Insurance Management with Premium Prediction

Insurance Management with Premium Prediction system is a web application which is developed for tracking the details of the insurance policy, customer details and company details. This web site is an online insurance Analysis and information management system that provides easy access to information regarding the people and resources of insurance. Users can view their own personal details when login into the Policy Holder module. This project is useful for any kind of insurance company to manage the insurance details, to sanction the insurance for customers, process the insurance policy details and all kinds of insurance processes online. The Insurance management system is a complete solution for organizations, which need to manage insurance for their vehicles, equipment, buildings, and other resources. This insurance management website has facilities like search tools for insurance awareness articles, guidelines, illustrations through images for visitors. This insurance management system can efficiently manage the company, records, provides instant access and one that improves productivity. In this online process the user enters into the website it will show details about insurance and its types, also it will show the details about different duration schemes to the corresponding insurance type or insurance policy. The main objective of the developed system is to allow admin users to register insured persons with their name, date of birth, residence address, medical history and also policy details.

Powder Spread Process Monitoring in Polymer Laser Sintering and its Influences on Part Properties

Confidence in additive manufacturing technologies is directly related to the predictability of part properties, which is influenced by several factors. To gain confidence, online process monitoring with dedicated and reliable feedback is desirable for every process. In this project, a powder bed monitoring system was developed as a retrofit solution for the EOS P3 laser sintering machines. A high-resolution camera records each layer, which is analyzed by a Region-Based Convolutional Neural Network (Mask R-CNN). Over 2500 images were annotated and classified to train the network in detecting defects in the powder bed at a very high level. Each defect is checked for intersection with exposure areas. To distinguish between acceptable imperfections and critical defects that lead to part rejection, the impact of these imperfections on part properties is investigated.

A Novel Prediction Process of the Remaining Useful Life of Electric Vehicle Battery Using Real-World Data

In modern society, environmental sustainability is always a top priority, and thus electric vehicles (EVs) equipped with lithium-ion batteries are becoming more and more popular. As a key component of EVs, the remaining useful life of battery directly affects the demand of the EV supply chain. Accurate prediction of the remaining useful life (RUL) benefits not only EV users but also the battery inventory management. There are many existing methods to predict RUL based on state of health (SOH), but few of them are suitable for real-world data. There are several difficulties: (1) battery capacity is not easy to obtain in the real world; (2) most of these methods use the individual data for each battery, and the computing processes are difficult to perform in the cloud; (3) there is a lack of approaches for real-time SOH estimating and RUL predicting. This paper adopts several statistical methods to perform the prediction and compars the results of different models on experimental data (NASA dataset). Then, real-world data were implemented for an online process of RUL prediction. The main finding of this research is that the required CPU time was short enough to meet the daily usage after the real-world data was implemented for an online process of RUL prediction. The feasibility and precision of the prediction model can help to support the frequency control in power systems.

Peran Orang Tua Dalam Proses Pembelajaran Dalam Jaringan di Masa Pandemi Covid-19

Pandemi Covid-19 telah berlangsung selama 1 tahun. Sejak saat itu, proses kegiatan belajar mengajar pun mengalami perubahan. Proses belajar Dalam Jaringan (Daring) menjadi solusi dari pemerintah untuk menekan angka penyebaran dari virus tersebut. Akan tetap pada praktiknya, guru, murid serta orang tua khususnya merasa kewalahan dalam melaksanakan proses Daring tersebut. Penelitian ini bertujuan untuk mengetahui peran orang tua dalam proses belajar Daring di masa Covid-19 serta faktor yang mempengaruhi pembelajaran daring bagi anak. Penelitian ini menggunakan metode studi kasus dengan menggunakan analisa kualitatif deskriptif. Penelitian ini dilakukan kepada 10 orang tua (3 ayah dan 7 ibu). Hasil menunjukkan bahwa orang tua memiliki peran ekstra selama masa pandemi berlangsung. Adapun peran orang tua dalam proses belajar daring antara lain mengawasi anak selama menggunakan gadget, mendampingi anak mengerjakan tugas sekolah, menjalin komunikasi yang baik dengan anak, memberikan edukasi serta menciptakan lingkungan bersih aman dan nyaman bagi anak. Kata Kunci : Peran Orang Tua; Masa Pandemi Covid-19; ABSTRACT The Covid-19 pandemic has been going on for 1 year. Since then, the teaching and learning process has changed. The online learning process is a solution from the government to reduce the spread of the virus. However, in practice, teachers, students and parents in particular feel overwhelmed in carrying out the Online process. This study aims to determine the role of parents in the online learning process during the Covid-19 period and the factors that influence online learning for children. This research uses case study method using descriptive qualitative analysis. This research was conducted to 10 parents (3 fathers and 7 mothers). The results show that parents have an extra role during the pandemic. The role of parents in the online learning process includes supervising children while using gadgets, assisting children with school assignments, establishing good communication with children, providing education and creating a clean, safe and comfortable environment for children. Keywords : The Role of Parents; The Covid-19 Pandemi Period;

An Intelligent Process Fault Diagnosis System Based on Neural Networks and Andrews Plot

This paper proposes a neural network-based process fault diagnosis system with Andrews plot for information pre-processing to enhance the performance of online process fault diagnosis. By using features extracted from Andrews plot as the inputs to a neural network, as a classifier, the diagnosis speed and reliability are improved. A method for determining the important features in the Andrews function is proposed. The proposed fault diagnosis system is applied to a simulated continuous stirred tank reactor process and is compared with two conventional neural network-based fault diagnosis systems: scheme B where the monitored measurements are directly fed to a neural network after scaling and scheme C where the monitored measurements are converted to qualitative trend data before feeding to a neural network. Of all the considered faults, the proposed fault diagnosis system diagnosed the abrupt faults on average 5.45 s and 2.66 s earlier than schemes B and C, respectively and diagnosed the incipient faults on average 13.82 s and 5.09 s earlier than schemes B and C, respectively. The results reveal that Andrews plot method utilized in online process monitoring has a great potential in industrial process monitoring.

Online process monitoring of a batch distillation by medium field NMR spectroscopy

Medium field NMR spectrometers are attractive for online process monitoring. Therefore, in the present work, a single-stage laboratory batch distillation still was coupled online with a medium field NMR spectrometer. This enables quantitative non-invasive measurements without calibration. The technique was used for studying isobaric and isothermal residue curves in two ternary systems: (dimethyl sulfoxide + acetonitrile + ethyl formate) and (ethyl acetate + acetone + diethyl ether) and boiling curves and high-boiling azeotropes in two binary systems: (acetic acid + pyridine) and (methanol + diethylamine). The results of the online NMR spectroscopic analysis were compared to results from offline analysis as well as to results from thermodynamic modeling using NRTL parameters that were parametrized with literature data. The new method for online process monitoring gives reliable results and is well-suited for fast and robust measurements of residue curves.

The impact of online learning on students

Online education has been introduced as a tool in the learning process in the majority of international universities worldwide. The term “e-learning” is defined as “any learning that involves using the internet or intranet. In this research, we tried the check the impact of online learning upon the students of Lebanese French University Erbil, Kurdistan region Iraq. The Objectives of the study are multi-folded. Firstly, to evaluate the influence of online learning upon the performance of students and secondly, to test the motivation of online learning towards the students. For this purpose, a detailed questionnaire was developed in order to get the response of the students. The questionnaire was built up and distributed to almost eighty respondents in which we got back a perfect response in complete shape only fifty. Graph analysis has been used in order to present the response of the respondent. Mix response was recorded in which slightly negative response was in high portion. Furthermore, results showed that 60 % of respondents answered they are not happy with the online learning process and they want to have a traditional learning process that is on campus. Similarly, in each question, an extraordinary negative response toward online learning is recorded such as 76 % respondents said that they are not satisfied with this implementation of online learning. Also, they are facing hurdles and 58 % of people showed their response one of the big challenges toward online learning is a poor internet connection. 60% claimed that the instructor is not helping them to understand this whole process as a tool of online learning. The possible reason that was claimed from respondents are following: (i)This online process is first time they are interacting with,(ii) Lack of training of such online tools for the online learning process, (iii) once any student is facing trouble while this online process less support is available from the department and technical staff of the university