Miracle-dz/UniFAR-FTUs huggingface dataset:
Laudatio for Professor Dr. Wilfried Imrich on the occasion of his 75th birthday∗

Wilfried Imrich was born on May 25th, 1941 in Vienna and so we all have gathered here to express our best wishes on the occasion of his 75th birthday. His childhood fell within the last years of World War II and the years following immediately after the war, which was no easy time for getting up regarding all aspects of life. In 1959 Wilfried began his studies of Mathematics and Physics at the University of Vienna. At this time no Bachelor or Master studies were known at Vienna University, but there was a so-called free scientific study in the classical Humboldtian sense, which directly led to a PhD degree, if after some years of attending lectures you were able to prepare a PhD thesis with new scientific results and to pass a so-called Rigorosum examination on the whole subject of Mathematics and a second discipline. No good system for students who were not gifted enough, but a very good system for students like Wilfried, to be initiated in doing mathematical research as early as possible. Wilfried completed his studies with a thesis on Lattices and Volume in the area of the Geometry of Numbers in 1965 and started to work at the Technical University of Vienna, first as an assistant professor, later on achieving venia docendi in Mathematics and being appointed to associate professor in 1972. In the late sixties Wilfried held a position at New York State University at Albany. This was followed by a semester at Lomonossow University in Moscow and numerous visiting lecturer and researcher positions all over the world up to now. In 1973 he became full professor of Applied Mathematics at the University of Leoben, a position that he held until his retirement in 2009, thus being the professor serving for the third longest period in the history of this university. Wilfried advised several PhD theses in Mathematics and Engineering some of his students are Professors of Mathematics now and he was organizer and coorganizer of numerous national and international scientific conferences and meetings, in particular I would like to mention the Leoben-Ljubljana Graph Theory Seminars, that have become an institution in between.
A Novel Approach For Feature Extraction From RGB-D Data

With the emergence of RGBD image acquisition techniques, there has been a lot of research about various kinds of feature extractions that can be used for the purpose. In this paper, we propose a novel way of feature extraction for RGBD images. Its strength can be gauged from the fact that it gives excellent results (95.4% on category recognition and 86% on instance recognition) without the use of any complex classification technique. Our proposed method of feature extraction, combines Local Binary Pattern, Wavelet transform and Color Auto Corellogram features from RGB data and Principal Component Analysis (PCA) features from its corresponding depth data. This is the first time that PCA has been used for extraction of depth features to give good results. Keywords— Principal Component Analysis; K Nearest Neigbor; RGB, LBP, RGB-D, Wavelet Transform, PCA, Color Auto Corellogram features from RGB data and Principal Component Analysis, feature extraction, classification, computer vision
CHANGING PERCEPTIONS OF THE EXTENT OF DAMAGE TO WELDED STEEL MOMENT FRAMES IN THE NORTHRIDGE EARTHQUAKE

Studies of the post-Northridge inspection reports of welded steel moment frame buildings in Los Angeles are described. The studies show that the distribution of W1 damage as defined by SAC is inconsistent with the distribution of all other non-W1 fracture categories, which strongly suggest that W1's are unrelated to earthquake shaking. With this understanding, an evaluation of the inspection reports reveals that relatively few buildings experienced significant fracturing with approximately 90% of all reported non-W1 occurring in just 27 buildings. The inspection reports also show that visual inspection is a more effective and less expensive method for post-earthquake damage assessment than is ultrasonic inspection.
Protective effect of Ixeris sonchifolia hance injection against endothelial dysfunction in patients undergoing tourniquet ischemia

Objective: To investigate the effects of Ixeris sonchifolia Hance injection (ISHI), a traditional Chinese medicine, on endothelial dysfunction and skeletal muscle injury in patients undergoing tourniquet-induced ischemia reperfusion (IR). Methods: Sixty patients undergoing elective unilateral total knee arthroplasty under epidural anesthesia were randomly assigned into IR+ISHI group or IR group. The patients in IR+ISHI group received intravenous infusion of ISHI 0.6 ml/kg before tourniquet inflation, while same volume of normal saline was given in IR group. Flow-mediated dilation (FMD) value and perfusion index (PI) were measured, serum levels of malondialdehyde (MDA), von Willebrand factor (vWF), nitric oxide (NO), endothelin-1 (ET-1), superoxide dismutase (SOD), creative kinase (CK), CK-MB and lactate dehydrogenase (LDH) activities were also measured respectively prior to anesthesia and 60 min after reperfusion. Results: Compared with baselines, serum levels of MDA, vWF, ET-1, CK, CK-MB and LDH in both groups were significantly increased while SOD activity, NO level, FMD and PI values were decreased at 60 min after reperfusion (P < 0.05). The values of FMD and PI were increased in IR+ISHI group as compared to IR group (P < 0.05), and the changes in serum variables were also attenuated by pretreatment with ISHI. Conclusion: Pretreatment with ISHI could prevent against endothelial dysfunction and attenuate skeletal muscle injury in patients undergoing tourniquet-induced IR.
A New Method for Calculating Word Sense Similarity in WordNet 1

Semantic similarity between word senses is hot topic in many applications of computational linguistics and artificial intelligence, such as word sense disambiguation, information extraction, semantic annotation and ontology learning. Many methods for calculating word sense similarity have been proposed. In recent years the methods based on WordNet have shown its talents and attracted great concern. In the paper, we present a new method in WordNet for calculating word sense similarity, which is noun and is-a relation based. We evaluate our method on the data set of Rubenstein and Goodenough, which is traditional and widely used. The correlation with human judgment is o.8804 in proposed measure, which is more close to human judgments than related works. Experiments show that our new measure significantly outperformed than other existing computational methods.
HISTOGRAM-BASED SMOKE SEGMENTATION IN FOREST FIRE DETECTION SYSTEM

A focus of this paper is a pixel level analysis and segmentation of smoke colored pixels for the automated forest fire detection. Variations in the smoke color tones, environmental illumination, atmospheric conditions and low quality of the images of wide outdoor area make smoke detection a complex task. In order to find an efficient combination of a color space and pixel level smoke segmentation algorithm, several color space transformations are evaluated by measuring separability between smoke and non-smoke classes of pixels. However, exhaustive evaluation of the histogram-based smoke segmentation algorithms in different color spaces suggests that the peak performance is the distinctive feature of the algorithm itself rather than the algorithm-color space combination. Abstract. A focus of this paper is a pixel level analysis and segmentation of smoke colored pixels for the auto- mated forest fire detection. Variations in the smoke color tones, environmental illumination, atmospheric conditions and low quality of the images of wide outdoor area make smoke detection a complex task. In order to find an efficient combination of a color space and pixel level smoke segmentation algorithm, several color space transformations are evaluated by measuring separability between smoke and non-smoke classes of pixels. However, exhaustive evaluation of the histogram-based smoke segmentation algorithms in different color spaces suggests that the peak performance is the distinctive feature of the algorithm itself rather than the algorithm-color space combination.
Mathematical Optimization of Solar Thermal Collectors Efficiency Function Using MATLAB RALUCA LATES

Solar thermal collectors are devices which collect solar radiation, they transform it into heat and they deliver it to a heat exchanger through the heat carrier. The aim of the paper is to make an optimization of their efficiency using MATLAB. The efficiency is expressed as a function of geometric and material parameters which are variable. Some of the parameters are fixed and some vary in certain ranges. The maximum value is found for efficiency which corresponds to the optimal combination of values for the variable parameters. In conclusion comparisons between are made with known values for efficiency given by solar collectors producers. Key-Words: Solar thermal collectors, Efficiency, Optimization, MATLAB, Function, Non-linear minimization
An embedded sigmoidal neural network for modeling of nonlinear systems

This paper discusses the problem of applying sigmoidal neural network to prediction and control of nonlinear dynamical systems. Instead of directly using neural networks as nonlinear models, we first develop a shield based on application specific knowledge, and then embed a sigmoidal neural network model in the shield. An embedded sigmoidal neural network model obtained in this way not only has a structure favorable for certain applications such as controller design, but also has useful interpretation on part of model parameters. Corresponding to the meaningful part and the meaningless part of model parameters, a hierarchical training algorithm consisting of two learning loops is introduced to train the model, which has good performance on solving local minimum problems. The usefulness of the proposed prediction model is demonstrated by applying it to prediction and control of a simulated nonlinear system.
Software implemented hardware fault tolerance

Transient errors in computer systems can cause abnormal behavior and degrade system reliability, data integrity and availability. This is especially true in a space environment where transient errors are a major cause of concern. Fault avoidance techniques such as radiation hardening and shielding have been major approaches to obtaining the required reliability. Recently, unhardened Commercial Off-The-Shelf (COTS) components have been investigated for space applications because of their higher density, faster clock rate, lower power consumption and lower price. Since COTS components are not radiation hardened, and it is desirable to avoid shielding, Software-Implemented Hardware Fault Tolerance (SIHFT) has been proposed to increase the data integrity and availability of COTS systems. This dissertation presents three new SIHFT techniques for error detection: Control Flow Checking by Software Signatures (CFCSS), Error Detection by Duplicated Instructions (EDDI), and Error Detection by Diverse Data and Duplicated Instructions (ED4I). Previously studied software techniques are either inadequate or require assistance from special hardware, but CFCSS, EDDI and ED4I are pure software methods. In CFCSS, signatures are embedded into the program during compilation and compared with run-time signatures during execution. In EDDI, instructions are duplicated at compile-time, and scheduled by exploiting Instruction-Level Parallelism (ILP) to reduce performance overhead. CFCSS and EDDI detect transient errors but not permanent faults. However, in ED4I, a program is compiled to a new program with diverse data so that it can detect a permanent fault. Our fault injection experiment simulating bit flips in memory shows that EDDI provides over 98% fault coverage without any extra hardware. Because of instruction duplication, code size overhead is approximately 100%, but by exploiting ILP, we reduce the performance overhead down to 61% on average. For control flow checking experiment simulating branching faults, CFCSS provides 97% fault coverage. In addition, when we duplicate programs or instructions, we can use ED4I to enhance data integrity in the system. Furthermore, for space experiments, we implemented EDDI and CFCSS in sort and FFT programs running in the ARGOS satellite. During a 136 day period, our techniques detected a total of 198 out of 203 errors, and show 98% error detection coverage.
Ontology-Based Multilabel Text Classification of Construction Regulatory Documents

AbstractIn order to fully automate the environmental regulatory compliance checking process, rules should be automatically extracted from applicable environmental regulatory textual documents, such as energy conservation codes. In the authors’ automated compliance checking (ACC) approach, prior to rule extraction, the text is first classified into predefined categories to only retrieve relevant clauses and filter out irrelevant ones, thereby improving the efficiency and accuracy of rule extraction. Machine learning (ML) techniques have been commonly used for text classification (TC). Nonontology-based, ML-based TC has, generally, performed well. However, given the need for an exceptionally high performance in TC to support high performance in ACC, further TC performance improvement is needed. To address this need, an ontology-based TC algorithm is proposed to further improve the classification performance by utilizing the semantic features of the text. A domain ontology for conceptualizing the environment.
DEGRADATION OF ORGANIC , IRON , COLOR AND TURBIDITY FROM PEAT WATER

This paper evaluates the Fenton process, involving oxidation and settling after coagulation and flocculation for the removal of organic, iron, color and turbidity from peat water. The experiment is to examine the operation condition which can result in the highest removal efficiency. The experimental variables studied include oxidation time, molar ratio of [H2O2]/[Fe], coagulation and flocculation pHs and settling time. The highest removal efficiency is resulted from operation condition of 60 minute oxidation and the coagulation pH of 8. The organic removal efficiency is around 33.40% to 46.86% for oxidation and 53% to 79.66% for settling. The highest removal of 37.92 mg/L organic is resulted from the [H2O2]/[Fe] molar ratio of 4.5. For organic concentration of 26.65 mg/L, the highest removal is resulted from the [H2O2]/[Fe] molar ratio of 3.5. The removal efficiency of iron, color and turbidity by settling process is 99% for all of the [H2O2]/[Fe] molar ratio. In oxidation process, the removal efficiency of iron, color and turbidity are 2% to 4%, 20% to 57%, and 17% to 42% respectively. The experiment results also show that the maximum effect of removing pollutant is occurring on settling process after coagulation and flocculation.
Credit risk mangement in finance : a review of various approaches

Classification of customers of banks and financial institutions is an important task in today’s business world. Reducing the number of loans granted to companies of questionable credibility can positively influence banks’ performance. The appropriate measurement of potential bankruptcy or probability of default is another step in credit risk management. Among the most commonly used methods, we can enumerate discriminant analysis models, scoring methods, decision trees, logit and probit regression, neural networks, probability of default models, standard models, reduced models, etc. This paper investigates the use of various methods used in the initial step of credit risk management and corresponding decision process. Their potential advantages and drawbacks from the point of view of the principles for the management of credit risk are presented. A comparison of their usability and accuracy is also made.
The Application of Chaotic-FM Signal to UWAC System : Theory and Sea Test Results

In order to improve the data rate of long-range underwater acoustic communication (UWAC) system working on low frequency band, a new type of communication mode is presented, that is Chaotic Frequency Modulation (CFM) M-ary mode. Firstly, this paper introduces chaotic sequences into UWAC field. Secondly, the paper studies CFM signal and its good properties. Finally, one sea test is designed to verify its performance. The experimental results are in excellent agreement with theoretical results. The CFM M-ary mode is both feasible and reliable. It can improve the data rate of UWAC system.
Overcoming the difficulties associated with interfacing different simulation programs

In this paper the technique of interfacing transient stability and EMTP programs to achieve a broadband fully digital simulator will be presented. There is fundamental different between the two simulators: the TSP is a phasor-like solution, balanced and without distortion, while the EMTP waveforms can be unbalanced and distorted. The passing of data between the two programs requires some premanipulation (e.g. extraction of fundamental components of waveforms), which also must be done in the real-time environment. Furthermore, the mechanisms involved in the transfer of data lead to time delays, which must be compensated with appropriate prediction routines. We have overcome the main difficulties, and how we did this will be presented in this paper. A verification study was performed in HYPERSIM, where an SSSC was modelled in MATLAB and ported into HYPERSIM, and connected through a real-time interface with a small power system model. Comparisons were made between the hybrid approach (using the interface) with combined networks without the use of an interface.
CROWD ATTRIBUTES RECOGNITION AND ALERTING USING SPARSE RECOGNITION

Human behavior analysis has become a critical area of research in computer vision and artificial intelligence research community. In recent years, video surveillance systems of crowd scenes have witnessed an increased demand in different applications, such as safety, security, entertainment, and personal mental health. Although many methods have been proposed, certain limitations exist, and many unresolved issues remain open. In this work, the proposed novel-temporal sparse coding representation, based on sparse coded features with k-means singular value decomposition for robust classification of crowd behaviors has been considered. Extensive experiments have shown that, with sparsely coded features captured with vital structures of video scenes yields discriminant descriptors for classifications than conventional bag-of-visual-features. Relying on the measurable features of crowd scenes and motion characteristics, it can be used to represent different attributes of crowd behaviors. Experiments on hundreds of video scenes were carried out on publicly available datasets. Quantitative evaluation indicates that, the proposed method display superior accuracy, precision and recall in classifying human behaviors with linear support vector machine when compared with the state-of –the-art methods. The detected image will be processed by a processing unit and then an alert can be send to the authorized person through Gmail. Keywords— Human behavior, crowd scenes, histogram of optical flow, histogram of oriented gradient, artificial intelligence, sparse coding, bag-of-visual features.
Self-synchronization of second order PLLs in communication networks

Synchronous, distributed timing clocks are the basic building blocks in digital communication systems. Conventional systems mainly employ a tree-like network of cascaded timing clocks for synchronous clocking. On the other hand, decentralized, synchronous networks of timing clocks, which have been proposed from a very early stage of the digital communication, are gaining attention in the consumer communication networks and also recently in VLSI clocking. In this paper, we present a theoretical study of synchronous networks of timing clocks consisting of locally connected second order phase-locked loops (PLLs). We find a close connection between the stability properties of the first and second order networks. The particular examples of one way and two way nearest neighbor coupling, with a lag-lead filter and a triangular phase detector (PD) are analyzed in detail. Both the synchronized in-phase solution and the wave-like "mode-lock" solution are examined. A criterion is found for the stability of the one-way coupled network while the two way coupled network is found to be always stable. The existence of a wave-like state is undesirable in synchronizing networks, but may be removed by its destabilization.
THE FIELD ORIENTED CONTROL OF A PERMANENT MAGNET SYNCHROUNOUS MOTOR (PMSM) BY USING FUZZY LOGIC

This project presents the comprehensive performance analysis on the principle of operation, design considerations and control algorithms of the field oriented control (FOC) for a permanent magnet synchronous motor (PMSM) drive system of Fuzzy Logic Controller (FLC) and proportional-integral PI for speed control in closed loop operation. To perform speed control of typical PMSM drives, PI controllers and FOC method are classically used. PI Controller controller suffers from the drawback that for its proper performance, the limits of the controller gains and the rate at which they would change have to be appropriately chosen. Fuzzy based gain scheduling of PI controller has been proposed in which uses in order to overcome the PI speed controller problem. The simulation results show that the proposed FLC speed controller produce significant improvement control performance compare to the PI controller. FLC speed controller produced a better performance than PI speed controller where the overshoot is totally removed and the settling time faster than PI speed controller in achieving desired output speed. The fuzzy algorithm is based on human intuition and experience and can be regarded as a set of heuristic decision rules. It is possible to obtain very good performance in the presence of varying load conditions changes of mechanical parameters and inaccuracy in the process modelling. Research and application of fuzzy logic are developing very rapidly, with promising impacts on electric drives and power electronics in future.
Zone Defense : Why Liberal Cities Build Fewer Houses

In this paper, I investigate a puzzling feature of American urban politics: cities with more liberal residents tend to permit fewer new housing units each year than similar conservative cities. Empirically, I show that this relationship is not attributable to differences in income, demographics, geography, or characteristics of the housing stock. To help explain this puzzle, I develop a formal model of municipal zoning policy. In this model, liberal cities are characterized by generous levels of public goods spending. This, in turn, attracts new households, who have an incentive to construct inexpensive housing. If permitted to do so, the added property tax revenue from these new households would be insufficient to cover their share of public spending. In a spatial sorting equilibrium, any city that offers generous public goods spending must also enact restrictive zoning to defend it.