Search results

The purpose of this study is to investigate forecast models using data provided by the Texas Commission on Environmental Quality (TCEQ) to monitor and develop forecast models for air quality management.

The models used in this research are the LDF (Fisher Linear Discriminant Function), QDF (Quadratic Discriminant Function), REGF (Regression Function), BPNN (Backprop Neural Network), and the RBFN (Radial Basis Function Network). The data used for model evaluations span a 12‐year period from 1990 to 2002. A control chart of the data is also examined for possible shifts in the distribution of ozone present in the Houston atmosphere during this time period.

Results of this research reveal variables that are significantly related to the ozone problem in the Houston area.

Models developed in this paper may assist air quality managers in modeling and forecasting ozone formations using meteorological variables.

This is the first study that has extensively compared the efficiency of LDF, QDF, REGF, BPNN and RBFN forecast models used for tracking air quality. Prior studies have evaluated Neural Networks, ARIMA and regression models.

There has been a growing concern about air quality because in recent years, industrial and vehicle emissions have resulted in unsatisfactory human health conditions. There is an urgent need for the measurements and estimations of particulate pollutants levels, especially in urban areas. As a contribution to this issue, the purpose of this paper is to use data from measured concentrations of particulate matter and meteorological conditions for the predictions of PM₁₀.

The procedure included daily data collection of current PM₁₀ concentrations for the city of São Carlos-SP, Brazil. These data series enabled to use an estimator based on artificial neural networks. Data sets were collected using the high-volume sampler equipment (VFA-MP10) in the period ranging from 1997 to 2006 and from 2014 to 2015. The predictive models were created using statistics from meteorological data. The models were developed using two neural network architectures, namely, perceptron multilayer (MLP) and non-linear autoregressive exogenous (NARX) inputs network.

It was observed that, over time, there was a decrease in the PM₁₀ concentration rates. This is due to the implementation of more strict environmental laws and the development of less polluting technologies. The model NARX that used as input layer the climatic variables and the PM₁₀ of the previous day presented the highest average absolute error. However, the NARX model presented the fastest convergence compared with the MLP network.

The presentation of a given PM₁₀ concentration of the previous day improved the performance of the predictive models. This paper brings contributions with the NARX model applications.

The purpose of this paper is to examine the impact of green supply chain management (GSCM) on environmental performance (EP) and export performance in the context of a developing country, Jordan. In addition, the mediating effect of EP on the relationship between GSCM and export performance is investigated.

The study is based on survey data collected from 221 manufacturing companies in Jordan. The companies were selected from different industry types to ensure diversity. Validity and reliability analyses were performed using SPSS and Amos, and structural equation modeling was used to test the study hypotheses.

The results revealed that GSCM positively and significantly affects both EP and export performance. In addition, the results demonstrated that EP positively and significantly affects export performance. Further, it is also found that EP positively and significantly mediates the relationship between GSCM and export performance.

The current study is one of the first to investigate the impact of GSCM on export performance, especially in the context of a developing country. In addition, this study contributes to the existing literature by highlighting the mediating effect of EP on GSCM—export performance relationship. GSCM is an under-investigated area in Jordan. The results are expected to promote GSCM implementation among manufacturing companies in Jordan in order to achieve economic benefits by increasing their exports through improvements in EP.

The purpose of this paper is to examine the impact of lean management (LM) on operational performance (OP) in the context of health care in Jordanian private hospitals. LM is measured using four bundles: total quality management (TQM), human resource management (HRM), just-in-time system (JIT) and total productive maintenance (TPM). The study also investigates the effects of OP dimensions on hospitals’ business performance (BP).

The study is based on survey data collected from 260 respondents from 25 private hospitals in Jordan. Validity and reliability analyses were performed using SPSS and Amos, and the study hypotheses were tested using structural equation modeling.

The study found that the TQM bundle affects quality performance positively, but does not affect efficiency and accessibility performances, while the HRM bundle positively affects all OP dimensions. Furthermore, the JIT bundle positively contributes to both efficiency and accessibility performances, while the TPM bundle positively influences quality and accessibility performances. Moreover, the results have demonstrated that OP dimensions of quality and accessibility significantly and positively affect hospitals’ BP.

This study is one of the first to adapt the four lean bundles popularized in the manufacturing sector and apply them in a health-care context. It examines the effects of the four lean bundles on hospitals’ OP in terms of efficiency, quality and accessibility. In addition, the study demonstrates the role of OP dimensions in improving private hospitals’ BP.

The purpose of this paper is to examine the effect of agile manufacturing (AM) on business performance and operational performance (OP) dimensions in manufacturing companies in Jordan. It also explores the indirect effect of AM on business performance through OP dimensions of cost, quality, delivery and flexibility.

The study analyzes survey data collected from 282 manufacturing companies from different industries in Jordan. Validity and reliability analyses were performed using SPSS and Amos, and the research hypotheses were tested using structural equation modeling.

The results demonstrated that AM positively and directly affected business performance. It also positively affected OP dimensions of quality, delivery and flexibility. However, cost performance was not significantly affected by AM. In addition, quality performance and flexibility performance fully mediated the relationship between AM and business performance, whereas cost performance and delivery performance did not show mediating effects.

To the best of the knowledge, this is the first study that investigates the mediating effects of OP dimensions on the relationship between AM and business performance. In addition, a limited number of previous studies investigated the performance outcomes of AM. Furthermore, this area is under-investigated in the Middle East in general and in Jordan in particular.

The first approach mainly aims at measurement of SPM, SO2 and NO2 from different sources in the Gwalior region and the second and third approach aims at the quantification of water and noise quality of the city of Gwalior. The purpose of this paper is to discuss these approaches.

The water analysis was carried out by the standard methods of APHA, 2005 and the air and noise analysis were carried out by the standard procedures of CPCB, New Delhi and published work earlier respectively.

The water quality in the city was well within the standards, however, the noise and air quality in the city was above the standards set by CPCB, New Delhi.

This is the first approach in the city of Gwalior that related air pollution, water pollution and noise pollution to acute and chronic illnesses amongst all age groups. This will lead to the development of a sustainable city, while working to transform the city of Gwalior into a sustainable city.

The purpose of this paper is to analyse the operation of p-type side gate junctionless silicon transistor (SGJLT) in accumulation region through experimental measurements and 3-D TCAD simulation results. The variation of electric field components, carrier’s concentration and valence band edge energy towards the accumulation region is explored with the aim of finding the origin of SGJLT performance in the accumulation operational condition.

The device is fabricated by atomic force microscopy nanolithography on silicon-on-insulator wafer. The output and transfer characteristics of the device are obtained using 3-D Technology Computer Aided Design (TCAD) Sentaurus software and compared with experimental measurement results. The advantages of AFM nanolithography in contact mode and Silicon on Insulator (SOI) technology were implemented to fabricate a simple structure which exhibits the behaviour of field effect transistors. The device has 200-nm channel length, 100-nm gate gap and 4 μm for the distance between the source and drain contacts. The characteristics of the fabricated device were measured using an Agilent HP4156C semiconductor parameter analyzer (SPA). A 3-D TCAD Sentaurus tool is used as the simulation platform. The Boltzmann statistics is adopted because of the low doping concentration of the channel. Hydrodynamic model is taken to be as the main transport model for all simulations, and the quantum mechanical effects are ignored. A doping dependent Masetti mobility model was also included as well as an electric field dependent model with Shockley–Read–Hall (SRH) carrier recombination/generation.

We have obtained that the device is a normally on state device mainly because of the lack of work functional difference between the gate and the channel. Analysis of electric field components’ variation, carrier’s concentration and valence band edge energy reveals that increasing the negative gate voltage drives the device into accumulation region; however, it is unable to increase the drain current significantly. The positive slope of the hole quasi-Fermi level in the accumulation region presents mechanism of carriers’ movement from source to drain. The influence of electric field because of drain and gate voltage on charge distribution explains a low increasing of the drain current when the device operates in accumulation regime.

The proposed side gate junctionless transistors simplify the fabrication process, because of the lack of gate oxide and physical junctions, and implement the atomic force microscopy nanolithography for fabrication process. The optimized structure with lower gap between gate and channel and narrower channel would present the output characteristics near the ideal transistors for next generation of scaled-down devices in both accumulation and depletion region. The presented findings are verified through experimental measurements and simulation results.

The present study aims to examine the impact of relational communication, operationalized in terms of information sharing, quality and frequency of information, on buyer's trust and relationship satisfaction in a buyer–vendor relationship. The study also tests the mediating role of trust and the moderating role of relationship commitment in relational communication and satisfaction relationship.

The data for the study were collected through a questionnaire survey from 321 managers of the different firms who were directly or indirectly involved in making procurement or purchasing decision in the firm and were familiar with the firm's supplier relationships.

Relational communication was found to be positively related to relational satisfaction and trust partially mediated this relationship. Further, relationship commitment moderated relational communication-satisfaction relationship, such that the positive affect of relational communication on relational satisfaction was accentuated when buyer experienced higher relationship commitment towards the supplier.

Using single source, self-reported questionnaire data and cross-sectional research design are the limitations of this study. Studies in future should consider a dyadic perspective. The study outlines the need to explore investments and strategies in enhancing relational communication in buyer–vendor relationships.

Anchored in theoretical foundations of social exchange theory, the study integrates and tests behavioral aspects of buyer–vendor relationship. Testing an integrated model with direct and indirect effects of relational communication on relationship satisfaction in buyer–vendor is a significant contribution of the research. The study also contributes by examining relational exchanges in buyer-vendor relationships in India, an underrepresented context in buyer–supplier relationship (BSR) literature.

Supply chain efficiency can be enhanced by integrating the activities in supply chain through digitalization. Advancements in digital technologies has facilitated in designing robust and dynamic supply chain by bringing in efficiency, transparency and reduction in lead times. This research tries to identify and prioritize the customer requirements and design requirements for effective integration of supply chain through digitalization.

The key nine customer requirements and 16 design requirements applicable for an electronics company were shortlisted in consultation with the experts from the company and academia. An integrated analytic network process (ANP) and quality function deployment (QFD) methodology has been applied for prioritizing the customer and design requirements. The relative importance and interdependence of these requirements were identified and a House of Quality (HOQ) is constructed.

The HOQ constructed has prioritized and identified interrelationships among customer requirements and design requirements for effective supply chain digitalization. These findings could be effectively used by managers for planning the objectives on long-term, medium-term and short-term basis.

This study tries to bridge the gap of identifying and prioritizing the design and customer requirements for effective supply chain integration through digitalization. The results could aid practicing managers and academicians in decision-making on supply chain digitalization process.

The purpose of this paper is to search for toxic anticorrosive pigments’ substitute in protective coatings is one of the important tasks that the specialists in the field of steel corrosion face.

One of the ways to solve the problem of metal corrosion is to use complex oxides as pigments, which are characterized as low-toxic compounds and possess the ability to inhibit corrosion.

In the production of ferrites, it is possible to use production waste as raw material, and that makes it possible to reduce the price of the resulting product and solve environmental problems simultaneously.

Permanent growth of world production is accompanied by the increasing environment corrosiveness, associated with the intensification of air, water basin and soil pollution by industrial waste. This, as well as the continuously increasing operated metal stock, has recently made the tendency of metals’ total loss from corrosion steadily increasing. All of this points to the importance of studying corrosion processes and the systematic and effective fight against metal corrosion.