Search results for: task force on MI

Authors: Fahad Alahmadi, Norhan Abd Rahman, Mohammad Abdulrazzak, Zulikifli Yusop

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Runoff prediction of ungauged catchment is still a challenging task especially in arid regions with a unique land cover such as volcanic basalt rocks where geological weathering and fractures are highly significant. In this study, Bathan catchment in Madinah western Saudi Arabia was selected for analysis. The aim of this paper is to evaluate different rainfall loss methods; soil conservation Services curve number (SCS-CN), green-ampt and initial-constant rate. Different direct runoff methods were evaluated: soil conservation services dimensionless unit hydrograph (SCS-UH), Snyder unit hydrograph and Clark unit hydrograph. The study showed the superiority of SCS-CN loss method and Clark unit hydrograph method for ungauged catchment where there is no observed runoff data.

Keywords: urban runoff modelling, arid regions, ungauged catchments, volcanic rocks, Madinah, Saudi Arabia

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Authors: Rania Ahmed Kadry Abdel Gawad Birry, Mohamed El-Habrouk

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This paper presents a brief survey of the techniques used for sign language recognition along with the types of sensors used to perform the task. It presents a modified method for identification of an isolated sign language gesture using Microsoft Kinect with the OpenNI framework. It presents the way of extracting robust features from the depth image provided by Microsoft Kinect and the OpenNI interface and to use them in creating a robust and accurate gesture recognition system, for the purpose of ASL translation. The Prime Sense’s Natural Interaction Technology for End-user - NITE™ - was also used in the C++ implementation of the system. The algorithm presents a simple finger counting algorithm for static signs as well as directional Finite State Machine (FSM) description of the hand motion in order to help in translating a sign language gesture. This includes both letters and numbers performed by a user, which in-turn may be used as an input for voice pronunciation systems.

Keywords: American sign language, finger counting, hand tracking, Microsoft Kinect

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Authors: Mohammad Iqbal Malik

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Economic development of a country depends on its business ethics and values. Islamic teachings provide obvious guidelines in this regard. Mutual understanding, honesty and ethics possess central place in Islamic teachings. These teachings not only prohibit from amalgamation, black-marketing, hoarding and deception but also force to treat a customer amiably. Business ethics are broad spectrum in Islamic society due to these high moral values. One can estimate the importance of business ethics in Islam for economic development in Islamic society is evident by the Hadith of Prophet Muhammad (PBUH) in which He excluded a trader from Muslim community who did not behave in good manners with his clients. In this study we present impact of business ethics on economic development of a Muslim society. This study is based on basic teachings of Quran and Sunnah, Fiqh, Economics and other books. This study explores the behavior of Muslim traders and reveals useful inferences. Policy makers, traders, academia, scholars, and general public may learn lessons from this study with respect to business ethics in Islamic perspective.

Keywords: ethics, business, Islam, economic perspective

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Cross-domain learning in the medical field is a research challenge as many conditions, like in oncology imaging, use different imaging modalities. Moreover, in most of the medical learning applications, the sample training size is relatively small. Although few-shot learning (FSL) through the use of a Siamese neural network was able to be trained on a small sample with remarkable accuracy, FSL fails to be effective for use in multiple domains as their convolution weights are set for task-specific applications. In this paper, we are addressing this problem by enabling FSL to possess the ability to shift across domains by designing a two-layer FSL network that can learn individually from each domain and produce a shared features map with extra modulation to be used at the second layer that can recognize important targets from mix domains. Our initial experimentations based on mixed medical datasets like the Medical-MNIST reveal promising results. We aim to continue this research to perform full-scale analytics for testing our cross-domain FSL learning.

Keywords: Siamese neural network, few-shot learning, meta-learning, metric-based learning, thick data transformation and analytics

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Authors: Yuta Moriyama, Tsuyoshi Yamazaki, Etsuo Morishita

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Several aerodynamic devices currently attract engineers and research students. The plasma actuator is one of them, and it is very effective to control the flow. The actuator recovers a separated flow to an attached one. The actuator is also inversely applied to a spoiler. The model aircraft might be controlled by this actuator. We develop a model aircraft with the plasma actuator. Another interesting device is the Wells turbine which rotates in one direction. The present authors propose a bicycle with the Wells turbine in the wheels. Power reduction is measured when the turbine is driven by an electric motor at the exit of a wind tunnel. Several Watts power reduction might be possible. This means that the torque of the bike can be augmented by the turbine in the cross wind. These devices are tested in the wind tunnel with a three-component balance and the aerodynamic forces and moment are obtained. In this paper, we introduce these devices and their aerodynamic characteristics. The control force and moment of the plasma actuator are clarified and the power reduction of the bicycle is quantified.

Keywords: aerodynamics, model aircraft, plasma actuator, Wells turbine

Procedia PDF Downloads 246

Authors: Mohammad Akram

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The aim of this study is to improve classroom management while teaching especially ESL/EFL. At the same time, it has been discussed about the standard of the students through some surveys held in Jazan University in the month of February and March, 2013. The present research is a classroom action-oriented study. The subject of the study is mainly the students whose first language is not English at all. The study is prepared in one cycle that has planning, action, and reaction as well. Teachers of English as a second language/foreign language generally face numerous of unexpected problems while dealing with their students. To make the classes practical, meaningful, and easy like fun for the students is really a cumbersome task. It's a very practical move towards classroom ESL/EFL teaching if we want to apply anything new, I mean new policies, tactics, recent/smart teaching methodologies, we must peep into the hole of past because it will give us the best solution for the present strategies. We need to academically study the past of our students to make their present fruitful. Here, author wants to present a few important problematic issues like classroom management in the area of ESL/EFL while teaching ESL students. Impact these are suggestions to combat drawbacks of 'Classroom Teaching'. “Classroom management is to put into practice and a process through teaching and learning process”.

Keywords: global, teachers, perceptions, classroom, management, integrated, segregated, comprehension, productive

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Authors: Mohd Ridzwan Yaakub, Muhammad Iqbal Abu Latiffi

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Online business has become popular recently due to the massive amount of information and medium available on the Internet. This has resulted in the huge number of reviews where the consumers share their opinion, criticisms, and satisfaction on the products they have purchased on the websites or the social media such as Facebook and Twitter. However, to analyze customer’s behavior has become very important for organizations to find new market trends and insights. The reviews from the websites or the social media are in structured and unstructured data that need a sentiment analysis approach in analyzing customer’s review. In this article, techniques used in will be defined. Definition of the ontology and description of its possible usage in sentiment analysis will be defined. It will lead to empirical research that related to mobile phones used in research and the ontology used in the experiment. The researcher also will explore the role of preprocessing data and feature selection methodology. As the result, ontology-based approach in sentiment analysis can help in achieving high accuracy for the classification task.

Keywords: feature selection, ontology, opinion, preprocessing data, sentiment analysis

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Authors: Naman Jain, Shaun Fernandes

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With the increasing prevalence of online healthcare services, selecting the most suitable doctor has become a complex task, requiring careful consideration of both public sentiment and personal preferences. This paper proposes a sentiment analysis-driven method that integrates public reviews with user-specific criteria and correlated attributes to recommend online doctors. By leveraging Natural Language Processing (NLP) techniques, public sentiment is extracted from online reviews, which is then combined with user-defined preferences such as specialty, years of experience, location, and consultation fees. Additionally, correlated attributes like education and certifications are incorporated to enhance the recommendation accuracy. Experimental results demonstrate that the proposed system significantly improves user satisfaction by providing personalized doctor recommendations that align with both public opinion and individual needs.

Keywords: sentiment analysis, online doctors, personal preferences, correlated attributes, recommendation system, healthcare, natural language processing

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Authors: Vijaya Yuvaram Singh V M, Kameshwar Rao J V

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The challenge with development of neural network based methods for medical is the availability of data. Anatomical landmark detection in the medical domain is a process to find points on the x-ray scan report of the patient. Most of the time this task is done manually by trained professionals as it requires precision and domain knowledge. Traditionally object detection based methods are used for landmark detection. Here, we utilize reinforcement learning and query based method to train a single agent capable of detecting multiple landmarks. A deep Q network agent is trained to detect single and multiple landmarks present on hip and shoulder from x-ray scan of a patient. Here a single agent is trained to find multiple landmark making it superior to having individual agents per landmark. For the initial study, five images of different patients are used as the environment and tested the agents performance on two unseen images.

Keywords: reinforcement learning, medical landmark detection, multi target detection, deep neural network

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Authors: Mannan Malik Muhammad Naeem, Jeong Myung Yung

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Functional near infrared spectroscopy (fNIRS) has a favorable position in non-invasive brain imaging techniques. The concentration change of oxygenated hemoglobin and de-oxygenated hemoglobin during particular cognitive activity is the basis for this neuro-imaging modality. Two wavelengths of near-infrared light can be used with modified Beer-Lambert law to explain the indirect status of neuronal activity inside brain. The temporal resolution of fNIRS is very good for real-time brain computer-interface applications. The portability, low cost and an acceptable temporal resolution of fNIRS put it on a better position in neuro-imaging modalities. In this study, an optimization model for impulse response function has been used to estimate/predict initial dip using fNIRS data. In addition, the activity strength parameter related to motor based cognitive task has been analyzed. We found an initial dip that remains around 200-300 millisecond and better localize neural activity.

Keywords: fNIRS, brain-computer interface, optimization algorithm, adaptive signal processing

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Authors: Benjamin Kaufmann, Michael Hofstätter, Nadine Raidl, Peter Supancic

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ZnO varistors are the leading overvoltage protection elements in today’s electronic industry. Their highly non-linear current-voltage characteristics, very fast response times, good reliability and attractive cost of production are unique in this field. There are challenges and questions unsolved. Especially, the urge to create even smaller, versatile and reliable parts, that fit industry’s demands, brings manufacturers to the limits of their abilities. Although, the varistor effect of sintered ZnO is known since the 1960’s, and a lot of work was done on this field to explain the sudden exponential increase of conductivity, the strict dependency on sinter parameters, as well as the influence of the complex microstructure, is not sufficiently understood. For further enhancement and down-scaling of varistors, a better understanding of the microscopic processes is needed. This work attempts a microscopic approach to investigate ZnO varistor performance. In order to cope with the polycrystalline varistor ceramic and in order to account for all possible current paths through the material, a preferably realistic model of the microstructure was set up in the form of three-dimensional networks where every grain has a constant electric potential, and voltage drop occurs only at the grain boundaries. The electro-thermal workload, depending on different grain size distributions, was investigated as well as the influence of the metal-semiconductor contact between the electrodes and the ZnO grains. A number of experimental methods are used, firstly, to feed the simulations with realistic parameters and, secondly, to verify the obtained results. These methods are: a micro 4-point probes method system (M4PPS) to investigate the current-voltage characteristics between single ZnO grains and between ZnO grains and the metal electrode inside the varistor, micro lock-in infrared thermography (MLIRT) to detect current paths, electron back scattering diffraction and piezoresponse force microscopy to determine grain orientations, atom probe to determine atomic substituents, Kelvin probe force microscopy for investigating grain surface potentials. The simulations showed that, within a critical voltage range, the current flow is localized along paths which represent only a tiny part of the available volume. This effect could be observed via MLIRT. Furthermore, the simulations exhibit that the electric power density, which is inversely proportional to the number of active current paths, since this number determines the electrical active volume, is dependent on the grain size distribution. M4PPS measurements showed that the electrode-grain contacts behave like Schottky diodes and are crucial for asymmetric current path development. Furthermore, evaluation of actual data suggests that current flow is influenced by grain orientations. The present results deepen the knowledge of influencing microscopic factors on ZnO varistor performance and can give some recommendations on fabrication for obtaining more reliable ZnO varistors.

Keywords: metal-semiconductor contact, Schottky diode, varistor, zinc oxide

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Authors: Hamideh Marefat, Eskandar Samadi

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This study examined the effect of semantics on processing ambiguous sentences containing Relative Clauses (RCs) preceded by a complex Determiner Phrase (DP) by Persian-speaking learners of L2 English with different proficiency and Working Memory Capacities (WMCs). The semantic relationship studied was one between the subject of the main clause and one of the DPs in the complex DP to see if, as predicted by Spreading Activation Model, priming one of the DPs through this semantic manipulation affects the L2ers’ preference. The results of a task using Rapid Serial Visual Processing (time-controlled paradigm) showed that manipulation of the relationship between the subject of the main clause and one of the DPs in the complex DP preceding RC has no effect on the choice of the antecedent; rather, the L2ers' processing is guided by the phrase structure information. Moreover, while proficiency did not have any effect on the participants’ preferences, WMC brought about a difference in their preferences, with a DP1 preference by those with a low WMC. This finding supports the chunking hypothesis and the predicate proximity principle, which is the strategy also used by monolingual Persian speakers.

Keywords: semantics, relative clause processing, ambiguity resolution, proficiency, working memory capacity

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Authors: Sean Paulsen, Michael Casey

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In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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Authors: Wan Noorul Hafilah Binti Wan Ariffin

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Dam safety management is the crucial infrastructure as dam failure has a catastrophic effect on the community. Dam safety management is the effective framework of key actions and activities for the dam owner to manage the safety of the dam for its entire life cycle. However, maintaining dam safety is a challenging task as there are changes in current dam states. These changes introduce new risks to the dam's safety, which had not been considered when the dam was designed. A new framework has to be developed to adapt to the changes in the dam risk and make the dams resilient. This study proposes a risk-based decision-making adaptation framework for dam safety management. The research focuses on climate change's impact on hydrological situations as it causes floods and damages the dam structure. The risk analysis framework is adopted to improve the dam management strategies. The proposed study encompasses four phases. To start with, measuring the effect by assessing the impact of climate change on embankment dam, the second phase is to analyze the potential embankment dam failures. The third is analyzing the different components of risks related to the dam and, finally, developing a robust decision-making framework.

Keywords: climate change, embankment dam, failure, risk-informed decision making

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Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal

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Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.

Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks

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Authors: Huang Yajing

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Multimodal discourse refers to the phenomenon of using various senses such as hearing, vision, and touch to communicate through various means and symbolic resources such as language, images, sounds, and movements. With the development of modern technology and multimedia, language and technology have become inseparable, and foreign language teaching is becoming more and more modal. Teacher-student communication resorts to multiple senses and uses multiple symbol systems to construct and interpret meaning. The classroom is a semiotic space where multimodal discourses are intertwined. College English multi-modal teaching is to rationally utilize traditional teaching methods while mobilizing and coordinating various modern teaching methods to form a joint force to promote teaching and learning. Multimodal teaching makes full and reasonable use of various meaning resources and can maximize the advantages of multimedia and network environments. Based upon the above theories about multimodal discourse and multimedia technology, the present paper will propose a multi-modal teaching model for college English in China.

Keywords: multimodal discourse, multimedia technology, English education, applied linguistics

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Authors: Jin-Sim, Kwan-U Kim, Ryong-Jin Jang, Sung-Duk Kim

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Earth rotation is one of astronomical phenomena without which it is impossible to think of human life. That is why the investigation of the Earth's rotation is very important, and it has a long history of study. The invention of quartz clocks in the 1930s, atomic time in the 1950s, and the introduction of modern technology into astronomic observation in recent years resulted in rapid development of the study of Earth’s rotation. The theory of the Earth's rotation, however, has not been up to the high level of astronomic observation due to the limitation of time. As a typical example, we can take the problems that cover the instabilities of the Earth’s rotation, proved completely by the astronomic observations as well as polar motion, the precession and nutation of the Earth's rotation axis, which have not been described in a single equation in a quantificational way from the unique law of Earth rotation. In particular, at present the problem of what is the main factor causing the instabilities of the Earth rotation has not been solved clearly in quantificational ways yet. Therefore, this paper gives quantificational proof that the main factor that causes the instabilities of the Earth's rotation is the moment of external force other than variations in the relative atmospheric angular momentum due to the time limitation and under some assumptions or the moment of inertia of the Earth’s body.

Keywords: atmospheric angular momentum, instabilities of the earth’s rotation, law of the earth’s rotation change, moment of inertia of the earth

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Authors: Magdaléna Náplavová, Tomáš Ludík, Petr Hrůza, František Božek

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The use of IT equipment has become a part of every day. However, each device that is part of cyberspace should be secured against unauthorized use. It is very important to know the basics of these security devices, but also the basics of safe conduct their owners. This information should be part of every curriculum computer science education in primary and secondary schools. Therefore, the work focuses on the education of pupils in primary and secondary schools on the Internet. Analysis of the current state describes approaches to the education of pupils in security issues on the Internet. The paper presents a questionnaire-based survey which was carried out in the Czech Republic, whose task was to ascertain the level of opinion pupils in primary and secondary schools on the issue of communication in social networks. The research showed that awareness of socio-pathological phenomena on the Internet environment is very low. Based on the results it was proposed appropriate ways of teaching to this issue and its inclusion a proposal of curriculum for primary and secondary schools.

Keywords: information security, cyber space, general awareness, questionnaire, socio-pathological phenomena, educational system

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Anzor Abralava, Ketevan Kokrashvili, Rusudan Kutateladze, Nino Pailodze, Ketevan Kutateladze, Giorgi Sulashvili

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Nowadays when the integration of states is growing fast, it is urgent to study the rules of behavior which they resort to in case of conflicts and disagreements. The reason of disagreement in many ways is the Foreign policy carried out by separate countries, as the market participants define production and export capacity and structure as well as level of international division of labor due to the competition among them. We can say over and over again that outbreak of conflicts in Georgia displays the serious controversy between political and economic powerhouses. However, to tell the truth existence of the unsolved conflicts in Georgia is the result of weakness and inadequacy of Georgian politics. Today the main task of political quarters in Georgia should be a direction to Caucasus, as to the region burdened with the most complicated problems which blockade the settlement of conflicts and farther development of our country (or vice versa). In this situation rehabilitation of our authority, leading role and hegemony; expansion and consolidation of peacekeeping and other missions are considered as the exact activities for accomplishing all Georgian economic and political goals.

Keywords: Awara Group, political centers, administrative services, dynamic process

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: E. A. Tkachenko, E. M. Rogova, A. S. Osipenko

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The problems of technological development for the Russian Federation take on special significance in the context of modernization of the production base. The complexity of the position of the Russian economy is that it cannot be attributed fully to developing ones. Russia is a strong industrial power that has gone through the processes of destructive de-industrialization in the conditions of changing its economic and political structure. The need to find ways for re-industrialization is not a unique task for the economies of industrially developed countries. Under the influence of production outsourcing for 20 years, the industrial potential of leading economies of the world was regressed against the backdrop of the ascent of China, a new industrial giant. Therefore, methods, tools, and techniques utilized for industrial renaissance in EU may be used to achieve a technological leap in the Russian Federation, especially since the temporary gap of 5-7 years makes it possible to analyze best practices and use those technological transfer tools that have shown the greatest efficiency. In this article, methods of technological transfer are analyzed, the role of technological audit is justified, and factors are analyzed that influence the successful process of commercialization of technologies.

Keywords: technological transfer, productivity, technological audit, commercialization of technologies

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Authors: Hesamoddin Abdollahpour, Roghayeh Abdollahpour, Elham Rahgozar

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This paper we deal with an analysis of the free vibrations of the governing partial differential equation that it is Danel equation in the shells. The problem considered represents the governing equation of the nonlinear, large amplitude free vibrations of the hinged shell. A new implementation of the new method is presented to obtain natural frequency and corresponding displacement on the shell. Our purpose is to enhance the ability to solve the mentioned complicated partial differential equation (PDE) with a simple and innovative approach. The results reveal that this new method to solve Danel equation is very effective and simple, and can be applied to other nonlinear partial differential equations. It is necessary to mention that there are some valuable advantages in this way of solving nonlinear differential equations and also most of the sets of partial differential equations can be answered in this manner which in the other methods they have not had acceptable solutions up to now. We can solve equation(s), and consequently, there is no need to utilize similarity solutions which make the solution procedure a time-consuming task.

Keywords: large amplitude, free vibrations, analytical solution, Danell Equation, diagram of phase plane

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Authors: Haonan Hu, Shuge Lei, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Jijun Tang

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This paper focuses on the classification task of breast ultrasound images and conducts research on the reliability measurement of classification results. A dual-channel evaluation framework was developed based on the proposed inference reliability and predictive reliability scores. For the inference reliability evaluation, human-aligned and doctor-agreed inference rationals based on the improved feature attribution algorithm SP-RISA are gracefully applied. Uncertainty quantification is used to evaluate the predictive reliability via the test time enhancement. The effectiveness of this reliability evaluation framework has been verified on the breast ultrasound clinical dataset YBUS, and its robustness is verified on the public dataset BUSI. The expected calibration errors on both datasets are significantly lower than traditional evaluation methods, which proves the effectiveness of the proposed reliability measurement.

Keywords: medical imaging, ultrasound imaging, XAI, uncertainty measurement, trustworthy AI

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Authors: Seul-Ki Park, Jong-Chun Park, Gyu-Mok Jeon, Dae-Kyung Ock, Seung-Gyu Jeong

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Rogue waves cause frequent accidents of ships and offshore structures, which can result in severe damage to the structures. The Rogue waves, which are also known as big waves, freak waves, extreme waves, monster waves, focused waves, giant waves and abnormal waves, are unexpected and suddenly appearing, and can have a breaking force to destroy the structure even though modern structures are designed to tolerate a breaking wave. In the present study, a series of focused waves are numerically reproduced by concentrating nonlinear multi-directional waves into a target point using a commercial CFD software, Star-CCM+. A flow analysis for investigating the physical characteristics of the focused waves is performed using the Star-CCM+, while it has several difficulties to examine the inner properties of the waves in existing potential theory and experiments. Additionally, the 6-DOF (Degree of Freedom) motion of a floating body interacting with the focused waves are simulated, and the dynamic response of the body are discussed.

Keywords: multidirectional waves, focused waves, rogue waves, wave-structure interaction, numerical wave tank, computational fluid dynamics

Procedia PDF Downloads 251

Authors: Xian Xie, Qinghua Fang

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This study used quantitative and qualitative methods to explore the characteristics of flipped classroom’s influence on classroom environment of college English reading, writing, and translating, and to summarize and reflect on the teaching characteristics of college English Reading, writing, and translating. The results of the study indicated that after the flipped classroom applied to reading, writing, and translating, students’ performance was improved to a certain extent, the classroom environment was improved to some extent, students of the flipped classroom are generally satisfied with the classroom environment; students showed a certain degree of individual differences to the degree of cooperation, participation, self-responsibility, task-orientation, and the teacher leadership and innovation. The study indicated that the implementation of flipped classroom teaching mode can optimize College English reading, writing, and translating classroom environment and realize target－learner as the center in foreign language teaching and learning, but bring a greater challenge to teachers.

Keywords: classroom environment, college English reading, writing and translating, individual differences, flipped classroom

Procedia PDF Downloads 265

Authors: Tatyana Aleksandrovna Barbasova, Lev Sergeevich Kazarinov, Olga Valerevna Kolesnikova, Aleksandra Aleksandrovna Filimonova

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We regard forecasting of energy consumption by private production areas of a large industrial facility as well as by the facility itself. As for production areas the forecast is made based on empirical dependencies of the specific energy consumption and the production output. As for the facility itself implementation of the task to minimize the energy consumption forecasting error is based on adjustment of the facility’s actual energy consumption values evaluated with the metering device and the total design energy consumption of separate production areas of the facility. The suggested procedure of optimal energy consumption was tested based on the actual data of core product output and energy consumption by a group of workshops and power plants of the large iron and steel facility. Test results show that implementation of this procedure gives the mean accuracy of energy consumption forecasting for winter 2014 of 0.11% for the group of workshops and 0.137% for the power plants.

Keywords: energy consumption, energy consumption forecasting error, energy efficiency, forecasting accuracy, forecasting

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Authors: Merve Ermis, Akif Kutlu, Nihal Eratlı, Mehmet H. Omurtag

Abstract:

In this study, the free vibration analysis of conical helicoidal rods with two different elliptically oriented cross sections is investigated and the results are compared by the circular cross-section keeping the net area for all cases equal to each other. Problems are solved by using the mixed finite element formulation. Element matrices based on Timoshenko beam theory are employed. The finite element matrices are derived by directly inserting the analytical expressions (arc length, curvature, and torsion) defining helix geometry into the formulation. Helicoidal rod domain is discretized by a two-noded curvilinear element. Each node of the element has 12 DOFs, namely, three translations, three rotations, two shear forces, one axial force, two bending moments and one torque. A parametric study is performed to investigate the influence of elliptical cross sectional geometry and its orientation over the natural frequencies of the conical type helicoidal rod.

Keywords: conical helix, elliptical cross section, finite element, free vibration

Procedia PDF Downloads 315

Authors: Gaoguang Yang, Shan Fu

Abstract:

Human-machine interface (HMI) intermediate system information to human operators to facilitate human ability to manage and control the system. Well-designed HMI would enhance human ability. An evaluation must be performed to confirm that the designed HMI would enhance but not degrade human ability. However, the prevalent HMI evaluation techniques have difficulties in more thoroughly and accurately evaluating the suitability and fitness of a given HMI for the wide variety of uncertainty contained in both the existing HMI evaluation techniques and the large number of task scenarios. The first limitation should be attributed to the subjective and qualitative analysis characteristics of these evaluation methods, and the second one should be attributed to the cost balance. This study aims to explore the connection between objective HMI characters and ergonomic safety and step forward toward solving these limitations with objective, characterized HMI parameters. A simulation experiment was performed with the time needed for human operators to recognize the HMI information as characterized HMI parameter, and the result showed a strong correlation between the parameter and ergonomic safety level.

Keywords: Human-Machine Interface (HMI), evaluation, objective, characterization, simulation

Procedia PDF Downloads 66