Abstract By determining the hydraulic flow units (HFUs) in reservoir rock and examining distribution of porosity permeability variables, it is possible to identify areas with suitable quality. In conventional methods, HFUs are determined using core data. This while considering non-continuity data along well, there a great uncertainty generalizing their results entire depth reservoir. Therefore,...

For software development, availability of resources is limited, thereby necessitating efficient and effective utilization of resources. This can be achieved through prediction of key attributes, which affect software quality such as fault proneness, change proneness, effort, maintainability, etc. The primary aim of this chapter is to investigate the relationship between object-oriented metrics ...

Protein fold prediction problem is considered as a key point to protein structure recognition and structural discoveries. Recent advances in pattern recognition field brought a great interest to apply pattern classification techniques to tackle this problem. From the pattern recognition point of view, the protein fold prediction problem can be expressed as a multi-class classification task that...

We propose a multi-stock automated trading system that relies on a layered structure consisting of a machine learning algorithm, an online learning utility, and a risk management overlay. Alternating decision tree (ADT), which is implemented with Logitboost, was chosen as the underlying algorithm. One of the strengths of our approach is that the algorithm is able to select the best combination ...

Emotional illiteracy exists in current e-learning environment, which will decay learning enthusiasm and productivity, and now gets more attentions in recent researches. Inspired by affective computing and active listening strategy, in this paper, a research and application framework of recognizing emotion based on textual interaction is presented first. Second, an emotion category model for e-l...

The global expansion of the sports betting industry has brought prediction outcomes sport events into foreground scientific research. In this work, soccer outcome methods are evaluated, focusing on Greek Super League. Data analysis, including data cleaning, Sequential Forward Selection (SFS), feature engineering and augmentation is conducted. most important features used to train five machine l...

In this research project a set of computer vision algorithms for interpretation of the non-urban environment from low altitude aerial images is presented. Considering the size and spread of natural resources in non-urban areas, automating the task of gathering information about various land-covers is of particular importance. The utilization of videos captured by small aerial vehicles has many ...

Short overview of the Chapter—Motion estimation necessitates an appropriate choice of similarity function. Because generic similarity functions derived from simple assumptions are insufficient to model complex yet structured appearance variations in motion estimation, we propose to learn a discriminative similarity function to match images under varying appearances by casting image matching int...

In this paper we investigate how much various classes of Web spam features, some requiring very high computational effort, add to the classification accuracy. We realize that advances in machine learning, an area that has received less attention in the adversarial IR community, yields more improvement than new features and result in low cost yet accurate spam filters. Our original contributions...

The objective of this paper is to present and discuss the results of a link mining algorithm called CorpInterlock that integrates the metrics of an extended corporate interlock (social network of directors and financial analysts) with corporate fundamental variables and analysts’ predictions (consensus) in order to forecast the trend of the cumulative abnormal return and earnings surprise using...