Search results for: trends visualization

Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Kamal Kumar Tanti, Nayan Moni Saikia, Markynti Swer

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This study aims to investigate and analyse the trends and variability of rainfall in Shillong and its nearby areas, located in Meghalaya hills of North-East India; which is geographically a neighbouring area to the wettest places of the Earth, i.e., Cherrapunji and Mawsynram. The analysis of variability and trends to annual, seasonal, monthly and daily rainfall was carried out, using the data collected from the IMD station at Shillong; thereby attempting to highlight whether rainfall in Shillong area has been increasing or decreasing over the years. Rainfall variability coefficient is utilized to compare the current rainfall trend of the area with its past rainfall trends. The present study also aims to analyse the frequency of occurrence of extreme rainfall events over the region. These studies will help us to establish a correlation between the current rainfall trend and climate change scenario of the study area.

Keywords: trends and variability of rainfall, annual, seasonal, monthly and daily rainfall, rainfall variability coefficient, extreme rainfall events, climate change, Shillong, Cherrapunji, Mawsynram

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Authors: Thomas Lauer

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The paper aims to give an overview of change management research by using bibliometric methodology. Based on research papers of the last decade, which are listed on Research Gate, a multidimensional categorization is done. Considering categories like topic (e.g., success factors), industry, or research methodology, the development of the discipline is traced and, in a second step, confronted with external developments of the business environment, such as climate change, gen Z or COVID, to name a few. Based on these findings, a final evaluation concerning the thematical fit of previous research topics is also made, as well as a preview of likely future trends in change management sciences.

Keywords: change management, bibliometrics, scientific trends, research topics

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Authors: Moulana Mohammed

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Topic models are widely used in building clusters of documents for more than a decade, yet problems occurring in choosing optimal number of topics. The main problem is the lack of a stable metric of the quality of topics obtained during the construction of topic models. The authors analyzed from previous works, most of the models used in determining the number of topics are non-parametric and quality of topics determined by using perplexity and coherence measures and concluded that they are not applicable in solving this problem. In this paper, we used the parametric method, which is an extension of the traditional topic model with visual access tendency for visualization of the number of topics (clusters) to complement clustering and to choose optimal number of topics based on results of cluster validity indices. Developed hybrid topic models are demonstrated with different Twitter datasets on various topics in obtaining the optimal number of topics and in measuring the quality of clusters. The experimental results showed that the Visual Non-negative Matrix Factorization (VNMF) topic model performs well in determining the optimal number of topics with interactive visualization and in performance measure of the quality of clusters with validity indices.

Keywords: interactive visualization, visual mon-negative matrix factorization model, optimal number of topics, cluster validity indices, Twitter data clustering

Procedia PDF Downloads 133

Authors: Xiaochun Huang, Xuejun Zhao, Yun Zou, Feiyu Yang, Wenbin Liu, Nan Deng, Ming Zhang, Nengbin Cai

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A simple device termed infrared radiation (IR) was developed for rapid visualization of sweat fingerprints deposit on paper with blue light (450 nm, 11 W). In this approach, IR serves as the pretreatment device before the sweat fingerprints was illuminated by blue light. An annular blue light source was adopted for visualizing latent sweat fingerprints. Sample fingerprints were examined under various conditions after deposition, and experimental results indicate that the recovery rate of the latent sweat fingerprints is in the range of 50%-100% without chemical treatments. A mechanism for the observed visibility is proposed based on transportation and re-impregnation of fluorescer in paper at the region of water. And further exploratory experimental results gave the full support to the visible mechanism. Therefore, such a method as IR-pretreated in detecting latent fingerprints may be better for examination in the case where biological information of samples is needed for consequent testing.

Keywords: forensic science, visualization, infrared radiation, blue light, latent sweat fingerprints, detection

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Authors: Nemi Bhattarai

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In recent years, there has been a rapid increase in the use of Unmanned Aerial Vehicle (UAVs) in search and rescue (SAR) operations, disaster management, and many more areas where information about the location of human beings are important. This research will primarily focus on the use of optical and thermal camera via UAV platform in real-time detection, localization, and visualization of human beings on GIS. This research will be beneficial in disaster management search of lost humans in wilderness or difficult terrain, detecting abnormal human behaviors in border or security tight areas, studying distribution of people at night, counting people density in crowd, manage people flow during evacuation, planning provisions in areas with high human density and many more.

Keywords: UAV, human detection, real-time, localization, visualization, haar-like, GIS, thermal sensor

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Authors: Satoshi Nishimura

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Although much information has been garnered from the genomes of humans and mice, it remains difficult to extend that information to explain physiological and pathological phenomena. This is because the processes underlying life are by nature stochastic and fluctuate with time. Thus, we developed novel "in vivo molecular imaging" method based on single and two-photon microscopy. We visualized and analyzed many life phenomena, including common adult diseases. We integrated the knowledge obtained, and established new models that will serve as the basis for new minimally invasive therapeutic approaches.

Keywords: two photon microscope, intravital visualization, thrombus, artery

Procedia PDF Downloads 371

Authors: D. F. Carigma, E. Cruzado, M. J. Hagos, K. Perater, D. Ramos, R. Navarro, R. Galingan

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Korean culture disseminates rapidly across the globe. The young generation is highly engaged in Korean trends, such as Korean pop music, dramas or movies, fashion, food, and beauty standards. With the use of media, the effects of Korean trends may have resulted in the effects of media on people and society, such as addiction, perceptual influence, psychological effect, time consumption, and impulsive spending. The study aimed to determine whether there is a relationship between variable factors affecting the student's academic performance. The proponents used a quantitative approach in the 388 participants at the Technological Institute of the Philippines. This study shows that the Korean trends and the effect of media on people and society correlated to its variable factors. Moreover, this study may help future research in colleges and universities in the Philippines about how the students in higher education who engage in Korean trends affect their behavior and academic performance.

Keywords: academic performance, addiction, effect of media on people and society, Korean trend, perceptual influence, psychological effect

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Authors: Duygu Dere, Mert Ergeneci, Kaan Gokcesu

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Google Trends data has gained increasing popularity in the applications of behavioral finance, decision science and risk management. Because of Google’s wide range of use, the Trends statistics provide significant information about the investor sentiment and intention, which can be used as decisive factors for corporate and risk management fields. However, an anomaly, a significant increase or decrease, in a certain query cannot be detected by the state of the art applications of computation due to the random baseline noise of the Trends data, which is modelled as an Additive white Gaussian noise (AWGN). Since through time, the baseline noise power shows a gradual change an adaptive thresholding method is required to track and learn the baseline noise for a correct classification. To this end, we introduce an online method to classify meaningful deviations in Google Trends data. Through extensive experiments, we demonstrate that our method can successfully classify various anomalies for plenty of different data.

Keywords: adaptive data processing, behavioral finance , convex optimization, online learning, soft minimum thresholding

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Authors: Muhammad Usman

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Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

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Authors: Sean McCarthy, Patrice M. Ludwig, Will Watson

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This exploratory case study explores the deployment of Social Network Analysis (SNA) in mapping community assets in an interdisciplinary, undergraduate, team-taught course focused on income insecure populations in a rural area in the US. Specifically, it analyzes how students were taught to collect data on community assets and to visualize the connections between those assets using Kumu, an SNA data visualization tool. Further, the case study shows how social network data was also collected about student teams via their written communications in Slack, an enterprise messaging tool, which enabled instructors to manage and guide student research activity throughout the semester. The discussion presents how SNA methods can simultaneously inform both community-based research and social innovation pedagogy through the use of data visualization and collaboration-focused communication technologies.

Keywords: social innovation, social network analysis, pedagogy, problem-based learning, data visualization, information communication technologies

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Authors: Ashraf M. Ward, Ruban S. Yu

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Data consisting of 2757 records from tow Holstein herds made between 2000 and 2010 were used to examine environmental factors affecting age at first calving (AFC) and calving intervals (CI) and consequently estimate genetic and phenotypic parameters and trends. The overall means and standard errors for AFC and CI were 39.4 ± 7.2 months and 487.5 ± 151.6 days respectively. The respective heritability estimates were 0.091 ± 0.05 and 0.044 ± 0.032, while the repeatability estimate for CI was 0.096 ± 0.001. The genetic trends for CI and AFC were -0.6 d/yr and -0.01 mo/yr respectively and were both significant (P < 0.001), indicating a decrease in mean breeding value over the study period. Phenotypic trends were -0.31 mo/yr and -0.35 d/yr for AFC and CI respectively though non-significant (P > 0.05). The low heritability for CI and AFC indicated that temporary environmental influences were much greater than genetic influences or permanent environmental influences on these traits.

Keywords: Holstein, reproductive, genetic parameters, heritability

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Authors: Francisca Onaolapo Oladipo, Peter Afam Ugwu

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Records of user activities which are valuable for forensic investigation purposes are provided by web browsers -these records in most cases are not in visual formats that are easily understood, thereby requiring some extra processes. This paper describes the implementation of a software tool for client-side web history visualization providing suitable forensic evidence for investigative purposes. Visual C#, Perl and gnuplot were deployed on Windows Operating System (OS) environment to implement the system and the resulting tool parses and transforms a web browser history into a visual format that enables an investigator to quickly and efficiently explore, understand, and interpret the user online activities in the context of a specific investigation. The system was tested using two forensic cases: the client-side web history files generated by Mozilla Firefox browser was extracted using MozillaHistoryView utility, then parsed and visualized using bar and stacked column charts. From the visual representation, results of user web activities across various productive and non-productive websites were obtained.

Keywords: history, forensics, visualization, web activities

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Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

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Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization

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Authors: Hyo Lim Kang, Tae An Kim, Seung Ho Han

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A 3-way reversing valve has been used in automotive washing machines to remove remaining oil and dirt on machined engine and transmission blocks. It provides rapid and accurate changes of water flow direction without any precise control device. However, due to its complicated bottom-plug shape, a cavitation occurs in a wide range of the bottom-plug in a downstream. In this study, the cavitation index and POC (percent of cavitation) were used to evaluate quantitatively the cavitation phenomena occurring at the bottom-plug. An optimal shape design was carried out via parametric study for geometries of the bottom-plug, in which a simple CAE-model was used in order to avoid time-consuming CFD analysis and hard to achieve convergence. To verify the results of numerical analysis, a flow visualization test was carried out using a test specimen with a transparent acryl pipe according to ISA-RP75.23. The flow characteristics such as the cavitation occurring in the downstream were investigated by using a flow test equipment with valve and pump including a flow control system and high-speed camera.

Keywords: cavitation, flow visualization test, optimal shape design, percent of cavitation, reversing valve

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Authors: Mohd Hazwan bin Yusof, Hiroshi Katanoda

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In order to clarify the structure of the cold flow discharged from the vortex tube (VT), the pressure of the cold flow was measured, and a simple flow visualization technique using a 0.75 mm-diameter needle and an oily paint is made to study the reverse flow at the cold exit. It is clear that a negative pressure and positive pressure region exist at a certain pressure and cold fraction area, and that a reverse flow is observed in the negative pressure region.

Keywords: flow visualization, pressure measurement, reverse flow, vortex tube

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Authors: Emmanuel Bintaayi Jeil, Kabila Abass, David Forkuor, Divine Odame Appiah

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In Ghana, the nature and trends of climate change-related research are not clear. This study synthesises various research evidence on climate change published in Ghana between 1999 and 2018. Data for the review was gathered using a set of search words performed in Google Scholar, Web of Science, ProQuest, and ScienceDirect following scoping review guidelines stipulated by the Joanna Briggs Institute. Data were analysed using a scoping review. A total of 114 eligible articles were identified and included in the synthesis. Findings revealed that research on climate change in Ghana is growing steadily, and most of the studies were conducted in 2018. Trends in climate change research in Ghana relate to agriculture and development. There is a lack of attention on climate change issues related to women, water availability and management, and health. Future research should therefore focus on addressing these issues in addition to alternative livelihoods for vulnerable people.

Keywords: scoping review, trends, climate change, research, Ghana

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Authors: Hayoung Cho, Gabi Cho

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In response to the continuing increase of demands for living environment safety, the Korean government has established and implemented various environmental health policies and set a high priority to the related R&D. However, the level of related technologies such as environmental risk assessment are still relatively low, and there is a need for detailed investment strategies in the field of environmental health research. As scientific research papers can give valuable implications on the development of a certain field, this study analyzed the global research trends in the field of environmental health over the past 10 years (2005~2015). Research topics were extracted from abstracts of the collected SCI papers using topic modeling to study the changes in research trends and discover emerging technologies. The method of topic modeling can improve the traditional bibliometric approach and provide a more comprehensive review of the global research development. The results of this study are expected to help provide insights for effective policy making and R&D investment direction.

Keywords: environmental health, paper analysis, research trends, topic modeling

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Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava

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Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.

Keywords: microarray analysis, R language, affymetrix visualization, bioconductor

Procedia PDF Downloads 478

Authors: Peng Chun-Yi, Chen Wei-Hsuan, Ueng Shyh-Kuang

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Jose Gois

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The paper presents the development of a porous porcelain frappe with thermochromic visualization for port wines, having as a partner the Institute of Vinhos do Douro and Porto. This ceramic frappe is intended to promote the cooling and maintenance of the temperature of port wines through porous ceramic materials, consisting of a porcelain composite with sawdust addition, so as to contain, on the one hand, the similar cooling properties of the terracotta and, on the other, the resistance of materials such as porcelain. The application of the thermochromic element makes it possible to see if the wine is at optimal service temperatures, allowing users to drink the wine in the ideal conditions and contributing to more efficient maintenance of the service.

Keywords: design, frappe, porcelain, porous, thermochromic

Procedia PDF Downloads 134

Authors: Agarana Michael C., Akinlabi Esther T., Pule Kholopane

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Innovation in manufacturing process technologies and associated product design affects the prospects for manufacturing today and in near future. In this study some theoretical methods, useful as tools in advanced manufacturing, are considered. In particular, some basic Mathematical, Operational Research, Heuristic, and Statistical techniques are discussed. These techniques/methods are very handy in many areas of advanced manufacturing processes, including process planning optimization, modelling and analysis. Generally the production rate requires the application of Mathematical methods. The Emerging Trends Processes in Advanced Manufacturing can be enhanced by using Mathematical Modelling and Optimization techniques.

Keywords: mathematical modelling, optimization, emerging trends, advanced manufacturing

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Authors: Samba Lamine Cisse, Cheick Oumar Tangara, Seynabou Sissoko, Mahamadou Diakite, Seydou Doumbia

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Introduction: Over the past two decades, the world has been constantly changing, with new trends in project management. These trends are transforming the methods and priorities of research project management. They include the rise of digital technologies, multidisciplinary, open science, and the pressure for high-impact results. Managers, therefore, find themselves at a crossroads between the challenges and opportunities offered by these new trends. This paper aims to identify the challenges and opportunities they face while proposing strategies for effectively navigating this dynamic context. Methodology: This is a qualitative study based on an analysis of the challenges and opportunities facing the University Clinical Research Center in terms of new technologies and project management methods. This blended approach provides an overview of emerging trends and practices. Results: This article shows how research managers can turn new research trends in their favor and how they can adapt to the changes they face to optimize the productivity of research teams while ensuring the quality and ethics of the work. It also explores the importance of developing skills in data management, international collaboration, and innovation management. Finally, it proposes strategies for responding effectively to the challenges posed by these new trends while strengthening the position of research managers as essential facilitators of scientific progress. Conclusion: Navigating this changing landscape requires research managers to be highly flexible and able to anticipate the realities of their institution. By adopting modern project management methodologies and cultivating a culture of innovation, they can turn challenges into opportunities and propel research toward new horizons. This paper provides a strategic framework for overcoming current obstacles and capitalizing on future developments in research.

Keywords: new trends, research management, opportunities, challenges

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Authors: E. Kharaishvili, M. Chavleishvili, M. Natsvaladze

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The article presents the trends in Georgian wine market development and evaluates the competitive advantages of Georgia to enter the wine market based on its customs, traditions and historical practices combined with modern technologies. In order to analyze the supply of wine, dynamics of vineyard land area and grape varieties are discussed, trends in wine production are presented, trends in export and import are evaluated, local wine market, its micro and macro environments are studied and analyzed based on the interviews with experts and analysis of initial recording materials. For strengthening its position on the international market, the level of competitiveness of Georgian wine is defined, which is evaluated by “ex-ante” and “ex-post” methods, as well as by four basic and two additional factors of the Porter’s diamond method; potential advantages and disadvantages of Georgian wine are revealed. Conclusions are made by identifying the factors that hinder the development of Georgian wine market. Based on the conclusions, relevant recommendations are developed.

Keywords: Georgian wine market, competitive advantage, bio wine, export-import, Porter's diamond model

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Authors: Dena Alhaloul

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The Middle East and North Africa (MENA) region is characterized by diverse cultures, economies, and social structures. Fertility rates in MENA have seen significant changes over time, with variations among countries and subregions. Understanding fertility patterns in this region is essential due to its impact on demographic dynamics, healthcare, labor markets, and social policies. Rising or declining fertility rates have far-reaching consequences for the region's socioeconomic development. The main thrust of this study is to comprehensively examine fertility rates in the Middle East and North Africa (MENA) region. It aims to understand the distribution, determinants, and temporal trends of fertility rates in MENA countries. The study seeks to provide insights into the factors influencing fertility decisions, assess how fertility rates have evolved over time, and potentially develop statistical models to characterize these trends. As for the methodology of the study, the study uses descriptive statistics to summarize and visualize fertility rate data. It also uses regression analyses to identify determinants of fertility rates as well as statistical modeling to characterize temporal trends in fertility rates. The conclusion of this study The research will contribute to a deeper understanding of fertility dynamics in the MENA region, shedding light on the distribution of fertility rates, their determinants, and historical trends.

Keywords: fertility, distribution, modeling, regression

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Authors: Sara Rankohi, Lloyd Waugh

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Construction sites are information saturated. Digitalization is hitting construction sites to meet the incredible demand of knowledge sharing and information documentations. From flying drones, 3D Lasers scanners, pocket mobile applications, to augmented reality glasses and smart helmet, visualization technologies help real-time information imposed straight onto construction professional’s field of vision. Although these technologies are very applicable and can have the direct impact on project cost and productivity, experience shows that only a minority of construction professionals quickly adapt themselves to benefit from them in practice. The majority of construction managers still tend to apply traditional construction management methods. This paper investigates a) current applications of visualization technologies in construction projects management, b) the direct effect of these technologies on productivity improvement and cost saving of a multi-residential building project via a case study on Mac Taggart Senior Care project located in Edmonton, Alberta. The research shows the imaged based technologies have a direct impact on improving project productivity and cost savings.

Keywords: image-based technologies, project management, cost, productivity improvement

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Authors: Yang L. Frances

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Women's health and wellness has been becoming an increasingly important issue in mass media in the age of globalization. In this context, the current research focuses on comparing the construction of healthy bodies in women's health magazines of China and U.S. Trends Health in China and Women's Health in U.S are chosen. Textual analysis and in depth interviews are combined to examine how the healthy bodies are constructed in two magazines through discursive strategies. The interviews with the Deputy Editorial Director, Creative Director and Senior Visual Design of two magazines are undertaken to make the further comparisons. In both Trends Health and Women's Health, women's subjectivity is realized in the construction of ideal healthy body; nevertheless in the process of constructing healthy body, the disciplinary practices imposed on women's bodies are different in two magazines. This paper argues that women's health magazines in both China and America provide an alternative discourse to speak their voices on the one hand, but on the other hand, Women's Health and Trends Health construct the healthy body through disparate disciplinary practices because of the different socio-cultural contexts in two societies.

Keywords: healthy body, women's health magazines, Foucault, textual analysis

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Authors: M. T. Islam, S. H. Shakif, R. Hasan, S. H. Kobi

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Investigation of rainfall trends is crucial considering climate change, food security, and the economy of a particular region. This research aims to study seasonal and annual precipitation trends and their abrupt changes over time in the south-central climatic zone of Bangladesh using monthly time series data of 50 years (1970-2019). A trend-free pre-whitening method has been employed to make necessary adjustments for autocorrelations in the rainfall data. Trends in rainfall and their intensity have been observed using the non-parametric Mann-Kendall test and Theil-Sen estimator. Significant changes and fluctuation points in the data series have been detected using the sequential Mann-Kendall test at the 95% confidence limit. The study findings show that most of the rainfall stations in the study area have a decreasing precipitation pattern throughout all seasons. The maximum decline in the rainfall intensity has been found for the Tangail station (-8.24 mm/year) during monsoon. Madaripur and Chandpur stations have shown slight positive trends in post-monsoon rainfall. In terms of annual precipitation, a negative rainfall pattern has been identified in each station, with a maximum decrement (-) of 14.48 mm/year at Chandpur. However, all the trends are statistically non-significant within the 95% confidence interval, and their monotonic association with time ranges from very weak to weak. From the sequential Mann-Kendall test, the year of changing points for annual and seasonal downward precipitation trends occur mostly after the 90s for Dhaka and Barishal stations. For Chandpur, the fluctuation points arrive after the mid-70s in most cases.

Keywords: trend analysis, Mann-Kendall test, Theil-Sen estimator, sequential Mann-Kendall test, rainfall trend

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Authors: Lim Yi Wei

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Structural equation modelling (SEM) is well-known in statistics due to its flexibility and accessibility. It plays an increasingly important role in the development of the education field. The number of research publications using SEM in education has increased in recent decades. However, there is a lack of scientific review conducted on SEM in education. The purpose of this study is to investigate research trends related to SEM in education. The researcher will use Vosviewer, Datawrapper, and SciMAT to do bibliometric analysis on 5549 papers that have been published in the Scopus database in the last five years. The result will show the publication trends of the most cited documents, the top contributing authors, countries, institutions, and journals in the research field. It will also look at how they relate to each other in terms of co-citation, collaboration, and co-occurrence of keywords. This study will benefit researchers and practitioners by identifying research trends and the current state of SEM in education.

Keywords: structural equation modeling, education, bibliometric analysis, Vosviewer

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Authors: Kwang Chun, John Kemeny

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Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

Procedia PDF Downloads 170