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Protein function prediction is an active research area in bioinformatics. Protein functions are highly related to their structures. Therefore, effective structure based protein representations are required. Pires et al. [BMC Genomics, 12, S12 (2011)] proposed a cutoff scanning matrix (CSM) method for protein representation that utilizes distance patterns between protein residues and a maximum cutoff...
We explore the feasibility of measuring learner engagement and classifying the engagement level based on machine learning applied on data from 2D/3D camera sensors and eye trackers in a 1:1 learning setting. Our results are based on nine pilot sessions held in a local high school where we recorded features related to student engagement while consuming educational content. We label the collected data...
Big data is a set of very large and complex data that is hard to load on computers. The main challenge in big data world is related to their search, categorize and analyze specially, when they are unbalanced. Despite, there are a lot of works in the field of big data but analyzing unbalanced big data is still a fundamental challenge in this area. In this paper we try to solve the problem of RSIO-LFCM...
Spectrum-based fault localization techniques leverage coverage information to identify the faulty elements of the program via passed and failed runs. However, the effectiveness of these techniques can be affected adversely by coincidental correctness, which occurs when faulty elements are executed, but the program produces the correct output. This paper proposes a clustering-based strategy to improve...
The ability to determine mood is one of fundamental challenges in affective computing. In this paper, we present a novel approach for mood detection via emotional variations. In this approach, the mood is considered as a low magnitude and more stable, i.e. low frequency, emotion that can be detected using emotion detection approaches. A Bayes classification is applied on a feature vector composed...
Existing algorithms of mining preferred browsing paths just consider the influence of user visiting times, but ignore the accuracy influenced by other factors. In order to solve the problem, an improved algorithm which imports page similarity and support-preference concepts is proposed. Firstly a Web-log-based user access matrix is set up. Then by calculating the angel cosine similarity and support-preference,...
This paper presents an empirical study on selecting a small amount of useful unlabeled data with which the classification accuracy of semi-supervised learning algorithms can be improved. In particular, a hybrid method of unifying the simply recycled selection method and the incrementally reinforced selection method is considered and empirically evaluated. The experimental results, obtained using well-known...
Network intrusion is recognized as a chronic and recurring problem. Hacking techniques continually change and several countermeasure methods have been suggested in the literature including statistical and machine learning approaches. However, no single solution can be claimed as a rule of thumb for the wide spectrum of attacks. In this paper, a novel methodology is proposed for network intrusion detection...
To explore the academic progression of the students, higher educational institutions need better assessment and prediction tools. In this regard, Multilayer Perceptron (MLP) based prediction application is proposed to predict the Grade Point Average (GPA) of the Undergraduate students by the make use of student's Previous Academic History, Regularity, No. of Backlogs, Degree of Intelligence, Working...
In order to expand the application of rough set operator, we analyzed two kinds of operator and the relationship between conversion structure based on the degree of rough set operator and variable precision rough set operator. By introducing a parameter, we give a Graded-Variable precision rough set model. And we get the Upper approximation operator and Lower approximation operator and some of its...
To deal with the existence of malicious secondary users bring damage to the performance of cooperative spectrum sensing, a trust game model named FRTrust is proposed. In FRTrust, the reputation status is used to describe the performance of a secondary user in cooperative spectrum sensing process. It encourages secondary users to choose positive and honest behavior strategies for greater and long term...
Physical activities play important role in having better health. However, due to the nature of our jobs, most of us have developed sedentary habits and it is very seldom that we find dedicated time for exercise or other physical activities. Sedentary behavior has been identified as an important factor in preventing good health and there is a need to push adults to carry out physical activities regularly,...
This work addresses to problems in design and testing of the computer systems and their components, which are considered in content of natural development of the resources for solving these challenges. The resources are examined as target and natural. The target resources contain the models, methods and means. The natural resources are considered like their particularities. Development of the resources...
Error concealment is a useful method for improving the damaged video quality in the decoder side. In this paper, a dynamic method with low computational complexity is presented to improve the visual quality of videos when up to 50% of the frames are damaged. In the proposed method, temporal replacement and the improved outer boundary matching algorithm are used for dynamical error concealment in inter-frames...
In several research areas, e.g. in the field of human-robot interaction, ratings or questionnaires are applied using offline and online methods. An argument for the use of online methods is the efficiency. By using the Internet, data can be collected much faster than in an offline experiment and the administration effort is very low. The goal of our study was to find out, if there is a difference...
Different etiquette of software could trigger different attitudes and behaviors of users. This paper conducted a series of word-learning studies in which users either received polite feedback offering compliments and encouragements, or impolite feedback belittling users. Through the analysis on the results of e-learning experiment and post-test questionnaires, it was found that the polite feedback...
Feature selection is one of several factors affecting text classification systems. Feature selection aims to choose a representative subset of all features to reduce the complexity of classification problems. Usually a single method is used for feature selection. For English, several attempts were reported examining the combination of different feature selection methods. To the best of our knowledge...
Multi-granulation rough set (MGRS) is a new research direction of rough set theory in recent years. This paper introduces the MGRS into the incomplete fuzzy information systems based on dominance relation. A model of dominance-based multi-granulation rough set (DMGRS) is established. Then a number of important properties are obtained. Moreover, a conclusion is presented by comparing the approximation...
POI updates have a direct influence on data up-to-date state, thereby affecting the data value of POI. Aimed at solving the problem facing POI rapid and accurate update, an update approach for POI based on Weibo check-in data is brought forward in this paper. Firstly, regarding to the quality issue of check-in data, a pre-processing approach with spatial registration is proposed. Then, a POI data...
User-based collaborative filtering recommends items to users by analyzing user preferences. Nearest neighbors are identified based on similarity between users and preference prediction of items is performed by using the nearest neighbors. The prediction accuracy depends on how the nearest neighbors are identified among users. In this paper, we propose link strength-based user modeling by applying...
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