Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed algorithms for Wireless Physical Layer Network Coding self-organisation in cloud communication networks

Communication networks of present-days are growing in complexity to follow a never-ending demand for fast, smooth, energy efficient and cheap connection. This demand is a driving force of new technologies. Two of them – cloud network concept and Wireless Physical Layer Network Coding (WPLNC) – are in the focus of this thesis. Both together represent a paradigm shift that can bring benefits to the networks of the future. With WPLNC the communicating nodes are no more separated in orthogonal resources, such as time, frequency or code space. Instead, they are allowed to overlap directly at the level of electromagnetic waves. Overlapping signals are no more considered as nuisance, rather, they form new super-signals that are processed as one. With slightly more complicated signal processing some big advantages in throughput, reliability and/or efficiency can be achieved by this technique. Cloud network concept introduces an intelligent network, that is able to react on changing conditions. The network is formed by self-aware relay nodes that cooperate to provide communication service to the terminals. The network is assumed distributed and decentralised to be able to react fast and adapt to local variations. WPLNC technique seems to be a favourable scheme for such a network. In this thesis I focus on distributed algorithms for implementation of WPLNC in the context of cloud network. The algorithms equip the relay nodes with ability to self-adapt and self-organise their WPLNC processing, such that it is aligned optimally across the whole network. Particularly, as an example an algorithm that assigns WPLNC mappings to individual relays is provided. This algorithm is transformed into a form of suitable communication protocol. Some other versions of the algorithm are proposed that focus on more complex situations – when the relays do not perform fair and try to harm the network or when some form of behaviour is dependent on relay node state, such as battery level. Whenever it is possible not only a mathematical solution of studied issues is provided but also software simulation is shown and more importantly a verification by hardware testing in real conditions is done and presented.
Automatic epilepsy detection from EEG introducing a new edge weight method in the complex network

Automatic diagnosis of epilepsy using electroencephalogram (EEG) signals is a hot topic in medical community as traditional diagnosis relies on tedious visual screening by highly trained clinicians from lengthy EEG recording. Hence, a new methodology to automatically detect epilepsy from EEG signals considering complex network as the principal dynamics of the epileptic EEG signals can be perfectly described by complex network is introduced. A novel edge weight method for visibility graph in the complex network for detection of epilepsy syndrome is presented. The effect of new edge weights for one key characteristic (such as, average weighted degree ) of complex network is investigated. Finally, the extracted feature set is evaluated by two popular machine learning classifiers: support vector machine (SVM) with several kernel functions and linear discriminant analysis. The experimental results on Bonn University datasets show that the proposed approach is able to characterise the epilepsy from EEG signals generating up to 100% classification performance by SVM with polynomial kernel.
Frequency Estimation and Tracking for Harmonics Analysis of Power Systems

In this paper,a set of formulas for frequency estimation of multiple frequency signal is deduced and a method of frequency estimation and tracking fo r harmonics analysis of power systems is developed. The set of formulas consists of DFT of sampled data,phase difference calculation and frequency calculation. Frequency tracking means that sampling intervals of following sampling is updat ed according to new frequency estimation,so the synchronous sampling error will be reduced step by step. The method can provide very high accurate for real tim e harmonics analysis of power signal and it's computation is very simply. Matla b simulations show efficiency of the method.
Information System and its implications on organizational performance: Human Resource as the key Efficiency Determinant

Information System aims to provide accessible and understandable information that is reliable and complete for the users of the system in a timely manner. Key Efficiency Determinants for Information System (IS) are classified into three major categories i.e. Human Resource (HR) such as Information System Personnel Skills & Information System Human Resource Specialty; IT Infrastructure Flexibility such as platform, network, data & applications sophistications; and Effective Relationship such as the relationship of IS unit with vendors and service providers. Amongst those human resource plays an important role as from decision makers to the operational level humans play the major role to interact with the Information Systems. It was found that most important efficiency determinant for IS is Human Resource (HR) that is responsible to operate and manage IS. Currently the commercial banks in Pakistan are investing a handsome capital for IT to make their information systems efficient as the banks can operate their processes effectively and provide the better online services to their clients. This research is based on empirical study of commercial banking sector in Pakistan, which will evaluate the Information System in the context of organizational performance for this we have taken a case study of the commercial banks operating in Sindh Pakistan. However, we have covered other determinants also in our overall research but in this paper we are emphasizing the HR as the backbone of the computer and human interaction and of the human resources available at the banking sector. The overall findings would play an important role according to the objectives of the information systems to make Information Systems working better for the organizations.
Assessing the Probability of Financial Distress in Commercial Banks of India

The present paper attempts to assess the probability of financial distress in 46 Indian commercial banks covering 26 public sector banks and 20 private sector banks for the period of 2005-06 to 2011-12. Using Z-score test for four different ratios namely, working capital to total assets, retained earnings to total assets, earnings before interest and taxes to total assets and equity to total asset, the study finds that all commercial banks in India are distress free except three banks. There is a significant difference in the value of Z-score of public and private sector banks. The study also concludes that there is consistency in the performance of public sector banks while there is much variation in the performance of private sector banks.
Some applications of stochastic process techniques to statistics

Consider a sequence of estimators θ̂n which converges almost surely to θ0 as the sample size n tends to infinity. Under weak smoothness conditions, we identify the asymptotic limit of the last time θ̂n is further than ε away from θ0 when ε → 0. These limits lead to the construction of sequentially fixed width confidence regions for which we find analytic approximations. The smoothness conditions we impose is that θ̂n is to be close to a Hadamard-differentiable functional of the empirical distribution, an assumption valid for a large class of widely used statistical estimators. Similar results were derived in Hjort and Fenstad (1992, Annals of Statistics) for the case of Euclidean parameter spaces; part of the present contribution is to lift these results to situations involving parameter functionals. The apparatus we develop is also used to derive appropriate limit distributions of other quantities related to the far tail of an almost surely convergent sequence of estimators, like the number of times the estimator is more than ε away from its target. We illustrate our results by giving a new sequential simultaneous confidence set for the cumulative hazard function based on the Nelson–Aalen estimator and investigate a problem in stochastic programming related to computational complexity.
Improving transaction acceptance of incoherent updates using dynamic merging in a relational database

Despite its tenure, mobile computing continues to move to the forefront of technology and business. This ever expansive field holds no shortages of opportunity for either party. Its benefits and demand are abundant but it is not without its challenges. Maintaining both data consistency and availability is one of the most challenging prospects for mobile computing. These difficulties are exacerbated by the unique ability of mobile platforms to disconnect for extended periods of time while continuing to function normally. Data collected and modified while in such a state poses considerable risk of abandon as there exists no static algorithm to determine that it is consistent when integrated back to the server. This thesis proposes a mechanism to improve transaction acceptance without sacrificing consistency of the related data on both the client and server. Particular consideration is placed towards honoring data which a client may produce or modify while in a disconnected state. The underlying framework leverages merging strategies to resolve conflicts in data using a custom tiered dynamic merge granularity. The merge process is aided by a custom lock promotion scheme applied in the application layer at the server. The improved incoherence resolution process is then examined for impacts to the fate of such transactions and related bandwidth utilization.
The Dynamic Scheduling of a Distributed Workflow Management System FlowAgent

Real enterprise processes require WFMS (workflow management system) to run under heterogeneous environments involving human and automated tasks distributed across enterprises. But most of the WFMSs are based on traditional centralized DBMS, and constructed under the limitation of static organization structure. FlowAgent develops its own way to realize dynamical task scheduling logic, and a federation structure for enterprise processes.
Application of Improved SIR Model in Information Transmission in Social Networks

Based on the analysis of social network structure,this paper introduces the hot transmission node into network,and proposes an information transmission model based on the improved SIR model,which is simulated with the data-based Tumblr social network.The simulation results show that with the decrease of immune probability and the increase of contact between the Internet marketers or ordinary information disseminators and those easily infected,the information transmission scope and velocity in the network will be enhanced to some degree.Without artificial control,the information will be disseminated to a vast majority of the users in a specific social network.The improved information transmission model can reveal the inherent law of information transmission in social network more accurately.
Numerical and Analytical Aspects of POD-Based Reduced-Order Modeling in Computational Fluid Dynamics

This thesis studies projection-based reduced-order models (ROMs) in the context of computational fluid dynamics. Proper Orthogonal Decomposition (POD) is employed to compute the reduced-order basis from snapshots, which are assumed to represent the finite element solution of a partial differential equation. All investigations involve either convection-diffusion-reaction equation or the incompressible Navier–Stokes equations. The main contribution of the thesis can be divided into three parts. Firstly, a Streamline-Upwind Petrov–Galerkin reduced-order model (SUPG-ROM) is investigated theoretically and numerically for convection-dominated convection-diffusionreaction equations. Numerical analysis is utilized to propose the scaling of the stabilization parameter for the SUPG-ROM. Two approaches are used: One based on the underlying finite element discretization and the other one based on the POD truncation. The resulting SUPG-ROMs and the standard Galerkin ROM are studied numerically on several convection-dominated test problems aiming at answering several questions. One of the choices for the stabilization parameter is recommended. Secondly, an alternative approach for the computation of the ROM initial condition is derived for problems, for which the standard approach, that is usually used in the literature, results in the ROM initial condition being polluted by spurious oscillations. The principal idea of the method consists in modifying the conventional ROM initial condition in a post-processing step by a filtering procedure. Numerical studies are performed in order to investigate the influence of the filtered initial condition on the ROM results. With respect to the minimum and maximum values of the ROM solution, which characterize the underand overshoots, ROM results could be partly significantly improved compared to the results obtained with the standard ROM initial condition. Thirdly, three velocity-pressure reduced-order models (vp-ROMs) for incompressible flows are investigated numerically. One method computes the ROM pressure solely based on the velocity POD modes, whereas the other two ROMs use pressure modes as well. One of the latter methods denoted by SM-ROM is developed within the framework of this dissertation. Moreover, the impact of the snapshot accuracy as well as of utilizing different linearization techniques on the ROM results is investigated numerically. Based on weakly divergence-free velocity snapshots, SM-ROM could reproduce the results of the finite element simulations in many cases better than the other vp-ROMs. Together with the fact that SM-ROM does not need any specification of additional pressure boundary conditions, which is required in the other methods, SM-ROM can be considered to be superior to other vp-ROMs for the computation of the ROM pressure.
The Impact of Employees Capabilities on Organizational Legitimate Interest

This study tried to identify the impact of organizational policies, employee’s capability, organizational behavior and employee’s altruism on organizational legitimate interest in textile sector. Organizational policies, employee’s capability and organizational behavior had significant relationship at organizational level. Convenience sampling is used as the sampling strategy. This survey is based on questionnaire and data is collected from 120 top and middle level managers of textile sector organizations located in Faisalabad. This study will provide a guideline to numerous leaders or managers in considering the fusion to enhance legitimate interest. Results reveal that if leader’s instrumental and expressive traits will be higher, and then organizational legitimate interest will also be high. To analyses the data, SPSS version 21.0 is used. To check the relationship between the variables correlation and regression analysis is used to check the cause and effect relationship among all variables. As a result, all the hypotheses showed significant results.
Centralized versus Decentralized Banking: Bank-level evidence from U.S. Call Reports

This paper demonstrates that decentralized banking has been the primary model of banking in the US since the mid-90s. This evidence is obtained by using a large number of bank-level observations from US Call Reports. The ownership structure that I infer from these data allow me to use a unique identification strategy to determine the independent effects of subsidiary-specific and owner-specific financial conditions (decentralized and centralized effects, respectively) on subsidiaries’ lending. The results show that subsidiaries financial conditions were, in general, more important for lending decisions than those of its owners. In other words, decentralized banking is more pronounced than centralized banking. Considering a broad set of factors that have a systematic effect on financial markets, I also find that the effects of these push factors on subsidiary lending mainly feed through the financial conditions of the subsidiaries and not their owners.
Innovations in Finance as Regulators Push Open Banking - Understanding innovative processes and market change in the Swedish banking market as of payment services directive 2

Digital technologies are transforming each layer of every stack in society. Within the financial industry, authorities in the EU and in Sweden believe that the development of digital technologies is being held back. Competitive authorities urge for the industry to provide better products, increased customer choice and higher price competition. One regulation that aims toward enhancing innovation within banking in Europe is the directive payment services directive 2 (PSD2), introduced in 2018. PSD2 requires banks to enable external parties to use their account services, and transaction services, through technical APIs. Banks’ compliance of PSD2 is sometimes referred to as open banking. The purpose of this report is to, from an academic perspective, explore the market changes in Sweden as of PSD2 and open banking. Specific theory related to technologies, and more general theory applicable on market change, disruption, and innovation, is used. Further, disruptive tendencies toward incumbent banks are analyzed. The study shows that there are reasons to believe that the industry has moved to an un-optimal state in terms of innovation, and that PSD2 can partly move it to a more efficient state. It shows strong incentives for collaborations between FinTechs and banks post PSD2 and open banking, based on utilizing each other’s strengths to enhance value offerings toward end consumers. The research concluded that there are no direct disruptive effects of PSD2 and open banking. However, PSD2 and open banking lowers the efforts for a business to configure itself as a marketplace bank. While incumbent banks rely on providing their own provision services and loans on their “platforms”, marketplace banking subjects these services to competition on a non-discriminating platform and thus potentially offers higher value to end customers. A conclusion is that the business model of marketplace banking has disruptive qualities.
Microstructure Representations: Applied Computer Vision Methods for Microstructure Characterization

Recent advances in computing power and automated microstructural image acquisition have opened the doors to data-driven quantitative microstructure analysis. Extraction of salient microstructure features is a crucial enabling component in this rapidly developing field of research; in the past decade the computer vision community has made enormous progress in this area, much of which has gone relatively unexplored by the quantitative microstructure analysis community. This dissertation explores applications of image texture recognition algorithms to engineer efficiently computable generic microstructure descriptors, enabling quantitative microstructure comparisons between and across a wide variety of materials systems. The literature review serves as a broad, high-level introduction for the materials scientist to some of the major themes in image recognition, along with some brief discussion of their relationship to contemporary microstructure science. After establishing that these image texture recognition algorithms can be effectively applied to classify diverse microstructure datasets, I begin to explore novel materials science applications. These include characterization and qualification of powder materials, exploratory analysis of large microstructure datasets, and extraction of quantitative relationships between materials processing and properties metadata and microstructural image features. The fusion of microstructure image analysis and contemporary machine vision techniques will facilitate development of robust autonomous microscopy systems, and may support quantitative engineering standards for complex hierarchical microstructure systems.
Implementation Innovation and Value Creation in Improving Business Performance Muslim Fashion

The development of Muslim fashion business in Indonesia continues to increase. The data shows, the number of Muslim fashion people in business, especially in West Java province also continues to grow, but its performance fluctuates. This research, purpose to reveal the effect of applying innovation on business performance through value creation. This research used a descriptive survey method with verification approach through Partial Least Square (PLS) analysis. This research used 30 women's fashion Muslim entrepreneur sample in West Java Province. This research has resulted that there is significant influence between innovation applied to business performance through value creation.
Withholding-tax non-compliance: the case of cum-ex stock-market transactions

This paper explores withholding-tax non-compliance in the context of dividend taxation. It focuses on a specific type of stock-market transactions around ex-dividend dates, so-called “cum-ex” trades, which caused considerable revenue losses due to illegitimate tax refunds in Germany and other countries. We use a stylized model of the stock-market equilibrium to analyze the incentives of traders on the German stock market and find that cum-ex trades are only profitable for both buyer and seller in the presence of collusive tax fraud. Our empirical analysis of market data for publicly traded German stocks from 2009 to 2015 confirms that transaction numbers of stocks suitable for cum-ex trades show the expected increase shortly before ex-dividend dates in the period before the tax refunding was reformed. In line with the collusion hypothesis, effects on stock-market prices are not found.
Complex Network Property and Reliability Simulation Analysis of Urban Street Networks

The concepts of average path length,clustering coefficient and degree distribution were firstly introduced into road network analysis;the property of complex network mapping from road network was studied and the road network of Heifei city was demonstrated as an example.Based on the analysis,the reliability of urban road network was discussed by applying complex network theory and Heifei city was taken as an example to simulate and analyze the reliability of road network under selective attacks and random failures,and theirs results show that the road network exhibits different robustness against different failures.The application of the complex network theory into the analyses of urban road networks may extend the research method on urban road networks.
Dynamic Gesture Learning and Recognition Based on the Hermite Neural Network

In order to improve the training speed and identification accuracy,a method of dynamic gesture recognition based on the Hermite orthogonal basis feed-forward neural network is put forward.At first,the CamShift algorithm is used to track trajectories of moving fingertips and the characteristic vector of gesture is extracted as the input of the neural network.Then,a feed-forward neural network which hides the layer neurons is activated by a group of Hermite orthogonal polynomial functions is,and a method to determine the network weights directly and determine the number of hidden layer nodes adaptively is proposed.Finally,gestures based on machine vision are recognized through the trained Hermite neural network.The experimental results show that the Hermite neural network can enhance the speed and precision of network training,improve the learning speed and identification accuracy of gesture recognition and has good robustness and generalization ability.