Search results for: learning Maltese as a second language
Commenced in January 2007
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Edition: International
Paper Count: 9684

Search results for: learning Maltese as a second language

1704 Challenges of Technical and Engineering Students in the Application of Scientific Cancer Knowledge to Preserve the Future Generation in Sub-Saharan Africa

Authors: K. Shaloom Mbambu, M. Pascal Tshimbalanga, K. Ruth Mutala, K. Roger Kabuya, N. Dieudonné Kabeya, Y. L. Kabeya Mukeba

Abstract:

In this article, the authors examine the even more worrying situation of girls in sub-Saharan Africa. Two-girls on five are private of Global Education, which represents a real loss to the development of communities and countries. Cultural traditions, poverty, violence, early and forced marriages, early pregnancies, and many other gender inequalities were the causes of this cancer development. Namely, "it is no more efficient development tool that is educating girls." The non-schooling of girls and their lack of supervision by liberal professions have serious consequences for the life of each of them. To improve the conditions of their inferior status, girls to men introduce poverty and health risks. Raising awareness among parents and communities on the importance of girls' education, improving children's access to school, girl-boy equality with their rights, creating income, and generating activities for girls, girls, and girls learning of liberal trades to make them self-sufficient. Organizations such as the United Nations Organization can save the children. ASEAD and the AEDA group are predicting the impact of this cancer on the development of a nation's future generation must be preserved.

Keywords: young girl, Sub-Saharan Africa, higher and vocational education, development, society, environment

Procedia PDF Downloads 257
1703 Children Protection in the Digital Space

Authors: Beverly Komen

Abstract:

Online crimes have been on the rise in the recent days, especially with the hit of the covid-19 pandemic. The coronavirus pandemic has led to an unprecedented rise in screen time, this means more families are relying on technology and digital solutions to keep children learning, spending more time on the virtual platforms can leave children vulnerable to online abuse and exploitation. With ease access of affordable phones, internet, and increased online activities, all children are at risk of being abused online hence making the digital space unsafe for children. With these increased use of technology and its accessibility, children are at risk of facing challenges such as access to inappropriate content, online grooming, identity theft, cyber bullying, among other risks. The big question is; as we enjoy the benefits brought in by technology, how do we ensure that our children are save in this digital space? With the analysis of the current trends, there is a gap in knowledge on people’s understanding on child online protection and safety measures when using the digital space. A survey conducted among 50 parents in Nairobi in Kenya indicated that there is a gap in knowledge on online protection of children and over 50 % of the participants shared that for sure they have no idea on how to protect children online. This paper seeks to address the concept of child protection in the digital space and come up with viable solutions in protecting children from online vices.

Keywords: child protection, digital space, online risks, online grooming, cyber bulying, online child sexual exploitation, and abuse

Procedia PDF Downloads 187
1702 Students’ Perceptions of Formative Assessment Feedback: A Case Study for Undergraduate Students in Bahrain

Authors: Hasan Husain Ali Abdulnabi

Abstract:

Formative assessment feedback is increasingly practiced in higher education. Instructors allocate great time and effort to provide assessment feedback. However, educators are not sure about students’ perceptions, understanding and respond to the feedback given, as very limited research have been done about what students do with feedback and whether if they understand it. This study aims to explore students’ conceptions and perceptions of formative assessment feedback through questionnaire and focus group interviews. One hundred eighty undergraduate students doing different courses filled the questionnaire, and ten focus group discussions were conducted. Basic descriptive and content analyses were used to analyze students’ responses to the questionnaire, while grounded theory with open coding was used to analyze the focus group interviews. The study revealed that most students believe assessment feedback is helpful to improve their academic performance, and they take time to read, think and discuss their feedback. Also, the study shows most students understand the feedback given. However, students expressed that most of the written feedback given are too general, and they prefer individual oral feedback as it can lead to better understanding on how what and where to improve. The study concluded that students believe formative assessment feedback is valuable, students have reasonable understanding and respond to the feedback provided. However, this practice could be improved by requesting lecturers to make more specific feedback and communicate with students on the way of interpreting and using assessment feedback as a part of the learning and teaching process.

Keywords: assessment, feedback, formative, undergraduate, higher education

Procedia PDF Downloads 89
1701 Charter versus District Schools and Student Achievement: Implications for School Leaders

Authors: Kara Rosenblatt, Kevin Badgett, James Eldridge

Abstract:

There is a preponderance of information regarding the overall effectiveness of charter schools and their ability to increase academic achievement compared to traditional district schools. Most research on the topic is focused on comparing long and short-term outcomes, academic achievement in mathematics and reading, and locale (i.e., urban, v. Rural). While the lingering unanswered questions regarding effectiveness continue to loom for school leaders, data on charter schools suggests that enrollment increases by 10% annually and that charter schools educate more than 2 million U.S. students across 40 states each year. Given the increasing share of U.S. students educated in charter schools, it is important to better understand possible differences in student achievement defined in multiple ways for students in charter schools and for those in Independent School District (ISD) settings in the state of Texas. Data were retrieved from the Texas Education Agency’s (TEA) repository that includes data organized annually and available on the TEA website. Specific data points and definitions of achievement were based on characterizations of achievement found in the relevant literature. Specific data points include but were not limited to graduation rate, student performance on standardized testing, and teacher-related factors such as experience and longevity in the district. Initial findings indicate some similarities with the current literature on long-term student achievement in English/Language Arts; however, the findings differ substantially from other recent research related to long-term student achievement in social studies. There are a number of interesting findings also related to differences between achievement for students in charters and ISDs and within different types of charter schools in Texas. In addition to findings, implications for leadership in different settings will be explored.

Keywords: charter schools, ISDs, student achievement, implications for PK-12 school leadership

Procedia PDF Downloads 130
1700 An Informetrics Analysis of Research on Phishing in Scopus and Web of Science Databases from 2012 to 2021

Authors: Nkosingiphile Mbusozayo Zungu

Abstract:

The purpose of the current study is to adopt informetrics methods to analyse the research on phishing from 2012 to 2021 in three selected databases in order to contribute to global cybersecurity through impactful research. The study follows a quantitative research methodology. We opted for the positivist epistemology and objectivist ontology. The analysis focuses on: (i) the productivity of individual authors, institutions, and countries; (ii) the research contributions, using co-authorship as a measure of collaboration; (iii) the altmetrics of selected research contributions; (iv) the citation patterns and research impact of research on phishing; and (v) research contributions by keywords, to discover the concepts that are related to phishing. The preliminary findings favour developed countries in terms of quantity and quality of research in the domain. There are unique research trends and patterns in the developing countries, including those in Africa, that provide opportunities for research development in the domain in the region. This study explores an important research domain by using unexplored method in the region. The study supports the SDG Agenda 2030, such as ending abuse, exploitation, trafficking, and all other forms of violence and torture of children through the use of cyberspace (SDG 16). Further, the results from this study can inform research, teaching, and learning largely in Africa. Invariably, the study contributes to cybersecurity awareness that will mitigate cybersecurity threats against vulnerable communities.

Keywords: phishing, cybersecurity, informetrics, information security

Procedia PDF Downloads 115
1699 Understanding the Semantic Network of Tourism Studies in Taiwan by Using Bibliometrics Analysis

Authors: Chun-Min Lin, Yuh-Jen Wu, Ching-Ting Chung

Abstract:

The formulation of tourism policies requires objective academic research and evidence as support, especially research from local academia. Taiwan is a small island, and its economic growth relies heavily on tourism revenue. Taiwanese government has been devoting to the promotion of the tourism industry over the past few decades. Scientific research outcomes by Taiwanese scholars may and will help lay the foundations for drafting future tourism policy by the government. In this study, a total of 120 full journal articles published between 2008 and 2016 from the Journal of Tourism and Leisure Studies (JTSL) were examined to explore the scientific research trend of tourism study in Taiwan. JTSL is one of the most important Taiwanese journals in the tourism discipline which focuses on tourism-related issues and uses traditional Chinese as the study language. The method of co-word analysis from bibliometrics approaches was employed for semantic analysis in this study. When analyzing Chinese words and phrases, word segmentation analysis is a crucial step. It must be carried out initially and precisely in order to obtain meaningful word or word chunks for further frequency calculation. A word segmentation system basing on N-gram algorithm was developed in this study to conduct semantic analysis, and 100 groups of meaningful phrases with the highest recurrent rates were located. Subsequently, co-word analysis was employed for semantic classification. The results showed that the themes of tourism research in Taiwan in recent years cover the scope of tourism education, environmental protection, hotel management, information technology, and senior tourism. The results can give insight on the related issues and serve as a reference for tourism-related policy making and follow-up research.

Keywords: bibliometrics, co-word analysis, word segmentation, tourism research, policy

Procedia PDF Downloads 229
1698 Compilation and Statistical Analysis of an Arabic-English Legal Corpus in Sketch Engine

Authors: C. Brierley, H. El-Farahaty, A. Farhan

Abstract:

The Leeds Parallel Corpus of Arabic-English Constitutions is a parallel corpus for the Arabic legal domain. Analysis of legal language via Corpus Linguistics techniques is an important development. In legal proceedings, a corpus-based approach to disambiguating meaning is set to replace the dictionary as an interpretative tool, and legal scholarship in the States is now attuned to the potential for Text Analytics over vast quantities of text-based legal material, following the business and medical industries. This trend is reflected in Europe: the interdisciplinary research group in Computer Assisted Legal Linguistics mines big data collections of legal and non-legal texts to analyse: legal interpretations; legal discourse; the comprehensibility of legal texts; conflict resolution; and linguistic human rights. This paper focuses on ‘dignity’ as an important aspect of the overarching concept of human rights in current constitutions across the Arab world. We have compiled a parallel, Arabic-English raw text corpus (169,861 Arabic words and 205,893 English words) from reputable websites such as the World Intellectual Property Organisation and CONSTITUTE, and uploaded and queried our corpus in Sketch Engine. Our most challenging task was sentence-level alignment of Arabic-English data. This entailed manual intervention to ensure correspondence on a one-to-many basis since Arabic sentences differ from English in length and punctuation. We have searched for morphological variants of ‘dignity’ (رامة ك, karāma) in the Arabic data and inspected their English translation equivalents. The term occurs most frequently in the Sudanese constitution (10 instances), and not at all in the constitution of Palestine. Its most frequent collocate, determined via the logDice statistic in Sketch Engine, is ‘human’ as in ‘human dignity’.

Keywords: Arabic constitution, corpus-based legal linguistics, human rights, parallel Arabic-English legal corpora

Procedia PDF Downloads 183
1697 Optimizing Electric Vehicle Charging with Charging Data Analytics

Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

Abstract:

Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

Procedia PDF Downloads 197
1696 Performance Comparison and Visualization of COMSOL Multiphysics, Matlab, and Fortran for Predicting the Reservoir Pressure on Oil Production in a Multiple Leases Reservoir with Boundary Element Method

Authors: N. Alias, W. Z. W. Muhammad, M. N. M. Ibrahim, M. Mohamed, H. F. S. Saipol, U. N. Z. Ariffin, N. A. Zakaria, M. S. Z. Suardi

Abstract:

This paper presents the performance comparison of some computation software for solving the boundary element method (BEM). BEM formulation is the numerical technique and high potential for solving the advance mathematical modeling to predict the production of oil well in arbitrarily shaped based on multiple leases reservoir. The limitation of data validation for ensuring that a program meets the accuracy of the mathematical modeling is considered as the research motivation of this paper. Thus, based on this limitation, there are three steps involved to validate the accuracy of the oil production simulation process. In the first step, identify the mathematical modeling based on partial differential equation (PDE) with Poisson-elliptic type to perform the BEM discretization. In the second step, implement the simulation of the 2D BEM discretization using COMSOL Multiphysic and MATLAB programming languages. In the last step, analyze the numerical performance indicators for both programming languages by using the validation of Fortran programming. The performance comparisons of numerical analysis are investigated in terms of percentage error, comparison graph and 2D visualization of pressure on oil production of multiple leases reservoir. According to the performance comparison, the structured programming in Fortran programming is the alternative software for implementing the accurate numerical simulation of BEM. As a conclusion, high-level language for numerical computation and numerical performance evaluation are satisfied to prove that Fortran is well suited for capturing the visualization of the production of oil well in arbitrarily shaped.

Keywords: performance comparison, 2D visualization, COMSOL multiphysic, MATLAB, Fortran, modelling and simulation, boundary element method, reservoir pressure

Procedia PDF Downloads 492
1695 Ancient Cities of Deltaic Bengal: Origin and Nature on the Riverine Bed of Ganges Valley

Authors: Sajid Bin Doza

Abstract:

A town or a city contributes a lot to human mankind. City evolves memory, ambition, frustration and achievement. The city is something that offers life, as the character of the city is. A city is having confined image to the human being. Time place and matter generate this vive, city celebrates with its inhabitant, belongs and to care for each other. Apart from all these; although city and settlements are the contentious and changing phenomenon; the origin of the city in the very delta land started with unique and strategic sequences. Religious belief, topography, availability of resource and connection with commercial hub make the potential of the settlement. Ancient cities of Bengal are not the exception from these phenomenologies. From time immemorial; Bengal is enriched with numerous cities and notorious settlements. These cities and settlements were connected with other inland ports and Bengal became an important trade route, trailed by the Riverine connections. The delta land formation is valued for its geographic situation, consequences of this position; a new story or a new conception could be found in origin of an ancient city. However, the objective of this research is to understand the origin and spirit of the ancient city of Bengal, the research would also try to unfold the authentic and rational meaning of soul of the city, this research addresses the interest to elaborate the soul of the ancient sites of Riverine Delta. As rivers used to have the common character in this very landform; river supported community generated as well. River gives people wealth, sometimes fall us in sorrow. The river provides us commerce and trading. River gives us faith and religion. All these potentials have evolved from the Riverine excel. So the research would approach thoroughly to justify the riverine value as the soul for the ancient cities of Bengal. Cartographic information and illustration would be the preferred language for this research. Preferably, the historic mapping would be the unique folio of this study.

Keywords: memory of the city, riverine network, ancient cities, cartographic mapping, settlement pattern

Procedia PDF Downloads 294
1694 Daily Stand-up Meetings - Relationships with Psychological Safety and Well-being in Teams

Authors: Sarah Rietze, Hannes Zacher

Abstract:

Daily stand-up meetings are the most commonly used method in agile teams. In daily stand-ups, team members gather to coordinate and align their efforts, typically for a predefined period of no more than 15 minutes. The primary purpose is to ask and answer the following three questions: What was accomplished yesterday? What will be done today? What obstacles are impeding my progress? Daily stand-ups aim to enhance communication, mutual understanding, and support within the team, as well as promote collective learning from mistakes through daily synchronization and transparency. The use of daily stand-ups is intended to positively influence psychological safety within teams, which is the belief that it is safe to show oneself and take personal risks. Two studies will be presented, which explore the relationships between daily stand-ups, psychological safety, and psychological well-being. In a first study, based on survey results (n = 318), we demonstrated that daily stand-ups have a positive indirect effect on job satisfaction and a negative indirect effect on turnover intention through their impact on psychological safety. In a second study, we investigate, using an experimental design, how the use of daily stand-ups in teams enhances psychological safety and well-being compared to a control group that does not use daily stand-ups. Psychological safety is considered one of the most crucial cultural factors for a sustainable, agile organization. Agile approaches, such as daily stand-ups, are a critical part of the evolving work environment and offer a proactive means to shape and foster psychological safety within teams.

Keywords: occupational wellbeing, agile work practices, psychological safety, daily stand-ups

Procedia PDF Downloads 66
1693 English Language Teaching Graduate Students' Use of Discussion Moves in Research Articles

Authors: Gamzegul Koca, Evrim Eveyik-Aydin

Abstract:

Genre and discipline-specific knowledge of academic discourse in writing has long been acknowledged as being a core skill to achieve formidable tasks that are expected of graduate students in academic settings. Genre analysis approaches can be adopted to unveil the challenges encountered in these tasks to be able to take instructional actions addressing the aspects of graduate writing that need improvement. In an attempt to find genre-specific academic writing needs of Turkish students enrolled in a graduate program in ELT, this study examines the rhetorical structure of discussion sections of research articles written during the course load stage of their graduate studies. The 35.437-word specialized corpus of graduate papers compiled for the purpose of the study includes discussions of 58 unpublished reports of empirical studies, 31 written in MA courses and 27 in Ph.D. courses by a total of 44 graduate students. The study does sentence-based move structure analysis using the framework developed by Eveyik-Aydın, Karabacak and Akyel in a corpus-based study that analyzed the discussion moves of expert writers in published articles in ELT journals indexed by Social Sciences Citation. The coding of 1577 sentences by three graders using this framework revealed that while the graduate papers included the same moves used in published articles, the rhetorical structure of MA and Ph.D. papers showed considerable differences in terms of the frequency of occurrence of main discussion moves, including interpretation of the results and drawing implications. The implications of these findings will be discussed with respect to the needs of graduate writers and the expectations of discourse community.

Keywords: discussion moves, genre-specific rhetorical structure, move analysis, research articles, the specialized corpus of graduate papers

Procedia PDF Downloads 166
1692 A Hybrid Expert System for Generating Stock Trading Signals

Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

Abstract:

In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

Procedia PDF Downloads 332
1691 The 'Plain Style' in the Theory and Practice of Project Design: Contributions to the Shaping of an Urban Image on the Waterfront Prior to the 1755 Earthquake

Authors: Armenio Lopes, Carlos Ferreira

Abstract:

In the specific context of the Iberian Union between 1580 and 1640, characteristics emerged in Portuguese architecture that stood out from the main architectural production of the period. Recognised and identified aspects that had begun making their appearance decades before (1521) became significantly more marked during the Hapsburg-Spanish occupation. Distinctive even from the imperialist language of Spain, this trend would endure even after the restoration of independence (1706), continuing through to the start of the age of absolutism. Or perhaps not. This trend, recognised as Plain Style (Kubler), associated with a certain scarcity of resources, involved a certain formal and decorative simplification, as well as a particular set of conventions that would subsequently mark the landscape. This expression could also be seen as a means of asserting a certain spirit of independence as the Iberian Union breathed its last. The image of a simple, bare-bones architecture with purer design lines is associated by various authors –most notably Kubler– with the narratives of modernism, to whose principles it is similar, in a context-specific to the period. There is a contrast with some of the exuberance of the baroque or its expression in the Manueline period, in a similar fashion to modernism's responses to nineteenth-century eclecticism. This assertion and practice of simple architecture, drafted from the interpretation of the treaties, and highlighting a certain classical inspiration, was to become a benchmark in the theory of architecture, spanning the Baroque and Mannerism, until achieving contemporary recognition within certain originality and modernity. At a time when the baroque and its scenography became generally very widespread, it is important also to recognise the role played by plain style architecture in the construction of a rather complex and contradictory waterfront landscape, featuring promises of exuberance and more discrete practices.

Keywords: Carlos Mardel, Lisbon's waterfront, plain style, urban image on the waterfront

Procedia PDF Downloads 140
1690 Self-Attention Mechanism for Target Hiding Based on Satellite Images

Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

Abstract:

Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

Procedia PDF Downloads 140
1689 The Artificial Intelligence (AI) Impact on Project Management: A Destructive or Transformative Agent

Authors: Kwame Amoah

Abstract:

Artificial intelligence (AI) has the prospect of transforming project management, significantly improving efficiency and accuracy. By automating specific tasks with defined guidelines, AI can assist project managers in making better decisions and allocating resources efficiently, with possible risk mitigation. This study explores how AI is already impacting project management and likely future AI's impact on the field. The AI's reaction has been a divided opinion; while others picture it as a destroyer of jobs, some welcome it as an innovation advocate. Both sides agree that AI will be disruptive and revolutionize PM's functions. If current research is to go by, AI or some form will replace one-third of all learning graduate PM jobs by as early as 2030. A recent survey indicates AI spending will reach $97.9 billion by the end of 2023. Considering such a profound impact, the project management profession will also see a paradigm shift driven by AI. The study examines what the project management profession will look like in the next 5-10 years after this technological disruption. The research methods incorporate existing literature, develop trend analysis, and conduct structured interviews with project management stakeholders from North America to gauge the trend. PM professionals can harness the power of AI, ensuring a smooth transition and positive outcomes. AI adoption will maximize benefits, minimize adverse consequences, and uphold ethical standards, leading to improved project performance.

Keywords: project management, disruptive teacnologies, project management function, AL applications, artificial intelligence

Procedia PDF Downloads 85
1688 Development of Prediction Models of Day-Ahead Hourly Building Electricity Consumption and Peak Power Demand Using the Machine Learning Method

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

Procedia PDF Downloads 317
1687 A Quantitative Analysis for the Correlation between Corporate Financial and Social Performance

Authors: Wafaa Salah, Mostafa A. Salama, Jane Doe

Abstract:

Recently, the corporate social performance (CSP) is not less important than the corporate financial performance (CFP). Debate still exists about the nature of the relationship between the CSP and CFP, whether it is a positive, negative or a neutral correlation. The objective of this study is to explore the relationship between corporate social responsibility (CSR) reports and CFP. The study uses the accounting-based and market-based quantitative measures to quantify the financial performance of seven organizations listed on the Egyptian Stock Exchange in 2007-2014. Then uses the information retrieval technologies to quantify the contribution of each of the three dimensions of the corporate social responsibility report (environmental, social and economic). Finally, the correlation between these two sets of variables is viewed together in a model to detect the correlations between them. This model is applied on seven firms that generate social responsibility reports. The results show a positive correlation between the Earnings per share (market based measure) and the economical dimension in the CSR report. On the other hand, total assets and property, plant and equipment (accounting-based measure) are positively correlated to the environmental and social dimensions of the CSR reports. While there is not any significant relationship between ROA, ROE, Operating income and corporate social responsibility. This study contributes to the literature by providing more clarification of the relationship between CFP and the isolated CSR activities in a developing country.

Keywords: financial, social, machine learning, corporate social performance, corporate social responsibility

Procedia PDF Downloads 312
1686 Dynamic Route Optimization in Vehicle Adhoc Networks: A Heuristics Routing Protocol

Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

Procedia PDF Downloads 180
1685 Web Data Scraping Technology Using Term Frequency Inverse Document Frequency to Enhance the Big Data Quality on Sentiment Analysis

Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

Abstract:

Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

Procedia PDF Downloads 88
1684 Embracing Complex Femininity: A Comparative Analysis of the Representation of Female Sexuality in John Webster and William Faulkner

Authors: Elisabeth Pedersen

Abstract:

Representations and interpretations of womanhood and female sexualities bring forth various questions regarding gender norms, and the implications of these norms, which are permeating and repetitive within various societies. Literature is one form of media which provides the space to represent and interpret women, their bodies, and sexualities, and also reveals the power of language as an affective and affected force. As literature allows an opportunity to explore history and the representations of gender, power dynamics, and sexuality through historical contexts, this paper uses engaged theory through a comparative analysis of two work of literature, The Duchess of Malfi by John Wester, and The Sound and the Fury by William Faulkner. These novels span across space and time, which lends to the theory that repetitive tropes of womanhood and female sexuality in literature are influenced by and have an influence on the hegemonic social order throughout history. It analyzes how the representation of the dichotomy of male chivalry and honor, and female purity are disputed and questioned when a woman is portrayed as sexually emancipated, and explores the historical context in which these works were written to examine how socioeconomic events challenged the hegemonic social order. The analysis looks at how stereotypical ideals of womanhood and manhood have damaging implications on women, as the structure of society provides more privilege and power to men than to women, thus creating a double standard for men and women in regards to sexuality, sexual expression, and rights to sexual desire. This comparative analysis reveals how strict gender norms are permeating and have negative consequences. However, re-reading stories through a critical lens can provide an opportunity to challenge the repetitive tropes of female sexuality, and thus lead to the embrace of the complexity of female sexuality and expression.

Keywords: femininity, literature, representation, sexuality

Procedia PDF Downloads 361
1683 Detecting and Thwarting Interest Flooding Attack in Information Centric Network

Authors: Vimala Rani P, Narasimha Malikarjunan, Mercy Shalinie S

Abstract:

Data Networking was brought forth as an instantiation of information-centric networking. The attackers can send a colossal number of spoofs to take hold of the Pending Interest Table (PIT) named an Interest Flooding attack (IFA) since the in- interests are recorded in the PITs of the intermediate routers until they receive corresponding Data Packets are go beyond the time limit. These attacks can be detrimental to network performance. PIT expiration rate or the Interest satisfaction rate, which cannot differentiate the IFA from attacks, is the criterion Traditional IFA detection techniques are concerned with. Threshold values can casually affect Threshold-based traditional methods. This article proposes an accurate IFA detection mechanism based on a Multiple Feature-based Extreme Learning Machine (MF-ELM). Accuracy of the attack detection can be increased by presenting the entropy of Internet names, Interest satisfaction rate and PIT usage as features extracted in the MF-ELM classifier. Furthermore, we deploy a queue-based hostile Interest prefix mitigation mechanism. The inference of this real-time test bed is that the mechanism can help the network to resist IFA with higher accuracy and efficiency.

Keywords: information-centric network, pending interest table, interest flooding attack, MF-ELM classifier, queue-based mitigation strategy

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1682 An Experiential Learning of Ontology-Based Multi-document Summarization by Removal Summarization Techniques

Authors: Pranjali Avinash Yadav-Deshmukh

Abstract:

Remarkable development of the Internet along with the new technological innovation, such as high-speed systems and affordable large storage space have led to a tremendous increase in the amount and accessibility to digital records. For any person, studying of all these data is tremendously time intensive, so there is a great need to access effective multi-document summarization (MDS) systems, which can successfully reduce details found in several records into a short, understandable summary or conclusion. For semantic representation of textual details in ontology area, as a theoretical design, our system provides a significant structure. The stability of using the ontology in fixing multi-document summarization problems in the sector of catastrophe control is finding its recommended design. Saliency ranking is usually allocated to each phrase and phrases are rated according to the ranking, then the top rated phrases are chosen as the conclusion. With regards to the conclusion quality, wide tests on a selection of media announcements are appropriate for “Jammu Kashmir Overflow in 2014” records. Ontology centered multi-document summarization methods using “NLP centered extraction” outshine other baselines. Our participation in recommended component is to implement the details removal methods (NLP) to enhance the results.

Keywords: disaster management, extraction technique, k-means, multi-document summarization, NLP, ontology, sentence extraction

Procedia PDF Downloads 388
1681 A Collection of Voices on Higher Educational Access, Quality and Equity in Africa: A Systematic Review

Authors: Araba A. Z. Osei-Tutu, Ebenezer Odame, Joseph Bawa, Samuel Amponsah

Abstract:

Education is recognized as a fundamental human right and a catalyst for development. Despite progress in the provision of higher education on the African continent, there persist challenges with the tripartite areas of access, equity and quality. Therefore, this systematic review aimed at providing a comprehensive overview of conversations and voices of scholars on these three concepts in HE in Africa. The systematic review employed a thematic analysis approach, synthesizing findings from 38 selected sources. After a critical analysis of the sources included in the systematic review, deficits in access, quality, and equity were outlined, focusing on infrastructure, regional disparities, and privatization challenges. The review also revealed the weak enforcement of quality assurance measures. Strategies for improvement, proffered by the study, include expanding public sector HE, deregulating the educational sector, promoting open and distance learning, implementing preferential admission policies, and enhancing financial aid. This research contributes valuable insights for policymakers, educators, and stakeholders, fostering a collaborative approach to address challenges and promote holistic development in African higher education.

Keywords: access, equity, quality, higher education, Africa, systematic review, strategies

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1680 The Use of Network Tool for Brain Signal Data Analysis: A Case Study with Blind and Sighted Individuals

Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

Abstract:

Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

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1679 Deep Learning Approach to Trademark Design Code Identification

Authors: Girish J. Showkatramani, Arthi M. Krishna, Sashi Nareddi, Naresh Nula, Aaron Pepe, Glen Brown, Greg Gabel, Chris Doninger

Abstract:

Trademark examination and approval is a complex process that involves analysis and review of the design components of the marks such as the visual representation as well as the textual data associated with marks such as marks' description. Currently, the process of identifying marks with similar visual representation is done manually in United States Patent and Trademark Office (USPTO) and takes a considerable amount of time. Moreover, the accuracy of these searches depends heavily on the experts determining the trademark design codes used to catalog the visual design codes in the mark. In this study, we explore several methods to automate trademark design code classification. Based on recent successes of convolutional neural networks in image classification, we have used several different convolutional neural networks such as Google’s Inception v3, Inception-ResNet-v2, and Xception net. The study also looks into other techniques to augment the results from CNNs such as using Open Source Computer Vision Library (OpenCV) to pre-process the images. This paper reports the results of the various models trained on year of annotated trademark images.

Keywords: trademark design code, convolutional neural networks, trademark image classification, trademark image search, Inception-ResNet-v2

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1678 Interlingual Melodious Constructions: Romanian Translation of References to Songs in James Joyce’s Ulysses

Authors: Andra-Iulia Ursa

Abstract:

James Joyce employs several unconventional stylistic features in this landmark novel meant to experiment with language. The episode known as “Sirens” is entirely conceived around music and linguistic structures subordinated to sound. However, the aspiration to the condition of music is reflected throughout this entire literary work, as musical effects are echoed systematically. The numerous melodies scattered across the narrative play an important role in enhancing the thoughts and feelings that pass through the minds of the characters. Often the lyrics are distorted or interweaved with other words, preoccupations or memories, intensifying the stylistic effect. The Victorian song “Love’s old sweet song” is one of the most commonly referred to and meaningful musical allusions in Ulysses, becoming a leitmotif of infidelity. The lyrics of the song “M’appari”, from the opera “Martha”, are compared to an event from Molly and Bloom’s romantic history. Moreover, repeated phrases using words from “The bloom is on the rye” or “The croppy boy” serve as glances into the minds of the characters. Therefore, the central purpose of this study is to shed light on the way musical allusions flit through the episodes from the point of view of the stream of consciousness technique and to compare and analyse how these constructions are rendered into Romanian. Mircea Ivănescu, the single Romanian translator who succeeded in carrying out the translation of the entire ‘stylistic odyssey’, received both praises and disapprovals from the critics. This paper is not meant to call forth eventual flaws of the Romanian translation, but rather to elaborate the complexity of the task. Following an attentive examination and analysis of the two texts, from the point of view of form and meaning of the references to various songs, the conclusions of this study will be able to point out the intricacies of the process of translation.

Keywords: Joyce, melodious constructions, stream of consciousness, style, translation

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1677 Elite Female Football Coaches’ Experiences and Reflections in a Male-dominated Environment: The Case of Ghana

Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

Abstract:

The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching, including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders, including Ghana Football Association (GFA), to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

Procedia PDF Downloads 70
1676 Elite Female Football Coaches’ Experiences and Reflections in a Male-Dominated Environment: The Case of Ghana

Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

Abstract:

The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders including Ghana Football Association (GFA) to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

Procedia PDF Downloads 62
1675 Transportation Mode Classification Using GPS Coordinates and Recurrent Neural Networks

Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

Abstract:

The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

Procedia PDF Downloads 138