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In this paper, a novel is proposed for real-time tracking human targets in cases of high influence from complexity environment with a normal camera. Firstly, based on Oriented FAST and Rotated BRIEF features, the Lucas-Kanade Optical Flow algorithm is used to track reliable keypoints. This method represents a valuable performance to decline the effect of…

The main contribution of this paper is the framework of Application Programming Interface (API) to be integrated on a smartphone app. The integration with algorithm that generates fingerprints from the method ST-PSD with several parameter configurations (Windows size, threshold, and sub-score linear combination coefficient). An approach capable of recognizing an audio piece of music with…

Harassment and violence against women have become one of the social security problems in Bangladesh. In this paper, we aim to develop safety devices for women named BOHNNI and BADHON which resemble legitimate jewelry. We used a microcontroller for the hardware device to make it most decisive and less immoderate. BOHNNI, a locating device, is…

Haze removal is an extremely challenging task, and object detection in the hazy environment has recently gained much attention due to the popularity of autonomous driving and traffic surveillance. In this work, the authors propose a multiple linear regression haze removal model based on a widely adopted dehazing algorithm named Dark Channel Prior. Training this…

Brain-computer interface (BCI) has extensively been used for rehabilitation purposes. Being in the research phase, the brainwave based wheelchair controlled systems suffer from several limitations, e.g., lack of focus on mental activity, complexity in neural behavior in different conditions, and lower accuracy. Being sensitive to the color stimuli, the EEG signal changes promises a better…

This work is concerned with the detection and classification of birds that have applications like monitoring extinct and migrated birds. Recent computer vision algorithms can precise this kind of task but still there are some dominant issues like low light, very little differences between subspecies of birds, etc are to be studied. As Convolution Neural…

Music Emotion Recognition (MER) is a study to recognize emotion in a music or song. MER is still challenging in the music world since recognizing emotion in music is affected by several features; audio is one of them. This paper uses a deep learning approach for MER, specifically Convolutional Neural Network (CNN) and Convolutional Recurrent…

Waste is currently a serious problem often found in rural areas, rural areas, and even industrial areas. Waste is a side effect of activities carried out by humans to meet social or industrial needs. Increasing human productivity will also increase the amount of waste produced. To overcome this, a sorting management system is needed. Good…

Automatic Speech Recognition (ASR) technology has the potential to improve the learning experience of students in the classroom. This article addresses some of the key theoretical areas identified in the pursuit of implementing a speech recognition system, capable of lesson summary generation in the educational setting. The article discusses: some of the applica- tions of…

Rated a high-risk cyber-attack type, Advanced Persistent Threat (APT) has become a cause for concern to cyber security experts. Detecting the presence of APT in order to mitigate this attack has been a major challenge as successful attacks to large organizations still abound. Our approach combines static rule anomaly detection through pattern recognition and machine…

Forecasting the gold price movement’s volatility has essential applications in areas such as risk management, options pricing, and asset allocation. The multivariate model is expected to generate more accurate forecasts than univariate models in time series data like gold prices. Multivariate analysis is based on observation and analysis of more than one statistical variable at…

In view of the current short-term traffic flow prediction methods that fail to fully consider the spatial correlation of traffic flow, and fail to make full use of historical data features, resulting in low prediction accuracy and poor robustness. Therefore, in paper, combining Non-negative Matrix Factorization (NMF) and LSTM model Based on Attention Mechanism (AttLSTM),…

Software maintenance contributes the majority of software system life cycle costs. However, existing approaches with automated code analysis are limited by accuracy and scope. Using human-assessed methods or implementing quality standards are more comprehensive alternatives, but they are much more costly for smaller organizations, especially in open- source software projects. Instead, bugs are generally used…

In the phosphate industry, sulfuric acid is a key compound in phosphoric acid and fertilizer production. Industrially, the sulfuric acid H2SO4 is made generally in a sequence of three main steps: burning liquid sulfur with air, catalytic oxidation of sulfur dioxide SO2 to sulfur trioxide SO3, and formation of H2SO4 by the reaction of H2O…

Sustainable urban development and utilization of Internet of Things (IoT) technology is driving cities globally to evolve into Smart Cities (SC). The power of IoT services and applications will enable public agencies to provide personalized services to the citizens and inevitably improves their much-needed quality of life. However, although the use of IoT technology proves…

Robotic arms or industrial robots are a machinery that is widely used in the medical and military industries because it is a flexible, highly accurate and reliable. It is very necessary to work in complex tasks requiring more accuracy than humans can work. This paper presents an estimate of the standard uncertainty of 6 DOF…

Contracts may range from a simple agreement between a tenant and a landlord or a gym contract, or it could be as important as an employment or marital contract. No matter the level of importance, individuals are legally obligated to obey and carry out all clauses in the contract. In this paper, we have identified…

Recently, numerous scholars have suggested fuzzy time series (FTS) models to forecast many different fields. One of the vital issues for high accurate forecasting in FTS model is method of partitioning in Universe of discourse (UoD). In this research, we propose a novel FTS model, which is established by using hedge algebra (HA) and particle…

For systems using rotating machinery, diagnosing the faults of the rotating machinery is critical for system maintenance. Recently, a machine learning algorithm has been employed as one of the methods for diagnosing the faults of rotating machinery. This algorithm has an advantage of automatically classifying faults without an expert knowledge. However, despite a good training…

In this work we propose an algorithm for Peruvian counterfeit banknotes detection. Our algorithm operates in banknotes with 50, 100 and 200 soles denominations that were manufactured from 2009 onwards. This algorithm offers an automatic diagnosis based on digital image processing and support vector machines (SVM). Current Peruvian counterfeit detection systems are specially designed to…

Online fashion market is constantly growing, and an algorithm capable of identifying garments can help companies in the clothing sales sector to understand the profile of potential buyers and focus on sales targeting specific niches, as well as developing campaigns based on the taste of customers and improve user experience. Artificial Intelligence approaches able to…

Addiction such as tobacco smoking affects the human brain and thus causes significant changes in the brainwaves. The changes in brain wave due to smoking can be identified by focusing on changes in electroencephalogram pattern, extracting different time-frequency domain features. In this aspect, a laboratory-based study has been presented in this paper, for assessing the…

The dramatic growth of social media during the last years has been associated with the emergence of a new bullying types. Platforms such as Facebook, Twitter, YouTube, and others are now privileged ways to disseminate all kinds of information. Indeed, communicating through social media without revealing the real identity has emerged an ideal atmosphere for…

E-learning, among the most prominent modes of learning, offers learners the opportunity to attend online courses. To improve the quality of online learning, social learning through social networks promotes interaction and collaboration among learners. As part of the learning process management in these environments, the implementation of recommendation systems facilitates the provision of content adapted…

The paper treats a problem for detection and recognition objects in computer vision sector, where researchers recommended OpenCV software and development tool, it’s several and better-remembered library resource for isolating, detecting, and recognition of particular objects, what we would find an appropriate system for detecting and recognition traffic roads signs. The robustness with optimization is…