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The imbalanced learning problem is becoming pervasive in today's data mining applications. This problem refers to the uneven distribution of instances among the classes which poses difficulty in the classification of rare instances. Several undersampling as well as oversampling methods were proposed to deal with such imbalance. Many undersampling techniques do not consider distribution of information...
Multiclass classification is the task of classifying the samples into more than two classes. Generally multi-classifiers face difficulty in classifying samples those are very close to the separating hyperplane, known as Generalization error. Generalization error can be reduced by maximizing the margin of the separating hyperplanes. Support Vector Machine (SVM) is a maximum-margin classifier, its aim...
Physical memory forensic« has grown in popularity in recent years. Since malware typically operate in user space, it is important to reconstruct and track their process behavior. This paper focuses on detecting malware through a comparison of the information in the user space memory data structures. In order to expedite information extraction and ensure accuracy, the data in multiple memory management...
Carrying out effective and sustainable agriculture product has become an important issue in recent years. Agricultural production has to keep up with an ever-increasing population. A key to this is the usage of modern techniques (for precision agriculture) to take advantage of the quality in the market. The paper reviews various quality evaluation and grading techniques of Oryza Sativa L. (rice) in...
The Windows CE registry plays a very important role from physical memory and contains lots of important information that are of potential evidential value in forensic analysis. Memory acquisition and analysis is the most important in Windows CE devices forensic. The paper introduces physical memory acquisition and analysis methods in Windows environment and the procedure of memory analysis on the...
Memory Forensics is a novel and fast growing field in computer forensics, providing access to volatile information unavailable from a disk image. The memory forensics commenced when malware writers began reducing their footprints on the victim's hard disk and instead started storing crucial information within the machine's Random Access Memory. Windows 7 claims to be the most secure version of windows...
Manual alert detection on modern high performance clusters (HPC) is cumbersome given their increasing complexity and size of their logs. The ability to automatically detect such alerts quickly and accurately with little or no human intervention is therefore desirable. The entropy-based approach of the Nodeinfo framework, which is in production use at Sandia National Laboratories, is one approach to...
Document classification is a key task for many text mining applications. However, traditional text classification requires labeled data to construct reliable and accurate classifiers. Unfortunately, labeled data are seldom available. In this work, we propose a universal text classifier, which does not require any labeled document. Our approach simulates the capability of people to classify documents...
Recent technological developments made available various many-core hardware platforms. For example, a SIMD-like hardware architecture became easily accessible for many users who have their computers equipped with modern NVIDIA GPU cards with CUDA technology. In this paper we redesign the maximal accepting predecessors algorithm for LTL model checking in terms of matrix-vector product in order to accelerate...
In this paper we explore the capabilities of a framework that can use different machine learning algorithms to successfully detect malware files, aiming to minimize the number of false positives. We report the results obtained in our framework, working firstly with cascades of one-sided perceptron and kernelized one-sides perceptrons and secondly with cascade of one-sided support vector machines.
We present GamePod, a portable system that enables mobile users to use the same persistent, gaming environment on any available computer. No matter what computer is being used, GamePod provides a consistent gaming environment, maintaining all of a user's games, including active game state. This is achieved by leveraging rapid improvements in capacity, cost, and size of portable storage devices. GamePod...
This paper provides a novel and totally statistical method to search similar questions from a large question archive for a given queried question. Firstly, a word relevance model is trained based on the whole question archive which is made up of millions of natural language questions proposed by users on the Web. The word relevance model is utilized to find most semantically related words to a specific...
Clustering is the hot spot in the study of data mining. In this paper, refer to the distillation of "energy", data object and clustering can be described by energy. With the function of clustering optimized by energy, energy driven about the user's demands will be brought into effect in all data-space, and all data object, including the outlier, is planed as a whole at the unified cognition...
This paper briefly introduces the challenges facing collection of volatile data in a target computer. Reasons to favor physical memory analysis are also given. After describing the related work of the memory analysis, details of a windows memory analysing method are given through which it is possible to extract useful information, such as running processes , current network connections, file contents,...
In this paper, the intrusion detection system is introduced, and point out two important prerequisite that the IDS work normally must depend on, and in view of the prerequisite, the paper proposed a solution which is based on k-nearest neighbor algorithm of kernel and the active defence technology anti-host intrusion. The solution can distinguish normal event from the unknown event efficiently, and...
Ontology is applied to a real-world Web intelligent question answering system in PC troubleshooting domain as an improvement, so semantic relations need to be extracted to construct ontology semi-automatically. The paper mainly pays attention to "product-trouble" relation and "product-attribute" relation. A two stage semantic relation extraction method is proposed. In stage one,...
In these days, Linux system is widely used because of its freedom to use and develop. With this trend, to find vulnerabilities in Linux kernel has become more important. Linux kernel is so huge that we need a machine based error detecting approach. There are some former studies about error detection in software code. However, they are not suitable for detecting unknown vulnerabilities related to Linux...
We present a method for the synthesis of non-linear ranking function of a program loop. Based on the region-based search, it reduces the non-linear ranking function discovering to the inequality checking. The inequality prover BOTTEMA then can be utilized to check validity for inequalities. In contrast to other approaches, the new approach can also discover the ranking function with the radicals due...
A sentence group is a processing unit between a sentence and a paragraph or an article. It is described with three aspects: domain, situation and background. Domain is the conceptual category of a sentence group. Situation is the conceptual framework of a sentence group. The conceptual framework of a sentence group is defined with several serial sentence categories (SCs), the semantic chunks in the...
In this paper, a novel fault monitoring and diagnosis approach based on kernel partial least squares(KPLS) is introduced. Unlike other nonlinear least squares (PLS) techniques, KPLS does not consider any nonlinear systems optimization procedures and has the characteristics similar to that of linear PLS. In this paper, KPLS provides good monitoring performance by finding those latent variables that...
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