Search results for: waste classification

Authors: Prasanna Haddela

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Document analysis is a well matured yet still active research field, partly as a result of the intricate nature of building computational tools but also due to the inherent problems arising from the variety and complexity of human languages. Breaking down language barriers is vital in enabling access to a number of recent technologies. This paper investigates the application of document classification methods to new Sinhalese datasets. This language is geographically isolated and rich with many of its own unique features. We will examine the interpretability of the classification models with a particular focus on the use of evolved Lucene search queries generated using a Genetic Algorithm (GA) as a method of document classification. We will compare the accuracy and interpretability of these search queries with other popular classifiers. The results are promising and are roughly in line with previous work on English language datasets.

Keywords: evolved search queries, Sinhala document classification, Lucene Sinhala analyzer, interpretable text classification, genetic algorithm

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Authors: Issam A. Al-Khatib

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In order to achieve a significant reduction of waste amount flowing into landfills, it is important to first understand the composition of the solid municipal waste generated. Hence a detailed analysis of municipal solid waste composition has been conducted in Nablus city. The aim is to provide data on the potential recyclable fractions in the actual waste stream, with a focus on the plastic fraction. Hence, waste-sorting campaigns were conducted on mixed waste containers from five districts in Nablus city. The districts vary in terms of infrastructure and average income. The target is to obtain representative data about the potential quantity and quality of household plastic waste. The study has measured the composition of municipal solid waste collected/ transported by Nablus municipality. The analysis was done by categorizing the samples into eight primary fractions (organic and food waste, paper and cardboard, glass, metals, textiles, plastic, a fine fraction (<10 mm), and others). The study results reveal that the MSW stream in Nablus city has a significant bio- and organic waste fraction (about 68% of the total MSW). The second largest fraction is paper and cardboard (13.6%), followed by plastics (10.1%), textiles (3.2%), glass (1.9%), metals (1.8%), a fine fraction (0.5%), and other waste (0.3%). After this complete and detailed characterization of MSW collected in Nablus and taking into account the content of biodegradable organic matter, the composting could be a solution for the city of Nablus where the surrounding areas of Nablus city have agricultural activities and could be a natural outlet to the compost product. Different waste management options could be practiced in the future in addition to composting, such as energy recovery and recycling, which result in a greater possibility of reducing substantial amounts that are disposed of at landfills.

Keywords: developing countries, composition, management, recyclable, waste.

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Authors: Wafa Baccouch, Adel Ghith, Xavier Legrand, Faten Fayala

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Textile waste recycling has become a necessity considering the augmentation of the amount of waste generated each year and the ecological problems that landfilling and burning can cause. Textile waste can be recycled into many different forms according to its composition and its final utilization. Using this waste as reinforcement to composite panels is a new recycling area that is being studied. Compared to virgin fabrics, recycled ones present the disadvantage of having lower structural characteristics, when they are eco-friendly and with low cost. The objective of this work is transforming textile waste into composite material with good characteristic and low price. In this study, we used sewing as a method to improve the characteristics of the recycled textile waste in order to use it as reinforcement to composite material. Textile non-woven waste was afforded by a local textile recycling industry. Performances tests were evaluated using tensile testing machine and based on the testing direction for both reinforcements and composite panels; machine and transverse direction. Tensile tests were conducted on sewed and non sewed fabrics, and then they were used as reinforcements to composite panels via epoxy resin infusion method. Rule of mixtures is used to predict composite characteristics and then compared to experimental ones.

Keywords: composite material, epoxy resin, non woven waste, recycling, sewing, textile

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Authors: Mohammad Saberian, Reza Porhoseini, Mohammad Ali Rahgozar

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Peat is a partially carbonized vegetable tissue which is formed in wet conditions by decomposition of various plants, mosses and animal remains. This restricted definition, including only materials which are entirely of vegetative origin, conflicts with several established soil classification systems. Peat soils are usually defined as soils having more than 75 percent organic matter. Due to this composition, the structure of peat soil is highly different from the mineral soils such as silt, clay and sand. Peat has high compressibility, high moisture content, low shear strength and low bearing capacity, so it is considered to be in the category of problematic. Since this kind of soil is generally found in many countries and various zones, except for desert and polar zones, recognizing this soil is inevitably significant. The objective of this paper is to review the classification of peats based on various properties of peat soils such as organic contents, water content, color, odor, and decomposition, scholars offer various classification systems which Von Post classification system is one of the most well-known and efficient system.

Keywords: peat soil, degree of decomposition, organic content, water content, Von Post classification

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Authors: Wahyu Eko Diyanto, Amalia Dyah Arumsari, Ulfatu Layinatinnahdiyah Arrosyadi

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Tofu industry is one of the local food industry which is can being competitive industry in the ASEAN Economic Community (AEC). However, a lot of tofu entrepreneurs just thinking how to produce good quality product without considering the impact of environmental conditions from the production process. Production of tofu per day requires a number of 15 kg with liquid waste generated is 652.5 liters. That liquid waste is discharged directly into waterways, whereas tofu liquid waste contains organic compounds that quickly unraveled, so it can pollute waterways. In addition, tofu liquid waste is high in Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solid (TSS), nitrogen and phosphorus. This research is aim to create a method of handling liquid waste effectively and efficiently by using water lettuce. The method is done by observation and experiment by using phytoremediation method in the tofu liquid waste using water lettuce and adding aeration to reduce the concentration of contaminants. The results of the research analyzed the waste quality standard parameters based on SNI (National Standardization Agency of Indonesia). The efficiency concentration and parameters average of tofu liquid waste are obtained pH 3,42% (from 4,0 to be 3,3), COD 76,13% (from 3579 ppm to be 854 ppm), BOD 55 % (from 11600 ppm to be 5242 ppm), TSS 93,6% (from 3174 ppm to be 203 ppm), turbidity is 64,8% (from 977 NTU to be 1013 NTU), and temperature 36oC (from 45oC to be 40oC). The efficiency of these parameters indicates a safe value for the effluent to be channeled in waterways. Water lettuce and tofu liquid waste phytoremediation result will be used as biogas as renewable energy.

Keywords: aeration, phytoremediation, water letuce, tofu liquid waste

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Authors: Ching-Hsu Huang, Shang-Huan Wu

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In recent years, environmental awareness has increased, environmental issues caused by meat-eating have been extended to promote reducing food surplus and waste advocates. We lose more than 3 million tons of food on average on a daily basis. Private households represent the largest food-waste faction. The main purpose of this study is to design and develop household dishes by using edible food surplus. The questionnaires were conducted to find the majority of food surplus from households, including carrot peel, pumpkin, fish skin, and soy dregs—this study designed and developed the household dishes by using the leftovers. We briefly discuss the contributions of the dishes. Mapping the household dishes deepens the promotion of household food waste prevention strategies. This study also linked the results with a set of policy, education, and restaurant business options

Keywords: food waste, food surplus, household dishes design, food waste prevention strategies

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Authors: Dolores Hidalgo, Jesús M. Martín-Marroquín, Francisco Corona

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Municipal waste consist of a variety of items that are everyday discarded by the population. They are usually collected by municipalities and include waste generated by households, commercial activities (local shops) and public buildings. The composition of municipal waste varies greatly from place to place, being mostly related to levels and patterns of consumption, rates of urbanization, lifestyles, and local or national waste management practices. Each year, a huge amount of resources is consumed in the EU, and according to that, also a huge amount of waste is produced. The environmental problems derived from the management and processing of these waste streams are well known, and include impacts on land, water and air. The situation in remote areas is even worst. Difficult access when climatic conditions are adverse, remoteness of centralized municipal treatment systems or dispersion of the population, are all factors that make remote areas a real municipal waste treatment challenge. Furthermore, the scope of the problem increases significantly because the total lack of awareness of the existing risks in this area together with the poor implementation of advanced culture on waste minimization and recycling responsibly. The aim of this work is to analyze the existing situation in remote areas in reference to the production of municipal waste and evaluate the efficiency of different management alternatives. Ideas for improving waste management in remote areas include, for example: the implementation of self-management systems for the organic fraction; establish door-to-door collection models; promote small-scale treatment facilities or adjust the rates of waste generation thereof.

Keywords: door to door collection, islands, isolated areas, municipal waste, remote areas, rural communities

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Authors: Qingsheng Qi, Cuijuan Gao, Carol Sze Ki Lin

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Food waste can be defined as a by-product of food processing by industries and consumers, which has not been recycled or used for other purposes. Stringent waste regulations worldwide are pushing local companies and sectors towards higher sustainability standards. The development of novel strategies for food waste re-use is economically and environmentally sound, as it solves a waste management issue and represents an inexpensive nutrient source for biotechnological processes. For example, Yarrowia lipolytica is a yeast which can utilize hydrophobic substrates, such as fatty acids, lipids, and alkanes and simple carbon sources, such as glucose and glycerol, which can all be found in food waste. This broad substrate range makes Y. lipolytica a promising candidate for the degradation and valorisation of food waste, and for the production of organic acids, such as citric and α-ketoglutaric acids. Current research conducted in our group demonstrated that Y. lipolytica was shown to be able to produce succinic acid. In this talk, we will focus on the application of genetically modified yeast Y. lipolytica for fermentative succinic acid production with an aim to increase productivity and yield.

Keywords: food waste, succinic acid, Yarrowia lipolytica, bioplastic

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Authors: Kunwar Paritosh, Vivekanand Vivekanand, Nidhi Pareek

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Presently, India depends primarily on fossil fuels for its acute energy demand. The swift in development of India in last two decades is accentuating its natural resources and compelling expenditures to cope energy security for the habitats. A total inhabitant of 1.2 billion, observing growing industrialization; is generating 68.8 million tonnes of municipal solid waste per year, 53.7 million tonnes is collected, and only trifling amount of 10.3 million tonnes of waste is treated per year that integrates to a massive amount of unimaginable land hill. In India, waste is mostly landfilled and/or incinerated with low technology and is poorly managed. Underutilization of this waste not only gulps resources but also stresses environment, public health and bionetwork thus affecting the bioeconomy negatively. It also creates conditions that invoke inevitable expenditures and loss of its renewable energy potential. The non-scientific approach to manage waste may lead to an economy downfall, underutilization and degradation of natural resources. Waste treatment technologies must be scientifically tailored and engineered as per the type of waste where it may be utilized as a source of energy (here biogas) and nutrients employing anaerobic digestion to the sorted waste. This paper presents a brief review on current practices, key achievements and forthcoming aspects of harnessing energy from municipal solid waste in Indian scenario.

Keywords: municipal discards, organic waste, anaerobic digestion, incineration, energy

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Authors: Soukaina Oujana, Peggy Zwolinski

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Fines are heterogeneous residues created during the shredding of non-hazardous waste. They are one of the most challenging issues faced by recyclers, because they are at the present time considered as non-sortable and non-reusable mixtures destined to landfill. However, fines contain a large amount of recoverable materials that could be recycled or reused for the production of solid recovered fuel. This research is conducted in relation to a project named ValoRABES. The aim is to characterize fines and establish a suitable sorting process in order to extract the materials contained in the mixture and define their suitable recovery paths. This paper will highlight the importance of a good sampling and will propose a sampling methodology for fines characterization. First results about the characterization will be also presented.

Keywords: fines, non-hazardous waste, recovery, shredding residues, waste characterization, waste sampling

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Authors: Nadia Adnan, Muhammad Mohsin Raza, Latha Ravindran

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Based on the principles above, the study presents an economic model of food waste for consumers, intermediaries, and producers. We discriminate between purchasing and selling, purchases versus customers consumption, and gross output versus sales for each intermediary. To compensate for waste at each level of the supply chain, agents must charge higher sales prices. The research model can produce more accurate predictions about how actions (public regulations or private efforts) to reduce food waste impact markets, including indirect (cascading) effects. With a formal model, researchers demonstrate the uniqueness of these interaction effects and simulate an empirical model calibrated to market characteristics and waste rates in Saudi Arabia. Researchers demonstrate that the effects of waste reduction differ per commodity, depending on supply and demand elasticities, degree of openness to international commerce, and the beginning rates of food loss and waste at each level of the value chain. Because of the consequential effects related to the supply chain, initiatives to minimize food waste will be strengthened in some circumstances and partially countered in others.

Keywords: food loss, food waste, supply chain management, Saudi Arabia, food supply

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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Authors: Talat Ghomashchi, Zahra Akbari, Shirin Malekpour, Marjan Alimirzaee

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Mixing the waste water of industries with natural water has caused environmental pollution. So researcher try to obtain methods and optimum conditions for waste water treatment. One of important stage in waste water treatment is dissolved air flotation. DAF is used for the removal of suspended solids and oils from waste water. In this paper, the effect of several parameters on flotation efficiency with Cationic polyacrylamide as flocculant, was examined, namely, (a) concentration of cationic flocculants, (b) pH (c) fast mixing time, (d) fast mixing speed,(e) slow mixing time,(f) retention time and temperature. After design of experiment, in each trial turbidity of waste water was measured by spectrophotometer. Results show that contribution of pH and concentration of flocculant on flotation efficiency are 75% and 9% respectively. Cationic polyacrylamide led to a significant increase in the settling speed and effect of temperature is negligible. In the optimum condition, the outcome of the DAF unit is increased and amount of suspended solid and oil in waste water is decreased effectively.

Keywords: dissolved air flotation, oil industry, waste water, treatment

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Authors: R. Korchiyne, A. Sbihi, S. M. Farssi, R. Touahni, M. Tahiri Alaoui

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Trabecular bone structure is important texture in the study of osteoporosis. Legendre multifractal spectrum can reflect the complex and self-similarity characteristic of structures. The main objective of this paper is to develop a new technique of medical image classification based on Legendre multifractal spectrum. Novel features have been developed from basic geometrical properties of this spectrum in a supervised image classification. The proposed method has been successfully used to classify medical images of bone trabeculations, and could be a useful supplement to the clinical observations for osteoporosis diagnosis. A comparative study with existing data reveals that the results of this approach are concordant.

Keywords: multifractal analysis, medical image, osteoporosis, fractal dimension, Legendre spectrum, supervised classification

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Authors: Ren Moses

Abstract:

The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

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Authors: R. Santos Jiménez, A. San-Antonio-González, M. del Río Merino, M. González Cortina, C. Viñas Arrebola

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On average, Europe generates around 890 million tons of construction and demolition waste (CDW) per year and only 50% of these CDW are recycled. This is far from the objectives determined in the European Directive for 2020 and aware of this situation, the European Countries are implementing national policies to prevent the waste that can be avoidable and to promote measures to increase recycling and recovering. In Spain, one of these measures has been the development of a CDW recycling guide for the manufacture of mortar, concrete, bricks and lightweight aggregates. However, there is still not enough information on the possibility of incorporating CDW materials in the manufacture of gypsum products. In view of the foregoing, the Universidad Politécnica de Madrid is creating a database with information on the possibility of incorporating CDW materials in the manufacture of gypsum products. The objective of this study is to improve this database by analysing the feasibility of incorporating two different CDW in a gypsum matrix: ceramic waste bricks (perforated brick and double hollow brick), and extruded polystyrene (XPS) waste. Results show that it is possible to incorporate up to 25% of ceramic waste and 4% of XPS waste over the weight of gypsum in a gypsum matrix. Furhtermore, with the addition of ceramic waste an 8% of surface hardness increase and a 25% of capillary water absorption reduction can be obtained. On the other hand, with the addition of XPS, a 26% reduction of density and a 37% improvement of thermal conductivity can be obtained.

Keywords: CDW, waste materials, ceramic waste, XPS, construction materials, gypsum

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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Authors: C. Asha Poorna, P. G. Vinod, A. R. R. Menon

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Currently increasing population and their activities like urbanization and industrialization generating the greatest environmental, issue called Waste. And the major problem in waste management is selection of an appropriate site for waste disposal. The selection of suitable site have constrains like environmental, economical and political considerations. In this paper we discuss the strategies to be followed while selecting a site for decentralized system for solid waste disposal, using Geographic Information System (GIS), the Analytical Hierarchy Process (AHP) and the remote sensing method for Thiruvananthapuram corporation area. It is located on the west coast of India near the extreme south of the mainland. It lies on the shores of Killiyar and Karamana River. Being on the basin the waste managements must be regulated with the water body. The different criteria considered for waste disposal site selection are lithology, surface water, aquifer, groundwater, land use, contours, aspect, elevation, slope, and distance to road, distance from settlement are examined in relation to land fill site selection. Each criterion was identified and weighted by AHP score and mapped using GIS technique and suitable map is prepared by overlay analysis.

Keywords: waste disposal, solid waste management, Geographic Information System (GIS), Analytical Hierarchy Process (AHP)

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Authors: Anung Style Bukhori, Ani Dijah Rahajoe

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Poverty poses a significant challenge in Indonesia, requiring an effective analytical approach to understand and address this issue. In this research, we applied the Naïve Bayes classification method to examine and classify poverty data in Indonesia. The main focus is on classifying data using RapidMiner, a powerful data analysis platform. The analysis process involves data splitting to train and test the classification model. First, we collected and prepared a poverty dataset that includes various factors such as education, employment, and health..The experimental results indicate that the Naïve Bayes classification model can provide accurate predictions regarding the risk of poverty. The use of RapidMiner in the analysis process offers flexibility and efficiency in evaluating the model's performance. The classification produces several values to serve as the standard for classifying poverty data in Indonesia using Naive Bayes. The accuracy result obtained is 40.26%, with a moderate recall result of 35.94%, a high recall result of 63.16%, and a low recall result of 38.03%. The precision for the moderate class is 58.97%, for the high class is 17.39%, and for the low class is 58.70%. These results can be seen from the graph below.

Keywords: poverty, classification, naïve bayes, Indonesia

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Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

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This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

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Authors: Syali Pradhan, Neetu Jha

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The Marigold flower is used in religious places for offering and decoration purpose every day. The flowers are discarded near trees or in aquatic bodies. This floral waste can be used for extracting dyes or oils. Still the secondary waste remains after processing which need to be addressed. This research aims to provide green and clean power using secondary floral waste available after processing. The carbonization of floral waste produce carbon material with high surface area and enhance active site for more reaction. The Hybrid supercapacitors are more stable, offer improved operating temperature and use less toxic material compared to battery. They provide enhanced energy density compared to supercapacitors. Hence, hybrid supercapacitor designed using waste material would be more practicable for future energy application. Here, we present the utilization of carbonized floral waste as supercapacitor electrode material. This material after carbonization gets graphitized and shows high surface area, optimum porosity along with high conductivity. Hence, this material has been tested as cathode electrode material for high performance zinc storage hybrid supercapacitor. High energy storage along with high stability has been obtained using this cathodic waste material as electrode.

Keywords: marigold, flower waste, energy storage, cathode, supercapacitor

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Authors: Jalel Khelil

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In order to improve reliability of Gas Turbine machine especially its generator equipment, a fault diagnosis system based on fuzzy approach is proposed. Three various methods namely K-NN (K-nearest neighbors), F-KNN (Fuzzy K-nearest neighbors) and FNM (Fuzzy nearest mean) are adopted to provide the measurement of relative strength of vibration defaults. Both applications consist of two major steps: Feature extraction and default classification. 09 statistical features are extracted from vibration signals. 03 different classes are used in this study which describes vibrations condition: Normal, unbalance defect, and misalignment defect. The use of the fuzzy approaches and the classification results are discussed. Results show that these approaches yield high successful rates of vibration default classification.

Keywords: fault diagnosis, fuzzy classification k-nearest neighbor, vibration

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Authors: Khamdan Cahyari, Gumbolo Hadi Susanto, Pratikno Hidayat, Sukirman

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University canteen waste was used as raw material to produce biogas in Faculty of Industrial Technology, Islamic University of Indonesia. This faculty was home to more than 3000 students and lecturers who work and study for 5 days/week (8 hours/day). It produced approximately 85 ton/year organic fraction of canteen waste. Yet, this waste had been dumped for years in landfill area which cause severe environmental problems. It was proposed to utilize the waste as raw material for producing renewable energy source of biogas. This research activities was meant to investigate the effect of organic loading rate (OLR) and retention time (RT) of continuous anaerobic digestion process for 200 days. Organic loading rate was set at value 2, 3, 4 and 5 g VS/l/d whereas the retention time was adjusted at 30, 24, 18 and 14.4 days. Optimum condition was achieved at OLR 4 g VS/l/d and RT 24 days with biogas production rate between 0.75 to 1.25 liter/day (40-60% CH4). This indicated that the utilization of canteen waste to produce biogas was promising method to mitigate environmental problem of university canteen waste. Furthermore, biogas could be used as alternative energy source to supply energy demand at the university. This implementation is simultaneous solution for both waste and energy problems to achieve green campus.

Keywords: canteen waste, biogas, anaerobic digestion, university, green campus

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Authors: Bing Li, Zhi Li, Yilong Yang

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Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

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Authors: Bhalke D. G., Bormane D. S., Kharate G. K.

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This paper presents classification of musical instrument using machine learning techniques. The classification has been carried out using temporal, spectral, cepstral and wavelet features. Detail feature analysis is carried out using separate and combined features. Further, instrument model has been developed using K-Nearest Neighbor and Support Vector Machine (SVM). Benchmarked McGill university database has been used to test the performance of the system. Experimental result shows that SVM performs better as compared to KNN classifier.

Keywords: feature extraction, SVM, KNN, musical instruments

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Authors: Hankyu Lee, Seoung Bum Kim

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The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

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Authors: Fahad K. Alqahtani

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Nowadays construction industry is developing means to incorporate waste products in concrete to ensure sustainability. To meet the need of construction industry, a synthetic aggregate was developed using optimized technique called compression moulding press technique. The manufactured aggregate comprises mixture of plastic, waste which acts as binder, together with by-product waste which acts as fillers. The physical properties and microstructures of the inert materials and the manufactured aggregate were examined and compared with the conventional available aggregates. The outcomes suggest that the developed aggregate has potential to be used as substitution of conventional aggregate due to its less weight and water absorption. The microstructure analysis confirmed the efficiency of the manufacturing process where the final product has the same mixture of binder and filler.

Keywords: fly ash, plastic waste, quarry fine, red sand, synthetic aggregate

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Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

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Planet image is a new data source from planet lab. This research is concerned with the assessment of Planet image for land cover mapping. Two pixel based classifiers and one subpixel based classifier were compared. Firstly, rectification of Planet image was performed. Secondly, a comparison between minimum distance, maximum likelihood and neural network classifications for classification of Planet image was performed. Thirdly, the overall accuracy of classification and kappa coefficient were calculated. Results indicate that neural network classification is best followed by maximum likelihood classifier then minimum distance classification for land cover mapping.

Keywords: planet image, land cover mapping, rectification, neural network classification, multilayer perceptron, soft classifiers, hard classifiers

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Authors: Saidu Ibrahim, Winston M. W. Shakantu

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The problem of construction material waste remains unresolved, as a significant percentage of the materials delivered to some project sites end up as waste which might result in additional project cost. Cost overrun is a problem which affects 90% of the completed projects in the world. The argument on how to eliminate it has been on-going for the past 70 years, but there is neither substantial improvement nor significant solution for mitigating its detrimental effects. Research evidence has proposed various construction cost overruns and material-waste management approaches; nonetheless, these studies failed to give a clear indication on the framework and the equation for managing construction material waste and cost overruns. Hence, this research aims to develop a conceptual framework and a mathematical equation for managing material waste and cost overrun in the construction industry. The paper adopts the desktop methodological approach. This involves comparing the causes of material waste and those of cost overruns from the literature to determine the possible relationship. The review revealed a relationship between material waste and cost overrun that; increase in material waste would result to a corresponding increase in the amount of cost overrun at both the pre-contract and the post contract stages of a project. It was found from the equation that achieving an effective construction material waste management must ensure a “Good Quality-of-Planning, Estimating, and Design Management” and a “Good Quality- of-Construction, Procurement and Site Management”; a decrease in “Design Complexity” which would reduce “Material Waste” and subsequently reduce the amount of cost overrun by 86.74%. The conceptual framework and the mathematical equation developed in this study are recommended to the professionals of the construction industry.

Keywords: conceptual framework, cost overrun, material waste, project stags

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Authors: José Dinis-Carvalho, Levi Guimarães, Celina Leão, Rui Sousa, Rosa Eliza Vieira, Larissa Thomaz, Kelliane Guerreiro

Abstract:

This research paper investigates the efficacy of waste identification diagrams (WIDs) as a tool for waste reduction and management within the Manaus Industrial Pole. The study focuses on assessing the practical application and effectiveness of WIDs in identifying, categorizing, and mitigating various forms of waste generated across industrial processes. Employing a mixed-methods approach, including a qualitative questionnaire applied to 5 companies and quantitative data analysis with SPSS statistical software, the research evaluates the implementation and impact of WIDs on waste reduction practices in select industries within the Manaus Industrial Pole. The findings contribute to understanding the utility of WIDs as a proactive strategy for waste management, offering insights into their potential for fostering sustainable practices and promoting environmental stewardship in industrial settings. The study also discusses challenges, best practices, and recommendations for optimizing the utilization of WIDs in industrial waste management, thereby addressing the broader implications for sustainable industrial development.

Keywords: waste identification diagram, value stream mapping, overall equipment effectiveness, lean manufacturing

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