Sentiment analysis is a branch of Natural Language Processing (NLP) and machine learning in which text is classified into two categories: positive and negative. Because the use of the internet and social media is growing at a rapid pace, the products created by these two are receiving far more client input than in the past. Text generated by social media, blogs, posts, and product reviews, among other places, has become the best-suited examples for consumer sentiment, delivering the best-suited notion for that particular product. As a result, the hybrid feature selection proposed in this paper is a combination of particle swarm optimization (PSO) and cuckoo search. The hybrid feature selection technique surpasses the standard technique due to the subjective nature of social media reviews. Support Vector Machine (SVM) classifier was used to examine performance criteria such as f-measure, recall, precision, and accuracy on the Twitter dataset, and it was compared to a convolution neural network. The proposed work outperforms the existing work, according to the findings of this paper's experiments based on various factors.
Social media has become an important part of our daily lives due to the recent trends. Sites are flooding with tons of posts and opinions of people and social media communication has been on the rise. Although this has mostly been a boon to us, unfortunately it involves enormous dangers, since online texts with high toxicity can cause personal attacks, online harassment and bullying behaviours. People hiding behind closed doors with anonymity can do whatever they want with a keyboard. Unfortunately, not enough means exist to tackle this issue. Recently the employment of Convolutional Neural Networks and Recurrent Neural Networks are approached for computational purposes for the text classification systems. This work utilizes this for finding foul and malicious comments using the Kaggle data set. The work aims to classify a comment into 6 labels of toxicity. This work also implements a completely functional frontend environment built using React JS and MongoDB, which classifies a user entered text into the mentioned labels of toxicity.
This study explored the Influence of School Heads Competence and Qualifications to the School Performance. This quantitative research utilized Descriptive-correlational and determined 48 School heads from Elementary and Secondary schools in Narra District, Narra, Palawan, Philippines. A self-completed questionnaire developed by the researchers was administered to gather the school heads’ profile and school’s performance. Mean, percentage, and standard deviation was used in analyzing the school heads’ profile and the school’s performance while the Pearson correlation was employed to test the relationship of the research’s variables. Results showed that in terms of the profile, majority of the respondents were graduates of bachelor’s degree with units in master’s program and almost half of them have international level of training while more than half were Principal III and have 4 to 7 years of practice as school head. In terms of their performance in the last three years, both in the years 2017-2018 and 2018-2019, the school heads obtained a very satisfactory performance and outstanding performance in the year 2019-2020. Both in the school years 2017-2018 and 2018-2019, the schools in Narra District obtained a maturing level. However, in the school year 2019-2020, the schools in Narra District got a rating, which was described as advanced level. It was found out also that there was no significant relationship between the school heads’ profile and the school performance was established. The result lead to recommendation to strengthen the school-based management areas where the schools obtained a maturing level while sustain the current level of practice in the SBM areas where they obtained an advanced level.
AI in agriculture is a fast-developing technology in this world. It helps farmers to identify the present condition of the field where they are in. There are several applications in AI which helps them to improve the income of their family and their yield. The applications of AI in agriculture are drones, crops, soil monitoring and predictive analysis. This helps in food security concerns forced the innovations and technological advancements in agriculture. In applications of AI in agriculture. The farmers can gain the information about the yield in easier way which can reduce the loss for the farmers by using this we may reduce the loss of the crops. It helps them in autonomous robots to handle essential agricultural tasks easily. And it gives potential invasions and information about the crops. Precision agriculture is used in AI technology is for aid in detecting diseases in plants, pests, and poor plant nutrition.
Data visualization has been rising rapidly for the past a few years in the BI and analytics industry, as part of the modern BI movement which emphasizes on self-service. Secondly, data visualization concepts and guidelines are realized through features in BI software, which makes it easy to apply the concepts. This is similar to the concept of Object-Oriented programming. Object Oriented Programming is a concept that could be implemented in any programming language, such as C. Compared to other types and applications of visualization, business data visualization, particularly concerns about the visualization of business data, is mainly for the purpose of communication, information seeking, analysis, and decision support.
Cloud computing is a set of IT services that are provided to a customer over a network on a leased basis and with the ability to scale up or down their service requirements. Usually Cloud Computing services are delivered by a third party provider who owns the infrastructure. Cloud Computing holds the potential to the “CLOUD COMPUTING WITH AWS is designed to be the most flexible and secured cloud network. It has come of age since Amazon’s rollout of the first of its kind of cloud services in 2006. It provides scalable and highly reliable platform that enables customers to deploy applications and data quickly and securely
Multimedia is increasingly being used in a number of formats (text, graphics, audio, animation, and video) to enhance human-computer interactions. The challenge is how to use the most successful presentation style which will boost efficiency. One of which is the use of a digital application namely Powtoon. The goal of this study was to define the teachers' perspective on developing Powtoon-based video media, the efficiency of developed Powtoon-based video media, and the efficacy of Powtoon based video media to improve learning outcomes in science teaching. A descriptive method of research was used to evaluate the perspective of the teachers in terms of learning resource, student engagement and inclusion of learning. A test of difference on the perspective of the teachers on the instructional video in terms of overall production, timing and content was tested. The result shows that there is no significant difference on their perspective in overall production and timing, however, in content, a significant difference was result. The study further imply that the use of video in education will improve the learning to the learners if it was utilized properly.
This research aimed to identify the relationship between the perceptions of the students and the level of satisfaction after using DepEd Commons. This study also included the problems encountered by the students in using DepEd Commons. This study used quantitative research, specifically descriptive method of research. The subjects of this study were the one hundred thirty six (136) Grade 12 students taking Physical Science subject at Mataasnakahoy Senior High School. The researchers used questionnaire-checklist as the research instrument in data gathering. The result of the study showed students’ continual learning of the Physical Science subject after the utilization of the platform.
In this modern world of information, the term Bigdata is a massive volume of both structured and unstructured data. And it is difficult to process using traditional database and software techniques. Bigdata system faces the series of technical challenges. In most scenarios, the volume of data is too large or it moves too fast or it exceeds current processing capacity. To find the useful information from massive amount of data, we need to analyze the data and that requires a lot of efforts at multiple levels. This paper presents the overview of bigdata.
Data mining is the technique of hidden, valid, and potentially useful patterns in huge data sets. Data Mining is all about discovering the previously unknown relationships amongst the data. It is a multi-disciplinary method that uses Machine Learning, Statistics, AI and Database Technologies. Data mining is also called as Knowledge Discovery, Knowledge Extraction, Data analysis, Information harvesting, etc. Data mining can able to handle the various types of data like Relational databases, Data warehouses, Object-Oriented and Object-Relational databases, Transactional and Spatial databases, Text mining and Web mining. This paper describes and discusses the various techniques associated with Data Mining Process.
The COVID-19 pandemic changed the landscape of all the industries around the world, and the education sector is no exception. Mental fatigue is being experienced by a number of teachers that were mandated to shift to online learning, which is new to everyone. These new system is being complicated by the heavier workloads the teachers must do, in addition to the online classes. On the positive side, they are able to withstand these difficult times with the help of taking some time to reflect and some breathers. The institutions are offering webinars in ensuring that the mental health of the teachers are properly addressed, but it was deemed that moral support can be of great help, especially in this hard times.
Communication plays an important role in the ongoing communication process. Verbal and non-verbal communication can be understood by others to first achieve a purpose and then enter the mind (Nelson Rolihlahla Mandela, 2000). In India, the media has played an important role in entertaining, educating and advocating the public over the past century. Radio is an inexpensive and primary media source for immediate and simultaneous communication. The Indian Broadcasting Service is available as a public broadcaster All India Broadcasting (AIR), a commercial dedicated FM channel (CPFM) and a community radio station (CRS) in a three-tier system. In the past 20 years, private FM channels and community radio stations have surpassed public service broadcasters. The focus of community broadcasting is a low-cost and low-income model of the cognitive process closest to the citizen. Unlike private FM broadcasts, private FM broadcasts are primarily for entertainment and business considerations, aiming to educate and master the community using their own expressions and voices. (Snehasis Sur, 2008).
Electricity is currently the realm of main concern as a result of the energy consumption is rising very briskly and thus despoliation of energy is exaggerated most. So, it's necessary for a system that lessens the consumption of energy. This paper recommended a research work that encompasses a sensible system which has a capability to govern the entire system within the building like fan, motor and all lightning connected system. This control system is initiated with the concept which uses Raspberry Pi controller with Bluetooth Beacon Communication. With this propound system consumer can easily steer the various systems in their building. By using this kind of control system consumers can straightforwardly save their electricity. The proposed system plays curious role in energy efficiency. This paper suggests a non-stop tracking of appliances. The designed system will assist in decreasing the electricity despoilment by using continuous tracking and controlling the electrical appliances. This appliances controlling primarily based on sensors input with the help of Raspberry pi.
Reversible data hiding in encrypted images is a technique that embedded additional data into an encrypted image without accessing the content of the original image, the embedded data can be extracted and the encrypted image can be recovered to the original one. In this work, two reversible data hiding methods in encrypted images, namely a joint method and a separable method, are introduced by adopting prediction error. In this paper, we propose joint and separable RDH techniques using an improved embedding pattern and a new measurement function in encrypted images with a high payload. The first problem in recent joint data hiding is that the encrypted image is divided into blocks, and the spatial correlation in the block cannot fully reflect the smoothness of a natural image. The second problem is that half embedding is used to embed data and the prediction error is exploited to calculate the smoothness, which also fails to give good performance In the joint method, data extraction and image reconstruction are performed at the same time. The reversibility, number of incorrect extracted bits are significantly improved while maintaining good visual quality of recovered image, especially when embedding rate is high. In the separable method, data extraction and image recovery are separated. The separable method also provides improved reversibility and good visual quality of recovered image for high payload embedding.
Understanding the long-term outlook on a particular stock is very important for investors to see the growth of their investment. This paper will give the idea about how to predict the fair price of the shares using DCF method and understanding short term outlook of that investment. The various technologies used in the paper are free cash flow, the terminal value, net present value, ARIMA, Linear Regression. Traditional techniques lack in covering long term stock price movements and so new approaches have been developed for analysis of stock price variations.
As technology advances, the goal of Blockchain-based E-Voting is to create a trustworthy voting system that contains all details and helps to prevent controversies during the voting process. Blockchain provides a decentralized architecture to run and support the voting scheme (i.e,) independently verifiable. It is used to secure an electronic voting system and Blockchain-enabled E-Voting could reduce voter fraud and increase voter access. In each ballot fingerprint sensor is placed, by each person’s fingerprint recognition, a voter can access the vote for a candidate. It brings out solutions to common problems like fraud, bribery, anonymous character of the vote, and absence of good independent monitoring.
Technology is a big part of our daily lives. Many of our daily tasks require the use of technology to make our lives efficient and productive, but the world becomes dependent on it. The world is evolving as a technological society where all information is readily available to the extent that all you need is just one click away, from communication, entertainment, production, infrastructure, security, marketing, innovation, and even education. The technology was introduced by children at an early stage, from learning the alphabet using the cellphone through learning how to talk can be made accessible through technology. There are various researches prove that integrating technology increases student achievements tremendously. Thus, the use of technology in teaching the students these days become a priority in public schools. However, there are researches stated that teachers have an inadequacy in Technological Knowledge (TK) and Technological Pedagogical Knowledge (TPK). Therefore, this research aims to assess the Public School Highschool Science Teachers' Technological Knowledge (TK) and Technological Pedagogical Knowledge (TPK) and their willingness to attend a seminar for improvement of their Technological Knowledge (TK) and Technological-Pedagogical Knowledge (TPK). The mixed-method approach used for the study. The qualitative data collected through online google form with an 84.6% retrieval rate from the chosen respondents. The quantitative data collected with the Online TPACK Competencies Survey adopted by Dr. Rebusquillo and qualitative data were collected through Open-Ended Surveys and focus group discussion. A total of 121 Science Teachers comprise the sample chosen randomly. The results of the study show that the level of Technological Knowledge (TK) and Technological-Pedagogical Knowledge (TPK) revealed that the Science Teachers are not confident when it comes to Technological-Pedagogical Knowledge (TPK) and are fairly confident in Technological Knowledge (TK). Otherwise, the Science Teachers have a high willingness to attend a seminar to improve their Technological Knowledge (TK) and Technological-Pedagogical Knowledge (TPK). The study revealed that the problems encountered by most of the Science Teachers are lack of ability to identify learning strategies in technology-based instruction to meet the objectives based on the students' needs.
Misconceptions are the barriers in the learning of the students. Concepts can be identified in two kinds, namely abstract and concrete ones. Concrete ideas can provide students with direct experience on it while it is difficult for students to perceive abstract ideas due to indirect practices towards it. Teachers take part in a crucial part in the understanding of the students. Therefore, teachers must be mindful of the misconceptions and potential practice to work out the misconceptions. This research aims to identify the misconceptions of science teachers in Chemistry. The study was conducted with 54 science teachers in one of the cities in Metro Manila, Philippines. The mixed-method approach was chosen for the study wherein quantitative data was collected through online google form with 92% retrieval rate from the chosen respondents. A multiple-choice identification test consisting of questions from Earth Science, Chemistry, Physics and Biology adopted from the research of Biilent and Esra study. The 25 items each survey was pilot tested with the 35 science teachers in public schools in Pasig City, Philippines. The Cronbach Alpha coefficient was found to be .971 to test the coefficient of reliability or consistency of the questions in the survey while the qualitative data was collected from the focus group discussion. This research reveals that there are 19 misconceptions out of 25 questions identified in Chemistry. Furthermore, research shows that the number one source of the misconceptions of Science Teachers is the Electronic Media, followed by Textbooks, then the teachers and other sources of misconceptions are peers, parents and colleagues. The researcher suggested that there should be a series of seminars to correct the misconceptions of teachers, there should be a list of credible websites for the teachers’ reference and to provide rigorous seminars for the Secondary School Science Teachers.
It is a paper is using the “Educational Data Mining” and the higher education system of academic performance. It has been using various methods of clustering, classification, prediction algorithm, DM classifies and 3D cubes classification. Since the education rate increased in the competition of placement. Thus, the papers will consider the five potential faculties to measures the correlation attributes to improve the students’ academic performance. It is using the weak and real time data set. They can be the academic analytics and data mining in higher education course management system techniques. Thus, the concept of techniques and the data they produce might be useful to those who practice the scholarship of teaching and learning.
The study of lenses is one of the least mastered skill in Physics. Students find it difficult to understand the concept of lens, ray diagramming and the lens equation. Henceforth, this study proposed a context-based lessons with topic and activities associated with the students’ authentic real life experiences that heightened learners’ enthusiasm and learnings. This research examined the effectiveness of the context-based lesson on students’ motivation level and conceptual understanding on the topic of Lens. This study was conducted at San Isidro National High School for two weeks participated by fifty (50) Grade 10 students. A quasi-experimental research one group pre-test and post-test was implemented to facilitate the collection of data. The following instruments: Lens Test (LT), Science Motivation Questionnaire (SMQ) were used to gather quantitative data. Statistical analysis revealed that there was a significant difference in the pre-test and post-test on academic performance. However, there is no significant difference in the students’ motivation before and after the conduct of the study.
