Search results for: face sketch image retrieval
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5590

Search results for: face sketch image retrieval

2080 Improving Decision-Making in Multi-Project Environments within Organizational Information Systems Using Blockchain Technology

Authors: Seyed Hossein Iranmanesh, Hassan Nouri, Seyed Reza Iranmanesh

Abstract:

In the dynamic and complex landscape of today’s business, organizations often face challenges in impactful decision-making across multi-project settings. To efficiently allocate resources, coordinate tasks, and optimize project outcomes, establishing robust decision-making processes is essential. Furthermore, the increasing importance of information systems and their integration within organizational workflows introduces an additional layer of complexity. This research proposes the use of blockchain technology as a suitable solution to enhance decision-making in multi-project environments, particularly within the realm of information systems. The conceptual framework in this study comprises four independent variables and one dependent variable. The identified independent variables for the targeted research include: Blockchain Layer in Integrated Systems, Quality of Generated Information ,User Satisfaction with Integrated Systems and Utilization of Integrated Systems. The project’s performance, considered as the dependent variable and moderated by organizational policies and procedures, reflects the impact of blockchain technology adoption on organizational effectiveness1. The results highlight the significant influence of blockchain implementation on organizational performance.

Keywords: multi-project environments, decision support systems, information systems, blockchain technology, decentralized systems.

Procedia PDF Downloads 52
2079 The Use of Remote Sensing in the Study of Vegetation Jebel Boutaleb, Setif, Algeria

Authors: Khaled Missaoui, Amina Beldjazia, Rachid Gharzouli, Yamna Djellouli

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Optical remote sensing makes use of visible, near infrared and short-wave infrared sensors to form images of the earth's surface by detecting the solar radiation reflected from targets on the ground. Different materials reflect and absorb differently at different wavelengths. Thus, the targets can be differentiated by their spectral reflectance signatures in the remotely sensed images. In this work, we are interested to study the distribution of vegetation in the massif forest of Boutaleb (North East of Algeria) which suffered between 1998 and 1999 very large fires. In this case, we use remote sensing with Landsat images from two dates (1984 and 2000) to see the results of these fires. Vegetation has a unique spectral signature which enables it to be distinguished readily from other types of land cover in an optical/near-infrared image. Normalized Difference Vegetation Index (NDVI) is calculated with ENVI 4.7 from Band 3 and 4. The results showed a very important floristic diversity in this forest. The comparison of NDVI from the two dates confirms that there is a decrease of the density of vegetation in this area due to repeated fires.

Keywords: remote sensing, boutaleb, diversity, forest

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2078 Movement of the Viscous Elastic Fixed Vertically Located Cylinder in Liquid with the Free Surface Under the Influence of Waves

Authors: T. J. Hasanova, C. N. Imamalieva

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The problem about the movement of the rigid cylinder keeping the vertical position under the influence of running superficial waves in a liquid is considered. The indignation of a falling wave caused by the presence of the cylinder which moves is thus considered. Special decomposition on a falling harmonious wave is used. The problem dares an operational method. For a finding of the original decision, Considering that the image denominator represents a tabular function, Voltaire's integrated equation of the first sort which dares a numerical method is used. Cylinder movement in the continuous environment under the influence of waves is considered in work. Problems are solved by an operational method, thus originals of required functions are looked for by the numerical definition of poles of combinations of transcendental functions and calculation of not own integrals. Using specificity of a task below, Decisions are under construction the numerical solution of the integrated equation of Volter of the first sort that does not create computing problems of the complex roots of transcendental functions connected with search.

Keywords: rigid cylinder, linear interpolation, fluctuations, Voltaire's integrated equation, harmonious wave

Procedia PDF Downloads 316
2077 Advanced Analytical Competency Is Necessary for Strategic Leadership to Achieve High-Quality Decision-Making

Authors: Amal Mohammed Alqahatni

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This paper is a non-empirical analysis of existing literature on digital leadership competency, data-driven organizations, and dealing with AI technology (big data). This paper will provide insights into the importance of developing the leader’s analytical skills and style to be more effective for high-quality decision-making in a data-driven organization and achieve creativity during the organization's transformation to be digitalized. Despite the enormous potential that big data has, there are not enough experts in the field. Many organizations faced an issue with leadership style, which was considered an obstacle to organizational improvement. It investigates the obstacles to leadership style in this context and the challenges leaders face in coaching and development. The leader's lack of analytical skill with AI technology, such as big data tools, was noticed, as was the lack of understanding of the value of that data, resulting in poor communication with others, especially in meetings when the decision should be made. By acknowledging the different dynamics of work competency and organizational structure and culture, organizations can make the necessary adjustments to best support their leaders. This paper reviews prior research studies and applies what is known to assist with current obstacles. This paper addresses how analytical leadership will assist in overcoming challenges in a data-driven organization's work environment.

Keywords: digital leadership, big data, leadership style, digital leadership challenge

Procedia PDF Downloads 64
2076 Hard Coatings Characterization Based on Chromium Nitrides: Applications for Wood Machining

Authors: B. Chemani, H. Aknouche, A. Zerizer, R. Marchal

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The phenomena occurring during machining are related to the internal friction of the material that deforms and the friction the flake on the rake face of tool. Various researches have been conducted to improve the wear resistance of the tool by thin film deposition. This work aims to present an experimental approach related to wood machining technique to evaluate the wear for the case of ripping Aleppo pine, a species well established in the Mediterranean in general and in Algeria in particular. The study will be done on tungsten carbide cutting tools widely used in woodworking and coated with chrome nitride (CrN) and Chromium Nitride enriched Aluminium (CrAlN) with percentage different of aluminum sputtered through frame magnetron mark Nordiko 3500. The deposition conditions are already optimized by previous studies. The wear tests were performed in the laboratory of ENSAM Cluny (France) on a numerical control ripper of recordi type. This comparative study of the behavior of tools, coated and uncoated, showed that the addition of the aluminum chromium nitride films does not improve the tool ability to resist abrasive wear that is predominant when ripping the Aleppo pine. By against the aluminum addition improves the crystallization of chromium nitride films.

Keywords: Aleppo pine, PVD, coatings, CrAlN, wear

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2075 Immersive Block Scheduling in Higher Education: A Case Study in Curriculum Reform and Increased Student Success

Authors: Thomas Roche, Erica Wilson, Elizabeth Goode

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Universities across the globe are considering how to effect meaningful change in their higher education (HE) delivery in the face of increasingly diverse student cohorts and shifting student learning preferences. This paper reports on a descriptive case study of whole-of-institution curriculum reform at one regional Australian university, where more traditional 13-week semesters were replaced with a 6-week immersive block model drawing on active learning pedagogy. Based on a synthesis of literature in best practice HE pedagogy and principles, the case study draws on student performance data and senior management staff interviews (N = 5) to outline the key changes necessary for successful HE transformation to deliver increased student pass rates and retention. The findings from this case study indicate that an institutional transformation to an immersive block model requires both a considered change in institutional policy and process as well as the appropriate resourcing of roles, governance committees, technical solutions, and, importantly, communities of practice. Implications for practice at higher education institutions considering reforming their curriculum model are also discussed.

Keywords: student retention, immersive scheduling, block model, curriculum reform, active learning, higher education pedagogy, higher education policy

Procedia PDF Downloads 66
2074 Jungle Justice on Emotional Health Challenges among Lagosians

Authors: Aaron Akinloye

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This research examined the influence of jungle justice as it affects the emotional health challenges among residents in Lagos metropolitan city. Descriptive survey research design was used along with the questionnaire as research instrument. Population for the study comprised residents in Yaba and Shomolu Communities of Lagos State, Nigeria. Accidental sampling technique was used to sample 300 Residents. Self-developed questionnaire was used to obtain data on the variables under investigation. Research instrument was validated following the face, content, and construct validation of the instrument. Thereafter, the reliability coefficient yielded 0.84. It is therefore concluded and recommended that; there is a significant influence of jungle justice on trauma among residents- df (298) t= 2.33, p< 0.05; there is a significant influence of jungle justice on pressure among residents- df (298) t= 2.16, p< 0.05: there is a significant influence of jungle justice on fear among residents- df (298) t= 2.20, p< 0.05; there is a significant influence of jungle justice on depression among residents- df (298) t= 2.14, p< 0.05. Recommendations were made that; there should be deliberate effort to implement comprehensive awareness campaigns to educate the residents on the detrimental effects of jungle justice on individuals and the community members as a whole; there should be an improvement in the effectiveness and efficiency of the existing law enforcement agencies in Lagos metropolitan city; development and implementation of support systems for victims of jungle justice, which include trauma, counselling, mental health services, and rehabilitation programmes; there should be proper review and revision of the legal framework to address the issue of jungle justice effectively.

Keywords: jungle justice, emotional health, depression, fear

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2073 A Review of Different Studies on Hidden Markov Models for Multi-Temporal Satellite Images: Stationarity and Non-Stationarity Issues

Authors: Ali Ben Abbes, Imed Riadh Farah

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Due to the considerable advances in Multi-Temporal Satellite Images (MTSI), remote sensing application became more accurate. Recently, many advances in modeling MTSI are developed using various models. The purpose of this article is to present an overview of studies using Hidden Markov Model (HMM). First of all, we provide a background of using HMM and their applications in this context. A comparison of the different works is discussed, and possible areas and challenges are highlighted. Secondly, we discussed the difference on vegetation monitoring as well as urban growth. Nevertheless, most research efforts have been used only stationary data. From another point of view, in this paper, we describe a new non-stationarity HMM, that is defined with a set of parts of the time series e.g. seasonal, trend and random. In addition, a new approach giving more accurate results and improve the applicability of the HMM in modeling a non-stationary data series. In order to assess the performance of the HMM, different experiments are carried out using Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI time series of the northwestern region of Tunisia and Landsat time series of tres Cantos-Madrid in Spain.

Keywords: multi-temporal satellite image, HMM , nonstationarity, vegetation, urban

Procedia PDF Downloads 349
2072 Vibration-Based Data-Driven Model for Road Health Monitoring

Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

Procedia PDF Downloads 81
2071 Flood Monitoring in the Vietnamese Mekong Delta Using Sentinel-1 SAR with Global Flood Mapper

Authors: Ahmed S. Afifi, Ahmed Magdy

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Satellite monitoring is an essential tool to study, understand, and map large-scale environmental changes that affect humans, climate, and biodiversity. The Sentinel-1 Synthetic Aperture Radar (SAR) instrument provides a high collection of data in all-weather, short revisit time, and high spatial resolution that can be used effectively in flood management. Floods occur when an overflow of water submerges dry land that requires to be distinguished from flooded areas. In this study, we use global flood mapper (GFM), a new google earth engine application that allows users to quickly map floods using Sentinel-1 SAR. The GFM enables the users to adjust manually the flood map parameters, e.g., the threshold for Z-value for VV and VH bands and the elevation and slope mask threshold. The composite R:G:B image results by coupling the bands of Sentinel-1 (VH:VV:VH) reduces false classification to a large extent compared to using one separate band (e.g., VH polarization band). The flood mapping algorithm in the GFM and the Otsu thresholding are compared with Sentinel-2 optical data. And the results show that the GFM algorithm can overcome the misclassification of a flooded area in An Giang, Vietnam.

Keywords: SAR backscattering, Sentinel-1, flood mapping, disaster

Procedia PDF Downloads 100
2070 New Insights Into Fog Role In Atmospheric Deposition Using Satellite Images

Authors: Suruchi

Abstract:

This study aims to examine the spatial and temporal patterns of fog occurrences across Czech Republic. It utilizes satellite imagery and other data sources to achieve this goal. The main objective is to understand the role of fog in atmospheric deposition processes and its potential impact on the environment and ecosystems. Through satellite image analysis, the study will identify and categorize different types of fog, including radiation fog, orographic fog, and mountain fog. Fog detection algorithms and cloud type products will be evaluated to assess the frequency and distribution of fog events throughout the Czech Republic. Furthermore, the regions covered by fog will be classified based on their fog type and associated pollution levels. This will provide insights into the variability in fog characteristics and its implications for atmospheric deposition. Spatial analysis techniques will be used to pinpoint areas prone to frequent fog events and evaluate their pollution levels. Statistical methods will be employed to analyze patterns in fog occurrence over time and its connection with environmental factors. The ultimate goal of this research is to offer fresh perspectives on fog's role in atmospheric deposition processes, enhancing our understanding of its environmental significance and informing future research and environmental management initiatives.

Keywords: pollution, GIS, FOG, satellie, atmospheric deposition

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2069 Multimodal Direct Neural Network Positron Emission Tomography Reconstruction

Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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2068 Interest Charges and Sustainability Challenges: The Case of OECD Countries

Authors: Zapji Ymele Aime Philombe

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Servicing public debt is a significant budgetary burden in the sense that the payment of interest charges is a liability on the balance sheet of the public budget and affects fiscal policy. Interest charges can sometimes become a burden if they crowd out private activities. In order to analyse and understand the determinants of the debt burden and its impact on the sustainability of public finances, the present work focuses on OECD countries. It is noted from the literature that the factors that determine interest charges are macroeconomic (inflation, GDP growth and interest rates) and public finances (primary balance and public debt). After analysing a panel of 33 OECD countries and using ordinary least squares (OLS), we find that public debt, inflation and long-term interest rates are positively correlated with interest charges. An increase in any of these variables leads to an increase in debt charges. On the other hand, a growth in GDP is negatively associated with interest charges. Indeed, an increase in GDP generates enough revenue to meet the repayment of debt charges. According to the empirical analysis, we can say that, despite the large and growing debt-to-GDP ratio of major OECD countries, interest charges are not a threat to the sustainability of public finances. However, it is important for these countries to reduce the ratio of public debt to GDP because, in the face of the many challenges (health, aging population, etc.) that are looming on the horizon, an increase in interest rates could bring with it considerable burdens that would threaten the budgetary balance of these states.

Keywords: interests charges, public debt, sustainability, interest rates

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2067 Trade-Offs between Verb Frequency and Syntactic Complexity in Children with Developmental Language Disorder

Authors: Pui I. Chao, Shanju Lin

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Purpose: Children with developmental language disorder (DLD) have persistent language difficulties and often face great challenges when demands are high. The aim of this study was to investigate whether verb frequency would trade-off with syntactic complexity when they talk. Method: Forty-five children with DLD, 45 chronological age matches with TD (AGE), and 45 MLU-matches with TD (MLU) who were Mandarin speakers were selected from the previous study. Language samples were collected under three contexts: conversation about children’s family and school, story retelling, and free play. MLU, verb density, utterance length difference, verb density difference, and average verb frequency were calculated and further analyzed by ANOVAs. Results: Children with DLD and their MLU matches produced shorter utterances and used fewer verbs in expressions than the AGE matches. Compared to their AGE matches, the DLD group used more verbs and verbs with lower frequency in shorter utterances but used fewer verbs and verbs with higher frequency in longer utterances. Conclusion: Mandarin-speaking children with DLD showed difficulties in verb usage and were more vulnerable to trade-offs than their age-matched peers in utterances with high demand. As a result, task demand should be taken into account as speech-language pathologists assess whether children with DLD have adequate abilities in verb usage.

Keywords: developmental language disorder, syntactic complexity, trade-offs, verb frequency

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2066 Rethinking the Concept of Classroom Management during COVID-19 Times: An EFL Perspective

Authors: Hadjer Chellia

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In the light of the recent global pandemic, different issues in educational research seem to invite careful considerations. Following this perspective, this study sets out to question the concept of classroom management in an EFL higher education context during Covid-19. In order to gain an in-depth understanding of their experiences, 6 EFL teachers from different Algerian universities took part in semi-structured interviews. The main emerging themes revealed that EFL teachers have different pedagogical practices in relation to classroom management during the global crisis than those of normal times. In relation to flexible education theory, the teachers’ experiences suggest flexible classroom management during Covid-19; flexibility in the teaching methods, approach and design, flexibility in time, flexibility in space and pace (speed), flexibility in assessment modes and flexibility in coping with students’ well-being. The flexibility awareness helps them to develop readiness towards the future, mainly in terms of maintaining an appropriate pedagogy to face the future crisis. In terms of theoretical concepts, working on classroom management under unusual circumstances in relation to flexible education helped come out with the concept of flexible classroom management (FCM) and virtual classroom management (VCM). It is then important for educators and researchers to rethink different pedagogical concepts and mind a careful application in the case of unusual times.

Keywords: Covid-19, EFL educators, flexible classroom management, flexible education, virtual classroom management

Procedia PDF Downloads 153
2065 Personas Help Understand Users’ Needs, Goals and Desires in an Online Institutional Repository

Authors: Maha ALjohani, James Blustein

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Communicating users' needs, goals and problems help designers and developers overcome challenges faced by end users. Personas are used to represent end users’ needs. In our research, creating personas allowed the following questions to be answered: Who are the potential user groups? What do they want to achieve by using the service? What are the problems that users face? What should the service provide to them? To develop realistic personas, we conducted a focus group discussion with undergraduate and graduate students and also interviewed a university librarian. The personas were created to help evaluating the Institutional Repository that is based on the DSpace system. The profiles helped to communicate users' needs, abilities, tasks, and problems, and the task scenarios used in the heuristic evaluation were based on these personas. Four personas resulted of a focus group discussion with undergraduate and graduate students and from interviewing a university librarian. We then used these personas to create focused task-scenarios for a heuristic evaluation on the system interface to ensure that it met users' needs, goals, problems and desires. In this paper, we present the process that we used to create the personas that led to devise the task scenarios used in the heuristic evaluation as a follow up study of the DSpace university repository.

Keywords: heuristic evaluation, institutional repositories, user experience, human computer interaction, user profiles, personas, task scenarios, heuristics

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2064 Assessing the Impact of Pharmacist-Led Medication Therapy Management on Treatment Adherence and Clinical Outcomes in Cancer Patients: A Prospective Intervention Study

Authors: Omer Ibrahim Abdallh Omer

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Cancer patients often face complex medication regimens, leading to challenges in treatment adherence and clinical outcomes. Pharmacist-led medication therapy management (MTM) has emerged as a potential solution to optimize medication use and improve patient outcomes in oncology settings. In this prospective intervention study, we aimed to evaluate the impact of pharmacist-led MTM on treatment adherence and clinical outcomes among cancer patients. Participants were randomized to receive either pharmacist-led MTM or standard care, with assessments conducted at baseline and follow-up visits. Pharmacist interventions included medication reconciliation, adherence counseling, and personalized care plans. Our findings reveal that pharmacist-led MTM significantly improved medication adherence rates and clinical outcomes compared to standard care. Patients receiving pharmacist interventions reported higher satisfaction levels and perceived value in pharmacist involvement in their cancer care. These results underscore the critical role of pharmacists in optimizing medication therapy and enhancing patient-centered care in oncology settings. Integration of pharmacist-led MTM into routine cancer care pathways holds promise for improving treatment outcomes and quality of life for cancer patients.

Keywords: cancer, medications adherence, medication therapy management, pharmacist

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2063 Development and in vitro Characterization of Loteprednol Etabonate-Loaded Polymeric Nanoparticles for Ocular Delivery

Authors: Abhishek Kumar Sah, Preeti K. Suresh

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Effective drug delivery to the eye is a massive challenge, due to complicated physiological ocular barriers, rapid washout by tear and nasolachrymal drainage. Thus, most of the conventional ophthalmic formulations face the problem of low ocular bioavailability. Ophthalmic drug therapy can be improved by enhancing the precorneal drug retention along with improved drug penetration. The aim of the present investigation was to develop and evaluate a biodegradable polymer poly (D, L-lactide-co-glycolide) (PLGA) coated nanoparticulate carrier of loteprednol etabonate. PLGA nanoparticles were prepared by modified emulsification/solvent diffusion method using high-speed homogenizer followed by sonication. The nanoparticles were characterized for various parameters such as particle size, zeta potential, polydispersity index, X-ray powder diffraction (XRD), Transmission electron microscopy (TEM), in vitro drug release profile and stability. The prepared nanocarriers displayed mean particle size in the range of 271.7 to 424.4 nm, with zeta potential less than –10 mV. In vitro release in simulated tear fluid (STF) nanocarrier showed an extended release profile of loteprednol etabonate. TEM confirmed the spherical morphology and smooth surface of the particles. All the prepared formulations were found to be stable at varying temperatures.

Keywords: drug delivery, ocular delivery, polymeric nanoparticles, loteprednol etabonate

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2062 Cognitive Development Theories as Determinant of Children's Brand Recall and Ad Recognition: An Indian Perspective

Authors: Ruchika Sharma

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In the past decade, there has been an explosion of research that has examined children’s understanding of TV advertisements and its persuasive intent, socialization of child consumer and child psychology. However, it is evident from the literature review that no studies in this area have covered advertising messages and its impact on children’s brand recall and ad recognition. Copywriters use various creative devices to lure the consumers and very impressionable consumers such as children face far more drastic effects of these creative ways of persuasion. On the basis of Piaget’s theory of cognitive development as a theoretical basis for predicting/understanding children’s response and understanding, a quasi-experiment was carried out for the study, that manipulated measurement timing and advertising messages (familiar vs. unfamiliar) keeping gender and age group as two prominent factors. This study also examines children’s understanding of Advertisements and its elements, predominantly - Language, keeping in view Fishbein’s model. Study revealed significant associations between above mentioned factors and children’s brand recall and ad identification. Further, to test the reliability of the findings on larger sample, bootstrap simulation technique was used. The simulation results are in accordance with the findings of experiment, suggesting that the conclusions obtained from the study can be generalized for entire children’s (as consumers) market in India.

Keywords: advertising, brand recall, cognitive development, preferences

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2061 Clinical Factors of Quality Switched Ruby Laser Therapy for Lentigo Depigmentation

Authors: SunWoo Lee, TaeBum Lee, YoonHwa Park, YooJeong Kim

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Solar lentigines appear predominantly on chronically sun-exposed areas of skin, such as the face and the back of the hands. Among the several ways to lentigines treatment, quality-switched lasers are well-known effective treatment for removing solar lentigines. The present pilot study was therefore designed to assess the efficacy of quality-switched ruby laser treatment of such lentigines compare between pretreatment and posttreatment of skin brightness. Twenty-two adults with chronic sun-damaged skin (mean age 52.8 years, range 37–74 years) were treated at the Korean site. A 694 nm Q-switched ruby laser was used, with the energy density set from 1.4 to 12.5 J/cm2, to treat solar lentigines. Average brightness of skin color before ruby laser treatment was 137.3 and its skin color was brightened after ruby laser treatment by 150.5. Also, standard deviation of skin color was decreased from 17.8 to 16.4. Regarding the multivariate model, age and energy were identified as significant factors for skin color brightness change in lentigo depigmentation by ruby laser treatment. Their respective odds ratios were 1.082 (95% CI, 1.007–1.163), and 1.431 (95% CI, 1.051–1.946). Lentigo depigmentation treatment using ruby lasers resulted in a high performance in skin color brightness. Among the relative factors involve with ruby laser treatment, age and energy were the most effective factors which skin color change to brighter than pretreatment.

Keywords: depigmentation, lentigine, quality switched ruby laser, skin color

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2060 Potential Determinants of Research Output: Comparing Economics and Business

Authors: Osiris Jorge Parcero, Néstor Gandelman, Flavia Roldán, Josef Montag

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This paper uses cross-country unbalanced panel data of up to 146 countries over the period 1996 to 2015 to be the first study to identify potential determinants of a country’s relative research output in Economics versus Business. More generally, it is also one of the first studies comparing Economics and Business. The results show that better policy-related data availability, higher income inequality, and lower ethnic fractionalization relatively favor economics. The findings are robust to two alternative fixed effects specifications, three alternative definitions of economics and business, two alternative measures of research output (publications and citations), and the inclusion of meaningful control variables. To the best of our knowledge, our paper is also the first to demonstrate the importance of policy-related data as drivers of economic research. Our regressions show that the availability of this type of data is the single most important factor associated with the prevalence of economics over business as a research domain. Thus, our work has policy implications, as the availability of policy-related data is partially under policy control. Moreover, it has implications for students, professionals, universities, university departments, and research-funding agencies that face choices between profiles oriented toward economics and those oriented toward business. Finally, the conclusions show potential lines for further research.

Keywords: research output, publication performance, bibliometrics, economics, business, policy-related data

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2059 Emotion Recognition Using Artificial Intelligence

Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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2058 The Socio-Culturals Factors Hindering Female Sport Participation, in the Centre for Biokinetics, Recreation and Sport Science, University of Venda

Authors: P. Mambanga, Goon, L. O. Amusa

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The purpose of the study was to investigate the socio-cultural factors hindering sport participation among female students in the Centre for Biokinetics, Recreation and Sport Science, University of Venda. A descriptive survey of 100 female student selected by simple random sampling was used and utilises the close ended questionnaire designed in a likert format was use for data collection. Face and content validity was employed in which the supervisor went through the instrument and correct and accept it thus checking the validity of the instrument. The test-retest approach was used to test the reliability of the instrument. Ethical considerations were ensured and confidentiality respected. Data was collected and presented in tables and results interpreted. Chi square which is a measure of non-parametric investigation was employed in order to analyse the observed and expected scores, with the probability value was set at 0.05 levels of significance on a two-tailed test of the hypotheses formulated for the study. Findings of the study established significant socio-cultural factors that hinder female sport participation among female students in the Centre for Biokinetics, Recreation and Sport Science. The study concluded that the low level participation of female students at the University of Venda might be as a result of socio-cultural factors.

Keywords: female students, sport participation, University of Venda, biokinetic

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2057 Scientific Linux Cluster for BIG-DATA Analysis (SLBD): A Case of Fayoum University

Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

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2056 Multimodal Biometric Cryptography Based Authentication in Cloud Environment to Enhance Information Security

Authors: D. Pugazhenthi, B. Sree Vidya

Abstract:

Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

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2055 Language Rights and the Challenge of National Integration: The Nigerian Experience

Authors: Odewumi Olatunde, Adegun Sunday

Abstract:

Linguistic diversity is seen to complicate attempts to build a stable and cohesive political community. Hence, the challenge of integration is enormous in a multi-ethno-lingual country like Nigeria. In the same vein, justification for minority language rights claims in relation to broader political theories of justice, freedom and democracy cannot be ignored. It is in the light of the fore-going that this paper explores Nigeria’s experiments at language policy and planning(LPP) and the long drawn agitations for self-determination and linguistic freedom by the minority ethnic groups in the polity which has been exacerbated by the National Policy on Education language provisions. The paper succinctly reviews Nigeria’s LPP efforts and its attendant theater of conflicts; explores international attempts at evolving normative principles of freedom and equality for language policy and finally evaluates the position of the Nigerian LPP in the light of evolving international conventions. On this premise, it is concluded that giving a conscientious and honest implementation of the Nigerian language provisions as assessed from their face validity, the nation’s efforts could be exonerated from running afoul of any known civilized values and best practices. It is, therefore, recommended that an effectual and consistent commitment to implementation driven by a renewed political will is what is required for the nation to succeed in this direction.

Keywords: integration, rights, challenge, conventions, policy

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2054 The Use of YouTube and Its Relation to Changing the Kuwaiti Children’s Social Values from Parents’ Perspectives: Field Study

Authors: Laila Alkhayat

Abstract:

In this study, the researcher explored the positive and negative effects of children watching YouTube on changing social values from the perspective of parents in Kuwait. This study also explored whether any correlation exists between changed values from watching YouTube and the following variables: relationship with a child, social situation, school level, gender, and age. The researcher collected data from 286 questionnaires distributed randomly to parents in Kuwait. The results of the study show that parents face many disadvantages when dealing with children watching YouTube, such as children spending too much time in front of screens, inability to organize bedtime, and children’s social isolation. However, the researcher found some positives come from watching YouTube, such as learning new information, enabling children to search for new information, and introducing children to the culture of their society and other cultures around them. Moreover, this study found that boys are more likely to have negative viewing habits than girls. Given the results, this study shows that the biggest impact on social values from children watching YouTube is that they are preoccupied with watching YouTube and they waste time, which makes them feel disturbed, and this affects the value of time management and delays children’s sleeping times. This study concludes that watching YouTube simultaneously has negative and positive effects on changing social values, but it plays a negative role in changing social values of children from the parents’ perspective.

Keywords: YouTube, children, social value, social media effects

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2053 Challenges and Problems of the Implementation of the Individual's Right to a Safe and Clean Environment

Authors: Dalia Perkumiene

Abstract:

The process of globalization has several unforeseen negative effects on the quality of the environment, including increased pollution, climate change, and the depletion and destruction of natural resources. The impact of these processes makes it difficult to guarantee citizens' rights to a clean environment, and complex legal solutions are needed to implement this right. In order to implement human rights in a clean and safe environment, international legal documents and court rulings are analyzed. It is important to find a balance between the legal context: the right to a clean environment and environmental challenges such as climate change and global warming. Research Methods: The following methods were used in this study: analytical, analysis, and synthesis of scientific literature and legal documents, comparative analysis of legal acts, and generalization. Major Findings: It is difficult to implement the right to a clean, safe and sustainable environment. The successful implementation of this right depends on the application of various complex ideas and rational, not only legal solutions. Legislative measures aim to maximize the implementation of citizens' rights in the face of climate change and other environmental challenges. This area remains problematic, especially in international law. Concluding Statement: The right to a clean environment should allow a person to live in a harmonious system, where environmental factors do not pose a risk to human health and well-being.

Keywords: clean and safe and clean environmen, environmen, persons’ rights, right to a clean and safe and clean environment

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2052 Computer-Integrated Surgery of the Human Brain, New Possibilities

Authors: Ugo Galvanetto, Pirto G. Pavan, Mirco Zaccariotto

Abstract:

The discipline of Computer-integrated surgery (CIS) will provide equipment able to improve the efficiency of healthcare systems and, which is more important, clinical results. Surgeons and machines will cooperate in new ways that will extend surgeons’ ability to train, plan and carry out surgery. Patient specific CIS of the brain requires several steps: 1 - Fast generation of brain models. Based on image recognition of MR images and equipped with artificial intelligence, image recognition techniques should differentiate among all brain tissues and segment them. After that, automatic mesh generation should create the mathematical model of the brain in which the various tissues (white matter, grey matter, cerebrospinal fluid …) are clearly located in the correct positions. 2 – Reliable and fast simulation of the surgical process. Computational mechanics will be the crucial aspect of the entire procedure. New algorithms will be used to simulate the mechanical behaviour of cutting through cerebral tissues. 3 – Real time provision of visual and haptic feedback A sophisticated human-machine interface based on ergonomics and psychology will provide the feedback to the surgeon. The present work will address in particular point 2. Modelling the cutting of soft tissue in a structure as complex as the human brain is an extremely challenging problem in computational mechanics. The finite element method (FEM), that accurately represents complex geometries and accounts for material and geometrical nonlinearities, is the most used computational tool to simulate the mechanical response of soft tissues. However, the main drawback of FEM lies in the mechanics theory on which it is based, classical continuum Mechanics, which assumes matter is a continuum with no discontinuity. FEM must resort to complex tools such as pre-defined cohesive zones, external phase-field variables, and demanding remeshing techniques to include discontinuities. However, all approaches to equip FEM computational methods with the capability to describe material separation, such as interface elements with cohesive zone models, X-FEM, element erosion, phase-field, have some drawbacks that make them unsuitable for surgery simulation. Interface elements require a-priori knowledge of crack paths. The use of XFEM in 3D is cumbersome. Element erosion does not conserve mass. The Phase Field approach adopts a diffusive crack model instead of describing true tissue separation typical of surgical procedures. Modelling discontinuities, so difficult when using computational approaches based on classical continuum Mechanics, is instead easy for novel computational methods based on Peridynamics (PD). PD is a non-local theory of mechanics formulated with no use of spatial derivatives. Its governing equations are valid at points or surfaces of discontinuity, and it is, therefore especially suited to describe crack propagation and fragmentation problems. Moreover, PD does not require any criterium to decide the direction of crack propagation or the conditions for crack branching or coalescence; in the PD-based computational methods, cracks develop spontaneously in the way which is the most convenient from an energy point of view. Therefore, in PD computational methods, crack propagation in 3D is as easy as it is in 2D, with a remarkable advantage with respect to all other computational techniques.

Keywords: computational mechanics, peridynamics, finite element, biomechanics

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2051 Impact of Advertisement on Audience Retention of YouTube Comedy Skits – The Most Watched Content on YouTube in Lagos, Nigeria

Authors: Igbozuruike Chigozie Jude, Agwu Agwu Ejem

Abstract:

This study investigated that advertisement has an impact on audience retention on YouTube Comedy skits, which is the most watched content on YouTube in Lagos, Nigeria. The main objective was to determine if the advertisements affect the average number of times they spend watching YouTube comedy skits. The study was anchored on Festinger's (1952) cognitive dissonance theory. The research method for this exercise was a survey to get responses from people in Lagos state on how they react to the advertisements they face when watching YouTube comedy skits in Lagos state. The sample size derived from the Krejcie and Morgan (1970) Table was 384 YouTube users. The instrument that was used to gather data was a questionnaire. The findings showed that the adverts have far-reaching exposure by the target audience, but most of the audience perceived them to be intrusive. It was also found that there is not enough evidence to infer that advertisement is indeed impacting audience retention on YouTube comedy skits in Lagos, Nigeria. The reason is that, for a majority of the audience, adverts do not essentially affect their retention on those skits, but for a considerable percentage (34%), these adverts do break their concentration and affect how much time they end up spending on the YouTube comedy skits. It was recommended that, among others, there should be regular monitoring and adaptation of YouTube advertisements to the audience preferences and behaviors of the audience. Insights on changes or trends in audience preferences can be gained through surveys.

Keywords: advertisement, audience, YouTube, comedy skits, Lagos Nigeria

Procedia PDF Downloads 76