Search results for: Ai driven tools

Authors: Patrick Innocenti, Elias Montini, Silvia Menato, Marzio Sorlini

Abstract:

Documented experiences of industrial symbiosis are always triggered and driven only by economic goals: environmental and (even rarely) social results are sometimes assessed and declared as effects of virtuous behaviours, but are merely casual and un-pursued side externalities. Even worse: all the symbiotic project candidates entailing economic loss for just one of the (also dozen) partners are simply stopped without considering the overall benefit for the whole partnership. The here-presented approach aims at providing methodologies and tools to effectively manage these situations and fostering the implementation of virtuous symbiotic investments in manufacturing aggregations for a more sustainable production.

Keywords: business model, industrial symbiosis, industrial agglomerations, sustainability

Procedia PDF Downloads 290

Authors: Charlotte Bose Iro-Idoro, Adebisi Folake Osore, Tajudeen Adisa Jimoh

Abstract:

All changes in the office environment were and are still driven by advances in technology. The impact of computers on office work has resulted in numerous changes in office activities, procedures and the expectations from office managers and secretaries. This study investigated the level of knowledge and use of computer office application packages by secretaries and office managers in higher educational institutions in Ogun State and the implications of these on their performance enhancement. The study is an ex post facto research and adopted the survey design for the collection of data. Two hypotheses were formulated, and a questionnaire was developed and tested at 0.05 level of significance. All office managers and secretaries in the service of higher educational institutions in Ogun State, Nigeria formed the population of the study. The study was limited to federal institutions and a total of 120 office managers/secretaries were selected to form the sample such that 40 office managers/secretaries were randomly selected from each of the three Federal higher institutions in the State, that is Federal University of Agriculture, Abeokuta, Federal Polytechnic, Ilaro and Federal College of Education, Osiele, Abeokuta, Ogun State. Analysis of data and hypotheses tests were carried out with frequency counts, percentage and T-Test. The result indicated varying levels of awareness on office application tools with limited knowledge and use of computer application packages by office managers/secretaries. The results also showed that good knowledge and high use of office application tools enhance performance of office managers/secretaries. The study recommended that there should be maximum institutional resources and support and personal development on the part of the office managers to ensure update knowledge and maximal use of office application tools by office managers/secretaries.

Keywords: application packages, computer, office managers, performance enhancement

Procedia PDF Downloads 180

Authors: Julio Brégains, Ángel Carro, José-Manuel Andión

Abstract:

Virtual 3D objects constitute invaluable tools for teaching practical engineering subjects at all -from basic to advanced- educational levels. For instance, they can be equipped with animation or informative labels, manipulated by mouse movements, and even be immersed in a real environment through augmented reality. In this paper, we present the investigation and description of a set of applications prepared for creating, editing, and making use of interactive 3D models to represent electric and electronic devices and systems. Several examples designed with the described tools are exhibited, mainly to show their capabilities as educational technological aids, applicable not only to the field of electricity and electronics but also to a much wider range of technical areas.

Keywords: educational technology, Google model viewer, ICT educational tools, interactive teaching, new tools for teaching

Procedia PDF Downloads 75

Authors: Su Xiaohan, Jin Chicheng, Liu Yijing, Burra Venkata Durga Kumar

Abstract:

Energy-aware scheduling in real-time systems aims to minimize energy consumption, but issues related to resource reservation and timing constraints remain challenges. This study focuses on analyzing two scheduling algorithms, Fair-Share Scheduling (FFS) and Priority-Driven Preemptive Scheduling (PDPS), for solving these issues and energy-aware scheduling in real-time systems. Based on research on both algorithms and the processes of solving two problems, it can be found that Fair-Share Scheduling ensures fair allocation of resources but needs to improve with an imbalanced system load, and Priority-Driven Preemptive Scheduling prioritizes tasks based on criticality to meet timing constraints through preemption but relies heavily on task prioritization and may not be energy efficient. Therefore, improvements to both algorithms with energy-aware features will be proposed. Future work should focus on developing hybrid scheduling techniques that minimize energy consumption through intelligent task prioritization, resource allocation, and meeting time constraints.

Keywords: energy-aware scheduling, fair-share scheduling, priority-driven preemptive scheduling, real-time systems, optimization, resource reservation, timing constraints

Procedia PDF Downloads 119

Authors: Kim Lindsay F. Restua, Jeehan Kyra A. Rivero, Joneka Myles D. Taguba

Abstract:

Lean construction is defined as an approach in construction with the purpose of reducing waste in the process without compromising the value of the project. There are numerous lean construction tools that are applied in the construction process, which maximizes the efficiency of work and satisfaction of customers while minimizing waste. However, the complexity and differences of construction projects cause a rise in challenges on achieving the lean benefits construction can give, such as improvement in safety performance. The objective of this study is to determine the relationship between lean construction tools and their effects on safety performance. The relationship between construction tools applied in construction and safety performance is identified through Logistic Regression Analysis, and Correlation Analysis was conducted thereafter. Based on the findings, it was concluded that almost 60% of the factors listed in the study, which are different tools and effects of lean construction, were determined to have a significant relationship with the level of safety in construction projects.

Keywords: correlation analysis, lean construction tools, lean construction, logistic regression analysis, risk management, safety

Procedia PDF Downloads 187

Authors: Laili Farhana Md Ibharim, Maizatul Hayati Mohamad Yatim

Abstract:

The main purpose of this study is to evaluate the heuristic inspection of children’s authoring tools to develop games. The researcher has selected 15 authoring tools for making games specifically for educational purposes. Nine students from Diploma of Game Design and Development course and four lecturers from the computing department involved in this evaluation. A set of usability heuristic checklist used as a guideline for the students and lecturers to observe and test the authoring tools selected. The study found that there are just a few authoring tools that fulfill most of the heuristic requirement and suitable to apply to children. In this evaluation, only six out of fifteen authoring tools have passed above than five elements in the heuristic inspection checklist. The researcher identified that in order to develop a usable authoring tool developer has to emphasis children acceptance and interaction of the authoring tool. Furthermore, the authoring tool can be a tool to enhance their mental development especially in creativity and skill.

Keywords: authoring tool, children, game making, heuristic

Procedia PDF Downloads 349

Authors: Qinghua Zhang, Yanhe Zhu, Xiang Zhao, Yeqin Yang, Hongwei Jing, Guoan Zhang, Jie Zhao

Abstract:

This paper presents a wearable reconfigurable supernumerary robotic limb with differential actuated joints, which is lightweight, compact and comfortable for the wearers. Compared to the existing supernumerary robotic limbs which mostly adopted series structure with large movement space but poor carrying capacity, a prototype with the series-parallel configuration to better adapt to different task requirements has been developed in this design. To achieve a compact structure, two kinds of cable-driven mechanical structures based on guide pulleys and differential actuated joints were designed. Moreover, two different tension devices were also designed to ensure the reliability and accuracy of the cable-driven transmission. The proposed device also employed self-designed bearings which greatly simplified the structure and reduced the cost.

Keywords: cable-driven, differential actuated joints, reconfigurable, supernumerary robotic limb

Procedia PDF Downloads 222

Authors: Anil Kumar, Lavisha Gupta

Abstract:

Domain-driven design (DDD) is a pivotal methodology in software development, emphasizing the understanding and modeling of core business domains to create effective solutions. This paper explores the significance of DDD in aligning software architecture with real-world domains, with a focus on its application within Siemens. We delve into the challenges faced by development teams in understanding domains and propose DDD as a solution to bridge the gap between problem and solution spaces. Key concepts of DDD, such as Ubiquitous Language, Bounded Contexts, Entities, Value Objects, and Aggregates, are discussed, along with their practical implications in software development. Through a real project example in the automatic generation of hardware and software plant engineering, we illustrate how DDD principles can transform complex domains into coherent and adaptable software solutions, echoing Siemens' commitment to excellence and innovation.

Keywords: domain-driven design, software architecture, ubiquitous language, bounded contexts, entities, value objects, aggregates

Procedia PDF Downloads 41

Authors: Angel Daniel Muñoz Guzmán

Abstract:

E-learning is becoming more and more common every day. For online, hybrid or traditional face-to-face programs, there are some e-teaching platforms like Google classroom, Blackboard, Moodle and Canvas, and there are platforms for full e-learning like Coursera, edX or Udemy. These tools are changing the way students acquire knowledge at schools; however, in today’s changing world that is not enough. As students’ needs and skills change and become more complex, new tools will need to be added to keep them engaged and potentialize their learning. This is especially important in the current global situation that is changing everything: the Covid-19 pandemic. Due to Covid-19, education had to make an unexpected switch from face-to-face courses to digital courses. In this study, the students’ learning experience is analyzed by applying different e-tools and following the Tec21 Model and a flexible and digital model, both developed by the Tecnologico de Monterrey University. The evaluation of the students’ learning experience has been made by the quantitative PrEmo method of emotions. Findings suggest that the quantity of e-tools used during a course does not affect the students’ learning experience as much as how a teacher links every available tool and makes them work as one in order to keep the student engaged and motivated.

Keywords: student, experience, e-learning, e-teaching, e-tools, technology, education

Procedia PDF Downloads 111

Authors: Panagodage Janaka Sampath Fernando

Abstract:

Brain circulation has become a buzzword in the skilled migration literature. However, promoting brain circulation; returning of skilled migrants is challenging. Success stories in Asia, for instances, Taiwan, and China, are results of rigorous policy interventions of the respective governments. Nonetheless, the same policy mix has failed in other countries making it skeptical to attribute the success of brain circulation to the policy interventions per se. The paper seeks to answer whether the success of brain circulation within the Knowledge Services Industry (KSI) in Sri Lanka is a policy driven or a market driven process. Mixed method approach, which is a combination of case study and survey methods, was employed. Qualitative data derived from ten case studies of returned entrepreneurs whereas quantitative data generated from a self-administered survey of 205 returned skilled migrants (returned skilled employees and entrepreneurs) within KSI. The pull factors have driven the current flow of brain circulation within KSI but to a lesser extent, push factors also have influenced. The founding stone of the industry has been laid by a group of returned entrepreneurs, and the subsequent growth of the industry has attracted returning skilled employees. Sri Lankan government has not actively implemented the reverse brain drain model, however, has played a passive role by creating a peaceful and healthy environment for the industry. Therefore, in contrast to the other stories, brain circulation within KSI has emerged as a market driven process with minimal government interventions. Entrepreneurs play the main role in a market-driven process of brain circulation, and it is free from the inherent limitations of the reverse brain drain model such as discriminating non-migrants and generating a sudden flow of low-skilled migrants. Thus, to experience a successful brain circulation, developing countries should promote returned entrepreneurs by creating opportunities in knowledge-based industries.

Keywords: brain circulation, knowledge services industry, return migration, Sri Lanka

Procedia PDF Downloads 280

Authors: Yi Anson Lam, Siu Ming Yiu, Kam Pui Chow

Abstract:

Digital evidence has been tendering to courts at an exponential rate in recent years. As an industrial practice, most digital evidence is extracted and preserved using specialized and well-accepted forensics tools. On the other hand, the advancement in technologies enables the creation of quite a few emerging platforms such as Telegram, Signal etc. Existing (well-accepted) forensics tools were not designed to extract evidence from these emerging platforms. While new forensics tools require a significant amount of time and effort to be developed and verified, this paper tries to address how to fill this gap using quick-fix alternative methods for digital evidence collection (e.g., based on APIs provided by Apps) and discuss issues related to the admissibility of this evidence to courts with support from international courts’ stance and the circumstances of accepting digital evidence using these proposed alternatives.

Keywords: extraction, digital evidence, laws, investigation

Procedia PDF Downloads 68

Authors: D. Motlhanka, M. Mine, T. Bagaketse, T. Ngakane

Abstract:

There is a plethora of evidence from numerous sources that highlights the triumph of naturally derived medicinal plant metabolites with antioxidant capability for repurposed therapeutics. As post-COVID-19 syndromes and non-communicable diseases are on the rise, there is an urgent need to come up with new therapeutic strategies to address the problem. Non-communicable diseases and Post COVID-19 syndromes are classified as socio-economic diseases and are ranked high among threats to health security due to the economic burden they pose to any government budget commitment. Research has shown a strong link between accumulation of free radicals and oxidative stress critical for pathogenesis of non-communicable diseases and COVID-19 syndromes. Botswana has embarked on a robust programme derived from ethno-pharmacognosy and drug repurposing to address these threats to health security. In the current approach, a number of medicinally active plant-derived polyphenolics are repurposed and combined into new medicinal tools to target diabetes, Hypertension, Prostate Cancer and oxidative stress induced Post COVID 19 syndromes such as “brain fog”. All four formulants demonstrated Free Radical scavenging capacities above 95% at 200µg/ml using the diphenylpicryalhydrazyl free radical scavenging assay and the total phenolic contents between 6899-15000GAE(g/L) using the folin-ciocalteau assay respectively. These repurposed medicinal tools offer new hope and potential in the fight against emerging health threats driven by hyper-inflammation and free radical-induced oxidative stress.

Keywords: drug repurposed plant polyphenolics, free radical damage, non-communicable diseases, post COVID 19 syndromes

Procedia PDF Downloads 129

Authors: M. Graus, K. Westhoff, X. Xu

Abstract:

The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: data analytics, green production, industrial energy management, optimization, renewable energies, simulation

Procedia PDF Downloads 436

Authors: Hassam Muazzam

Abstract:

This paper devises an autonomous self-driven vehicle that is capable of taking a disabled person to his/her desired location using three different power sources (gasoline, solar, electric) without any control from the user, avoiding the obstacles in the way. The GPS co-ordinates of the desired location are sent to the main processing board via a GSM module. After the GPS co-ordinates are sent, the path to be followed by the vehicle is devised by Pythagoras theorem. The distance and angle between the present location and the desired location is calculated and then the vehicle starts moving in the desired direction. Meanwhile real-time data from ultrasonic sensors is fed to the board for obstacle avoidance mechanism. Ultrasonic sensors are used to quantify the distance of the vehicle from the object. The distance and position of the object is then used to make decisions regarding the direction of vehicle in order to avoid the obstacles using artificial neural network which is implemented using ATmega1280. Also the vehicle provides the feedback location at remote location.

Keywords: autonomous self-driven vehicle, obstacle avoidance, desired location, pythagoras theorem, neural network, remote location

Procedia PDF Downloads 410

Authors: Joshua Adan Valdez, Shawn Gallaher

Abstract:

Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport, modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116km3/year across the Beaufort Gyre. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff, and is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity-driven pycnocline as opposed to the temperature-driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and dynamic ocean topography (DOT). In situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time-consuming. Utilizing NASA’s ICESat-2’s DOT remote sensing capabilities and Air Expendable CTD (AXCTD) data from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), a linear regression model between DOT and freshwater content is determined along the 150° west meridian. Freshwater content is calculated by integrating the volume of water between the surface and a depth with a reference salinity of ~34.8. Using this model, we compare interannual variability in freshwater content within the gyre, which could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non-in situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially demonstrate the value of remote sensing tools to reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: Cryosphere, remote sensing, Arctic oceanography, climate modeling, Ekman transport

Procedia PDF Downloads 77

Authors: Eurico Lima Basto, Ofélia Pinto, Anabela Silva, Amélia Ferreira-Da-Silva

Abstract:

The purpose if this study is two-fold: on the one hand, to identify the accounting information systems implemented in third sector organizations, as well as its components, its tools and the decisions and control purposes they serve; on the other hand, and by confronting these two theories - institutional theory versus rational choice – we intent to go further by understanding the reasons behind the adoption of the aforementioned tools. Data has been collected from third sector organizations operating in Portugal. Our sample includes all juridical types of organizations such as foundations, cooperative, associations or private institutions of social solidarity. The questionnaire contained sixteen close-ended questions and four open-questions. Results confirm the theoretical perspective of institutionalism. Most third sector organizations operating in Portugal implemented only traditional accounting tools like standard accounting statements, cost accounting, budgeting. Moreover, there is clear evidence that the decisions about the implementation of these tools were coercive oriented. With this study it is intended to contribute to a better understanding of the context of third sector organizations in Portugal, in particular the role that accounting plays in this sector, with a special focus on management accounting tools, and the factors that influence their use and the degree of their usefulness in the process of decision making.

Keywords: third sector, accounting tools, institutional theory, Portugal, descriptive research

Procedia PDF Downloads 307

Authors: Nasim Eslamirad, Mahdi Rasoulinezhad, Francesco De Luca, Sadok Ben Yahia, Kimmo Sakari Lylykangas, Francesco Pilla

Abstract:

With the ongoing urbanization, cities face increasing environmental challenges impacting human well-being. To tackle these issues, data-driven approaches in urban analysis have gained prominence, leveraging urban data to promote sustainability. Integrating Machine Learning techniques enables researchers to analyze and predict complex environmental phenomena like Urban Heat Island occurrences in urban areas. This paper demonstrates the implementation of data-driven approach and interpretable Machine Learning algorithms with interpretability techniques to conduct comprehensive data analyses for sustainable urban design. The developed framework and algorithms are demonstrated for Tallinn, Estonia to develop sustainable urban strategies to mitigate urban heat waves. Geospatial data, preprocessed and labeled with UHI levels, are used to train various ML models, with Logistic Regression emerging as the best-performing model based on evaluation metrics to derive a mathematical equation representing the area with UHI or without UHI effects, providing insights into UHI occurrences based on buildings and urban features. The derived formula highlights the importance of building volume, height, area, and shape length to create an urban environment with UHI impact. The data-driven approach and derived equation inform mitigation strategies and sustainable urban development in Tallinn and offer valuable guidance for other locations with varying climates.

Keywords: data-driven approach, machine learning transparent models, interpretable machine learning models, urban heat island effect

Procedia PDF Downloads 41

Authors: Raphael Tuor, Denis Lalanne

Abstract:

The ATM research community is missing suitable tools to design, test, and validate new UI prototypes. Important stakes underline the implementation of both DSS and XAI methods into current systems. ML-based DSS are gaining in relevance as ATFM becomes increasingly complex. However, these systems only prove useful if a human can understand them, and thus new XAI methods are needed. The human-machine dyad should work as a team and should understand each other. We present xSky, a configurable benchmark tool that allows us to compare different versions of an ATC interface in conflict detection tasks. Our main contributions to the ATC research community are (1) a conflict detection task simulator (xSky) that allows to test the applicability of visual prototypes on scenarios of varying difficulty and outputting relevant operational metrics (2) a theoretical approach to the explanations of AI-driven trajectory predictions. xSky addresses several issues that were identified within available research tools. Researchers can configure the dimensions affecting scenario difficulty with a simple CSV file. Both the content and appearance of the XAI elements can be customized in a few steps. As a proof-of-concept, we implemented an XAI prototype inspired by the maritime field.

Keywords: air traffic control, air traffic simulation, conflict detection, explainable artificial intelligence, explainability, human-automation collaboration, human factors, information visualization, interpretability, trajectory prediction

Procedia PDF Downloads 160

Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

Abstract:

In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

Procedia PDF Downloads 386

Authors: Francys Souza, Alberto Ohashi, Dorival Leao

Abstract:

We present a general solution for finding the ε-optimal controls for non-Markovian stochastic systems as stochastic differential equations driven by Brownian motion, which is a problem recognized as a difficult solution. The contribution appears in the development of mathematical tools to deal with modeling and control of non-Markovian systems, whose applicability in different areas is well known. The methodology used consists to discretize the problem through a random discretization. In this way, we transform an infinite dimensional problem in a finite dimensional, thereafter we use measurable selection arguments, to find a control on an explicit form for the discretized problem. Then, we prove the control found for the discretized problem is a ε-optimal control for the original problem. Our theory provides a concrete description of a rather general class, among the principals, we can highlight financial problems such as portfolio control, hedging, super-hedging, pairs-trading and others. Therefore, our main contribution is the development of a tool to explicitly the ε-optimal control for non-Markovian stochastic systems. The pathwise analysis was made through a random discretization jointly with measurable selection arguments, has provided us with a structure to transform an infinite dimensional problem into a finite dimensional. The theory is applied to stochastic control problems based on path-dependent stochastic differential equations, where both drift and diffusion components are controlled. We are able to explicitly show optimal control with our method.

Keywords: dynamic programming equation, optimal control, stochastic control, stochastic differential equation

Procedia PDF Downloads 189

Authors: Adele Pierre, Nadia Amoroso

Abstract:

Changing climate patterns are resulting in increased in storm severity, challenging traditional methods of managing stormwater runoff. This research compares a system of bioswales to existing curb and gutter infrastructure in a post-industrial streetscape of Hamilton, Ontario. Using the geodesign process, including rule-based set parameters and an integrated approach combining geospatial information with stakeholder input, a section of Ottawa St. North was modelled to show how green infrastructure can ease the burden on aging, combined sewer systems. Qualitative data was gathered from residents of the neighbourhood through field notes, and quantitative geospatial data through GIS and site analysis. Parametric modelling was used to generate multiple design scenarios, each visualizing resulting impacts on stormwater runoff along with their calculations. The selected design scenarios offered both an aesthetically pleasing urban bioswale street-scape system while minimizing and controlling stormwater runoff. Interactive maps, videos and the 3D model were presented for stakeholder comment via ESRI’s (Environmental System Research Institute) web-scene. The results of the study demonstrate powerful tools that can assist landscape architects in designing, collaborating and communicating stormwater strategies.

Keywords: bioswale, geodesign, data-driven and rule-based design, geodesign, GIS, stormwater management

Procedia PDF Downloads 182

Authors: Ayesha Sanjana Kawser Parsha

Abstract:

S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

Procedia PDF Downloads 79

Authors: Zeynep Turhan

Abstract:

Digital tools can improve knowledge and awareness of strategies and skills for healthy and respectful intimate relationships. The website of the Healthy and Respectful Relationship Program has been developed and included five key videos about how to build healthy intimate relationships. This study examined the perspectives about informative videos by focusing on how individuals learn new information or challenge their preconceptions or attitudes regarding male privilege and women's oppression. Five individuals who received no-contact orders and attended group intervention were the sample of this study. The observation notes were the major methodology examining how participants responded to video tools. The data analysis method was the interpretative phenomenological analysis. The results showed that many participants found the tools useful in learning the types of violence and communication strategies. Nevertheless, obstacles to implementing some techniques were found in their relationships. These digital tools might enhance healthy and respectful relationships despite some limitations.

Keywords: healthy relationship, digital tools, intimate partner violence, perpetrators, video interventions

Procedia PDF Downloads 97

Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

Abstract:

The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

Procedia PDF Downloads 286

Authors: Omar Alshehri, Vic Lally

Abstract:

This paper examined the attitudes of using social media tools to support learning at a university in Saudi Arabia. Moreover, it investigated the students’ current usage of these tools and examined the barriers they could face during the use of social media tools in the education process. Participants in this study were 42 university students. A web-based survey was used to collect data for this study. The results indicate that all of the students were familiar with social media and had used at least one type of social media for learning. It was found out that all students had very positive attitudes towards the use of social media and welcomed using these tools as a supplementary to the curriculum. However, the results indicated that the major barriers to using these tools in learning were distraction, opposing Islamic religious teachings, privacy issues, and cyberbullying. The study recommended that this study could be replicated at other Saudi universities to investigate factors and barriers that might affect Saudi students’ attitudes toward using social media to support learning.

Keywords: barriers to social media use, benefits of social media use, higher education, Saudi Arabia, social media

Procedia PDF Downloads 168

Authors: Abdul Sattar Jamali, Imdad Ali Memon, Maqsood Ahmed Memon

Abstract:

Quality of production near to zero defects is an objective of every manufacturing and service organization. In order to maintain and improve the quality by reduction in defects, Statistical tools are being used by any organizations. There are many statistical tools are available to assess the quality. Keeping in view the importance of many statistical tools, traditional 7QC tools has been used in any manufacturing and automobile Industry. Therefore, the 7QC tools have been successfully applied at one of the Automobile Company Pakistan. Preliminary survey has been done for the implementation of 7QC tool in the assembly line of Automobile Industry. During preliminary survey two inspection points were decided to collect the data, which are Chassis line and trim line. The data for defects at Chassis line and trim line were collected for reduction in defects which ultimately improve productivity. Every 7QC tools has its benefits observed from the results. The flow charts developed for better understanding about inspection point for data collection. The check sheets developed for helps for defects data collection. Histogram represents the severity level of defects. Pareto charts show the cumulative effect of defects. The Cause and Effect diagrams developed for finding the root causes of each defects. Scatter diagram developed the relation of defects increasing or decreasing. The P-Control charts developed for showing out of control points beyond the limits for corrective actions. The successful implementation of 7QC tools at the inspection points at Automobile Industry concluded that the considerable amount of reduction on defects level, as in Chassis line from 132 defects to 13 defects. The total 90% defects were reduced in Chassis Line. In Trim line defects were reduced from 157 defects to 28 defects. The total 82% defects were reduced in Trim Line. As the Automobile Company exercised only few of the 7 QC tools, not fully getting the fruits by the application of 7 QC tools. Therefore, it is suggested the company may need to manage a mechanism for the application of 7 QC tools at every section.

Keywords: check sheet, cause and effect diagram, control chart, histogram

Procedia PDF Downloads 327

Authors: M. Naveed Akhter, Jawad Aslam, Omer Gillani

Abstract:

To aid and rehabilitate increasing number of patients suffering from spinal cord injury (SCI) and stroke, a lightweight, wearable, and 3D printable exoskeletal glove has been developed. Unlike previously developed metal or fabric-based exoskeletons, this research presents the development of soft exoskeletal glove made of thermoplastic polyurethane (TPU). The drive mechanism consists of a single motor-driven antagonistic tendon to perform extension or flexion of middle and index finger. The tendon-based differential drive has been incorporated to allow for grasping of irregularly shaped objects. The design features easy 3D-printability with TPU without a need for supports. The overall weight of the glove and the actuation unit is approximately 500g. Performance of the glove was tested on a custom test-bench with integrated load cells, and the grip strength was tested to be around 30N per finger while grasping objects of irregular shape.

Keywords: 3D printable, differential drive, exoskeletal glove, rehabilitation, single motor driven

Procedia PDF Downloads 144

Authors: Takwa Belwakess

Abstract:

With the wave of the digitization that invades the modern world, communication tools took their place in the world of business. As for organizations, being part of the digital era necessarily involves an evolution of the management style, mainly in processes management, knowing also as quality management system (QMS). For more than 50 years quality management standards have been adopted by organizations to prove their operational and financial performances. We believe that achieving a high-level of communication can lead to better quality management and greater customer satisfaction, which is essential to make sure long-term competitiveness. In this paper, a questionnaire survey was developed to investigate the use of collaboration tools such as Content Management System and Social Networks. Data from more than 100 companies based in France was analyzed, the results show that adopting new digital communication tools while applying quality management practices over a reasonable period, contributed to delivering a better implementation of the QMS for a better business performance.

Keywords: communication tools, content management system, digital, effectiveness, French companies, quality management system, quality management practices, social networks

Procedia PDF Downloads 268

Authors: J. Kontoleon, D.Gall, M.Pidskalny

Abstract:

FisherONE offers a distinct pedagogic model for senior secondary education that integrates advanced technology to meet the learning needs of Year 11 and 12 students across Catholic schools in Queensland. As a fully online platform, FisherONE employs pedagogy that combines flexibility with personalized, data-driven learning. The model leverages tools like the MaxHub hybrid interactive system and AI-powered learning assistants to create tailored learning pathways that promote student autonomy and engagement. This paper examines FisherONE’s success in employing pedagogic strategies through technology. Initial findings suggest that students benefit from the blended approach of virtual assessments and real-time support, even as AI-assisted tools remain in the proof-of-concept phase. The study outlines how FisherONE plans to continue refining its educational methods to better serve students in distance learning environments, specifically in challenging subjects like physics. The integration of technology in FisherONE enhances the effectiveness of teaching and learning, addressing common challenges in online education by offering scalable, individualized learning experiences. This approach demonstrates the future potential of technology in education and the role it can play in fostering meaningful student outcomes.

Keywords: AI-assisted learning, innovative pedagogy, personalized learning, senior education, technology in education

Procedia PDF Downloads 20

Authors: Mohammed Abu Shquier

Abstract:

This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

Procedia PDF Downloads 44