometric and material parameters;, formant interval

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Authors: Haggag H. Mohamed, Ghatass F. Zekry, Shalaby A. Elsayed

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Most sources of air pollution in Egypt are of anthropogenic origin. Alexandria Governorate is located at north of Egypt. The main contributing sectors of air pollution in Alexandria are industry, transportation and area source due to human activities. Alexandria includes more than 40% of the industrial activities in Egypt. Cement manufacture contributes a significant amount to the particulate pollution load. Alexandria Portland Cement Company (APCC) surrounding was selected to be the study area. APCC main kiln stack Total Suspended Particulate (TSP) continuous monitoring data was collected for assessment of dust emission control technology. Electro Static Precipitator (ESP) was fixed on the cement kiln since 2002. The collected data of TSP for first quarter of 2012 was compared to that one in first quarter of 2013 after installation of new bag house filter. In the present study, based on these monitoring data and metrological data a detailed air dispersion modeling investigation was carried out using the Industrial Source Complex Short Term model (ISC3-ST) to find out the impact of applying new bag house filter control technology on the neighborhood ambient air quality. The model results show a drastic reduction of the ambient TSP hourly average concentration from 44.94μg/m3 to 5.78μg/m3 which assures the huge positive impact on the ambient air quality by applying bag house filter technology on APCC cement kiln

Keywords: air pollution modeling, ambient air quality, baghouse filter, cement industry

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Authors: Ahmad Rabby

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The demographic trend analyses of Bombay-duck from time series catch data using CMSY and BSM for the first time in Bangladesh. During 2000-2018, CMSY indicates average lowest production in 2000 and highest in 2018. This has been used in the estimation of prior biomass by the default rules. Possible 31030 viable trajectories for 3422 r-k pairs were found by the CMSY analysis and the final estimates for intrinsic rate of population increase (r) was 1.19 year-1 with 95% CL= 0.957-1.48 year-1. The carrying capacity(k) of Bombay-duck was 283×103 tons with 95% CL=173×103 - 464×103 tons and MSY was 84.3×103tons year-1, 95% CL=49.1×103-145×103 tons year-1. Results from Bayesian state-space implementation of the Schaefer production model (BSM) using catch & CPUE data, found catchabilitiy coefficient(q) was 1.63 ×10-6 from lcl=1.27×10-6 to ucl=2.10×10-6 and r= 1.06 year-1 with 95% CL= 0.727 - 1.55 year-1, k was 226×103 tons with 95% CL=170×103-301×103 tons and MSY was 60×103 tons year-1 with 95% CL=49.9 ×103- 72.2 ×103 tons year-1. Results for Bombay-duck fishery management based on BSM assessment from time series catch data illustrated that, Fmsy=0.531 with 95% CL =0.364 - 0.775 (if B > 1/2 Bmsy then Fmsy =0.5r); Fmsy=0.531 with 95% CL =0.364-0.775 (r and Fmsy are linearly reduced if B < 1/2Bmsy). Biomass in 2018 was 110×103 tons with 2.5th to 97.5th percentile=82.3-155×103 tons. Relative biomass (B/Bmsy) in last year was 0.972 from 2.5th percentile to 97.5th percentile=0.728 -1.37. Fishing mortality in last year was 0.738 with 2.5th-97.5th percentile=0.525-1.37. Exploitation F/Fmsy was 1.39, from 2.5th to 97.5th percentile it was 0.988 -1.86. The biological reference points of B/BMSY was smaller than 1.0, while F/FMSY was higher than 1.0 revealed an over-exploitation of the fishery, indicating that more conservative management strategies are required for Bombay-duck fishery.

Keywords: biological reference points, catchability coefficient, carrying capacity, intrinsic rate of population increase

Procedia PDF Downloads 116

Authors: Marcin Szlachetka, Mateusz Paszko, Grzegorz Baranski

Abstract:

This paper discusses the AVL EXCITE Designer simulation research into loads applied to main and crank bearings in the compression-ignition two-stroke engine. There was created a model of engine lubrication system which covers the part of this system related to particular nodes of a bearing system, i.e. a connection of main bearings in an engine block with a crankshaft, a connection of crank pins with a connecting rod. The analysis focused on the load given as a distribution of hydrodynamic oil film pressure corresponding different values of radial internal clearance. There was also studied the impact of gas force on minimal oil film thickness in main and crank bearings versus crankshaft rotational speed. Our model calculates oil film parameters, an oil film pressure distribution, an oil temperature change and dimensions of bearings as well as an oil temperature distribution on surfaces of bearing seats. Accordingly, it was possible to select, for example, a correct clearance for each of the node bearings. The research was performed for several values of engine crankshaft speed ranging from 800 RPM to 4000 RPM. Bearing oil pressure was changed according to engine speed ranging between 1 bar and 5 bar and an oil temperature of 90°C. The main bearing clearances made initially for the calculation and research were: 0.015 mm, 0.025 mm, 0.035 mm, 0.05 mm, 0.1 mm. The oil used for the research corresponded the SAE 5W-40 classification. The paper presents the selected research results referring to certain specific operating points and bearing radial internal clearances. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A. and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: crank bearings, diesel engine, oil film, two-stroke engine

Procedia PDF Downloads 195

Authors: Hamide Farshad, Mohammadreza Javidi Abdollah Zadeh Aval

Abstract:

As a result of the growing penetration of the media into human life, a new role under the title of "audience" is defined in the social life .A kind of role which is dramatically changed since its formation. This article aims to define the audience position in the new media equations which is concluded to the transformation of the media role. By using the Library and Attributive method to study the history, the evolutionary outlook to the audience and the recognition of the audience and the media relation in the new media context is studied. It was perceived in past that public communication would result in receiving the audience. But after the emergence of the interactional media and transformation in the audience social life, a new kind of public communication is formed, and also the imaginary picture of the audience is replaced by the audience impact on the communication process. Part of this impact can be seen in the form of feedback which is one of the public communication elements. In public communication, the audience feedback is completely accepted. But in many cases, and along with the audience feedback, the media changes its direction; this direction shift is known as media feedback. At this state, the media and the audience are both doers and consistently change their positions in an interaction. With the greater number of the audience and the media, this process has taken a new role, and the role of this doer is sometimes taken by an audience while influencing another audience, or a media while influencing another media. In this article, this multiple public communication process is shown through representing a model under the title of ”The bilateral influence of the audience and the media.” Based on this model, the audience and the media power are not the two sides of a coin, and as a result, by accepting these two as the doers, the bilateral power of the audience and the media will be complementary to each other. Also more, the compatibility between the media and the audience is analyzed in the bilateral and interactional relation hypothesis, and by analyzing the action law hypothesis, the dos and don’ts of this role are defined, and media is obliged to know and accept them in order to be able to survive. They also have a determining role in the strategic studies of a media.

Keywords: audience, effect, media, interaction, action laws

Procedia PDF Downloads 470

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 106

Authors: Nagmani Lnu

Abstract:

Test automation is a vital requirement of any organization to release products faster to their customers. In most cases, an organization has an approach to developing automation but struggles to maintain it. It results in an increased number of Flaky Tests, reducing return on investments and stakeholders’ confidence. Challenges grow in multiple folds when automation is for UI behaviors. This paper describes the approaches taken to identify the root cause of automation instability in an extensive payments application and the best practices to address that using processes, tools, and technologies, resulting in a 75% reduction of effort.

Keywords: automation stability, test stability, Flaky Test, test quality, test automation quality

Procedia PDF Downloads 66

Authors: G. Singh, H.Schuster, U. Füssel

Abstract:

The stability of electric arc and durability of electrode tip used in Tungsten Inert Gas (TIG) welding demand a metallurgical study about the chemical transport mechanism of emitter oxide particles in tungsten electrode during its real welding conditions. The tungsten electrodes doped with emitter oxides of rare earth oxides such as La₂O₃, Th₂O₃, Y₂O₃, CeO₂ and ZrO₂ feature a comparatively lower work function than tungsten and thus have superior emission characteristics due to lesser surface temperature of the cathode. The local change in concentration of these emitter particles in tungsten electrode due to high temperature diffusion (chemical transport) can change its functional properties like electrode temperature, work function, electron emission, and stability of the electrode tip shape. The resulting increment in tip surface temperature results in the electrode material loss. It was also observed that the tungsten recrystallizes to large grains at high temperature. When the shape of grain boundaries are granular in shape, the intergranular diffusion of oxide emitter particles takes more time to reach the electrode surface. In the experimental work, the microstructure of the used electrode's tip surface will be studied by scanning electron microscope and reflective X-ray technique in order to gauge the extent of the diffusion and chemical reaction of emitter particles. Besides, a simulated model is proposed to explain the effect of oxide particles diffusion on the electrode’s microstructure, electron emission characteristics, and electrode tip erosion. This model suggests metallurgical modifications in tungsten electrode to enhance its erosion resistance.

Keywords: rare-earth emitter particles, temperature-dependent diffusion, TIG welding, Tungsten electrode

Procedia PDF Downloads 170

Authors: Alma Lucero Ortiz, Mario Gomez

Abstract:

Technological advances contribute to the well-being of humanity by allowing man to perform in a more efficient way. Technology offers tangible advantages to countries with the adoption of information technologies, communication, and the Internet in all social and productive sectors. The Internet is a networking infrastructure that allows the communication of people throughout the world, exceeding the limits of time and space. Nowadays the internet has changed the way of doing business leading to a digital economy. In this way, e-commerce has emerged as a commercial transaction conducted over the Internet. For this inquiry e-commerce is seen as a source of economic growth for the country. Thereby, these research aims to answer the research question, which are the main variables that have affected the development of e-commerce in Mexico. The research includes a period of study from 1990 to 2017. This inquiry aims to get insight on how the independent variables influence the e-commerce development. The independent variables are information infrastructure construction, urbanization level, economic level, technology level, human capital level, educational level, standards of living, and price index. The results suggest that the independent variables have an impact on development of the e-commerce in Mexico. The present study is carried out in five parts. After the introduction, in the second part, a literature review about the main qualitative and quantitative studies to measure the variables subject to the study is presented. After, an empirical study is applied through time series data, and to process the data an econometric model is performed. In the fourth part, the analysis and discussion of results are presented, and finally, some conclusions are included.

Keywords: digital economy, e-commerce, econometric model, economic growth, internet

Procedia PDF Downloads 221

Authors: Tai Yuan Yu, Pei-Jen Wang

Abstract:

Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings, abbreviated as GFBs, are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional, abbreviated as 3D, fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: fluid-structure interaction, multi-physics simulations, gas foil bearing, oil-free, transient thermo-hydrodynamic

Procedia PDF Downloads 155

Authors: Heikki Valmu, Eero Kupila, Raisa Vartia

Abstract:

A major curricular reform was implemented in Metropolia UAS in 2014. The teaching was to be based on larger course entities and collaborative pedagogy. The most thorough reform was conducted in the department of electrical engineering and automation technology. It has been already shown that the reform has been extremely successful with respect to student progression and drop-out rate. The improvement of the results has been much more significant in this department compared to the other engineering departments making only minor pedagogical changes. In the beginning of the spring term of 2017, a thorough student feedback project was conducted in the department. The study consisted of thirty questions about the implementation of the curriculum, the student workload and other matters related to student satisfaction. The reply rate was more than 40%. The students were divided to four different categories: first year students [cat.1] and students of all the three different majors [categories 2-4]. These categories were found valid since all the students have the same course structure in the first two semesters after which they may freely select the major. All staff members are divided into four teams respectively. The curriculum consists of consecutive 15 credit (ECTS) courses each taught by a group of teachers (3-5). There are to be no end exams and continuous assessment is to be employed. In 2014 the different teacher groups were encouraged to employ innovatively different assessment methods within the given specs. One of these methods has been since used in categories 1 and 2. These students have to complete a number of compulsory tasks each week to pass the course and the actual grade is defined by a smaller number of tests throughout the course. The tasks vary from homework assignments, reports and laboratory exercises to larger projects and the actual smaller tests are usually organized during the regular lecture hours. The teachers of the other two majors have been pedagogically more conservative. The student progression has been better in categories 1 and 2 compared to categories 3 and 4. One of the main goals of this survey was to analyze the reasons for the difference and the assessment methods in detail besides the general student satisfaction. The results show that in the categories following more strictly the specified assessment model much more versatile assessment methods are used and the basic spirit of the new pedagogy is followed. Also, the student satisfaction is significantly better in categories 1 and 2. It may be clearly stated that continuous assessment and teacher cooperation improve the learning outcomes, student progression as well as student satisfaction. Too much academic freedom seems to lead to worse results [cat 3 and 4]. A standardized assessment model is launched for all students in autumn 2017. This model is different from the one used so far in categories 1 and 2 allowing more flexibility to teacher groups, but it will force all the teacher groups to follow the general rules in order to improve the results and the student satisfaction further.

Keywords: continuous assessment, course integration, curricular reform, student feedback

Procedia PDF Downloads 192

Authors: Maik Kschischo, Dominik Kahl, Philipp Wendland, Andreas Weber

Abstract:

Understanding and modelling of real-world complex dynamic systems in biology, engineering and other fields is often made difficult by incomplete knowledge about the interactions between systems states and by unknown disturbances to the system. In fact, most real-world dynamic networks are open systems receiving unknown inputs from their environment. To understand a system and to estimate the state dynamics, these inputs need to be reconstructed from output measurements. Reconstructing the input of a dynamic system from its measured outputs is an ill-posed problem if only a limited number of states is directly measurable. A first requirement for solving this problem is the invertibility of the input-output map. In our work, we exploit the fact that invertibility of a dynamic system is a structural property, which depends only on the network topology. Therefore, it is possible to check for invertibility using a structural invertibility algorithm which counts the number of node disjoint paths linking inputs and outputs. The algorithm is efficient enough, even for large networks up to a million nodes. To understand structural features influencing the invertibility of a complex dynamic network, we analyze synthetic and real networks using the structural invertibility algorithm. We find that invertibility largely depends on the degree distribution and that dense random networks are easier to invert than sparse inhomogeneous networks. We show that real networks are often very difficult to invert unless the sensor nodes are carefully chosen. To overcome this problem, we present a sensor node placement algorithm to achieve invertibility with a minimum set of measured states. This greedy algorithm is very fast and also guaranteed to find an optimal sensor node-set if it exists. Our results provide a practical approach to experimental design for open, dynamic systems. Since invertibility is a necessary condition for unknown input observers and data assimilation filters to work, it can be used as a preprocessing step to check, whether these input reconstruction algorithms can be successful. If not, we can suggest additional measurements providing sufficient information for input reconstruction. Invertibility is also important for systems design and model building. Dynamic models are always incomplete, and synthetic systems act in an environment, where they receive inputs or even attack signals from their exterior. Being able to monitor these inputs is an important design requirement, which can be achieved by our algorithms for invertibility analysis and sensor node placement.

Keywords: data-driven dynamic systems, inversion of dynamic systems, observability, experimental design, sensor node placement

Procedia PDF Downloads 131

Authors: Arpine Maghakyan

Abstract:

The purpose of this paper is to study the relationship between the level of industry digitalization and audit fees, especially, the relationship between Big 4 auditor fees and industry digitalization level. On the one hand, automation of business processes decreases internal control weakness and manual mistakes; increases work effectiveness and integrations. On the other hand, it may cause serious misstatements, high business risks or even bankruptcy, typically in early stages of automation. Incomplete automation can bring high audit risk especially if the auditor does not fully understand client’s business automation model. Higher audit risk consequently will cause higher audit fees. Higher audit fees for clients with high automation level are more highlighted in Big 4 auditor’s behavior. Using data of US firms from 2005-2015, we found that industry level digitalization is an interaction for the auditor quality on audit fees. Moreover, the choice of Big4 or non-Big4 is correlated with client’s industry digitalization level. Big4 client, which has higher digitalization level, pays more than one with low digitalization level. In addition, a high-digitalized firm that has Big 4 auditor pays higher audit fee than non-Big 4 client. We use audit fees and firm-specific variables from Audit Analytics and Compustat databases. We analyze collected data by using fixed effects regression methods and Wald tests for sensitivity check. We use fixed effects regression models for firms for determination of the connections between technology use in business and audit fees. We control for firm size, complexity, inherent risk, profitability and auditor quality. We chose fixed effects model as it makes possible to control for variables that have not or cannot be measured.

Keywords: audit fees, auditor quality, digitalization, Big4

Procedia PDF Downloads 286