Organizations now deal with massive amounts of data. Data is collected from various points such as hospitals, credit card companies, and search engines. After collecting this voluminous data, it is ...published and shared for research. Data that is collected may have sensitive information that might be used to identify an individual and consequently lead to privacy violations when published. To address this challenge, privacy-preserving data publishing (PPDP) seeks to remove threats to privacy while ensuring that the necessary information is released for data mining. Various techniques have been proposed to solve the problems associated with sensitive information. One such technique is k- anonymity. This technique is the best and very efficient. However, it also leads to loss of information, reduces data utility, and works well only with static tables. In this paper, we proposed a technique that addresses the challenges of K-anonymity known as the Bit-Coded-Sensitive Algorithm (BCSA). This algorithm is more efficient and effective and ensures that the privacy of the individual is preserved by avoiding disclosure, and linkages and at the same time ensuring high quality and utility of data. BCSA first identifies the source of data and based on that, uses bits to code sensitive data with a key.
Nowadays data is growing tremendously. Therefore, there is a great need to store and process data. The problem of Pattern Searching has different applications. When searching for text or words in ...computer application systems, Pattern searching is used to display the search results. The purpose of Pattern searching is to find text within another text. For example, searching for text in books will take a long time and is hard work. Using Pattern searching will save you time and effort. If similar words are found within the requested text, it will underline the word similar to what was requested, otherwise it does not display any matches if there are no similar words within a text. This paper presents comparisons of the speed of different Pattern searching algorithms, precisely the Naive, KMP, Rabin-Karp, Finite Automata, Boyer-Moore, Aho-Corasick, Z Algorithm algorithms. We will test the time complexity of these algorithms in the three programming languages C#, Java and Python using three different CPUs. According to the results that appear in this comparison, we are able to perform the comparison between the programming languages and the comparison between the CPUs used in this research.
Today, smart devices such smart watches and smart cell phones are becoming ever-present in all fields that influence the quality of life of the modern people. These on-board systems have ...revolutionized the behavior of human beings and especially their way of communicating. In this context and to improve the experience of using these devices, we aim to develop a system that recognizes hand poses in the air by a smart device. In this work, the system is based on Histogram of Oriented Gradient (HOG) features and Support Vector Machine (SVM) classifier. The impact of using HOG and SVM on mobile devices is studied. To carry out this study, we used an improved version of the "NUS I" dataset and obtained a recognition rate of approximately 94%. In addition, we conducted run speed experiments on various mobile devices to study the impact of this task on this embedded platform. The main contribution of this work is to test the impact of using the HOG descriptor and the SVM classifier in terms of recognition rate and execution time on low-end smartphones.Today, smart devices such smart watches and smart cell phones are becoming ever-present in all fields that influence the quality of life of the modern people. These on-board systems have revolutionized the behavior of human beings and especially their way of communicating. In this context and to improve the experience of using these devices, we aim to develop a system that recognizes hand poses in the air by a smart device. In this work, the system is based on Histogram of Oriented Gradient (HOG) features and Support Vector Machine (SVM) classifier. The impact of using HOG and SVM on mobile devices is studied. To carry out this study, we used an improved version of the "NUS I" dataset and obtained a recognition rate of approximately 94%. In addition, we conducted run speed experiments on various mobile devices to study the impact of this task on this embedded platform. The main contribution of this work is to test the impact of using the HOG descriptor and the SVM classifier in terms of recognition rate and execution time on low-end smartphones.
Abstract— Background subtraction is the dominant approach in the domain of moving object detection. Lots of research have been done to design or improve background subtraction models. However, there ...is a few well known and state of the art models which applied as a benchmark. Generally, these models are applied on different dataset benchmarks. Most of the time Choosing appropriate dataset is challenging due to the lack of datasets availability and the tedious process of creating the ground-truth frames for the sake of quantitative evaluation.
Therefore, in this article we collected local video scenes for street and river taken by stationary camera focusing on dynamic background challenge. We presented a new technique for creating ground-truth frames using modelling, composing, tracking, and rendering each frame. Eventually we applied nine promising benchmark algorithms used in this domain on our local dataset. Results obtained by quantitative evaluations exposed the effectiveness of our new technique for generating the ground-truth scenes to be benchmarked with the original scenes using number of statistical metrics. Furthermore, results shows the outperformance of SuBSENSE model against other tested models.
This work is part of a larger research, conducted in Greece, about the students' difficulties in understanding the concepts and phenomena of Electricity. The goal of this study is to present the high ...school students’ difficulties and their causes into the study of basic direct current (dc) circuits, due to the concept of the electromotive force (emf). Researches in over the world have highlighted that the concepts of the emf and the potential difference (pd) create many problems to the students in the study of dc circuits. These difficulties are presented, analyzed and is made an attempt to identify their causes. The results show that, in addition to confirming the existing literature enriched with new findings, to address these difficulties is necessary the development of a teaching approach based on an education model with a new curriculum, where needed (in Greece, for example) and an appropriate education material so that to overcome the lack of understanding of the concepts and laws shown by the students.
It is essential to consider the public’s viewpoints when it comes to significant issues, such as the adoption and integration of technologies in education. This study aims at analyzing and ...comprehending the public’s perspectives, sentiments and attitudes towards the use of virtual reality in general and in educational settings. After setting the necessary data requirements, 10,457,344 related tweets from Twitter were identified and retrieved. The data was then analyzed using text mining and sentiment analysis. Based on the results, the public positively perceived the use of virtual reality and mostly expressed emotions of anticipation, trust and joy when referring to its use in education. Finally, the role of virtual reality as an effective educational tool that can enhance students’ engagement, motivation and academic performance was highlighted.
Deep Learning Approaches to Predict Future Frames in Videos Islam, Tariqul; Md. Hafizul Imran; Md. Ramim Hossain ...
International journal of recent contributions from engineering, science & IT,
11/2022, Letnik:
10, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Deep neural networks are becoming central in several areas of computer vision. While there have been a lot of studies regarding the classification of images and videos, future frame prediction is ...still a rarely investigated approach, and even some applications could make good use of the knowledge regarding the next frame of an image sequence in pixel-space. Examples include video compression and autonomous agents in robotics that have to act in natural environments. Learning how to forecast the future of an image sequence requires the system to understand and efficiently encode the content and dynamics for a certain period. It is viewed as a promising avenue from which even supervised tasks could benefit since labeled video data is limited and hard to obtain. Therefore, this work gives an overview of scientific advances covering future frame prediction and proposes a recurrent network model which utilizes recent techniques from deep learning research. The presented architecture is based on the recurrent decoder-encoder framework with convolutional cells, which allows the preservation of Spatio-temporal data correlations. Driven by perceptual-motivated objective functions and a modern recurrent learning strategy, it can outperform existing approaches concerning future frame generation in several video content types. All this can be achieved with fewer training iterations and model parameters.
This study investigated lecturers’ adoption of ICT tools in Ghanaian colleges of education. The participants of this study were 390 lecturers from 25 colleges of education in Ghana. Data was ...collected using a questionnaire and lesson observation, and the results were analysed quantitatively and qualitatively using descriptive statistics and thematic analysis. The study revealed that more than two-thirds of the participants/respondents used personal computers, projectors, social media, and LMSs in their education. The lecturers asserted that they utilise ICT tools for research, for storing, retrieving, and sharing files and information in addition to utilising them to teach their courses. The respondents/participants recounted that they grow professionally as a result of using these ICT tools. Additionally, it was discovered that the respondents/participants employed ICT tools in their instruction due to its mobility, time-saving qualities, accessibility, and user-friendliness which aided in the planning and delivery of lessons which boosted the T&L process. It was therefore recommended, among other things, that the Ghanaian government keep the necessary pedagogical ICT tools accessible to lecturers, and that workshops and seminars be organised for all lecturers in Ghana's COEs on how to use some common pedagogical ICT tools that will enhance lecturers' teaching techniques to promote effective learning and fulfill 21st-century teaching skills.
This article deals with the problem of Berber handwritten character recognition using Extreme Learning Machine. This paradigm has gained significant attention in pattern recognition field thanks to ...its efficient learning speed and its high accuracy. In this paper, we have used a fast Extreme Learning Machine to recognize efficiently the Latin Berber characters. So, the proposed ELM has been trained over a Berber-MNIST dataset containing images of Amazigh alphabets. This algorithm learns much faster than traditional popular learning algorithms thanks to the use of JAX library which contains several functions to reduce the execution time of our solution. The simulation results show that the handwritten recognition system based on our developed extreme learning machine decreases computational cost and reduces the time required for the whole recognition process. Furthermore, the developed ELM achieves a high performance in terms of recognition accuracy.
Often we are wrong in choosing a good programming language to create a website backend to process the data we have so that the impact is that our website is not able to handle so many requests with a ...lot of data so users feel uncomfortable because our application takes a very long time to process. processing each user's request. So in this journal, we will try to discuss the selection of the right programming language in making application backends according to the function of the programming language. In this journal, we will compare the programming languages PHP, Python, Java and C# for the manufacture of an application backend that must be able to process very large population data
