Search results for: Advanced Monitoring

Authors: Deepak Goswami, Padma Lochan Hazarika, Kandarpa Kumar Sarma

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The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we formulate an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management.

Keywords: Industrial, Health, Classification, ANN, MLP, MSE.

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Authors: Saemee Jun, Dong-Hyeon Shin, Tae-Sang Ahn, Hyung-Joon Kim

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Building loss estimation methodologies which have been advanced considerably in recent decades are usually used to estimate socio and economic impacts resulting from seismic structural damage. In accordance with these methods, this paper presents the evaluation of an annual loss probability of a reinforced concrete moment resisting frame designed according to Korean Building Code. The annual loss probability is defined by (1) a fragility curve obtained from a capacity spectrum method which is similar to a method adopted from HAZUS, and (2) a seismic hazard curve derived from annual frequencies of exceedance per peak ground acceleration. Seismic fragilities are computed to calculate the annual loss probability of a certain structure using functions depending on structural capacity, seismic demand, structural response and the probability of exceeding damage state thresholds. This study carried out a nonlinear static analysis to obtain the capacity of a RC moment resisting frame selected as a prototype building. The analysis results show that the probability of being extensive structural damage in the prototype building is expected to 0.01% in a year.

Keywords: Expected annual loss, Loss estimation, RC structure, Fragility analysis.

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Authors: Sulaiman Al Amro

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There are currently considerable challenges concerning data security and privacy, particularly in relation to modern technologies. This includes the virtual world known as the Metaverse, which consists of a virtual space that integrates various technologies, and therefore susceptible to cyber threats such as malware, phishing, and identity theft. This has led recent studies to propose the development of Metaverse forensic frameworks and the integration of advanced technologies, including machine learning for intrusion detection and security. In this context, the application of first-order logic offers a formal and systematic approach to defining the conditions of cyberattacks, thereby contributing to the development of effective detection mechanisms. In addition, formalizing the rules and patterns of cyber threats has the potential to enhance the overall security posture of the Metaverse and thus the integrity and safety of this virtual environment. The current paper focuses on the primary actions employed by avatars for potential attacks, including Interval Temporal Logic (ITL) and behavior-based detection to detect an avatar’s abnormal activities within the Metaverse. The research established that the proposed framework attained an accuracy of 92.307%, resulting in the experimental results demonstrating the efficacy of ITL, including its superior performance in addressing the threats posed by avatars within the Metaverse domain.

Keywords: Cyberattacks, detection, first-order logic, Metaverse, privacy, security.

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Authors: Bashaiar Alsanaa

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Never has a revolution affected all aspects of humanity as the communication revolution during the past two decades. This revolution, with all its advances and utilities, swept the world thus becoming an integral part of our lives, hence giving way to emerging applications at the social, economic, political, and educational levels. More specifically, such applications have changed the delivery system through which learning is acquired by students. Interaction with educators, accessibility to content, and creative delivery options are but a few facets of the new learning experience now being offered through the use of technology in the educational field. With different success rates, third world countries have tried to pace themselves with use of educational technology in advanced parts of the world. One such country is the small rich-oil state of Kuwait which has tried to adopt the e-educational model, however, an evaluation of such trial is yet to be done. This study aimed to fill the void of research conducted around that topic. The study explored students' acceptance of incorporating communication technologies in higher education in Kuwait. Students' responses to survey questions presented an overview of the e-learning experience in this country, and drew a framework through which implications and suggestions for future research were discussed to better serve the advancement of e-education in developing countries.

Keywords: Communication technologies, E-learning, Kuwait, Social media

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Authors: Ming-Ta Yang, Jyh-Cherng Gu, Chun-Wei Huang, Jin-Lung Guan

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Time base maintenance (TBM) is conventionally applied by the power utilities to maintain circuit breakers (CBs), transformers, bus bars and cables, which may result in under maintenance or over maintenance. As information and communication technology (ICT) industry develops, the maintenance policies of many power utilities have gradually changed from TBM to condition base maintenance (CBM) to improve system operating efficiency, operation cost and power supply reliability. This paper discusses the feasibility of using intelligent electronic devices (IEDs) to construct a CB CBM management platform. CBs in power substations can be monitored using IEDs with additional logic configuration and wire connections. The CB monitoring data can be sent through intranet to a control center and be analyzed and integrated by the Elipse Power Studio software. Finally, a human-machine interface (HMI) of supervisory control and data acquisition (SCADA) system can be designed to construct a CBM management platform to provide maintenance decision information for the maintenance personnel, management personnel and CB manufacturers.

Keywords: Circuit breaker, Condition base maintenance, Intelligent electronic device, Time base maintenance, SCADA.

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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This paper aims to provide an interpretation of artificial neural networks (ANNs) and explore some of its implications. The interpretation views ANNs as a memory which encodes instances of experience. An experiment explores the behavior of encoding and retrieval of instances from memory. A localised representation ANN is created that allows control over encoding and retrieved memory sample size and is experimented with using the MNIST digits dataset. The relationship between input familiarity, conflict within retrieved samples, and error rates is described and demonstrated to be an effective driver for memory encoding. Results indicate that selective encoding and retrieval samples that allow detection of memory conflicts produce optimal performance, and that error rates are normally distributed with input familiarity and conflict. By using input familiarity and sample consistency to guide memory encoding, the number of encoding trials on the dataset were reduced to 18.33% of the training data while maintaining good recognition performance on the test data.

Keywords: Artificial Neural Networks, ANNs, representation, memory, conflict monitoring, confidence.

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Authors: Bayar Shahab

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The fast development of technology that has advanced neuroscience and human interaction with computers has enabled solutions to various problems and issues of this new era. The Brain-Computer Interface (BCI) has opened the door to several new research areas and have been able to provide solutions to critical and vital issues such as supporting a paralyzed patient to interact with the outside world, controlling a robot arm, playing games in VR with the brain, driving a wheelchair. This review presents the state-of-the-art methods and improvements of canonical correlation analyses (CCA), an SSVEP-based BCI method. These are the methods used to extract EEG signal features or, to be said differently, the features of interest that we are looking for in the EEG analyses. Each of the methods from oldest to newest has been discussed while comparing their advantages and disadvantages. This would create a great context and help researchers understand the most state-of-the-art methods available in this field, their pros and cons, and their mathematical representations and usage. This work makes a vital contribution to the existing field of study. It differs from other similar recently published works by providing the following: (1) stating most of the main methods used in this field in a hierarchical way, (2) explaining the pros and cons of each method and their performance, (3) presenting the gaps that exist at the end of each method that can improve the understanding and open doors to new researches or improvements. 

Keywords: BCI, CCA, SSVEP, EEG

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Authors: Jedol Dayou, Jackson Hian Wui Chang, Rubena Yusoff, Ag. Sufiyan Abd. Hamid, Fauziah Sulaiman, Justin Sentian

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Aerosols are small particles suspended in air that have wide varying spatial and temporal distributions. The concentration of aerosol in total columnar atmosphere is normally measured using aerosol optical depth (AOD). In long-term monitoring stations, accurate AOD retrieval is often difficult due to the lack of frequent calibration. To overcome this problem, a near-sea-level Langley calibration algorithm is developed using the combination of clear-sky detection model and statistical filter. It attempts to produce a dataset that consists of only homogenous and stable atmospheric condition for the Langley calibration purposes. In this paper, a radiance-based validation method is performed to further investigate the feasibility and consistency of the proposed algorithm at different location, day, and time. The algorithm is validated using SMARTS model based n DNI value. The overall results confirmed that the proposed calibration algorithm feasible and consistent for measurements taken at different sites and weather conditions.

Keywords: Aerosol optical depth, direct normal irradiance, Langley calibration, radiance-based validation, SMARTS.

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Authors: C. Iraklis, G. Evmiridis, A. Iraklis

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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: Congestion, distribution networks, loss reduction, particle swarm optimization, smart grid.

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Authors: Nhon Do, Thuong Huynh, An Pham

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Nowadays, organizing a repository of documents and resources for learning on a special field as Information Technology (IT), together with search techniques based on domain knowledge or document-s content is an urgent need in practice of teaching, learning and researching. There have been several works related to methods of organization and search by content. However, the results are still limited and insufficient to meet user-s demand for semantic document retrieval. This paper presents a solution for the organization of a repository that supports semantic representation and processing in search. The proposed solution is a model which integrates components such as an ontology describing domain knowledge, a database of document repository, semantic representation for documents and a file system; with problems, semantic processing techniques and advanced search techniques based on measuring semantic similarity. The solution is applied to build a IT learning materials management system of a university with semantic search function serving students, teachers, and manager as well. The application has been implemented, tested at the University of Information Technology, Ho Chi Minh City, Vietnam and has achieved good results.

Keywords: document retrieval system, knowledgerepresentation, document representation, semantic search, ontology.

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Authors: Chiung-Ju Huang, Yuan-Hong Ho

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This study utilizes the International Monetary Fund (IMF) Fiscal Rules Dataset focusing on four specific fiscal rules such as expenditure rule, revenue rule, budget balance rule, and debt rule and five main characteristics of each fiscal rule those are monitoring, enforcement, coverage, legal basis, and escape clause to construct the Fiscal Rule Index for nine countries in the Asia-Pacific region from 1996 to 2015. After constructing the fiscal rule index for each country, we utilize the Panel Generalized Method of Moments (Panel GMM) by using the constructed fiscal rule index to examine the effectiveness of fiscal rules in reducing procyclicality. Empirical results show that national fiscal rules have a significantly negative impact on procyclicality of government expenditure. Additionally, stricter fiscal rules combined with high government effectiveness are effective in reducing procyclicality of government expenditure. Results of this study indicate that for nine Asia-Pacific countries, policymakers’ use of fiscal rules and government effectiveness to reducing procyclicality of fiscal policy are effective.

Keywords: Counter-cyclical policy, fiscal rules, government effectiveness, procyclical policy.

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Authors: Razieh Arian, Hadi Adibi-Asl

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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine.

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Authors: Miroslava Šidlovská, Ida Petrovičová, Tomáš Pilka, Branislav Kolena

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Phthalates are ubiquitous environmental pollutants well known because of their endocrine disrupting activity in human organism. The aim of our study was, by biological monitoring, investigate exposure to phthalates of Roma ethnicity group i.e. children and adults from 5 families (n=29, average age 11.8 ± 7.6 years) living in western Slovakia. Additionally, we analysed some associations between anthropometric measures, questionnaire data i.e. socio-economic status, eating and drinking habits, practise of personal care products and household conditions in comparison with concentrations of phthalate metabolites. We used for analysis of urine samples high performance liquid chromatography and tandem mass spectrometry (HPLC-MS/MS) to determine concentrations of phthalate metabolites monoethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-iso-butyl phthalate (MiBP), mono(2-ethyl- 5-hydroxyhexyl) phthalate (5OH-MEHP), mono(2-ethyl-5-oxohexyl) phthalate (5oxo-MEHP) and mono(2-etylhexyl) phthalate (MEHP). Our results indicate that ethnicity, lower socioeconomic status and different housing conditions in Roma population can affect urinary concentration of phthalate metabolites.

Keywords: Biomonitoring, ethnicity, human exposure, phthalate metabolites.

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Authors: Shane D. Inder, Mehrdad Khamooshi

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Efficient energy storage is a crucial factor in facilitating the uptake of renewable energy resources. Among the many options available for energy storage systems required to balance imbalanced supply and demand cycles, compressed air energy storage (CAES) is a proven technology in grid-scale applications. This paper reviews the current state of micro scale CAES technology and describes a micro-scale advanced adiabatic CAES (A-CAES) system, where heat generated during compression is stored for use in the discharge phase. It will also describe a thermodynamic model, developed in EES (Engineering Equation Solver) to evaluate the performance and critical parameters of the discharge phase of the proposed system. Three configurations are explained including: single turbine without preheater, two turbines with preheaters, and three turbines with preheaters. It is shown that the micro-scale A-CAES is highly dependent upon key parameters including; regulator pressure, air pressure and volume, thermal energy storage temperature and flow rate and the number of turbines. It was found that a micro-scale AA-CAES, when optimized with an appropriate configuration, could deliver energy input to output efficiency of up to 70%.

Keywords: CAES, adiabatic compressed air energy storage, expansion phase, micro generation, thermodynamic.

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Authors: Abimbola O. Aniki, Esther T. Akinlabi

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This paper proposes an effective maintenance method by considering the implementation of the Computerized Maintenance Management System (CMMS) software to plan a maintenance activity in a manufacturing industry. Globally, maintenance is a very important activity in the manufacturing sector to prolong the life span of equipment and machinery; it is also applicable to all household items. It is obvious and well known that apart from giving long life to equipment, it reduces the substantial financial losses for repairs and save the production downtime. In some cases, appropriate maintenance of plant equipment and machinery reduces the tendencies of injuries to personnel in the job floor. But before the maintenance process can be carried out, proper and effective work order planning and scheduling must be in place in other to achieve the set goals and objectives of a maintenance shop. Brief reviews of common planning tools which include the Computerized Maintenance Management System (CMMS) are presented. An interesting outline of analyses on planning and scheduling for effective job planning in a typical manufacturing industry using the CMMS is also presented and discussed. Finally, the steps to adhere to in making job planning effective in a manufacturing industry are also highlighted.

Keywords: Advanced Downtime Analysis Programme (ADAP), Computerized Maintenance Management System (CMMS), Corrective Maintenance (CM), Executing Department (ED), Maintenance Department (MD), Preventive Maintenance (PM).

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Authors: Sidhartha Panda, Narayana Prasad Padhy

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This paper presents a systematic procedure for modelling and simulation of a power system installed with a power system stabilizer (PSS) and a flexible ac transmission system (FACTS)-based controller. For the design purpose, the model of example power system which is a single-machine infinite-bus power system installed with the proposed controllers is developed in MATLAB/SIMULINK. In the developed model synchronous generator is represented by model 1.1. which includes both the generator main field winding and the damper winding in q-axis so as to evaluate the impact of PSS and FACTS-based controller on power system stability. The model can be can be used for teaching the power system stability phenomena, and also for research works especially to develop generator controllers using advanced technologies. Further, to avoid adverse interactions, PSS and FACTS-based controller are simultaneously designed employing genetic algorithm (GA). The non-linear simulation results are presented for the example power system under various disturbance conditions to validate the effectiveness of the proposed modelling and simultaneous design approach.

Keywords: Genetic algorithm, modelling and simulation, MATLAB/SIMULINK, power system stabilizer, thyristor controlledseries compensator, simultaneous design, power system stability.

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Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

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The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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Authors: Reem I. Altamimi, Geoff D. Skinner

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Extended periods engaged in sedentary behavior increases the risk of becoming overweight and/or obese which is linked to other health problems. Adding technology to the term ‘active living’ permits its inclusion in promoting and facilitating habitual physical activity. Technology can either act as a barrier to, or facilitate this lifestyle, depending on the chosen technology. Physical Activity Monitoring Technologies (PAMTs) are a popular example of such technologies. Different contemporary PAMTs have been evaluated based on customer reviews; however, there is a lack of published experimental research into the efficacy of PAMTs. This research aims to investigate the reliability of four PAMTs: two wristbands (Fitbit Flex and Jawbone UP), a waist-clip (Fitbit One), and a mobile application (iPhone Health Application) for recording a specific distance walked on a treadmill (1.5km) at constant speed. Physical activity tracking technologies are varied in their recordings, even while performing the same activity. This research demonstrates that Jawbone UP band recorded the most accurate distance compared to Fitbit One, Fitbit Flex, and iPhone Health Application.

Keywords: Fitbit, Jawbone UP, mobile tracking applications, physical activity tracking technologies.

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Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

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A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: Bistatic radar cross section, passive radar, propagation losses, radar coverage.

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Authors: Mauro Giacomini, Stefania Bertone, Federico Caneva Soumetz, Carmelina Ruggiero

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Environmental micro-organisms include a large number of taxa and some species that are generally considered nonpathogenic, but can represent a risk in certain conditions, especially for elderly people and immunocompromised individuals. Chemotaxonomic identification techniques are powerful tools for environmental micro-organisms, and cellular fatty acid methyl esters (FAME) content is a powerful fingerprinting identification technique. A system based on an unsupervised artificial neural network (ANN) was set up using the fatty acid profiles of standard bacterial strains, obtained by gas-chromatography, used as learning data. We analysed 45 certified strains belonging to Acinetobacter, Aeromonas, Alcaligenes, Aquaspirillum, Arthrobacter, Bacillus, Brevundimonas, Enterobacter, Flavobacterium, Micrococcus, Pseudomonas, Serratia, Shewanella and Vibrio genera. A set of 79 bacteria isolated from a drinking water line (AMGA, the major water supply system in Genoa) were used as an example for identification compared to standard MIDI method. The resulting ANN output map was found to be a very powerful tool to identify these fresh isolates.

Keywords: Cellular fatty acid methyl esters, environmental bacteria, gas-chromatography, unsupervised ANN.

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Authors: Amira Shakila Razali, Faridah Lisa Supian, Muhammad Mat Salleh, Suraini Abu Bakar

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Water contamination by toxic compound is one of the serious environmental problems today. These toxic compounds mostly originated from industrial effluents, agriculture, natural sources and human waste. These studies focus on modification of multiwalled carbon nanotube (MWCNTs) with nanoparticle of calixarene and explore the possibility of using this modification for the remediation of cadmium in water. The nanocomposites were prepared by dissolving calixarene in chloroform solution as solvent, followed by additional multiwalled carbon nanotube (MWCNTs) then sonication process for 3 hour and fabricated the nanocomposites on substrate by spin coating method. Finally, the nanocomposites were tested on cadmium ion (10 mg/ml). The morphology of nanocomposites was investigated by FESEM showing the formation of calixarene on the outer walls of carbon nanotube and cadmium ion also clearly seen from the micrograph. This formation was supported by using energy dispersive x-ray (EDX). The presence of cadmium ions in the films, leads to some changes in the surface potential and Fourier Transform Infrared spectroscopy (FTIR).The nanocomposites MWCNTs-calixarene have potential for development of sensor for pollutant monitoring and nanoelectronics devices applications.

Keywords: Calixarene, Multiwalled Carbon Nanotubes, Cadmium, Surface Potential.

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Authors: Kaumil B. Shah, Hina Chandwani

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The modular multilevel converter (MMC) is one of the advanced topologies for medium and high-voltage applications. In high-power, high-voltage MMC, a large number of switching power devices are required. These switching power devices (IGBT) considerable switching losses. This paper analyzes the performance of different discontinuous pulse width modulation (DPWM) techniques and compares the results against a conventional carrier based pulse width modulation method, in order to reduce the switching losses of an MMC. The DPWM reference wave can be generated by adding the zero-sequence component to the original (sine) reference modulation signal. The result of the addition gives the reference signal of DPWM techniques. To minimize the switching losses of the MMC, the clamping period is controlled according to the absolute value of the output load current. No switching is generated in the clamping period so overall switching of the power device is reduced. The simulation result of the different DPWM techniques is compared with conventional carrier-based pulse-width modulation technique.

Keywords: Modular multilevel converter, discontinuous pulse width modulation, switching losses, zero-sequence voltage.

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Authors: S. Bennoud, S. Hocine, H. Slme

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Developments in turbine cooling technology play an important role in increasing the thermal efficiency and the power output of recent gas turbines, in particular the turbojets.

Advanced turbojets operate at high temperatures to improve thermal efficiency and power output. These temperatures are far above the permissible metal temperatures. Therefore, there is a critical need to cool the blades in order to give theirs a maximum life period for safe operation.

The focused objective of this work is to calculate the turbojet performances, as well as the calculation of turbine blades cooling.

The developed application able the calculation of turbojet performances to different altitudes in order to find a point of optimal use making possible to maintain the turbine blades at an acceptable maximum temperature and to limit the local variations in temperatures in order to guarantee their integrity during all the lifespan of the engine.

Keywords: Brayton cycle, Turbine Blades Cooling, Turbojet Cycle, turbojet performances.

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Authors: E. Izsó, M. Bartalné-Berceli, Sz. Gergely, A. Salgó

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The aim of this investigation is to elaborate nearinfrared methods for testing and recognition of chemical components and quality in “Pannon wheat” allied (i.e. true to variety or variety identified) milling fractions as well as to develop spectroscopic methods following the milling processes and evaluate the stability of the milling technology by different types of milling products and according to sampling times, respectively. These wheat categories produced under industrial conditions where samples were collected versus sampling time and maximum or minimum yields. The changes of the main chemical components (such as starch, protein, lipid) and physical properties of fractions (particle size) were analysed by dispersive spectrophotometers using visible (VIS) and near-infrared (NIR) regions of the electromagnetic radiation. Close correlation were obtained between the data of spectroscopic measurement techniques processed by various chemometric methods (e.g. principal component analysis [PCA], cluster analysis [CA]) and operation condition of milling technology. It is obvious that NIR methods are able to detect the deviation of the yield parameters and differences of the sampling times by a wide variety of fractions, respectively. NIR technology can be used in the sensitive monitoring of milling technology.

Keywords: Allied wheat fractions, CA, milling process, nearinfrared spectroscopy, PCA.

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Authors: Caje F. Pinto, Jivan S. Parab, Gourish M. Naik

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This paper is about the development of non-invasive heart rate and oxygen saturation in human blood using Altera NIOS II soft-core processor system. In today's world, monitoring oxygen saturation and heart rate is very important in hospitals to keep track of low oxygen levels in blood. We have designed an Embedded System On Peripheral Chip (SOPC) reconfigurable system by interfacing two LED’s of different wavelengths (660 nm/940 nm) with a single photo-detector to measure the absorptions of hemoglobin species at different wavelengths. The implementation of the interface with Finger Probe and Liquid Crystal Display (LCD) was carried out using NIOS II soft-core system running on Altera NANO DE0 board having target as Cyclone IVE. This designed system is used to monitor oxygen saturation in blood and heart rate for different test subjects. The designed NIOS II processor based non-invasive heart rate and oxygen saturation was verified with another Operon Pulse oximeter for 50 measurements on 10 different subjects. It was found that the readings taken were very close to the Operon Pulse oximeter.

Keywords: Heart rate, NIOS II, Oxygen Saturation, photoplethysmography, soft-core, SOPC.

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Authors: Maryam Alimardani, Kazuo Hiraki

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This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.

Keywords: Hypnosis, EEG, robotherapy, brain-computer interface.

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Authors: Mohammed Kamil, M. M. Rahman, Rosli A. Bakar

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Modeling of hydrogen fueled engine (H₂ICE) injection system is a very important tool that can be used for explaining or predicting the effect of advanced injection strategies on combustion and emissions. In this paper, a common rail injection system (CRIS) is proposed for 4-strokes 4-cylinders hydrogen fueled engine with port injection feeding system (PIH₂ICE). For this system, a numerical one-dimensional gas dynamic model is developed considering single injection event for each injector per a cycle. One-dimensional flow equations in conservation form are used to simulate wave propagation phenomenon throughout the CR (accumulator). Using this model, the effect of common rail on the injection system characteristics is clarified. These characteristics include: rail pressure, sound velocity, rail mass flow rate, injected mass flow rate and pressure drop across injectors. The interaction effects of operational conditions (engine speed and rail pressure) and geometrical features (injector hole diameter) are illustrated; and the required compromised solutions are highlighted. The CRIS is shown to be a promising enhancement for PIH₂ICE.

Keywords: Common rail, hydrogen engine, port injection, wave propagation.

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Authors: Mohammad Iman Mokhlespour Esfahani, Masoud Mosayebi, Mohammad Pourshams, Ahmad Keshavarzi

Abstract:

Simulation accuracy by recent dynamic vehicle simulation multidimensional expression significantly has progressed and acceptable results not only for passive vehicles but also for active vehicles normally equipped with advanced electronic components is also provided. Recently, one of the subjects that has it been considered, is increasing the safety car in design. Therefore, many efforts have been done to increase vehicle stability especially in the turn. One of the most important efforts is adjusting the camber angle in the car suspension system. Optimum control camber angle in addition to the vehicle stability is effective in the wheel adhesion on road, reducing rubber abrasion and acceleration and braking. Since the increase or decrease in the camber angle impacts on the stability of vehicles, in this paper, a car suspension system mechanism is introduced that could be adjust camber angle and the mechanism is application and also inexpensive. In order to reach this purpose, in this paper, a passive double wishbone suspension system with variable camber angle is introduced and then variable camber mechanism designed and analyzed for study the designed system performance, this mechanism is modeled in Visual Nastran software and kinematic analysis is revealed.

Keywords: Suspension molding, double wishbone, variablecamber, hydraulic mechanism

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Authors: K. Shiba, T. Kaburagi, Y. Kurihara

Abstract:

With global aging, people who require care, such as people with dementia (PwD), are increasing within many developed countries. And PwDs may wander and unconsciously set foot outdoors, it may lead serious accidents, such as, traffic accidents. Here, round-the-clock monitoring by caregivers is necessary, which can be a burden for the caregivers. Therefore, an automatic wandering detection system is required when an elderly person wanders outdoors, in which case the detection system transmits a ‘moving’ followed by an ‘absence’ state. In this paper, we focus on the transition from the ‘resting’ to the ‘absence’ state, via the ‘moving’ state as one of the wandering transitions. To capture the transition of the three states, our method based on the hidden Markov model (HMM) is built. Using our method, the restraint where the ‘resting’ state and ‘absence’ state cannot be transmitted to each other is applied. To validate our method, we conducted the experiment with 10 subjects. Our results show that the method can classify three states with 0.92 accuracy.

Keywords: Wander, microwave Doppler sensor, respiratory frequency band, the state transition, hidden Markov model.

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Authors: Mohd Iskandar Illyas Tan, Raziah Noor Razali, Zuhra Junaida Husny

Abstract:

The purpose of this study is i) to investigate the driving factors and barriers of the adoption of Information and Communication Technology (ICT) in Halal logistic and ii) to develop an ICT adoption framework for Halal logistic service provider. The Halal LSPs selected for the study currently used ICT service platforms, such as accounting and management system for Halal logistic business. The study categorizes the factors influencing the adoption decision and process by LSPs into four groups: technology related factors, organizational and environmental factors, Halal assurance related factors, and government related factors. The major contribution in this study is the discovery that technology related factors (ICT compatibility with Halal requirement) and Halal assurance related factors are the most crucial factors among the Halal LSPs applying ICT for Halal control in transportation-s operation. Among the government related factors, ICT requirement for monitoring Halal included in Halal Logistic Standard on Transportation (MS2400:2010) are the most influencing factors in the adoption of ICT with the support of the government. In addition, the government related factors are very important in the reducing the main barriers and the creation of the atmosphere of ICT adoption in Halal LSP sector.

Keywords: Information and communication technology (ICT), Halal logistic, Halal transportation, Technology adoption

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