Search results for: image processing

Authors: Danilo Habermann, Aleksander Medella, Carla Cremon, Yusef Caceres

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This paper aims to analyze the ability of 2d point clouds features to classify different models of helicopters using radars. This method does not need to estimate the blade length, the number of blades of helicopters, and the period of their micro-Doppler signatures. It is also not necessary to generate spectrograms (or any other image based on time and frequency domain). This work transforms a radar return signal into a 2D point cloud and extracts features of it. Three classifiers are used to distinguish 9 different helicopter models in order to analyze the performance of the features used in this work. The high accuracy obtained with each of the classifiers demonstrates that the 2D point clouds features are very useful for classifying helicopters from radar signal.

Keywords: helicopter classification, point clouds features, radar, supervised classifiers

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Authors: Alexander Buhr, Klaus Ehrenfried

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Trackside induced airflow velocities, also known as slipstream velocities, are an important criterion for the design of high-speed trains. The maximum permitted values are given by the Technical Specifications for Interoperability (TSI) and have to be checked in the approval process. For train manufactures it is of great interest to know in advance, how new train geometries would perform in TSI tests. The Reynolds number in moving model experiments is lower compared to full-scale. Especially the limited model length leads to a thinner boundary layer at the rear end. The hypothesis is that the boundary layer rolls up to characteristic flow structures in the train wake, in which the maximum flow velocities can be observed. The idea is to enlarge the boundary layer using roughness elements at the train model head so that the ratio between the boundary layer thickness and the car width at the rear end is comparable to a full-scale train. This may lead to similar flow structures in the wake and better prediction accuracy for TSI tests. In this case, the design of the roughness elements is limited by the moving model rig. Small rectangular roughness shapes are used to get a sufficient effect on the boundary layer, while the elements are robust enough to withstand the high accelerating and decelerating forces during the test runs. For this investigation, High-Speed Particle Image Velocimetry (HS-PIV) measurements on an ICE3 train model have been realized in the moving model rig of the DLR in Göttingen, the so called tunnel simulation facility Göttingen (TSG). The flow velocities within the boundary layer are analysed in a plain parallel to the ground. The height of the plane corresponds to a test position in the EN standard (TSI). Three different shapes of roughness elements are tested. The boundary layer thickness and displacement thickness as well as the momentum thickness and the form factor are calculated along the train model. Conditional sampling is used to analyse the size and dynamics of the flow structures at the time of maximum velocity in the train wake behind the train. As expected, larger roughness elements increase the boundary layer thickness and lead to larger flow velocities in the boundary layer and in the wake flow structures. The boundary layer thickness, displacement thickness and momentum thickness are increased by using larger roughness especially when applied in the height close to the measuring plane. The roughness elements also cause high fluctuations in the form factors of the boundary layer. Behind the roughness elements, the form factors rapidly are approaching toward constant values. This indicates that the boundary layer, while growing slowly along the second half of the train model, has reached a state of equilibrium.

Keywords: boundary layer, high-speed PIV, ICE3, moving train model, roughness elements

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Authors: Mohammad Reza Dawoudi

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With the increasing rate of patients suffering from chronic pain, several methods for evaluating of chronic pain are suggested. Motion of morbid has been defined as the rate of pine and it is linked with various co-morbid conditions. This study provides a summary of procedure useful to statistics performing direct behavioral observation in hospital settings. We describe the need for and usefulness of comprehensive “morbid motions” observations; provide a primer on the identification, definition, and assessment of morbid behaviors; and outline and discuss specific statistical procedures, including formulating referral motions, describing and conducting the observation. We also provide practical devices for observing and analyzing the obtained information into a report that guides clinical intervention.

Keywords: assessing pain, DNA modeling, image matching technique, pain scale

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

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Authors: Justyna Humięcka-Jakubowska

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1. Background in music analysis. Traditionally, when we think about a composer’s sketches, the chances are that we are thinking in terms of the working out of detail, rather than the evolution of an overall concept. Since music is a “time art’, it follows that questions of a form cannot be entirely detached from considerations of time. One could say that composers tend to regard time either as a place gradually and partially intuitively filled, or they can look for a specific strategy to occupy it. In my opinion, one thing that sheds light on Stockhausen's compositional thinking is his frequent use of 'form schemas', that is often a single-page representation of the entire structure of a piece. 2. Background in music technology. Sonic Visualiser is a program used to study a musical recording. It is an open source application for viewing, analysing, and annotating music audio files. It contains a number of visualisation tools, which are designed with useful default parameters for musical analysis. Additionally, the Vamp plugin format of SV supports to provide analysis such as for example structural segmentation. 3. Aims. The aim of my paper is to show how SV may be used to obtain a better understanding of the specific musical work, and how the compositional strategy does impact on musical structures and musical surfaces. I want to show that ‘traditional” music analytic methods don’t allow to indicate interrelationships between musical surface (which is perceived) and underlying musical/acoustical structure. 4. Main Contribution. Stockhausen had dealt with the most diverse musical problems by the most varied methods. A characteristic which he had never ceased to be placed at the center of his thought and works, it was the quest for a new balance founded upon an acute connection between speculation and intuition. In the case with Mikrophonie I (1964) for tam-tam and 6 players Stockhausen makes a distinction between the "connection scheme", which indicates the ground rules underlying all versions, and the form scheme, which is associated with a particular version. The preface to the published score includes both the connection scheme, and a single instance of a "form scheme", which is what one can hear on the CD recording. In the current study, the insight into the compositional strategy chosen by Stockhausen was been compared with auditory image, that is, with the perceived musical surface. Stockhausen's musical work is analyzed both in terms of melodic/voice and timbre evolution. 5. Implications The current study shows how musical structures have determined of musical surface. My general assumption is this, that while listening to music we can extract basic kinds of musical information from musical surfaces. It is shown that an interactive strategies of musical structure analysis can offer a very fruitful way of looking directly into certain structural features of music.

Keywords: automated analysis, composer's strategy, mikrophonie I, musical surface, stockhausen

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Authors: Bogale Tadesse, Krutik Parikh, Ndagha Mkandawire, Boris Albijanic, Nimal Subasinghe

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It is well established that the floatability and selectivity of mineral particles are highly dependent on the particle size. Generally, a particle size of 10 micron is considered as the critical size below which both flotation selectivity and recovery decline sharply. It is widely accepted that the majority of ultrafine particles, including highly liberated valuable minerals, will be lost in tailings during a conventional flotation process. This is highly undesirable particularly in the processing of finely disseminated complex and refractory ores where there is a requirement for fine grinding in order to liberate the valuable minerals. In addition, the continuing decline in ore grade worldwide necessitates intensive processing of low grade mineral deposits. Recent advances in comminution allow the economic grinding of particles down to 10 micron sizes to enhance the probability of liberating locked minerals from low grade ores. Thus, it is timely that the flotation of fine and ultrafine particles is improved in order to reduce the amount of valuable minerals lost as slimes. It is believed that the use of fine bubbles in flotation increases the bubble-particle collision efficiency and hence the flotation performance. Electroflotation, where bubbles are generated by the electrolytic breakdown of water to produce oxygen and hydrogen gases, leads to the formation of extremely finely dispersed gas bubbles with dimensions varying from 5 to 95 micron. The sizes of bubbles generated by this method are significantly smaller than those found in conventional flotation (> 600 micron). In this study, microbubbles generated by electrolysis of water were injected into a bench top flotation cell to assess the performance electroflotation in enhancing the flotation of fine and ultrafine pyrite particles of sizes ranging from 5 to 53 micron. The design of the cell and the results from optimization of the process variables such as current density, pH, percent solid and particle size will be presented at this conference.

Keywords: electroflotation, fine bubbles, pyrite, ultrafine particles

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Authors: Susana Marques

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Research on how store environment cues influence consumers’ store choice decision criteria, such as store operations, product quality, monetary price, store image and sales promotion, is sparse. Especially absent research on the simultaneous impact of multiple store environment cues. The authors propose a comprehensive store choice model that includes: three types of store environment cues as exogenous constructs; various store choice criteria as possible mediating constructs, and store patronage intentions as an endogenous construct. On the basis of testing with a sample of 561 customers of hypermarkets, the model is partially supported. This study used structural equation modelling to test the proposed model.

Keywords: store choice, store patronage, structural equation modelling, retailing

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Authors: Zeina Merabi, Arij Dao

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The temporal order of information processing in the brain is an important code in many acoustic signals, including speech, music, and animal vocalizations. Despite its significance, surprisingly little is known about its underlying cellular mechanisms and network manifestations. In the songbird telencephalic nucleus HVC, a subset of neurons shows temporal combination sensitivity (TCS). These neurons show a high temporal specificity, responding differently to distinct patterns of spectral elements and their combinations. HVC neuron types include basal-ganglia-projecting HVCX, forebrain-projecting HVCRA, and interneurons (HVC¬INT), each exhibiting distinct cellular, electrophysiological and functional properties. In this work, we develop conductance-based neural network models connecting the different classes of HVC neurons via different wiring scenarios, aiming to explore possible neural mechanisms that orchestrate the combination sensitivity property exhibited by HVCX, as well as replicating in vivo firing patterns observed when TCS neurons are presented with various auditory stimuli. The ionic and synaptic currents for each class of neurons that are presented in our networks and are based on pharmacological studies, rendering our networks biologically plausible. We present for the first time several realistic scenarios in which the different types of HVC neurons can interact to produce this behavior. The different networks highlight neural mechanisms that could potentially help to explain some aspects of combination sensitivity, including 1) interplay between inhibitory interneurons’ activity and the post inhibitory firing of the HVCX neurons enabled by T-type Ca2+ and H currents, 2) temporal summation of synaptic inputs at the TCS site of opposing signals that are time-and frequency- dependent, and 3) reciprocal inhibitory and excitatory loops as a potent mechanism to encode information over many milliseconds. The result is a plausible network model characterizing auditory processing in HVC. Our next step is to test the predictions of the model.

Keywords: combination sensitivity, songbirds, neural networks, spatiotemporal integration

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Authors: Shahriar Ghammamy, Mehrnoosh Saboony

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Purpose: To evaluate the spectral specification (IR-XRD and SEM) of nano-ciprofloxacin that prepared by up-down method (satellite mill). Methods: the ciprofloxacin was minimized to nano-scale with satellite mill and its characterization evaluated by Infrared spectroscopy, XRD diffraction and semi electron microscope (SEM). Expectation enhances the antibacterial property of nano-ciprofloxacin in comparison to ciprofloxacin. IR spectrum of nano-ciprofloxacin compared with spectrum of ciprofloxacin, and both of them were almost agreement with a difference: the peaks in spectrum of nano-ciprofloxacin were sharper than peaks in spectrum of ciprofloxacin. X-Ray powder diffraction analysis of nano-ciprofloxacin shows the diameter of particles equal to 90.9nm. (on the basis of Scherer Equation). SEM image shows the global shape for nano-ciprofloxacin.

Keywords: antibiotic, ciprofloxacin, nano, IR, XRD, SEM

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Authors: Shahriar Ghammamy, Mehrnoosh Saboony

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Purpose: to evaluate the spectral specification(IR-XRD and SEM) of nano ciprofloxacin that prepared by up-down method (satellite mill). Methods: the ciprofloxacin was minimized to nano-scale with satellite mill and it,s characterization evaluated by Infrared spectroscopy, XRD diffraction and semi electron microscope (SEM). Expectation: to enhance the antibacterial property of nano ciprofloxacin in comparison to ciprofloxacin.IR spectrum of nano ciprofloxacin compared with spectrum of ciprofloxacin, and both of them were almost agreement with a difference: the peaks in spectrum of nano ciprofloxacin was sharper than peaks in spectrum of ciprofloxacin. X-Ray powder diffraction analysis of nano ciprofloxacin showes the diameter of particles equal to 90.9 nm (on the basis of scherrer equation). SEM image showes the global shape for nano ciprofloxacin.

Keywords: antibiotic, ciprofloxacin, nano, IR, XRD, SEM

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Authors: C. Bay, A. Mahr, H. Groneberg, F. Döpper

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Additive Manufacturing processes are becoming increasingly established in the industry for the economic production of complex prototypes and functional components. Laser beam melting (LBM), the most frequently used Additive Manufacturing technology for metal parts, has been gaining in industrial importance for several years. The LBM process chain – from material storage to machine set-up and component post-processing – requires many manual operations. These steps often depend on the manufactured component and are therefore not standardized. These operations are often not performed in a standardized manner, but depend on the experience of the machine operator, e.g., levelling of the build plate and adjusting the first powder layer in the LBM machine. This lack of standardization limits the reproducibility of the component quality. When processing metal powders with inhalable and alveolar particle fractions, the machine operator is at high risk due to the high reactivity and the toxic (e.g., carcinogenic) effect of the various metal powders. Faulty execution of the operation or unintentional omission of safety-relevant steps can impair the health of the machine operator. In this paper, all the steps of the LBM process chain are first analysed in terms of their influence on the two aforementioned challenges: reproducibility and work safety. Standardization to avoid errors increases the reproducibility of component quality as well as the adherence to and correct execution of safety-relevant operations. The corresponding lean method 5S will therefore be applied, in order to develop approaches in the form of recommended actions that standardize the work processes. These approaches will then be evaluated in terms of ease of implementation and their potential for improving reproducibility and work safety. The analysis and evaluation showed that sorting tools and spare parts as well as standardizing the workflow are likely to increase reproducibility. Organizing the operational steps and production environment decreases the hazards of material handling and consequently improves work safety.

Keywords: additive manufacturing, lean production, reproducibility, work safety

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Authors: Nouara Boulfoul, Fatima Brabez

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This article presents the status of ISO 9001: 2000 certification in some agro-food companies in Algeria. The article discusses challenges and contributions of certification as perceived by quality managers as well as the difficulties encountered during certification. It also provides the recommendations of these managers for companies that have a certification project. The results show that the top three reasons for adopting ISO 9001: 2000 certification are building a better organization, reducing the costs of non-compliance and meeting customer expectations. The contributions are of an external nature (recognition, brand image, extension of markets, etc.) but also of an internal nature (improvement of the organization, etc.). The recommendations mainly concern management motivation, staff awareness and involvement and compliance with the requirements of the standard.

Keywords: quality management, certification, ISO 9001: 2000, food companies

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Authors: Sara Khan Mohammadi

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The world is facing a major challenge of feeding a growing population while ensuring the sustainability of food systems. The United Nations estimates that the global population will reach 9.7 billion by 2050, which means that food production needs to increase by 70% to meet the demand. However, this increase in food production should not come at the cost of environmental degradation, loss of biodiversity, and climate change. Therefore, there is a need for sustainable food systems that can provide healthy and nutritious food while minimizing their impact on the environment. Nutrition and Food Engineering: Nutrition and food engineering play a crucial role in promoting sustainable food system. Nutrition is concerned with the study of nutrients in foods, their absorption, metabolism, and their effects on health. Food engineering involves the application of engineering principles to design, develop, and optimize food processing operations. Together, nutrition and food engineering can help to create sustainable food systems by: 1. Developing Nutritious Foods: Nutritionists and food engineers can work together to develop foods that are rich in nutrients such as vitamins, minerals, fiber, and protein. These foods can be designed to meet the nutritional needs of different populations while minimizing waste. 2. Reducing Food Waste: Food waste is a major problem globally as it contributes to greenhouse gas emissions and wastes resources such as water and land. Nutritionists and food engineers can work together to develop technologies that reduce waste during processing, storage, transportation, and consumption. 3. Improving Food Safety: Unsafe foods can cause illnesses such as diarrhea, cholera, typhoid fever among others which are major public health concerns globally. Nutritionists and food engineers can work together to develop technologies that improve the safety of foods from farm to fork. 4. Enhancing Sustainability: Sustainable agriculture practices such as conservation agriculture can help reduce soil erosion while improving soil fertility. Nutritionists and food engineers can work together to develop technologies that promote sustainable agriculture practices.

Keywords: sustainable food, developing food, reducing food waste, food safety

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Authors: M. Sarraf, J. E. Moros, M. C. Sánchez

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Oleogels are self-standing systems that are able to trap edible liquid oil into a tridimensional network and also help to use less fat by forming crystallization oleogelators. There are different ways to generate oleogelation and oil structuring, including direct dispersion, structured biphasic systems, oil sorption, and indirect method (emulsion-template). The selection of processing conditions as well as the composition of the oleogels is essential to obtain a stable oleogel with characteristics suitable for its purpose. In this sense, one of the ingredients widely used in food products to produce oleogels and emulsions is polysaccharides. Basil seed gum (BSG), with the scientific name Ocimum basilicum, is a new native polysaccharide with high viscosity and pseudoplastic behavior because of its high molecular weight in the food industry. Also, proteins can stabilize oil in water due to the presence of amino and carboxyl moieties that result in surface activity. Whey proteins are widely used in the food industry due to available, cheap ingredients, nutritional and functional characteristics such as emulsifier and a gelling agent, thickening, and water-binding capacity. In general, the interaction of protein and polysaccharides has a significant effect on the food structures and their stability, like the texture of dairy products, by controlling the interactions in macromolecular systems. Using edible oleogels as oil structuring helps for targeted delivery of a component trapped in a structural network. Therefore, the development of efficient oleogel is essential in the food industry. A complete understanding of the important points, such as the ratio oil phase, processing conditions, and concentrations of biopolymers that affect the formation and stability of the emulsion, can result in crucial information in the production of a suitable oleogel. In this research, the effects of oil concentration and pressure used in the manufacture of the emulsion prior to obtaining the oleogel have been evaluated through the analysis of droplet size and rheological properties of obtained emulsions and oleogels. The results show that the emulsion prepared in the high-pressure homogenizer (HPH) at higher pressure values has smaller droplet sizes and a higher uniformity in the size distribution curve. On the other hand, in relation to the rheological characteristics of the emulsions and oleogels obtained, the predominantly elastic character of the systems must be noted, as they present values of the storage modulus higher than those of losses, also showing an important plateau zone, typical of structured systems. In the same way, if steady-state viscous flow tests have been analyzed on both emulsions and oleogels, the result is that, once again, the pressure used in the homogenizer is an important factor for obtaining emulsions with adequate droplet size and the subsequent oleogel. Thus, various routes for trapping oil inside a biopolymer matrix with adjustable mechanical properties could be applied for the creation of the three-dimensional network in order to the oil absorption and creating oleogel.

Keywords: basil seed gum, particle size, viscoelastic properties, whey protein

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Authors: R. Sekula

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Epoxy composites are broadly used as an electrical insulation for the high voltage applications since only such materials can fulfill particular mechanical, thermal, and dielectric requirements. However, properties of the final product are strongly dependent on proper manufacturing process with minimized material failures, as too large shrinkage, voids and cracks. Therefore, application of proper materials (epoxy, hardener, and filler) and process parameters (mold temperature, filling time, filling velocity, initial temperature of internal parts, gelation time), as well as design and geometric parameters are essential features for final quality of the produced components. In this paper, an approach for three-dimensional modeling of all molding stages, namely filling, curing and post-curing is presented. The reactive molding simulation tool is based on a commercial CFD package, and include dedicated models describing viscosity and reaction kinetics that have been successfully implemented to simulate the reactive nature of the system with exothermic effect. Also a dedicated simulation procedure for stress and shrinkage calculations, as well as simulation results are presented in the paper. Second part of the paper is dedicated to recent developments on formulations of functional composites for electrical insulation applications, focusing on thermally conductive materials. Concepts based on filler modifications for epoxy electrical composites have been presented, including the results of the obtained properties. Finally, having in mind tough environmental regulations, in addition to current process and design aspects, an approach for product re-design has been presented focusing on replacement of epoxy material with the thermoplastic one. Such “design-for-recycling” method is one of new directions associated with development of new material and processing concepts of electrical products and brings a lot of additional research challenges. For that, one of the successful products has been presented to illustrate the presented methodology.

Keywords: curing, epoxy insulation, numerical simulations, recycling

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Authors: Yohana Fessehazion

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Mercury is a prominent example of a heavy metal contaminant in the environment, and it has been extensively investigated for its potential health risk in humans and other organisms. In South Africa, massive mercury contamination happened in1980s when the England-based mercury reclamation processing plant relocated to Cato Ridge, KwaZulu-Natal Province, and discharged mercury waste into the Mngceweni River. This mercury waste discharge resulted in high mercury concentration that exceeded the acceptable levels in Mngceweni River, Umgeni River, and human hair of the nearby villagers. This environmental issue raised the alarm, and over the years, several environmental assessments were reported the dire environmental crises resulting from the Thor Chemicals (now known as Metallica Chemicals) and urged the immediate removal of the around 3,000 tons of mercury waste stored in the factory storage facility over two decades. Recently theft of some containers with the toxic substance from the Thor Chemicals warehouse and the subsequent fire that ravaged the facility furtherly put the factory on the spot escalating the urgency of left behind deadly mercury waste removal. This project aims to investigate the mercury contamination leaking from an old Thor Chemicals mercury processing plant. The focus will be on sediments, water, terrestrial plants, and aquatic weeds such as the prominent water hyacinth weeds in the nearby water systems of Mngceweni River, Umgeni River, and Inanda Dam as a bio-indicator and phytoremediator for mercury pollution. Samples will be collected in spring around October when the condition is favourable for microbial activity to methylate mercury incorporated in sediments and blooming season for some aquatic weeds, particularly water hyacinth. Samples of soil, sediment, water, terrestrial plant, and aquatic weed will be collected per sample site from the point of source (Thor Chemicals), Mngceweni River, Umgeni River, and the Inanda Dam. One-way analysis of variance (ANOVA) tests will be conducted to determine any significant differences in the Hg concentration among all sampling sites, followed by Least Significant Difference post hoc test to determine if mercury contamination varies with the gradient distance from the source point of pollution. The flow injection atomic spectrometry (FIAS) analysis will also be used to compare the mercury sequestration between the different plant tissues (roots and stems). The principal component analysis is also envisaged for use to determine the relationship between the source of mercury pollution and any of the sampling points (Umgeni and Mngceweni Rivers and the Inanda Dam). All the Hg values will be expressed in µg/L or µg/g in order to compare the result with the previous studies and regulatory standards. Sediments are expected to have relatively higher levels of Hg compared to the soils, and aquatic macrophytes, water hyacinth weeds are expected to accumulate a higher concentration of mercury than terrestrial plants and crops.

Keywords: mercury, phytoremediation, Thor chemicals, water hyacinth

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Authors: K. S. Parlak, E. Turan

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The separation of marbles according to the pattern quality is a process made according to expert decision. The classification phase is the most critical part in terms of economic value. In this study, a self-learning system is proposed which performs the classification of marbles quickly and with high success. This system performs ten feature extraction by taking ten marble images from the camera. The marbles are classified by decision tree method using the obtained properties. The user forms the training set by training the system at the marble classification stage. The system evolves itself in every marble image that is classified. The aim of the proposed system is to minimize the error caused by the person performing the classification and achieve it quickly.

Keywords: decision tree, feature extraction, k-means clustering, marble classification

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Authors: Diane Ghanem, Arjun Gupta, Rohan Vijayan, Ali Uneri, Babar Shafiq

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Introduction: Ankle sprains and fractures often result in syndesmosis injuries. Unstable syndesmotic injuries result from relative motion between the distal ends of the tibia and fibula, anatomic juncture which should otherwise be rigid, and warrant operative management. Clinical and radiological evaluations of intraoperative syndesmosis stability remain a challenging task as traditional 2D fluoroscopy is limited to a uniplanar translational displacement. The purpose of this pilot cadaveric study is to compare the 2D fluoroscopy and 3D cone beam computed tomography (CBCT) stress-induced syndesmosis displacements. Methods: Three fresh-frozen lower legs underwent 2D fluoroscopy and 3D CIOS CBCT to measure syndesmosis position before dissection. Syndesmotic injury was simulated by resecting the (1) anterior inferior tibiofibular ligament (AITFL), the (2) posterior inferior tibiofibular ligament (PITFL) and the inferior transverse ligament (ITL) simultaneously, followed by the (3) interosseous membrane (IOM). Manual external rotation and Cotton stress test were performed after each of the three resections and 2D and 3D images were acquired. Relevant 2D and 3D parameters included the tibiofibular overlap (TFO), tibiofibular clear space (TCS), relative rotation of the fibula, and anterior-posterior (AP) and medial-lateral (ML) translations of the fibula relative to the tibia. Parameters were measured by two independent observers. Inter-rater reliability was assessed by intraclass correlation coefficient (ICC) to determine measurement precision. Results: Significant mismatches were found in the trends between the 2D and 3D measurements when assessing for TFO, TCS and AP translation across the different resection states. Using 3D CBCT, TFO was inversely proportional to the number of resected ligaments while TCS was directly proportional to the latter across all cadavers and ‘resection + stress’ states. Using 2D fluoroscopy, this trend was not respected under the Cotton stress test. 3D AP translation did not show a reliable trend whereas 2D AP translation of the fibula was positive under the Cotton stress test and negative under the external rotation. 3D relative rotation of the fibula, assessed using the Tang et al. ratio method and Beisemann et al. angular method, suggested slight overall internal rotation with complete resection of the ligaments, with a change < 2mm - threshold which corresponds to the commonly used buffer to account for physiologic laxity as per clinical judgment of the surgeon. Excellent agreement (>0.90) was found between the two independent observers for each of the parameters in both 2D and 3D (overall ICC 0.9968, 95% CI 0.995 - 0.999). Conclusions: The 3D CIOS CBCT appears to reliably depict the trend in TFO and TCS. This might be due to the additional detection of relevant rotational malpositions of the fibula in comparison to the standard 2D fluoroscopy which is limited to a single plane translation. A better understanding of 3D imaging may help surgeons identify the precise measurements planes needed to achieve better syndesmosis repair.

Keywords: 2D fluoroscopy, 3D computed tomography, image processing, syndesmosis injury

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Authors: B. Baran, S. N. Kaptanoglu, M. Ocal, Y. Kagnici, E. Esen, E. Siyez, D. M. Siyez

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Infertility is the fact that couples cannot have children despite 1 year of unprotected sexual life. Infertility can be considered as an important problem affecting not only sexual life but also social and psychological conditions of couples. Learning about information about preventable factors related to infertility during university years plays an important role in preventing a possible infertility case in older ages. The possibility to facilitate access to information with the internet has provided the opportunity to reach a broad audience in the diverse learning environments and educational environment. Moreover, the internet has become a basic resource for the 21st-century learners. Providing information about infertility over the internet will enable more people to reach in a short time. When studies conducted abroad about infertility are examined, interactive websites and online education programs come to the fore. In Turkey, while there is no comprehensive online education program for university students, it seems that existing studies are aimed to make more advertisements for doctors or hospitals. In this study, it was aimed to design and develop online infertility prevention education for university students. Mayer’s Multimedia Learning Theory made up the framework for the online learning environment in this study. The results of the needs analysis collected from the university students in Turkey who were selected with sampling to represent the audience for online learning contributed to the design phase. In this study, an infertility prevention online education environment designed as a 4-week education was developed by explaining the theoretical basis and needs analysis results. As a result; in the development of the online environment, different kind of visual aids that will increase teaching were used in the environment of online education according to Mayer’s principles of extraneous processing (coherence, signaling, spatial contiguity, temporal contiguity, redundancy, expectation principles), essential processing (segmenting, pre-training, modality principles) and generative processing (multimedia, personalization, voice principles). For example, the important points in reproductive systems’ expression were emphasized by visuals in order to draw learners’ attention, and the presentation of the information was also supported by the human voice. In addition, because of the limited knowledge of university students in the subject, the issue of female reproductive and male reproductive systems was taught before preventable factors related to infertility. Furthermore, 3D video and augmented reality application were developed in order to embody female and male reproductive systems. In conclusion, this study aims to develop an interactive Online Infertility Prevention Education in which university students can easily access reliable information and evaluate their own level of knowledge about the subject. It is believed that the study will also guide the researchers who want to develop online education in this area as it contains design-stage decisions of interactive online infertility prevention education for university students.

Keywords: infertility, multimedia learning theory, online education, reproductive health

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Authors: Lin Cheng, Zijiang Yang

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Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.

Keywords: program synthesis, flow chart, specification, graph recognition, CNN

Procedia PDF Downloads 119

Authors: Osakwe Jude Odiakaosa

Abstract:

Today’s digital society is characterized by e-education or e-learning, e-commerce, and so on. All these have been propelled by digital revolution. Digital technology such as computer technology, Global Positioning System (GPS) and Geographic Information System (GIS) has been having a tremendous impact on the field of technology. This development has positively affected the scope, methods, speed of data acquisition, data management and the rate of delivery of the results (map and other map products) of data processing. This paper tries to address the impact of revolution brought by digital technology.

Keywords: digital revolution, internet, technology, data management

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Authors: Iva Buchberger, Vesna Kovač

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Global education policy trends and recommendations underline the importance of (distributive) school leadership as a school effectiveness key factor. In this context, the broader aim of this research (supported by the Croatian Science Foundation) is to identify school leadership characteristics in Croatian schools and to examine the correlation between school leadership and school effectiveness. The aim of the proposed conference paper is to focus on the school leadership characteristics which are additionally explained with school leadership facilitators that contribute to (distributive) school leadership development. The aforementioned school leadership characteristics include the following dimensions: (a) participation in the process of making different types of decisions, (b) influence in the decision making process, (c) social interactions between different stakeholders in the decision making process in schools. Further, the school leadership facilitators are categorized as follows: (a) principal’s activities (such as providing support to different stakeholders and developing mutual trust among them), (b) stakeholders’ characteristics (such as developed stakeholders’ interest and competence to participate in decision-making process), (c) organizational and material resources (such as school material conditions, the necessary information and time as resources for making decisions). The data were collected by a constructed and validated questionnaire for examining the school leadership characteristics and facilitators from teachers’ perspective. The main population in this study consists of all primary schools in Croatia while the sample is comprised of 100 primary schools, selected by random sampling. Furthermore, the sample of teachers was selected by an additional procedure taking into consideration the independent variables of sex, work experience, etc. Data processing was performed by standard statistical methods of descriptive and inferential statistics. Statistical program IBM SPSS 20.0 was used for data processing. The results of this study show that there is a (positive) correlation between school leadership characteristics and school leadership facilitators. Specifically, it is noteworthy to mention that all the dimensions of school leadership characteristics are in positive correlation with the categories of school leadership facilitators. These results are indicative for the education policy creators who should ensure positive and supportive environment for the school leadership development including the development of school leadership characteristics and school leadership facilitators.

Keywords: distributive school leadership, school effectiveness , school leadership characteristics, school leadership facilitators

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Authors: Belen Montero, Carmen Ramirez, Maite Rico, Rebeca Bouza, Irene Derungs

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Starch is a promising polymer for producing biocomposite materials because it is renewable, completely biodegradable and easily available at a low cost. Thermoplastic starches (TPS) can be obtained after the disruption and plasticization of native starch with a plasticizer. In this work, the solvent casting method was used to obtain TPS films from wheat starch plasticized with glycerol and reinforced with nanocellulose (CNC). X-ray diffraction analysis was used to follow the evolution of the crystallinity. The native wheat starch granules have shown a profile corresponding to A-type crystal structures typical for cereal starches. When TPS films are analyzed a high amorphous halo centered on 19º is obtained, indicating the plasticization process is completed. SEM imaging was made in order to analyse the morphology. The image from the raw wheat starch granules shows a bimodal granule size distribution with some granules in large round disk-shape forms (A-type) and the others as smaller spherical particles (B-type). The image from the neat TPS surface shows a continuous surface. No starch aggregates or swollen granules can be seen so, the plasticization process is complete. In the surfaces of reinforced TPS films aggregates are seen as the CNC concentration in the matrix increases. The CNC influence on the mechanical properties of TPS films has been studied by dynamic mechanical analysis. A direct relation exists between the storage modulus values, E’, and the CNC content in reinforced TPS films: higher is the content of nanocellulose in the composite, higher is the value of E’. This reinforcement effect can be explained by the appearance of a strong and crystalline nanoparticle-TPS interphase. Thermal stability of films was analysed by TGA. It has not observed any influence on the behaviour related to the thermal degradation of films with the incorporation of the CNC. Finally, the resistance to the water absorption films was analysed following the standard UNE-EN ISO 1998:483. The percentage of water absorbed by the samples at each time was calculated. The addition of 5 wt % of CNC to the TPS matrix leads to a significant improvement in the moisture resistance of the starch based material decreasing their diffusivity. It has been associated to the formation of a nanocrystal network that prevents swelling of the starch and therefore water absorption and to the high crystallinity of cellulose compared to starch. As a conclusion, the wheat film reinforced with 5 wt % of cellulose nanocrystals seems to be a good alternative for short-life applications into the packaging industry, because of its greatest rigidity, thermal stability and moisture sorption resistance.

Keywords: biocomposites, nanocellulose, starch, wheat

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Authors: Hsin Lee, Hsuan Lee

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Legal artificial intelligence (LegalAI) has been increasing applications within legal systems, propelled by advancements in natural language processing (NLP). Compared with general documents, legal case documents are typically long text sequences with intrinsic logical structures. Most existing language models have difficulty understanding the long-distance dependencies between different structures. Another unique challenge is that while the Judiciary of Taiwan has released legal judgments from various levels of courts over the years, there remains a significant obstacle in the lack of labeled datasets. This deficiency makes it difficult to train models with strong generalization capabilities, as well as accurately evaluate model performance. To date, models in Taiwan have yet to be specifically trained on judgment data. Given these challenges, this research proposes a Longformer-based pre-trained language model explicitly devised for retrieving similar judgments in Taiwanese legal documents. This model is trained on a self-constructed dataset, which this research has independently labeled to measure judgment similarities, thereby addressing a void left by the lack of an existing labeled dataset for Taiwanese judgments. This research adopts strategies such as early stopping and gradient clipping to prevent overfitting and manage gradient explosion, respectively, thereby enhancing the model's performance. The model in this research is evaluated using both the dataset and the Average Entropy of Offense-charged Clustering (AEOC) metric, which utilizes the notion of similar case scenarios within the same type of legal cases. Our experimental results illustrate our model's significant advancements in handling similarity comparisons within extensive legal judgments. By enabling more efficient retrieval and analysis of legal case documents, our model holds the potential to facilitate legal research, aid legal decision-making, and contribute to the further development of LegalAI in Taiwan.

Keywords: legal artificial intelligence, computation and language, language model, Taiwanese legal cases

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Authors: Nurcihan Kiris

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Restricted sleep is common in young adults and adolescents. The results of a few objective studies of sleep deprivation on cognitive performance were not clarified. In particular, the effect of sleep deprivation on the cognitive functions associated with frontal lobe such as attention, executive functions, working memory is not well known. The aim of this study is to investigate the effect of partial sleep deprivation experimentally in adolescents on the cognitive tasks of frontal lobe including working memory, strategic thinking, simple attention, continuous attention, executive functions, and cognitive flexibility. Subjects of the study were recruited from voluntary students of Cukurova University. Eighteen adolescents underwent four consecutive nights of monitored sleep restriction (6–6.5 hr/night) and four nights of sleep extension (10–10.5 hr/night), in counterbalanced order, and separated by a washout period. Following each sleep period, cognitive performance was assessed, at a fixed morning time, using a computerized neuropsychological battery based on frontal lobe functions task, a timed test providing both accuracy and reaction time outcome measures. Only the spatial working memory performance of cognitive tasks was found to be statistically lower in a restricted sleep condition than the extended sleep condition. On the other hand, there was no significant difference in the performance of cognitive tasks evaluating simple attention, constant attention, executive functions, and cognitive flexibility. It is thought that especially the spatial working memory and strategic thinking skills of adolescents may be susceptible to sleep deprivation. On the other hand, adolescents are predicted to be optimally successful in ideal sleep conditions, especially in the circumstances requiring for the short term storage of visual information, processing of stored information, and strategic thinking. The findings of this study may also be associated with possible negative functional effects on the processing of academic social and emotional inputs in adolescents for partial sleep deprivation. Acknowledgment: This research was supported by Cukurova University Scientific Research Projects Unit.

Keywords: attention, cognitive functions, sleep deprivation, working memory

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Authors: Shu-Yu Hsu, Chen-Chien Hsu, Wei-Yen Wang

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Color segmentation is a basic and simple way for recognizing the visual markers in a robotic tracking system. In this paper, we propose a new method for color segmentation by incorporating differential evolution algorithm and connected component labeling to autonomously preset the HSV threshold of visual markers. To evaluate the effectiveness of the proposed algorithm, a ROBOTIS OP2 humanoid robot is used to conduct the experiment, where five most commonly used color including red, purple, blue, yellow, and green in visual markers are given for comparisons.

Keywords: color segmentation, differential evolution, connected component labeling, humanoid robot

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

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A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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Authors: Mr. P. Suryaprasad, R. Lalitha

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This paper presents an efficient area and delay architectures for the implementation of one dimensional and two dimensional discrete cosine transform (DCT). These are supported to different lengths (4, 8, 16, and 32). DCT blocks are used in the different video coding standards for the image compression. The 2D- DCT calculation is made using the 2D-DCT separability property, such that the whole architecture is divided into two 1D-DCT calculations by using a transpose buffer. Based on the existing 1D-DCT architecture two different types of 2D-DCT architectures, folded and parallel types are implemented. Both of these two structures use the same transpose buffer. Proposed transpose buffer occupies less area and high speed than existing transpose buffer. Hence the area, low power and delay of both the 2D-DCT architectures are reduced.

Keywords: transposition buffer, video compression, discrete cosine transform, high efficiency video coding, two dimensional picture

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Authors: Changhwan Choi, Yongwan Park

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In this paper, we propose a method that allows faster and more accurate detection of traffic lights by a vision sensor during driving, DGPS is used to obtain physical location of a traffic light, extract from the image information of the vision sensor only the traffic light area at this location and ascertain if the sign is in operation and determine its form. This method can solve the problem in existing research where low visibility at night or reflection under bright light makes it difficult to recognize the form of traffic light, thus making driving unstable. We compared our success rate of traffic light recognition in day and night road environments. Compared to previous researches, it showed similar performance during the day but 50% improvement at night.

Keywords: traffic light, intelligent vehicle, night, detection, DGPS

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Authors: Parya Tabei, Maryam Habibifar

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Decision-making is an important cognitive function that can be defined as the process of choosing an option among available options to achieve a specific goal. Consumer ‘need’ is the main reason for purchasing decisions. Human decision-making while buying products online is subject to various factors, one of which is the quality and effect of advertising photos. Advertising photo editing can have a significant impact on people's virtual purchase decisions. This technique helps improve the quality and overall appearance of photos by adjusting various aspects such as brightness, contrast, colors, cropping, resizing, and adding filters. This study, by examining the effect of editing advertising photos on the virtual purchase decision using EEG data, tries to investigate the effect of edited images on the decision-making of customers. A group of 30 participants were asked to react to 24 edited and unedited images while their EEG was recorded. Analysis of the EEG data revealed increased alpha wave activity in the occipital regions (O1, O2) for both edited and unedited images, which is related to visual processing and attention. Additionally, there was an increase in beta wave activity in the frontal regions (FP1, FP2, F4, F8) when participants viewed edited images, suggesting involvement in cognitive processes such as decision-making and evaluating advertising content. Gamma wave activity also increased in various regions, especially the frontal and parietal regions, which are associated with higher cognitive functions, such as attention, memory, and perception, when viewing the edited images. While the visual processing reflected by alpha waves remained consistent across different visual conditions, editing advertising photos appeared to boost neural activity in frontal and parietal regions associated with decision-making processes. These Findings suggest that photo editing could potentially influence consumer perceptions during virtual shopping experiences by modulating brain activity related to product assessment and purchase decisions.

Keywords: virtual purchase decision, advertising photo, EEG parameters, decision Making

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