Increasing population density in urban centers demands adequate provision of services and infrastructure to meet the needs city inhabitants, encompassing residents, workers, visitors. The utilization information communications technologies achieve this objective presents an opportunity for development smart cities, where management citizens are given access a wealth real-time about environment upon which base decisions, actions, future planning. This paper framework realization cities...

Heart rate variability (HRV) is concerned with the analysis of intervals between heartbeats. An emerging technique Poincaré plot, which takes a sequence and plots each interval against following interval. The geometry this plot has been shown to distinguish healthy unhealthy subjects in clinical settings. valuable HRV due its ability display nonlinear aspects sequence. problem is, how do we quantitatively characterize capture useful summary descriptors that are independent existing measures?...

Very large (VL) data or big are any that you cannot load into your computer's working memory. This is not an objective definition, but a definition easy to understand and one practical, because there dataset too for computer might use; hence, this VL you. Clustering of the primary tasks used in pattern recognition mining communities search databases (including images) various applications, so, clustering algorithms scale well important useful. paper compares efficacy three different...

Ageing influences gait patterns causing constant threats to control of locomotor balance. Automated recognition changes has many advantages including, early identification at-risk and monitoring the progress treatment outcomes. In this paper, we apply an artificial intelligence technique [support vector machines (SVM)] for automatic young-old types from their respective gait-patterns. Minimum foot clearance (MFC) data 30 young 28 elderly participants were analyzed using a PEAK-2D motion...

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Obstructive sleep apnea syndrome (OSAS) is associated with cardiovascular morbidity as well excessive daytime sleepiness and poor quality of life. In this study, we apply a machine learning technique [support vector machines (SVMs)] for automated recognition OSAS types from their nocturnal ECG recordings. A total 125 sets recordings acquired normal subjects (OSAS<formula formulatype="inline"><tex...

Fog/Edge computing emerges as a novel paradigm that harnesses resources in the proximity of Internet Things (IoT) devices so that, alongside with cloud servers, provide services timely manner. However, due to ever-increasing growth IoT resource-hungry applications, fog/edge servers limited cannot efficiently satisfy requirements applications. Therefore, application placement environment, which several distributed and centralized are available, is challenging issue. In this article, we...

Anomaly detection in wireless sensor networks is an important challenge for tasks such as fault diagnosis, intrusion detection, and monitoring applications. The algorithms developed anomaly have to consider the inherent limitations of their design so that energy consumption nodes minimized lifetime network maximized. In this survey article we analyze state art techniques discuss some open issues research.

For constrained end devices in Internet of Things, such as smart meters (SMs), data transmission is an energy-consuming operation. To address this problem, we propose efficient and privacy-preserving aggregation system with the aid Fog computing architecture, named PPFA, which enables intermediate nodes to periodically collect from nearby SMs accurately derive aggregate statistics fine-grained level aggregation. The Cloud/utility supplier computes overall by aggregating minimize privacy...

In this paper, we develop a physiological oscillator model of which the output mimics shape R-R interval Poincaré plot. To validate model, simulations various nervous conditions are compared with heart rate variability (HRV) data obtained from subjects under each prescribed condition. For variety sympathovagal balances, our generates plots that undergo alterations strongly resembling those actual intervals. By exploiting basis detail way low- and high-frequency modulation sinus node...

Identifying misbehaviors is an important challenge for monitoring, fault diagnosis and intrusion detection in wireless sensor networks. A key problem how to minimize the communication overhead energy consumption network when identifying misbehaviors. Our approach this based on a distributed, cluster-based anomaly algorithm. We by clustering measurements merging clusters before sending description of other nodes. In order evaluate our distributed scheme, we implemented algorithm simulation...

We propose a new algorithm for the incremental training of support vector machines (SVMs) that is suitable problems sequentially arriving data and fast constraint parameter variation. Our method involves using "warm-start" SVMs, which allows us to take advantage natural properties standard active set approach linearly constrained optimization problems. Incremental quickly retraining machine after adding small number additional vectors an existing (trained) machine. Similarly, problem...

Security is a critical challenge for creating robust and reliable sensor networks. For example, routing attacks have the ability to disconnect network from its central base station. In this paper, we present method intrusion detection in wireless Our scheme uses clustering algorithm build model of normal traffic behavior, then detect abnormal patterns. A key advantage our approach that it able not previously been seen. Moreover, based on set features can potentially be applied wide range...

A typical wireless sensor node has little protection against radio jamming. The situation becomes worse if energy-efficient jamming can be achieved by exploiting knowledge of the data link layer. Encrypting packets may help to prevent jammer from taking actions based on content packets, but temporal arrangement induced nature protocol might unravel patterns that take advantage of, even when are encrypted. By looking at packet interarrival times in three representative MAC protocols, S-MAC,...

Anomaly detection is an important challenge for tasks such as fault diagnosis and intrusion in energy constrained wireless sensor networks. A key problem how to minimise the communication overhead network while performing in-network computation when detecting anomalies. Our approach this based on a formulation that uses distributed, one-class quarter-sphere support vector machines identify anomalous measurements data. We demonstrate using data from Great Duck Island Project our distributed...

Poincaré plot is one of the important techniques used for visually representing heart rate variability. It valuable due to its ability display nonlinear aspects data sequence. However, problem lies in capturing temporal information quantitatively. The standard descriptors quantifying (SD1, SD2) measure gross variability time series data. Determination advanced methods properties pose a significant challenge. In this paper, we propose novel descriptor "Complex Correlation Measure (CCM)"...

Anomaly detection in wireless sensor networks is an important challenge for tasks such as intrusion and monitoring applications. This paper proposes two approaches to detecting anomalies from measurements networks. The first approach a linear programming-based hyperellipsoidal formulation, which called centered support vector machine (CESVM). While this CESVM has advantages terms of its flexibility the selection parameters computational complexity, it limited scope distributed implementation...

Obstructive sleep apnea or hypopnea causes a pause reduction in airflow with continuous breathing effort. The aim of this study is to identify individual and events from normal using wavelet-based features 5-s ECG signals (sampling rate = 250 Hz) estimate the surrogate index (AI)/hypopnea (HI) (AHI). Total 82,535 epochs (each duration) during sleep, 1638 689 events, 3151 1862 were collected 17 patients training set. Two-staged feedforward neural network model was trained...

Cardiac autonomic neuropathy (CAN) in diabetes has been called a "silent killer", because so few patients realize that they suffer from it, and yet its effect can be lethal. Early sub clinical detection of CAN intervention are prime importance for risk stratification preventing sudden death due to silent myocardial infarction. This study presents the usefulness heart rate variability (HRV) complexity analyses short term ECG recordings as screening tool CAN. A total 17 sets during supine rest...

Security of wireless sensor networks (WSN) is an important research area in computer and communications sciences. Anomaly detection a key challenge ensuring the security WSN. Several anomaly algorithms have been proposed validated recently using labeled datasets that are not publicly available. Our group ellipsoid-based algorithm but demonstrated its performance synthetic real Intel Berkeley Research Laboratory Grand St. Bernard which with anomalies. This approach requires manual assignment...