Search results for "Mach"

Support vector machine integrated with game-theoretic approach and genetic algorithm for the detection and classification of malware

2013

Abstract. —In the modern world, a rapid growth of mali- cious software production has become one of the most signifi- cant threats to the network security. Unfortunately, wides pread signature-based anti-malware strategies can not help to de tect malware unseen previously nor deal with code obfuscation te ch- niques employed by malware designers. In our study, the prob lem of malware detection and classification is solved by applyin g a data-mining-based approach that relies on supervised mach ine- learning. Executable files are presented in the form of byte a nd opcode sequences and n-gram models are employed to extract essential features from these sequences. Feature vectors o btained are…

Evaluating the performance of artificial neural networks for the classification of freshwater benthic macroinvertebrates

2014

Abstract Macroinvertebrates form an important functional component of aquatic ecosystems. Their ability to indicate various types of anthropogenic stressors is widely recognized which has made them an integral component of freshwater biomonitoring. The use of macroinvertebrates in biomonitoring is dependent on manual taxa identification which is currently a time-consuming and cost-intensive process conducted by highly trained taxonomical experts. Automated taxa identification of macroinvertebrates is a relatively recent research development. Previous studies have displayed great potential for solutions to this demanding data mining application. In this research we have a collection of 1350 …

Real-time recognition of personal routes using instance-based learning

2011

Predicting routes is a critical enabler for many new location-based applications and services, such as warning drivers about congestion- or accident-risky areas. Hybrid vehicles can also utilize the route prediction for optimizing their charging and discharging phases. In this paper, a new lightweight route recognition approach using instance-based learning is introduced. In this approach, the current route is compared in real-time against the route instances observed in past, and the most similar route is selected. In order to assess the similarity between the routes, a similarity measure based on the longest common subsequence (LCSS) is employed, and an algorithm for incrementally evaluat…

Online anomaly detection using dimensionality reduction techniques for HTTP log analysis

2015

Modern web services face an increasing number of new threats. Logs are collected from almost all web servers, and for this reason analyzing them is beneficial when trying to prevent intrusions. Intrusive behavior often differs from the normal web traffic. This paper proposes a framework to find abnormal behavior from these logs. We compare random projection, principal component analysis and diffusion map for anomaly detection. In addition, the framework has online capabilities. The first two methods have intuitive extensions while diffusion map uses the Nyström extension. This fast out-of-sample extension enables real-time analysis of web server traffic. The framework is demonstrated using …

Listwise Collaborative Filtering

2015

Recently, ranking-oriented collaborative filtering (CF) algorithms have achieved great success in recommender systems. They obtained state-of-the-art performances by estimating a preference ranking of items for each user rather than estimating the absolute ratings on unrated items (as conventional rating-oriented CF algorithms do). In this paper, we propose a new ranking-oriented CF algorithm, called ListCF. Following the memory-based CF framework, ListCF directly predicts a total order of items for each user based on similar users' probability distributions over permutations of the items, and thus differs from previous ranking-oriented memory-based CF algorithms that focus on predicting th…

Turing's error-revised

2016

Many important lines of argumentation have been presented during the last decades claiming that machines cannot think like people. Yet, it has been possible to construct devices and information systems, which replace people in tasks which have previously been occupied by people as the tasks require intelligence. The long and versatile discourse over, what machine intelligence is, suggests that there is something unclear in the foundations of the discourse itself. Therefore, we critically studied the foundations of used theory languages. By looking critically some of the main arguments of machine thinking, one can find unifying factors. Most of them are based on the fact that computers canno…

Mathematical models and stability analysis of three-phase synchronous machines

2013

The Connection of Machiavellianism, Self-control and Induced Emotions with Solving Tasks

2014

The presented research shows that there is a connection between Machiavellianism and the way of solving problem tasks in the situations of inducing chosen emotions. The results obtained in this research show that Machiavellians are characterised by the self-control of the stop type and that the induction of emotions has not such a connection with solving tasks by them as it is in case of people with a low level of Machiavellianism. Moreover, it has been shown that people with high Machiavellianism do not trust other people and are focused on the maximization of profit.

CCTVCV: Computer Vision model/dataset supporting CCTV forensics and privacy applications

2022

The increased, widespread, unwarranted, and unaccountable use of Closed-Circuit TeleVision (CCTV) cameras globally has raised concerns about privacy risks for the last several decades. Recent technological advances implemented in CCTV cameras, such as Artificial Intelligence (AI)-based facial recognition and Internet of Things (IoT) connectivity, fuel further concerns among privacy advocates. Machine learning and computer vision automated solutions may prove necessary and efficient to assist CCTV forensics of various types. In this paper, we introduce and release the first and only computer vision models are compatible with Microsoft common object in context (MS COCO) and capable of accurately…

CCTV-FullyAware: toward end-to-end feasible privacy-enhancing and CCTV forensics applications

2022

It is estimated that over 1 billion Closed-Circuit Television (CCTV) cameras are operational worldwide. The advertised main benefits of CCTV cameras have always been the same; physical security, safety, and crime deterrence. The current scale and rate of deployment of CCTV cameras bring additional research and technical challenges for CCTV forensics as well, as for privacy enhancements. This paper presents the first end-to-end system for CCTV forensics and feasible privacy-enhancing applications such as exposure measurement, CCTV route recovery, CCTV-aware routing/navigation, and crowd-sourcing. For this, we developed and evaluated four complex and distinct modules (CCTVCV [1], OSRM-CCTV [2],…