Search results for: reliable facility location model
Commenced in January 2007
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Edition: International
Paper Count: 20158

Search results for: reliable facility location model

12238 The Impacts of Export in Stimulating Economic Growth in Ethiopia: ARDL Model Analysis

Authors: Natnael Debalklie Teshome

Abstract:

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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12237 Production of Oral Vowels by Chinese Learners of Portuguese: Problems and Didactic Implications

Authors: Adelina Castelo

Abstract:

The increasing number of learners of Portuguese as Foreign Language in China justifies the need to define the phonetic profile of these learners and to design didactic materials that are adjusted to their specific problems in pronunciation. Different aspects of this topic have been studied, but the production of oral vowels still needs to be investigated. This study aims: (i) to identify the problems the Chinese learners of Portuguese experience in the pronunciation of oral vowels; (ii) to discuss the didactic implications drawn from those problems. The participants were eight native speakers of Mandarin Chinese that had been learning Portuguese in College for almost a year. They named pictured objects and their oral productions were recorded and phonetically transcribed. The selection of the objects to name took into account some linguistic variables (e.g. stress pattern, syllable structure, presence of the Portuguese oral vowels in different word positions according to stress location). The results are analysed in two ways: the impact of linguistic variables on the success rate in the vowels' production; the replacement strategies used in the non-target productions. Both analyses show that the Chinese learners of Portuguese (i) have significantly more difficulties with the mid vowels as well as the high central vowel and (ii) do not master the vowel height feature. These findings contribute to define the phonetic profile of these learners in terms of oral vowel production. Besides, they have important didactic implications for the pronunciation teaching to these specific learners. Those implications are discussed and exemplified.

Keywords: Chinese learners, learners’ phonetic profile, linguistic variables, Portuguese as foreign language, production data, pronunciation teaching, oral vowels

Procedia PDF Downloads 218
12236 Ulnar Parametacarpal Flap for Coverage of Fifth Finger Defects: Propeller Flap Concept

Authors: Ahmed M. Gad, Ahmed S. Hweidi

Abstract:

Background: Defects of the little finger and adjacent areas are not uncommon. It could be a traumatic, post-burn, or after contracture release. Different options could be used for resurfacing these defect, including skin grafts, local or regional flaps. Ulnar para-metacarpal flap described by Bakhach in 1995 based on the distal division of the dorsal branch of the ulnar artery considered a good option for that. In this work, we applied the concept of propeller flap for better mobilization and in-setting of the ulnar para-metacarpal flap. Methods: The study included 15 cases with 4 females and 11 male patients. 10 of the patients had severe post-burn contractures of little finger, and 5 had post-traumatic little finger defects. Contractures were released and resulting soft tissue defects were reconstructed with propeller ulnar para-metacarpal artery flap. The flap based on two main perforators communicating with the palmar system, it was raised based on one of them depending on the extent of the defect and rotated 180 degrees after judicious dissection of the perforator. Results: 13 flaps survived completely, one of the cases developed partial skin loss, which healed by dressing, another flap was completely lost and covered later by a full-thickness skin graft. Conclusion: Ulnar para-metacarpal flap is a reliable option to resurface the little finger as well as adjacent areas. The application of the propeller flap concept based on whether the proximal or distal communicating branch makes the rotation and in-setting of the flap easier.

Keywords: little finger defects, propeller flap, regional hand defects, ulnar parametacarpal flap

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12235 Municipal Solid Waste Management Using Life Cycle Assessment Approach: Case Study of Maku City, Iran

Authors: L. Heidari, M. Jalili Ghazizade

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This paper aims to determine the best environmental and economic scenario for Municipal Solid Waste (MSW) management of the Maku city by using Life Cycle Assessment (LCA) approach. The functional elements of this study are collection, transportation, and disposal of MSW in Maku city. Waste composition and density, as two key parameters of MSW, have been determined by field sampling, and then, the other important specifications of MSW like chemical formula, thermal energy and water content were calculated. These data beside other information related to collection and disposal facilities are used as a reliable source of data to assess the environmental impacts of different waste management options, including landfills, composting, recycling and energy recovery. The environmental impact of MSW management options has been investigated in 15 different scenarios by Integrated Waste Management (IWM) software. The photochemical smog, greenhouse gases, acid gases, toxic emissions, and energy consumption of each scenario are measured. Then, the environmental indices of each scenario are specified by weighting these parameters. Economic costs of scenarios have been also compared with each other based on literature. As final result, since the organic materials make more than 80% of the waste, compost can be a suitable method. Although the major part of the remaining 20% of waste can be recycled, due to the high cost of necessary equipment, the landfill option has been suggested. Therefore, the scenario with 80% composting and 20% landfilling is selected as superior environmental and economic scenario. This study shows that, to select a scenario with practical applications, simultaneously environmental and economic aspects of different scenarios must be considered.

Keywords: IWM software, life cycle assessment, Maku, municipal solid waste management

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12234 Developed CNN Model with Various Input Scale Data Evaluation for Bearing Faults Prognostics

Authors: Anas H. Aljemely, Jianping Xuan

Abstract:

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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12233 Revisiting Dispute Resolution Mechanisms in the Southern African Development Community: A Proposal for Synchronization

Authors: Tapiwa Shumba, Nyaradzo D. T. Karubwa

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Dispute resolution is the plinth of regional integration initiatives anchored on the rule of law and compliance with obligations. Without effective and reliable despite resolution mechanisms, it may be difficult to foster deeper integration. Within the Southern African Development Community (SADC) legal and institutional framework exists an apparent recognition that dispute resolution is an integral part of the regional integration. Almost all legal instruments of SADC include some provision for dispute resolution. Institutionally, the somewhat now defunct SADC Tribunal is meant to be the fulcrum for resolving disputes that arise under SADC instruments. However, after a closer analysis of the substance of these legal provisions and the attendant procedural mechanisms for addressing disputes, an argument can be made that dispute resolution in SADC is somewhat scant, fragmented and neglected. In most instruments, the common provision on dispute resolution appears to be a ‘mid-night clause’. In other instruments which have specialised provisions and procedures, questions of practicality and genius cannot be avoided. Worse still there now appears to be a lack of magnanimity between the substantive provisions in various instruments and the role of the transformed Tribunal. This scant, fragmented and neglected dispute resolution system may have an impact on the observance of the rule of law and compliance with obligations in the rules-based SADC system. This all, in turn, has an effect on the common agenda for deeper regional integration. This article seeks to expose this scant, fragmented and neglected SADC dispute resolution system and to propose a harmonised system that addresses these challenges. A ‘one stop shop’ system under a strengthened SADC tribunal is proposed as a responsive solution.

Keywords: regional integration, harmonisation, SADC tribunal, dispute resolution

Procedia PDF Downloads 184
12232 Complex Network Analysis of Seismicity and Applications to Short-Term Earthquake Forecasting

Authors: Kahlil Fredrick Cui, Marissa Pastor

Abstract:

Earthquakes are complex phenomena, exhibiting complex correlations in space, time, and magnitude. Recently, the concept of complex networks has been used to shed light on the statistical and dynamical characteristics of regional seismicity. In this work, we study the relationships and interactions of seismic regions in Chile, Japan, and the Philippines through weighted and directed complex network analysis. Geographical areas are digitized into cells of fixed dimensions which in turn become the nodes of the network when an earthquake has occurred therein. Nodes are linked if a correlation exists between them as determined and measured by a correlation metric. The networks are found to be scale-free, exhibiting power-law behavior in the distributions of their different centrality measures: the in- and out-degree and the in- and out-strength. The evidence is also found of preferential interaction between seismically active regions through their degree-degree correlations suggesting that seismicity is dictated by the activity of a few active regions. The importance of a seismic region to the overall seismicity is measured using a generalized centrality metric taken to be an indicator of its activity or passivity. The spatial distribution of earthquake activity indicates the areas where strong earthquakes have occurred in the past while the passivity distribution points toward the likely locations an earthquake would occur whenever another one happens elsewhere. Finally, we propose a method that would project the location of the next possible earthquake using the generalized centralities coupled with correlations calculated between the latest earthquakes and a geographical point in the future.

Keywords: complex networks, correlations, earthquake, hazard assessment

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12231 Emerging Dimensions of Intrinsic Motivation for Effective Performance

Authors: Prachi Bhatt

Abstract:

Motivated workforce is an important asset of an organisation. Intrinsic motivation is one of the key aspects of people operations and performance. Researches have emphasized the significance of internal factors in individuals’ motivation. In the changing business scenario, it is a challenge for the organizations’ leaders to inspire and motivate their workforce. The present study deals with the intrinsic motivation potential of an individual which govern the innate capability of an individual driving him or her to behave or perform in the changing work environment, tasks, teams. Differences at individual level significantly influence differences in levels of motivation. In the above context, the present research attempts to explore behavioral trait dimensions which influence motivational potential of an individual. The present research emphasizes the significance of intrinsic motivational potential and the significance of exploring the differences in the intrinsic motivational potential levels of individuals at work places. Thus, this paper empirically tests the framework of behavioral traits which affects motivational potential of an individual. With the help of two studies i.e., Study 1 and Study 2, exploratory factor analysis and confirmatory factor analysis, respectively, indicated a reliable measure assessing intrinsic motivational potential of an individual. Given the variety of challenges of motivating contemporary workforce, and with increasing importance of intrinsic motivation, the paper discusses the relevance of the findings and of the measure assessing intrinsic motivational potential. Assessment of such behavioral traits would assist in the effective realization of intrinsic motivational potential of individuals. Additionally, the paper discusses the practical implications and furnishes scope for future research.

Keywords: behavioral traits, individual differences, intrinsic motivational potential, intrinsic motivation, motivation, workplace motivation

Procedia PDF Downloads 194
12230 Building an Opinion Dynamics Model from Experimental Data

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

Abstract:

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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12229 Simulation, Optimization, and Analysis Approach of Microgrid Systems

Authors: Saqib Ali

Abstract:

Sources are classified into two depending upon the factor of reviving. These sources, which cannot be revived into their original shape once they are consumed, are considered as nonrenewable energy resources, i.e., (coal, fuel) Moreover, those energy resources which are revivable to the original condition even after being consumed are known as renewable energy resources, i.e., (wind, solar, hydel) Renewable energy is a cost-effective way to generate clean and green electrical energy Now a day’s majority of the countries are paying heed to energy generation from RES Pakistan is mostly relying on conventional energy resources which are mostly nonrenewable in nature coal, fuel is one of the major resources, and with the advent of time their prices are increasing on the other hand RES have great potential in the country with the deployment of RES greater reliability and an effective power system can be obtained In this thesis, a similar concept is being used and a hybrid power system is proposed which is composed of intermixing of renewable and nonrenewable sources The Source side is composed of solar, wind, fuel cells which will be used in an optimal manner to serve load The goal is to provide an economical, reliable, uninterruptable power supply. This is achieved by optimal controller (PI, PD, PID, FOPID) Optimization techniques are applied to the controllers to achieve the desired results. Advanced algorithms (Particle swarm optimization, Flower Pollination Algorithm) will be used to extract the desired output from the controller Detailed comparison in the form of tables and results will be provided, which will highlight the efficiency of the proposed system.

Keywords: distributed generation, demand-side management, hybrid power system, micro grid, renewable energy resources, supply-side management

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12228 Integrations of the Instructional System Design for Students Learning Achievement Motives and Science Attitudes with Stem Educational Model on Stoichiometry Issue in Chemistry Classes with Different Genders

Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

Abstract:

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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12227 Evaluation of the Ability of COVID-19 Infected Sera to Induce Netosis Using an Ex-Vivo NETosis Monitoring Tool

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

Abstract:

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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12226 Soil Arching Effect in Columnar Embankments: A Numerical Study

Authors: Riya Roy, Anjana Bhasi

Abstract:

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

Procedia PDF Downloads 375
12225 The Impact of Diesel Exhaust Particles on Tight Junction Proteins on Nose and Lung in a Mouse Model

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

Abstract:

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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12224 Using Machine Learning to Predict Answers to Big-Five Personality Questions

Authors: Aadityaa Singla

Abstract:

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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12223 A Mixed Approach to Assess Information System Risk, Operational Risk, and Congolese Microfinance Institutions Performance

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

Abstract:

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

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12222 Estimation and Utilization of Landfill Gas from Egyptian Municipal Waste: A Case Study

Authors: Ali A. Hashim Habib, Ahmed A. Abdel-Rehim

Abstract:

Assuredly, massive amounts of wastes that are not utilized and dumped in uncontrolled dumpsites will be one of the major sources of diseases, fires, and emissions. With easy steps and minimum effort, energy can be produced from these gases. The present work introduces an experimental and theoretical analysis to estimate the amount of landfill gas and the corresponding energy which can be produced based on actual Egyptian municipal wastes composition. Two models were utilized and compared, EPA (Environmental Protection Agency) model and CDM (Clean Development Mechanisms) model to estimate methane generation rates and total CH4 emissions based on a particular landfill. The results showed that for every ton of municipal waste, 140 m3 of landfill gas can be produced. About 800 kW of electricity for a minimum of 24 years can be generated form one million ton of municipal waste. A total amount of 549,025 ton of carbon emission can be avoided during these 24 years.

Keywords: energy from landfill gases, landfill biogas, methane emission, municipal solid waste, renewable energy sources

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12221 Ranking of Provinces in Iran for Capital Formation in Spatial Planning with Numerical Taxonomy Technique (An Improvement) Case Study: Agriculture Sector

Authors: Farhad Nouparast

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For more production we need more capital formation. Capital formation in each country should be based on comparative advantages in different economic sectors due to the different production possibility curves. In regional planning, recognizing the relative advantages and consequently investing in more production requires identifying areas with the necessary capabilities and location of each region compared to other regions. In this article, ranking of Iran's provinces is done according to the specific and given variables as the best investment position in agricultural activity. So we can provide the necessary background for investment analysis in different regions of the country to formulate national and regional planning and execute investment projects. It is used factor analysis technique and numerical taxonomy analysis to do this in thisarticle. At first, the provinces are homogenized and graded according to the variables using cross-sectional data obtained from the agricultural census and population and housing census of Iran as data matrix. The results show that which provinces have the most potential for capital formation in agronomy sub-sector. Taxonomy classifies organisms based on similar genetic traits in biology and botany. Numerical taxonomy using quantitative methods controls large amounts of information and get the number of samples and categories and take them based on inherent characteristics and differences indirectly accommodates. Numerical taxonomy is related to multivariate statistics.

Keywords: Capital Formation, Factor Analysis, Multivariate statistics, Numerical Taxonomy Analysis, Production, Ranking, Spatial Planning

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12220 The Geographic Distribution of Complementary, Alternative, and Traditional Medicine in the United States in 2018

Authors: Janis E. Campbell

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Most of what is known about complementary, alternative or traditional medicine (CATM) in the United States today is known from either the National Health Interview Survey a cross-sectional survey with a few questions or from small cross-sectional or cohort studies with specific populations. The broad geographical distribution in CATM use or providers is not known. For this project, we used geospatial cluster analysis to determine if there were clusters of CATM provider by county in the US. In this analysis, we used the National Provider Index to determine the geographic distribution of providers in the US. Of the 215,769 CAMT providers 211,603 resided in the contiguous US: Acupuncturist (26,563); Art, Poetry, Music and Dance Therapist (2,752); Chiropractor (89,514); Doula/Midwife (3,535); Exercise (507); Homeopath (380); Massage Therapist (36,540); Mechanotherapist (1,888); Naprapath (146); Naturopath (4,782); Nutrition (42,036); Reflexologist (522); Religious (2,438). ESRI® spatial autocorrelation was used to determine if the geographic location of CATM providers were random or clustered. For global analysis, we used Getis-Ord General G and for Local Indicators of Spatial Associations with an Optimized Hot Spot Analysis using an alpha of 0.05. Overall, CATM providers were clustered with both low and high. With Chiropractors, focusing in the Midwest, religious providers having very small clusters in the central US, and other types of CAMT focused in the northwest and west coast, Colorado and New Mexico, the great lakes areas and Florida. We will discuss some of the implications of this study, including associations with health, economic, social, and political systems.

Keywords: complementary medicine, alternative medicine, geospatial, United States

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12219 Characterization of Some Bread Wheat Genotypes for Drought Tolerance Using Molecular Markers

Authors: Begüm Terzi, Özlem Ateş Sönmezoğlu, Ahmet Yildirim

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Drought is the most important factor that limiting the production and productivity of wheat in the world. The yield of wheat, which is one of the most important crop in the world, reduced depend on drought. Researches to minimize effects of drought are one of the most important about breeding of drought resistant varieties. In recent years, benefiting from the drought resistance wild species and rapid advances in molecular biology studies, researches about drought have been accelerated and number of studies were made on molecular plant breeding which included the molecular mechanisms related to drought resistance. The aim of the present study was characterization of some bread wheat lines for drought tolerance which commonly cultivated in different location of Turkey. In this study, registered 9 bread wheat varieties which on the physiological tests about drought tolerance and 10 bread wheat line has been developed by Transitional Zone Agricultural Research Institute were used. SSR, STS, RAPD and SNP markers that associated with drought tolerance were used. The polymorphisms of the markers were determined by screening of two control varieties. For these purpose 40 molecular markers were used and 12 markers of them were polymorphic among the drought tolerance and the drought sensitive varieties. Control varieties were screened using polymorphic markers. All the DNAs on the genotypes will be searched for the presence of QTLs mapped to different chromosomes. Result of the research, the studied genotypes will be grouped according to drought tolerance and will be detected drought tolerance varieties by molecular markers. In addition, the results will be compared also with physiological tests. The drought tolerant wheat genotypes may be used in breeding studies related to drought stress.

Keywords: bread wheat, drought, molecular marker, Triticum aestivum

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12218 Determination of Water Pollution and Water Quality with Decision Trees

Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

Procedia PDF Downloads 77
12217 Utility Assessment Model for Wireless Technology in Construction

Authors: Yassir AbdelRazig, Amine Ghanem

Abstract:

Construction projects are information intensive in nature and involve many activities that are related to each other. Wireless technologies can be used to improve the accuracy and timeliness of data collected from construction sites and shares it with appropriate parties. Nonetheless, the construction industry tends to be conservative and shows hesitation to adopt new technologies. A main concern for owners, contractors or any person in charge on a job site is the cost of the technology in question. Wireless technologies are not cheap. There are a lot of expenses to be taken into consideration, and a study should be completed to make sure that the importance and savings resulting from the usage of this technology is worth the expenses. This research attempts to assess the effectiveness of using the appropriate wireless technologies based on criteria such as performance, reliability, and risk. The assessment is based on a utility function model that breaks down the selection issue into alternatives attribute. Then the attributes are assigned weights and single attributes are measured. Finally, single attribute are combined to develop one single aggregate utility index for each alternative.

Keywords: analytic hierarchy process, decision theory, utility function, wireless technologies

Procedia PDF Downloads 336
12216 Investigation of Self-Assembling of Maghemite Nanoparticles into Chain–Like Structures Using Birefringence Measurements

Authors: C. R. Stein; K. Skeff Neto, K. L. C. Miranda, P. P. C. Sartoratto, M. E. Xavier, Z. G. M. Lacava, S. M. De Freita, P. C. Morais

Abstract:

In this study, static magnetic birefringence (SMB) and transmission electron microscopy (TEM) were used to investigate the self-assembling of maghemite nanoparticles suspended as biocompatible magnetic fluid (BMF) while incubated or not with the Black Eyed–Pea Trypsin Chymotripsin Inhibitor–BTCI protein. The stock samples herein studied are dextran coated maghemite nanoparticles (average core diameter of 7.1 nm, diameter dispersion of 0.26, and containing 4.6×1016 particle/mL) and the dextran coated maghemite nanoparticles associated with the BTCI protein. Several samples were prepared by diluting the stock samples with deionized water while following their colloidal stability. The diluted samples were investigated using SMB measurements to assess the average sizes of the self-assembled and suspended mesoscopic structures whereas the TEM micrographs provide the morphology of the as-suspended units. The SMB data were analyzed using a model that includes the particle-particle interaction within the mean field model picture.

Keywords: biocompatible magnetic fluid, maghemite nanoparticles, self-assembling

Procedia PDF Downloads 477
12215 Integrated Business Model Innovation in Nigerian Higher Education: Challenges and Prospects

Authors: Nonso Ochinanwata, Patrick Oseloka Ezepue

Abstract:

This paper explores challenges and prospects in Nigerian higher education. The paper develops an integrated business model that aimed to innovate Nigeria higher education system. A survey and semi-structured interview among Nigerian higher education academics, students and graduates are used to explore the challenges and prospects. The study provides a comparison between lecturers, students and graduates opinions to evaluate challenges and prospects in Nigerian higher institutions. The study found to achieve efficient and effectiveness innovation in Nigerian higher education, there is a need for higher institutions to collaborate with industry professionals and other stakeholders such as company management, and government policy makers in designing higher education institutions curricula. The study found that the curriculum design and delivery need to blend theoretical understanding and real-life experience from industry, and with social cultural influences related to Nigerian environment. This will enable lecturers to organise their teaching and assessments such that students can learn around theoretical and practical study themes. The curriculum design and delivery need to link the core ideas to challenging problems in society, nationally and globally. Hence, this approach will support business start-ups and social entrepreneurship which resolve key societal problems. The study suggests that higher education executives, directors, deans, head of departments, and even individual academics need to emulate innovative business managers to create value-adding products and services from innovative research and academic work.

Keywords: higher education, curriculum innovation, business model innovation, teaching and research excellence, economic development

Procedia PDF Downloads 266
12214 Pakistan’s Counterinsurgency Operations: A Case Study of Swat

Authors: Arshad Ali

Abstract:

The Taliban insurgency in Swat which started apparently as a social movement in 2004 transformed into an anti-Pakistan Islamist insurgency by joining hands with the Tehrik-e-Taliban Pakistan (TTP) upon its formation in 2007. It quickly spread beyond Swat by 2009 making Swat the second stronghold of TTP after FATA. It prompted the Pakistan military to launch a full-scale counterinsurgency military operation code named Rah-i-Rast to regain the control of Swat. Operation Rah-i-Rast was successful not only in restoring the writ of the State but more importantly in creating a consensus against the spread of Taliban insurgency in Pakistan at political, social and military levels. This operation became a test case for civilian government and military to seek for a sustainable solution combating the TTP insurgency in the north-west of Pakistan. This study analyzes why the counterinsurgency operation Rah-i-Rast was successful and why the previous ones came into failure. The study also explores factors which created consensus against the Taliban insurgency at political and social level as well as reasons which hindered such a consensual approach in the past. The study argues that the previous initiatives failed due to various factors including Pakistan army’s lack of comprehensive counterinsurgency model, weak political will and public support, and states negligence. Also, the initial counterinsurgency policies were ad-hoc in nature fluctuating between military operations and peace deals. After continuous failure, the military revisited its approach to counterinsurgency in the operation Rah-i-Rast. The security forces learnt from their past experiences and developed a pragmatic counterinsurgency model: ‘clear, hold, build, and transfer.’ The military also adopted the population-centric approach to provide security to the local people. This case Study of Swat evaluates the strengths and weaknesses of the Pakistan's counterinsurgency operations as well as peace agreements. It will analyze operation Rah-i-Rast in the light of David Galula’s model of counterinsurgency. Unlike existing literature, the study underscores the bottom up approach adopted by the Pakistan’s military and government by engaging the local population to sustain the post-operation stability in Swat. More specifically, the study emphasizes on the hybrid counterinsurgency model “clear, hold, and build and Transfer” in Swat.

Keywords: Insurgency, Counterinsurgency, clear, hold, build, transfer

Procedia PDF Downloads 353
12213 Method Validation for Heavy Metal Determination in Spring Water and Sediments

Authors: Habtamu Abdisa

Abstract:

Spring water is particularly valuable due to its high mineral content, which is beneficial for human health. However, anthropogenic activities usually imbalance the natural levels of its composition, which can cause adverse health effects. Regular monitoring of a naturally given environmental resource is of great concern in the world today. The spectrophotometric application is one of the best methods for qualifying and quantifying the mineral contents of environmental water samples. This research was conducted to evaluate the quality of spring water concerning its heavy metal composition. A grab sampling technique was employed to collect representative samples, including duplicates. The samples were then treated with concentrated HNO3 to a pH level below 2 and stored at 4oC. The samples were digested and analyzed for cadmium (Cd), chromium (Cr), manganese (Mn), copper (Cu), iron (Fe), and zinc (Zn) following method validation. Atomic Absorption Spectrometry (AAS) was utilized for the sample analysis. Quality control measures, including blanks, duplicates, and certified reference materials (CRMs), were implemented to ensure the accuracy and precision of the analytical results. Of the metals analyzed in the water samples, Cd and Cr were found to be below the detection limit. However, the concentrations of Mn, Cu, Fe, and Zn ranged from mean values of 0.119-0.227 mg/L, 0.142-0.166 mg/L, 0.183-0.267 mg/L, and 0.074-0.181 mg/L, respectively. Sediment analysis revealed mean concentration ranges of 348.31-429.21 mg/kg, 0.23-0.28 mg/kg, 18.73-22.84 mg/kg, 2.76-3.15 mg/kg, 941.84-1128.56 mg/kg, and 42.39-66.53 mg/kg for Mn, Cd, Cu, Cr, Fe, and Zn, respectively. The study results established that the evaluated spring water and its associated sediment met the regulatory standards and guidelines for heavy metal concentrations. Furthermore, this research can enhance the quality assurance and control processes for environmental sample analysis, ensuring the generation of reliable data.

Keywords: method validation, heavy metal, spring water, sediment, method detection limit

Procedia PDF Downloads 65
12212 Solid-State Synthesis Approach and Optical study of Red Emitting Phosphors Li₃BaSrxCa₁₋ₓEu₂.₇Gd₀.₃(MoO₄)₈ for White LEDs

Authors: Priyansha Sharma, Sibani Mund, Sivakumar Vaidyanathan

Abstract:

Solid-state synthesis methods were used for the synthesis of pure red emissive Li¬3BaSrxCa(1-x)Eu2.7Gd0.3(MoO4)8 (x = 0.0 to 1.0) phosphors, XRD, SEM, and FTIR spectra were used to characterize the materials, and their optical properties were thoroughly investigated. PL studies were examined at different excitations 230 nm, 275nm, 465nm, and 395 nm. All the spectra show similar emissions with the highest transition at 616 nm due to ED transition. The given phosphor Li¬3BaSr0.25Ca0.75Eu2.7Gd0.3(MoO4)8 shows the highest intensity and is thus chosen for the temperature-dependent and Quantum yield study. According to the PL investigation, the phosphor-containing Eu3+ emits red light due to the (5D0 7F2) transition. The excitation analysis shows that all of the Eu3+ activated phosphors exhibited broad absorption due to the charge transfer band, O2-Mo6+, O2-Eu3+ transition, as well as narrow absorption bands related to the Eu3+ ion's 4f-4f electronic transition. Excitation spectra show Charge transfer band at 275 nm shows the highest intensity. The primary band in the spectra refers to Eu3+ ions occupying the lattice's non-centrosymmetric location. All of the compositions are monoclinic crystal structures with space group C2/c and match with reference powder patterns. The thermal stability of the 3BaSr0.25Ca0.75Eu2.7Gd0.3(MoO4)8 phosphor was investigated at (300 k- 500 K) as well as at low temperature from (20 K to 275 K) to be utilized for red and white LED fabrication. The Decay Lifetime of all the phosphor was measured. The best phosphor was used for White and Red LED fabrication.

Keywords: PL, phosphor, quantum yield, white LED

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12211 CO2 Adsorption on the Activated Klaten-Indonesian Natural Zeolite in a Packed Bed Adsorber

Authors: Sang Kompiang Wirawan, Chandra Purnomo

Abstract:

Carbon dioxide (CO2) adsorption on the activated Klaten-Indonesian natural zeolite (AKINZ) in a packed bed adsorber has been studied. Experiment works consisted of acid activation and adsorption experiments. The natural zeolite sample was activated using 0.3 M HCl at the temperature of 353 K. In the adsorption experiments the feed gas concentrations were 40 and 80 % CO2 in helium within various temperatures of 303; 323 and 373 K. The experiments were conducted by using transient step change adsorption and 20 % Ar/He tracer experiment was conducted to measure dispersion and time lag effect of the packed bed system. A mathematical model of CO2 adsorption had been set up by assuming plug flow;isothermal;isobaric and no gas film mass transport resistance. Single site Langmuir physisorption and Maxwell Stefan mass transport in micropore were applied. All the data were then optimized to get the best value of modified fitted parameter. The model was in a good agreement with the experiment data. Diffusivity tended to increase by increasing temperatures.

Keywords: adsorption, Langmuir, Maxwell-Stefan, natural zeolite, surface diffusion

Procedia PDF Downloads 350
12210 An Industrial Scada System Remote Control Using Mobile Phones

Authors: Ahmidah Elgali

Abstract:

SCADA is the abbreviation for "Administrative Control And Data Acquisition." SCADA frameworks are generally utilized in industry for administrative control and information securing of modern cycles. Regular SCADA frameworks use PC, journal, slim client, and PDA as a client. In this paper, a Java-empowered cell phone has been utilized as a client in an example SCADA application to show and regulate the place of an example model crane. The paper presents a genuine execution of the online controlling of the model crane through a cell phone. The remote correspondence between the cell phone and the SCADA server is performed through a base station by means of general parcel radio assistance GPRS and remote application convention WAP. This application can be used in industrial sites in areas that are likely to be exposed to a security emergency (like terrorist attacks) which causes the sudden exit of the operators; however, no time to perform the shutdown procedures for the plant. Hence this application allows shutting down units and equipment remotely by mobile and so avoids damage and losses.

Keywords: control, industrial, mobile, network, remote, SCADA

Procedia PDF Downloads 72
12209 Performance Comparison of Deep Convolutional Neural Networks for Binary Classification of Fine-Grained Leaf Images

Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

Abstract:

Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

Procedia PDF Downloads 183