The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
With the continuous drive towards integrated circuits scaling, efficient performance modeling is becoming more crucial yet, more challenging. In this paper, we propose a novel method of hierarchical performance modeling based on Bayesian co-learning. We exploit the hierarchical structure of a circuit to establish a Bayesian framework where unlabeled data samples are generated to improve modeling accuracy...
Approximate computing has applications in areas such as image processing, neural computation, distributed systems, and real-time systems, where the results may be acceptable in the presence of controlled levels of error. The promise of approximate computing is in its ability to render just enough performance to meet quality constraints. However, going from this theoretical promise to a practical implementation...
Due to the volatile nature of Service Level Agreements (SLA), dynamic management is vital for both service consumer and service providers. As a result of technology innovation, cloud computing SLA content updates are not accurate with consumer needs. Further, public SLAS are used as templates and when a new SLA is issued, requirement mapping to all its public SLA is necessary. To manage cloud SLAs...
In this paper, we analyze the temporal performance of multi-robot system which are performing a foraging object task. The coordination between different robotic agents was inspired by the ant colony optimization algorithms (ACO). The objective was to prospect about parameters influence on foraging objects time. In this work, we consider three possible influencing parameters including robotic group...
An important component of the modeling of sound propagation for virtual reality (VR) is the spatialization of the room impulse response (RIR) for directional listeners. This involves convolution of the listener's head-related transfer function (HRTF) with the RIR to generate a spatial room impulse response (SRIR) which can be used to auralize the sound entering the listener's ear canals. Previous...
Commodity depth cameras, such as the Microsoft Kinect®, have been widely used for the capture and reconstruction of the 3D structure of room-sized dynamic scenes. Camera placement and coverage during capture significantly impact the quality of the resulting reconstruction. In particular, dynamic occlusions and sensor interference have been shown to result in poor resolution and holes in the reconstruction...
The evaluation of dependability or performance of general systems usually relies on the assistance of stochastic modeling and simulation tools. Those software packages enables the creation of models and computation of metrics quickly and accurately. This paper introduces the Mercury tool, which is an integrated software that enables creating and evaluating Reliability Block Diagrams, Stochastic Petri...
Given the growing sophistication of cyber attacks, designing a perfectly secure system is not generally possible. Quantitative security metrics are thus needed to measure and compare the relative security of proposed security designs and policies. Since the investigation of security breaches has shown a strong impact of human errors, ignoring the human user in computing these metrics can lead to misleading...
Predicting the amount of resources available to system's users has become a task of interest to services providers even with the advent of elastic cloud computing, because the number of resources is finite despite being virtually infinite on the customer view. This paper proposes a model to evaluate node's capacity in a cloud computing environment based on the amount of available hardware resources...
The problem of sample size determination (SSD) for any black box model is addressed in this work. Four novel SSD algorithms namely HC, SOOP, HC+SOOP and V-SOOP, based on hypercube sampling, space filling and optimization study are proposed to tackle the issues of over-fitting, accuracy and computational speed of surrogate models. In this version, the novel algorithms are shown to run simultaneously...
Transformation of occurred rainfall into runoff generated within a catchment is a complex natural phenomenon that passes through various inter-related processes and influenced by many topographic, geographic, geologic and sociologic factors. To develop a model that can reliably imbibe the complex Rainfall-Runoff interaction, two different approaches namely, conventional regression and Artificial Neural...
Recommender system refers to an information system that predicts the intuition of user observing behavior of all the users. The idea of collaborative filtering lies in producing a set of recommendations based on similarity as well as knowledge of users' relationships to items. In this paper, we combine some traditional similarity metrics to find three types of similar users which are super similar,...
Cyber deception is usually synonymous with nefarious activities led by attackers. Motivated attackers will stop at nothing to accomplish their mission and deception is amongst the tools they use. Cyber defenders have also begun using deception as an instrument to further enhance overall defensive strength. Deception has been leveraged to research attacker behaviors and their associated tactic techniques...
Cache hierarchies have long been utilized to minimize the latency of main memory accesses by caching frequently used data closer to the processor. Significant research has been done to identify the most crucial metrics of cache performance. Though the majority of research focuses on measuring cache hit rates and data movement as the major cache performance metrics, cache utilization can be equally...
Dynamic networks can be characterised by many factors such as changes (e.g., vulnerability change, update of applications and services, topology changes). It is of vital importance to assess the security of such dynamic networks in order to improve the security of them. One way to assess the security is to use a graphical security model. However, the existing graphical security models (e.g., attack...
With the immense growth of online social applications, trust plays a more and more important role in connecting users to each other, sharing their personal information and attracting him to receive recommendations. Therefore, how to obtain trust relationships through mining online social networks became a critical issue. To calculate the level of trust between two users, many computational trust models...
Blur is a common artifact in video, which adds more complexity to text detection and recognition. To achieve good accuracies for text detection and recognition, this paper suggests a new method for classifying blurred and non-blurred frames in video. We explore quality metrics, namely, BRISQUE, NRIQA, GPC and SI, in a new way for classification. We estimate the values of these metrics with the help...
This paper proposes an efficient data-based anomaly detection method that can be used for monitoring nonlinear processes. The proposed method merges advantages of nonlinear projection to latent structures (NLPLS) modeling and those of Hellinger distance (HD) metric to identify abnormal changes in highly correlated multivariate data. Specifically, the HD is used to quantify the dissimilarity between...
The Arbitrary Lagrangian-Eulerian (ALE) method is used in a variety of engineering and scientific applications for enabling multi-physics simulations. Unfortunately, the ALE method can suffer from simulation failures that require users to adjust parameters iteratively in order to complete a simulation. In this paper, we present a supervised learning framework for predicting conditions leading to simulation...
Machine learning models are vulnerable to adversarial examples formed by applying small carefully chosen perturbations to inputs that cause unexpected classification errors. In this paper, we perform experiments on various adversarial example generation approaches with multiple deep convolutional neural networks including Residual Networks, the best performing models on ImageNet Large-Scale Visual...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.