Search results for: adaptive thermal comfort model

Authors: John Deely, Stephen Hynes, Mary Cawley, Sarah Hogan

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Domestic marine and coastal tourism have increased in importance over the last number of years due to the impacts of international travel, environmental concerns, associated health benefits and COVID-19 related travel restrictions. Consequently, this paper conceptualizes domestic marine and coastal tourism within an economic framework. Two logit models examine the factors that influence participation in the coastal day trips and overnight stays markets, respectively. Two truncated travel cost models are employed to explore trip duration, one analyzing the number of day trips taken and the other examining the number of nights spent in marine and coastal areas. Although a range of variables predicts participation, no one variable had a significant and consistent effect on every model. A division in access to domestic marine and coastal tourism is also observed based on variation in household income. The results also indicate a vibrant day trip market and large consumer surpluses.

Keywords: domestic marine and coastal tourism, day tripper, participation models, truncated travel cost model

Procedia PDF Downloads 128

Authors: Carlos Herrera Sierralta, Husain M. Muslim, Meshal T. Alsaiari, Daniel Fischer

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Preventing piping fatigue flow induced vibration in the Oil & Gas sector demands not only the constant development of engineering design methodologies based on available software packages, but also special piping support technologies for designing safe and reliable piping systems. The vast majority of piping vibration problems in the Oil & Gas industry are provoked by the process flow characteristics which are basically intrinsically related to the fluid properties, the type of service and its different operational scenarios. In general, the corrective actions recommended for flow induced vibration in piping systems can be grouped in two major areas: those which affect the excitation mechanisms typically associated to process variables, and those which affect the response mechanism of the pipework per se, and the pipework associated steel support structure. Where possible the first option is to try to solve the flow induced problem from the excitation mechanism perspective. However, in producing facilities the approach of changing process parameters might not always be convenient as it could lead to reduction of production rates or it may require the shutdown of the system in order to perform the required piping modification. That impediment might lead to a second option, which is to modify the response of the piping system to excitation generated by the type of process flow. In principle, the action of shifting the natural frequency of the system well above the frequency inherent to the process always favours the elimination, or considerably reduces, the level of vibration experienced by the piping system. Tightening up the clearances at the supports (ideally zero gap), and adding new static supports at the system, are typical ways of increasing the natural frequency of the piping system. However, only stiffening the piping system may not be sufficient to resolve the vibration problem, and in some cases, it might not be feasible to implement it at all, as the available piping layout could create limitations on adding supports due to thermal expansion/contraction requirements. In these cases, utilization of viscous damper supports could be recommended as these devices can allow relatively large quasi-static movement of piping while providing sufficient capabilities of dissipating the vibration. Therefore, when correctly selected and installed, viscous damper supports can provide a significant effect on the response of the piping system over a wide range of frequencies. Viscous dampers cannot be used to support sustained, static loads. This paper shows over a real case example, a methodology which allows to determine the selection of the viscous damper supports via a dynamic analysis model. By implementing this methodology, it was possible to resolve the piping vibration problem throughout redesigning adequately the existing static piping supports and by adding new viscous dampers supports. This was conducted on-stream at the oil crude pipeline in question without the necessity of reducing the production of the plant. Concluding that the application of the methodology of this paper can be applied to solve similar cases in a straightforward manner.

Keywords: dynamic analysis, flow induced vibration, piping supports, turbulent flow, slug flow, viscous damper

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Authors: Stuart W. Campbell, Alexander M. Galloway, Norman A. McPherson, Duncan Camilleri, Daniel Micallef

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Gas tungsten arc welding requires a gas shield to be present in order to protect the arc area from contamination by atmospheric gases. As a result of each gas having its own unique thermophysical properties, the shielding gas selected can have a major influence on the arc stability, welding speed, weld appearance and geometry, mechanical properties and fume generation. Alternating shielding gases is a relatively new method of discreetly supplying two different shielding gases to the welding region in order to take advantage of the beneficial properties of each gas, as well as the inherent pulsing effects generated. As part of an ongoing process to fully evaluate the effects of this novel supply method, a computational fluid dynamics model has been generated to include the gas dependent thermodynamic and transport properties in order to evaluate the effects that an alternating gas supply has on the arc plasma. Experimental trials have also been conducted to validate the model arc profile predictions.

Keywords: Alternating shielding gases, ANSYS CFX, Gas tungsten arc welding(GTAW), magnetohydrodynamics(MHD)

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Authors: Sadia Ilyas, Hyunjung Kim, Rajiv R. Srivastava

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Current work has attempted to establish the linkages between circular bio-economy and recycling of copper and gold from urban mine by applying microbial activities instead of the smelter and chemical technologies. Thereafter, based on the potential of microbial approaches and research hypothesis, the structural model has been tested for a significance level of 99%, which is supported by the corresponding standardization co-efficient values. A prediction model applied to determine the recycling impact on circular bio-economy indicates to re-circulate 51,833 tons of copper and 58 tons of gold by 2030 for the production of virgin metals/raw-materials, while recycling rate of the accumulated e-waste remains to be 20%. This restoration volume of copper and gold through the microbial activities corresponds to mitigate 174 million kg CO₂ emissions and 24 million m³ water consumption if compared with the primary production activities. The study potentially opens a new window for environmentally-friendly biotechnological recycling of e-waste urban mine under the umbrella concept of circular bio-economy.

Keywords: urban mining, biobleaching, circular bio-economy, environmental impact

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Authors: Laila Mahtout, Kerami Ahmed, Rabhi Souhila

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The objective of this work is to reduce the impact on the environment of an acid dye (Black Eriochrome T) using catalytic photo-degradation in the presence of the semiconductor powder (TiO₂) previously characterized. A series of tests have been carried out in order to demonstrate the influence of certain parameters on the degree of dye degradation by titanium dioxide in the presence of UV rays, such as contact time, the powder mass and the pH of the solution. X-ray diffraction analysis of the powder showed that the anatase structure is predominant and the rutile phase is presented by peaks of low intensity. The various chemical groups which characterize the presence of the bands corresponding to the anatase and rutile form and other chemical functions have been detected by the Fourier Transform Infrared spectroscopy. The photo degradation of the NET by TiO₂ is very interesting because it gives encouraging results. The study of photo-degradation at different concentrations of the dye showed that the lower concentrations give better removal rates. The degree of degradation of the dye increases with increasing pH; it reaches the maximum value at pH = 9. The ideal mass of TiO₂ which gives the high removal rate is 1.2 g/l. Thermal treatment of TiO₂ with the addition of CuO with contents of 5%, 10%, and 15% respectively gives better results of degradation of the NET dye. The high percentage of elimination is observed at a CuO content of 15%.

Keywords: acid dye, ultraviolet rays, degradation, photocatalyse

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Authors: Guneet Saini, Shahrukh, Sunil Sharma

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Traffic congestion is the most critical issue faced by those in the transportation profession today. Over the past few years, roundabouts have been recognized as a measure to promote efficiency at intersections globally. In developing countries like India, this type of intersection still faces a lot of issues, such as bottleneck situations, long queues and increased waiting times, due to increasing traffic which in turn affect the performance of the entire urban network. This research is a case study of a non-conventional roundabout, in terms of geometric design, in a small town in India. These types of roundabouts should be analyzed for their functionality in mixed traffic conditions, prevalent in many developing countries. Microscopic traffic simulation is an effective tool to analyze traffic conditions and estimate various measures of operational performance of intersections such as capacity, vehicle delay, queue length and Level of Service (LOS) of urban roadway network. This study involves analyzation of an unsymmetrical non-circular 6-legged roundabout known as “Kala Aam Chauraha” in a small town Bulandshahr in Uttar Pradesh, India using VISSIM simulation package which is the most widely used software for microscopic traffic simulation. For coding in VISSIM, data are collected from the site during morning and evening peak hours of a weekday and then analyzed for base model building. The model is calibrated on driving behavior and vehicle parameters and an optimal set of calibrated parameters is obtained followed by validation of the model to obtain the base model which can replicate the real field conditions. This calibrated and validated model is then used to analyze the prevailing operational traffic performance of the roundabout which is then compared with a proposed alternative to improve efficiency of roundabout network and to accommodate pedestrians in the geometry. The study results show that the alternative proposed is an advantage over the present roundabout as it considerably reduces congestion, vehicle delay and queue length and hence, successfully improves roundabout performance without compromising on pedestrian safety. The study proposes similar designs for modification of existing non-conventional roundabouts experiencing excessive delays and queues in order to improve their efficiency especially in the case of developing countries. From this study, it can be concluded that there is a need to improve the current geometry of such roundabouts to ensure better traffic performance and safety of drivers and pedestrians negotiating the intersection and hence this proposal may be considered as a best fit.

Keywords: operational performance, roundabout, simulation, VISSIM

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Authors: Yu-Kai Ting, Jia-Ying Tu, Chung-Chun Hsiao

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New physical insights into the nonlinear Lorenz equations related to flow resistance is discussed in this work. The chaotic dynamics related to Lorenz equations has been studied in many papers, which is due to the sensitivity of Lorenz equations to initial conditions and parameter uncertainties. However, the physical implication arising from Lorenz equations about convectional motion attracts little attention in the relevant literature. Therefore, as a first step to understand the related fluid mechanics of convectional motion, this paper derives the Lorenz equations again with different forced conditions in the model. Simulation work of the modified Lorenz equations without the viscosity or buoyancy force is discussed. The time-domain simulation results may imply that the states of the Lorenz equations are related to certain flow speed and flow resistance. The flow speed of the underlying fluid system increases as the flow resistance reduces. This observation would be helpful to analyze the coupling effects of different fluid parameters in a convectional model in future work.

Keywords: Galerkin method, Lorenz equations, Navier-Stokes equations, convectional motion

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Authors: Mert Tosun, Tuğba Tosun

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The evaporator is the utmost important component in the refrigeration system, since it enables the refrigerant to draw heat from the desired environment, i.e. the refrigerated space. Studies are being conducted on this component which generally affects the performance of the system, where energy efficient products are important. This study was designed to enhance the effectiveness of the evaporator in the refrigeration cycle of a domestic refrigerator by adjusting the capillary tube length, refrigerant amount, and the evaporator pipe diameter to reduce energy consumption. The experiments were conducted under identical thermal and ambient conditions. Experiment data were analysed using the Design of Experiment (DOE) technique which is a six-sigma method to determine effects of parameters. As a result, it has been determined that the most important parameters affecting the evaporator performance among the selected parameters are found to be the refrigerant amount and pipe diameter. It has been determined that the minimum energy consumption is 6-mm pipe diameter and 16-g refrigerant. It has also been noted that the overall consumption of the experiment sample decreased by 16.6% with respect to the reference system, which has 7-mm pipe diameter and 18-g refrigerant.

Keywords: heat exchanger, refrigerator, design of experiment, energy consumption

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Authors: Raghuveer Kaur, Kartikay Sharma, Ashu Khanna

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Earnings management has been present from times immemorial. The recent downfall of giant enterprises like Enron, Satyam and WorldCom has brought a lot of focus on the study and detection of earnings management. The present study is an attempt to study earnings management in one of the fastest emerging economy - India. The study makes an attempt to understand earnings management in different sectors of the economy. The paper first tests a hypothesis to check whether different sectors of India are engaged in earnings management or not. In the later section the paper aims to study the level of earnings management in 6 popular sectors of India: IT&BPO, Retail, Telecom, Biotech, Hotels and coffee. To measure earnings management two popular techniques of detecting earnings management has been employed: Modified Jones Model and Beniesh M Score. A total of 332 companies were studied. Publicly available data from Capitaline database has been used. The paper also classifies the top and bottom five performers on the basis of sales turnover in each sector and identifies whether they manage their earnings or not.

Keywords: earnings management, India, modified Jones model, Beneish M score

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Authors: Said Belaaouad

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This study aimed to explore the quantitative structure-activity relationship (QSAR) of 1,2,4-Triazine-3(2H)-one derivative as a potential anticancer agent against breast cancer. The electronic descriptors were obtained using the Density Functional Theory (DFT) method, and a multiple linear regression techniques was employed to construct the QSAR model. The model exhibited favorable statistical parameters, including R2=0.849, R2adj=0.656, MSE=0.056, R2test=0.710, and Q2cv=0.542, indicating its reliability. Among the descriptors analyzed, absolute electronegativity (χ), total energy (TE), number of hydrogen bond donors (NHD), water solubility (LogS), and shape coefficient (I) were identified as influential factors. Furthermore, leveraging the validated QSAR model, new derivatives of 1,2,4-Triazine-3(2H)-one were designed, and their activity and pharmacokinetic properties were estimated. Subsequently, molecular docking (MD) and molecular dynamics (MD) simulations were employed to assess the binding affinity of the designed molecules. The Tubulin colchicine binding site, which plays a crucial role in cancer treatment, was chosen as the target protein. Through the simulation trajectory spanning 100 ns, the binding affinity was calculated using the MMPBSA script. As a result, fourteen novel Tubulin-colchicine inhibitors with promising pharmacokinetic characteristics were identified. Overall, this study provides valuable insights into the QSAR of 1,2,4-Triazine-3(2H)-one derivative as potential anticancer agent, along with the design of new compounds and their assessment through molecular docking and dynamics simulations targeting the Tubulin-colchicine binding site.

Keywords: QSAR, molecular docking, ADMET, 1, 2, 4-triazin-3(2H)-ones, breast cancer, anticancer, molecular dynamic simulations, MMPBSA calculation

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Authors: Mingyan Hong, Shuozhao Hou

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Collaborative Strategic Learning (CSL) teaches students to use learning strategies while working cooperatively. Student strategies include the following steps: defining the learning task and purpose; conducting ongoing negotiation of the learning materials by deciding "click" (I get it and I can teach it – green card, I get it –yellow card) or "clunk" (I don't get it – red card) at the end of each learning unit; "getting the gist" of the most important parts of the learning materials; and "wrapping up" key ideas. Find out how to help students of mixed achievement levels apply learning strategies while learning content area in materials in small groups. The design of CSL is based on social-constructivism and Vygotsky’s best-known concept of the Zone of Proximal Development (ZPD). The definition of ZPD is the distance between the actual acquisition level as decided by individual problem solution case and the level of potential acquisition level, similar to Krashen (1980)’s i+1, as decided through the problem-solution case under the facilitator’s guidance, or in group work with other more capable members (Vygotsky, 1978). Vygotsky claimed that learners’ ideal learning environment is in the ZPD. An ideal teacher or more-knowledgable-other (MKO) should be able to recognize a learner’s ZPD and facilitates them to develop beyond it. Then the MKO is able to leave the support step by step until the learner can perform the task without aid. Steven Krashen (1980) proposed Input hypothesis including i+1 hypothesis. The input hypothesis models are the application of ZPD in second language acquisition and have been widely recognized until today. Krashen (2019)’s optimal language learning environment (2019) further developed the application of ZPD and added the component of strategic group learning. The strategic group learning is composed of desirable learning materials learners are motivated to learn and desirable group members who are more capable and are therefore able to offer meaningful input to the learners. Purpose-driven Collaborative Strategic Learning Model is a strategic integration of ZPD, i+1 hypothesis model, and Optimal Language Learning Environment Model. It is purpose driven to ensure group members are motivated. It is collaborative so that an optimal learning environment where meaningful input from meaningful conversation can be generated. It is strategic because facilitators in the model strategically assign each member a meaningful and collaborative role, e.g., team leader, technician, problem solver, appraiser, offer group learning instrument so that the learning process is structured, and integrate group learning and team building making sure holistic development of each participant. Using data collected from college year one and year two students’ English courses, this presentation will demonstrate how purpose-driven collaborative strategic learning model is implemented in the second/foreign language classroom, using the qualitative data from questionnaire and interview. Particular, this presentation will show how second/foreign language learners grow from functioning with facilitator or more capable peer’s aid to performing without aid. The implication of this research is that purpose-driven collaborative strategic learning model can be used not only in language learning, but also in any subject area.

Keywords: collaborative, strategic, optimal input, second language acquisition

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Authors: Ziwei Xu

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The increasing emphasis on mobility has driven the application of innovative communication technologies across various industries. In the retail sector, Near Field Communication (NFC) has emerged as a significant and transformative technology, particularly in the payment and retail supermarket sectors. NFC enables new payment methods, such as electronic wallets, and enhances information management in supermarkets, contributing to the growth of the trade. This report presents a comprehensive analysis of NFC technology, focusing on five key aspects. Firstly, it provides an overview of NFC, including its application methods and development history. Additionally, it incorporates Arthur's work on combinatorial evolution to elucidate the emergence and impact of NFC technology, while acknowledging the limitations of the model in analyzing NFC. The report then summarizes the positive influence of NFC on the retail industry along with its associated constraints. Furthermore, it explores the adoption of NFC from both organizational and individual perspectives, employing the Best Predictors of organizational IT adoption and UTAUT2 models, respectively. Finally, the report discusses the potential future replacement of NFC with biometrics technology, highlighting its advantages over NFC and leveraging Arthur's model to investigate its future development prospects.

Keywords: innovation, NFC, industry, biometrics

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Authors: Abubakar Mukhtar Yakasai, Muhammad Tahir Jan

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Purpose: This paper is aimed at exploring factors influencing online shopping intention among the young consumers in Nigeria. Design/Methodology/approach: The paper adopted and extended Technology Acceptance Model (TAM) as the basis for literature review. Additionally, the paper proposed a framework with the inclusion of culture as a moderating factor of consumer online shopping intention among consumers in Nigeria. Findings: Despite high rate of internet penetration in Nigerian, as well as the rapid advancement of online shopping in the world, little attention was paid to this important revolution specifically among Nigeria’s consumers. Based on the review of extant literature, the TAM extended to include perceived risk and enjoyment (PR and PE) was discovered to be a better alternative framework for predicting Nigeria’s young consumers’ online shopping intention. The moderating effect of culture in the proposed model is shown to help immensely in ascertaining differences, if any, between various cultural groups among online shoppers in Nigeria. Originality/ value: The critical analysis of different factors will assist practitioners (like online retailers, e-marketing managers, website developers, etc.) by signifying which combinations of factors can best predict consumer online shopping behaviour in particular instances, thereby resulting in effective value delivery. Online shopping is a newly adopted technology in Nigeria, hence the paper will give a clear focus for effective e-marketing strategy. In addition, the proposed framework in this paper will guide future researchers by providing a tool for systematic evaluation and testing of real empirical situation of online shopping in Nigeria.

Keywords: online shopping, perceived ease of use, perceived usefulness, perceived enjoyment, technology acceptance model, Nigeria

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

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Authors: Chun-Lin Zhang, Min Wan

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With the upgrade development of the tourism industry from the simple sightseeing tour to the leisure and vacation, people's travel idea has undergone a fundamental change. More and more people begin to pursue liberal and personal tourism, so self-driving tourism has become the main form of current tourism activities. With the self-driving tourism representing the general trend, the importance of convenient tourism transportation and perfect road traffic signs have become more and more prominent. A clear urban road traffic signs can help visitors quickly identify the direction and distance to the tourism destination. The purpose of this article is analyzing the planning of urban road traffic signs which can bring positive impact on the participation in the recreation involved of self-driving tourists. The content of this article is divided into three parts. Based on the literature review and theoretical analysis, the first part constructs a structural variance model. The model is from three dimensions: the attention of the self-driving tourists to the urban traffic signs along the road, the perception of the self-driving tourists to the road traffic signs itself, the perceptions of the self-driving tourists to the tourism destination information on the traffic signs. Through this model, the paper aims to explore the influence of the urban road traffic signs to the leisure psychological involvement and leisure behavior involvement of the self-driving tourists. The second part aims to verify through the hypothesis model the questionnaire survey and come to preliminary conclusions. The preliminary conclusions are as follows: firstly, the color, shape, size, setting mode and occurrence frequency of urban road traffic sign have significant influence on the leisure psychological involvement and leisure behavior involvement of the self-driving tourists. Secondly, the influence on the leisure behavior involvement is obviously higher than the influence on the leisure psychological involvement. Thirdly, the information about the tourism destination marked on the urban road traffic signs has not obviously influence on the leisure psychological involvement, but it has distinct influence on the leisure behavior involvement of self-driving tourists. The third part puts forward that the planning of urban road traffic signs should focus on the angle of the impact of road traffic signs on people's psychology and behavior. On the basis of the above conclusions, the paper researches the color, shape, size, setting mode and information labeling of urban road traffic signs so that they can preferably satisfy the demand of the leisure involvement of self-driving tourists.

Keywords: leisure involvement, self-driving tourism, structural equation, urban road traffic signs

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Authors: Marian Mihalik, Kornel Csach, Martin Kovalik, Matúš Mihalik, Martina Kubovčíková, Maria Zentková, Martin Vavra, Vladimír Girman, Jaroslav Briančin, Marija Perovic, Marija Boškovic, Magdalena Fitta, Robert Pelka

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Current nanomaterials for use in biomedicine are based mainly on iron oxides and on present knowledge on magnetic nanostructures. Manganites can represent another material which can be used optionally. Manganites and their unique electronic properties have been extensively studied in the last decades not only due to fundamental interest but to possible applications of colossal magnetoresistance, magnetocaloric effect, and ferroelectric properties. It was found that the oxygen-reduction reaction on perovskite oxide is intimately connected with metal ion e.g., orbital occupation. The effect of oxygen deviation from the stoichiometric composition on crystal structure was studied very carefully by many authors on LaMnO₃. Depending on oxygen content, the crystal structure changes from orthorhombic one to rhombohedric for oxygen content 3.1. In the case of hole-doped manganites, the change from the orthorhombic crystal structure, which is typical for La1-xCaxMnO3 based manganites, to the rhombohedric crystal structure (La1-xMxMnO₃ where M = K, Ag, and Sr based materials) results in an enormous increase of the Curie temperature. In our paper, we study the effect of oxygen content on crystal structure, thermal, and magnetic properties (including magnetocaloric effect) of La1-xAgxMnO₃nano particle system. The content of oxygen in samples was tuned by heat treatment in different thermal regimes and in various environment (air, oxygen, argon). Water nanosuspensions based on La0.80Ag0.15MnO₃ magnetic particles with the Curie temperature of about 43oC were prepared by two different approaches. First, by using a laboratory circulation mill for milling of powder in the presence of sodium dodecyl sulphate (SDS) and subsequent centrifugation. Second nanosuspension was prepared using an agate bowl, etching in citric acid and HNO3, ultrasound homogeniser, centrifugation, and dextran 40 kDA or 15 kDA as surfactant. Electrostatic stabilisation obtained by the first approach did not offer long term kinetic and aggregation colloidal stability and was unable to compensate for attractive forces between particles under a magnetic field. By the second approach, we prepared suspension oversaturated by dextran 40 kDA for steric stabilisation, with evidence of the presence of superparamagnetic behaviour. Low concentration of nanoparticles and not ideal coverage of nanoparticles impacting the stability of ferrofluids was the disadvantage of this approach. Strong steric stabilisation was observable at alcaic conditions under pH = ~10. Application of dextran 15 kDA leads to relatively stable ferrofluid with pH around physiological conditions, but desegregation of powder by HNO₃ was not effective enough, and the average size of fragments was to large of about 150 nm, and we did not see any signature of superparamagnetic behaviour. The prepared ferrofluids were characterised by scanning and transition microscope method, thermogravimetry, magnetization, and AC susceptibility measurements. Specific Absorption Rate measurements were undertaken on powder as well on ferrofluids in order to estimate the potential application of La₀.₈₀Ag₀.₁₅MnO₃ magnetic particles based ferrofluid for hyperthermia. Our complex study contains an investigation of biocompatibility and potential biohazard of this material.

Keywords: manganites, magnetic nanoparticles, oxygen content, magnetic phase transition, magnetocaloric effect, ferrofluid, hyperthermia

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Authors: Sijuade A. A., Oguntoye J. P., Awodoye O. O., Adedapo O. A., Wahab W. B., Okediran O. O., Omidiora E. O., Olabiyisi S. O.

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Electronic voting systems have been introduced to improve the efficiency, accuracy, and transparency of the election process in many countries around the world, including Nigeria. However, concerns have been raised about the security and integrity of these systems. One way to address these concerns is through the implementation of electronic forensic election audit systems. This study aims to evaluate voters' intention to the adoption of electronic forensic election audit systems using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. In the study, the UTAUT model which is a widely used model in the field of information systems to explain the factors that influence individuals' intention to use a technology by integrating performance expectancy, effort expectancy, social influence, facilitating conditions, cost factor and privacy factor to voters’ behavioural intention was proposed. A total of 294 sample data were collected from a selected population of electorates who had at one time or the other participated in at least an electioneering process in Nigeria. The data was then analyzed statistically using Partial Least Square Structural Equation Modeling (PLS-SEM). The results obtained show that all variables have a significant effect on the electorates’ behavioral intention to adopt the development and implementation of an electronic forensic election audit system in Nigeria.

Keywords: election Audi, voters, UTAUT, performance expectancy, effort expectancy, social influence, facilitating condition social influence, facilitating conditions, cost factor, privacy factor, behavioural intention

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Authors: Natnael Debalklie Teshome

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The purpose of the study was to empirically investigate the impacts of export performance and its volatility on economic growth in the Ethiopian economy. To do so, time-series data of the sample period from 1974/75 – 2017/18 were collected from databases and annual reports of IMF, WB, NBE, MoFED, UNCTD, and EEA. The extended Cobb-Douglas production function of the neoclassical growth model framed under the endogenous growth theory was used to consider both the performance and instability aspects of export. First, the unit root test was conducted using ADF and PP tests, and data were found in stationery with a mix of I(0) and I(1). Then, the bound test and Wald test were employed, and results showed that there exists long-run co-integration among study variables. All the diagnostic test results also reveal that the model fulfills the criteria of the best-fitted model. Therefore, the ARDL model and VECM were applied to estimate the long-run and short-run parameters, while the Granger causality test was used to test the causality between study variables. The empirical findings of the study reveal that only export and coefficient of variation had significant positive and negative impacts on RGDP in the long run, respectively, while other variables were found to have an insignificant impact on the economic growth of Ethiopia. In the short run, except for gross capital formation and coefficients of variation, which have a highly significant positive impact, all other variables have a strongly significant negative impact on RGDP. This shows exports had a strong, significant impact in both the short-run and long-run periods. However, its positive and statistically significant impact is observed only in the long run. Similarly, there was a highly significant export fluctuation in both periods, while significant commodity concentration (CCI) was observed only in the short run. Moreover, the Granger causality test reveals that unidirectional causality running from export performance to RGDP exists in the long run and from both export and RGDP to CCI in the short run. Therefore, the export-led growth strategy should be sustained and strengthened. In addition, boosting the industrial sector is vital to bring structural transformation. Hence, the government has to give different incentive schemes and supportive measures to exporters to extract the spillover effects of exports. Greater emphasis on price-oriented diversification and specialization on major primary products that the country has a comparative advantage should also be given to reduce value-based instability in the export earnings of the country. The government should also strive to increase capital formation and human capital development via enhancing investments in technology and quality of education to accelerate the economic growth of the country.

Keywords: export, economic growth, export diversification, instability, co-integration, granger causality, Ethiopian economy

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Authors: Anas H. Aljemely, Jianping Xuan

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Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

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Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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Authors: Enyia James Diwa, Isaiah Thank-God Ebi, Dodeye Ina Igbong

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The privatization of utilities has brought about very strong competition in industries such as petrochemical and gas distribution among others, considering the continuous increase in cost of fuel. This has brought about the intense reason for gas turbine owners and operators to reduce and control performance degradation of the engine in other to minimize cost. The most common and very crucial problem of the gas turbine is the fouling of compressor, which is mostly caused by a reduction in flow capacity, compressor efficiency, and pressure ratio, this, in turn, lead to the engine compressor re-matching and output power and thermal efficiency reduction. The content of this paper encompasses a detailed presentation of the major causes, effects and control mechanism of fouling. The major emphasis is on compressor water washing to enable power augmentation. A modelled gas turbine similar to that of GE LM6000 is modelled for the current study, based on TURBOMATCH which is a Cranfield University software specifically made for gas turbine performance simulation and fouling detection. The compounded and intricate challenges of compressor online water washing of large output gas turbine are carried out. The treatment is applied to axial compressor used in the petrochemical and hydrocarbon industry.

Keywords: gas turbine, fouling, degradation, compressor washing

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Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

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This research study was to investigate of education decisions must be made which a part of it should be passed on to future generations as obligatory for all members of a chemistry class for students who will prepare themselves for a special position. The descriptions of instructional design were provided and the recent criticisms are discussed. This research study to an outline of an integrative framework for the description of information and the instructional design model give structure to negotiate a semblance of conscious understanding. The aims of this study are to describe the instructional design model for comparisons between students’ genders of their effects on STEM educational learning achievement motives to their science attitudes and logical thinking abilities with a sample size of 18 students at the 11th grade level with the cluster random sampling technique in Mahawichanukul School were designed. The chemistry learning environment was administered with the STEM education method. To build up the 5-instrument lesson instructional plan issues were instructed innovations, the 30-item Logical Thinking Test (LTT) on 5 scales, namely; Inference, Recognition of Assumptions, Deduction, Interpretation and Evaluation scales was used. Students’ responses of their perceptions with the Test Of Chemistry-Related Attitude (TOCRA) were assessed of their attitude in science toward chemistry. The validity from Index Objective Congruence value (IOC) checked by five expert specialist educator in two chemistry classroom targets in STEM education, the E1/E2 process were equaled evidence of 84.05/81.42 which results based on criteria are higher than of 80/80 standard level with the IOC from the expert educators. Comparisons between students’ learning achievement motives with STEM educational model on stoichiometry issue in chemistry classes with different genders were differentiated at evidence level of .05, significantly. Associations between students’ learning achievement motives on their posttest outcomes and logical thinking abilities, the predictive efficiency (R2) values indicate that 69% and 70% of the variances in different male and female student groups of their logical thinking abilities. The predictive efficiency (R2) values indicate that 73%; and 74% of the variances in different male and female student groups of their science attitudes toward chemistry were associated. Statistically significant on students’ perceptions of their chemistry learning classroom environment and their science attitude toward chemistry when using the MCI and TOCRA, the predictive efficiency (R2) values indicated that 72% and 74% of the variances in different male and female student groups of their chemistry classroom climate, consequently. Suggestions that supporting chemistry or science teachers from science, technology, engineering and mathematics (STEM) in addressing complex teaching and learning issues related instructional design to develop, teach, and assess traditional are important strategies with a focus on STEM education instructional method.

Keywords: development, the instructional design model, students learning achievement motives, science attitudes with STEM educational model, stoichiometry issue, chemistry classes, genders

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Authors: Constant Gillot, Pauline Michaux, Julien Favresse, Jean-Michel Dogné, Jonathan Douxfils

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Introduction: NETosis has emerged as a crucial yet paradoxical factor in severe COVID-19 cases. While neutrophil extracellular traps (NETs) help contain and eliminate viral particles, excessive NET formation can lead to hyperinflammation, exacerbating tissue damage and acute respiratory distress syndrome (ARDS). Aims: This study evaluates the relationship between COVID-19-infected sera and NETosis using an ex-vivo model. Methods: Sera from 8 post-admission COVID-19 patients, after receiving corticoid therapy, were used to induce NETosis in neutrophils from a healthy donor. NET formation was tracked using fluorescent markers for DNA and neutrophil elastase (NE) every 2 minutes for 8 hours. The results were expressed as a percentage of DNA/NE released over time. Key metrics, including T50 (time to 50% release) and AUC (area under the curve), representing total NETosis potential), were calculated. A 27-cytokine screening kit was used to assess the cytokine composition of the sera. Results: COVID-19 sera induced NETosis based on their cytokine profile. The AUC of NE and DNA release decreased with time following corticoid therapy, showing a significant reduction in 6 of the 8 patients (p<0.05). T50 also decreased in parallel with AUC for both markers. Cytokines concentration decrease with time after therapy administration. There is correlation between 14 cytokines concentration and NE release. Conclusion: This ex-vivo model successfully demonstrated the induction of NETosis by COVID-19 sera using two markers. A clear decrease in NETosis potential was observed over time with glucocorticoid therapy. This model can be a valuable tool for monitoring NETosis and investigating potential NETosis inducers and inhibitors.

Keywords: NETosis, COVID-19, cytokine storm, biomarkers

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Authors: Riya Roy, Anjana Bhasi

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Column-supported embankments provide a practical and efficient solution for construction on soft soil due to the low cost and short construction times. In the recent years, geosynthetic have been used in combination with column systems to support embankments. The load transfer mechanism in these systems is a combination of soil arching effect, which occurs between columns and membrane effect of the geosynthetic. This paper aims at the study of soil arching effect on columnar embankments using finite element software, ABAQUS. An axisymmetric finite element model is generated and using this model, parametric studies are carried out. Thus the effects of various factors such as height of embankment fill, elastic modulus of pile and tensile stiffness of geosynthetic, on soil arching have been studied. The development of negative skin friction along the pile-soil interface have also been studied and the results obtained from this study are compared with the current design methods.

Keywords: ABAQUS, geosynthetic, negative skin friction, soil arching

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Authors: Jinrui Zhang, Tianlong Yang, Ying Pan

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Methane and carbon dioxide are major greenhouse gases contributor. CO₂ dry reforming of methane (DRM) for syngas production is a promising approach to reducing global CO₂ emission and extensive utilization of natural gas. However, the reported catalysts endured rapid deactivation due to severe carbon deposition at high temperature. Here, CO₂ reduction by CH4 on hexagonal nano-nickel flakes packed by porous SiO₂ (Ni@SiO₂) catalysts driven by thermal and solar light are tested. High resistance to carbon deposition and higher reactive activity are demonstrated under focused solar light at moderate temperature (400-500 ℃). Furthermore, the photocatalytic DRM under different wavelength is investigated, and even IR irradiation can enhance the catalytic activity. The mechanism of light-enhanced reaction reactivity and equilibrium is investigated by Infrared and Raman spectroscopy, and the unique reaction pathway with light is depicted. The photo-enhanced DRM provides a promising method of renewable solar energy conversion and CO₂ emission reduction due to the excellent activity and durability.

Keywords: CO₂ emission reduction, methane, photocatalytic DRM, resistance to carbon deposition, syngas

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Authors: Norhayati Mat Wajid, Abdul Murad Zainal Abidin, Hasila Jarimi, Kamaruzaman Sopian, Adnan Ibrahim, Ahmad Fazlizan, Afif Safwan

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Solar-adsorption air-conditioning system (SADCS) is an alternative to the conventional vapor compression system (VCS). SADCS have advantages over VCS system, such as 1) a green cooling technology which utilizes solar energy to drive the adsorption/desorption cycle, 2) can be operated using green refrigerant HFC free pure water, 3) mechanically simpler, and 4) lower operating noise level since it has no moving parts other than the magnetic valves. Several advancements have been achieved in these fields in the last decade, but further research is still needed to escalate this technology to a practical level. Hence, this paper presents a literature survey and a review that add insights into the current state-of-the-art of SADCS technologies with emphasis on the practical researches that were conducted at the laboratory scale and commercial level. In this paper, the performance evaluation of vermiculite as adsorbent material for SADCS in tropical climate discussed in comparison to other adsorbent material such as silica gel.

Keywords: adsorption cooling, solar-assisted cooling, HVAC, tropical climate, solar thermal

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Authors: Kim Byeong-Gon, Lee Pureun-Haneul, Hong Jisu, Jang An-Soo

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Background: Diesel exhaust particles (DEPs) lead to trigger airway hyperresponsiveness (AHR) and airway dysfunction or inflammation in respiratory systems. Whether tight junction protein changes can contribute to development or exacerbations of airway diseases remain to be clarified. Objective: The aim of this study was to observe the effect of DEP on tight junction proteins in one airway both nose and lung in a mouse model. Methods: Mice were treated with saline (Sham) and exposed to 100 μg/m³ DEPs 1 hour a day for 5 days a week for 4 weeks and 8 weeks in a closed-system chamber attached to a ultrasonic nebulizer. Airway hyperresponsiveness (AHR) was measured and bronchoalveolar lavage (BAL) fluid, nasal lavage (NAL) fluid, lung and nasal tissue was collected. The effects of DEP on tight junction proteins were estimated using western blot, immunohistochemical in lung and nasal tissue. Results: Airway hyperresponsiveness and number of inflammatory cells were higher in DEP exposure group than in control group, and were higher in 4 and 8 weeks model than in control group. The expression of tight junction proteins CLND4, -5, and -17 in both lung and nasal tissue were significantly increased in DEP exposure group than in the control group. Conclusion: These results suggesting that CLDN4, -5 and -17 may be involved in the airway both nose and lung, suggesting that air pollutants cause to disruption of epithelial and endothelial cell barriers. Acknowledgment: This research was supported by Korea Ministry of Environment (MOE) as 'The Environmental Health Action Program' (2016001360009) and Soonchunhyang University Research Fund.

Keywords: diesel exhaust particles, air pollutant, tight junction, Claudin, Airway inflammation

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Authors: Mona Awad Wanis Gad

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The method of factory making plans has changed loads, in particular, whilst it's miles approximately making plans the factory building itself. Factory making plans have the venture of designing merchandise, plants, tactics, organization, regions, and the construction of a factory. Ordinary restructuring is turning into greater essential for you to preserve the competitiveness of a manufacturing unit. Regulations in new regions, shorter lifestyle cycles of product and manufacturing era, in addition to a VUCA global (Volatility, Uncertainty, Complexity and Ambiguity) cause extra common restructuring measures inside a factory. A digital factory model is the planning foundation for rebuilding measures and turns into a critical device. Furthermore, digital building fashions are increasingly being utilized in factories to help facility management and manufacturing processes. First, exclusive styles of digital manufacturing unit fashions are investigated, and their residences and usabilities to be used instances are analyzed. Within the scope of research are point cloud fashions, building statistics fashions, photogrammetry fashions, and those enriched with sensor information are tested. It investigated which digital fashions permit a simple integration of sensor facts and in which the variations are. In the end, viable application areas of virtual manufacturing unit models are determined by a survey, and the respective digital manufacturing facility fashions are assigned to the application areas. Ultimately, an application case from upkeep is selected and implemented with the assistance of the best virtual factory version. It is shown how a completely digitalized preservation process can be supported by a digital manufacturing facility version by offering facts. Among different functions, the virtual manufacturing facility version is used for indoor navigation, facts provision, and display of sensor statistics. In summary, the paper suggests a structuring of virtual factory fashions that concentrates on the geometric representation of a manufacturing facility building and its technical facilities. A practical application case is proven and implemented. For that reason, the systematic selection of virtual manufacturing facility models with the corresponding utility cases is evaluated.

Keywords: augmented reality, digital factory model, factory planning, restructuring digital factory model, photogrammetry, factory planning, restructuring building information modeling, digital factory model, factory planning, maintenance

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Alfred Kamate Siviri, Angelus Mafikiri Tsongo, Jean Robert Kala Kamdjoug

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Digitalization and information systems well organized have been selected as relevant measures to mitigate operational risks within organizations. Unfortunately, information system comes with new threats that can cause severe damage and quick organization lockout. This study aims to measure perceived information system risks and their effects on operational risks within the microfinance institution in D.R. Congo. Also, the factors influencing the operational risk are identified, and the link between operational risk with other risks and performance is to be assessed. The study proposes a research model drawn on the combination of Resources-Based-View, dynamic capabilities, the agency theory, the Information System Security Model, and social theories of risk. Therefore, we suggest adopting a mixed methods research with the sole aim of increasing the literature that already exists on perceived operational risk assessment and its link with other risk and performance, a focus on IT risk.

Keywords: Democratic Republic Congo, information system risk, microfinance performance, operational risk

Procedia PDF Downloads 219