bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and Characterization of Surface Micro-Machined MEMS Based Varactor
Authors: Chakraborty Subha , Bhattacharya A. , Chaudhuri Ashesh Ray , Bhattacharyya T.K. 
Published: November 2017

Abstract
This paper presents complete behavioral analysis of a surface micro-machined MEMS varactor for frequency tuning application in voltage controlled oscillators in RF applications with high Quality factor and tunability. The dimensions of the MEMS device have been optimized with Finite Element Method based CoventorWare analysis and verified through lumped parameter analysis in Saber platform. The MEMS varactor has been fabricated with the PolyMUMPs process. The paper also describes the Mechanical and electrical characterization of the MEMS varactor to meet the designed specification.
Fiber Bragg Grating Sensors: New Ideas on Straintemperature Discrimination
Authors: Rahman Aashia , Asokan Sundarrajan 
Published: November 2017

Abstract
In this paper, two novel methods are discussed, wherein Fiber Bragg Gratings are used as sensors to discriminate strain and temperature, simultaneously. These methods provide a good linear response and involve simple fabrication & implementation of the sensors.
Micro-Generator Design for Smart Grid System (Comparative Study)
Authors: Shahat Adel El , Keyhani Ali , Shewy Hamed El 
Published: November 2017

Abstract
High Speed PM Generators driven by micro-turbines are widely used in Smart Grid System. So, this paper proposes comparative study among six classical, optimized and genetic analytical design cases for 400 kW output power at tip speed 200 m/s. These six design trials of High Speed Permanent Magnet Synchronous Generators (HSPMSGs) are: Classical Sizing; Unconstrained optimization for total losses and its minimization; Constrained optimized total mass with bounded constraints are introduced in the problem formulation. Then a genetic algorithm is formulated for obtaining maximum efficiency and minimizing machine size. In the second genetic problem formulation, we attempt to obtain minimum mass, the machine sizing that is constrained by the non-linear constraint function of machine losses. Finally, an optimum torque per ampere genetic sizing is predicted. All results are simulated with MATLAB, Optimization Toolbox and its Genetic Algorithm. Finally, six design examples comparisons are introduced with study of machines waveforms, THD and rotor losses.
Simulation Studies on a New Intelligent Scheme For Relative Humidity And Temperature Measurement Using Thermistors in 555 Timer Circuit
Authors: Dey Debangshu , Munshi Sugata 
Published: November 2017

Abstract
This paper presents a novel and cheap electronic version of wet and dry temperature hygrometer The instrument is centered around a 555 timer, operated in astable multivibrator mode. Two thermistors with negative temperature coefficients (NTC) serve as the two timing resistors of the multivibrator. These thermistors are used to sense the dry and wet temperatures. The durations of the ‘HIGH’ and ‘LOW’ levels of the multivibrator output are detected and these values are used to predict the relative humidity and ambient temperature by an appropriately trained Artificial Neural Network (ANN). The performance of the arrangement has been evaluated by numerical simulation studies using thermistor data from manufacturer’s table. Significantly good results have been obtained.
A High Resolution of Human Breath Gas Sensor and the Analysis of Hyperventilation for Rescue Robotics in Disaster Zones (IRIS2010)
Authors: Toda Hideki , Capi Genci 
Published: November 2017

Abstract
This paper presents a new type of ultrasonic gas molecule concentration sensor for rescue robotics and the performance of developed sensor is investigated by applying as human breath gas measurement sensor. This devise can measure the change of the gas concentration with a sampling rate of 400 kHz. Ideal gas experiment results show that the proposed sensor could detect the difference between 5% CO2 and pure air over 50 dB S/N and could discriminate humidified air and pure air with 55 dB S/N. Another important result is that our proposed respiratory sensor could detect the “dead space” distributed from lungs to mouth, which could not be detected by previously proposed commercial use gas concentration sensors. Therefore, this sensor can detect a human-specific smallamount of molecular gas change of the survivors in a disaster zones. In addition, we measured the hyperventilation state, in which it is assumed that the survivor is in critical conditions.
A Wavelet-Based Bridge Weigh-In-Motion System
Authors: Lechner B. , Lieschnegg M. , Mariani O. , Pircher M. , Fuchs A. 
Published: November 2017

Abstract
Bridge Weigh-in-Motion systems can be used to estimate vehicle parameters such as velocity, axle loads, or the distance between axles without affecting the traffic. These parameters and the classification of vehicles are necessary to determine vehicle overload and hence may help to reduce risks for road users and road infrastructure and allow optimized planning of maintenance work.
The Bridge Weigh-in-Motion system developed is based on a crack displacement sensor with intelligent data processing algorithms: In a first step, the number of axles, the distance between axles, and the velocity of the vehicle is obtained from the crack displacement signal by means of wavelet decomposition. In a subsequent step, the axle loads are found by means of optimizing the weights for axle loads that the measured crack displacement signal can be approximated by a superposition of (shifted and extended/compressed) ‘Lines of Influence’. Intensive test runs have been performed to verify results of the Bridge Weigh-in-Motion system.
Study Of Thermal-Magnetic Driving For Next-Generation Inkjet
Authors: Muraii Shinya , Han Hirofumi , Koshimoto Y. 
Published: November 2017

Abstract
In this paper, the authors proposed a novel type of inkjet where the ink is driving by maxwell stress employing the characteristic of thermalmagnetic. Different with the traditional inkjet technology like the piezo-vibration driving type or bubble driving type, in the proposed approach the moving elements or high temperature is absolutely unnecessary and having simple structure, so that high durability and reliability is promising with small size and strong pumping force. The working mechanism of the proposed method was explained and demonstrated by analysis and experiment.
Review Of Wet Gas Flow Measurement Using Venturi Tubes And Radio Active Materials
Authors: Seraj Hossein , Khaled Marzuki , Yusof Rubiyah , Rahmat Mohd Fuaad 
Published: November 2017

Abstract
This paper introduces the application of Venturi flow meter for wet gas flow measurement. Wet gas which is a gas containing small amount of liquid is mostly encountered in gas wells where the extracted gas has water and condensate inside. Venturi flow meters which originally were introduced for single phase flow measurement are adapted for wet gas measurement. In this paper, we elaborate using of Venturi meter as a device for measuring wet gas flow and explain versatile methods for correcting the reading of Venturi tube for wet gas application. Tracer injection method is introduced as a manual tool for measuring water and condensate flow rate in wet gas fluid. Also radioactive measuring method has been introduced as an automatic method for measuring the ratio between gas, water and condensate in wet gas fluid. Finally different aspects of using radioactive sources are elaborated.
Microcontroller based Power Efficient Signal Conditioning Unit for Detection of a Single Gas using MEMS based Sensor
Authors: Bhattacharyya P. , Verma D. , Banerjee D. 
Published: November 2017

Abstract
-A low power MEMS based sensor along with the embedded power efficient signal conditioning unit (Microcontroller based), which can be used with any suitable sensor-network to detect and quantify variations in a particular gas concentration, has been reported in this paper. The power consumption of the MEMS gas sensor is ~ 70mW to 100mW depending upon its operating temperature (150-250°C) and that of entire signal conditioning unit (consisting of low noise amplifier, switch, microcontroller and power management chip) is ~ 36mW in the ON state and only ~7.2μW in OFF state (sleep mode). The test gas in this particular case was methane for which sensor resistance varied from 100KΩ to 10KΩ. This hybrid sensor system is very much suitable for detecting a single gas with display of corresponding gas concentrations and subsequent alarming if the threshold limit is crossed.
Nanosensors Engineering: Ii. Superficial Functionalization Of Sno2 Nanowire For Sensing Performance Improvement
Authors: Dmitriev Serghei 
Published: November 2017

Abstract
Paper presents results of study aimed the tin dioxide nanowire gas sensing performance improvement via in situ functionalization with NiO. Developed nanostructures have demonstrated improved by order gas sensitivity toward H2 and CO and drastic increase of selectivity to H2 against CO. Obtained results are discussed from the point of view of NiO/Sno2 heterojunction formation and its influence on electrical transport through nanowire and nanowire interaction with target gases.
A Methodology for the Optimization Of Multi-program Shared Scratchpad Memory
Authors: Yang J. F. , Jiang H. , Hu W. 
Published: November 2017

Abstract
Processors used in wireless and ad hoc networks bring more strict requirements on performance and power consumption. The hardware and software need to coordinate more efficiently to meet such requirements. With the rapid development of semi-conductor technology, more memory can be integrated into the processor. ScratchPad Memory (SPM) is a kind of the on-chip memory, is a SRAM based memory with fast response, small on-chip area and low power consumption. It is still a big challenge on how to take advantages of SPM because SPM must be explicitly used by software to achieve high performance. This paper proposes a novel methodology to share SPM during multiprograms. The applications are analyzed and memory objects are generated. During the executions, multi-programs can share SPM through these memory objects. The experimental results show that our approach can reduce both the execution time and the energy consumption effectively.
Flexible Ph Sensor With Polyaniline Layer Based On Impedance Measurement
Authors: Chuang Cheng-Hsin , Wu Hsun-Pei , Chen Cheng-Ho , Wu Peng-Rong 
Published: November 2017

Abstract
A flexible sensor with conducting polyaniline layer for detecting pH value based on the impedance measurement is fabricated and demonstrated in this study. The pH sensor consists of an interdigital electrode array on a flexible printed circuit and a thin-film polyaniline as the sensing layer. As the conductivity of polyaniline depends on the redox state, the impedance change of the polyaniline after it has reacted with different pH value solutions works as the sensing mechanism. In order to obtain a reliable and stable impedance measurement result, a standard procedure for pH value detection is also developed. As the experimental results show, the impedance variation of the pH sensor is less than 1% in an ambient environment, and the measured impedance increases with pH values varying from 2 to 12. In addition, the impedance change between the unreacted sensor and the reacted sensor exhibit 3 orders of difference; thus, the resolution of the pH value detection is very high, making it possible to detect the impedance by means of a simple electronic device. Consequently, the low-cost, disposable, flexible IDT electrode sensor with a polyaniline layer effectively demonstrates the feasibility of pH value detection. Moreover, the sensor can be applied to other applications, such as gas detection, humidity and glucose, etc.
A Review of Artificial Fish Swarm Optimization Methods and Applications
Authors: Neshat Mehdi , Adeli Ali , Sepidnam Ghodrat , Sargolzaei Mehdi , Toosi Adel Najaran 
Published: November 2017

Abstract
The Swarm Intelligence is a new and modern method employed in optimization problems. The Swarm Intelligence method is based on the en masse movement of living animals like birds, fishes, ants and other social animals. Migration, seeking for food and fighting with enemies are social behaviors of animals. Optimization principle is seen in these animals. The Artificial Fish Swarm Optimization (AFSA) method is one of the Swarm Intelligence approaches that works based on the population and stochastic search. Fishes show very intelligently social behaviors. This algorithm is one of the best approaches of the Swarm Intelligence method with considerable advantages like high convergence speed, flexibility, error tolerance and high accuracy. this paper review the AFSA algorithm, its evolution stages from the start point up to now, improvements and applications in various fields like optimization, control, image processing, data mining, improving neural networks, networks, scheduling, and signal processing and so on. Also, various methods combining the AFSA with other optimization methods like PSO, Fuzzy Logic, Cellular Learning Automata or intelligent search methods like Tabu search, Simulated Annealing, Chaos Search and etc.
An Air Quality Monitoring System for Urban Areas Based on the Technology of Wireless Sensor Networks
Authors: Liu Jen-Hao , Chen Yu-Fan , Lin Tzu-Shiang , Chen Chia-Pang , Chen Po-Tang , Wen Tzai-Hung , Sun Chih-Hong , Juang Jehn-Yih , Jiang Joe-Air 
Published: November 2017

Abstract
Air pollution is one of environmental issues that cannot be ignored. The heavy transportation and urbanization result in the air pollutants concentrated in certain areas. Inhaling pollutants for a long time causes damages in human health. Traditional air quality monitoring methods, such as building air quality monitoring stations, are typically expensive. In addition, monitoring stations are generally less densely deployed and provide low resolution sensing data. This paper proposes an urban air quality monitoring system based on the technology of wireless sensor networks (WSNs). It also integrates with the global system for mobile communications (GSM). The system consists of sensor nodes, a gateway, and a control center managed by the LabVIEW program through which sensing data can be stored in a database. This system is deployed to the main roads in the Taipei city to monitor the carbon monoxide (CO) concentration caused by vehicle emissions. The experimental results show that the proposed system is suitable for micro-scale air quality monitoring in real-time through the WSN technology.
Development of Semi-Quantitative Analytical System for Metal Nanoparticle Ink Using Laser-Induced Breakdown Spectroscopy
Authors: Ikezawa S. , Wakamatsu M. , Ueda T. 
Published: November 2017

Abstract
This paper describes the semi-quantitative analysis of metal nanoparticle ink using laser-induced breakdown spectroscopy (LIBS). LIBS can be used to obtain information about the density and chemical composition of silver particles or copper particles, even ultrafine particles. Metal particles have been attracting much attention because of their increased use in new micro-nano technologies. In this work, LIBS was used as a fine metal particle measurement system for nanometallic materials used in printing. Good spectral peak resolutions were obtained when the Ag spectra were recorded at wavelengths of 328.068 nm and 338.289 nm and Cu spectra at 324.754 nm and 327.396 nm.
Spatial-temporal Collaborative Sequential Monte Carlo for Mobile Robot Localization in Distributed Intelligent Environments
Authors: Qian Kun , Ma Xudong , Dai Xian Zhong , Fang Fang 
Published: November 2017

Abstract
In this paper, a spatial-temporal collaborative sequential Monte Carlo architecture for mobile robot localization is designed to well suites intelligent environment for service robotic system. A proposed algorithm, namely Distributed Proportional Allocation-Augmented Particle Filter (DPA-APF), resolves the sensor collaboration problem by the processes of augmented sampling, inter-node resampling, inner-node resampling and particle exchange. These procedures exploit data parallelism and pipelining of resampling operations and improve the scalability of distributed particle filters (PFs). Moreover, modified visual and laser sensor perception models are also addressed to guarantee reliable and accurate robot localization in dynamic scenarios that robot coexists with people. The proposed method is applied to a home-care robotic intelligent room with distributed smart nodes, and the experimental results validate the effectiveness of the proposed method, which is hopeful to reduce the gap that exists between PF theory and their implementation using networked hardware.
Practical Sway Motion Control for Double Pendulum-Type Overhead Crane System
Authors: Zohari M. N. A. , Tumari M. Z. Mohd , Saealal M. S. , Ghazali K.H. , Ramli M.S. 
Published: November 2017

Abstract
The sway motion of crane can be successfully suppressed by properly shaping the reference command. Input shaping is a one type of feed-forward shaping method that is based on linear superposition. In this paper, we present the impact of double pendulum type overhead crane (DPTOC) system on the effectiveness of input shaping. An unshaped bang-bang input force is used to determine the characteristic parameters of the system for design and evaluation of the input shaping control techniques. The input shapers with the derivative effects are designed based on the properties of the system. The response DPTOC system to shaped input is experimentally verified in time and frequency domain. The performance of the input shaper is examined in terms of sway angle reduction and time response specification. Experimental results demonstrate the effectiveness of the proposed approach in reducing the sway motion of crane system.
The Dimensional Assessment of Personality Pathology – Short Form for Adolescents (DAPP-SF-A): normative data for Flemish adolescents aged 16 to 21 years
Authors: Raaijmakers Daphne , Polak Marike G. , Arends Lidia R. , van Eldik Willemijn M. , Prinzie Peter 
Published: November 2017

Abstract

Background
The Dimensional Assessment of Personality Pathology – Short Form for Adolescents (DAPP-SF-A) is an age-adapted version of the DAPP Basic Questionnaire (DAPP-BQ). The psychometric properties of this questionnaire were established by Tromp and Koot. However, norming data are currently available exclusively for Dutch adolescents.

Objective
The main aim of this study was to provide community-based norming data for the DAPP-SF-A in Flemish adolescents and separately for boys and girls. The second aim was to compare the Flemish norms with the Dutch norms.

Method
The sample consisted of 425 adolescents (52% girls), aged 16 to 21 years (mean, 18.6; SD, 1.16), from the general Flemish population. In 2012, all respondents completed the DAPP-SF-A and the Youth Self-Report as a part of the longitudinal Flemish Study on Parenting, Personality, and Development.

Results:
Internal consistency reliabilities of the lower-order dimensions were acceptable to good (a ranged from 0.71 to 0.87, median=0.85, mean item-rest correlations ranged from 0.44 to 0.67). The lower-order dimensions showed distinctive mean patterns for boys and girls, with higher scores for girls on Affective Instability and Insecure Attachment [effect sizes (d) were both −0.35] and higher scores for boys on all lower-order dimensions of Dissocial Behavior, Inhibitedness, and three lower-order dimensions of Emotional Dysregulation (d ranged from 0.21 to 0.79). The comparison of the Flemish scores with the Dutch scores showed substantial inter-cultural differences (d ranged from 0.13 to −1.78).

Conclusions
The DAPP-SF-A shows satisfactory reliability in a Flemish community-based sample of adolescents. Furthermore, given the differences between boys and girls, the use of gender-based norms seems appropriate. Finally, substantial differences with the Dutch general population norms warrant the use of separate norms in Flemish adolescents.
Computerised Recommendations on E-Transaction Finalisation by Means of Machine Learning
Authors: Budnikas Germanas 
Published: November 2017

Abstract
Nowadays a vast majority of businesses are supported or executed online. Website-to-user interaction is extremely important and user browsing activity on a website is becoming important to analyse. This paper is devoted to the research on user online behaviour and making computerised advices. Several problems and their solutions are discussed: to know user behaviour online pattern with respect to business objectives and estimate a possible highest impact on user online activity. The approach suggested in the paper uses the following techniques: Business Process Modelling for formalisation of user online activity; Google Analytics tracking code function for gathering statistical data about user online activities; Naïve Bayes classifier and a feedforward neural network for a classification of online patterns of user behaviour as well as for an estimation of a website component that has the highest impact on a fulfilment of business objective by a user and which will be advised to be looked at. The technique is illustrated by an example.
Application of the Random Forest model for chlorophyll-a forecasts in fresh and brackish water bodies in Japan, using multivariate long-term databases
Authors: Yajima Hiroshi , Derot Jonathan 
Published: November 2017

Abstract
There is a growing world need for predicting algal blooms in lakes and reservoirs to better manage water quality. We applied the random forest model with a sliding window strategy, which is one of the machine learning algorithms, to forecast chlorophyll-a concentrations in the fresh water of the Urayama Reservoir and the saline water of Lake Shinji. Both water bodies are situated in Japan and have historical water records containing more than ten years of data. The Random Forest (RF) model allowed us to forecast trends in time series of chlorophyll-a in these two water bodies. In the case of the reservoir, we used the data separately from two sampling stations. We found that the best model parameters for the number of min-leaf, and with/without pre-selection of predictors, varied at different stations in the same reservoir. We also found that the best performance of lead-time and accuracy of the prediction varied between the two stations. In the case of the lake, we found the best combination of a min-leaf and pre-selection of predictors was different from that of the reservoir case. Finally, the most influential parameters for the random forest model in the two water bodies were identified as biochemical oxygen demand (BOD), chemical oxygen demand (COD), pH, and total nitrogen/total phosphorus (TN/TP).
Hydrochemical characterization and evaluation of the impact of AMD processes on river basin areas in the Iberian Pyrite Belt
Authors: Grande J. A. , de la Torre M. L. , Santisteban M. , Fortes J. C. 
Published: November 2017

Abstract
The hydrographic network in the Iberian Pyrite Belt (IPB) (south-west Europe) is intensively affected by acid mine drainage (AMD) processes. This represents a unique worldwide scenario of extractive mining activity for more than 4,000 years. In order to be able to achieve possible restorations, it is necessary to reduce the scale of possible actions for future environmental improvements, at the river basin level. Therefore, the delineation of watersheds and subwatersheds in the IPB has been carried out, as well as the definition of the degree of impact by AMD processes in these basins in the dry season and in the rainy season. The results show that all basins are affected by AMD processes during the entire hydrological year, with pH values between 2 and 3, for most cases, and high concentrations of sulfates, metals and arsenic.