Search

Most manufactured electrical cables suffer from reductions in their physical, mechanical and electrical properties. These setbacks are mainly attributed to the improper control of wire tension during the cable manufacturing process. Hence, this paper systematically reviewed different control algorithms involved in controlling tension in moving webs, which include conventional control, advanced control, observer-based control, artificial intelligence-based control and hybrid control techniques. Thus, the review provided information about existing tension control techniques in moving webs, including their strengths and weaknesses. It was observed in this review that although a significant research effort has been made on web tension control systems, a thorough literature review is still lacking. It was concluded that controller optimisation using hybrid control algorithms is gaining popularity in web tension control due to their improved control response. Hence, its application in wire tension control can better help cable manufacturers improve the quality of manufactured cables. [ABSTRACT FROM AUTHOR]

The intense competition in the field of new shipbuilding business today requires shipyards to increase their productivity in terms of quality, cost, on-time delivery performance, and flexibility. Product-oriented Work Breakdown Structure (PWBS)-based steel ship production technology has played a vital role in the shipyard's success in competition. A block and modular assembly approach using the PWBS method was prepared to guide shipyards. This paper presents a study on the technology capability of four selected Indonesian medium-sized shipyards and one leading shipyard as the benchmark in using the PWBS method. The technology capability in shipbuilding is measured using the technometric assessment model by the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP), which consists of four indicators; technoware, humanware, infoware, and orgaware. The results show that the shipyards' Technology Coefficient Contribution (TCC) is between 0.5 and 0.7 (TCC maximum 1.0). This value indicates that the four shipyards in this case study are capable of building ships based on PWBS method. However, some aspects have to be improved to ensure the method is implemented properly, including: better design software that could prepare comprehensive production engineering documents, production lane with more automation, and more crane capacity. Of course, large additional investments must be supported by continuous orders for new ships with relatively the same type and size of ships, so that they are more productive and gradually able to compete in the global market. [ABSTRACT FROM AUTHOR]

This paper gives an investigation into the morphological analysis of boron carbide and the mechanical properties of the Jutton-Glass hybrid polymer nanocomposites. As reinforcements, hybrid nanoparticles comprising boron carbide and graphene nanoplatelets were used. For laying the composites, the vacuum bagging technique was used with the composition of hybrid nanomaterial taken as 0, 0.25 and 0.5 wt.% of Gr and B4C, and the samples were tested for mechanical properties as per ASTM standards. The samples prepared have been subjected to various tests, and the results are reported. Before the preparation of composites, the polymer was mixed with surface-modified nanomaterial and stability tests were conducted to assess uniform dispersion with the aid of UV spectroscopy, and the outcomes showed that the samples had been exceptionally uniform over some time. It is determined that the mechanical behavior of hybrid composites, which include B4C with Gr, shows better properties than base, B4C, and Gr. However, the multi-layered samples with graphene nanoplatelets also showcased encouraging mechanical properties like hardness and tensile strength. [ABSTRACT FROM AUTHOR]

This paper describes deep neural network (DNN) models based on hyperparameter optimization for the prediction of the compressive strength of concrete. The novelty of this research lies in the implementation of optimized hyperparameters to train the DNN models with the aim to enhance their predictive accuracy. Utilizing the Keras Tuner library, the most effective hyperparameters for the DNN models were identified. These models are then trained and evaluated using an experimental dataset of 1030 instances, encompassing nine quantitative variables that include various concrete mix ingredients and age. The target variable for all models is the compressive strength of concrete. The assessment of model performance, based on metrics like mean squared error (MSE) and R² values, was conducted on previously unseen test data. The optimal configuration for the hidden layers in the model was identified as five layers, containing 12, 16, 16, 40, and 26 neurons, respectively. The optimal learning rate for the model was 0.001. With this set of optimal hyperparameters, the best DNN model achieved an MSE of 28.76 and an R² value of 0.89 on the testing data. The results demonstrate a significant improvement in the DNN models' performance when trained with the optimized hyperparameters. In comparison to the regression model, the performance of the DNN models was significantly better. Adopting the predictive models developed in this research offers the potential for substantial cost and time savings by circumventing the need for labour-intensive and time-consuming laboratory tests. [ABSTRACT FROM AUTHOR]

In this paper, some exact solutions of the stochastic generalized nonlinear shallow water wave equation are investigated. This equation is important in fluid mechanics' fields since it can model the propagation of disturbances in water and other incompressible fluids. Opposite to what is usually considered in the literature, the two dispersion coefficients of the nonlinear terms are considered dependent random quantities as a more realistic case. The modified extended-tanh function (METF) method is combined with the random variable transformation (RVT) technique to get full probabilistic solutions of the problem via computing the probability density functions (PDFs) of the solution processes. Based on the probability density function, any statistical moment of the solution can be evaluated. Through two different applications for the input random variables (dispersion coefficients), my findings are applied efficiently. Finally, numerical results are presented graphically along the spatial dimension at a certain wave speed and time. The obtained results ratify that the proposed technique is efficient and powerful for obtaining analytical probabilistic solutions for the problem. [ABSTRACT FROM AUTHOR]

Studies reviewed in this paper show anomaly for temperature pertaining to streamflow and rainfall showing different trends, especially in Ethiopia to support the research findings and interpretation. There are many hydrological models, including 54 physically distributed, lumped, and conceptual hydrological models, of which 28 have been used in Ethiopian river basins. The models include the most adaptable and commonly used SWAT model applicable from small areas up to large basins. It is indeed a challenge to use a single hydrological model as the data rely on consistency, limitation-free, and exactly fitted output. The overall performance of individual physically-based, conceptual, and machine learning (ML) models varied at different watersheds. Reasonably, ML performs very well, up to 0.99 for R² and NSE and up to 0.001 for PBIAS. Inopportunely, using a single hydrological model has its limitations; ensemble multi-individual models, coupling or hybridization of physical or conceptual models with machine learning, combining evolutionary optimization algorithms with ML, and also comparisons of multi-single hydrological models, and selecting the best one are recommended options. No single hydrological model is indispensable and can be termed as better than the other for any watershed. Somewhat, ML outperforms SWAT but cannot be considered an absolute substitute. The size of the watershed, the number of data used, and the ratio between calibrations year to validation year do not have a clear correlation with the performance, particularly for the SWAT model accounted for in this review. Optimization algorithms explore multiple options and choosing the right one is a tedious task before a final decision is taken. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of powder waste glass (PWG) at 10%, 15%, and 20 wt.% replacement of cement on the flow characteristic, setting time, compressive strength, water sorption, rate of the heat of hydration, cumulative heat of hydration; alkali-silica reaction (ASR), and microstructure characteristics of the resulting paste and mortar mixtures. A total of eight cementitious mixtures including two control mixtures have been investigated in this experimental program to evaluate the effect of PWG on the fresh and hardened state characteristics of paste and mortar mixtures. Test results show that the incorporation of PWG in the cementitious mixtures results in significant enhancement of their microstructure, increase in compressive strength, improvement in moisture barrier characteristics, and considerable reduction in the rate of the heat of hydration and cumulative heat of hydration. Up to 20 wt.% replacement of cement with fine PWG is seen to be innocuous from the standpoint of ASR. Furthermore, the use of PWG in paste results in delaying the initial and final setting times and increases the flow characteristic of the mortar mixture. [ABSTRACT FROM AUTHOR]

Deepfakes are a rapidly growing technological trend that is revolutionizing many digital processes, from media production to digital access. They offer various advantages for both users and creators alike. For example, they can provide entertainment value by allowing users to create humorous or satirical versions of existing media content without having to film new scenes. They can also automate production workflows by generating background characters or extras for movies. Additionally, deepfakes could be used in healthcare applications, such as virtual avatars for doctors who require assistance during consultations with patients located far from hospitals or clinics. However, deepfakes also pose a threat to society as they can be used for malicious purposes, including spreading false information or exploiting the likenesses of others for financial gain. To address these concerns, various types of regulations have been introduced across jurisdictions worldwide. These laws prohibit doctored audio recordings and visual materials aimed at influencing election outcomes. Some countries have even gone as far as requiring companies producing deepfake materials to identify themselves as such, to make audiences aware that what they are seeing may not always be authentic representations of events. In this paper, the author will discuss what deepfakes are, their potential benefits and risks, the various types of deepfakes that exist, and how the USA has attempted to regulate them. The author will also suggest some policy recommendations aimed at mitigating the risks associated with deepfakes while still preserving their creative potential. [ABSTRACT FROM AUTHOR]

To correctly evaluate the effects of treatments, conducting randomized controlled trials (RCTs) is a reasonable approach. However, because it is generally difficult to implement RCTs for all treatments, methods to estimate the treatment effects using observational data have been actively studied and used in various decision-making processes. Observational data accumulated in business activities and elsewhere contains the results of various previously implemented treatments, and correctly estimating the effects of any given treatment without separating the impacts of other treatments is challenging. Against this background, this paper proposes a method to estimate the effects of multiple treatments of various types while considering various causal relationships. Specifically, the proposal is a variational inference method that estimates the effect of multiple treatments using four latent factors estimated from observations, making assumptions that are independent of the type and number of treatments. The proposed method makes it possible to appropriately estimate the effects of measures even in situations with complex causal relationships. In addition, in situations where measures with continuous parameters are being implemented, it is possible to estimate the effects of measures that have not been implemented in the past by treating the content of the measures as a continuous variable. [ABSTRACT FROM AUTHOR]

A drastic decline in the number of students that are enrolled for Engineering is now being experienced in developed as well as developing countries. Learning is becoming boring as a generation brought up on technology is losing the ability to pay attention in traditional classes for a long stretch of time. This has led to the idea that other teaching methods do exist and can be applied in teaching/learning. This work leveraged the use of Digital Game-Based Learning (DGBL) in Engineering classrooms to develop a serious game named LogicHouse Version 1 (LogicHouse-V1 or LogicHouse for short). The game, is a web-based serious game prototype that targets selected topics in Digital Electronics course. This course is a core component of undergraduate curriculum in Electrical & Electronics Engineering, Computer Engineering, Information Technology, Communication Engineering, Computer Science and other related Science Technology Engineering and Mathematics (STEM) courses. LogicHouse involves a virtual broken house where the player has to play the various levels to fix the house and gain points along the way. This game was designed based on the Learning Mechanics-Game Mechanics (LM-GM) model and the Unified Modeling Language (UML). Furthermore, the design was implemented using Adobe Illustrator, Procreate, Unity Engine, C#, Microsoft Azure Playfab and deployed on itch.io. Preliminary evaluation results indicate that students are interested in the game and its application. Based on this, there is a prospect of improved performance in any course in which the game is implemented. [ABSTRACT FROM AUTHOR]

The non-centrifugal cane sugar (panela) subsector stands out in Colombia as one of the most important agro-businesses, with economic growth and projection for the export of its products. For its part, the application of the Lean-Kaizen philosophy has proven to be effective for organizations to achieve continuous improvement in quality and productivity. This paper exposes the implementation of the pillars of Kaizen for the improvement of the panela manufacturing process applied in an artisan mill (Trapiche) in the Santander region, Colombia. Through the case study methodological approach, a Trapiche was selected and its production process was studied in terms of waste, order and cleanliness, and standardization. The results evidenced the types of waste that occur throughout the panela production process, the current state of order and cleanliness, and the way in which the operations are carried out to obtain the finished product. With the implementation housekeeping program (5S) and the standardization of the operational procedures, the main waste, sources of dirt and the reduction of the time used for the manufacture of panela were eliminated. The Kaizen actions improved the order and cleanliness of the Trapiche by 63% and the panela manufacturing time by 10%, complying with product quality standards. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of the SiC and triplex thermal aging treatment (TTAT) on the mechanical behavior of compound bars. The bars were fabricated by varying the SiC (2, 4 and 6wt. %) in Al6061. Initially, bars were tested for hardness and compression strength in homogenized conditions. It is observed that as SiC is increased in the matrix, mechanical properties have improved. The bars with composite cores exhibited better properties as compared to bars with composite casing. For the bar having a composite core, with 2 wt. % SiC, the compression strength was 530.70 MPa, for the 4 wt.% SiC core it was 589.35 MPa and for the 6 wt.% SiC it was 691.88 MPa. Failure was progressive, with noticeable signs of failure, and the load-bearing ability was found to be fairly stable up to nearly 218 kN. Later, the bar with a 6 wt. % SiC core was subjected to TTAT, and surface hardness, compression strength, and interfacial shear strength were found to have increased by 11.2, 3.2 and 11.11%, respectively. SiC are the hard particles; reinforcing them in a soft matrix induces strain in the lattice and thus enhances the hardness of the composite. During aging, the diffusion of alloy atoms is blocked by the generated dislocations present around the SiC particles. Hence, the bars with a higher quantity of SiC in the composite core can be used for high load-bearing structural applications due to their superior mechanical properties as an alternative to the simple composite bars with the same SiC quantity. [ABSTRACT FROM AUTHOR]

This paper gives the investigation of the mechanical properties of Jutton-Glass hybrid polymer nanocomposite with multi walled carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) as reinforcements. For preparing the composites, the vacuum bagging technique was used with the composition of hybrid nano-material taken as 0, 0.25, and 0.5 wt. % of Graphene nanoplatelets and MWCNTs and the samples were tested for mechanical properties as per ASTM standards. The samples prepared have been subjected to various testing, and the results are reported. Prior to the preparations of composites, the polymer was mixed with surface-modified nanomaterials and stability tests were conducted to assess uniform dispersion with the aid of UV-Vis spectroscopy, the outcomes showed that the samples were exceptionally uniform over a period. The hardness and tensile properties were evaluated, and it was found that surface-modified nanomaterials could improve the properties better compared to the use of pristine nanomaterials as reinforcements. It was found that 0.25% MWCNT and graphene nanoplatelets (GNPs) show more improved properties than 0.5% MWCNT and Graphene nanoplatelets. However, the composite samples with Graphene nanoplatelets also showcased encouraging mechanical properties like hardness and tensile strength. [ABSTRACT FROM AUTHOR]

Waste is considered a significant environmental issue in modern times thus the purpose of this paper is to compare the use of different waste materials in replacing aggregates in concrete. This study investigates the potential of incorporating plastic waste (PW), textile sludge (TS), and construction and demolition waste (CDW) into concrete as sustainable alternatives to traditional construction materials, by evaluating its mechanical, durability characteristics as well as the cost related to different process of the project. The study focuses on the use of PW and TS as a replacement for fine aggregate, and CDW as replacements for coarse aggregate. Thus, four concrete mixes incorporating PW and TS were prepared, using 0% 10%, 25%, 40% replacement levels. The compressive strength of concrete with 10% plastic waste as fine aggregate was 32.49 N/mm² showing higher results than that of TS. Furthermore, another four concrete mixes incorporating CDW were prepared, using 0%, 25%, 50%, 75% replacement levels. The compressive strength of concrete with 25% CDW was 30.90 N/mm² indicating an increase of 2% than the control block. The study concluded that the best strategy is to incorporate construction and demolition waste as a replacement for coarse aggregate in concrete. This is because it resulted in an increase in compressive strength as well as a decrease in cost. [ABSTRACT FROM AUTHOR]

The behavior of steel bolted connections is a complex structural problem which involves various factors such as material nonlinearity, large deformation and contact. The investigation of this behavior is one of challenging subjects in structural analyses. Unlike other structural modelling, the connections of bolted structures involve a large number of contacts, which are critical to the behavior of the joints. This paper focuses on investigating the behavior of a type of the external diaphragm which is used in rectangular hollow section column-to-beam bolted connections. The creation of a reliable finite element model is a primary aim of this research. The ABAQUS finite element package is used to simulate the experimental behavior, and three highly complex 3D finite element models are created, accounting for material nonlinearly, large deformation and contact behavior involved in the models. The connection models have been analyzed under some loading conditions up to failure. Comparisons with experimental data show that the models have high levels of accuracy, and these models may be used to gain an insight into important issues such as the connection tying force capacity of an external diaphragm, bolt and plate bearing behavior, and bolt shearing. [ABSTRACT FROM AUTHOR]

The m-polar fuzzy set (mFs) algorithm is a novel approach to solving multi-polar uncertainty problems. Combining other multi-criteria decision-making techniques can improve this algorithm in efficient ways. This work examines the ELimination Et Choice Translating Reality-I (ELECTRE-I) approach. The input data given to any MCDM technique will change the rank of alternatives based on the method of normalization used and the weight calculation method utilized for the criteria weight calculation purpose. Various normalization approaches and criteria weight methods are required to transform real data into normalized data for MCDM method implementation. This study uses a framework to implement the mFs ELECTRE-I algorithm to investigate the effect of AHP weight and Shannon's entropy weight (SEW) calculation combined with normalization strategies. In this paper, selecting nontraditional machining (NTM) processes is evaluated to assess the impact of the created framework on choices and rank performance analysis. The study results in linear sum and vector normalization are suitable normalization techniques with AHP as well as Shannon's entropy weight (SEW) criteria weight methodology with Spearman's rank correlation coefficients as 0.8333 and 0.9285, respectively, which shows consistency of the rank of alternatives with the results obtained by previous researchers. This study can be used to select suitable normalization and criteria weight methods for the m-polar fuzzy set ELECTRE-I algorithm while solving multi-criteria decision-making problems. The framework is intended to address various industrial problems with many criteria, including the selection of robots, non-traditional machining techniques, and various industrial challenges without considering their subgroups. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the mechanism of soot formation in biodiesel by analyzing the combustion of individual components. The paper presents a numerical analysis of the effect of preheat temperatures on nucleation rates, coagulation rates, and soot volume fraction in methyl linolenate (MLe) co-flow flame. In this work, Moss-Brooke's soot model and a reduced kinetic mechanism containing 177 chemical species and 2904 chemical reactions were used to simulate the pyrolysis and combustion of MLe. A laminar jet flame with inlet velocities of 0.4 m/s was studied. The preheat temperature of the fuel was varied between 300 and 450 K. The burner walls were stationary and no-slip conditions were applied. The pressure outlet had Neumann boundary conditions and the tangential velocity was set to zero at the wall. It was established that an increase in fuel preheat temperatures causes an increase in nucleation rates and the amount of soot due to accelerated fuel pyrolysis, improved diffusion, acceleration from buoyancy, and earlier formation of PAHs. It was discovered that increasing the fuel preheat temperature had a greater impact on soot formation along the centerline than on the wing. [ABSTRACT FROM AUTHOR]

Power Electronics (PE) is pivotal in fostering renewable energy. However, focusing on usage efficiency shifts environmental impacts across its life cycle, leading to excessive resource extraction and waste accumulation. Integrating environmental impact indicators in PE development is crucial for informed design decisions. Nevertheless, the current literature lacks the provision of adequate understanding of the PE product development process for successful ecodesign in PE industry. To effectively tackle the industrial integration aspect of ecodesign that enable functional and system innovation, this study employs empirical research, combining literature analysis with in-depth interviews with PE designers. Requirements for an ecodesign support to integrate ecodesign practices into the Product Development Process (PDP) of PCB-based Power Electronic Components (PECs) is proposed in this paper based on the interview results. These specifications are delineating the necessary working and decision- making steps. Subsequently, a parameterized Functional Block-based Life Cycle Analysis (FB-LCA) model is proposed under the requirement. A five-step methodology is proposed to operationalise the implementation of the FB-LCA model, aiming to supporting the definition of functional structure, configuration of technical solutions and choice of hardware components by considering environmental impacts generated all along life cycle, from manufacturing, transport, use, circularity scenario, end-of-life .The case study of a PCB-based boost converter design is conducted in collaboration with a PE engineer to test the practical implementation of FB-LCA model. [ABSTRACT FROM AUTHOR]

The challenge of swift and reliable earthquake location prediction within earthquake early warning (EEW) systems underscore the need for innovative solutions. Existing methods provide predictions, yet there is a clear demand for enhanced accuracy and expediency in the process of resolving. The article intends in prediction of both magnitude of earthquakes and the affected areas in a specific region, focusing on California, United States, by leveraging historical data using neural networks (NNs). Neural networks outperform other algorithms such as XGBoost, linear regression, random forest, gradient boosting and support vector machine (SVM), in terms of high R² score and low score of MAE and also mean squared error (MSE). The derived results of R² score, MSE and MAE are 0.1607, 0.1615 and 0.2951, respectively. It seamlessly integrates geospatial visualization through Folium and GeoPandas. These tools enhance the predictive model's capabilities by generating dynamic maps enriched with markers, each representing the anticipated impact of earthquakes. The user interface facilitates interactive input, enabling users to input earthquake parameters for real-time predictions. The resultant map not only showcases the predicted impact zone but also provides valuable insights into the severity of seismic events. It stands as a testament to the synergy between machine learning and geospatial visualization, offering a holistic solution for earthquake prediction and geographical representation. [ABSTRACT FROM AUTHOR]

The construction industry faces challenges in evaluating success due to inconsistent methods and a lack of uniformity. Traditional evaluation methods often result in subjective and biased results. Professionals, stakeholders, and researchers disagree on assessment techniques. The paper aims to identify stakeholder-responsive evaluation criteria, establish an evaluation criteria model, develop a quantitative evaluation algorithm, and provide an evaluation process framework. This method and framework fill traditional evaluation gaps, reduce subjectivity and bias, enhance accuracy, simplify evaluation, and are suitable for project evaluation. Data was gathered from experts and project stakeholders through focus group discussions, interviews, archive documents, and site observations. First, identify criteria and subcriteria and develop a criteria-relation model that achieves fitness indices and passes validity and reliability tests. Next, quantitative evaluation weighted coefficients were determined, and an algorithm was developed. A quantitative evaluation of a case study revealed that project seven has very high success; projects three, six, eight, and nine have high success; project two has medium success; projects one, four, and five have low success; and there is no project with a very low success. Projects achieved average success rates of 86.42, 79.6, 66.5, 71.17, 83.63, 81.27, and 89.14% in quality, cost, time, safety, impact, satisfaction, and lesson learning, respectively. This study is novel and original due to its criteria structural equation model, quantitative evaluation algorithm with inclusive criteria index, and unique evaluation processes framework. This enhances evaluation science, providing new insights for stakeholders, professionals, academics, and policymakers, and enhancing stakeholder communication in future project success evaluations. [ABSTRACT FROM AUTHOR]

This paper aims to assess the level of awareness of safety precautions in the use of extension cords in Ho Municipality in Ghana. The relevance of this study is to provide an understanding of the awareness level of safety measures likely to lead to a significant reduction in incidents of domestic fire outbreaks when using an extension cord. A cross-sectional research was carried out in the Ho Municipality between February and April 2022. Six hundred and one (601) individuals were chosen from houses using a random selection method. A standardised questionnaire was used to gather data, and then entered and analysed using the Statistical Package for Social Science (SPSS) V.16. Descriptive statistics, Binary logistic regression analysis with a 0.05 p-value and the adjusted odds ratio (AOR) with a 95% confidence interval (CI), Relative Importance Index (RII), and the Sample T-test were used to examine the significance of connections. Among the participants, there is a low level of awareness of extension cord ratings and standard labels from autonomous testing facilities. The participants' knowledge of awareness was significantly related to gender; [0.722 (95% (CI): 1.476 - 2.869), p = 0.001 < (0.05)]. Again, most participants overload the extension cord during usage and practice poor safety measures that could result in a fire outbreak. The study suggests that users should purchase extension cords that have been endorsed by an autonomous testing laboratory and fully be educated on the safety procedures that will aid in safeguarding lives and property by both government and non-governmental agencies. [ABSTRACT FROM AUTHOR]

The present paper explains the performance of a production process of finite capacity for two classes of customers who may exhibit impatience. The arrivals can be found in terms of batches and will be picked for service in FIFO mode. The production requests can come in two ways (i) on immediate demand, (ii) for future stock purposes. Taking this point, we have taken two-class customers with different arrival rates. Also assumed state-dependent service with which process has to be triggered to avoid congestion. A computer programme has been executed for the R-K method to solve the transient equations for transient probabilities with the given input values of arrival rates of two-class customer orders, service rates and system capacity. System performance indices have been computed and shown numerical illustrations to assess the influence input parameters on performance indices. [ABSTRACT FROM AUTHOR]

This literature review emphasizes the importance of stakeholder-responsive success criteria and appropriate evaluation techniques for the construction industry. Traditional evaluation methods can lead to subjective and biased results. Disagreements between industry professionals and researchers on criteria and assessment techniques contribute to ineffective project evaluation. The review aims to identify the most important holistic and stakeholder-responsive success criteria and methods from the literature. The review utilized a systematic approach, downloading 102 references from various databases, including published journal articles, conference proceedings, books, and book sections, using search engines and keywords. The review process involved refining and limiting the number of references using eligibility criteria, with 55 references from 2001 to 2024 being used for review. The review flow chart outlines each step. The findings indicate five main evaluation criteria, such as efficiency, effectiveness, sustainability, environmental impact, and satisfaction. The five evaluation criteria include quality, cost, time, health and safety, environmental impact, stakeholder satisfaction, and lesson learning and development. Furthermore, the quantitative success evaluation method is the best technique due to its reduced subjectivity. The review provides valuable knowledge among industry stakeholders, professionals, academics, and policymakers on the most suitable project success evaluation criteria and methods to evaluate future construction projects. [ABSTRACT FROM AUTHOR]

Many optimization problems in engineering and industrial design applications can be formulated as optimization problems with highly nonlinear objectives, subject to multiple complex constraints. Solving such optimization problems requires sophisticated algorithms and optimization techniques. A major trend in recent years is the use of nature-inspired metaheustic algorithms (NIMA). Despite the popularity of nature-inspired metaheuristic algorithms, there are still some challenging issues and open problems to be resolved. Two main issues related to current NIMAs are: there are over 540 algorithms in the literature, and there is no unified framework to understand the search mechanisms of different algorithms. Therefore, this paper attempts to analyse some similarities and differences among different algorithms and then presents a generalized evolutionary metaheuristic (GEM) in an attempt to unify some of the existing algorithms. After a brief discussion of some insights into nature-inspired algorithms and some open problems, we propose a generalized evolutionary metaheuristic algorithm to unify more than 20 different algorithms so as to understand their main steps and search mechanisms. We then test the unified GEM using 15 test benchmarks to validate its performance. Finally, further research topics are briefly discussed. [ABSTRACT FROM AUTHOR]

Dc microgrids (MG) have drawn more attention due to the demand for renewable energy sources, energy storage devices in distributed generation, and the separation of DC loads requiring more power converters. This system needed protection DC circuit breakers (DCCB) that could quickly isolate the faults in the system. These devices must be as small and light as possible but should only produce low power loss during the ON state. The impedance source DC circuit breaker was introduced as an improved structure (SSCB) which provided automatic turns off without needing external command due to its natural commutation operation principle. In addition, it had many advantages such as faster response, simpler control design, restricted fault current magnitude, which makes the system more fault-resilient, the fault current will not affect the source or the SCR, coordination of cascaded breakers is automatic, and convenience for protection with power converters. This paper presents different impedance source DC circuit breakers such as ZCB, CCB, TCB, and YCB. It will show their benefits and drawbacks, which could be used as a helping guide while choosing which type of impedance source DC circuit breakers is suitable for a specific application. [ABSTRACT FROM AUTHOR]

This paper introduces a compact, circularly polarized spidron-fractal slot antenna with a rectangular island. The reflection-coefficient |S11| of the proposed antenna covers the band from 7 GHz to 10 GHz. The proposed antenna is circularly polarized with an axial-ratio (AR) bandwidth that extends from 7 GHz to 10 GHz. It offers simultaneous dual circular polarization (RHCP and LHCP). The gain of the proposed antenna varies between 4 dBi and 6.9 dBi. The simulated efficiency reaches 97%. The overall dimensions of the antenna are 19.7 x 23 x 0.508 mm³ (0.55λ0 x 0.65λ0 x 0.014λ0), making it suitable for CubeSats with limited surface area. The proposed antenna can be employed for both the X-band satellite downlink (from 7.25 GHz to 7.75 GHz) and uplink (from 7.9 GHz to 8.4 GHz) frequency bands. Additionally, the antenna can be utilized in small satellite Synthetic-Aperture-Radar (SAR) systems operating from 9 GHz to 10 GHz, military applications, and RFID tag tracking-equipment. A prototype of the proposed antenna has been fabricated and then measured using Vector-Network-Analyzer (VNA) and inside an Anechoic chamber. The measurement results of the proposed antenna are in excellent match with the simulated results. [ABSTRACT FROM AUTHOR]

Ride-share platforms are contemporary businesses that match passengers with drivers, unlike taxis that can be hailed from the street. In the literature, the problem of optimizing the operations of such companies is mostly considered in static settings. We use in this paper a dynamic model and propose differential equations to model the evolution of the system. The objective is to maximize the profit during the planning horizon. Using optimal control theory, we determine the optimal rate of change in the ride price rate. An illustrative example along with sensitivity analyses shows the effect of the system parameters on the optimal solution obtained. [ABSTRACT FROM AUTHOR]

Since its inception in the early 1970s by Daniel Gurney, the Gurney flaps have proven to be an effective means of enhancing the aerodynamic performance of an airfoil. Current applications of Gurney flaps include wind turbine blades, race car spoilers, helicopter rotors, and certain high-lift devices. This study compares the influence of Gurney flaps on flow characteristics and the effects of design parameters of the flap, namely the length and position of the flap on a NACA 23,112 airfoil. A review of the studies conducted so far has shown that studies have been carried out on a select few airfoils only and mainly studied the effects of variation of only one of the characteristics, like length, position, or angle. This paper has been crried out to find the optimum balance between these design parameters. Additionally, this paper aims to investigate the accuracy and feasibility of numerical investigation methods to estimate the aerodynamic characteristics of airfoils and wings compared to conventional techniques like wind tunnel testing. This cost-effective computation method is less susceptible to external factors like weather changes. The CFD process also allows testing at conditions that might otherwise be impractical to test in wind tunnels. The workflow comprised a review of literature, validation of solver settings, preparation and testing of the model, extraction of results and analysis of results. Autodesk Fusion360 and Ansys Workbench 22R1 were used to make and test the models. The airfoil designs were tested at Re = 2 × 106, at angles of attack varying from 0° to 15°. The GF height ranged from 1% to 3% chord and placed at 95% to 100% chord. A reliable methodology has been arrived at and validated by implementing the best practices prescribed for CFD. The k-ω SST turbulence model, along with second-order spatial discretization, was used. Coefficients of lift and drag were considered the study parameters. Gurney flaps were found to increase the performance of the airfoil, and better results were obtained at higher angles of attack. The modified designs noted the separation point further downstream than the baseline model. Overall, the presence of Gurney flaps proved beneficial over the baseline model. [ABSTRACT FROM AUTHOR]

This paper proposes a mathematical model approach to predict the Ultrasonic Pulse Velocity (UPV) of concrete. This paper presents the formulation, calibration, evaluation, and validation of the proposed UPV model. An experimental program was developed to calibrate and evaluate the proposed model. Furthermore, the model was validated using a separate group of measurements in the experimental program, to test its accuracy and generalization capability. Analysis of the results reveals that the proposed model provides a good fit to the experimental data and does not contain outliers or discerning pattern. The corresponding standard error and determination coefficient are 45 m/s and 0.92, respectively. Model validation demonstrates high predictability and generalization capability. The corresponding standard error and determination coefficient are 74 m/s and 0.91, respectively. [ABSTRACT FROM AUTHOR]

An infant in the first 28 days following birth is referred to as a newborn baby. In Ethiopia, neonatal mortality is a serious problem that accounts for the lion's share of under-five mortality. Diagnosis and treatment of infant disease need specialized medical resources with plenty of expert knowledge and experience. Globally and particularly in low-income countries, there is a lack of such professional which make the diagnosis and treatment more difficult. The goal of this paper is to design a knowledge-based system for the diagnosis and treatment recommendation of neonatal diseases by collaborating with the knowledge obtained from machine learning and health experts. Design science research approach has been employed as the overall research design, and the hybrid data mining process model is used to extract knowledge from the collected clinical dataset. To this end, three classification algorithms in WEKA tools, namely, J48, PART, and JRip, were considered. Then, a partial decision tree (PART) algorithm under 10-fold cross-validation achieved the highest performance result with an accuracy of 98.06% and the researchers decided to use the generated rules for the development of a knowledge-based system. Evaluation results show that the developed prototype registers 90.9% accuracy in system performance testing and 89.2% in user acceptance testing. In conclusion, the system is used as an assistant tool for healthcare experts and could be effective if it could be implemented. [ABSTRACT FROM AUTHOR]

The response spectra defined in the appropriate Euro standards from the first and second generation (EN 1998-1 and EN 1998-1-1), which determine the seismic load for common buildings, are critically presented first. To avoid a reduction in earthquake loading on structures using response spectra, only a few points of the response spectra in the second generation of EN 1998-1-1 are determined by applying the probabilistic concept of seismic hazard assessment. The comparison of current response spectra in EN 1998-1 is made with the uniform hazard spectra (UHS). The comment and application of the second generation of EN 1998-1-1 is a novelty that is introduced in this paper. On the basis of response spectra presented here according to EN 1998-1 and EN 1998-1-1 and other spectra obtained from real and artificial records, comparative different methods of analysis on one regular simple eight-story reinforced concrete frame structure are illustrated to find out how the kind of spectra and used methods of analysis influence the story displacements and story drifts of one simple regular structure. So, at the same time, the reader will be informed not only about novelties in the second generation of EN 1998-1-1 as far as response spectra are concerned but also understand the implication of various response spectra on the methods of analysis of building structures. [ABSTRACT FROM AUTHOR]

In the last years, particularly after Covid-19, Health care waste (HCW) has increased significantly due to the increasing population and number of healthcare organizations. HCW produces a significant risk of infectious contamination and injury. Accordingly, healthcare waste management plays a vital role in creating waste management strategies, and policies and implementing waste management plans. To build robust healthcare management systems, the risk assessment process is a key step. This paper assesses the top hazards of healthcare waste at Sultan Qaboos University Hospital (SQUH) in Oman using the Exponential Weighted Geometric Mean-Failure Mode and Effect Analysis (EWGM-FMEA). Fifteen healthcare waste hazards were selected to apply the tool. These hazards are ranked to prioritize the top hazards wastes. This assessment helps in identifying the most crucial hazards, whiche the policymakers should pay attention thus, the main countermeasures could be conducted. These hazards were proposed based on the conducted survey questionnaire and interviews accordingly, and analyses of the data have been carried out. The applied tool examined the importance of quantifying healthcare waste to apply the appropriate corrective actions which can be applied to mitigate the harm and the negative effects of healthcare waste. The results of the assessment tool will help policymakers in developing clear plans for management, disposal of wastes, and segregation. Furthermore, prioritizing healthcare waste explored the importance of integrating tthe raining plans of workers with the healthcare waste management policy. Although the prospective managerial and policy implications of this research, some limitations could be studied by future researchers. Firstly, the sample covered one hospital that may be representative of only one hospital in Oman which constrains the generalization of results. Secondly, the number of identified waste hazards is fifteen so, increased the number of hazards may help policymakers in building a more effective healthcare waste management plan which will reflect in improving the healthcare management system in the organization, mitigating the harmful effects on human health and the negative effects on the environment. [ABSTRACT FROM AUTHOR]

Electrocardiogram (ECG) is the most common and simple technique to diagnose cardiovascular diseases. Cardiovascular diseases can be detected effectively if ECG signals are monitored for a long time, producing innovative clinical outcomes to diagnose and treat cardiovascular diseases. Due to skin irritation and degradation of signal quality with time, traditional wet electrodes are unsuitable for long-term ECG monitoring. Researchers are trying to fabricate flexible, wearable, highly conductive and lightweight ECG sensors, which can be applied for long-term monitoring of ECG signals and the detection of several cardiovascular diseases. Graphene is used for fabricating dry ECG electrodes because it exhibits robust mechanical flexibility, good environmental stability and excellent carrier mobility. This review paper presents the progress of various fabrication methods to make graphene-based ECG electrodes and provides the researcher's clarification on recent advancements and direction in this domain. This paper focuses on a systematic review and comparative study of various fabrication methods of graphene-based ECG electrodes, such as screen printing, dip coating, drop casting, wet transfer, electrospinning, wet transfer and dry patterning, spin coating, spray coating, inkjet printing etc. [ABSTRACT FROM AUTHOR]

This research aims to develop mitigation techniques for the implications that affect the city planning sectors in Egypt during COVID-19, which will guide urban planners and policymakers to enhance Egyptian citizen life during pandemics. A statistical thematic methodology was adopted by the research. The research method divided into three phases. The first phase considers the attitude of Egyptian citizens toward the global pandemic through conducting surveys. These surveys discuss the global effects of the pandemic and if these effects are felt in the Egyptian context or not. The second phase targets the citizen that disagree with the global effects as a result of the phase one survey through structured interviews. These interviews concluded the reasons behind the disagreement of the surveys in phase one as well as the effects that they personally suffer from during the pandemic. The third phase targets the policymakers and planners inside Egypt and their perspectives on the suitable mitigation techniques that can be implemented in the Egyptian context. This will finally lead to suggesting a set of mitigation techniques suitable for Egyptian cities. The research paper identified through a review of literature the mostly affected city planning sectors during COVID-19 which were 6 sectors. In addition, 25 global mitigation measures were identified through the literature. Results of the Surveys and structured interviews confirmed that the most affected sectors are transport & land use, housing, and ICT respectively. Findings of data analysis showed that 10 extra mitigation measures were encountered to better enhance the Egyptian cities. These findings help planners and policy makers to plan cities that can cope with future pandemics. This research presents mitigation techniques for the implications that affect the city planning sectors in Egypt during COVID-19. It was based on research from case studies, a literature review, and a survey questionnaire. The mitigation techniques developed in a practical procedure where the goals of the research; required activities; techniques, and tools; elaborated the citizen needs and outputs. The mitigation techniques was authenticated by 24 of the Egyptian professionals' planners and policy makers to ensure its viability and practicability for implementation. The research categorized and examined the global effects that changed the quality of life during pandemics. Moreover, real life case study authenticated the global effects and explored the most successful mitigation countermeasures that suites the Egyptian context. The study focused on a subject that has recently attracted interest on a global scale. In addition, this paper developed 10 extra mitigation measures to better enhance the Egyptian cities and other developing countries of similar context. It represents a novel contribution that planners and policy makers can employ in similar context to the Egyptian cities. [ABSTRACT FROM AUTHOR]

The aim of this paper is to identify and select an appropriate business model for the utilization of maize shelling technologies in small-scale farming practices. Though a very old practice, agriculture is still the central activity of the entire globe due the reason that it directly or indirectly affects the livelihood of the inhabitants. West Gojjam zone of the Amhara National Regional State (ANRS) in Ethiopia is among the known maize producing zones in Country for both consumption and as a cash crop. But, the problem is the high wastage of production due to post-harvest losses (PHL) due to mechanical shelling practices. Aiming to solve this PHL of maize production, at the shelling stage, assessments and discussion with the maize growing farmers and experts concerned were conducted. This paper tries to present an appropriate business model for enabling local small holder farmers get access to different maize shelling technologies. The research follows a survey-type design which provides both a quantitative and a qualitative description of operational and business variables, attitudes, or opinions of a population in the target area, and overall insight of the technology market. The current data shows that rental maize shelling service is feasible for the fragmented maize production of the West Gojjam zone, in the Amhara National Regional State of Ethiopia. Hence, a generic conceptual model has been developed based on the feedbacks of local smallholder farmers, agricultural agents, service providers and suppliers. This model shows how to select and make available appropriate maize shelling technologies that will fit the actual demand at household level. It also shows a rent-to-own approach of maize shelling service that will help the unemployed youth in the localities. [ABSTRACT FROM AUTHOR]

Although collaborative decision-making with multiple stakeholders in supply chain has become an important research issue in recent years, current research on the mechanism/process, methods, and performance assessment of collaborative decision-making still lags behind the practical needs in supply chain management. This paper reviews the existing literature in the past decade on collaborative supply chain from the perspective of decision-making in four stages with a causal framework. This paper reveals a general retrospect of the main subjects developed and investigated with related applications of cases, which includes both theoretical assumptions and practical data. The findings indicate that most articles in this field are based on a direct relationship between collaboration and performance improvement but lack of a mechanism between them. Additionally, dynamic collaboration with members in the whole supply chain both horizontally and vertically has not been conducted by previous studies. This paper provides a new conceptual framework and future research directions for further study in supply chain collaboration. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to provide a validation framework to guide future validation practitioners towards completing utility validation projects in small and medium enterprise successfully and in shorter duration compared to current practice. Design/methodology/approach: Literature review was carried out on various existing validation frameworks to analyse the positive and negative elements of the frameworks. The identified positive key elements from this analysis were incorporated to develop a comprehensive validation framework that can be used by future validation practitioners to validate utility system in manufacturing companies. Findings: The case study results proved the capability and effectiveness of the new framework as the validation of the reverse osmosis water system was completed successfully with proper documentation and within shorter period compared to previous validation projects in the case study company. Research limitations/implications: The proposed validation framework is well suited for use in small and medium enterprise companies. Further studies should be carried out to ascertain the effect of the framework. Originality/value: This paper provides a comprehensive validation framework that can guide future validation practitioners towards completing validation projects in small and medium enterprise companies successfully and in shorter period. [ABSTRACT FROM AUTHOR]

Cyber-Physical Systems (CPS) is a new generation of digital technology that is concerned with the integration and inter-dependencies of the cyber and physical world alongside computational elements. As a new and leading technology, its applications are seen in different projects involving energy and this has however generated lots of interest from the industry, researchers in academia and the government. This paper presents an extensive overview and modernistic research on the applications relating to energy CPS and the security issues and challenges revolving around this research path. In order to achieve this, a systematic literature review was carried out which enabled the analysing and classifying of different applications and security issues described in selected publications. Furthermore, the systematic review permitted the discourse stringing these research areas as well as providing future lines of research. Also, results from the review show the paths where there are increasing research focus and expected research trend in the future years to come. These results will not only be useful in serving as a guide to researchers but will also create new research paths to more experienced researchers to actively follow. [ABSTRACT FROM AUTHOR]

Software testing is an important and expensive phase of development. Whenever changes are made in the code, it becomes a time-consuming process to execute all the test cases in regression testing. Therefore, the testing process needs some test case reduction techniques and prioritization techniques to improve the regression testing process. Test case prioritization aims at ordering test cases to increase the fault detection capability. There are many existing techniques for test case reduction as well as for prioritization that use the coverage information which degrades the number of ties uncounted during the prioritization. This paper will take its focus on the multi-level random walk algorithm, which has been used for test case reduction. In this process, test case selection for further reduction is done randomly on every iteration that degrades the performance of a testing process in terms of coverage and will also generate a situation for random test case tie. To overcome this situation of random test case selection and handling test case tie, a solution is being proposed in this paper, which includes a combination of optimized multi-level random walk and genetic algorithm. In regression testing, another important aspect is the test case prioritization that finds fault as early as possible if test cases are prioritized properly. So, this paper introduces new prioritization techniques, which are based on fault prediction in acceptance testing. The performance of the proposed approach in terms of fault detection is evaluated with the help of many programs. [ABSTRACT FROM AUTHOR]

This paper focused on applying social network analysis techniques to co-authorship network in order to discover the influencers in Civil engineering research field in Nigeria. It further applies the Latent Dirichlet allocation (LDA) algorithm to uncover the major research topics in this field. The research used 663 publications downloaded from the Scopus database, with the year of publication ranging from 1968 to 2018, using Nigeria as the case study, Civil and Structural engineering as the field of research. The study was carried out using the centrality measures in network analysis such as degree centrality, closeness centrality, and betweenness centrality for co-authorship network analysis of authors and text mining using the LDA algorithm to discover the research focus of the authors. Also, the relationship between the centrality measures and authors' performance, measured in terms of citation was investigated using regression analysis. The results showed that there was a significantly positive relationship with betweenness centrality and closeness centrality for performance, but a negative relationship with degree centrality. Also the topics discovered using the LDA algorithm helped to reveal the major focus of Civil Engineering research in Nigeria. In conclusion, it is recommended that based on the co-authorship network of civil engineering research in Nigeria, which was found to be a healthy small-world community, the environment discovered can be improved upon to support collaboration and sharing of ideas between researchers in the civil engineering field. [ABSTRACT FROM AUTHOR]

Vehicle Routing Problem (VRP) is the problem for finding optimal routes in the distribution system, and this problem needs attention because it can improve distribution performance. One of the problems in VRP is the Vehicle Routing Problem for Perishable Goods (VRPfPG). This issue addresses VRP for products that are rapidly losing quality and perishable. This paper attempts to review the Vehicle Routing Problem for Perishable Goods (VRPfPG). A systematic review has been carried out on fifty-nine (59) published papers from 2001 to March 2020. The optimization methods in this review were classified into single and multi-objective problems. In addition, the review was also conducted based on the objective function. The results show the metaheuristic algorithm to be a popular optimization method for solving single and multi-objective problems. Further, the results also show that minimizing the total cost distribution to be the objective function that was often used by researchers. Finally, future studies are suggested to explore a more comprehensive investigation in the VRPfPG. [ABSTRACT FROM AUTHOR]

With increasing population and motorization, Kenya as well as other African countries are faced with a tragic road traffic accidents (RTA). This paper looks at 5-year (2015–2020) data downloaded from National Transport and Safety Authority (NTSA) website, to identify trends and review progress of the traffic accidents in the country. The objective is to assess the prevalence of accidents within affected groups and location to identify trends and generalized causative agency from the reported data. From literature review, research activity focused on RTA in the country is minimal compared to the social significance accidents poses. The data were extracted and classified using Latent Dirichlet Allocation, a machine learning algorithm modelled in Matlab to group reported accident briefs into general categories/topic which are closely related. Four categories were identified as leading causes of fatality in the country: Knocking down victims, hit-and-run, losing control and head on collision. The identified causes point to preventable driver's errors which agrees with other researchers. From trend analysis, fatalities and injuries have increased by 26% and 46.5%, respectively since January 2015 to January 2020. This paper found that injuries in vulnerable road users: pedestrians, pillion passengers and motorcyclist, has seen a foldfold increment compared to 2015 data. From the discussion, urgent fine-tuning of policing to protect vulnerable road user as well as curb the overly decried driver behavior is needed. The paper recommends fine-tuning of data collection, capturing details of accident that will be useful in modeling and data analysis for future planning. [ABSTRACT FROM AUTHOR]

Standards and best practices for software quality guide on handling each quality characteristic individually, but not when two or more characteristics come into conflict such as security and usability. The objectives of this paper are twofold: (a) to argue on the importance of handling the conflicts between quality characteristics in general; (b) to formulate a framework for conflict examination of the software quality characteristics, we do so while considering the specific case of security and usability. In line with the objectives, a framework called Pattern-oriented Design Framework (PoDF) was formulated. The PoDF provides a mechanism for identification of the conflicts, modeling the conflicts to illuminate the reason for their occurrence, and eliciting the suitable trade-offs between the conflicting characteristics. The suitable trade-offs are thus documented as design patterns. The patterns can assist developers and designers in handling the conflicts in other but similar context of use. To validate and instantiate the PoDF, two studies were conducted. Usable security patterns discovered as a result of the studies are also presented in the paper. [ABSTRACT FROM AUTHOR]

As our understanding and modeling capabilities evolve, an ever-increasing complexity of models representing the behaviour of geologic medium are analyzed. One way to evaluate these substantial problems is to optimize the underlying discretization of the governing differential equations by concentrating finite elements where solution accuracy counts the most. This paper develops and evaluates the performance of a priori local p-refinement method for finite element mesh improvement for stress analysis of underground excavations. This type of refinement entails a mesh with higher-order elements near the region of interest and lower-order elements elsewhere. The focus of the paper is the automated insertion of transitional elements at the interface of the two regions. The method relies on transitional finite elements in order to connect a mesh of quadratic interpolation order elements with a mesh of linear interpolation order elements. Four types of transitional elements were considered (4-node and 5-node triangles, 5-node and 7-node quadrilaterals). These were incorporated into a finite element code, and their performance was tested using representative problems such as a pressurized cavity or tunnelling through rock. For these problems the global stiffness matrix size was reduced on average by 85% and by 81% for the models using triangles and quadrilaterals, respectively, as a result, the calculation times were considerably shortened as well. While the average percentage of error with respect to the models without improvement, measured at critical points, was 0.04% and 0.02% in the case of triangular and quadrilateral elements, respectively. [ABSTRACT FROM AUTHOR]

The rising use of electric mobility has weakened the relationship between wholesale energy prices and price-responsive demand such as charging Electric vehicles (EV). This adversely affects network flows. The situation can further worsen, causing congestion in the distribution network and a rise in energy prices. In this paper, an attempt is made to resolve this issue through Distributed generators (DGs) placed in a grid-connected microgrid. The authors propose a methodology based on "Distribution Locational Marginal pricing (DLMP)" and the use of "Hybrid optimal Firefly Particle Swarm Optimization" with "TOPSIS" (HFPSO-TOPSIS) approach for optimal DG sizing in this methodology. The methodology consists of two stages. The first stage is locating DGs on the bus, and the second stage is sizing DGs and their participation in providing ancillary service of congestion management through a grid-connected microgrid. The method is tested on a "modified IEEE 33 bus radial active distribution system". Two different system conditions in which congestion can occur are analyzed and congestion is successfully removed by this proposed method. Power Loss reduction of more than 75% is achieved in each case after the implementation of the proposed methodology. Minimization of voltage deviation and maximization of voltage stability is achieved. The generation cost is minimized by almost 70%. The results obtained show better performance of HFPSO-TOPSIS as compared with other existing techniques. The results obtained exhibit that the methodology is generic and can be implemented for any congestion condition and can successfully remove congestion with improvement in system performance bringing social welfare. [ABSTRACT FROM AUTHOR]

Research and development concerning the electrification of the easily affordable two-wheel vehicle segments operating at low power capacity are significant for a highly populated country like India to attain sustainable transportation. Hence, a novel approach is proposed in this paper focussing on the investigation of bi-directional quasi-Z source inverter (BD-qZSI) using a modified shoot through hysteresis current control (STHCC) loop for brushless direct current (BLDC)-motor-based low power electric vehicle (EV) applications to address this issue. The practical vehicle dynamics, without the computational burden of the complete drive cycle. are suitably established in this research work by achieving different speed and torque conditions with the inclusion of five different modes of operations consisting of three motoring modes (eco, coast, and wrap) and two regenerative braking modes (soft regen and hard regen). The combination of the closed loop speed control of BLDC motor involving PI control in cascade with modified STHCC for the operation of BD-qZSI is analysed in MATLAB/Simulink environement. The performance of the bidirectional power transfer in a single stage including regenerative braking is examined. The results confirm the validity of the proposed system for low-power EV applications. The modified STHCC is easy to implement with quick response compared to other control methods. The performance of single stage BD-qZSI is superior to the conventional two stage converter topologies and to that of Z source inverters. The commutation ripple observed in the torque profile is insignificant in low-power BLDC drive applications. The overall drivetrain efficiency of 84.82% is achieved at rated load condition. [ABSTRACT FROM AUTHOR]

In this paper, we propose a tractable Kumaraswamy Bell exponential (KwBE) distribution as a submodel of the Kumaraswamy Bell-G family of distributions. Several well-established properties are obtained for the KwBE distribution, such as the linear functional representation, $r$ r th moment, incomplete moment, moment generating function using Wright generalized hyper-geometric function, conditional moment and Réyni entropy. Based on the KwBE model, a group acceptance sampling plan (GASP) for the truncated life test is presented using median life as a quality index. Moreover, the essential design parameters are derived by defining the consumer risk and the test termination duration. The comparative study of GASP with ordinary sampling plan (OSP) is performed. A simulation study is performed to highlight the behavior of the estimates. On the inferential side, the associated parameters are estimated using a well-established maximum likelihood estimation method. The detailed model's comparison analysis, graphical as well as numerical evidence to real-data applications, supports the theoretical work. [ABSTRACT FROM AUTHOR]

Elastomers are the class of materials that are widely used in a variety of industrial, commercial, and consumer applications due to their unique mechanical properties, including high elasticity, high flexibility, and high resilience. However, there are many challenges in machining of elastomers such as poor surface finish, build up of heat, degradation of elastomers, etc. To overcome these challenges, cryogenic cooling assistance has been introduced as a means of improving the machinability of elastomers. This paper presents a soft computing approach for optimizing the surface roughness and cutting force during turning of elastomers under different lubrication conditions. Three types of elastomers, namely Nitrile Rubber (NBR), Polyurethane Rubber (PU), and Neoprene Rubber (CR), are studied, and a cryogenic fluid delivery system is employed to improve the machining process. Taguchi's L27 array is used to vary the input parameters, and a Back-Propagation Artificial Neural Network (BPANN) model is developed to predict the cutting force and surface roughness. The cutting force and surface roughness are analyzed under different cooling conditions, cutting speeds, feeds, and depths of cut for various elastomers. The results show that changes in cutting conditions significantly affect the cutting force and that the type of lubrication used affects the cutting force by altering the material's physical properties. Cutting force is significantly influenced by cutting conditions, and NBR requires the highest cutting force compared to PU and CR. Further, at a cutting speed of 55 m/min, a feed of 0.11 mm/rev, and a depth of cut of 0.25 mm, the cutting force for NBR (85.1 N), while for PU (75.1 N) and CR (80.3 N), respectively. Finally, with LN2 lubrication conditions, the Cutting Force decreased by 45% and Surface Roughness decreased by 16.9%. This study provides insights into the factors affecting the elastomer machining process, which can be useful for optimizing the machining process parameters and improving machining efficiency. [ABSTRACT FROM AUTHOR]

This paper discusses about process input optimization to obtain desired output characteristics such as Surface Roughness (microns), Thrust Force (N) and Torque (N-m) during drilling of AISI 316 L Stainless Steel under minimum quantity formulated neem oil lubrication condition based on Taguchi Design of Experiments (TDOE), Response Surface Methodology (RSM) and Desirability Functional Analysis (DFA) by varying flow rate (ml.min−1), stand-off distance (mm), flow pressure (Bar) and nozzle exit diameter (mm). Formulated Neem Oil possesses natural lubricating properties that reduce friction and heat generation, thus prolonging the tool life and improving surface finish. Additionally, it is biodegradable and environmentally friendly, making it a sustainable choice for machining operations. From the experimental investigation using TDOE, it was observed that there was considerable improvement in thrust force, surface roughness and torque with modified neem oil as a lubricant. Further, plot for main effects and Analysis of Variance (ANOVA) are successfully used to identify the optimum process input parameters and their percentage of contribution (P%) on output parameters. RSM is successfully used to generate a second order mathematical model which can be effectively used to analyze the process parameters. Further, from Desirability Functional Analysis (DFA), minimum surface roughness (0.34 microns), thrust force (1292.37 N) and torque (14.71 N-m) value were predicted. Finally, Back Propagation Artificial Neural Network (BPANN) analysis has been adopted to predict the surface roughness, thrust force and torque with a minimal error of 1.46%, 0.017% & 0.17%, respectively. The adoption of Neem oil formulations has been successful in improving machining characteristics. Its versatility across an array of machining processes and materials, in tandem with the global momentum toward greener manufacturing paradigms, positions it as a promising lubricant for various machining practices. [ABSTRACT FROM AUTHOR]