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Studies on visual attention of patients with Alzheimer's disease and dementia are a promising way for keeping track of an individual patients image recognition ability over time. This research seeks to expand upon the current applications of combining the Android operating system with TensorFlow by providing QA diagnostics alongside a visual question answering (VQA) platform for image analysis. This...
In this paper, we propose an online spatiotemporal data-driven methodology to detect malicious cyber attacks that target power system balancing and frequency control. The anomaly detection, which spots abnormal generator behavioral patterns in real time, is achieved locally at a power plant with peer to peer communication capability. We mainly consider the data integrity attack targeting Automatic...
Change point analysis is a statistical tool to identify homogeneity within time series data. We propose a pruning approach for approximate nonparametric estimation of multiple change points. This general purpose change point detection procedure 'cp3o' applies a pruning routine within a dynamic program to greatly reduce the search space and computational costs. Existing goodness-of-fit change point...
Class imbalance exists in many applications of bioinformatics and biomedicine, while dimension reduction in the feature space is often needed when building prediction models on a dataset. When the above two issues need to be considered simultaneously for skewed/imbalanced datasets, practitioners and researchers in machine learning may raise the following question: should feature selection be conducted...
The number of triangles in a graph is useful to deduce a plethora of important features of the network that the graph is modeling. However, finding the exact value of this number is computationally expensive. Hence, a number of approximation algorithms based on random sampling of edges, or wedges (adjacent edge pairs) have been proposed for estimating this value. We argue that for large sparse graphs...
The methodology of community detection can be divided into two principles: imposing a network model on a given graph, or optimizing a designed objective function. The former provides guarantees on theoretical detectability but falls short when the graph is inconsistent with the underlying model. The latter is model-free but fails to provide quality assurance for the detected communities. In this paper,...
Non-intrusive load monitoring (NILM) systems estimate the amount of energy each appliance consumes using as input the aggregate building energy consumption. Typically, NILM results are presented for a single sampling rate. To evaluate tradeoffs between end-uses and sensor costs, it is important to study the performance of NILM systems across sampling rates. In this work, we examine the performance...
Benchmarking and profiling virtual network functions (VNFs) generates input knowledge for resource management decisions taken by management and orchestration systems. Such VNFs are usually not executed in isolation but are often deployed as part of a service function chain (SFC) that connects single functions into complex structures. To manage such chains, isolated performance profiles of single functions...
SDN aims to facilitate the management of increasingly complex, dynamic network environments and optimize the use of the resources available therein with minimal operator intervention. To this end, SDN controllers maintain a global view of the network topology and its state. However, the extraction of information about network flows and other network metrics remains a non-trivial challenge. Network...
This article examines the problems of distance learning and one of their possible solution. An adaptive learning system is described that allows to provide an individual approach when passing a course of study. An example of the response of an adaptive learning system to the actions of students while performing tasks and its proposal for a level change is given.
Lane estimation plays a central role for Driver Assistance Systems, therefore many approaches have been proposed to measure its performance. However, no commonly agreed metric exists. In this work, we first present a detailed survey of the current measures. Most of them apply pixel-level benchmarks on camera images and require a time-consuming and fault-prone labeling process. Moreover, these metrics...
Intrusion detection systems are a central component of cyber security architecture, and their accuracy is a critical performance metric for any security deployment. Most of the current performance analysis of intrusion detection systems relies on empirical profiling of a given algorithm or implementation against a benchmark dataset. Whilst effective to a point, this traditional evaluation methodology...
Within the context of road estimation, the present paper addresses the problem of the fusion of several sources with different reliabilities. Thereby, reliability represents a higher-level uncertainty. This problem arises in automated driving and ADAS due to changing environmental conditions, e.g., road type or visibility of lane markings. Thus, we present an online sensor reliability assessment and...
We live in interesting times. Our systems have unprecedented levels of device integration. Analog and mixed signal components and devices form increasingly large parts of our designs built for low power and high flexibility. New architectures and models of computation that embrace variation like neuromorphic computing are a part of our horizon. Architectures specialized for neural networks and learning...
In Systems-on-Chip (SoCs) based on Networks-on-Chip (NoCs), the timing requirements of target applications can be met by using virtual channels and traffic differentiation mechanisms to prioritize the most urgent communication streams. However, the use of virtual channels in NoCs results in silicon and power overheads as they are usually implemented by means of additional buffers and multiplexers...
We describe and evaluate the development of mission planners in intralogistics for a commercial unmanned aerial vehicle equipped with a robotic gripper in an industrial environment, which consists of an input warehouse, production lines, and a product depot. In this particular study, the planner produces the needed commands for carrying out a given mission, which includes the delivery of inputs picked...
Currently, open source projects receive various kinds of issues daily, because of the extreme openness of Issue Tracking System (ITS) in GitHub. ITS is a labor-intensive and time-consuming task of issue categorization for project managers. However, a contributor is only required a short textual abstract to report an issue in GitHub. Thus, most traditional classification approaches based on detailed...
Pairwise surface rigid registration aims to find the rigid transformation that best register two surfaces represented by point clouds. This work presents a comparison between seven algorithms, with different strategies to tackle rigid registration tasks. We focus on the frame-to-frame problem by using both point clouds and a RGB-D video stream in the experimental results. The former, is considered...
This paper describes the implementation of a 3D handheld scanning approach based on Kinect. User may get the 3D scans at a very fast rate using real time scanning devices like Kinect. These devices have been utilized in several applications, but the scanning lacks in the accuracy and reliability of the 3D data, which makes their employment a difficult task. This research proposed the 3D handheld scanning...
It remains unclear when it is the right time to introduce software quality into the computing curriculum. Introductory students often cannot afford to also worry about software quality, while advanced students may have been groomed into undisciplined development practices already. To answer these questions satisfactorily, educators need strong quantitative evidence about the pervasiveness of software...
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