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Short-term load forecasting (STLF) plays an important role in building business strategies, ensuring reliability and safe operation for any electrical system. There are many different methods, including: regression models, time series, neural networks, expert systems, fuzzy logic, machine learning and statistical algorithms used for short-term forecasts. However, the practical requirement is how to minimize the…

This paper presents a solution for question answering system for Vietnamese language by integrating diacritics restoration and question classification via deep learning approach. It could be said that this will be the first research integrating two phases into Vietnamese question answering system. Question classification has a critical role in the question answering system. However if…

Physical computing is important for ICT (information and communication technology) Education and other informatics education such as software education since physical computing can provide learning-by-doing education for students. It is also a strong tool to increase students’ programming ability using various type of physical computing tools like a robot. In physical computing, it is necessary…

The importance of programming skills has increased with advances in information and communication technology (ICT). However, the difficulty of learning programming is a major problem for novices. Therefore, we propose a logic error detection algorithm based on structure patterns, which are an index of similarity based on abstract syntax trees, and error degree, which is…

Recommender Systems (RSs) are termed as web-based applications that make use of filtering methods and several machine learning algorithms to suggest relevant user objects. It can be said that some techniques are usually adopted or trained to develop these systems that generate lists of suitable recommendations. Conventionally, RS uses a single rating approach to preference…

There is no doubt that a good knowledge of traffic demand has a direct impact on improving traffic management. Road traffic is strongly correlated with many factors such as day of week, time of day, season and holidays which make it suitable for prediction. In this paper, we develop a neural network model for hourly…

With the advancement in the field of Internet-of-Things (IoT), event monitoring applications have rapidly evolved from a simple event data acquisition towards predictive event analytics involving multi-sensory data aggregation in a distributed environment. Existing event monitoring schemes are mainly relying on ine_cient centralized processing mechanism, which may lead to the common single-point of failure for…

Clustering is one of the well-known unsupervised learning methods that groups data into homogeneous clusters, and has been successfully used in various applications. Fuzzy C-Means(FCM) is one of the representative methods in fuzzy clustering. In FCM, however, cluster centers tend leaning to high density area because the sum of Euclidean distances in FCM forces high…

Currently, one of the challenges of educational institutions is drop-out student issues. Several factors have been found and determined potentially capable to stimulate dropouts. Many researchers have been applied data mining methods to analyze, predict dropout students and also optimize finding dropout variables in advance. The main objective of this study is to find the…

The major problem in electric utility is Electrical Theft, which is harmful to electric power suppliers and causes economic loss. Detecting and controlling electrical theft is a challenging task that involves several aspects like economic, social, regional, managerial, political, infrastructural, literacy rate, etc. Numerous methods were proposed formerly for detecting electricity theft. However, the previous…

From the collection of supervised machine learning technique, an ensemble procedure is used in Random Forest. In the arena of Data mining, there is an excellent claim for machine learning techniques. Random Forest has tremendous latent of becoming a widespread technique for forthcoming classifiers as its performance has been found analogous with ensemble techniques bagging…

Over the years, alternative medicine has carried out numerous systematic studies related to the ophthalmological field, specifically the eye. Studies that propose as support of analysis to the Iridology, which studies the alterations of the iris in correspondence with the organs of the human body. Thus, it presents the opportunity to investigate neuronal diseases related…

The use of technology in the learning process has become the most significant point in helping teachers reaching the objectives of the learning. This study focuses on the use of multimedia by novice teachers in comprehending the internship program’s guidance. The Islamic Critical Reflection model is a new and innovative model in the field of…

Enhancing underwater visualization using hybrid technique is generally employed into oceanic production. Through growing oceanic learning, undersea processing has drawn extra importance owing towards necessary task of picture towards attaining data. Although, suitable to reality of dust-like constituent and beam reduction, undersea descriptions continually experience small contrast and color alteration. In this paper, we estimate…

Music genre classification is an important multimedia research domain, including aspects of music piece representation, distances between genres, and categorization of music databases. The objective of this study was to develop a model for automatic classification of musical genres from audio data by using features from low-level time and frequency domains. These features can highlight…

Face sketch recognition aims at matching face sketch images to face photo images. The main challenge lies in modality discrepancy between face photo and sketch images. In this work, we propose a new facial sketch-to-photo recognition approach by adopting VGG-Face deep learning network, with which face images can be represented by compact and highly discriminative…

Relation Extraction is an important subtask of Information Extraction that involves extracting significant facts from natural language text. Extracting structured information from the plaintext is the ultimate goal of IE systems. The Indian language content on the internet is increasing day to day. Extracting relevant information from this huge unstructured data is a challenging task…

Robotic catching of thrown objects is one of the common robotic tasks, which is explored in a number of papers. This task includes subtask of tracking and forecasting the trajectory of the thrown object. Here we propose an algorithm for estimating future trajectory based on video signal from two cameras. Most of existing implementations use…

Low contrast images degrade the performance of image processing system. To solve the issue, plenty of image enhancement methods have been proposed. But the methods work properly on the fixed environment or specific images. The methods dependent on fixed image conditions cannot perform image enhancement properly and perspective of smart device users, algorithms including iterative…

The application of protective coatings is the primary method of protecting marine and offshore structures from corrosion. Coating breakdown and corrosion (CBC) assessment is a major aspect of coating failure management. Evaluation methods can result in unnecessary maintenance costs and a higher risk of failure. To achieve a comprehensive collection of data for CBC assessment,…

Many existing system modeling techniques based on statistical modeling, data mining and machine learning have a shortcoming of building variable relations for the full ranges of variable values using one model, although certain variable relations may hold for only some but not all variable values. This shortcoming is overcome by the Partial-Value Association Discovery (PVAD)…

In this research work, we are implementing a student performance evaluation model using Mamdani Fuzzy Inference System (FIS) and Neuro Fuzzy system and comparing the results with classical averaging method for Network Analysis (NA) course studied by third semester Electronics and Communication Engineering students. This work explains the designing of scoring rubrics using Bloom’s levels…

A mobile retail app is a growing innovation in a retailing setting and there is an argument on the prominent status of a mobile application in contrast with a mobile website and web applications. The study used quantitative data to run multiple regression analysis with keen attention to linear regression assumption and compare four models…

Language skill is a rule-like operation, based on generalized connections. The main property of language skills is awareness. They are formed with conscious mastery of the language means of communication (phonetic, lexical and grammatical). Language acquisition is a complex process which includes a large number of different parameters. Therefore, the study and improvement of language…

Virtual Reality (VR) technology has become one of the most advanced techniques that is used currently in many fields. The role of education is extremely important in every society; therefore, it should always be updated to be in line with new technologies and lifestyles. Applying technology in education enhances the way of teaching and learning.…