Implementation Of Real System Research Articles

Real Property Tax Administration System Implementation and Clients’ Satisfaction in Calamba City Barangays

The study attempted to investigate real estate owners' views on computerizing the Real Property Tax Administration in Calamba City's barangays. Transparency, accountability, involvement, and compliance were critical due to the high rate of delinquent taxpayers. The study analyzed the connection between customer satisfaction and implementation level. A questionnaire was used to collect 140 responses. Mean, correlation, and Likert scale were used to analyze the data. The main findings of the study revealed that real estate owners in barangay had a positive view of the computerization of real estate tax administration. The combined percentage of "very satisfactory" and "satisfactory" responses was consistent in all key areas. This indicates that the public perceived the local government's services as proactive and customer-centric. Since the variables were inter-connected in a way, this study proved that the implementation of the Real Property Tax System and the Client’s Satisfaction level in Calamba City did meet the expected outcome of the research. Respondents positively matched all the questions, which led to a satisfactory result or more, and projected the implementation of the system. The Sub-Variables Responsiveness, Reliability, and Assurance provided a lot of positive results in this research; the answers of the respondents created an idea of advancing the proposal of this study. Despite the high satisfaction rate, there is always room for improvement. Therefore, the output of the study recommended an action plan to enhance the ongoing initiative, develop innovative approaches, and boost the confidence and productivity of barangay workers.

ABC REAL ESTATE MANAGEMENT SYSTEM

Abstract— This thesis presents the development and implementation of the ABC Real Estate Management System, a web-based application built using PHP and MySQL. The system is designed to streamline property management for real estate agencies, property managers, and individual landlords. It offers a user-friendly interface that caters to two primary user groups: general users and administrators. Users can search for properties based on location and features, utilize a loan calculator for financial planning, and express interest in properties. Administrators have comprehensive control over the system, including managing user accounts, property listings, and potentially real estate agents. The system emphasizes three key aspects: improved user experience, enhanced efficiency, and increased security. User-friendliness ensures that both users and admins can interact with the system intuitively. Efficiency is achieved through quick property discovery and streamlined property management tasks. Security is reinforced by implementing role-based access control, ensuring that only authorized users can access and modify sensitive data. By leveraging PHP and MySQL, the ABC Real Estate Management System addresses common challenges in property management, fostering a more efficient, secure, and user-friendly experience for both property seekers and managers. This thesis provides a detailed analysis of the system’s design, development, and potential impact on the real estate industry. Keywords: Real estate management system (REMS), Efficiency in property management, Streamlining property operations.

Neuroadaptive Control for Active Suspension Systems With Time-Varying Motion Constraints: A Feasibility-Condition-Free Method.

This work is devoted to solving the control problem of vehicle active suspension systems (ASSs) subject to time-varying dynamic constraints. An adaptive control scheme based on nonlinear state-dependent function (NSDF) is proposed to stabilize the vertical displacement of the vehicle body. It provides a reliable guarantee of driving safety, ride comfort, and operational stability. It is commonly known that in the existing work, either the state constraints are ignored which may reduce the stability and safety of the system, or the virtual controller is subjected to some feasibility conditions affecting real system implementation. In this work, it is the first attempt to directly deal with the time-varying displacement and velocity of the vehicle constraints in ASSs without involving any specific feasibility conditions. A novel coordinate transformation based on the NSDF is introduced and integrated into each step of the backstepping design. Thus, the proposed control scheme not only adapts to the time-varying motion (time-varying vertical displacement and velocity) constraints, but also eliminates the feasibility conditions of the virtual controller without the difficulty of obtaining system parameters. Finally, the control scheme for ASSs used in this work is compared with existing control schemes in order to demonstrate its superiority and rationality.

Implementation of Digital Twin and Real Production System to Address Actual and Future Challenges in Assembly Technology

Increasing volatility in manufacturing and rising sustainability requirements demand more efficient processes in production, especially in employee qualification and engineering during development and on-site adjustments before and after the start of production. One possible solution is using digital twins for virtual commissioning, which can speed up engineering processes, qualify employees, and save valuable resources. To solve these challenges, it is necessary to identify promising approaches for using the digital twin and virtual commissioning. Furthermore, creating an environment where these approaches can be optimally explored is essential. This paper presents promising research approaches and demonstrates the development of an assembly process and a production system with a digital twin designed to explore these aspects. The presented system is an interlinked production system for assembling an actual industrial product. It includes different levels of human–robot interaction and automation, which can be implemented virtually in the digital twin.

FaaSDeliver: Cost-Efficient and QoS-Aware Function Delivery in Computing Continuum

Serverless Function-as-a-Service (FaaS) is a rapidly growing computing paradigm in the cloud era. To provide rapid service response and save network bandwidth, traditional cloud-based FaaS platforms have been extended to the edge. However, launching functions in a heterogeneous computing continuum (HCC) that includes the cloud, fog, and the edge brings new challenges: determining <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">where functions should be delivered and how many resources should be allocated.</i> To optimize the cost of running functions in the HCC, we propose an adaptive and efficient function delivery engine, named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FaaSDeliver</i> , which automatically unearths a cost-efficient function delivery policy (FDP) for each function, including the FaaS platform selection and resource allocation. Real system implementation and evaluations in a practical HCC demonstrate that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FaaSDeliver</i> can unearth the most cost-efficient FDPs from among 180,200 FDPs after a few trials. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FaaSDeliver</i> reduces the average cost of function execution from 38% to 78% compared to some state-of-the-art approaches.

Investigation on the performance of an active noise control window system mounted on the top-hung window of a residential room

Urban noise mitigation experiment through active noise control window is not commonly carried out in in situ urban setting. This paper outlines our experimental settings of performing active noise control across the open aperture of the top-hung window frame in a dormitory room. A multi-channel adaptive filtered-x least mean square method is implemented in real-time. Experiments and analyses are carried out to investigate how the noise reduction performance of this active noise control window system is affected by the number of reference microphones, the distance between reference microphones and secondary sources, and the distributions of error microphones under practical restrictions of the real system implementation. Variation of the secondary path estimation is another important consideration in active noise control system design. Real-time experiments are carried out to investigate the sensitivity of the ANC window system over the secondary path variation caused by varying window opening status, and whether a generalised secondary path measured in one window opening setting can be applied to other window opening conditions.

A novel comprehensive optimal PMU placement considering practical issues in design and implementation of a wide-area measurement system

• Several WAMS-based applications are considered in the OPP problem. • Concept of the line-wise observability is presented. • Observability of multi-TSO power systems in the OPP problem is investigated • The proposed OPP model is originally a MILP one and its global solution can be easily found. Since phasor measurement units (PMUs) are increasingly installed in power systems, many research works have investigated the optimal PMU placement (OPP) problem with the sake of maximizing observability over the power grid, while minimizing the cost of purchasing PMUs. However, there are still some practical challenges that have not been considered in the previous research studies, and are needed to be addressed for a real wide-area measurement system (WAMS) implementation. In this paper, a comprehensive OPP model is proposed which employs a set of basic and novel constraints for a WAMS design. In this regard, the line-wise observability concept is proposed for the first time to consider the requirements of observability for a range of WAMS-based applications such as restoration management, model validation of power system components, and dynamic line rating (DLR) monitoring. In addition, observability constraints for multi-transmission system operator (multi-TSO) power systems that are operated by different legal entities are provided, which can considerably affect the OPP result. The proposed model is formulated based on a mixed-integer linear programming (MILP) formulation which enables the optimization problem to be solved easily and effectively by existing commercial optimization tools, without any need for linearization. The performance of the proposed OPP model is first verified through simulation results on an 86-bus real power system. Then, simulations are applied to IEEE 118-bus and 300-bus test systems, to certify the performance of the proposed model in comparison with other OPPs in the literature.

Systematic Review on Deep Reinforcement Learning-Based Energy Management for Different Building Types

Owing to the high energy demand of buildings, which accounted for 36% of the global share in 2020, they are one of the core targets for energy-efficiency research and regulations. Hence, coupled with the increasing complexity of decentralized power grids and high renewable energy penetration, the inception of smart buildings is becoming increasingly urgent. Data-driven building energy management systems (BEMS) based on deep reinforcement learning (DRL) have attracted significant research interest, particularly in recent years, primarily owing to their ability to overcome many of the challenges faced by conventional control methods related to real-time building modelling, multi-objective optimization, and the generalization of BEMS for efficient wide deployment. A PRISMA-based systematic assessment of a large database of 470 papers was conducted to review recent advancements in DRL-based BEMS for different building types, their research directions, and knowledge gaps. Five building types were identified: residential, offices, educational, data centres, and other commercial buildings. Their comparative analysis was conducted based on the types of appliances and systems controlled by the BEMS, renewable energy integration, DR, and unique system objectives other than energy, such as cost, and comfort. Moreover, it is worth considering that only approximately 11% of the recent research considers real system implementations.

Foreword to the Special Section on Information and Communication Technologies (ICT) for a New Space Vision

The main objective of this special is to offer the interested audience an overview of the most recent advancements in information and communication technologies that can enable the “New Space” vision, turning it from a conceptual design philosophy to real system implementation.

Federated Learning for the Internet of Things: Applications, Challenges, and Opportunities

Billions of IoT devices will be deployed in the near future, taking advantage of faster Internet speed and the possibility of orders of magnitude more endpoints brought by 5G/6G. With the growth of IoT devices, vast quantities of data that may contain users' private information will be generated. The high communication and storage costs, mixed with privacy concerns, will increasingly challenge the traditional eco-system of centralized over-the-cloud learning and processing for IoT platforms. Federated learning (FL) has emerged as the most promising alternative approach to this problem. In FL, training data-driven machine learning models is an act of collaboration between multiple clients without requiring the data to be brought to a central point, hence alleviating communication and storage costs and providing a great degree of user-level privacy. However, there are still some challenges existing in the real FL system implementation on IoT networks. In this article, we discuss the opportunities and challenges of FL in IoT platforms, as well as how it can enable diverse IoT applications. In particular, we identify and discuss seven critical challenges of FL in IoT platforms and highlight some recent promising approaches toward addressing them.

Power quality assessment and power quality improvement in hospital facility

The power quality (PQ) assessment is carried out at a KIMS hospital facility by conducting the harmonic study as per IEEE3002.8 guidelines. As per PQ data obtained, the hospital facility is experiencing a significant number of PQ disturbances and violating IEEE519 limits for PQ in special application systems. It is found necessary to use a compensator for PQ improvement. A cost-effective compensator, DVR, is designed to improve PQ in the hospital facility. The designed DVR controller model is tested in the RT-LAB hardware-in-the-loop real-time simulation platform using OPAL-RT with multicore FPGA processors to validate the compatibility of the designed controller to be applied for real system implementation. Thus, PQ assessment helps in the appropriate design of compensating controllers to suit practicality. A comparative study of choice of designed DVR controllers such as PI, Fuzzy, ANN, ANFIS-PI optimised and ANFIS-Fuzzy optimised controllers tested in real-time for different cases and for different loading conditions are summarised.

Constellation Design for Deep Joint Source-Channel Coding

Deep learning-based joint source-channel coding (JSCC) has shown excellent performance in image and feature transmission. However, the output values of the JSCC encoder are continuous, which makes the constellation of modulation complex and dense. It is hard and expensive to design radio frequency chains for transmitting such full-resolution constellation points. In this paper, two methods of mapping the full-resolution constellation to finite constellation are proposed for real system implementation. The constellation mapping results of the proposed methods correspond to regular constellation and irregular constellation, respectively. We apply the methods to existing deep JSCC models and evaluate them on AWGN channels with different signal-to-noise ratios (SNRs). Experimental results show that the proposed methods outperform the traditional uniform quadrature amplitude modulation (QAM) constellation mapping method by only adding a few additional parameters.

Event Detection for Distributed Acoustic Sensing: Combining Knowledge-Based, Classical Machine Learning, and Deep Learning Approaches.

Distributed Acoustic Sensing (DAS) is a promising new technology for pipeline monitoring and protection. However, a big challenge is distinguishing between relevant events, like intrusion by an excavator near the pipeline, and interference, like land machines. This paper investigates whether it is possible to achieve adequate detection accuracy with classic machine learning algorithms using simulations and real system implementation. Then, we compare classical machine learning with a deep learning approach and analyze the advantages and disadvantages of both approaches. Although acceptable performance can be achieved with both approaches, preliminary results show that deep learning is the more promising approach, eliminating the need for laborious feature extraction and offering a six times lower event detection delay and twelve times lower execution time. However, we achieved the best results by combining deep learning with the knowledge-based and classical machine learning approaches. At the end of this manuscript, we propose general guidelines for efficient system design combining knowledge-based, classical machine learning, and deep learning approaches.

Design and Implementation of Real Time Data Processing System Based on Spark Streaming

With the rapid development of Internet technology, people have more abundant ways to obtain information through the Internet.More and more information is spread in the network, which will produce a large amount of data.The big data type is more complicated. In order to implement data implementation, the industry is generally combined with different data types and business scenes, special development and design of different processing subsystems.This method has a large research cost and learning cost, and a unified computing system platform is relatively lacking, which further makes developers unable to maintain and expand the system formed by different sets of technology systems.Based on the above situation, this paper designs a universal real-time data analysis and processing system based on Spark Streaming.

Optimal ANC System Arrangement Based on Complete System Analyses Applying COSMOL Multiphysics and Matlab

In real active noise control system implementation, the arrangement of secondary sources and error microphones have significant effect on the performance of the system. Analytical and experimental ways are usually combined to determine the best system layout. In this paper, we use COSMOL Multiphysics to accurately model the acoustic environment in enclosures with the real measured dimensions and parameters. Matlab is adopted to simulate the basic active noise control algorithms. The combined simulation results are used to decide the optimal system layout of the real ANC system. Experiments are conducted on a real ANC system with EVAL-21489-EZLITE from ADI to validate the analyzed and simulation results.

Air Quality Monitoring System Based on IoT

The system presented in this paper is an advanced real-time air quality reporting system supported by the Internet of Things (IoT) architecture. Air quality in an environment heavily affected by the community’s state in a region may affect human, animal, and plant safety. Therefore, air quality levels in a region should be tracked regularly. This study aimed to build an IoT-based air quality system to evaluate air quality conditions in a given region. The device can track the air rates of different substances including O3, SO2, CO and particulate matter using sensors. Read the Arduino microcontroller sensor detail. The data sent to the cloud system then accessed the cloud system through a WIFI module on Arduino. The effects of the tracking are available through a cloud Site page. The current model is implemented successfully and can be deployed for real system implementations.

Design and Implementation of Real Time Monitoring System of Textile Equipment Based on MQTT

At present, with the progress of network information technology, the idea of intelligent factory and intelligent manufacturing is imperative. It is imperative to realize intellectualization and informatization in traditional manufacturing plants. According to the intelligentized demand of textile equipment, the real-time monitoring of the spindle status of the textile machine is designed and realized, and the functions of the real-time statistics of the operation efficiency, the number of broken ends, the spindle status of the textile machine, the statistical report and so on are made in real time. It has achieved remote and efficient production management and fault detection. It effectively reduces the cost of manual operation and maintenance, and improves the intelligence level of textile mills.

Practical Study and Implementation of an Isolated Word Speech Recognition System.(Dept.E)

The art and science of speech recognition have been advanced to the state where it is now possible to communicate reliably with a machine by speaking to it in a disciplined manner using a vocabulary of moderate size. It is the purpose of this paper to present a hardware implementation of a simple real time speech recognition system for isolated words. The system determines the energy of the spoken word through a bank of four channels band pass filters. The output from each filter is passed through a rectifier followed by a low pass filter to provide an average level which is proportional to the total signal energy within the particular filter band. The energy measurements from each channel is then passed to a personal computer where a recognition algorithm program is then executed. The program detects the starting and ending points of each spoken word. compares the energy features with the reference stored in the library, and chooses the most close pattern that matches the pattern of the spoken word. Results from experiments conducted by simulation and by the hardware prototype using Arabic speech show that the system provides recognition score between 76 % and 94%.

Analysis of algorithms and implementation of real time speaker identification system

The article describes an implementing a real time speaker identification system by voice for embedded and general purpose computers. A review and analysis of existing speaker identification algorithms are made. The speaker's input speech is recorded in the system, go through the preprocessing stage, extract features and voice parameters for further identification. To recognize the speaker by voice parameters, the Vector quantization and Hidden Markov model algorithms are used. The VQ and HMM algorithms showed recognition accuracy of 96% and 98%, respectively.

Implementation of real estate contract system using zero knowledge proof algorithm based blockchain

A real estate contract is a high-risk contract with a large amount of money, and there are many problems in the risk and reliability of fraud. In particular, online contracts have low reliability and high risk. If you can manage information on these issues and prevent forgery and duplication of contract information, you can maintain low cost and high efficiency. Blockchain technology is being used as an alternative to the enormous cost and reliability issues associated with offline real estate contracts. When blockchain technology is applied to an online contract management system, reliability and scalability are efficient and confidentiality can be ensured. However, as real estate transactions using blockchain technology increase online, problems arise in scalability. Therefore, in this paper, we implemented an Ethereum-based online real estate contract system that solved the scalability using the zero-knowledge proof algorithm. The real estate contract system enables online contract management and discrimination of contract forgery through blockchain. In particular, it was possible to prevent fraud until the contract was concluded and the contract was terminated.