Transactions on Engineering Technologies

The least squares piecewise monotonic data approximation method is applied to daily Covid-19 new cases and deaths data of the UK for the period 31-01-2020 to 19-11-2021. The data demonstrate wide variation in parts and noticeable peaks over time. We are interested in estimating turning points of the data in that the fit is useful to analyzing the progress of the pandemic. An enormous number of combinations of turning points need be considered in order to find an optimal combination, but the method provides quite efficiently a global solution. Our results show the efficacy of the piecewise monotonicity method in locating optimal turning points that are significant to the Covid-19 analyses. We consider the facts that influence the choice of the number of peaks. Our analysis provided us with insights regarding the driving forces behind the turning points that the method detected, which further may be helpful to management, as part of the information on which decisions will be made.

In the paper, the stationary and non-stationary fluid flows of large viscosity and low Reynolds number in 2D bounded area are considered. 2D Stokes equation in the area partly filled with the very viscous fluid is studied. Upper bound of the fluid is unknown. Under the influence of certain pressure and body forces, the waves (free surface) in the fluid are generated. The case of the solenoidal body force and a harmonic pressure is considered. Solutions of the Stokes system with the appropriate initial-boundary conditions by means of the methods of conformal mapping and integral equations are obtained. It is assumed, that the pressure is given. The existence and uniqueness of the solution is proved. The solutions of the non-stationary problem are derived by means of the step-wise approximation method. The profiles of free surfaces for the different pressure are plotted by means of Maplesoft.

Bluetooth or Wi-Fi access point connections allow us to discover people’s physical proximity. However, their analysis is often difficult because the collected data is noisy and misleading. In this study, we use network modeling to analyze proximity information from these types of data sets. We extracted proximity networks from three different systems: Haggle Infocomm conference and MIT Reality Mining Bluetooth connections; and Sabanci University Wi-Fi access point connections, such that it is extracted as a static proximity network for the first time in this study. We explored both the extracted networks’ properties and the 12 community detection algorithms’ results. According to the descriptive analysis and statistical tests of all the setups, the performance of the algorithms depends on the data sets. The Haggle Infocomm network is noisy enough to make community detection difficult. However, the other two networks are suitable for the analysis. They contain a distinguishable community structure. Partitioning algorithms find large communities, while overlapping algorithms can detect smaller ones. The EMOC, which we proposed in our previous work, is able to find tiny communities with more overlapping nodes than any other algorithm. Such communities may correspond to small groups of friends in the same place in proximity networks.

In recent years, firms have been able to collate large customer data sets, and this has led to both challenges and opportunities when making marketing and sales-related decisions. Large customer data sets can enable an intimate understanding of customers. However, this can pose additional costs to the firm while also requiring new data analysis and management capabilities. To address this problem, we develop a new approach to market segmentation and the identification of relative segment purchase probabilities using a large point-of-sale (POS) customer data set in the Sri Lankan retail context. Stage one of our method involves supervised and unsupervised learning approaches that analyze three purchase characteristics (Recency, Frequency, and Monetary value—RFM) and product attributes to identify segments in the customer data set. Stage two of our method involves market basket analysis (MBA) to determine the probabilities of purchase behaviors for each segment. Our new approach is among the first to establish a relationship between a machine learning-based approach to market segmentation and purchase prediction.

This simulation study demonstrates the electrical, financial, and environmental feasibility of installing in Ghana small photovoltaic power systems of both the stand-alone and grid-tied variety. Comparisons are made with appropriate competing generation methods: diesel in the stand-alone case and gas/hydro in the grid case. In both cases, the photovoltaic systems are shown to meet the electrical demands placed on them at significantly lower costs and with huge savings in greenhouse gas emissions.

In this study, we propose a vibration reduction method for brush cutters. By changing the placement spans of multiple bearings (rubber bushings) which support a driveshaft inside the main pipe, we utilized bending mode vibrations of the driveshaft as dynamic vibration absorbers called ST-DVAs. Results of finite element (FE) frequency response analysis showed that the ST-DVAs generated anti-resonances at each target frequency for both the first-order inertial force of the cutting head and engine. As an applied design method, we tuned the natural frequency of the ST-DVAs via iterative optimization calculation with the FE frequency response analysis. As a result, the optimized ST-DVAs smoothed acceleration response over a wide frequency range for a single excitation source, e.g., first-order inertial force of the cutting head.

Landslide is a rare occurrence in Nigeria; however, in recent time, it has been reported to have occurred. Therefore, it is important to simulate tensile failure and the associated crack number by subjecting the sandstone to compressional stress. The aim is to relate crack number to micro-structural disaggregation which is the degree of isotropic and deviatoric stress in the material. Therefore, the framework for tracking the damage mechanism of Ughelli formation has been provided using strain data. Strain gauges were employed to track the grain slippage during confined compression test, while micro-elastic properties were evaluated as bond stiffness measured from ultrasonic wave velocity. Next the granular assembly of the sandstone was simulated by clumping particles. The granular model was subjected to confined test to reproduce the elastic properties of the natural sandstone. The existing micro-cracks in the rock progress by grain slip and bond breakage of the cementing clay content between the grains. The damage was reached at an observed grain slippage stress of 90 MPa in the natural formation. The systematic crack growth peaks at a stress level of 160 MPa with a straining rate of 10^–5(s⁻¹). By shifting away from representing a grain of sandstone with single spherical particles, the significant discrepancies between the elastic properties of observed core sample and the simulated model are improved. The identification of the first grain slippage at possible fracture localized points during a drilling program will suggest injection of plugging pills to maintain wellbore stability. This is because it is often easier and effective to prevent undue landslides than to remedy the occurrence.

A vortex generator is utilized to create a significant amount of vortex that is capable of rotating the vortex turbine. This investigation has been undertaken regarding the geometry of two vortex basins designed in cylindrical and conical structures. The productive model of gravitational vortex setup has been extracted by taking various aspect ratios of the two basin installations. Numerical investigations have been carried out with these two basins of different geometrical parameters at different aspect ratios where the cylindrical basin has been found more effective than the conical basin in terms of pressure loss at its maximum aspect ratio, and the conical basin has been found more productive at its minimum aspect ratio from the observation of swirling strength and vortex core velocity. By considering all the conditions, an efficient geometrical setup of vortex generator from different geometries has been observed from the numerical analysis to carry out further experiments.