•PSO based CVRP model for waste collection and route optimization.•TWL and scheduling concepts are applied in PSO based CVRP model.•Waste route is optimized based on collected waste, travel distance ...and tightness.•PSO based CVRP model is a valuable tool for waste collection route optimization.
Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70–75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts.
•Waste collection and transportation incur the huge budget in waste management.•BSA in CVRP model for waste collection and route optimization.•TWL and scheduling concepts are applied in BSA based ...CVRP model.•BSA in CVRP model improves collection efficiency, reduces costs and emissions.•BSA in CVRP model is a valuable tool for waste collection route optimization.
Waste collection is an important part of waste management that involves different issues, including environmental, economic, and social, among others. Waste collection optimization can reduce the waste collection budget and environmental emissions by reducing the collection route distance. This paper presents a modified Backtracking Search Algorithm (BSA) in capacitated vehicle routing problem (CVRP) models with the smart bin concept to find the best optimized waste collection route solutions. The objective function minimizes the sum of the waste collection route distances. The study introduces the concept of the threshold waste level (TWL) of waste bins to reduce the number of bins to be emptied by finding an optimal range, thus minimizing the distance. A scheduling model is also introduced to compare the feasibility of the proposed model with that of the conventional collection system in terms of travel distance, collected waste, fuel consumption, fuel cost, efficiency and CO2 emission. The optimal TWL was found to be between 70% and 75% of the fill level of waste collection nodes and had the maximum tightness value for different problem cases. The obtained results for four days show a 36.80% distance reduction for 91.40% of the total waste collection, which eventually increases the average waste collection efficiency by 36.78% and reduces the fuel consumption, fuel cost and CO2 emission by 50%, 47.77% and 44.68%, respectively. Thus, the proposed optimization model can be considered a viable tool for optimizing waste collection routes to reduce economic costs and environmental impacts.
•Classification of available technologies for SWM system in four core category.•Organization of technology based SWM systems in three main groups.•Summary of SWM systems with target application, ...methodology and functional domain.•Issues and challenges are highlighted for further design of a sustainable system.
In the backdrop of prompt advancement, information and communication technology (ICT) has become an inevitable part to plan and design of modern solid waste management (SWM) systems. This study presents a critical review of the existing ICTs and their usage in SWM systems to unfold the issues and challenges towards using integrated technologies based system. To plan, monitor, collect and manage solid waste, the ICTs are divided into four categories such as spatial technologies, identification technologies, data acquisition technologies and data communication technologies. The ICT based SWM systems classified in this paper are based on the first three technologies while the forth one is employed by almost every systems. This review may guide the reader about the basics of available ICTs and their application in SWM to facilitate the search for planning and design of a sustainable new system.
Selecting a suitable Multi Criteria Decision Making (MCDM) method is a crucial stage to establish a Solid Waste Management (SWM) system. Main objective of the current study is to demonstrate and ...evaluate a proposed method using Multiple Criteria Decision Making methods (MCDM). An improved version of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) applied to obtain the best municipal solid waste management method by comparing and ranking the scenarios. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Besides, Viekriterijumsko Kompromisno Rangiranje (VIKOR) compromise solution method applied for sensitivity analyses. The proposed method can assist urban decision makers in prioritizing and selecting an optimized Municipal Solid Waste (MSW) treatment system. Besides, a logical and systematic scientific method was proposed to guide an appropriate decision-making.
A modified TOPSIS methodology as a superior to existing methods for first time was applied for MSW problems. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Next, 11 scenarios of MSW treatment methods are defined and compared environmentally and economically based on the waste management conditions. Results show that integrating a sanitary landfill (18.1%), RDF (3.1%), composting (2%), anaerobic digestion (40.4%), and recycling (36.4%) was an optimized model of integrated waste management. An applied decision-making structure provides the opportunity for optimum decision-making. Therefore, the mix of recycling and anaerobic digestion and a sanitary landfill with Electricity Production (EP) are the preferred options for MSW management.
•The study is a new approach of multi-criteria analysis by TOPSIS and VIKOR.•A systematic and logical scientific method was proposed for SWM.•TOPSIS was applied to rank treatment methods as a contribution of the study.•The model has less potential of environmental impacts and more economic benefits.
Although intratumor heterogeneity has been inferred in multiple myeloma (MM), little is known about its subclonal phylogeny. To describe such phylogenetic trees in a series of patients with MM, we ...perform whole-exome sequencing and single-cell genetic analysis. Our results demonstrate that at presentation myeloma is composed of two to six different major clones, which are related by linear and branching phylogenies. Remarkably, the earliest myeloma-initiating clones, some of which only had the initiating t(11;14), were still present at low frequencies at the time of diagnosis. For the first time in myeloma, we demonstrate parallel evolution whereby two independent clones activate the RAS/MAPK pathway through RAS mutations and give rise subsequently to distinct subclonal lineages. We also report the co-occurrence of RAS and interferon regulatory factor 4 (IRF4) p.K123R mutations in 4% of myeloma patients. Lastly, we describe the fluctuations of myeloma subclonal architecture in a patient analyzed at presentation and relapse and in NOD/SCID-IL2Rγ(null) xenografts, revealing clonal extinction and the emergence of new clones that acquire additional mutations. This study confirms that myeloma subclones exhibit different survival properties during treatment or mouse engraftment. We conclude that clonal diversity combined with varying selective pressures is the essential foundation for tumor progression and treatment resistance in myeloma.
Protection of groundwater quality from various natural and anthropogenic forces is a prime concern in Bangladesh. In this study, we utilized groundwater geochemistry of shallow and deeper aquifers to ...investigate the hydrogeochemical processes controlling water quality, and the sources and mechanism of Arsenic (As) release to water and associated human health risks in the Faridpur district, Bangladesh. Analysis of hydrochemical facies indicated that groundwaters were Ca–Mg–HCO
3
type and that water–rock interactions were the dominant factors controlling their major-ion chemical composition. The dissolution of calcite, dolomite, and silicates, as well as cation exchange processes regulated the major ions chemistry in the groundwater. Dissolved fluoride (F
−
) concentrations (0.02–0.4 mg/L) were lower than the drinking water standard of 1.5 mg/L set by the World Health Organization (WHO). Arsenic contamination of groundwater is among the biggest health threats in Bangladesh. The measured As concentration (0.01–1.46 mg/L with a mean of 0.12 mg/L) exceeded the maximum permissible limit of Bangladesh and WHO for drinking water. The estimated carcinogenic risk of As exceeded the upper benchmark of 1 × 10
–4
for both adult and children, and health threats from shallow groundwater were more severe than the deeper water. The vertical distribution of As resembled Fe and Mn with their higher concentrations in shallow Holocene aquifers and lower in deeper Pleistocene aquifers. Speciation calculation indicated the majority of groundwater samples were oversaturated with respect to siderite, calcite, and dolomite, while undersaturated with respect to rhodochrosite. The saturation state of the minerals along with other processes may exert kinetic control on As, Fe, and Mn distribution in groundwater and lead to their lack of statistically significant correlations. Microbially mediated reductive dissolution of Fe and Mn oxyhydroxides is envisaged as the primary controlling mechanism of As mobilization in Faridpur groundwater. Pyrite oxidation was not postulated as a plausible explanation of As pollution.
This paper presents solid waste bin level detection and classification using gray level co-occurrence matrix (GLCM) feature extraction methods. GLCM parameters, such as displacement, d, quantization, ...G, and the number of textural features, are investigated to determine the best parameter values of the bin images. The parameter values and number of texture features are used to form the GLCM database. The most appropriate features collected from the GLCM are then used as inputs to the multi-layer perceptron (MLP) and the K-nearest neighbor (KNN) classifiers for bin image classification and grading. The classification and grading performance for DB1, DB2 and DB3 features were selected with both MLP and KNN classifiers. The results demonstrated that the KNN classifier, at KNN = 3, d = 1 and maximum G values, performs better than using the MLP classifier with the same database. Based on the results, this method has the potential to be used in solid waste bin level classification and grading to provide a robust solution for solid waste bin level detection, monitoring and management.
► A GLCM method is used for solid waste bin level detection and classification. ► GLCM is investigated to determine the best parameter values of the bin images. ► MLP and KNN classifiers are used for bin image classification and grading. ► The KNN classifier performs better than that of the MLP with the same database. ► A robust solution for bin level detection, collection, monitoring and management.
► GLAM feature extraction method is used for bin level detection and classification. ► The GLAM parameters are investigated to determine the best parameter values of the bin images. ► MLP and KNN ...classifiers are used for bin image classification and grading. ► MLP classifier performs better than that of the KNN with the same database. ► A robust solution for solid waste bin level detection, collection, monitoring and management.
An advanced image processing approach integrated with communication technologies and a camera for waste bin level detection has been presented. The proposed system is developed to address environmental concerns associated with waste bins and the variety of waste being disposed in them. A gray level aura matrix (GLAM) approach is proposed to extract the bin image texture. GLAM parameters, such as neighboring systems, are investigated to determine their optimal values. To evaluate the performance of the system, the extracted image is trained and tested using multi-layer perceptions (MLPs) and K-nearest neighbor (KNN) classifiers. The results have shown that the accuracy of bin level classification reach acceptable performance levels for class and grade classification with rates of 98.98% and 90.19% using the MLP classifier and 96.91% and 89.14% using the KNN classifier, respectively. The results demonstrated that the system performance is robust and can be applied to a variety of waste and waste bin level detection under various conditions.
► RFID and communication technologies have been integrated for solid waste bin and truck monitoring system. ► Theoretical framework and algorithm have been developed for the successful hardware ...implementation. ► The information’s are complied and stored for monitoring and management activities. ► The waste estimation and related information have been displayed in the GUI. ► The developed system provides a robust solution for solid waste monitoring and management.
This paper deals with a system of integration of Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system. RFID, GPS, GPRS and GIS along with camera technologies have been integrated and developed the bin and truck intelligent monitoring system. A new kind of integrated theoretical framework, hardware architecture and interface algorithm has been introduced between the technologies for the successful implementation of the proposed system. In this system, bin and truck database have been developed such a way that the information of bin and truck ID, date and time of waste collection, bin status, amount of waste and bin and truck GPS coordinates etc. are complied and stored for monitoring and management activities. The results showed that the real-time image processing, histogram analysis, waste estimation and other bin information have been displayed in the GUI of the monitoring system. The real-time test and experimental results showed that the performance of the developed system was stable and satisfied the monitoring system with high practicability and validity.
The survey description and the near-, mid-, and far-infrared flux properties are presented for the 258 galaxies in the Local Volume Legacy (LVL). LVL is a Spitzer Space Telescope legacy program that ...surveys the local universe out to 11 Mpc, built upon a foundation of ultraviolet, H Delta *a, and Hubble Space Telescope imaging from 11HUGS (11 Mpc H Delta *a and Ultraviolet Galaxy Survey) and ANGST (ACS Nearby Galaxy Survey Treasury). LVL covers an unbiased, representative, and statistically robust sample of nearby star-forming galaxies, exploiting the highest extragalactic spatial resolution achievable with Spitzer. As a result of its approximately volume-limited nature, LVL augments previous Spitzer observations of present-day galaxies with improved sampling of the low-luminosity galaxy population. The collection of LVL galaxies shows a large spread in mid-infrared colors, likely due to the conspicuous deficiency of 8 Delta *mm polycyclic aromatic hydrocarbon emission from low-metallicity, low-luminosity galaxies. Conversely, the far-infrared emission tightly tracks the total infrared emission, with a dispersion in their flux ratio of only 0.1 dex. In terms of the relation between the infrared-to-ultraviolet ratio and the ultraviolet spectral slope, the LVL sample shows redder colors and/or lower infrared-to-ultraviolet ratios than starburst galaxies, suggesting that reprocessing by dust is less important in the lower mass systems that dominate the LVL sample. Comparisons with theoretical models suggest that the amplitude of deviations from the relation found for starburst galaxies correlates with the age of the stellar populations that dominate the ultraviolet/optical luminosities.
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