Search results for: waste processing

Authors: Rahul Srivastava, Priti Pundir, Y. R. Sood, Rajnish Shrivastava

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For the interpretation of the signatures of sweep frequency response analysis(SFRA) of transformer different types of statistical techniques serves as an effective tool for doing either phase to phase comparison or sister unit comparison. In this paper with the discussion on SFRA several statistics techniques like cross correlation coefficient (CCF), root square error (RSQ), comparative standard deviation (CSD), Absolute difference, mean square error(MSE),Min-Max ratio(MM) are presented through several case studies. These methods require sample data size and spot frequencies of SFRA signatures that are being compared. The techniques used are based on power signal processing tools that can simplify result and limits can be created for the severity of the fault occurring in the transformer due to several short circuit forces or due to ageing. The advantages of using statistics techniques for analyzing of SFRA result are being indicated through several case studies and hence the results are obtained which determines the state of the transformer.

Keywords: absolute difference (DABS), cross correlation coefficient (CCF), mean square error (MSE), min-max ratio (MM-ratio), root square error (RSQ), standard deviation (CSD), sweep frequency response analysis (SFRA)

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Authors: Mulubrhan Berihu, Supratic Gupta, Zena Gebriel

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Due to the design versatility, availability, and cost efficiency, concrete is continuing to be the most used construction material on earth. However, the production of Portland cement, the primary component of concrete mix is causing to have a serious effect on environmental and economic impacts. This shows there is a need to study using of supplementary cementitious materials (SCMs). The most commonly used supplementary cementitious materials are wastes and the use of these industrial waste products has technical, economical and environmental benefits besides the reduction of CO2 emission from cement production. The study aims to document the effect on strength property of concrete due to use of low cement by maximizing supplementary cementitious materials like fly ash or marble powder. Based on the different mix proportion of pozzolana and marble powder a range of mix design was formulated. The first part of the project is to study the strength of low cement concrete using fly ash replacement experimentally. The test results showed that using up to 85 kg/m3 of cement is possible for plain concrete works like hollow block concrete to achieve 9.8 Mpa and the experimental results indicates that strength is a function of w/b. In the second part a new set of mix design has been carried out with fly ash and marble powder to study the strength of both binary and ternary mixes. In this experimental study, three groups of mix design (c+FA, c+FA+m and c+m), four sets of mixes for each group were taken up. Experimental results show that c+FA has maintained the best strength and impermeability whereas c+m obtained less compressive strength, poorer permeability and split tensile strength. c+FA shows a big difference in gaining of compressive strength from 7 days to 28 days compression strength compared to others and this obviously shows the slow rate of hydration of fly ash concrete. As the w/b ratio increases the strength decreases significantly. At the same time higher permeability has been seen in the specimens which were tested for three hours than one hour.

Keywords: efficiency factor, cement content, compressive strength, mix proportion, w/c ratio, water permeability, SCMs

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Authors: Niladri Sekhar Barma, Satish Dhandole

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Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.

Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification

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Authors: Stefan Wagenpfeil, Felix Engel, Paul McKevitt, Matthias Hemmje

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Multimedia Indexing and Retrieval is generally designed and implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results but also leads to more complex graph structures. However, graph-traversal-based algorithms for similarity are quite inefficient and computation intensive, especially for large data structures. To deliver fast and effective retrieval, an efficient similarity algorithm, particularly for large graphs, is mandatory. Hence, in this paper, we define a graph-projection into a 2D space (Graph Code) as well as the corresponding algorithms for indexing and retrieval. We show that calculations in this space can be performed more efficiently than graph-traversals due to a simpler processing model and a high level of parallelization. In consequence, we prove that the effectiveness of retrieval also increases substantially, as Graph Codes facilitate more levels of detail in feature fusion. Thus, Graph Codes provide a significant increase in efficiency and effectiveness (especially for Multimedia indexing and retrieval) and can be applied to images, videos, audio, and text information.

Keywords: indexing, retrieval, multimedia, graph algorithm, graph code

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Authors: C. Benhamideche

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Fluoroaluminate glasses have been reported as the earliest heavy metal fluoride glasses. By comparison with flurozirconate glasses, they offer a set of similar optical features, but also some differences in their elastic and chemical properties. In practice they have been less developed because their stability against devitrification is smaller than that of the most stable fluoroziconates. The purpose of this study was to investigate glass formation in systems AlF3-YF3-PbF2-MgF2-MF2 (M= Li, Na, K). Synthesis was implemented at room atmosphere using the ammonium fluoride processing. After fining, the liquid was into a preheated brass mold, then annealed below the glass transition temperature for several hours. The samples were polished for optical measurements. Glass formation has been investigated in a systematic way, using pseudo ternary systems in order to allow parameters to vary at the same time. We have chosen the most stable glass compositions for the determination of the physical properties. These properties including characteristic temperatures, density and proprieties elastic. Glass stability increases in multicomponent glasses. Bulk samples have been prepared for physical characterization. These glasses have a potential interest for passive optical fibers because they are less sensitive to water attack than ZBLAN glass, mechanically stronger. It is expected they could have a larger damage threshold for laser power transmission.

Keywords: fluoride glass, aluminium fluoride, thermal properties, density, proprieties elastic

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Authors: Paschal A. Ubi, Salawu Abdul Rahman Asipita

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The use of suitable engineering materials which poses less harm to ,an and the environment is sort for in recent times, thus giving rise to polymer composites filled with natural organic reinforcement which are biodegradable. Treatment of natural fibres is essential in improving matrix to filler adhesion, hence improving its mechanical properties. In this study, investigations were carried out to determine the effect of sodium hydroxide treatment on the tensile, flexural, impact and hardness properties of crushed and uncrushed luffa cylindrica fibre reinforced recycled low density polyethylene composites. The LC (Luffa Cylindrica) fibres were treated with 0%, 2%, 4%, 6%, 8%, and 10% wt. NaOH concentrations for a period of 24 hours under room temperature conditions. The compounding of the waste LDPE was done using a two roll mill at a temperature of 150 oC and cured in a hydraulic press at a temperature of 150oC for 3 minutes at 3 metric tonnes. A formulation of 20/80g (reinforcement to matrix ratio in grams) was maintained for all fabricated samples. Analysis of the results showed that the uncrushed luffa fibre samples gave better mechanical properties compared with the crushed luffa fibre samples. The uncrushed luffa fibre composites had optimum tensile and flexural strengths of 7.65MPa and 17.08Mpa respectively corresponding to a young modulus and flexural modulus of 21.08MPa and 232.22MPa for the 8% and 4%wt. NaOH concentration respectively. Results obtained in the research showed that NaOH treatment with the 8% NaOH concentration improves the mechanical properties of the LC fibre reinforced composites when compared with other NaOH treatment concentration values.

Keywords: LC fibres, NaOH concentration, LC/rLDPE composite, tensile strength, flexural strength

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Authors: Junaid Asimiyu Mohammed, Olakunle Docas Tosin

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The housing environment in many developing countries is fraught with risks that have potential negative impacts on the lives of the residents. The study examined the risk factors in residential areas of two neighborhoods in Bosso Local Government Areas of Minna in Nigeria with a view to determining the level of their potential impacts. A sample of 378 households was drawn from the estimated population of 22,751 household heads. The questionnaire and direct observation were used as instruments for data collection. The data collected were analyzed using the Relative Importance Index (RII) rule to determine the level of the potential impact of the risk factors while ArcGIS was used for mapping the spatial distribution of the risks. The study established that the housing environment of Angwan Biri and El-Waziri areas of Bosso is poor and vulnerable as 26% of the houses were not habitable and 57% were only fairly habitable. The risks of epidemics, building collapse and rainstorms were evident in the area as 53% of the houses had poor ventilation; 20% of residents had no access to toilets; 47% practiced open waste dumping; 46% of the houses had cracked walls while 52% of the roofs were weak and sagging. The results of the analysis of the potential impact of the risk factors indicate a RII score of 0.528 for building collapse, 0.758 for rainstorms and 0.830 for epidemics, indicating a moderate to very high level of potential impacts. The mean RII score of 0.639 shows a significant potential impact of the risk factors. The study recommends the implementation of sanitation measures, provision of basic urban facilities and neighborhood revitalization through housing infrastructure retrofitting as measures to mitigate the risks of disasters and improve the living conditions of the residents of the study area.

Keywords: assessment, risk, residential, Nigeria

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Authors: Aelina Franz

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In recent years, the scientific community has witnessed a paradigm shift in the exploration of unconventional levitation methods, particularly in the domain of spherical combat platforms. This paper explores aerodynamics and levitational dynamics inherent in these spheres by examining interactions at the quantum level. Our research unravels the nuanced aerodynamic phenomena governing the levitation of spherical combat platforms. Through an analysis of the quantum fluid dynamics surrounding these spheres, we reveal the crucial interactions between air resistance, surface irregularities, and the quantum fluctuations that influence their levitational behavior. Our findings challenge conventional understanding, providing a perspective on the aerodynamic forces at play during the levitation of spherical combat platforms. Furthermore, we propose design modifications and control strategies informed by both classical aerodynamics and quantum information processing principles. These advancements not only enhance the stability and maneuverability of the combat platforms but also open new avenues for exploration in the interdisciplinary realm of engineering and quantum information sciences. This paper aims to contribute to levitation technologies and their applications in the field of spherical combat platforms. We anticipate that our work will stimulate further research to create a deeper understanding of aerodynamics and quantum phenomena in unconventional levitation systems.

Keywords: spherical combat platforms, levitation technologies, aerodynamics, maneuverable platforms

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Authors: Shi-Yu Xu

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The top three risk factors that have contributed to building collapses during past earthquake events in Taiwan are: "irregular floor plans or elevations," "insufficient columns in single-bay buildings," and the "weak-story problem." Fortunately, these unsound structural characteristics can be directly identified from the floor plans. However, due to the vast number of old buildings, conducting manual inspections to identify these compromised structural features in all existing structures would be time-consuming and prone to human errors. This study aims to develop an algorithm that utilizes artificial intelligence techniques to automatically pinpoint the structural components within a building's floor plans. The obtained spatial information will be utilized to construct a digital structural model of the building. This information, particularly regarding the distribution of columns in the floor plan, can then be used to conduct preliminary seismic assessments of the building. The study employs various image processing and pattern recognition techniques to enhance detection efficiency and accuracy. The study enables a large-scale evaluation of structural vulnerability for numerous old buildings, providing ample time to arrange for structural retrofitting in those buildings that are at risk of significant damage or collapse during earthquakes.

Keywords: structural vulnerability detection, object recognition, seismic capacity assessment, old buildings, artificial intelligence

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Usama Mohamed, Sam Booth, Aliysn J. Nedoma

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As part of the transition to electric vehicles, there has been a recent increase in demand for battery manufacturing. Cathodes typically account for approximately 50% of the total lithium-ion battery cell cost and are a pivotal factor in determining the viability of new industrial infrastructure. Cathodes which offer lower costs whilst maintaining or increasing performance, such as nickel-rich layered cathodes, have a significant competitive advantage when scaling up the manufacturing process. This project evaluates the techno-economic value proposition of an integrated industrial scale cathode active material (CAM) production process, closing the mass and energy balances, and optimizing the operation conditions using a sensitivity analysis. This is done by developing a process model of a co-precipitation synthesis route using Aspen Plus software and validated based on experimental data. The mechanism chemistry and equilibrium conditions were established based on previous literature and HSC-Chemistry software. This is then followed by integrating the energy streams, adding waste recovery and treatment processes, as well as testing the effect of key parameters (temperature, pH, reaction time, etc.) on CAM production yield and emissions. Finally, an economic analysis estimating the fixed and variable costs (including capital expenditure, labor costs, raw materials, etc.) to calculate the cost of CAM ($/kg and $/kWh), total plant cost ($) and net present value (NPV). This work sets the foundational blueprint for future research into sustainable industrial scale processes for CAM manufacturing.

Keywords: cathodes, industrial production, nickel-rich layered cathodes, process modelling, techno-economic analysis

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Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio

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This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.

Keywords: contour orientation histogram, meteors, night sky, RSC neural classifier, stars

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Authors: Xiang Shijie, Zhou Dong, Tian Dan

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Speaker recognition is a crucial task in the field of speech processing, aimed at identifying individuals based on their vocal characteristics. However, existing speaker recognition methods face numerous challenges. Traditional methods primarily rely on audio signals, which often suffer from limitations in noisy environments, variations in speaking style, and insufficient sample sizes. Additionally, relying solely on audio features can sometimes fail to capture the unique identity of the speaker comprehensively, impacting recognition accuracy. To address these issues, we propose a multi-modal network architecture that simultaneously processes both audio and text signals. By gradually integrating audio and text features, we leverage the strengths of both modalities to enhance the robustness and accuracy of speaker recognition. Our experiments demonstrate significant improvements with this multi-modal approach, particularly in complex environments, where recognition performance has been notably enhanced. Our research not only highlights the limitations of current speaker recognition methods but also showcases the effectiveness of multi-modal fusion techniques in overcoming these limitations, providing valuable insights for future research.

Keywords: feature fusion, memory network, multimodal input, speaker recognition

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Authors: Halil Ibrahim Demir, Caner Erden, Abdullah Hulusi Kokcam, Mumtaz Ipek

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Process planning, scheduling, and due date assignment are three important manufacturing functions which are studied independently in literature. There are hundreds of works on IPPS and SWDDA problems but a few works on IPPSDDA problem. Integrating these three functions is very crucial due to the high relationship between them. Since the scheduling problem is in the NP-Hard problem class without any integration, an integrated problem is even harder to solve. This study focuses on the integration of these functions. Sum of weighted tardiness, earliness, and due date related costs are used as a penalty function. Random search and hybrid metaheuristics are used to solve the integrated problem. Marginal improvement in random search is very high in the early iterations and reduces enormously in later iterations. At that point directed search contribute to marginal improvement more than random search. In this study, random and genetic search methods are combined to find better solutions. Results show that overall performance becomes better as the integration level increases.

Keywords: process planning, genetic algorithm, hybrid search, random search, weighted due-date assignment, weighted scheduling

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Authors: Dessie Tibebe, Muluken Asmare, Marye Mulugeta, Yezbie Kassa, Zerubabel Moges, Dereje Yenealem, Tarekegn Fentie, Agmas Amare

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The performance of electrocoagulation (EC) using Aluminium electrodes for the treatment of effluent-containing chromium metal using a fixed bed electrochemical batch reactor was studied. In the present work, the efficiency evaluation of EC in removing physicochemical and heavy metals from real industrial tannery wastewater in the Amhara region, collected from Bahirdar, Debre Brihan, and Haik, was investigated. The treated and untreated samples were determined by AAS and ICP OES spectrophotometers. The results indicated that selected heavy metals were removed in all experiments with high removal percentages. The optimal results were obtained regarding both cost and electrocoagulation efficiency with initial pH = 3, initial concentration = 40 mg/L, electrolysis time = 30 min, current density = 40 mA/cm2, and temperature = 25oC favored metal removal. The maximum removal percentages of selected metals obtained were 84.42% for Haik, 92.64% for Bahir Dar and 94.90% for Debre Brihan. The sacrificial electrode and sludge were characterized by FT-IR, SEM and XRD. After treatment, some metals like chromium will be used again as a tanning agent in leather processing to promote a circular economy.

Keywords: electrochemical, treatment, aluminum, tannery effluent

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Authors: Mehrnoosh Ghadimi, Golnoush Ghadimi

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Precise monitoring of glacier velocity is critical in determining glacier-related hazards. Zardkooh Mountain was studied in terms of glacial activity rate in Zagros Mountainous region in Iran. In this study, we assessed the ability of optical and radar imagery to derive glacier-surface velocities in mountainous terrain. We processed Landsat 8 for optical data and Sentinel-1a for radar data. We used methods that are commonly used to measure glacier surface movements, such as cross correlation of optical and radar satellite images, SAR tracking techniques, and multiple aperture InSAR (MAI). We also assessed time series glacier surface displacement using our modified method, Enhanced Small Baseline Subset (ESBAS). The ESBAS has been implemented in StaMPS software, with several aspects of the processing chain modified, including filtering prior to phase unwrapping, topographic correction within three-dimensional phase unwrapping, reducing atmospheric noise, and removing the ramp caused by ionosphere turbulence and/or orbit errors. Our findings indicate an average surface velocity rate of 32 mm/yr in the Zardkooh mountainous areas.

Keywords: active rock glaciers, landsat 8, sentinel-1a, zagros mountainous region

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Authors: Ouafa Benaida, Abdelhamid Loukil, Adda Ali Pacha

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In recent years, the growing interest of scientists in the field of image processing and analysis of underwater images and videos has been strengthened following the emergence of new underwater exploration techniques, such as the emergence of autonomous underwater vehicles and the use of underwater image sensors facilitating the exploration of underwater mineral resources as well as the search for new species of aquatic life by biologists. Indeed, underwater images and videos have several defects and must be preprocessed before their analysis. Underwater landscapes are usually darkened due to the interaction of light with the marine environment: light is absorbed as it travels through deep waters depending on its wavelength. Additionally, light does not follow a linear direction but is scattered due to its interaction with microparticles in water, resulting in low contrast, low brightness, color distortion, and restricted visibility. The improvement of the underwater image is, therefore, more than necessary in order to facilitate its analysis. The research presented in this paper aims to implement and evaluate a set of classical techniques used in the field of improving the quality of underwater images in several color representation spaces. These methods have the particularity of being simple to implement and do not require prior knowledge of the physical model at the origin of the degradation.

Keywords: underwater image enhancement, histogram normalization, histogram equalization, contrast limited adaptive histogram equalization, single-scale retinex

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Authors: Carolina Gouveia, José Vieira, Pedro Pinho

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The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: bio-signals, DC component, Doppler effect, ellipse fitting, radar, SDR

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Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

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In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

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Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

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In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

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Authors: Aawag Mohsen Al-Awag, Wesam Salah Alaloul, M. S. Liew

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Industrialized building system (IBS) is a method of construction with concentrated practices consisting of techniques, products, and a set of linked elements which operate collectively to accomplish objectives. The Industrialised Building System (IBS) has been recognised as a viable method for improving overall construction performance in terms of quality, cost, safety and health, waste reduction, and productivity. The Malaysian construction industry is considered one of the contributors to the development of the country. The acceptance level of IBS is still below government expectations. Thus, the Malaysian government has been continuously encouraging the industry to use and implement IBS. Conventional systems have several drawbacks, including project delays, low economic efficiency, excess inventory, and poor product quality. When it comes to implementing IBS, construction companies still face several obstacles and problems, notably in terms of contractual and procurement concerns, which leads to the low adoption of IBS in Malaysia. There are barriers to the acceptance of IBS technology, focused on awareness of historical failure and risks connected to IBS practices to provide enhanced performance. Therefore, the transformation from the existing conventional building systems to the industrialized building systems (IBS) is needed more than ever. The flexibility of IBS in Malaysia’s construction industry is very low due to numerous shortcomings and obstacles. Due to its environmental, economic, and social benefits, IBS could play a significant role in the Malaysian construction industry in the future. This paper concentrates on the potential role of IBS in sustainable construction practices in Malaysia. It also highlights the awareness, barriers, advantages, and disadvantages of IBS in the construction sector. The study concludes with recommendations for Malaysian construction stakeholders to encourage and increase the utilization of industrialised building systems.

Keywords: construction industry, industrialized building system, barriers, advantages and disadvantages, construction, sustainability, Malaysia

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Authors: Amir Amiri, Naghmeh Morakabati

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During the recent years the six-fold growth of cancer in Iran has led the production of healthy products to become a challenge in the food industry. Due to the young population in the country, the consumption of fast foods is growing. The chemical cancer-causing preservatives are used to produce these products more than the standard; so using an appropriate alternative seems to be important. On the one hand, the plant essential oils show the high antimicrobial potential against pathogenic and spoilage microorganisms and on the other hand they are highly volatile and decomposed under the processing conditions. The study aims to produce the loaded chitosan nanoparticles with different concentrations of savory essential oil to improve the anti-microbial property and increase the resistance of essential oil to oxygen and heat. The encapsulation efficiency was obtained in the range of 32.07% to 39.93% and the particle size distribution of the samples was observed in the range of 159 to 210 nm. The range of Zeta potential was obtained between -11.9 to -23.1 mV. The essential oil loaded in chitosan showed stronger antifungal activity against Rhizopus stolonifer. The results showed that the antioxidant property is directly related to the concentration of loaded essential oil so that the antioxidant property increases by increasing the concentration of essential oil. In general, it seems that the savory essential oil loaded in chitosan particles can be used as a food processor.

Keywords: chitosan, encapsulation, essential oil, nanogel

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Authors: Noah G. Akhimien, Eshrar Latif

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The natural environment is in need for an urgent rescue due to dilapidation and recession of resources. Passive design strategies have proven to be one of the effective ways to reduce CO₂ emissions and to improve building performance. On the other hand, there is a huge drop in material availability due to poor recycling culture. Consequently, building waste pose environmental hazard due to unrecycled building materials from construction and deconstruction. Buildings are seen to be material banks for a circular economy, therefore incorporating circular economy into passive housing will not only safe guide the climate but also improve resource efficiency. The study focuses on incorporating a circular economy in passive design strategies for an affordable energy and resource efficient residential building in Nigeria. Carbon dioxide (CO₂) concentration is still on the increase as buildings are responsible for a significant amount of this emission globally. Therefore, prompt measures need to be taken to combat the effect of global warming and associated threats. Nigeria is rapidly growing in human population, resources on the other hand have receded greatly, and there is an abrupt need for recycling even in the built environment. It is necessary that Nigeria responds to these challenges effectively and efficiently considering building resource and energy. Passive design strategies were assessed using simulations to obtain qualitative and quantitative data which were inferred to case studies as it relates to the Nigeria climate. Building materials were analysed using the ReSOLVE model in order to explore possible recycling phase. This provided relevant information and strategies to illustrate the possibility of circular economy in passive buildings. The study offers an alternative approach, as it is the general principle for the reworking of an economy on ecological lines in passive housing and by closing material loops in circular economy.

Keywords: building, circular, efficiency, environment, sustainability

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Authors: O. E. Okafor, L. U. S. Ezeanyika, C. G. Nkwonta, C. J. Okonkwo

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The effect of processing on plasma lipid profile and atherogenic indices of rats fed Artocarpus heterophyllus seed diets at different concentrations were investigated. Fifty five rats were used for this study, they were divided into eleven groups of five rats each (one control group and ten test groups), the test groups were fed raw, boiled, roasted, fermented, and soaked diets at 10 % and 40% concentrations. The study lasted for thirty five days. The diets led to significant decrease (p < 0.05) in plasma cholesterol and triacylglycerol of rats fed 10% and 40% concentrations of the diets, and a significant increase (p < 0.05) in high density lipoprotein (HDL) levels at 40% concentrations of the test diets. The diets also produced decrease in low density lipoprotein (LDL), very low density lipoprotein (VLDL), cardiac risk ratio (CRR), atherogenic index of plasma (AIP) and atherogenic coefficient (AC) at 40% concentrations except the soaked group that showed slight elevation of LDL, CRR, AC and AIP at 40% concentration. Artocarpus heterophyllus seeds could be beneficial to health because of its ability to increase plasma HDL and reduce plasma LDL, VLDL, cholesterol, triglycerides and atherogenic indices at higher diet concentration.

Keywords: artocarpus heterophyllus, atherogenic indices, concentrations, lipid profile

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Authors: Ashmita Mukherjee, Yogesh Harishchandra Kabutare, Suritra Bandyopadhyay, Paulomi Ghosh

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Uncontrolled bleeding in the battlefield and the operation rooms can lead to serious injuries, trauma and even be lethal. Keratin was reported to be a haemostatic material which rapidly activates thrombin followed by activation of fibrinogen leading to the formation of insoluble fibrin. Also platelets, the main initiator of haemostasis are reported to adhere to keratin. However, the major limitation of pure keratin as a biomaterial is its poor physical property and corresponding low mechanical strength. To overcome this problem, keratin was cross-linked with alginate to increase its mechanical stability. In our study, Keratin extracted from feather waste showed yield of 80.5% and protein content of 8.05 ± 0.43 mg/mL (n=3). FTIR and CD spectroscopy confirmed the presence of the essential functional groups and preservation of the secondary structures of keratin. The keratin was then cross-linked with alginate to make a dope. The dope was used to draw fibers of desired diameters in a suitable coagulation bath using a customized wet spinning setup. The resultant morphology of keratin fibers was observed under a brightfield microscope. The FT-IR analysis implied that there was a presence of both keratin and alginate peaks in the fibers. The cross-linking was confirmed in the keratin alginate fibers by a shift of the amide A and amide B peaks towards the right and disappearance of the peak for N-H stretching (1534.68 cm-1). Blood was drawn in citrate vacutainers for whole blood clotting test and blood clotting kinetics, which showed that the keratin fibers could accelerate blood coagulation compared to that of alginate fibers and tissue culture plate. Additionally, cross-linked keratin-alginate fiber was found to have lower haemolytic potential compared to alginate fiber. Thus, keratin cross-linked fibers can have potential applications to combat unrestrained bleeding.

Keywords: biomaterial, biowaste, fiber, keratin

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Authors: Sangeeta Palekar, Mahima Rana, Jayu Kalambe

Abstract:

In this paper, a microfluidic-based platform for the quantification of contaminants in the water is proposed. The proposed system uses microfluidic channels with an embedded environment for contaminants detection in water. Microfluidics-based platforms present an evident stage of innovation for fluid analysis, with different applications advancing minimal efforts and simplicity of fabrication. Polydimethylsiloxane (PDMS)-based microfluidics channel is fabricated using a soft lithography technique. Vertical and horizontal connections for fluid dispensing with the microfluidic channel are explored. The principle of colorimetry, which incorporates the use of Griess reagent for the detection of nitrite, has been adopted. Nitrite has high water solubility and water retention, due to which it has a greater potential to stay in groundwater, endangering aquatic life along with human health, hence taken as a case study in this work. The developed platform also compares the detection methodology, containing photodetectors for measuring absorbance and image sensors for measuring color change for quantification of contaminants like nitrite in water. The utilization of image processing techniques offers the advantage of operational flexibility, as the same system can be used to identify other contaminants present in water by introducing minor software changes.

Keywords: colorimetric, fluid contaminants, nitrite detection, microfluidics

Procedia PDF Downloads 195

Authors: Anita Vidacs, Robert Rajko, Csaba Vagvolgyi, Judit Krisch

Abstract:

With the optimization of a new disinfectant the number of tests could be decreased and the cost of processing too. Good sanitizers are eco-friendly and allow no resistance evolvement of bacteria. The essential oils (EOs) are natural antimicrobials, and most of them have the Generally Recognized As Safe (GRAS) status. In our study, the effect of the EOs cinnamon, marjoram, and thyme was investigated against mixed species bacterial biofilms of Escherichia coli, Listeria monocytogenes, Pseudomonas putida, and Staphylococcus aureus. The optimal concentration of EOs, disinfection time and level of pH were evaluated with the aid of Response Surface Box-Behnken Design (RSD) on 1 day and 7 days old biofilms on metal, plastic, and wood surfaces. The variable factors were in the range of 1-3 times of minimum bactericide concentration (MBC); 10-110 minutes acting time and 4.5- 7.5 pH. The optimized EO disinfectant was compared to industrial used chemicals (HC-DPE, Hypo). The natural based disinfectants were applicable; the acting time was below 30 minutes. EOs were able to eliminate the biofilm from the used surfaces except from wood. The disinfection effect of the EO based natural solutions was in most cases equivalent or better compared to chemical sanitizers used in food industry.

Keywords: biofilm, Box-Behnken design, disinfectant, essential oil

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Authors: Shweta Lall

Abstract:

The intent of this paper is to demonstrate the role of computerized auxiliary science in advancing the desired and necessary alliance of historians, surveyors, topographers, and analysts of architectural conservation and management. The digital era practice of recording architectural and cultural heritage in view of its preservation, dissemination, and planning developments are discussed in this paper. Geomatics include practices like remote sensing, photogrammetry, surveying, Geographic Information System (GIS), laser scanning technology, etc. These all resources help in architectural and conservation applications which will be identified through various case studies analysed in this paper. The standardised outcomes and the methodologies using relevant case studies are listed and described. The main component of geomatics methodology adapted in conservation is data acquisition, processing, and presentation. Geomatics is used in a wide range of activities involved in architectural and cultural heritage – damage and risk assessment analysis, documentation, 3-D model construction, virtual reconstruction, spatial and structural decision – making analysis and monitoring. This paper will project the summary answers of the capabilities and limitations of the geomatics field in architectural and cultural conservation. Policy-makers, urban planners, architects, and conservationist not only need answers to these questions but also need to practice them in a predictable, transparent, spatially explicit and inexpensive manner.

Keywords: architectural and cultural conservation, geomatics, GIS, remote sensing

Procedia PDF Downloads 140

Authors: Ming-Yen Chang, Sheng-Hung Ke

Abstract:

This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

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Authors: Chellammal Surianarayanan

Abstract:

Healthcare industry is generating large amounts of data driven by various needs such as record keeping, physician’s prescription, medical imaging, sensor data, Electronic Patient Record(EPR), laboratory, pharmacy, etc. Healthcare data is so big and complex that they cannot be managed by conventional hardware and software. The complexity of healthcare big data arises from large volume of data, the velocity with which the data is accumulated and different varieties such as structured, semi-structured and unstructured nature of data. Despite the complexity of big data, if the trends and patterns that exist within the big data are uncovered and analyzed, higher quality healthcare at lower cost can be provided. Hadoop is an open source software framework for distributed processing of large data sets across clusters of commodity hardware using a simple programming model. The core components of Hadoop include Hadoop Distributed File System which offers way to store large amount of data across multiple machines and MapReduce which offers way to process large data sets with a parallel, distributed algorithm on a cluster. Hadoop ecosystem also includes various other tools such as Hive (a SQL-like query language), Pig (a higher level query language for MapReduce), Hbase(a columnar data store), etc. In this paper an analysis has been done as how healthcare big data can be processed and analyzed using Hadoop ecosystem.

Keywords: big data analytics, Hadoop, healthcare data, towards quality healthcare

Procedia PDF Downloads 410