Prototype Model Research Articles

Effect of scale factor on the dynamic response of frame foundations

Abstract In geotechnical engineering, a scale factor “n” is a numerical ratio that relates the physical properties of a physical model to those of a prototype. The effect of scale factor on the dynamic response of a frame foundation used for high-speed turbo machines is examined through numerical analyses to clarify the influence of scaling dimensions, frequency, static and dynamic loads, and scaled models’ material on the dynamic responses of the frame foundation. The static and dynamic analyses were conducted using Ansys Workbench software. The total number of analyses used to investigate the scale factor effect was 28. Both modal and harmonic analyses were performed to calculate the natural frequencies and displacement responses of the scaled and prototype models under the scaled dynamic loading. Five scale factors were used in this study for concrete models (1, 20, 25, 32, and 40), and two additional analyses on steel models of scale (1 and 20) were used to study the material scaling. The prototype results were first verified, and then the models were investigated after scaling the dynamic loads and dimensions. The results of this study revealed the importance of scaling the frequency when studying the high-speed turbo machine foundation models to reflect the correct responses of the prototype foundation.

Optimising the review of electronic monitoring information for management of commercial fisheries

Electronic monitoring (EM) systems incorporating cameras and other devices can collect a broad range of data to support fisheries management. We reviewed the data collection capabilities of EM and considered approaches to increasing efficiency, including cost effectiveness, of EM review. EM can provide information on catch, effort, catch handling, bycatch mitigation, fishing gear and operational data, which are relevant for fisheries management including by Regional Fisheries Management Organisations (RFMOs). Methods to increase efficiency and decrease costs of EM review apply from the programme design phase, through data collection and review. At review, costs may be reduced by sampling imagery optimally to meet monitoring objectives. Considering RFMOs as users of EM-collected information, we applied EMoptim, an open-source simulation model developed in R that estimates the amount of EM review necessary to meet one or more user-specified monitoring objectives. EMoptim uses stratification to increase review efficiency and incorporates a function to explore review costs against the monitoring objectives set. We evaluated the amount of EM review needed to estimate catch with specified precision, using fishery data available from the Western and Central Pacific Fisheries Commission. Model outputs show that EM review requirements increase as catch frequency decreases, dispersion of catch events increases, and when more precise catch estimates are required. Geographical stratification reduced the amount of review required for more commonly caught species and when catch events were focused in a limited area. Optimising review rates across multiple monitoring objectives was most effective for more commonly caught species. We highlight opportunities for future use and development of this prototype modelling package.

Virtual prototype modeling and fuzzy control of the heave compensation system for a 500-ton deep-sea mining vessel

The unexpected heave motion of vessels generated by waves has always threatened the safe operation of mining vessels. The heave compensation system is a critical equipment for offshore cranes to ensure the safety and stability of the deep-sea mining vessel operation. Unfortunately, the nominal load of the mining vessel transporting minerals has become increasingly large, which has led to the dynamic performance of the heave compensation decline and a significant increase in energy consumption. To solve these problems, a semiactive heave compensation system and fuzzy logic-based controller are proposed in this paper. First, an active-passive hybrid heave compensation system is designed to reduce energy consumption greatly. The virtual prototype models of the proposed heave compensation system in a 500-ton deep-sea mining vessel are also built. Then, an adaptive tuning PID controller is developed based on the Transfer function of the heave compensation system and Mamdani-type fuzzy logic. Virtual prototype simulation results of AMESim-Simulink joint simulation illustrate that the accuracy of compensation for the four or six sea states reaches more than 90% with the proposed method and the power of the active compensation system is about 21% of the total power. Finally, the experimental results are included to demonstrate the effectiveness of the proposed semiactive heave compensation system.

Digital creativity-based professional learning communities’ model to encourage differentiated learning design skills in elementary school teacher

The professional practice of Learning Communities (PLC) demonstrates ineffectiveness when collaborative work hinders innovation in understanding individual student needs. This study aims to describe design of digital creativity-based PLC models for teachers to support the skills of developing differentiated learning in elementary school. The research used the Borg & Gall development design. The research subjects consisted of 180 elementary school teachers who had at least five years of teaching experience. The research data were obtained through questionnaires and documentation. Research data analysis was carried out with an interactive model. The results show that the findings of the needs analysis show that teachers need software to implement PLC. Products in the form of PLCs can be accessed via the website. Prototype of application PLC model based on digital creativity has four main menus consisting of the “KKG Team”, “Training”, “Work Space”, and “News” menus. The digital creativity-based PLC model was developed by producing an output in the form of an application that can be accessed via the website. The prototype model has not been validated by experts, so further studies are expected to be able to test the validity of the model and conduct field trials.

Design and Integration of Information Systems for the Halal Inspection Institute (LPH) UIN Syarif Hidayatullah Jakarta with SiHalal Ministry of Religion of the Republic of Indonesia

In the context of the globalization of the halal industry, the Halal Inspection Institute (LPH) UIN Syarif Hidayatullah Jakarta faces challenges in improving halal certification services. This research develops a web-based information system with the integration of the Indonesian Ministry of Religion's SiHalal using the REST API and Prototype model. The main goal is to increase LPH credibility, integrate the LPH system with SiHalal, and improve LPH operational management performance. The system development method used is the Prototype Model, involving data collection through observation, interviews, and literature study to understand user needs. The first stage focuses on communication to understand needs, followed by rapid planning and prototype design. System implementation using JavaScript, NodeJs, and ReactJs. After a series of tests, the system resulted in effective integration with SiHalal and more efficient operational management. The research results include three prototypes. The first prototype focused on building an LPH profile website to increase credibility and access to information. The second prototype successfully integrated the LPH system with SiHalal, ensuring the efficiency and validity of audit reports. The third prototype adds report management, income/expenditure recording, and information updates, increasing LPH's operational efficiency.

Review of Earthquake Resistance and Mitigation of Underground Structures

The rapid development of underground structural engineering in China has been accompanied by pressing issues in the research of earthquake resistance and mitigation. Typically, underground structures exhibit good seismic performance with relatively few disasters. However, once they are damaged by earthquakes, the consequences can be severe and difficult to repair. This paper first elaborates on the prototype observation, theoretical analysis, model testing, and numerical simulation involved in seismic response analysis of underground structures. It comprehensively analyzes the advantages, disadvantages, and applicability of different research methods. Finally, it summarizes the research achievements on technical measures to mitigate earthquake damage to underground structures in strong earthquake regions, both domestically and internationally.

Utility of photoplethysmography in detecting elevated blood glucose among non-diabetics.

This study aimed to evaluate a technique of using photoplethysmography (PPG) for detecting elevated blood glucose in individuals. This is a prospective, cross-sectional study in which 500 healthy volunteers were recruited at a tertiary hospital in Singapore from October 2021 to February 2023. Capillary glucose was measured concurrently with PPG signals acquired using the wrist-worn Actxa Tracker (Spark + Series 2) and the In-Ear Prototype model SVT, which were worn for a duration of 8 min. Participants with a capillary blood test reading ≤11.1 mmol/dL had to consume a standard glucose tolerance drink and return 1 h later for a second capillary blood test. Two hundred and forty-four features were subsequently extracted from the PPG signals. Of the 500 volunteers, 17 were excluded because of incomplete records. This led to a total of 483 participants' records being included in the final analysis. For predicting elevated capillary blood glucose level, demographics alone achieved an area under the curve (AUC) of 0.75. When wearable features derived from PPG were combined with demographics, AUC improved significantly to 0.82 (P = 0.0001). This study shows that a non-invasive method of assessing diabetes mellitus risk using PPG combined with demographics is a viable option to provide a cheaper and more accessible modality for population-wide diabetes mellitus risk assessment.

PERANCANGAN APLIKASI MANAJEMEN PRODUKSI KOPI PT. KARYA BAKTI BERBASIS WEB DENGAN MENGGUNAKAN MODEL PROTOTYPE

The coffee industry has a complex production process right up to the distribution of the final product. Along with increasing competition in the coffee industry, PT. Karya Bakti faces the challenge of increasing productivity, maintaining product quality, and optimizing the supply chain. To manage this process efficiently and effectively, PT. Karya Bakti requires a management system that is reliable and can be accessed easily. Thus, this research will discuss how to design and build an information system and find out how to implement coffee production management applications at PT. Web-based Bakti Work. In this research, the UML method is used as a means of designing an object-oriented system with a Prototype model. In this research, to find out the problems that occur in a system, it is a good idea to analyze the operating system and try to understand how the system works well. After that, the proposed system design is carried out, there will be an admin who will have full control over the system by creating use cases, class diagrams, activity diagrams. In the design of a web-based coffee production management application, the users who can use this application are the authorized departments in production management. In accordance with the system design previously discovered, the application has several list display designs for the data displayed on the application pages. This research produces a management information system to help PT. Karya Bakti in processing data, both sales data, income data, roasting data, purchase or order data. With this information system, it has made it easier for PT. Karya Bakti in making monthly or annual reports with a success rate of 70%, coffee production management information system PT. Karya Bakti can increase efficiency and productivity and this coffee production management information system was only developed specifically for PT. Community Service. However, the author hopes that this system will be developed in a mobile version and because this information system is not yet equipped with employee management, recitation and inventory features, it is highly recommended for future research to add these features. Keywords: Design, Application, Management, Web, Prototype

Implementation of fuzzy logic controller for positive output LUO converter

This paper describes the fuzzy logic controller (FLC) for a positive output LUO converter (POLC), which uses a voltage controller to achieve the output voltage regulation. The fourth-order POLC DC–DC converter produces positive output voltage utilizing the voltage lift technique. Due to the converter’s switching functions and its inherently time-varying nature, it exhibits a highly nonlinear dynamic response. To enhance the dynamic performance of the converter, controllers are designed using small signal model and frequency response analysis. The closed loop is used to evaluate converter performance in the presence of variations in reference voltage, source voltage and load disturbances. The power loss analysis of the converter is performed. The comparative results show that FLC gives good dynamic response for wide range of variations than the proportional–integral (PI) controller. The prototype model is built using dsPIC (30F4011) microcontroller, and the experimental results are presented to validate the simulation results.

Effectiveness of non-pharmaceutical interventions for COVID-19 in USA

Worldwide, governments imposed non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic to contain the pandemic more effectively. We examined the effectiveness of individual NPIs in the United States during the first wave of the pandemic. Three types of analyses were performed. First, a prototypical Bayesian hierarchical model was employed to gauge the effectiveness of five NPIs and they are gathering restriction, restaurant capacity restriction, business closure, school closure, and stay-at-home order in the 42 states with over 100 deaths by the end of the wave. Second, we examined the effectiveness of the face mask mandate, the sixth and most controversial NPI by counterfactual modeling, which is a variant of the prototypical Bayesian hierarchical model allowing us to answer the question of what if the state had imposed the mandate or not. The third analysis used an advanced Bayesian hierarchical model to evaluate the effectiveness of all six NPIs in all 50 states and the District of Columbia, and thereby provide a full-scale estimation of the effectiveness of NPIs and the relative effectiveness of each NPI in the entire United States. Our results have enhanced the collective knowledge on the general effectiveness of NPIs in arresting the spread of COVID-19.

Increasing the certainty of prototype models of medical organizations using functional-parametric analysis to initialize variable elements of the project from the point of view of a systems approach.

Increasing the certainty of prototype models of medical organizations using functional-parametric analysis to initialize variable elements of the project from the point of view of a systems approach.

Extending speech emotion recognition systems to non-prototypical emotions using mixed-emotion model

In the conventional approach to speech emotion recognition (SER), the classifier is usually trained on acted emotional speech data to predict individual basic emotions. In this work, we extend the SER systems with the realistic assumption of the coexistence of multiple basic emotions in an utterance. We utilize the MSP-Podcast database for developing the SER system, which contains spontaneous speech utterances. From the primary and secondary emotion annotations of this database, we organize six prototypical and seven non-prototypical emotions. We then propose the mixed-emotion model and express the non-prototypical emotions as a linear combination of prototypical emotions. The combination weights of the mixed-emotion model are computed using a normalized dominance scale based algorithm inspired by the integration of basic emotion theory and dimensional emotion theory in human psychology. We first train a prototypical SER model using the ECAPA-TDNN architecture. The softmax predictions from this model serve as emotion profile inputs to the mixed-emotion model, which then predicts the non-prototypical emotions. Assuming the coexistence of multiple emotions, we only apply the utterances with uniform emotion profiles to the mixed-emotion model. The developed system continues with the conventional SER model if the emotion profile tends to delta function owing to the probable occurrence of a single prototypical emotion. We develop the proposed mixed-emotion model based SER framework using MFCC and wav2vec 2.0 extracted features. Further, we show that due to human perception variations, there exist prominent annotation variations in the non-prototypical emotion ground truths. To address that, we extend the supervised evaluation protocols in four different formulations that capture the subjective variability at different levels. The proposed system shows a best-case performance improvement of 7.10% and 8.39% over the conventional prototypical SER model for the MFCC and wav2vec 2.0 features, respectively.

Prerelaxation in quantum, classical, and quantum-classical two-impurity models

We numerically study the relaxation dynamics of impurity-host systems, focusing on the presence of long-lived metastable states in the nonequilibrium dynamics after an initial excitation of the impurities. In generic systems, an excited impurity coupled to a large bath at zero temperature is expected to relax and approach its ground state over time. However, certain exceptional cases exhibit metastability, where the system remains in an excited state on timescales largely exceeding the typical relaxation time. We study this phenomenon for three prototypical impurity models: a tight-binding quantum model of independent spinless fermions on a lattice with two stub impurities, a classical-spin Heisenberg model with two weakly coupled classical impurity spins, and a tight-binding quantum model of independent electrons with two classical impurity spins. Through numerical integration of the fundamental equations of motion, we find that all three models exhibit similar qualitative behavior: complete relaxation for nearest-neighbor impurities and incomplete or strongly delayed relaxation for next-nearest-neighbor impurities. The underlying mechanisms leading to this behavior differ between models and include impurity-induced bound states, emergent approximately conserved local observables, and exact cancellation of local and nonlocal dissipation effects. Published by the American Physical Society 2024

EXPERIMENTAL STUDY ON OPTIMIZING THE FUSED DEPOSITION MODELING PARAMETERS FOR POLYETHYLENE TEREPHTHALATE GLYCOL MATERIAL USING TAGUCHI METHOD

In many different manufacturing techniques, additive manufacturing technologies have proven to be quite useful for developing a prototype model in wide range of applications. In that technique, Fused Deposition Modeling (FDM) is one of the concern favorite methods used in industries, because it can create complex structures at a low cost. FDM uses the polymer ingredients that are melted, extruded, and layered on top of one another to create the desired product, independent of design intricacy. This examination analyzes the effects of several process variables on the flexural and impact characteristics of parts produced of polyethylene terephthalate glycol (PETG)material, including infill structure, layer thinness, infill multi-layering, and infill concentration. The L9 orthogonal array was developed by the Taguchi method to be employed in this design of experiment. Through the analysis of variance (ANOVA), the study elucidated the relative substance and percentage effort of each process parametric quantity to the desired outcomes. The results obtained through the Taguchi method revealed optimal parameters for both impact strength and flexural tests. For impact strength, the optimum factor was determined as a layer thinness of 0.12-millimeter, quarter cubic infill structure, 30% infill denseness (density), and a multi-layering of 3. Conversely, for the flexural test, the optimal factor was found to be a layer thinness of 0.12-millimeter, cross 3D infill structure, 60% infill denseness, and a multi-layering of 4 respectively.

Research on Satellite Navigation Control of Six‐Crawler Machinery Based on Fuzzy PID Algorithm

ABSTRACTThe six‐crawler driving mechanism plays a crucial role in the operation of large machines such as bucket‐wheel excavators, dumping machines, and mobile crushing stations, as it serves functions like bearing, movement and steering. The driving characteristics of this mechanism directly influence the safety and efficiency of these machinery systems. To enhance the design methodology for multi‐crawler machinery, improve path controllability, and achieve adaptive driving, a satellite navigation control system for six‐crawler machinery was developed based on the principles of real‐time kinematic (RTK) satellite positioning. This system utilizes the distance deviation and heading angle deviation between the actual path and the predetermined path of the six‐crawler machinery as inputs to a fuzzy proportion integration differentiation (fuzzy PID) controller. This controller regulates the deviation angle of the steering crawler and the driving speeds of each track, thereby ensuring precise path tracking control. To evaluate the path tracking control performance under both straight and curved driving conditions, a virtual prototype model of the six‐crawler mechanical system was established, and co‐simulation analysis was conducted. In addition, an experimental platform for path tracking control of six‐crawler machinery was established to validate the efficacy of the satellite navigation system. The actual tracking data obtained from various driving conditions and initial deviations demonstrated that the RTK satellite navigation path tracking control system exhibited excellent control performance.

Structural state nonlinearity-based design and modification formulae of inerter-based systems

As structural safety emerges as a paramount concern and with the advancement in vibration control technology, a notable gap persists in accurately simulating structural state nonlinearity, especially within the field of inerter-based seismic control technology. Dealing with the need to upgrade the seismic performance of practical nonlinear structures, this study proposes a structural state nonlinearity-based design method for inerter-incorporated civil structures by incorporating the target seismic performance, structural nonlinearity level, and ground motion effects. By establishing mechanical models of inerter-based systems with straightforward parameters and a prototypical bilinear model for the primary structure, governing equations for inerter-incorporated structures were derived. Later, structural state nonlinearity-based design method for inerter-based systems, including optimization criteria and parameter distribution pattern, is elaborated. Simultaneously, this study also provides structural state nonlinearity-based design curves and modification formulae related to structural state nonlinearity and peak ground acceleration of earthquake. Validated using a 10-story multiple-degree-of-freedom (MDOF) structure subjected to earthquakes, the results highlight the effectiveness of the method, emphasizing its potential in controlling seismic responses of structures within the predetermined performance target. In addition, the absolute acceleration mitigation effect of inerter-based systems is investigated. The efficiency and robustness of the proposed method are also verified under near-fault and far-fault earthquakes. In essence, this research pioneers an approach in inerter-based design, bridging structural state nonlinearity, and potentially reshaping seismic control strategies to align with diverse structural states.

Clinical and Radiographic Evaluation of Soft Tissue and Bone Status in Immediate Loaded Implants Placed Following Their Extraction in the Maxillary Anterior Region.

In the maxillary anterior region, teeth extraction leads to significant soft and hard tissue changes. Immediate implant placement following extraction aims to reduce bone loss and overall treatment time. However, it may result in adverse soft tissue changes impacting esthetics. This study evaluates the clinical and radiographic outcomes of immediately loaded implants in the maxillary anterior region, focusing on soft tissue preservation and bone status. This study, conducted from April 2022 to August 2024 at the Department of Oral and Maxillofacial Surgery, Ragas Dental College and Hospital, included 10 immediately loaded implants in seven patients. Following atraumatic extraction, implants were placed and loaded with functional provisional crowns fabricated using three-dimensional (3D) rapid prototyping models. Parameters such as crestal bone loss, buccal and palatal bone width, and interdental papilla thickness were evaluated preoperatively and postoperatively using radiographsand clinical assessments. The study found significant crestal bone loss at both mesial and distal sites over time, with the greatest loss observed at the three-month follow-up. Buccal and palatal bone width showed no significant differences preoperatively and postoperatively. Interdental papilla thickness and overall pink esthetic scores also showed no significant differences between preoperative and postoperative evaluations. Immediate implant placement in the maxillary anterior region, using 3D rapid prototyping for custom splint fabrication, demonstrated effective preservation of soft tissue profile and bone architecture. This approach provides functional and esthetic benefits, although careful monitoring of crestal bone loss is necessary.

Выбор элемента(ов) прототипа модели медицинской организации в целях оптимизации процессов регионального проекта с использованием методов динамического программирования.

Changes in federal legislation regulating the provision of patients suffering from cardiovascular diseases initiate a revision of the regional legislation, and inevitably raises questions of practical adaptation and optimization of the processes of ongoing projects, taking into account resources in the established management model in medical organizations. Finding elements of a prototype model of a medical organization implementing a regional project as objects of influence for theoretical proof of hypotheses using the dynamic programming method (callback function, recursion) is the task of optimizing the project processes considered in this article. The purposeof the research question was to optimize the processes of a regional project using the dynamic programming method, which is focused on finding the objective function F(i) – the number of ways to return the function. The subgoal was to justify the use of dynamic programming methods. Materials and methods. The information base for the study was federal and regional regulatory legal acts published in the legislative reference and legal systems of the Russian Federation, and electronic resources. The study was carried out using methods of dynamic programming, optimization, recursion, and modeling. Results. We did not find similar studies in the available literature. This study was carried out using the dynamic programming method, which is designed to solve the problem of finding the target function(s) F(i) of regional projects. The authors attempted to find a prototype of an operating procedure at the level of project executors, which is indivisible and elementary for subsequent optimization of the variable (non-constant) elements of the prototype of a medical organization model from the found objective function. Finding F(i) by categories of patients (object of influence) registered at the dispensary, obtained using the callback function F(0), F(1), F(2), F(3), …F(k); F (0) ←F (1) ←F (2) ← F (3) ……F(n‑1) ← Fn (recursion) consists of decomposing the problem into smaller subproblems, finding the optimal solution to the subproblems recursively and using the resulting solution subtasks for constructing a solution to the original problem – optimizing an element of a prototype model of a medical organization, a regional project as a whole. Conclusion. The main tasks associated with project optimization are the tasks of minimizing the cost of the project for a given deadline for its implementation and minimizing (maximizing) the project completion period for a given marginal cost of its implementation. In search of a solution to optimization issues, the authors proposed finding F(i) by categories of patients (object of influence) registered as “D”, obtained using the callback function F (0) ←F (1) ←F (2) ← F (3) ……F(n‑1) ← Fn (recursion).

Real time Cloud based fishes health monitoring using IoT.

This work is based on a prototype model for the Fishery Management System with the help of Internet of Things i.e., IOT. The proposed system works on IOT & provides real-time monitoring of the fishery system. With the help of various hardware & software devices like Sensors & the Arduino Cloud, data from the fishery system can be collected and analysed using the Cloud which also helps in maintenance of the fishes from time to time. This also helps in creating awareness about the fish whenever necessary. Along with IOT, Water Level Sensor, Temperature Sensor & pH Sensor is also used to measure the water level, temperature level and get the pH values in the system. The system can be made automatic as well as configured according to the requirement for the survival of the fishes. The Node MCU ESP8266 helps in collecting the information through the sensors & display it in the Cloud which can be accessed from Smartphones, PCs, and Tablets etc.

Enhancing Learning Management Systems with Intrusion Alerts and Forensic Logging

Web-based Learning Management Systems (LMS) are gaining popularity in the education sector as they provide more convenience in the teaching and learning experience. However, these systems are vulnerable to cyber-attacks, such as intrusion attempts. In the event of a security incident, it is imperative to conduct thorough investigations. Therefore, this study proposed Sistem Pengurusan Pembelajaran (SiPP) an LMS developed with intrusion alert and forensic log to provide incident notification and forensic-ready LMS. The prototyping model was adopted to develop the SiPP system, which includes modules such as login, intrusion notification, forensic log, activity log, teacher management, student management, learning material, and assessments. Functional testing results confirm SiPP's ability to log user activities, detect intrusion attempts, and notify users through Short Messaging Service (SMS) and other system modules function successfully. The user acceptance test shows positive feedback and high satisfaction, confirming the effectiveness of SiPP's features and performance. To sum up, SiPP demonstrates promising features that protect against intrusions and ensures forensic readiness.