Computer Science: Recent submissions
Now showing items 281-300 of 549
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Risk-driven model-based testing of washing machine software: an industrial case study
(IEEE, 2018-07-16)We previously introduced an approach for risk-driven model-based testing. In that approach, test models are represented in the form of Markov chains and test case generation is steered by state transition probabilities. ... -
Towards a testing framework with visual feedback for actor-based systems
(IEEE, 2018-08-02)We introduce a prototype testing framework as an extension of JUnit for testing actor-based systems. Our framework runs a given JUnit test in various schedules and records the execution trace for each run. In case a failure ... -
Optimum encoding approaches on video resolution changes: a comparative study
(IEEE, 2018)Video resolution changes in an HTTP adaptive streaming session may negatively affect the viewer's quality of experience. Our goal is, through encoding, to make such resolution changes less noticeable for the viewers. This ... -
Modeling the development of infant imitation using inverse reinforcement learning
(IEEE, 2018-09)Little is known about the computational mechanisms of how imitation skills develop along with infant sensorimotor learning. In robotics, there are several well developed frameworks for imitation learning or so called ... -
Learning and reasoning in complex coalition information environments: a critical analysis
(IEEE, 2018-09-05)In this paper we provide a critical analysis with metrics that will inform guidelines for designing distributed systems for Collective Situational Understanding (CSU). CSU requires both collective insight - i.e., accurate ... -
Trust estimation of sources over correlated propositions
(IEEE, 2018-09-05)This work analyzes the impact of correlated propositions when estimating the reporting behavior of information sources. These behavior estimates are critical for fusion, and traditional methods assume the propositions are ... -
Stream analytics and adaptive windows for operational mode identification of time-varying industrial systems
(IEEE, 2018-09-07)It is necessary to develop accurate, yet simple and efficient models that can be used with high-speed industrial data streams. In this paper, we develop a mode identification technique using stream analytics and show that ... -
On context-aware DDoS attacks using deep generative networks
(IEEE, 2018-10)Distributed Denial of Service (DDoS) attacks continue to be one of the most severe threats in the Internet. The intrinsic challenge in preventing DDoS attacks is to distinguish them from legitimate flash crowds since two ... -
Implementation of SAND architecture Using SDN
(IEEE, 2018)The server and network-assisted DASH (SAND) concept aims to increase the performance of Dynamic Adaptive Streaming over HTTP (DASH) systems. As being one of the future Internet technologies, SDN provides advantages to ... -
On characterizing sectoral interactions via connections between employees in professional online social networks
(Elsevier, 2018-12)The collaboration among individuals is essential to maximize economic efficiency. Today most of the technological and economical advancements require multidisciplinary efforts. Therefore promoting interaction and knowledge ... -
CPU design simplified
(IEEE, 2018-12-10)The first goal of this paper is to introduce a simple and customizable soft CPU named VerySimpleCPU (VSCPU), which could be easily implemented on FPGAs with a complete toolchain including instruction set simulator, assembler, ... -
A generalized stereotype learning approach and its instantiation in trust modeling
(Elsevier, 2018-08)Owing to the lack of historical data regarding an entity in online communities, a user may rely on stereotyping to estimate its behavior based on historical data about others. However, these stereotypes cannot accurately ... -
Variational closed-Form deep neural net inference
(Elsevier, 2018-09)We introduce a Bayesian construction for deep neural networks that is amenable to mean field variational inference that operates solely by closed-form update rules. Hence, it does not require any learning rate to be manually ... -
Multivariate sensor data analysis for oil refineries and multi-mode identification of system behavior in real-time
(IEEE, 2018)Large-scale oil refineries are equipped with mission-critical heavy machinery (boilers, engines, turbines, and so on) and are continuously monitored by thousands of sensors for process efficiency, environmental safety, and ... -
Increasing test efficiency by risk-driven model-based testing
(Elsevier, 2018-10)We introduce an approach and a tool, RIMA, for adapting test models used for model-based testing to augment information regarding failure risk. We represent test models in the form of Markov chains. These models comprise ... -
A distributed approach for bitrate selection in HTTP adaptive streaming
(ACM, 2018)Past research has shown that concurrent HTTP adaptive streaming (HAS) players behave selfishly and the resulting competition for shared resources leads to underutilization or oversubscription of the network, presentation ... -
Shoulder glenohumeral elevation estimation based on upper arm orientation
(IEEE, 2018-10-26)In this paper, the shoulder glenohumeral displacement during the movement of the upper arm is studied. Four modeling approaches were examined and compared to estimate the humeral head elevation (vertical displacement) and ... -
Introduction of a spatio-temporal mapping based POE method for outdoor spaces: Suburban university campus as a case study
(Elsevier, 2018-11)Outdoor spaces are important to sustainable cities because they establish a common identity for social life by improving quality of urban living. The relation between outdoor spaces and building groups, competency, use ... -
Results of the first annual human-agent league of the automated negotiating agents competition
(The ACM Digital Library, 2018)We present the results of the first annual Human-Agent League of ANAC. By introducing a new human-agent negotiating platform to the research community at large, we facilitated new advancements in human-aware agents. This ... -
Human-in-the-loop control and task learning for pneumatically actuated muscle based robots
(Frontiers Media, 2018-11-06)Pneumatically actuated muscles (PAMs) provide a low cost, lightweight, and high power-To-weight ratio solution for many robotic applications. In addition, the antagonist pair configuration for robotic arms make it open to ...
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