National Industrialization Strategies and Firm Level IR/HR Practices: Case Studies in Malaysia and Philippines

[Excerpt] Any economy is characterized by several different patterns of industrial relations (IR)and human resource (HR) practices at the level of the workplace. Often, the patterns of IR/HR practices of firms differ based on the nature of the industry, the nature of technology and production methods used, the specific economic circumstances facing firms, and in some cases the IR/HR philosophy of key individuals. Patterns of IR/HR practices also differ based on economic sectors, with IR/HR practices in the service sector showing differences with patterns in the manufacturing sector

Assessment of multi-temporal, multi-sensor radar and ancillary spatial data for grasslands monitoring in Ireland using machine learning approaches

Accurate inventories of grasslands are important for studies of carbon dynamics, biodiversity conservation and agricultural management. For regions with persistent cloud cover the use of multi-temporal synthetic aperture radar (SAR) data provides an attractive solution for generating up-to-date inventories of grasslands. This is even more appealing considering the data that will be available from upcoming missions such as Sentinel-1 and ALOS-2. In this study, the performance of three machine learning algorithms; Random Forests (RF), Support Vector Machines (SVM) and the relatively underused Extremely Randomised Trees (ERT) is evaluated for discriminating between grassland types over two large heterogeneous areas of Ireland using multi-temporal, multi-sensor radar and ancillary spatial datasets. A detailed accuracy assessment shows the efficacy of the three algorithms to classify different types of grasslands. Overall accuracies ≥ 88.7% (with kappa coefficient of 0.87) were achieved for the single frequency classifications and maximum accuracies of 97.9% (kappa coefficient of 0.98) for the combined frequency classifications. For most datasets, the ERT classifier outperforms SVM and RF

PLC Code Vulnerabilities Through SCADA Systems

Supervisory Control and Data Acquisition (SCADA) systems are widely used in automated manufacturing and in all areas of our nation\u27s infrastructure. Applications range from chemical processes and water treatment facilities to oil and gas production and electric power generation and distribution. Current research on SCADA system security focuses on the primary SCADA components and targets network centric attacks. Security risks via attacks against the peripheral devices such as the Programmable Logic Controllers (PLCs) have not been sufficiently addressed. Our research results address the need to develop PLC applications that are correct, safe and secure. This research provides an analysis of software safety and security threats. We develop countermeasures that are compatible with the existing PLC technologies. We study both intentional and unintentional software errors and propose methods to prevent them. The main contributions of this dissertation are: 1). Develop a taxonomy of software errors and attacks in ladder logic 2). Model ladder logic vulnerabilities 3). Develop security design patterns to avoid software vulnerabilities and incorrect practices 4). Implement a proof of concept static analysis tool which detects the vulnerabilities in the PLC code and recommend corresponding design patterns

Managing competences in entrepreneurial technology firms: a comparative institutional analysis of Germany, Sweden and the UK

Innovative firms face two major kinds of risks in developing new technologies: competence destruction and appropriability. High levels of technical uncertainty and radical changes in knowledge in some fields generate high technical failure risks and make it difficult to plan research and development programmes. They therefore encourage high levels of flexibility in acquiring and using skilled staff. Appropriability risks, on the other hand, encourage innovative firms to develop organisation-specific competences through investing in complementary assets, such as marketing and distribution capabilities, that involve longer-term employer-employee commitments to building complex organisations. These connections between technology risks and employment policies help to explain why different kinds of market economies with contrasting labour market institutions develop varied innovation patterns. This study focuses on subsectors of the computer software and biotechnology industries in three distinct Europea n countries, UK, Germany and Sweden, that vary in their level of technical change and appropriability.n/a

Comparison of Support Vector Machine and Back Propagation Neural Network in Evaluating the Enterprise Financial Distress

Recently, applying the novel data mining techniques for evaluating enterprise financial distress has received much research alternation. Support Vector Machine (SVM) and back propagation neural (BPN) network has been applied successfully in many areas with excellent generalization results, such as rule extraction, classification and evaluation. In this paper, a model based on SVM with Gaussian RBF kernel is proposed here for enterprise financial distress evaluation. BPN network is considered one of the simplest and are most general methods used for supervised training of multilayered neural network. The comparative results show that through the difference between the performance measures is marginal; SVM gives higher precision and lower error rates.Comment: 13 pages, 1 figur