Search results for: waste processing

Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

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Authors: Marcela Ondova, Adriana Estokova

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Rapid industrialization results in increased use of natural resources bring along serious ecological and environmental imbalance due to the dumping of industrial wastes. Principles of sustainable construction have to be accepted with regard to the consumption of natural resources and the production of harmful emissions. Cement is a great importance raw material in the building industry and today is its large amount used in the construction of concrete pavements. Concerning raw materials cost and producing CO2 emission the replacing of cement in concrete mixtures with more sustainable materials is necessary. To reduce this environmental impact people all over the world are looking for a solution. Over a period of last ten years, the image of fly ash has completely been changed from a polluting waste to resource material and it can solve the major problems of cement use. Fly ash concretes are proposed as a potential approach for achieving substantial reductions in cement. It is known that it improves the workability of concrete, extends the life cycle of concrete roads, and reduces energy use and greenhouse gas as well as amount of coal combustion products that must be disposed in landfills. Life cycle assessment also proved that a concrete pavement with fly ash cement replacement is considerably more environmentally friendly compared to standard concrete roads. In addition, fly ash is cheap raw material, and the costs saving are guaranteed. The strength properties, resistance to a frost or de-icing salts, which are important characteristics in the construction of concrete pavements, have reached the required standards as well. In terms of human health it can´t be stated that a concrete cover with fly ash could be dangerous compared with a cover without fly ash. Final Multi-criteria analysis also pointed that a concrete with fly ash is a clearly proper solution.

Keywords: life cycle assessment, fly ash, waste, concrete pavements

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Authors: Saugata Bose, Ritambhra Korpal

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The internet has increased the copy-paste scenarios amongst students as well as amongst researchers leading to different levels of plagiarized documents. For this reason, much of research is focused on for detecting plagiarism automatically. In this paper, an initiative is discussed where Natural Language Processing (NLP) techniques as well as supervised machine learning algorithms have been combined to detect plagiarized texts. Here, the major emphasis is on to construct a framework which detects external plagiarism from monolingual texts successfully. For successfully detecting the plagiarism, n-gram frequency comparison approach has been implemented to construct the model framework. The framework is based on 120 characteristics which have been extracted during pre-processing the documents using NLP approach. Afterwards, filter metrics has been applied to select most relevant characteristics and then supervised classification learning algorithm has been used to classify the documents in four levels of plagiarism. Confusion matrix was built to estimate the false positives and false negatives. Our plagiarism framework achieved a very high the accuracy score.

Keywords: lexical matching, shallow NLP, supervised machine learning algorithm, word n-gram

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

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Authors: Temitope Adewale, Oladapo Raji

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The study was designed to investigate the assessment of women's involvement in fishing. In order to give the study a direction, five research questions, as well as two hypotheses, were postulated, and a total of fifty (50) respondents each were selected from two local government areas for the study. This brings a total of one hundred (100) respondents selected from these local government areas in Lagos state. The outcome of the finding indicates that the percentage of the respondents’ age, 49% was between 31 and 35 years, 56% has a working experience of 6-10 years, 61% were married, 69% had secondary education as their educational level. However, findings show that socio-economic characteristics (x2 =15.504, df=6, p < 0.05) and income (r=0.83, p < 0.05) have a significant relationship on the fishing. It was established that the Women in Fish production/processing were faced with a lot of constraints such as high cost of inputs, inadequate electricity supply, lack of adequate capital, non-availability of the improved oven, non-availability of extension agents, inadequate fish landing, lack of transportation facilities, lack of training on financial management and loan acquisition which affected the level of output of women in Fish processing adversely.

Keywords: women, fishing, agriculture, Lagos

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Authors: Joaquin Navarro Perales, Ana Lidia Franzoni Velázquez, Francisco Cervantes Pérez

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The Mexican educational system faces diverse challenges related with the quality and coverage of education. The development of Intelligent Tutoring Systems (ITS) may help to solve some of them by helping teachers to customize their classes according to the performance of the students in online courses. In this work, we propose the adaptation of a functional ITS based on Bloom’s taxonomy called Sistema de Apoyo Generalizado para la Enseñanza Individualizada (SAGE), to measure student’s metacognition and their emotional response based on Marzano’s taxonomy. The students and the system will share the control over the advance in the course, so they can improve their metacognitive skills. The system will not allow students to get access to subjects not mastered yet. The interaction between the system and the student will be implemented through Natural Language Processing techniques, thus avoiding the use of sensors to evaluate student’s response. The teacher will evaluate student’s knowledge utilization, which is equivalent to the last cognitive level in Marzano’s taxonomy.

Keywords: intelligent tutoring systems, student modelling, metacognition, affective computing, natural language processing

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Authors: Palash Kumar Mollick, Leire Olazar, Laura Santamaria, Pablo Comendador, Manomita Mollick, Gartzen Lopez, Martin Olazar

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The entire world is skeptical towards a silver line technology of converting plastic waste into valuable synthetic gas. At this junction, besides an adequately studied conventional catalytic process for steam reforming, a non-thermal plasma is being introduced. Organic volatiles are produced in the first step, pyrolysing the plastic materials. Resultant lightweight olefins and carbon monoxide are the major components that undergo a steam reforming process to achieve syngas. A non-thermal plasma consists of ionized gases and free electrons with an electronic temperature as high as 10³ K. Organic volatiles are, in general, endorganics inactive and thus demand huge bond-breaking energy. Conventional catalyst is incapable of providing the required activation energy, leading to poor thermodynamic equilibrium, whereas a non-thermal plasma can actively collide with reactants to produce a rich mix of reactive species, including vibrationally or electronically excited molecules, radicals, atoms, and ions. In addition, non-thermal plasma provides nonequilibrium conditions leading to electric discharge only in certain degrees of freedom without affecting the intrinsic chemical conditions of the participating reactants and products. In this work, we report thermodynamic and kinetic aspects of the conversion of organic volatiles into syngas using a non-thermal plasma. Detailed characteristics of plasma and its effect on the overall yield of the process will be presented.

Keywords: non thermal plasma, plasma catalysis, steam reforming, syngas, plastic waste, green energy

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Authors: Peng Zhang, Cai Liang

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The non-biodegradable plastic wastes have posed severe environmental and ecological contaminations. Numerous technologies, such as pyrolysis, incineration, and landfilling, have already been employed for the treatment of plastic waste. Compared with conventional methods, microwave has displayed unique advantages in the rapid production of hydrogen from plastic wastes. Understanding the interaction between microwave radiation and materials would promote the optimization of several parameters for the microwave reaction system. In this work, various carbon materials have been investigated to reveal microwave heating performance and the ensuing catalytic activity. Results showed that the diversity in the heating characteristic was mainly due to the dielectric properties and the individual microstructures. Furthermore, the gaps and steps among the surface of carbon materials would lead to the distortion of the electromagnetic field, which correspondingly induced plasma discharging. The intensity and location of local plasma were also studied. For high-yield H₂ production, iron nanoparticles were selected as the active sites, and a series of iron/carbon bifunctional catalysts were synthesized. Apart from the high catalytic activity, the iron particles in nano-size close to the microwave skin depth would transfer microwave irradiation to the heat, intensifying the decomposition of plastics. Under microwave radiation, iron is supported on activated carbon material with 10wt.% loading exhibited the best catalytic activity for H₂ production. Specifically, the plastics were rapidly heated up and subsequently converted into H₂ with a hydrogen efficiency of 85%. This work demonstrated a deep understanding of microwave reaction systems and provided the optimization for plastic treatment.

Keywords: plastic waste, recycling, hydrogen, microwave

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Authors: Subhasree Majumdar, Sovan Dey, Sayari Mukherjee, Sourav Dutta, Dalia Dasgupta Mandal

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Bacterial isolates from Planococcus genus are known for the production of yellowish orange pigment that belongs to the carotenoid family. These pigments are of immense pharmacological importance as antioxidant, anticancer, eye and liver protective agent, etc. The production of this pigment in a cost effective manner is a challenging task. The present study explored paper mill sludge (PMS), a solid lignocellulosic waste generated in large quantities from pulp and paper mill industry as a substrate for carotenoid pigment production by Planococcus sp. TRC1. PMS was compared in terms of efficacy with sugarcane bagasse, which is a highly explored substrate for valuable product generation via solid state fermentation. The results showed that both the biomasses yielded the highest carotenoid during 48 hours of incubation, 31.6 mg/gm and 42.1 mg/gm for PMS and bagasse respectively. Compositional alterations of both the biomasses showed reduction in lignin, hemicellulose and cellulose content by 41%, 15%, 1% for PMS and 38%, 25% and 6% for sugarcane bagasse after 72 hours of incubation. Structural changes in the biomasses were examined by FT-IR, FESEM, and XRD which further confirmed modification of solid biomasses by bacterial isolate. This study revealed the potential of PMS to act as cheap substrate for carotenoid pigment production by Planococcus sp. TRC1, as it showed a significant production in comparison to sugarcane bagasse which gave only 1.3 fold higher production than PMS. Delignification of PMS by TRC1 during pigment production is another important finding for the reuse of this waste from the paper industry.

Keywords: carotenoid, lignocellulosic, paper mill sludge, Planococcus sp. TRC1, solid state fermentation, sugarcane bagasse

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Authors: Huashan Tai, Chien-Hui Lung

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Nowadays people use massive fossil fuels which not only cause environmental impacts and global climate change, but also cause the depletion of non-renewable energy such as coal and oil. Bioenergy is currently the most widely used renewable energy, and agricultural waste is one of the main raw materials for bioenergy. In this study, we use orange peel residue, which is easier to collect from agricultural waste to produce bio-coal by torrefaction. The orange peel residue (with 25 to 30% moisture) was treated by torrefaction, and the experiments were conducted with initial temperature at room temperature (approximately at 25° C), with heating rates of 10, 30, and 50°C / min, with terminal temperatures at 150, 200, 250, 300, 350℃, and with residence time of 10, 20, and 30 minutes. The results revealed that the heating value, ash content and energy densification ratio of the solid products after torrefaction are in direct proportion to terminal temperatures and residence time, and are inversely proportional to heating rates. The moisture content, solid mass yield, energy yield, and volumetric energy density of the solid products after torrefaction are inversely proportional to terminal temperatures and residence time, and are in direct proportion to heating rates. In conclusion, we found that the heating values of the solid products were 1.3 times higher than those of the raw orange peels before torrefaction, and the volumetric energy densities were increased by 1.45 times under operating parameters with terminal temperature at 250°C, residence time of 10 minutes, and heating rate of 10°C / min of torrefaction. The results indicated that the residue of orange peel treated by torrefaction improved its energy density and fuel properties, and became more suitable for bio-fuel applications.

Keywords: biomass energy, orange, torrefaction

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Authors: Adha Bayu Wijaya, A. Zainal Abidin, Naufal Baihaqi, Joko Suprayitno, Astika Titistiti, Muslim Adi Wijaya, Endah Tri Lestari, Agung Wibowo

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Sulfur is a non-metallic chemical element in the form of a yellow crystalline solid with the chemical formula, and is formed from several types of natural and artificial chemical reactions. Commercial applications of sulfur processed products can be found in various aspects of life, for example in the use of processed sulfur as paving blocks. The Gundih Central Processing Plant (CPP) is capable of producing 14 tons/day of sulfur pellets. This amount comes from the high H2S content of the wells with a total concentration of 20,000 ppm and a volume accumulation of 14 MMSCFD acid gas. H2S is converted to sulfur using the thiobacillus microbe in the Biological Sulfur Recovery Unit (BSRU) with a sulfur product purity level greater than 95%. In 2018 sulfur production at Gundih CPP was recorded at 4044 tons which could potentially trigger serious problems from an environmental aspect. The use of sulfur as material for making paving blocks is an alternative solution in addressing the potential impact on the environment, as regulated by Government Regulation No.22 of Year 2021 concerning the Waste Management of Non-Hazardous and Toxic Substances (B3), and the high cost of handling sulfur by third parties. The design mix of ratio sulfur paving blocks is 22% cements, rock ash 67%, and 11% of sulfur pellets. The sulfur used in making the paving mixture is pure sulfur, namely the side product category without any contaminants, thereby eliminating the potential for environmental pollution when implementing sulfur paving. Strength tests of sulfur paving materials have also been confirmed by external laboratories. The standard used in making sulfur paving blocks refers to the SNI 03-0691-1996 standard. With the results of sulfur paving blocks made according to quality B. Currently, sulfur paving blocks are used in building access to wells locations and in public roads in the Cepu Field area as a contribution from Corporate Social Responsibility (CSR).

Keywords: sulphur, innovation, paving block, CSR, sulphur paving

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Authors: Petri Kouvo, Aino Kainulainen, Kimmo Koivunen

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Separate collection system for recyclable wastes in the Helsinki region was ranked second best of European capitals. The collection system includes paper, cardboard, glass, metals and biowaste. Residual waste is collected and used in energy production. The collection system excluding paper is managed by the Helsinki Region Environmental Services HSY, a public organization owned by four municipalities (Helsinki, Espoo, Kauniainen and Vantaa). Paper collection is handled by the producer responsibility scheme. The efficiency of the collection system in the Helsinki region relies on a good coverage of door-to-door-collection. All properties with 10 or more dwelling units are required to source separate biowaste and cardboard. This covers about 75% of the population of the area. The obligation is extended to glass and metal in properties with 20 or more dwelling units. Other success factors include public awareness campaigns and a fee system that encourages recycling. As a result of waste management regulations for source separation of recyclables and biowaste, nearly 50 percent of recycling rate of household waste has been reached. For households and small and medium size enterprises, there is a sorting station fleet of five stations available. More than 50 percent of wastes received at sorting stations is utilized as material. The separate collection of plastic packaging in Finland will begin in 2016 within the producer responsibility scheme. HSY started supplementing the national bring point system with door-to-door-collection and pilot operations will begin in spring 2016. The result of plastic packages pilot project has been encouraging. Until the end of 2016, over 3500 apartment buildings have been joined the piloting, and more than 1800 tons of plastic packages have been collected separately. In the summer 2015 a novel partial flow digestion process combining digestion and tunnel composting was adopted for source separated household and commercial biowaste management. The product gas form digestion process is converted in to heat and electricity in piston engine and organic Rankine cycle process with very high overall efficiency. This paper describes the efficient collection system and discusses key success factors as well as main obstacles and lessons learned as well as the partial flow process for biowaste management.

Keywords: biowaste, HSY, MSW, plastic packages, recycling, separate collection

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Authors: Jamie A. Prowse Turner, Jamie I. D. Campbell, Valerie A. Thompson

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The objective of the current research was to use a dual-process theory framework to explain these age-related differences in reasoning. Seventy-two older (M = 80.0 years) and 72 younger (M = 24.6 years) adults were given a variety of reasoning tests (i.e., a syllogistic task, base rate task, the Cognitive Reflection Test, and a perspective manipulation), as well as independent tests of capacity (working memory, processing speed, and inhibition), thinking styles, and metacognitive ability, to account for these age-related differences. It was revealed that age-related differences were limited to problems that required Type 2 processing and were related to differences in cognitive capacity, individual difference factors, and strategy choice. Furthermore, older adults’ performance can be improved by reasoning from another’s’ perspective and cannot, at this time, be explained by metacognitive differences between young and older adults. All of these findings fit well within a dual-process theory of reasoning, which provides an integrative framework accounting for previous findings and the findings presented in the current manuscript.

Keywords: aging, dual-process theory, performance, reasoning ability

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Authors: Muhammad Faisal, Zai-Jin You, Muhammad Naeem

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Concerns about the environment, public health, and the economy are raised by the fact that the world produces around 6 trillion cigarettes annually. Arguably the most pervasive forms of environmental litter, this dangerous trash must be eliminated. The researchers wanted to get an idea of how much pollution is seeping out of cigarette butts in metropolitan areas by studying their distribution and concentration. In order to accomplish this goal, the cigarette butt pollution indicator was applied in 29 different areas. The locations were monitored monthly for a full calendar year. The conditions for conducting the investigation of the venues were the same on both weekends and during the weekdays. By averaging the metal leakage ratio in various climates and the average weight of cigarette butts, we were able to estimate the total amount of heavy metal leakage. The findings revealed that the annual average value of the index for the areas that were investigated ranged from 1.38 to 10.4. According to these numbers, just 27.5% of the areas had a low pollution rating, while 43.5% had a major pollution status or worse. Weekends witnessed the largest fall (31% on average) in all locations' indices, while spring and summer saw the largest increase (26% on average) compared to autumn and winter. It was calculated that the average amount of heavy metals such as Cr, Cu, Cd, Zn, and Pb that seep into the environment from discarded cigarette butts in commercial, residential, and park areas, respectively, is 0.25 µg/m2, 0.078 µg/m2, and 0.18 µg/m2. Butt from cigarettes is one of the most prevalent forms of litter in the area that was examined. This litter is the origin of a wide variety of contaminants, including heavy metals. This toxic garbage poses a significant risk to the city.

Keywords: heavy metal, hazardous waste, waste management, litter

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Authors: Shafiq Alam, Yen Ning Lee

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Conventional hydrometallurgical processing of metals involves the use of large quantities of toxic chemicals. Realizing a need to develop sustainable technologies, extensive research studies are being carried out to recover and recycle base, precious and rare earth metals from their pregnant leach solutions (PLS) using green chemicals/biomaterials prepared from biomass wastes derived from agriculture, marine and forest resources. Our innovative research showed that bio-adsorbents prepared from such biomass wastes can effectively adsorb precious metals, especially gold after conversion of their functional groups in a very simple process. The highly effective ‘Adsorption-coupled-Reduction’ phenomenon witnessed appears promising for the potential use of this gold biosorption process in the mining industry. Proper management and effective use of biomass wastes as value added green chemicals will not only reduce the volume of wastes being generated every day in our society, but will also have a high-end value to the mining and mineral processing industries as those biomaterials would be cheap, but very selective for gold recovery/recycling from low grade ore, leach residue or e-wastes.

Keywords: biosorption, hydrometallurgy, gold, adsorption, reduction, biomass, sustainability

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Authors: Anam Naveed, Asma Andleeb, Mehreen Sirshar

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In the article, Image processing techniques have been applied on cardiac images for enhancing the image quality. Two types of methodologies considers for survey, invasive techniques and non-invasive techniques. Different image processes for improvement of cardiac image quality and reduce the amount of radiation exposure for invasive techniques are explored. Different image processing algorithms for enhancing the noninvasive cardiac image qualities are described. Beside these two methodologies, third methodology has applied on live streaming of heart rate on ECG window for extracting necessary information, removing noise and enhancing quality. Sensitivity analyses have been carried out to investigate the impacts of cardiac images for diagnosis of cardiac arteries disease and how the enhancement on images will help the cardiologist to diagnoses disease. The paper evaluates strengths and weaknesses of different techniques applied for improved the image quality and draw a conclusion. Some specific limitations must be considered for whole survey, like the patient heart beat must be 70-75 beats/minute while doing the angiography, similarly patient weight and exposure radiation amount has some limitation.

Keywords: cardiac images, CT angiography, critical analysis, exposure radiation, invasive techniques, invasive techniques, non-invasive techniques

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Authors: Chikwelu Edward Emenike, Ogbuagu Uchenna Fredrick

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About 34% of the solar radiant energy reaching the earth is immediately reflected back to space as incoming radiation by clouds, chemicals, dust in the atmosphere and by the earth’s surface. Most of the remaining 66% warms the atmosphere and land. Most of the incoming solar radiation not reflect away is degraded into low-quality heat and flows into space. The rate at which this energy returns to space as low-quality heat is affected by the presence of molecules of greenhouse gases. Gaseous emission was measured with the aid of Growen gas Analyzer with a digital readout. Total measurements of eight parameters of twelve selected sample locations taken at two different seasons within two months were made. The ambient air quality investigation in Anambra State has shown the overall mean concentrations of gaseous emission at twelve (12) locations. The mean gaseous emissions showed (NO2=0.66ppm, SO2=0.30ppm, CO=43.93ppm, H2S=2.17ppm, CH4=1.27ppm, CFC=1.59ppb, CO2=316.33ppm, N2O=302.67ppb and O3=0.37ppm). These values do not conform to the National Ambient Air Quality Standard (NAAQS) and thus contribute significantly to the global warming. Because some of these gaseous emissions (SO2, NO2) are oxidizing agents, they act as irritants that damage delicate tissues in the eyes and respiratory passages. These can impair lung function and trigger cardiovascular problems as the heart tries to compensate for lack of Oxygen by pumping faster and harder. The major sources of air pollution are transportation, industrial processes, stationary fuel combustion and solid waste disposal, thus much is yet to be done in a developing country like Nigeria. Air pollution control using pollution-control equipment to reduce the major conventional pollutants, relocating people who live very close to dumpsites, processing and treatment of gases to produce electricity, heat, fuel and various chemical components should be encouraged.

Keywords: ambient air, atmosphere, greenhouse gases, anambra state

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Authors: Bowen Ding, Yihao Kuang

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In recent years, with the development of large-scale pre-trained lan-guage models, building vector representations of text through deep neural network models has become a standard practice for natural language processing tasks. From the performance on downstream tasks, we can know that the text representation constructed by these models contains linguistic information, but its encoding mode and extent are unclear. In this work, a structural probe is proposed to detect whether the vector representation produced by a deep neural network is embedded with a syntax tree. The probe is trained with the deep metric learning method, so that the distance between word vectors in the metric space it defines encodes the distance of words on the syntax tree, and the norm of word vectors encodes the depth of words on the syntax tree. The experiment results on ELMo and BERT show that the syntax tree is encoded in their parameters and the word representations they produce.

Keywords: deep metric learning, syntax tree probing, natural language processing, word representations

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Authors: Feleke Terefe Fanta

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Background: The existence of heavy metals and coliform bacteria contaminants in aquatic system of Akaki river basin, a sub city of Addis Ababa, Ethiopia has become a public concern as human population increases and land development continues. Hence, it is the right time to design treatment technologies that can handle multiple pollutants. Results: In this study, we prepared a synthetic zeolites and copper doped zeolite composite adsorbents as cost effective and simple approach to simultaneously remove heavy metals and total coliforms from wastewater of Akaki river. The synthesized copper–zeolite X composite was obtained by ion exchange method of copper ions into zeolites frameworks. Iodine test, XRD, FTIR and autosorb IQ automated gas sorption analyzer were used to characterize the adsorbents. The mean concentrations of Cd, Cr, and Pb in untreated sample were 0.795, 0.654 and 0.7025 mg/L respectively. These concentrations decreased to Cd (0.005 mg/L), Cr (0.052 mg/L) and Pb (bellow detection limit, BDL) for sample treated with bare zeolite X while a further decrease in concentration of Cd (0.005 mg/L), Cr (BDL) and Pb (BDL) was observed for the sample treated with copper–zeolite composite. Zeolite X and copper-modified zeolite X showed complete elimination of total coliforms after 90 and 50 min contact time respectively. Conclusion: The results obtained in this study showed high antimicrobial disinfection and heavy metal removal efficiencies of the synthesized adsorbents. Furthermore, these sorbents are efficient in significantly reducing physical parameters such as electrical conductivity, turbidity, BOD and COD.

Keywords: WASTE WATER, COPPER DOPED ZEOITE X, ADSORPITION, HEAVY METAL, DISINFECTION, AKAKI RIVER

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Authors: Zakeia Benmoussa

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Pressure on freshwater systems comes from removing too much water to grow crops; contamination from economic activities, land use practices, and human waste. The paper will be focusing on how water management can influence the design, implementation, and impacts of the ecological principles of biomimicry as sustainable methods in recycling wastewater. At Texas State, United States of America, in particular the lower area of the Trinity River refuge, there is a true example of the diversity to be found in that area, whether when exploring the lands or the waterways. However, as the Trinity River supplies water to the state’s residents, the lower part of the river at Liberty County presents several problem of wastewater discharge in the river. Therefore, conservation efforts are particularly important in the Trinity River basin. Clearly, alternative ways must be considered in order to conserve water to meet future demands. As a result, there should be another system provided rather than the conventional water treatment. Mimicking ecosystem's technologies out of context is not enough, but if we incorporate plants into building architecture, in addition to their beauty, they can filter waste, absorb excess water, and purify air. By providing an architectural proposal center, a living system can be explored through several methods that influence natural resources on the micro-scale in order to impact sustainability on the macro-scale. The center consists of an ecological program of Plant and Water Biomimicry study which becomes a living organism that purifies the river water in a natural way through architecture. Consequently, a rich beautiful nature could be used as an educational destination, observation and adventure, as well as providing unpolluted fresh water to the major cities of Texas. As a result, these facts raise a couple of questions: Why is conservation so rarely practiced by those who must extract a living from the land? Are we sufficiently enlightened to realize that we must now challenge that dogma? Do architects respond to the environment and reflect on it in the correct way through their public projects? The method adopted in this paper consists of general research into careful study of the system of the living machine, in how to integrate it at architectural level, and finally, the consolidation of the all the conclusions formed into design proposal. To summarise, this paper attempts to provide a sustainable alternative perspective in bridging physical and mental interaction with biodiversity to enhance nature by using architecture.

Keywords: Biodiversity, Design with Nature, Sustainable architecture, Waste water treatment.

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Authors: M. Owlia, M. H. Azarsa, M. Khabbazan, A. Mirbagheri

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Proprioceptive neuromuscular facilitation exercises are a series of stretching techniques that are commonly used in rehabilitation and exercise therapy. Assessment of these exercises for true maneuvering requires extensive experience in this field and could not be down with patients themselves. In this paper, we developed software that uses Microsoft Kinect sensor, a spherical color marker, and real-time image processing methods to evaluate patient’s performance in generating true patterns of movements. The software also provides the patient with a visual feedback by showing his/her avatar in a Virtual Reality environment along with the correct path of moving hand, wrist and marker. Primary results during PNF exercise therapy of a patient in a room environment shows the ability of the system to identify any deviation of maneuvering path and direction of the hand from the one that has been performed by an expert physician.

Keywords: image processing, Microsoft Kinect, proprioceptive neuromuscular facilitation, upper extremities assessment, virtual reality

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Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

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Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

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Authors: Razieh Shamsi, Mehdi Faezipour, Ali Abdolkhani

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In this research, the characteristics of composites prepared from waste silk fibers and recycled polycarbonate polymer (used compacted boards) at four levels of 0, 10, 20, and 30% (silk fibers) and using 2% N- 2-Aminoethyl-3-Aminopropyltrimethoxysilane was investigated as a coupling agent and melt process method. Silk fibers (carpet weaving waste) with dimensions of 8-18 mm were prepared, and recycled polymer with 9 mesh grading was ground. Production boards in 3 thicknesses, 3 mm (tensile test samples), 5 mm (bending test samples, water absorption, and thickness shrinkage), 7 mm (impact resistance test samples) ) with a specific weight of 1 gram per cubic centimeter, hot pressing time and temperature of 12 minutes and 190 degrees Celsius with a pressure of 130 bar, cold pressing time of 6 minutes with a pressure of 50 bar and using the coupling agent N- (2- Aminoethyl)-3-aminopropyltrimethoxysilane was prepared in a constant amount of 2% of the dry weight of the filler. The results showed that, in general, by adding silk fibers to the base polymer, compared to the control samples (pure recycled polycarbonate polymer) and also by increasing the amount of silk fibers, almost all the resistances increased. The amount of water absorption of the constructed composite increased with the increase in the amount of silk fibers, and the thickness absorption was equal to 0% even after 72 hours of immersion in water. The thermal resistance of the pure recycled polymer was higher than the prepared composites, and by adding silk fibers to the base polymer and also by increasing the amount of silk fibers from 10 to 30%, the thermal resistance of the composites decreased.

Keywords: wood composite, recycled polycarbonate, silk fibers, polymer

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi

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This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.

Keywords: land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle

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Authors: Mahdi Allaoua Seklab, Süleyman BaşTürk

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In the quest to enhance coastal environmental health, this study introduces a fully autonomous beach cleaning machine, a breakthrough in leveraging green energy and advanced artificial intelligence for ecological preservation. Designed to operate independently, the machine is propelled by a solar-powered system, underscoring a commitment to sustainability and the use of renewable energy in autonomous robotics. The vehicle's autonomous navigation is achieved through a sophisticated integration of LIDAR and a camera system, utilizing an SSD MobileNet V2 object detection model for accurate and real-time trash identification. The SSD framework, renowned for its efficiency in detecting objects in various scenarios, is coupled with the lightweight and precise highly MobileNet V2 architecture, making it particularly suited for the computational constraints of on-board processing in mobile robotics. Training of the SSD MobileNet V2 model was conducted on Google Colab, harnessing cloud-based GPU resources to facilitate a rapid and cost-effective learning process. The model was refined with an extensive dataset of annotated beach debris, optimizing the parameters using the Adam optimizer and a cross-entropy loss function to achieve high-precision trash detection. This capability allows the machine to intelligently categorize and target waste, leading to more effective cleaning operations. This paper details the design and functionality of the beach cleaning machine, emphasizing its autonomous operational capabilities and the novel application of AI in environmental robotics. The results showcase the potential of such technology to fill existing gaps in beach maintenance, offering a scalable and eco-friendly solution to the growing problem of coastal pollution. The deployment of this machine represents a significant advancement in the field, setting a new standard for the integration of autonomous systems in the service of environmental stewardship.

Keywords: autonomous beach cleaning machine, renewable energy systems, coastal management, environmental robotics

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Authors: Agnė Kairyte, Saulius Vaitkus

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The gradual depletion of fossil feedstock and growing environmental concerns attracted extensive attention to natural resources due to their low cost, high abundance, renewability, sustainability, and biodegradability. Lignin is a significant by-product of the pulp and paper industry, having unique functional groups. Recently it became interesting for the manufacturing of high value-added products such as polyurethane and polyisocyanurate foams. This study focuses on the development of high-performance polyurethane foams with various amounts of lignin as a filler. It is determined that the incorporation of lignin as a filler material results in brittle and hard products due to the low molecular mobility of isocyanates and the inherent stiffness of lignin. Therefore, the current study analyses new techniques and possibilities of liquid glass infusion onto the surface of lignin particles to reduce the negative aspects and improve the performance characteristics of the modified foams. The foams modified with sole lignin and liquid glass-infused lignin had an apparent density ranging from 35 kg/m3 to 45 kg/m3 and closed-cell content (80–90%). The incorporation of sole lignin reduced the compressive and tensile strengths and increased dimensional stability and water absorption, while the contrary results were observed for polyurethane foams with liquid glass-infused lignin particles. The effect on rheological parameters of lignin and liquid glass infused lignin modified polyurethane premixes and morphology of polyurethane foam products were monitored to optimize the conditions and reveal the significant influence of the interaction between particles and polymer matrix.

Keywords: filler, lignin waste, liquid glass, polymer matrix, polyurethane foam, sustainability

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

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Authors: Aishatu Ibrahim Birma, Aminu Tukur, Abdulkarim Abbass Gora

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Machine translation plays a vital role in the Field of Natural Language Processing (NLP), breaking down language barriers and enabling communication across diverse communities. In the context of Hausa, a widely spoken language in West Africa, mainly in Nigeria, effective translation systems are essential for enabling seamless communication and promoting cultural exchange. However, due to the unique linguistic characteristics of Hausa, accurate translation remains a challenging task. The research proposes an approach to improving the machine learning translation of Hausa by integrating Named Entity Recognition (NER) techniques. Named entities, such as person names, locations, organizations, and dates, are critical components of a language's structure and meaning. Incorporating NER into the translation process can enhance the quality and accuracy of translations by preserving the integrity of named entities and also maintaining consistency in translating entities (e.g., proper names), and addressing the cultural references specific to Hausa. The NER will be incorporated into Neural Machine Translation (NMT) for the Hausa to English Translation.

Keywords: machine translation, natural language processing (NLP), named entity recognition (NER), neural machine translation (NMT)

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Authors: Sifatullah Bahij, Safiullah Omary, Francoise Feugeas, Amanullah Faqiri

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Plastic packages have been broadly used for a long time. Such widespread usage of plastic has resulted in an increased amount of plastic wastes and many environmental impacts. Plastic wastes are one of the most significant types of waste materials because of their non-degradation and low biodegradability. It is why many researchers tried to find a safe and environmentally friendly solution for plastic wastes. In this goal, in the civil engineering industry, many types of plastic wastes have been incorporated, as a partial substitution of aggregates or as additive materials (fibers) in concrete mixtures because of their lengthier lifetime and lower weight. This work aims to study the mechanical properties (compressive, split tensile and flexural strengths) of concrete with a water-cement ratio (w/c) of 0.45 and with the incorporation of non-woven PET plastic sheets. Five configurations -without PET (reference), 1-layer sheet, 2-side, 3-side, and full sample wrapping- were applied. The 7, 14 and 28-days samples’ compressive strengths, flexural strength and split tensile strength were measured. The outcomes of the study show that the compressive strength was improved for the wrapped samples, particularly for the cylindrical specimens. Also, split tensile and flexural behaviors of the wrapped samples improved significantly compared to the reference ones. Moreover, reference samples were damaged into many parts after mechanical testing, while wrapped specimens were taken by the applied configurations and were not divided into many small fragments. Therefore, non-woven fabrics appeared to improve some properties of the concrete.

Keywords: solid waste plastic, non-woven polyethylene terephthalate sheets, mechanical behaviors, crack pattern

Procedia PDF Downloads 125