Search results for: laser processing of fiber-reinforced plastics (FRP)

Authors: Diqin Qi, Jiaming Li, Siman Li

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Based on the use of the three-point smoothing method for selectively processing original data columns, this paper establishes a group of grey GM(1,1) models to predict the concentration ranges of four major air pollutants in Shanghai from 2023 to 2024. The results indicate that PM₁₀, SO₂, and NO₂ maintain the national Grade I standards, while the concentration of PM₂.₅ has decreased but still remains within the national Grade II standards. Combining the forecast results, recommendations are provided for the Shanghai municipal government's efforts in air pollution prevention and control.

Keywords: atmospheric pollutant prediction, Grey GM(1, 1), model group, three-point smoothing method

Procedia PDF Downloads 35

Authors: Karen Louise Lacey, Dario Javier Pavon Vargas, Massimiliano Rinaldi, Luca Cattani, Sara Rainieri

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The effects of high-pressure processing (HPP) and thermal treatments (TT) on quality markers of strawberry nectar (12 °Brix, 3,3 pH) was studied before and after treatments. TT and HPP treatments ensured a 3-log aerobic bacteria inactivation. No significant difference was detected in terms of pH and °Brix. TT samples were less red (a* less positive) than all HPP treated samples, while all samples were less red than the control. Apparent viscosity was significantly increased in all the HPP treatments, at 10 1/s shear rate, control was 79.04±7.94 mPa•s and the 600 MPa-20 min treatment were 327.10±1.64 mPa•s. This work suggests that HPP treatments may maintain the quality markers of strawberry nectar better.

Keywords: HPP, strawberry nectar, colour , viscosity

Procedia PDF Downloads 130

Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

Procedia PDF Downloads 164

Authors: Sylwia Laba, Robert Laba, Krystian Szczepanski, Mikolaj Niedek, Anna Kaminska-Dworznicka

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Meat and its products are considered food products, having the most unfavorable effect on the environment that requires rational management of these products and waste, originating throughout the whole chain of manufacture, processing, transport, and trade of meat. From the economic and environmental viewpoints, it is important to limit the losses and food wastage and the food waste in the whole meat sector. The link to basic production includes obtaining raw meat, i.e., animal breeding, management, and transport of animals to the slaughterhouse. Food is any substance or product, intended to be consumed by humans. It was determined (for the needs of the present studies) when the raw material is considered as a food. It is the moment when the animals are prepared to loading with the aim to be transported to a slaughterhouse and utilized for food purposes. The aim of the studies was to determine the reasons for loss generation in the basic production of the meat sector in Poland during the years 2017 – 2018. The studies on food losses and waste in the meat sector in basic production were carried out in two areas: red meat i.e., pork and beef and poultry meat. The studies of basic production were conducted in the period of March-May 2019 at the territory of the whole country on a representative trial of 278 farms, including 102 pork production, 55–beef production, and 121 poultry meat production. The surveys were carried out with the utilization of questionnaires by the PAPI (Paper & Pen Personal Interview) method; the pollsters conducted direct questionnaire interviews. Research results indicate that it is followed that any losses were not recorded during the preparation, loading, and transport of the animals to the slaughterhouse in 33% of the visited farms. In the farms where the losses were indicated, the crushing and suffocations, occurring during the production of pigs, beef cattle and poultry, were the main reasons for these losses. They constituted ca. 40% of the reported reasons. The stress generated by loading and transport caused 16 – 17% (depending on the season of the year) of the loss reasons. In the case of poultry production, in 2017, additionally, 10.7% of losses were caused by inappropriate conditions of loading and transportation, while in 2018 – 11.8%. The diseases were one of the reasons for the losses in pork and beef production (7% of the losses). The losses and waste, generated during livestock production and in meat processing and trade cannot be managed or recovered. They have to be disposed of. It is, therefore, important to prevent and minimize the losses throughout the whole production chain. It is possible to introduce the appropriate measures, connected mainly with the appropriate conditions and methods of animal loading and transport.

Keywords: food losses, food waste, livestock production, meat sector

Procedia PDF Downloads 144

Authors: Emin Gundogar, Burak Erkayman, Nusret Sazak

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Providing effective management performance through the whole supply chain is critical issue and hard to applicate. The proper evaluation of integrated data may conclude with accurate information. Analysing the supply chain data through OLAP (On-Line Analytical Processing) technologies may provide multi-angle view of the work and consolidation. In this study, association rules and classification techniques are applied to measure the supply chain performance metrics of an automotive manufacturer in Turkey. Main criteria and important rules are determined. The comparison of the results of the algorithms is presented.

Keywords: supply chain performance, performance measurement, data mining, automotive

Procedia PDF Downloads 513

Authors: Ajayi Oluwasola Felix

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Management information system (MIS) provides information for the managerial activities in an organization. The main purpose of this research is, MIS provides accurate and timely information necessary to facilitate the decision-making process and enable the organizations planning control and operational functions to be carried out effectively. Management information system (MIS) is basically concerned with processing data into information and is then communicated to the various departments in an organization for appropriate decision-making. MIS is a subset of the overall planning and control activities covering the application of humans technologies, and procedures of the organization. The information system is the mechanism to ensure that information is available to the managers in the form they want it and when they need it.

Keywords: Management Information Systems (MIS), information technology, decision-making, MIS in Organizations

Procedia PDF Downloads 557

Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Parisa Khoshvaght, Mehdi Hosseinzadeh

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During the past few years, the Residue Number System (RNS) has been receiving considerable interest due to its parallel and fault-tolerant properties. This system is a useful tool for Digital Signal Processing (DSP) since it can support parallel, carry-free, high-speed and low power arithmetic. One of the drawbacks of Residue Number System is the fractional numbers, that is, the corresponding circuit is very hard to realize in conventional CMOS technology. In this paper, we propose a method in which the numbers of transistors are significantly reduced. The related delay is extremely diminished, in the first glance we use this method to solve concerning problem of one decimal functional number some how this proposition can be extended to generalize the idea. Another advantage of this method is the independency on the kind of moduli.

Keywords: computer arithmetic, residue number system, number system, one-Hot, VLSI

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Authors: Simon Komesker, Achim Wagner, Martin Ruskowski

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In times of volatile markets with fluctuating demand and the uncertainty of global supply chains, flexible production systems are the key to an efficient implementation of a desired production program. In this publication, the authors present a holistic information concept taking into account various influencing factors for operating towards the global optimum. Therefore, a strategy for the implementation of multi-level planning for a flexible, reconfigurable production system with an alternative production concept in the automotive industry is developed. The main contribution of this work is a system structure mixing central and decentral planning and control evaluated in a simulation framework. The information system structure in current production systems in the automotive industry is rigidly hierarchically organized in monolithic systems. The production program is created rule-based with the premise of achieving uniform cycle time. This program then provides the information basis for execution in subsystems at the station and process execution level. In today's era of mixed-(car-)model factories, complex conditions and conflicts arise in achieving logistics, quality, and production goals. There is no provision for feedback loops of results from the process execution level (resources) and process supporting (quality and logistics) systems and reconsideration in the planning systems. To enable a robust production flow, the complexity of production system control is artificially reduced by the line structure and results, for example in material-intensive processes (buffers and safety stocks - two container principle also for different variants). The limited degrees of freedom of line production have produced the principle of progress figure control, which results in one-time sequencing, sequential order release, and relatively inflexible capacity control. As a result, modularly structured production systems such as modular production according to known approaches with more degrees of freedom are currently difficult to represent in terms of information technology. The remedy is an information concept that supports cross-system and cross-level information processing for centralized and decentralized decision-making. Through an architecture of hierarchically organized but decoupled subsystems, the paradigm of hybrid control is used, and a holonic manufacturing system is offered, which enables flexible information provisioning and processing support. In this way, the influences from quality, logistics, and production processes can be linked holistically with the advantages of mixed centralized and decentralized planning and control. Modular production systems also require modularly networked information systems with semi-autonomous optimization for a robust production flow. Dynamic prioritization of different key figures between subsystems should lead the production system to an overall optimum. The tasks and goals of quality, logistics, process, resource, and product areas in a cyber-physical production system are designed as an interconnected multi-agent-system. The result is an alternative system structure that executes centralized process planning and decentralized processing. An agent-based manufacturing control is used to enable different flexibility and reconfigurability states and manufacturing strategies in order to find optimal partial solutions of subsystems, that lead to a near global optimum for hybrid planning. This allows a robust near to plan execution with integrated quality control and intralogistics.

Keywords: holonic manufacturing system, modular production system, planning, and control, system structure

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Authors: M. Chumburidze, N. Salia, T. Namchevadze

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This work deal with case processing problems in business. The task of strategic credit requirements management of cases portfolio is discussed. The information model of credit requirements in a binary tree diagram is considered. The algorithms to solve issues of prioritizing clusters of cases in business have been investigated. An implementation of priority queues to support case management operations has been presented. The corresponding pseudo codes for the programming application have been constructed. The tools applied in this development are based on binary tree ordering algorithms, optimization theory, and business management methods.

Keywords: credit network, case portfolio, binary tree, priority queue, stack

Procedia PDF Downloads 150

Authors: Pan Hongxia, Wang Zhenhua

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In this paper, the EMD decomposition in the process of endpoint effect adopted data based on AR model to predict the continuation and window function method of combining the two effective inhibition. Proven by simulation of the simulation signal obtained the ideal effect, then, apply this method to the gearbox test data is also achieved good effect in the process, for the analysis of the subsequent data processing to improve the calculation accuracy. In the end, under various working conditions for the gearbox fault diagnosis laid a good foundation.

Keywords: gearbox, fault diagnosis, ar model, end effect

Procedia PDF Downloads 366

Authors: Dhananjay Singh, M. Abdullah-Al-Wadud

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The Internet of Things is a concept of a large scale ecosystem of wireless actuators. The actuators are defined as things in the IoT, those which contribute or produces some data to the ecosystem. However, ubiquitous data collection, data security, privacy preserving, large volume data processing, and intelligent analytics are some of the key challenges into the IoT technologies. In order to solve the security requirements, challenges and threats in the IoT, we have discussed a message authentication mechanism for IoT applications. Finally, we have discussed data encryption mechanism for messages authentication before propagating into IoT networks.

Keywords: Internet of Things (IoT), message authentication, privacy, security

Procedia PDF Downloads 382

Authors: Kira Rysakova, Vitaly Novikov

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An improved method of obtaining enzymatic collagen hydrolysate from the tissues of marine hydrobionts is proposed, which allows to obtain hydrolysate without pre-isolation of pure collagen. The method can be used to isolate enzymatic collagen hydrolysate from the waste of industrial processing of Red King crab and non-traditional objects - marine holothurias. Comparative analysis of collagen hydrolysates has shown the possibility of their use in a number of nutrient media, but this requires additional optimization of their composition and biological tests on wide sets of test strains of microorganisms.

Keywords: collagen hydrolysate, marine hydrobionts, red king crab, marine holothurias, enzymes, exclusive HPLC

Procedia PDF Downloads 170

Authors: Erekle Magradze, Davit Soselia, Levan Shughliashvili, Irakli Koberidze, Shota Tsiskaridze, Victor Kakhniashvili, Tamar Chaghiashvili

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Since the beginning of active publishing activity in Georgia, voluminous printed material has been accumulated, the digitization of which is an important task. Digitized materials will be available to the audience, and it will be possible to find text in them and conduct various factual research. Digitizing scanned documents means scanning documents, extracting text from the scanned documents, and processing the text into a corresponding language model to detect inaccuracies and grammatical errors. Implementing these stages requires a unified, scalable, and automated platform, where the digital service developed for each stage will perform the task assigned to it; at the same time, it will be possible to develop these services dynamically so that there is no interruption in the work of the platform.

Keywords: NLP, OCR, BERT, Kubernetes, transformers

Procedia PDF Downloads 145

Authors: C. C .D. Kulathilake, M. Jayatilake, T. Takahashi

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The myocardium is composed of specialized muscle which relies mainly on fatty acid and sugar metabolism and it is widely contribute to the heart functioning. The changes of the cardiac energy-producing system during heart failure have been proved using autoradiography techniques. This study focused on evaluating sugar and fatty acid metabolism in myocardium as cardiac energy getting system using heart-accumulated radiopharmaceuticals. Two sets of autoradiographs of heart cross sections of Lewis male rats were analyzed and the time- accumulation curve obtained with use of the MATLAB image processing software to evaluate fatty acid and sugar metabolic functions.

Keywords: autoradiographs, fatty acid, radiopharmaceuticals, sugar

Procedia PDF Downloads 451

Authors: Bekmurza H. Aitchanov, Sholpan K. Aitchanova, Olimzhon A. Baimuratov, Aitkul N. Aldibekova

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This work considers the automated control system (ACS) of milk quality during its magnetic field processing. For achieving high level of quality control methods were applied transformation of complex nonlinear systems in a linearized system with a less complex structure. Presented ACS is adjustable by seven parameters: mass fraction of fat, mass fraction of dry skim milk residues (DSMR), density, mass fraction of added water, temperature, mass fraction of protein, acidity.

Keywords: fluids magnetization, nuclear magnetic resonance, automated control system, dynamic pulse-frequency modulator, PFM, nonlinear systems, structural model

Procedia PDF Downloads 375

Authors: Pingping Lin, Xudong Luo

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Natural language often conveys emotions of speakers. Therefore, sentiment analysis on what people say is prevalent in the field of natural language process and has great application value in many practical problems. Thus, to help people understand its application value, in this paper, we survey various applications of sentiment analysis, including the ones in online business and offline business as well as other types of its applications. In particular, we give some application examples in intelligent customer service systems in China. Besides, we compare the applications of sentiment analysis on Twitter, Weibo, Taobao and Facebook, and discuss some challenges. Finally, we point out the challenges faced in the applications of sentiment analysis and the work that is worth being studied in the future.

Keywords: application, natural language processing, online comments, sentiment analysis

Procedia PDF Downloads 263

Authors: Balthazar Temu, Zhao Yan, Bogdan-Petrin Ratiu, Sang Soon Oh, Qiang Li

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Nanowire based Photonic Crystal Surface Emitting Lasers (PCSELs) reported in the literature have been designed using a triangular, square or honeycomb patterns. The triangular and square pattern PCSELs have limited degrees of freedom in tuning the design parameters which hinders the ability to design high quality factor (Q-factor) devices. Nanowire based PCSELs designed using triangular and square patterns have been reported with the lasing thresholds of 130 kW/〖cm〗^2 and 7 kW/〖cm〗^2 respectively. On the other hand the honeycomb pattern gives more degrees of freedom in tuning the design parameters, which can allow one to design high Q-factor devices. A deformed honeycomb pattern device was reported with lasing threshold of 6.25 W/〖cm〗^2 corresponding to a simulated Q-factor of 5.84X〖10〗^5.Despite this achievement, the design principles which can lead to realization of even higher Q-factor honeycomb pattern PCSELs have not yet been investigated. In this work we show that through deforming the honeycomb pattern and tuning the heigh and lattice constants of the nanowires, it is possible to achieve even higher Q-factor devices. Considering three different band edge modes, we investigate how the resonance wavelength changes as the device is deformed, which is useful in designing high Q-factor devices in different wavelength bands. We eventually establish the design and simulation of honeycomb PCSELs operating around the wavelength of 960nm , in the O and the C band with Q-factors up to 7X〖10〗^7. We also investigate the Q-factors of undeformed device, and establish that the mode at the band edge close to 960nm can attain highest Q-factor of all the modes when the device is undeformed and the Q-factor degrades as the device is deformed. This work is a stepping stone towards the fabrication of very high Q-factor, nanowire based honey comb PCSELs, which are expected to have very low lasing threshold.

Keywords: designing nanowire PCSEL, designing PCSEL on silicon substrates, low threshold nanowire laser, simulation of photonic crystal lasers

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Authors: Lucas Nascimento, Ana Rita, Margarida Soares, André Ribeiro, Zlatina Genisheva, Hugo Silva, Joana Carvalho

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The footwear industry is an essential fashion industry, focusing on producing various types of footwear, such as shoes, boots, sandals, sneakers, and slippers. Global footwear consumption has doubled every 20 years since the 1950s. It is estimated that in 1950, each person consumed one new pair of shoes yearly; by 2005, over 20 billion pairs of shoes were consumed. To meet global footwear demand, production reached $24.2 billion, equivalent to about $74 per person in the United States. This means three new pairs of shoes per person worldwide. The issue of footwear waste is related to the fact that shoe production can generate a large amount of waste, much of which is difficult to recycle or reuse. This waste includes scraps of leather, fabric, rubber, plastics, toxic chemicals, and other materials. The search for alternative solutions for waste treatment and valorization is increasingly relevant in the current context, mainly when focused on utilizing waste as a source of substitute materials. From the perspective of the new circular economy paradigm, this approach is of utmost importance as it aims to preserve natural resources and minimize the environmental impact associated with sending waste to landfills. In this sense, the incorporation of waste into industrial sectors that allow for the recovery of large volumes, such as road construction, becomes an urgent and necessary solution from an environmental standpoint. This study explores the use of plastic waste from the footwear industry as a substitute for virgin polymers in bitumen modification, a solution that presents a more sustainable future. Replacing conventional polymers with plastic waste in asphalt composition reduces the amount of waste sent to landfills and offers an opportunity to extend the lifespan of road infrastructures. By incorporating waste into construction materials, reducing the consumption of natural resources and the emission of pollutants is possible, promoting a more circular and efficient economy. In the initial phase of this study, waste materials from end-of-life footwear were selected, and plastic waste with the highest potential for application was separated. Based on a literature review, EVA (ethylene vinyl acetate) and PU (polyurethane) were identified as the polymers suitable for modifying 50/70 classification bitumen. Each polymer was analysed at concentrations of 3% and 5%. The production process involved the polymer's fragmentation to a size of 4 millimetres after heating the materials to 180 ºC and mixing for 10 minutes at low speed. After was mixed for 30 minutes in a high-speed mixer. The tests included penetration, softening point, viscosity, and rheological assessments. With the results obtained from the tests, the mixtures with EVA demonstrated better results than those with PU, as EVA had more resistance to temperature, a better viscosity curve and a greater elastic recovery in rheology.

Keywords: footwear waste, hot asphalt pavement, modified bitumen, polymers

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Authors: Jacob Wood, David Wilson, Stephen Hughes

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The Ausmelt Top Submerged Lance (TSL) Process has been widely applied for the processing of both primary and secondary copper, nickel, lead, tin, and zinc-bearing feed materials. Continual development and evolution of the technology over more than 30 years has resulted in a more intense smelting process with higher energy efficiency, improved metal recoveries, lower operating costs, and reduced fossil fuel consumption. This paper covers a number of recent advances to the technology, highlighting their positive impacts on smelter operating costs, environmental performance, and contribution towards increased circularity in metals production.

Keywords: ausmelt TSL, smelting, circular economy, energy efficiency

Procedia PDF Downloads 244

Authors: Chanchai Supaartagorn

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Structured Query Language (SQL) is the standard de facto language to access and manipulate data in a relational database. Although SQL is a language that is simple and powerful, most novice users will have trouble with SQL syntax. Thus, we are presenting SQL generator tool which is capable of translating actions and displaying SQL commands and data sets simultaneously. The tool was developed based on Model-View-Controller (MVC) pattern. The MVC pattern is a widely used software design pattern that enforces the separation between the input, processing, and output of an application. Developers take full advantage of it to reduce the complexity in architectural design and to increase flexibility and reuse of code. In addition, we use White-Box testing for the code verification in the Model module.

Keywords: MVC, relational database, SQL, White-Box testing

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Authors: Peter Pfeifer, Julian Pfeifer, Niko Pfeifer

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Information processing is the focus of brain and cognition research. This work has a different perspective; it starts with behaviors. The detailed analysis of behaviors leads to the discovery that a significant proportion of them are based on only five basic drives. These basic drives are combinable, and the combinations result in the diversity of human behavior and thinking. The key elements are drive memories. They collect memories of drive-related situations and feelings. They contain variations of basic drives in numerous areas of life and build combinations with different meanings depending on the area. Human thinking could be explained with variations on these nested combinations of basic drives.

Keywords: cognition, psycholinguistics, psychology, psychophysiology of cognition

Procedia PDF Downloads 161

Authors: Boris Barbolyas, Kristina Buckova, Tomas Volensky, Cyril Belavy, Ladislav Dedik

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Background: Based on statokinezigram, the human balance control is often studied. Approach to human postural reaction analysis is based on a combination of stabilometry output signal with retroreflective marker data signal processing, analysis, and understanding, in this study. The study shows another original application of Method of Developed Statokinesigram Trajectory (MDST), too. Methods: In this study, the participants maintained quiet bipedal standing for 10 s on stabilometry platform. Consequently, bilateral vibration stimuli to Achilles tendons in 20 s interval was applied. Vibration stimuli caused that human postural system took the new pseudo-steady state. Vibration frequencies were 20, 60 and 80 Hz. Participant's body segments - head, shoulders, hips, knees, ankles and little fingers were marked by 12 retroreflective markers. Markers positions were scanned by six cameras system BTS SMART DX. Registration of their postural reaction lasted 60 s. Sampling frequency was 100 Hz. For measured data processing were used Method of Developed Statokinesigram Trajectory. Regression analysis of developed statokinesigram trajectory (DST) data and retroreflective marker developed trajectory (DMT) data were used to find out which marker trajectories most correlate with stabilometry platform output signals. Scaling coefficients (λ) between DST and DMT by linear regression analysis were evaluated, too. Results: Scaling coefficients for marker trajectories were identified for all body segments. Head markers trajectories reached maximal value and ankle markers trajectories had a minimal value of scaling coefficient. Hips, knees and ankles markers were approximately symmetrical in the meaning of scaling coefficient. Notable differences of scaling coefficient were detected in head and shoulders markers trajectories which were not symmetrical. The model of postural system behavior was identified by MDST. Conclusion: Value of scaling factor identifies which body segment is predisposed to postural instability. Hypothetically, if statokinesigram represents overall human postural system response to vibration stimuli, then markers data represented particular postural responses. It can be assumed that cumulative sum of particular marker postural responses is equal to statokinesigram.

Keywords: center of pressure (CoP), method of developed statokinesigram trajectory (MDST), model of postural system behavior, retroreflective marker data

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Authors: Juan Pablo Botero Torres, Alba Avila, Luis Felipe Giraldo

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Independent navigation and mobility through unknown spaces pose a challenge for the autonomy of visually impaired people (VIP), who have relied on the use of traditional assistive tools like the white cane and trained dogs. However, emerging visually assistive technologies (VAT) have proposed several human-machine interfaces (HMIs) that could improve VIP’s ability for self-guidance. Hereby, we introduce the design and implementation of a visually assistive device, Anajaa – Visual Substitution System (AVSS). This system integrates ultrasonic sensors with custom electronics, and computer vision models (convolutional neural networks), in order to achieve a robust system that acquires information of the surrounding space and transmits it to the user in an intuitive and efficient manner. AVSS consists of two modules: the sensing and the actuation module, which are fitted to a chest mount and belt that communicate via Bluetooth. The sensing module was designed for the acquisition and processing of proximity signals provided by an array of ultrasonic sensors. The distribution of these within the chest mount allows an accurate representation of the surrounding space, discretized in three different levels of proximity, ranging from 0 to 6 meters. Additionally, this module is fitted with an RGB-D camera used to detect potentially threatening obstacles, like staircases, using a convolutional neural network specifically trained for this purpose. Posteriorly, the depth data is used to estimate the distance between the stairs and the user. The information gathered from this module is then sent to the actuation module that creates an HMI, by the means of a 3x2 array of vibration motors that make up the tactile display and allow the system to deliver haptic feedback. The actuation module uses vibrational messages (tactones); changing both in amplitude and frequency to deliver different awareness levels according to the proximity of the obstacle. This enables the system to deliver an intuitive interface. Both modules were tested under lab conditions, and the HMI was additionally tested with a focal group of VIP. The lab testing was conducted in order to establish the processing speed of the computer vision algorithms. This experimentation determined that the model can process 0.59 frames per second (FPS); this is considered as an adequate processing speed taking into account that the walking speed of VIP is 1.439 m/s. In order to test the HMI, we conducted a focal group composed of two females and two males between the ages of 35-65 years. The subject selection was aided by the Colombian Cooperative of Work and Services for the Sightless (COOTRASIN). We analyzed the learning process of the haptic messages throughout five experimentation sessions using two metrics: message discrimination and localization success. These correspond to the ability of the subjects to recognize different tactones and locate them within the tactile display. Both were calculated as the mean across all subjects. Results show that the focal group achieved message discrimination of 70% and a localization success of 80%, demonstrating how the proposed HMI leads to the appropriation and understanding of the feedback messages, enabling the user’s awareness of its surrounding space.

Keywords: computer vision on embedded systems, electronic trave aids, human-machine interface, haptic feedback, visual assistive technologies, vision substitution systems

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Authors: Liat Shamri-Zeevi, Neta Ram-Vlasov

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Today the world as a whole is attempting to cope with the COVID-19, which has affected all facets of personal and social life from country-wide confinement to maintaining social distance and taking protective measures to maintain hygiene. One of the populations faced with the most severe restrictions is seniors. Various studies have shown that creativity plays a crucial role in dealing with crisis events. Painting - regardless of media - allows for emotional and cognitive processing of these situations, and enables the expression of experiences in a tangible creative way that conveys and endows meaning to the artwork. The current study was conducted in Israel immediately after a 6-week lockdown. It was designed to specifically examine the impact of the COVID-19 pandemic on the quality of life of elderly women as reflected in their artworks. The sample was composed of 21 Israeli women aged 60-90, in good mental health (without diagnosed dementia or Alzheimer's), all of whom were Hebrew-speaking, and retired with an extended family, who indicated that they painted and had engaged in artwork on an ongoing basis throughout the lockdown (from March 12 to May 30, 2020). The participants' artworks were collected, and a semi-structured in-depth interview was conducted that lasted one to two hours. The participants were asked about their feelings during the pandemic and the artworks they produced during this time, and completed a questionnaire on well-being and mental health. The initial analysis of the interviews and artworks revealed themes related to the specific role of each piece of artwork. The first theme included notions that the artwork was an activity and a framework for doing, which supported positive emotions, and provided a sense of vitality during the closure. Most of the participants painted images of nature and growth which were ascribed concrete and symbolic meaning. The second theme was that the artwork enabled the processing of difficult and /or conflicting emotions related to the situation, including anxiety about death and loneliness that were symbolically expressed in the artworks, such as images of the Corona virus and the respiratory machines. The third theme suggested that the time and space prompted by the lockdown gave the participants time for a gathering together of the self, and freed up time for creative activities. Many participants stated that they painted more and more frequently during the Corona lockdown. At the conference, additional themes and findings will be presented.

Keywords: Corona virus, artwork, quality of life of elderly

Procedia PDF Downloads 143

Authors: Z. Abdollahnejad, P. Torgal, J. Barroso Aguiar

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Publications on the field of alkali-activated binders, state that this new material is likely to have high potential to become an alternative to Portland cement. Classical alkali-activated cements could be made more eco-efficient if the use of sodium silicate is avoided. Besides, most alkali-activated cements suffer from severe efflorescence originated by the fact that alkaline and/or soluble silicates that are added during processing cannot be totally consumed. This paper presents experimental results on hybrid alkaline cements. Compressive strength results and efflorescence’s observations show that the new mixes already analyzed are promising. SEM results show that no traditional porous ITZ was detected in these binders.

Keywords: hybrid alkaline cements, compressive strength, efflorescence, SEM, ITZ

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Authors: Priya Saha, Sourav Dey Roy Jr., Debotosh Bhattacharjee, Mita Nasipuri, Barin Kumar De, Mrinal Kanti Bhowmik

Abstract:

Biometric face recognition technology (FRT) has gained a lot of attention due to its extensive variety of applications in both security and non-security perspectives. It has come into view to provide a secure solution in identification and verification of person identity. Although other biometric based methods like fingerprint scans, iris scans are available, FRT is verified as an efficient technology for its user-friendliness and contact freeness. Accurate facial feature localization plays an important role for many facial analysis applications including biometrics and emotion recognition. But, there are certain factors, which make facial feature localization a challenging task. On human face, expressions can be seen from the subtle movements of facial muscles and influenced by internal emotional states. These non-rigid facial movements cause noticeable alterations in locations of facial landmarks, their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper proposes a new hybrid based technique for automatic landmark detection in both neutral and expressive frontal and near frontal face images. The method uses the concept of thresholding, sequential searching and other image processing techniques for locating the landmark points on the face. Also, a Graphical User Interface (GUI) based software is designed that could automatically detect 16 landmark points around eyes, nose and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Cohn Kanade database. Also, the system is tested on DeitY-TU face database which is created in the Biometrics Laboratory of Tripura University under the research project funded by Department of Electronics & Information Technology, Govt. of India. The performance of the proposed method has been done in terms of error measure and accuracy. The method has detection rate of 98.82% on JAFFE database, 91.27% on Cohn Kanade database and 93.05% on DeitY-TU database. Also, we have done comparative study of our proposed method with other techniques developed by other researchers. This paper will put into focus emotion-oriented systems through AU detection in future based on the located features.

Keywords: biometrics, face recognition, facial landmarks, image processing

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Authors: Sriraman Kothuri, Komal Teja Mattupalli

Abstract:

In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

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Authors: Zan Azma Nasruddin, Irwan Mazlin, Nor Aziah Daud, Fauziah Redzuan, Fariza Hanis Abdul Razak

Abstract:

This paper focuses on a machine learning that learn the correct pronunciation of Makhraj Huroofs. Usually, people need to find an expert to pronounce the Huroof accurately. In this study, the researchers have developed a system that is able to learn the selected Huroofs which are ha, tsa, zho, and dza using the Convolutional Neural Network. The researchers present the chosen type of the CNN architecture to make the system that is able to learn the data (Huroofs) as quick as possible and produces high accuracy during the prediction. The researchers have experimented the system to measure the accuracy and the cross entropy in the training process.

Keywords: convolutional neural network, Makhraj recognition, speech recognition, signal processing, tensorflow

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Authors: F. Viprey, H. Nouira, S. Lavernhe, C. Tournier

Abstract:

Manufacturing of freeform parts may be achieved on 5-axis machine tools currently considered as a common means of production. In particular, the geometrical quality of the freeform parts depends on the accuracy of the multi-axis structural loop, which is composed of several component assemblies maintaining the relative positioning between the tool and the workpiece. Therefore, to reach high quality of the geometries of the freeform parts the geometric errors of the 5 axis machine should be evaluated and compensated, which leads one to master the deviations between the tool and the workpiece (volumetric accuracy). In this study, a novel hole-bar design was developed and used for the characterization of the geometric errors of a RRTTT 5-axis machine tool. The hole-bar standard design is made of Invar material, selected since it is less sensitive to thermal drift. The proposed design allows once to extract 3 intrinsic parameters: one linear positioning and two straightnesses. These parameters can be obtained by measuring the cylindricity of 12 holes (bores) and 11 cylinders located on a perpendicular plane. By mathematical analysis, twelve 3D points coordinates can be identified and correspond to the intersection of each hole axis with the least square plane passing through two perpendicular neighbour cylinders axes. The hole-bar was calibrated using a precision CMM at LNE traceable the SI meter definition. The reversal technique was applied in order to separate the error forms of the hole bar from the motion errors of the mechanical guiding systems. An inter-comparison was additionally conducted between four NMIs (National Metrology Institutes) within the EMRP IND62: JRP-TIM project. Afterwards, the hole-bar was integrated in RRTTT 5-axis machine tool to identify its volumetric errors. Measurements were carried out in real time and combine raw data acquired by the Renishaw RMP600 touch probe and the linear and rotary encoders. The geometric errors of the 5 axis machine were also evaluated by an accurate laser tracer interferometer system. The results were compared to those obtained with the hole bar.

Keywords: volumetric errors, CMM, 3D hole-bar, inter-comparison

Procedia PDF Downloads 384