Search results for: Competitive Intelligence

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

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Authors: Nikolett Deutsch, Éva Pintér, Péter Bagó, Miklós Hetényi

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Strategic technology management has emerged and evolved parallelly with strategic management paradigms. It focuses on the opportunity for organizations operating mainly in technology-intensive industries to explore and exploit technological capabilities upon which competitive advantage can be obtained. As strategic technology management involves multifunction within an organization, requires broad and diversified knowledge, and must be developed and implemented with business objectives to enable a firm’s profitability and growth, excellence in strategic technology management provides unique opportunities for organizations in terms of building a successful future. Accordingly, a framework supporting the evaluation of the technological readiness level of management can significantly contribute to developing organizational competitiveness through a better understanding of strategic-level capabilities and deficiencies in operations. In the last decade, several innovation maturity assessment models have appeared and become designated management tools that can serve as references for future practical approaches expected to be used by corporate leaders, strategists, and technology managers to understand and manage technological capabilities and capacities. The aim of this paper is to provide a comprehensive review of the state-of-the-art innovation maturity frameworks, to investigate the critical lessons learned from their application, to identify the similarities and differences among the models, and identify the main aspects and elements valid for the field and critical functions of technology management. To this end, a systematic literature review was carried out considering the relevant papers and articles published in highly ranked international journals around the 27 most widely known innovation maturity models from four relevant digital sources. Key findings suggest that despite the diversity of the given models, there is still room for improvement regarding the common understanding of innovation typologies, the full coverage of innovation capabilities, and the generalist approach to the validation and practical applicability of the structure and content of the models. Furthermore, the paper proposes an initial structure by considering the maturity assessment of the technological capacities and capabilities - i.e., technology identification, technology selection, technology acquisition, technology exploitation, and technology protection - covered by strategic technology management.

Keywords: innovation capabilities, innovation maturity models, technology audit, technology management, technology management maturity models

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Authors: Oscar Covarrubias, Diane Ghanem, Christopher Murdock, Babar Shafiq

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Introduction: ChatGPT is an advanced language AI tool designed to understand and generate human-like text. The aim of this study is to assess the ability of ChatGPT-4 to re-write orthopaedic trauma patient education materials at the recommended 6th-grade level. Methods: Two independent reviewers accessed ChatGPT-4 (chat.openai.com) and gave identical instructions to simplify the readability of provided text to a 6th-grade level. All trauma-related articles by the Orthopaedic Trauma Association (OTA) and American Academy of Orthopaedic Surgeons (AAOS) were sequentially provided. The academic grade level was determined using the Flesh-Kincaid Grade Level (FKGL) and Flesch Reading Ease (FRE). Paired t-tests and Wilcox-rank sum tests were used to compare the FKGL and FRE between the ChatGPT-4 revised and original text. Inter-rater correlation coefficient (ICC) was used to assess variability in ChatGPT-4 generated text between the two reviewers. Results: ChatGPT-4 significantly reduced FKGL and increased FRE scores in the OTA (FKGL: 5.7±0.5 compared to the original 8.2±1.1, FRE: 76.4±5.7 compared to the original 65.5±6.6, p < 0.001) and AAOS articles (FKGL: 5.8±0.8 compared to the original 8.9±0.8, FRE: 76±5.5 compared to the original 56.7±5.9, p < 0.001). On average, 14.6% of OTA and 28.6% of AAOS articles required at least two revisions by ChatGPT-4 to achieve a 6th-grade reading level. ICC demonstrated poor reliability for FKGL (OTA 0.24, AAOS 0.45) and moderate reliability for FRE (OTA 0.61, AAOS 0.73). Conclusion: This study provides a novel, simple and efficient method using language AI to optimize the readability of patient education content which may only require the surgeon’s final proofreading. This method would likely be as effective for other medical specialties.

Keywords: artificial intelligence, AI, chatGPT, patient education, readability, trauma education

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Authors: Sareh Enjavi

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In recent years, the field of visual communication design has seen a significant shift in the way that art is created and consumed, with the advent of new technologies like virtual reality, augmented reality, and artificial intelligence. This paper explores the ways in which technology is changing the landscape of visual communication design, and how designers are incorporating new technological tools into their artistic practices. The primary objective of this research paper is to investigate the ways in which technology is influencing the creative process of designers and artists in the field of visual communication design. The paper also aims to examine the challenges and limitations that arise from the intersection of art and technology in visual communication design, and to identify strategies for overcoming these challenges. Drawing on examples from a range of fields, including advertising, fine art, and digital media, this paper highlights the exciting innovations that are emerging as artists and designers use technology to push the boundaries of traditional artistic expression. The paper argues that embracing technological innovation is essential for the continued evolution of visual communication design. By exploring the intersection of art and technology, designers can create new and exciting visual experiences that engage and inspire audiences in new ways. The research also contributes to the theoretical and methodological understanding of the intersection of art and technology, a topic that has gained significant attention in recent years. Ultimately, this paper emphasizes the importance of embracing innovation and experimentation in the field of visual communication design, and highlights the exciting innovations that are emerging as a result of the intersection of art and technology, and emphasizes the importance of embracing innovation and experimentation in the field of visual communication design.

Keywords: visual communication design, art and technology, virtual reality, interactive art, creative process

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Authors: K. Caban-Piaskowska

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The aim of the article is to show how the role of a designer has changed, from the point of view of human resources management and thanks to the increased importance of design management, and is to present how a rehabilitation product, through technology approach to designing, becomes a universal product. Designing for the disabled is a very undiscovered area on the pattern-designing market, most often because it is associated with devices which support rehabilitation. In consequence, it means that the realizations have a limited group of receivers and are not that attractive for designers. The relation between using modern design in building rehabilitation devices and increasing the efficiency of treatment and physiotherapy. Using modern technology can have marketing significance. Rehabilitation products designed and produced in a modern way makes an impression that experts and professionals are involved in the lives of the user – patient. In order to illustrate the problem presented above i.e. Creating a rehabilitation product as an example of design management, the case study method was used in the research. The analysis of the case was created on the basis of an interview conducted by the author with a designer who took part in meetings with people who use rehabilitation and their physiotherapists, and created universal products in Poland in the years of 2012 to 2017. Usually, engineers and constructors deal with creating products which remind us of old torture devices, however, they are indestructible in construction. Such image of those products for the disabled clearly indicates that it is a wonderful niche for designers and emphasizes the need to make those products more attractive and innovative. Products for the disabled cannot be limited to rehabilitation equipment only e.g. wheelchairs or standing frames. Introducing the idea of universal designing can significantly broaden the circle of pattern-designing receivers – everyday-use items – with the disabled people. Fulfilling these criteria will decide about the advantage on the competitive market. It is possible due to the usage of the design management concept in the functioning of an organization. Using modern technology and materials in the production of equipment, and changing the role of a designer broadening the circle of receivers by designing a wide use process which makes it possible to use the product by people with various needs. What is more, introducing rehabilitation functions in everyday-use items can also become an innovative accent in designing. In the reality of the market, each group of users can and should be treated as a problem and a realization task.

Keywords: design management, innovation, rehabilitation product, universal product

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Authors: Ali Asgary, Haopeng Zhou, Ghassem Tofighi

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Use of virtual (VR), augmented reality (AR), and extended reality technologies for training and education has increased in recent years as more hardware and software tools have become available and accessible to larger groups of users. Similarly, the applications of these technologies in earthquake related training and education are on the rise. Several studies have reported promising results for the use of VR and AR for evacuation behaviour and training under earthquake situations. They simulate the impacts that earthquake has on buildings, buildings’ contents, and how building occupants and users can find safe spots or open paths to outside. Considering that considerable number of earthquake injuries and fatalities are linked to the behaviour, our goal is to use these technologies to reduce the impacts of building contents on people. Building on our artificial intelligence (AI) based indoor earthquake risk assessment application that enables users to use their mobile device to assess the risks associated with building contents during earthquakes, we develop a virtual reality application to demonstrate the behavior of different building contents during earthquakes, their associate moving, spreading, falling, and collapsing risks, and their risk mitigation methods. We integrate realistic seismic models, building contents behavior with and without risk mitigation measures in virtual reality environment. The application can be used for training of architects, interior design experts, and building users to enhance indoor safety of the buildings that can sustain earthquakes. This paper describes and demonstrates the application development background, structure, components, and usage.

Keywords: virtual reality, earthquake damage, building content, indoor risks, earthquake risk mitigation, interior design, unity game engine, oculus

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Authors: Kerolis Samoul Zaghloul Noaman

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area law is the brand new access in the basket of worldwide law in the latter half of the 20 th Century. inside the last hundred and fifty years, courts and pupils advanced a consensus that, the custom is an vital supply of global law. Article 38(1) (b) of the statute of the international court of Justice identified global custom as a supply of global law. country practices and usages have a more role to play in formulating commonplace international regulation. This paper examines those country practices which may be certified to emerge as global standard law. due to the fact that, 1979 (after Moon Treaty) no hard law had been developed within the vicinity of space exploration. It attempts to link among country practices and custom in area exploration and development of standard global regulation in area activities. The paper makes use of doctrinal approach of felony research for inspecting the current questions of worldwide regulation. The paper explores exceptional worldwide prison files which include general meeting Resolutions, Treaty standards, working papers of UN, cases relating to commonplace global law and writing of jurists regarding area law and standard international law. it's far argued that, ideas such as common background of mankind, non-navy region, sovereign equality, nuclear weapon unfastened area and protection of outer area environment, etc. evolved nation practices a number of the worldwide community which can be certified to turn out to be international customary regulation.

Keywords: social networks privacy issues, social networks security issues, social networks privacy precautions measures, social networks security precautions measures

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Authors: Samuel Nderitu Muchiri, Tracy Wangechi Maina

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Truck drivers face a myriad of challenges in their profession. Enhancements in logistics effectiveness can be pivotal in propelling economic developments. The specific objective of the study was to assess the influence of driver distraction on crash risk. The study is significant as it elucidates best practices that truck drivers can embrace in an effort to enhance road safety. These include amalgamating behaviors that enable drivers to fruitfully execute multifaceted functions such as finding and following routes, evading collisions, monitoring speed, adhering to road regulations, and evaluating vehicle systems’ conditions. The analysis involved an empirical review of ten previous studies related to the research topic. The articles revealed that driver distraction plays a substantial role in road accidents and other crucial road security incidents across the globe. Africa depends immensely on the freight transport sector to facilitate supply chain operations. Several studies indicate that drivers who operate primarily on rural roads, such as those found in Sub-Saharan Africa, have an increased propensity to engage in distracted activities such as cell phone usage while driving. The findings also identified the need for digitalization in truck driving operations, including carrier management techniques such as fatigue management, artificial intelligence, and automating functions like cell phone usage controls. The recommendations can aid policymakers and commercial truck carriers in deepening their understanding of driver distraction and enforcing mitigations to foster road safety.

Keywords: truck drivers, distraction, digitalization, crash risk, road safety

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Authors: Arunas Emeljanovas, Brigita Mieziene, Tomas Venckunas

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Background statement: Level of aerobic capacity in school age children provides important information about the current and future cardiovascular, skeletal and mental health. It is widely recognised that risk factors for modern chronic diseases of the adults have their origins in childhood and adolescence. The aim of the study was to analyse the trends of aerobic capacity across decades within groups of gender and age. Methods. The research included data of participants from the three nationally representative cohort studies performed in Lithuania in the years 1992, 2002 and 2012 among 11 to 18-years-old school children. Total of 18,294 school children were recruited for testing. Only those who had their body weight and height measured and completed 20 m shuttle endurance test were included in the analysis. The total number of students included in the analyses was 15,213 (7608 boys and 7605 girls). The permission to conduct the study was obtained from the Lithuanian Bioethics Committee (permission number BE-2-45). Major findings: Results are performed across gender and age groups. The comparison of shuttle endurance test, controlling for body mass index, indicated that in general there is a constant decrease of aerobic capacity across decades in both genders and age groups. The deterioration in aerobic capacity in boys accounted for 17 to 43 percent across age groups within decades. The biggest decrease was in 14 years-old boys. The deterioration in girls accounted for 19 to 37 percent across age groups with the highest decrease in 11 years-old girls. Though, girls had lower levels of aerobic capacity through all age groups and across three decades. Body mass index, as a covariate, accounted for up to six percent in deterioration of aerobic capacity. Final statement: The detected relationships may reflect the level and pattern of engagement in physical activity and sports where increased activity associates with superior performance in the tests because of the upregulated physiological function and instigated competitive/motivational level. The significance of the decade indirectly supports the importance of the recently changed activity among schoolchildren for this relationship.

Keywords: aerobic capacity, cardiovascular health, endurance, school age children

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Authors: Francisco Toledo-Castillo, Pilar Peiró-Torres, María Josefa Sospedra-Baeza, Sergio Hidalgo-Fuentes

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The communication presented is about tasks that are been developed in the research project “safeRoute”, “Information safety system for professional road driving” (IPT-2012-110-370000). This R&D project was proposed by the consortium formed by Fagor Electronica la SEU 3 and the University of Valencia to the Ministry of Economy and Competitiveness, which approved it inside the INNPACTO subprogramme grants. Through this type of calls, the Ministry promote the innovative capacity of the Spanish companies and turn on the mechanism for competing internationally. With this kind of calls, private investments for technological and industrial development join their R & D resources with public entities to implement innovative project that could have an international exposure. Thus INNPACTO subprogramme promotes the creation of research projects with public-private partnerships that create exploitable final products. The “safeRoute” Project pretends develop a tool to help to make more safety the travels of commercial transport vehicles of goods and passengers. To achieve its objectives, the project is focused in three main lines of research: vehicle safety, the safety of the roads that they are using, and the safety which drivers do their job, their behaviour while they are driving. To improve safety, the project gives information about these three factors to all people that are involved in the safety of the professional transport. These three factors have influence to the occurrence of traffic accidents, thanks to the information provided and treated about these factors, we can achieve a significant reduction in occupational accidents in the transport sector. SafeRoute provide information about routes, vehicles, and driver behaviours, and in this manner pretends provide to transport companies a tool which could result in a safer driving results and could reduce their costs related to traffic accidents of their vehicles, in that way, this tool could help them to be more competitive, and give a more reliable service. This paper will focus mainly on the information about routes that drivers use to travel in their professional work, and how the researchers of this project have catalogued and evaluated these routes, and finally how that information will be provided to users.

Keywords: driver support systems, professional drivers, road safety, safeRoute

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Authors: Krassimir Todorov

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The purpose of the paper is to redefine the levels of structure of corporate, business and functional strategies that were established over the past several decades, to a conceptual model, consisting of corporate, business and operations strategies, that are reinforced by functional strategies. We will propose a conceptual framework of different perspectives in the role of strategic operations as a separate strategic place and reposition the remaining functional strategies as supporting tools, existing at all three levels. The proposed model is called ‘the strategic engine’, since the mutual relationships of its ingredients are identical with main elements and working principle of the internal combustion engine. Based on theoretical essence, related to every strategic level, we will prove that the strategic engine model is useful for managers seeking to safeguard the competitive advantage of their companies. Each strategy level is researched through its basic elements. At the corporate level we examine the scope of firm’s product, the vertical and geographical coverage. At the business level, the point of interest is limited to the SWOT analysis’ basic elements. While at operations level, the key research issue relates to the scope of the following performance indicators: cost, quality, speed, flexibility and dependability. In this relationship, the paper provides a different view for the role of operations strategy within the overall strategy concept. We will prove that the theoretical essence of operations goes far beyond the scope of traditionally accepted business functions. Exploring the applications of Resource-based theory and Market-based theory within the strategic levels framework, we will prove that there is a logical consequence of the theoretical impact in corporate, business and operations strategy – at every strategic level, the validity of one theory is substituted to the level of the other. Practical application of the conceptual model is tested in automotive industry. Actually, the proposed theoretical concept is inspired by a leading global automotive group – Inchcape PLC, listed on the London Stock Exchange, and constituent of the FTSE 250 Index.

Keywords: business strategy, corporate strategy, functional strategies, operations strategy

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Authors: Faiza Abdul Latip

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One of the ultimate goals of any nation is to produce competitive manpower and this includes Philippines. Inclination in the field of Mathematics has a significant role in achieving this goal. However, Mathematics, as considered by most people, is the most difficult subject matter along with its topics to learn. This could be manifested from the low performance of students in national and international assessments. Educators have been widely using learning style models in identifying the way students learn. Moreover, it could be the frontline in knowing the difficulties held by each learner in a particular topic specifically concepts pertaining to fractions. However, as what many educators observed, students show difficulties in doing mathematical tasks and in great degree in dealing with fractions most specifically in the district of Datu Odin Sinsuat, Maguindanao. This study focused on the Datu Odin Sinsuat district grade six pupils’ learning styles along with their achievements and difficulties in learning concepts on fractions. Five hundred thirty-two pupils from ten different public elementary schools of the Datu Odin Sinsuat districts were purposively used as the respondents of the study. A descriptive research using the survey method was employed in this study. Quantitative analysis on the pupils’ learning styles on the Kolb’s Learning Style Inventory (KLSI) and scores on the mathematics diagnostic test on fraction concepts were made using this method. The simple frequency and percentage counts were used to analyze the pupils’ learning styles and their achievements on fractions. To determine the pupils’ difficulties in fractions, the index of difficulty on every item was determined. Lastly, the Kruskal-Wallis Test was used in determining the significant difference in the pupils’ achievements on fractions classified by their learning styles. This test was set at 0.05 level of significance. The minimum H-Value of 7.82 was used to determine the significance of the test. The results revealed that the pupils of Datu Odin Sinsuat districts learn fractions in varied ways as they are of different learning styles. However, their achievements in fractions are low regardless of their learning styles. Difficulties in learning fractions were found most in the area of Estimation, Comparing/Ordering, and Division Interpretation of Fractions. Most of the pupils find it very difficult to use fraction as a measure, compare or arrange series of fractions and use the concept of fraction as a quotient.

Keywords: difficulties in fraction, fraction, Kolb's model, learning styles

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Authors: Mourad Morsli, Mohamed Tahiri, Azzedine Samdi

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The Cities are the urbanized territories most favorable to the consumption of resources (materials, energy). In Morocco, the economic capital Casablanca is one of them, with its 4M inhabitants and its 60% share in the economic and industrial activity of the kingdom. In the absence of legal status in force, urban development has favored the generation of millions of tons of demolition and construction waste scattered in open spaces causing a significant nuisance to the environment and citizens. Hence the main objective of our work is to valorize concrete waste. The representative wastes are mainly concrete, concrete, and fired clay bricks, ceramic tiles, marble panels, gypsum, and scrap metal. The work carried out includes: geolocation with a combination of artificial intelligence, GIS, and Google Earth, which allowed the estimation of the quantity of these wastes per site; then the sorting, crushing, grinding, and physicochemical characterization of the collected samples allowed the definition of the exploitation ways for each extracted fraction for integrated management of the said wastes. In the present work, we proceeded to the exploitation of the fractions obtained after sieving the representative samples to incorporate them in the manufacture of new ecological materials for construction. These formulations prepared studies have been tested and characterized: physical criteria (specific surface, resistance to flexion and compression) and appearance (cracks, deformation). We will present in detail the main results of our research work and also describe the specific properties of each material developed.

Keywords: demolition and construction waste, GIS combination software, inert waste recovery, ecological materials, Casablanca, Morocco

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Authors: Schnell Zsuzsanna

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Background: The interpretation of written texts, language processing in the visual domain, in other words, atypical reading abilities, also known as dyslexia, is an ever-growing phenomenon in today’s societies and educational communities. The much-researched problem affects cognitive abilities and, coupled with normal intelligence normally manifests difficulties in the differentiation of sounds and orthography and in the holistic processing of written words. The factors of susceptibility are varied: social, cognitive psychological, and linguistic factors interact with each other. Methods: The research will explain the psycholinguistics of dyslexia on the basis of several empirical experiments and demonstrate how domain-general abilities of inhibition, retrieval from the mental lexicon, priming, phonological processing, and visual modality transfer affect successful language processing and interpretation. Interpretation of visual stimuli is hindered, and the problem seems to be embedded in a sociocultural, psycholinguistic, and cognitive background. This makes the picture even more complex, suggesting that the understanding and resolving of the issues of dyslexia has to be interdisciplinary, aided by several disciplines in the field of humanities and social sciences, and should be researched from an empirical approach, where the practical, educational corollaries can be analyzed on an applied basis. Aim and applicability: The lecture sheds light on the applied, cognitive aspects of interpretation, social cognitive traits of language processing, the mental underpinnings of cognitive interpretation strategies in different languages (namely, Hungarian and English), offering solutions with a few applied techniques for success in foreign language learning that can be useful advice for the developers of testing methodologies and measures across ESL teaching and testing platforms.

Keywords: dyslexia, social cognition, transparency, modalities

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Authors: Bismark Agbemble

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This paper talks about how project-based learning (PBL) is being infused or implemented in the educational sphere of Africa. The paper navigates through the liminal aspects of PBL as a pedagogical approach to bridge the divide between theoretical knowledge and its application within school curriculums. Given that contextualized learning can be embodied, the abstract vehemently discusses that PBL creates an opportunity for students to work on projects that are of academic relevance in their local settings. It presents PBL’s growth of critical thinking, problem-solving, cooperation, and communications, which is vital in getting young citizens to prepare for the 21st-century revolution. In addition, the abstract stresses the possibility that PBL could become a stimulus to creativity and innovation wherein learning becomes motivated from within by intrinsic motivations. The paper advocates for a holistic approach that is based on teacher’s professional development with the provision of adequate infrastructural facilities and resource allocation, thus ensuring the success and sustainability of PBLs in African education systems. In the end, the paper positions this as a transformative educational methodology that has great potential in helping to shape an African generation that is prepared for a great future.

Keywords: student centered pedagogy, constructivist learning theory, self-directed learning, active exploration, real world challenges, STEM, 21st century skills, curriculum design, classroom management, project base learning curriculum, global intelligence, social and communication skills, transferable skills, critical thinking, investigatable learning, life skills

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Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li, Shuo Zhu, Shiming Duan, Xuezhe Yao

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Accurate calculation of wellbore pressure is of great significance to prevent wellbore risk during drilling. The traditional mechanism model needs a lot of iterative solving procedures in the calculation process, which reduces the calculation efficiency and is difficult to meet the demand of dynamic control of wellbore pressure. In recent years, many scholars have introduced artificial intelligence algorithms into wellbore pressure calculation, which significantly improves the calculation efficiency and accuracy of wellbore pressure. However, due to the ‘black box’ property of intelligent algorithm, the existing intelligent calculation model of wellbore pressure is difficult to play a role outside the scope of training data and overreacts to data noise, often resulting in abnormal calculation results. In this study, the multi-phase flow mechanism is embedded into the objective function of the neural network model as a constraint condition, and an intelligent prediction model of wellbore pressure under the constraint condition is established based on more than 400,000 sets of pressure measurement while drilling (MPD) data. The constraint of the multi-phase flow mechanism makes the prediction results of the neural network model more consistent with the distribution law of wellbore pressure, which overcomes the black-box attribute of the neural network model to some extent. The main performance is that the accuracy of the independent test data set is further improved, and the abnormal calculation values basically disappear. This method is a prediction method driven by MPD data and multi-phase flow mechanism, and it is the main way to predict wellbore pressure accurately and efficiently in the future.

Keywords: multiphase flow mechanism, pressure while drilling data, wellbore pressure, mechanism constraints, combined drive

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Authors: Mohammad Hossein Bayati Chaleshtari, Hadi Khoramishad

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Minimizing the stress concentration around triangular cutout in infinite perforated plates subjected to a uniform heat flux induces thermal stresses is an important consideration in engineering design. Furthermore, understanding the effective parameters on stress concentration and proper selection of these parameters enables the designer to achieve a reliable design. In the analysis of thermal stress, the effective parameters on stress distribution around cutout include fiber angle, flux angle, bluntness and rotation angle of the cutout for orthotropic materials. This paper was tried to examine effect of these parameters on thermal stress analysis of infinite perforated plates with central triangular cutout. In order to achieve the least amount of thermal stress around a triangular cutout using a novel swarm intelligence optimization technique called dragonfly optimizer that inspired by the life method and hunting behavior of dragonfly in nature. In this study, using the two-dimensional thermoelastic theory and based on the Likhnitskiiʼ complex variable technique, the stress analysis of orthotropic infinite plate with a circular cutout under a uniform heat flux was developed to the plate containing a quasi-triangular cutout in thermal steady state condition. To achieve this goal, a conformal mapping function was used to map an infinite plate containing a quasi- triangular cutout into the outside of a unit circle. The plate is under uniform heat flux at infinity and Neumann boundary conditions and thermal-insulated condition at the edge of the cutout were considered.

Keywords: infinite perforated plate, complex variable method, thermal stress, optimization method

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Authors: Aydemir Akyürek, Osman Nuri Ağdağ

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Construction industry is in a rapid development for many years around the world and especially in Turkey. In the last three years sector has 10% growth and provides significant support on Turkey’s national economy. Many construction projects are on-going at urban and rural areas of Turkey which have substantial environmental impacts. Environmental impacts during construction phase are quite diversified and widespread. Environmental impacts of construction industry cannot be inspected properly in all cases and negative impacts may occur frequently in many projects in Turkey. In this study, implementation of ISO 14001 Environmental Management System (EMS) in construction plants is evaluated. In the beginning stage quality management systems generally reviewed and ISO 14001 EMS is selected for implementation. Standard requirements are examined first and implementation of every standard requirement is elaborated for the selected construction plant in the following stage. Key issues and common problems, gained benefits by execution of this type of international EMS standard are examined. As can be seen in sample projects, construction projects are being completed very fast and contractors are working in a highly competitive environment with low profit ratios in our country and mostly qualified work force cannot be accessible. Addition to this there are deficits on waste handling and environmental infrastructure. Besides construction companies which have substantial investments on EMSs can be faced with difficulties on competitiveness in domestic market, however professional Turkish contractors which implementing managements systems in larger scale at international projects are gaining successful results. Also the concept of ‘construction project management’ which is being implemented in successful projects worldwide cannot be implemented except larger projects in Turkey. In case of nonexistence of main management system (quality) implementation of EMSs cannot be managed. Despite all constraints, EMSs that will be implemented in this industry with commitment of top managements and demand of customers will be an enabling, facilitating tool to determine environmental aspects and impacts of construction sites, will provide higher compliance levels for environmental legislation, to establish best available methods for operational control on waste management, chemicals management etc. and to plan monitoring and measurement, to prioritize environmental aspects for investment schedules and waste management.

Keywords: environmental management system, construction projects, ISO 14001, quality

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Authors: Stephen L. Roberts

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This article offers a critical analysis of the rise of syndromic surveillance systems for the advanced detection of pandemic threats within contemporary global health security frameworks. The article traces the iterative evolution and ascendancy of three such novel syndromic surveillance systems for the strengthening of health security initiatives over the past two decades: 1) The Program for Monitoring Emerging Diseases (ProMED-mail); 2) The Global Public Health Intelligence Network (GPHIN); and 3) HealthMap. This article demonstrates how each newly introduced syndromic surveillance system has become increasingly oriented towards the integration of digital algorithms into core surveillance capacities to continually harness and forecast upon infinitely generating sets of digital, open-source data, potentially indicative of forthcoming pandemic threats. This article argues that the increased centrality of the algorithm within these next-generation syndromic surveillance systems produces a new and distinct form of infectious disease surveillance for the governing of emergent pathogenic contingencies. Conceptually, the article also shows how the rise of this algorithmic mode of infectious disease surveillance produces divergences in the governmental rationalities of global health security, leading to the rise of an algorithmic governmentality within contemporary contexts of Big Data and these surveillance systems. Empirically, this article demonstrates how this new form of algorithmic infectious disease surveillance has been rapidly integrated into diplomatic, legal, and political frameworks to strengthen the practice of global health security – producing subtle, yet distinct shifts in the outbreak notification and reporting transparency of states, increasingly scrutinized by the algorithmic gaze of syndromic surveillance.

Keywords: algorithms, global health, pandemic, surveillance

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Authors: Michael P. Mannino, Gerald W. Hart

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The majority of glucose metabolism proceeds through glycolytic pathways such as glycolysis or pentose phosphate pathway, however, about 5% is shunted through the hexosamine biosynthetic pathway, producing uridine diphosphate N-acetyl glucosamine (UDP-GlcNAc). This precursor can then be incorporated into complex oligosaccharides decorating the cell surface or remain as an intracellular post-translational-modification (PTM) of serine/threonine residues (O-GlcNAcylation, OGN), which has been identified on over 4,000 cytosolic or nuclear proteins. Intracellular OGN has major implications on cellularprocesses, typically by modulating protein localization, protein-protein interactions, protein degradation, and gene expression. Additionally, OGN is known to have an extensive cross-talk with phosphorylation, be in a competitive or cooperative manner. Unlike other PTMs there are only two cycling enzymes that are capable of adding or removing the GlcNAc moiety, O-linked N-aceytl glucosamine Transferase (OGT) and O-linked N-acetyl glucoamidase (OGA), respectively. The activity of OGT has been shown to be sensitive to cellular UDP-GlcNAc levels, even changing substrate affinity. Owing to this and that the concentration of UDP-GlcNAc is related to the metabolisms of glucose, amino acid, fatty acid, and nucleotides, O-GlcNAc is often referred to as a nutrient sensing rheostat. Indeed OGN is known to regulate several signaling pathways as a result of nutrient levels, such as insulin signaling. Dysregulation of OGN is associated with several disease states such as cancer, diabetes, and neurodegeneration. Improvements in glycomics over the past 10-15 years has significantly increased the OGT substrate pool, suggesting O-GlcNAc’s involvement in a wide variety of signaling pathways. However, O-GlcNAc’s role at the receptor level has only been identified in a case-by-case basis of known pathways. Examining the OGN of the plasma membrane (PM) may better focus our understanding of O-GlcNAc-effected signaling pathways. In this current study, PM fractions were isolated from several cell types via ultracentrifugation, followed by purification and MS/MS analysis in several cell lines. This process was repeated with or without OGT/OGA inhibitors or with increased/decreased glucose levels in media to ascertain the importance of OGN. Various pathways are followed up on in more detailed studies employing methods to localize OGN at the PM specifically.

Keywords: GlcNAc, nutrient sensitive, post-translational-modification, receptor

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Authors: Yassine Bouzouita, Oumaima Belghith, Cyrine Zitoun, Charles Bonneau

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Performance measurement framework (PMF) is an essential tool in any organization to assess the performance of its processes. It guides businesses to stay on track with their objectives and benchmark themselves from the market. With the growing trend of the digital transformation of business processes, led by innovations in artificial intelligence (AI) & Big Data applications, developing a mature system capable of capturing the impact of digital solutions across different industries became a necessity. Based on the conducted research, no such system has been developed in academia nor the industry. In this context, this paper covers a variety of methodologies on performance measurement, overviews the major AI and big data applications in the banking sector, and covers an exhaustive list of relevant metrics. Consequently, this paper is of interest to both researchers and practitioners. From an academic perspective, it offers a comparative analysis of the reviewed performance measurement frameworks. From an industry perspective, it offers exhaustive research, from market leaders, of the major applications of AI and Big Data technologies, across the different departments of an organization. Moreover, it suggests a standardized classification model with a well-defined structure of intelligent digital solutions. The aforementioned classification is mapped to a centralized library that contains an indexed collection of potential metrics for each application. This library is arranged in a manner that facilitates the rapid search and retrieval of relevant metrics. This proposed framework is meant to guide professionals in identifying the most appropriate AI and big data applications that should be adopted. Furthermore, it will help them meet their business objectives through understanding the potential impact of such solutions on the entire organization.

Keywords: AI and Big Data applications, impact assessment, metrics, performance measurement

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Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

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The relation between stock price volatility and trading volume represents a controversial issue which has received a remarkable attention over the past decades. In fact, an extensive literature shows a positive relation between price volatility and trading volume in the financial markets, but the causal relationship which originates such association is an open question, from both a theoretical and empirical point of view. In this regard, various models, which can be considered as complementary rather than competitive, have been introduced to explain this relationship. They include the long debated Mixture of Distributions Hypothesis (MDH); the Sequential Arrival of Information Hypothesis (SAIH); the Dispersion of Beliefs Hypothesis (DBH); the Noise Trader Hypothesis (NTH). In this work, we analyze whether stock market efficiency can explain the diversity of results achieved during the years. For this purpose, we propose an alternative measure of market efficiency, based on the pointwise regularity of a stochastic process, which is the Hurst–H¨older dynamic exponent. In particular, we model the stock market by means of the multifractional Brownian motion (mBm) that displays the property of a time-changing regularity. Mostly, such models have in common the fact that they locally behave as a fractional Brownian motion, in the sense that their local regularity at time t0 (measured by the local Hurst–H¨older exponent in a neighborhood of t0 equals the exponent of a fractional Brownian motion of parameter H(t0)). Assuming that the stock price follows an mBm, we introduce and theoretically justify the Hurst–H¨older dynamical exponent as a measure of market efficiency. This allows to measure, at any time t, markets’ departures from the martingale property, i.e. from efficiency as stated by the Efficient Market Hypothesis. This approach is applied to financial markets; using data for the SP500 index from 1978 to 2017, on the one hand we find that when efficiency is not accounted for, a positive contemporaneous relationship emerges and is stable over time. Conversely, it disappears as soon as efficiency is taken into account. In particular, this association is more pronounced during time frames of high volatility and tends to disappear when market becomes fully efficient.

Keywords: volume–volatility relationship, efficient market hypothesis, martingale model, Hurst–Hölder exponent

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Authors: Shraddha Jain Sharma, Ratnalata Gupta

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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

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Authors: Y. Saylan, F. Yılmaz, A. Denizli

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Rheumatoid arthritis (RA) which is the most common autoimmune disorder of the body's own immune system attacking healthy cells. RA has both articular and systemic effects.Until now romatiod factor (RF) assay is used the most commonly diagnosed RA but it is not specific. Anti-cyclic citrullinated peptide (anti-CCP) antibodies are IgG autoantibodies which recognize citrullinated peptides and offer improved specificity in early diagnosis of RA compared to RF. Anti-CCP antibodies have specificity for the diagnosis of RA from 91 to 98% and the sensitivity rate of 41-68%. Molecularly imprinted polymers (MIP) are materials that are easy to prepare, less expensive, stable have a talent for molecular recognition and also can be manufactured in large quantities with good reproducibility. Molecular recognition-based adsorption techniques have received much attention in several fields because of their high selectivity for target molecules. Quartz crystal microbalance (QCM) is an effective, simple, inexpensive approach mass changes that can be converted into an electrical signal. The applications for specific determination of chemical substances or biomolecules, crystal electrodes, cover by the thin films for bind or adsorption of molecules. In this study, we have focused our attention on combining of molecular imprinting into nanofilms and QCM nanosensor approaches and producing QCM nanosensor for anti-CCP, chosen as a model protein, using anti-CCP imprinted nanofilms. For this aim, anti-CCP imprinted QCM nanosensor was characterized by Fourier transform infrared spectroscopy, atomic force microscopy, contact angle measurements and ellipsometry. The non-imprinted nanosensor was also prepared to evaluate the selectivity of the imprinted nanosensor. Anti-CCP imprinted QCM nanosensor was tested for real-time detection of anti-CCP from aqueous solution. The kinetic and affinity studies were determined by using anti-CCP solutions with different concentrations. The responses related with mass shifts (Δm) and frequency shifts (Δf) were used to evaluate adsorption properties and to calculate binding (Ka) and dissociation (Kd) constants. To show the selectivity of the anti-CCP imprinted QCM nanosensor, competitive adsorption of anti-CCP and IgM was investigated.The results indicate that anti-CCP imprinted QCM nanosensor has a higher adsorption capabilities for anti-CCP than for IgM, due to selective cavities in the polymer structure.

Keywords: anti-CCP, molecular imprinting, nanosensor, rheumatoid arthritis, QCM

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Authors: Nimet Yildirim Tirgil, Ahmed Busnaina, April Z. Gu

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Environmental waters are monitored worldwide to protect people from infectious diseases primarily caused by enteric pathogens. All long, Escherichia coli (E. coli) is a good indicator for potential enteric pathogens in waters. Thus, a rapid and simple detection method for E. coli is very important to predict the pathogen contamination. In this study, to the best of our knowledge, as the first time we developed a rapid, direct and reusable SWCNTs (single walled carbon nanotubes) based biosensor system for sensitive and selective E. coli detection in water samples. We use a novel and newly developed flexible biosensor device which was fabricated by high-rate nanoscale offset printing process using directed assembly and transfer of SWCNTs. By simple directed assembly and non-covalent functionalization, aptamer (biorecognition element that specifically distinguish the E. coli O157:H7 strain from other pathogens) based SWCNTs biosensor system was designed and was further evaluated for environmental applications with simple and cost-effective steps. The two gold electrode terminals and SWCNTs-bridge between them allow continuous resistance response monitoring for the E. coli detection. The detection procedure is based on competitive mode detection. A known concentration of aptamer and E. coli cells were mixed and after a certain time filtered. The rest of free aptamers injected to the system. With hybridization of the free aptamers and their SWCNTs surface immobilized probe DNA (complementary-DNA for E. coli aptamer), we can monitor the resistance difference which is proportional to the amount of the E. coli. Thus, we can detect the E. coli without injecting it directly onto the sensing surface, and we could protect the electrode surface from the aggregation of target bacteria or other pollutants that may come from real wastewater samples. After optimization experiments, the linear detection range was determined from 2 cfu/ml to 10⁵ cfu/ml with higher than 0.98 R² value. The system was regenerated successfully with 5 % SDS solution over 100 times without any significant deterioration of the sensor performance. The developed system had high specificity towards E. coli (less than 20 % signal with other pathogens), and it could be applied to real water samples with 86 to 101 % recovery and 3 to 18 % cv values (n=3).

Keywords: aptamer, E. coli, environmental detection, nanobiosensor, SWCTs

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Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

Procedia PDF Downloads 148

Authors: Maznieda Mahjom, Rohaida Ismail, Masita Arip, Mohd Shaiful Azlan, Nor’Ashikin Othman, Hafizah Abdullah, nor Zahrin Hasran, Joshita Jothimanickam, Syaqilah Shawaluddin, Nadia Mohamad, Raheel Nazakat, Tuan Mohd Amin, Mizanurfakhri Ghazali, Rosmanajihah Mat Lazim

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COVID-19 outbreak is particularly detrimental to the mental health of everyone as well as leaving a long devastating crisis in the healthcare sector. Daily increment of COVID-19 cases and close contact, necessitating the testing of a large number of samples, thus increasing the workload and burden to laboratory personnel. This study aims to determine the prevalence of personal-, work- and client-related burnout as well as to measure the concentration of salivary cortisol among laboratory personnel in the main laboratories in Klang Valley, Malaysia. This cross-sectional study was conducted in late 2021 and recruited a total of 404 respondents from three laboratories in Klang Valley, Malaysia. The level of burnout was assessed using Copenhagen Burnout Inventory (CBI) comprising three sub-dimensions of personal-, work- and client-related burnout. The cut-off score of 50% and above indicated possible burnout. Meanwhile, salivary cortisol was measured using a competitive enzyme immunoassay kit (Salimetrics, State College, PA, USA). Normal levels of salivary cortisol concentration in adults are within 0.094 to 1.551 μg/dl (morning) and can be none detected to 0.359 μg/dl (evening). The prevalence of personal-, work- and client-related burnout among laboratory personnel were 36.1%, 17.8% and 7.2% respectively. Meanwhile, the abnormal morning and evening cortisol concentration recorded were 29.5% and 21.8% excluding 6.9%-7.4% missing data. While the IgA level is normal for most of the respondents, which recorded at 95.53%. Laboratory personnel were at risk of suffering burnout during the COVID-19 pandemic. Thus, mental health programs need to be addressed at the department and hospital level by regularly screening healthcare workers and designing an intervention program. It is also vital to improve the coping skills of laboratory personnel by increasing the awareness of good coping skill techniques. The training must be in an innovative way to ensure that the lab personnel can internalise the technique and practise it in real life.

Keywords: burnout, COVID-19, laborotary personnel, salivary cortisol

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Authors: L. Freeborn

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This paper discusses the application of complex dynamic system theory (DST) to the study of individual differences in second language development. This transdisciplinary framework allows researchers to view the trajectory of language development as a dynamic, non-linear process. A DST approach views language as multi-componential, consisting of multiple complex systems and nested layers. These multiple components and systems continuously interact and influence each other at both the macro- and micro-level. Dynamic systems theory aims to explain and describe the development of the language system, rather than make predictions about its trajectory. Such a holistic and ecological approach to second language development allows researchers to include various research methods from neurological, cognitive, and social perspectives. A DST perspective would involve in-depth analyses as well as mixed methods research. To illustrate, a neurobiological approach to second language development could include non-invasive neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to investigate areas of brain activation during language-related tasks. A cognitive framework would further include behavioural research methods to assess the influence of intelligence and personality traits, as well as individual differences in foreign language aptitude, such as phonetic coding ability and working memory capacity. Exploring second language development from a DST approach would also benefit from including perspectives from the field of applied linguistics, regarding the teaching context, second language input, and the role of affective factors such as motivation. In this way, applying mixed research methods from neurobiological, cognitive, and social approaches would enable researchers to have a more holistic view of the dynamic and complex processes of second language development.

Keywords: dynamic systems theory, mixed methods, research design, second language development

Procedia PDF Downloads 135

Authors: Wanjiku Karanja

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Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

Procedia PDF Downloads 123

Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

Procedia PDF Downloads 110