Application of Transform Fourier for Dynamic Control of Structures with Global Positioning System

Given the evolution of viaducts, structural health monitoring requires more complex techniques to define their state. two alternatives can be distinguished: experimental and operational modal analysis. Although accelerometers or Global Positioning System (GPS) have been applied for the monitoring of structures under exploitation, the dynamic monitoring during the stage of construction is not common. This research analyzes whether GPS data can be applied to certain dynamic geometric controls of evolving structures. The fundamentals of this work were applied to the New Bridge of Cádiz (Spain), a worldwide milestone in bridge building. GPS data were recorded with an interval of 1 second during the erection of segments and turned to the frequency domain with Fourier transform. The vibration period and amplitude were contrasted with those provided by the finite element model, with differences of less than 10%, which is admissible. This process provides a vibration record of the structure with GPS, avoiding specific equipment.

Assessment of Analytical Equations for the Derivation of Young’s Modulus of Bonded Rubber Materials

The prediction of the vibration response of rubber products by analytical or numerical method depends mainly on the predefined intrinsic material properties such as Young’s modulus, damping factor and Poisson’s ratio. Such intrinsic properties are determined experimentally by subjecting a bonded rubber sample to compression tests. The compression tests on such a sample yield an apparent Young’s modulus which is greater in magnitude than the intrinsic Young’s modulus of the rubber. As a result, many analytical equations have been developed to determine Young’s modulus from an apparent Young’s modulus of bonded rubber materials. In this work, the applicability of some of these analytical equations is assessed via experimental testing. The assessment is based on testing of vulcanized nitrile butadiene rubber (NBR70) samples using tensile test and compression test methods. The analytical equations are used to determine the intrinsic Young’s modulus from the apparent modulus that is derived from the compression test data of the bonded rubber samples. Then, these Young’s moduli are compared with the actual Young’s modulus that is derived from the tensile test data. The results show significant discrepancy between the Young’s modulus derived using the analytical equations and the actual Young’s modulus.

Pilot-Assisted Direct-Current Biased Optical Orthogonal Frequency Division Multiplexing Visible Light Communication System

Visible light communication (VLC) is a new approach of optical wireless communication proposed to support the congested radio frequency (RF) spectrum. VLC systems are combined with orthogonal frequency division multiplexing (OFDM) to achieve high rate transmission and high spectral efficiency. In this paper, we investigate the Pilot-Assisted Channel Estimation for DC biased Optical OFDM (PACE-DCO-OFDM) systems to reduce the effects of the distortion on the transmitted signal. Least-square (LS) and linear minimum mean-squared error (LMMSE) estimators are implemented in MATLAB/Simulink to enhance the bit-error-rate (BER) of PACE-DCO-OFDM. Results show that DCO-OFDM system based on PACE scheme has achieved better BER performance compared to conventional system without pilot assisted channel estimation. Simulation results show that the proposed PACE-DCO-OFDM based on LMMSE algorithm can more accurately estimate the channel and achieves better BER performance when compared to the LS based PACE-DCO-OFDM and the traditional system without PACE. For the same signal to noise ratio (SNR) of 25 dB, the achieved BER is about 5×10-4 for LMMSE-PACE and 4.2×10-3 with LS-PACE while it is about 2×10-1 for system without PACE scheme.

Corrosion Analysis and Interfacial Characterization of Al – Steel Metal Inert Gas Weld - Braze Dissimilar Joints by Micro Area X-Ray Diffraction Technique

Automotive light weighting is of major prominence in the current times due to its contribution in improved fuel economy and reduced environmental pollution. Various arc welding technologies are being employed in the production of automobile components with reduced weight. The present study is of practical importance since it involves preferential substitution of Zinc coated mild steel with a light weight alloy such as 6061 Aluminium by means of Gas Metal Arc Welding (GMAW) – Brazing technique at different processing parameters. However, the fabricated joints have shown the generation of Al – Fe layer at the interfacial regions which was confirmed by the Scanning Electron Microscope and Energy Dispersion Spectroscopy. These Al-Fe compounds not only affect the mechanical strength, but also predominantly deteriorate the corrosion resistance of the joints. Hence, it is essential to understand the phases formed in this layer and their crystal structure. Micro area X - ray diffraction technique has been exclusively used for this study. Moreover, the crevice corrosion analysis at the joint interfaces was done by exposing the joints to 5 wt.% FeCl3 solution at regular time intervals as per ASTM G 48-03. The joints have shown a decreased crevice corrosion resistance with increased heat intensity. Inner surfaces of welds have shown severe oxide cracking and a remarkable weight loss when exposed to concentrated FeCl3. The weight loss was enhanced with decreased filler wire feed rate and increased heat intensity. 

Effects of Humidity and Silica Sand Particles on Vibration Generation by Friction Materials of Automotive Brake System

This paper presents the experimental study of vibration generated by friction materials of an automotive disc brake system using brake test rig. Effects of silica sand particles which are available on the road surface as an environmental condition with a size varied from 150 μm to 600 μm are evaluated. Also, the vibration of the brake disc is examined against the friction material in humidity environment conditions under variable rotational speed. The experimental results showed that the silica sand particles have significant contribution on the value of vibration amplitude which enhances with increasing the size of silica sand particles at different speed conditions. Also, it is noticed that the friction material is sensitive to humidity and the vibration magnitude increases under wet testing conditions. Moreover, it can be reported that with increasing the applied pressure and rotational speed of the braking system, the vibration amplitudes decrease for all cases.

Developing a Web-Based Tender Evaluation System Based on Fuzzy Multi-Attributes Group Decision Making for Nigerian Public Sector Tendering

Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Effect of Architecture and Operating Conditions of Vehicle on Bulb Lifetime in Automotive

Automotive lighting is the leading function in the configuration of vehicle architecture. Especially headlights and taillights from external lighting functions are among the structures that determine the stylistic character of the vehicle. At the same time, the fact that lighting functions are related to many other functions brings along difficulties in design. Customers expect maximum quality from the vehicle. In these circumstances, it is necessary to make designs that aim to keep the performance of bulbs with limited working lives at the highest level. With this study, the factors that influence the working lives of filament lamps were examined and bulb explosions that can occur sooner than anticipated in the future were prevented while the vehicle was still in the design phase by determining the relations with electrical, dynamical and static variables. Especially the filaments of the bulbs used in the front lighting of the vehicle are deformed in a shorter time due to the high voltage requirement. In addition to this, rear lighting lamps vibrate as a result of the tailgate opening and closing and cause the filaments to be exposed to high stress. With this study, the findings that cause bulb explosions were evaluated. Among the most important findings: 1. The structure of the cables to the lighting functions of the vehicle and the effect of the voltage values are drawn; 2. The effect of the vibration to bulb throughout the life of the vehicle; 3 The effect of the loads carried to bulb while the vehicle doors are opened and closed. At the end of the study, the maximum performance was established in the bulb lifetimes with the optimum changes made in the vehicle architecture based on the findings obtained.

Weak Instability in Direct Integration Methods for Structural Dynamics

Three structure-dependent integration methods have been developed for solving equations of motion, which are second-order ordinary differential equations, for structural dynamics and earthquake engineering applications. Although they generally have the same numerical properties, such as explicit formulation, unconditional stability and second-order accuracy, a different performance is found in solving the free vibration response to either linear elastic or nonlinear systems with high frequency modes. The root cause of this different performance in the free vibration responses is analytically explored herein. As a result, it is verified that a weak instability is responsible for the different performance of the integration methods. In general, a weak instability will result in an inaccurate solution or even numerical instability in the free vibration responses of high frequency modes. As a result, a weak instability must be prohibited for time integration methods.

Discovering Semantic Links Between Synonyms, Hyponyms and Hypernyms

This proposal aims for semantic enrichment between glossaries using the Simple Knowledge Organization System (SKOS) vocabulary to discover synonyms, hyponyms and hyperonyms semiautomatically, in Brazilian Portuguese, generating new semantic relationships based on WordNet. To evaluate the quality of this proposed model, experiments were performed by the use of two sets containing new relations, being one generated automatically and the other manually mapped by the domain expert. The applied evaluation metrics were precision, recall, f-score, and confidence interval. The results obtained demonstrate that the applied method in the field of Oil Production and Extraction (E&P) is effective, which suggests that it can be used to improve the quality of terminological mappings. The procedure, although adding complexity in its elaboration, can be reproduced in others domains.

EEG-Based Screening Tool for School Student’s Brain Disorders Using Machine Learning Algorithms

Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Investigating the Pedestrian Willingness to Pay to Choose Appropriate Policies for Improving the Safety of Pedestrian Facilities

Road traffic accidents lead to a higher rate of death and injury, especially in vulnerable road users such as pedestrians. Improving the safety of facilities for pedestrians is a major concern for policymakers because of the high number of pedestrian fatalities and direct and indirect costs which are imposed to the society. This study focuses on the idea of determining the willingness to pay of pedestrians for increasing their safety while crossing the street. In this study, three different scenarios including crossing the street with zebra crossing facilities, crossing the street with zebra crossing facilities and installing a pedestrian traffic light and constructing a pedestrian bridge with escalator are presented. The research was conducted based on stated preferences method. The required data were collected from a questionnaire that consisted of three parts: pedestrian’s demographic characteristics, travel characteristics and scenarios. Four different payment amounts are presented for each scenario and a logit model has been built for each proposed payment. The results show that sex, age, education, average household income and individual salary have significant effect on choosing a scenario. Among the policies that have been mentioned through the questionnaire scenarios, the scenario of crossing the street with zebra crossing facilities and installing a traffic lights is the most frequent, with willingness to pay 10,000 Rials and the scenario of crossing the street with a zebra crossing with a willingness to pay 100,000 Rials having the least frequency. For all scenarios, as the payment is increasing, the willingness to pay decreases.

An Implementation of Fuzzy Logic Technique for Prediction of the Power Transformer Faults

Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.

The Tourist Satisfaction on Brand Identity Design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province

The aims of this research were twofold: 1) to brand identity design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province and 2) to study the level of tourist satisfaction towards brand identity design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province. tourist satisfaction was measured using six criteria: clear brand positioning, likeable brand personality, memorable logo, attractive color palette, professional typography and on-brand supporting graphics. The researcher utilized a probability sampling method via simple random sampling. The sample consisted of 30 tourists in the Creative Agriculture Community Enterprise. Statistics utilized for data analysis were percentage, mean, and standard deviation. The results suggest that tourist had high levels of satisfaction towards all six criteria of the brand identity design that was designed to target them. This study proposes that specifically brand identity designed of Creative Agriculture Community Enterprise could also be implemented with other real media already available on the market.

Achieving Environmentally Sustainable Supply Chain in Textile and Apparel Industries

Most of the manufacturing entities cause negative footprint to nature that demand due attention. Textile industries have one of the longest supply chains and bear the liability of significant environmental impact to our planet. Issues of environmental safety, scarcity of energy and resources, and demand for eco-friendly products have driven research to search for safe and suitable alternatives in apparel processing. Consumer awareness, increased pressure from fashion brands and actions from local legislative authorities have somewhat been able to improve the practices. Objective of this paper is to reveal the best selection of raw materials and methods of production, taking environmental sustainability into account. Methodology used in this study is exploratory in nature based on personal experience, field visits in the factories of Bangladesh and secondary sources. Findings are limited to exploring better alternatives to conventional operations of a Readymade Garment manufacturing, from fibre selection to final product delivery, therefore showing some ways of achieving greener environment in the supply chain of a clothing industry.

Conceptual Design of a Customer Friendly Variable Volume and Variable Spinning Speed Washing Machine

In this paper using smart materials we have proposed a specially manufactured variable volume spin tub for loading clothes for negating the vibration to a certain extent for getting better operating performance. Additionally, we have recommended a variable spinning speed rotor for handling varieties of garments for an efficient washing, aiming for increasing the life span of both the garments and the machine. As a part of the conflicting dynamic constraints and demands of the customer friendly design optimization of a lucrative and cosmetic washing machine we have proposed a drier and a desalination system capable to supply desirable heat and a pleasing fragrance to the garments. We thus concluded that while incorporating variable volume and variable spinning speed tub integrated with a drier and desalination system, the washing machine could meet the varieties of domestic requirements of the customers cost-effectively.

Negative RT-PCR in a Newborn Infected with Zika Virus: A Case Report

Congenital Zika Virus Syndrome is an entity composed by a variety of birth defects presented in newborns that have been exposed to the Zika Virus during pregnancy. The syndrome characteristic features are severe microcephaly, cerebral tissue abnormalities, ophthalmological abnormalities such as uveitis and chorioretinitis, arthrogryposis, clubfoot deformity and muscular tone abnormalities. The confirmatory test is the Reverse transcription polymerase chain reaction (RT-PCR) associated to the physical findings. Here we present the case of a newborn with microcephaly whose mother presented a confirmed Zika Virus infection during the third trimester of pregnancy, despite of the evident findings and the history of Zika infection the RT-PCR in amniotic and cerebrospinal fluid of the newborn was negative. RT-PCR has demonstrated a low sensibility in samples with low viral loads, reason why, we propose a clinical diagnosis in patients with clinical history of Zika Virus infection during pregnancy accompanied by evident clinical manifestations of the child.

Use of Hierarchical Temporal Memory Algorithm in Heart Attack Detection

In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.

Predictive Semi-Empirical NOx Model for Diesel Engine

Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O2 concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO2/NOx ratio etc.

Branding Good Corporate Governance: A Pathway to Strengthen Investors’ Perception and Brand Equity

Corporate governance has become a crucial issue in both the business and academic world as a result of world-wide financial scandals and lack of trust in corporate practices. There is no doubt that in order to thrive and attain growth in the market, a company must earn the trust of its stakeholders by consistently delivering on its commitments. Directors of the companies thus comprehend the importance of upfront communication with relevant stakeholders to increase their confidence. The authors of this article argue that practicing good corporate governance is not enough in this highly competitive market place; corporate leaders need to market their good corporate governance practices in order to make the company more attractive to investors. This article also contends that the strength of corporate governance relies wholly upon the extent to which it is communicated simply, effectively and unceasingly to its stakeholders. The main objective of this study, therefore, is to explore the importance of branding good corporate governance in order to increase corporate brand equity, attract investors, and capture market share. A structured questionnaire comprising three sections and a total of 34 questions was prepared and surveyed by the authors among respondents residing in Bangladesh and who also have an academic and corporate background, to investigate the potential impact of branding good corporate governance in the market place. High mean values for individual questions and overall section depict that communicating and branding good corporate governance to the stakeholders will not only boost the investors’ confidence but also increase the corporate brand equity, yielding both profitable and sustainable business environment.