Concept Of Optimization Research Articles

A novel twisted rotor blade suitable for high-speed turbomolecular pumps: Numerical modelling and structural optimisation

To meet the urgent need for a new design concept and solve the inaccuracy of existing performance prediction algorithms for high-speed turbomolecular pumps (TMPs), a new algorithm based on a novel twisted rotor blade is proposed. In this algorithm, the blade angle of the turbine rotor row progressively decreases from the root to the tip of the blade tooth. The feasibility and accuracy of the simulation algorithm were verified through experiments. The dependence of the simulation results on the number of simulated molecules was discussed. Both theoretical analysis and simulations confirmed the necessity of setting a twisted rotor blade in the turbine combined blade row. A comparative analysis on the performance of conventional straight-blade and twisted-blade structures based on the first-four stages of turbine combined blade rows of the F-63/55 TMP was conducted. The results indicated that the maximum pumping speed coefficient and maximum compression ratio of the optimised twisted-blade structure increased by 4.59% and 22.26%, respectively. This novel blade structure overcomes the limitations of the conventional straight-blade structure. Progressively decreasing the rotor blade angle from the root to the tip of the blade tooth is beneficial for improving the performance of TMPs. This study provides a new design concept and performance prediction algorithm for the structural optimisation of high-speed TMPs.

Implementasi Smart Home pada Platform Apple Homekit dan Google Home dengan Raspberry Pi 4B

This research examines the significant impact of technological advances, especially in the Internet of Things (IoT) paradigm, on various aspects of human life strongly manifested during the In-dustrial Revolution Era 4.0. The main focus of this research is on the application of advanced and innovative IoT concepts in the context of smart homes, integrating popular platforms such as Apple HomeKit and Google Home. The temperature sensor (DHT11) and light sensor (LDR) play a key role as important input elements, enabling the optimization of smart home automation functions. Raspberry Pi 4B was chosen as the main platform, the "brain" of the system, providing reliable computing capabilities. Using four-channel relays, this research specifically aims to increase ef-ficiency and integration in controlling devices in the smart home ecosystem. By emphasizing the concept of optimization, this research proposes a smart solution that is expected to not only provide an integrated and efficient experience for smart home users but also unlock the potential for further development of IoT technology. As a result, the implementation of the solutions proposed in this research is expected to create a smart home that is not only technologically smart but also responsive to the needs and preferences of its occupants, paving the way for further in-novation in the development and application of the Internet of Things in various contexts of human life.

An integrated optimal-GICP design for the SPRT control chart with estimated process parameters based on the average number of observations to signal

ABSTRACT As a variable-sample-size control scheme, the sequential probability ratio test (SPRT) chart is favoured due to its sensitivity and high sampling efficiency. It is frequently documented that the SPRT chart inspects only a small number of observations at each sampling stage, making the said chart extremely appealing to quality engineers. In the current literature, most developments of the SPRT chart are established based on the average run length and average time to signal metrics. However, these metrics do not consider sampling efficiency. In this paper, we develop two optimal designs of the SPRT chart, based on (i) the average value of the average number of observations to signal (AANOS) and (ii) the expected value of the AANOS, with consideration of Phase-I process parameter estimation. We develop a model that integrates the concept of optimization and the guaranteed in-control performance (GICP) framework to neutralize the adverse effects of parameter estimation. Results show that the proposed optimal-GICP design preserves satisfactory out-of-control performances for moderate and large mean shifts, while keeping the false alarm rates at reasonably low levels. Finally, we illustrate an example of the SPRT chart with estimated process parameters for monitoring loop height measurements from a wire bonding dataset.

Horan Valley Basin Geomorphological Aspects Assessment by Integrating Hypsometric Analysis with Remotely Sensed Morphometric Characteristics

The extraction, study, and accurate interpretation of the morphology database of a basin are the basic blocks for building a valid geomorphological understanding of this basin. In this work, a new approach is presented which is to use three different GIS based methods to extract databases with specific geographical information and then use the concept of information intersection to make a realistic geomorphological perspective for the study area. In the first method, data integration of remote sensing images from Google Map and SRTM DEM images were used to identify Horan basin borders. In the second method, the principle of data integration was represented by extracting the quantitative values of the morphometric characteristics that were affected by the geomorphological condition of the studied basin, such as the shape factor, circulation factor, and relief ratio, then eliciting an optimal conception of the geomorphological condition of the basin from the meanings and connotations of these combined transactions. The third method used the same principle by taking the optimal inferences from the integration of the interpretation of the values of the Hypsometry integration coefficients for each area in the basin separately with the integration value of the drawing curve for the relative heights of the basin areas with their relative areas. It was found, from the values of the coefficients, that the areas (A, B, C, D, and F) were still in the early stages of youth. Whereas the E region was in the maturity stage and the G region was in the monadnock stage of the geomorphological cycle. As for the integral value of the curve, it indicated 48. 559 % erosion from the surface of the basin only, and that its boundaries were subject to change and widening.

Concept for Optimization and Simulation of renewable energy parks with desalination

This paper is about the concept of the combination of renewable energy parks and water desalination. During the energy production a lot of waste heat is produced which is in the majority of cases unused. The needed (waste) heat for the water desalination unit can be generated with biomass power plants, geo thermal or solar power. So the idea is to use this unused energy to convert saltwater into freshwater. This water can be used to irrigate fields or to produce common products. The advantage is that the produced water and energy can be used independent from each other. The current project is about the optimization between the water desalination unit from the company Terrawater [5] and the produced waste heat from a renewable energy source. At first there will be coded a simulation programme for a physical – mathematical model. Furthermore a control programme will be written which works together with the simulation programme to control the heat flow volume from the power plant or heat generator to the desalination unit to get the best performance and a best amount of freshwater. During the simulation process a lot of different aspects have to be regarded and they have to be included in the control programme.

Design of a PFC rectifier with fast start up response and low input current distortion

For a PFC rectifier, normally designing of the PI compensator is based on the frequency domain model which is derived from the dynamic model of the rectifier, so it cannot guarantee a fast start up response. As the high input current quality and fast start up response are conflicting objectives and with improving one of them, another is degraded, for designing a PI controller which can provide both of them, a Multi-Objective optimization approach can be implemented. In this paper, for the first time, Strength Pareto Evolutionary Algorithm which is based on Pareto Optimality concept is used to gain a fast start up response as well as low input current distortion. In order to validate the proposed PI controller, simulation results are presented.

Dramaturgy Study: The Story of “Si Pandir” on The Effectiveness of Village Fund Management

Purpose: The aim of this study was to uncover the intricacies of village fund budget management by offering a comprehensive portrayal of the behaviors exhibited by the key actors involved in village budget management, both in front and behind the scenes. The aim of this study focuses on the workings of the X village fund budget, highlighting the role of third parties in optimizing the utilization of the X village fund budget.
 
 Method: A qualitative method with a dramaturgical study approach is used in this study to answer the proposed study proposition
 
 Results: The findings indicate that the dynamics observed in the management of the X village fund budget can lead to optimal resource allocation aligned with the village's development objectives and the well-being of its community. This is because the village fund administrators engage in strategic budgetary maneuvers to achieve the utmost efficiency in budget management. The positive impact stemming from the proactive involvement of the village apparatus, colloquially referred to as "Si Pandir," is the promotion of equitable development and the enhancement of village welfare. Through collaboration with relevant government entities, the village apparatus can facilitate the provision of advanced and fair amenities for the village, fostering cooperation that benefits the entire community.
 
 Implications: The results of this study can be used for future research to develop an optimal village fund management concept, not only from the perspective of the related village apparatus but also involving the active participation of the local community.
 
 Novelty: This research elaborates on village fund management with the Pandir legend as the most popular folklore in Java.

Optimizing Rebar Consumption and Cutting Waste in Column Reinforcement: Integrated Mechanical Couplers and a Special-Length-Priority Minimization Algorithm

The construction of reinforced concrete (RC) structures inevitably consumes an excessive number of rebars, leading to significant cutting waste and carbon emissions. Extensive research has been conducted to minimize this issue and its consequences; however, these methods consistently consume a substantial number of rebars. This includes a previous study that utilizes the lap splice position optimization and special-length rebar concept without considering the lapping zone regulation. Moreover, conventional lap splices pose inherent drawbacks that could jeopardize the structural integrity of RC members. In contrast, mechanical couplers eliminate the need for rebar lapping, effectively reducing rebar consumption. This research aims to evaluate the impact of an integrated mechanical coupler and special-length-priority minimization algorithm on the reduction in rebar consumption and cutting waste in RC columns, achieving near-zero cutting waste. To validate the effectiveness of the proposed algorithm, it was applied to the column rebars of an RC building. The results revealed a significant reduction in the ordered rebar consumption by 18.25%, accompanied by substantial reductions in the cutting waste (8.93%), carbon emissions (12.99%), and total costs (9.94%) compared with a previous study. The outcomes provide the industry with insights into further reducing rebar consumption and its related consequences. Applying the proposed algorithm to various construction projects will further amplify the corresponding benefits.

Scenario Development for Evaluating Carbon Capture and Utilization Concepts Using Steel Mill Exhaust Gases with Linear Optimization Models

Utilizing exhaust gases from the steel mill generation to produce chemicals presents a promising avenue for carbon capture and utilization (CCU) concepts. Employing a model-based mathematical approach, specifically mixed-integer linear programming (MILP), enables the identification of optimal production concepts. To evaluate the long-term feasibility under uncertain future conditions, the construction of hypothetical scenarios to depict possible future states is necessary. This study introduces novel and tailored scenarios for a specific CCU concept aimed at producing methanol, ammonia, urea and/or acetic acid from steel mill exhaust gases by the year 2040 to enhance decision-making processes for identifying the optimal concept. These scenarios provide comprehensive insights into potential future conditions, spanning technical, economic and ecological domains. Unlike prior studies that focus on individual key factors, this approach involves analyzing the interactions of 24 identified key factors within the investigated CCU concept. The method yields five distinct scenarios: (1) Business as Usual (BAU), (2) CO2 Reduction and Renewable Energy Target (RE-Boom), (3) Technical Improvement and Market Booming (Market-Boom), (4) Energy and Market Crisis (Crisis) and (5) Hydrogen Booming (H2-Boom). These five scenarios can be directly integrated into MILP models, enhancing the significance of the optimization results for identifying the optimal CCU concept.

Speckle noise reduction in US images: Enhanced filtering with optimal filter coefficients

Ultrasound (US) imaging is one of the prominent techniques, which is widely used for its advantages such as affordability, non-radiation, and non-invasiveness. However, the visual evaluation in this imaging model was hampered by speckle noise. De-specking is therefore seen as the most important task. The preservation of every minute detail in the US images is the main challenge of de-speckling. This paper proposes a new de-speckling model that includes two major phases: the preprocessing stage and the noise reduction phase. Preprocessing is carried out by the anisotropic filtering process. In the noise reduction phase, two levels of decomposition take place. In the first level of decomposition, Discrete Waveform Transform (DWT) is used. The next level of decomposition (2-level) intakes the output from the first level, the sub-bands. The 2-level uses improved Weighted Guided Image Filtering (WGIF), and Gradient Domain Guided Image Filtering (GDGIF) for surpassing the noise. To make the process even more specific on efficient de-speckling, the concept of optimization is incorporated and eventually tunes the filter coefficients by considering Structural Similarity Index (SSIM) and Peak Signal to Noise Ratio (PSNR). This optimal tuning process is carried out by a new Shark Solution Integrated Coot Optimization Algorithm (SSI-COA). Finally, the noise-free image is produced through the inverse DWT. The efficiency of SSI-COA is evaluated over the conventional methods under various measures. The cost values using SSI-COA are less than (around 0.0518) when compared to other models. Moreover, a PSNR of 0.053275 is attained using SSI-COA for best-case scenarios.

An adaptive evolutionary multi-objective clustering based on the data properties of the base partitions

Evolutionary multi-objective clustering (EMOC) is a modern clustering technique in which the general concepts of evolutionary multi-objective optimization are applied to the clustering problem. The design and definition of clustering are difficult problems, and the choice of the objective functions and parameter setting of the algorithms are still challenges. In this paper, we propose the adaptive evolutionary multi-objective clustering approach based on data properties (AEMOC). AEMOC considers a new metric to evaluate the base partitions (candidate solutions used in the initial population) generated by minimum spanning tree clustering. This metric is applied to: (1) determine properties of the data, such as separation and overlap; and (2) define an offline selection of objective functions and parameter settings of the multi-objective algorithm. The information regarding the data properties allows AEMOC to avoid unnecessary data processing in datasets in which the initialization provides optimal solutions and optimization is not required. AEMOC presented promising results considering a diverse set of artificial and real-life datasets, based on two aspects: (1) it succeeded in the determination of the data properties of the base partitions and verifying the potential clustering quality, presenting a correlation of 0.8 with a reference metric, and (2) it provided better clustering results than reference EMOC approaches, achieving a general gain in the clustering performance of 3% in real-life datasets and 7% in artificial datasets.

Reconfiguring the endogenous electric field of a wound through a conductive hydrogel for effective exudate management to enhance skin wound healing.

The ionic environment has a strong influence on the bioelectricity of skin, which is also present in the wound healing process. Inspired by this, we proposed a mechanism for hydrogel-based dressings to respond to endogenous electric fields through exudate absorption and conducted a verification study using a typical hydrogel, namely, polyacrylamide and sodium alginate (PAM-SA) hydrogels, as an example. Theoretical calculations showed that the PAM-SA hydrogels could absorb and orient the various electrolytes of exudate in the hydrogel at the wound site, contributing to the reconstruction of the electric field at the wound site. During the treatment process, this effect significantly accelerated the healing process of the rat epidermis, which exceeded the conventional dressing in terms of healing speed and efficacy, and the wounds on the complete layer of rat skin (wound area: 1.13 cm2) could be rapidly repaired within 10 days. Revealing the electrophysiological behavior of PAM-SA dressings during wound healing can help further improve the design model, the optimization concept, and development paths for the bioelectrical structures of modern dressings and bioelectrical stimulation in wound healing.

Efficient Task Scheduling in Cloud Computing: A Multiobjective Strategy Using Horse Herd–Squirrel Search Algorithm

Cloud computing (CC) is a technology that enables the delivery of IT services outside of the workplace. CC, on the other hand, has had several drawbacks. The task scheduling issue is taken as one of the important difficulties because a solid mapping between available resources and users’ activities is essential to reduce the execution time of users’ jobs (i.e., minimize makespan) and maximize resource utilization. Because the service provider must offer several customers’ benefits at distinct times and from distinct locations, task scheduling is indeed a serious challenge in CC. As a result, in the CC environment, these operations must be scheduled in a more dynamic and timely manner. The objective is to provide an enhanced task scheduling algorithm for allocating the task of the user to different computing resources. The major aim of the research work is to reduce the cost and the execution time as well as to improve the resource utilization of the task scheduling problem using the improved support vector machine (ISVM) and the optimization concept. The novel algorithm used here merges two familiar algorithms as squirrel search algorithm (SSA) and the horse herd optimization algorithm (HOA) leading to a new hybrid metaheuristic algorithm called the horse herd–squirrel search algorithm (HO–SSA). The developed HO–SSA assists in introducing a multiobjective optimization for efficiently handling task scheduling issues in the cloud sector. The proposed HO–SSA method for the task scheduling in CC model in terms of cost is 22.22%, 15.73%, and 38.74% better than SSA, HOA, and TSA, respectively. Similarly, the proposed HO–SSA method for the task scheduling in CC model with respect to energy is 9.68%, 5.35%, and 22.50% superior to SSA, HOA, and TSA, respectively. The proposed method outperformed the existing methods like SSA, HOA, and TSA in terms of cost, energy, degree of imbalance, makespan, speedup, and efficiency.

Enhanced Light‐Gradient Boosting Machine (GBM)‐Based Artificial Intelligence‐Blockchain‐Based Telesurgery in Sixth Generation Communication Using Optimization Concept

Telesurgery and robotic surgery are two real‐time mission‐critical applications where Artificial Intelligence (AI) has a lot of perspective. In this work, a blockchain‐ and AI‐powered telesurgery system for 6 G communication is suggested, which describes a transparent, safe, self‐managing, and trustworthy structure having massive Ultra‐Reliable Low‐Latency Communication (mURLLC). The condition is categorized using AI methods like Enhanced Light GBM, whose criticality scores range from 0 to 1 (after the predicted output, the criticality score of the corresponding disease is divided into high critical, medium critical, and low critical on the basis of the scores that range from 0 to 1). Here, the parameter tuning in light GBM is performed using the Tasmanian Devil Optimization (TDO) with the consideration of attaining the fitness function and thus referred to as Enhanced Light GBM. This proposed novel Enhanced Light GBM predicts the final output based on the criticality scores. In the future, recent deep learning algorithms can be considered for drone‐assisted telesurgery framework together with the consideration of hybrid optimization algorithms. The proposed Enhanced Light GBM‐TDO model for the drone‐oriented telesurgery framework with respect to prediction accuracy is 3.22%, 3.11%, 1.84%, 3.40%, 2.26%, and 1.15% advanced than Aayush, Habits, BATS, CSIMH, MGA, and heuristic approach, respectively.

A Novel IPT System With Full-Range Soft-Switching Operation and Magnetic Integration Based on Dual-Decoupling Concept for Efficiency and Power Density Optimization

A Novel IPT System With Full-Range Soft-Switching Operation and Magnetic Integration Based on Dual-Decoupling Concept for Efficiency and Power Density Optimization

Explicit Topology Optimization of Voronoi Foams.

Topology optimization can maximally leverage the high DOFs and mechanical potentiality of porous foams but faces challenges in adapting to free-form outer shapes, maintaining full connectivity between adjacent foam cells, and achieving high simulation accuracy. Utilizing the concept of Voronoi tessellation may help overcome the challenges owing to its distinguished properties on highly flexible topology, natural edge connectivity, and easy shape conforming. However, a variational optimization of the so-called Voronoi foams has not yet been fully explored. In addressing the issue, a concept of explicit topology optimization of open-cell Voronoi foams is proposed that can efficiently and reliably guide the foam's topology and geometry variations under critical physical and geometric requirements. Taking the site (or seed) positions and beam radii as the DOFs, we explore the differentiability of the open-cell Voronoi foams w.r.t. its seed locations, and propose a highly efficient local finite difference method to estimate the derivatives. During the gradient-based optimization, the foam topology can change freely, and some seeds may even be pushed out of shape, which greatly alleviates the challenges of prescribing a fixed underlying grid. The foam's mechanical property is also computed with a much-improved efficiency by an order of magnitude, in comparison with benchmark FEM, via a new material-aware numerical coarsening method on its highly heterogeneous density field counterpart. We show the improved performance of our Voronoi foam in comparison with classical topology optimization approaches and demonstrate its advantages in various settings.

ТЕНДЕНЦІЇ РОЗВИТКУ МАРКЕТИНГОВОЇ КОМУНІКАЦІЇ В УКРАЇНІ

The article examines the trends in the development of marketing communication in Ukraine, because with the emergence of search engines such as Yahoo, AltaVista, and later Google, new opportunities for promotion in the network appeared. As a result, the concept of search engine optimization (SEO) and contextual advertising arose. Since then, companies have started optimizing their websites to improve their search engine rankings. The concept of innovation and features of marketing communication are defined, the essence of electronic business and electronic commerce is considered. Types and features of virtual goods (stores) are considered: corporate virtual stores and intermediary virtual stores. An analysis of online marketing, as well as the number of Internet users worldwide for a certain period, was carried out. We considered the reasons for the growing popularity of online marketing and expanding the possibilities of its use. It is analyzed how the war affected the e-commerce market and the development of marketing communication in Ukraine. The scope of the e-commerce market in Ukraine is considered. The article analyzes the costs of Internet advertising in Europe. The concepts and features of interactive advertising are defined. Progressive methods for the latest communication technologies are evaluated, such as: social networks, wearables – mobile devices, youtubers, content marketing, crowdsourcing and co-creation, experimental and reverse marketing, holistic marketing, Lovemarks marketing, viral and guerilla marketing. Customer relationship management, the use of new technologies in modern marketing, individual video content, Beacon – Proximity, accessibility of social networks, 3D printers, visual Internet, mobile applications, smart sensors and geoentertainment are characterized. It was analyzed that every year marketing communications continue to develop, new technologies, strategies and approaches appear to meet changes in consumer behavior and technology. Successful marketing requires constant improvement and adaptation to change, and companies that are open to new ideas and willing to experiment will have a better chance of success in the future.

Neutrosophic parametric study of piecewise quadratic fuzzy multi-objective dynamic programming problems

The goal of this research is to investigate fuzzy multiobjective dynamic programming issues with fuzzy parameters in the objective functions and single valued trapezoidal neutrosophic numbers in the left hand side of the constraints. Piecewise quadratic fuzzy numbers characterize these fuzzy parameters. In addition, applying the score function of the neutrosophic numbers to convert the constraints parameters into its crisp . Some basic notions in the problem under the pareto optimal solution concept is redefined and analyzed to study the stability of the problem. Furthermore, a technique is presented for obtaining a subset of the parametric space that has the same pareto optimal solution. For a better understanding and comprehension of the suggested concept, a numerical example is provided.

Stakeholder-driven Design and Exploration of Sociotechnical Systems using Virtual-Reality

With ever-shorter product and technology lifecycles, companies are pressured to shorten the time-to-market for new products. This requires faster and more agile design processes both in product development and in setting up new production environments. Technological advances in the field of immersive technologies, such as extended-reality, provide tools to address these challenges and increase process agility. One tool is virtual prototyping. Virtual prototyping enables the involvement of users and other stakeholders early in the development process. Currently, the use of virtual prototypes is largely limited to design reviews and assessments of existing system concepts. Inspired by the paradigms of creative collaboration (co-creation) and exploration, we have developed a participatory design method where users and other stakeholders can explore and directly adapt virtual prototypes within the virtual environment to find the optimal design concept. In this paper, we present an exploratory and stakeholder-driven design paradigm and its application in the context of two industrial use-cases in product development and production training. We illustrate how virtual exploration environments can be built, how the exploration and design process is orchestrated with the involvement of all relevant stakeholders, and how the results and findings can be utilized in later system development phases.

Approach Maximizes Marginal Field Value by Going Back to Basics

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 32379, “Marginal Field Value Maximization by Going Back to Basics With Design-to-Value Enhancement,” by Yen P. Chan, Muhammad Y.S.M. Yasin, and Ahgheelan S. Thurai, Petronas, et al. The paper has not been peer reviewed. Copyright 2023 Offshore Technology Conference. Reproduced by permission. _ Value is defined by a quantum of functions or returns received from resources invested. In extremely marginal oil and gas fields, returns hardly meet invested resources profitably. Stranded, widely scattered resources add to the complication. The complete paper shares an approach to notional well- and facility-development concept generation for such fields by shifting emphasis to designing for value to improve project viability rigorously. Problem Statement Based on Case Study Case study Field X, located offshore Asia, is one of many oil resources in the region with virgin reservoir pockets and layers that are marginal in volume yet can provide a considerable recoverable volume if developed collectively. However, being horizontally scattered and shallow, with a reservoir true vertical depth (TVD) of less than 2000 m, the field was designed initially with up to 12 wells to maximize reach, thus requiring a large wellhead platform (WHP) at the surface. Gas lift was required from the first day of production, leading to two pipelines at a minimum. Given the number of wells and surface facilities required, this led to a highly negative economic outcome. To quantify the extent of cost reductions and increase the recoverable targeted resources required to meet targeted economic indicators for a business case, the project team performed a series of sensitivity analyses. Despite efforts to phase out field development, minimize surface facilities, and simplify well design where possible, the project remained negative in net present value because reducing the number of wells and facilities will lead to a dramatically lower estimated ultimate recovery (EUR), which is the key driver in any oil and gas development. The project team thus was presented with an almost unworkable situation where scope and cost reduction to satisfy economic returns simply meant that installation of neither wells nor facilities was viable. The authors refer to the approach they describe in the complete paper as “going back to basics.” This approach, coupled with a design-to-value (D2V) approach, was effective in countering seemingly irreversible economic results. This approach is a systematic way to develop an optimal concept for maximum value realization because the agile approach questions every aspect of concept development to achieve minimum technical requirements while providing better clarity in cost/risk tradeoff through concept evaluation in a staircase manner. The process of executing D2V for marginal field development while managing technical risks is detailed in the following subsections for both well design and in facility-concept design.