Abstract: This paper presents a survey of the main publications and general design requirements and problems of inductive power transfer systems for dynamic charging of electric vehicles (EVs). The main different roadbed geometries, based on a single transmitter track and segmented transmitter coil array have been discussed. Different case studies considering charging scenario, vehicle speeds, power levels and transmitting and receiving coils geometry have been conducted. Some problems about the design of charging station and EV side control system and energy management system have been analysed. A prototype of a charging station has been developed and built to supply inductive power transfer system which delivers 10-35 kW power at an air gap between transmitting and receiving parts of 75-100 mm and horizontal misalignment of ± 200 mm. The results have shown that the system can transfer the specified electrical power at efficiency of about 82-92% and that the inductive power transfer module and its dynamic matching during charging, exhibited high degree of stability under a misaligned (x-y-z) condition and battery state of charge.
Keywords: electric vehicle; contactless charging; transmitting and receiving coil; inductive power transfer; energy management system
Abstract: This paper presents an extended model for solving time-varying resourceconstrained scheduling problems. The motivation for our research comes from the automotive industry. The problem is to create fine schedules for a complex manufacturing system to satisfy diverse customer demands. The detailed characteristics of the analyzed scheduling problem and the developed solving approach are described in this paper. To consider the impact of the assistant processes that are connected to the manufacturing primary processes, we elaborated a problem-transformation procedure and a new extended scheduling model that can manage time-varying availability constraints of parallel resources, unit processing times, job-dependent release times and due dates. This paper also presents slack-oriented and JIT-oriented algorithms that can solve the resourceconstrained scheduling problems. The research results have been successfully applied and tested in practice.
Keywords: scheduling; resource availability constraint; multi-objective optimization; production planning and control; manufacturing operations management
Abstract: This paper presents a rigorous information-theoretic analysis of iris biometrics with the aim to develop optimized biometric cryptosystems. By estimating local entropy and mutual information, we identify the iris regions that are most suitable for these purposes. Parameter optimization of the appropriate wavelet transform produces higher entropy and low mutual information in the transformation domain. This establishes an effective framework for the development of systems for the extraction of truly random sequences from iris biometrics, while not compromising its proven authentication features.
Keywords: iris biometrics; image analysis; information theory; image texture; biometric cryptosystems
Abstract: The Ontology for Linked Open University Data (OLOUD) is a practical approach to model course information at a typical Hungarian university. OLOUD aims to integrate data from several sources and provide personal timetables, navigation and other types of help for students and lecturers. The modeled domains include curricula, subjects, courses, semesters and personnel, but also buildings and events. Although there are several ontologies for the mentioned domains, selecting a set of ontologies fitting our use case was not an easy task. We summarize problems we met such as missing links, inconsistencies as well as many overlaps between ontologies. Finally, OLOUD acts as a glue for a selection of existing ontologies, and thus enables us to formulate SPARQL queries for a wide range of practical questions of university students.
Keywords: Linked Open Data; Linked Open University Data; Ontology; OWL
Abstract: Utilizing dynamic resource allocation for load balancing is considered as an important optimization process in cloud computing. In order to achieve maximum resource efficiency and scalability in a speedy manner this process is concerned with multiple objectives for an effective distribution of loads among virtual machines. In this realm, exploring new algorithms, as well as development of novel algorithms, is highly desired for technological advancement and continued progress in resource allocation application in cloud computing. Accordingly, this paper explores the application of two relatively new optimization algorithms and further proposes a hybrid algorithm for load balancing which can contribute well in maximizing the throughput of the cloud provider's network. The proposed algorithm is a hybrid of teaching-learning-based optimization algorithm (TLBO) and grey wolves optimization algorithm (GW). The hybrid algorithm performs more efficiently than utilizing every single one of these algorithms. Furthermore, it well balances the priorities and effectively considers load balancing based on time, cost, and avoidance of local optimum traps, which consequently leads to minimal amount of waiting time. To evaluate the effectiveness of the proposed algorithm, a comparison with the TLBO and GW algorithms is conducted and the experimental results are presented.
Abstract: The stacker cranes in automated storage/retrieval systems (AS/RS) of warehouses often have very high dynamical loads. These dynamical loads may generate harmful mast vibrations in the frame structure of stacker cranes which can reduce the stability and positioning accuracy of these machines. The aim of this paper is to develop controller design methods which have proper reference signal tracking and mast-vibration attenuation properties. First, the dynamic modeling of single-mast stacker cranes by means of multibody modeling approach is summarized. Based on this modeling technique a H∞ and a robust control design method are proposed for achieving the appointed purposes. The analyses of the controlled systems are carried out by time domain simulations.
Keywords: stacker crane; modeling uncertainties; robust control; multi-body model
Abstract: A bot is one of the main elements of all computer video games, frequently used for the creation of various opponent characters within a game. Opponent modeling is the problem of predicting the agent actions in a gaming environment. This paper proposes and describes the implementation of a bot as a personal opponent in a small educational game. In order to increase the efficiency when using such a small educational application/module, artificial intelligence was added in the form of a bot competing with the students. Pedagogical elements of the intelligent learning system are introduced through the pedagogical model and the student model. This paper demonstrates the use of the student model to present the player model built by the experience of a human teacher, with true/false questions incorporated with the bot strategy into the opponent model. The authors use the Monte Carlo approach in this implementation, known as artificial intelligence technique and a best-first search method used in most video games, but to the best of their knowledge, it has not been used for prediction in educational games based on bot strategy. The results highlight that the Monte Carlo approach presented via the BFTree classifier provides the best classification accuracy compared with other predictive models based on data mining classifiers. It was shown that the training data from the human player can help in creating a bot strategy for a personalized game-based learning system. The Help option can be used for the assessment of the students’ current knowledge by counting the number of Help option accesses, the player relies on Help as a ‘source of knowledge’ needed to complete the game task successfully. The obtained results show that the bot (personal opponent) stimulated players to replay the game multiple times, which may contribute to the increase of the students’ knowledge.
Keywords: knowledge personalization and customization; educational games; intelligent tutoring systems; personalized e-learning
Abstract: The optimisation of land use structure is crucial to have a competitive agricultural production. In Hungary land consolidation lacks some important conditions such as a reasonable decision making support system based on Geoinformatics. In the paper, we optimize the land structure based on landownership. The present paper analyses the DigiTerra software that operates on the basis of Cluster Analysis and it provides a solution for the development. The improved software is introduced on a sample area. The efficiency of the allocation is proven by the internationally accepted fragmentation (Simmons, Januszewski, Igozurike) indices for parcels.
Keywords: land consolidation; cluster analysis; land valuation
Abstract: The paper focuses on problem of development of autonomous power-supply systems based on micro hydropower plants, which are using small watercourse power. The design and development of such systems is influenced by a number of conflicting objectives. The power source has to generate ac voltage with steady-state magnitude and frequency and, at the same time, it has to be fairly simple and inexpensive. One of the future-proof designs that provides fulfillment of the above mentioned requirements is a gearless micro hydropower plant with a combined impeller of axial-flow turbine and an electric arc-shape inductor generator. The authors have identified how geometrical parameters of the arc-shape inductor generator influences the machine operation factors. In addition, they have found that the air gap impacts the ripple factor significantly. Finally the paper shows functional dependence of the slot chamfer factor on chamfer angle, which simplifies the problem of choosing reasonable, in terms of efficiency, design parameters of the generator for the micro hydropower plant.
Keywords: micro hydropower plant; arc-shape inductor generator; form factor; design solutions; parameter optimization; ripple factor; chamfer angle
Abstract: Production and service systems are generally evaluated based on financial information. The financial approach looks for opportunities to boost profits in two main ways: by decreasing operating costs and/or by increasing production quantity. Consequently, the cost of operation is evaluated and cost reduction possibilities are explored with proper cost analysis methods. Scoring methods extend the frontiers of performance evaluation by also employing non-financial information, although these methods generally contain several subjective elements. Data Envelopment Analysis (DEA) aims to integrate several performance measures into an aggregate output measure and several resource usage characteristics into an aggregate input measure. Based on the inputs applied and on the outputs generated, an efficiency score is calculated using linear programming. The objective of this paper is to illustrate the differences between performance evaluations, based on financial information, versus the DEA results. The results of a production simulation game are used to show how a DEA based performance evaluation can be carried out. The additional information provided by DEA may help to identify the causes of inefficient operation and to explore ways of improving efficiency.
Keywords: Data envelopment analysis (DEA); Performance evaluation; Production management; Simulation games; Linear programming
Abstract: For the scientific community worldwide, developing a new actuator is a challenging task. New types of actuators are needed, especially in humanoid robotics in order to replace real human muscle. There are several approaches for how to obtain this goal. One approach is to realize real muscle using new synthetic materials such as piezoelectric components or pneumatic polymer materials. A second approach is to improve standard electromotor-gear actuators. Another unconventional approach is to use standard electromotor together with a tendon-based driving system. This paper presents a successful realization and control model for a proposed twisted-string actuator. Controller design is based on the National Instruments Single Board RIO driving a MAXON motor type tendon driven muscle. A Powerful Spartan FPGA is a key element for the presented hardware implementation. To program the whole system, LabVIEW software is used. Theoretically explained simulation results for adopted model design, as well as real measured experimental movement under the load force, are presented in the paper.
Keywords: twisted string; tendon; actuator; SB-Rio; LabVIEW
Abstract: The subject of this paper is the self-organized grouping of droplet epitaxial III-Vbased nano-structures. For the nano-structure grouping, our developed algorithm - called Quantum Structure Analyzer 1.0 - is used. The operation of this software is based on the principles of the Kohonen Self-Organizing Network. Here, three possibilities for nanostructured groupings are shown. On one hand, we examine the classification of nanostructures with Kohonen Self-Organizing Maps, on the other hand, fuzzy inference systems are applied for the same goal. In the case of the fuzzy methods two approaches are examined in detail. According to the first fuzzy inference approach, the shape factor is calculated from the size of nanostructures. According to the second fuzzy inference approach, the shape factor calculation is based on the controllable parameters of the growth process (eg. pressure and the temperature of the substrate).
Keywords: nanostructure; classification; self-assembling; Kohonen SOM; fuzzy inference system; shape factor
Abstract: Air passengers are particularly faced with uncertainty during their travel. Information regarding the expected check-in time is not sufficient enough. In many cases, there is no infrastructure to measure the time of check-in process and to inform passengers. The aim of our research was to elaborate a method based on historical data in order to reveal the influencing factors and their effects on time elements (queuing and service time). We have considered various air-carrier operational types, periods of the year and destinations. The cases of each type and their combinations have been fully investigated. The most important influencing factors are: passenger numbers, baggage to passenger ratio, ratio of wheelchair passengers and the number of open check-in counters. The results serve as input data for prediction of check-in time in a personalized passenger information service.
Keywords: airport check-in; historical data; passenger queues; regression analysis