Search Results

Environmental sound recognition (ESR) has become a hot topic in recent years. ESR is mainly based on machine learning (ML) and ML algorithms require first a training database. This database must comprise the sounds to be recognized and other related sounds. An ESR system needs the database during training, testing and in the production stage.…

Nowadays, Ischemic Heart Disease (IHD) (Heart Attack) is ubiquitous and one of the major reasons of death worldwide. Early screening of people at risk of having IHD may lead to minimize morbidity and mortality. A simple approach is proposed in this paper to predict risk of developing heart attack using smartphone and data mining. Clinical…

Described herein is a general-purpose software engineering architecture for autonomous, computer controlled opponent implementation in modern maneuver warfare simulation and training. The implementation has been developed, refined, and tested in the user crucible for several years. The approach represents a hybrid application of various well-known AI techniques, including domain modeling, agent modeling, and object-oriented programming.…

In Computer Aided Diagnosis (CAD) tools, vertebra localization and detection are the essential steps for the diagnosis of cervical spine injuries. The accurate localization leads to accurate treatment, which is more challenging in case of poor contrast and noisy radiographs. This paper targets c-spine radiographs for the localization of vertebra using different vertebra templates, vertebra…

The objective of this paper is to investigate the use of the 1-D wavelet analysis to extract several patterns from signals data sets collected from healthy and faulty input-output signals of control systems as a preliminary step in real-time implementation of fault detection diagnosis and isolation strategies. The 1-D wavelet analysis proved that is an…

To perform an exploration process over complex structured data within unsupervised settings, the so-called kernel spectral clustering (KSC) is one of the most recommended and appealing approaches, given its versatility and elegant formulation. In this work, we explore the relationship between (KSC) and other well-known approaches, namely normalized cut clustering and kernel k-means. To do…

Electroencephalography (EEG) can globally monitor neural activity in millisecond scale, which is critical for identifying causality of human brain functions and mechanisms. However, to obtain accurate EEG stimulation-response relationship one usually needs to repeat multiple-ten times of stimulation-response recording to average out background signals of other irreverent brain activities, making real-time monitoring difficult to be…

This paper is an extension of work originally presented at conference Applied Machine Intelligence and Informatics (SAMI), 2017 IEEE 13th International Symposium. The article performs a comparative study between the image compression technique Local Binary Compressed format (LBC) proposed by the authors and the standard image compression techniques used today (BMP, JPEG, PNG and GIF).…

Abstract— The process of mapping large numbers of markers is computationally complex, as the increase of numbers of markers results in an exponential increase in the mapping runtime. Also, having unreliable markers in the dataset adds more complexity to the mapping process. In this research, we have addressed these two issues and proposed our solution.…

Listening to auditory stimuli during study can give positive and negative influence on human cognitive processing. Thus, it has attracted researchers to conduct studies using various types of auditory stimuli. Some researchers believe that Mozart music and white noise are able to give positive influence on cognitive performance. However, most of the past studies gave…

Epilepsy is a neurological disorder which is most widespread in human beings after stroke. Approximately 70% of epilepsy cases can be cured if diagnosed and medicated properly. Electro-encephalogram (EEG) signals are recording of brain electrical activity that provides insight information and understanding of the mechanisms inside the brain. Since epileptic seizures occur erratically, it is…

A functional near-infrared spectroscopy (fNIRS) can be employed to investigate brain activation by measuring the absorption of near-infrared light through the intact skull. The general linear model (GLM) as a standard model for fMRI analysis has been applied to functional near-infrared spectroscopic (fNIRS) imaging analysis as well. The GLM has drawback of failure in fNIRS…

The research in Neuro-Prosthetics is gaining more significance and popularity as the advancement in prosthetics control allows amputees to perform even more tasks. Indeed, the improvement of classification accuracy is a challenge in prosthetics control. In this research, a system is developed in order to improve the multiclass classification rate. Two classifiers namely Artificial Neural…

In this paper a novel approach to extract 2D skeleton information (skeletonization) from natural image is proposed. The work presented here is the extension of our previous paper presented at the International Sympsosium on Multimedia 2016. In the past work, a threshold based method is utilized. Here the algorithm is further improved by using a…

Classification of EEG signals in self-paced Brain Computer Interfaces (BCI) is an extremely challenging task. The main difficulty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing…

Diffusion MRI-based tractography, which is built by connecting the principal components of the estimated water diffusion pattern, is used to elucidate neuronal connectivity. However, the anatomical accuracy of the method is affected by factors such as noise and imaging misalignments. In this manuscript, we present a method to clean diffusion datasets by rotating the diffusion…

Recently, the field of prosthetics has seen many accomplishments especially with the integration of technological advancements. In this paper, different arm types (robotic, surgical, bionic, prosthetic and static) are analyzed in terms of resistance, usage, flexibility, cost and potential. Most of these techniques have some problems; they are extremely expensive, hard to install and maintain…

Discretization is the process of converting numerical values into categorical values. Contemporary literature study reveals that there are many techniques available for numerical data discretization. The performance of classification method is dependent on the exploitation of the data discretizing method. In this article, we investigate the effect of discretization methods on the performance of associative…

The availability of traffic data and computational advances now make it possible to build data-driven models that capture the evolution of the state of traffic along modeled stretches of road. These models are used for short-time prediction so that transportation facilities can be operated in an efficient way that guarantees a high level of service.…

Jaw cyst is one of the most common pathology observed in the field of dentistry. Early detection of the cystic lesion will help the surgeons to take appropriate therapeutic measures after a thorough diagnostic procedure. One of the challenging task for surgeons is to differentiate the cysts from the other pathologies. The appearance of these…

The presence of microaneurysms(MAs) in retinal images is a pathognomonic sign of Diabetic Retinopathy (DR). This is one of the leading causes of blindness in the working population worldwide. This paper introduces a novel algorithm that combines information from spatial views of the retina for the purpose of MA detection. Most published research in the…

This paper proposes a novel intelligent technique that has been designed to optimise the performance of Software Defined Networks (SDN). The proposed hybrid intelligent system has employed integration of intelligence-based optimisation approaches with the artificial neural network. These heuristic optimisation methods include Genetic Algorithms (GA) and Particle Swarm Optimisation (PSO). These methods were utilised separately…

Small animal modeling is an exciting research field where human pathogenic frameworks can be replicated in a controlled environment. Accurate Imaging is in high demand when modeling abnormalities and, magnetic resonance imaging plays a vital role due to its demonstrated lowest intrusion when compared with other imaging methods. However, the required high-resolution yields low-quality images…

The evolution of technology has changed the face of education, especially when combined with appropriate pedagogical bases. This combination has created innovation opportunities in order to add quality to teaching through new perspectives for traditional methods applied in the classroom. In the Health field, particularly, augmented reality and interaction design techniques can assist the teacher…

Breast cancer is one of the most common cancers among female diseases all over the world. Early diagnosis and treatment is particularly important in reducing the mortality rate. This research is focused on the prevention of breast cancer, therefore it is important to detect micro-calcifications (MCs) which are a sign of early stage breast cancer.…