Search results for: fixed effect model

Authors: Elisabeth Brandenburg, Robert Woll, Rainer Stark

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This paper presents how smart glasses and voice commands can be used for improving the maintenance process of industrial gas turbines. It presents the process of inspecting a gas turbine’s combustion chamber and how it is currently performed using a set of paper-based documents. In order to improve this process, a portable hands-free process assistance system has been conceived. In the following, it will be presented how the approach of user-centered design and the method of paper prototyping have been successfully applied in order to design a user interface and a corresponding workflow model that describes the possible interaction patterns between the user and the interface. The presented evaluation of these results suggests that the assistance system could help the user by rendering multiple manual activities obsolete, thus allowing him to work hands-free and to save time for generating protocols.

Keywords: paper prototyping, smart glasses, turbine maintenance, user centered design

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Authors: Ricardo Merlo

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The use of simulation as a digital didactic tool allowed students to reproduce the laws of Physics in order to improve their academic performance. The didactic resource of simulation also favored the motivation of most of the young people, depending on the subject of Physics to be developed in the classroom and in that sense, it was significant to know the favorable or unfavorable attitude that the students presented about the use of simulation resources to maximize the anchorage of the contents planned for the different classes developed in the classroom. The different real-time simulation applications that were offered free of charge through the Internet were not presented as a specific resource that could be used in a didactic model, and in that framework, the teachers of Physics at the university level did not apply these resources in a systematic way with the knowledge of the favorable or unfavorable attitude of the students towards these didactic resources. For this reason, this work proposed the design and application of attitude questionnaires to enhance the use of those simulation resources that allowed for improving the quality of the class and the academic performance of the students.

Keywords: physics teaching, attitude, motivation, didactic resources

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Authors: Shruti Sengupta

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According to the nationally representative data, about 73% of India's rural workforce is engaged in agriculture. While women make significant contributions to total agriculture production, they contribute to about one-third in India. In terms of gender composition, about 80% of the female and 69% of the male workforce is engaged in agriculture in rural India. Still, it is common to find gender differences in plot management within the household. In the last two and half years, India's agri-food system has undergone several changes due to this pandemic, both the demand and supply side, making agriculture more information and knowledge-intensive. Therefore, this paper investigates, using a nationally representative sample, how information asymmetry affects the net returns per hectare of land between female and male farm managers. Empirical results show that information intensity has a significant positive effect on net farm returns per hectare. Results suggest that if females have the same access to technical information as their male counterparts, their farm income can go up by .96 pp compared to male-headed farms. Results also indicate that literate females have higher farm incomes than non-literate females. The study contributes to the literature by employing gender differentials in farm income due to the information gap.

Keywords: agriculture, gender, information asymmetry, farm income, social bias

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Authors: Anna Claudia Pellicelli, Silvia Procacci

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The study aims to demonstrate how different locations, where the same product is unveiled and tested, can provide a different result in terms of perception by the same kind of people. The experiment was done in occasion of the presentation of a new bike. A group of dealers has been invited in Lloret de Mar, two persons from the headquarter were present to run the presentation, together with an outsourced trainer. Half day dedicated to the theoretical presentation and half day to the test of the new bike on the road, including the test of its direct competitors. The same presentation, organized in the same way, has been delivered in Italy, in 4 locations often used to run business meetings with dealers. In the end of all days of the presentation, dealers had to fill a questionnaire regarding the evaluation of the different bikes tested. The result of the questionnaire showed how the group invited in Spain rated much higher the new bike compared with the dealers testing the bike in locations already known and close to their home. So, in terms of business strategy, it is important to take into account how the location and the way of presenting any product or service can have a favourable impact on the people we want to convince. The next step of the experiment will be to cross check the sales of that bike with the dealers and measure if there is a relation between the top sellers and the one that appreciated the bike the most, in Spain. It would mean that they were able to transfer to customers the same good feelings and impressions they had in Spain.

Keywords: product presentation, locations, emotional effect, business strategy

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Authors: Phornpat Chewasoonthorn, Surat Kwanmuang

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Indoor positioning technologies have been evolved rapidly. They augment the Global Positioning System (GPS) which requires line-of-sight to the sky to track the location of people or objects. This study developed an error correction method for an indoor real-time location system (RTLS) based on an ultra-wideband (UWB) sensor from Decawave. Multiple stationary nodes (anchor) were installed throughout the workspace. The distance between stationary and moving nodes (tag) can be measured using a two-way-ranging (TWR) scheme. The result has shown that the uncorrected ranging error from the sensor system can be as large as 1 m. To reduce ranging error and thus increase positioning accuracy, This study purposes an online correction algorithm using the Kalman filter. The results from experiments have shown that the system can reduce ranging error down to 5 cm.

Keywords: indoor positioning, ultra-wideband, error correction, Kalman filter

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Authors: Mohammad Sadeghi, Mahdieh Saniee

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Nowadays, development laws have become a major branch of engineering science, laws help humankind achieve his/her basic needs, and it is attracted to the attention of the nations. Therefore, lawyers have been invited to contemplate legislator's approaches respecting legislating countries' economic, social and cultural development plans and to observe the reliance of approaches on two elements of distributive justice and transitional justice in light of legal rationality. Legal rationality in development planning has encountered us with this question that whether a rational approach and existing models in the Iran development planning system approximate us to the goal of development laws respecting the rationalist approach and also regarding wisely decision-making model. The present study will investigate processes, approaches, and damages of development planning in the legislation of country development plans to answer this question.

Keywords: rationality, decision-making process, policymaking, development

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Authors: Abdelkader Basli, Jean-Claude Delaunay, Eric Pedrot, Jean-Michel Mérillon, Jean-Pierre Monti, Khodir Madani, Mohamed Chibane, Tristan Richard

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The antioxidant and antimicrobial activities of Origanum glandulosum collected in Algeria have been studied. Extract was prepared from aerial part of endemic Algerian oregano. The produced extract has been characterized in terms of total phenols (using Folin method), total flavonoid, antioxidant activities (using the DPPH radical scavenging method and ORAC assay) and microbial activity against four bacteria: Streptococcus aureus, Bacillus subtilis, Escherichia coli, Klebsiella pneumoniae one yeast: Candida albicans and one fungi: Aspergillus niger. The results pointed the antioxidant activities of the extract of O. glandulosum and antimicrobial activities against all bacteria and C. Candida, but no effect on A. niger. High performance liquid chromatography combined with mass spectrometry (LC-MS) and nuclear magnetic resonance (LC-NMR) were used to separate and identify the major compounds present in the oregano extract. Rosmarinic acid, globoidnan A and B, lithospermic acid B and three flavonoids were identified.

Keywords: origanum glandulosum, antioxidant, microbial activity, polyphenol, LC-MS, LC-NMR

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Authors: Leila Anjomshoa, Firooz Sadighi

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This study investigated the effects of three types of pre-reading activities (vocabulary definitions, text summary and pre-passage questions) on EFL learners’ English reading comprehension. On the basis of the results of a placement test administered to two hundred and thirty English students at Kerman Azad University, 200 subjects (one hundred intermediate and one hundred advanced) were selected.Four texts, two of them at intermediate level and two of them at advanced level were chosen. The data gathered was subjected to the statistical procedures of ANOVA. A close examination of the results through Tukey’s HSD showed the fact that the experimental groups performed better than the control group, highlighting the effect of the treatment on them. Also, the experimental group C (text summary), performed remarkably better than the other three groups (both experimental & control). Group B subjects, vocabulary definitions, performed better than groups A and D. The pre-passage questions group’s (D) performance showed higher scores than the control condition.

Keywords: pre-reading activities, text summary, vocabulary definition, and pre-passage questions, reading comprehension

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Authors: Krzysztof Rafał, Weronika Radziszewska, Hubert Biedka, Oskar Grabowski, Krzysztof Mik

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We present a method to choose energy storage technologies and their parameters for the economic operation of a microgrid. A grid-connected system with local loads and PV generation is assumed, where an energy storage system (ESS) is attached to minimize energy cost by providing energy balancing and arbitrage functionalities. The ESS operates in a hybrid configuration and consists of two unique technologies operated in a coordinated way. Based on given energy profiles and economical data a model calculates financial flow for ESS investment, including energy cost and ESS depreciation resulting from degradation. The optimization strategy proposes a hybrid set of two technologies with their respective power and energy ratings to minimize overall system cost in a given timeframe. Results are validated through microgrid simulations using real-life input profiles.

Keywords: energy storage, hybrid energy storage, cost-benefit analysis, microgrid, battery sizing

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Authors: Sayed Amir Hamzeh Mirkheshti

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Offshore wind energy as a strategic renewable energy, has been growing rapidly due to availability, abundance and clean nature of it. On the other hand, budget of this project is incredibly higher in comparison with other renewable energies and it takes more duration. Accordingly, precise estimation of time and cost is needed in order to promote awareness in the developers and society and to convince them to develop this kind of energy despite its difficulties. Occurrence risks during on project would cause its duration and cost constantly changed. Therefore, to develop offshore wind power, it is critical to consider all potential risks which impacted project and to simulate their impact. Hence, knowing about these risks could be useful for the selection of most influencing strategies such as avoidance, transition, and act in order to decrease their probability and impact. This paper presents an evaluation of the feasibility of 500 MV offshore wind project in the Persian Gulf and compares its situation with uncertainty resources and risk. The purpose of this study is to evaluate time and cost of offshore wind project under risk circumstances and uncertain resources by using Monte Carlo simulation. We analyzed each risk and activity along with their distribution function and their effect on the project.

Keywords: wind energy project, uncertain resources, risks, Monte Carlo simulation

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Authors: Somtop Keawchuer

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This research aims to study (1) the relationship between competency-based learning and learning efficiency of new media communication students at Suan Sunandha University (2) the demographic factor effect on learning efficiency of students at Suan Sunandha University. This research method will use quantitative research; data was collected by questionnaires distributed to students from new media communication in management science faculty of Suan Sunandha Rajabhat University for 1340 sample by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic including T-test, ANOVA and Pearson correlation for hypothesis testing. The results showed that the competency-based learning in term of ability to communicate, ability to think and solve the problem, life skills and ability to use technology has a significant relationship with learning efficiency in term of the cognitive domain, psychomotor domain and affective domain at the 0.05 level and which is in harmony with the research hypotheses.

Keywords: competency-based learning, learning efficiency, new media communication students, Suan Sunandha Rajabhat University

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Authors: Paulo José Sigaúque, Paulo Rosman

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The Itajurú channel, located in the Eastern side of the Araruama lagoon, Rio de Janeiro state, is the one who makes the connection between Araruama lagoon and the sea. It is important to understand the hydrodynamic circulation of the location and effects of the sedimentological processes, and also estimate of the hydrodynamic and sedimentological processes in the future after the sea level change due to effects of climate change. This work presents results of a study about sediments dynamics in the Araruama lagoon focusing on the Itajurú channel region considering the present mean sea level and a foreseen sea level rise of 0.5 meters due to climate changes. The study was conducted with the aid of computer modeling for hydrodynamic and morphodynamic in SisBaHiA®. The results indicate that Araruama lagoon is composed by two hydrodynamics compartments; one is dominated by the action of the tide between the entrance of the channel and the strait of Perynas, and another one by the action of wind in narrow region between strait of Perynas and western extreme of the lagoon. With sea level rise, the magnitude of current velocities and flow rates is increased and consequently flow of sediment transport from upstream to downstream of Itajurú channel is increased and has more effect in the bridge Feliciano Sodré.

Keywords: hydrodinamic, superelevation, sea level, climate change

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Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

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In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, water temperature, and conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: dissolved oxygen, water quality, predication DO, support vector machine

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Authors: N. V. V. S. D. Prasad

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Field experiments were conducted at Regional Agricultural Research Station, Lam, Guntur, Andhra Pradesh, India for two seasons during 2011-13 to evaluate the efficacy of flupyradifurone SL 200 a new class of insecticide in butenolide group against leaf hoppers, aphids and whitefly in Cotton. The test insecticide flupyradifurone 200 was evaluated at three doses @ 150, 200 and 250 g ai/ha ha along with imidacloprid 200 SL @ 20g ai/ha, acetamiprid 20 SP @ 20g ai/ha, thiamethoxam 25 WG @ 25g ai/ha and monocrotophos 36 SL @ 360 g ai/ha as standards. Flupyradifurone SL 200 even at lower dose of 150g ai/ha exhibited superior efficacy against cotton leafhopper, Amrasca devastans than the neonicotinoids which are widely used for control of sucking pests in cotton. Against cotton aphids, Aphis gossypii. Flupyradifurone SL 200 @ 200 and 250 g ai/ha ha was proved to be effective and the lower dose @ 150g ai/ha performed better than some of the neonicotinoids. The effect of flupyradifurone SL 200 on cotton against whitefly, Bemisia tabaci was evident at higher doses of 200 and 250 g ai/ha and superior to all standard treatments, however, the lower dose is at par with neonicotinoids. The seed cotton yield of flupyradifurone 200 SL at all the doses tested was superior than imidacloprid 200 SL @ 20g ai/ha and acetamiprid 20 SP @ 20g ai/ha. There is no significant difference among the insecticidal treatments with regards to natural enemies. The results clearly suggest that flupyradifurone is a new tool to combat sucking pest problems in cotton and can well fit in IRM strategies in light of wide spread insecticide resistance in cotton sucking pests.

Keywords: cotton, flupyradifurone, neonicotinoids, sucking pests

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Authors: Aristeidis Samitas, Stathis Polyzos

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As the UK and the EU prepare to start negotiations for Brexit, it is important for both sides to comprehend the full extent of the consequences of this process. In this paper, we employ an object oriented simulation framework in order to test for the short-term and long-term effects of Brexit on both sides of the Channel. The relative strength of the UK economy and the banking sector vis-à-vis the EU is taken under consideration. Our results confirm predictions in the relevant literature regarding the output cost of Brexit, with particular emphasis on the EU. Furthermore, we show that financial stability is also an important issue on both sides, with the banking system suffering significant losses, particularly over the longer term. Our findings suggest that policymakers should be extremely careful in handling Brexit negotiations, making sure to consider dynamic effects that may be caused by UK bank assets moving to the EU after Brexit. The model results show that, as the UK banking system loses its assets, the end state of the UK economy is deteriorated while the end state of EU economy is improved.

Keywords: Banking Crises, Brexit, Financial Stability, VBanking

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Authors: Anastasiia Kuptsevych, Robert J. Johnson, Olena Antonaccio, Ekaterina V. Botchkovar

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Ukraine has recently experienced one of the bloodiest conflicts taking place on the European continent. Many active duty personnel and civilians have died, and millions of people have been displaced. This situation can lead to disorder in the country characterized by acceptance of violence and crime. There is a gap in the literature addressing the issues related to attitudes towards violence resulting from war, as well as focusing on the world’s more vulnerable civilian populations – those that live in lower and middle-income countries, such as Ukraine. Using a random sample of 1200 adults from two major Ukrainian cities, this study explores the relationship between different types of war exposure (direct and vicarious) and attitudes to violence. Multivariate models reveal that multiple types of war exposure (e.g., being injured, being a witness of death, watching war events on TV) are significantly associated with the attitudes to political and interpersonal violence. In addition, the KHB decomposition procedure showed that experiencing certain mental illnesses serve as important mediating mechanisms between war exposure and attitudes towards violence. Finally, in order to prevent society from disorder and high levels of violence, future studies need to pay more attention to exploring how vital and traumatic life events can lead a population to find violent acts acceptable.

Keywords: attitudes, Ukraine, violence, war

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Authors: D. P. Rollinson, B. J. Dilley, P. G. Ryan

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The white-chinned petrel (Procellaria aequinoctialis) is the seabird species most commonly killed by Southern Hemisphere longline fisheries. Despite the importance of diving ability for mitigating longline bycatch, little is known of this species’ diving behaviour. We obtained data from temperature–depth recorders from nine white-chinned petrels breeding on Marion Island, southwestern Indian Ocean, during the late incubation and chickrearing period. Maximum dive depth (16 m) was slightly deeper than the previous estimate (13 m), but varied considerably among individuals (range 2–16 m). Males dived deeper than females, and birds feeding chicks dived deeper than incubating birds, but dive rate did not differ between the sexes. Time of day had no significant effect on dive depth or rate. Our findings will help to improve the design and performance of mitigation measures aimed at reducing seabird bycatch in longline fisheries, such as the calculation of minimum line sink rates and optimum aerial coverage of bird-scaring lines.

Keywords: dive depth, dive duration, temperature–depth recorders, seabirds, bird-scaring lines

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Authors: Chaouch Souad, Abdou Latifa, Larbi Chrifi Alaoui

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This paper deals with sensorless backstepping control of induction motor using MRAS technique associated to sliding mode approach. A high order genetic algorithm structure is used to approximate a control law designed by the Backstepping technique, and to find the best parameters globally optimized. However, the Backstepping control approach is unsuitable for high performance applications because the need of a speed sensor for increased accuracy and the absence of any error decay mechanism. In this paper a nonlinear observer, obtained by combining sliding mode structure and model reference adaptive system (MRAS), is designed for the rotor flux and rotor speed estimations. To validate the proposed method, the results are presented for showing the improved drive characteristics and performances.

Keywords: Backstepping Control, Induction Motor, Genetic Algorithm, Sliding Mode observer

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Authors: Espinoza S. Clara, Gamarra Q. Flor, Marianela F. Ramos Quispe S. Miguel, Flores R. Omar

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Tropaeolum majus L. is a native plant to South and Central America, used since ancient times by our ancestors to combat different diseases. Glucotropaeolonin is one of its main components, which when hydrolyzed, forms benzyl isothiocyanate (BIT) that promotes cellular apoptosis (programmed cell death in cancer cells). Therefore, the present research aims to evaluate the effect of the pressure and temperature of BIT extraction by supercritical CO₂ from Tropaeolum majus L. The extraction was carried out in a supercritical fluid extractor equipment Speed SFE BASIC Brand: Poly science, the leaves of Tropaeolum majus L. were ground for one hour and lyophilized until obtaining a humidity of 6%. The extraction with supercritical CO₂ was carried out with pressures of 200 bar and 300 bar, temperatures of 50°C, 60°C and 70°C, obtained by the conjugation of these six treatments. BIT was identified by thin layer chromatography using 98% BIT as the standard, and as the mobile phase hexane: dichloromethane (4:2). Subsequently, BIT quantification was performed by high performance liquid chromatography (HPLC). The highest yield of oleoresin by supercritical CO₂ extraction was obtained pressure 300 bar and temperature at 60°C; and the higher content of BIT at pressure 200 bar and 70°C for 30 minutes to obtain 113.615 ± 0.03 mg BIT/100 g dry matter was obtained.

Keywords: solvent extraction, Tropaeolum majus L., supercritical fluids, benzyl isothiocyanate

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Authors: Muhammad Shehu Garba

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The financial statements of the firms between the periods of 2013 and 2022 were collected using the secondary method of data collection, and the study aims to investigate the effect of ownership structure on the financial performance of listed industrial goods companies in Nigeria. 10 firms were used as the study's sample size. The study used panel data variables of the study. The ownership structure is measured with managerial ownership, institutional ownership and foreign ownership, while financial performance is measured with return on asset and return on equity; the study made use of control variables leverage and firm size. The result shows a multivariate relationship that exists between variables of the study, which shows ROA has a positive correlation with ROE (0.4053), MO (0.2001), and FS (0.3048). It has a negative correlation with FO (-0.1933), IO (-0.0919), and LEV (-0.3367). ROE has a positive correlation with ROA (0.4053), MO (0.2001), and FS (0.2640). It has a negative correlation with FO (-0.1864), IO (-0.1847), and LEV (-0.0319). It is recommended that firms should focus on increasing their ROA. Firms should also consider increasing their MO, as this can help to align the interests of managers and shareholders. Firms should also be aware of the potential impact of FO and IO on their ROA.

Keywords: firm size, ownership structure, financial performance, leaverage

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Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

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Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

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Authors: Anna Solovyeva, Ivan Levakin, Nickolai Galaktionov, Olga Podgornaya

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Animals that reproduce asexually were thought to have the same genotypes within generations for a long time. However, some refuting examples were found, and mobile genetic elements (MGEs) or transposons are considered to be the most probable source of genetic instability. Dispersed nature and the ability to change their genomic localization enables MGEs to be efficient mutators. Hence the study of MGEs genomic impact requires an appropriate object which comprehends both representative amounts of various MGEs and options to evaluate the genomic influence of MGEs. Animals that reproduce asexually seem to be a decent model to study MGEs impact in genomic variability. We found a small marine trematode Himasthla elongata (Himasthlidae) to be a good model for such investigation as it has a small genome size, diverse MGEs and parthenogenetic stages in the lifecycle. In the current work, clonal diversity of cercaria was traced with an AFLP (Amplified fragment length polymorphism) method, diverse zones from electrophoretic patterns were cloned, and the nature of the fragments explored. Polymorphic patterns of individual cercariae AFLP-based fingerprints are enriched with retrotransposons of different families. The bulk of those sequences are represented by open reading frames of non-Long Terminal Repeats containing elements(non-LTR) yet Long-Terminal Repeats containing elements (LTR), to a lesser extent in variable figments of AFLP array. The CR1 elements expose both in polymorphic and conservative patterns are remarkably more frequent than the other non-LTR retrotransposons. This data was confirmed with shotgun sequencing-based on Illumina HiSeq 2500 platform. Individual cercaria of the same clone (i.e., originated from a single miracidium and inhabiting one host) has a various distribution of MGE families detected in sequenced AFLP patterns. The most numerous are CR1 and RTE-Bov retrotransposons, typical for trematode genomes. Also, we identified LTR-retrotransposons of Pao and Gypsy families among DNA transposons of CMC-EnSpm, Tc1/Mariner, MuLE-MuDR and Merlin families. We detected many of them in H. elongata transcriptome. Such uneven MGEs distribution in AFLP sequences’ sets reflects the different patterns of transposons spreading in cercarial genomes as transposons affect the genome in many ways (ectopic recombination, gene structure interruption, epigenetic silencing). It is considered that they play a key role in the origins of trematode clonal polymorphism. The authors greatly appreciate the help received at the Kartesh White Sea Biological Station of the Russian Academy of Sciences Zoological Institute. This work is funded with RSF 19-74-20102 and RFBR 17-04-02161 grants and the research program of the Zoological Institute of the Russian Academy of Sciences (project number AAAA-A19-119020690109-2).

Keywords: AFLP, clonal polymorphism, Himasthla elongata, mobile genetic elements, NGS

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Authors: Darren Zou

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Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: BART, Bayesian, predict, stock

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Authors: Oliver Mărunţălu, Gheorghe Lăzăroiu, Elena Elisabeta Manea, Dana Andreya Bondrea, Lăcrămioara Diana Robescu

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This paper presents the results obtained by numerical simulation of the pollutants dispersion in the atmosphere coming from the evacuation of combustion gases resulting from the fuel combustion used by electric thermal power plant using the software ANSYS CFX-CFD. The model uses the Navier-Stokes equation to simulate the dispersion of pollutants in the atmosphere. We considered as important factors in elaboration of simulation the atmospheric conditions (pressure, temperature, wind speed, wind direction), the exhaust velocity of the combustion gases, chimney height and the obstacles (buildings). Using the air quality monitoring stations we have measured the concentrations of main pollutants (SO2, NOx and PM). The pollutants were monitored over a period of 3 months, after that we calculated the average concentration, which is used by the software. The concentrations are: 8.915 μg/m3 (NOx), 9.587 μg/m3 (SO2) and 42 μg/m3 (PM). A comparison of test data with simulation results demonstrated that CFX was able to describe the dispersion of the pollutant as well the concentration of this pollutants in the atmosphere.

Keywords: air pollutants, computational fluid dynamics, dispersion, simulation

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Authors: Mahnoor Khan, Bashir Ahmad, Khizar Hayat, Saad Ahmad Khan, Laiba Ahmad, Shumaila Bashir, Abid Ali Khan

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The objective of this study was to synthesize the smallest possible size of ZnO NPs using a modified wet chemical synthesis method and to prepare core shell using polyethylene glycol (PEG) as shell material. Advanced and sophisticated techniques were used to confirm the synthesis, size, and shape of these NPs. Rounded, clustered NPs of size 5.343 nm were formed. Both the plain and core shell NPs were tested against MDR bacteria (E. cloacae, E. amnigenus, Shigella, S. odorifacae, Citrobacter, and E. coli). Both of the NPs showed excellent antibacterial properties, whereas E. cloacae showed maximum zone of inhibition of 16 mm, 27 mm, and 32 mm for 500 μg/ml, 1000 μg/ml, and 1500 μg/ml, respectively for plain ZnO NPs and 18 mm, 28 mm and 35 mm for 500 μg/ml, 1000 μg/ml and 1500 μg/ml for core shell NPs. These NPs were also biocompatible on human red blood cells showing little hemolysis of only 4% for 70 μg/ml for plain NPs and 1.5% for 70 μg/ml for core shell NPs. Core shell NPs were highly biocompatible because of the PEG. Their therapeutic effect as photosensitizers in photodynamic therapy (PDT) for cancer treatment was also monitored. The cytotoxicity of ZnO and PEG-ZnO was evaluated using MTT assay. Our results demonstrated that these NPs could generate ROS inside tumor cells after irradiation which in turn initiates an apoptotic pathway leading to cell death hence proving to be an effective candidate for PDT.

Keywords: ZnO, hemolysis, cytotoxiciy assay, photodynamic therapy, antibacterial

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Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

Abstract:

Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

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Authors: Fahad Ahmed Qureshi

Abstract:

There were abundant renowned financial markets in Pre-Islamic Arabs. Most of those were patterned and settled during pre-particularized sunshine. Those markets were classified either as vernacular markets helping the neighboring clans, or habitual markets that people sojourned to from all articulations of the Arabian Peninsula, such as Okaz near Mecca. Some of those markets had leading significance due to their geographical positions, such as Prime market of Eden, because of their entanglement in international trade i.e. with the markets of Sub-Continent, Abyssinia, Persia and China. Other markets such as Market of Yamamah annex its gist from being situated on the caravan crossroads. Islamic worldview and Islamic epistemology base of Financial Market’s realistic theory, pragmatic model and operative approach is moderately constrained in terms of its growth. The existent situation only parasol the form of accommodative-modification and splendid-methodologies, which due to depleted and decorous endeavor in explaining Islamic financial market theoretically. This is the demand of time that particular studies should be conduct to magnify the devours in developing theoretical framework for Islamic Financial Market.

Keywords: Islam, financial market, history, research, product development

Procedia PDF Downloads 397

Authors: Gia Lam Le, Dennis T. Bergado, Thi Ngoc Truc Nguyen

Abstract:

This study focuses on behaviors of improved soft clay using prefabricated vertical drain (PVD) combined with vacuum and electro-osmotic preloading. Large-scale consolidations of reconstituted soft Bangkok clay were conducted for PVD improvement with vacuum (vacuum-PVD), and vacuum combined with heat (vacuum-thermo-PVD). The research revealed that vacuum-thermo-PVD gives high efficiency of the consolidation rate compared to the vacuum-PVD. In addition, the magnitude of settlement of the specimen improved by the vacuum-thermo-PVD is higher than the vacuum-PVD because the assistance of heat causes the collapse of the clay structure. Particularly, to reach 90% degree of consolidation, the thermal-vacuum-PVD reduced about 58% consolidation time compared to the vacuum-PVD. The increase in consolidation rate is resulted from the increase in horizontal coefficient of consolidation, Ch, the reduction of the smear effect expressed by the ratio of the horizontal hydraulic conductivity in the undisturbed zone, kh, and the horizontal hydraulic conductivity in the smeared zone, ks. Furthermore, the shear strength, Su, increased about 100% when compared using the vacuum-thermal-PVD to the vacuum PVD. In addition, numerical simulations gave reasonable results compared to the laboratory data.

Keywords: PVD improvement, vacuum preloading, prefabricated vertical drain, thermal PVD

Procedia PDF Downloads 446

Authors: S. Benbellil-Tafoughalt, J. M. Koene

Abstract:

Growth strategies are often plastic and influenced by environmental conditions. Terrestrial gastropods are particularly affected by seasonal and climatic variables, and growth rate and size at maturity are key traits in their life history. Therefore, we investigated juvenile growth of Helix aperta snails under four combinations of temperature and photoperiod using two sets of young snails, born in the laboratory from adults collected in either the autumn (aestivating snails) or spring (active snails). Parental snails were collected from Bakaro (Northeastern Algeria). Higher temperature increased adult size and reduced time to reproduction. Long day photoperiod also increased the final body weight, but had no effect on the length of the growth period. The season of birth had significant effects on length of the growth period and weight of hatchings, whereas this weight difference disappeared by adulthood. The spring snails took less time to develop and reached similar adult body weight as the autumn snails. These differences may be due to differences in egg size or quality between the snails from different seasons. More rapid growth in spring snails results in larger snails entering aestivation, a period with size-related mortality in this species.

Keywords: growth, Hélix aperta, photoperiod, temperature

Procedia PDF Downloads 325

Authors: Beulah Rani Inbanathan

Abstract:

In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

Procedia PDF Downloads 75