Search results for: interactive user navigation

Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Adham Al Yaari, Aayah Al Yaari, Montaha Al Yaari, Ayman Al Yaari, Sajedah Al Yaari, Fatehi Eissa

Abstract:

The recent rise of smart educational aids and the move away from traditional listening aids are leading to a fundamental shift in the way in which individuals with attention and listening problems (ALP) manipulate listening inputs and/or act appropriately to the spoken information presented to them. A total sample of twenty-six ALP pupils (m=20 and f=6) between 7-12 years old was selected from different strata based on gender, region and school. In the sample size, thirteen (10 males and 3 females) received the treatment in terms of smart classes provided with smart educational aids in a listening course that lasted for four months, while others did not (they studied the same course by the same instructor but in ordinary class). A pretest was administered to assess participants’ levels, and a posttest was given to evaluate their attention and listening comprehension performance, namely in phonetic and phonological tests with sociolinguistic themes that have been designed for this purpose. Test results were analyzed both psychoneurolinguistically and statistically. Results reveal a remarkable change in pupils’ behavioral listening where scores witnessed a significant difference in the performance of the experimental ALP group in the pretest compared to the posttest (Pupils performed better at the pretest-posttest on phonetics than at the two tests on phonology). It is concluded that smart educational aids designed for listening skills help not only increase the listening command of pupils with ALP to understand what they listen to but also develop their interactive listening capability and, at the same rate, are responsible for increasing concentrated and in-depth listening capacity. Plus, ALP pupils become able to grasp the audio content of text recordings, including educational audio recordings, news, oral stories and tales, views, spiritual/religious text and general knowledge. However, the pupils have not experienced individual smart audio-visual aids that connect listening to other language receptive and productive skills, which could be the future area of research.

Keywords: smart aids, attention, listening, problems

Procedia PDF Downloads 42

Authors: Naman Solanki, Souraj Mondal

Abstract:

With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

Procedia PDF Downloads 114

Authors: Ali Al-Dahoud, Mohamed Fezari, Thamer Al-Rawashdeh, Ismail Jannoud

Abstract:

Monitoring and detecting faults on a set of Solar panels, using a wireless sensor network (WNS) is our contribution in this paper, This work is part of the project we are working on at Al-Zaytoonah University. The research problem has been exposed by engineers and technicians or operators dealing with PV panels maintenance, in order to monitor and detect faults within solar panels which affect considerably the energy produced by the solar panels. The proposed solution is based on installing WSN nodes with appropriate sensors for more often occurred faults on the 45 solar panels installed on the roof of IT faculty. A simulation has been done on nodes distribution and a study for the design of a node with appropriate sensors taking into account the priorities of the processing faults. Finally, a graphic user interface is designed and adapted to telemonitoring panels using WSN. The primary tests of hardware implementation gave interesting results, the sensors calibration and interference transmission problem have been solved. A friendly GUI using high level language Visial Basic was developed to carry out the monitoring process and to save data on Exel File.

Keywords: Arduino Mega microcnotroller, solar panels, fault-detection, simulation, node design

Procedia PDF Downloads 465

Authors: Diego Adrian Cardenas Jorge, Gerardo Mirando Guisado, Alfredo Barrientos Padilla

Abstract:

A system based on Affective Computing can detect and interpret human information like voice, facial expressions and body movement to detect emotions and execute a corresponding response. This data is important due to the fact that a person can communicate more effectively with emotions than can be possible with words. This information can be processed through technological components like Facial Recognition, Gait Recognition or Gesture Recognition. As of now, solutions proposed using this technology only consider one component at a given moment. This research investigation proposes two solutions based on Affective Computing taking into account more than one component for emotion detection. The proposals reflect the levels of dependency between hardware devices and software, as well as the interaction process between the system and the user which implies the development of scenarios where both proposals will be put to the test in a live environment. Both solutions are to be developed in code by software engineers to prove the feasibility. To validate the impact on society and business interest, interviews with stakeholders are conducted with an investment mind set where each solution is labeled on a scale of 1 through 5, being one a minimum possible investment and 5 the maximum.

Keywords: affective computing, emotions, emotion detection, face recognition, gait recognition

Procedia PDF Downloads 369

Authors: K. O'Malley

Abstract:

Background: The emergence and rapid evolution of large language models (LLMs) (i.e., models of generative artificial intelligence, or AI) has been unprecedented. ChatGPT is one of the most widely used LLM platforms. Using natural language processing technology, it generates customized responses to user prompts, enabling it to mimic human conversation. Responses are generated using predictive modeling of vast internet text and data swathes and are further refined and reinforced through user feedback. The popularity of LLMs is increasing, with a growing number of students utilizing these platforms for study and revision purposes. Notwithstanding its many novel applications, LLM technology is inherently susceptible to bias and error. This poses a significant challenge in the educational setting, where academic integrity may be undermined. This study aims to evaluate the performance of the latest iteration of ChatGPT (ChatGPT4.0) in standardized state medical licensing examinations. Methods: A considered search strategy was used to interrogate the PubMed electronic database. The keywords ‘ChatGPT’ AND ‘medical education’ OR ‘medical school’ OR ‘medical licensing exam’ were used to identify relevant literature. The search included all peer-reviewed literature published in the past five years. The search was limited to publications in the English language only. Eligibility was ascertained based on the study title and abstract and confirmed by consulting the full-text document. Data was extracted into a Microsoft Excel document for analysis. Results: The search yielded 345 publications that were screened. 225 original articles were identified, of which 11 met the pre-determined criteria for inclusion in a narrative synthesis. These studies included performance assessments in national medical licensing examinations from the United States, United Kingdom, Saudi Arabia, Poland, Taiwan, Japan and Germany. ChatGPT 4.0 achieved scores ranging from 67.1 to 88.6 percent. The mean score across all studies was 82.49 percent (SD= 5.95). In all studies, ChatGPT exceeded the threshold for a passing grade in the corresponding exam. Conclusion: The capabilities of ChatGPT in standardized academic assessment in medicine are robust. While this technology can potentially revolutionize higher education, it also presents several challenges with which educators have not had to contend before. The overall strong performance of ChatGPT, as outlined above, may lend itself to unfair use (such as the plagiarism of deliverable coursework) and pose unforeseen ethical challenges (arising from algorithmic bias). Conversely, it highlights potential pitfalls if users assume LLM-generated content to be entirely accurate. In the aforementioned studies, ChatGPT exhibits a margin of error between 11.4 and 32.9 percent, which resonates strongly with concerns regarding the quality and veracity of LLM-generated content. It is imperative to highlight these limitations, particularly to students in the early stages of their education who are less likely to possess the requisite insight or knowledge to recognize errors, inaccuracies or false information. Educators must inform themselves of these emerging challenges to effectively address them and mitigate potential disruption in academic fora.

Keywords: artificial intelligence, ChatGPT, generative ai, large language models, licensing exam, medical education, medicine, university

Procedia PDF Downloads 32

Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

Abstract:

The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

Procedia PDF Downloads 114

Authors: Rima Almalla

Abstract:

The purpose of the research project in Geography is to evaluate the applicability of urban green infrastructure approach in Finnish climate. The key focus will be on the operation and efficiency of green infrastructure on urban stormwater management. Green infrastructure approach refers to the employment of sufficient green covers as a modern and smart environmental solution to improve the quality of urban environments. Green infrastructure provides a wide variety of micro-scale ecosystem services, such as stormwater runoff management, regulation of extreme air temperatures, reduction of energy consumption, plus a variety of social benefits and human health and wellbeing. However, the cold climate of Finland with seasonal ground frost, snow cover and relatively short growing season bring about questions of whether green infrastructure works as efficiently as expected. To tackle this question, green infrastructure solutions will be studied and analyzed with manifold methods: stakeholder perspectives regarding existing and planned GI solutions will be collected by web based questionnaires, semi structured interviews and group discussions, and analyzed in both qualitative and quantitative methods. Targeted empirical field campaigns will be conducted on selected sites. A systematic literature review with global perspective will support the analyses. The findings will be collected, compiled and analyzed using geographic information systems (GIS). The findings of the research will improve our understanding of the functioning of green infrastructure in the Finnish environment in urban stormwater management, as a landscape element for citizens’ wellbeing, and in climate change mitigation and adaptation. The acquired information will be shared with stakeholders in interactive co-design workshops. As green covers have great demand and potential globally, the conclusions will have relevance in other cool climate regions and may support Finnish business in green infrastructure sector.

Keywords: climate change adaptation, climate change, green infrastructure, stormwater

Procedia PDF Downloads 167

Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Adham Al Yaari, Ayah Al Yaari, Ayman Al Yaari, Montaha Al Yaari, Sajedah Al Yaari, Fatehi Eissa

Abstract:

The recent rise of smart educational aids and the move away from traditional listening aids are leading to a fundamental shift in the way in which individuals with attention and listening problems (ALP) manipulate listening inputs and/or act appropriately to the spoken information presented to them. A total sample of twenty-six ALP pupils (m=20 and f=6) between 7-12 years old was selected from different strata based on gender, region and school. In the sample size, thirteen (10 males and 3 females) received the treatment in terms of smart classes provided with smart educational aids in a listening course that lasted for four months, while others did not (they studied the same course by the same instructor but in ordinary class). A pretest was administered to assess participants’ levels, and a posttest was given to evaluate their attention and listening comprehension performance, namely in phonetic and phonological tests with sociolinguistic themes that have been designed for this purpose. Test results were analyzed both psychoneurolinguistically and statistically. Results reveal a remarkable change in pupils’ behavioral listening where scores witnessed a significant difference in the performance of the experimental ALP group in the pretest compared to the posttest (Pupils performed better at the pretest-posttest on phonetics than at the two tests on phonology). It is concluded that smart educational aids designed for listening skills help not only increase the listening command of pupils with ALP to understand what they listen to but also develop their interactive listening capability and, at the same rate, are responsible for increasing concentrated and in-depth listening capacity. Plus, ALP pupils become able to grasp the audio content of text recordings, including educational audio recordings, news, oral stories and tales, views, spiritual/religious text and general knowledge. However, the pupils have not experienced individual smart audio-visual aids that connect listening to other language receptive and productive skills, which could be the future area of research.

Keywords: smart educational aids, listening attention, pupils, problems

Procedia PDF Downloads 52

Authors: Sheikh Omar Sillah

Abstract:

Introduction: Monitoring is an important means of ensuring the smooth implementation and quality of clinical trials. For many years, traditional site monitoring approaches have been critical in detecting data errors but not optimal in identifying fabricated and implanted data as well as non-random data distributions that may significantly invalidate study results. The objective of this paper was to provide recommendations based on best statistical monitoring practices for detecting data-integrity issues suggestive of fabrication and implantation early in the study conduct to allow implementation of meaningful corrective and preventive actions. Methodology: Electronic bibliographic databases (Medline, Embase, PubMed, Scopus, and Web of Science) were used for the literature search, and both qualitative and quantitative studies were sought. Search results were uploaded into Eppi-Reviewer Software, and only publications written in the English language from 2012 were included in the review. Gray literature not considered to present reproducible methods was excluded. Results: A total of 18 peer-reviewed publications were included in the review. The publications demonstrated that traditional site monitoring techniques are not efficient in detecting data anomalies. By specifying project-specific parameters such as laboratory reference range values, visit schedules, etc., with appropriate interactive data monitoring, statistical monitoring can offer early signals of data anomalies to study teams. The review further revealed that statistical monitoring is useful to identify unusual data patterns that might be revealing issues that could impact data integrity or may potentially impact study participants' safety. However, subjective measures may not be good candidates for statistical monitoring. Conclusion: The statistical monitoring approach requires a combination of education, training, and experience sufficient to implement its principles in detecting data anomalies for the statistical aspects of a clinical trial.

Keywords: statistical monitoring, data anomalies, clinical trials, traditional monitoring

Procedia PDF Downloads 75

Authors: Sefik Can Karakaya, Ibrahim Demir

Abstract:

In this study, the relationship between musical preferences and personality traits has been investigated in terms of Spotify audio analysis features. The aim of this paper is to build such a classifier capable of segmenting people into their Myers-Briggs Type Index (MBTI) personality type based on their Spotify playlists. Music takes an important place in the lives of people all over the world and online music streaming platforms make it easier to reach musical contents. In this context, the motivation to build such a classifier is allowing people to gain access to their MBTI personality type and perhaps for more reliably and more quickly. For this purpose, logistic regression and deep neural networks have been selected for classifier and their performances are compared. In conclusion, it has been found that musical preferences differ statistically between personality traits, and evaluated models are able to distinguish personality types based on given musical data structure with over %60 accuracy rate.

Keywords: myers-briggs type indicator, music psychology, Spotify, behavioural user profiling, deep neural networks, logistic regression

Procedia PDF Downloads 144

Authors: Laxmi Prasad Bhattarai

Abstract:

Climate change is regarded as one of the most fundamental threats to sustainable livelihood and global development. There is a growing global concern in linking community-managed forests as potential climate change mitigation projects. This study was conducted to explore local people’s perception on climate change and the role of community forestry (CF) to combat climate change impacts. Two active community forest user groups (CFUGs) from Kaski and Syangja Districts in Nepal were selected as study sites, and various participatory tools were applied to collect primary data. Although most of the respondents were unaware about the words “Climate Change” in study sites, they were quite familiar with the irregularities in rainfall season and other weather extremities. 60% of the respondents had the idea that, due to increase in precipitation, there is a frequent occurrence of erosion, floods, and landslide. Around 85% of the people agreed that community forests help in stabilizing soil, reducing the natural hazards like erosion, landslide. Biogas as an alternative source of cooking energy, and changes in crops and their varieties are the common adaptation measures that local people start practicing in both CFUGs in Nepal.

Keywords: community forestry, climate change, global warming, adaptation, Nepal

Procedia PDF Downloads 305

Authors: Haziyah Hussin, Syazwan Abdul Samad, Rosnani Jusoh

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This study is aimed towards the automisation of basic patternmaking for traditional clothes for the purpose of mass production using AutoCAD to apply AutoLISP feature under software Hazi Attire. A standard dress form (industrial form) with the size of small (S), medium (M) and large (L) size is measured using full body scanning machine. Later, the pattern for the clothes is designed parametrically based on the measured dress form. Hazi Attire program is used within the framework of AutoCAD to generate the basic pattern of front bodice, back bodice, front skirt, back skirt and sleeve block (sloper). The generation of pattern is based on the parameters inputted by user, whereby in this study, the parameters were determined based on the measured size of dress form. The finalized pattern parameter shows that the pattern fit perfectly on the dress form. Since the pattern is generated almost instantly, these proved that using the AutoLISP programming, the manufacturing lead time for the mass production of the traditional clothes can be decreased.

Keywords: apparel, AutoLISP, Malay traditional clothes, pattern ganeration

Procedia PDF Downloads 256

Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

Procedia PDF Downloads 91

Authors: Husnain Mushtaq, Mary Anjum, Muhammad Aleem

Abstract:

The main objective of this paper is used to develop a high security in Automatic Teller Machine (ATM). In these system bankers will collect the mobile numbers from the customers and then provide a code on their mobile number. In most country existing ATM machine use the magnetic card reader. The customer is identifying by inserting an ATM card with magnetic card that hold unique information such as card number and some security limitations. By entering a personal identification number, first the customer is authenticated then will access bank account in order to make cash withdraw or other services provided by the bank. Cases of card fraud are another problem once the user’s bank card is missing and the password is stolen, or simply steal a customer’s card & PIN the criminal will draw all cash in very short time, which will being great financial losses in customer, this type of fraud has increase worldwide. So to resolve this problem we are going to provide the solution using “Mobile SMS code” and ATM “PIN code” in order to improve the verify the security of customers using ATM system and confidence in the banking area.

Keywords: PIN, inquiry, biometric, magnetic strip, iris recognition, face recognition

Procedia PDF Downloads 364

Authors: Niddal Imam, Vassilios G. Vassilakis

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After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

Procedia PDF Downloads 78

Authors: Neeru Bhatia

Abstract:

This article presents the results of a case study designed to analyze and deduce Information seekers and the Information Providers in today’s context, wherein we come across a sea of change in the provision of Information services due to the changing electronic environment. The Panjab University Library is one of the biggest libraries of India and was inaugurated in 1963 by Pt. Jawaharlal Nehru, the then Prime Minister of India. The library always thrives to assimilate new technology for the provision of Information services. As we know that the Information seekers today are a whole lot different, they are tech savvy, like to be on their electronic gadgets most of the time, and their Information seeking patterns are also different, the challenge that lies before the libraries is to be always ready for these day to day challenges. The study explores the current status of the Information Services being provided by the Panjab University Library (the Information Providers) vs. the evaluation of these Information services by the users of Library (the Information Seekers). The present study aimed at finding out whether Panjab University Library is able to achieve its mission to be an innovative and user-oriented library by exploring all the new vistas and reach up to the expectations of the information seekers by taking up all the challenges being posed by the ever changing technological scenario.

Keywords: electronic environment, information seekers, information providers, new technology

Procedia PDF Downloads 262

Authors: Christopher Lama, Alix Rieser, Aleksandra Molchanova, Charles Thangaraj

Abstract:

New technologies like Tesla’s Dojo have made high-performance embedded computing more available. Although automobile computing has developed and benefited enormously from these more recent technologies, the costs are still high, prohibitively high in some cases for broader adaptation, particularly for the after-market and enthusiast markets. This project aims to implement a Raspberry Pi-based low-power (under one hundred Watts) highly mobile computing cluster for a neural network. The computing cluster built from off-the-shelf components is more affordable and, therefore, makes wider adoption possible. The paper describes the design of the neural network, Raspberry Pi-based cluster, and applications the cluster will run. The neural network will use input data from sensors and cameras to project a live view of the road state as the user drives. The neural network will be trained to predict traffic behavior and generate warnings when potentially dangerous situations are predicted. The significant outcomes of this study will be two folds, firstly, to implement and test the low-cost cluster, and secondly, to ascertain the effectiveness of the predictive AI implemented on the cluster.

Keywords: CS pedagogy, student research, cluster computing, machine learning

Procedia PDF Downloads 102

Authors: Helle Nissen

Abstract:

Physical objects surrounding people in healthcare environments are carriers of institutional logics materialized into the objects by its producers. However, institutional logics research lacks to inform us how logics become materialized and are perceived by producers vs. users of an object. The study is based on a 3-year longitudinal case study of a Danish Public Private Innovation project aiming to co-create an innovative healthcare bed commercialized to public psychiatric hospitals. The producers are a private metal firm and industrial designers from two Danish regions. The findings demonstrate that the metal firm and designers, as producers, negotiate about materializing different logics into the bed throughout the innovation process. An aesthetic logic is prioritized most, and the producers encode it with the intention to develop a bed that looks homely and less hospital-like compared to previous and existing healthcare beds. After the bed is put into use, the aesthetic logic is decoded by the users. Their perception of it differs significantly from the producers’ intended meaning, as the healthcare bed is perceived as sterile. The study has theoretical implications: It demonstrates how logics become materialized ‘here and now’, and it reveals logics as less governed by stable and clear meanings but rather as subject to changeable perceptions.

Keywords: co-creation, healthcare innovation, commercialization, institutional logics

Procedia PDF Downloads 86

Authors: Cristian Matti, Valerie Fowles, Eva Enyedi, Piotr Pogorzelski

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The system mapping process can be defined as a knowledge service where a team of facilitators, experts and practitioners facilitate a guided conversation, enable the exchange of information and support an iterative curation process. System mapping processes rely on science-based tools to introduce and simplify a variety of components and concepts of socio-technical systems through metaphors while facilitating an interactive dialogue process to enable the design of co-created maps. System maps work then as “artifacts” to provide information and focus the conversation into specific areas around the defined challenge and related decision-making process. Knowledge management facilitates the curation of that data gathered during the system mapping sessions through practices of documentation and subsequent knowledge co-production for which common practices from data science are applied to identify new patterns, hidden insights, recurrent loops and unexpected elements. This study presents empirical evidence on the application of these techniques to explore mechanisms by which visual tools provide guiding principles to portray system components, key variables and types of data through the lens of climate change. In addition, data science facilitates the structuring of elements that allow the analysis of layers of information through affinity and clustering analysis and, therefore, develop simple indicators for supporting the decision-making process. This paper addresses methodological and empirical elements on the horizontal learning process that integrate system mapping through visual tools, interpretation, cognitive transformation and analysis. The process is designed to introduce practitioners to simple iterative and inclusive processes that create actionable knowledge and enable a shared understanding of the system in which they are embedded.

Keywords: indicators, knowledge management, system mapping, visual tools

Procedia PDF Downloads 195

Authors: Beatrice Wamuyu Muchiri, Monika M. L. Dos Santos

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An increasingly recognised prevention approach for substance use entails reduction in risk factors and enhancement of promotive or protective factors in individuals and the environment surrounding them during their growth and development. However, in order to enhance the effectiveness of this approach, continuous study of risk aspects targeting different cultures, social groups and mixture of society has been recommended. This study evaluated the impact of potential risk and protective factors associated with family management and relations on adolescent substance abuse in South Africa. Exploratory analysis and cumulative odds ordinal logistic regression modelling was performed on the data while controlling for demographic and socio-economic characteristics on adolescent substance use. The most intensely used substances were tobacco, cannabis, cocaine, heroin and alcohol in decreasing order of use intensity. The specific protective or risk impact of family management or relations factors varied from substance to substance. Risk factors associated with demographic and socio-economic factors included being male, younger age, being in lower education grades, coloured ethnicity, adolescents from divorced parents and unemployed or fully employed mothers. Significant family relations risk and protective factors against substance use were classified as either family functioning and conflict or family bonding and support. Several family management factors, categorised as parental monitoring, discipline, behavioural control and rewards, demonstrated either risk or protective effect on adolescent substance use. Some factors had either interactive risk or protective impact on substance use or lost significance when analysed jointly with other factors such as controlled variables. Interaction amongst risk or protective factors as well as the type of substance should be considered when further considering interventions based on these risk or protective factors. Studies in other geographical regions, institutions and with better gender balance are recommended to improve upon the representativeness of the results. Several other considerations to be made when formulating interventions, the shortcomings of this study and possible improvements as well as future studies are also suggested.

Keywords: risk factors, protective factors, substance use, adolescents

Procedia PDF Downloads 204

Authors: Kashi Raj Pandey

Abstract:

Transformative learning is a form of learning rooted in learners' life experiences and their inherent love for learning. It emphasizes the importance of incorporating students' everyday work through the use of learning diaries and reflective journals. It encourages learners to take a proactive role in their own improvement, fostering creativity and promoting informed discussions about the learning process. Reflecting on the personal experience with English language learning in a rural village in Nepal where rote memorization was the prevailing teaching method, this traditional approach hindered a deeper understanding of the language, prompting the author to recognize the need for more effective pedagogy. In this study, the author delved into the cultural contextualization of English language learning, taking into account learners' backgrounds. The study’s findings highlighted the importance of equity, inclusion, mutuality, and social justice in the classroom, emphasizing the significance of integrating students' lived experiences into the pedagogical approach. This, in turn, can encourage students to engage in profound and collaborative learning practices within the realm of English language education. Upon successfully implementing the research findings, including the eight key conditions of transformative learning, in multiple classrooms, the author collaborated with international educationists and government stakeholders in Nepal. The purpose was to disseminate the research findings, conduct teacher training workshops, and systematically enhance Nepali students’ English language learning. These methods have already demonstrated a significant improvement in student engagement within the same school where the author once learned English as a child. This study aims to explore teachers’ decision-making process regarding the transition from traditional teaching methods to interactive ones, which have gained national recognition within the ESL/EFL teaching community in Nepal. By sharing these experiences, it is expected that other teachers will also contemplate adopting transformative learning pedagogy in their own classrooms.

Keywords: reflection, student engagement, pedagogy, transformative learning

Procedia PDF Downloads 80

Authors: Ahmed Hariri

Abstract:

E-Learning has become a necessity in the advanced education. It is easier for the student and teacher communication also it speed up the process with less time and less effort. With the progress and the enormous development of distance education must keep up with this age of making a website that allows students and teachers to take all the advantages of advanced education. In this regards, we developed University Short courses web application which is specially designed for Faculty of computing and information technology, Rabigh, Kingdom of Saudi Arabia. After an elaborate review of the current state-of-the-art methods of teaching and learning, we found that instructors deliver extra short courses and workshop to students to enhance the knowledge of students. Moreover, this process is completely manual. The prevailing methods of teaching and learning consume a lot of time; therefore in this context, University Short courses web application will help to make process easy and user friendly. The site allows for students can view and register short courses online conducted by instructor also they can see courses starting dates, finishing date and locations. It also allows the instructor to put things on his courses on the site and see the students enrolled in the study material. Finally, student can print the certificate after finished the course online. ASP.NET, SQLSERVER, JavaScript SQL SERVER Database will use to develop the University Short Courses web application.

Keywords: e-learning, short courses, ASP.NET, SQL SERVER

Procedia PDF Downloads 134

Authors: Saeed Sayyad Hagh Shomar

Abstract:

Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using questionnaire of stated preference models users’ departure time choice affected by congestion pricing plan in downtown Tehran. Experimental results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: modeling, departure time, travel timing, time of the day, congestion pricing, transportation planning

Procedia PDF Downloads 433

Authors: Aulia F. Hadining, Atya Nur Aisha, Dimas Kurninatoro Aji

Abstract:

Utilization of social media as a marketing tool is growing rapidly, including for SMEs. Social media allows the user to give product evaluation and recommendations to the public. In addition, the social media facilitate word-of-mouth marketing communication. One of the social media that can be used is Facebook, with Facebook Ads. This study aimed to evaluate the location of Facebook Ads, to obtain an appropriate advertising design. There are three alternatives location consist of desktop, right-hand column and mobile. The effectiveness and efficiency of advertising will be measured based on advertising metrics such as reach, click, Cost per Click (CUC) and Unique Click-Through-Rate (UCTR). Facebook's Ads Manager was used for seven days, targeted by age (18-24), location (Bandung), language (Indonesia) and keywords. The result was 13,999 total reach, as well as 342 clicks. Based on the results of comparison using ANOVA, there was a significant difference for each placement location based on advertising metrics. Mobile location was chosen to be successful ads, because it produces the lowest CUC, amounting to Rp 691,- per click and 14% UCTR. Results of this study showed Facebook Ads was useful and cost-effective media to promote the product of SME, because it could be view by many people in the same time.

Keywords: marketing communication, social media, Facebook Ads, mobile location

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Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

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With the development of virtualization technologies, a new type of service named cloud computing service is produced. Cloud users usually encounter the problem of how to use the virtualized platform easily over the web without requiring the plug-in or installation of special software. The object of this paper is to develop a system and a method enabling process interfacing within an automation scenario for accessing remote application by using the web browser. To meet this challenge, we have devised a web-based interface that system has allowed to shift the GUI application from the traditional local environment to the cloud platform, which is stored on the remote virtual machine. We designed the sketch of web interface following the cloud virtualization concept that sought to enable communication and collaboration among users. We describe the design requirements of remote application technology and present implementation details of the web application and its associated components. We conclude that this effort has the potential to provide an elastic and resilience environment for several application services. Users no longer have to burden the system maintenances and reduce the overall cost of software licenses and hardware. Moreover, this remote application service represents the next step to the mobile workplace, and it lets user to use the remote application virtually from anywhere.

Keywords: virtualization technology, virtualized platform, web interface, remote application

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Authors: Virginia Chambers, Kamryn York, Mark Marnich

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T.I.M.E. for STEM (Transforming Integrative Maker Education for STEM learning) focuses on improving the quality and effectiveness of STEM education for pre-service teachers through a focus on the integration of maker space pedagogy. This National Science Foundation-funded project primarily focuses on undergraduate pre-service teaching students majoring in elementary education. The study contributes to the knowledge about teaching and learning by developing, implementing, and assessing faculty development, interactive instruction, and STEM lesson plan development. This project offers a valuable opportunity to improve STEM thinking skills by formally integrating STEM concepts throughout the pre-service teacher curriculum using an interdisciplinary approach. T.I.M.E. for STEM utilizes a maker space laboratory at Point Park University in Pittsburgh, PA, USA. However, the project design is such that other institutions of higher education can replicate the program with or without a physical maker space lab as the project’s findings and “maker mindset” are employed. Utilizing qualitative research methodology, the project investigates the following research question: What do pre-service teachers (education students) and faculty members identify as areas of pedagogical growth in STEM learning and teaching in a makerspace environment? This research highlights the impact of makerspace pedagogy on improving STEM education learning outcomes through an interdisciplinary constructivist approach. The project is expected to have a multiplier effect as it impacts STEM disciplinary and higher education faculty, pre-service teachers, and teacher preparation programs at other universities that benefit from what is learned at Point Park University. Ultimately, the future elementary students of the well-prepared pre-service teachers steeped in maker pedagogy and STEM content will have the potential to develop higher-level thinking skills and improve their mathematics and scientific achievement, which are essential for the 21st century STEM workforce.

Keywords: maker education, STEM learning, teacher education, elementary education

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Authors: Fabio Fabris, Alex A. Freitas

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Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Jorn Fricke, Frans Melissen

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Citizens in urban areas are prone to increased levels of stress due to urbanization, inadequate and overburdened infrastructure and services, and environmental degradation. Moreover, communities are fragile and subject to shocks and stresses through various social and political processes. A loss of (a sense of) community is often seen as related to increasing political and civic disintegration. Feelings of community can manifest themselves in various ways but underlying all these manifestations is the need for trust between people. One of the main drivers of trust between individuals is (shared) experiences. It is these shared experiences that may play an important role in building resilience, i.e., the ability of a community and its members to adapt to and deal with stresses, as well as ensure the ongoing development of a community. So far, experience design, as a discipline and academic field, has mainly focused on designing products or services. However, people-to-people experiences are the ones that play a pivotal role in building inclusiveness, safety, and resilience in communities. These experiences represent challenging objects of design as they develop in an interactive space of spontaneity, serendipity, and uniqueness that is based on intuition, freedom of expression, and interaction. Therefore, there is a need for research to identify which elements are required in designing the social and physical environment (or ‘experience scape’) to increase the chance for people-to-people experiences to be successful and what elements are required for these experiences to help in building resilience in urban communities that can resist shocks and stresses. By means of a comparative case study approach in urban areas in Germany and the Netherlands, using a range of qualitative research methods such as in-depth interviews, focus groups, participant observation, storytelling techniques, and life stories, this research identifies relevant actors and their roles in creating building blocks of optimal experience scrapes for building resilience in communities.

Keywords: community development, experiences, experience scapes, resilience

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Authors: Baikunthanath Sahoo, Santosh Kumar Sahu, Krishna Malakar

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With the essence of global environmental sustainability and green business management, the wind of business research moved towards Corporate Social Responsibility. In addition to international and national treaties, businesses have also started realising environmental protection and energy efficiency through CSR as part of business strategy in response to climate change. Considering the ambitious emission reduction target and rapid economic development of India, this study is an attempt to explore the effect of CSR on the energy efficiency management of manufacturing firms in India. By using firm-level data, the panel fixed effect model shows that the CSR dummy variable is negatively influencing the energy intensity or technically, they are energy efficient. The result demonstrates that in the presence of CSR, all the production economic variables are significant. The result also shows that doing environmental expenditure does not improve energy efficiency might be because very few firms are motivated to do such expenditure and also not common to all sectors. The interactive effect model result conforms that without considering CSR dummy as an intervening variable only Manufacturers of Chemical and Chemical products, Manufacturers of Pharmaceutical, medical chemical, and botanical products firms energy intensity low but after considering CSR in their business practices all six sub-sector firms become energy efficient. The empirical result also validate that firms are continuously engaged in CSR activities they are highly energy efficient. It is an important motivational factor for firms to become economically and environmentally sustainable in the corporate world. This analysis would help business practitioners to know how to manage today’s profitability and tomorrow’s sustainability to achieve a comparative advantage in the emerging market economy. The paper concludes that reducing energy consumption as part of their social responsibility to care for the environment, will need collaborative efforts of business society and policy bodies.

Keywords: CSR, Energy Efficiency, Indian manufacturing Sector, Business strategy

Procedia PDF Downloads 82