DOI: 10.12700/APH.10.02.2013.2.1

DOI: 10.12700/APH.10.02.2013.2.2

Abstract: The paper examines the asymmetry of correlation between the Eurozone’s stock market returns. The asymmetry of correlation is investigated pair-wise, by estimating the exceedance correlation between returns of two stock markets at a time. As markets can be very volatile, especially in crisis periods, and because there are investors with different investment horizons, we investigate whether the results are sensitive to time interval of stock market returns. We found that the results of the exceedance correlation estimates and the asymmetric correlation test do depend on the time interval of returns. When longer time interval returns (20-day moving average returns) are used, the Eurozone stock markets’ returns’ dynamics are more (pair-wise) correlated in the falling markets than in the up markets, while for daily returns, the correlations in the up markets are higher for most of the investigated Eurozone’s stock indices pairs. An important implication of the results of the paper is that investors in stock markets should investigate the exceedance correlations and asymmetry of correlation for those return intervals (daily, weekly, monthly, etc.) that correspond to their investment horizon.

Keywords: stock markets; asymmetric correlation; Eurozone

DOI: 10.12700/APH.10.02.2013.2.3

Abstract: Our intention is to evolve agents genetically to maximize their stock price prediction ability. A newly designed stock price prediction algorithm benchmark is used as a fitness function. A portfolio of seven US blue-chip stocks has been set for experimental purposes. We use daily time series of stock prices from 2000 to 2011 divided into two segments, in-sample for genetic algorithm evolution and out-of-sample for evaluation. Agents act as prediction algorithms based on Japanese candlestick patterns expressed as logical formulas and encoded by a tree encoding. Evaluation by the benchmark shows this is a promising way to develop successful stock prices prediction algorithm.

Keywords: agent; genetic; multi-agent; genetic algorithm; time series; financial; stock; stock market; prediction; forecast

DOI: 10.12700/APH.10.02.2013.2.4

Abstract: Assuming that not more audits but better coordinated ones are preferred, the key objective of the article is to explore how deeper exploitation of the current IT background could improve the efficiency of audits and controls of EU funds for Cohesion policy. After presenting the internal control and external audit functions, various scenarios of IT utilization which form different levels of IT convergence are delineated. Finally, the author concludes that audit and control activities could be further developed, particularly by a more extensive use of the IT background. From a professional point of view, direct access to core national databases would provide auditors with additional information on systems at Member States level. The research method applied was interviews with professionals of the European Court of Auditors, as well as with the developer of the Unified Monitoring Information System and different authorities in Hungary. In addition, documents were consulted which are available at the Historical Archives of the European Union and the European Court of Auditors, through the Postgraduate Research Grant Programme, which offered a unique opportunity.

Keywords: Unified Monitoring Information System; multi-level assurance system; Cohesion policy

DOI: 10.12700/APH.10.02.2013.2.5

Abstract: Smart Grid Solutions include different technologies to improve the efficiency of electricity distribution network operations (e.g. distribution automation systems, smart metering, home automation and demand response solutions). The benefits arising from the implementation of distribution automation systems are investigated and evaluated in this article (e.g., the reduction of power losses and the reduction in outage costs and network development costs), taking into consideration the environment of an open electricity market. The investment costs and operation and maintenance costs for the deployment of such systems are analysed as well. Finally, a comparison of the benefits and costs is provided, and relevant conclusions to achieve profitability of the distribution automation systems are considered.

Keywords: Cost Benefit Analysis; Distribution Automation System; Open Electricity Market; Power Distribution; Smart Grid Solutions

DOI: 10.12700/APH.10.02.2013.2.6

Abstract: The growth of Small, Medium and Micro Enterprises (SMMEs) is important to the economic development of Africa. This growth can be greatly enhanced by leveraging IT in business activities since e-commerce is a vital tool to allow participation in globalization. Many SMMEs cannot afford to own e-commerce facilities and to reduce cost. An SMME can pay for just the e-commerce facility they use without owning the services or infrastructure. Due to the dynamic nature of the business domain, delivering such on-demand functionalities involves high flexibility in adapting to new client requirements; therefore, a systematic approach to software component reuse must be adopted to reduce cost and the time to market for new products. This work explores the reuse capabilities of a hybridization of Service Oriented Architecture (SOA) and Software Product Line (SPL).

Keywords: E-commerce; Service Oriented Architecture; Software Product line; and Small Medium and Micro Enterprises

DOI: 10.12700/APH.10.02.2013.2.7

Abstract: Interactive, co-creative relations and collaboration of consumers, users and producers are quickly developing recently. Living Labs [LL] integrate users in the development process of new technologies as co-creators themselves. They have a special bridging role between market pull and technology push innovation and they realise some sort of concurrent innovation. LLs are an interactive search for new products/services in real life milieus together with users/consumers, without the mediation of marketing experts. They receive a different role. Our article highlights LLs first as providers of a collaborative working environment for users. This paper emphasises that LLs have a strong methodology and describes and assesses the “LL Harmonization cube”. Further, it puts emphasis on the difference between a prospective notion of a LL and the recent reality of the LL practice. Recent LLs mostly work at the end phase of the innovation ‘chain’. The article secondly outlines what advantages LLs can bring for SMEs. The main added value of LLs for SMEs is that they provide for innovation services by integrating SMEs as users in a collaborative working environment that would otherwise not be available for them.

Keywords: Open innovation; Living Lab; Harmonization cube; SME involvement

DOI: 10.12700/APH.10.02.2013.2.8

Abstract: This paper presents the development of a wireless temperature monitoring system and the application of measurement data for computer model validation, and its application to the simulation of energy use in a school building in Cacak, Serbia. The system for temperature monitoring was realized with a GPS/GPRS (Global Positioning System/General Packet Radio Service) system for low power data acquisition, using an MSP430 Texas Instruments microcontroller. With respect to heat loss analysis, the continual measurement of ambient and inside temperatures with a sampling time of one hour has been performed. For the simulation, DesignBuilder software is used. The simulation model, which reproduces the temperature measurement of school buildings, was developed and tested for energy analysis. Results are used to develop generalized guidelines for the determination of the efficiency of energy saving measures and the evaluation of low-energy buildings.

Keywords: temperature measurement; energy efficiency; low power microcontroller; DesignBuilder simulation

DOI: 10.12700/APH.10.02.2013.2.9

Abstract: Knowledge management (KM) is a range of strategies and practices in organizations to identify, create, represent, distribute, and enable the adoption of insights and experiences. Knowledge is present in organizations in two forms: explicit (well-structured and unambiguously captured) and tacit (vague or informal, based on experience and beliefs stored in human brains). These two types split knowledge management into its “hard” and “soft” components. Each of them can contribute to an organization’s development and prosperity but must be controlled in different ways. In hard knowledge management, the elements of knowledge, insight and experience are embedded in organizational processes and practice. To control them, traditional (rational) managerial approaches can be applied. However, people do not always act rationally. To benefit from knowledge embodied in individuals, more sophisticated strategies should be used. First we show examples of lower rationality studied by earlier researchers. Then, we use the SECI model to disclose situations deserving managers’ special care. We demonstrate the presence of non-rationality in all SECI stages and exemplify its manifestations. Our conclusions can help managers concentrate on the core problems of knowledge management and apply it more efficiently. Keywords:

Keywords: Knowledge management; Rationality; Irrationality; Emotions; SECI Model; Tacit & explicit Knowledge, Managing tacit knowledge

DOI: 10.12700/APH.10.02.2013.2.10

Abstract: In this paper we propose a novel semi-supervised learning algorithm, called Random Split Statistic algorithm (RSSalg), designed to exploit the advantages of co-training algorithm, while being exempt from co-training requirement for the existence of adequate feature split in the dataset. In our method, co-training algorithm is run for a predefined number of times, using a different random split of features in each run. Each run of co-training produces a different enlarged training set, consisting of initial labeled data and data labeled in the co-training process. Examples from the enlarged training sets are combined in a final training set and pruned in order to keep only the most confidently labeled ones. The final classifier in RSSalg is obtained by training the base learner on a set created this way. Pruning of the examples is done by employing a genetic algorithm that keeps only the most reliable and informative cases. Our experiments performed on 17 datasets with various characteristics show that RSSalg outperforms all considered alternative methods on the more redundant natural language datasets and is comparable to considered alternative settings on the datasets with less redundancy.

Keywords: semi-supervised learning; co-training; ensemble learning; genetic algorithm

DOI: 10.12700/APH.10.02.2013.2.11

Abstract: This paper presents progress in the investigation and development of methods for the automatic localization, extraction, analysis and comparison/classification of the features in signals and their spectra. With diverse applications, different feature attributes turn out to be significant for the investigated phenomena. The general feature characteristics are morphologic and therefore suitable for a variety of algorithms focused on visual data processing, which we use in the automatic feature recognition. Our major applications were in the analysis of biological signals, and acoustic, sonar and radar signals; the methods presented here are applicable in other areas as well.

Keywords: Automatic detection of spectral features; Invariants of signal features; Brain Computer Interface; Noise elimination in radar signals

DOI: 10.12700/APH.10.02.2013.2.12

Abstract: This paper proposes information and knowledge mining in the source code of medium and large enterprise projects. Our methods try to recognize structures and types of source code, identify authors and users to enhance collaborative programming, and support knowledge management in software companies. Developers within and outside the teams can receive and utilize visualized information from the code and apply it to their projects. This new level of aggregated 3D visualization improves refactoring, source code reusing, implementing new features and exchanging knowledge.

Keywords: information and knowledge mining; knowledge management; collaborative programming; visualization; recognition; authors; users; source code type; code tagging

DOI: 10.12700/APH.10.02.2013.2.13

Abstract: The simulation of the business and manufacturing processes plays an essential role in modern scientific research and decision-making in management. However, this simulation, especially its output performance measures, can be very tricky because these simulations depend on the calculations of particular simulation software. The objective of this paper is to confront the average values of performance indicators of the manufacturing simulation model in three well-known manufacturing-focused simulation tools. Thus, we applied advanced inferential statistical technique after normality test and the homogeneity of variances to analyze the output data of the model in three different simulation tools. We performed statistical analysis on the data of the average waiting time in queue and the number of completed parts obtained from 1500 replications together. The simulation model of this study employs a single-machine workstation driven by M/G/1 queue with FIFO queue discipline. The findings from the partial and overall results are offered in the conclusion and discussion part of the paper.

Keywords: simulation; technique; inferential statistics; queue; model; process

DOI: 10.12700/APH.10.02.2013.2.14

Abstract: The aim of this study is to investigate the influence of knowledge management practices on organizational performance in small and medium enterprises (SMEs) using structural equation modeling (SEM). A number of 282 senior managers from these enterprises were chosen using simple random sampling and the data were analyzed with the structural equation model. The results showed that knowledge acquisition, knowledge storage, knowledge creation, knowledge sharing, and knowledge implementation have significant factor loading on knowledge management; and also productivity, financial performance, staff performance, innovation, work relationships, and customer satisfaction have significant factor loading on organizational performance. Finally, the results of this study suggest that knowledge management practices directly influence the organizational performance of SMEs.

Keywords: knowledge management; organizational performance; SMEs

DOI: 10.12700/APH.10.02.2013.2.15

Abstract: The current product model consists of features and unstructured contextual connections in order to relate features. The feature modifies the previous state of the product model producing contextual connections with previously defined features. Active knowledge is applied for the adaptive modification of product model features in the case of a changed situation or event. Starting from this state-of-the-art, the authors of this paper introduced a new method to achieve higher-level and more advanced active feature driven product model definition. As part of the related research program, new situation driven model definition processes and model entities are explained in this paper. Higher-level knowledge representation in the product model is motivated by a recent trend in industrial product modeling systems towards more advanced and efficient situation-based self-adaptive model generation. The proposed model represents one of the possible future ways of product model development for product lifecycle management (PLM) systems on the global or product level of decisions. Its implementation will be new application-oriented model entity generation and representation utilizing existing modeling resources in industrial PLM systems by use of application programming interfaces (API).

Keywords: product model; situation-based product definition; active knowledge in product model; product behavior driven feature definition