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Bull service is the natural copulation by a purebred male carabao with a female counterpart. This is part of the bull loan agenda of the Philippine Carabao Center-Visayas State University (PCC-VSU), one of the 12 regional centers of PCC. For the past years, PCC-VSU used averaging of bull services count of previous years and sometimes…

This paper studies and compares the effectiveness of four different features and their combinations on the recognition accuracy of handwritten Bangla characters. The longest run, chain code histogram, shadow, and Gabor filter-based features and their eleven (11) combinations were tested on a standard Bangla database of 15; 000 basic handwritten characters to compare their recognition…

Recurrent Neural Networks has been widely used by researchers in the domain of weather prediction. Weather Prediction is forecasting the atmosphere for the future. In this proposed paper, Deep LSTM networks has been implemented which is the variant of RNNs having additional memory block and gates making them capable of remembering long term dependencies. Fifteen…

This paper focuses on the issue of distributed reinforcement learning (RL) for decision-making in cooperative multi-agent systems. Although this problem has been a topic of interest to many researchers, results obtained from these works aren’t sufficient and several difficulties have not yet been resolved, such as, the curse of dimensionality and the multi-agent coordination problem.…

An emerging trend has been observed in the Trust and Reputation (T & R) systems in field of decision-making support for a majority of the provisions propagated by the Internet. It is the extreme importance that peers (users) are able to trust each other and rely on them for file sharing and for services. This…

In order to further improve the feature extraction performance of the convolutional neural networks, we focus on the selection and reorganization of key features and suspect that simple changes in the pooling layers can cause changes in the performance of neural networks. According to the conjecture, we design a funnel convolution module, which can filter…

Noninvasive measurement of skin tissue oxygen saturation, StO2, is of interest especially in the studies of wound healing and detection of vascular diseases. This work aims to compare Partial Least Square (PLS) regression, K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN) technique in the prediction of StO2 using spectral data obtained from Monte Carlo simulations.…

In this paper, we present an experimental approach that allows a humanoid robot to effectively plan and execute whole body motions, like climbing obstacles and straight stairs up or down, besides jumping over obstacles using only on-board sensing. Re- liable and accurate motion sequence for humanoid employed in complex indoor en- vironments is a necessity…

E-mail is one of the media services used at the contact center. The challenge faced by e-mail services is how to handle e-mails that enter large quantities every day efficiently to provide fast and appropriate service to customers. The purpose of this study is to find which method has the best accuracy in classifying emails…

The greenhouse climate system is very hard to manipulate because the variables involved are closely correlated. This study aims to enhance the regulation performance of greenhouse climate system based on adaptive neural-fuzzy inference system (ANFIS). The ANFIS is a hybrid technique that incorporates the fuzzy logic theory and artificial neural network algorithms. The employed control…

Over the past decades, huge efforts have been devoted for image enhancement under uncontrolled scene such as fog and haze. This work proposes Multi-stage de-hazing approach for improving the quality of hazy images. Four main stages are introduced, in our approach, to achieve an automated, efficient and robust de-hazy processing. The first two stages are…

A fuzzy system is a rule-based system that uses human experts’ knowledge to make a particular decision, while fuzzy modeling refers to the identification process of the fuzzy parameters. To generate the fuzzy parameters automatically, an optimization method is needed. One of the suitable methods provides the Firefly Algorithm (FA). FA is a nature-inspired algorithm…

This paper presents the setup of eye tracking calibration methodology and the preliminary test results of the training model from the eye tracking data. Eye tracking requires good accuracy from the calibration process of the human eyes feature extraction from facial region. Viola-Jones algorithm is applied for this purpose by using Haar Basic feature filters…

Recitation and listening of the Holy Quran with Tajweed is an essential activity as a Muslim and is a part of the faith. In this article, we use a machine learning approach for the Quran Reciter recognition. We use the database of Twelve Qari who recites the last Ten Surah of Quran. The twelve Qari…

This paper addresses the generation of stylized texts in a multilingual setup. A long short-term memory (LSTM) language model with extended phonetic and semantic embeddings is shown to capture poetic style when trained end-to-end without any expert knowledge. Phonetics seems to have a comparable contribution to the overall model performance as the information on the…

Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of…

Anomaly detection aims at identification of suspicious items, observations or events by differing from most of the data. Intrusion Detection, Fault Detection, and Fraud Detection are some of the various applications of Anomaly Detection. The Machine learning classifier algorithms used in these applications would greatly affect the overall efficiency. This work is an extension of…

With the progress of IoT, everything is going to be connected to the network. It will bring us a lot of benefits however some security risks will be occurred by connecting network. To avoid such problems, it is indispensable to strengthen security more than now. We focus on personal authentication as one of the security.…

TransJakarta is one of the methods to reduce congestion in Jakarta. However, the number of TransJakarta users compared to number of private vehicle users is very small, only 24% of the total population in Jakarta. The purpose of this research is to know public opinions about TransJakarta whether positive or negative by doing sentiment analysis…

In this paper, a multiple-objective Metaheuristics study is discussed. Initially, three mono-objective metaheuristics will be explored in order to design and optimize Radio-Frequency integrated inductors. These metaheuristics are: An evolutionary algorithm called The Differential Evolution (DE), An algorithm supported on Newton’s laws of gravity and motion called the Gravitational Search Algorithm (GSA) and, finally, A…

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…

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…

This work deals with the issue of understanding a user’s behaviour as this is expressed via a gamified application. The notion of ontologies and the association of concepts in relevance to decisions that have to be made is used. The current work introduces a new process-based approach, based on collected large log files and associations…

The increasing number of breast cancer in recent years has attracted numerous researchers’ attention. Several techniques of Computer Aided Diagnosis System have been proposed as alternative solutions to diagnose breast cancer. The flaw of simply using the naked eye to see the differences between normal and with cancer mammogram images makes the texture analysis play…