Desirable Approach Research Articles

Optimization of performance and emission characteristics of liquid fuel fired porous medium burner using RSM and desirability approach

ABSTRACT The porous medium combustion (PMC) is an emerging area in liquid fuel combustion, which has the ability to reduce emission and increase the fuel economy. Various operational parameters will affect the performance of liquid fuel-fired Porous Medium Burner (PMB). So, this present work focuses on finding the effect of operational parameters on the performance of PMB and to optimize it. This study was conducted in a double-layered porous burner with self-aspirated pressurized stove. Three input factors were selected, namely, fuel pressure (bar), throttle angle (°), and type of burner (Conventional burner (CB), PMB). The three output responses selected are thermal efficiency (ηth), CO (ppm), and NOX (ppm) emissions. The inscribed central composite design (ICCD) was used to design the experimental run. The response surface methodology (RSM) with desirability approach was used to optimize the multi-objective responses. The statistical analysis with ANOVA confirmed the significance of all the three input variables on the output responses. The regression model was developed with quadratic fit and it well predicts the burner performance and emission with R2 value close to 1. The multi-objective optimum input settings are found by desirability approach, i.e. fuel pressure = 1.60 bar, throttle angle = 161.3°, and burner type = PMB. The corresponding optimized responses are found as ηth = 58.39%, CO = 201. 49 ppm, and NOX = 6.43 ppm. The above optimum settings and responses are confirmed with experimental confirmation test, which is in the satisfactory level.

SOLID PARTICLE AIRJET EROSION AND CORROSION BEHAVIOR OF AA6063 ALUMINUM ALLOY

Aluminum alloy 6063 has excellent mechanical properties and it is used in automotive industries. This research focuses on solid particle airjet erosion behavior in different input parameters such as mass flow rate of 2, 3, and 4 gm/min, impingement angle of 30[Formula: see text], 60[Formula: see text], and 90[Formula: see text] and erodent velocity of 100, 150, and 200 m/s. The alumina erodent is mixed with an airjet which acts as an impingement fluid jet. Taguchi was utilized for investigating the influence of the process parameter on erosion rate, and ANOVA was performed to evaluate the parameter contribution. The impingement velocity is the most significant parameter to reduce the erosion rate rather than the impingement angle and the mass flow rate. The increase in velocity of the impingement fluid jet accelerates the erosion rate due to the high kinetic energy impact. The desirability approach is used to optimize the input parameters. At 99% confidence levels, the models were considered significant. The importance of the factor is increased by a reduced [Formula: see text]-value. From the overall analysis, the optimum conditions of solid particle airjet erosion are impingement angle of 90[Formula: see text], erodent velocity of 100 m/s and erodent flow rate of 2 gm/min. Utilizing the cyclic sweep approach, corrosion behavior and NaCl solution are involved in the test of AA6063. As the corrosion current density increased, the corrosion potential became more positive.

Experimental Modeling and Multi-Response Optimization in Friction Stir Welding Process Parameters of AA2024-T3 Using Response Surface Methodology and Desirability Approach

Experimental Modeling and Multi-Response Optimization in Friction Stir Welding Process Parameters of AA2024-T3 Using Response Surface Methodology and Desirability Approach

What should be next in lifelong posterior hypospadias: Conclusions from the 2023 ERN eUROGEN and EJP-RD networking meeting.

A congenital disease is for life. Posterior hypospadias, the severe form of hypospadias with a penoscrotal, scrotal, or perineal meatus, is a challenging condition with a major impact on lifelong quality of life. Our network meeting is aimed to identify what is currently missing in the lifelong treatment of posterior hypospadias, to improve care, quality of life, and awareness for these patients. The network meeting "Lifelong Posterior Hypospadias"in Utrecht, The Netherlands was granted by the European Joint Programme on Rare Diseases-Networking Support Scheme. There was a combination of interactive sessions (hackathons) and lectures. This paper can be regarded as the last phase of the hackathon. Surgery for hypospadias remains challenging and complications may occur until adulthood. Posterior hypospadias affects sexual function, fertility, and hormonal status. Transitional care from childhood into adulthood is currently insufficiently established. Patients should be more involved in defining desired treatment approach and outcome measures. For optimal outcome evaluation standardization of data collection and registration at European level is necessary. Tissue engineering may provide a solution to the shortage of healthy tissue in posterior hypospadias. For optimal results, cooperation between basic researchers from different centers, as well as involving clinicians and patients is necessary. To improve outcomes for patients with posterior hypospadias, patient voices should be included and lifelong care by dedicated healthcare professionals guaranteed. Other requirements are joining forces at European level in uniform registration of outcome data and cooperation in basic research.

Photodynamic Therapy as a Desirable Approach in the Treatment of Colorectal Cancer, with Special Focus on Photodynamic Nanotherapeutics in Immunotherapy.

Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide; however, there is not a convincing treatment for this disease. Limitations of conventional CRC therapies force scientists to develop novel treatment concepts for both primary care alongside adjuvant therapy. Photodynamic therapy (PDT) has been introduced as a promising therapeutic procedure for CRC mediated through theranostic principle in which special dyes, photosensitizers (PSs), are excited by near-infrared (NIR) and visible light. Recent studies showed that PDT has synergistic effects in combination with chemotherapy or immunotherapy in the treatment of CRC patients. Of note, nanoformulation of PS or immunotherapeutic agents could augment the PDT effectiveness. In this review, we summarize PDT application in CRC management with a special focus on the nanoparticles-based delivery system from the perspective of targeting deeper CRC and increased PDT efficiency, which could provide a desirable approach for clinical translation.

Analysis of a novel high-speed homogenizer technique for methyl ester production using waste cooking oil: Multi-objective optimization and energy analysis

While fossil fuels continue to be the predominant energy source, the use of renewable energy is consistently growing. Biodiesel, with its various advantages over traditional fossil fuels, stands out as a promising alternative fuel that is produced from a sustainable and abundant waste cooking oil (WCO) via a transesterification reaction (due to the low acid value of WCO) with alcohol (MeOH) and homogeneous catalyst (KOH) in a high-speed homogenizer. Biodiesel is produced in the industry using conventional mechanical stirring techniques, which are time-consuming and less efficient. It has been recently reported that high-speed homogenizers have the scale-up potential as per industrial requirements and can significantly reduce the transesterification/esterification reaction time. In the present investigation, the Taguchi technique has been applied for the design of experiments and multi-response process optimization using a composite desirability approach. The optimized values observed for yield, yield efficiency, and pour point were 99.18 ± 0.2%, 5.4 × 10–3 g/J, and − 14.9 ± 0.5 °C, respectively, at alcohol to oil molar proportion of 7:1, KOH amount of 0.5 wt%, rotor speed of 14000 rpm and 10 min of process time. The physicochemical properties of produced biodiesel were found within EN 14214 and ASTM D6751 standards limits.

Determining the Effects of Inter-Layer Time Interval in Powder-Fed Laser-Directed Energy Deposition on the Microstructure of Inconel 718 via In Situ Thermal Monitoring.

Cylindrical Inconel 718 specimens were fabricated via a blown-powder, laser-directed energy deposition (DED-L) additive manufacturing (AM) process equipped with a dual thermal monitoring system to learn key process-structure relationships. Thermographic inspection of the heat affected zone (HAZ) and melt pool was performed with different layer-to-layer time intervals of ~0 s, 5 s, and 10 s, using an infrared camera and dual-wavelength pyrometer, respectively. Maximum melt pool temperatures were found to increase with layer number within a substrate affected zone (SAZ), and then asymptotically decrease. As the layer-to-layer time interval increased the HAZ temperature responses became more repetitive, indicating a desirable approach for achieving a more homogeneous microstructure along the height of a part. Microstructural variations in grain size and the coexistence of specific precipitate phases and Laves phases persisted among the investigated samples despite the employed standard heat treatment. This indicates that the effectiveness of any post DED-L heat treatment depends significantly on the initial, as-printed microstructure. Overall, this study demonstrates the importance of part size, part number per build, and time intervals on DED-L process parameter selection and post-process heat treatments for achieving better quality control.

Optimizing design of a free piston Stirling engine using response surface methodology and grey relation analysis

The performance analysis and optimization of a γ-type free-piston Stirling engine (FPSE) are conducted using Response Surface Methodology (RSM) and Grey Relation Analysis (GRA). The input-output parameters table is determined by the RSM. A regression model is presented to investigate the influence of structural parameters of FPSE on its performance. The relation coefficients for the four output parameters obtained from the RSM are determined to be 0.9980, 0.9983, 0.9999, and 0.9995, respectively, thus unequivocally demonstrating the exceptional precision of the RSM model. Also, the relationship between displacer and piston amplitudes, operating frequency, and output power and these parameters of Stirling engine is presented via 3D surface plots. The performance of the FPSE is optimized using the desirability approach and GRA, respectively, followed by a comparison of four groups of optimization results to determine the most suitable model. The maximum output power achieved is 78.02 W, with corresponding operating frequency, displacer amplitude, and piston amplitude values of 60.24 Hz, 2.55 mm, and 7.27 mm. Finally, by comparing pre- and post-optimization, the output power is increased by 36.85%. The GRA exhibits superior optimization compared to the RSM, thus providing valuable guidance for enhancing the optimization of FPSE in this study.

Room temperature wafer bonding through conversion of polysilazane into SiO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {SiO}_{2}$$\\end{document}

Room temperature wafer bonding is a desirable approach for the packaging and assembly of diverse electronic devices. The formation of SiO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {SiO}_{2}$$\\end{document} layer at the bonding interface is crucial for a reliable wafer bonding as represented by conventional bonding techniques such as hydrophilic bonding and glass frit bonding. This paper reports a novel concept of room temperature wafer bonding based on the conversion of polysilazane to SiO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {SiO}_{2}$$\\end{document} at the bonding interface. As polysilazane is converted to SiO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {SiO}_{2}$$\\end{document} by hydrolysis, in this work, adsorbed water is introduced to the bonding interface by plasma treatment, thereby facilitating the formation of SiO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {SiO}_{2}$$\\end{document} at the wafer bonding interface. The experimental results indicate that the adsorbed water from the plasma treatment diffuses into the polysilazane layer and facilitates its hydrolysis and conversion. The proposed method demonstrates the successful wafer bonding at room temperature with high bond strength without interfacial voids. This technique will provide a new approach of bonding wafers at room temperature for electronics packaging.

Parametric investigation of W-EDM factors for machining AM60B conductive biomaterial

Wire—electrical discharge machining (W-EDM) is a precise and efficient non-traditional technology employed to cut intricate shapes in conductive biomaterials. These biomaterials are challenging to machine using traditional methods. This present study delves into the impact of various process parameters, namely discharge duration (Ddur), spark gap time (Stime), discharge voltage (Dvolt), and wire advance rate rate (Wadv). This research evaluates the impact of several factors on response variables, namely the machining rate (MR) and surface irregularity (SR), during the machining process of the AM60B magnesium alloy. The confirmation of the material used in the machining process is achieved via the utilisation of a scanning electron microscopy (SEM) image in conjunction with an energy dispersive spectroscopic (EDS) image. The experiment is designed as L9 orthogonal array by using Taguchi's approach, taking into account 4 factors with 3 levels. The objective of this experiment is to ascertain the most favourable values for machining parameters while working with AM60B magnesium alloy using brass wire. Through analysis of variance (ANOVA), the study confirms that wire advance rate (43.10%) is the most influencing parameter for machining rate and surface irregularity followed by spark gap time (33.91%) and discharge duration (11.48%). Additionally, The TOPSIS-CRITIC and the desirability approach were used in order to determine the optimum parameter combinations that provide the most favourable combined output. Confirmatory testing is used to evaluate the efficiency of the stated ideal conditions. The maximum improvement in Desirability approach is obtained at 4.56% and 4.193% for MR and SR respectively. The maximum improvement in TOPSIS approach is obtained at 1.77% and 2.78% for MR and SR respectively.

Using VIKOR and RSM-DA in the optimization of dry turning of 9XC steel

Dry turning is an effective method for reducing the production costs and environmental impact of machining processes. In this study, the effect of cutting speed (Vc), feed rate (fz), and depth of cut (ap) on the surface roughness (Ra) and material removal rate (MRR) of 9XC steel during dry turning was investigated. A Box-Behnken experimental design was employed to analyze the main effects and interaction effects of these cutting parameters. In this research, the combining Response Surface Methodology - Desirability Approach (RSM-DA) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method were both employed for solving multiple objective optimization problems, and their performance was compared. The results from both methods can be assessed based on their ability to identify the optimal set of parameters that simultaneously optimize surface quality and production rate, as well as their computational efficiency and ease of implementation. Both RSM-DA and VIKOR have been found effective for solving multi-objective optimization problems, such as optimizing cutting parameters in dry turning. While RSM-DA is a statistical tool that combines multiple objectives into a single function, VIKOR is a decision-making method that ranks alternatives based on multiple criteria. The choice of which method to use depends on the specific requirements of the problem and the availability of resources for implementation. The research results show that both VIKOR and RSM-DA are suitable for solving the multi-objective optimization problem of the turning process. According to the VIKOR method, the optimum cutting conditions were found to be a cutting speed Vc of 120 m/min, a depth of cut ap of 0.1 mm a feed rate fz of 0.06 mm/rev, and, which resulted in a surface roughness of 0.209 um and a material removal rate of 0.72 cm3/min. Meanwhile, RSM-DA predicts the optimal Ra and MRR values of 0.254 um and 3.36 cm3/min, respectively; corresponding to the Vc of 180m/min, fz of 0.06mm/rev and ap of 0.3mm; That means, the increasing the value of surface roughness by 21.5% will increase the MRR by 366.7%. The findings of this study can provide guidance for selecting the appropriate cutting parameters for dry turning of 9XC steel to achieve desired surface roughness Ra and material removal rate MRR in the specific case.

A stable hybrid catalyst (POM-PPPh3/L/Ni) for the reduction of toxic nitroarene compounds in water.

Reduction of nitroarenes to aminoarenes using novel and selective catalysts is an important and desirable approach in green chemistry. In this work, a new heterogeneous nanocatalyst, POM-PPPh3/L/Ni, was designed and prepared via functionalizing a Keggin-type polyoxometalate (H3PMo12O40) with (3-bromopropyl)triphenylphosphonium bromide (BPPPh3Br) through strong electrostatic interactions to prepare [PMo12O40][PPPh3]3 (denoted as POM-PPPh3). The obtained compound was modified via nucleophilic attack of the nitrogen donor of a multidentate Schiff base ligand (L) on its propyl chain to produce [PMo12O40][PPPh3/L]2 (denoted as POM-PPPh3/L), which was finally metallated with nickel cations to achieve [PMo12O40][PPPh3/L/Ni]2 (denoted as POM-PPPh3/L/Ni). After full characterization of the prepared material with various physicochemical methods, its catalytic behavior was investigated in the catalytic nitroarene reduction. The influence of various factors on catalytic conversion and selectivity was considered. The synthesized nanocatalyst showed excellent performance in the reduction of nitroarenes in aqueous media in the presence of NaBH4 as a reducing agent. Mild reaction conditions and a short reaction time (10 min) are the prominent features of this new nanocatalyst. In addition, the catalyst was recovered and reused for up to four cycles of catalytic reduction without any significant loss of conversion.

Ce-doping induces rapid electron transfer in a bimetallic phosphide heterostructure to achieve efficient hydrogen production.

Using electrochemical water splitting to generate hydrogen is considered a desirable approach, which is greatly impeded by the sluggish dissociation of H2O and adsorption and desorption of H*. Effective hydrogen production can be achieved by speeding up the chemical process with a suitable electrocatalyst. In this work, we designed and synthesized a rare earth element cerium (Ce) regulated iron-nickel bimetallic phosphide Ce-NiFeP@NF (here NiFeP represents Fe2P/NiP2) nanoarray with nanoflowers. For the hydrogen evolution reaction (HER), Ce-NiFeP@NF only needs an overpotential of 106 mV to provide a current density of 10 mA cm-2, compared to NiFeP@NF (175 mV@10 mA cm-2). This self-supported electrocatalyst Ce-NiFeP@NF with a composite morphology exhibits excellent performance in the HER. Specifically, the introduction of Ce promotes the electron transfer process at the Fe2P/NiP2 heterojunction interface and the Ce-NiFeP@NF nanocomposite structure with nanoflowers has a larger electrochemically active specific surface area, which is more conducive to improving the intrinsic catalytic activity. Also, a dual-electrode alkaline electrolytic cell (Ce-NiFeP@NF functions as both the anode and the cathode) operates with a cell voltage of only 1.56 V to achieve a current density of 10 mA cm-2. The synergistic effect of rare earth element doping and heterojunction engineering can improve the morphology of intrinsic catalysts to achieve more efficient electrochemical water splitting for hydrogen production.

Acute Effects of Cadence-Controlled Walking on Cognition and Vascular Function in Physically Inactive Older Adults: A Randomized Crossover Study.

Cadence-controlled walking may be a desirable approach for older adults to self-monitor exercise intensity and achieve physical activity guidelines. We examined the acute effects of cadence-controlled walking on cognition and vascular function in physically inactive older adults. In a randomized crossover design, 26 participants (65% females, 67.8 ± 11.3years) underwent 30-min acute exercise (walking at 100steps/min) and control (sitting) conditions. We measured cognition, central blood pressure (BP), and arterial stiffness before, and immediately, after each condition. We observed significant Time × Condition interactions in the Flanker Inhibitory Control and Attention (Flanker) test and Dimensional Change Card Sort (DCCS) test scores, and in central systolic BP, central pulse pressure, and carotid to femoral pulse wave velocity (p < .05). The Flanker and DCCS scores significantly increased after walking (d = 0.4 and 0.5, respectively), but not after sitting. Central systolic BP, central pulse pressure, and carotid to femoral pulse wave velocity significantly increased after sitting but remained unchanged after acute walking (d = 0.4-0.2), with p-values < .05. After walking, significant correlations were observed between DCCS and diastolic BP and central pulse pressure change scores and change scores in central pulse wave velocity,Flanker, and DCCS (rs = -0.45 to -0.52). These findings suggest that a single bout of cadence-controlled walking elicited an immediate improvement in cognition and might have mitigated increases in arterial stiffness and central BP observed in the seated control condition. Further research is needed to examine the association between cognition and vascular function following acute exercise compared to control conditions. Our findings may have practical implications for developing daily physical activity recommendations for improving the cognitive health for successful aging.

Colon-targeted piperine-glycyrrhizic acid nanocrystals for ulcerative colitis synergetic therapy via macrophage polarization.

Ulcerative colitis (UC) is a chronic inflammatory disease that affects the gastrointestinal tract and is characterized by immune dysregulation. Oral administration of nanoformulations containing immunomodulators is a desirable approach to treating UC. However, low drug-loading (<10%, typically), premature drug release, and systemic absorption of these nanoformulations continue to be significant challenges restricting clinical applications. Herein, we developed colon-targeted piperine-glycyrrhizic acid nanocrystals (ES100-PIP/GA NCs) to treat UC through the regulation of macrophages. The ES100-PIP/GA NCs exhibited ultra-high drug loading and colon-specific drug release. In vitro studies demonstrated that the ES100-PIP/GA NCs could effectively be internalized by lipopolysaccharide (LPS)-induced RAW 264.7 and Caco-2 cells. More importantly, the ES100-PIP/GA NCs could downregulate pro-inflammatory factors (IL-1β, IL-17A), upregulate anti-inflammatory factors (TGF-β1), and repair the intestinal mucosal barrier. In a murine model of acute colitis induced by dextran sodium sulfate (DSS), ES100-PIP/GA NCs could protect PIP and GA from gastric acid destruction, reach the colon, and significantly inhibit colitis. Surprisingly, ES100-PIP/GA NCs enhance M2 macrophages by increasing the mammalian target of rapamycin (mTOR), and inhibit M1 macrophages by reducing hypoxia-inducible factor-1α (HIF-1α). Overall, this study shows that ES100-PIP/GA NCs have synergistic immunotherapy capabilities with macrophage regulation, which offers a promising blueprint for the oral delivery of multicomponent drugs in UC therapy.

Enhancing Sustainability of Water‐Emulsified Diesel–Hydrogen Carrier Biogas as Fuel in Dual‐Fuel Engines through the Parametric Optimization

This study investigates the usage of biodiesel‐based emulsified fuel as pilot fuel and waste‐derived biogas as prime fuel to run dual‐fuel engines at varying compression ratios (17, 17.5, 18), injection timing (23°, 26°, 29°, 32° BTDCs), and engine loads (20%, 40%, 60% 80%, 100%). Mahua biodiesel, surfactants, and water were used to produce two‐phase stable emulsification. The findings showed that using biodiesel‐based emulsified fuel as pilot fuel combined at the compression ratio of 18 and advanced fuel injection time of 29° BTDC increased performance and lowered emissions. Additionally, response surface methodology with variance analysis was used to create prediction models for all engine outputs with a robust R2 value (0.8927–0.9974). The engine operation was optimized employing the desirability approach to be 85.3% of engine load, compression ratio of 18, and injection timing of 29° BTDC. At optimal settings, the anticipated engine outputs were 17.46% for brake thermal efficiency, 318.5°C for exhaust gas temperature, 76.1% for liquid fuel replacement, 45.3 bar of peak in‐cylinder pressure, 3.97 vol.% carbon dioxide, 137.43 ppm carbon monoxide, 132 ppm hydrocarbon, and 42 ppm oxides of nitrogen. The lab‐based engine testing found that the results were well within 7.14% of the projected values at these optimal operating parameters.

The Evaluation of Entropy-based Algorithm towards the Production of Closed-Loop Edge

This research concerns the common problem of edge detection that produces a disjointed and incomplete edge, leading to the misdetection of visual objects. The entropy-based algorithm can potentially solve this problem by classifying the pixel belonging to which objects in an image. Hence, the paper aims to evaluate the performance of entropy-based algorithm to produce the closed-loop edge representing the formation of object boundary. The research utilizes the concept of Entropy to sense the uncertainty of pixel membership to the existing objects to classify pixels as the edge or object. Six entropy-based algorithms are evaluated, i.e., the optimum Entropy based on Shannon formula, the optimum of relative-entropy based on Kullback-Leibler divergence, the maximum of optimum entropy neighbor, the minimum of optimum relative-entropy neighbor, the thinning of optimum entropy neighbor, and the thinning of optimum relative-entropy neighbor. The experiment is held to compare the developed algorithms against Canny as a benchmark by employing five performance parameters, i.e., the average number of detected objects, the average number of detected edge pixels, the average size of detected objects, the ratio of the number of edge pixel per object, and the average of ten biggest sizes. The experiment shows that the entropy-based algorithms significantly improve the production of closed-loop edges, and the optimum of relative-entropy neighbor based on Kullback-Leibler divergence becomes the most desired approach among others due to the production of more considerable closed-loop edge in the average. This finding suggests that the entropy-based algorithm is the best choice for edge-based segmentation. The effectiveness of Entropy in the segmentation task is addressed for further research.

The Evaluation of Entropy-based Algorithm towards the Production of Closed-Loop Edge

This research concerns the common problem of edge detection that produces a disjointed and incomplete edge, leading to the misdetection of visual objects. The entropy-based algorithm can potentially solve this problem by classifying the pixel belonging to which objects in an image. Hence, the paper aims to evaluate the performance of entropy-based algorithm to produce the closed-loop edge representing the formation of object boundary. The research utilizes the concept of Entropy to sense the uncertainty of pixel membership to the existing objects to classify pixels as the edge or object. Six entropy-based algorithms are evaluated, i.e., the optimum Entropy based on Shannon formula, the optimum of relative-entropy based on Kullback-Leibler divergence, the maximum of optimum entropy neighbor, the minimum of optimum relative-entropy neighbor, the thinning of optimum entropy neighbor, and the thinning of optimum relative-entropy neighbor. The experiment is held to compare the developed algorithms against Canny as a benchmark by employing five performance parameters, i.e., the average number of detected objects, the average number of detected edge pixels, the average size of detected objects, the ratio of the number of edge pixel per object, and the average of ten biggest sizes. The experiment shows that the entropy-based algorithms significantly improve the production of closed-loop edges, and the optimum of relative-entropy neighbor based on Kullback-Leibler divergence becomes the most desired approach among others due to the production of more considerable closed-loop edge in the average. This finding suggests that the entropy-based algorithm is the best choice for edge-based segmentation. The effectiveness of Entropy in the segmentation task is addressed for further research.

The Evaluation of Entropy-based Algorithm towards the Production of Closed-Loop Edge

This research concerns the common problem of edge detection that produces a disjointed and incomplete edge, leading to the misdetection of visual objects. The entropy-based algorithm can potentially solve this problem by classifying the pixel belonging to which objects in an image. Hence, the paper aims to evaluate the performance of entropy-based algorithm to produce the closed-loop edge representing the formation of object boundary. The research utilizes the concept of Entropy to sense the uncertainty of pixel membership to the existing objects to classify pixels as the edge or object. Six entropy-based algorithms are evaluated, i.e., the optimum Entropy based on Shannon formula, the optimum of relative-entropy based on Kullback-Leibler divergence, the maximum of optimum entropy neighbor, the minimum of optimum relative-entropy neighbor, the thinning of optimum entropy neighbor, and the thinning of optimum relative-entropy neighbor. The experiment is held to compare the developed algorithms against Canny as a benchmark by employing five performance parameters, i.e., the average number of detected objects, the average number of detected edge pixels, the average size of detected objects, the ratio of the number of edge pixel per object, and the average of ten biggest sizes. The experiment shows that the entropy-based algorithms significantly improve the production of closed-loop edges, and the optimum of relative-entropy neighbor based on Kullback-Leibler divergence becomes the most desired approach among others due to the production of more considerable closed-loop edge in the average. This finding suggests that the entropy-based algorithm is the best choice for edge-based segmentation. The effectiveness of Entropy in the segmentation task is addressed for further research.

Multi-Objective Optimization in WEDM Process of Titanium Alloy (Ti-3Al-2.5V-2.0WC) using Desirability Approach

Recently, Titanium alloy (Ti-3Al-2.5V) reinforced with Tungsten Carbide (Ti-3Al-2.5V-2.0WC) developed using the microwave sintering process has plays a major role in mining industry. It has very good mechanical property and corrosion resistance. Due to its better strength and high melting point, it is difficult to machine in conventional machining process. Therefore, WEDM process give the solution to cut this high strength material in an effective manner. In this present work, the WEDM input variables such as Servo Voltage (SV), Pulse Time - On (PT-ON), Pulse Time – Off (PT-OFF) and Cutting Speed Percentage (CSP) are considered. L09 Orthogonal Array Matrix (OAM) is considered for experimental work. The output variables like Material Removal Rate (MRR) and Surface Roughness (SR) are considered to obtained the quality machining process. Multi objective optimization technique like Taguchi-Desirability Approach method is implemented to find the optimum input variables. The Improvement of MRR from 0.05978 g/min to 0.06420 g/min and SR from 3.812 μm to 3.452 μm are obtained using Desirability Approach.