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Cloud Computing is the key technology of today's cyber world which provides online provisioning of resources on demand and pay per use basis. Malware attacks such as virus, worm and rootkits etc. are some threats to virtual machines (VMs) in cloud environment. In this paper, we present a system call analysis approach to detect malware attacks which maliciously affect the legitimate programs running...
With the increased volume of patent databases during the past years, it becomes necessary for companies to correctly classify and identify innovative patents in a timely manner though the use of automation. Although many patent classification methods have been proposed, the accuracy remains the most challenging factor for the success of a classification model. This paper presents an empirical study...
In this era of globalisation and technology, determining the gender of a person from forenames has numerous applications especially in the machine translation and natural language processing fields. In this paper, we used a supervised machine learning approach to classify 10000 first names into either a male or female name. The names were manually extracted from an online telephone directory and then...
Radio frequency fingerprinting, based on Wi-Fi signals is a popular approach for indoor localization. Recently a few works have explored applicability of machine learning techniques to this problem. However, the challenging task of accurately finding the position depends on prior efforts of fingerprinting. Another challenge is that, distance sensitivity of signal strength depends on proximity to the...
Making information stored in database accessible for non expert users, has become one of the problems of great interest for the research community of database querying system. Hence for overriding the complexity of using database language such as Structured Query Language (SQL), the using of natural language can be a very important and simple method. But without helps computer cannot understand this...
Facial micro-expression refers to split-second muscle changes in the face, indicating that a person is either consciously or unconsciously suppressing their true emotions. Although these expressions are constantly occurring on people faces, they were easily ignored by people with the eye blinking. That is to say, most people don't notice them and it is the true representation of people emotions and...
This paper presents a hybrid filter-wrapper approach to sentiment polarity classification. It is a two-phase feature selection method that differs from other approaches in a main aspect: an initial preprocessing step with typical data mining filters. After applying such filters, a wrapper-based feature selection method, which integrates the genetic algorithm and the support vector machine classifier,...
This paper presents a novel method for fingerprint ROI (region of interest) segmentation using Deep learning technique — Convolutional Neural Networks. Experimental results, obtained using a publicly available test database of 200 fingerprint images in two variations — with and without Gaussian noise, demonstrate that this method is competitive with Fourier coefficients and NN based method for fingerprint...
The adequate representation of states in the construction of intelligent agents is fundamental for allowing them to achieve a satisfactory performance, principally for those that actuate in a competitive environment that possesses a high state space. One particular type of representation that is very appropriate for these situations is the NetFeatureMap, which describes by means of features the relevant...
The overall goal of our Software Engineering Teamwork Assessment and Prediction (SETAP) project is to develop effective machine-learning-based methods for assessment and early prediction of student learning effectiveness in software engineering teamwork. Specifically, we use the Random Forest (RF) machine learning (ML) method to predict the effectiveness of software engineering teamwork learning based...
Configuration bugs are among the dominant causes of software failures. Software organizations often use bug tracking systems to manage bug reports collected from developers and users. In order for software developers to understand and reproduce configuration bugs, it is vital for them to know whether a bug in the bug report is related to configuration issues, this is not often easily discerned due...
Twitter1 is a micro-blogging website which provides platform for people to share and express their views about topics, happenings, products and other services. Tweets can be classified into different classes based on their relevance with the topic searched. Various Machine Learning algorithms are currently employed in classification of tweets into positive and negative classes based on their sentiments,...
Automatic prediction of photo aesthetic quality is useful for many practical purposes. Current computational approaches typically solved this problem by assigning a categorical label (good or bad) to a photo. However, due to the subjectivity and complexity of humans aesthetic judgments, only a categorical label is insufficient to represent humans perceived aesthetic quality of a photo. This paper...
The success of the deep learning and specifically learning layer by layer led to many impressive results in several contexts that include neural network. This gave us the idea to apply this principle of learning on wavelet network because it is an active research topic at the moment. This paper present our approach for image classification by the combination of two techniques of learning: the wavelet...
GitHub is one of the most commonly used web-based code repository hosting service. Majority of projects hosted on GitHub are really small but, on the other hand, developers spend most of their time working in medium to large repositories. Developers can freely join and leave projects following their current needs and interests. Based on real data collected from GitHub we have tried to predict which...
This paper presents a new flexible approach to predict the gender of the writers from their handwriting samples. Handwriting features can be extracted from different methods. Therefore, the multi-feature sets are irrelevant and redundant. The conflict of the features exists in the sets, which affects the accuracy of classification and the computing cost. This paper proposes a Mutual Information (MI)...
The lung cancer is the reason of a lot of deaths on population around the world. An early diagnosis brings a most curable and simpler treatment options. Due to complexity diagnosis of small pulmonary nodules, Computer-Aided Diagnosis (CAD) tools provides an assistance to radiologist aiming the improvement in the diagnosis. Extracting relevant image features is of great importance for these tools....
We propose a Convolutional Neural Network model to learn spatial footstep features end-to-end from a floor sensor system for biometric applications. Our model's generalization performance is assessed by independent validation and evaluation datasets from the largest footstep database to date, containing nearly 20,000 footstep signals from 127 users. We report footstep recognition performance as Equal...
This paper proposed a novel hybrid transactional memory(HyTM) that exploits the benefits of both Haswell's RTM(restricted transactional memory) and software transactional memory(STM). Unlike the existing HyTMs, the proposed HyTM can predict and resolve conflicts between transaction running concurrently by using a prediction matrix and transaction metadata. Also the proposed HyTM can provide the optimal...
Through the processes set out by Learning Analytics, this paper describes a decision making model which supports the managers of higher education institutions at the moment of making academic decisions. In the analysis and requirements phase, the importance of creating and categorizing indicators is presented in detail, thereby facilitating the finding of hidden patterns in the educational information...
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