bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced Rssi-Based High Accuracy Real-Time User Location Tracking System For Indoor And Outdoor Environments
Authors: Lau Erin-Ee-Lin , Lee Boon-Giin , Lee Seung-Chul , Chung Wan-Young
Published: November 2017

Existing researches on location tracking focus either entirely on indoor or entirely on outdoor by using different devices and techniques. Several solutions have been proposed to adopt a single location sensing technology that fits in both situations. This paper aims to track a user position in both indoor and outdoor environments by using a single wireless device with minimal tracking error. RSSI (Received Signal Strength Indication) technique together with enhancement algorithms is proposed to cater this solution. The proposed RSSI-based tracking technique is divided into two main phases, namely the calibration of RSSI coefficients (deterministic phase) and the distance along with position estimation of user location by iterative trilateration (probabilistic phase). A low complexity RSSI smoothing algorithm is implemented to minimize the dynamic fluctuation of radio signal received from each reference node when the target node is moving. Experiment measurements are carried out to analyze the sensitivity of RSSI. The results reveal the feasibility of these algorithms in designing a more accurate real-time position monitoring system
Hydrogen Gas Sensing Performance Of Pt/Sno2 Nanowires/Sic Mos Devices
Authors: Shafiei M. , Kalantar-zadeh K. , Wlodarski W. , Comini E. , Ferroni M. , Sberveglieri G. , Kaciulis S. , Pandolfi L.
Published: November 2017

This paper presents material and gas sensing properties of Pt/SnO2 nanowires/SiC metal oxide semiconductor devices towards hydrogen. The SnO2 nanowires were deposited onto the SiC substrates by vapor-liquid-solid growth mechanism. The material properties of the sensors were investigated using scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. The current-voltage characteristics have been analyzed. The effective change in the barrier height for 1% hydrogen was found to be 142.91 meV. The dynamic response of the sensors towards hydrogen at different temperatures has also been studied. At 530°C, voltage shift of 310 mV for 1% hydrogen was observed
Leak Rate And Location Analysis Through Slits And Cracks In Pipes By Nano Porous CeramiC Humidity Sensors
Authors: Ghara Dilip Kumar , Saha Debdulal , Sengupta Kamalendu
Published: November 2017

Nano porous sol gel thin film humidity sensor was studied using commercially available reference humidity sensor from Honeywell Corporation. The main advantages of our developed set up for humidity measurements is low cost and high resolution yielding a full set of information on the variation of humidity at 250°C. Humidity is considered to be one of the most effective indicators of the leakage. On this ground we developed nano porous sensor which can be used for LBB (Leak before break) application. The ceramic sensors, based on sol gel thin film are shown to increase its capacitance upon water adsorption over the temperature range upto 250°C. The variation of capacity to voltage is shown to provide useful information on both break rate and location. The sensor installation spacing on the outer surface of the piping is determined as a function of the detection sensitivity. In this paper we have summarize the results of the development and characterization of ceramic humidity sensor for leak rate and location analysis by a microcontroller device
Determining The Step-Change Conductivity Profiles Within Layered Metal Structures Using Inductance Spectroscopy
Authors: Yin Wuliang , Peyton Anthony J
Published: November 2017

This paper presents an inverse method for determining the conductivity distribution of a flat, layered conductor using a multi-frequency electromagnetic sensor based on phase signature alone. Eddy current sensors are used in a wide range of non-destructive testing (NDT) applications. Single frequency sensors are very common, however, the potential of an eddy current sensor with spectroscopic techniques offer the ability to extract depth profiles and examine more fully the internal structure of the test piece. In this paper, we found a simplified model that can estimate the phase signature of a cylindrical coil above a conductor with an arbitrary conductivity profile. This simplified model improves the computational efficiency by many fold compared to the complete analytic solution. For inverse solution, a simplex search method was used to fit a set of multi-frequency phase values in a least-squared sense. Experimental eddy-current tests are performed by taking the difference in inductance of the coil when placed in free space and next to a layered conductor over the range 100Hz -1MHz. Good estimates for the conductivity profile from experimental and simulated data were obtained
Training Data Compression Algorithms and Reliability in Large Wireless Sensor Networks
Authors: Iyer Vasanth , Murthy Garimella Ram , Srinivas M.B.
Published: November 2017

With the availability of low-cost sensor nodes there have been many standards developed to integrate and network these nodes to form a reliable network allowing many different types of hardware vendors to coexist. Most of these solutions however have aimed at industry-specific interoperability but not the size of the sensor network and the large amount of data which is collected in course of its lifetime. In this paper we use well studied data compression algorithms which optimize on bringing down the data redundancy which is related to correlated sensor readings and using a probability model to efficiently compress data at the cluster heads. As in the case of sensor networks the data reliability goes down as the network resource depletes and these types of networks lacks any central synchronization making it even more a global problem to compare different reading at the central coordinator. The complexity of calibrating each sensor and using an adaptable measured threshold to correct the reading from sensors is a severe drain in terms of network resources and energy consumption. In this paper we separate the task of comparative global analysis to a central coordinator and use a reference PM ax which is a normalized probability of individual source which reflects the current lifetime reliability of the sensors calculated at the cluster heads which then is compared with the current global reliability index based on all the PMax of cluster heads. As this implementation does not need any synchronization at the local nodes it uses compress once and stamp locally without any threshold such as application specific calibration values (30±C ) and the summarization can be application independent making it more a sensor network reliability index and using it independent of the actual measured values.
Sensitivity Improvement of Wireless Pressure Sensor by Incorporating a Saw Reflective Delay Line
Authors: Oh Haekwan , Wang Weng , Lee Keekeun , Park Ikmo , Yang Sang Sik
Published: November 2017

this paper presents a wireless surface acoustic wave (SAW) pressure sensor on 41oYX LiNbO3 for tire pressure monitoring system (TPMS) application, in which a reflective delay line composed of an interdigital transducer (IDT) and several reflectors was used as the sensor element. Using the coupling of modes (COM), the SAW reflective delay line was simulated, and the optimal design parameters were determined. The fabricated 2.4GHz SAW sensor was wirelessly characterized by the network analyzer. Sharp reflection peaks, few spurious signals, and relatively high signal-to-noise (S/N) ratio were observed. High sensitivity of 2.9 deg/kPa and good linearity were observed.
Detection of Transverse Cracks in a Composite Beam Using Combined Features of Lamb Wave and Vibration Techniques in Ann Environment
Authors: Ramadas C. , Balasubramaniam Krishnan , Joshi M. , Krishnamurthy C.V.
Published: November 2017

The detection, location and sizing of transverse cracks in a composite beam, by combining damage features of Lamb wave and vibration based techniques in artificial neural network (ANN) environment, using numerical finite element model, is discussed. Four damage features, time of flight (TOF) and amplitude ratio, which are Lamb wave based features and first and second natural frequencies, which are vibration based features were used as input to ANN. The output of ANN was crack location and depth. It was demonstrated that through the simultaneous employment of features from the two modalities in an ANN environment, the sizing could be done more effectively.
INVITED PAPER: Scalability and Performance Issues in Deeply Embedded Sensor Systems
Authors: Sridhar Prasanna , Madni Asad M.
Published: November 2017

The property of scalability for a given system indicates the ability of a system or a subsystem to be modified with changing load on the system. For a sufficiently large complex system, there are several factors that influence the ability of the system to scale. It is necessary to incorporate solutions to these factors (or bottlenecks) in the design for scalability of a given system. In this paper, we discuss such design principles to handle the key factors that influence the scalability of large complex systems. Specifically, we demonstrate design and implementation of simple, innovative, and relatively less expensive methodology to guarantee that a large complex system (such as network of sensors) is scalable under varying load conditions.
An Attitude Based Multi-agent Problem Solving in a Hostile World
Authors: Goyal Madhu
Published: November 2017

In multi-agent setting agent often encounter conflicts in agents’ plans and actions. This paper presents an attitude based cooperative decision making methodology that allows agents to act appropriately to various options in a hostile and dynamic fire world. It shows that attitude based decision making explore the attitudes and behaviors that help agents to solve problems constructively. The application and implementation of this methodology to a virtual fire-fighting domain has revealed a promising prospect in negotiating conflicts and solving them
OSGi-Based Context-Aware Middleware for Building Intelligent Services in a Smart Home Environment
Authors: Cheng Shu-Chen , Lai Chien-Feng
Published: November 2017

Context awareness technology is a key technology of digital home that brings a more convenient life. Context awareness technology is a system that catches the information from the sensor network, which is built in environment, the network could get the environment data immediately, and through this data information that network provides, the system could do the exactly the right thing that help people’s like getting better. These information data could be location, temperature or humidity. However, these data are used by context awareness system to analysis and process, so as to realize different person in different environment using every kind of devices and through any different existing network system, and still could enjoy the personality applications and services in any time they want. This thesis proposed Intelligent Context-Aware Middleware is including system core modeling, context provider, context analysis model, reasoning system, scenario analysis model and some other APIs to achieve the context awareness system that a digital home needs. Besides, this middleware collaborates with OSGi framework in paralleled. In other words, this Intelligent Context-Aware Middleware is totally associated to each other, which means every new devices could be compatible to either OSGi framework or Intelligent Context-Aware Middleware this thesis proposed immediately
Modeling And Measurement System For Magnetic Field Distributions In Biological Structures
Authors: Marinova I. , Mateev V. , Endo H. , Saito Y.
Published: November 2017

In this paper we develop a system for modeling and measurement of magnetic field distributions in biological structures caused by the externally applied electromagnetic field. We describe an effective and versatile approach for three-dimensional reconstruction of the field distributions from two-dimensional visualization the measured magnetic field data. The finite element model for magnetic field calculation is built. The magnetic fields of very thin slices of the 3D object are determined and visualized. Using these 2D images as slices of 3D image and based on the field theory and image processing techniques we developed a reconstruction approach for 3D visualization of magnetic field. This approach combines new technologies of 3D visualizations and characterizes with flexibility, simplicity and portability. The proposed approach was successfully applied for 3D reconstruction and visualization of magnetic field and current distributions in biological structures. The virtual microscope is developed for investigations of magnetic field distributions in biological structures during magnetic stimulation. Anisotropic Magneto-Resistive (AMR) sensors are applied for magnetic field measurements. AMR sensors are combined in array probes in order to increase productivity of measurement process and improving the performance of probes.
A Simple And Countable Method For The Assessment Of Perceived Well-Being Among Elderly People
Authors: Reijula Jori , Rosendahl Toni , Reijula Kari , Linnavuo Matti , Sepponen Raimo
Published: November 2017

This report illustrates the technical design for the monitoring system of wellbeing and demonstrates its feasibility in elderly people. The Con-Dis device consists of three buttons with a happy, neutral or unhappy face, each describing the mood of the patient. The functionality of the device was tested on 5 test persons who were asked to demonstrate their state of well-being by pressing one of the three buttons representing present condition three times per day for a time period of one week (5 working days). The device is based on Atmel’s 8-bit AVR microcontroller, ATMEGA 128, placed on an AVR-MT-128 development board. The software used by the ATMEGA microcontroller was developed using the C language in the AVRStudio development environment. On the basis of the collected results, the Con-Dis - device functioned reliably in monitoring the perceived wellbeing and mood of the test persons.
Portable Automatic Conjecturing and Announcing System for RealTime Accident Detection
Authors: Lai Chin Feng , Liu Chen Ying , Chang Sung-Yen , Huang Yueh Min
Published: November 2017

In this paper, we propose the portable automatic conjecturing and announcing system for real-time accident detection. There are six sensors with 3-axis accelerometers and the ZigBee transmission standard mounted on the patients’ specific region. After being transmitted to the mobile device through the ZigBee devices, the data are analyzed immediately. When the accident occurs, the mobile device could get the user’s location with Assisted Global Positioning System (AGPS) and transmit the information of accident to the medical staff through the 3rd-generation (3G) network. The medical staff will make a careful check of this accident with the patient again. In order to improve the limit of Regional Health Network (RHN), the environment constraints, the mobile computing capability, the power consumption and the device portability are considered in this system architecture we proposed.
Adaptive Routing Protocol for Reliable Sensor Network Applications
Authors: Chen Jiann-Liang , Hsu Yu-Ming , Chang I-Cheng
Published: November 2017

The existing routing protocol for sensor networking can be divided into proactive routing protocol, reactive routing protocol and hybrid routing protocol. Each routing protocol has its merits and shortcomings. The lifetime will end when the working routing protocol can no longer support the whole wireless sensor network. An adaptive method based on redundancy node and dual routing protocol was proposed in the study. Redundancy node, when wireless sensor network is being deployed, can divide the wireless sensor network into operating and sleeping modes, and can use the different routing protocol. Dual routing protocol individually designs two kinds of different routing protocols in the sensor node, using the merits of these two different kinds of routing protocols to accomplish the mission of sending the data. The scenario set up is when the wireless sensor network has been used for a long time; the power kept in these sensor nodes is different. It is possible that some sensor nodes contain lower power because the heavy load of work, and some with more power because of less work load. After we send a query to the source node and unfortunately find out there is more than one wireless sensor in the routing path, and if there is power shortage, we can only query a message to send the sink to the source node. At the meantime, the source node will judge the storing condition of the power in all the sensor nodes when sending the query from the sink to the source node. Then the target wireless sensor will send a broadcast to all the neighbors. If there is a sleeping node in the neighbor and run a second kind of routing protocol, the sleeping wireless sensor will wake up. The woken sensor node will build up a path to ensure the data get sent from the source to the sink. Simulation results showed that the proposed mechanism is about 44% of packet delivery ratio can be increased compared to existing proactive/reactive routing protocol.
Non-Invasive Characterization of total Hip Arthroplasty by Means of Passive Acceleration Measurement
Authors: Lieschnegg M. , Zacherl M. , Lechner B. , Weger C. , Fuchs A.
Published: November 2017

This paper presents a non-invasive measurement method to detect and characterize failures and material imperfections in total joint prostheses based on acceleration measurement. Therefore, a prototype sensor has been developed to fulfill the requirements of a medical-technical sensor. This sensor has been tested on patients with total hip arthroplasty. Special emphasis is put on the real-time processing of measurement data by means of intelligent signal processing as well as reliable and repeatable measurement procedures, including standardized positions for the sensor front-end and a standardized motion-sequence the patient is performing.
Microstructuring of SU-8 Resist for MEMS and Bio-Applications
Authors: Dey P.K. , Pramanick B. , RaviShankar A. , Ganguly P. , Das S.
Published: November 2017

Some studies on the fabrication of micro-needles, micro-pillers, and micro-channels using SU-8 negative photoresist for MEMS and bio-applications are reported. The SU-8 processing technology was standardized for the purpose. Micro-pillars were fabricated on SU-8 polymer by soft lithographic technique. Micro-needles were realized on SU-8 film utilizing lensing effect of the etched groove structure of the glass substrate. Micro-channel was fabricated by molding of PDMS polymer on patterned SU-8 ridge structure. Structural characterization of the fabricated structures were investigated using optical microscope and SEM.
Dual Modality Tomography System Using Optical and Electrodynamic Sensors for Tomographic Imaging Solid Flow
Authors: Rahmat M. F. , Ibrahim S. , Elmajri M. M. , Mohammed N. F. , Isa M.D
Published: November 2017

Process tomography is a technique to realize flow imaging in a process vessel or pipeline by using the sensor system. This technique involves the use of tomographic imaging methods to manipulate data from sensors in order to collect sufficient information about the flow in the pipeline. The overall aim of this paper is to investigate the benefits of dual modality (optical and electrodynamic) tomography system for the measurement of tomographic images of solids flow. This research will investigate the distribution of conveying plastic beads in a conveying pipe by placing optical and electrodynamic sensors around the pipe without interrupting the flow inside the pipe.
Real-Time Path Planning Tracing of Deformable Object by Robot
Authors: Sahari Khairul Salleh Mohamed , Seki Hiroaki , Kamiya Yoshitsugu , Hikizu Masatoshi
Published: November 2017

Edge tracing is considered important for deformable object manipulation in order to spread and reveal the original shape of an object before it can be sorted. This paper proposes a unique realtime path-planning tracing method for clothes manipulation by robots. Tracing in this paper context involves tracing the clothes edge, with the robot arm movement based on the calculated path and feedback from sensors. Using tracing method to find a second corner has been proven to be efficient in finding a second corner next to the first corner and not apposite it, resulting in the robot properly spreading the clothes. Adequate force control is also applied to the gripper during tracing so that it doesn't grip the clothes too hard or vice versa which can affect the performance of the robot. Vision sensor is used from time to time to check whether the static gripper has reached the second corner or not. Practical experiments were conducted to evaluate the proposed method. Experimental results have demonstrated the uniqueness and effectiveness of the proposed method.
Design of Vibration-Based Miniature Generator Using Piezoelectric Bender
Authors: Li Wei , Liu Tzong-Shi , Lin Heng-I , Tsai Yi-Jeng
Published: November 2017

For the use of green energy and ubiquitous computing, this study investigates miniature electric generators that are constructed with piezoelectric benders. Electric power is generated by vibratory deformation of piezoelectric benders. Three different designs of piezoelectric generators are created and compared in this study by using mechanics analysis. The result shows that the cantilever design yields more power than symmetric and airfoil designs. Experimental results show that generated voltage rises with not only attached point masses, but also the swing frequency of a swing arm, to which the proposed piezoelectric generator is attached. In addition, At 6.5 Hz swing frequency, the maximum power 0.3μW is generated.
Model identification and Smart structural vibration Control using H
∞ controller
Authors: Sridevi M. , Madhavasarma P.
Published: November 2017

A smart structure plays a vital role in aerospace applications and robotics and other applications. It presents many challenging control problems due to their non-linear dynamic behavior. The Objective of this work is to design a controller that minimizes the structural vibration using H∞ controller. Vibration as a measured parameter has been used to evaluate model of a nonlinear process (piezoelectric actuator and sensor) at different modes .The model was generated using an ARMAX technique. By selecting appropriate weighting functions H
∞
controller were designed based on mixed sensitivity approach using singular loop shaping method. The performance of
H
∞
controller was compared with LQG controller based on vibration reduction. From the results it is observed that the H∞ controller is the best suited for smart structural process.
Application Of Draw Wire Sensor In Position Tracking Of Electro Hydraulic Actuator System
Authors: Rahmat MF , Rozali S Md , Wahab N Abdul , Zulfatman
Published: November 2017

Draw-wire sensor is classified as a contact measurement method. This sensor is ideal for applications with large measuring ranges, small sensor dimensions and when a low cost solution is required. The objective of this research is to explain the application of a draw-wire sensor in position tracking of electro-hydraulic actuator system. The work started with the modeling of the electro hydraulic actuator system. Draw wire sensor is attached to the load of electro hydraulic system to measure its motion when an input signal is injected to the system. The sensor output is the displacement in millimeter and converted to the voltage based on the input signal given. These input and output readings are collected and applied to a system identification procedure in order to obtain the best mathematical model of the system. The modeling process is followed by designed a proportional integral and derivative controller (PID) for the system to assure the output is tracking the input given. The designed controller is applied to the system in both simulation and real time mode. The output performance of the system for these two modes is compared and it can be seen that the simulation and real-time output are almost similar. The overall process of this work shows the important role of draw wire sensor in capturing the output data of the electro hydraulic actuator system precisely either with or without controller. Other displacement transducer might be used in future work of position tracking of electro-hydraulic actuator system.
Cyclic Temporal Network Density and its impact on Information Diffusion for Delay Tolerant Networks
Authors: Yang Lintao , Wang Sai , Jiang Hao
Published: November 2017

We adopt temporal graph model to explore the dynamic temporal properties of three mobility datasets in DTN (Delay Tolerant Network), collected from different sources, including one university campus WLAN and two conferences WLANs. With this model, we observe that the temporal network density of DTN changes with time and approximate varies periodically. Then we study the impact of this phenomenon on information diffusion. Our studies and findings can be used for establishing more realistic mobile model, building intelligent routing algorithm, and design advanced applications for DTNs.
A Low Cost Portable Temperature-Moisture Sensing Unit With Artificial Neural Network Based Signal Conditioning For Smart Irrigation Applications
Authors: Tyagi Aman , Reddy Arrabothu Apoorv , Singh Jasmeet , Chowdhury Shubhajit Roy
Published: November 2017

The recent trends in developing low cost techniques to support cost effective agriculture in developing countries with large population has motivated the development of low cost sensing systems to provide for low cost irrigation facilities and also to provide for conservation of water at the same time. The current paper highlights the development of temperature and soil moisture sensor that can be placed on suitable locations on field for monitoring of temperature and moisture of soil, the two parameters to which the crops are susceptive. The sensing system is based on a feedback control mechanism with a centralized control unit which regulates the flow of water on to the field in the real time based on the instantaneous temperature and moisture values. Depending on the varied requirement of different crops, a lookup table has been prepared and referred to for ascertaining the amount of water needed by that crop. The system based on a microcontroller has been applied on rice and maize fields spanning over area of 1 acres each for 3 weeks and more than 94% of the plants were found to be alive after experimentation. The cost of the system has been estimated to be as low as 120 INR and is therefore easily deployable in developing countries.
A Method For Fine Bonding Wire Detection Using Light Diffraction
Authors: Xiao Yong , Wang Xiaoyan , Zhu Kuanyi , Ge Xiaoyu , Sun Jingna
Published: November 2017

In manufacturing industry, bonding wires are used to interconnect the pads of a semiconductor chip to terminals of a package containing the chip [1]. With increasing demand of fine wires, current detection apparatus encounters some limitations. In this paper, a method to detect breakage of fine bonding wires using diffraction of light is proposed, where a laser head generates the light beam, and a slot introduced in the path of light source generates diffraction pattern. Then, irradiance loss of the corresponding diffraction pattern at the receiver could be observed, due to the presence of a wire. Simulation and experimental results show that the proposed method with a slot design renders satisfactory performance of wire detection.
Topology Optimization Control with Balanced Energy and Load in Underwater Acoustic Sensor Networks
Authors: Fu Wenyan , Li Deshi , chen Jian , Han Yanyan , Nie Jugen
Published: November 2017

In view of unbalanced link bandwidth and node energy consumption in Underwater Acoustic Sensor Networks (UASNs), a distributed topology optimization control algorithm (EL-BatCA) is proposed, which is based on balanced network energy and load. A hierarchical network model is designed based on minimum-hop, by which the nodes are divided into n layers. EL-BatCA is implemented through three stages-topology graph formation in initialization, an innovative transmission power adjustment in topology control, and finally topology optimization through object functions. Simulation results show that EL-BatCA not only balances energy consumption and network load, but also prolongs network lifetime and improves network throughout.
Modeling and Control of Ball and Beam System using Model Based and Non-Model Based Control Approaches
Authors: Keshmiri Mohammad , Jahromi Ali Fellah , Mohebbi Abolfazl , Amoozgar Mohammad Hadi , Xie Wen-Fang
Published: November 2017

The ball and beam system is a laboratory equipment with high nonlinearity in its dynamics. The aims of this research are to model the ball and beam system considering nonlinear factors and coupling effect and to design controllers to control the ball position. The LQR is designed considering two Degrees-of-Freedom and coupling dynamics. The parameters of the LQR are tuned using Genetic Algorithm (GA). Jacobian linearization method is used to linearize the system around operating-point. Due to the noise of the sensor in the experimental setup, a state observer is designed to observe the velocity of the ball. In order to compare the performance of the LQR and study the effect of simplifying assumptions, two control strategies are designed and implemented: Proportional Derivative Integral (PID) as non-model based control strategy, hybrid PID and Linear Quadratic Regulator (LQR) as combination of model based and non-model based control strategies. The experimental results of this research prove the model based control strategies outperforms the non-model based or hybrid controllers in a nonlinear and noisy ball and beam system. In addition, it is shown that the coupling dynamics cannot be eliminated as a simplifying assumption in designing the controller.
Feedforward Control of Temperature-Induced Head Skew for Hard Disk Drives
Authors: Xiao Yong , Zhang Chi , Ge Xiaoyu , Pan Peiqi
Published: November 2017

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 accurate estimation of head skew based on drive temperature, smart feedforward control strategy during drive startup is embedded. Experimental results demonstrating its effectiveness to enhance drive performance are given.
Passive Uhf Rfid Strain Sensor Tag for Detecting Limb Movement
Authors: Merilampi S. , Björninen T. , Sydänheimo L. , Ukkonen L.
Published: November 2017

A strain sensor tag with screen printed antenna for seamless integration with clothing is examined to provide a wireless method for monitoring of human body movements. The strain response of the tag is investigated in air and on human body. While the results indicate strong antenna-body interaction, the strain response of the tag is found to be a monotonic function of the strain.
Optical Probe Current Sensor Module Using the Kerr Effect of Exchange-Coupled Magnetic Film and its Application to Igbt Switching Current Measurements
Authors: Ogawa K. , Suzuki S. , Sonehara M. , Sato T. , Asanuma K.
Published: November 2017

An optical probe current sensor module using the Kerr effect of exchange-coupled magnetic film has been fabricated and applied to switching current measurements for IGBT used for the DC-DC converter and the DC-AC inverter of EV/HEV. Since the sensor module using the Kerr effect of the single domain exchange-coupled magnetic film utilizes magnetization rotation only, Barkhausen noise due to domain wall pinning can be excluded. The current sensor consists of a Laser-diode, a polarizer, a Fe-Si/Mn-Ir exchange-coupled film, a quarter-wavelength plate, PIN Photodiodes and a differential amplifier. The current sensor has a current measurement range of ±60 A and a frequency range of DC 200 kHz. The switching current of IGBT has been measured by it.
A New Kind of Pso: Predator Particle Swarm Optimization
Authors: Neshat Mehdi , Sargolzaei Mehdi , Masoumi Azra , Najaran Adel
Published: November 2017

Today, swarm intelligence is widely used in optimization problems. PSO is one the best swarm intelligence methods. In the method, each particle moves toward the direction in which the best individual and group experience has happened. The most important disadvantage of this method is that it falls in local optima. To fix the problem, a metaheuristic method is proposed in this paper. There has always been a competition between prey and predator in the nature. Little birds often fly in a colony form to run away from birds of prey. Being inspired by the phenomenon, a new particle is added to PSO algorithm known as predator, also a new behavior called “Take flight from predator” is defined.
This particle is responsible for attacking the colony of particles so as to prevent the premature convergence. With the predator attack to the colony, particles run away and again the chance rises for a Global optimum to be gained. The attack just caused particles dispersion and no particle dies. It can be repeated for m times and the optimal point is saved each time. To test the method, 12 benchmark functions were employed and the results were compared to OPSO, VPSO, LPSO, and GPSO methods. Regarding the results, the proposed method had a better performance.
Classification Problems Based on Regression Models for Multi-Dimensional Functional Data
Authors: Górecki Tomasz , Krzyśko Mirosław , Wołyński Waldemar
Published: November 2017

Data in the form of a continuous vector function on a given interval are referred to as multivariate functional data. These data are treated as realizations of multivariate random processes. We use multivariate functional regression techniques for the classification of multivariate functional data. The approaches discussed are illustrated with an application to two real data sets.
An Approximation to the Optimal Subsample Allocation for Small Areas
Authors: Molefe W. B. , Shangodoyin D. K. , Clark R. G.
Published: November 2017

This paper develops allocation methods for stratified sample surveys in which small area estimation is a priority. We assume stratified sampling with small areas as the strata. Similar to Longford (2006), we seek efficient allocation that minimizes a linear combination of the mean squared errors of composite small area estimators and of an estimator of the overall mean. Unlike Longford, we define mean-squared error in a model-assisted framework, allowing a more natural interpretation of results using an intra-class correlation parameter. This allocation has an analytical form for a special case, and has the unappealing property that some strata may be allocated no sample. We derive a Taylor approximation to the stratum sample sizes for small area estimation using composite estimation giving priority to both small area and national estimation.
A Measure for Regional Resilience to Economic Crisis1
Authors: Markowska Małgorzata
Published: November 2017

The purpose of the study (presented in this article) was to develop a measure of resilience to crisis, one that may be applied to regional data. In principle, such measure can take either positive or negative values. A positive value confirms resilience to crisis, whereas a negative one confirms the absence of resilience (sensitivity/vulnerability). The measure uses growth rates referred to the previous year under the assumption that crisis results in a slowdown in growth, or even in a decline in values of important economic indicators. Growth rates are standardized by dividing values of original change rates by medians specified based on spatio-temporal data modules. Such division results in each characteristic being brought to equal validity. Simultaneously, the original character is maintained and variables are not “flattened” by the outliers. Changing destimulants into stimulants occurs during growth rates calculation. The measure of resilience to crisis is calculated as an arithmetic mean of the values of characteristics brought to comparability. The measure of resilience can be converted into the measure of sensitivity by multiplying it by (-1).

The application of the proposed measure to assessing the resilience to crisis in the period 2006-2011 is presented for regions meant as the European Union NUTS2 units. The measure is based on comparable data, which allowed for using only six variables measuring changes in GDP, salaries, investments, household income, employment and unemployment.
Exploiting Ordinal Data for Subjective Well-Being Evaluation
Authors: Fattore Marco , Maggino Filomena , Arcagni Alberto
Published: November 2017

The evaluation of subjective well-being, and of similar issues related to quality of life, is usually addressed through composite indicators or counting procedures. This leads to inconsistencies and inefficiency in the treatment of ordinal data that, in turn, affect the quality of information provided to scholars and to policy-makers. In this paper we take a different path and prove that the evaluation of multidimensional ordinal well-being can be addressed in an effective and consistent way, using the theory of partially ordered sets. We first show that the proper evaluation space of well-being is the partially ordered set of achievement profiles and that its structure depends upon the importance assigned to well-being attributes. We then describe how evaluation can be performed extracting information out of the evaluation space, respecting the ordinal nature of data and producing synthetic indicators without attribute aggregation. An application to subjective well-being in Italy illustrates the procedure.
On Measuring Income Polarization: An Approach Based on Regression Trees
Authors: Mussini Mauro
Published: November 2017

This article proposes the application of regression trees for analysing income polarization. Using an approach to polarization based on the analysis of variance, we show that regression trees can uncover groups of homogeneous income receivers in a data-driven way. The regression tree can deal with nonlinear relationships between income and the characteristics of income receivers, and it can detect which characteristics and their interactions actually play a role in explaining income polarization. For these features, the regression tree is a flexible statistical tool to explore whether income receivers concentrate around local poles. An application to Italian individual income data shows an interesting partition of income receivers.
New Method of Variable Selection for Binary Data Cluster Analysis
Authors: Korzeniewski Jerzy
Published: November 2017

Cluster analysis of binary data is a relatively poorly developed task in comparison with cluster analysis for data measured on stronger scales. For example, at the stage of variable selection one can use many methods arranged for arbitrary measurement scales but the results are usually of poor quality. In practice, the only methods dedicated for variable selection for binary data are the ones proposed by Brusco (2004), Dash et al. (2000) and Talavera (2000). In this paper the efficiency of these methods will be discussed with reference to the marketing type data of Dimitriadou et al. (2002). Moreover, the primary objective is a new proposal of variable selection method based on connecting the filtering of the input set of all variables with grouping of sets of variables similar with respect to similar groupings of objects. The new method is an attempt to link good features of two entirely different approaches to variable selection in cluster analysis, i.e. filtering methods and wrapper methods. The new method of variable selection returns best results when the classical k-means method of objects grouping is slightly modified.
Sujatha Distribution and its Applications
Authors: Shanker Rama
Published: November 2017

In this paper a new one-parameter lifetime distribution named “Sujatha Distribution” with an increasing hazard rate for modelling lifetime data has been suggested. Its first four moments about origin and moments about mean have been obtained and expressions for coefficient of variation, skewness, kurtosis and index of dispersion have been given. Various mathematical and statistical properties of the proposed distribution including its hazard rate function, mean residual life function, stochastic ordering, mean deviations, Bonferroni and Lorenz curves, and stress-strength reliability have been discussed. Estimation of its parameter has been discussed using the method of maximum likelihood and the method of moments. The applications and goodness of fit of the distribution have been discussed with three real lifetime data sets and the fit has been compared with one-parameter lifetime distributions including Akash, Shanker, Lindley and exponential distributions.
Estimation of Mean on the Basis of Conditional Simple Random Sample
Authors: Wywiał Janusz
Published: November 2017

Estimation of the population mean in a finite and fixed population on the basis of the conditional simple random sampling design dependent on order statistics (quantiles) of an auxiliary variable is considered. Properties of the well-known Horvitz-Thompson and ratio type estimators as well as the sample mean are taken into account under the conditional simple random sampling designs. The considered examples of empirical analysis lead to the conclusion that under some additional conditions the proposed estimation strategies based on the conditional simple random sample are usually more accurate than the mean from the simple random sample drawn without replacement.
Prediction of a Function of Misclassified Binary Data
Authors: Al-Kandari Noriah M. , Lahiri Partha
Published: November 2017

We consider the problem of predicting a function of misclassified binary variables. We make an interesting observation that the naive predictor, which ignores the misclassification errors, is unbiased even if the total misclassification error is high as long as the probabilities of false positives and false negatives are identical. Other than this case, the bias of the naive predictor depends on the misclassification distribution and the magnitude of the bias can be high in certain cases. We correct the bias of the naive predictor using a double sampling idea where both inaccurate and accurate measurements are taken on the binary variable for all the units of a sample drawn from the original data using a probability sampling scheme. Using this additional information and design-based sample survey theory, we derive a bias-corrected predictor. We examine the cases where the new bias-corrected predictors can also improve over the naive predictor in terms of mean square error (MSE).
Changing Mortality Distribution in Developed Countries from 1970 to 2010: Looking at Averages and Beyond Them
Authors: Szulc Adam
Published: November 2017

The methods typically developed in income inequality and poverty research are employed to observe changes in life spans distribution in 35 developed countries. The analyses are performed at two levels, using the same methods when possible: i/ taking the countries as the units with a mean length of life being a single parameter representing the distribution, ii/ utilizing the country life tables (taking people as the units) in order to compare other than mean length of life attributes of mortality distribution. Increasing divergence in the mean length of life across the countries is due to growing distance of the countries below the median, mainly the post-communist ones, to the upper half. The comparisons of the within-country distributions of ages at death by means of the Kullback-Leibler divergence provides similar results. However, poverty and inequality indices calculated at this level yield opposite conclusions. Hence, most of the between-country variation might be attributed to the variation in the mean length of life while the changes in within-country inequality reduced this effect. At the same time, huge alterations in the within-country mortality rankings can be observed. Australia, Japan, Taiwan, Austria and Luxembourg may be said to be the “winners” while most of the post-communist countries are among the “losers”.
Spatial Autocorrelation in Assessment of Financial Self-Sufficiency of Communes of Wielkopolska Province
Authors: Kozera Agnieszka , Głowicka-Wołoszyn Romana
Published: November 2017

The aim of the article was to identify the spatial effects in assessment of financial self-sufficiency of the governments of communes (gminas) of Wielkopolska province (voivodship) in 2014, employing global and local Moran I statistics. The level of the governments’ self-sufficiency was examined by positional TOPSIS method. The study was based on publicly accessible databases compiled by the Ministry of Finance (Wskaźniki do oceny sytuacji finansowej jednostek samorządu terytorialnego) and the Central Statistical Office (Local Data Bank). Calculations were performed in R with packages spdep, maptools and shapefiles.

The study demonstrated that the communes of Wielkopolska province of comparable levels of financial self-sufficiency exhibited a moderate tendency to cluster. Clusters of high levels gathered around larger urban centres, especially around Poznań, while clusters of low levels – in economically underdeveloped agricultural south-eastern and northern part of the province.
In Search of Hedges and Safe Havens in Global Financial Markets
Authors: Wanat Stanisław , Śmiech Sławomir , Papież Monika
Published: November 2017

The aim of the paper is to search for hedges and safe havens within three instrument classes: assets (represented by the S&P500 index), gold and oil prices, and dollar exchange rates. Weekly series of returns of all the instruments from the period January 1995 – June 2015 are analysed. The study is based on conditional correlations between the instruments in different market regimes obtained with the use of copula-DCC GARCH models. It is assumed that different market regimes will be identified by statistical clustering techniques; however, only conditional variances (without conditional covariances) will be taken into account. The reason for this assumption is connected with the fact that variances can be understood as market risk, and, as such, are a good indicator of market conditions. A considerable advantage of such an approach is the lack of need to determine the number of market regimes, as it is established by clustering quality measures. What is more, the methodology used in the paper makes it possible to treat the relations between instruments symmetrically. The results obtained in the study reveal that only dollar exchange rates can be treated as a (strong) hedge and a (strong) safe haven for other instruments, while gold and oil are a hedge for assets.
Bayesian Accelerated Failure Time and its Application in Chemotherapy Drug Treatment Trial
Authors: Prabhash Kumar , Patil Vijay M , Noronha Vanita , Joshi Amit , Bhattacharjee Atanu
Published: November 2017

The Cox proportional hazards model (CPH) is normally applied in clinical trial data analysis, but it can generate severe problems with breaking the proportion hazard assumption. An accelerated failure time (AFT) is considered as an alternative to the proportional hazard model. The model can be used through consideration of different covariates of interest and random effects in each section. The model is simple to fit by using OpenBugs software and is revealed to be a good fit to the Chemotherapy data.