Search results for: squid processing by-products
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3673

Search results for: squid processing by-products

3343 Status of Sensory Profile Score among Children with Autism in Selected Centers of Dhaka City

Authors: Nupur A. D., Miah M. S., Moniruzzaman S. K.

Abstract:

Autism is a neurobiological disorder that affects physical, social, and language skills of a person. A child with autism feels difficulty for processing, integrating, and responding to sensory stimuli. Current estimates have shown that 45% to 96 % of children with Autism Spectrum Disorder demonstrate sensory difficulties. As autism is a worldwide burning issue, it has become a highly prioritized and important service provision in Bangladesh. The sensory deficit does not only hamper the normal development of a child, it also hampers the learning process and functional independency. The purpose of this study was to find out the prevalence of sensory dysfunction among children with autism and recognize common patterns of sensory dysfunction. A cross-sectional study design was chosen to carry out this research work. This study enrolled eighty children with autism and their parents by using the systematic sampling method. In this study, data were collected through the Short Sensory Profile (SSP) assessment tool, which consists of 38 items in the questionnaire, and qualified graduate Occupational Therapists were directly involved in interviewing parents as well as observing child responses to sensory related activities of the children with autism from four selected autism centers in Dhaka, Bangladesh. All item analyses were conducted to identify items yielding or resulting in the highest reported sensory processing dysfunction among those children through using SSP and Statistical Package for Social Sciences (SPSS) version 21.0 for data analysis. This study revealed that almost 78.25% of children with autism had significant sensory processing dysfunction based on their sensory response to relevant activities. Under-responsive sensory seeking and auditory filtering were the least common problems among them. On the other hand, most of them (95%) represented that they had definite to probable differences in sensory processing, including under-response or sensory seeking, auditory filtering, and tactile sensitivity. Besides, the result also shows that the definite difference in sensory processing among 64 children was within 100%; it means those children with autism suffered from sensory difficulties, and thus it drew a great impact on the children’s Daily Living Activities (ADLs) as well as social interaction with others. Almost 95% of children with autism require intervention to overcome or normalize the problem. The result gives insight regarding types of sensory processing dysfunction to consider during diagnosis and ascertaining the treatment. So, early sensory problem identification is very important and thus will help to provide appropriate sensory input to minimize the maladaptive behavior and enhance to reach the normal range of adaptive behavior.

Keywords: autism, sensory processing difficulties, sensory profile, occupational therapy

Procedia PDF Downloads 37
3342 Production and Distribution Network Planning Optimization: A Case Study of Large Cement Company

Authors: Lokendra Kumar Devangan, Ajay Mishra

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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

Procedia PDF Downloads 40
3341 Geometallurgy of Niobium Deposits: An Integrated Multi-Disciplined Approach

Authors: Mohamed Nasraoui

Abstract:

Spatial ore distribution, ore heterogeneity and their links with geological processes involved in Niobium concentration are all factors for consideration when bridging field observations to extraction scheme. Indeed, mineralogy changes of Nb-hosting phases, their textural relationships with hydrothermal or secondary minerals, play a key control over mineral processing. This study based both on filed work and ore characterization presents data from several Nb-deposits related to carbonatite complexes. The results obtained by a wide range of analytical techniques, including, XRD, XRF, ICP-MS, SEM, Microprobe, Spectro-CL, FTIR-DTA and Mössbauer spectroscopy, demonstrate how geometallurgical assessment, at all stage of mine development, can greatly assist in the design of a suitable extraction flowsheet and data reconciliation.

Keywords: carbonatites, Nb-geometallurgy, Nb-mineralogy, mineral processing.

Procedia PDF Downloads 142
3340 Fluoranthene Removal in Wastewater Using Biological and Physico-Chemical Methods

Authors: Angelica Salmeron Alcocer, Deifilia Ahuatzi Chacon, Felipe Rodriguez Casasola

Abstract:

Polycyclic aromatic hydrocarbons (PAHs) are produced naturally (forest fires, volcanic eruptions) and human activity (burning fossil fuels). Concern for PAHs is due to their toxic, mutagenic and carcinogenic effects and so pose a potential risk to human health and ecology. Therefore these are considered the most toxic components of oil, they are highly hydrophobic, making them easily depositable on the floor, air and water. One method of removing PAHs of contaminated soil used surfactants such as Tween 80, which it has been reported as less toxic and also increases the solubility of the PAH compared to other surfactants, fluoranthene is a PAH with molecular formula C16H10, its name derives from the fluorescence which presents to UV light. In this paper, a study of the fluoranthene removal solubilized with Tween 80 in synthetic wastewater using a microbial community (isolated from soil of coffee plantations in the state of Veracruz, Mexico) and Fenton oxidation method was performed. The microbial community was able to use both tween 80 and fluoranthene as carbon sources for growth, when the biological treatment in batch culture was applied, 100% of fluoranthene was mineralized, this only occurred at an initial concentration of 100 ppm, but by increasing the initial concentration of fluoranthene the removal efficiencies decay and degradation time increases due to the accumulation of byproducts more toxic or less biodegradable, however when the Fenton oxidation was previously applied to the biological treatment, it was observed that removal of fluoranthene improved because it is consumed approximately 2.4 times faster.

Keywords: fluoranthene, polycyclic aromatic hydrocarbons, biological treatment, fenton oxidation

Procedia PDF Downloads 222
3339 Early Diagnosis of Alzheimer's Disease Using a Combination of Images Processing and Brain Signals

Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, LOO cycle, medial temporal atrophy

Procedia PDF Downloads 177
3338 Reading Comprehension in Profound Deaf Readers

Authors: S. Raghibdoust, E. Kamari

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Research show that reduced functional hearing has a detrimental influence on the ability of an individual to establish proper phonological representations of words, since the phonological representations are claimed to mediate the conceptual processing of written words. Word processing efficiency is expected to decrease with a decrease in functional hearing. In other words, it is predicted that hearing individuals would be more capable of word processing than individuals with hearing loss, as their functional hearing works normally. Studies also demonstrate that the quality of the functional hearing affects reading comprehension via its effect on their word processing skills. In other words, better hearing facilitates the development of phonological knowledge, and can promote enhanced strategies for the recognition of written words, which in turn positively affect higher-order processes underlying reading comprehension. The aims of this study were to investigate and compare the effect of deafness on the participants’ abilities to process written words at the lexical and sentence levels through using two online and one offline reading comprehension tests. The performance of a group of 8 deaf male students (ages 8-12) was compared with that of a control group of normal hearing male students. All the participants had normal IQ and visual status, and came from an average socioeconomic background. None were diagnosed with a particular learning or motor disability. The language spoken in the homes of all participants was Persian. Two tests of word processing were developed and presented to the participants using OpenSesame software, in order to measure the speed and accuracy of their performance at the two perceptual and conceptual levels. In the third offline test of reading comprehension which comprised of semantically plausible and semantically implausible subject relative clauses, the participants had to select the correct answer out of two choices. The data derived from the statistical analysis using SPSS software indicated that hearing and deaf participants had a similar word processing performance both in terms of speed and accuracy of their responses. The results also showed that there was no significant difference between the performance of the deaf and hearing participants in comprehending semantically plausible sentences (p > 0/05). However, a significant difference between the performances of the two groups was observed with respect to their comprehension of semantically implausible sentences (p < 0/05). In sum, the findings revealed that the seriously impoverished sentence reading ability characterizing the profound deaf subjects of the present research, exhibited their reliance on reading strategies that are based on insufficient or deviant structural knowledge, in particular in processing semantically implausible sentences, rather than a failure to efficiently process written words at the lexical level. This conclusion, of course, does not mean to say that deaf individuals may never experience deficits at the word processing level, deficits that impede their understanding of written texts. However, as stated in previous researches, it sounds reasonable to assume that the more deaf individuals get familiar with written words, the better they can recognize them, despite having a profound phonological weakness.

Keywords: deafness, reading comprehension, reading strategy, word processing, subject and object relative sentences

Procedia PDF Downloads 319
3337 Bamboo: A Trendy and New Alternative to Wood

Authors: R. T. Aggangan, R. J. Cabangon

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Bamboo is getting worldwide attention over the last 20 to 30 years due to numerous uses and it is regarded as the closest material that can be used as substitute to wood. In the domestic market, high quality bamboo products are sold in high-end markets while lower quality products are generally sold to medium and low income consumers. The global market in 2006 stands at about 7 billion US dollars and was projected to increase to US$ 17 B from 2015 to 2020. The Philippines had been actively producing and processing bamboo products for the furniture, handicrafts and construction industry. It was however in 2010 that the Philippine bamboo industry was formalized by virtue of Executive Order 879 that stated that the Philippine bamboo industry development is made a priority program of the government and created the Philippine Bamboo Industry Development Council (PBIDC) to provide the overall policy and program directions of the program for all stakeholders. At present, the most extensive use of bamboo is for the manufacture of engineered bamboo for school desks for all public schools as mandated by EO 879. Also, engineered bamboo products are used for high-end construction and furniture as well as for handicrafts. Development of cheap adhesives, preservatives, and finishing chemicals from local species of plants, development of economical methods of drying and preservation, product development and processing of lesser-used species of bamboo, development of processing tools, equipment and machineries are the strategies that will be employed to reduce the price and mainstream engineered bamboo products in the local and foreign market. In addition, processing wastes from bamboo can be recycled into fuel products such as charcoal are already in use. The more exciting possibility, however, is the production of bamboo pellets that can be used as a substitute for wood pellets for heating, cooking and generating electricity.

Keywords: bamboo charcoal and light distillates, engineered bamboo, furniture and handicraft industries, housing and construction, pellets

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3336 Evaluation of Condyle Alterations after Orthognathic Surgery with a Digital Image Processing Technique

Authors: Livia Eisler, Cristiane C. B. Alves, Cristina L. F. Ortolani, Kurt Faltin Jr.

Abstract:

Purpose: This paper proposes a technically simple diagnosis method among orthodontists and maxillofacial surgeons in order to evaluate discrete bone alterations. The methodology consists of a protocol to optimize the diagnosis and minimize the possibility for orthodontic and ortho-surgical retreatment. Materials and Methods: A protocol of image processing and analysis, through ImageJ software and its plugins, was applied to 20 pairs of lateral cephalometric images obtained from cone beam computerized tomographies, before and 1 year after undergoing orthognathic surgery. The optical density of the images was analyzed in the condylar region to determine possible bone alteration after surgical correction. Results: Image density was shown to be altered in all image pairs, especially regarding the condyle contours. According to measures, condyle had a gender-related density reduction for p=0.05 and condylar contours had their alterations registered in mm. Conclusion: A simple, viable and cost-effective technique can be applied to achieve the more detailed image-based diagnosis, not depending on the human eye and therefore, offering more reliable, quantitative results.

Keywords: bone resorption, computer-assisted image processing, orthodontics, orthognathic surgery

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3335 The Structural Pattern: An Event-Related Potential Study on Tang Poetry

Authors: ShuHui Yang, ChingChing Lu

Abstract:

Measuring event-related potentials (ERPs) has been fundamental to our understanding of how people process language. One specific ERP component, a P600, has been hypothesized to be associated with syntactic reanalysis processes. We, however, propose that the P600 is not restricted to reanalysis processes, but is the index of the structural pattern processing. To investigate the structural pattern processing, we utilized the effects of stimulus degradation in structural priming. To put it another way, there was no P600 effect if the structure of the prime was the same with the structure of the target. Otherwise, there would be a P600 effect if the structure were different between the prime and the target. In the experiment, twenty-two participants were presented with four sentences of Tang poetry. All of the first two sentences, being prime, were conducted with SVO+VP. The last two sentences, being the target, were divided into three types. Type one of the targets was SVO+VP. Type two of the targets was SVO+VPVP. Type three of the targets was VP+VP. The result showed that both of the targets, SVO+VPVP and VP+VP, elicited positive-going brainwave, a P600 effect, at 600~900ms time window. Furthermore, the P600 component was lager for the target’ VP+VP’ than the target’ SVO+VPVP’. That meant the more dissimilar the structure was, the lager the P600 effect we got. These results indicate that P600 was the index of the structure processing, and it would affect the P600 effect intensity with the degrees of structural heterogeneity.

Keywords: ERPs, P600, structural pattern, structural priming, Tang poetry

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3334 Memory Retrieval and Implicit Prosody during Reading: Anaphora Resolution by L1 and L2 Speakers of English

Authors: Duong Thuy Nguyen, Giulia Bencini

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The present study examined structural and prosodic factors on the computation of antecedent-reflexive relationships and sentence comprehension in native English (L1) and Vietnamese-English bilinguals (L2). Participants read sentences presented on the computer screen in one of three presentation formats aimed at manipulating prosodic parsing: word-by-word (RSVP), phrase-segment (self-paced), or whole-sentence (self-paced), then completed a grammaticality rating and a comprehension task (following Pratt & Fernandez, 2016). The design crossed three factors: syntactic structure (simple; complex), grammaticality (target-match; target-mismatch) and presentation format. An example item is provided in (1): (1) The actress that (Mary/John) interviewed at the awards ceremony (about two years ago/organized outside the theater) described (herself/himself) as an extreme workaholic). Results showed that overall, both L1 and L2 speakers made use of a good-enough processing strategy at the expense of more detailed syntactic analyses. L1 and L2 speakers’ comprehension and grammaticality judgements were negatively affected by the most prosodically disrupting condition (word-by-word). However, the two groups demonstrated differences in their performance in the other two reading conditions. For L1 speakers, the whole-sentence and the phrase-segment formats were both facilitative in the grammaticality rating and comprehension tasks; for L2, compared with the whole-sentence condition, the phrase-segment paradigm did not significantly improve accuracy or comprehension. These findings are consistent with the findings of Pratt & Fernandez (2016), who found a similar pattern of results in the processing of subject-verb agreement relations using the same experimental paradigm and prosodic manipulation with English L1 and L2 English-Spanish speakers. The results provide further support for a Good-Enough cue model of sentence processing that integrates cue-based retrieval and implicit prosodic parsing (Pratt & Fernandez, 2016) and highlights similarities and differences between L1 and L2 sentence processing and comprehension.

Keywords: anaphora resolution, bilingualism, implicit prosody, sentence processing

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3333 Neural Correlates of Arabic Digits Naming

Authors: Fernando Ojedo, Alejandro Alvarez, Pedro Macizo

Abstract:

In the present study, we explored electrophysiological correlates of Arabic digits naming to determine semantic processing of numbers. Participants named Arabic digits grouped by category or intermixed with exemplars of other semantic categories while the N400 event-related potential was examined. Around 350-450 ms after the presentation of Arabic digits, brain waves were more positive in anterior regions and more negative in posterior regions when stimuli were grouped by category relative to the mixed condition. Contrary to what was found in other studies, electrophysiological results suggested that the production of numerals involved semantic mediation.

Keywords: Arabic digit naming, event-related potentials, semantic processing, number production

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3332 Elevated Temperature Shot Peening for M50 Steel

Authors: Xinxin Ma, Guangze Tang, Shuxin Yang, Jinguang He, Fan Zhang, Peiling Sun, Ming Liu, Minyu Sun, Liqin Wang

Abstract:

As a traditional surface hardening technique, shot peening is widely used in industry. By using shot peening, a residual compressive stress is formed in the surface which is beneficial for improving the fatigue life of metal materials. At the same time, very fine grains and high density defects are generated in the surface layer which enhances the surface hardness, either. However, most of the processes are carried out at room temperature. For high strength steel, such as M50, the thickness of the strengthen layer is limited. In order to obtain a thick strengthen surface layer, elevated temperature shot peening was carried out in this work by using Φ1mm cast ion balls with a speed of 80m/s. Considering the tempering temperature of M50 steel is about 550 oC, the processing temperature was in the range from 300 to 500 oC. The effect of processing temperature and processing time of shot peening on distribution of residual stress and surface hardness was investigated. As we known, the working temperature of M50 steel can be as high as 315 oC. Because the defects formed by shot peening are unstable when the working temperature goes higher, it is worthy to understand what happens during the shot peening process, and what happens when the strengthen samples were kept at a certain temperature. In our work, the shot peening time was selected from 2 to 10 min. And after the strengthening process, the samples were annealed at various temperatures from 200 to 500 oC up to 60 h. The results show that the maximum residual compressive stress is near 900 MPa. Compared with room temperature shot peening, the strengthening depth of 500 oC shot peening sample is about 2 times deep. The surface hardness increased with the processing temperature, and the saturation peening time decreases. After annealing, the residual compressive stress decreases, however, for 500 oC peening sample, even annealing at 500 oC for 20 h, the residual compressive stress is still over 600 MPa. However, it is clean to see from SEM that the grain size of surface layers is still very small.

Keywords: shot peening, M50 steel, residual compressive stress, elevated temperature

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3331 Comparing Image Processing and AI Techniques for Disease Detection in Plants

Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

Abstract:

Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

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3330 A Comprehensive Survey of Artificial Intelligence and Machine Learning Approaches across Distinct Phases of Wildland Fire Management

Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

Abstract:

Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

Procedia PDF Downloads 46
3329 Computer Aided Analysis of Breast Based Diagnostic Problems from Mammograms Using Image Processing and Deep Learning Methods

Authors: Ali Berkan Ural

Abstract:

This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

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3328 Implementing a Database from a Requirement Specification

Authors: M. Omer, D. Wilson

Abstract:

Creating a database scheme is essentially a manual process. From a requirement specification, the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time-consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that the first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore, this method is a step forward in finding a solution that requires little or no user intervention.

Keywords: information extraction, natural language processing, relation extraction

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3327 Legal Issues of Collecting and Processing Big Health Data in the Light of European Regulation 679/2016

Authors: Ioannis Iglezakis, Theodoros D. Trokanas, Panagiota Kiortsi

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This paper aims to explore major legal issues arising from the collection and processing of Health Big Data in the light of the new European secondary legislation for the protection of personal data of natural persons, placing emphasis on the General Data Protection Regulation 679/2016. Whether Big Health Data can be characterised as ‘personal data’ or not is really the crux of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Another key point is that the application of some provisions of GPDR to Big Health Data may both absolve the data controller of his legal obligations and deprive the data subject of his rights (e.g., the right to be informed), ultimately undermining the fundamental right to the protection of personal data of natural persons. Moreover, data subject’s rights (e.g., the right not to be subject to a decision based solely on automated processing) are heavily impacted by the use of AI, algorithms, and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have a substantial impact on individuals. On the other hand, as the COVID-19 pandemic has revealed, Big Data analytics can offer crucial sources of information. In this respect, this paper identifies and systematises the legal provisions concerned, offering interpretative solutions that tackle dangers concerning data subject’s rights while embracing the opportunities that Big Health Data has to offer. In addition, particular attention is attached to the scope of ‘consent’ as a legal basis in the collection and processing of Big Health Data, as the application of data analytics in Big Health Data signals the construction of new data and subject’s profiles. Finally, the paper addresses the knotty problem of role assignment (i.e., distinguishing between controller and processor/joint controllers and joint processors) in an era of extensive Big Health data sharing. The findings are the fruit of a current research project conducted by a three-member research team at the Faculty of Law of the Aristotle University of Thessaloniki and funded by the Greek Ministry of Education and Religious Affairs.

Keywords: big health data, data subject rights, GDPR, pandemic

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3326 Elder Abuse: An Exploration of China, the United States, and Israel’s Perspectives on Elder Abuse and What Their Differences Reveal about Its Underreported Nature

Authors: Sydney Burnett

Abstract:

The history of the relationship between elder abuse and its tendency to go underreported is rooted in the oppressive nature of ageism and victimization. Approximately 8% of the world's population was aged sixty or over in 1950, whereas, in 2020, the number more than doubled to 16.9%. By 2050, that number is expected to reach 22%. Although difficult for individuals of any age to feel completely supported in society, this task proves especially difficult for the elderly demographic. And as the elderly population continues to grow, the systemic abuse and neglect that this group encounters, and thus its underreported nature, multiply at a similar rate. Although a recent increase in awareness has initiated stronger efforts towards addressing the meager resources, processes, and personnel present to manage elder abuse, both reported and unreported, the destructive complexities of ageism and victimization persist. Examining the byproducts of the rapidly growing elderly demographic in China, the United States, and Israel, in cohesion with the inherent challenges in the context of terminology, definition, and typologies of elder abuse should provide insight into the pernicious influences of elder abuse that contribute to the non-identification and non-recognition of elder maltreatment present in these three countries in different stages of development. This investigation aims to understand the intricacy of elder abuse and its correlation to a lack of acknowledgment as well as its consequences in society by exploring the variation between China, the United States, and Israel's attitudes surrounding the subject. Furthermore, the systemic abuse and neglect embedded in global ageism can be revealed by the differences between the three countries' approaches to reporting elder abuse.

Keywords: elder abuse, ageism, mistreatment, underreported

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3325 Toxicological Validation during the Development of New Catalytic Systems Using Air/Liquid Interface Cell Exposure

Authors: M. Al Zallouha, Y. Landkocz, J. Brunet, R. Cousin, J. M. Halket, E. Genty, P. J. Martin, A. Verdin, D. Courcot, S. Siffert, P. Shirali, S. Billet

Abstract:

Toluene is one of the most used Volatile Organic Compounds (VOCs) in the industry. Amongst VOCs, Benzene, Toluene, Ethylbenzene and Xylenes (BTEX) emitted into the atmosphere have a major and direct impact on human health. It is, therefore, necessary to minimize emissions directly at source. Catalytic oxidation is an industrial technique which provides remediation efficiency in the treatment of these organic compounds. However, during operation, the catalysts can release some compounds, called byproducts, more toxic than the original VOCs. The catalytic oxidation of a gas stream containing 1000ppm of toluene on Pd/α-Al2O3 can release a few ppm of benzene, according to the operating temperature of the catalyst. The development of new catalysts must, therefore, include chemical and toxicological validation phases. In this project, A549 human lung cells were exposed in air/liquid interface (Vitrocell®) to gas mixtures derived from the oxidation of toluene with a catalyst of Pd/α-Al2O3. Both exposure concentrations (i.e. 10 and 100% of catalytic emission) resulted in increased gene expression of Xenobiotics Metabolising Enzymes (XME) (CYP2E1 CYP2S1, CYP1A1, CYP1B1, EPHX1, and NQO1). Some of these XMEs are known to be induced by polycyclic organic compounds conventionally not searched during the development of catalysts for VOCs degradation. The increase in gene expression suggests the presence of undetected compounds whose toxicity must be assessed before the adoption of new catalyst. This enhances the relevance of toxicological validation of such systems before scaling-up and marketing.

Keywords: BTEX toxicity, air/liquid interface cell exposure, Vitrocell®, catalytic oxidation

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3324 Performance Analysis of the Precise Point Positioning Data Online Processing Service and Using for Monitoring Plate Tectonic of Thailand

Authors: Nateepat Srivarom, Weng Jingnong, Serm Chinnarat

Abstract:

Precise Point Positioning (PPP) technique is use to improve accuracy by using precise satellite orbit and clock correction data, but this technique is complicated methods and high costs. Currently, there are several online processing service providers which offer simplified calculation. In the first part of this research, we compare the efficiency and precision of four software. There are three popular online processing service providers: Australian Online GPS Processing Service (AUSPOS), CSRS-Precise Point Positioning and CenterPoint RTX post processing by Trimble and 1 offline software, RTKLIB, which collected data from 10 the International GNSS Service (IGS) stations for 10 days. The results indicated that AUSPOS has the least distance root mean square (DRMS) value of 0.0029 which is good enough to be calculated for monitoring the movement of tectonic plates. The second, we use AUSPOS to process the data of geodetic network of Thailand. In December 26, 2004, the earthquake occurred a 9.3 MW at the north of Sumatra that highly affected all nearby countries, including Thailand. Earthquake effects have led to errors of the coordinate system of Thailand. The Royal Thai Survey Department (RTSD) is primarily responsible for monitoring of the crustal movement of the country. The difference of the geodetic network movement is not the same network and relatively large. This result is needed for survey to continue to improve GPS coordinates system in every year. Therefore, in this research we chose the AUSPOS to calculate the magnitude and direction of movement, to improve coordinates adjustment of the geodetic network consisting of 19 pins in Thailand during October 2013 to November 2017. Finally, results are displayed on the simulation map by using the ArcMap program with the Inverse Distance Weighting (IDW) method. The pin with the maximum movement is pin no. 3239 (Tak) in the northern part of Thailand. This pin moved in the south-western direction to 11.04 cm. Meanwhile, the directional movement of the other pins in the south gradually changed from south-west to south-east, i.e., in the direction noticed before the earthquake. The magnitude of the movement is in the range of 4 - 7 cm, implying small impact of the earthquake. However, the GPS network should be continuously surveyed in order to secure accuracy of the geodetic network of Thailand.

Keywords: precise point positioning, online processing service, geodetic network, inverse distance weighting

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3323 An Advanced Automated Brain Tumor Diagnostics Approach

Authors: Berkan Ural, Arif Eser, Sinan Apaydin

Abstract:

Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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3322 Analysis of Control by Flattening of the Welded Tubes

Authors: Hannachi Med Tahar, H. Djebaili, B. Daheche

Abstract:

In this approach, we have tried to describe the flattening of welded tubes, and its experimental application. The test is carried out at the (National product processing company dishes and tubes production). Usually, the final products (tubes) undergo a series of non-destructive inspection online and offline welding, and obviously destructive mechanical testing (bending, flattening, flaring, etc.). For this and for the purpose of implementing the flattening test, which applies to the processing of round tubes in other forms, it took four sections of welded tubes draft (before stretching hot) and welded tubes finished (after drawing hot and annealing), it was also noted the report 'health' flattened tubes must not show or crack or tear. The test is considered poor if it reveals a lack of ductility of the metal.

Keywords: flattening, destructive testing, tube drafts, finished tube, Castem 2001

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3321 Determinaton of Processing Parameters of Decaffeinated Black Tea by Using Pilot-Scale Supercritical CO₂ Extraction

Authors: Saziye Ilgaz, Atilla Polat

Abstract:

There is a need for development of new processing techniques to ensure safety and quality of final product while minimizing the adverse impact of extraction solvents on environment and residue levels of these solvents in final product, decaffeinated black tea. In this study pilot scale supercritical carbon dioxide (SCCO₂) extraction was used to produce decaffeinated black tea in place of solvent extraction. Pressure (250, 375, 500 bar), extraction time (60, 180, 300 min), temperature (55, 62.5, 70 °C), CO₂ flow rate (1, 2 ,3 LPM) and co-solvent quantity (0, 2.5, 5 %mol) were selected as extraction parameters. The five factors BoxBehnken experimental design with three center points was performed to generate 46 different processing conditions for caffeine removal from black tea samples. As a result of these 46 experiments caffeine content of black tea samples were reduced from 2.16 % to 0 – 1.81 %. The experiments showed that extraction time, pressure, CO₂ flow rate and co-solvent quantity had great impact on decaffeination yield. Response surface methodology (RSM) was used to optimize the parameters of the supercritical carbon dioxide extraction. Optimum extraction parameters obtained of decaffeinated black tea were as follows: extraction temperature of 62,5 °C, extraction pressure of 375 bar, CO₂ flow rate of 3 LPM, extraction time of 176.5 min and co-solvent quantity of 5 %mol.

Keywords: supercritical carbon dioxide, decaffeination, black tea, extraction

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3320 Difficulties in the Emotional Processing of Intimate Partner Violence Perpetrators

Authors: Javier Comes Fayos, Isabel RodríGuez Moreno, Sara Bressanutti, Marisol Lila, Angel Romero MartíNez, Luis Moya Albiol

Abstract:

Given the great impact produced by gender-based violence, its comprehensive approach seems essential. Consequently, research has focused on risk factors for violent behaviour, linking various psychosocial variables, as well as cognitive and neuropsychological deficits with the aggressors. However, studies on affective processing are scarce, so the present study investigates possible emotional alterations in men convicted of gender violence. The participants were 51 aggressors, who attended the CONTEXTO program with sentences of less than two years, and 47 men with no history of violence. The sample did not differ in age, socioeconomic level, education, or alcohol and other substances consumption. Anger, alexithymia and facial recognition of other people´s emotions were assessed through the State-Trait Anger Expression Inventory (STAXI-2), the Toronto Alexithymia Scale (TAS-20) and Reading the mind in the eyes (REM), respectively. Men convicted of gender-based violence showed higher scores on the anger trait and temperament dimensions, as well as on the anger expression index. They also scored higher on alexithymia and in the identification and emotional expression subscales. In addition, they showed greater difficulties in the facial recognition of emotions by having a lower score in the REM. These results seem to show difficulties in different affective areas in men condemned for gender violence. The deficits are reflected in greater difficulty in identifying and expressing emotions, in processing anger and in recognizing the emotions of others. All these difficulties have been related to the use of violent behavior. Consequently, it is essential and necessary to include emotional regulation in intervention programs for men who have been convicted of gender-based violence.

Keywords: alexithymia, anger, emotional processing, emotional recognition, empathy, intimate partner violence

Procedia PDF Downloads 171
3319 Fed-Batch Mixotrophic Cultivation of Microalgae Scenedesmus sp., Using Airlift Photobioreactor

Authors: Lakshmidevi Rajendran, Bharathidasan Kanniappan, Gopi Raja, Muthukumar Karuppan

Abstract:

This study investigates the feasibility of fed-batch mixotrophic cultivation of microalgae Scenedesmus sp. in a 3-litre airlift photobioreactor under standard operating conditions. The results of this study suggest the algae species may serve as an excellent feed for aquatic species using organic byproducts. Microalgae Scenedesmus sp., was cultured using a synthetic wastewater by stepwise addition of crude glycerol concentration ranging from 2-10g/l under fed-batch mixotrophic mode for a period of 15 days. The attempts were made with the stepwise addition of crude glycerol as a carbon source in the initial growth phase to evade the inhibitory nature of high glycerol concentration on the growth of Scenedesmus sp. Crude glycerol was chosen since it is readily accessible as byproduct from biodiesel production sectors. Highest biomass concentration was achieved to be 2.43 g/l at the crude glycerol concentration of 6g/l after 10 days which is 3 fold times the increase in the biomass concentration compared with the control medium without the addition of glycerol. Biomass growth data obtained for the microalgae Scenedesmus sp. was fitted well with the modified Logistic equation. Substrate utilization kinetics was also employed to model the biomass productivity with respect to the various crude glycerol concentration. The results indicated that the supplement of crude glycerol to the mixotrophic culture of Scenedesmus sp., enhances the biomass concentration, chlorophyll and lutein productivity. Thus the application of fed-batch mixotrophic cultivation with stepwise addition of crude glycerol to Scenedesmus sp., provides a subtle way to reduce the production cost and improvisation in the large-scale cultivation along with biochemical compound synthesis.

Keywords: airlift photobioreactor, crude glycerol, microalgae Scenedesmus sp., mixotrophic cultivation, lutein production

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3318 Cognitive SATP for Airborne Radar Based on Slow-Time Coding

Authors: Fanqiang Kong, Jindong Zhang, Daiyin Zhu

Abstract:

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, the notion of cognitive radar is extended to STAP technique, and cognitive STAP is discussed. The principle for improving signal-to-clutter ratio (SCNR) based on slow-time coding is given, and the corresponding optimization algorithm based on cyclic and power-like algorithms is presented. Numerical examples show the effectiveness of the proposed method.

Keywords: space-time adaptive processing (STAP), airborne radar, signal-to-clutter ratio, slow-time coding

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3317 Influence of Some Technological Parameters on the Content of Voids in Composite during On-Line Consolidation with Filament Winding Technology

Authors: M. Stefanovska, B. Samakoski, S. Risteska, G. Maneski

Abstract:

In this study was performed in situ consolidation of polypropylene matrix/glass reinforced roving by combining heating systems and roll pressing. The commingled roving during hoop winding was winded on a cylindrical mandrel. The work also presents the advances made in the processing of these materials into composites by conventional technique filament winding. Experimental studies were performed with changing parameters – temperature, pressure and speed. Finally, it describes the investigation of the optimal processing conditions that maximize the mechanical properties of the composites. These properties are good enough for composites to be used as engineering materials in many structural applications.

Keywords: commingled fiber, consolidation heat, filament winding, voids

Procedia PDF Downloads 244
3316 Low Field Microwave Absorption and Magnetic Anisotropy in TM Co-Doped ZnO System

Authors: J. Das, T. S. Mahule, V. V. Srinivasu

Abstract:

Electron spin resonance (ESR) study at 9.45 GHz and a field modulation frequency of 100Hz was performed on bulk polycrystalline samples of Mn:TM (Fe/Ni) and Mn:RE (Gd/Sm) co doped ZnO samples with composition Zn1-xMn:TM/RE)xO synthesised by solid state reaction route and sintered at 500 0C temperature. The room temperature microwave absorption data collected by sweeping the DC magnetic field from -500 to 9500 G for the Mn:Fe and Mn:Ni co doped ZnO samples exhibit a rarely reported non resonant low field absorption (NRLFA) in addition to a strong absorption at around 3350G, usually associated with ferromagnetic resonance (FMR) satisfying Larmor’s relation due to absorption in the full saturation state. Observed low field absorption is distinct to ferromagnetic resonance even at low temperature and shows hysteresis. Interestingly, it shows a phase opposite with respect to the main ESR signal of the samples, which indicates that the low field absorption has a minimum value at zero magnetic field whereas the ESR signal has a maximum value. The major resonance peak as well as the peak corresponding to low field absorption exhibit asymmetric nature indicating magnetic anisotropy in the sample normally associated with intrinsic ferromagnetism. Anisotropy parameter for Mn:Ni codoped ZnO sample is noticed to be quite higher. The g values also support the presence of oxygen vacancies and clusters in the samples. These samples have shown room temperature ferromagnetism in the SQUID measurement. However, in rare earth (RE) co doped samples (Zn1-x (Mn: Gd/Sm)xO), which show paramagnetic behavior at room temperature, the low field microwave signals are not observed. As microwave currents due to itinerary electrons can lead to ohmic losses inside the sample, we speculate that more delocalized 3d electrons contributed from the TM dopants facilitate such microwave currents leading to the loss and hence absorption at the low field which is also supported by the increase in current with increased micro wave power. Besides, since Fe and Ni has intrinsic spin polarization with polarisability of around 45%, doping of Fe and Ni is expected to enhance the spin polarization related effect in ZnO. We emphasize that in this case Fe and Ni doping contribute to polarized current which interacts with the magnetization (spin) vector and get scattered giving rise to the absorption loss.

Keywords: co-doping, electron spin resonance, hysteresis, non-resonant microwave absorption

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3315 The Trajectory of the Ball in Football Game

Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

Abstract:

Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

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3314 The Principle Probabilities of Space-Distance Resolution for a Monostatic Radar and Realization in Cylindrical Array

Authors: Anatoly D. Pluzhnikov, Elena N. Pribludova, Alexander G. Ryndyk

Abstract:

In conjunction with the problem of the target selection on a clutter background, the analysis of the scanning rate influence on the spatial-temporal signal structure, the generalized multivariate correlation function and the quality of the resolution with the increase pulse repetition frequency is made. The possibility of the object space-distance resolution, which is conditioned by the range-to-angle conversion with an increased scanning rate, is substantiated. The calculations for the real cylindrical array at high scanning rate are presented. The high scanning rate let to get the signal to noise improvement of the order of 10 dB for the space-time signal processing.

Keywords: antenna pattern, array, signal processing, spatial resolution

Procedia PDF Downloads 160