Search results for: Volker Koch

Authors: A. Taqaddas

Abstract:

This mini literature review discusses casual relationships between HIV and AIDS in view of Koch’s postulates.

Keywords: AIDS, Causal Relationship, HIV, Koch’s Postulates.

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Authors: Volker Koch

Abstract:

This paper deals with the education of purchasing professionals in Austria. In this education, equivalent and measurable criteria are collected in order to create a comparison. The comparison shows the problem. To make the aforementioned comparison possible, methodologies such as KODE-Competence Atlas or presentations in a matrix form are used. The result shows the content taught and whether there are any similarities or interesting differences in the current Austrian purchasers’ formations. Purchasing professionals learning competencies are also illustrated in the study result.

Keywords: Competencies, education, purchasing professional, technological-oriented.

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Authors: V. V. Reddy, N. V. S. N. Sarma

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A circularly polarized fractal boundary microstrip antenna is presented. The sides of a square patch along x- axis, yaxis are replaced with Minkowski and Koch curves correspondingly. By using the fractal curves as edges, asymmetry in the structure is created to excite two orthogonal modes for circular polarization (CP) operation. The indentation factors of the fractal curves are optimized for pure CP. The simulated results of the novel polyfractal antenna are demonstrated.

Keywords: Circular polarization, Fractal, Koch, Minkowski.

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Authors: Amar Partap Singh Pharwaha, Shweta Rani

Abstract:

To develop a reliable and cost effective communication platform for the telemedicine applications, novel antenna design has been presented using bacterial foraging optimization (BFO) technique. The proposed antenna geometry is achieved by etching a modified Koch curve fractal shape at the edges and a square shape slot at the center of the radiating element of a patch antenna. It has been found that the new antenna has achieved 43.79% size reduction and better resonating characteristic than the original patch. Representative results for both simulations and numerical validations are reported in order to assess the effectiveness of the developed methodology.

Keywords: BFO, electrical permittivity, fractals, Koch curve.

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Authors: Sh. Edrisi, M. Moeeni, A. Farahbakhsh

Abstract:

To study the effect of nitrogenous additive spray solution on the efficacy of three herbicides i.e. pinoxaden (Trade name: Axial), sulfosulfuron+metsulfuron-methyl (Trade name: Total) and sulfosulfuron (Trade name: Apirus) in controlling wild barley (Hordeum spontaneum C. Koch), in different growth stages, a greenhouse experiment as a split plot in a completely randomized design in three replications was conducted. One month after treatments, all plants were harvested and growth parameters were determined. The data were analyzed with computer. The results showed that the herbicide applications with and without nitrogen additive caused significant reductions in growth parameters of wild barley at 2-4 leaf stage. However, the plants were not killed by this herbicide. Plants were killed completely due to applications of the two other herbicides i.e. Apirus and Total at 2-4 leaf. There was no significant difference between the effect of these two herbicides. There was no significant difference between the highest rate of each herbicide used alone and that of the lowest rate with nitrogenous additive.

Keywords: Growth stage, herbicide, nitrogenous additive, wild barley.

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Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. In this paper, we investigated three approaches to build a meta-classifier in order to increase the classification accuracy. The basic idea is to learn a metaclassifier to optimally select the best component classifier for each data point. The experimental results show that combining classifiers can significantly improve the accuracy of classification and that our meta-classification strategy gives better results than each individual classifier. For 7083 Reuters text documents we obtained a classification accuracies up to 92.04%.

Keywords: Meta-classification, Learning with Kernels, Support Vector Machine, and Performance Evaluation.

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Authors: Sanmohan Krüger, Volker Krüger

Abstract:

Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper an online algorithm to recognize parametric actions with object context is presented. Objects are key instruments in understanding an action when there is uncertainty. Ambiguities arising in similar actions can be resolved with objectn context. We classify actions according to the changes they make to the object space. Actions that produce the same state change in the object movement space are classified to belong to the same class. This allow us to define several classes of actions where members of each class are connected with a semantic interpretation.

Keywords: Parametric actions, Action primitives, Hand gesture recognition, Imitation learning

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Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Keywords: Feature Selection, Learning with Kernels, Support Vector Machine, Genetic Algorithm, and Classification.

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, three feature selection methods are evaluated: Random Selection, Information Gain (IG) and Support Vector Machine feature selection (called SVM_FS). We show that the best results were obtained with SVM_FS method for a relatively small dimension of the feature vector. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Feature Selection, Learning with Kernels, SupportVector Machine, and Classification.

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Authors: Jes Søndergaard, Torben Tambo, Christian Koch

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It is not a secret that, IT management has become more and more and integrated part of almost all organizations. IT managers posses an enormous amount of knowledge within both organizational knowledge and general IT knowledge. This article investigates how IT managers keep themselves updated on IT knowledge in general and looks into how much time IT managers spend on weekly basis searching the net for new or problem solving IT knowledge. The theory used in this paper is used to investigate the current role of IT managers and what issues they are facing. Furthermore a research is conducted where 7 IT managers in medium sized and large Danish companies are interviewed to add further focus on the role of the IT manager and to focus on how they keep themselves updated. Beside finding substantial need for more research, IT managers – generalists or specialists – only have limited knowledge resources at hand in updating their own knowledge – leaving much initiative to vendors.

Keywords: CIO, information Technology, Knowledge, Management, Organization

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: Outlier detection, generative adversary networks, semi-supervised learning.

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Authors: Volker Lange, Stephanie Moede, Christiane Auffermann

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From an economic standpoint the current and future road traffic situation in urban areas is a cost factor. Traffic jams and congestion prolong journey times and tie up resources in trucks and personnel. Many discussions about imposing charges or tolls for cities in Europe in order to reduce traffic congestion are currently in progress. Both of these effects lead – directly or indirectly - to additional costs for the urban distribution systems in retail companies. One approach towards improving the efficiency of retail distribution systems, and thus towards avoiding negative environmental factors in urban areas, is horizontal collaboration for deliveries to retail outlets – Urban Retail Logistics. This paper presents a classification system to help reveal where cooperation between retail companies is possible and makes sense for deliveries to retail outlets in urban areas.

Keywords: City Logistics, Horizontal Collaboration, Urban Freight Transport, Urban Retail Logistics.

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Authors: Volker Heierhoff, Aurilla Aurelie Bechina Arntzen, Gerrit Muller

Abstract:

It well recognized that one feature that makes a successful company is its ability to successfully align its business goals with its information communication technologies platform. Enterprise Resource Planning (ERP) systems contribute to achieve better performance by integrating various business functions and providing support for information flows. However, the technological systems complexity is known to prevent the business users to exploit in an efficient way the Enterprise Resource Planning Systems (ERP). This paper aims to investigate the role of training in improving the usage of ERP systems. To this end, we have designed an instrument survey to employees of a Norwegian multinational global provider of technology solutions. Based on the analysis of collected data, we have delineated a training model that could be high relevance for both researchers and practitioners as a step towards a better understanding of ERP system implementation.

Keywords: Business User Training, Enterprise resource planning system, Global consulting company, Role and responsibilities

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of features selection methods to reduce the dimensionality of the document-representation vector. Four feature selection methods are evaluated: Random Selection, Information Gain (IG), Support Vector Machine (called SVM_FS) and Genetic Algorithm with SVM (GA_FS). We showed that the best results were obtained with SVM_FS and GA_FS methods for a relatively small dimension of the features vector comparative with the IG method that involves longer vectors, for quite similar classification accuracies. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Features selection, learning with kernels, support vector machine, genetic algorithms and classification.

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Authors: C. Bruni, F. Delli Priscoli, G. Koch, I. Marchetti

Abstract:

The Connection Admission Control (CAC) problem is formulated in this paper as a discrete time optimal control problem. The control variables account for the acceptance/ rejection of new connections and forced dropping of in-progress connections. These variables are constrained to meet suitable conditions which account for the QoS requirements (Link Availability, Blocking Probability, Dropping Probability). The performance index evaluates the total throughput. At each discrete time, the problem is solved as an integer-valued linear programming one. The proposed procedure was successfully tested against suitably simulated data.

Keywords: Connection Admission Control, Optimal Control, Integer valued Linear Programming, Quality of Service Requirements, Robust Control.

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Authors: Carlo Bruni, Francesco Delli Priscoli, Giorgio Koch, Ilaria Marchetti

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This paper proposes an innovative approach for the Connection Admission Control (CAC) problem. Starting from an abstract network modelling, the CAC problem is formulated in a technology independent fashion allowing the proposed concepts to be applied to any wireless and wired domain. The proposed CAC is decoupled from the other Resource Management procedures, but cooperates with them in order to guarantee the desired QoS requirements. Moreover, it is based on suitable performance measurements which, by using proper predictors, allow to forecast the domain dynamics in the next future. Finally, the proposed CAC control scheme is based on a feedback loop aiming at maximizing a suitable performance index accounting for the domain throughput, whilst respecting a set of constraints accounting for the QoS requirements.

Keywords: Network Management, Quality of Service (QoS) requirements, Optimal Control.

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Authors: Edina Koch, Péter Hudacsek

Abstract:

In railways transition zone is present at the boundaries of zones with different stiffness. When a train rides from an embankment onto a stiff structure, such as a bridge, tunnel or culvert, an abrupt change in the support stiffness occurs possibly inducing differential settlements. This in long term can yield to the degradation of the tracks and foundations in the transition zones. A number of techniques have been proposed or implemented to provide gradual stiffness transition at the problem zones, such as methods to ensure gradually changing pad stiffness, application of long sleepers or installation of auxiliary rails in the transition zone. Aim of the research presented in this paper is to analyze the 3D and the dynamic effects induced by the passing train over an area where significant difference in the support stiffness exists. The effects were analyzed for different arrangements associated with certain differential settlement mitigation strategies of the transition zones.

Keywords: Culvert, dynamic load, HS small model, railway transition zone.

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Authors: Kholoud A. Al-Shammery , Badr El-Sabah A. Fetoh, Ahmed M. Alshammari

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Protein and Esterase electrophoresis were used to genetically identify two Saudi tick species. Engorged females of the camel tick Hyalomma dromedarii (Koch) (Acari: Ixodidae) and the cattle tick Boophilus annulatus (Say) (Acari: Ixodidae) ticks collected from infested camels and cattle in the animals resting house at Hail region in KSA were used. The results showed that there are a variation in both of protein and esterase activity levels and a high polymorphism within and between the genera and species of Hyalomma and Boophilus . In conclusion, the protein and esterase electrophoretic analysis used in the present study could successfully distinguish among tick species, commonly found in Saudi Arabia.

Keywords: Molecular biology, The camel tick Hyalomma dromedarii, The cattle tick Boophilus annulatus , Ticks.

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Authors: C. Elavarasi, T. Shanmuganantham

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A coplanar waveguide (CPW) feed is presented, and comprising a split ring resonator (SRR) loaded fractal with water lily shape is used for multi band applications. The impedance matching of the antenna is determined by the number of Koch curve fractal unit cells. The antenna is designed on a FR4 substrate with a permittivity of ε_{r =} 4.4 and size of 14 x 16 x 1.6 mm³ to generate multi resonant mode at 3.8 GHz covering S band, 8.68 GHz at X band, 13.96 GHz at Ku band, and 19.74 GHz at K band with reflection coefficient better than -10 dB. Simulation results show that the antenna exhibits the desired voltage standing wave ratio (VSWR) level and radiation patterns across the wide frequency range. The fundamental parameters of the antenna such as return loss, VSWR, good radiation pattern with reasonable gain across the operating bands are obtained.

Keywords: Monopole antenna, fractal, metamaterial, waterlily shape, split ring resonator, multiband.

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Authors: A. Özköse

Abstract:

This study was conducted to determination of yield and yield components of some fodder beet types (Amarilla Barres, Feldherr, Kyros, Magnum ve Rota) under the Konya region conditions. Fodder beet was obtained from the Selcuk University, Faculty of Agriculture, at 2006-2007 season and the experiment was established in a randomized complete block design with three replicates. Differences among the averages of the fodder beet cultivars are statistically important in terms of all the characteristics investigated. Leaf attitude value was 1.2 – 2.2 (1=erect; 5= prostrate), root shape scale value was (1=spheroidal – 9=cylindrical), root diameter 11.0 – 12.2cm, remaining part of root on the ground was 6.3 – 13.7cm, root length was 21.4 – 29.6cm, leaf yield 1592 – 1917 kg/da, root yield was 10083 – 12258 kg/da, root dry matter content was %8.2 – 18.6 and root dry matter yield was 889 – 1887 kg/da. As a result of the study, it was determined that fodder beet cultivars are different conditions in terms of yield and yield components. Therefore, determination of appropriate cultivars for each region affect crop yield importantly.

Keywords: Fodder beet, root yield, yield components.

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Authors: Robert Koch, Mario Golling, Gabi Dreo Rodosek

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Tracing and locating the geographical location of users (Geolocation) is used extensively in todays Internet. Whenever we, e.g., request a page from google we are - unless there was a specific configuration made - automatically forwarded to the page with the relevant language and amongst others, dependent on our location identified, specific commercials are presented. Especially within the area of Network Security, Geolocation has a significant impact. Because of the way the Internet works, attacks can be executed from almost everywhere. Therefore, for an attribution, knowledge of the origination of an attack - and thus Geolocation - is mandatory in order to be able to trace back an attacker. In addition, Geolocation can also be used very successfully to increase the security of a network during operation (i.e. before an intrusion actually has taken place). Similar to greylisting in emails, Geolocation allows to (i) correlate attacks detected with new connections and (ii) as a consequence to classify traffic a priori as more suspicious (thus particularly allowing to inspect this traffic in more detail). Although numerous techniques for Geolocation are existing, each strategy is subject to certain restrictions. Following the ideas of Endo et al., this publication tries to overcome these shortcomings with a combined solution of different methods to allow improved and optimized Geolocation. Thus, we present our architecture for improved Geolocation, by designing a new algorithm, which combines several Geolocation techniques to increase the accuracy.

Keywords: IP geolocation, prosecution of computer fraud, attack attribution, target-analysis

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Authors: Robert Koch, Mario Golling, Gabi Dreo

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During the last couple of years, the degree of dependence on IT systems has reached a dimension nobody imagined to be possible 10 years ago. The increased usage of mobile devices (e.g., smart phones), wireless sensor networks and embedded devices (Internet of Things) are only some examples of the dependency of modern societies on cyber space. At the same time, the complexity of IT applications, e.g., because of the increasing use of cloud computing, is rising continuously. Along with this, the threats to IT security have increased both quantitatively and qualitatively, as recent examples like STUXNET or the supposed cyber attack on Illinois water system are proofing impressively. Once isolated control systems are nowadays often publicly available - a fact that has never been intended by the developers. Threats to IT systems don’t care about areas of responsibility. Especially with regard to Cyber Warfare, IT threats are no longer limited to company or industry boundaries, administrative jurisdictions or state boundaries. One of the important countermeasures is increased cooperation among the participants especially in the field of Cyber Defence. Besides political and legal challenges, there are technical ones as well. A better, at least partially automated exchange of information is essential to (i) enable sophisticated situational awareness and to (ii) counter the attacker in a coordinated way. Therefore, this publication performs an evaluation of state of the art Intrusion Detection Message Exchange protocols in order to guarantee a secure information exchange between different entities.

Keywords: Cyber Defence, Cyber Warfare, Intrusion Detection Information Exchange, Early Warning Systems, Joint Intrusion Detection, Cyber Conflict

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Authors: Volker Wannack

Abstract:

Regional and global strategies focusing on hydrogen (H2) and blockchain technologies are fueling remarkable advancements. These strategies underpin the revolutionary 'Blockchain Based Hydrogen Market (BBH2)' project, with the primary objective of creating a Blockchain Minimum Viable Product (B-MVP) tailored to the hydrogen market. The B-MVP harnesses blockchain's capabilities, establishing a unified platform for secure, automated transactions via smart contracts. This innovation promises to reshape hydrogen logistics, trade, and transactions. The B-MVP carries transformative potential across diverse sectors, benefiting renewable energy producers, surplus energy-based hydrogen manufacturers, grid operators, and consumers. By implementing standardized, automated, tamper-proof processes, it bolsters cost-efficiency and enables transparent, traceable transactions. Its core mission is to verify the integrity of 'green' hydrogen, tracing its journey from renewable producers to end-users. This emphasis on transparency fosters economic, ecological, and social sustainability within a secure, transparent market. A standout feature of the B-MVP is its cross-border adaptability, obviating the need for nation-specific data storage, and broadening its global reach. This adaptability also spurs long-term job creation by establishing a dedicated blockchain operating firm. By attracting skilled labor and offering training, the B-MVP fortifies the hydrogen sector's workforce. Furthermore, it catalyzes innovative business models, luring more companies and startups, contributing to sustained job growth. For example, data analysis can tailor tariffs to offer demand-centric network capacities to producers and operators, providing tamper-proof pricing options to redistributors and end-customers. Beyond technological and economic progress, the B-MVP amplifies the prominence of national and international standards efforts. The region implementing the B-MVP becomes recognized as a pioneer in climate-friendly, sustainable, and forward-thinking practices, generating interest and attention beyond its geographic boundaries. Additionally, it fosters knowledge transfer between academia and industry, promoting scientific advancements, aligning with innovation management, and nurturing an innovation culture in the hydrogen sector. Through blockchain-hydrogen integration, the B-MVP champions comprehensive innovation, contributing to a sustainable future in the hydrogen industry. Implementation involves evaluating blockchain tech, developing smart contracts, and ensuring interoperability with existing systems. Scalability testing and data format development further validate the B-MVP's potential. BBH2 secures funding under the 'Technology Offensive Hydrogen,' a part of the Federal Ministry of Economics and Climate Protection's 7th Energy Research Program.

Keywords: Hydrogen, blockchain, sustainability, structural change.

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