Search results for: digital transformation artificial intelligence

Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

Abstract:

Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

Procedia PDF Downloads 243

Authors: Kuo-Wei Liao, Jessica Gitomarsono

Abstract:

Bridge reliability against natural hazards such as floods or earthquakes is an interdisciplinary problem that involves a wide range of knowledge. Moreover, due to the global climate change, engineers have to design a structure against the multi-hazard threats. Currently, few of the practical design guideline has included such concept. The bridge foundation in Taiwan often does not have a uniform width. However, few of the researches have focused on safety evaluation of a bridge with a complex pier. Investigation of the scouring depth under such situation is very important. Thus, this study first focuses on investigating and improving the scour prediction formula for a bridge with complicated foundation via experiments and artificial intelligence. Secondly, a probabilistic design procedure is proposed using the established prediction formula for practical engineers under the multi-hazard attacks.

Keywords: bridge, reliability, multi-hazards, scour

Procedia PDF Downloads 355

Authors: Nikolina Ribarić

Abstract:

This paper compares the readiness of chemistry teachers to use information and communication technologies in chemistry in 2018. and 2021. A survey conducted in 2018 on a sample of teachers showed that most teachers occasionally use visualization and digitization tools in chemistry teaching (65%) but feel that they are not educated enough to use them (56%). Also, most teachers do not have adequate equipment in their schools and are not able to use ICT in teaching or digital tools for visualization and digitization of content (44%). None of the teachers find the use of digitization and visualization tools useless. Furthermore, a survey conducted in 2021 shows that most teachers occasionally use visualization and digitization tools in chemistry teaching (83%). Also, the research shows that some teachers still do not have adequate equipment in their schools and are not able to use ICT in chemistry teaching or digital tools for visualization and digitization of content (14%). Advances in the use of ICT in chemistry teaching are linked to pandemic conditions and the obligation to conduct online teaching. The share of 14% of teachers who still do not have adequate equipment to use digital tools in teaching is worrying.

Keywords: chemistry, digital content, e-learning, ICT, visualization

Procedia PDF Downloads 139

Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

Abstract:

In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

Procedia PDF Downloads 109

Authors: Hassan Sher

Abstract:

God has made this world with all of his essences and beautified it with his countless blessings. In Islam, no doubt, beauty is a very important characteristic but also an aspect of the body and the heart. In a world where the standards of beauty seem to change from year to year according to trends and norms. Moreover, in this world, many people want to look good and feel satisfied and will be willing to go through many ways for their ideal look. likewise, several products came into use for beautifying, cleansing, and promoting attractiveness. These products include components of cosmetics, they are utilized for health and beauty purposes. There are concerns regarding the existence of harmful or ḥarām chemicals, but With the advancement in (technology), it results in the transformation of unlawful and forbidden cosmetic products into permissible several new ingredients and products. The process of transforming certain items or products from one form to another, Muslim jurists tend to use terms like Istiḥālah (transformation).Istiḥālah is an Islamic principle unknown to many Muslims. LinguisticallyIstiḥālah carries the meaning of a transformation or a change in the nature of a thing into something else.According to the religious contact, Istiḥālah signifies a turning of a matter from a state of impurity or inedibility into a matter of different nature, name, properties, and characteristics (colour, taste, and smell) (Zuhayli, 1997). This principle, which is unanimously accepted by Muslim scholars, are breaths of fresh air to Muslims suffering from the suffocation of excessive prohibition. This will allow the invention to be utilized fully. This research tends to highlight the different ideological concepts of Istiḥālah from the perspective of Islamic Shariah and jurisprudence and its application in cosmetic products. However, the study focuses on the issues related to alcohol and pig ingredients in beauty products.

Keywords: istiḥālah. harām, jurisprudence, cosmetic, pig

Procedia PDF Downloads 117

Authors: Rachid Dehini, Brahim Berbaoui

Abstract:

The main objectives of shunt active power filter (SAPF) is to preserve the power system from unwanted harmonic currents produced by nonlinear loads, as well as to compensate the reactive power. The aim of this paper is to present a (PAPF) supplied by the Photovoltaic cells ,in such a way that the (PAPF) feeds the linear and nonlinear loads by harmonics currents and the excess of the energy is injected into the power system. In order to improve the performances of conventional (PAPF) This paper also proposes artificial neural networks (ANN) for harmonics identification and DC link voltage control. The simulation study results of the new (SAPF) identification technique are found quite satisfactory by assuring good filtering characteristics and high system stability.

Keywords: SAPF, harmonics current, photovoltaic cells, MPPT, artificial neural networks (ANN)

Procedia PDF Downloads 316

Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

Abstract:

In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

Procedia PDF Downloads 127

Authors: Anwesha Pathak

Abstract:

With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

Procedia PDF Downloads 54

Authors: Stavros Palavouzis, Alexandra Triantafyllopoulou, Aliki Tzima, Epaminondas Paplomatas

Abstract:

Mating-type genes are present in most filamentous fungi, even though teleomorphs for all species have not been recorded. Our study tries to explore the effect of different growth conditions on the expression of MAT genes in Neofusicoccum mediterraneum. As such, selected isolates were grown in potato dextrose broth or in water agar supplemented with pine needles under a 12 h photoperiod, as well as in constant darkness. Mycelia and spores were collected at different time points, and RNA extraction was performed, with the extracted product being used for cDNA synthesis. New primers for MAT gene expression were designed while qPCR results are underway. The second part of the study involved the isolation and cloning in a selected pGEM-T vector of the Botryosphaeria dothidea MAT1 1 1 and MAT1 2 1 mating genes, including flanking regions. As a next step, the genes were amplified using newly designed primers with engineered restriction sites. Amplicons were excised and subsequently sub-cloned in appropriate binary vectors. The constructs were afterward inserted into Agrobacterium tumefaciens and utilized for Agrobacterium-mediated transformation (ATMT) of Neofusicoccum mediterraneum. At the same time, the transformation of a Verticillium dahliae tomato race 1 strain (70V) was performed as a control. While the procedure was successful in regards to V. dahliae, transformed strains of N. mediterraneum could not be obtained. At present, a new transformation protocol, which utilizes a combination of protoplast and Agro transformation, is being evaluated.

Keywords: anamorph, heterothallism, perithecia, pycnidia, sexual stage

Procedia PDF Downloads 169

Authors: Tina Wu, Andrew Martin

Abstract:

The expansion of the Internet of Things (IoT) brings a new level of threat. Attacks on IoT are already being used by criminals to form botnets, launch Distributed Denial of Service (DDoS) and distribute malware. This opens a whole new digital forensic arena to develop forensic methodologies in order to have the capability to investigate IoT related crimes. However, existing proposed IoT forensic models are still premature requiring further improvement and validation, many lack details on the acquisition and analysis phase. This paper proposes an enhanced theoretical IoT digital forensic model focused on identifying and acquiring the main sources of evidence in a methodical way. In addition, this paper presents a theoretical acquisition framework of the different stages required in order to be capable of acquiring evidence from IoT devices.

Keywords: acquisition, Internet of Things, model, zoning

Procedia PDF Downloads 250

Authors: M. H. Hussain, I. Musirin, A. F. Abidin, S. R. A. Rahim

Abstract:

This paper presents the implementation of Artificial Bees Colony (ABC) algorithm in solving Directional OverCurrent Relays (DOCRs) coordination problem for near-end faults occurring in fixed network topology. The coordination optimization of DOCRs is formulated as linear programming (LP) problem. The objective function is introduced to minimize the operating time of the associated relay which depends on the time multiplier setting. The proposed technique is to taken as a technique for comparison purpose in order to highlight its superiority. The proposed algorithms have been tested successfully on 8 bus test system. The simulation results demonstrated that the ABC algorithm which has been proved to have good search ability is capable in dealing with constraint optimization problems.

Keywords: artificial bees colony, directional overcurrent relay coordination problem, relay settings, time multiplier setting

Procedia PDF Downloads 312

Authors: Tugce Talay, Kadir Erkan

Abstract:

In this study, the necessary steps for the design of axial flow permanent magnet motors are shown. The design and analysis of the engine were carried out based on ANSYS Maxwell program. The design parameters of the ANSYS Maxwell program and the artificial neural network system were established in MATLAB and the most efficient design parameters were found with the trained neural network. The results of the Maxwell program and the results of the artificial neural networks are compared and optimal working design parameters are found. The most efficient design parameters were submitted to the ANSYS Maxwell 3D design and the cogging torque was examined and design studies were carried out to reduce the cogging torque.

Keywords: AFPM, ANSYS Maxwell, cogging torque, design optimisation, efficiency, NNTOOL

Procedia PDF Downloads 204

Authors: Chris Landorf, Stephen Ward

Abstract:

This paper addresses a virtual environment approach to work integrated learning for students in construction-related disciplines. The virtual approach provides a safe and pedagogically rigorous environment where students can apply theoretical knowledge in a simulated real-world context. The paper describes the development of a 4-dimensional digital construction environment and associated learning activities funded by the Australian Office for Learning and Teaching. The environment was trialled with over 1,300 students and evaluated through questionnaires, observational studies and coursework analysis. Results demonstrate a positive impact on students’ technical learning and collaboration skills, but there is need for further research in relation to critical thinking skills and work-readiness.

Keywords: architectural education, construction industry, digital learning environments, immersive learning

Procedia PDF Downloads 389

Authors: Madad Ali

Abstract:

In the contemporary landscape of international travel, the infusion of digital technologies has given rise to innovative business models that are reshaping the dynamics of tourism. This research delves into the transformative potential of these novel business models within the realm of digital tourism and their multifaceted impact on local businesses, residents' quality of life, and the overall travel experience. The study focuses on the captivating backdrop of Yunnan Province, China, renowned for its rich cultural heritage and diverse ethnic minorities, to uncover the intricate nuances of this phenomenon. The primary objectives of this research encompass the identification and categorization of emerging business models facilitated by digital technologies, their implications on tourist engagement, and their integration into the operations of local businesses. By employing a mixed-methods approach, blending qualitative techniques like interviews and content analysis with quantitative tools such as surveys and data analysis, the study provides a comprehensive evaluation of these business models' effects on various dimensions of the tourism landscape. The distinctiveness of this research lies in its exclusive focus on Yunnan Province, China. By concentrating on Yunnan Province, the research contributes exceptional insights into the interplay between digital tourism, ethnic diversity, cultural heritage, and sustainable development. The study's outcomes hold significance for both scholarly discourse and the stakeholders involved in shaping the region's tourism strategies.

Keywords: business model, digital tourism, international travel, local businesses, quality of life

Procedia PDF Downloads 40

Authors: Yingxu Wang, Jianhua Lu, Jun Peng, Jiawei Zhang

Abstract:

The fundamental demand in contemporary intelligent science towards Autonomous AI (AI*) is the creation of unprecedented formal means of Intelligent Mathematics (IM). It is discovered that natural intelligence is inductively created rather than exhaustively trained. Therefore, IM is a family of algebraic and denotational mathematics encompassing Inference Algebra, Real-Time Process Algebra, Concept Algebra, Semantic Algebra, Visual Frame Algebra, etc., developed in our labs. IM plays indispensable roles in training-free AI* theories and systems beyond traditional empirical data-driven technologies. A set of applications of IM-driven AI* systems will be demonstrated in contemporary intelligence science, AI*, and cognitive computers.

Keywords: intelligence mathematics, foundations of intelligent science, autonomous AI, cognitive computers, inference algebra, real-time process algebra, concept algebra, semantic algebra, applications

Procedia PDF Downloads 39

Authors: Judit Vilarmau

Abstract:

Generative AI is emerging rapidly and transforming higher education in many ways, occasioning new challenges and disrupting traditional models and methods. The studies and authors explored remark on the impact on the ethics, curriculum, and pedagogical methods. Students are increasingly using generative AI for study, as a virtual tutor, and as a resource for generating works and doing assignments. This point is crucial for educators to make sure that students are using generative AI with ethical considerations. Generative AI also has relevant benefits for educators and can help them personalize learning experiences and promote self-regulation. Educators must seek and explore tools like ChatGPT to innovate without forgetting an ethical and pedagogical perspective. Eighteen studies were systematically reviewed, and the findings provide implementation guidelines with pedagogical and ethical considerations.

Keywords: ethics, generative artificial intelligence, guidelines, higher education, pedagogy

Procedia PDF Downloads 63

Authors: Badr M. Alshammari, T. Guesmi

Abstract:

This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.

Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones

Procedia PDF Downloads 242

Authors: Samar Alarif

Abstract:

Smart sustainable educational campuses are the latest paradigm of innovation in the education domain. Campuses become a hub for sustainable environmental innovations. University has a vital role in paving the road for digital transformations in the infrastructure domain by preparing skilled engineers and specialists. The open digital platform enables smart campuses to simulate real education experience by managing their infrastructure within the curriculums. Moreover, it allows the engagement between governments, businesses, and citizens to push for innovation and sustainable services. Urban and building information modeling platforms have recently attained widespread attention in smart campuses due to their applications and benefits for creating the campus's digital twin in the form of an open digital platform. Qualitative and quantitative strategies were used in directing this research to develop and validate the UIM/BIM platform benefits for smart campuses FM and its impact on the institution's sustainable vision. The research findings are based on literature reviews and case studies of the TU berlin El-Gouna campus. Textual data will be collected using semi-structured interviews with actors, secondary data like BIM course student projects, documents, and publications related to the campus actors. The study results indicated that UIM/BIM has several benefits for the smart campus. Universities can achieve better capacity-building by integrating all the actors in the UIM/BIM process. Universities would achieve their community outreach vision by launching an online outreach of UIM/BIM course for the academic and professional community. The UIM/BIM training courses would integrate students from different disciplines and alumni graduated as well as engineers and planners and technicians. Open platforms enable universities to build a partnership with the industry; companies should be involved in the development of BIM technology courses. The collaboration between academia and the industry would fix the gap, promote the academic courses to reply to the professional requirements, and transfer the industry's academic innovations. In addition to that, the collaboration between academia, industry, government vocational and training centers, and civil society should be promoted by co-creation workshops, a series of seminars, and conferences. These co-creation activities target the capacity buildings and build governmental strategies and policies to support expanding the sustainable innovations and to agree on the expected role of all the stakeholders to support the transformation.

Keywords: smart city, smart educational campus, UIM, urban platforms, sustainable campus

Procedia PDF Downloads 108

Authors: Seham Elia Moussa Shenouda

Abstract:

The relationship between development and human rights has long been the subject of academic debate. To understand the dynamics between these two concepts, various principles are adopted, from the right to development to development-based human rights. Despite the initiatives taken, the relationship between development and human rights remains unclear. However, the overlap between these two views and the idea that efforts should be made in the field of human rights have increased in recent years. It is then evaluated whether the right to sustainable development is acceptable or not. The article concludes that the principles of sustainable development are directly or indirectly recognized in various human rights instruments, which is a good answer to the question posed above. This book therefore cites regional and international human rights agreements such as , as well as the jurisprudence and interpretative guidelines of human rights institutions, to prove this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

Procedia PDF Downloads 13

Authors: R. Bouhennache, T. Bouden, A. A. Taleb, A. Chaddad

Abstract:

In this paper we propose a method to map the urban areas. The method uses an arithmetic calculation processed from the land features indexes and Tasseled cap transformation TC of multi spectral Thematic Mapper Landsat TM image. For this purpose the derived indexes image from the original image such SAVI the soil adjusted vegetation index, UI the urban Index, and EBBI the enhanced built up and bareness index were staked to form a new image and the bands were uncorrelated, also the Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification approaches were first applied on the new image TM data using the reference spectra of the spectral library and subsequently the four urban, vegetation, water and soil land cover categories were extracted with their accuracy assessment.The urban features were represented using a logic calculation applied to the brightness, UI-SAVI, NDBI-greenness and EBBI- brightness data sets. The study applied to Blida and mentioned that the urban features can be mapped with an accuracy ranging from 92 % to 95%.

Keywords: EBBI, SAVI, Tasseled Cap Transformation, UI

Procedia PDF Downloads 471

Authors: Chih Yuan Chen, Chien Chon Chen, Jin-Shyong Lin

Abstract:

The microstructure characterization of tempered nanocrystalline bainitic steel is investigated in the present study. It is found that two types of plastic relaxation, dislocation debris and nanotwin, occurs in the displacive transformation due to relatively low transformation temperature and high carbon content. Because most carbon atoms trap in the dislocation, high dislocation density can be sustained during the tempering process. More carbides only can be found in the high tempered temperature due to intense recovery progression.

Keywords: nanostructure bainitic steel, tempered, TEM, nano-twin, dislocation debris, accommodation

Procedia PDF Downloads 515

Authors: Arūnas Burinskas

Abstract:

Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, industry 4.0, industrial organisation, monopolistic competition

Procedia PDF Downloads 125

Authors: Ana-Marija Stjepić, Luka Sušac, Dalia Suša Vugec

Abstract:

In the last few years, examples from scientific literature and business practices show that the adoption of technological innovations increases enterprises' performance. Recently, when it comes to the field of information technology innovation, business intelligence systems (BISs) have drawn a significant amount of attention of the scientific circles. BISs can be understood as a form of technological innovation which can bring certain benefits to the organizations that are adopting it. Therefore, the aim of this paper is twofold: (1) to define determinants of successful BISs adoption in small and medium enterprises and thus contribute to this neglected research area and (2) to present the current state of BISs adoption in small and medium-sized companies. In order to do so, determinants are defined and classified into three dimensions, according to the Technology – Organization – Environment (TOE) theoretical framework that describes the impact of each dimension on technological innovations adoption. Moreover, paper brings a case study presenting the adoption of BISs in practice within an organization from tertiary (service) industry sector. Based on the results of the study, guidelines for more efficient, faster and easier BISs adoption are presented.

Keywords: adoption, business intelligence, business intelligence systems, case study, TOE framework

Procedia PDF Downloads 131

Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

Abstract:

Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

Procedia PDF Downloads 131

Authors: Shih-Heng Tung, Ming-Hsiang Shih, Wen-Pei Sung

Abstract:

Because of the rapid development of digital camera and computer, digital image correlation method has drawn lots of attention recently and has been applied to a variety of fields. However, the image distortion is inevitable when the image is captured through a lens. This image distortion problem can result in an innegligible error while using digital image correlation method. There are already many different ways to correct the image distortion, and most of them require specific image patterns or precise control points. A new distortion correction method is proposed in this study. The proposed method is based on the fact that a flat surface should keep flat when it is measured using three-dimensional (3D) digital image measurement technique. Lens distortion can be divided into radial distortion, decentering distortion and thin prism distortion. Because radial distortion has a more noticeable influence than the other types of distortions, this method deals only with radial distortion. The simplified 3D digital image measurement technique is adopted to measure the surface coordinates of a flat specimen. Then the gradient method is applied to find the best correction parameters. A few experiments are carried out in this study to verify the correctness of this method. The results show that this method can achieve a good accuracy and it is suitable for both large and small distortion conditions. The most important advantage is that it requires neither mark with specific pattern nor precise control points.

Keywords: 3D DIC, radial distortion, distortion correction, planarity

Procedia PDF Downloads 539

Authors: Peter A. L’vov, Roman S. Konovalov, Alexey A. L’vov

Abstract:

The paper presents the advanced digital modification of the conventional current loop circuit for pressure piezoelectric transducers. The optimal DSP algorithms of current loop responses by the maximum likelihood method are applied for diminishing of measurement errors. The loop circuit has some additional advantages such as the possibility to operate with any type of resistance or reactance sensors, and a considerable increase in accuracy and quality of measurements to be compared with AC bridges. The results obtained are dedicated to replace high-accuracy and expensive measuring bridges with current loop circuits.

Keywords: current loop, maximum likelihood method, optimal digital signal processing, precise pressure measurement

Procedia PDF Downloads 511

Authors: Guadalupe López-Bonilla

Abstract:

Students of all educational levels participate in literacy practices that may involve print or digital media. Scholars from the New Literacy Studies distinguish practices that fulfill institutional purposes such as those established at schools from literate practices aimed at doing other kinds of activities, such as reading instructions in order to play a video game; the first are known as institutional practices while the latter are considered vernacular literacies. When students perform these kinds of activities they engage with print and digital media according to the demands of the task. In this paper, it is aimed to discuss the results of a research project focusing on literacy practices of high school students at 10 urban cybercafés in Mexico. The main objective was to analyze the literacy practices of students performing both school tasks and vernacular literacies. The methodology included a focused ethnography with online and face to face observations of 10 high school students (5 male and 5 female) and interviews after performing each task. In the results, it is presented how students treat texts as open, dynamic and relational artifacts when engaging in vernacular literacies; while texts are conceived as closed, authoritarian and fixed documents when performing school activities. Samples of each type of activity are shown followed by a discussion of the pedagogical implications for improving school literacy.

Keywords: digital literacy, text, school literacy, vernacular practices

Procedia PDF Downloads 255

Authors: Shraddha Jain Sharma, Ratnalata Gupta

Abstract:

Predicting stock movements in the financial market is both difficult and rewarding. Analysts and academics are increasingly using advanced approaches such as machine learning techniques to anticipate stock price patterns, thanks to the expanding capacity of computing and the recent advent of graphics processing units and tensor processing units. Stock market prediction is a type of time series prediction that is incredibly difficult to do since stock prices are influenced by a variety of financial, socioeconomic, and political factors. Furthermore, even minor mistakes in stock market price forecasts can result in significant losses for companies that employ the findings of stock market price prediction for financial analysis and investment. Soft computing techniques are increasingly being employed for stock market prediction due to their better accuracy than traditional statistical methodologies. The proposed research looks at the need for soft computing techniques in stock market prediction, the numerous soft computing approaches that are important to the field, past work in the area with their prominent features, and the significant problems or issue domain that the area involves. For constructing a predictive model, the major focus is on neural networks and fuzzy logic. The stock market is extremely unpredictable, and it is unquestionably tough to correctly predict based on certain characteristics. This study provides a complete overview of the numerous strategies investigated for high accuracy prediction, with a focus on the most important characteristics.

Keywords: stock market prediction, artificial intelligence, artificial neural networks, fuzzy logic, accuracy, deep learning, machine learning, stock price, trading volume

Procedia PDF Downloads 72

Authors: Sergey Chirun

Abstract:

Using of a combination of institutional analysis and network access has allowed the author to identify the characteristics of the informal institutions of regional political power and political regimes. According to the author, ‘field’ of activity of post-Soviet regimes, formed under the influence of informal institutions, often contradicts democratic institutional regional changes which are aimed at creating of a legal-rational type of political domination and balanced model of separation of powers. This leads to the gap between the formal structure of institutions and the real nature of power, predetermining the specific character of the existing political regimes.

Keywords: authoritarianism, institutions, political regime, social networks, transformation

Procedia PDF Downloads 476

Authors: Marta Gràcia, Ana Luisa Adam-Alcocer, Jesús M. Alvarado, Verónica Quezada, Tere Zarza, Priscila Garza

Abstract:

In secondary education, integrating linguistic content and reflection on it is a crucial challenge that should be included in course plans to enhance students' oral communication competence. In secondary education classrooms, a continuum can be identified in relation to teaching methodologies: 1) the traditional teacher-dominated transmission approach, which is described as that in which teachers transmit content to students unidirectionally; 2) dialogical, bidirectional teaching approach that encourages students to adopt a critical vision of the information provided by the teacher or that is generated through students’ discussion. In this context, the EVALOE-DSS (Assessment Scale of Oral Language Teaching in the School Context-Decision Support System) digital instrument has emerged to help teachers in transforming their classes into spaces for communication, dialogue, reflection, evaluation of the learning process, teaching linguistic contents, and to develop curricular competencies. The tool includes various resources, such as a tutorial with the objectives and an initial screen for teachers to describe the class to be evaluated. One of the main resources of the digital instrument consists of 30 items-actions with three qualitative response options (green, orange, and red face emoji) grouped in five dimensions. In the context of the participation of secondary education teachers in a professional development program using EVALOE-DSS, a digital tool resource aimed to generate more participatory, interactive, dialogic classes, the objectives of the study were: 1) understanding the changes in classrooms’ dynamics and in the teachers’ strategies during their participation in the professional developmental program; 2) analyzing the impact of these changes in students’ oral language development according to their teachers; 3) Deeping on the impact of these changes in the students’ assessment of the classes and the self-assessment of oral competence; 4) knowing teachers’ assessment and reflections about their participation in the professional developmental program. Participants were ten teachers of different subjects and 250 students of secondary education (16-18 years) schools in Spain. The principal instrument used was the digital tool EVALOE-DSS. For 6 months, teachers used the digital tool to reflect on their classes, assess them (their actions and their students’ actions), make decisions, and introduce changes in their classes to be more participatory, interactive, and reflective about linguistic contents. Other collecting data instruments and techniques used during the study were: 1) a questionnaire to assess students’ oral language competence before and at the end of the study, 2) a questionnaire for students’ assessment of the characteristics of classes, 3) teachers’ meetings during the professional developmental program to reflect collaboratively on their experience, 4) questionnaire to assess teacher’s experience during their participation in the professional developmental program, 5) focus group meetings between the teachers and two researchers at the end of the study. The results showed relevant changes in teaching strategies, in the dynamics of the classes, which were more interactive, participative, dialogic and self-managed by the students. Both teachers and students agree about the progressive classes’ transformation into spaces for communication, discussion, and reflection on the language, its development, and its use as an essential instrument to develop curricular competencies.

Keywords: digital tool, individual and collaborative reflection, oral language competence, professional development program, secondary education

Procedia PDF Downloads 12