System Design Applications Research Articles

Imaging of low Z masked with high Z (Pb, U) materials using 14 MeV neutron

An experimental study has been performed using 14 MeV neutrons for imaging of low Z material (particularly composed of C, H, O elements) masked with thick layers of dense and high Z materials. The experimental setup consists of a D-T neutron generator, a metallic collimator and an imaging system. The imaging system is designed with a polypropylene zinc sulphide scintillator screen integrated with a lens coupled 16-bit ICCD camera. Imaging capability of the system was investigated using iron test samples with holes and line pair features. The minimum hole size of 2 mm could be imaged at a contrast of 36% and a line of 2 mm width visible at a contrast of 24% indicating the system's resolution of ∼ mm. Low Z samples such as water (H2O) and polyethylene (C2H2) n placed behind thick layers of Pb (40 mm) and Uranium (35 mm), were imaged successfully. These images reveal the system's ability towards low Z material imaging in the presence of heavier metals. Good contrast images acquired at a lower neutron yield of ∼ 5 × 108 n/sec of D-T neutron generator has provided a possibility to realise fast neutron imaging having moderate resolution (∼ mm) with a smaller footprint and an economical system design for field applications.

Optimization Method for Space-Based Target Detection System Based on Background-Oriented Schlieren.

Currently, the visual detection of a target's shock flow field through background schlieren technology is a novel detection system. However, there are very few studies on the long-distance background schlieren imaging mechanism and its application in system design in the field of target detection. This paper proposes a design optimization method for space-based BOS detection system metrics. By establishing sensitivity evaluation models and image signal-to-noise ratio evaluation models for BOS detection systems, the influence of the different flight parameters and key parameters of BOS systems (detection spectral bands and spatial resolution) on target detection efficiency is explored. Furthermore, an optimization method based on the image signal-to-noise ratio of the BOS system and the overall metrics for specific scenarios are provided. The simulation results demonstrate that under satellite background images and speckle background images, the system metrics can detect and identify the schlieren of high-speed targets, with better applicability to disordered and complex real background images. This research contributes to advancing the development of high-speed target detection technology based on BOS.

Construction of a meteorological application system based on BDS ground-based augmentation network and water vapor products validation

The national Beidou Navigation Satellite System (BDS) ground-based augmentation network (BGAN) of China is constructed with the existing GNSS observation resources of industrial sectors and local governments, based on the concept of joint building and sharing with sustainable development. This study provides a detailed introduction to the design, construction and operation of a meteorological application system based on BGAN, and validation of its water vapor products. BDS and GPS real-time observation of atmospheric water vapor is achieved nationwide in China and multi-GNSS applications. Through the application of multi-GNSS data and validation of the water vapor products from 2018 to 2020, the accuracy of precipitable water vapor (PWV) derived from BDS only is equivalent to that from GPS only. The root mean square error (RMSE) between them is about 2 mm with high correlation coefficient. Based on radiosonde data, the validation is conducted with the products of BDS-PWV, GPS-PWV, and Combined-PWV derived with multi-GNSS of BDS and GPS. The error characteristics of the three products show a consistent trend over the months. The bias is relatively small. The RMSE of the three products is in the range of 2.18–2.73 mm. The BDS-PWV has the largest RMSE, followed by GPS-PWV, and Combined-PWV has the smallest RMSE.

Classification of mental workload using brain connectivity and machine learning on electroencephalogram data

Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In this paper, we propose innovative methods to assess mental workload from EEG data that use effective brain connectivity for the purpose of extracting features, a hierarchical feature selection algorithm to select the most significant features, and finally machine learning models. We have used the Simultaneous Task EEG Workload (STEW) dataset, an open-access collection of raw EEG data from 48 subjects. We extracted brain-effective connectivities by the direct directed transfer function and then selected the top 30 connectivities for each standard frequency band. Then we applied three feature selection algorithms (forward feature selection, Relief-F, and minimum-redundancy-maximum-relevance) on the top 150 features from all frequencies. Finally, we applied sevenfold cross-validation on four machine learning models (support vector machine (SVM), linear discriminant analysis, random forest, and decision tree). The results revealed that SVM as the machine learning model and forward feature selection as the feature selection method work better than others and could classify the mental workload levels with accuracy equal to 89.53% (± 1.36).

Air–Water Two-Phase Flow Dynamics Analysis in Complex U-Bend Systems through Numerical Modeling

This study aims to provide insights into the intricate interactions between gas and liquid phases within flow components, which are pivotal in various industrial sectors such as nuclear reactors, oil and gas pipelines, and thermal management systems. Employing the Eulerian–Eulerian approach, our computational model incorporates interphase relations, including drag and non-drag forces, to analyze phase distribution and velocities within a complex U-bend system. Comprising two horizontal-to-vertical bends and one vertical 180-degree elbow, the U-bend system’s behavior concerning bend geometry and airflow rates is scrutinized, highlighting their significant impact on multiphase flow dynamics. The study not only presents a detailed exposition of the numerical modeling techniques tailored for this complex geometry but also discusses the results obtained. Detailed analyses of local void fraction and phase velocities for each phase are provided. Furthermore, experimental validation enhances the reliability of our computational findings, with close agreement observed between computational and experimental results. Overall, the study underscores the efficacy of the Eulerian approach with interphase relations in capturing the complex behavior of the multiphase flow in U-bend systems, offering valuable insights for hydraulic system design and optimization in industrial applications.

Machine Learning-Driven Energy Harvesting and Storage System Design for IoT Applications in Smart Buildings.

The advent of Internet of Things (IoT) technologies has revolutionized the concept of smart buildings, integrating diverse sensors and devices for enhanced automation and efficiency. Avinash B. Raut, Energy harvesting and storage technologies have emerged as promising solutions to address the power requirements of IoT devices in smart buildings. This abstract provides a comprehensive overview of machine learning-driven energy harvesting and storage system design tailored specifically for IoT applications in smart buildings. Traditional energy management systems often face challenges such as suboptimal energy utilization, limited scalability, and lack of adaptability to dynamic environmental conditions. In contrast, machine learning techniques offer adaptive, data-driven solutions to optimize energy harvesting, storage, and distribution in smart buildings. [1] This paper explores various machine learning algorithms, including supervised learning, reinforcement learning, and deep learning, and their application in optimizing energy harvesting from ambient sources such as solar, kinetic, and thermal energy. Moreover, machine learning enables predictive energy demand modeling by analyzing historical data and environmental factors, thus enhancing the efficiency of energy storage and distribution systems. Real-world case studies and experimental results are presented to demonstrate the effectiveness and potential of machine learning-driven energy management systems in improving energy efficiency, reliability, and autonomy in IoT-enabled smart buildings DOI: https://doi.org/10.52783/tjjpt.v45.i02.6318

The Influence of Current Magnitudes and Profiles on the Sedimentation of Magnetorheological Fluids: An Experimental Work

Magnetorheological fluids (MRFs) are widely used for various kinds of controllable devices since their properties can be controlled by an external magnetic field. Despite many benefits of MRFs, such as fast response time, the sedimentation arisen due to the density mismatch of the compositions between iron particles and carrier oil is still one of bottlenecks to be resolved. Many studies on the sedimentation problem of MR fluids have been carried out considering appropriate additives, nanoparticles, and several carrier oils with different densities. However, a study on the effect of current magnitudes and profiles on the sedimentation is considerably rare. Therefore, this study experimentally investigates sedimentation behaviors due to different current magnitudes and different magnitude profiles such as square and sine waves in different diameters. The evaluation was performed by visual observation to obtain the sedimentation rate. It was found that the average sedimentation rate of the square type of current is slower compared to the sinusoidal type. It has also been identified that the higher intensity of the applied current results in a stronger electromagnetic field, which could slow down the sedimentation. The results achieved in this work can be effectively used to reduce particle sedimentation in the controller design of various application systems utilizing MRFs in which the controller generates a different magnitude and different profile of the external magnetic field.

Endo-Surgical Force Feedback System Design for Virtual Reality Applications in Medical Planning

Virtual reality (VR) applications for surgical planning and mentoring are currently becoming more widespread. Within these fields of applications, haptic systems are crucial to help the understanding of the feedback provided by the tissue during the interaction with the surgical tool. The accuracy of the VR scenario is related to many aspects, among them the ability of the haptic device to provide the force feedback and thus the adoption of proper characterization and modeling of the soft tissue behavior during deformation. This paper presents the current development concerning a VR environment to be equipped with a force feedback haptic device to simulate and experience clamping in colorectal surgery. The reaction at the clamp handle is provided starting from a FEA of the contact between the surgical tool and the tissue, coupled with the kinematic analysis of the mechanism. Connecting the virtual scenario to a microcontroller board, the reaction force is applied to the the haptic device, shaped as a clamping tool handle, so that the user may experience the tissue impedence during clamping. By simulations made through Simscape, a concept is evaluated according to some simulation paths that involve common scenarios of the virtual reality experience (such as collision, partial or total clamping operation). The novelty of the research regards the system design oriented to increase the accuracy of the soft tissue material behaviour through a preliminary off-line dedicated FEA investigation. Through Simulink simulations, the system design is verified so that the VR system set-up may be carried out. The results highlighted: (a) a good correspondence among the theoretical study of the reference kinematism that the haptic device must reproduce; (b) the implementation of a bilinear material model, derived off-line from FEA, is suitable to capture hyperelastic and geometric non-linearities of the soft tissue; (c) the feasibility of the open loop haptic control in accordance to the explored kinematism. The final goal of the research is to propose a system design approach able to tune the VR experince for teaching and mentoring through a in-house set-up easy to be tailored.

DESIGN AND APPLICATION OF LOW-COST FUSE CURRENT TESTER IN CARS

By measuring the voltage drop on the fuses in vehicles with a multimeter and using the fuse voltage drop cards, it is possible to determine the current drawn by the load based on the color, type, and current value listed on the fuse label. Arduino is a family of microcontroller development devices that are utilized in numerous digital system design applications. In this study, a fuse current analyzer is proposed for measuring the voltage drop across the fuses in a vehicle using an Arduino development board and obtaining the load current. The developed current analyzer can be utilized in automotive electricity and electronics courses, circuit studies, and for determining whether the fuse value on vehicles is sufficient and detecting load current leakage. The proposed system is tested on vehicle fuses, and an approximate 4% mean error rate is determined. This system can be used to perform tests in automotive electrical laboratories, or it can be implemented in the classroom to give students hands-on experience.

Penerapan Sistem Informasi Penjualan Baju Berbasis Android Sebagai Peningkatan Layanan Konsumen

The development of the internet world is highly expected for the present because more and more private companies, agencies, and educational institutions are very highly in need to serve as information services. In this study, we will try to make an Android-based Jersey Shirt Sales System Application that is addressed at the Berugak Jersey Lombok Store. The Berugak Jersey Lombok shop only uses social media and manuals in marketing its products. So, most of the consumers/customers come from the people around them and the social media they use. Currently, a business field is certainly less competitive if it does not have online marketing media such as e-commerce applications/websites. The existence of an application/website will be able to expand the reach in marketing the products sold at this store. The method used in the design and manufacture of this software is the waterfall method. The purpose of this final project research is to produce a sales system application design that can make it easier for consumers to place orders/transactions at the Berugak Jersey Lombok store and as a means to promote products to be more communicative and informative, to expand the marketing area and increase the number of consumers

Sistem Mitigasi Dan Adaptasi Bencana Dalam Menghadapi Potensi Acaman Mentawai Megathrust Sebagai Inovasi Teknologi Edukasi Kebencanaan

The urgency of this research is to provide an understanding and education system for disaster adaptation mitigation to communities living on the coast of West Sumatra and outside West Sumatra so that people are smarter and ready to face situations that occur when a disaster strikes. In this way the risk of greater loss of life can be avoided. The aim of this research is to produce a geographic educational information system for disaster adaptation mitigation in dealing with the potential threat of the Mentawai Megathrust based on WebGIS. The method used is four-D, namely Define, Design, Development, and Disseminate. The process of presenting the model is carried out through the define stage, namely finding data about predicted locations and impacts of disasters. The second stage of design is creating a geographic mitigation and disaster adaptation educational information system application design which contains evacuation route map designs, shelter location map designs and independent evacuation animations. The third stage of development is developing the system after testing and implementing the system, the disseminate stage is socializing the use of the application to people living on the coast of West Sumatra and disseminating research results through research results books.

T-UFF (Tracker stuff): application development for warehouse tracking

Era Society 5.0, requires the logistics agents to adapt and follow technology development to create supply chain efficiency. One of the ways is to apply the IoT to warehousing activities, creating a system design Warehouse Tracking app that works to increase order picking time efficiency. This system design application method is using the System Development Live Cycle (SDLC) and follows Object-oriented programming (OOP). This final result study is a system design application based on the IoT and QR codes for operating order-tracking goods in a warehouse. With this Tracker Stuff (T-UFF) app, the time it takes for order picking will be decreased so that it can create activity-efficient logistics for the company.

A pragmatic analysis of text-based sentiment analysis models from an analytical perspective

NLP sentiment analysis involves pre-processing, feature extraction, feature selection, sentiment classification, and post-processing. Pre-processing can include PoS tagging, stopword removal, language-specific missing work detection and correction, etc. Word2vec, N Gramme, term frequency (TF), distance measures, etc. can extract and select features. CNNs, DNNs, and other machine learning and deep learning models can be used for classification and post-processing. These models form a sentiment analysis engine, which can be assessed for accuracy, precision, recall, analysis delay, computational complexity, etc. The wide variation in algorithmic combination and performance makes it difficult for researchers to choose the best model(s) for their application. This task requires a lot of model testing and validation, which increases time-to-market and product cost. This text surveys recently proposed sentiment analysis models to reduce ambiguity and speed up system development. This survey characterises reviewed models’ nuances, advantages, limitations, and future research scopes to help readers choose the best models for their application deployment. These models’ delay, accuracy, precision, recall, computational complexity, and probable use are also compared in this text. This comparison lets readers choose the best model(s) for their application deployment and use them without validation. Reducing testing delay will improve model performance for system design and deployment for multiple sentiment analysis applications

Research on the intelligent education system design and local application practice of architecture major based on red resources

Abstract Red resources are an important part of China’s red culture, condensing red genes such as firm ideals and lofty revolutionary spirit, and have rich values of education. This paper combines red resources and Internet technology to design an intelligent parenting system for architecture majors and uses questionnaires to analyze the changes in students’ cognition of red resources and ideological quality level after the application of the parenting system. At the same time, we construct an evaluation index system for the implementation quality of the intelligent parenting system and obtain evaluation results by constructing an affiliation matrix between the indexes. Then analyze the correlation between the level of ideological quality and the quality of implementation of the parenting system. After the parenting system is applied, the mean value of each dimension of students’ ideological quality is distributed between 3.52 and 4.65 points, as evidenced by the application practice results. It has also been found that the average assessment score of the overall implementation quality of the intelligent parenting system for architecture majors based on red resources in colleges and universities is 3.94 points. The level of ideological quality and the implementation quality of the parenting system have a strong correlation. This paper lays the foundation for achieving the all-around integration of red resources and human education for architectural students and provides a reference basis for improving their ideological quality.

Analysis and Design of Disease Diagnosis Systems and Patient Medicine Recommendations with Forward Chaining Method

Technological developments have had a significant impact on many aspects of life, one of which is patient care in hospitals. Apart from using technology in patient care, technology also provides access to effective and efficient information storage and management to record patient data for treatment purposes. In outpatient services at hospitals, there are often complaints from employees regarding the health recording system which is less than optimal. Therefore, a system that manages disease diagnoses and patient treatment recommendations is something that needs to be developed, with the hope of speeding up the performance of medical personnel, so that they can help more patients who need help. The application system design aims to help manage information related to disease diagnosis and patient drug recommendations, where this system uses Forward Chaining to assist users in identifying diseases and prescribing drugs according to the diagnosis the patient is complaining about. By using the Forward Chaining methodology, medical personnel are able to obtain patient diagnosis results more quickly. The result is an application that can help medical personnel in serving outpatients from registration, examination, to exchanging medicines. This application has been tested using black-box testing involving several respondents, where respondents can feel that this application works well and helps hospital staff in examining patients.

Application of decision system design based on improved association rules in rural social security

Application of decision system design based on improved association rules in rural social security

“Cumulative effect” of second harmonic Lamb waves in a lossy plate

The second harmonic Lamb waves have high sensitivity to microstructural defects in materials and are therefore promising for incipient damage detection and monitoring of thin-walled structures. Existing studies have shown that the second harmonic Lamb waves can be cumulative with increasing propagation distance under the internal resonance conditions, which is conducive to nonlinear wave measurements in view of structural health monitoring. However, when propagating in a lossy structure with damping, the cumulative properties of the second harmonic Lamb waves are affected by energy dissipation and thus need to be re-examined. In this paper, a method for predicting the cumulative characteristics of second harmonic Lamb waves in damped plates is proposed. Instead of using material damping parameters which are difficult to obtain in practice, the proposed method relies on the attenuation patterns of Lamb waves at fundamental and double frequencies while taking into account the influence of the wave beam divergence. The proposed methodology is validated by finite element simulations and experiments. The results show that the cumulative second harmonic Lamb waves in the damped plate tend to increase and then decrease, and a “sweet” zone of relatively large amplitude can be predicted using the proposed method. The elucidation of the cumulative characteristics of the second harmonic Lamb waves provides guidance for effective system design for structural damage detection and monitoring applications.

SISTEM INFORMASI PENGELOLAAN KEGIATAN PENGAJIAN ANTARA MAGHRIB DAN ISYA (STUDI KASUS : KELURAHAN PENYENGAT RENDAH KOTA JAMBI )

The current problem is the reporting of data on maghrib and isha recitation activities and the non-exposure of maghrib and isha recitation activities to the wider community so that many people do not know the maghrib and isha recitation activities. To design a web-based information system so that data processing can be effective, efficient and computerized that can be used by the data processing of Maghrib and Isya Studies Teachers (PAMI) in Penyengat Low Village to facilitate the process of managing teacher data. The research approach used by the author is qualitative research. The system development method used by the author is the waterfall model. The information system is designed using Visual Studio Code tools and uses PHP programming language with Codeigniter framework and uses MySQl database. For this reason, the Jambi City Low Stinger Subdistrict Office, specifically in the Social Welfare Office, really needs a tool that is more efficient and effective in managing data on maghrib and isya recitation activities by inputting data and displaying reports that can be printed out. With the design of this system, the Social Welfare Office is helped in the process of obtaining information about teacher data, mosque data, activity data, RT data, and student data. In making an information system design application for data management of maghrib and isya activities of Penyengat Low Village Jambi City, the author uses the Visual Studio Code application with PHP programming language for designing the application.

Digital Transformation of the Management Information System (MIS) at Pondok AnNahdloh, Selangor, Malaysia

The role of information technology in enhancing institutional quality, particularly at Pondok AnNahdloh in Malaysia, cannot be underestimated. Information technology is vital in elevating an institution's standards by improving efficiency, communication, decision-making, security, and innovation. Institutions that effectively embrace information technology can optimize their operations and achieve higher levels of quality, resulting in enhanced competitiveness and desired outcomes. The research's primary objective is to describe the Education Management Information System (MIS) for educational documents at Pondok AnNahdloh in Malaysia, which is up-to-date and integrated. The research methodology involves focus group discussions to identify administrative activities, system application design, system testing, improvement, operator training, limited user testing, launching, and evaluation. Data collection methods include field observations, interviews, and activity documentation. Data analysis follows the theory of Miles and Huberman. The research findings reveal the successful implementation of MIS, leading to up-to-date and integrated educational document data, both in terms of input and processes. Adopting information technology in the academic environment through this system ensures efficient and accurate access, management, and utilization of essential data and information in the educational process. With this system in place, improvements in activity quality are expected, positively impacting community empowerment and national development.

Warehouse Management System Design at PT XYZ

The warehouse is one of the most important parts of a company. Ineffective warehousing processes can disrupt warehouse operations. Recording warehouse transactions that are done manually will require checking one by one on the hardcopy form that has been stored. Therefore, this internship program aims to improve the performance of warehousing operations at PT XYZ. The method used in the analysis is data collection and application system design using the prototype method. The data is taken based on the results of interviews and observations in the warehouse. This activity creates a web-based warehouse management system application to help control incoming and outgoing inventory. The system built makes it easy for administrators to see the number of items made for each event. The results of black box testing show that the application has 100% functionality. The test results illustrate that the application functions properly according to user needs and has been accepted by PT XYZ