Search results for: success metrics
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3030

Search results for: success metrics

1770 Unforeseen Inequity: Childhood Sexual Abuse in Aotearoa, New Zealand

Authors: Nicola Harrison

Abstract:

Familial childhood sexual abuse (FCSA) prevalence rates in Aotearoa, New Zealand, are amongst the highest globally, particularly in indigenous communities. However, such statistics seem incongruent with indigenous paradigms of unity, care, and connection. The inability of policymakers and mainstream service providers to acknowledge the direct links between the social contexts created by colonisation for indigenous families in Aotearoa and intergenerational FCSA has meant there has been little meaningful success in combatting this significant social problem. This research traces the conditions of intergenerational FCSA to the systemic inequalities created by colonization. Kaupapa Māori methodologies were applied to this qualitative piece of empirical research wherein 17 indigenous contributors shared their stories of FCSA. From these stories and existing literature, we can identify how the machinations of colonisation are mirrored by techniques used to perpetrate abuse. Once identified, we are then able to recommend actions for halting FCSA for future generations.

Keywords: indigenity, family violence, childhood sexual abuse, colonization

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1769 IT and Security Experts' Innovation and Investment Front for IT-Entrepreneurship in Pakistan

Authors: Ahmed Mateen, Zhu Qingsheng, Muhammad Awais, Muhammad Yahya Saeed

Abstract:

This paper targets the rising factor of entrepreneurship innovation, which lacks in Pakistan as compared to the other countries or the regions like China, India, and Malaysia, etc. This is an exploratory and explanatory study. Major aspects have identified as the direction for the policymakers while highlighting the issues in true spirit. IT needs to be considered not only as a technology but also as itself growing as a new community. IT management processes are complex and broad, so generally requires extensive attention to the collective aspects of human variables, capital and technology. In addition, projects tend to have a special set of critical success factors, and if these are processed and given attention, it will improve the chances of successful implementation. This is only possible with state of the art intelligent decision support systems and accumulating IT staff to some extent in decision processes. This paper explores this issue carefully and discusses six issues to observe the implemented strength and possible enhancement.

Keywords: security and defense forces, IT-incentives, big IT-players, IT-entrepreneurial-culture

Procedia PDF Downloads 221
1768 Transformer-Driven Multi-Category Classification for an Automated Academic Strand Recommendation Framework

Authors: Ma Cecilia Siva

Abstract:

This study introduces a Bidirectional Encoder Representations from Transformers (BERT)-based machine learning model aimed at improving educational counseling by automating the process of recommending academic strands for students. The framework is designed to streamline and enhance the strand selection process by analyzing students' profiles and suggesting suitable academic paths based on their interests, strengths, and goals. Data was gathered from a sample of 200 grade 10 students, which included personal essays and survey responses relevant to strand alignment. After thorough preprocessing, the text data was tokenized, label-encoded, and input into a fine-tuned BERT model set up for multi-label classification. The model was optimized for balanced accuracy and computational efficiency, featuring a multi-category classification layer with sigmoid activation for independent strand predictions. Performance metrics showed an F1 score of 88%, indicating a well-balanced model with precision at 80% and recall at 100%, demonstrating its effectiveness in providing reliable recommendations while reducing irrelevant strand suggestions. To facilitate practical use, the final deployment phase created a recommendation framework that processes new student data through the trained model and generates personalized academic strand suggestions. This automated recommendation system presents a scalable solution for academic guidance, potentially enhancing student satisfaction and alignment with educational objectives. The study's findings indicate that expanding the data set, integrating additional features, and refining the model iteratively could improve the framework's accuracy and broaden its applicability in various educational contexts.

Keywords: tokenized, sigmoid activation, transformer, multi category classification

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1767 Citizens’ Satisfaction Causal Factors in E-Government Services

Authors: Abdullah Alshehab

Abstract:

Governments worldwide are intensely focused on digitizing public transactions to establish reliable e-government services. The advent of new digital technologies and ongoing advancements in ICT have profoundly transformed business operations. Citizen engagement and participation in e-government services are crucial for the system's success. However, it is essential to measure and enhance citizen satisfaction levels to effectively evaluate and improve these systems. Citizen satisfaction is a key criterion that allows government institutions to assess the quality of their services. There is a strong connection between information quality, service quality, and system quality, all of which directly impact user satisfaction. Additionally, both system quality and information quality have indirect effects on citizen satisfaction. A causal map, which is a network diagram representing causes and effects, can illustrate these relationships. According to the literature, the main factors influencing citizen satisfaction are trust, reliability, citizen support, convenience, and transparency. This paper investigates the causal relationships among these factors and identifies any interrelatedness between them.

Keywords: e-government services, e-satisfaction, citizen satisfaction, causal map.

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1766 Load Forecasting in Microgrid Systems with R and Cortana Intelligence Suite

Authors: F. Lazzeri, I. Reiter

Abstract:

Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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1765 Project Progress Prediction in Software Devlopment Integrating Time Prediction Algorithms and Large Language Modeling

Authors: Dong Wu, Michael Grenn

Abstract:

Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

Procedia PDF Downloads 80
1764 The Relationship between Confidence, Accuracy, and Decision Making in a Mobile Review Program

Authors: Carla Van De Sande, Jana Vandenberg

Abstract:

Just like physical skills, cognitive skills grow rusty over time unless they are regularly used and practiced, so academic breaks can have negative consequences on student learning and success. The Keeping in School Shape (KiSS) program is an engaging, accessible, and cost-effective intervention that harnesses the benefits of retrieval practice by using technology to help students maintain proficiency over breaks from school by delivering a daily review problem via text message or email. A growth mindset is promoted through feedback messages encouraging students to try again if they get a problem wrong and to take on a challenging problem if they get a problem correct. This paper reports on the relationship between confidence, accuracy, and decision-making during the implementation of the KiSS Program at a large university during winter break for students enrolled in an engineering introductory Calculus course sequence.

Keywords: growth mindset, learning loss, on-the-go learning, retrieval practice

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1763 The Role of Brand Authenticity in Egyptian Destination Marketing

Authors: Hala Hilaly, Nermin Morsy, Jala Morsy Ibrahim

Abstract:

Brand authenticity has a significant impact on brand trust and can help grow within the markets. Consumers have become more concerned with the 'authenticity' due to the doubt of credibility of the value of mass production. This is why people prefer authentic products, which making authenticity a cornerstone of contemporary marketing and a major factor for brand success. Therefore, it is important to embrace a culture that encourages and promotes authentic values. Hence, the purpose of the research is to investigate the impact of using local products as an authentic brand on promoting Egyptian tourist destination and explore the effect of Globalized authenticity on the local product in Egypt. Results confirmed that local products provide an excellent opportunity to worldwide advertising with positive impact on promoting Egypt as tourist destination. However, number of problems are facing local products in Egypt such as imported 'Made in China' products as well as other obstacles.

Keywords: authentic brand, contemporary marketing, destination marketing, local products

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1762 Predicting Low Birth Weight Using Machine Learning: A Study on 53,637 Ethiopian Birth Data

Authors: Kehabtimer Shiferaw Kotiso, Getachew Hailemariam, Abiy Seifu Estifanos

Abstract:

Introduction: Despite the highest share of low birth weight (LBW) for neonatal mortality and morbidity, predicting births with LBW for better intervention preparation is challenging. This study aims to predict LBW using a dataset encompassing 53,637 birth cohorts collected from 36 primary hospitals across seven regions in Ethiopia from February 2022 to June 2024. Methods: We identified ten explanatory variables related to maternal and neonatal characteristics, including maternal education, age, residence, history of miscarriage or abortion, history of preterm birth, type of pregnancy, number of livebirths, number of stillbirths, antenatal care frequency, and sex of the fetus to predict LBW. Using WEKA 3.8.2, we developed and compared seven machine learning algorithms. Data preprocessing included handling missing values, outlier detection, and ensuring data integrity in birth weight records. Model performance was evaluated through metrics such as accuracy, precision, recall, F1-score, and area under the Receiver Operating Characteristic curve (ROC AUC) using 10-fold cross-validation. Results: The results demonstrated that the decision tree, J48, logistic regression, and gradient boosted trees model achieved the highest accuracy (94.5% to 94.6%) with a precision of 93.1% to 93.3%, F1-score of 92.7% to 93.1%, and ROC AUC of 71.8% to 76.6%. Conclusion: This study demonstrates the effectiveness of machine learning models in predicting LBW. The high accuracy and recall rates achieved indicate that these models can serve as valuable tools for healthcare policymakers and providers in identifying at-risk newborns and implementing timely interventions to achieve the sustainable developmental goal (SDG) related to neonatal mortality.

Keywords: low birth weight, machine learning, classification, neonatal mortality, Ethiopia

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1761 Crude Distillation Process Simulation Using Unisim Design Simulator

Authors: C. Patrascioiu, M. Jamali

Abstract:

The paper deals with the simulation of the crude distillation process using the Unisim Design simulator. The necessity of simulating this process is argued both by considerations related to the design of the crude distillation column, but also by considerations related to the design of advanced control systems. In order to use the Unisim Design simulator to simulate the crude distillation process, the identification of the simulators used in Romania and an analysis of the PRO/II, HYSYS, and Aspen HYSYS simulators were carried out. Analysis of the simulators for the crude distillation process has allowed the authors to elaborate the conclusions of the success of the crude modelling. A first aspect developed by the authors is the implementation of specific problems of petroleum liquid-vapors equilibrium using Unisim Design simulator. The second major element of the article is the development of the methodology and the elaboration of the simulation program for the crude distillation process, using Unisim Design resources. The obtained results validate the proposed methodology and will allow dynamic simulation of the process.  

Keywords: crude oil, distillation, simulation, Unisim Design, simulators

Procedia PDF Downloads 249
1760 Information Exchange Process Analysis between Authoring Design Tools and Lighting Simulation Tools

Authors: Rudan Xue, Annika Moscati, Rehel Zeleke Kebede, Peter Johansson

Abstract:

Successful buildings’ simulation and analysis inevitably require information exchange between multiple building information modeling (BIM) software. The BIM infor-mation exchange based on IFC is widely used. However, Industry Foundation Classifi-cation (IFC) files are not always reliable and information can get lost when using dif-ferent software for modeling and simulations. In this research, interviews with lighting simulation experts and a case study provided by a company producing lighting devices have been the research methods used to identify the necessary steps and data for suc-cessful information exchange between lighting simulation tools and authoring design tools. Model creation, information exchange, and model simulation have been identi-fied as key aspects for the success of information exchange. The paper concludes with recommendations for improved information exchange and more reliable simulations that take all the needed parameters into consideration.

Keywords: BIM, data exchange, interoperability issues, lighting simulations

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1759 The Impact of Shariah Non-Compliance Risk on Islamic Financial Institutions

Authors: Ibtissam Mharzi Alaoui, Camélia Sehaqui

Abstract:

The success of a bank depends upon its effective risk management. With the growing complexity and diversity of financial products and services, as well as the accelerating pace of globalization over the past decade, risk management is becoming increasingly difficult. thus, all measurement and monitoring functions must be much more vigorous, relevant and adequate. The Shariah non-compliance risk is specific aspect of Islamic finance which ipso facto, deserves particular attention. It affects the validity of all Islamic financial contracts and it turns out to be likely to result in considerable losses on the overall Islamic financial institutions (IFIs). The purpose of this paper is to review the theoretical literature on Shariah non-compliance risk in order to give a clearer understanding of its sources, causes and consequences. Our intention through this work is to bring added value to the Islamic finance industry all over the world. The findings provide a useful reference work for the Islamic banks in structuring (or restructuring) of their own system of shariah risk management and internal control.

Keywords: Shariah non-compliance, risk management, financial products, Islamic finance.

Procedia PDF Downloads 92
1758 Evaluation of IMERG Performance at Estimating the Rainfall Properties through Convective and Stratiform Rain Events in a Semi-Arid Region of Mexico

Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

Abstract:

Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

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1757 Competency Based Talent Acquisition: Concept, Practice, and Model, with Reference to Indian Industries

Authors: Manasi V. Shah

Abstract:

Organizations, in the competitive era, are participating in the competency act. They have discerned that, strategically researched and defined competencies when put up on the shelf, can help in achieving business goals. The research focuses on critical elements of competency-based talent acquisition process from practical vantage, with significant experience in a variety of business settings. The research is exploratory and descriptive in nature. The research conduct and outcome is the hinge on with reference to Indian Industries. It elaborates about the concept, practice and a brief model that human resource practitioner can use for effective talent acquisition process, which in turn would be in alignment with business performance. The research helps to present a prudent understanding of recruiting and selecting apt human capital, that can fit in a given job role and has action oriented competency based assessment approach for measuring the probable success of a job incumbent in a given job role.

Keywords: competency based talent acquisition, competency model, talent acquisition concept, talent acquisition practice

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1756 Knowing Where the Learning is a Shift from Summative to Formative Assessment

Authors: Eric Ho

Abstract:

Pedagogical approaches in Asia nowadays are imported from the West. In Confucian Heritage Culture (CHC), however, there is a dichotomy between the perceived benefits of Western pedagogies and the real classroom practices in Chinese societies. The success of Hong Kong students in large-scale international assessments has proved that both the strengths of both Western pedagogies and CHC educational approaches should be integrated for the sake of the students. University students aim to equip themselves with employability skills upon graduation. Formative assessments allow students to receive detailed, positive, and timely feedback and they can identify their strengths and weaknesses before they start working. However, there remains a question of whether university year 1 students who come from an examination-driven secondary education background are ready to respond to more formative assessments. The findings show that year 1 students are less concerned about competition in the university and more open to new teaching approaches that will allow them to improve as professionals in their major study areas.

Keywords: formative assessment, higher education, learning styles, Confucian heritage cultures

Procedia PDF Downloads 335
1755 A Comprehensive Study on Quality Assurance in Game Development

Authors: Maria Komal, Zaineb Khalil, Mehreen Sirshar

Abstract:

Due to the recent technological advancements, Games have become one of the most demanding applications. Gaming industry is rapidly growing and the key to success in this industry is the development of good quality games, which is a highly competitive issue. The ultimate goal of game developers is to provide player’s satisfaction by developing high-quality games. This research is the comprehensive survey of techniques followed by game industries to ensure games quality. After analysis of various techniques, it has been found that quality simulation according to ISO standards and play test methods are used to ensure games quality. Because game development requires cross-disciplined team, an increasing trend towards distributed game development has been observed. This paper evaluates the strengths and weaknesses of current methodologies used in game industry and draws a conclusion. We have also proposed quality parameters which can be used as a heuristic framework to identify those attributes which have high testing priorities.

Keywords: game development, computer games, video games, gaming industry, quality assurance, playability, user experience

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1754 Model-Independent Price Bounds for the Swiss Re Mortality Bond 2003

Authors: Raj Kumari Bahl, Sotirios Sabanis

Abstract:

In this paper, we are concerned with the valuation of the first Catastrophic Mortality Bond that was launched in the market namely the Swiss Re Mortality Bond 2003. This bond encapsulates the behavior of a well-defined mortality index to generate payoffs for the bondholders. Pricing this bond is a challenging task. We adapt the payoff of the terminal principal of the bond in terms of the payoff of an Asian put option and present an approach to derive model-independent bounds exploiting comonotonic theory. We invoke Jensen’s inequality for the computation of lower bounds and employ Lagrange optimization technique to achieve the upper bound. The success of these bounds is based on the availability of compatible European mortality options in the market. We carry out Monte Carlo simulations to estimate the bond price and illustrate the strength of these bounds across a variety of models. The fact that our bounds are model-independent is a crucial breakthrough in the pricing of catastrophic mortality bonds.

Keywords: mortality bond, Swiss Re Bond, mortality index, comonotonicity

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1753 Supply Chain Management in the Oil Industry: Challenges and Opportunities

Authors: Mehmood Faisal

Abstract:

In this globalization era, the supply chain management has acquired strategic importance in diverse business environments. In the current highly competitive business environment, the success of any business considerably depends on the efficiency of the supply chain. The importance of petroleum industry cannot be avoided in the global market; however, supply chain management in the petroleum industry is facing various challenges, particularly in the logistics area. These logistical challenges have a main influence on the cost of crude oil; therefore, the opportunities to save cost in logistics still do exist. The large oil producing companies are undertaking future contracts through 'swaps or options' practice that saves their millions of dollars. The objective of this paper is to throw light on the supply chain challenges and opportunities in the oil industry and on swap practices which are widely employed by large oil producing companies around the world, such as Chevron Corporation, Saudi Arabian Oil Company, BP and Exxon Mobil.

Keywords: logistics, oil industry, swap practice, supply chain management

Procedia PDF Downloads 157
1752 Lean Implementation: Manufacturing vs. Construction a Roadmap for Success

Authors: Patrick Ahern, David Collery

Abstract:

The implementation of lean thinking in the manufacturing industry revolutionized the traditional approach to large-scale production through the process of identifying the waste in each task and putting in place mitigation measures to eliminate the waste in all its forms. The Irish construction industry, however, has been much slower to adopt the principles of lean, opting instead to stick with the traditional approach to construction project delivery which is inherently wasteful. Lean thinking holds the potential to revolutionize the construction industry in a similar manner to the adoption of lean manufacturing. Lean principles present opportunities for reduced project duration, reduced project cost, improved quality, and elimination of re-works and non-value-added activities. The following research has been designed to accumulate research data through available literature, electronic surveys, and interviews. The results show an industry reluctant to accept change and an undefined path to successful lean construction implementation.

Keywords: barriers, lean construction, lean implementation, lean manufacturing, lean philosophy

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1751 Exploring Academic English Language Needs of Iranian Students of Geology: A Triangulated Approach

Authors: Rose Shayeghi, Pejman Hosseinioun

Abstract:

During the academic year of 2014-2015, a needs analysis was conducted in four major universities of Iran to assess the present and target situation academic language needs of undergraduate students of geology. Participants included undergraduate students (N = 102), graduate students (N = 47), subject-specific teachers (N = 12), and ESAP teachers (N = 20). Instrumentation included four needs analysis questionnaires, self-assessment and semi-structured interviews. The results indicated that, despite some inconsistencies in participants’ perceptions, ‘reading subject specific texts’, ‘knowledge of general vocabulary’, ‘using bilingual technical dictionaries’, and ‘writing e-mails to teachers and field experts’ were perceived as either ‘important’ or ‘very important’ to students’ success by all the participants. Moreover, the findings revealed that undergraduate students’ General English Proficiency (GEP) level was generally lower than what is required in the EAP courses. The findings of the study can have implications for improving and renewing EAP courses under study.

Keywords: ESP, EAP, needs analysis, triangulation, geology

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1750 Analysing the Benefit of Real-Time Digital Translation for ESL Learners in a Post-secondary Canadian Classroom

Authors: Jordan Shuler

Abstract:

The goal of this study is to determine whether real-time language translation benefits ESL learners by contributing to overall equity in the classroom. Equity will be measured quantitatively through assessment performance and qualitatively through student survey. Two separate sections of students studying the same course will receive identical curriculum: one group, the control, will be taught in English and the other group in English with real-time translation into the students' first languages. The professor will use Microsoft Translator during lectures, in-class discussions, and Q&A time. The college is committed to finding new ways of teaching and learning, as outlined in Strategy 2022. If this research finds a positive relationship between language translation and student academic success, the technology will surely be encouraged for adoption by all George Brown College faculty. With greater acceptance, this technology could influence equity and pedagogy in the larger educational community.

Keywords: ESL learners, equity, innovative teaching strategies, language translation

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1749 Trends in Arabic Drama Series (Musalsalat) Production

Authors: Paradigm Shift

Abstract:

In an overwhelmingly import oriented content bazaar of Arabian TV industry, Musalsalat stand unique in their indigenousness and mass popularity, being rivalled only by movies and football. The Arabic term ‘Musalsalat’ stands for drama series with episodes of 30-45 minutes duration; the format being close to Latin American Telenovela concept-clear cut stories with definitive endings that permit narrative closures. Traditionally Musalsalat were either situational comedies or religiously inspired. Present-day productions have started addressing historical, creative and socially progressive issues targeting the young and well-travelled audiences. Though these soaps get prime ratings throughout the year, it is during Ramadan, that they become a raving success in securing viewership. That Musalsalat have become paramount Ramadan programming is evident by their dominance on the grid and attracting heavy ad-spend. The number of Musalsalats produced specifically for Ramadan reached over 100 last year with Ramadan TV advertising amounting to USD1, 947bn constituting 21% of the total regional TV Adspend of USD 9,189bn.

Keywords: Musalsalat, drama, pan Arab, television

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1748 Cervical Cell Classification Using Random Forests

Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh

Abstract:

The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.

Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features

Procedia PDF Downloads 529
1747 Communicating Safety: A Digital Ethnography Investigating Social Media Use for Workplace Safety

Authors: Kelly Jaunzems

Abstract:

Social media is a powerful instrument of communication, enabling the presentation of information in multiple forms and modes, amplifying the interactions between people, organisations, and stakeholders, and increasing the range of communication channels available. Younger generations are highly engaged with social media and more likely to use this channel than any other to seek information. Given this, it may appear extraordinary that occupational safety and health professionals have yet to seriously engage with social media for communicating safety messages to younger audiences who, in many industries, might be statistically more likely to encounter more workplace harm or injury. Millennials, defined as those born between 1981-2000, have distinctive characteristics that also impact their interaction patterns rendering many traditional occupational safety and health communication channels sub-optimal or near obsolete. Used to immediate responses, 280-character communication, shares, likes, and visual imagery, millennials struggle to take seriously the low-tech, top-down communication channels such as safety noticeboards, toolbox meetings, and passive tick-box online inductions favoured by traditional OSH professionals. This paper draws upon well-established communication findings, which argue that it is important to know a target audience and reach them using their preferred communication pathways, particularly if the aim is to impact attitudes and behaviours. Health practitioners have adopted social media as a communication channel with great success, yet safety practitioners have failed to follow this lead. Using a digital ethnography approach, this paper examines seven organisations’ Facebook posts from two one-month periods one year apart, one in 2018 and one in 2019. Each of the years informs organisation-based case studies. Comparing, contrasting, and drawing upon these case studies, the paper discusses and evaluates the (non) use of social media communication of safety information in terms of user engagement, shareability, and overall appeal. The success of health practitioners’ use of social media provides a compelling template for the implementation of social media into organisations’ safety communication strategies. Highly visible content such as that found on social media allows an organization to become more responsive and engage in two-way conversations with their audience, creating more engaged and participatory conversations around safety. Further, using social media to address younger audiences with a range of tonal qualities (for example, the use of humour) can achieve cut through in a way that grim statistics fail to do. On the basis of 18 months of interviews, filed work, and data analysis, the paper concludes with recommendations for communicating safety information via social media. It proposes exploration of the social media communication formula that, when utilised by safety practitioners, may create an effective social media presence. It is anticipated that such social media use will increase engagement, expand the number of followers and reduce the likelihood and severity of safety-related incidents. The tools offered may provide a path for safety practitioners to reach a disengaged generation of workers to build a cohesive and inclusive conversation around ways to keep people safe at work.

Keywords: social media, workplace safety, communication strategies, young workers

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1746 Supporting Older Workers in the Workforce: Identifying Best Practices to Increase Participation

Authors: Dr Elliroma Gardiner

Abstract:

Extending the working life of older workers is one important strategy in alleviating the social and economic challenges associated with the ageing population. The Australian government has implemented several strategies to improve the participation rates of older workers, however, the success of these initiatives has been limited. The aim of this project is to identify what workplace practices influence the workforce participation decisions of older workers. Thirty semi-structured interviews were conducted with older Australians who were either recently retired or currently working. Participants were asks about the factors that influenced their decision to retire/continue working and their current (or former) workplace practices. The results of the thematic analysis identified several factors which either supported (i.e., job autonomy and managerial support) or hindered (i.e., perceptions of age discrimination and age-based stereotypes) continued workplace participation. This research has several important applications for organisation managing intergenerational workforces, as well as policy makers interested in increasing the working life of ageing workers.

Keywords: ageing workers, older workers, age discrimination, age diversity

Procedia PDF Downloads 123
1745 Characteristics of Female Offenders: Using Childhood Victimization Model for Treatment

Authors: Jane E. Hill

Abstract:

Sexual, physical, or emotional abuses are behaviors used by one person in a relationship or within a family unit to control the other person. Physical abuse can consist of, but not limited to hitting, pushing, and shoving. Sexual abuse is unwanted or forced sexual activity on a person without their consent. Abusive behaviors include intimidation, manipulation, humiliation, isolation, frightening, terrorizing, coercing, threatening, blaming, hurting, injuring, or wounding another individual. Although emotional, psychological and financial abuses are not criminal behaviors, they are forms of abuse and can leave emotional scars on their victim. The purpose of this literature review research was to examine characteristics of female offenders, past abuse, and pathways to offending. The question that guided this research: does past abuse influence recidivism? The theoretical foundation used was relational theory by Jean Baker Miller. One common feature of female offenders is abuse (sexual, physical, or verbal). Abuse can cause mental illnesses and substance abuse. The abuse does not directly affect the women's recidivism. However, results indicated the psychological and maladaptive behaviors as a result of the abuse did contribute to indirect pathways to continue offending. The female offenders’ symptoms of ongoing depression, anxiety, and engaging in substance abuse (self medicating) did lead to the women's incarceration. Using the childhood victimization model as the treatment approach for women's mental illness and substance abuse disorders that were a result from history of child abuse have shown success. With that in mind, if issues surrounding early victimization are not addressed, then the women offenders may not recover from their mental illness or addiction and are at a higher risk of reoffending. However, if the women are not emotionally ready to engage in the treatment process, then it should not be forced onto them because it may cause harm (targeting prior traumatic experiences). Social capital is family support and sources that assist in helping the individual with education, employment opportunities that can lead to success. Human capital refers to internal knowledge, skills, and capacities that help the individual act in new and appropriate ways. The lack of human and social capital is common among female offenders, which leads to extreme poverty and economic marginalization, more often in frequent numbers than men. In addition, the changes in welfare reform have exacerbated women’s difficulties in gaining adequate-paying jobs to support themselves and their children that have contributed to female offenders reoffending. With that in mind, one way to lower the risk factor of female offenders from reoffending is to provide them with educational and vocational training, enhance their self-efficacy, and teach them appropriate coping skills and life skills. Furthermore, it is important to strengthen family bonds and support. Having a supportive family relationship was a statistically significant protective factor for women offenders.

Keywords: characteristics, childhood victimization model, female offenders, treatment

Procedia PDF Downloads 112
1744 On Increase and Development Prospects of Competitiveness of Georgia’s Transport-Logistical System on the Contemporary Stage

Authors: Ketevan Goletiani

Abstract:

MMultimodal transport is Europe-Asia’s rational decision of the XXI century. Success prerequisite of this form of cargo carriage is not technologic decision, but the comprehensive attitude towards it. Integration of the transport industry must refer to both technical and organizational-economic fields. Support of the multimodal’s must be the priority of the transport policy in different organizations of Europe and Asia. The method of approach to the transport as a unified system has been changed to a certain extent in the market conditions. Nowadays the competition between the different kinds of transport is not to be considered as a competition of one kind of transport towards another one, but is to be considered as a stimulator of the transport development. Basically, transport logistic, as the recent methodology and organization of the rationally flow of cargos at the specialized logistic centres during their procession provides effective rise of such flow of cargos, decreases non-operating expenses and gives the opportunity to the transport companies to come along with the time, to meet market clients’ requirements. It is apparent that the advanced transport-forwarding and logistic firms are being analized.

Keywords: transport systems, multimodal transport, competition, transport logistics

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1743 Artificial Intelligence in Duolingo

Authors: Elana Mahboub, Lamar Bakhurji, Hind Alhindi, Sara Alesayi

Abstract:

Duolingo is a revolutionary language learning platform that offers an interactive and accessible learning experience. Its gamified approach makes language learning engaging and enjoyable, with a diverse range of languages available. The platform's adaptive learning system tailors lessons to individual proficiency levels, ensuring a personalized and efficient learning journey. The incorporation of multimedia elements enhances the learning experience and promotes practical language application. Duolingo's success is attributed to its mobile accessibility, offering basic access to language courses for free, with optional premium features for those seeking additional resources. Research shows positive outcomes for users, and the app's global impact extends beyond individual learning to formal language education initiatives. Duolingo is a transformative force in language education, breaking down barriers and making language learning an attainable goal for millions worldwide.

Keywords: duolingo, artificial intelligence, artificial intelligence in duolingo, benefit of artificial intelligence

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1742 A Study of Small Business Failure: Impact of Leadership and the Leadership Process

Authors: Theresa Robinson Harris

Abstract:

Small businesses are important to the United States economy, yet the majority struggle to remain relevant and close before their fifth year. This qualitative study explored small business failure by comparing the experiences of small-business owners to understand their involvement with leadership during the early stages of the business, and the impact of this on the firms’ ability to survive. Participants’ experiences from two groups were compared to glean an understanding of the leadership process, how leadership differs between the groups, and to see what themes or constructs emerged that could help to explain the high failure rate. Leadership was perceived to be important when envisioning a path for the future and when providing a platform for employees to succeed. Those who embraced leadership as a skillset were more likely to get through the challenges of the early developmental years while those ignoring the importance of leadership were more likely to close prematurely. These findings suggest a disconnect with regards to the understanding, role, and benefits of leadership in small organizations, particularly young organizations in the early stages of development.

Keywords: leadership, small business, entrepreneurship, success, failure

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1741 AI-Driven Solutions for Optimizing Master Data Management

Authors: Srinivas Vangari

Abstract:

In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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