Search results

The study aims to determine the the optimal value of output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The performance parameters like brake thermal efficiency (BTE) and brake specific energy consumption (BSEC), whereas CO emission, HC emission, CO₂ emission, NO_x emission, exhaust gas temperature (EGT) and opacity are the emission parameters measured during the test. Tests are conducted for 2, 6 and 10 kg of load, 16.5 and 17.5 of CR.

In this investigation, the first engine was fueled with 100% diesel and 100% Calophyllum inophyllum oil in single-fuel mode. Then Calophyllum inophyllum oil with producer gas was fed to the engine. Calophyllum inophyllum oil offers lower BTE, CO and HC emissions, opacity and higher EGT, BSEC, CO₂ emission and NO_x emissions compared to diesel fuel in both fuel modes of operation observed. The performance optimization using the Taguchi approach is carried out to determine the optimal input parameters for maximum performance and minimum emissions for the test engine. The optimized value of the input parameters is then fed into the prediction techniques, such as the artificial neural network (ANN).

From multiple response optimization, the minimum emissions of 0.58% of CO, 42% of HC, 191 ppm NO_x and maximum BTE of 21.56% for 16.5 CR, 10 kg load and dual fuel mode of operation are determined. Based on generated errors, the ANN is also ranked for precision. The proposed ANN model provides better prediction with minimum experimental data sets. The values of the R² correlation coefficient are 1, 0.95552, 0.94367 and 0.97789 for training, validation, testing and all, respectively. The said biodiesel may be used as a substitute for conventional diesel fuel.

The blend of Calophyllum inophyllum oil-producer gas is used to run the diesel engine. Performance and emission analysis has been carried out, compared, optimized and validated.

This study aims to assess dietary choices of pregnant women and its relationship with their anaemia status.

A mixed-method study comprising a survey and three focus group discussions (FGDs). The survey included 380 adult pregnant women with data collected on food choices, preferences and haemoglobin (Hb) status.

More than 50% of women in the study had Hb concentration < 11.0 g/dl; mean Hb was 10.24 g/dl (SD = 1.59). Univariate analysis was used to generate descriptive tabulations for socio-demographic characteristics of respondents, dietary choices for women and anaemia status. T-test and bivariate analysis between dietary diversity score of the women among the food groups consumed as well as their anaemia (Hb) status. This showed that women with high dietary diversity score had improved Hb status (P = 0.003), and those who consumed meat and fish as well as dark leafy vegetables had significantly high diversity scores (P = 0.031 and P = 0.049). Thematic analysis was used for analysing qualitative data.

The sample used in the study is unlikely to be fully representative of pregnant women in the Accra Metropolis. In addition, this study used a cross-sectional study design, making it difficult to establish causal associations between nutritional status and food choice of pregnant women. It does not also show variation in dietary practices by seasons of the year. The scope of the study did not allow for a detailed analysis, and this should be considered in future studies. Also, the study did not explore an obstetric factor like past bleeding history as well as the menstrual cycle of these pregnant women, as these factors are likely to interfere with the anaemia status of the pregnant women.

This paper contributes significant value by specifically focusing on and clarifying the complex relationship between dietary choices and aneamia among pregnant women. It also provides insights into the distinct dietary patterns and preferences of pregnant women, which may be contributing to the high prevalence of aneamia. The results of the study can inform the development of localized, evidence-based interventions to address this critical public health concern, ultimately leading to improved maternal and foetal health outcomes.

Due to the environmental issues caused by petroleum lubricants used in lubrication, the concept of creating various bio-lubricants requires research globally. Thus, this study aims to develop, characterize and test the base ficus carica oil (fig oil) for its ethylene vinyl acetate copolymer (EVA) and sodium dodecylbenzene sulfonate (SDBS) content.

The sample characterization was done using the Fourier transmission infrared spectrum, whereas the morphologies of the EVA, SDBS particles and lubricated surfaces were carried out under scanning electron microscope equipment. To ensure the homogeneity of the solution (base oil and additives), the formulations were subjected to the sonication process. The anti-friction and anti-wear properties of EVA and SDBS particles as lubricant additives were investigated using a ball on a flat high-frequency reciprocating rig tribo-tester.

According to the findings, the base oil’s anti-friction and anti-wear capabilities can be greatly enhanced by the additions. revealed that the best results were obtained when 1.2% EVA + 2% SDBS was applied for the examination of wear (597.8 µm) and friction coefficient (0.106). Commercial references were used, nevertheless, and the results were excellent. This is because the particles in the contact area during lubrication have strong solubility and quickly penetrate the contact zone. The lubricating mechanisms were explained by a tribological model of the EVA + SDBS and SDBS particles.

The coefficient of friction and wear reduction caused by the use of the additives will certainly enhance system performance and protect the machine components from excessive wear that could cause damage or failure.

The originality and uniqueness of this work are officially affirmed by the authors. The authors’ autonomous and original contribution to the development of sustainable lubrication is represented in this work. To the best of the authors’ knowledge, no other study has been published or made publicly available that duplicates the precise scope and goals of our research, and this conclusion is based on a thorough literature assessment.

The urgency to address climate change and its devastating consequences has never been more pressing. As societies become increasingly aware of the detrimental impact of traditional housing on the planet, there is a growing demand for eco-friendly housing solutions that prioritize energy efficiency, resource conservation and reduced carbon emissions. Therefore, this study aims to investigate the factors that influence customers’ priority toward eco-friendly house purchasing intention.

This study collected 386 data using a quantitative research strategy and purposive sampling method. This study uses a hybrid analysis technique using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approaches to identify the influencing factors.

The PLS-SEM analysis found that attitude toward the eco-friendly house, subjective norms, performance expectancy, environmental knowledge and environmental sensitivity have a positive influence on eco-friendly house purchasing intention. However, perceived behavioral control and willingness to pay were found to have insignificant effect on customers’ intention to purchase eco-friendly houses. The fsQCA results further revealed complex causal relationships between the influencing factors.

This research will not only contribute to academic knowledge but also provide practical guidance to real estate developers, policymakers and individuals looking to make environmentally responsible choices. By understanding the factors that influence consumers’ intentions to purchase eco-friendly houses, we can pave the way for a more sustainable and resilient future.

This study has used a hybrid analysis technique, combining PLS-SEM and fsQCA, to enhance the predictive accuracy of eco-friendly house purchase intentions among individuals residing in densely populated and highly polluted developing countries, such as Bangladesh.

This Friction stir welding study aims to weld thick AA8011 aluminium plates, and the interface joints created with a variety of tool pin profiles were examined for their effects on the welding process.

Scanning electron microscopy and optical microscopy and X-ray diffraction were used to examine the macro and micro-structural characteristics, as well as the fracture surfaces, of tensile specimens. The mechanical properties (tensile, hardness tests) of the base metal and the welded specimens under a variety of situations being tested. Additionally, a fracture toughness test was used to analyse the resilience of the base metal and the best weldments to crack formation. Using a response surface methodology with a Box–Behnken design, the optimum values for the three key parameters (rotational speed, welding speed and tool pin profile) positively affecting the weld quality were established.

The results demonstrate that a defect-free junction can be obtained by using a cylindrical tool pin profile, increasing the rotational speed while decreasing the welding speeds. The high temperature and compressive residual stress generated during welding leads to the increase in grain size. The grain size of the welded zone for optimal conditions is significantly smaller and the hardness of the stir zone is higher than the other experimental run parameters.

The work focuses on the careful examination of microstructures behaviour under various tool pin profile responsible for the change in mechanical properties. The mathematical model generated using Taguchi approach and parameters was optimized by using multi-objectives response surface methodology techniques.

This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image. The authors used three feature extraction methods: handcrafted features, convolutional features and autoencoder features. Subsequently, these features were mapped to contact locations through a contact location regression network. Finally, the network performance was evaluated using spherical fittings of three different radii to further determine the optimal feature extraction method.

This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image.

This research indicates that data collected by probes can be used for contact localization. Introducing a batch normalization layer after the feature extraction stage significantly enhances the model’s generalization performance. Through qualitative and quantitative analyses, the authors conclude that convolutional methods can more accurately estimate contact locations.

The paper provides both qualitative and quantitative analyses of the performance of three contact localization methods across different datasets. To address the challenge of obtaining accurate contact locations in quantitative analysis, an indirect measurement metric is proposed.

The purpose of this study is to experimentally determine whether mechanical properties of concrete can be improved by using olive pomace aggregates (OPA) as a substitute for natural sand. Two types of OPA were tested by replacing an equivalent amount of natural sand. The first type was OPA mixed with olive mill wastewater (OMW), and the second type was OPA not mixed with OMW. For each type, two series of concrete were produced using OPA in both dry and saturated states. The percentage of partial substitution of natural sand by OPA varied from 0% to 15%.

The addition of OPA leads to a reduction in the dry density of hardened concrete, causing a 5.69% decrease in density when compared to the reference concrete. After 28 days, ultrasonic pulse velocity tests indicated that the resulting material is of good quality, with a velocity of 4.45 km/s. To understand the mechanism of resistance development, microstructural analysis was conducted to observe the arrangement of OPA and calcium silicate hydrates within the cementitious matrix. The analysis revealed that there is a low level of adhesion between the cement matrix and OPA at interfacial transition zone level, which was subsequently validated by further microstructural analysis.

The laboratory mechanical tests indicated that the OPCD_OPW (5) sample, containing 5% of OPA, in a dry state and mixed with OMW, demonstrated the best mechanical performance compared to the reference concrete. After 28 days of curing, this sample exhibited a compressive strength (R_c) of 25 MPa. Furthermore, it demonstrated a tensile strength of 4.61 MPa and a dynamic modulus of elasticity of 44.39 GPa, with rebound values of 27 MPa. The slump of the specimens ranged from 5 cm to 9 cm, falling within the acceptable range of consistency (Class S2). Based on these findings, the OPCD_OPW (5) formulation is considered optimal for use in concrete production.

This research paper provides a valuable contribution to the management of OPA and OMW (OPA_OMW) generated from the olive processing industry, which is known to have significant negative environmental impacts. The paper presents an intriguing approach to recycling these materials for use in civil engineering applications.

This study investigates the impact of contract farming in onion, okra and pomegranate production on profits of smallholder farmers in India. It also investigates the determinants of farmers’ participation in contract farming. The study is based on a survey of 1,131 farmers from Maharashtra, India engaged in the cultivation of these three crops.

This study uses instrumental variable regressions and quasi-experimental methods to decipher the impact of contract farming.

The study reveals that contract farming ensures higher returns for smallholders, enables their access to high-end markets and brings in risk-sharing with protection during price fluctuations. Farm size and farmers’ risk perceptions are significantly associated with their participation in contract farming.

The study is based on cross-sectional data, which presents limitations on considering unobserved farmer-level individual heterogeneity.

The study shows that contracts highlight the functioning of the contractor/integrator on both the input and output sides of the market. By providing better-quality inputs on credit and at discounted prices and by providing training, the integrator helps small farmers meet international food safety and quality standards, a historically difficult challenge for smallholders in India.

This study examines the impact of agricultural credit on rice farmers' technical efficiency (TE) in Côte d'Ivoire by considering the heterogeneity among credit sources.

A multistage sampling technique was used to collect data from 588 randomly sampled rice farmers in seven rice areas of the country. The authors use the endogenous stochastic frontier production (ESFP) model to account for the endogeneity of access to agricultural credit.

On the one hand, agricultural credit has a significant and positive impact on rice farmers' TE. Rice farmers receiving agricultural credit have an average of 5% increase in their TE, confirming the positive impact of agricultural credit on TE. On the other hand, the study provides evidence that the impact of credit on rice production efficiency differs depending on the source of credit. Borrowing from agricultural cooperatives and paddy rice buyers/processors positively and significantly influences the TE, while borrowing from microfinance institutions (MFIs) negatively and significantly influences the TE. Moreover, borrowing from relatives/friends does not significantly influence TE.

Future research can further explore the contribution of agricultural credit by including several agricultural productions and using panel data.

The study provides evidence that the impact of agricultural credit on agricultural production efficiency depends on the source of credit. This study contributes to the literature on the impact of agricultural credit and enlightens policymakers in the design of agricultural credit models in developing countries, particularly Côte d'Ivoire.

This paper aims to present a case study of virtual-reality-based product demonstrations featuring items of furniture. The results will be of use in further design and development of virtual-reality-based product demonstration systems and could also support effective student learning.

A new method was introduced to guide the experiment by confirming orthogonal arrays. User interactions were then planned, and a furniture demonstration system was implemented. The experiment comprised two stages. In the evaluation stage, participants were invited to experience the virtual-reality (VR)-based furniture demonstration system and complete a user experience (UX) survey. Taguchi-style robust design methods were used to design orthogonal table experiments and planning and design operation methods were used to implement an experimental display system in order to obtain optimized combinations of control factors and levels. The second stage involved a confirmatory test for the optimized combinations. A pilot questionnaire was first applied to survey demonstration scenarios that are important to customers.

The author found in terms of furniture products, product interactive display through VR can achieve good user satisfaction through quality design planning. VR can better grasp the characteristics of products than paper catalogs and website catalogs. And VR can better grasp the characteristics of products than online videos. For “interactive inspection”, “function simulation”, “style customization” and “set-out customization” were the most valuable demonstration scenarios for customers. The results of the experiment confirmed that the “overall rating”, “hedonic appeal” and “practical quality” were the three most important optimized operating methods, constituting a benchmark of user satisfaction.

The author found that it is possible to design and build a VR-based furniture demonstration system with a good level of usability when a suitable quality design method is applied. The optimized user interaction indicators and implementation experience for the VR-based product demonstration presented in this study will be of use in further design and development of similar systems.