WEBCAM-BASED LASER DOT DETECTION TECHNIQUE IN COMPUTER REMOTE CONTROL

ABSTRACTIn this paper, the authors propose a method to detect the laser dot in an interactive system using laser pointers. The method is designed for presenters who need to interact with the computer during the presentation by using the laserpointer. The detection technique is developed by using a camera to capture the presentation screen and processing every frames transferred to the ara computer. This paper focuses on the detection and tracking of laser dots, based on their characteristics to distinguish a laser dotfrom other areas on the captured frames. Experimental results showed that the proposed method could reduce the rate of misdetection by light noises of a factor of 10 and achieve an average accuracy of 82% of detection in normal presentation environments. The results point out that the better way to describe the laser dots’ features based on visual concept is to use the HSI color space instead of the normal RGB space.Keywords.  laser pointer; laser dot/spot; laser pointer interaction; control; mouse; computer screen/display

CC2Vec: Distributed representations of code changes

National Research Foundation (NRF) Singapore; ANR ITrans projec

Investigating and implementing a student vocational education model for educational innovation

The development of each student's awareness serves as the governing principle for high school vocational education programs. This awareness then becomes the driving force behind the progression of the educational process. Career education activities for students are the relationships between the objectives, contents, methods and forms of organization of educational activities that are directly and constantly influenced by the educational environment. Student career education activities are the relationships between these aspects of educational activities as determined by research into the programs, textbooks, systematization and theoretical analysis of these activities. This investigation focuses on the following areas: (1) Developing preschool and high school teachers in the province of Dong Thap to meet the criteria of the new educational program (2) Developing models of applying local educational material for students in the province of Dong Thap. Both of these initiatives are part of the Dong Thap Educational Development Project. Findings: Assess the current state of activities for students in the province of Dong Thap that are related to vocational education between 2018- 2021. Develop a model for carrying out activities for students participating in vocational education in the province of Dong Thap to fulfill educational innovation requirements

A HEDGE ALGEBRAS BASED CLASSIFICATION REASONING METHOD WITH MULTI-GRANULARITY FUZZY PARTITIONING

During last years, lots of the fuzzy rule based classifier (FRBC) design methods have been proposed to improve the classification accuracy and the interpretability of the proposed classification models. Most of them are based on the fuzzy set theory approach in such a way that the fuzzy classification rules are generated from the grid partitions combined with the pre-designed fuzzy partitions using fuzzy sets. Some mechanisms are studied to automatically generate fuzzy partitions from data such as discretization, granular computing, etc. Even those, linguistic terms are intuitively assigned to fuzzy sets because there is no formalisms to link inherent semantics of linguistic terms to fuzzy sets. In view of that trend, genetic design methods of linguistic terms along with their (triangular and trapezoidal) fuzzy sets based semantics for FRBCs, using hedge algebras as the mathematical formalism, have been proposed. Those hedge algebras-based design methods utilize semantically quantifying mapping values of linguistic terms to generate their fuzzy sets based semantics so as to make use of fuzzy sets based-classification reasoning methods proposed in design methods based on fuzzy set theoretic approach for data classification. If there exists a classification reasoning method which bases merely on semantic parameters of hedge algebras, fuzzy sets-based semantics of the linguistic terms in fuzzy classification rule bases can be replaced by semantics - based hedge algebras. This paper presents a FRBC design method based on hedge algebras approach by introducing a hedge algebra- based classification reasoning method with multi-granularity fuzzy partitioning for data classification so that the semantic of linguistic terms in rule bases can be hedge algebras-based semantics. Experimental results over 17 real world datasets are compared to existing methods based on hedge algebras and the state-of-the-art fuzzy sets theoretic-based approaches, showing that the proposed FRBC in this paper is an effective classifier and produces good results

Etude des mécanismes de rupture d'un assemblage boulonné

Cette étude expérimentale et numérique traite de l’analyse du comportement et de la rupture d’un assemblage ponctuel (boulonné) soumis à un chargement statique de cisaillement. La technique de l’émission acoustique a été utilisée pour prédire la chronologie des différents mécanismes d’endommagement. Une mesure de champs de déformations par corrélation d’images a été mise en œuvre. Les cas étudiés ont été simulé par la technique des éléments finis 3D

Trade-off analysis of cost and nutrient efficiency of coffee farms in vietnam: A more generalised approach

Analysis of economic and environmental performance of agricultural production has received increasing attention in both the theoretical and empirical literature (Aldieri et al., 2019). Several methodological approaches have been proposed to measure environmental efficiency and to analyse trade-offs between economic and environmental performance (e.g., Fang, 2020; Shuai and Fan, 2020; Azad and Ancev, 2014; Picazo-Tadeo and Prior, 2009; Reinhard et al., 2000). Within this literature strand, Coelli et al., (2007) offer a distinct approach that utilises the material balance principle to derive cost and environmental efficiency measures. Empirical applications of Coelli et al. (2007) for the purpose of environmental and economic analysis have flourished recently (Hoang and Alauddin, 2012; Nguyen et al., 2012; Hoang and Rao, 2010). However, these empirical applications focus only on the economic and environmental trade-off of technically efficient farms, not all the farms

Silent Vulnerable Dependency Alert Prediction with Vulnerability Key Aspect Explanation

Due to convenience, open-source software is widely used. For beneficial reasons, open-source maintainers often fix the vulnerabilities silently, exposing their users unaware of the updates to threats. Previous works all focus on black-box binary detection of the silent dependency alerts that suffer from high false-positive rates. Open-source software users need to analyze and explain AI prediction themselves. Explainable AI becomes remarkable as a complementary of black-box AI models, providing details in various forms to explain AI decisions. Noticing there is still no technique that can discover silent dependency alert on time, in this work, we propose a framework using an encoder-decoder model with a binary detector to provide explainable silent dependency alert prediction. Our model generates 4 types of vulnerability key aspects including vulnerability type, root cause, attack vector, and impact to enhance the trustworthiness and users' acceptance to alert prediction. By experiments with several models and inputs, we confirm CodeBERT with both commit messages and code changes achieves the best results. Our user study shows that explainable alert predictions can help users find silent dependency alert more easily than black-box predictions. To the best of our knowledge, this is the first research work on the application of Explainable AI in silent dependency alert prediction, which opens the door of the related domains