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Search results for: REGRESSION ANALYSIS
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Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach
PublicationMonitoring contamination in river water is an expensive procedure, particularly for developing countries where pollution is a significant problem. This study was conducted to provide a pollution monitoring strategy that reduces the cost of laboratory analysis. The new monitoring strategy was designed as a result of cluster and regression analysis on field data collected from an industrially influenced river. Pollution sources in...
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Gender wage gap convergence and skills heterogeneity in Poland (2005-2014) - quantile regression analysis based on microdata from EUSILC.
PublicationIn this article we quantify the magnitude and evolution of gender wage differentials in Poland over the years 2005 – 2014 using microlevel data from EU-SILC database (Statistics on Income and Living Conditions). In the study gender wage gap is examined through quantile regression analysis. It is shown that the gender wage gap varies along the wage distribution with workers’ skills heterogeneity playing a role. Additionally, the...
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The Modifiable Areal Unit Problem – Analysis of Correlation and Regression
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Sensitivity analysis based on non-intrusive regression-based polynomial chaos expansion for surgical mesh modelling
PublicationThe modelling of a system containing implants used in ventral hernia repair and human tissue suffers from many uncertainties. Thus, a probabilistic approach is needed. The goal of this study is to define an efficient numerical method to solve non-linear biomechanical models supporting the surgeon in decisions about ventral hernia repair. The model parameters are subject to substantial variability owing to, e.g., abdominal wall...
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Metabolic activity of tree saps of different origin towards cultured human cells in the light of grade correspondence analysis and multiple regression modeling
PublicationTree saps are nourishing biological media commonly used for beverage and syrup production. Although the nutritional aspect of tree saps is widely acknowledged, the exact relationship between the sap composition, origin, and effect on the metabolic rate of human cells is still elusive. Thus, we collected saps from seven different tree species and conducted composition-activity analysis. Saps from trees of Betulaceae, but not from...
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Fast and Efficient Four-Class Motor Imagery EEG Signals Analysis Using CSP-Ridge Regression Algorithm for the Purpose of Brain-Computer Interface."
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The Effect of Probiotics on Symptoms, Gut Microbiota and Inflammatory Markers in Infantile Colic: A Systematic Review, Meta-Analysis and Meta-Regression of Randomized Controlled Trials
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The Effect of Probiotics and Synbiotics on Risk Factors Associated with Cardiometabolic Diseases in Healthy People—A Systematic Review and Meta-Analysis with Meta-Regression of Randomized Controlled Trials
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Application of Regression Line to Obtain Specified Number of Points in Reduced Large Datasets
PublicationModern measurement techniques like scanning technology or sonar measurements, provide large datasets, which are a reliable source of information about measured object, however such datasets are sometimes difficult to develop. Therefore, the algorithms for reducing the number of such sets are incorporated into their processing. In the reduction algorithms based on the...
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Tolerance-Aware Multi-Objective Optimization of Antennas by Means of Feature-Based Regression Surrogates
PublicationAssessing the immunity of antenna design to fabrication tolerances is an important consideration, especially when the manufacturing process has not been predetermined. At the same time, the antenna parameter tuning should be oriented toward improving the performance figures pertinent to both electrical (e.g., input matching) and field properties (e.g., axial ratio bandwidth) as much as possible. Identification of available trade-offs...
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Assessment of wastewater quality indicators for wastewater treatment influent using an advanced logistic regression model
PublicationInfluent quality indicators play a significant role in wastewater treatment plant performance due to their correlation with reactor operations and effluent quality. However, selecting a specific/best parameter indicator for predicting influent wastewater quality is one of the challenges in wastewa- ter treatment. This study, therefore, focused on determining suitable variables as influent quality indicators. For this purpose, a...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublicationThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Application of Generalized Regression Neural Network and Gaussian Process Regression for Modelling Hybrid Micro-Electric Discharge Machining: A Comparative Study
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Application of Multivariate Analysis Methods in Welding Engineering
PublicationPhenomena and processes taking place during welding are usually very complex and, for this reason, should be described using multivariate methods. The article discusses the methodological basis and selected application areas as regards the solving of welding problems using statistical multivariate methods. In addition, the article presents exemplary applications of the design of experiment, multiple regression analysis, cluster...
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Novel liquid chromatography method based on linear weighted regression for the fast determination of isoprostane isomers in plasma samples using sensitive tandem mass spectrometry detection
PublicationA simple, fast, sensitive and accurate methodology based on a LLE followed by liquid chromatography–tandem mass spectrometry for simultaneous determination of four regioisomers (8-iso prostaglandin F2α, 8-iso-15(R)-prostaglandin F2α, 11β-prostaglandin F2α, 15(R)-prostaglandin F2α) in routine analysis of human plasma samples was developed. Isoprostanes are stable products of arachidonic acid peroxidation and are regarded as the...
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Determination of benzo(a)pyrene content in PM10 using regression methods
PublicationThe paper presents an attempt of application of multidimensional linear regression to estimation of an empirical model describing the factors influencing on B(a)P content in suspended dust PM10 in Olsztyn and Elbląg city regions between 2010 and 2013. During this period annual average concentration of B(a)P in PM10 exceeded the admissible level 1.5-3 times. Conducted investigations confirm that the reasons of B(a)P concentration...
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Aerodynamic Shape Optimization for Delaying Dynamic Stall of Airfoils by Regression Kriging
PublicationThe phenomenon of dynamic stall produce adverse aerodynamic loading which can adversely affect the structural strength and life of aerodynamic systems. Aerodynamic shape optimization (ASO) provides an effective approach for delaying and mitigating dynamic stall characteristics without the addition of auxiliary system. ASO, however, requires multiple evaluations time-consuming computational fluid dynamics models. Metamodel-based...
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Iterative‐recursive estimation of parameters of regression models with resistance to outliers on practical examples
PublicationHere, identification of processes and systems in the sense of the least sum of absolute values is taken into consideration. The respective absolute value estimators are recognised as exceptionally insensitive to large measurement faults or other defects in the processed data, whereas the classical least squares procedure appears to be completely impractical for processing the data contaminated with such parasitic distortions. Since...
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Effect of Protoberberine-Rich Fraction of Chelidonium majus L. on Endometriosis Regression
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Regression points in non-intrusive polynomial chaos expansion method and D-optimal design
PublicationThe paper addresses selected issues of uncertainty quantification in the modelling of a system containing surgical mesh used in ventral hernia repair. Uncertainties in the models occur e.g. due to variability of abdominal wall properties among others. In order to include them, a non-intrusive regression-based polynomial chaos expansion method is employed. Its accuracy depends on the choice of regression points. In the study a relation...
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The analysis of firms’ involvement in internationalisation and determinants of its intensity – an analysis for developing and post-transition economies
PublicationThe study presents the empirical analysis of firms’ involvement in different forms of internationalisation: export, indirect export, import, indirect import and finally simultaneous exporting and importing. The analysis is based on firm-level data from the World Bank Enterprise Survey (March 2017 release). The empirical part is divided into two stages. Firstly account is taken of firms’ heterogeneity and then a Melitz type analysis...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Decisional DNA with embedded Relief-F linear regression for knowledge and experience management
PublicationOmowiono zastowania Decyzyjnego DNA, regresji liniowej oraz funkcji RELIEF-F w procesach formalnego modelowania i wspomagania zarzadzania wiedza oraz zarzadzania doswiadczeniem.
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublicationFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm
PublicationThis paper analyses the effectiveness of determining gas concentrations by using a prototype WO3 resistive gas sensor together with fluctuation enhanced sensing. We have earlier demonstrated that this method can determine the composition of a gas mixture by using only a single sensor. In the present study, we apply Least-Squares Support-Vector-Machine-based (LS-SVM-based) nonlinear regression to determine the gas concentration...
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Fuzzy regresion approach to road safety analysis at regional level
PublicationRoad safety modelling on regional level of NUTS 2 in the EU is the complex issue and authors of this article indicate this in previous publications. NUTS 2 are basic regions for the application of regional policies (0.8-3 m inhabitants). During multivariate models development they discovered that it is difficult to make regression model well described all regions, even if they are from one country. In the first step Poisson model...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Prediction of Peptide Retention at Different HPLC Conditions from Multiple Linear Regression Models
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SZACOWANIE ZAWARTOŚCI BENZO(a)PIRENU W PYLE ZAWIESZONYM PM10 W AGLOMERACJI TRÓJMIEJSKIEJ ZA POMOCĄ WIELOWYMIAROWEJ REGRESJI LINIOWEJ=ESTIMATION OF BENZO(A)PYRENE CONTENT IN SUSPENDED DUST PM10 IN TRI-CITY AGGLOMERATION USING MULTIDIMENSIONAL LINEAR REGRESSION
PublicationW pracy przedstawiono próbę oszacowania przy pomocy wielowymiarowej regresji liniowej modelu empirycznego opisującego czynniki wpływające na zawartość B(a)P w pyle zawieszonym PM10 w Aglomeracji Trójmiejskiej w latach 2008-2011. Na przestrzeni tych lat średnioroczne stężenie B(a)P w PM10 wzrosło ponad dwukrotnie i ponad trzykrotnie przewyższa poziom docelowy. Z przeprowadzonych analiz wynika, że główną przyczyną wzrostu stężenia...
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Rapid Design Tuning of Miniaturized Rat-Race Couplers Using Regression-Based Equivalent Network Surrogates
PublicationA simple technique for fast design tuning of compact rat-race couplers is presented. Our approach involves equivalent circuit representation, corrected by nonlinear functions of frequency with coefficients extracted through nonlinear regression. At the same time, the tuning process connects two levels of coupler representation: EM simulation of the entire circuit and re-optimization of the coupler building blocks (slow-wave cells...
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Application of Multinomial Logistic Regression to Model the Impact of Rainfall Genesis on the Performance of Storm Overflows: Case Study
PublicationIn this study, a mathematical model was proposed to analyze the performance of storm overfows. The model included the infuence of rainfall genesis on the duration of storm overfow, its volume, and the maximum instantaneous fow. The multinomial logistic regression model, which has not been used so far to model objects located in a stormwater system, was proposed to simulate the duration of storm overfow. The Iman–Conover method,...
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Optimization-Based Robustness Enhancement of Compact Microwave Component Designs with Response Feature Regression Surrogates
PublicationThe ability to evaluate the effects of fabrication tolerances and other types of uncertainties is a critical part of microwave design process. Improving the immunity of the device to parameter deviations is equally important, especially when the performance specifications are stringent and can barely be met even assuming a perfect manufacturing process. In the case of modern miniaturized microwave components of complex topologies,...
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublicationThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method
PublicationElectrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric...
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Residue-Pole Methods for Variability Analysis of S-parameters of Microwave Devices with 3D FEM and Mesh Deformation
PublicationThis paper presents a new approach for variability analysis of microwave devices with a high dimension of uncertain parameters. The proposed technique is based on modeling an approximation of system by its poles and residues using several modeling methods, including ordinary kriging, Adaptive Polynomial Chaos (APCE), and Support Vector Machine Regression (SVM). The computational cost is compared with the traditional Monte-Carlo...
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Roughness evaluation of turned composite surfaces by analysis of the shape of Autocorrelation Function
PublicationIn this paper, the application of an Autocorrelation Function for the characterisation of surface topography was validated. The roughness evaluation of turned composite surfaces was supported by sophisticated studies of the Autocorrelation Function properties, considering especially the shape of the function. Details were measured with the optical method. The selection of the surface roughness evaluation procedures was carried...
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Fracture mechanics model of cutting power versus widespread regression equations while wood sawing with circular saw blades
PublicationA comparison of the theoretical cutting power consumption results forecasted with the model (FM_CM model) which include work of separation (fracture toughness) in addition to plasticity and friction, and two widespread regression equations while wood sawing with circular saw blades has been described. in and cutting power consumption forecasted. In computations of the cutting power consumption during rip sawing of Scots pine wood...
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Three-dimensional geographically weighted inverse regression (3GWR) model for satellite derived bathymetry using Sentinel-2 observations
PublicationCurrent trends of development of satellite derived bathymetry (SDB) models rely on applying calibration techniques including analytical approaches, neuro-fuzzy systems, regression optimization and others. In most of the cases, the SDB models are calibrated and verified for test sites, that provide favourable conditions for the remote derivation of bathymetry such as high water clarity, homogenous bottom type, low amount of sediment...
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A Meta-Analysis of Pulse Arrival Time Based Blood Pressure Estimation
PublicationThe paper presents a preliminary meta-analysis of the sample correlation between pulse arrival time (PAT) and blood pressure (BP). The aim of the study was to verify sample correlation coefficient between PAT and BP using an affine model BP = a · P AT + b for systolic and diastolic blood pressure. The databases included in the search were the IEEE Xplore Digital Library, Springer Link and Google Scholar. Only papers from 2005 to...
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Estimation of Average Speed of Road Vehicles by Sound Intensity Analysis
PublicationConstant monitoring of road traffic is important part of modern smart city systems. The proposed method estimates average speed of road vehicles in the observation period, using a passive acoustic vector sensor. Speed estimation based on sound intensity analysis is a novel approach to the described problem. Sound intensity in two orthogonal axes is measured with a sensor placed alongside the road. Position of the apparent sound...
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Global sensitivity analysis of membrane model of abdominal wall with surgical mesh
PublicationThe paper addresses the issue of ventral hernia repair. Finite Element simulations can be helpful in the optimization of hernia parameters. A membrane abdominal wall model is proposed in two variants: a healthy one and including hernia defect repaired by implant. The models include many uncertainties, e.g. due to variability of abdominal wall, intraabdominal pressure value etc. Measuring mechanical properties with high accuracy...
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Advanced sensitivity analysis of the impact of the temporal distribution and intensity of rainfall on hydrograph parameters in urban catchments
PublicationKnowledge of the variability of the hydrograph of outflow from urban catchments is highly important for measurements and evaluation of the operation of sewer networks. Currently, hydrodynamic models are most frequently used for hydrograph modeling. Since a large number of their parameters have to be identified, there may be problems at the calibration stage. Hence, sensitivity analysis is used to limit the number of parameters....
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Variable‐fidelity modeling of antenna input characteristics using domain confinement and two‐stage Gaussian process regression surrogates
PublicationThe major bottleneck of electromagnetic (EM)-driven antenna design is the high CPU cost of massive simulations required by parametric optimization, uncertainty quantification, or robust design procedures. Fast surrogate models may be employed to mitigate this issue to a certain extent. Unfortunately, the curse of dimensionality is a serious limiting factor, hindering the construction of conventional data-driven models valid over...
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SENSITIVITY ANALYSIS IN THE REHABILITATION OF HISTORIC TIMBER STRUCTURES ON THE EXAMPLES OF GREEK CATHOLIC CHURCHES IN POLISH SUBCARPATHIA
PublicationThis work concerns structural and sensitivity analysis of carpentry joints used in historic wooden buildings in south-eastern Poland and western Ukraine. These are primarily sacred buildings and the types of joints characteristic for this region are saddle notch and dovetail joints. Thus, in the study the authors focus on these types of corner log joints. Numerical models of the joints are defined and finite element simulations...
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Analysis of effect of overloaded vehicles on fatigue life of flexible pavements based on weigh in motion (WIM) data
PublicationOverloaded vehicles have a significant impact on pavement fatigue life and distress. As the studies show, the phenomena intensify when the control of traffic is poor. The paper presents the results of the research including analysis of weigh in motion data from eight stations and analysis of asphalt pavement fatigue caused by mixed traffic. Distributions of vehicles axles load including the multiple axles effects are presented....
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Qualitative and Quantitative Analysis of Selected Tonic Waters by Potentiometric Taste Sensor With All-Solid-State Electrodes
PublicationTaste sensor with five all-solid-state electrodes (ASSE) III (third version) was used for qualitative and quantitative analysis of selected tonic waters (J.Gasco, Kinley, Jurajski, Jurajski with citrus flavor, Carrefour, Schweppes Indian Tonic, and Schweppes Bitter Lemon). The results obtained by this taste sensor analyzed with principal component analysis, agglomerative hierarchical clustering methods show that this sensor can...
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Elevated ambulatory systolic-diastolic pressure regression index is genetically determined in hypertensive patients with coronary heart disease
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Assessment of the factors influencing on the formation of energy-oriented modes of electric power consumption by water-drainage installations of the mines
PublicationPurpose. Performing the analysis to determine energy-efficient modes and assess the characteristics of the main indicators of electric power consumption by mine water-drainage installations based on the developed research mathematical model. Methods. To achieve the purpose set, a methodology is used to develop the multiple multifactor correlation-regression modeling with respect to the modes of electric power consumption by electrical...
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Numerical Modelling for Prediction of Compression Index from Soil Index Properties in Jimma town, Ethiopia
PublicationIn this study, correlations are developed to predict compression index (Cc) from index parameters so that one can be able to model Jimma soils with compression index using simple laboratory tests. Undisturbed and disturbed soil samples from twelve different locations in Jimma town were collected. Laboratory tests like specific gravity, grain size analysis, Atterberg limit, and one-dimensional consolidation test for a total of twenty-four...