Search results for: waste classification

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

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 The resulting synthesis gas is continuously withdrawn from the unit through the cooling and cleaning system.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

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

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Authors: Lebogang L. R. Mphahlele, Bruce B. Sithole

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Chicken meat is the highest consumed meat in south Africa, with a per capita consumption of >33 kg yearly. Hence, South Africa produces over 250 million kg of waste chicken feathers each year, the majority of which is landfilled or incinerated. The discarded feathers have caused environmental pollution and natural protein resource waste. Therefore, the valorisation of waste chicken feathers is measured as a more environmentally friendly and cost-effective treatment. Feather contains 91% protein, the main component being beta-keratin, a fibrous and insoluble structural protein extensively cross linked by disulfide bonds. Keratin is usually converted it into nanofibers via electrospinning for a variety of applications. keratin nanofiber composites have many potential biomedical applications for their attractive features, such as high surface-to-volume ratio and very high porosity. The application of nanofibers in the biomedical wound dressing requires antimicrobial properties for materials. One approach is incorporating inorganic nanoparticles, among which silver nanoparticles played an important alternative antibacterial agent and have been studied against many types of microbes. The objective of this study is to combine synthetic polymer, chicken feather keratin, and antibacterial nanoparticles to develop novel electrospun antibacterial nanofibrous composites for possible wound dressing application. Furthermore, this study will converting a two-dimensional electrospun nanofiber membrane to three-dimensional fiber networks that resemble the structure of the extracellular matrix (ECM)

Keywords: chicken feather keratin, nanofibers, nanoparticles, nanocomposites, wound dressing

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: S. Kherchaoui, A. Houacine

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This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

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Authors: Farramae Francisco, Rhoda Mae Simora, Sharon Nunal

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Deproteination and demineralization efficiencies of shrimp waste using two Lactobacillus species treated with different carbohydrate sources for chitin production, its chemical conversion to chitosan and the quality of chitin and chitosan produced were determined. Using 5% glucose and 5% cassava starch as carbohydrate sources, pH slightly increased from the initial pH of 6.0 to 6.8 and 7.2, respectively after 24 h and maintained their pH at 6.7 to 7.3 throughout the treatment period. Demineralization (%) in 5 % glucose and 5 % cassava was highest during the first day of treatment which was 82% and 83%, respectively. Deproteination (%) was highest in 5% cassava starch on the 3rd day of treatment at 84.4%. The obtained chitin from 5% cassava and 5% glucose had a residual ash and protein below 1% and solubility of 59% and 44.3%, respectively. Chitosan produced from 5% cassava and 5% glucose had protein content below 0.05%; residual ash was 1.1% and 0.8%, respectively. Chitosan solubility and degree of deacetylation were 56% and 33% in 5% glucose and 48% and 29% in 5% cassava, respectively. The advantage this alternative technology offers over that of chemical extraction is large reduction in chemicals needed thus less effluent production and generation of a protein-rich liquor, although the demineralization process should be improved to achieve greater degree of deacetylation.

Keywords: alternative carbon source, bioprocessing, lactic acid bacteria, waste utilization

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Authors: Efil Yusrianto, Noraini Marsi, Noraniah Kassim, Izzati Abdul Manaf, Hafizuddin Hakim Shariff

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Today, municipal solid waste (MSW), noise pollution, and attack fire are three ongoing issues for inhabitants of urban including in Malaysia. To solve these issues, eco-friendly autoclaved aerated concrete (AAC) containing recycled ceramic and gypsum waste (CGW) as a partial replacement for sand with different ratios (0%, 5%, 10%, 15%, 20%, and 25% wt) has been prepared. The performance of samples, such as the physical, mechanical, sound absorption coefficient, and direct fire resistance, has been investigated. All samples showed normal color behavior, i.e., grey and free crack. The compressive strength was increased in the range of 6.10% to 29.88%. The maximum value of compressive strength was 2.13MPa for 15% wt of CGW. The positive effect of CGW on the compressive strength of AAC has also been confirmed by crystalline phase and microstructure analysis. The acoustic performances, such as sound absorption coefficients of samples at low frequencies (500Hz), are higher than the reference sample (RS). AAC-CGW samples are categorized as AAC material classes B and C. The fire resistance results showed the physical surface of the samples had a free crack and was not burned during the direct fire at 950ºC for 300s. The results showed that CGW succeeded in enhancing the performance of fresh AAC, such as compressive strength, crystalline phase, sound absorption coefficient, and fire resistance of samples.

Keywords: physical, mechanical, acoustic, direct fire resistance performance, autoclaved aerated concrete, recycled ceramic-gypsum waste

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Authors: Chaouki Ghenai

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Computational Fluid Dynamic analysis of co-combustion of coal/biomass waste fuel blends is presented in this study. The main objective of this study is to investigate the effects of biomass portions (0%, 10%, 20%, 30%: weight percent) blended with coal and oxygen concentrations (21% for air, 35%, 50%, 75% and 100 % for pure oxygen) on the combustion performance and emissions. The goal is to reduce the air emissions from power plants coal combustion. Sub-bituminous Nigerian coal with calorific value of 32.51 MJ/kg and sawdust (biomass) with calorific value of 16.68 MJ/kg is used in this study. Coal/Biomass fuel blends co-combustion is modeled using mixture fraction/pdf approach for non-premixed combustion and Discrete Phase Modeling (DPM) to predict the trajectories and the heat/mass transfer of the fuel blend particles. The results show the effects of oxygen concentrations and biomass portions in the coal/biomass fuel blends on the gas and particles temperatures, the flow field, the devolitization and burnout rates inside the combustor and the CO2 and NOX emissions at the exit from the combustor. The results obtained in the course of this study show the benefits of enriching combustion air with oxygen and blending biomass waste with coal for reducing the harmful emissions from coal power plants.

Keywords: co-combustion, coal, biomass, fuel blends, CFD, air emissions

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Authors: Firas Daghistani, Hossam Abuel Naga

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Waste tyres is a global problem that has a negative effect on the environment, where there are approximately one billion waste tyres discarded worldwide yearly. Waste tyres are discarded in stockpiles, where they provide harm to the environment in many ways. Finding applications to these materials can help in reducing this global problem. One of these applications is recycling these waste materials and using them in geotechnical engineering. Recycled waste tyre particulates can be mixed with sand to form a lightweight material with varying shear strength characteristics. Contradicting results were found in the literature on the inclusion of particulate rubber to sand, where some experiments found that the inclusion of particulate rubber can increase the shear strength of the mixture, while other experiments stated that the addition of particulate rubber decreases the shear strength of the mixture. This research further investigates the inclusion of particulate rubber to sand and whether it can increase or decrease the shear strength characteristics of the mixture. For the experiment, a series of direct shear tests were performed on a poorly graded sand with a mean particle size of 0.32 mm mixed with recycled poorly graded particulate rubber with a mean particle size of 0.51 mm. The shear tests were performedon four normal stresses 30, 55, 105, 200 kPa at a shear rate of 1 mm/minute. Different percentages ofparticulate rubber content were used in the mixture i.e., 10%, 20%, 30% and 50% of sand dry weight at three density states, namely loose, slight dense, and dense state. The size ratio of the mixture,which is the mean particle size of the particulate rubber divided by the mean particle size of the sand, was 1.59. The results identified multiple parameters that can influence the shear strength of the mixture. The parameters were: normal stress, particulate rubber content, mixture gradation, mixture size ratio, and the mixture’s density. The inclusion of particulate rubber tosand showed a decrease to the internal friction angle and an increase to the apparent cohesion. Overall, the inclusion of particulate rubber did not have a significant influenceon the shear strength of the mixture. For all the dense states at the low normal stresses 33 and 55 kPa, the inclusion of particulate rubber showed aslight increase in the shear strength where the peak was at 20% rubber content of the sand’s dry weight. On the other hand, at the high normal stresses 105, and 200 kPa, there was a slight decrease in the shear strength.

Keywords: shear strength, direct shear, sand-rubber mixture, waste material, granular material

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Authors: Michelle Zeyuan Ma, Hermann Heilmeier

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Recently, meat production ecosystem impacts initiated many hot discussions and researchers, and it is a difficult implementation to reduce such impacts due to the demand of meat products. It calls for better management and control of ecosystem impacts from every aspects of meat production. This article analyzes the ecosystem impacts of meat production based on meat products life cycle. The analysis shows that considerable ecosystem impacts are caused by different meat production steps: initial establishment phase, animal raising, slaughterhouse processing, meat consumption, and wastes management. Based on this analysis, the impacts are summarized as: leading factor for biodiversity loss; water waste, land use waste and land degradation; greenhouse gases emissions; pollution to air, water, and soil; related major diseases. The article also provides a discussion on a solution-sustainable food system, which could help in reducing ecosystem impacts. The analysis method is based on the life cycle level, it provides a concept of the whole meat industry ecosystem impacts, and the analysis result could be useful to manage or control meat production ecosystem impacts from investor, producer and consumer sides.

Keywords: eutrophication, life cycle based analysis, sustainable food, waste management

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Authors: Kemal Polat

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In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

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Authors: Nourmalita Safitri Ningsih, Ridwan, Iqri Puspa Yunanda

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The aim of this study was to utilize the waste from slaughterhouses for chicken feed ingredients is probiotic. Livestock waste produced by livestock activities such as feces, urine, food remains, as well as water from livestock and cage cleaning. The process starts with the isolation of bacteria. Rumen fluid is taken at Slaughterhouse Giwangan, Yogyakarta. Isolation of Lactobacillus ruminus is done by using de Mann Rogosa Sharpe (MRS) medium. In the sample showed a rod-shaped bacteria are streaked onto an agar plates. After it was incubated at 37ºC for 48 hours, after which it is observed. The observation of these lactic acid bacteria it will show a clear zone at about the colony. These bacterial colonies are white, round, small, shiny on the agar plate mikroenkapsul In the manufacturing process carried out by the method of freeze dried using skim milk in addition capsulated material. Then the results of these capsulated bacteria are mixed with feed for livestock. The results from the mixing of capsulated bacteria in feed are to increase the quality of animal feed so as to provide a good effect on livestock. Scanning electron microscope testing we have done show the results of bacteria have been shrouded in skim milk. It can protect the bacteria so it is more durable in use. The observation of the bacteria showed a sheath on Lactobacillus sp. Preservation of bacteria in this way makes the bacteria more durable for use. As well as skim milk can protect bacteria that are resistant to the outside environment. Results of probiotics in chicken feed showed significant weight gain in chickens. Calculation Anova (P <0.005) shows the average chicken given probiotics her weight increased.

Keywords: chicken, probiotics, waste, Lactobacillus sp, bacteria

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Authors: Naghmeh Moradpoor Sheykhkanloo

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Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

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Authors: V. E. Messerle, A. B. Ustimenko, O. A. Lavrichshev

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A large amount of manure and its irrational use negatively affect the environment. As compared with biomass fermentation, plasma processing of manure enhances makes it possible to intensify the process of obtaining fuel gas, which consists mainly of synthesis gas (CO + H₂), and increase plant productivity by 150–200 times. This is achieved due to the high temperature in the plasma reactor and a multiple reduction in waste processing time. This paper examines the plasma processing of biomass using the example of dried mixed animal manure (dung with a moisture content of 30%). Characteristic composition of dung, wt.%: Н₂О – 30, С – 29.07, Н – 4.06, О – 32.08, S – 0.26, N – 1.22, P₂O₅ – 0.61, K₂O – 1.47, СаО – 0.86, MgO – 0.37. The thermodynamic code TERRA was used to numerically analyze dung plasma gasification and pyrolysis. Plasma gasification and pyrolysis of dung were analyzed in the temperature range 300–3,000 K and pressure 0.1 MPa for the following thermodynamic systems: 100% dung + 25% air (plasma gasification) and 100% dung + 25% nitrogen (plasma pyrolysis). Calculations were conducted to determine the composition of the gas phase, the degree of carbon gasification, and the specific energy consumption of the processes. At an optimum temperature of 1,500 K, which provides both complete gasification of dung carbon and the maximum yield of combustible components (99.4 vol.% during dung gasification and 99.5 vol.% during pyrolysis), and decomposition of toxic compounds of furan, dioxin, and benz(a)pyrene, the following composition of combustible gas was obtained, vol.%: СО – 29.6, Н₂ – 35.6, СО₂ – 5.7, N₂ – 10.6, H₂O – 17.9 (gasification) and СО – 30.2, Н₂ – 38.3, СО₂ – 4.1, N₂ – 13.3, H₂O – 13.6 (pyrolysis). The specific energy consumption of gasification and pyrolysis of dung at 1,500 K is 1.28 and 1.33 kWh/kg, respectively. An installation with a DC plasma torch with a rated power of 100 kW and a plasma reactor with a dung capacity of 50 kg/h was used for dung processing experiments. The dung was gasified in an air (or nitrogen during pyrolysis) plasma jet, which provided a mass-average temperature in the reactor volume of at least 1,600 K. The organic part of the dung was gasified, and the inorganic part of the waste was melted. For pyrolysis and gasification of dung, the specific energy consumption was 1.5 kWh/kg and 1.4 kWh/kg, respectively. The maximum temperature in the reactor reached 1,887 K. At the outlet of the reactor, a gas of the following composition was obtained, vol.%: СO – 25.9, H₂ – 32.9, СO₂ – 3.5, N₂ – 37.3 (pyrolysis in nitrogen plasma); СO – 32.6, H₂ – 24.1, СO₂ – 5.7, N₂ – 35.8 (air plasma gasification). The specific heat of combustion of the combustible gas formed during pyrolysis and plasma-air gasification of agricultural waste is 10,500 and 10,340 kJ/kg, respectively. Comparison of the integral indicators of dung plasma processing showed satisfactory agreement between the calculation and experiment.

Keywords: agricultural waste, experiment, plasma gasification, thermodynamic calculation

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Authors: Katsumi Hirata

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Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.

Keywords: environmental sound, bispectrum, spectrogram, slice bispectrogram, convolutional neural network

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Authors: Bencherif Kada

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In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

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Authors: Farzaneh Tahmoorian, Bijan Samali, John Yeaman

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Road networks are expanding all over the world during the past few decades to meet the increasing freight volumes created by the population growth and industrial development. At the same time, the rate of generation of solid wastes in the society is increasing with the population growth, technological development, and changes in the lifestyle of people. Thus, the management of solid wastes has become an acute problem. Accordingly, there is a need for greater efficiency in the construction and maintenance of road networks, in reducing the overall cost, especially the utilization of natural materials such as aggregates. An efficient means to reduce construction and maintenance costs of road networks is to replace natural (virgin) materials by secondary, recycled materials. Recycling will also help to reduce pressure on landfills and demand for extraction of natural virgin materials thus ensuring sustainability. Application of solid wastes in asphalt layer reduces not only environmental issues associated with waste disposal but also the demand for virgin materials which will subsequently result in sustainability. Therefore, this research aims to investigate the feasibility of the application of some of the waste materials such as glass, construction and demolition wastes, etc. as alternative materials in pavement construction, particularly flexible pavements. To this end, various combination of different waste materials in certain percentages is considered in designing the asphalt mixture. One of the goals of this research is to determine the optimum percentage of all these materials in the mixture. This is done through a series of tests to evaluate the volumetric properties and resilient modulus of the mixture. The information and data collected from these tests are used to select the adequate samples for further assessment through advanced tests such as triaxial dynamic test and fatigue test, in order to investigate the asphalt mixture resistance to permanent deformation and also cracking. This paper presents the results of these investigations on the application of waste materials in asphalt mixture for production of a sustainable asphalt mix.

Keywords: asphalt, glass, pavement, recycled aggregate, sustainability

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Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

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With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

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Authors: R. Sharma, S. Kumar, C. Sharma

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A number of toxic chlorophenolic compounds are formed during pulp bleaching. The nature and concentration of these chlorophenolic compounds largely depends upon the amount and nature of bleaching chemicals used. These compounds are highly recalcitrant and difficult to remove but are partially removed by the biochemical treatment processes adopted by the paper industry. Identification and estimation of these chlorophenolic compounds has been carried out in the primary and secondary clarified effluents from the paper mill by GCMS. Twenty-six chorophenolic compounds have been identified and estimated in paper mill waste waters. Electrochemical treatment is an efficient method for oxidation of pollutants and has successfully been used to treat textile and oil waste water. Electrochemical treatment using less expensive anode material, stainless steel electrodes has been tried to study their removal. The electrochemical assembly comprised a DC power supply, a magnetic stirrer and stainless steel (316 L) electrode. The optimization of operating conditions has been carried out and treatment has been performed under optimized treatment conditions. Results indicate that 68.7% and 83.8% of cholorphenolic compounds are removed during 2 h of electrochemical treatment from primary and secondary clarified effluent respectively. Further, there is a reduction of 65.1, 60 and 92.6% of COD, AOX and color, respectively for primary clarified and 83.8%, 75.9% and 96.8% of COD, AOX and color, respectively for secondary clarified effluent. EC treatment has also been found to increase significantly the biodegradability index of wastewater because of conversion of non- biodegradable fraction into biodegradable fraction. Thus, electrochemical treatment is an efficient method for the degradation of cholorophenolic compounds, removal of color, AOX and other recalcitrant organic matter present in paper mill waste water.

Keywords: chlorophenolics, effluent, electrochemical treatment, wastewater

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Authors: Helena Macedo, Larissa Tomaz, Levi Guimarães, Luís Cerqueira-Pinto, José Dinis-Carvalho

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In the context of retail logistics, the pursuit of operational efficiency and cost optimization involves a rigorous distinction between value-added and non-value-added activities. In today's competitive market, optimizing efficiency and reducing operational costs are paramount for retail businesses. This research paper focuses on the development of a classification model adapted to the retail sector, specifically examining internal logistics processes. Based on a comprehensive analysis conducted in a retail supermarket located in the north of Portugal, which covered various aspects of internal retail logistics, this study questions the concept of value and the definition of wastes traditionally applied in a manufacturing context and proposes a new way to assess activities in the context of internal logistics. This study combines quantitative data analysis with qualitative evaluations. The proposed classification model offers a systematic approach to categorize operations within the retail logistics chain, providing actionable insights for decision-makers to streamline processes, enhance productivity, and allocate resources more effectively. This model contributes not only to academic discourse but also serves as a practical tool for retail businesses, aiding in the enhancement of their internal logistics dynamics.

Keywords: lean retail, lean logisitcs, retail logistics, value-added and non-value-added

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Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

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Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

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Authors: Louise Ödlund, Danica Djuric Ilic

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From a system perspective, there are several benefits of DH. A possibility to utilize the excess heat from waste incineration and biomass-based combined heat and power (CHP) production (e.g. possibility to utilize the excess heat from electricity production) are two examples. However, in a future sustainable society, the benefits of DH may be less obvious. Due to the climate changes and increased energy efficiency of buildings, the demand for space heating is expected to decrease. Due to the society´s development towards circular economy, a larger amount of the waste will be material recycled, and the possibility for DH production by the energy recovery through waste incineration will be reduced. Furthermore, the benefits of biomass-based CHP production will be less obvious since the marginal electricity production will no longer be linked to high greenhouse gas emissions due to an increased share of renewable electricity capacity in the electricity system. The purpose of the study is (1) to provide an overview of the possible development of other sectors which may influence the DH in the future and (2) to detect new business strategies which would enable for DH to adapt to the future conditions and remain competitive to alternative heat production in the future. A system approach was applied where DH is seen as a part of an integrated system which consists of other sectors as well. The possible future development of other sectors and the possible business strategies for DH producers were searched through a systematic literature review In order to remain competitive to the alternative heat production in the future, DH producers need to develop new business strategies. While the demand for space heating is expected to decrease, the space cooling demand will probably increase due to the climate changes, but also due to the better insulation of buildings in the cases where the home appliances are the heat sources. This opens up a possibility for applying DH-driven absorption cooling, which would increase the annual capacity utilization of the DH plants. The benefits of the DH related to the energy recovery from the waste incineration will exist in the future since there will always be a need to take care of materials and waste that cannot be recycled (e.g. waste containing organic toxins, bacteria, such as diapers and hospital waste). Furthermore, by operating central controlled heat pumps, CHP plants, and heat storage depending on the intermittent electricity production variation, the DH companies may enable an increased share of intermittent electricity production in the national electricity grid. DH producers can also enable development of local biofuel supply chains and reduce biofuel production costs by integrating biofuel and DH production in local DH systems.

Keywords: district heating, sustainable business strategies, sustainable development, system approach

Procedia PDF Downloads 79

Authors: Bencherif Kada

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In forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects, and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction and area of an object, etc.) and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants and bare soils. Texture attributes seem to provide no useful information while spatial attributes of shape, compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, biodiversity, shrublands

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Authors: Krishna Prasad Regmi, Jun-Bo Tu, Cheng-Qun Hou, Li-Feng Li

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Maxillofacial trauma in a pediatric group of patients is particularly challenging, as these patients have significant differences from adults as far as the facial skeleton is concerned. Mandibular condylar fractures are common presentations to hospitals across the globe and remain the most important cause of temporomandibular joint (TMJ) ankylosis. The etiology and epidemiology of pediatric trauma involving the diacapitular condylar fractures (DFs) have been reported in a large series of patients. Nevertheless, little is known about treatment protocols for DFs in children. Accordingly, the treatment modalities for the management of pediatric fractures also differ. We suggest following the PDA and intracapsular ABC classification of condylar fracture to increase the overall postoperative satisfaction level that bypasses the change of subjective feelings of patients’ from preoperative to the postoperative condition. At the same time, use of 3-D technology and surgical navigation may also increase treatment accuracy.

Keywords: maxillofacial trauma, diacapitular fracture, condylar fracture, PDA classification

Procedia PDF Downloads 262

Authors: Ali Kirkbas

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R peaks in an electrocardiogram (ECG) are signs of cardiac activity in individuals that reveal valuable information about cardiac abnormalities, which can lead to mortalities in some cases. This paper examines the problem of detecting R-peaks in ECG signals, which is a two-class pattern classification problem in fact. To handle this problem with a reliable high accuracy, we propose to use the common vector approach which is a successful machine learning algorithm. The dataset used in the proposed method is obtained from MIT-BIH, which is publicly available. The results are compared with the other popular methods under the performance metrics. The obtained results show that the proposed method shows good performance than that of the other. methods compared in the meaning of diagnosis accuracy and simplicity which can be operated on wearable devices.

Keywords: ECG, R-peak classification, common vector approach, machine learning

Procedia PDF Downloads 52

Authors: B.-Y.-S. Lau, Y.-C.-T. Jonathan, M.-S. Alias

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Heritage trees are natural large, individual trees with exceptionally value due to association with age or event or distinguished people. In Malaysia, there is an abundance of tropical heritage trees throughout the country. It is essential to set up a repository of heritage trees to prevent valuable trees from being cut down. In this cross domain study, a web-based online expert system namely the Heritage Tree Expert Assessment and Classification (HTEAC) is developed and deployed for public to nominate potential heritage trees. Based on the nomination, tree care experts or arborists would evaluate and verify the nominated trees as heritage trees. The expert system automatically rates the approved heritage trees according to pre-defined grades via Delphi technique. Features and usability test of the expert system are presented. Preliminary result is promising for the system to be used as a full scale public system.

Keywords: arboriculture, Delphi, expert system, heritage tree, urban forestry

Procedia PDF Downloads 300

Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

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Authors: Stanislav Perepechko

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Industrial companies - one of the major sources of harmful substances to the atmosphere. The main cause of pollution on the concrete plants are cement dust emissions. All the cement silos, pneumatic transport, and ventilation systems equipped with filters, to avoid this. Today, many Russian companies have to decide on replacement morally and physically outdated filters and guided back to the electrostatic filters as usual equipment. The offered way of a cleaning of waste-free filtering of air differs in the fact that a filtering medium of the filter is used in concrete manufacture. Basalt is widespread and pollution-free material. In the course of cleaning, one part of basalt fiber and cement immediately goes to the mixer through flow-control units of initial basalt fiber and cement. Another part of basalt fiber goes to filters for purification of the air used in systems of an air lift, and ventilating emissions passes through them, and with trapped particles also goes to the mixer through flow-control units of the basalt fiber fulfilled in filters. At the same time, regulators are adjusted in such a way that total supply of basalt fiber and cement into the mixer remains invariable and corresponds to a given technological mode.

Keywords: waste-free air filtration, concrete, basalt fiber, building automation

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Authors: Liana Claudia Salanță, Anca Corina Fărcaș

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Valorization of agro-industrial by-products offers significant economic and environmental advantages. This study investigates the transformation of tomato processing residues into value-added products, contributing to waste reduction and promoting a circular, sustainable economy. Specifically, the development of sorghum flour-based crackers enriched with tomato waste powder targets the dietary requirements of individuals with celiac disease and diabetes, evaluating their nutritional and sensory properties. Tomato residues were obtained from Roma-Spania tomatoes and processed into powder through drying and grinding. The bioactive compounds, including carotenoids, lycopene, and polyphenols, were quantified using established analytical methods. Formulation of the crackers involved optimizing the incorporation of tomato powder into sorghum flour. Subsequently, their nutritional and sensory attributes were assessed. The tomato waste powder demonstrated considerable bioactive potential, with total carotenoid content measured at 66 mg/100g, lycopene at 52.61 mg/100g, and total polyphenols at 463.60 mg GAE/100g. Additionally, the crackers with a 30% powder addition exhibited the highest concentration of polyphenols. Consequently, this sample also demonstrated a high antioxidant activity of 15.04% inhibition of DPPH radicals. Nutritionally, the crackers showed a 30% increase in fiber content and a 25% increase in protein content compared to standard gluten-free products. Sensory evaluation indicated positive consumer acceptance, with an average score of 8 out of 10 for taste and 7.5 out of 10 for color, attributed to the natural pigments from tomato waste. This innovative approach highlights the potential of tomato by-products in creating nutritionally enhanced gluten-free foods. Future research should explore the long-term stability of these bioactive compounds in finished products and evaluate the scalability of this process for industrial applications. Integrating such sustainable practices can significantly contribute to waste reduction and the development of functional foods.

Keywords: tomato waste, circular economy, bioactive compounds, sustainability, health benefits

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Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

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In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.

Keywords: general metric, unsupervised learning, classification, intersection over union

Procedia PDF Downloads 35

Authors: Francielo Vendruscolo

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During industrial processing of raw materials of animal and vegetable origin, large amounts of solid, liquid and gaseous wastes are generated. Solid residues are usually materials rich in carbohydrates, protein, fiber and minerals. Brewer’s spent grain (BSG) is the main waste generated in the brewing industry, representing 85% of the waste generated in this industry. It is estimated that world’s BSG generation is approximately 38.6 x 106 t per year and represents 20-30% (w/w) of the initial mass of added malt, resulting in low commercial value by-product, however, does not have economic value, but it must be removed from the brewery, as its spontaneous fermentation can attract insects and rodents. For every 100 grams in dry basis, BSG has approximately 68 g total fiber, being divided into 3.5 g of soluble fiber and 64.3 g of insoluble fiber (cellulose, hemicellulose and lignin). In addition to dietary fibers, depending on the efficiency of the grinding process and mashing, BSG may also have starch, reducing sugars, lipids, phenolics and antioxidants, emphasizing that its composition will depend on the barley variety and cultivation conditions, malting and technology involved in the production of beer. BSG demands space for storage, but studies have proposed alternatives such as the use of drying, extrusion, pressing with superheated steam, and grinding to facilitate storage. Other important characteristics that enhance its applicability in bioremediation, effluent treatment and biotechnology, is the surface area (SBET) of 1.748 m2 g-1, total pore volume of 0.0053 cm3 g-1 and mean pore diameter of 121.784 Å, characterized as a macroporous and possess fewer adsorption properties but have great ability to trap suspended solids for separation from liquid solutions. It has low economic value; however, it has enormous potential for technological applications that can improve or add value to this agro-industrial waste. Due to its composition, this material has been used in several industrial applications such as in the production of food ingredients, fiber enrichment by its addition in foods such as breads and cookies in bioremediation processes, substrate for microorganism and production of biomolecules, bioenergy generation, and civil construction, among others. Therefore, the use of this waste or by-product becomes essential and aimed at reducing the amount of organic waste in different industrial processes, especially in breweries.

Keywords: brewer’s spent malt, agro-industrial residue, lignocellulosic material, waste generation

Procedia PDF Downloads 201