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A bio-inspired model for head pose recognition is described in this paper. The bio-inspired model recognizes the head by using gray scale information as well as the silhouette of the person. A set of descriptors is generated from this analysis by a hierarchical model based on the visual cortex. Then the descriptors are classified by a multilayer perceptron artificial neural network to identify the...
The paper presents a system to accurately differentiate between unique individuals by utilizing the various eye-movement biometric features. Eye Movements are highly resistant to forgery as the generation of eye movements occur due to the involvement of complex neurological interactions and extra ocular muscle properties. We have employed Linear Multiclass SVM model to classify the numerous eye movement...
Even though artificial vision has been in development for over half a century it still fares poorly when compared to biological vision. The processing capabilities of biological visual systems are vastly superior in terms of power, speed, and performance. Inspired by this robust performance artificial vision systems have sought to take inspiration from biology by modeling aspects of biological vision...
The worldwide increase in the integration of photovoltaic generation has necessitated improvements in the forecasting approaches. Two models are proposed to cater for PV generation forecasts for few minutes to several hours look-ahead times. A very fast and accurate prediction model based on extreme learning machine is deployed for day-ahead prediction. Moreover, an adaptive and sequential model is...
The relationship between fire and long-term trends in tallgrass prairie vegetation was assessed at Fort Riley and Konza Prairie Biological Station (KPBS) in Kansas. Linear trends of surface greenness were previously estimated using BFAST and MODIS MOD13Q1 NDVI composite images from 2001 to 2010. To explain trends, fire frequency and seasonality (fire regime) was determined and each site was divided...
Age classification is a useful tool for creating an automatic system that can identify or verify and classify a person into an age group. In this paper a unique approach for classifying different aged people based on their forearm electromyography (EMG) signal, which has different characteristics from teenager to old is proposed. The Electromyography signal generates from the movement of brachioradialis...
In this paper we examine efficacy of occlusion-free appearance learning for part based model. Appearance modeling with less accurate appearance data is problematic because it adversely affects entire learning process. We evaluate the effectiveness of excluding occluded body parts to be modeled for better appearance modeling process. To meet this end, We employ a simple but effective occlusion detection...
Interconnected computing units are used more and more in our daily lives, starting from the transportation systems and ending with gas and electricity distribution, together with tenths or hundreds of systems and sensors, called critical infrastructures. In this context, cyber protection is vital because they represent one of the most important parts of a country's economy thus making them very attractive...
In the article problems of control in complex modern technical systems are considered. The main features of these systems are globality, large scalability, heterogeneity, situation uncertainty. The analysis of the existing approaches to solving given problem using self-organization methods and multiagent technology is carried out. The conclusion about necessity of development self-organizing systems...
A circuit architecture modelling rate-independent hysteretic phenomena is presented and discussed. The core of the circuit is a ladder structure with longitudinal nonlinear resistors and transverse linear capacitors. In a separate loop, a linear combination of input and capacitor voltages provides the driving voltage for a resistor with monotonic, piecewise-linear driving-point characteristic. The...
This paper describes feed-forward sigmoid connectionist models to classify healthy and mastitis Sahiwal cows using pH, electrical conductivity, temperature (udder, milk and skin), milk somatic cells, milk yield and dielectric constant. Mastitis was determined according to two criteria: Somatic Cell Counts (SCC) over 2,00,000/ml and SCC over 5,00,000/ml. Cows with milk SCC below 2,00,000 were categorised...
Artificial Neural networks are a major soft-computing technology. Multi-layer perceptron network with back propagation training algorithm, are used in various scientific and engineering areas. In order to enhance the ability of data interpretation and to provide better solutions for some applications, artificial neural networks are integrated with fuzzy logic and wavelet based neural network. Along...
Human tracking across multiple cameras is highly demanded for large scale video surveillance. To successfully track human across multiple uncalibrated cameras that have no overlapping field of views, a system to train more reliable camera link models is proposed in this paper. We employ a novel approach of combining multiple camera links and building bidirectional transition time distribution in the...
We have designed a Turkish dictation system for Broadcast news applications. Turkish is an agglutinative language with free word order. These characteristics of the language result in the vocabulary explosion, large number of out-of-vocabulary (OOV) words and the complexity of the N-gram language models in speech recognition when words are used as recognition units. Therefore, we proposed new recognition...
The Enterprise Resource Planning (ERP) system is an integrated software package applied by many enterprises as an operations platform over the past years. However, according to an industrial survey, the failure rate of ERP system implementation is relatively high because of high implementation costs and long implementation time, incapable implementation teams, process misfits, resistance to change...
Work in progress for the development of a novel virtual training environment for training a kidney biopsy procedure is presented. Our goal is to provide an affordable high fidelity simulation through the integration of some of the latest off-the-shelf technology components. The range of forces that are encountered during this procedure have been recorded using a custom designed force sensitive glove...
Adoption of reverse logistics practices in existing supply chains has emerged as an important incentive for manufacturers to gain financial and competitive advantage. Growing environmental and social concerns are driving firms to incorporate sustainable strategies into designing of their reverse supply chain (RSC) network. A sustainable RSC can be attained by following the triple bottom line (TBL)...
The selection of the most suitable SG with regard to a given learning objective seems to be less well addressed in the literature. This paper reports on the application a new Characterizing and Assessing Serious Games Grid (CASGG) in the higher education field with 41 graduate students to assess their learning performance according to one leaning objective using a specific SG. The tested SG was Star...
In order to predict the intensity of valence and arousal of the terms contained in a blog post we use the text mining subfield such as emotion mining. It is used to infer the opinion or emotion or sentiment and represent the inference result in the form of ordinal states. Here the content of the blog post is first analyzed to identify the relevant content using concept search engine(CSE) and topic...
This paper presents a new approach for shortterm load forecasting using the participatory learning paradigm. Participatory learning paradigm is a new training procedure that follows the human learning mechanism adopting an acceptance mechanism to determine which observation is used based upon its compatibility with the current beliefs. Here, participatory learning is used to train a class of hybrid...
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