The high school students must be observed for their slow learning or quick learning abilities to provide them with the best education practices. Such analysis can be perfectly performed over the student performance data. The high school student data has been obtained from the schools from the various regions in Punjab, a pivotal state of India. The complete student data and the selective data o...

According to existing literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA) systems and three-stage iterative geographic object-oriented image analysis (GEOOIA) systems, where GEOOIA  GEOBIA, remain affected by a lack of productivity, general consensus and research. To outperform the degree of automation, accur...

This paper presents a multi-stage approach toward the robust classification of travel-modes from GPS traces. Due to the fact that GPS traces are often composed of more than one travel-mode, they are segmented to find sub-traces characterized as an individual travel-mode. This is conducted by finding individual movement segments by identifying stops. In the first stage of classification three ma...

This paper addresses learning and recognition of human behaviour models from multi-modal observations in a smart home environment. The proposed approach successfully implements concurrent Hidden Markov Models that identify the occurring situation. This approach corresponds to the highlevel part from a framework to obtain high-level classification of human behaviour analysis. The results were ob...

This paper proposes an identification framework of the possible criminal offences charges based on textual criminal cases of the Civil Law system. The framework is constructed as the model, devised as a multi-stage based on the defined charges structure in criminal law codes. The first stage is to modularly identify type of action which is designed based on the offences charges abstractly categ...

The solution of binary classification problems using the Support Vector Machine (SVM) method has been well developed. Though multi-class classification is typically solved by combining several binary classifiers, recently, several multi-class methods that consider all classes at once have been proposed. However, these methods require resolving a much larger optimization problem and are applicab...

classification ensemble, which uses the weighed polling of outputs, is the art of combining a set of basic classifiers for generating high-performance, robust and more stable results. this study aims to improve the results of identifying the persian handwritten letters using error correcting output coding (ecoc) ensemble method. furthermore, the feature selection is used to reduce the costs of ...

Conventional data envelopment analysis (DEA) models are used to measure efficiency score of production systems when they are considered as black boxes and their internal relationship is ignored. This paper deals with a common special case of network systems which is called multi-stage production system and can be generalized to many organizations. A multi stage production system has some stages...