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Owing to the high cost of data acquisition (DAQ) card in the market, the purpose of this paper is to develop a high speed, low‐cost microprocessor and ethernet controller‐based DAQ in optical tomography system.

Microprocessor is the main core to control the sensor circuitry while ethernet controller has the responsibility of transmitting data to PC and thus insuring the reliability of data.

The data transfer rate will be up to megabytes per seconds. In this optical tomography system, projection geometry combining two orthogonal and two rectilinear in one layer is modeled.

This paper presents a new application in optical tomography.

The purpose of this paper is to present an implementation of ultrasonic tomography simulation to investigate the laminar flow of stratified liquid between water and oil.

The velocity of ultrasonic waves varies in water, oil, and different composition of water and oil. The composition of water and oil can be determined from the measurement of this propagation time. Sixteen pairs of ultrasonic sensors are mounted non‐invasively around the periphery of an acrylic pipe. The grease is used as the coupling material to mount these ultrasonic sensors. Different compositions of water and oil are used and the propagation times of the ultrasonic waves through the medium are measured. The composition of the water and oil of the flow is determined from the reconstructed images.

The paper finds that information about the distribution of the components within the sensing zone is obtained from the sensors' measurements. These measurements are then used to reconstruct the cross‐sectional image which can be analyzed to provide information, such as concentration of the flow components, the flow condition, velocity, mass flow rate, and identification of the distribution of mixing zones in stirred reactors and interface measurement in complex separation processes. The image can also be analyzed quantitatively for subsequent use to improve process control or develop models to describe individual process.

The paper shows that industries which may benefit from this technique could be the raw material processing industry, large‐scale and intermediate chemical production, and food biotechnology.

Takes a strategic journey into the future of the airline industry and air travel. The strategic trends and profound changes that are sweeping through the world airline industry and air travel currently, as well as into the next millennium, are analysed. So too are the responses of the lead airlines that are leading the charge in shaping as well as responding to these changes, which will present new opportunities, threats and challenges to airlines with global aspirations operating on the world stage. Singapore Airlines was analysed with British Airways and United Airlines as the leading European and US comparison airlines, respectively, for comparative and benchmarking purposes.

With the growth of social media and online communications, consumers are becoming more informed about hotels' services than ever before. They are writing online review to share their experiences, as well as reading online review before making a hotel reservation. Hotel customers considered it as reliable source and it influences customers' hotel selection. Most of these reviews reside in unstructured format, scattered across in the Internet and inherently unorganized. The purpose of this study was to use predictive text analytics to identify sentiment drivers from unstructured online reviews.

The research used sentiment classifications to analyze customers' reviews on hotels from TripAdvisor. In total, 9,286 written reviews by hotel customers were scrapped from 442 hotels in Malaysia. A detailed text analytic was conducted and was followed by a development of a theoretical framework based on the hybrid approach. AMOS was used to analyze the relationship between customer sentiments and overall review rating.

With the use of Structural Equation Modeling (SEM) and clustering technique, a list of sentiment drivers was detected, i.e. location, room, service, sleep, value for money and cleanliness. Among these variables, service quality and room facilities emerged as the most influential factors. Sentiment drivers obtained in this study provided the insights to hotel operators to improve the hotel conditions.

Although this study extended the existing literature on sentiment analysis by providing valuable insights to hoteliers, it is not without its limitations. For instance, online hotel reviews collected for this study were limited to one specific online review platform. Despite the large sample size to support and justify the findings, the generalizability power was restricted. Thus, future research should also consider and expand to other type of online review channels. Therefore, a need to examine these data reside various social media applications, i.e. Facebook, Instagram and YouTube.

This study highlights the significance of hybrid predictive model in analyzing the unstructured hotel reviews. Based on the hybrid predictive model we developed, six sentiment drivers emerged from the data analysis, i.e. location, service quality, value for money, sleep quality, room design and cleanliness. This consideration is critical due to the ever-increasing unstructured data resides in the online space. This explores the possibility of applying data analytic technique in a more efficient manner to obtain customer insights for hotel managerial consideration.

This study analyzed customer sentiments toward the hotel in Malaysia with the use of predictive text analytics technique. The main contribution was the list of sentiment drivers and the insights needed to improve the hotel conditions in Malaysia. In addition, the findings demonstrated motivating findings from different methodological perspective and provided hoteliers with the recommendation for improved review ratings.

Worldwide efforts to transform the public sector under the theme of “New Public Management” have been concerned with the issues of organizational change management. The change in the Accounting sector is one of the pillars of such efforts. This paper promotes the importance of leadership roles within the accounting change process by studying them within the context of a corporatized public sector entity. It offers a longitudinal analysis (1998‐2005) through the framework of “levers of control”. Leadership roles within the accounting scenario are compared with leadership roles within the engineering scenario to demonstrate the importance of accounting in mediating leadership roles, and in the end, promote the organization’s operational and financial performance. Through the framework of levers of control, this paper examines the different approaches and styles of an organizational leader in aligning beliefs systems among the workers, and creating management control systems through the mobilization of accounting calculative and constitutive power. This paper argues the importance of studying the characteristics of good leadership with in the organizational transformation process, particularly within the change management accounting practice that could lead to better organizational performance of the organization.

Presents over sixty abstracts summarising the 1999 Employment Research Unit annual conference held at the University of Cardiff. Explores the multiple impacts of globalization on work and employment in contemporary organizations. Covers the human resource management implications of organizational responses to globalization. Examines the theoretical, methodological, empirical and comparative issues pertaining to competitiveness and the management of human resources, the impact of organisational strategies and international production on the workplace, the organization of labour markets, human resource development, cultural change in organisations, trade union responses, and trans‐national corporations. Cites many case studies showing how globalization has brought a lot of opportunities together with much change both to the employee and the employer. Considers the threats to existing cultures, structures and systems.

It has been forecast that before the turn of the millennium air travel in Asia will account for 40 percent of global travel rising to 50 percent by 2010. The International Air Transport Association also forecast world international scheduled passenger numbers to grow by an average of 7.1 percent annually to 2000, to reach 522 million. Air wars over Asia are hotting up, with some of the world’s biggest airlines engaged in intense competition over Asian skies – potentially the richest and most lucrative air travel market on Planet Earth, notwithstanding the 1997 currency turmoil. This article looks at how competition in the Asia Pacific air travel industry was played out in the 1990s. A glimpse of what is to come can be drawn from the several tough skirmishes seen thus far in the 1990s.

Automated valuation models (AVMs) are statistical asset pricing models omnipresent in residential real estate markets, where they inform property tax assessment, mortgage underwriting and marketing. Use of these asset pricing models outside of residential real estate is rare. The purpose of the paper is to explore key characteristics of commercial office lease contracts and test an application in estimating office market rental prices using an AVM.

The authors apply a semi-log ordinary least squares hedonic regression approach to estimate either contract rent or the total costs of occupancy (TOC) (“grossed up” rent). Furthermore, the authors adopt a training/test split in the observed leasing data to evaluate the accuracy of using these pricing models for prediction. In the study, 80% of the samples are randomly selected to train the AVM and 20% was held back to test accuracy out of sample. A naive prediction model is used to establish accuracy prediction benchmarks for the AVM using the out-of-sample test data. To evaluate the performance of the AVM, the authors use a Monte Carlo simulation to run the selection process 100 times and calculate the test dataset's mean error (ME), mean absolute error (MAE), mean absolute percentage error (MAPE), median absolute percentage error (MdAPE), coefficient of dispersion (COD) and the training model's r-squared statistic (R²) for each run.

Using a sample of office lease transactions in Sydney CBD (Central Business District), Australia, the authors demonstrate accuracy statistics that are comparable to those used in residential valuation and outperform a naive model.

AVMs in an office leasing context have significant implications for practice. First, an AVM can act as an impartial arbiter in market rent review disputes. Second, the technology may enable frequent market rent reviews as a lease negotiation strategy that allows tenants and property owners to share market risk by limiting concerns over high costs and adversarial litigation that can emerge in a market rent review dispute.