Optimal Output Research Articles

Cost function criteria using muscle synergies: Exploring the potential of muscle synergy hypothesis

Background and objectiveSolving the redundant optimization problem for human muscles depends on the cost function. Choosing the appropriate cost function helps to address a specific problem. Muscle synergies are currently limited to those obtained by electromyography. Furthermore, debate continues regarding whether muscle synergy is derived or real. This study proposes new cost functions based on the muscle synergy hypothesis for solving the optimal muscle force output problem through musculoskeletal modeling. MethodsWe propose two new computational cost functions involving muscle synergies, which are extracted from muscle activations predicted by musculoskeletal modelling rather than electromyography. In this study, we constructed a musculoskeletal model for simulation using the “Grand Challenge Competition to Predict In Vivo Knee Loads” dataset. Muscle synergies were obtained using non-negative matrix factorization. Two cost functions with muscle synergies were constructed by integrating the polynomial and min/max criterion. Two new functions were verified and validated in normal, smooth, and bouncy gaits. ResultsThe muscle synergies based on normal gaits were classified into four modules. The cosine similarities of the first three modules were all >0.9. In the normal and smooth gaits, the forces in most muscles predicted using the two new functions were within three standard deviations of the root mean square error for electromyographic comparisons. Predicted muscle force curves using the four methods as well as characteristic points (i.e., time points in the gait cycle when the significant difference was observed between normal and bouncy gaits) were obtained to validate their predictive capabilities. ConclusionsThis study constructed two new cost functions involving muscle synergies, verified and validated the ability, and explored the potential of muscle synergy hypothesis.

Calculation on maximum output power of wave energy-PTO system

The energy conversion efficiency of wave energy device is one of the key problems in the large-scale utilization of wave energy. The study of the maximum output POWER of PTO (Power-Take-Off) system provides a theoretical reference for the efficient utilization of energy. In this paper, genetic algorithm and adaptive differential evolution algorithm based on neighborhood search are used to optimize the two-objective multi-order differential equations for the maximum output power of PTO system, and the global optimal solution is obtained. Compared with the traversal algorithm, the algorithm involved in this paper is efficient and the optimal output power obtained can provide a scientific basis for the structural optimization design and material selection of the wave energy device.

Environmental and economic scheduling for wind-pumped storage-thermal integrated energy system based on priority ranking

With the rapid access of wind power clusters (WPC), it is difficult for the traditional active scheduling mode to take into account the security, economy and environmental protection of the power system. Pumped storage power station (PSPS), with its flexible regulation characteristics, can reduce the volatility of wind power and enhance the capacity of wind power accommodation to a certain extent. Therefore, this paper proposes an environmental and economic scheduling strategy for the wind-pumped storage-thermal integrated energy system, and rationally arranges the sequence of the units based on the principle of energy saving and emission reduction. The scheduling strategy involves optimizing operational decision-making for pumped storage units to enhance their regulation performance. Firstly, a pre-scheduling of the wind-pumped storage bundling system is carried out, aiming at achieving the highest wind power accommodation rate, the smallest output fluctuation and the lowest pumped storage scheduling cost. Next, the joint scheduling of the wind-pumped storage-thermal system is carried out, and the priority ranking method is used to arrange the generation schedule of the thermal units according to the optimal wind-pumped storage joint output. Finally, the proposed environmental-economic scheduling model is solved by the improved NSGA-II algorithm to verify the effectiveness of the scheduling strategy.

Multiphysics simulations of uniaxial compression applied to various rock samples subject to microwave pretreatment

PurposeAmong the various applications involving the use of microwave energy, its growing utility within the mining industry is particularly noteworthy. Conventional grinding processes are often overburdened by energy inefficiencies that are directly related to machine wear, pollution and rising project costs. In this work, we numerically investigate the effects of microwave pretreatment through a series of compression tests as a means to help mitigate these energy inefficiencies.Design/methodology/approachWe investigate the effects of microwave pretreatment on various rock samples, as quantified by uniaxial compression tests. In particular, we assign sample heterogeneity based on a Gaussian statistical distribution and invoke a damage model for elemental tensile and compressive stresses based on the maximum tensile stress and the Mohr–Coulomb theories, respectively. We further couple the electromagnetic, thermal and solid displacement relations using finite element modeling.Findings(1) Increased power intensity during microwave pretreatment results in decreased axial compressive stress. (2) Leveraging statistics to induce variable compressive and tensile strength can greatly facilitate sample heterogeneity and prove necessary for damage modeling. (3) There exists a nonlinear trend to the reduction in smax with increasing power levels, implying an optimum energy output efficiency to create the maximum degradation-power cost relationship.Originality/valuePrevious research in this area has been largely limited to two-dimensional thermo-electric models. The onset of high-performance computing has allowed for the development of high-fidelity, three-dimensional models with coupled equations for electromagnetics, heat transfer and solid mechanics.

Multi-Objective Optimization of Vortex Magnetohydrodynamics (MHD) Generator using Response Surface Methodology

The introduction of electromagnetic fields in fluid dynamics in magnetohydrodynamics (MHD), particularly when those fields are vector and non-uniform, complicates its application in vortex geometry. The imperative to optimize MHD generators arises from the inherent trade-off between voltage and pressure drop in energy conversion systems, to maximize voltage output while minimizing associated pressure drop. This study focuses on optimizing vortex MHD generators by applying Response Surface Methodology (RSM), which is based on mathematical models that capture the complex relationships between factor and response variables. This method offers a comprehensive approach to obtaining the optimum solution to the objectives, voltage and pressure drop, based on fluid velocity and magnetic field strength input parameters. Numerical optimization RSM generates 11 solutions. The optimum solutions obtained are a velocity of 1.415 m/s, and magnetic field strength of 0.43 T, and the corresponding optimum output voltage and pressure drop will be 4.264 mV and 4.254 psi, respectively, with a desirability level of the selected solution is 0.770. This study suggests the RSM method shows a good measurement of R2 and RSME. Our findings contribute to the understanding of optimizing vortex MHD generators and offer insights into achieving efficient energy conversion systems of a set of optimum generator operating parameters.

Exploiting the Capabilities of Classifiers to Examine a Website Defacement Data Set

Website defacement is the illegal electronic act of changing a website. In this paper, the capabilities of robust machine learning classifiers are exploited to select the best input feature set for evaluation of a website’s defacement risk. A defacement mining data set was obtained from Zone-H, a private organization, and a sample consisting of 93,644 data points was pre-processed and used for modelling purposes. Using multi-dimensional features as input, enormous modelling computations were carried out to determine the optimal outputs, in terms of performance. Reason and hackmode presented the highest contributions for the evaluation of website defacement, and were thus chosen as outputs. Various machine learning models were examined, and decision tree (DT), k-nearest neighbours (k-NN), and random forest (RF) were found to be the most powerful algorithms for prediction of the target model. The input variables 'domain', 'system', 'web_server', 'redefacement', 'type', 'def_grade', and 'reason/hackmode' were tested and used to shape the final model. Using the cross-validation (CV) technique, the key performance factors of the models were calculated and reported. After calculating the average scores for the hyperparameter metrics (i.e., max-depth, min-sample-leaf, weight, max-features, and CV), both targets were evaluated, and the learning algorithms were ranked as RF > DT > k-NN. The reason and hackmode variables were thoroughly analysed, and the average score accuracies for the reason and hackmode targets were 0.85 and 0.585, respectively. The results comprise a significant development, in terms of modelling and optimizing website defacement risk. This study successfully addresses key cybersecurity concerns, particularly website defacement.

Structural and magnetic properties of M-type hexaferrite nanoparticles: A comparative analysis of BaFe12O19 and SrFe12O19 synthesized via chemical co-precipitation

In this work, a comprehensive analysis of the structural and magnetic properties of the M-type hexaferrite (BaFe12O19 and SrFe12O19) was conducted using the chemical co-precipitation approach. The analytical techniques employed include powder X-ray diffraction, Transmission Electron Microscopy, Fourier Transform Infrared Spectroscopy, and Thermogravimetric Analysis. Powder Neutron Diffraction was utilized to analyse the magnetic ordering and crystal structure. A hexagonal crystal structure with space group P63/mmc was obtained from to structural analysis. Additionally, the investigation encompassed an assessment of the maximum energy product (BH)max and magnetic properties utilizing Vibrating Sample Magnetometry across all synthesized materials. Magnetic investigations of the studied materials showed several interesting characteristics: SrM showed a maximum saturation magnetization of 49.67 emu/g and a maximum coercivity of 4874.55 Oe. Remarkably, SrFe12O19 showed twice as much saturation magnetization and remnant magnetization than BaFe12O19, suggesting more robust and effective magnetic parameters. The overarching objective of this study is to discern the optimal hexaferrite material, evaluating magnetism, coercivity, thermal stability, and energy output through a systematic exploration of crystal structure, magnetic properties, thermal behaviour, manufacturing methodologies, and microstructure. This research endeavour not only contributes crucial insights into the potential applications of both BaM and SrM but also considers their environmental implications. The study further provides valuable recommendations for selecting the most efficacious material for specific permanent magnet applications, thereby contributing to the advancement on the field of magnetic engineering. The culmination of this work is poised to facilitate informed decision-making and technological progress in the realm of hexaferrite materials with a deliberate consideration of their environmental impact.

The Problem Statement of Optimal Petroleum Engineering Output with Respect to Various Techniques and Materials Used

The Problem Statement of Optimal Petroleum Engineering Output with Respect to Various Techniques and Materials Used

Model predictive control for Vienna rectifier with constant frequency based on inductance parameters online identification

When the finite control set model predictive control (FCS-MPC) is applied to the three-level converter, there are problems such as large current harmonics, high requirements for the computing efficiency of the microcontroller, complex multi-objective optimization and limited output vector switching. In addition,the mismatch of inductance parameter may directly affect the observation accuracy of FCS-MPC. To solve the above problem,a double vector model predictive control strategy with constant frequency strategy based on the inductance parameters on-line identification is presented.First, a single objective cost function based on the direct power is constructed by optimizing the redundant vector which is selected to balance the neutral-point potential, the design of weighting factor is avoided.At the same time, in order to effectively reduce the grid current ripple under single vector modulation, space vector pulse width modulation (SVPWM) is realized by combining with zero vector control mode. And, a parameter identification method based on model reference adaptive system(MARS) is proposed to overcome the effect of model parameter mismatch.Finally, the results show that the proposed F-MPCCF has good steady-state and dynamic performance from the static, transient and neutral-point potential control.

Comparative Analysis of Two-Stage and Single-Stage Models in Batteryless PV Systems for Motor Power Supply

Implementing photovoltaic (PV) systems as direct power sources for motors without batteries is a complex process that requires a sophisticated control mechanism. The crucial aspect of PV systems is the Maximum Power Point Tracking (MPPT) process, which ensures that the installed PV system generates optimal energy output. A recent study has analyzed research related to PV systems supplying power to pump motors, and the results have successfully classified these systems into two main models: the two-stage and the single-stage. The two-stage model involves separate power tracking and load consumption control processes, while the single-stage model integrates power tracking and load consumption control into a single process. A comparative analysis of these two models has revealed that the two-stage model exhibits higher stability due to the separate power tracking and load consumption control processes. Aspects such as the MPPT process, motor power consumption, and the utilization of DC-link capacitors were examined in this study. The findings of this comparative study contribute valuable insights into the effectiveness and stability of two-stage and single-stage models in PV systems supplying power to motors without batteries. The results will significantly interest researchers and practitioners working in Photovoltaic systems and motor control, providing helpful information for designing and implementing more efficient and reliable PV systems.

Investigation of RF performance of Ku-band GaN HEMT device and an in-depth analysis of short channel effects

In this paper, we have characterized an AlGaN/GaN High Electron Mobility Transistor (HEMT) with a short gate length (Lg ≈ 0.15 μm). We have studied the effect of short gate length on the small signal parameters, linearity parameters and gm-gd ratio in GaN HEMT devices. To understand how scaling results in the variation of the above-mentioned parameters a comparative study with higher gate length devices on similar heterostructure is also presented here. We have scaled down the gate length but the barrier thickness(tbar) remained same which affects the aspect ratio (Lg/tbar) of the device and its inseparable consequences are the prominent short channel effects (SCEs) barring the optimum output performance of the device. These interesting phenomena were studied in detail and explored over a temperature range of −40 °C to 80 °C. To the best of our knowledge this paper explores temperature dependence of SCEs of GaN HEMT for the first time. With an approach to reduce the impact of SCEs a simulation study in Silvaco TCAD was carried out and it is observed that a recessed gate structure on conventional heterostructure successfully reduces SCEs and improves RF performance of the device. This work gives an overall view of gate length scaling on conventional AlGaN/GaN HEMTs.

Effects of training module regarding learning management system (LMS) on knowledge and attitude of dental undergraduates toward use of LMS

Objectives: The objective of this study was to evaluate the differences in knowledge and attitude of dental students regarding learning management system (LMS) after receiving a specific training regarding the same. Material and Methods: A questionnaire-based cross-sectional study was done among the 2nd and 3rd-year students of Ranjeet Deshmukh Dental College and Research Centre, Nagpur. Data were collected by a questionnaire containing ten questions. The training module was designed including a didactic session and trouble shooting session for the students. Results: When analyzed, a maximum number of students showed increased knowledge and positive attitude toward LMS after the module. Few students were not using LMS but a maximum number of questions were with a higher percentage of positive responses. There is much awareness and knowledge about LMS after the module. Conclusion: It is critical to train the students regarding various aspects of LMS and its technical details to make navigation easier. The use of information communication technologies in learning involves efforts from not only teachers but also students to make it an effective way of learning. Regular follow-ups and troubleshooting will help maximize students’ active participation in online learning using LMS. Students’ feedback and necessary upgradation of the system are strongly recommended to achieve optimum learning output using LMS.

Solar System Implementation Performance at Universiti Sains Malaysia (USM)

Universiti Sains Malaysia (USM) has embarked on several solar energy initiatives to promote greener operations and sustainability. However, concerns exist regarding the actual performance of existing systems falling short of their potential. This project delves into the limitations of the current solar systems at USM, focusing on identifying and analyzing factors hindering optimal output. The research aims to understand the performance gaps affecting USM's solar systems comprehensively. By meticulously analyzing historical data, including solar irradiance, temperature, and system output, alongside a thorough study of existing infrastructure and maintenance practices, the project seeks to pinpoint specific bottlenecks. An in-depth interview with USM solar system specialists further assesses the systems' efficiency. This approach allows for a holistic evaluation of current practices and identification of key improvement areas. The ultimate goal is to establish concrete recommendations for optimizing USM's solar systems. These will encompass technical solutions, such as system upgrades, maintenance improvements, and operational adjustments, including data-driven monitoring and dynamic energy management strategies. Through this research, we strive to unlock the full potential of USM's solar infrastructure, enhancing its contribution to campus sustainability while providing valuable insights for wider solar energy implementation across Malaysia.

Principal parameters of thermoelectric generator module design for effective industrial waste heat recovery

In the sustainable energy agenda, thermoelectric generators (TEG) can be a central technology for low-cost combined heat and power (CHP) systems. TEG module (TEM) is the combination of TEG cells, heat pipes, heat sinks and copper blocks that produce electrical power and thermal energy for low temperature heating simultaneously. Two TEG cells were used in each TEM for CHP in a bakery factory with a reference waste heat temperature of 250°C. Different designs of TEM affect the heat transfer mechanics through the components. However, actual testing of each design requires high cost and time consuming. Identifying the principal parameters affecting the desired output is indeed important before investing in actual design fabrication. One-dimensional model is developed in this manuscript to evaluate the fundamental interactions between each component. Parametric variation for nine main parameters characterized the steady-state response of each parameter under four novel heat sink configurations. The parameter sweeps approach benefits in designing a novel TEM for optimum system output. An improved TEM with 6 TEG cells was designed and it increased the heat recovery ratio from an initial 14% to 38%. The Reynolds number of streams are the major operating parameter as it influences the heat sink effectiveness. Large heat exchanger frontal area and copper block housing surface area are also significant parameters. Identification of these principle parameters would assist in effective designs of TEM systems for industrial CHP.

Design of Aluminum Doped ZnO/Phenyl-C-Butyric Acid Methyl Ester/Tungsten Disulfide (AZO/PCBM/WS2) Heterojunction-Based Device for Applications in Solar Cells and Broadband Self-Powered Photodetectors.

The domain related to the use of renewable energy is showing high interest among the researchers in the current days, and light energy can be considered as one of such. Solar cells are the kind of devices that use light energy in an efficient way to generate electricity. Hence, designing and developing a solar cell requires meticulous attention to get an optimum output. This work focuses on designing and optimization of aluminum dope ZnO/phenyl-C-butyric acid methyl ester/tungsten disulfide (AZO/PCBM/WS2) heterojunction-based device for applications in solar cells. Moreover, considering the high demand of optoelectronics like photodetectors, this work also uncovers the capabilities of the device in the applications of broadband self-powered photodetectors. The optimized values of several parameters of the device such as the thickness and doping density of the WS2 layer, the defect density of the WS2 layer, and the interface PCBM/WS2 were 2 μm, 1017 cm-3, 1014 cm-3, and 1010 cm-2, respectively. These optimal conditions facilitated in obtaining fill factor and efficiency values of 84.78 and 23.92%, respectively. Further, the photodetection performance was evaluated with the parameters like responsivity and detectivity. The maximum calculated responsivity of the device at 0 V bias was 0.63 A/W at 880 nm, whereas the maximum detectivity was 1.54 × 1013 Jones. This study also extensively focuses on the in-depth understanding of the physics associated with the movement of the charge carriers under the illuminated conditions by studying the band diagrams and the electric fields of the heterojunctions at various conditions.

Dynamic Cooperative Oligopolies

An n-person cooperative oligopoly is considered without product differentiation. It is assumed that the firms know the unit price function but have no access to the cost functions of the competitors. From market data, they have information about the industry output. The firms want to find the output levels that guarantee maximum industry profit. First, the existence of a unique maximizer is proven, which the firms cannot determine directly because of the lack of the knowledge of the cost functions. Instead, a dynamic model is constructed, which is asymptotically stable under realistic conditions, and the state trajectories converge to the optimum output levels of the firms. Three models are constructed: first, no time delay is assumed; second, information delay is considered for the firms on the industry output; and third, in addition, information delay is also assumed about the firms’ own output levels. The stability of the resulting no-delay, one-delay, and two-delay dynamics is examined.

INTELLIGENT MONITORING SYSTEM FOR REAL-TIME OPTIMIZATION OF ULTRA-PRECISION MANUFACTURING PROCESSES

In the realm of ultra-precision manufacturing, the minutiae of process control and material handling are paramount to achieving the highest levels of product quality and manufacturing efficiency. The industry faces a significant challenge: maintaining and enhancing the precision of manufacturing processes in real-time to ensure optimal output quality while minimizing waste and energy consumption. This challenge is compounded by the increasing complexity of products and the materials used, requiring ever more precise and adaptive manufacturing techniques. The importance of addressing this challenge cannot be overstated, as it directly impacts the competitiveness, sustainability, and innovation capacity of manufacturing firms. The development of an intelligent monitoring system that integrates advanced precision metrology techniques presents a promising solution to this problem. Such a system would enable real-time optimization of manufacturing processes, leveraging cutting-edge technologies and data analytics to dynamically adjust parameters for optimal performance. By doing so, it would not only enhance the precision and efficiency of manufacturing operations but also contribute significantly to sustainable manufacturing practices by reducing waste and energy consumption. This concept paper proposes the development of this intelligent monitoring system, outlining its potential impact on the ultra-precision manufacturing industry.
 Keywords: Ultra Precision, Monitoring, Processing, Real Time.

Improving thermal efficiency of solar stills: Bioactive nano-PCM and Cramer’s rule analysis

Green-sourced Petroselinum crispum leaf (P) was carefully harvested and underwent extraction processes. This material was then combined with TiO2 nanoparticles (T) into paraffin wax (P) to create the PTP nanocomposite, using an economically viable and environmentally friendly approach, with P serving as a consistent, reducing, and stabilizing element. The synthesized PTP was thoroughly analyzed using Spectrophotometer, Fourier-transform-IR spectroscopy, X-Ray diffraction, DSC, TGA, and SEM for characterization. The PTP samples were applied in constructing a Single Slope Wick Solar Still (SWS), aiming to induce surface plasmon resonance around 450 nm across the absorber plate. The excitation of PTP at SPR led to the release of significant heat, contributing to temperature increments of the aqueous medium by varying percentages (10 %, 20 %, 30 %, and 40 %) under different ratios upon exposure to solar radiation at the precise plasmon resonance wavelength. This study introduced the first-time application of Cramer's rule (determinant technique) in solving energy balance equations for temperature components. Evaluation revealed that incorporating 30 % PTP notably enhanced SWS efficiency, achieving an optimal distillate output of 8.70 l/m2day, including 1.95 l/m2 at night, resulting in an efficiency of 42.74 %.

An experimental and theoretical study on Dy3+-doped ZBLAN fiber laser, core-pumped at 1.1 μm

An experimental and theoretical investigation into a core-pumped Dy3+-doped ZBLAN fiber laser with 1.1 μm pumping was conducted to figure out a configuration for better slope efficiency. First, the laser was experimentally constructed with a simple Fabry–Pérot cavity incorporating AlF3 no-core fiber endcaps. The maximum output power of 607 mW was obtained readily with a slope efficiency of 25%. Next, a 5-energy level model was adopted for a numerical simulation to figure out the optimum output mirror reflectivity for the particular experimental laser setup in terms of slope efficiency. The best slope efficiency of 30% was shown to be obtainable with an output mirror of a 22% reflection.

Revolutionizing Business Administration and Management with Information Technology: A Study of NITEL in Port Harcourt

Information technology is the creation, processing, storing, securing, and exchanging of all types of electronic data through the use of computers, networking, storage, and other physical devices, infrastructure, and procedures. It is typically utilized in relation to business operations as opposed to personal or recreational technology. This paper therefore examines the revolutionization of information technology on business administration and management. The aim is to determine the impact of information technology on NITEL, Port Harcourt. To achieve this, the researcher adopted the survey research design vis-à-vis a qualitative study because of the use of a questionnaire as a survey instrument. The findings of this research show that information technology optimizes business administration and management. It also shows that certain factors, such as staff redundancy, fraud, and high maintenance or repair costs, are some of the problems associated with information technology at NITEL. The research concludes that information technology has had a significant impact on the management and administration of business at Nigerian Telecommunication (NITEL). For optimal operation and optimum output service, the various machines or equipment originating from information technology require adequate and efficient handling.