Engineering and Applied Science Research

Climate change and the behaviour of meteorological drought and its impact on wheat yield

Hasan Jamal Al-Bazaz, Omar M.A. Mahmood Agha — Thu, 07 Mar 2024 00:00:00 +0700

Climate change is the most prominent issue in this decade. The expected impacts of this change have become a reality, with rising sea levels and long, intense heat waves occurring globally. The present study examines the characteristics of drought in Nineveh Governorate and its impact on the wheat crop. Two drought indices were used in the study: (1) the Standardised Precipitation Index (SPI) and (2) the Chinese Z Index (CZI). The study used climate data on rainfall and temperature for the period 1990–2020 from eight meteorological stations distributed in the study area. Results showed a nonsignificant decrease in rainfall and an increase in maximum and minimum temperatures. Results also showed that the highest recurrence rates of drought (recorded at the Tal-Abta) are 51.2% and 56% for SPI and CZI, whereas the lowest rates (recorded at Mosul, Sheikhan and Sinjar) are 45.1% and 50.8% for SPI and CZI, respectively. The two drought indices match in identifying wet and dry periods, with R² values ranging from 0.84 to 0.94. Furthermore, a relationship was found between productivity and climatic drought indices and it was concluded that wheat productivity is more significantly influenced by the distribution of rainfall than by drought. The current study can help demonstrate the extent of climate change’s impacts on wheat productivity. Thus, the results can contribute to planning and managing agricultural production according to climate change.

Enhancing Lean-Kaizen practices through IoT and automation: A comprehensive analysis with simulation modeling in the Thai food industry

Siwasit Pitjamit, Parida Jewpanya, Pinit Nuangpirom — Tue, 26 Mar 2024 00:00:00 +0700

This research delves into a comprehensive examination of the noodle production process within the Thai food industry, focusing on pivotal challenges related to quality control during steaming, weighing, sealing, and vacuum packaging. In response to these challenges, our study investigates the strategic integration of Internet of Things (IoT) and automation solutions to amplify production efficiency. Employing advanced plant simulation tools, including lean manufacturing and Kaizen principles, coupled with methodologies like value stream mapping and flow process charts, we explore four distinct improvement scenarios. Scenario 1 targets enhancements in the dough-baking system during the steaming process, while Scenario 2 concentrates on optimizing the boiler control system. Scenario 3 addresses the weighing and packing process, and Scenario 4 aims at automating the packing process. These scenarios collectively showcase substantial reductions in cycle time, labor costs, and improvements in production capacity. The research design spans a 30-day data collection period, capturing critical metrics related to cycle time, changeover time, workforce, lead time, value-added time, and inventory levels. The gathered data unveils inefficiencies and challenges within the noodle production process, offering a foundation for identifying bottlenecks and areas for enhancement. The study's outcomes underscore the efficacy of technology-driven solutions in addressing production challenges and boosting operational efficiency. Specifically, Scenario 1 and Scenario 4, integrating IoT technology and automation, exhibit a remarkable 7.8% increase in productivity with a one-year payback period. Meanwhile, Scenario 3 significantly reduces labor costs and enhances overall efficiency. These findings contribute to the broader industry discourse, emphasizing the transformative potential of technology-driven solutions in addressing key production challenges and advancing operational excellence. The research provides valuable insights for practitioners seeking innovative approaches to enhance their processes and embrace Industry 4.0 advancements.

Analysis of knowledge and skills essential for industrial engineers in context of Industry 4.0 within Thai automobile sector

Rungchat Chompu-inwai, Waratinad Wichajaroen, Trasapong Thaiupathump — Mon, 19 Feb 2024 00:00:00 +0700

Industry 4.0 has rapidly transformed traditional industries and manufacturing processes by seamlessly integrating digital technologies, automation, data analytics, and the Internet of Things. It represents a profound shift in business operations, emphasizing efficiency, flexibility, and responsiveness to customers. As a result, the required knowledge and skills are evolving for all relevant personnel including industrial engineers (IEs), to achieve success in the Industry 4.0 era. Preparing a capable IE workforce to meet these changing demands is a persistent challenge, particularly in a rapidly evolving environment. This study aims to identify the needs of Thai automobile companies regarding the knowledge and skills of IEs for Industry 4.0. Furthermore, it aims to rank these IE knowledge and skills in terms of importance. In this study, a questionnaire was developed and used as a tool for the research. Respondents representing 31 companies in the Thai automobile industry were asked to rate the importance of each knowledge area and skill. Questions in the knowledge section were divided into 15 knowledge areas across four categories: core subjects, global subjects, engineering subjects, and technological fundamentals. The questions in the skill section were divided into 18 skills spanning five categories: communication, system thinking, creative thinking/ adaptation/ decision-making, learning, and technical proficiency. There are also 12 questions asking respondents to evaluate their level of Industry 4.0 adoption. The findings indicate that the importance rankings for essential IE knowledge and skills vary across a distinct group of Industry 4.0 adoption levels. The rankings of vital IE knowledge and skills across these diverse adoption levels are comparatively analyzed and discussed. While this study primarily centers on the automotive industry, it has the potential to illuminate broader trends that extend to other sectors as well.

Designing a feedback breathable soft-stuffed robot: Exploring its potential for enhancing sleep quality

Kanjanapan Sukvichai, Tanapon Kitmuti, Kan Yajai — Wed, 24 Apr 2024 00:00:00 +0700

Insomnia significantly impacts human productivity and can lead to long-term health issues. Sleeplessness is often caused by stress, particularly in adults. While hugging another human or animal can effectively reduce stress due to the breathing motion synchronization, but it is often challenging and impractical in many situations. This study proposes a potential alternative solution to alleviate stress by utilizing a soft-stuffed robot. The robot is designed with a breathing mechanism that mimics the respiration of a living being. By using flexible 3D materials, artificial ribs and spine are created to imitate animal breathing motion. The 3D materials are carefully selected due to their properties. To measure the human breathing rhythm, a biosensor called Medtex, consisting of conductive fabric, can captures the human signal. This signal is then utilized as feedback in a control system, employing a PID control algorithm to achieve synchronization between the robot and human breathing motion in terms of phase and frequency. The robot imitator actuator, a customized Maxon RE motor, is controlled by a magnetic encoder and feedback signal. To ensure safety and comfort, the imitator is enveloped in a cushion. Experimental trials conducted during nighttime involved volunteers hugging the robot while sleeping, with the resulting output recorded and analyzed. The findings demonstrate that the designed robot can be effectively controlled and accurately determine sleep states with proper synchronization.

Accurate ultimate tensile strength classification in friction stir welding of symmetric AA5052 weld seams using ensemble deep learning model

Chakat Chueadee, Rungwasun Kraiklang, Surasak Matitopanum, Sarayut Gonwirat — Mon, 04 Mar 2024 00:00:00 +0700

This research introduces a comprehensive classification and analysis system tailored for accurately determining the ultimate tensile strength (UTS) of weld seams. Traditional UTS assessment methods typically depend on destructive testing, which tends to be both lengthy and expensive, limiting their continuous application in quality control of welding procedures. This study leverages deep learning techniques, segmenting the dataset into subsets for training and validation in both multi-class and binary classification scenarios. The model devised in this study incorporates cutting-edge methodologies including geometric enhancement, U-Net based image segmentation, an image augmentation of diverse deep learning models, and decision fusion tactics. A significant aspect of this research was the success of Experiment 33, which skillfully combined various methodologies, resulting in outstanding performance. This experiment demonstrated exceptional accuracy in multiclass classification, alongside impressive outcomes in binary classification, achieving a high accuracy rate of 97.4% and an F1 score of 96.5%. This level of accuracy is indicative of the average performance across all models that incorporated the He-UWA for decision fusion strategy. It encompasses the efficacy of all models using He-UWA, with or without image segmentation. These findings underscore the effectiveness of our proposed model in accurately classifying UTS in friction stir welding. This represents a crucial advancement in assessing the quality of welding processes and provides a solid foundation for future investigations in this area.

The applications of Artificial Hummingbird Algorithm (AHA) in the optimization problems: A review of the state-of-the-art

Atchara Thongsamai, Sirikarn Chansombat, Saisumpan Sooncharoen — Mon, 12 Feb 2024 00:00:00 +0700

Nature-inspired algorithms have been developed and applied to solve a wide range of real-world optimization problems. Artificial Hummingbird Algorithm (AHA) is one of the recently introduced ones. The foraging and flight behaviors of hummingbirds inspire the mechanisms of the AHA. It has a simple structure and operates exploitation and exploration processes based on the visitation of hummingbirds, to find optimal solutions effectively with a few parameter settings. To the best of our knowledge, there has been no comprehensive and systematic review of the AHA, which is the objective of this paper. Researchers have demonstrated AHA's effectiveness in various applications, including antenna design, biomedical, networking, optimization, prediction and forecasting, scheduling, and power generation and controlling. Many studies have reported that the efficiency of AHA can be increased by modifying and hybridizing it with other algorithms. The most well-known problem that AHA has solved is the renewable energy issue. The AHA is also classified as a bio-inspired algorithm frequently used to compare performance. Although the AHA has been published recently and applied to many problems, there are limitations to some application areas, such as scheduling problems and robotics, security, fuzzy systems, data mining, and other interesting optimization problems.

Experimental study of geotechnical behaviour of different shell foundations on unreinforced and reinforced sandy soil

Kangujam Monika, Thokchom Kiranbala Devi, Suresh Thokchom — Wed, 10 Jan 2024 00:00:00 +0700

This paper presents the performance of three types of small-scale shell foundations (pyramidal frustum, semi-cylindrical and prismatic shell) of the same plan area on different states of sand provided with or without reinforcement. To understand the effect of reinforcement and its dependency on the vertical embedment depth, two cases were considered, i.e. reinforcement at a depth equal to 0.5 B (B=width of foundation) and another case at a depth equal to B. Bearing capacity for different shell foundations models and settlement behaviour were studied based on the load settlement curves and compared with that of conventional flat foundation model. The experimental results show that shell models perform better than the flat foundation model in terms of bearing capacity and settlement resistance on the different states of sand with or without reinforcement. The relationship of ultimate load with the angle of internal friction was found. Reinforcement embedded at 0.5B depth was found to be better than provided at B depth in all the states of sand. It is also noticed that the bearing capacity ratio is lower for the sand reinforced at a depth of B than that of 0.5B, showing the dependency on reinforcement embedment depth.

Development of a computational model for the estimation of biogas production from putrescible wastes

Ogundola A.C., Orhadahwe T.A., Ojetoye A.O., Emmanuel C.O., Ogundola O.C. — Thu, 11 Jan 2024 00:00:00 +0700

The use of putrescible wastes as a feed source for biogas production has been a research subject. The study aims to develop a simple computer model for estimating the volume of biogas produced from putrescible wastes. The predictive model was developed to predict the volume of biogas produced based on three parameters, the mass of waste used, the anaerobic processing time, and the percentage of residue accumulation in the reactor. The biogas estimator application was developed using the 2017 edition of Microsoft’s Visual Studio .Net software developer’s kit (SDK). The simple model does not require rigorous mathematical computations as the process parameters can readily be imputed in the simple data fields created. The model can operate in both batch and continuous modes. The result from both the batch and continuous biodegradation processes of 1.0 kg of putrescible waste per day in a biodigester using the Biogas Estimator model provided certain significant outputs. In the case of the batch process, a 1.0 kg mass of biodegradable putrescible waste yielded an average biogas production volume of about 0.236 m³ per day, while the resulting volume from the continuous process, 1.0 kg mass of biodegradable putrescible waste produced on average an estimated biogas volume of about 0.164 m³ per day. The values obtained are comparable to those of similar studies thereby validating the efficacy of the model. The model has been validated and is considered suitable for the estimation of biogas production from putrescible wastes.

Mixed-Integer Linear programming for scheduling of radiotherapy patients

Nattapon Emsamrit, Chawis Boonmee — Thu, 11 Jan 2024 00:00:00 +0700

This study presents an advanced mathematical model to optimize the scheduling of radiotherapy patients, thereby expediting solution discovery. The paper commences with an in-depth analysis of cancer treatment protocols and prior mathematical models. We then introduce some enhancements to an existing mathematical framework with the intent of expediting the derivation of solutions. The validity of the model is ensured through a meticulous evaluation of the constraints, leading to the removal of redundant constraints. This improved model is validated through the generation and assessment of five small-scale cases, and its efficacy is confirmed. The experimental results underscore the substantial time reduction achieved by the enhanced mathematical model in terms of finding solutions. To bolster its applicability to real-world scenarios, the model is enriched by incorporating additional constraints, for example related to surgical and radiotherapy processing times. The application of this comprehensive model to a real-world case demonstrates its ability to accurately determine the durations of simulation and radiotherapy while adhering to the specified constraints. It successfully allocates patients to specific rooms and technologies, and outlines the optimal frequency for radiotherapy sessions within each interval. The proposed model is expected to assume a pivotal role in facilitating informed decision-making among stakeholders. By substantially curtailing the treatment planning time and mitigating errors in radiotherapy patient scheduling, this model will be a valuable asset to healthcare practitioners and decision-makers alike.

Desirability analysis of Commercial-off-the-shelf (COTS) alternative foaming agents for foamed concrete production

Jedea Jethro A. Bullanday, Joel Galupo Opon — Tue, 05 Mar 2024 00:00:00 +0700

Foamed concrete (FC) offers potential for various lightweight construction applications, making the need for industry-standard foaming agents crucial in achieving its desired properties. However, the limited availability of quality foaming agents hampers FC’s widespread use in many economies. To address this, the potential of commercial-off-the-shelf (COTS) products capable of foaming has been explored in this paper. Three widely available COTS alternatives – Coconut Diethanolamide (CDEA), liquid detergent, and dishwashing liquid – were examined for FC production. Response Surface Methodology (RSM) and desirability analysis were employed to differentiate the effects of these COTS alternatives on various FC properties. Moreover, adjusting additional factors like foam volume, water-to-cement ratio, and maximum aggregate size – known influencers of FC properties – during the experiments revealed distinct impacts of each COTS alternative foaming agent on FC properties. Results revealed that FCs exhibiting highest compressive strengths are those made using CDEA, then followed by liquid detergent, and dishwashing liquid. In terms of absorption, FC samples made using CDEA exhibited the lowest values, followed by liquid detergent, then dishwashing liquid. In terms of unit cost, FC samples made using CDEA is the most economical, followed dishwashing liquid, then liquid detergent. However, regardless of the type of COTS alternative foaming the impact of FC density and CO2 emission equivalence values is similar. Furthermore, desirability analysis identified that CDEA yields the most desirable FC with optimal values for factors such as foam volume of about 60.073%, water-cement ratio of about 0.50, and maximum aggregate size of 1.611mm. Liquid detergent and dishwashing liquid also yields combinations of input factors which can produce FC conforming to corresponding ASTM standards for foamed concrete but with lower desirability. In conclusion, the investigation demonstrated the potential effectiveness of locally available COTS alternative foaming agents in FC production, contributing to their practical utilization and promoting more sustainable construction materials.

Conversion of methyl methacrylate to methyl isobutyrate via hydrogenation over Ni/zeolites catalysts

Ramzi Saif, Surachet Hongkailers, Napida Hinchiranan — Wed, 31 Jan 2024 00:00:00 +0700

According to the zero waste and upcycling policy, this work aims to utilize waste polymethyl methacrylate (PMMA) by its conversion to methyl isobutyrate (MIB) via hydrogenation over nickel (Ni) based catalysts supported on the commercial zeolites: HY, H-Beta-27 (SiO₂/Al₂O₃ mol ratio = 27), H-Beta-40 (SiO₂/Al₂O₃ mol ratio = 40), and H-ZSM-5. The appropriate catalyst support was first screened by using MMA monomer as the substrate for hydrogenation. Under 30 bar initial hydrogen pressure (P_H2) at 250 °C for 3 h, the Ni/H-beta-27 catalyst effectively promoted hydrogenation to achieve an 85% MMA conversion level with a 56.2 wt% MIB yield because of its larger external surface area and pore size. A higher initial P_H2 (40 bar) and longer reaction time (5 h) improved the MIB yield up to 84.6 wt%. For hydrogenation of the MMA portion in a pyrolysis liquid product derived from waste PMMA, a MMA conversion level of 99.7% was achieved when hydrogenation was operated under 30 bar initial P_H2 and 250 ^oC for 5 h. However, only a 36.3 wt% MIB yield was obtained with a noticeable formation of coupling and cyclic compounds at 42 wt% and 18 wt%, respectively. The enhancement of the initial P_H2 to 40 bar overcame this problem and increased the MIB yield to 47.6 wt%.

Image based durian (Durie azomethines Linn) sweetness measurement by ResNet50

Chomtip Pornpanomchai — Wed, 21 Feb 2024 00:00:00 +0700

Development of the capability to determine durian sweetness using a single image is the main objective of this research. The developed system is called the “Durian Sweetness Measurement System” or DSMS. The DSMS employed ResNet50 in the MATLAB toolbox to recognize durian imagery. The system consists of four main subprograms, 1) durian dataset creation, 2) image acquisition, 3) durian sweetness evaluation, and 4) results illustration. The system was used to conduct experiments on 17 Monthong durian pulps in 102 video clips. The DSMS determined that sweetness of the raw, mature and ripe durian was around 14–19, 20–26 and 27–31 ^oBrix, respectively. The accuracy of the DSMS is 97.57%, with an average access time of 1.5248 sec per image.

Application of 5D building information modeling using Cubicost in estimating construction structure work costs (Case study: Emergency Room and Hemodialysis Building at Waras Wiris Local General Hospital of Boyolali, Indonesia)

Mon, 25 Mar 2024 00:00:00 +0700

In construction projects, quantity take-off is an important process that must be considered because it will substantially impact the estimate of the overall project cost. The components that make up the structure of a building are very complex, so time inefficiencies and accuracy in calculating the volume of work often occur, which are fatal to construction costs. Therefore, in this study, an analysis of the application of 5D BIM in construction projects was carried out to identify its effectiveness, accuracy, and efficiency in determining the quantity take-off. The 5D BIM application used in this case is 5D BIM Cubicost TAS to determine the quantity take-off of concrete and formwork and 5D BIM Cubicost TRB to determine the quantity take-off of reinforcement in detail. The research method used was a comparative analysis method of the use of 5D BIM and conventional applications. The object of this research was the construction project of the Emergency Room and Hemodialysis Building at Waras Wiris Local General Hospital of Boyolali. The analysis shows that the 5D BIM Cubicost TAS and TRB efficiency in structure work was IDR 220,526,781.12 or 9.254%.

Enhancing of the rapid evaluation of sugarcane energy content for energy cane varieties selection purposes in breeding program using Near-Infrared spectroscopy (NIRS)

Fri, 22 Dec 2023 00:00:00 +0700

The integration of Near-Infrared spectroscopy (NIRs) as a predictive tool for rapidly assessing the gross calorific value (GCV) of dried shredded sugarcane addresses a significant bottleneck in sugarcane breeding programs. A total of 110 samples were collected, and a lab-type Fourier Transform near infrared (FT-NIR) spectrometer operating across a wavenumber range of 12,800 to 3,600 cm^-1 was utilized for spectral acquisition. This study explored various variable selection algorithms with partial least squares (PLS) regression for model development. Variable selection methods included variable importance in projection (VIP), successive projections algorithm (SPA), genetic method (GA), and correlation (r). The r-PLS algorithm along with standard normal variate and first derivative (SNV + D¹) pre-treatment yielded a highly effective model exhibiting a coefficient of determination in prediction (R²_p) of 0.88 and the root mean square error of prediction (RMSE_P) of 278.0 J/g. This study showed that the NIRs could provide a reliable method for rapid, fairly accurate, and precise GCV estimation. However, future research should investigate the use of additional modeling algorithms, such as non-linear regression, to improve model accuracy and utilize sample data with an evenly spread range of GCV values to validate the model performance with greater confidence.

Drying of tamarind foam-mats using far-infrared radiation combined with a belt conveyor system: Drying kinetics, quality attributes, and mathematical modeling

Poomjai Sa-adchom — Thu, 26 Oct 2023 00:00:00 +0700

The study aimed to evaluate the effects of far-infrared radiation (FIR) power level and the thickness of tamarind foam-mats (TFMs) on changes in moisture content during the drying process. This process involved the use of far-infrared radiation, combined with a belt conveyor system (FIR+BCS), to dry the TFMs. Specific energy consumption (SEC) and quality attributes of tamarind powder, such as color and dissolution time, were examined. The study also investigated a mathematical model to describe the suitable drying characteristics of TFMs. In the experiment, cylindrical TFMs with a diameter of 5 cm and thicknesses of 3 and 6 mm were dried using FIR+BCS at FIR power levels of 400, 500, and 600 W until the moisture content of the TFMs was reduced to less than 13% w.b. Based on the experimental results, it was found that higher FIR power levels led to more rapid decreases in moisture content in TFMs, lower SEC, and quicker dissolution of tamarind powder in water, compared to lower FIR power levels. The 3 mm thick TFMs exhibited faster moisture content reduction, lower SEC, and more rapid dissolution of tamarind powder in water than the 6 mm thick ones. In addition, tamarind powder produced from 6 mm thick TFMs had higher lightness (L* value) and yellowness (b* value), but lower redness (a* value) than those of 3 mm thick TFMs. However, tamarind powder produced from TFMs with FIR power levels of 400, 500, and 600 W were not significantly different in color values (L*, a*, and b* values). Among the seven mathematical models, the Midilli et al. model satisfactorily described the drying kinetics of TFMs, with an R² value of 0.993269, an RMSE of 0.005117, and a χ² value of 0.000321. The effective moisture diffusivity values of TFMs ranged from 9.41×10^-10 to 2.33×10^-9 m²/s.

Assessment of flood mitigation services in Khon Kaen City through integrated modelling and scenario simulations

Wed, 08 Nov 2023 00:00:00 +0700

This study highlighted the identifying remedial measures for flood mitigation under varying rainfall intensity. The MIKE URBAN was coupled with the MIKE 21 within the MIKE FLOOD URBAN model to simulate flood propagation in Khon Kaen City. The reliability of 1D model was proven through calibration and validation, in which the water level observed in Nong Khot Lake was satisfactorily predicted as the values of coefficients of determination (R²) and Nash-Sutcliffe Efficiency (NSE) are greater than 0.80, Root Mean Square Error (RMSE) is close to zero, and Percent bias (PBIAS) is less than 10%. The MIKE FLOOD URBAN was further calibrated for the rainfall event of 1 September 2019, while the results from a low Relative Error (RE) of 0.14 and a high F-statistics (F_S) of 83.72% indicated a high goodness of fit between UAV-based mapping (0.196 km²) and MIKE FLOOD URBAN simulated flood extents (0.169 km²). The MIKE FLOOD URBAN was validated against floodmarks on 25 September 2022, and there was a satisfactory correlation between flood depth reported by news reports and the simulated results. To respond to floods caused by tropical storms Podul and Noru of September 2019 and September 2022, respectively, five flood mitigation scenarios were examined for their effectiveness compared to the baseline. The integration between the drainage improvement project of Maliwan Road and advance depletion of water level in Nong Khot Lake by 3.5 m, was the most promising combination to alleviate flood consequences at repeatedly flooded areas with the maximum decrease in flood depths of 0.77 m. The average flood depth and total flooded areas were decreased by up to 27.66% and 10.66%, respectively, which is an optimistic sign to convince agencies to extend these management actions to include other flood mitigation works for enhancing flood resilience of Khon Kaen City.

Cocoon waste reinforced in epoxy matrix composite: Investigation on tensile properties and surface morphology

Jeerasak Jarupong, Apichart Artnaseaw, Suparat Sasrimuang — Thu, 26 Oct 2023 00:00:00 +0700

There is potential for using silkworm cocoon waste such as broken, damaged, discarded and uncoiled cocoons as well as the caterpillars that remain inside. Cocoon waste is estimated to account for up to 11% of raw cocoon input in the textile industry. The aim of the present work is to use cocoon waste as the natural fiber reinforcement in an epoxy resin matrix composite. Cocoon waste with different weight fractions of 0 wt%, 25 wt%, 42 wt%, 58 wt%, and 75 wt% were used as reinforcement with an epoxy resin matrix to fabricate the composite material by hand lay-up technique. Subsequently, tensile testing and scanning electron microscopy observations were employed to evaluate the performance of the proposed composite materials. Experimental results demonstrated that the tensile strength continuously increased as cocoon waste fiber increased from 25 wt% to 58 wt%, reaching a maximum tensile strength of 61.04 MPa. Elastic modulus showed a slight difference of 25 wt% to 58 wt%, a maximum of 762.91 MPa. However, at 75 wt%, the tensile strength and elastic modulus declined by 57.07 MPa and 515.69 MPa, respectively. The 58 wt% of cocoon waste was presented as the optimum ratio for reinforcement with an epoxy resin matrix. The SEM image revealed the dispersion of cocoon waste in an epoxy resin matrix, presenting the close-packed interfacial bonding between cocoon waste fiber and matrix. This research is useful for the development of cocoon waste-based composites with improved mechanical properties.

Influence of laminar and turbulent flow on signal response of gas sensors in electronic nose chamber for detecting rancid odor in brown rice (cv. Khao Dawk Mali 105)

Phongprapan Kantakaew, Damorn Bundhurat, Viboon Changrue, Natawut Neamsorn — Mon, 04 Mar 2024 00:00:00 +0700

The aim of this research was to investigate the influence of flow pattern of the gas carrier inside the electronic nose chamber on the response rate of the signal from an array of gas sensors. The gas sensors in the electronic nose chamber were tested with laminar flow and turbulent flow. The principles of Reynolds number and the Navier-Stokes equation were employed to calculate and model the airflow in Computational Fluid Dynamics (CFD) simulations. The simulated airflow was compared to the actual airflow using smoke as a visual indicator to indicate the type of flow. Variables and conditions derived from the flow patterns were used in an actual experiment of electronic nose to detect specific odor compounds in brown rice (cv. KDML105). The six sensors were installed in an electronic nose chamber. The signals from the experiment were then used to determine the most effective sensor response between laminar and turbulent flow. Significantly different results were observed between the two flow patterns with a p-value < 0.05 for five out of six sensors. Additionally, the analysis of the rate of signal change indicated that the laminar flow pattern had higher values compared to the turbulent flow pattern.

Evaluating limit of detection and quantification for higher heating value and ultimate analysis of fast-growing trees and agricultural residues biomass using NIRS

Mon, 30 Oct 2023 00:00:00 +0700

Accurate non-destructive assessment of biomass energy properties is essential for optimizing its use as an alternative fuel. In this study, 200 biomass samples were used to determine higher heating value (HHV) and 120 biomass samples for analyzing ultimate analysis parameters using near-infrared spectroscopy within the full wavenumber range of 12489.48 – 3594.87 cm^-1. The samples were grounded, and five different types of partial least squares regression (PLSR) models were developed using traditional preprocessing, multi-preprocessing (MP) with 5 range, MP with 3 range, genetic algorithm, and successive projection algorithm. Limit of detection (LOD) and quantification (LOQ) were calculated using the best-performing model among five different PLSR models for HHV in kJ/kg, as well as the weight percentage (wt.%) of carbon (C), oxygen (O), hydrogen (H), and nitrogen (N). The LOD and LOQ for HHV were calculated as 622.42 kJ/kg and 1886.13 kJ/kg, respectively. Additionally, LOD and LOQ for ultimate analysis parameters, including C, O, H, and N were calculated as: 3.24 weight percentage (wt.%) and 9.81 wt.% for C, 2.04 wt.% and 6.18 wt.% for O, 0.35 wt.% and 1.05 wt.% for H, and 0.22 wt.% and 0.68 wt.% for N. The LOD and LOQ values for HHV, C, O, and H were lower than the minimum reference values used for model development, demonstrating the models’ high sensitivity and potential to reliably detect and precisely quantify these parameters. However, the LOD and LOQ values exceeded the minimum reference value used during model development for the N, indicating that the selected models have certain limitations in assessing the N content in biomass. The sample range should be expanded for wt.% of N to enhance the model’s performance, surpassing the LOD and LOQ values. This will improve the overall sensitivity of the model for reliable detection and quantification of N content in biomass samples.

Fixed-structure heading-autopilot controller design using meta-heuristics

Thu, 14 Dec 2023 00:00:00 +0700

This work presents an alternative efficient means to synthesise a fixed-structure autopilot controller that is both robust and optimal using meta-heuristics (MHs). The problem is aimed at finding controllers in several sections with the objective of minimising integral square error, subject to several constraints to ensure a robust, precise, and rapid reference tracking control system. An optimum control problem was posed while several MHs were employed to solve the problem, and their performances were investigated. Based on the results, a Self-Adaptive Differential Evolution (JADE) was found to be the most efficient algorithm. The study presents a simple but effective tool for designing a robust and optimum autopilot flight controller. It also explores the performance of several MHs in the new optimisation design field of robust and optimal flight control systems.

The experimental study of rear fender production using plastic injection molding with Moldex3D simulation

Wed, 08 Nov 2023 00:00:00 +0700

In the automotive industry are currently getting more attention because of a significant rise in demand for plastic products, particularly in the automotive, aerospace, sports, and household markets. To produce elaborate shapes and complex geometries with good dimensional precision, manufacturers placed increased focus on plastic injection molding. Adopting various cutting-edge technologies, such as CAD/CAM/CAE, is crucial to meeting demand since they help us understand the injection molding process and manufacture high-quality products. This article focuses on the analysis of the rear fender for automotive products used in the injection molding process using the software Moldex3D. One of the various types of software used to simulate a component's model is Moldex3D. Software called Moldex3D is commonly referred to as computer-aided engineering (CAE). According to the material and technological factors utilized, determines the melt front time, and sprue pressure. Polypropylene (PP) material has been taken into consideration in current research. The qualities of plastic products are influenced by a variety of factors. According to the investigation, the most suitable gate position for a consistent flow of mold material has been suggested. The injection speed and injection pressure are factors that affect the melt front time, according to the multilevel factorial design. To generate the best quality product, the operational factors must be accurate. With a change in parameters, there are changes in the product. The quality of manufacturing products without defects such improper location of runner, flow marks, short shots, hesitation, over packing, and others are referred to as the optimal parameter.

Correlation-based feature selection and Smote-Tomek Link to improve the performance of machine learning methods on cancer disease prediction

Lalu Ganda Rady Putra, Khairani Marzuki, Hairani Hairani — Fri, 20 Oct 2023 00:00:00 +0700

Indonesia is an archipelago with the fourth largest population in the world, with a population of 283 million. In Indonesia, breast cancer ranks first in cancer and is the highest contributor to death. Deaths caused by breast cancer can be minimized by screening and early detection to avoid the risk of more severe cancer. Early detection of breast cancer can delay the growth of cancer cells and increase the chances of recovery. This research proposed a machine learning-based application for screening and early detection of breast cancer independently based on perceived symptoms. However, developing breast cancer early detection applications requires a very high level of accuracy to minimize prediction errors. This research focused on finding the optimal accuracy of the machine learning method so that it could predict breast cancer with a very low error rate. This research aimed to improve the performance of classification methods in breast cancer disease prediction using the correlation feature selection approach and hybrid sampling Smote-Tomek Link. This research utilized Support Vector Machine (SVM) and Naive Bayes classification methods with a combination of Smote-Tomek Link hybrid sampling approach and correlation feature selection. Hybrid Sampling Smote-Tomek Link balanced the data by minimizing noise in the data created. At the same time, the correlation feature selection method was used to select relevant or influential attributes with class attributes based on a strong correlation level (≥ 0.6) between input attributes and classes. The results of this study obtained that the SVM method with hybrid sampling and correlation feature selection obtained the best performance compared to the Naive Bayes method and previous research referred to with an accuracy of 96.80%, sensitivity of 96.80%, and specificity of 96.80%. Thus, using the Smote-Tomek Link hybrid sampling approach and correlation feature selection positively impacted the performance increase in the SVM and Naive Bayes methods for breast cancer prediction.

Effect of uncertainties in prediction models of shallow and deep foundations

Houcine Djeffal, Laid Rouaski, Smain Belkacemi — Wed, 18 Oct 2023 00:00:00 +0700

The primary objective in foundation design is to ensure that the foundation exhibits satisfactory behavior under regulatory loading conditions while addressing critical safety concerns. This study aims to investigate the impact of parameter uncertainties in prediction models for bearing capacity and settlement of shallow and deep foundations on resulting failure probabilities using various approximation methods. Recognizing the complexity of reliability studies, this research explores the possibility of not probabilizing all variables and simplifying calculations for future applications. Additionally, it aims to assess the effectiveness of commonly used approximation methods in geotechnical engineering for estimating failure probabilities. The study's findings would enhance foundation reliability indices and decrease the probability of failure. The parametric study has enabled us to identify the variables that are most sensitive to changes in their coefficient of variation. The influence of model selection on foundation reliability is emphasized, and a critical evaluation of model bias is crucial for reliability analysis. It is evident that conservative models may shift subsequently calculated failure probabilities by inaccurately assigning situations from the safe domain to the failure domain due to inherent conservatism.

Comparative effects of prebiotic addition on the physicochemical and microstructural properties of spray-dried yogurt powder

Peerawat Taengsopha, Tiraporn Junyusen, Pornpimol Moolkaew, Payungsak Junyusen — Wed, 08 Nov 2023 00:00:00 +0700

This experimental study examined the effects of inulin and fructooligosaccharides (FOS) additions as partial maltodextrin (MD) replacement on the physicochemical and microstructural properties of spray-dried yogurt powder. Pasteurized whole milk, maltitol, yogurt cultures, and carrier materials were used to make yogurt. The carrier materials were 15% MD (Control), a combination of 5% MD and 10% inulin (Inulin), and a combination of 5% MD and 10% FOS (FOS). Spray-drying conditions were inlet and outlet temperature of 150ºC and 90ºC, with a feed rate of 9 mL/min. Physicochemical properties, solubility, hygroscopicity, particle size, and microstructure of the spray-dried yogurt powder were analyzed. Results showed that replacement of MD with inulin and FOS did not affect product yield (13.16–15.07%), moisture content (2.47–2.70%), and water activity (0.21–0.25) of the powder. Inulin and FOS additions significantly increased powder tapped density compared to the Control (p<0.05), indicating smooth and uniform particle surfaces. Replacement of MD with inulin and FOS improved the solubility of the powder, while addition of inulin decreased powder hygroscopicity and flowability compared to the Control (p<0.05). Mean particle diameters of the powder ranged from 26.43 to 29.99 µm, with morphological structure as spherically shaped with smooth surfaces and varying particle size with uniform distribution. Results suggested that inulin effectively enhanced the quality of spray-dried yogurt powder by reducing hygroscopicity and improving the solubility and tapped density.

Investigation of seed quality and seed surface modification changes in black soybean (Glycine max L. Merr) affected by plasma activated solution

Laongdown Sangla, Viboon Changrue, Tanachai Pankasemsuk, Sangtiwa Suriyong — Sat, 28 Oct 2023 00:00:00 +0700

Plasma-activated solution (PAS) is attractive due to the shorter process and no need gaseous phase. The objective was to find whether PAS can improve seed quality of black soybean cv. Sukhothai 3 by seed coat modification and to enquire optimum treatment times. PAS was generated by treating 0.05% H₂O₂ with UV-C radiation at 0.5 l min-1 flow rate to obtain PAS-H₂O₂. Treated seeds and untreated were determined physical properties, seed quality, microbial population, and morphology changes. The results revealed that seed germination and the number of normal seedlings treated by PAS-H₂O₂ were non-significantly higher than untreated samples. While seed vigor, root length, and seedling dry weight showed the maximum level when subjected to the PAS-H₂O₂ condition for 5 minutes. The exposure duration of PAS-H₂O₂treatment did not affect seedling stem development. The PAS-H₂O₂ could control total microorganisms to a standard level and the colony was reduced. The seed coat features, the changes of cell expansion and the number and size of seed pores increased than control treatment. This study indicated that plasma-activated solution could improve soybean seed germination and seedling establishment by modifying seed coat properties cooperated with different effects of treating times.

Improved Symbiotic Organism Search (I-SOS) for global numerical optimization

Umar Umar, Faanzir Faanzir, Iswan Iswan, Muhammad Said, Haryati Haryati — Tue, 19 Sep 2023 00:00:00 +0700

The no free lunch theory states that no specific heuristic method can effectively solve all problems. This theory has created opportunities for researchers to improve existing heuristic methods or even discover new approaches. One algorithm that has gained considerable attention from researchers is the Symbiotic Organism Search (SOS) algorithm. Its appeal lies in its simplicity and minimal parameter requirements, making it applicable to various problem domains. However, the SOS algorithm also has its limitations. This study focuses on the enhancement of SOS by introducing a modified random weight (MRW) method during the parasitism phase, resulting in the Improved SOS (I-SOS) algorithm. The effectiveness of this algorithm is tested in solving unconstrained problems using 26 benchmark functions and compared to several existing heuristic methods in the literature. The simulation results show that I-SOS outperforms basic SOS as well as several other algorithms.

Comparative study on material models for BS 080M46 medium carbon steel

Nattarawee Siripath, Surasak Suranuntchai, Sedthawatt Sucharitpwatskul — Thu, 14 Dec 2023 00:00:00 +0700

This work focused on studying the flow behavior of BS 080M46 medium carbon steel through hot compression tests, covering a deformation temperature of 900, 1000, 1100, and 1200°C and strain rates varying from 0.1 to 10 s^-1. The purpose of this work was to effectively predict the flow behavior of the material at elevated temperatures using two different constitutive models: the Arrhenius-based and the Hansel-Spittel model. The application of the regression method involved fitting the experimental stress-strain data to obtain the material constants for these models. A comparison was made between the experimental and predicted flow stresses based on the two constitutive models, demonstrating a strong correlation with the experimental data. The developed Arrhenius-based constitutive model exhibited greater accuracy and reliability in its predictability compared to the Hansel-Spittel constitutive model, with AARE of 7.5231%, an RMS of 7.3565 MPa, and an R value of 0.98450. To further validate the predictive capability of the two constitutive models, they were incorporated into finite element software to conduct simulations of the hot compression tests. Comparing the actual load-displacement curves with those obtained curves obtained through finite element simulations revealed a comparable consistency between the predicted and actual load-displacement curves.

Performance and sustainability evaluation of rice husk-powered dryer under natural and forced convection mode

Thu, 02 Nov 2023 00:00:00 +0700

Sun drying method has been used for drying agricultural commodities for centuries worldwide. The sun drying can be performed either by direct drying of the product under sunlight or drying using a solar collector-based dryer. However, a problem arises during the rainy season when there are lack of sunlight for proper drying. The application of biomass waste-powered dryers is a potential sustainable technology to encounter the problem. The present work aims to evaluate the performance and sustainability indicator of the rice husk-powered dryer under natural and forced convection modes while drying chili. The performance of the dryer evaluated is energy and exergy efficiency, and specific energy consumption (SEC). Meanwhile, the sustainability indicators evaluated are the waste-to-energy ratio (WER) and sustainability index (SI). The results show the performance and the sustainability indicator of the dryer are better under forced convection mode than that under natural convection mode. Overall energy and exergy efficiencies of the dryer are 3.58% and 4.93% under natural convection mode and the values are 16.85% and 16.13%, under force convection mode. Whereas, the SEC of the dryer is 26602.91 kg of rice husk/kg of water vapour for natural convection mode and 6979.89423 kg of rice husk/kg of water vapour under force convection mode. Furthermore, the sustainability of the dryer is better under force convection than under natural convection mode. WER under forced convection mode is lower than WER under natural convection mode. This gives a higher sustainability index (SI) of the dryer when operated under forced convection. The SI of the dryer ranges from 1.42 under natural convection to 1.92 under forced convection mode.

A new weighting scheme for document ranking based on the modified word-embedding method

Mohammad Edalatfard, Morteza Mohammadi Zanjireh, Mahdi Bahaghighat — Mon, 11 Mar 2024 00:00:00 +0700

Finding documents related to a search query or similar to a specific document is among the important duties of information retrieval. The vector space model has fundamental techniques, including the bag-of-words model and the TF-IDF model. These techniques are the main strategies for determining the documents' similarities. Another method for producing a document vector is using word vectors. Thanks to recent advancements in distributed meaning, word vectors can be created with significant volumes of unlabeled textual input, primarily through artificial neural network (ANN)-based methods. A semantic space is built using this data, and word-embedding vectors represent words in this semantic space. The present study examines various approaches for transforming word-embedded vectors into document vectors and offers a new approach. Ad-hoc retrieval is one of the information retrieval tasks to employ these techniques. In this research, the metrics of mean average precision (MAP) and normalized discounted cumulative gain (NDCG) are used to assess the algorithm, followed by comparing various approaches using these two measures. The findings of this investigation demonstrate that the suggested TAW-TFIDF method outperforms alternative weighting methodologies.

Appraising the impacts of binary blends of limestone powder – metakaolin mixtures on the geomechanical behaviour of black fine-grained soil and its microstructural evolution

Imoh Christopher Attah — Wed, 31 Jan 2024 00:00:00 +0700

This study strives for the usage of zero - cement/lime binders on the geomechanical performance of black fine-grained soil ameliorated with the mixtures of waste derivatives. In a nutshell, this study is aimed at appraising the impacts of limestone powder (LP) and metakaolin powder (MP) on black expansive soil (BES) via mechanical and microstructural means. During the compaction testing, an increment in the dosage of additive materials resulted in a gradual increase in maximum dry density (MDDs) with a corresponding decline in optimum moisture contents (OMCs). The strength testing revealed that the incorporation of the LP-MP prompted a significant rate of improvement and it was affirmed through qualitative analysis. Furthermore, both the original and additive-treated soil materials were examined qualitatively via the means of scanning electron microscopy (SEM) and Energy dispersive spectroscopy (EDS) techniques. The result from the SEM testing indicates well-compacted soil chemistry whereas the EDS revealed higher peaks of aluminosilicate minerals which is a good pointer towards soil improvement.