Search results for: artificial microRNA approach

Authors: Yaseein S. Hussein, Victor P. Gil Jiménez, Abdulmajeed Al-Jumaily

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Due to the rapid advancement of technology, there is an increasing demand for wireless connections that are both fast and reliable, with minimal latency. New wireless communication standards are developed every decade, and the year 2030 is expected to see the introduction of 6G. The primary objectives of 6G network and terminal designs are focused on sustainability and environmental friendliness. The International Telecommunication Union-Recommendation division (ITU-R) has established the minimum requirements for 6G, with peak and user data rates of 1 Tbps and 10-100 Gbps, respectively. In this context, Light Fidelity (Li-Fi) technology is the most promising candidate to meet these requirements. This article will explore the various advantages, features, and potential applications of Li-Fi technology, and compare it with 5G networking, to showcase its potential impact among other emerging technologies that aim to enable 6G networks.

Keywords: 6G networks, artificial intelligence (AI), Li-Fi technology, Terahertz (THz) communication, visible light communication (VLC)

Procedia PDF Downloads 94

Authors: P. Krachodnok

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In this paper, the design of a multiple U-slotted microstrip patch antenna with frequency selective surface (FSS) as a superstrate for WLAN and WiMAX applications is presented. The proposed antenna is designed by using substrate FR4 having permittivity of 4.4 and air substrate. The characteristics of the antenna are designed and evaluated the performance of modelled antenna using CST Microwave studio. The proposed antenna dual resonant frequency has been achieved in the band of 2.37-2.55 GHz and 3.4-3.6 GHz. Because of the impact of FSS superstrate, it is found that the bandwidths have been improved from 6.12% to 7.35 % and 3.7% to 5.7% at resonant frequencies 2.45 GHz and 3.5 GHz, respectively. The maximum gain at the resonant frequency of 2.45 and 3.5 GHz are 9.3 and 11.33 dBi, respectively.

Keywords: multi-slotted antenna, microstrip patch antenna, frequency selective surface, artificial magnetic conduction

Procedia PDF Downloads 380

Authors: Andras Gyorfi, Andras Torma, Adrienn Buruzs

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Mobility has been evolved to a determining field of science. The continuously developing segment involves a variety of affected issues such as public and economic sectors. Beside the changes in mobility the state of environment had also changed in the last period. Alternative mobility as a separate category and the idea of its widespread appliance is such a new field that needs to be studied deeper. Alternative mobility implies finding new types of propulsion, using innovative kinds of power and energy resources, revolutionizing the approach to vehicular control. Including new resources and excluding others has such a complex effect which cannot be unequivocally confirmed by today’s scientific achievements. Changes in specific parameters will most likely reduce the environmental impacts, however, the production of new substances or even their subtraction of the system will cause probably energy deficit as well. The aim of this research is to elaborate the environmental impact matrix of alternative mobility and cognize the factors that are yet unknown, analyse them, look for alternative solutions and conclude all the above in a coherent system. In order to this, we analyse it with a method called ‘the system of systems (SoS) method’ to model the effects and the dynamics of the system. A part of the research process is to examine its impacts on the environment, and to decide whether the newly developed versions of alternative mobility are affecting the environmental state. As a final result, a complex approach will be used which can supplement the current scientific studies. By using the SoS approach, we create a framework of reference containing elements in which we examine the interactions as well. In such a way, a flexible and modular model can be established which supports the prioritizing of effects and the deeper analysis of the complex system.

Keywords: environment, alternative mobility, complex model, element analysis, multidimensional map

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Authors: Pradeep Kumar Sahoo

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Facilitating writing skill among the young techies seems a bit challenging. Various factors may owe to this difficulty. Inappropriate syllabus, inadequate infrastructure, to some extent, untrained faculty members and above all the background of learners may be treated as the components that make the process challenging. In order to convert/create/prepare writing skill friendly, the focused items will have to be different from the classroom the present day traditional classroom situation. This paper focuses on the multiple contemporary strategies for approaching a wide range of typical problems that the writers face in a specific technical university of Odisha.

Keywords: background of learners, classroom friendly approach, inappropriate syllabus, traditional classroom situation

Procedia PDF Downloads 336

Authors: R. Chanajaree, D. Luanwiset, K. Pongpratea

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Dye removal is an environmental concern because the textile industries have been increasing by world population and industrialization. Adsorption is the technique to find adsorbents to remove dyes from wastewater. This method is low-cost and effective for dye removal. This work tries to develop effective adsorbents using the computational approach because it will be able to predict the possibility of the adsorbents for specific dyes in terms of binding free energies. The computational approach is faster and cheaper than the experimental approach in case of finding the best adsorbents. All starting structures of dyes and adsorbents are optimized by quantum calculation. The complexes between dyes and adsorbents are generated by the docking method. The obtained binding free energies from docking are compared to binding free energies from the experimental data. The calculated energies can be ranked as same as the experimental results. In addition, this work also shows the possible orientation of the complexes. This work used two experimental groups of the complexes of the dyes and adsorbents. In the first group, there are chitosan (adsorbent) and two dyes (reactive red (RR) and direct sun yellow (DY)). In the second group, there are poly(1,2-epoxy-3-phenoxy) propane (PEPP), which is the adsorbent, and 2 dyes of bromocresol green (BCG) and alizarin yellow (AY).

Keywords: dyes removal, binding free energies, quantum calculation, docking

Procedia PDF Downloads 154

Authors: Olga Shvetsova

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The research paper contains the different issues of competence management in innovation companies. The theoretical bases of human resources management and practical issues of innovative enterprises’ competitiveness are considered. The research is focused on the modern innovative enterprise management problems; it focuses on the effective management of the personnel of innovative enterprises on the basis of competence approach. The concept of core competence approach is discussed. The point of view, that the key competences of the company create the competitive advantages, support strategy development and protect business from external negative factors is considered. The used methodology is background research.

Keywords: competence model, competitiveness, innovation management, implementation

Procedia PDF Downloads 317

Authors: Alfred Hasanaj , Ardit Gjeta, Miranda Kullolli

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The approach in analyzing defects on different pipe lines is conducted through Failure Assessment Diagram (FAD). These methods of analyses have further extended in recent years. This approach is used to identify and stress out a solution for the defects which randomly occur with gas pipes such are corrosion defects, gauge defects, and combination of defects where gauge and dents are included. Few of the defects are to be analyzed in this paper where our main focus will be the fracture of cast Iron pipes, elastic-plastic failure and plastic collapse of X52 steel pipes for gas transport. We need to conduct a calculation of probability of the defects in order to predict and avoid such costly defects.

Keywords: defects, failure assessment diagrams, steel pipes, safety factor

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Authors: Hanafizan Hussain

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This study shows that several projects will be conducted at the workshop in which using the conceptual model for knowledge sharing approach to create an idea for mobile application. The sharing idea has been done through the collaborative activity in which a group of different field sought to define the mobile application which will lead to new media approach of using social media platform. The collaborative activity will be provided and implemented in the form of one day workshop to determine the approach towards the theme given. The activity later will be continued for four weeks for the participant to prepare for the pitch day workshop. This paper shows the pitch of idea including the interface and prototype for the said products. The collaboration between the members with different field of study shows that social media influenced the knowledge sharing model and its creation or innovations. One of the projects supported a collaborative activity in which a group of young designers sought to define the knowledge sharing model of their ability in creating idea for mobile applications.

Keywords: mobile application, collaborative activity, conceptual knowledge sharing model, social media platform

Procedia PDF Downloads 143

Authors: Dávid Kovács, Bálint Csanády, Dániel Boros, Iván Ivkovic, Lóránt Nagy, Dalma Tóth-Lakits, László Márkus, András Lukács

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The modeling practice of financial instruments has seen significant change over the last decade due to the recognition of time-dependent and stochastically changing correlations among the market prices or the prices and market characteristics. To represent this phenomenon, the Stochastic Correlation Process (SCP) has come to the fore in the joint modeling of prices, offering a more nuanced description of their interdependence. This approach has allowed for the attainment of realistic tail dependencies, highlighting that prices tend to synchronize more during intense or volatile trading periods, resulting in stronger correlations. Evidence in statistical literature suggests that, similarly to the volatility, the SCP of certain stock prices follows rough paths, which can be described using fractional differential equations. However, estimating parameters for these equations often involves complex and computation-intensive algorithms, creating a necessity for alternative solutions. In this regard, the Fractional Ornstein-Uhlenbeck (fOU) process from the family of fractional processes offers a promising path. We can effectively describe the rough SCP by utilizing certain transformations of the fOU. We employed neural networks to understand the behavior of these processes. We had to develop a fast algorithm to generate a valid and suitably large sample from the appropriate process to train the network. With an extensive training set, the neural network can estimate the process parameters accurately and efficiently. Although the initial focus was the fOU, the resulting model displayed broader applicability, thus paving the way for further investigation of other processes in the realm of financial mathematics. The utility of SCP extends beyond its immediate application. It also serves as a springboard for a deeper exploration of fractional processes and for extending existing models that use ordinary Wiener processes to fractional scenarios. In essence, deploying both SCP and fractional processes in financial models provides new, more accurate ways to depict market dynamics.

Keywords: fractional Ornstein-Uhlenbeck process, fractional stochastic processes, Heston model, neural networks, stochastic correlation, stochastic differential equations, stochastic volatility

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

Procedia PDF Downloads 111

Authors: M. Ndeley

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The performance of global manufacturing supply chains depends on the interaction of production and transport processes. Currently, the scheduling of these processes is done separately without considering mutual requirements, which leads to no optimal solutions. An integrated scheduling of both processes enables the improvement of supply chain performance. The integrated production and transport scheduling problem (PTSP) is NP-hard, so that heuristic methods are necessary to efficiently solve large problem instances as in the case of global manufacturing supply chains. This paper presents a heuristic scheduling approach which handles the integration of flexible production processes with intermodal transport, incorporating flexible land transport. The method is based on a graph that allows a reformulation of the PTSP as a shortest path problem for each job, which can be solved in polynomial time. The proposed method is applied to a supply chain scenario with a manufacturing facility in South Africa and shipments of finished product to customers within the Country. The obtained results show that the approach is suitable for the scheduling of large-scale problems and can be flexibly adapted to different scenarios.

Keywords: production and transport scheduling problem, graph based scheduling, integrated scheduling

Procedia PDF Downloads 474

Authors: Ali A. Abdollahi

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During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49.

Keywords: multiple criteria decision making, Data envelopment analysis (DEA), Charnes Cooper Rhodes (CCR), Weighted Sum Approach (WSA)

Procedia PDF Downloads 218

Authors: Kai Qian, Lixin Tao

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Mobile devices such as smartphones are getting more and more popular in our daily lives. The security vulnerability and threat attacks become a very emerging and important research and education topic in computing security discipline. There is a need to have an innovative mobile security hands-on laboratory to provide students with real world relevant mobile threat analysis and protection experience. This paper presents an authentic teaching and learning mobile security approach with smartphone devices which covers most important mobile threats in most aspects of mobile security. Each lab focuses on one type of mobile threats, such as mobile messaging threat, and conveys the threat analysis and protection in multiple ways, including lectures and tutorials, multimedia or app-based demonstration for threats analysis, and mobile app development for threat protections. This authentic learning approach is affordable and easily-adoptable which immerse students in a real world relevant learning environment with real devices. This approach can also be applied to many other mobile related courses such as mobile Java programming, database, network, and any security relevant courses so that can learn concepts and principles better with the hands-on authentic learning experience.

Keywords: mobile computing, Android, network, security, labware

Procedia PDF Downloads 406

Authors: J. Jessa

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Background: Autism is a pervasive developmental disorder, the incidence of which has significantly increased in recent years. Children with autism have impairments in social skills, communication, and imagination. Children with autism has more common than healthy children feeding problems: food selectivity, problems with gastrointestinal tract: diarrhea, constipations, abdominal pain, reflux and others. Many parents of autistic children report that after implementation of gluten-, casein- and sugar free diet those symptoms disappear and even cognitive functions become better. Some children begin to understand speech and to communicate with parents, regain eye contact, become more calm, sleep better and has better concentration. Probably at the root of this phenomenon lies elimination from the diet peptides construction of which is similar to opiates. Enhanced permeability of gut causes absorption of not fully digested opioid-like peptides from food, like gluten and casein and probably others (proteins from soy and corn) which impact on brain of autistic children. Aim of the study: The aim of the study is to assess the safety of gluten-free diet in children with autism, aged 2,5-7. Methods: Participants of the study (n=70) – children aged 2,5-7 with autism are divided into 3 groups. The first group (research group) are patients whose parents want to implement a gluten-free diet. The second group are patients who have been recommended to eliminate from the diet artificial substances, such as preservatives, artificial colors and flavors, and others (control group 1). The third group (control group 2) are children whose parents did not agree for implementation of the diet. Caregivers of children on the diet are educated about the specifics of the diet and how to avoid malnutrition. At the start of the study we exclude celiac disease. Before the implementation of the diet we performe a blood test for patients (morphology, ferritin, total cholesterol, dry peripheral blood drops to detect some genetic metabolic diseases), plasma aminogram) and urine tests (excretion of ions: Mg, Na, Ca, the profile of organic acids in urine), which assess nutritional status as well as the psychological test assessing the degree of the child's psychological functioning (PEP-R). All of these tests will be repeated after one year from the implementation of the diet. Results: To the present moment we examined 42 children with autism. 12 of children are on gluten- free diet. Our preliminary results are promising. Parents of 9 of them report that, there is a big improvement in child behavior, concentration, less aggression incidents, better eye contact and better verbal skills. Conclusion: Our preliminary results suggest that dietary intervention may positively affect developmental outcome for some children diagnosed with ASD.

Keywords: gluten free diet, autism spectrum disorder, autism, blood test

Procedia PDF Downloads 323

Authors: Santiago Quesada-García, María Lozano-Gómez, Pablo Valero-Flores

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The recent digital revolution, together with modern technologies, is changing the environment and the way people interact with inhabited space. However, in society, the elderly are a very broad and varied group that presents serious difficulties in understanding these modern technologies. Outpatients with cognitive disabilities, such as those suffering from Alzheimer's disease (AD), are distinguished within this cluster. This population group is in constant growth, and they have specific requirements for their inhabited space. According to architecture, which is one of the health humanities, environments are designed to promote well-being and improve the quality of life for all. Buildings, as well as the tools and technologies integrated into them, must be accessible, inclusive, and foster health. In this new digital paradigm, artificial intelligence (AI) appears as an innovative resource to help this population group improve their autonomy and quality of life. Some experiences and solutions, such as those that interact with users through chatbots and voicebots, show the potential of AI in its practical application. In the design of healthy spaces, the integration of AI in architecture will allow the living environment to become a kind of 'exo-brain' that can make up for certain cognitive deficiencies in this population. The objective of this paper is to address, from the discipline of neuroarchitecture, how modern technologies can be integrated into everyday environments and be an accessible resource for people with cognitive disabilities. For this, the methodology has a mixed structure. On the one hand, from an empirical point of view, the research carries out a review of the existing literature about the applications of AI to build space, following the critical review foundations. As a unconventional architectural research, an experimental analysis is proposed based on people with AD as a resource of data to study how the environment in which they live influences their regular activities. The results presented in this communication are part of the progress achieved in the competitive R&D&I project ALZARQ (PID2020-115790RB-I00). These outcomes are aimed at the specific needs of people with cognitive disabilities, especially those with AD, since, due to the comfort and wellness that the solutions entail, they can also be extrapolated to the whole society. As a provisional conclusion, it can be stated that, in the immediate future, AI will be an essential element in the design and construction of healthy new environments. The discipline of architecture has the compositional resources to, through this emerging technology, build an 'exo-brain' capable of becoming a personal assistant for the inhabitants, with whom to interact proactively and contribute to their general well-being. The main objective of this work is to show how this is possible.

Keywords: Alzheimer’s disease, artificial intelligence, healthy architecture, neuroarchitecture, architectural design

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Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

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Authors: Timothy Garvey, Don Driscoll

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Within Tasmania, the growling grass frog (Litoria raniformis) has experienced a rapid contraction in distribution. This decline is primarily attributed to habitat loss through landscape modification and improved land drainage. Reductions in seasonal water-sources have placed increasing importance on permanent water bodies for reproduction and foraging. Tasmanian agricultural and commercial forestry landscapes often feature small artificial ponds, utilized for watering livestock and fighting wildfires. Improved knowledge of how L. raniformis may be exploiting anthropogenic ponds is required for improved conservation management. We implemented telemetric tracking in order to evaluate the spatial ecology of L. raniformis (n = 20) within agricultural and managed forestry sites, with tracking conducted periodically over the breeding season (November/December, January/February, March/April). We investigated (1) potential differences in habitat utilization between agricultural and plantation sites, and (2) the post-breeding dispersal of individual frogs. Frogs were found to remain in close proximity to ponds throughout November/December, with individuals occupying vegetative depauperate water bodies beginning to disperse by January/February. Dispersing individuals traversed exposed plantation understory and agricultural pasture land in order to enter patches of native scrubland. By March/April all individuals captured at minimally vegetated ponds had retreated to adjacent scrub corridors. Animals found in ponds featuring dense riparian vegetation were not recorded to disperse. No difference in behavior was recorded between sexes. Rising temperatures coincided with increased movement by individuals towards native scrub refugia. The patterns of movement reported in this investigation emphasize the significant contribution of manmade water-bodies towards the conservation of L. raniformis within modified landscapes. The use of natural scrubland as cyclical retreats between breeding seasons also highlights the importance of the continued preservation of remnant vegetation corridors. Loss of artificial dams or buffering scrubland in heavily altered landscapes could see the breakdown of the greater L. raniformis meta-population further threatening their regional persistence.

Keywords: habitat loss, modified landscapes, spatial ecology, telemetry

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Authors: Oluwaponmile David Alao

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Misdiagnosis has been the major problem in health sector. Heart attack has been one of diseases that have high level of misdiagnosis recorded on the part of physicians. In this paper, an intelligent system has been developed for diagnosis of heart attack in the health sector. Dataset of heart attack obtained from UCI repository has been used. This dataset is made up of thirteen attributes which are very vital in diagnosis of heart disease. The system is developed on the multilayer perceptron trained with back propagation neural network then simulated with feed forward neural network and a recognition rate of 87% was obtained which is a good result for diagnosis of heart attack in medical field.

Keywords: heart attack, artificial neural network, diagnosis, intelligent system

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Authors: Daniel Tochwin

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Continuous improvement is an essential part of effective process performance management. In order to achieve continuous quality improvement, each organization must use the appropriate selection of tools and techniques. The basic condition for success is a proper understanding of the business need faced by the company and the selection of appropriate methods to improve a given production process. The main aim of this article is to analyze the methods of conduct which are popular in practice when implementing process improvements and then to determine whether the tested methods include repetitive systematics of the approach, i.e., a similar sequence of the same or similar actions. Based on an extensive literature review, 4 methods of continuous improvement of production processes were selected: A3 report, Gemba Kaizen, PDCA cycle, and Deming cycle. The research shows that all frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re)interpretation" and the need to adapt the continuous improvement approach to the specific business process. The research shows that all the frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re) interpretation" and the need to adapt the continuous improvement approach to the specific business process.

Keywords: continuous improvement, lean methods, process improvement, PDCA

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Authors: İkbal Eski

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This investigation is researched on design of robust neural network predictors for analyzing vibration effects on moving parts of a drilling machine. Moreover, the research is divided two parts; first part is experimental investigation, second part is simulation analysis with neural networks. Therefore, a real time the drilling machine is used to vibrations during working conditions. The measured real vibration parameters are analyzed with proposed neural network. As results: Simulation approaches show that Radial Basis Neural Network has good performance to adapt real time parameters of the drilling machine.

Keywords: artificial neural network, vibration analyses, drilling machine, robust

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Authors: Merih Welay Welesilassie

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Understanding educators' readiness to incorporate AI tools into their teaching methods requires comprehensively examining the influencing factors. This understanding is crucial, given the potential of these technologies to personalise learning experiences, improve instructional effectiveness, and foster innovative pedagogical approaches. This study evaluated factors affecting teachers' adoption of AI tools in their English language instruction by extending the Technology Acceptance Model (TAM) to encompass digital readiness support, perceived risk, and trust. A cross-sectional quantitative survey was conducted with 128 English language teachers, supplemented by qualitative data collection from 15 English teachers. The structural mode analysis indicated that implementing AI tools in Ethiopian higher education was notably influenced by digital readiness support, perceived ease of use, perceived usefulness, perceived risk, and trust. Digital readiness support positively impacted perceived ease of use, usefulness, and trust while reducing safety and privacy risks. Perceived ease of use positively correlated with perceived usefulness but negatively influenced trust. Furthermore, perceived usefulness strengthened trust in AI tools, while perceived safety and privacy risks significantly undermined trust. Trust was crucial in increasing educators' willingness to adopt AI technologies. The qualitative analysis revealed that the teachers exhibited strong content and pedagogical knowledge but needed more technology-related knowledge. Moreover, It was found that the teachers did not utilise digital tools to teach English. The study identified several obstacles to incorporating digital tools into English lessons, such as insufficient digital infrastructure, a shortage of educational resources, inadequate professional development opportunities, and challenging policies and governance. The findings provide valuable guidance for educators, inform policymakers about creating supportive digital environments, and offer a foundation for further investigation into technology adoption in educational settings in Ethiopia and similar contexts.

Keywords: digital readiness support, AI acceptance, risk, trust

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Authors: Andrea Giacomelli, Luciano Massetti, Elena Maggi, Antonio Raschi

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The presentation will report the activities managed during the Summer of 2017 by a team composed by staff from a University Department, a National Research Council Institute, and an outreach NGO, collecting measurements of night sky brightness and other information on artificial lighting, in order to characterize light pollution issues on portions of the Tuscan coast, in Central Italy. These activities combine measurements collected by the principal scientists, citizen science observations led by students, and outreach events targeting a broad audience. This campaign aggregates the efforts of three actors: the BuioMetria Partecipativa project, which started collecting light pollution data on a national scale in 2008 with an environmental engineering and free/open source GIS core team; the Institute of Biometeorology from the National Research Council, with ongoing studies on light and urban vegetation and a consolidated track record in environmental education and citizen science; the Department of Biology from the University of Pisa, which started experiments to assess the impact of light pollution in coastal environments in 2015. While the core of the activities concerns in situ data, the campaign will account also for remote sensing data, thus considering heterogeneous data sources. The aim of the campaign is twofold: (1) To test actions of citizen and student engagement in monitoring sky brightness (2) To collect night sky brightness data and test a protocol for applications to studies on the ecological impact of light pollution, with a special focus on marine coastal ecosystems. The collaboration of an interdisciplinary team in the study of artificial lighting issues is not a common case in Italy, and the possibility of undertaking the campaign in Tuscany has the added value of operating in one of the territories where it is possible to observe both sites with extremely high lighting levels, and areas with extremely low light pollution, especially in the Southern part of the region. Combining environmental monitoring and communication actions in the context of the campaign, this effort will contribute to the promotion of night skies with a good quality as an important asset for the sustainability of coastal ecosystems, as well as to increase citizen awareness through star gazing, night photography and actively participating in field campaign measurements.

Keywords: citizen science, light pollution, marine coastal biodiversity, environmental education

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Authors: Jeffrey Tzu-Hao Tsai, Yi-Shan Wong

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This article proposes a cohort-age-period (CAP) model to characterize multi-population mortality processes using cohort, age, and period variables. Distinct from the factor-based Lee-Carter-type decomposition mortality model, this approach is empirically based and includes the age, period, and cohort variables into the equation system. The model not only provides a fruitful intuition for explaining multivariate mortality change rates but also has a better performance in forecasting future patterns. Using the US and the UK mortality data and performing ten-year out-of-sample tests, our approach shows smaller mean square errors in both countries compared to the models in the literature.

Keywords: longevity risk, stochastic mortality model, multivariate mortality rate, risk management

Procedia PDF Downloads 54

Authors: Ernest Tambo, Ghislaine Madjou, Jeanne Y. Ngogang, Shenglan Tang, Zhou XiaoNong

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Implementing national to community-based 'One Health' surveillance approach for human, animal and environmental consequences mitigation offers great opportunities and value-added in sustainable development and wellbeing. 'One Health' surveillance approach global partnerships, policy commitment and financial investment are much needed in addressing the evolving threats and epidemics crises mitigation in African countries. The paper provides insights onto how China-Africa health development cooperation in promoting “One Health” surveillance approach in response advocacy and mitigation. China-Africa health development initiatives provide new prospects in guiding and moving forward appropriate and evidence-based advocacy and mitigation management approaches and strategies in attaining Universal Health Coverage (UHC) and Sustainable Development Goals (SDGs). Early and continuous quality and timely surveillance data collection and coordinated information sharing practices in malaria and other diseases are demonstrated in Comoros, Zanzibar, Ghana and Cameroon. Improvements of variety of access to contextual sources and network of data sharing platforms are needed in guiding evidence-based and tailored detection and response to unusual hazardous events. Moreover, understanding threats and diseases trends, frontline or point of care response delivery is crucial to promote integrated and sustainable targeted local, national “One Health” surveillance and response approach needs implementation. Importantly, operational guidelines are vital in increasing coherent financing and national workforce capacity development mechanisms. Strengthening participatory partnerships, collaboration and monitoring strategies in achieving global health agenda effectiveness in Africa. At the same enhancing surveillance data information streams reporting and dissemination usefulness in informing policies decisions, health systems programming and financial mobilization and prioritized allocation pre, during and post threats and epidemics crises programs strengths and weaknesses. Thus, capitalizing on “One Health” surveillance and response approach advocacy and mitigation implementation is timely in consolidating Africa Union 2063 agenda and Africa renaissance capabilities and expectations.

Keywords: Africa, one health approach, surveillance, response

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Authors: Bhavna Rajagopal, Mrinmoyi Kulkarni

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Today women experience more menstrual cycles than their ancestors did a hundred years ago, owing to early puberty, fewer pregnancies and dietary changes. Much of the research in menstruation is located in the medical domain with a focus on physical symptoms. The research in psychology is largely concerned with premenstrual syndrome (PMS), whereas the focus in sociology is on social and cultural practices relating to menstruation. Research that simultaneously studies the physical, psychological, social and cultural aspects is lacking. Therefore, in this study, an attempt has been made to identify socio-cultural, psychological and physical factors that interact to influence a woman’s experience of menstruation in the urban setting. The study included seven unmarried women in the age group of 24-30 and data was obtained through a focus group discussion. The transcript of the focus group discussion was thematically analysed. Two major themes relating to the self and social experience of menstruation emerged. Themes relating to the self included menarcheal experiences, self-perception, mood and management of menstrual hygiene and symptoms while themes relating to social experience included the construction of menstruation by family and peers, and cultural factors. Attitudes towards the menstrual cycle appeared to be primarily influenced by severity of symptoms and the resulting disruption to daily life. Outcomes of this study have indicated that future research needs to study menstruation and its impact on women’s wellbeing by adopting a socio-ecological approach and by collecting data using the whole cycle approach across a woman’s reproductive years.

Keywords: India, menstrual cycle, psychosocial approach, wellbeing

Procedia PDF Downloads 133

Authors: Tsega Asresa Mengistu, Getahun Tigistu

Abstract:

Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.

Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network

Procedia PDF Downloads 438

Authors: K. P. Mredula, D. C. Vakaskar

Abstract:

The article traces developments and evolution of various algorithms developed for solving partial differential equations using the significant combination of wavelet with few already explored solution procedures. The approach depicts a study over a decade of traces and remarks on the modifications in implementing multi-resolution of wavelet, finite difference approach, finite element method and finite volume in dealing with a variety of partial differential equations in the areas like plasma physics, astrophysics, shallow water models, modified Burger equations used in optical fibers, biology, fluid dynamics, chemical kinetics etc.

Keywords: multi-resolution, Haar Wavelet, partial differential equation, numerical methods

Procedia PDF Downloads 299

Authors: Ahmet Kaya

Abstract:

Incoming cash flows and outgoing claims play an important role to determine how is companies’ profit or loss. In this matter, ruin probability provides to describe vulnerability of the companies against ruin. Quantum mechanism is one of the significant approaches to model ruin probability as stochastically. Using the Hamiltonian method, we have performed formalisation of quantum mechanics < x|e-ᵗᴴ|x' > and obtained the transition probability of 2x2 and 3x3 matrix as traditional and eigenvector basis where A is a ruin operator and H|x' > is a Schroedinger equation. This operator A and Schroedinger equation are defined by a Hamiltonian matrix H. As a result, probability of not to be in ruin can be simulated and calculated as stochastically.

Keywords: ruin probability, quantum mechanics, Hamiltonian technique, operator approach

Procedia PDF Downloads 341

Authors: Bikram Jung Kunwar, Pralhad Kunwor

Abstract:

The Community-Based Forest Management (CBFM) approach is often glorified as the best forest management alternatives in the developing countries. However, how the approach has been understood by the local user households, who implement it is remained unanswered for many planners, policy makers, and sometimes researcher as well. The study attempts to assess the understanding of ecology and economics of CBFM in Nepal, where community forest program has been implemented since the 1970s. In order to understand the impacts of the program, eight criteria and sixteen indicators for ecological conservation and similarly same number of criteria and indicators for socio-economic impacts of the program were designed and compared between before and after the program implementation. The community forestry program has positive effects in forest ecology conservation and at the same time rural livelihood improvement of local people. The study revealed that collective understanding of forest ecology and economics leads the CBFM approach towards the sustainability of the program in a win-win situation. The recommendations of the study are expected to be useful to natural resource managers, planners, and policy makers.

Keywords: community, forest management, ecology, economics, Nepal

Procedia PDF Downloads 394

Authors: Yujie Zhang

Abstract:

There are debates around the legitimacy of capital punishment, i.e., whether death could serve as a proper execution in our legal system or not. Different arguments have been raised. However, none of them seem able to provide a determined answer to the issue; this results in a lack of instruction in the legal practice. This article, therefore, devotes itself to the effort to find such an answer. It takes the perspective of rights, through interpreting the concept of right to life, which capital punishment appears to be in confliction with in the two traditional approaches, to reveal a possibly best account of the right and its conclusion on capital punishment. However, this effort is not a normative one which focuses on what ought to be. It means the article does not try to work out which argument we should choose and solve the hot debate on whether capital punishment should be allowed or not. It, again, does not propose which perspective we should take to approach this issue or generally which account of right must be better; rather, it is more a thought experiment. It attempts to raise a new perspective to approach the issue of the legitimacy of capital punishment. Both its perspective and conclusion therefore are tentative: what if we view this issue in a way we have never tried before, for example the different accounts of right to life? In this sense, the perspective could be defied, while the conclusion could be rejected. Other perspectives and conclusions are also possible. Notwithstanding, this tentative perspective and account of the right still could not be denied from serving as a potential approach, since it does have the ability to provide us with a determined attitude toward capital punishment that is hard to achieve through existing arguments.

Keywords: capital punishment, right to life, theories of rights, the choice theory

Procedia PDF Downloads 195