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research-article | 30-November-2019

Concept Drift Evolution In Machine Learning Approaches: A Systematic Literature Review

Big Data (BD) is participating in the current computing revolution immensely. Industries and organizations are utilizing their insights for Business Intelligence using Machine Learning (ML) models. However, BD’s dynamic characteristics introduce many critical issues for ML models, such as the Concept Drift (CD) issue. The issue of CD is observed when the statistical properties of data vary at a different time step. For example, a set of class examples has legitimate class labels at one time

Manzoor Ahmed Hashmani, Syed Muslim Jameel, Mobashar Rehman, Atsushi Inoue

International Journal on Smart Sensing and Intelligent Systems, Volume 13 , ISSUE 1, 1–16

Research Article | 11-January-2018

MEMS Seismic Sensor with FPAA-Based Interface Circuit for Frequency-Drift Compensation Using ANN

analog array (FPAA) (Anadigm AN231E04) based hardware implementation of artificial neural network (ANN) model with minimized error in frequency drift in the range of 3.68% to about 0.64% as compared to ANN simulated results in the range of 23.07% to 0.99%. Single neuron consumes power of 206.62 mW with minimum block wise resource utilization. The proposed hardware uses all analog blocks removing the requirement of analog to digital converter and digital to analog converter, reducing significant power

Ramesh Pawase, Dr. N.P. Futane

International Journal on Smart Sensing and Intelligent Systems, Volume 11 , ISSUE 1, 1–6

Article | 11-April-2018

Equivalence on Quadratic Lyapunov Function Based Algorithms in Stochastic Networks

Quadratic Lyapunov function based Algorithms (QLAs) for stochastic network optimization problems, which are cross-layer scheduling algorithms designed by Lyapunov optimization technique, have been widely used and studied. In this paper, we investigate the performance of using Lyapunov drift and perturbation in QLAs. By analyzing attraction points and utility performance of four variants of OQLA (Original QLA), we examine the rationality of OQLA for using the first-order part of an upper bound

Li Hu, Gao Lu, Liu Jiaqi, Wang Shangyue

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 179–185

Research Article | 27-February-2017

PROSPECTS FIXATION DRIFT SANDS PHYSICOCHEMICAL METHOD

Maujuda MUZAFFAROVA, Makhamadjan MIRAKHMEDOV

Transport Problems, Volume 11 , ISSUE 3, 143–152

Research Article | 12-December-2017

A LOW COST PORTABLE TEMPERATURE-MOISTURE SENSING UNIT WITH ARTIFICIAL NEURAL NETWORK BASED SIGNAL CONDITIONING FOR SMART IRRIGATION APPLICATIONS

Aman Tyagi, Arrabothu Apoorv Reddy, Jasmeet Singh, Shubhajit Roy Chowdhury

International Journal on Smart Sensing and Intelligent Systems, Volume 4 , ISSUE 1, 94–111

Article | 01-March-2012

FEEDFORWARD CONTROL OF TEMPERATURE-INDUCED HEAD SKEW FOR HARD DISK DRIVES

In hard disk drives (HDDs), head skew error among multiple heads is calibrated during manufacturing process, and will be implemented prior to head switching seeks. In operational environment, additional head skew deviation due to temperature drift may be observed, which could introduce heavy handling burden for feedback controller along with unacceptable noise to HDD customers. Therefore, a thorough analysis of head skew variation against temperature is carried out in this paper. With help of

Yong Xiao, Chi Zhang, Xiaoyu Ge, Peiqi Pan

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 1, 95–106

Research Article | 15-February-2020

Physiological bending sensor based on tilt angle loss measurement using dual optical fibre

This paper presents the development of an extrinsic optical fibre sensor for continuous measurement of the human spine bending movement based on intensity modulation technique. Using the investigated sensor configuration, the bending angle was measurable in both flexion and extension direction with a maximum range of motion of 18o and -10o, respectively. From the output drift assessment of the sensor, bending accuracy of up to 0.5o was achievable, thus making it suitable for clinical

M. A. Zawawi, S. O’Keeffe, E. Lewis

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 5, 1–4

Article | 30-November-2018

Research of Oil Pump Control Based On Fuzzy Neural Network PID Algorithm

Chen Gong, Shengquan Yang

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 4, 63–68

Article | 01-June-2016

A COST-EFFECTIVE AND ACCURATE ELECTRICAL IMPEDANCE MEASUREMENT CIRCUIT DESIGN FOR SENSORS

Ciaran Doyle, Dr Daniel Riordan, Dr Joseph Walsh

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 509–525

Article | 09-April-2018

Multi - scale Target Tracking Algorithm with Kalman Filter in Compression Sensing

Real-time Compressive Tracking (CT) uses the compression sensing theory to provide a new research direction for the target tracking field. The algorithm is simple, efficient and real-time. But there are still shortcomings: tracking results prone to drift phenomenon, cannot adapt to tracking the target scale changes. In order to solve these problems, this paper proposes to use the Kalman filter to generate the distance weights, and then use the weighted Bayesian classifier to correct the

Yichen Duan, Xue Li, Peng Wang, Dan Xu

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 10–14

Article | 01-March-2015

OBJECT TRACKING BASED ON MACHINE VISION AND IMPROVED SVDD ALGORITHM

Object tracking is an important research topic in the applications of machine vision, and has made great progress in the past decades, among which the technique based on classification is a very efficient way to solve the tracking problem. The classifier classifies the objects and background into two different classes, where the tracking drift caused by noisy background can be effectively handled by one-class SVM. But the time and space complexities of traditional one-class SVM methods tend to

Yongqing Wang, Yanzhou Zhang

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 677–696

Article | 01-June-2016

NOVEL SVDD-BASED ALGORITHM FOR MOVING OBJECT DETECTING AND TRACKING UNDER DYNAMIC SCENES

features, where the detecting and tracking drift caused by noisy background can be effectively handled by robust maximum margin classifier, such as one-class SVM. But the time and space complexities of traditional one-class SVM methods tend to be high, which limits its wide applications to various fields. Inspired by the idea proposed by Support Vector Data Description (SVDD), in this paper we present a novel SVDD-based algorithm to efficiently deal with detecting and tracking moving object under

Chunxiang Wang, Dongfang Xu, Yongqing Wang

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 1130–1155

Research Article | 21-April-2017

GRAVITY PIPELINE TRANSPORT FOR HARDENING FILLING MIXTURES

through pipes. On the basis of these indicators is proposed methodology for calculating the parameters of pipeline transport hardening filling mixtures in drift mode when traffic on the horizontal part of the mixture under pressure column of the mixture in the vertical part of the backfill of the pipeline. This technique allows stable operation is guaranteed to provide pipeline transportation.

Leonid KROUPNIK, Roza ABDYKALYKOV, Aleksander SŁADKOWSKI, Yuryi SHAPOSHNIK, Sergeyi SHAPOSHNIK

Transport Problems, Volume 10 , ISSUE 4, 129–136

Article | 07-November-2017

Physical and Virtual Intelligent Sensors for Integrated Health Management Systems

. spike, drift, noise, is detected, it is reported, stored and sent to a remote system through an Ethernet connection. Hence the output of the PIS is data coupled with a confidence factor in the reliability of the data. The VIS discussed here is a virtual implantation of the PIS in C++. The VIS is designed to mirror the operations of the PIS; however, the VIS works on a computer at which digital data is provided as the input and is thus portable to any sensor system. This work lays the foundation for

Ajay Mahajan, Christopher Oesch, Haricharan Padmanaban, Lucas Utterback, Sanjeevi Chitikeshi, Fernando Figueroa

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 3, 559–575

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