Feedback Analysis System Research Articles

PSFAS: Progressive Student Feedback Analysis System for improved teaching learning with intelligent processing of open-responses

PSFAS: Progressive Student Feedback Analysis System for improved teaching learning with intelligent processing of open-responses

GAN Base feedback analysis system for industrial IOT networks

The internet, like automated tools, has grown to better our daily lives. Interacting IoT products and cyber-physical systems. Generative Adversarial Network's (GANs') generator and discriminator may have different inputs, allowing feedback in supervised models. AI systems use neural networks, and adversarial networks analyse neural network feedback. Cyber-physical production systems (CPPS) herald intelligent manufacturing . CPPS may launch cross-domain attacks since the virtual and real worlds are interwoven. This project addresses enhanced Cyber-Physical System(CPS) feedback structure for Denial-of-Service (DoS) defence . Comparing sensor-controller and controller-to-actuator DoS attack channels shows a swapping system modelling solution for the CPS's complex response feedback. Because of the differential in bandwidth between the two channels and the suspects' limited energy, one person can only launch so many DoS assaults. DoS attacks are old and widespread. Create a layered switching paradigm that employs packet-based transfer techniques to prevent assaults. The discriminator's probability may be used to assess whether feedback samples came from real or fictional data. Cognitive feedback can assess GA feedback data.

Faculty Feedback Analysis System with Efficient Graph-Based Reports

Feedback plays a vital role in the uprising of any educational institute. With the help of the proper Feedback analysis system the growth rate of the Institute will display an Inclination in its performance. For reputed Institutions which have large number of students, it is not easy to manage a proper feedback system manually, hence there is need for an automation in Faculty Feedback System Faculty Feedback Analysis System is a dynamic web application which is aimed to be anonymous while taking feedback from students and generate efficient and effective reports as prescribed by the NBA & UGC. The registered students of that particular institute can give the feedback of their faculty of present semester. While giving feedback, the student can see only his/her respective subjects and subject handling faculty names. The feedback form also shows Open Elective and Professional Elective subjects of the students based on their chosen choice. This system also provides the facility to the faculty to check their feedback at any point of time after the feedback is taken. It makes it easier for admin to view reports of all the previously taken feedback. This application is designed in such a way that it can be deployed in real time on a cloud server and can be accessed through smart phones and any small computing devices. All the passwords are encrypted with custom made encryption algorithm to secure the system from all the possible corners. The application has a ready and not ready state which will allow or not allow students to give feedback and will be managed from the admin panel which is beautifully created to be as user- friendly as it can get.The feedback form is also designed in two different models one for large screens where photos of the faculties are also presented with names and another for Smart phones which has its own beautiful custom made design-build for it. Overall performance wise it has been improved over the development cycle starting from version 1.0 to version 4.0.Various types of reports can be generated from the given feedback based on the admin requirements

Opinion mining technique for developing student feedback analysis system using lexicon-based approach (OMFeedback)

Online assessment systems are increasingly utilised as an evaluation tool for measuring the performance of lecturers in Institutions of Higher Learning (IHLs). These systems commonly have a set of questionnaires comprised of quantitative and qualitative questions. Most online lecturer teaching assessment systems are focused on the quantitative part of the questionnaire since it is easy to analyse. On the contrary, the qualitative part, which requires students’ opinions, is often omitted and neglected, and the level of opinion results are excluded. This is because students’ opinions are usually in the form of unstructured texts, which makes it hard to manually analyse all the feedback. To address this problem, a system that could automatically analyse students’ feedback (known as OMFeedback) was developed. This system applies an opinion mining technique to reveal the teaching assessment results, which are underpinned by a lexicon-based approach. Lexicon-based is a common textual data quantification method that can analyse the sentiment tendency of a student’s feedback. A database of English sentiment words, known as the Vader Lexicon, was utilised as a lexical source to determine the polarity of words. By analysing these sentiment words, which included intensifier words extracted from students’ feedback, this system was able to determine the results for the lecturer teaching assessment by describing the level of positive, negative, or neutral opinions. This system was also able to process new features, such as capitalised words and emoji characters to enhance the opinion results. Ultimately, this newly developed system will provide useful information to IHLs for improving lecturers’ teaching skills and course materials.

Implementation of Support Vector Machine Technique in Feedback Analysis System

E-commerce is very popular and interactive these days. Industries that produce new products and selling them on the Web often ask their customers to review the products which they have purchased. These reviews help both i.e. customers as well as producers. Producers get the idea from reviews about how their customers feel about the product which they have purchased and customers who want purchase the product read these reviews and take decision. As the number of responses are available very large in number, manually organizing large set of reviews/responses into required categories and analyzing them is time consuming, expensive and is often not feasible. So automated text classification is done to overcome these constraints. Various techniques can be used for automatic text classification. In this paper Support Vector Machine (SVM) which is a supervised learning technique is used in feedback analysis system which accepts the responses given by students as input preprocess it and lastly applies term weighting algorithm. After applying term weighting algorithm it displays analysis to the particular faculty. General Terms Web, E-commerce, Responses, Techniques

Opinion Analysis Using Domain Ontology for Implementing Natural Language Based Feedback System

This paper proposes a natural language based feedback analysis system that extracts semantic relations from feedback data in order to map it with the domain ontology. After pre-processing a set of words or phrases are extracted from the input data. The data are analyzed semantically to interpret its meaning. This meaning is in an intermediate form which is then mapped to the terms defined in the ontology using similarity function. The opinion analysis of the semantic data is carried out for measuring the polarity of the feedback by the use of opinion analysis method. The system is evaluated on the input feedback data.

Design of Multi-Parameter Psychophysiological Feedback Analysis System

In order to supply an effective and reliable tool for the Psychology research in quantity, a multi-parameters psychophysiological feedback analysis system was designed. It can measure several physiological parameters closely related to psychological factors and can realize automatically controlling test gain using a DAC feedback adaptive circuit. Communication protocol is used to increase reliability of data communication and LMS algorithm was used in the system for noise elimination, real-time and data accuracy can be guaranteed. After the debug and verified, multi-parameter system can collect real-time and stable physiological parameters with a higher precision, it provides a feasible monitoring program for psychological assessment.

Study and Apply the Visualization Intelligent Feedback Analysis System of Tunnel Construction

Aiming at the problems of conventional underground engineering feedback analysis methods, such as being limited in local optimization and computing data being very complex, the paper introduced difference evolution arithmetic and visualization toolkit, and combined three dimensional numerical simulation and orthogonal design, developing the intelligent feedback analysis system based on Visual c#. The system theory, software frame and develop method are introduced, the system could be used to calculate and evaluate the state of tunnel surrounding rock based on in-situ monitoring data. The system is applied in an actual tunnel engineering, the analysis results are satisfied, which states it is feasible and has good potential application.