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

Authors: W. H. El Garaihy, A. Nassef, S. Samy

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Equal channel angular pressing (ECAP) of commercial Al-Mg-Si alloy was conducted using two strain rates. The ECAP processing was conducted at room temperature and at 250 °C. Route A was adopted up to a total number of four passes in the present work. Structural evolution of the aluminum alloy discs was investigated before and after ECAP processing using optical microscopy (OM). Following ECAP, simple compression tests and Vicker’s hardness were performed. OM micrographs showed that, the average grain size of the as-received Al-Mg-Si disc tends to be larger than the size of the ECAP processed discs. Moreover, significant difference in the grain morphologies of the as-received and processed discs was observed. Intensity of deformation was observed via the alignment of the Al-Mg-Si consolidated particles (grains) in the direction of shear, which increased with increasing the number of passes via ECAP. Increasing the number of passes up to 4 resulted in increasing the grains aspect ratio up to ~5. It was found that the pressing temperature has a significant influence on the microstructure, Hv-values, and compressive strength of the processed discs. Hardness measurements demonstrated that 1-pass resulted in increase of Hv-value by 42% compared to that of the as-received alloy. 4-passes of ECAP processing resulted in additional increase in the Hv-value. A similar trend was observed for the yield and compressive strength. Experimental data of the Hv-values demonstrated that there is a lack of any significant dependence on the processing strain rate.

Keywords: Al-Mg-Si alloy, equal channel angular pressing, grain refinement, severe plastic deformation

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Authors: Weldeabrha Kiros Kidanemaryam, DepaTesfay Kelali Gidey, Yikaalo Welu Kidanemariam

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Dairy services are considered as sources of income, employment, nutrition and health for smallholder rural and urban farmers. The main objective of this study is to assess the interlinkage of dairy farms and small-scale dairy processing in Mekelle, Tigray. To achieve the stated objective, a descriptive research approach was employed where data was collected from 45 dairy farmers and 40 small-scale processors and analyzed by calculating the mean values and percentages. Findings show that the dairy business in the study area is characterized by a shortage of feed and water for the farm. The dairy farm is dominated by breeds of hybrid type, followed by the so called ‘begait’. Though the farms have access to medication and vaccination for the cattle, they fell short of hygiene practices, reliable shade for the cattle and separate space for the claves. The value chain at the milk production stage is characterized by a low production rate, selling raw milk without adding value and a very meager traditional processing practice. Furthermore, small-scale milk processors are characterized by collecting milk from farmers and producing cheese, butter, ghee and sour milk. They do not engage in modern milk processing like pasteurized milk, yogurt and table butter. Most small-scale milk processors are engaged in traditional production systems. Additionally, the milk consumption and marketing part of the chain is dominated by the informal market (channel), where market problems, lack of skill and technology, shortage of loans and weak policy support are being faced as the main challenges. Based on the findings, recommendations and future research areas are forwarded.

Keywords: value-chain, dairy, milk production, milk processing

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Authors: Kaaryn M. Cater

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Students with sensory processing sensitivity (SPS), Meares-Irlen Syndrome (MIS) and dyslexia can become overwhelmed and struggle to thrive in traditional tertiary learning environments. An estimated 50% of tertiary students who disclose learning related issues are dyslexic. This study explores the relationship between SPS, MIS and dyslexia. Baseline measures will be analysed to establish any correlation between these three minority methods of information processing. SPS is an innate sensitivity trait found in 15-20% of the population and has been identified in over 100 species of animals. Humans with SPS are referred to as Highly Sensitive People (HSP) and the measure of HSP is a 27 point self-test known as the Highly Sensitive Person Scale (HSPS). A 2016 study conducted by the author established base-line data for HSP students in a tertiary institution in New Zealand. The results of the study showed that all participating HSP students believed the knowledge of SPS to be life-changing and useful in managing life and study, in addition, they believed that all tutors and in-coming students should be given information on SPS. MIS is a visual processing and perception disorder that is found in approximately 10% of the population and has a variety of symptoms including visual fatigue, headaches and nausea. One way to ease some of these symptoms is through the use of colored lenses or overlays. Dyslexia is a complex phonological based information processing variation present in approximately 10% of the population. An estimated 50% of dyslexics are thought to have MIS. The study exploring possible correlations between these minority forms of information processing is due to begin in February 2017. An invitation will be extended to all first year students enrolled in degree programmes across all faculties and schools within the institution. An estimated 900 students will be eligible to participate in the study. Participants will be asked to complete a battery of on-line questionnaires including the Highly Sensitive Person Scale, the International Dyslexia Association adult self-assessment and the adapted Irlen indicator. All three scales have been used extensively in literature and have been validated among many populations. All participants whose score on any (or some) of the three questionnaires suggest a minority method of information processing will receive an invitation to meet with a learning advisor, and given access to counselling services if they choose. Meeting with a learning advisor is not mandatory, and some participants may choose not to receive help. Data will be collected using the Question Pro platform and base-line data will be analysed using correlation and regression analysis to identify relationships and predictors between SPS, MIS and dyslexia. This study forms part of a larger three year longitudinal study and participants will be required to complete questionnaires at annual intervals in subsequent years of the study until completion of (or withdrawal from) their degree. At these data collection points, participants will be questioned on any additional support received relating to their minority method(s) of information processing. Data from this study will be available by April 2017.

Keywords: dyslexia, highly sensitive person (HSP), Meares-Irlen Syndrome (MIS), minority forms of information processing, sensory processing sensitivity (SPS)

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: Christine H. Cubelo

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This study consists of 2-parts: a systematic review of current publications on the therapeutic use of autonomous sensory meridian response (ASMR) and a within-subjects auditory training trial using ASMR videos. The main intent is to explore ASMR as potentially therapeutically beneficial for those with atypical sensory processing. Many hearing-related disorders and mood or anxiety symptoms overlap with symptoms of sensory processing issues. For this reason, inclusion and exclusion criteria of the systematic review were generated in an effort to produce optimal search outcomes and avoid overly confined criteria that would limit yielded results. Criteria for inclusion in the review for Part 1 are (1) adult participants diagnosed with hearing loss or atypical sensory processing, (2) inclusion of measures related to ASMR as a treatment method, and (3) published between 2000 and 2022. A total of 1,088 publications were found in the preliminary search, and a total of 13 articles met the inclusion criteria. A total of 14 participants completed the trial and post-trial questionnaire. Of all responses, 64.29% agreed that the duration of auditory training sessions was reasonable. In addition, 71.43% agreed that the training improved their perception of music. Lastly, 64.29% agreed that the training improved their perception of a primary talker when there are other talkers or background noises present.

Keywords: autonomous sensory meridian response, auditory training, atypical sensory processing, hearing loss, hearing aids

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Authors: D. Sankara Reddy, T. Kranthi Kumar, K. Sreevani

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This paper investigates the impact of carrier frequency offset (CFO) on the performance of different MIMO-OFDM schemes with high spectral efficiency for next generation of terrestrial digital TV. We show that all studied MIMO-OFDM schemes are sensitive to CFO when it is greater than 1% of intercarrier spacing. We show also that the Alamouti scheme is the most sensitive MIMO scheme to CFO.

Keywords: modulation and multiplexing (MIMO-OFDM), signal processing for transmission carrier frequency offset, future digital TV, imaging and signal processing

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Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Nashwah Alnajjar

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This research paper provides an overview of Replika, an AI chatbot application that uses natural language processing technology to engage in conversations with users. The app was developed to provide users with a virtual AI friend who can converse with them on various topics, including mental health. This study explores the experiences of Replika users using quantitative research methodology. A survey was conducted with 12 participants to collect data on their demographics, usage patterns, and experiences with the Replika app. The results showed that Replika has the potential to play a role in mental health support and well-being.

Keywords: Replika, chatbot, mental health, artificial intelligence, natural language processing

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Authors: Anna Bohers, Emília Hroncová, Juraj Ladomerský

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Oil sludge with its main characteristic of high acidity is a waste product generated from the operation of refinery and petrochemical plants. Former refinery and petrochemical plant - Petrochema Dubová is present in Slovakia as well. Its activities was to process the crude oil through sulfonation and adsorption technology for production of lubricating and special oils, synthetic detergents and special white oils for cosmetic and medical purposes. Seventy years ago – period, when this historical acid sludge burden has been created – comparing to the environmental awareness the production was in preference. That is the reason why, as in many countries, also in Slovakia a historical environmental burden is present until now – 229 211 m3 of oil sludge in the middle of the National Park of Nízke Tatry mountain chain. Neither one of tried treatment methods – bio or non-biologic one - was proved as suitable for processing or for recovery in the reason of different factors admission: i.e. strong aggressivity, difficulty with handling because of its sludgy and liquid state et sim. As a potential solution, also incineration was tested, but it was not proven as a suitable method, as the concentration of SO2 in combustion gases was too high, and it was not possible to decrease it under the acceptable value of 2000 mg.mn-3. That is the reason why the operation of incineration plant has been terminated, and the acid sludge landfills are present until nowadays. The objective of this paper is to present a new possibility of processing and valorization of acid sludgy-waste. The processing of oil sludge was performed through the effective separation - thermal desorption technology, through which it is possible to split the sludgy material into the matrix (soil, sediments) and organic contaminants. In order to boost the efficiency in the processing of acid sludge through thermal desorption, the work will present the possibility of application of an original technology – Method of Blowing Decomposition for recovering of organic matter into technological lubricating oil.

Keywords: hazardous waste, oil sludge, remediation, thermal desorption

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Authors: Brandtner-Hafner Martin

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Biocomposites have established themselves as a sustainable material class in the industry. Their advantages include lower density, lower price, and easier recycling compared to conventional materials. Now there are a variety of ways to measure their technical performance. One possibility is mechanical tests, which are widely used and standardized. However, these provide only very limited insights into damage capacity, which is particularly problematic under cracking conditions. To overcome such shortcomings, experimental tests were performed applying the fracture energetically GF-concept to study the structural safety of the interface under crack opening (mode-I loading). Two different types of biocomposites based on extruded henequen-fibers (NFRP) and wood-particles (WPC) in an HDPE matrix were evaluated. The results show that the fracture energy values obtained are higher than those given in the literature. This suggests that alternatives to previous linear elastic testing methods are needed to perform authentic safety evaluations of green plastics.

Keywords: biocomposites, structural safety, Gғ-concept, fracture analysis

Procedia PDF Downloads 159

Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

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Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

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Authors: Asaolu Olugbenga Stephen, Afolabi Olusegun Temitope

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Lack of proper solid waste management is one of the main causes of environmental pollution and degradation in many cities, especially in developing countries. The aim of this study was to estimate the quantity of waste generated per capita per day, determine the composition and identify the potentials for recycling of waste generated. Characterization of wastes from selected households in the residential areas was done for over a 7 day period. The weight of each sorted category of waste was recorded in a structured database that calculated the proportion of each waste component. The results indicated that 85.4% of the sampled waste characterized was found to be recyclable; with an estimated average waste generated of 1.82kg/capita/day. The various solid waste fractions were organic (64.6%), plastics (15.6%), metals (9.2%), glass materials (1.6%) and unclassified (8.9%). It was concluded from this study that a large proportion of the waste generated from OAU campus residential area was recyclable and that there is a need to enact policy on waste recycling within the university campus.

Keywords: recycling, household wastes, residential, solid waste management

Procedia PDF Downloads 401

Authors: A. Abdouni, C. Thieulin, M. Djaghloul, R. Vargiolu, H. Zahouani

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A decline in the main sensory modalities (vision, hearing, taste, and smell) is well reported to occur with advancing age, it is expected a similar change to occur with touch sensation and perception. In this study, we have focused on the touch sensations highlighting ageing and gender influences with in vivo systems. The touch process can be divided into two main phases: The first phase is the first contact between the finger and the object, during this contact, an adhesive force has been created which is the needed force to permit an initial movement of the finger. In the second phase, the finger mechanical properties with their surface topography play an important role in the obtained sensation. In order to understand the age and gender effects on the touch sense, we develop different ideas and systems for each phase. To better characterize the contact, the mechanical properties and the surface topography of human finger, in vivo studies on the pulp of 40 subjects (20 of each gender) of four age groups of 26±3, 35+-3, 45+-2 and 58±6 have been performed. To understand the first touch phase a classical indentation system has been adapted to measure the finger contact properties. The normal force load, the indentation speed, the contact time, the penetration depth and the indenter geometry have been optimized. The penetration depth of a glass indenter is recorded as a function of the applied normal force. Main assessed parameter is the adhesive force F_ad. For the second phase, first, an innovative approach is proposed to characterize the dynamic finger mechanical properties. A contactless indentation test inspired from the techniques used in ophthalmology has been used. The test principle is to blow an air blast to the finger and measure the caused deformation by a linear laser. The advantage of this test is the real observation of the skin free return without any outside influence. Main obtained parameters are the wave propagation speed and the Young's modulus E. Second, negative silicon replicas of subject’s fingerprint have been analyzed by a probe laser defocusing. A laser diode transmits a light beam on the surface to be measured, and the reflected signal is returned to a set of four photodiodes. This technology allows reconstructing three-dimensional images. In order to study the age and gender effects on the roughness properties, a multi-scale characterization of roughness has been realized by applying continuous wavelet transform. After determining the decomposition of the surface, the method consists of quantifying the arithmetic mean of surface topographic at each scale SMA. Significant differences of the main parameters are shown with ageing and gender. The comparison between men and women groups reveals that the adhesive force is higher for women. The results of mechanical properties show a Young’s modulus higher for women and also increasing with age. The roughness analysis shows a significant difference in function of age and gender.

Keywords: ageing, finger, gender, touch

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Authors: April Hueimin Lu, Liangj-Ju Yao, Jun-Tin Lin, Susan Siru Liu

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This paper discusses the application of aerial survey technology and 3D laser scanning technology in the surveying and mapping work of the settlements and slate houses of the old Taiwanese aborigines. The relics of old Taiwanese aborigines with thousands of history are widely distributed in the deep mountains of Taiwan, with a vast area and inconvenient transportation. When constructing the basic data of cultural assets, it is necessary to apply new technology to carry out efficient and accurate settlement mapping work. In this paper, taking the old Paiwan as an example, the aerial survey of the settlement of about 5 hectares and the 3D laser scanning of a slate house were carried out. The obtained orthophoto image was used as an important basis for drawing the settlement map. This 3D landscape data of topography and buildings derived from the aerial survey is important for subsequent preservation planning as well as building 3D scan provides a more detailed record of architectural forms and materials. The 3D settlement data from the aerial survey can be further applied to the 3D virtual model and animation of the settlement for virtual presentation. The information from the 3D scanning of the slate house can also be used for further digital archives and data queries through network resources. The results of this study show that, in large-scale settlement surveys, aerial surveying technology is used to construct the topography of settlements with buildings and spatial information of landscape, as well as the application of 3D scanning for small-scale records of individual buildings. This application of 3D technology, greatly increasing the efficiency and accuracy of survey and mapping work of aboriginal settlements, is much helpful for further preservation planning and rejuvenation of aboriginal cultural heritage.

Keywords: aerial survey, 3D scanning, aboriginal settlement, settlement architecture cluster, ecological landscape area, old Paiwan settlements, slat house, photogrammetry, SfM, MVS), Point cloud, SIFT, DSM, 3D model

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Authors: Vadanasundari Vedarethinam, Kun Qian

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The metabolic analysis is more distal over proteomics and genomics engaging in clinics and needs rationally distinct techniques, designed materials, and device for clinical diagnosis. Conventional techniques such as spectroscopic techniques, biochemical analyzers, and electrochemical have been used for metabolic diagnosis. Currently, there are four major challenges including (I) long-term process in sample pretreatment; (II) difficulties in direct metabolic analysis of biosamples due to complexity (III) low molecular weight metabolite detection with accuracy and (IV) construction of diagnostic tools by materials and device-based platforms for real case application in biomedical applications. Development of chips with nanomaterial is promising to address these critical issues. Mass spectroscopy (MS) has displayed high sensitivity and accuracy, throughput, reproducibility, and resolution for molecular analysis. Particularly laser desorption/ ionization mass spectrometry (LDI MS) combined with devices affords desirable speed for mass measurement in seconds and high sensitivity with low cost towards large scale uses. We developed a plasmonic chip for clinical metabolic fingerprinting as a hot carrier in LDI MS by series of chips with gold nanoshells on the surface through controlled particle synthesis, dip-coating, and gold sputtering for mass production. We integrated the optimized chip with microarrays for laboratory automation and nanoscaled experiments, which afforded direct high-performance metabolic fingerprinting by LDI MS using 500 nL of serum, urine, cerebrospinal fluids (CSF) and exosomes. Further, we demonstrated on-chip direct in-vitro metabolic diagnosis of early-stage lung cancer patients using serum and exosomes without any pretreatment or purifications. To our best knowledge, this work initiates a bionanotechnology based platform for advanced metabolic analysis toward large-scale diagnostic use.

Keywords: plasmonic chip, metabolic fingerprinting, LDI MS, in-vitro diagnostics

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Authors: D. M. Eric, D. Milosevic, F. D. Eric

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Concurrent engineering technologies are a modern concept in manufacturing engineering. One of the key goals in designing modern technological processes is further reduction of production costs, both in the prototype and the preparatory part, as well as during the serial production. Thanks to many segments of concurrent engineering, these goals can be accomplished much more easily. In this paper, we give an overview of the advantages of using modern software simulations in relation to the classical aspects of designing technological processes of metal deformation. Significant savings are achieved thanks to the electronic simulation and software detection of all possible irregularities in the functional-working regime of the technological process. In order for the expected results to be optimal, it is necessary that the input parameters are very objective and that they reliably represent the values ​of these parameters in real conditions. Since it is a metal deformation treatment here, the particularly important parameters are the coefficient of internal friction between the working material and the tools, as well as the parameters related to the flow curve of the processing material. The paper will give a presentation for the experimental determination of some of these parameters.

Keywords: production technologies, metal processing, software simulations, effects of application

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Authors: Mouheb Mehdoui, Amel Fraisse, Mounir Zrigui

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This paper explores the potential of short texts through semantic enrichment and disambiguation techniques. By employing context fusion, we aim to enhance the comprehension and utility of concise textual information. The methodologies utilized are grounded in recent advancements in natural language processing, which allow for a deeper understanding of semantics within limited text formats. Specifically, topic classification is employed to understand the context of the sentence and assess the relevance of added expressions. Additionally, word sense disambiguation is used to clarify unclear words, replacing them with more precise terms. The implications of this research extend to various applications, including information retrieval and knowledge representation. Ultimately, this work highlights the importance of refining short text processing techniques to unlock their full potential in real-world applications.

Keywords: information traffic, text summarization, word-sense disambiguation, semantic enrichment, ambiguity resolution, short text enhancement, information retrieval, contextual understanding, natural language processing, ambiguity

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Authors: Beatriz Rebocho, Elisabete Valente, Carla Palma, Andreia Guilherme, Filipa Bessa, Paula Sobral

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The global accumulation of plastic in the oceans is a growing problem. Plastic is transported from its source to the oceans via rivers, which are considered the main route for plastic particles from land-based sources to the ocean. These plastics undergo physical and chemical degradation resulting in microplastics. The i-Plastic project aims to understand and predict the dispersion, accumulation and impacts of microplastics (5 mm to 1 µm) and nano plastics (below 1 µm) in marine environments from the tropical and temperate land-ocean interface to the open ocean under distinct flow and climate regimes. Seasonal monitoring of the fluxes of microplastics was carried out in (three) coastal areas in Brazil, Portugal and Spain. The present work shows the first results of in-situ seasonal monitoring and mapping of microplastics in ocean waters between Ovar and Vieira de Leiria (Portugal), in which 43 surface water samples and 43 water column samples were collected in contrasting seasons (spring and autumn). The spring and autumn surface water samples were collected with a 300 µm and 150 µm pore neuston net, respectively. In both campaigns, water column samples were collected using a conical mesh with a 150 µm pore. The experimental procedure comprises the following steps: i) sieving by a metal sieve; ii) digestion with potassium hydroxide to remove the organic matter original from the sample matrix. After a filtration step, the content is retained on a membrane and observed under a stereomicroscope, and physical and chemical characterization (type, color, size, and polymer composition) of the microparticles is performed. Results showed that 84% and 88% of the surface water and water column samples were contaminated with microplastics, respectively. Surface water samples collected during the spring campaign averaged 0.35 MP.m-3, while surface water samples collected during autumn recorded 0.39 MP.m-3. Water column samples from the spring campaign had an average of 1.46 MP.m-3, while those from the autumn recorded 2.54 MP.m-3. In the spring, all microplastics found were fibers, predominantly black and blue. In autumn, the dominant particles found in the surface waters were fibers, while in the water column, fragments were dominant. In spring, the average size of surface water particles was 888 μm, while in the water column was 1063 μm. In autumn, the average size of surface and water column microplastics was 1333 μm and 1393 μm, respectively. The main polymers identified by Attenuated Total Reflectance (ATR) and micro-ATR Fourier Transform Infrared (FTIR) spectroscopy from all samples were low-density polyethylene (LDPE), polypropylene (PP), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The significant difference between the microplastic concentration in the water column between the two campaigns could be due to the remixing of the water masses that occurred that week due to the occurrence of a storm. This work presents preliminary results since the i-Plastic project is still in progress. These results will contribute to the understanding of the spatial and temporal dispersion and accumulation of microplastics in this marine environment.

Keywords: microplastics, Portugal, Atlantic Ocean, water column, surface water

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Authors: V. E. Messerle, A. L. Mosse, O. A. Lavrichshev, A. N. Nikonchuk, A. B. Ustimenko

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One of the most serious environmental problems today is pollution by biomedical waste (BMW), which in most cases has undesirable properties such as toxicity, carcinogenicity, mutagenicity, fire. Sanitary and hygienic survey of typical solid BMW, made in Belarus, Kazakhstan, Russia and other countries shows that their risk to the environment is significantly higher than that of most chemical wastes. Utilization of toxic BMW requires use of the most universal methods to ensure disinfection and disposal of any of their components. Such technology is a plasma technology of BMW processing. To implement this technology a thermodynamic analysis of the plasma processing of BMW was fulfilled and plasma-box furnace was developed. The studies have been conducted on the example of the processing of bone. To perform thermodynamic calculations software package Terra was used. Calculations were carried out in the temperature range 300 - 3000 K and a pressure of 0.1 MPa. It is shown that the final products do not contain toxic substances. From the organic mass of BMW synthesis gas containing combustible components 77.4-84.6% was basically produced, and mineral part consists mainly of calcium oxide and contains no carbon. Degree of gasification of carbon reaches 100% by the temperature 1250 K. Specific power consumption for BMW processing increases with the temperature throughout its range and reaches 1 kWh/kg. To realize plasma processing of BMW experimental installation with DC plasma torch of 30 kW power was developed. The experiments allowed verifying the thermodynamic calculations. Wastes are packed in boxes weighing 5-7 kg. They are placed in the box furnace. Under the influence of air plasma flame average temperature in the box reaches 1800 OC, the organic part of the waste is gasified and inorganic part of the waste is melted. The resulting synthesis gas is continuously withdrawn from the unit through the cooling and cleaning system. Molten mineral part of the waste is removed from the furnace after it has been stopped. Experimental studies allowed determining operating modes of the plasma box furnace, the exhaust gases was analyzed, samples of condensed products were assembled and their chemical composition was determined. Gas at the outlet of the plasma box furnace has the following composition (vol.%): CO - 63.4, H2 - 6.2, N2 - 29.6, S - 0.8. The total concentration of synthesis gas (CO + H2) is 69.6%, which agrees well with the thermodynamic calculation. Experiments confirmed absence of the toxic substances in the final products.

Keywords: biomedical waste, box furnace, plasma torch, processing, synthesis gas

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Authors: Jalal Karam

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The methods of Fourier, Laplace, and Wavelet Transforms provide transfer functions and relationships between the input and the output signals in linear time invariant systems. This paper shows the equivalence among these three methods and in each case presenting an application of the appropriate (Fourier, Laplace or Wavelet) to the convolution theorem. In addition, it is shown that the same holds for a direct integration method. The Biorthogonal wavelets Bior3.5 and Bior3.9 are examined and the zeros distribution of their polynomials associated filters are located. This paper also presents the significance of utilizing wavelets as effective tools in processing speech signals for common multimedia applications in general, and for recognition and compression in particular. Theoretically and practically, wavelets have proved to be effective and competitive. The practical use of the Continuous Wavelet Transform (CWT) in processing and analysis of speech is then presented along with explanations of how the human ear can be thought of as a natural wavelet transformer of speech. This generates a variety of approaches for applying the (CWT) to many paradigms analysing speech, sound and music. For perception, the flexibility of implementation of this transform allows the construction of numerous scales and we include two of them. Results for speech recognition and speech compression are then included.

Keywords: continuous wavelet transform, biorthogonal wavelets, speech perception, recognition and compression

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Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

Abstract:

Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

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Authors: Cherry Yieng Siang Ling, Joong Hee Lee, Myung Hwan Yun

Abstract:

The quality of a product to be usable has become the basic requirement in consumer’s perspective while failing the requirement ends up the customer from not using the product. Identifying usability issues from analyzing quantitative and qualitative data collected from usability testing and evaluation activities aids in the process of product design, yet the lack of studies and researches regarding analysis methodologies in qualitative text data of usability field inhibits the potential of these data for more useful applications. While the possibility of analyzing qualitative text data found with the rapid development of data analysis studies such as natural language processing field in understanding human language in computer, and machine learning field in providing predictive model and clustering tool. Therefore, this research aims to study the application capability of text processing algorithm in analysis of qualitative text data collected from usability activities. This research utilized datasets collected from LG neckband headset usability experiment in which the datasets consist of headset survey text data, subject’s data and product physical data. In the analysis procedure, which integrated with the text-processing algorithm, the process includes training of comments onto vector space, labeling them with the subject and product physical feature data, and clustering to validate the result of comment vector clustering. The result shows 'volume and music control button' as the usability feature that matches best with the cluster of comment vectors where centroid comments of a cluster emphasized more on button positions, while centroid comments of the other cluster emphasized more on button interface issues. When volume and music control buttons are designed separately, the participant experienced less confusion, and thus, the comments mentioned only about the buttons' positions. While in the situation where the volume and music control buttons are designed as a single button, the participants experienced interface issues regarding the buttons such as operating methods of functions and confusion of functions' buttons. The relevance of the cluster centroid comments with the extracted feature explained the capability of text processing algorithms in analyzing qualitative text data from usability testing and evaluations.

Keywords: usability, qualitative data, text-processing algorithm, natural language processing

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Authors: Duckyong Kim, Jong Kang Park, Jong Tae Kim

Abstract:

DOA (Direction of Arrival) estimation is an important method in array signal processing and has a wide range of applications such as direction finding, beam forming, and so on. In this paper, we briefly introduce the MUSIC (Multiple Signal Classification) Algorithm, one of DOA estimation methods for analyzing several targets. Then we apply the MUSIC algorithm to the two-dimensional antenna array to analyze DOA estimation in 3D space through MATLAB simulation. We also analyze the design factors that can affect the accuracy of DOA estimation through simulation, and proceed with further consideration on how to apply the system.

Keywords: DOA estimation, MUSIC algorithm, spatial spectrum, array signal processing

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Authors: Khanh D.Do, Loi V.Nguyen, Thanh N.Nguyen, Thang M.Nguyen, Vu T.Tran

Abstract:

Along with the development of Secondary surveillance radar (SSR) in air traffic surveillance systems, the Multipath phenomena has always been a noticeable problem. This following article discusses the geometrical aspect and power aspect of the Multipath interference caused by reflection in SSR and proposes a method to deal with these unwanted multipath targets (ghosts) by false-target position predicting and adaptive target suppressing. A field-experiment example is mentioned at the end of the article to demonstrate the efficiency of this measure.

Keywords: multipath, secondary surveillance radar, digital signal processing, reflection

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Authors: Su Yin Chiam, Qing Xin Zhang, Jaehoon Chung

Abstract:

Complementary metal-oxide-semiconductor (CMOS) integrated circuits (ICs) have obtained increased attention in the biosensor community because CMOS technology provides cost-effective and high-performance signal processing at a mass-production level. In order to supply biological samples and reagents effectively to the sensing elements, there are increasing demands for seamless integration of microfluidic components on the fabricated CMOS wafers by post-processing. Although the PDMS microfluidic channels replicated from separately prepared silicon mold can be typically aligned and bonded onto the CMOS wafers, it remains challenging owing the inherently limited aligning accuracy ( > ± 10 μm) between the two layers. Here we present a new post-processing method to create three-dimensional microfluidic components using two different polarities of photoresists, an epoxy-based negative SU-8 photoresist and positive SPR220-7 photoresist. The positive photoresist serves as a sacrificial layer and the negative photoresist was utilized as a structural material to generate three-dimensional structures. Because both photoresists are patterned using a standard photolithography technology, the dimensions of the structures can be effectively controlled as well as the alignment accuracy, moreover, is dramatically improved (< ± 2 μm) and appropriately can be adopted as an alternative post-processing method. To validate the proposed processing method, we applied this technique to build cell-trapping structures. The SU8 photoresist was mainly used to generate structures and the SPR photoresist was used as a sacrificial layer to generate sub-channel in the SU8, allowing fluid to pass through. The sub-channel generated by etching the sacrificial layer works as a cell-capturing site. The well-controlled dimensions enabled single-cell capturing on each site and high-accuracy alignment made cells trapped exactly on the sensing units of CMOS biosensors.

Keywords: SU-8, microfluidic, MEMS, microfabrication

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Authors: Francis Ojo Ologunagba, Monday Olatunbosun Ale, Lewis A. Olutayo

Abstract:

The economic successes of commercial development of agricultural product processing depend upon the adaptability of each processing stage to mechanization. In maize processing, one of its post-harvest operations that is still facing a major challenge is dehusking. Therefore, a maize dehusking machine that could replace the prevalent traditional method of dehusking maize in developing countries, especially Nigeria was designed, constructed and tested at the Department of Agricultural and Bio-Environmental Engineering Technology, Rufus Giwa Polytechnic, Owo. The basic features of the machine are feeding unit (hopper), housing frame, dehusking unit, drive mechanism and discharge outlets. The machine was tested with maize of 50mm average diameter at 13% moisture content and 2.5mm machine roller clearance. Test results showed appreciable performance with the dehusking efficiency of 92% and throughput capacity of 200 Kg/hr at a machine speed of 400rpm. The estimated production cost of the machine at the time of construction is forty-five thousand, one hundred and eighty nairas (₦45,180) excluding the cost of the electric motor. It is therefore recommended for small and medium-scale maize farmers and processors in Nigeria.

Keywords: construction, dehusking, design, efficiency, maize

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Authors: Archit Yajnik

Abstract:

Part of Speech Tagging has always been a challenging task in the era of Natural Language Processing. This article presents POS tagging for Nepali text using Hidden Markov Model and Viterbi algorithm. From the Nepali text, annotated corpus training and testing data set are randomly separated. Both methods are employed on the data sets. Viterbi algorithm is found to be computationally faster and accurate as compared to HMM. The accuracy of 95.43% is achieved using Viterbi algorithm. Error analysis where the mismatches took place is elaborately discussed.

Keywords: hidden markov model, natural language processing, POS tagging, viterbi algorithm

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Authors: Abdulkader Helwan

Abstract:

Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Sehreen Moorat, Mussarat Lakho

Abstract:

A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: Pooya Niksiar, Ali Ashrafizadeh, Mehrzad Shams, Amir Hossein Madani

Abstract:

There are many computationally demanding applications in science and engineering which need efficient algorithms implemented on high performance computers. Recently, Graphics Processing Units (GPUs) have drawn much attention as compared to the traditional CPU-based hardware and have opened up new improvement venues in scientific computing. One particular application area is Computational Fluid Dynamics (CFD), in which mature CPU-based codes need to be converted to GPU-based algorithms to take advantage of this new technology. In this paper, numerical solutions of two classes of discrete fluid flow models via both CPU and GPU are discussed and compared. Test problems include an Eulerian model of a two-dimensional incompressible laminar flow case and a Lagrangian model of a two phase flow field. The CUDA programming standard is used to employ an NVIDIA GPU with 480 cores and a C++ serial code is run on a single core Intel quad-core CPU. Up to two orders of magnitude speed up is observed on GPU for a certain range of grid resolution or particle numbers. As expected, Lagrangian formulation is better suited for parallel computations on GPU although Eulerian formulation represents significant speed up too.

Keywords: CFD, Eulerian formulation, graphics processing units, Lagrangian formulation

Procedia PDF Downloads 417