Validity as a Measure of Data Quality in Internet of Things Systems

Data quality became significant with the emergence of data warehouse systems. While accuracy is intrinsic data quality, validity of data presents a wider perspective, which is more representational and contextual in nature. Through our article we present a different perspective in data collection and collation. We focus on faults experienced in data sets and present validity as a function of allied parameters such as completeness, usability, availability and timeliness for determining the data quality. We also analyze the applicability of these metrics and apply modifications to make it conform to IoT applications. Another major focus of this article is to verify these metrics on aggregated data set instead of separate data values. This work focuses on using the different validation parameters for determining the quality of data generated in a pervasive environment. Analysis approach presented is simple and can be employed to test the validity of collected data, isolate faults in the data set and also measure the suitability of data before applying algorithms for analysis. On analyzing the data quality of the two data sets on the basis of above-mentioned parameters. We show that validity for data set 1 was found to be 75% while it was found to be 67% only for data set 2. Availability and data freshness metrics performance were analyzed graphically. It was found that for data set 1, data freshness was better while availability metric was found better for data set 2. Usability obtained for data set 2 was 86% which was higher as compared to data set 1 whose usability metric was 69%. Thus, this work presents methods that can be leveraged for estimating data quality that can be beneficial in various IoT based industries which are essentially data centric and the decisions made by them depends upon the validity of data.

     

An Improved Multifactor User Authentication Scheme for Wireless Sensor Networks

Wireless Personal Communications - Wireless Sensor Networks (WSNs) are used to collect and transmitted the data in various applications from normal to those which requires significant security...     

Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals

Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals; these signals can be recorded, processed and classified into different hand movements, which can be used to control other IoT devices. Classification of hand movements will be one step closer to applying these algorithms in real-life situations using EEG headsets. This paper uses different feature extraction techniques and sophisticated machine learning algorithms to classify hand movements from EEG brain signals to control prosthetic hands for amputated persons. To achieve good classification accuracy, denoising and feature extraction of EEG signals is a significant step. We saw a considerable increase in all the machine learning models when the moving average filter was applied to the raw EEG data. Feature extraction techniques like a fast fourier transform (FFT) and continuous wave transform (CWT) were used in this study; three types of features were extracted, i.e., FFT Features, CWT Coefficients and CWT scalogram images. We trained and compared different machine learning (ML) models like logistic regression, random forest, k-nearest neighbors (KNN), light gradient boosting machine (GBM) and XG boost on FFT and CWT features and deep learning (DL) models like VGG-16, DenseNet201 and ResNet50 trained on CWT scalogram images. XG Boost with FFT features gave the maximum accuracy of 88%.     

Identifying factors causing cost overrun of the construction projects in India

Delay and cost overrun are common phenomena in projects worldwide. However, these are especially severe in developing countries. In India as per MOSPI report, 235 projects out of 410 were severely affected cost overrun due to certain factors. A short questionnaire was conducted with 15 prominent factors responsible for cost overrun and forwarded to 190 constructional professionals across India. Total 85 responses were received and it was analyzed using various statistical tools such as analysis of variance (ANOVA) and factor analysis tool using SPSS. In this study, top three factors affecting cost overruns were identified such as price escalation of raw material, delay in planned activity and lack of co-ordination between construction parties which could be significantly responsible for cost overnun of construction project in India. Factor analysis method was also carried out to group the factors into three components of overall questionnaire. These components, such as client control component, project management component, and contractor control component, would be useful to the various parties involved in the construction activities. This paper also provides suggestive frameworks which have been framed after discussing with large number of construction professionals or expert.     

Charge transport and structural morphology of HCl-doped polyaniline

The d.c. and a.c. (100 Hz–1 MHz) conductivities of HCl-doped polyaniline have been measured in the temperature range 77–300 K. At 77 K, the a.c. conductivity data, (), can be described by the relation ()=As, where the parameter s lies close to unity and decreases with increase in the doping level. The ratio of measured a.c. to d.c. conductivity shows dispersion at 77 K, which decreases with increase in the doping level. This decrease is found to be sharp around pH3.0. In the temperature range 77–150 K, the observed d.c. conductivity data can be described by Mott's three dimensional variable range hopping (VRH) model. Scanning electron microscopy studies reveal a sharp change in structural morphology of HCl-doped polyaniline at a pH3.0. A strikingly remarkable structural morphology has been observed in the formc of a channel at this pH value. This change is accompanied by a rapid increase in d.c. conductivity, dielectric constant, along with sharp changes in structural morphology, which indicates the existence of a doping-induced structural conductivity correlation in this system. © 1998 Chapman & Hall     

EPR study of Cu2+ in Na2O-NaF-B2O3-Bi2O3 glasses

Electron paramagnetic resonance (EPR) studies have been performed on the glass system (30–x) NaF-xNa₂O-50B₂O₃-20Bi₂O₃ doped with CuO as a paramagnetic probe. The calculated g values indicate that Cu²⁺ is in a tetragonally elongated octahedral co-ordination, and the Jahn-Teller character gives rise to anisotropic hyperfine structure. The spin-Hamiltonian parameters and -bonding parameter, ², are calculated. Varying the fluoride ion concentration and its effect on these parameters is also discussed.     

High order parameter-robust numerical method for time dependent singularly perturbed reaction–diffusion problems

We introduce a high order parameter-robust numerical method to solve a Dirichlet problem for one-dimensional time dependent singularly perturbed reaction-diffusion equation. A small parameter ε is multiplied with the second order spatial derivative in the equation. The parabolic boundary layers appear in the solution of the problem as the perturbation parameter ε tends to zero. To obtain the approximate solution of the problem we construct a numerical method by combining the Crank–Nicolson method on an uniform mesh in time direction, together with a hybrid scheme which is a suitable combination of a fourth order compact difference scheme and the standard central difference scheme on a generalized Shishkin mesh in spatial direction. We prove that the resulting method is parameter-robust or ε-uniform in the sense that its numerical solution converges to the exact solution uniformly well with respect to the singular perturbation parameter ε. More specifically, we prove that the numerical method is uniformly convergent of second order in time and almost fourth order in spatial variable, if the discretization parameters satisfy a non-restrictive relation. Numerical experiments are presented to validate the theoretical results and also indicate that the relation between the discretization parameters is not necessary in practice.     

Persistent ocean monitoring with underwater gliders: Adapting sampling resolution

Ocean processes are dynamic and complex and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high‐value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long‐term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show improvements in both data resolution and path reliability compared to previously executed sampling paths used in the respective regions. © 2011 Wiley Periodicals, Inc.