Search results for: David Armstrong
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 726

Search results for: David Armstrong

666 The Third Level Digital Divide: Millennials and Post-Millennials Online Activities in South Africa

Authors: Ayanda Magida, Brian Armstrong

Abstract:

The study aimed to assess the third level of the digital divide among the millennials and post-millennials in South Africa. The millennials are people born from 1981-to 1996, that is, people between the ages of 25-40 years old and post-millennials are people born from 1997 to date. For the study, only post-millennials born between 1997-2003 were included as they were old enough to consent to participation in the study. Data was collected as part of the Ph.D. project that focuses on the relationship between income inequality, the digital divide, and social cohesion in South Africa. The digital divide has three main levels, namely the first, second and third. The first and second focus on access and usage, respectively. The third-level digital divide can be defined as the differences in the benefits associated with being online. The current paper focuses on the third level: the benefits derived by being online using four domains: economic, educational, social, and personal benefits. The economic benefits include income, employment and finance-related activities; the social benefits include socializing belonging, identity, and informal networks. The personal benefits include personal wellbeing and self-actualization. A total of 763 participants completed the survey, and 61.3% were post-millennials between the ages of 18-24 and s 38.6 % were millennials between 25 and 40. The majority of the respondents were female (62%), male (34%) and nonbinary (1%), respectively. Most of the respondents were black, followed by whites, Indians and colored, respectively. Thus, they represented the status of the demographics of the country. Most of the respondents had access to the internet and smartphone. Most expressed that they use laptops (68%) or mobile (71%) to access the internet and 54 % access the internet using wireless/Wi-Fi. There were no differences between the millennial and post-millennial economic and educational benefits of being online. However, the post-millennials were more inclined to use the internet for social and personal benefits than the millennials. This could be attributed to many factors, such as age. The post-millennials are still discovering themselves and therefore would derive social and personal benefits associated with being online. The findings confirm studies that argue that younger generations derive more benefits from being online than the older generation. Based on the findings, it is evident that the post-millennials are not using the internet or online activities for social networks and socializing but can derive economic benefits such as job looking and education benefits from being online. It can be inferred that there are no significant differences between the two groups, and it seems like the third-level digital divide is not evident among the two groups as they both have been able to derive meaningful benefits from being online. Further studies should focus on the third-level divide between the baby boomers and Generation X.

Keywords: third-level digital divide, millennials, post-millennials, online activities

Procedia PDF Downloads 74
665 Predictive Maintenance Based on Oil Analysis Applicable to Transportation Fleets

Authors: Israel Ibarra Solis, Juan Carlos Rodriguez Sierra, Ma. del Carmen Salazar Hernandez, Isis Rodriguez Sanchez, David Perez Guerrero

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At the present paper we try to explain the analysis techniques use for the lubricating oil in a maintenance period of a city bus (Mercedes Benz Boxer 40), which is call ‘R-24 route’, line Coecillo Centro SA de CV in Leon Guanajuato, to estimate the optimal time for the oil change. Using devices such as the rotational viscometer and the atomic absorption spectrometer, they can detect the incipient form when the oil loses its lubricating properties and, therefore, cannot protect the mechanical components of diesel engines such these trucks. Timely detection of lost property in the oil, it allows us taking preventive plan maintenance for the fleet.

Keywords: atomic absorption spectrometry, maintenance, predictive velocity rate, lubricating oils

Procedia PDF Downloads 533
664 Assessment of Weaver Birds and Their Allies Within and Around Ngel-Nyaki Forest Reserve, Yelwa, Sardauna LGA, Taraba State, Nigeria

Authors: David Delpine Leila, Demnyo Sunita Femi, Musa David Garkida, Elisha Emmanuel Barde, Emmanuel Allahnanan, Yani Julius Philip

Abstract:

Birds are among the key components of the earth’s biodiversity and the most diverse and evolutionarily successful groups of animals. The weaverbirds are a large family of birds found mostly in Africa, with a few species found in southern Asia and the West Indian Ocean islands. This study assessed the diversity and abundance of weaver birds and their allies within and around Ngel-Nyaki Forest Reserve in Yelwa, Sardauna Local Government Area of Taraba State, Nigeria. A total of 602 weaver birds and allies’ bird species were recorded using the Point Count Line Transect. The data collected during the research period were analyzed using simple percentages, and diversity was calculated using the Shannon Wiener Diversity Index. The fenced (ungrazed area) was more abundant with 351 individuals while the unfenced (grazed area) was less abundant with 251 individuals recorded. In the fenced (ungrazed area), Yellow Bishop (Euplectes capensis) had the highest abundance of (102; 29.01%), followed by Village Weaver (Ploceus cucullatus) (80; 22.79%), then Vieillot's Black Weaver (Ploceus nigerrimus) (40; 11.42%), Red-collard Widowbird (Ploceus ardens) (6; 1.71%), Dark-backed Weaver (5; 1.42%) and the least was Hartlaub Marsh Widowbird (1; 0.28%) while in the unfenced (grazed area), the Village weaver (Ploceus cucullatus) (85; 33.86%) was the most abundant, followed by Spectacled Weaver (Ploceus ocularis) (36; 14.34%), then Yellow Bishop (Euplectes capensis) (30; 11.95%), Baglefecht Weaver (Ploceus baglafecht) (23; 9.16%), Bannerman’s Weaver (Ploceus bannermani) (17; 6.77%) and the least was Yellow-mantled Widowbird (Euplectes macroura) (5; 1.99%). In terms of diversity, there were more weaver bird species in the fenced area with a Shannon Wiener Diversity Index of (Hˈ 2.03417) than in the unfenced area with a Shannon Wiener Diversity Index of (Hˈ 1.862671). The Shannon Wiener Diversity Index in both fenced and unfenced areas is significant. There was more abundance of bird species in the fenced area than in the unfenced area of the Forest Reserve. Thorough research should be conducted on the abundance and diversity of weavers and their allies because we were only able to access 4 km2 out of 46 km2 of land available, according to the Annual Report of Ngel-Nyaki Forest Reserve of 2020. It shows that there are many species of weaver birds and their allies, such as the Black-billed Weaver (Ploceus melanogaster) and the Red-billed Quelea (Quelea quelea), which are available within the reserve.

Keywords: abundance, diversity, weaver birds, allies, Ngel-Nyaki

Procedia PDF Downloads 33
663 Unsupervised Learning of Spatiotemporally Coherent Metrics

Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.

Keywords: machine learning, pattern clustering, pooling, classification

Procedia PDF Downloads 419
662 A Descriptive Approach towards the Understanding of the Central American Coffee Business Demography Phenomena

Authors: Jesus David Argueta Moreno, Justa Rufina Martel, Edith Gabriela Carrasco

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The Central American Coffee small, medium, and large corporations search for excellence, sustainability, and continuous improvement, triggers in a still unknown scale the Local expansion, crusading, and franchising strategies towards a more suitable commercial opportunity, where the dynamics of the Central American business displacement can be explained through the markets permeability traits. By considering the previously mentioned, the present study aims to evaluate the franchising potentialities offered by Central American Coffee business scenario, in order to explain dynamics of the business demography phenomena and its relevance on the Central American competitiveness landscape.

Keywords: competitiveness, franchising, business demography, Central American Coffee

Procedia PDF Downloads 582
661 A Clinician’s Perspective on Electroencephalography Annotation and Analysis for Driver Drowsiness Estimation

Authors: Ruxandra Aursulesei, David O’Callaghan, Cian Ryan, Diarmaid O’Cualain, Viktor Varkarakis, Alina Sultana, Joseph Lemley

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Human errors caused by drowsiness are among the leading causes of road accidents. Neurobiological research gives information about the electrical signals emitted by neurons firing within the brain. Electrical signal frequencies can be determined by attaching bio-sensors to the head surface. By observing the electrical impulses and the rhythmic interaction of neurons with each other, we can predict the mental state of a person. In this paper, we aim to better understand intersubject and intrasubject variability in terms of electrophysiological patterns that occur at the onset of drowsiness and their evolution with the decreasing of vigilance. The purpose is to lay the foundations for an algorithm that detects the onset of drowsiness before the physical signs become apparent.

Keywords: electroencephalography, drowsiness, ADAS, annotations, clinician

Procedia PDF Downloads 78
660 Feasiblity of Replacing Inductive Instrument Transformers with Non-Conventional Intrument Transformers to replace

Authors: David A. Wallace, Salakjit J. Nilboworn

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Secure and reliable transmission and distribution of electrical power is crucial in today’s ever-increasing demand for electricity. Traditional methods of protecting the electrical grid have relied on relaying systems receiving voltage and current inputs from inductive instruments transformers (IT). This method has provided robust and stable performance throughout the years. Today with the advent of new non-conventional transformers (NCIT) and sensors, the electrical landscape is changing. These new systems have to ability to provide the same electrical performance as traditional instrument transformers with the added features of data acquisition, communication, smaller footprint, lower cost and resistance to GMD/GIC events.

Keywords: non-conventional instrument transformers, digital substations, smart grids, micro-grids

Procedia PDF Downloads 51
659 Sorting Maize Haploids from Hybrids Using Single-Kernel Near-Infrared Spectroscopy

Authors: Paul R Armstrong

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Doubled haploids (DHs) have become an important breeding tool for creating maize inbred lines, although several bottlenecks in the DH production process limit wider development, application, and adoption of the technique. DH kernels are typically sorted manually and represent about 10% of the seeds in a much larger pool where the remaining 90% are hybrid siblings. This introduces time constraints on DH production and manual sorting is often not accurate. Automated sorting based on the chemical composition of the kernel can be effective, but devices, namely NMR, have not achieved the sorting speed to be a cost-effective replacement to manual sorting. This study evaluated a single kernel near-infrared reflectance spectroscopy (skNIR) platform to accurately identify DH kernels based on oil content. The skNIR platform is a higher-throughput device, approximately 3 seeds/s, that uses spectra to predict oil content of each kernel from maize crosses intentionally developed to create larger than normal oil differences, 1.5%-2%, between DH and hybrid kernels. Spectra from the skNIR were used to construct a partial least squares regression (PLS) model for oil and for a categorical reference model of 1 (DH kernel) or 2 (hybrid kernel) and then used to sort several crosses to evaluate performance. Two approaches were used for sorting. The first used a general PLS model developed from all crosses to predict oil content and then used for sorting each induction cross, the second was the development of a specific model from a single induction cross where approximately fifty DH and one hundred hybrid kernels used. This second approach used a categorical reference value of 1 and 2, instead of oil content, for the PLS model and kernels selected for the calibration set were manually referenced based on traditional commercial methods using coloration of the tip cap and germ areas. The generalized PLS oil model statistics were R2 = 0.94 and RMSE = .93% for kernels spanning an oil content of 2.7% to 19.3%. Sorting by this model resulted in extracting 55% to 85% of haploid kernels from the four induction crosses. Using the second method of generating a model for each cross yielded model statistics ranging from R2s = 0.96 to 0.98 and RMSEs from 0.08 to 0.10. Sorting in this case resulted in 100% correct classification but required models that were cross. In summary, the first generalized model oil method could be used to sort a significant number of kernels from a kernel pool but was not close to the accuracy of developing a sorting model from a single cross. The penalty for the second method is that a PLS model would need to be developed for each individual cross. In conclusion both methods could find useful application in the sorting of DH from hybrid kernels.

Keywords: NIR, haploids, maize, sorting

Procedia PDF Downloads 276
658 Data Mining Algorithms Analysis: Case Study of Price Predictions of Lands

Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

Procedia PDF Downloads 342
657 Recognition of Early Enterococcus Faecalis through Image Treatment by Using Octave

Authors: Laura Victoria Vigoya Morales, David Rolando Suarez Mora

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The problem of detecting enterococcus faecalis is receiving considerable attention with the new cases of beachgoers infected with the bacteria, which can be found in fecal matter. The process detection of this kind of bacteria would be taking a long time, which waste time and money as a result of closing recreation place, like beach or pools. Hence, new methods for automating the process of detecting and recognition of this bacteria has become in a challenge. This article describes a novel approach to detect the enterococcus faecalis bacteria in water by using an octave algorithm, which embody a network neural. This document shows result of performance, quality and integrity of the algorithm.

Keywords: Enterococcus faecalis, image treatment, octave and network neuronal

Procedia PDF Downloads 194
656 Making Sense of Adversity Triggers Using Organisational Resilience, a Systematic Literature Review

Authors: Luke McGowan, David Pickernell, Martini Battisti

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In this paper, Adversity Triggers were explored through the lens of Organisational Resilience. Adversity Triggers are contextualized by temporal factors, thus, naturally aligning to Resilience literature. Resilience has been chosen as the theoretical framework as risk management approaches are often not geared towards providing meaningful responses to high-impact, low-probability events. Adversity Triggers and Organisational Resilience both consider temporal factors which enabled investigation of each phase of recovery. A systematic literature was employed to assess previous literature and define further areas of research. The systematic literature review method was chosen to catalogue and identify gaps in current literature.

Keywords: adversity triggers, crisis, extreme events, organisational resilience, resilience

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655 Redefining Success Beyond Borders: A Deep Dive into Effective Methods to Boost Morale Among Virtual Workers for Exponential Project Performance

Authors: Florence Ibeh, David Oyewmi Oyekunle, David Boohene

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The continuous advancement of information technology has completely transformed how businesses and organizations operate on a global scale. The widespread availability of virtual communication tools enables individuals to opt for remote work. While remote employment offers various benefits, such as facilitating corporate growth and enhancing customer support, it also presents distinct challenges. Therefore, investigating the intricacies of virtual team morale is crucial for ensuring the achievement of project objectives. For this study, content analysis of pre-existing secondary data was employed to examine the phenomenon. Essential elements vital for improving the success of projects within virtual teams were identified. These factors include technology adoption, creating a distraction-free work environment, effective leadership, trust-building, clear communication channels, well-defined task allocation, active team participation, and motivation. Furthermore, the study established a substantial correlation between morale levels and the participation and productivity of virtual team members. Higher levels of morale were associated with optimal performance among virtual teams. The study determined that the key factors for enhancing project performance in virtual teams are the adoption of technology, a focused environment, effective leadership, trust, communication, well-defined tasks, collaborative teamwork, and motivation. Additionally, the study discovered that modifying the optimal strategies employed by in-office teams can enhance the diminished morale prevalent in remote teams to sustain a high level of team morale for virtual teams. The findings of this study are highly significant in the dynamic field of project management. Currently, there is limited information regarding strategies that address challenges arising from external factors in virtual teams, such as ambient noise and disruptions caused by family members. The findings underscore the significance of selecting appropriate communication technologies, delineating distinct roles and responsibilities for virtual team members, and nurturing a culture of accountability and trust. Promoting seamless collaboration and instilling motivation among virtual team members are deemed highly effective in augmenting employee engagement and performance within virtual team setting.

Keywords: virtual teams, morale, project performance, distract-free environment, technology adaptation

Procedia PDF Downloads 33
654 Transition Pathways of Commercial-Urban Fleet Electrification

Authors: Emily Gould, Walter Wehremeyer, David Greaves, Rodney Turtle

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This paper considers current thinking on the pathway for electric vehicles, identifying the development blocks of alternative innovation within the market and analyse technological lock-in. The relationship between transition pathways and technological lock-in is largely under-researched particularly in the field of e-mobility. This paper is based on a study with three commercial-urban fleets that examines strategic decisions in new technology adaption alongside vehicle procurement and driver perspective. The paper will analyse the fleet’s decision matrix upon electric vehicles and seek to understand the influence of company culture, strategy and technology applicability, within the context of transition pathways.

Keywords: electric vehicles, fleets, path dependencies, transition pathways

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653 Study of Intergranular Corrosion in Austenitic Stainless Steels Using Electrochemical Impedance Spectroscopy

Authors: Satish Kolli, Adriana Ferancova, David Porter, Jukka Kömi

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Electrochemical impedance spectroscopy (EIS) has been used to detect sensitization in austenitic stainless steels that are heat treated in the temperature regime 600-820 °C to produce different degrees of sensitization in the material. The tests were conducted at five different DC potentials in the transpassive region. The quantitative determination of degree of sensitization has been done using double loop electrochemical potentiokinetic reactivation tests (DL-EPR). The correlation between EIS Nyquist diagrams and DL-EPR degree of sensitization values has been studied. The EIS technique can be used as a qualitative tool in determining the intergranular corrosion in austenitic stainless steels that are heat treated at a given temperature.

Keywords: electrochemical technique, intergranular corrosion, sensitization, stainless steels

Procedia PDF Downloads 150
652 Intelligent System for Diagnosis Heart Attack Using Neural Network

Authors: Oluwaponmile David Alao

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Misdiagnosis has been the major problem in health sector. Heart attack has been one of diseases that have high level of misdiagnosis recorded on the part of physicians. In this paper, an intelligent system has been developed for diagnosis of heart attack in the health sector. Dataset of heart attack obtained from UCI repository has been used. This dataset is made up of thirteen attributes which are very vital in diagnosis of heart disease. The system is developed on the multilayer perceptron trained with back propagation neural network then simulated with feed forward neural network and a recognition rate of 87% was obtained which is a good result for diagnosis of heart attack in medical field.

Keywords: heart attack, artificial neural network, diagnosis, intelligent system

Procedia PDF Downloads 618
651 Application of Facilities Management Practice in High Rise Commercial Properties: Jos in Perpective

Authors: Aliyu Ahmad Aliyu, Abubakar Ahmad, Muhammad Umar Bello, Rozilah Kasim, David Martin

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The article studied the application of facilities management practice in high rise commercial properties. Convenience sampling technique was used in administering questionnaires to the 60 respondents who responded to the survey. It was found out that the extent of application of facilities management in the subject properties is better described as below average. Similarly, the most frequently tools of facilities management in use and employed in the properties were outsourcing and in-house sourcing. This was influenced by the level of their familiarity with the tools. Planned and Preventive maintenance should be taken regularly in other to enhance the effectiveness of the facilities management and to satisfy both the owner and customers of the organization.

Keywords: commercial properties, facilities management, high-rise buildings, Jos metropolis and outsourcing

Procedia PDF Downloads 499
650 Using Nature-Based Solutions to Decarbonize Buildings in Canadian Cities

Authors: Zahra Jandaghian, Mehdi Ghobadi, Michal Bartko, Alex Hayes, Marianne Armstrong, Alexandra Thompson, Michael Lacasse

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The Intergovernmental Panel on Climate Change (IPCC) report stated the urgent need to cut greenhouse gas emissions to avoid the adverse impacts of climatic changes. The United Nations has forecasted that nearly 70 percent of people will live in urban areas by 2050 resulting in a doubling of the global building stock. Given that buildings are currently recognised as emitting 40 percent of global carbon emissions, there is thus an urgent incentive to decarbonize existing buildings and to build net-zero carbon buildings. To attain net zero carbon emissions in communities in the future requires action in two directions: I) reduction of emissions; and II) removal of on-going emissions from the atmosphere once de-carbonization measures have been implemented. Nature-based solutions (NBS) have a significant role to play in achieving net zero carbon communities, spanning both emission reductions and removal of on-going emissions. NBS for the decarbonisation of buildings can be achieved by using green roofs and green walls – increasing vertical and horizontal vegetation on the building envelopes – and using nature-based materials that either emit less heat to the atmosphere thus decreasing photochemical reaction rates, or store substantial amount of carbon during the whole building service life within their structure. The NBS approach can also mitigate urban flooding and overheating, improve urban climate and air quality, and provide better living conditions for the urban population. For existing buildings, de-carbonization mostly requires retrofitting existing envelopes efficiently to use NBS techniques whereas for future construction, de-carbonization involves designing new buildings with low carbon materials as well as having the integrity and system capacity to effectively employ NBS. This paper presents the opportunities and challenges in respect to the de-carbonization of buildings using NBS for both building retrofits and new construction. This review documents the effectiveness of NBS to de-carbonize Canadian buildings, identifies the missing links to implement these techniques in cold climatic conditions, and determine a road map and immediate approaches to mitigate the adverse impacts of climate change such as urban heat islanding. Recommendations are drafted for possible inclusion in the Canadian building and energy codes.

Keywords: decarbonization, nature-based solutions, GHG emissions, greenery enhancement, buildings

Procedia PDF Downloads 64
649 The Effectiveness of Lesson Study via Learning Communities in Increasing Instructional Self-Efficacy of Beginning Special Educators

Authors: David D. Hampton

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Lesson study is used as an instructional technique to promote both student and faculty learning. However, little is known about the usefulness of learning communities in supporting results of lesson study on the self-efficacy and development for tenure-track faculty. This study investigated the impact of participation in a lesson study learning community on 34 new faculty members at a mid-size Midwestern University, specifically regarding implementing lesson study evaluations by new faculty on their reported self-efficacy. Results indicate that participation in a lesson study learning community significantly increased faculty members’ lesson study self-efficacy as well as grant and manuscript production over one academic year. Suggestions for future lesson study around faculty learning communities are discussed.

Keywords: lesson study, learning community, lesson study self-efficacy, new faculty

Procedia PDF Downloads 122
648 Bidirectional Encoder Representations from Transformers Sentiment Analysis Applied to Three Presidential Pre-Candidates in Costa Rica

Authors: Félix David Suárez Bonilla

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A sentiment analysis service to detect polarity (positive, neural, and negative), based on transfer learning, was built using a Spanish version of BERT and applied to tweets written in Spanish. The dataset that was used consisted of 11975 reviews, which were extracted from Google Play using the google-play-scrapper package. The BETO trained model used: the AdamW optimizer, a batch size of 16, a learning rate of 2x10⁻⁵ and 10 epochs. The system was tested using tweets of three presidential pre-candidates from Costa Rica. The system was finally validated using human labeled examples, achieving an accuracy of 83.3%.

Keywords: NLP, transfer learning, BERT, sentiment analysis, social media, opinion mining

Procedia PDF Downloads 137
647 Investigating Water-Oxidation Using a Ru(III) Carboxamide Water Coordinated Complex

Authors: Yosra M. Badiei, Evelyn Ortiz, Marisa Portenti, David Szalda

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Water-oxidation half-reaction is a critical reaction that can be driven by a sustainable energy source (e.g., solar or wind) and be coupled with a chemical fuel making reaction which stores the released electrons and protons from water (e.g., H₂ or methanol). The use of molecular water-oxidation catalysts (WOC) allow the rationale design of redox active metal centers and provides a better understanding of their structure-activity-relationship. Herein, the structure of a Ru(III) complex bearing a doubly deprotonated N,N'-bis(aryl)pyridine-2,6-dicarboxamide ligand which contains a water molecule in its primary coordination sphere was elucidated by single-crystal X-ray diffraction. Further spectroscopic experimental data and pH-dependent electrochemical studies reveal its water-oxidation reactivity. Emphasis on mechanistic details for O₂ formation of this complex will be addressed.

Keywords: water-oxidation, catalysis, ruthenium, artificial photosynthesis

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646 Climate Change Effect on the Dynamic Modulus Property of Asphalt Concrete in Southern England Using UKCP09

Authors: David Idiata

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This paper is directed at using the UKCP09 climate change projection tool to predict the effect of climate change on the dynamic modulus of asphalt concrete is Southern England knowing that there is a pressing challenge directly facing infrastructure in the urban cities in the world today due to climate change. Climate change causes change in the environment which in turn impacts on the long-term structural performance of structures. From the projection values obtained, it was discovered that as the temperature increases, the dynamic modulus reduces and this effect was more on the South West which have temperature range of 36.8 oC to 48.3 oC and dynamic modulus range of 2,212 MPa to 1256 MPa.

Keywords: dynamic modulus, asphalt concrete, UKCP09, Southern England

Procedia PDF Downloads 332
645 Video Heart Rate Measurement for the Detection of Trauma-Related Stress States

Authors: Jarek Krajewski, David Daxberger, Luzi Beyer

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Finding objective and non-intrusive measurements of emotional and psychopathological states (e.g., post-traumatic stress disorder, PTSD) is an important challenge. Thus, the proposed approach here uses Photoplethysmographic imaging (PPGI) applying facial RGB Cam videos to estimate heart rate levels. A pipeline for the signal processing of the raw image has been proposed containing different preprocessing approaches, e.g., Independent Component Analysis, Non-negative Matrix factorization, and various other artefact correction approaches. Under resting and constant light conditions, we reached a sensitivity of 84% for pulse peak detection. The results indicate that PPGI can be a suitable solution for providing heart rate data derived from these indirectly post-traumatic stress states.

Keywords: heart rate, PTSD, PPGI, stress, preprocessing

Procedia PDF Downloads 99
644 Effect of Synthesis Method on Structural, Morphological Properties of Zr0.8Y0.2-xLax Oxides (x=0, 0.1, 0.2)

Authors: Abdelaziz Ghrib, Samir Hattali, Mouloud Ghrib, Mohamed Lamine Aouissia, David Ruch

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In the present study, the solid solutions with a chemical composition of Zr0.8Y0.2-xLaxO2 (x=0, 0.1, 0.2) were synthesized via two routes, by hydrothermal method using NaOH as precipitating agent at 230°C for 15h and by the sol–gel process using citric acid as complexing agent. Compounds have been characterized by powder X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), Thermo gravimetric Analysis (TGA) and Differential Thermal Analysis (DTA) techniques for appropriate characterization of the distinct thermal events occurring during synthesis. All the compounds crystallize in cubic fluorite structure, as indicated by X-ray diffraction studie. The microstructure of oxides synthesized by sol-gel showed porosity that increased with the lanthanum La3+ contents compared to hydrothermal method which gives a single crystal oxide.

Keywords: oxide, hydrothermal, rare earth, solubility, sol-gel, ternary mixture

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643 Sustainable Underground Structures Through Soil-Driven Bio-Protection of Concrete

Authors: Abdurahim Abogdera, Omar Hamza, David Elliott

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The soil bacteria can be affected by some factors such as pH, calcium ions and Electrical conductivity. Fresh concrete has high pH value, which is between 11 and 13 and these values will be prevented the bacteria to produce CO₂ to participate with Calcium ions that released from the concrete to get calcite. In this study we replaced 15% and 25% of cement with Fly ash as the fly ash reduce the value of the pH at the concrete. The main goal of this study was investigated whether bacteria can be used on the soil rather than in the concrete to avoid the challenges and limitations of containing bacteria inside the concrete. This was achieved by incubating cracked cement mortar specimens into fully saturated sterilized and non-sterilized soil. The crack sealing developed in the specimens during the incubation period in both soil conditions were evaluated and compared. Visual inspection, water absorption test, scanning electron microscopy (SEM), and Energy Dispersive X-ray (EDX) were conducted to evaluate the healing process.

Keywords: pH, calcium ions, MICP, salinity

Procedia PDF Downloads 83
642 Combining Shallow and Deep Unsupervised Machine Learning Techniques to Detect Bad Actors in Complex Datasets

Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

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Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

Procedia PDF Downloads 65
641 Supply Chain Fit and Firm Performance: The Role of the Environment

Authors: David Gligor

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The purpose of this study was to build on Fisher's (1997) seminal article. First, it sought to determine how companies can achieve supply chain fit (i.e., match between the products' characteristics and the underlying supply chain design). Second, it attempted to develop a better understanding of how environmental conditions impact the relationship between supply chain fit and performance. The findings indicate that firm supply chain agility allows organizations to quickly adjust the structure of their supply chains and therefore, achieve supply chain fit. In addition, archival and survey data were used to explore the moderating effects of six environmental uncertainty dimensions: munificence, market dynamism, technological dynamism, technical complexity, product diversity, and geographic dispersion. All environmental variables, except technological dynamism, were found to impact the relationship between supply chain fit and firm performance.

Keywords: supply chain fit, environmental uncertainty, supply chain agility, management engineering

Procedia PDF Downloads 561
640 The New Propensity Score Method and Assessment of Propensity Score: A Simulation Study

Authors: Azam Najafkouchak, David Todem, Dorothy Pathak, Pramod Pathak, Joseph Gardiner

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Propensity score (PS) methods have recently become the standard analysis tool for causal inference in observational studies where exposure is not randomly assigned. Thus, confounding can impact the estimation of treatment effect on the outcome. Due to the dangers of discretizing continuous variables, the focus of this paper will be on how the variation in cut-points or boundaries will affect the average treatment effect utilizing the stratification of the PS method. In this study, we will develop a new methodology to improve the efficiency of the PS analysis through stratification and simulation study. We will also explore the property of empirical distribution of average treatment effect theoretically, including asymptotic distribution, variance estimation and 95% confident Intervals.

Keywords: propensity score, stratification, emprical distribution, average treatment effect

Procedia PDF Downloads 66
639 Developments in Corporate Governance: The Case of Vietnam

Authors: Lien T. H. Tran, David A. Holloway

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Corporate governance practices have changed significantly across the world in the past three decades. Spectacular corporate failures during this period have acted as a catalyst for the development of codes and guidelines that have resulted in the global acceptance of a ‘best practice’ model. This study assesses the relevance of such a ‘one size fits all model’ for the developing nation state of Vietnam. The findings of this analytical paper is that there are three key elements (government, international institutions and the nature of business) that are pertinent and central to corporate governance developments in the country. We also find that the quality of corporate governance in Vietnam is at a medium level when compared to international practices. Vietnam still has a long way to go to construct and embed effective corporate governance policies and practices and promote ethical business behaviours and sound decision making at board level.

Keywords: corporate governance, government, international institutions, public companies, Vietnam

Procedia PDF Downloads 319
638 Mutual Coupling Reduction between Patch Antenna Array Elements Using Metamaterial Z Shaped Resonators

Authors: Oossama Tabbabi, Mondher Labidi, Fethi Choubani, J. David

Abstract:

Modern wireless communication systems require compact design, low cost and simple structure antennas to insure reliability, agility, and high efficiency characteristics. This paper presents a microstrip antenna array designed for 8 GHz applications. To reduce the mutual coupling effects, a Z shape metamaterial structure was imprinted in the microstrip antenna array composed of two elements. Simulation results show the improvement of mutual coupling by adding Z shape metamaterial structure to the antenna substrate. The proposed structure reduces mutual coupling by 19 dB. The simulation has been performed by using HFSS simulator.

Keywords: antenna array, compact design, modern wireless communication, mutual coupling effects

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637 Value Relevance of Accounting Information: Empirical Evidence from China

Authors: Ying Guo, Miaochan Li, David Yang, Xiao-Yan Li

Abstract:

This paper examines the relevance of accounting information to stock prices at different periods using manufacturing companies listed in China’s Growth Enterprise Market (GEM). We find that both the average stock price at fiscal year-end and the average stock price one month after fiscal year-end are more relevant to the accounting information than the closing stock price four months after fiscal year-end. This implies that Chinese stock markets react before the public disclosure of accounting information, which may be due to information leak before official announcements. Our findings confirm that accounting information is relevant to stock prices for Chinese listed manufacturing companies, which is a critical question to answer for investors who have interest in Chinese companies.

Keywords: accounting information, response time, value relevance, stock price

Procedia PDF Downloads 52