This paper describes the design of an efficient technique for correcting errors in the tag array of set-associative caches. The main idea behind this scheme is that for a cache tag array protected with ECC code, the stored ...

This paper focuses on coexistence and self-coexistence challenges between secondary heterogeneous wireless networks/users sharing TV Whitespace spectrum. The coexistence problems arise from having several primary and ...

In this paper, we present the results of our comprehensive measurement study of the timing and voltage guardbands in memories and cores of a commodity ARMv8 based micro-server. Using various synthetic micro-benchmarks, we ...

Motion capture sequences may contain erroneous data, especially when the motion is complex or performers are interacting closely and occlusions are frequent. Common practice is to have specialists visually detect the ...

Conditional Value-at-Risk, denoted as CVaRα, is becoming the prevailing measure of risk over two paramount economic domains: the insurance domain and the financial domain

In recent years, the increasing propagation of hate speech in online social networks and the need for effective counter-measures have drawn significant investment from social network companies and researchers. This has ...

‘‘Humans at rest tend to stay at rest. Humans in motion tend to cross the road – Isaac Newton.” Even though this response is meant to be a joke to indicate the answer is quite obvious, this important feature of real world ...

Edge computing is the emerging architectural paradigm extending cloud technologies to the logical extremes of the network for on-demand and delay-sensitive services. However, once service placement on edge-enabling resources ...

Real-time three-dimensional (3D) pose estimation is of high interest in interactive applications, virtual reality, activity recognition, and most importantly, in the growing gaming industry. In this work, we present a ...

Trying to extract features from complex sequential data for classification and prediction problems is an extremely difficult task. Deep Machine Learning techniques, such as Convolutional Neural Networks (CNNs), have been ...