Intelligent System for Recommending Study Level in English Language Course using CBR Method

In the admission process, an English Course uses a level placement test. The implementation of the test encountered some problems such as slow determination of student learning levels based on the results of paper based test that are still conventional. The purpose of this research provides the recommendations for an intelligent knowledgebased system in recommending student learning levels using the Case-Based Reasoning (CBR) method. CBR is one of the method that uses the Artificial Intelligence approach and focuses on solving problems based on knowledge from the previous cases, by calculating numerical local similarity and global similarity using the nearest neighbor algorithm as the basic for the technical development of this intelligent system. The result of the study was tested for the data accuracy with the confusion matrix method by the result 100% for the accuracy. For evaluating the system systematically was using the User Acceptance Test (UAT) method with the results of the evaluation is 88% of the system meets user needs and expectation

A USABILITY STUDY OF THE INTELLIGENT ASSISTANT FOR SENIOR CITIZENS TO SEEK HEALTH INFORMATION

This research study expands earlier works on the usability performance of multimodal intelligent assistants in the field of health information search by senior citizens. Intelligent assistants are able to bring the health information search to an advanced level by having conversations and touch interactions with the device instead of text-based searching engine. It is important to have usability evaluation of system and device to push the design and development of the information search and retrieval experience to be better. With the growth of the market and user need in the field of multimodal intelligent personal assistants, it is absolutely necessary to conduct research to understand the performance of the current system and figure out the present weaknesses and direction for future improvements.Bachelor of Scienc

Intelligent interface agents for biometric applications

This thesis investigates the benefits of applying the intelligent agent paradigm to biometric identity verification systems. Multimodal biometric systems, despite their additional complexity, hold the promise of providing a higher degree of accuracy and robustness. Multimodal biometric systems are examined in this work leading to the design and implementation of a novel distributed multi-modal identity verification system based on an intelligent agent framework. User interface design issues are also important in the domain of biometric systems and present an exceptional opportunity for employing adaptive interface agents. Through the use of such interface agents, system performance may be improved, leading to an increase in recognition rates over a non-adaptive system while producing a more robust and agreeable user experience. The investigation of such adaptive systems has been a focus of the work reported in this thesis. The research presented in this thesis is divided into two main parts. Firstly, the design, development and testing of a novel distributed multi-modal authentication system employing intelligent agents is presented. The second part details design and implementation of an adaptive interface layer based on interface agent technology and demonstrates its integration with a commercial fingerprint recognition system. The performance of these systems is then evaluated using databases of biometric samples gathered during the research. The results obtained from the experimental evaluation of the multi-modal system demonstrated a clear improvement in the accuracy of the system compared to a unimodal biometric approach. The adoption of the intelligent agent architecture at the interface level resulted in a system where false reject rates were reduced when compared to a system that did not employ an intelligent interface. The results obtained from both systems clearly express the benefits of combining an intelligent agent framework with a biometric system to provide a more robust and flexible application

SISTEM INTELIJEN EVALUASI KELAYAKAN PINJAMAN USAHA KECIL MENENGAH AGROINDUSTRI OLEH PERBANKAN

ABSTRACT The sustainability operation of an agroindustrial production system in a competitive global market shall be supported by  capital structural elements  (investment and working capital) that concern with assets, liability, and profitability of a company. Banking (conventional and syariah),  as the most important financial intermediation institution of the national economic system (Arifin, 2002),  has to feature small and medium enterprise (SME) in agroindustrial sector. The SME can strengthen the national economy, support the national industrial development objective, become the “back bone” of national economy, and answer important issues related with Indonesian reformation process (ADB, 2001). The feasibility study of the SME agroindustrial working capital loan that utillizes risk level concept and intelligent system method shall be done due to its complexity and uncertainty. The research aims to formulate the ANFIS structure in neuro-fuzzy system that is supported by risk level concept and feasibility study method of working capital loan worthiness evaluation, and verification.The result is a standard operating procedure (SOP) of intelligent worthiness evaluation of small and medium agroindustrial working capital loan, i.e. fuzzy inference system (FIS) and training process of fhe system. The conclusion is a model formulation process of FIS Takagi-Sugeno-Kang’s type, that integrates the training process of artifical neural network model with risk level as the parameter in regulating the rules, and weighted score in determining fuzzy score (risk level) interval. The verification indicates that to reach Accept A/clean worthiness in loan decision based on the FIS result, the evaluation of aspect judgment should be well, with the low risk level of aspect criteries (conventional and syariah banking). The result of training in FIS is the prediction of debtor condition, where the best condition is compulsory to reach commonly the low risk level towards the worthiness. The submitted sugesstion is the SOP development as an intelligent decision support system (IDSS) that shall be integrated based on neuro-fuzzy system, ANFIS and others, to reduce the limitation in steps of model implementation  (resources : human, software and hardware), and has the suitable weight of the worthiness aspects Key  words : Intelligent, Evaluation, Worthiness, SME, Agroindustr

SISTEM INTELIJEN EVALUASI KELAYAKAN PINJAMAN USAHA KECIL MENENGAH AGROINDUSTRI OLEH PERBANKAN

ABSTRACT The sustainability operation of an agroindustrial production system in a competitive global market shall be supported by  capital structural elements  (investment and working capital) that concern with assets, liability, and profitability of a company. Banking (conventional and syariah),  as the most important financial intermediation institution of the national economic system (Arifin, 2002),  has to feature small and medium enterprise (SME) in agroindustrial sector. The SME can strengthen the national economy, support the national industrial development objective, become the “back bone” of national economy, and answer important issues related with Indonesian reformation process (ADB, 2001). The feasibility study of the SME agroindustrial working capital loan that utillizes risk level concept and intelligent system method shall be done due to its complexity and uncertainty. The research aims to formulate the ANFIS structure in neuro-fuzzy system that is supported by risk level concept and feasibility study method of working capital loan worthiness evaluation, and verification.The result is a standard operating procedure (SOP) of intelligent worthiness evaluation of small and medium agroindustrial working capital loan, i.e. fuzzy inference system (FIS) and training process of fhe system. The conclusion is a model formulation process of FIS Takagi-Sugeno-Kang’s type, that integrates the training process of artifical neural network model with risk level as the parameter in regulating the rules, and weighted score in determining fuzzy score (risk level) interval. The verification indicates that to reach Accept A/clean worthiness in loan decision based on the FIS result, the evaluation of aspect judgment should be well, with the low risk level of aspect criteries (conventional and syariah banking). The result of training in FIS is the prediction of debtor condition, where the best condition is compulsory to reach commonly the low risk level towards the worthiness. The submitted sugesstion is the SOP development as an intelligent decision support system (IDSS) that shall be integrated based on neuro-fuzzy system, ANFIS and others, to reduce the limitation in steps of model implementation  (resources : human, software and hardware), and has the suitable weight of the worthiness aspects Key  words : Intelligent, Evaluation, Worthiness, SME, Agroindustr

Practical Research on Teacher Professional Development Paths Based on Digital Teacher Portraits

The Zhongliang Xiangyun Branch of Chengdu Longjiang Road Primary School, as a relatively young and inexperienced school, faced difficulties in guiding teachers towards suitable paths for their professional growth. To address this challenge and strengthen the teachers’ team, the school leverages its position as a key project school of digital teacher portraits in Wuhou District to conduct research on teachers’ professional growth paths. The study focuses on three directions, including teachers’ intelligent management path, teachers’ personalized research path, and teachers’ intelligent teaching implementation path. The school emphasizes the renewal of teachers’ education concepts and the improvement of their professional level, and develops a “Yunxin” teacher growth path planning map to construct a closed growth path through an all-round portrait of teachers. The school uses the intelligent management platform to realize paperless office work and to file teachers’ personal data and teaching resources online. Through the evaluation system of the digital teacher portrait platform, the school can effectively evaluate teachers’ work and establish a teacher development model. Furthermore, the school integrates both “offline centralized teaching” and “online personalized learning” to incorporate teacher classroom teaching data and student learning effect data into the important indicators of teacher “data portrait”. This integration promotes and supports teachers to carry out differentiated teaching, finally establishing a new model of “student-centered” intelligent education

การพัฒนารูปแบบเว็บฝึกอบรมอัจฉริยะผ่านการเรียนรู้โดยใช้ปัญหาเป็นหลักแบบมีระบบที่ปรึกษา

The research study aimed to achieve in developing a model of intelligent web-based training adopting problem-based learning with counseling system, and comparing the training achievement for intelligent with normal web-based training using test and problem solving scores of a basic knowledge of marine transport subject. Sixty staffs of RCL Public Company Limited, who never passed the training course were sampling for the research scope. The research instrument was intelligent web-based training of marine transport subject. The result found that a model of intelligent web-based training composed of 6 components: 1) Trainee Model Component provides data and records of the trainees, 2) Knowledge Component stores the content used in the training, 3) Expert Component offers functional analysis to classify the participants into groups based on their level of related knowledge, 4) Counseling Component guides trainees during the activities with tips that matched to their knowledge and monitors each trainer’s learning progress. This will assist trainees to achieve their training objectives more effectively 5) Training Component conducts the training and 6) Communication Component controls the interaction with the trainees. The model evaluation were accepted at highly rate ( = 4.29). The achievements of trainees in intelligent web-based training which classified in each group based on level of basic knowledge had shown with different effect. The group that had the most basic knowledge tended to outperform the moderated basic knowledge group which also performed better than group which contained minimum knowledge. An intelligent web-based training produced better result than a normal web-based training except the group which contained moderated basic knowledge at the statistical significant level .05

The Effect of the Program ' Right Intelligent System Knowledge ' on the Development of the Critical Thinking for Students Faculty of Agriculture in University of Teashreen A quasi-experimental study

The study main to know the effect of the program ' Right Intelligent System Knowledge 'on the development of the critical thinking for Students Faculty of Agriculture in University of Teashreen. The sample of the research was chosen intentionally , it composed of (72) students. The study had the quasi-experimental methodology in terms of dividing the research sample into two groups: the experimental group which consisted of (36) students, and the control group which consisted of (36) students. The researcher used "Right Intelligent System of Knowledge " Program: It is translated by Dr. Nadia Al-sourour in (2005), which taught the students how to think. The program consisted of four parts: Living Skills, The System, The Power of Thinking, and Success. It is suitable for students from the fifth grade till university level. And researcher used California's Test for critical thinking: is translated by each of Abdullal Ague and Adel Albanna, and it was adopted by the current study Photo-verbal of this test, for measuring the capacity: the total score, analysis, evaluation, inference. The study showed that: there was a statistically significant difference between experimental and control groups according to California's Test for critical thinking including with the dimensions of analysis, evaluation, inference, and the total degree as a result of the post, so this difference is due to the right intelligent system of knowledge program, and this shows the effectiveness of this program and its ability to develop critical thinking skills. Too, there was no statistically significant difference between male and female students from the experimental group on the California's Test of critical thinking including with the dimensions of analysis, evaluation, inference, and the total degree

Neuromorphic Vision Based Multivehicle Detection and Tracking for Intelligent Transportation System

Neuromorphic vision sensor is a new passive sensing modality and a frameless sensor with a number of advantages over traditional cameras. Instead of wastefully sending entire images at fixed frame rate, neuromorphic vision sensor only transmits the local pixel-level changes caused by the movement in a scene"jats:italic" at the time they occur"/jats:italic". This results in advantageous characteristics, in terms of low energy consumption, high dynamic range, sparse event stream, and low response latency, which can be very useful in intelligent perception systems for modern intelligent transportation system (ITS) that requires efficient wireless data communication and low power embedded computing resources. In this paper, we propose the first neuromorphic vision based multivehicle detection and tracking system in ITS. The performance of the system is evaluated with a dataset recorded by a neuromorphic vision sensor mounted on a highway bridge. We performed a preliminary multivehicle tracking-by-clustering study using three classical clustering approaches and four tracking approaches. Our experiment results indicate that, by making full use of the low latency and sparse event stream, we could easily integrate an online tracking-by-clustering system running at a high frame rate, which far exceeds the real-time capabilities of traditional frame-based cameras. If the accuracy is prioritized, the tracking task can also be performed robustly at a relatively high rate with different combinations of algorithms. We also provide our dataset and evaluation approaches serving as the first neuromorphic benchmark in ITS and hopefully can motivate further research on neuromorphic vision sensors for ITS solutions. Document type: Articl