Search results for: predictive mining
Commenced in January 2007
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Edition: International
Paper Count: 2060

Search results for: predictive mining

230 Learning Instructional Managements between the Problem-Based Learning and Stem Education Methods for Enhancing Students Learning Achievements and their Science Attitudes toward Physics the 12th Grade Level

Authors: Achirawatt Tungsombatsanti, Toansakul Santiboon, Kamon Ponkham

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Strategies of the STEM education was aimed to prepare of an interdisciplinary and applied approach for the instructional of science, technology, engineering, and mathematics in an integrated students for enhancing engagement of their science skills to the Problem-Based Learning (PBL) method in Borabu School with a sample consists of 80 students in 2 classes at the 12th grade level of their learning achievements on electromagnetic issue. Research administrations were to separate on two different instructional model groups, the 40-experimental group was designed with the STEM instructional experimenting preparation and induction in a 40-student class and the controlling group using the PBL was designed to students identify what they already know, what they need to know, and how and where to access new information that may lead to the resolution of the problem in other class. The learning environment perceptions were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI). Students’ creating attitude skills’ sustainable development toward physics were assessed with the Test Of Physics-Related Attitude (TOPRA) The term scaling was applied to the attempts to measure the attitude objectively with the TOPRA was used to assess students’ perceptions of their science attitude toward physics. Comparisons between pretest and posttest techniques were assessed students’ learning achievements on each their outcomes from each instructional model, differently. The results of these findings revealed that the efficiency of the PLB and the STEM based on criteria indicate that are higher than the standard level of the 80/80. Statistically, significant of students’ learning achievements to their later outcomes on the controlling and experimental physics class groups with the PLB and the STEM instructional designs were differentiated between groups at the .05 level, evidently. Comparisons between the averages mean scores of students’ responses to their instructional activities in the STEM education method are higher than the average mean scores of the PLB model. Associations between students’ perceptions of their physics classes to their attitudes toward physics, the predictive efficiency R2 values indicate that 77%, and 83% of the variances in students’ attitudes for the PLEI and the TOPRA in physics environment classes were attributable to their perceptions of their physics PLB and the STEM instructional design classes, consequently. An important of these findings was contributed to student understanding of scientific concepts, attitudes, and skills as evidence with STEM instructional ought to higher responding than PBL educational teaching. Statistically significant between students’ learning achievements were differentiated of pre and post assessments which overall on two instructional models.

Keywords: learning instructional managements, problem-based learning, STEM education, method, enhancement, students learning achievements, science attitude, physics classes

Procedia PDF Downloads 233
229 GenAI Agents in Product Management: A Case Study from the Manufacturing Sector

Authors: Aron Witkowski, Andrzej Wodecki

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Purpose: This study aims to explore the feasibility and effectiveness of utilizing Generative Artificial Intelligence (GenAI) agents as product managers within the manufacturing sector. It seeks to evaluate whether current GenAI capabilities can fulfill the complex requirements of product management and deliver comparable outcomes to human counterparts. Study Design/Methodology/Approach: This research involved the creation of a support application for product managers, utilizing high-quality sources on product management and generative AI technologies. The application was designed to assist in various aspects of product management tasks. To evaluate its effectiveness, a study was conducted involving 10 experienced product managers from the manufacturing sector. These professionals were tasked with using the application and providing feedback on the tool's responses to common questions and challenges they encounter in their daily work. The study employed a mixed-methods approach, combining quantitative assessments of the tool's performance with qualitative interviews to gather detailed insights into the user experience and perceived value of the application. Findings: The findings reveal that GenAI-based product management agents exhibit significant potential in handling routine tasks, data analysis, and predictive modeling. However, there are notable limitations in areas requiring nuanced decision-making, creativity, and complex stakeholder interactions. The case study demonstrates that while GenAI can augment human capabilities, it is not yet fully equipped to independently manage the holistic responsibilities of a product manager in the manufacturing sector. Originality/Value: This research provides an analysis of GenAI's role in product management within the manufacturing industry, contributing to the limited body of literature on the application of GenAI agents in this domain. It offers practical insights into the current capabilities and limitations of GenAI, helping organizations make informed decisions about integrating AI into their product management strategies. Implications for Academic and Practical Fields: For academia, the study suggests new avenues for research in AI-human collaboration and the development of advanced AI systems capable of higher-level managerial functions. Practically, it provides industry professionals with a nuanced understanding of how GenAI can be leveraged to enhance product management, guiding investments in AI technologies and training programs to bridge identified gaps.

Keywords: generative artificial intelligence, GenAI, NPD, new product development, product management, manufacturing

Procedia PDF Downloads 54
228 Epigenetic and Archeology: A Quest to Re-Read Humanity

Authors: Salma A. Mahmoud

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Epigenetic, or alteration in gene expression influenced by extragenetic factors, has emerged as one of the most promising areas that will address some of the gaps in our current knowledge in understanding patterns of human variation. In the last decade, the research investigating epigenetic mechanisms in many fields has flourished and witnessed significant progress. It paved the way for a new era of integrated research especially between anthropology/archeology and life sciences. Skeletal remains are considered the most significant source of information for studying human variations across history, and by utilizing these valuable remains, we can interpret the past events, cultures and populations. In addition to archeological, historical and anthropological importance, studying bones has great implications in other fields such as medicine and science. Bones also can hold within them the secrets of the future as they can act as predictive tools for health, society characteristics and dietary requirements. Bones in their basic forms are composed of cells (osteocytes) that are affected by both genetic and environmental factors, which can only explain a small part of their variability. The primary objective of this project is to examine the epigenetic landscape/signature within bones of archeological remains as a novel marker that could reveal new ways to conceptualize chronological events, gender differences, social status and ecological variations. We attempted here to address discrepancies in common variants such as methylome as well as novel epigenetic regulators such as chromatin remodelers, which to our best knowledge have not yet been investigated by anthropologists/ paleoepigenetists using plethora of techniques (biological, computational, and statistical). Moreover, extracting epigenetic information from bones will highlight the importance of osseous material as a vector to study human beings in several contexts (social, cultural and environmental), and strengthen their essential role as model systems that can be used to investigate and construct various cultural, political and economic events. We also address all steps required to plan and conduct an epigenetic analysis from bone materials (modern and ancient) as well as discussing the key challenges facing researchers aiming to investigate this field. In conclusion, this project will serve as a primer for bioarcheologists/anthropologists and human biologists interested in incorporating epigenetic data into their research programs. Understanding the roles of epigenetic mechanisms in bone structure and function will be very helpful for a better comprehension of their biology and highlighting their essentiality as interdisciplinary vectors and a key material in archeological research.

Keywords: epigenetics, archeology, bones, chromatin, methylome

Procedia PDF Downloads 111
227 Arabic Lexicon Learning to Analyze Sentiment in Microblogs

Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

Procedia PDF Downloads 191
226 Cleaning of Scientific References in Large Patent Databases Using Rule-Based Scoring and Clustering

Authors: Emiel Caron

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Patent databases contain patent related data, organized in a relational data model, and are used to produce various patent statistics. These databases store raw data about scientific references cited by patents. For example, Patstat holds references to tens of millions of scientific journal publications and conference proceedings. These references might be used to connect patent databases with bibliographic databases, e.g. to study to the relation between science, technology, and innovation in various domains. Problematic in such studies is the low data quality of the references, i.e. they are often ambiguous, unstructured, and incomplete. Moreover, a complete bibliographic reference is stored in only one attribute. Therefore, a computerized cleaning and disambiguation method for large patent databases is developed in this work. The method uses rule-based scoring and clustering. The rules are based on bibliographic metadata, retrieved from the raw data by regular expressions, and are transparent and adaptable. The rules in combination with string similarity measures are used to detect pairs of records that are potential duplicates. Due to the scoring, different rules can be combined, to join scientific references, i.e. the rules reinforce each other. The scores are based on expert knowledge and initial method evaluation. After the scoring, pairs of scientific references that are above a certain threshold, are clustered by means of single-linkage clustering algorithm to form connected components. The method is designed to disambiguate all the scientific references in the Patstat database. The performance evaluation of the clustering method, on a large golden set with highly cited papers, shows on average a 99% precision and a 95% recall. The method is therefore accurate but careful, i.e. it weighs precision over recall. Consequently, separate clusters of high precision are sometimes formed, when there is not enough evidence for connecting scientific references, e.g. in the case of missing year and journal information for a reference. The clusters produced by the method can be used to directly link the Patstat database with bibliographic databases as the Web of Science or Scopus.

Keywords: clustering, data cleaning, data disambiguation, data mining, patent analysis, scientometrics

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225 Physical Properties of Rice Field Receiving Irrigation Polluted by Gold Mine Tailing: Case Study in Dharmasraya, West Sumatra, Indonesia

Authors: Yulna Yulnafatmawita, Syafrimen Yasin, Lusi Maira

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Irrigation source is one of the factors affecting physical properties of rice field. This research was aimed to determine the impact of polluted irrigation wáter on soil physical properties of rice field. The study site was located in Koto Nan IV, Dharmasraya Regency, West Sumatra, Indonesia. The rice field was irrigated with wáter from Momongan river in which people do gold mining. The soil was sampled vertically from the top to 100 cm depth with 20 cm increment of soil profile from 2 year-fallowed rice field, as well as from the top 20 cm of cultivated rice field from the terrace-1 (the highest terrace) to terrace-5 (the lowest terrace) position. Soil samples were analysed in laboratory. For comparison, rice field receiving irrigation wáter from non-polluted source was also sampled at the top 20 cm and anaysed for the physical properties. The result showed that there was a change in soil physical properties of rice field after 9 years of getting irrigation from the river. Based on laboratory analyses, the total suspended solid (TSS) in the tailing reached 10,736 mg/L. The texture of rice field at polluted rice field (PRF) was dominated (>55%) by sand particles at the top 100 cm soil depth, and it tended to linearly decrease (R2=0.65) from the top 20 cm to 100 cm depth. Likewise, the sand particles also linearly decreased (R2=0.83), but clay particles linearly increased (R2=0.74) horizontally as the distance from the wáter input (terrace-1) was fartherst. Compared to nonpolluted rice field (NPRF), percentage of sand was higher, and clay was lower at PRF. This sandy texture of soil in PRF increased soil hydraulic conductivity (up to 19.1 times), soil bulk density (by 38%), and sharply decreased SOM (by 88.5 %), as well as soil total pore (by 22.1%) compared to the NPRF at the top 20 cm soil. The rice field was suggested to be reclaimed before reusing it. Otherwise the soil characteristics requirement, especially soil wáter retention, for rice field could not be fulfilled.

Keywords: gold mine tailing, polluted irrigation, rice field, soil physical properties

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224 A Location-Based Search Approach According to Users’ Application Scenario

Authors: Shih-Ting Yang, Chih-Yun Lin, Ming-Yu Li, Jhong-Ting Syue, Wei-Ming Huang

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Global positioning system (GPS) has become increasing precise in recent years, and the location-based service (LBS) has developed rapidly. Take the example of finding a parking lot (such as Parking apps). The location-based service can offer immediate information about a nearby parking lot, including the information about remaining parking spaces. However, it cannot provide expected search results according to the requirement situations of users. For that reason, this paper develops a “Location-based Search Approach according to Users’ Application Scenario” according to the location-based search and demand determination to help users obtain the information consistent with their requirements. The “Location-based Search Approach based on Users’ Application Scenario” of this paper consists of one mechanism and three kernel modules. First, in the Information Pre-processing Mechanism (IPM), this paper uses the cosine theorem to categorize the locations of users. Then, in the Information Category Evaluation Module (ICEM), the kNN (k-Nearest Neighbor) is employed to classify the browsing records of users. After that, in the Information Volume Level Determination Module (IVLDM), this paper makes a comparison between the number of users’ clicking the information at different locations and the average number of users’ clicking the information at a specific location, so as to evaluate the urgency of demand; then, the two-dimensional space is used to estimate the application situations of users. For the last step, in the Location-based Search Module (LBSM), this paper compares all search results and the average number of characters of the search results, categorizes the search results with the Manhattan Distance, and selects the results according to the application scenario of users. Additionally, this paper develops a Web-based system according to the methodology to demonstrate practical application of this paper. The application scenario-based estimate and the location-based search are used to evaluate the type and abundance of the information expected by the public at specific location, so that information demanders can obtain the information consistent with their application situations at specific location.

Keywords: data mining, knowledge management, location-based service, user application scenario

Procedia PDF Downloads 129
223 Surface Tension and Bulk Density of Ammonium Nitrate Solutions: A Molecular Dynamics Study

Authors: Sara Mosallanejad, Bogdan Z. Dlugogorski, Jeff Gore, Mohammednoor Altarawneh

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Ammonium nitrate (NH­₄NO₃, AN) is commonly used as the main component of AN emulsion and fuel oil (ANFO) explosives, that use extensively in civilian and mining operations for underground development and tunneling applications. The emulsion formulation and wettability of AN prills, which affect the physical stability and detonation of ANFO, highly depend on the surface tension, density, viscosity of the used liquid. Therefore, for engineering applications of this material, the determination of density and surface tension of concentrated aqueous solutions of AN is essential. The molecular dynamics (MD) simulation method have been used to investigate the density and the surface tension of high concentrated ammonium nitrate solutions; up to its solubility limit in water. Non-polarisable models for water and ions have carried out the simulations, and the electronic continuum correction model (ECC) uses a scaling of the charges of the ions to apply the polarisation implicitly into the non-polarisable model. The results of calculated density and the surface tension of the solutions have been compared to available experimental values. Our MD simulations show that the non-polarisable model with full-charge ions overestimates the experimental results while the reduce-charge model for the ions fits very well with the experimental data. Ions in the solutions show repulsion from the interface using the non-polarisable force fields. However, when charges of the ions in the original model are scaled in line with the scaling factor of the ECC model, the ions create a double ionic layer near the interface by the migration of anions toward the interface while cations stay in the bulk of the solutions. Similar ions orientations near the interface were observed when polarisable models were used in simulations. In conclusion, applying the ECC model to the non-polarisable force field yields the density and surface tension of the AN solutions with high accuracy in comparison to the experimental measurements.

Keywords: ammonium nitrate, electronic continuum correction, non-polarisable force field, surface tension

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222 Towards Accurate Velocity Profile Models in Turbulent Open-Channel Flows: Improved Eddy Viscosity Formulation

Authors: W. Meron Mebrahtu, R. Absi

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Velocity distribution in turbulent open-channel flows is organized in a complex manner. This is due to the large spatial and temporal variability of fluid motion resulting from the free-surface turbulent flow condition. This phenomenon is complicated further due to the complex geometry of channels and the presence of solids transported. Thus, several efforts were made to understand the phenomenon and obtain accurate mathematical models that are suitable for engineering applications. However, predictions are inaccurate because oversimplified assumptions are involved in modeling this complex phenomenon. Therefore, the aim of this work is to study velocity distribution profiles and obtain simple, more accurate, and predictive mathematical models. Particular focus will be made on the acceptable simplification of the general transport equations and an accurate representation of eddy viscosity. Wide rectangular open-channel seems suitable to begin the study; other assumptions are smooth-wall, and sediment-free flow under steady and uniform flow conditions. These assumptions will allow examining the effect of the bottom wall and the free surface only, which is a necessary step before dealing with more complex flow scenarios. For this flow condition, two ordinary differential equations are obtained for velocity profiles; from the Reynolds-averaged Navier-Stokes (RANS) equation and equilibrium consideration between turbulent kinetic energy (TKE) production and dissipation. Then different analytic models for eddy viscosity, TKE, and mixing length were assessed. Computation results for velocity profiles were compared to experimental data for different flow conditions and the well-known linear, log, and log-wake laws. Results show that the model based on the RANS equation provides more accurate velocity profiles. In the viscous sublayer and buffer layer, the method based on Prandtl’s eddy viscosity model and Van Driest mixing length give a more precise result. For the log layer and outer region, a mixing length equation derived from Von Karman’s similarity hypothesis provides the best agreement with measured data except near the free surface where an additional correction based on a damping function for eddy viscosity is used. This method allows more accurate velocity profiles with the same value of the damping coefficient that is valid under different flow conditions. This work continues with investigating narrow channels, complex geometries, and the effect of solids transported in sewers.

Keywords: accuracy, eddy viscosity, sewers, velocity profile

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221 Hydrological Analysis for Urban Water Management

Authors: Ranjit Kumar Sahu, Ramakar Jha

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Urban Water Management is the practice of managing freshwater, waste water, and storm water as components of a basin-wide management plan. It builds on existing water supply and sanitation considerations within an urban settlement by incorporating urban water management within the scope of the entire river basin. The pervasive problems generated by urban development have prompted, in the present work, to study the spatial extent of urbanization in Golden Triangle of Odisha connecting the cities Bhubaneswar (20.2700° N, 85.8400° E), Puri (19.8106° N, 85.8314° E) and Konark (19.9000° N, 86.1200° E)., and patterns of periodic changes in urban development (systematic/random) in order to develop future plans for (i) urbanization promotion areas, and (ii) urbanization control areas. Remote Sensing, using USGS (U.S. Geological Survey) Landsat8 maps, supervised classification of the Urban Sprawl has been done for during 1980 - 2014, specifically after 2000. This Work presents the following: (i) Time series analysis of Hydrological data (ground water and rainfall), (ii) Application of SWMM (Storm Water Management Model) and other soft computing techniques for Urban Water Management, and (iii) Uncertainty analysis of model parameters (Urban Sprawl and correlation analysis). The outcome of the study shows drastic growth results in urbanization and depletion of ground water levels in the area that has been discussed briefly. Other relative outcomes like declining trend of rainfall and rise of sand mining in local vicinity has been also discussed. Research on this kind of work will (i) improve water supply and consumption efficiency (ii) Upgrade drinking water quality and waste water treatment (iii) Increase economic efficiency of services to sustain operations and investments for water, waste water, and storm water management, and (iv) engage communities to reflect their needs and knowledge for water management.

Keywords: Storm Water Management Model (SWMM), uncertainty analysis, urban sprawl, land use change

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220 Exploring Faculty Attitudes about Grades and Alternative Approaches to Grading: Pilot Study

Authors: Scott Snyder

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Grading approaches in higher education have not changed meaningfully in over 100 years. While there is variation in the types of grades assigned across countries, most use approaches based on simple ordinal scales (e.g, letter grades). While grades are generally viewed as an indication of a student's performance, challenges arise regarding the clarity, validity, and reliability of letter grades. Research about grading in higher education has primarily focused on grade inflation, student attitudes toward grading, impacts of grades, and benefits of plus-minus letter grade systems. Little research is available about alternative approaches to grading, varying approaches used by faculty within and across colleges, and faculty attitudes toward grades and alternative approaches to grading. To begin to address these gaps, a survey was conducted of faculty in a sample of departments at three diverse colleges in a southeastern state in the US. The survey focused on faculty experiences with and attitudes toward grading, the degree to which faculty innovate in teaching and grading practices, and faculty interest in alternatives to the point system approach to grading. Responses were received from 104 instructors (21% response rate). The majority reported that teaching accounted for 50% or more of their academic duties. Almost all (92%) of respondents reported using point and percentage systems for their grading. While all respondents agreed that grades should reflect the degree to which objectives were mastered, half indicated that grades should also reflect effort or improvement. Over 60% felt that grades should be predictive of success in subsequent courses or real life applications. Most respondents disagreed that grades should compare students to other students. About 42% worried about their own grade inflation and grade inflation in their college. Only 17% disagreed that grades mean different things based on the instructor while 75% thought it would be good if there was agreement. Less than 50% of respondents felt that grades were directly useful for identifying students who should/should not continue, identify strengths/weaknesses, predict which students will be most successful, or contribute to program monitoring of student progress. Instructors were less willing to modify assessment than they were to modify instruction and curriculum. Most respondents (76%) were interested in learning about alternative approaches to grading (e.g., specifications grading). The factors that were most associated with willingness to adopt a new grading approach were clarity to students and simplicity of adoption of the approach. Follow-up studies are underway to investigate implementations of alternative grading approaches, expand the study to universities and departments not involved in the initial study, examine student attitudes about alternative approaches, and refine the measure of attitude toward adoption of alternative grading practices within the survey. Workshops about challenges of using percentage and point systems for determining grades and workshops regarding alternative approaches to grading are being offered.

Keywords: alternative approaches to grading, grades, higher education, letter grades

Procedia PDF Downloads 98
219 Screening Ecological Risk Assessment at an Old Abandoned Mine in Northern Taiwan

Authors: Hui-Chen Tsai, Chien-Jen Ho, Bo-Wei Power Liang, Ying Shen, Yi-Hsin Lai

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Former Taiwan Metal Mining Corporation and its associated 3 wasted flue gas tunnels, hereinafter referred to as 'TMMC', was contaminated with heavy metals, Polychlorinated biphenyls (PCBs) and Total Petroleum Hydrocarbons (TPHs) in soil. Since the contamination had been exposed and unmanaged in the environment for more than 40 years, the extent of the contamination area is estimated to be more than 25 acres. Additionally, TMMC is located in a remote, mountainous area where almost no residents are residing in the 1-km radius area. Thus, it was deemed necessary to conduct an ecological risk assessment in order to evaluate the details of future contaminated site management plan. According to the winter and summer, ecological investigation results, one type of endangered, multiple vulnerable and near threaten plant was discovered, as well as numerous other protected species, such as Crested Serpent Eagle, Crested Goshawk, Black Kite, Brown Shrike, Taiwan Blue Magpie were observed. Ecological soil screening level (Eco-SSLs) developed by USEPA was adopted as a reference to conduct screening assessment. Since all the protected species observed surrounding TMMC site were birds, screening ecological risk assessment was conducted on birds only. The assessment was assessed mainly based on the chemical evaluation, which the contamination in different environmental media was compared directly with the ecological impact levels (EIL) of each evaluation endpoints and the respective hazard quotient (HQ) and hazard index (HI) could be obtained. The preliminary ecological risk assessment results indicated HI is greater than 1. In other words, the biological stressors (birds) were exposed to the contamination, which was already exceeded the dosage that could cause unacceptable impacts to the ecological system. This result was mainly due to the high concentration of arsenic, metal and lead; thus it was suggested the above mention contaminants should be remediated as soon as possible or proper risk management measures should be taken.

Keywords: screening, ecological risk assessment, ecological impact levels, risk management

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218 The Predictive Utility of Subjective Cognitive Decline Using Item Level Data from the Everyday Cognition (ECog) Scales

Authors: J. Fox, J. Randhawa, M. Chan, L. Campbell, A. Weakely, D. J. Harvey, S. Tomaszewski Farias

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Early identification of individuals at risk for conversion to dementia provides an opportunity for preventative treatment. Many older adults (30-60%) report specific subjective cognitive decline (SCD); however, previous research is inconsistent in terms of what types of complaints predict future cognitive decline. The purpose of this study is to identify which specific complaints from the Everyday Cognition Scales (ECog) scales, a measure of self-reported concerns for everyday abilities across six cognitive domains, are associated with: 1) conversion from a clinical diagnosis of normal to either MCI or dementia (categorical variable) and 2) progressive cognitive decline in memory and executive function (continuous variables). 415 cognitively normal older adults were monitored annually for an average of 5 years. Cox proportional hazards models were used to assess associations between self-reported ECog items and progression to impairment (MCI or dementia). A total of 114 individuals progressed to impairment; the mean time to progression was 4.9 years (SD=3.4 years, range=0.8-13.8). Follow-up models were run controlling for depression. A subset of individuals (n=352) underwent repeat cognitive assessments for an average of 5.3 years. For those individuals, mixed effects models with random intercepts and slopes were used to assess associations between ECog items and change in neuropsychological measures of episodic memory or executive function. Prior to controlling for depression, subjective concerns on five of the eight Everyday Memory items, three of the nine Everyday Language items, one of the seven Everyday Visuospatial items, two of the five Everyday Planning items, and one of the six Everyday Organization items were associated with subsequent diagnostic conversion (HR=1.25 to 1.59, p=0.003 to 0.03). However, after controlling for depression, only two specific complaints of remembering appointments, meetings, and engagements and understanding spoken directions and instructions were associated with subsequent diagnostic conversion. Episodic memory in individuals reporting no concern on ECog items did not significantly change over time (p>0.4). More complaints on seven of the eight Everyday Memory items, three of the nine Everyday Language items, and three of the seven Everyday Visuospatial items were associated with a decline in episodic memory (Interaction estimate=-0.055 to 0.001, p=0.003 to 0.04). Executive function in those reporting no concern on ECog items declined slightly (p <0.001 to 0.06). More complaints on three of the eight Everyday Memory items and three of the nine Everyday Language items were associated with a decline in executive function (Interaction estimate=-0.021 to -0.012, p=0.002 to 0.04). These findings suggest that specific complaints across several cognitive domains are associated with diagnostic conversion. Specific complaints in the domains of Everyday Memory and Language are associated with a decline in both episodic memory and executive function. Increased monitoring and treatment of individuals with these specific SCD may be warranted.

Keywords: alzheimer’s disease, dementia, memory complaints, mild cognitive impairment, risk factors, subjective cognitive decline

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217 Reconciling the Fatigue of Space Property Rights

Authors: King Kumire

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The Outer Space Treaty and the Moon Treaty have been the backbone of space law. However, scientists, engineers, and policymakers have been silent about how human settlement on celestial bodies would change the legal dimensions of space law. Indeed, these legal space regimes should have a prescription on how galactic courts should deal with the aspect of space property ownership. On this planet earth, one can vindicate his own assets. In extraterrestrial environments, this is not the case because space law is fatigued by terrestrial body sovereignty, which must be upheld. However, the recent commercialization of microgravity environments requires property ownership laws to be enacted. Space activities have mutated to the extent that it is almost possible to build communities in space. The discussions on the moon village concept will be mentioned as well to give clarity on the subject to the audience. It should be stated that launchers can now explore the cosmos with space tourists. The world is also busy doing feasibility studies on how to implement space mining projects. These activities indisputably show that the research is important because it will not only expose how the cosmic world is constrained by existing legal frameworks, but it will provide a remedy for how the inevitable dilemma of property rights can be resolved through the formulation of multilateral and all-inclusive policies. The discussion will model various aspects of terrestrial property rights and the associated remedies against what can be applicable and customized for use in extraterrestrial environments. Transfer of ownership in space is also another area of interest as the researcher shall try to distinguish between envisaged personal and real rights in the new frontier vis-a-vis mainland transfer transactions. The writer imagines the extent to which the concepts of servitudes, accession, prescription and commixes, and other property templates can act as a starting point when cosmic probers move forward with the revision of orbital law. The article seeks to reconcile these ownership constraints by working towards the development of a living space common law which is elastic and embroidered by sustainable recommendations. A balance between transplanting terrestrial laws to the galactic arena and the need to enact new ones which will complement the existing space treaties will be meticulously pivoted.

Keywords: rights, commercialisation, ownership, sovereignty

Procedia PDF Downloads 143
216 Gradient Boosted Trees on Spark Platform for Supervised Learning in Health Care Big Data

Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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215 A Validated Estimation Method to Predict the Interior Wall of Residential Buildings Based on Easy to Collect Variables

Authors: B. Gepts, E. Meex, E. Nuyts, E. Knaepen, G. Verbeeck

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The importance of resource efficiency and environmental impact assessment has raised the interest in knowing the amount of materials used in buildings. If no BIM model or energy performance certificate is available, material quantities can be obtained through an estimation or time-consuming calculation. For the interior wall area, no validated estimation method exists. However, in the case of environmental impact assessment or evaluating the existing building stock as future material banks, knowledge of the material quantities used in interior walls is indispensable. This paper presents a validated method for the estimation of the interior wall area for dwellings based on easy-to-collect building characteristics. A database of 4963 residential buildings spread all over Belgium is used. The data are collected through onsite measurements of the buildings during the construction phase (between mid-2010 and mid-2017). The interior wall area refers to the area of all interior walls in the building, including the inner leaf of exterior (party) walls, minus the area of windows and doors, unless mentioned otherwise. The two predictive modelling techniques used are 1) a (stepwise) linear regression and 2) a decision tree. The best estimation method is selected based on the best R² k-fold (5) fit. The research shows that the building volume is by far the most important variable to estimate the interior wall area. A stepwise regression based on building volume per building, building typology, and type of house provides the best fit, with R² k-fold (5) = 0.88. Although the best R² k-fold value is obtained when the other parameters ‘building typology’ and ‘type of house’ are included, the contribution of these variables can be seen as statistically significant but practically irrelevant. Thus, if these parameters are not available, a simplified estimation method based on only the volume of the building can also be applied (R² k-fold = 0.87). The robustness and precision of the method (output) are validated three times. Firstly, the prediction of the interior wall area is checked by means of alternative calculations of the building volume and of the interior wall area; thus, other definitions are applied to the same data. Secondly, the output is tested on an extension of the database, so it has the same definitions but on other data. Thirdly, the output is checked on an unrelated database with other definitions and other data. The validation of the estimation methods demonstrates that the methods remain accurate when underlying data are changed. The method can support environmental as well as economic dimensions of impact assessment, as it can be used in early design. As it allows the prediction of the amount of interior wall materials to be produced in the future or that might become available after demolition, the presented estimation method can be part of material flow analyses on input and on output.

Keywords: buildings as material banks, building stock, estimation method, interior wall area

Procedia PDF Downloads 37
214 Identifying Protein-Coding and Non-Coding Regions in Transcriptomes

Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

Procedia PDF Downloads 73
213 Comparison of Gait Variability in Individuals with Trans-Tibial and Trans-Femoral Lower Limb Loss: A Pilot Study

Authors: Hilal Keklicek, Fatih Erbahceci, Elif Kirdi, Ali Yalcin, Semra Topuz, Ozlem Ulger, Gul Sener

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Objectives and Goals: The stride-to-stride fluctuations in gait is a determinant of qualified locomotion as known as gait variability. Gait variability is an important predictive factor of fall risk and useful for monitoring the effects of therapeutic interventions and rehabilitation. Comparison of gait variability in individuals with trans-tibial lower limb loss and trans femoral lower limb loss was the aim of the study. Methods: Ten individuals with traumatic unilateral trans femoral limb loss(TF), 12 individuals with traumatic transtibial lower limb loss(TT) and 12 healthy individuals(HI) were the participants of the study. All participants were evaluated with treadmill. Gait characteristics including mean step length, step length variability, ambulation index, time on each foot of participants were evaluated with treadmill. Participants were walked at their preferred speed for six minutes. Data from 4th minutes to 6th minutes were selected for statistical analyses to eliminate learning effect. Results: There were differences between the groups in intact limb step length variation, time on each foot, ambulation index and mean age (p < .05) according to the Kruskal Wallis Test. Pairwise analyses showed that there were differences between the TT and TF in residual limb variation (p=.041), time on intact foot (p=.024), time on prosthetic foot(p=.024), ambulation index(p = .003) in favor of TT group. There were differences between the TT and HI group in intact limb variation (p = .002), time on intact foot (p<.001), time on prosthetic foot (p < .001), ambulation index result (p < .001) in favor of HI group. There were differences between the TF and HI group in intact limb variation (p = .001), time on intact foot (p=.01) ambulation index result (p < .001) in favor of HI group. There was difference between the groups in mean age result from HI group were younger (p < .05).There were similarity between the groups in step lengths (p>.05) and time of prosthesis using in individuals with lower limb loss (p > .05). Conclusions: The pilot study provided basic data about gait stability in individuals with traumatic lower limb loss. Results of the study showed that to evaluate the gait differences between in different amputation level, long-range gait analyses methods may be useful to get more valuable information. On the other hand, similarity in step length may be resulted from effective prosthetic using or effective gait rehabilitation, in conclusion, all participants with lower limb loss were already trained. The differences between the TT and HI; TF and HI may be resulted from the age related features, therefore, age matched population in HI were recommended future studies. Increasing the number of participants and comparison of age-matched groups also recommended to generalize these result.

Keywords: lower limb loss, amputee, gait variability, gait analyses

Procedia PDF Downloads 281
212 Nickel Removal from Industrial Wastewater by Eucalyptus Leaves and Poplar Ashes

Authors: Negin Bayat, Nahid HasanZadeh

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Effluents of different industries such as metalworking, battery industry, mining, including heavy metal are considered problematic issues for both humans and the environment. These heavy metals include cadmium, copper, zinc, nickel, chromium, cyanide, lead, etc. Different physicochemical and biological methods are used to remove heavy metals, such as sedimentation, coagulation, flotation, chemical precipitation, filtration, membrane processes (reverse osmosis and nanofiltration), ion exchange, biological methods, adsorption with activated carbon, etc. These methods are generally either expensive or ineffective. In recent years, considerable attention has been given to the removal of heavy metal ions from solution by absorption using discarded and low-cost materials. In this study, nickel removal using an adsorption process by eucalyptus powdered leaves and poplar ash was investigated. This is an applied study. The effect of various parameters on metal removal, such as pH, amount of adsorbent, contact time, and stirring speed, was studied using a discontinuous method. This research was conducted in aqueous solutions on the laboratory scale. Then, optimum absorption conditions were obtained. Then, the study was conducted on real wastewater samples. In addition, the nickel concentration in the wastewater before and after the absorption process was measured. In all experiments, the remaining nickel was measured using an atomic absorption spectrometry device at 382 nm wavelength after an appropriate time and filtration. The results showed that increasing both adsorbent and pH parameters increase the metal removal rate. Nickel removal increased at the first 60 minutes. Then, the absorption rate remained constant and reached equilibrium. A desired removal rate with 40 mg in 100 ml adsorbent solution at pH = 9.5 was observed. According to the obtained results, the best absorption rate was observed at 40 mg dose using a combination of eucalyptus leaves and poplar ash in this study, which was equal to 99.76%. Thus, this combined method can be used as an inexpensive and effective absorbent for the removal of nickel from aqueous solutions.

Keywords: absorption, wastewater, nickel, poplar ash, eucalyptus leaf, treatment

Procedia PDF Downloads 25
211 Quantifying Multivariate Spatiotemporal Dynamics of Malaria Risk Using Graph-Based Optimization in Southern Ethiopia

Authors: Yonas Shuke Kitawa

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Background: Although malaria incidence has substantially fallen sharply over the past few years, the rate of decline varies by district, time, and malaria type. Despite this turn-down, malaria remains a major public health threat in various districts of Ethiopia. Consequently, the present study is aimed at developing a predictive model that helps to identify the spatio-temporal variation in malaria risk by multiple plasmodium species. Methods: We propose a multivariate spatio-temporal Bayesian model to obtain a more coherent picture of the temporally varying spatial variation in disease risk. The spatial autocorrelation in such a data set is typically modeled by a set of random effects that assign a conditional autoregressive prior distribution. However, the autocorrelation considered in such cases depends on a binary neighborhood matrix specified through the border-sharing rule. Over here, we propose a graph-based optimization algorithm for estimating the neighborhood matrix that merely represents the spatial correlation by exploring the areal units as the vertices of a graph and the neighbor relations as the series of edges. Furthermore, we used aggregated malaria count in southern Ethiopia from August 2013 to May 2019. Results: We recognized that precipitation, temperature, and humidity are positively associated with the malaria threat in the area. On the other hand, enhanced vegetation index, nighttime light (NTL), and distance from coastal areas are negatively associated. Moreover, nonlinear relationships were observed between malaria incidence and precipitation, temperature, and NTL. Additionally, lagged effects of temperature and humidity have a significant effect on malaria risk by either species. More elevated risk of P. falciparum was observed following the rainy season, and unstable transmission of P. vivax was observed in the area. Finally, P. vivax risks are less sensitive to environmental factors than those of P. falciparum. Conclusion: The improved inference was gained by employing the proposed approach in comparison to the commonly used border-sharing rule. Additionally, different covariates are identified, including delayed effects, and elevated risks of either of the cases were observed in districts found in the central and western regions. As malaria transmission operates in a spatially continuous manner, a spatially continuous model should be employed when it is computationally feasible.

Keywords: disease mapping, MSTCAR, graph-based optimization algorithm, P. falciparum, P. vivax, waiting matrix

Procedia PDF Downloads 85
210 Heavy Sulphide Material Characterization of Grasberg Block Cave Mine, Mimika, Papua: Implication for Tunnel Development and Mill Issue

Authors: Cahya Wimar Wicaksono, Reynara Davin Chen, Alvian Kristianto Santoso

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Grasberg Cu-Au ore deposit as one of the biggest porphyry deposits located in Papua Province, Indonesia produced by several intrusion that restricted by Heavy Sulphide Zone (HSZ) in peripheral. HSZ is the rock that becomes the contact between Grassberg Igneous Complex (GIC) with sedimentary and igneous rock outside, which is rich in sulphide minerals such as pyrite ± pyrrhotite. This research is to obtain the characteristic of HSZ based on geotechnical, geochemical and mineralogy aspect and those implication for daily mining operational activities. Method used in this research are geological and alteration mapping, core logging, FAA (Fire Assay Analysis), AAS (Atomic absorption spectroscopy), RQD (Rock Quality Designation) and rock water content. Data generated from methods among RQD data, mineral composition and grade, lithological and structural geology distribution in research area. The mapping data show that HSZ material characteristics divided into three type based on rocks association, there are near igneous rocks, sedimentary rocks and on HSZ area. And also divided based on its location, north and south part of research area. HSZ material characteristic consist of rock which rich of pyrite ± pyrrhotite, and RQD range valued about 25%-100%. Pyrite ± pyrrhotite which outcropped will react with H₂O and O₂ resulting acid that generates corrosive effect on steel wire and rockbolt. Whereas, pyrite precipitation proses in HSZ forming combustible H₂S gas which is harmful during blasting activities. Furthermore, the impact of H₂S gas in blasting activities is forming poison gas SO₂. Although HSZ high grade Cu-Au, however those high grade Cu-Au rich in sulphide components which is affected in flotation milling process. Pyrite ± pyrrhotite in HSZ will chemically react with Cu-Au that will settle in milling process instead of floating.

Keywords: combustible, corrosive, heavy sulphide zone, pyrite ± pyrrhotite

Procedia PDF Downloads 331
209 Risk Assessment of Flood Defences by Utilising Condition Grade Based Probabilistic Approach

Authors: M. Bahari Mehrabani, Hua-Peng Chen

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Management and maintenance of coastal defence structures during the expected life cycle have become a real challenge for decision makers and engineers. Accurate evaluation of the current condition and future performance of flood defence structures is essential for effective practical maintenance strategies on the basis of available field inspection data. Moreover, as coastal defence structures age, it becomes more challenging to implement maintenance and management plans to avoid structural failure. Therefore, condition inspection data are essential for assessing damage and forecasting deterioration of ageing flood defence structures in order to keep the structures in an acceptable condition. The inspection data for flood defence structures are often collected using discrete visual condition rating schemes. In order to evaluate future condition of the structure, a probabilistic deterioration model needs to be utilised. However, existing deterioration models may not provide a reliable prediction of performance deterioration for a long period due to uncertainties. To tackle the limitation, a time-dependent condition-based model associated with a transition probability needs to be developed on the basis of condition grade scheme for flood defences. This paper presents a probabilistic method for predicting future performance deterioration of coastal flood defence structures based on condition grading inspection data and deterioration curves estimated by expert judgement. In condition-based deterioration modelling, the main task is to estimate transition probability matrices. The deterioration process of the structure related to the transition states is modelled according to Markov chain process, and a reliability-based approach is used to estimate the probability of structural failure. Visual inspection data according to the United Kingdom Condition Assessment Manual are used to obtain the initial condition grade curve of the coastal flood defences. The initial curves then modified in order to develop transition probabilities through non-linear regression based optimisation algorithms. The Monte Carlo simulations are then used to evaluate the future performance of the structure on the basis of the estimated transition probabilities. Finally, a case study is given to demonstrate the applicability of the proposed method under no-maintenance and medium-maintenance scenarios. Results show that the proposed method can provide an effective predictive model for various situations in terms of available condition grading data. The proposed model also provides useful information on time-dependent probability of failure in coastal flood defences.

Keywords: condition grading, flood defense, performance assessment, stochastic deterioration modelling

Procedia PDF Downloads 241
208 Application of Building Information Modeling in Energy Management of Individual Departments Occupying University Facilities

Authors: Kung-Jen Tu, Danny Vernatha

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To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: database, electricity sub-meters, energy anomaly detection, sensor

Procedia PDF Downloads 309
207 Pediatric Health Nursing Research in Jordan: Evaluating the State of Knowledge and Determining Future Research Direction

Authors: Inaam Khalaf, Nadin M. Abdel Razeq, Hamza Alduraidi, Suhaila Halasa, Omayyah S. Nassar, Eman Al-Horani, Jumana Shehadeh, Anna Talal

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Background: Nursing researchers are responsible for generating knowledge that corresponds to national and global research priorities in order to promote, restore, and maintain the health of individuals and societies. The objectives of this scoping review of Jordanian literature are to assess the existing research on pediatric nursing in terms of evolution, authorship and collaborations, funding sources, methodologies, topics of research, and pediatric subjects' age groups so as to identify gaps in research. Methodology: A search was conducted using related keywords obtained from national and international databases. The reviewed literature included pediatric health articles published through December 2019 in English and Arabic, authored by nursing researchers. The investigators assessed the retrieved studies and extracted data using a data-mining checklist. Results: The review included 265 articles authored by Jordanian nursing researchers concerning children's health, published between 1987 and 2019; 95% were published between 2009 and 2019. The most commonly applied research methodology was the descriptive non-experimental method (76%). The main generic topics were health promotion and disease prevention (23%), chronic physical conditions (19%), mental health, behavioral disorders, and forensic issues (16%). Conclusion: The review findings identified a grave shortage of evidence concerning nursing care issues for children below five years of age, especially those between ages two and five years. The research priorities identified in this review resonate with those identified in international reports. Implications: Nursing researchers are encouraged to conduct more research targeting topics of national-level importance in collaboration with clinically involved nurses and international scholars.

Keywords: Jordan, scoping review, children health nursing, pediatric, adolescents

Procedia PDF Downloads 91
206 Investigating the Impact of Task Demand and Duration on Passage of Time Judgements and Duration Estimates

Authors: Jesika A. Walker, Mohammed Aswad, Guy Lacroix, Denis Cousineau

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There is a fundamental disconnect between the experience of time passing and the chronometric units by which time is quantified. Specifically, there appears to be no relationship between the passage of time judgments (PoTJs) and verbal duration estimates at short durations (e.g., < 2000 milliseconds). When a duration is longer than several minutes, however, evidence suggests that a slower feeling of time passing is predictive of overestimation. Might the length of a task moderate the relation between PoTJs and duration estimates? Similarly, the estimation paradigm (prospective vs. retrospective) and the mental effort demanded of a task (task demand) have both been found to influence duration estimates. However, only a handful of experiments have investigated these effects for tasks of long durations, and the results have been mixed. Thus, might the length of a task also moderate the effects of the estimation paradigm and task demand on duration estimates? To investigate these questions, 273 participants performed either an easy or difficult visual and memory search task for either eight or 58 minutes, under prospective or retrospective instructions. Afterward, participants provided a duration estimate in minutes, followed by a PoTJ on a Likert scale (1 = very slow, 7 = very fast). A 2 (prospective vs. retrospective) × 2 (eight minutes vs. 58 minutes) × 2 (high vs. low difficulty) between-subjects ANOVA revealed a two-way interaction between task demand and task duration on PoTJs, p = .02. Specifically, time felt faster in the more challenging task, but only in the eight-minute condition, p < .01. Duration estimates were transformed into RATIOs (estimate/actual duration) to standardize estimates across durations. An ANOVA revealed a two-way interaction between estimation paradigm and task duration, p = .03. Specifically, participants overestimated the task more if they were given prospective instructions, but only in the eight-minute task. Surprisingly, there was no effect of task difficulty on duration estimates. Thus, the demands of a task may influence ‘feeling of time’ and ‘estimation time’ differently, contributing to the existing theory that these two forms of time judgement rely on separate underlying cognitive mechanisms. Finally, a significant main effect of task duration was found for both PoTJs and duration estimates (ps < .001). Participants underestimated the 58-minute task (m = 42.5 minutes) and overestimated the eight-minute task (m = 10.7 minutes). Yet, they reported the 58-minute task as passing significantly slower on a Likert scale (m = 2.5) compared to the eight-minute task (m = 4.1). In fact, a significant correlation was found between PoTJ and duration estimation (r = .27, p <.001). This experiment thus provides evidence for a compensatory effect at longer durations, in which people underestimate a ‘slow feeling condition and overestimate a ‘fast feeling condition. The results are discussed in relation to heuristics that might alter the relationship between these two variables when conditions range from several minutes up to almost an hour.

Keywords: duration estimates, long durations, passage of time judgements, task demands

Procedia PDF Downloads 134
205 A Qualitative Research of Online Fraud Decision-Making Process

Authors: Semire Yekta

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Many online retailers set up manual review teams to overcome the limitations of automated online fraud detection systems. This study critically examines the strategies they adapt in their decision-making process to set apart fraudulent individuals from non-fraudulent online shoppers. The study uses a mix method research approach. 32 in-depth interviews have been conducted alongside with participant observation and auto-ethnography. The study found out that all steps of the decision-making process are significantly affected by a level of subjectivity, personal understandings of online fraud, preferences and judgments and not necessarily by objectively identifiable facts. Rather clearly knowing who the fraudulent individuals are, the team members have to predict whether they think the customer might be a fraudster. Common strategies used are relying on the classification and fraud scorings in the automated fraud detection systems, weighing up arguments for and against the customer and making a decision, using cancellation to test customers’ reaction and making use of personal experiences and “the sixth sense”. The interaction in the team also plays a significant role given that some decisions turn into a group discussion. While customer data represent the basis for the decision-making, fraud management teams frequently make use of Google search and Google Maps to find out additional information about the customer and verify whether the customer is the person they claim to be. While this, on the one hand, raises ethical concerns, on the other hand, Google Street View on the address and area of the customer puts customers living in less privileged housing and areas at a higher risk of being classified as fraudsters. Phone validation is used as a final measurement to make decisions for or against the customer when previous strategies and Google Search do not suffice. However, phone validation is also characterized by individuals’ subjectivity, personal views and judgment on customer’s reaction on the phone that results in a final classification as genuine or fraudulent.

Keywords: online fraud, data mining, manual review, social construction

Procedia PDF Downloads 345
204 Assessing the Impacts of Riparian Land Use on Gully Development and Sediment Load: A Case Study of Nzhelele River Valley, Limpopo Province, South Africa

Authors: B. Mavhuru, N. S. Nethengwe

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Human activities on land degradation have triggered several environmental problems especially in rural areas that are underdeveloped. The main aim of this study is to analyze the contribution of different land uses to gully development and sediment load on the Nzhelele River Valley in the Limpopo Province. Data was collected using different methods such as observation, field data techniques and experiments. Satellite digital images, topographic maps, aerial photographs and the sediment load static model also assisted in determining how land use affects gully development and sediment load. For data analysis, the researcher used the following methods: Analysis of Variance (ANOVA), descriptive statistics, Pearson correlation coefficient and statistical correlation methods. The results of the research illustrate that high land use activities create negative changes especially in areas that are highly fragile and vulnerable. Distinct impact on land use change was observed within settlement area (9.6 %) within a period of 5 years. High correlation between soil organic matter and soil moisture (R=0.96) was observed. Furthermore, a significant variation (p ≤ 0.6) between the soil organic matter and soil moisture was also observed. A very significant variation (p ≤ 0.003) was observed in bulk density and extreme significant variations (p ≤ 0.0001) were observed in organic matter and soil particle size. The sand mining and agricultural activities has contributed significantly to the amount of sediment load in the Nzhelele River. A high significant amount of total suspended sediment (55.3 %) and bed load (53.8 %) was observed within the agricultural area. The connection which associates the development of gullies to various land use activities determines the amount of sediment load. These results are consistent with other previous research and suggest that land use activities are likely to exacerbate the development of gullies and sediment load in the Nzhelele River Valley.

Keywords: drainage basin, geomorphological processes, gully development, land degradation, riparian land use and sediment load

Procedia PDF Downloads 311
203 From Text to Data: Sentiment Analysis of Presidential Election Political Forums

Authors: Sergio V Davalos, Alison L. Watkins

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User generated content (UGC) such as website post has data associated with it: time of the post, gender, location, type of device, and number of words. The text entered in user generated content (UGC) can provide a valuable dimension for analysis. In this research, each user post is treated as a collection of terms (words). In addition to the number of words per post, the frequency of each term is determined by post and by the sum of occurrences in all posts. This research focuses on one specific aspect of UGC: sentiment. Sentiment analysis (SA) was applied to the content (user posts) of two sets of political forums related to the US presidential elections for 2012 and 2016. Sentiment analysis results in deriving data from the text. This enables the subsequent application of data analytic methods. The SASA (SAIL/SAI Sentiment Analyzer) model was used for sentiment analysis. The application of SASA resulted with a sentiment score for each post. Based on the sentiment scores for the posts there are significant differences between the content and sentiment of the two sets for the 2012 and 2016 presidential election forums. In the 2012 forums, 38% of the forums started with positive sentiment and 16% with negative sentiment. In the 2016 forums, 29% started with positive sentiment and 15% with negative sentiment. There also were changes in sentiment over time. For both elections as the election got closer, the cumulative sentiment score became negative. The candidate who won each election was in the more posts than the losing candidates. In the case of Trump, there were more negative posts than Clinton’s highest number of posts which were positive. KNIME topic modeling was used to derive topics from the posts. There were also changes in topics and keyword emphasis over time. Initially, the political parties were the most referenced and as the election got closer the emphasis changed to the candidates. The performance of the SASA method proved to predict sentiment better than four other methods in Sentibench. The research resulted in deriving sentiment data from text. In combination with other data, the sentiment data provided insight and discovery about user sentiment in the US presidential elections for 2012 and 2016.

Keywords: sentiment analysis, text mining, user generated content, US presidential elections

Procedia PDF Downloads 195
202 Advancing Environmental Remediation Through the Production of Functional Porous Materials from Phosphorite Residue Tailings

Authors: Ali Mohammed Yimer, Ayalew Assen, Youssef Belmabkhout

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Environmental remediation is a pressing global concern, necessitating innovative strategies to address the challenges posed by industrial waste and pollution. This study aims to advance environmental remediation by developing cutting-edge functional porous materials from phosphorite residue tailings. Phosphorite mining activities generate vast amounts of waste, which pose significant environmental risks due to their contaminants. The proposed approach involved transforming these phosphorite residue tailings into valuable porous materials through a series of physico-chemical processes including milling, acid-base leaching, designing or templating as well as formation processes. The key components of the tailings were extracted and processed to produce porous arrays with high surface area and porosity. These materials were engineered to possess specific properties suitable for environmental remediation applications, such as enhanced adsorption capacity and selectivity for target contaminants. The synthesized porous materials were thoroughly characterized using advanced analytical techniques (XRD, SEM-EDX, N2 sorption, TGA, FTIR) to assess their structural, morphological, and chemical properties. The performance of the materials in removing various pollutants, including heavy metals and organic compounds, were evaluated through batch adsorption experiments. Additionally, the potential for material regeneration and reusability was investigated to enhance the sustainability of the proposed remediation approach. The outdoors of this research holds significant promise for addressing the environmental challenges associated with phosphorite residue tailings. By valorizing these waste materials into porous materials with exceptional remediation capabilities, this study contributes to the development of sustainable and cost-effective solutions for environmental cleanup. Furthermore, the utilization of phosphorite residue tailings in this manner offers a potential avenue for the remediation of other contaminated sites, thereby fostering a circular economy approach to waste management.

Keywords: functional porous materials, phosphorite residue tailings, adsorption, environmental remediation, sustainable solutions

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201 Material Chemistry Level Deformation and Failure in Cementitious Materials

Authors: Ram V. Mohan, John Rivas-Murillo, Ahmed Mohamed, Wayne D. Hodo

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Cementitious materials, an excellent example of highly complex, heterogeneous material systems, are cement-based systems that include cement paste, mortar, and concrete that are heavily used in civil infrastructure; though commonly used are one of the most complex in terms of the material morphology and structure than most materials, for example, crystalline metals. Processes and features occurring at the nanometer sized morphological structures affect the performance, deformation/failure behavior at larger length scales. In addition, cementitious materials undergo chemical and morphological changes gaining strength during the transient hydration process. Hydration in cement is a very complex process creating complex microstructures and the associated molecular structures that vary with hydration. A fundamental understanding can be gained through multi-scale level modeling for the behavior and properties of cementitious materials starting from the material chemistry level atomistic scale to further explore their role and the manifested effects at larger length and engineering scales. This predictive modeling enables the understanding, and studying the influence of material chemistry level changes and nanomaterial additives on the expected resultant material characteristics and deformation behavior. Atomistic-molecular dynamic level modeling is required to couple material science to engineering mechanics. Starting at the molecular level a comprehensive description of the material’s chemistry is required to understand the fundamental properties that govern behavior occurring across each relevant length scale. Material chemistry level models and molecular dynamics modeling and simulations are employed in our work to describe the molecular-level chemistry features of calcium-silicate-hydrate (CSH), one of the key hydrated constituents of cement paste, their associated deformation and failure. The molecular level atomic structure for CSH can be represented by Jennite mineral structure. Jennite has been widely accepted by researchers and is typically used to represent the molecular structure of the CSH gel formed during the hydration of cement clinkers. This paper will focus on our recent work on the shear and compressive deformation and failure behavior of CSH represented by Jennite mineral structure that has been widely accepted by researchers and is typically used to represent the molecular structure of CSH formed during the hydration of cement clinkers. The deformation and failure behavior under shear and compression loading deformation in traditional hydrated CSH; effect of material chemistry changes on the predicted stress-strain behavior, transition from linear to non-linear behavior and identify the on-set of failure based on material chemistry structures of CSH Jennite and changes in its chemistry structure will be discussed.

Keywords: cementitious materials, deformation, failure, material chemistry modeling

Procedia PDF Downloads 291