Miracle-dz/UniFAR-FTUs huggingface dataset:
Scheduled Model Predictive Control of a Wind Tur bine

Through high order aeroelastic simulations in turbulent wind, it has been shown that a Scheduled Model Predictive Controller (SMPC) can successfully control a wind turbine in above rated wind conditions. The SMPC shows the ability to control Multi-Input MultiOutput systems with multiple control objectives, allow for system input constraints and also adjust to the aerodynamic nonlinearities of the turbine system. The implementation of the SMPC is also only as complex as implementing a Linear Model Predictive Controller (LMPC) but provides the benefits of being able to control nonlinear systems with higher performance. Furthermore it has been shown that by using a SMPC the user has the ability to finely tune each controller the SMPC is comprised of giving more tailored performance to various operating regions.
When Harry Resigns Unexpectedly: An Asynchronous Discussion Role-Play for the Online Management Classroom

Management instructors are continually challenged to create learning activities in online courses that duplicate the same opportunities to develop managerial skills afforded to students in traditional face-to-face courses. The purpose of this experiential exercise is to provide online students an opportunity to develop the soft skills all managers need to be successful in the 21st-century workplace. To do this, we use Kolb’s learning cycle theory to guide students through an experiential learning exercise. Specifically, an online and updated version of a previously published exercise is developed to facilitate student learning through demonstrating organizational behavior and leadership concepts in a group role-play. Instructors teaching organizational behavior and/or leadership courses at the undergraduate and graduate levels will find this exercise applicable to their classes and teaching portfolio. Teaching notes and instructions for conducting the exercise are outlined. All materials necessary for successfully conducting the exercise are provided as are student reactions to the experience.
Automated Attendance System Through Eigen Faces Using Image Processing

Eigen faces(PCA) approach for face recognition ,The face is an important part of who you are how people identify you. In face recognition there are two types of comparisons verification and identification. There are about 80 nodal points on a human face here are few nodal points that are measured by software that are distance between eyes ,width of the nose, Depth of the eye socket, Check bones, Jaw line and Chin By this method we can take automatic attendance . face recognition is done by projecting new image onto a low dimensional linear “face space” defined by the Eigen faces. This method is reliable , low cost , faster access and reduce man power.
Mesoscale analysis of a comma cloud observed during FASTEX

A cold‐air comma cloud crossed southern Britain early on 18 February 1997 bringing strong gusts and convective precipitation. Development of the comma cloud occurred in association with a positive upper tropospheric potential vorticity (PV) anomaly. A mesoscale analysis of the comma cloud was carried out using special three‐hourly soundings from UK radiosonde stations together with data from rainfall radar, satellite, NWP model output and a wind‐profiling radar. The analysis reveals that the comma cloud tail was of ana‐form whilst the polar cold front (behind which the comma cloud developed) was kata‐form. Further analysis indicates that the polar cold θw front and the comma cloud front were tending to become one entity at the surface and can thus be considered an example of a kata‐cold front undergoing a partial transition to more of an ana‐form locally in the region of an upper tropospheric positive PV anomaly. Copyright © 2000 Royal Meteorological Society
CEMR: Congestion evasion Multicast Routing to Maximize Throughput for Mobile Ad hoc Networks

This paper is focused on a new solution for congestion evasion in ad hoc multicast routing that referred as Congestion Evasion Multicast Routing short CEMR. CEMR is aimed at Congestion Evasion in Multicast Mobile Ad hoc routing protocol. The current MAC level routing strategy is independent which can work with any multicast routing protocol irrespective of tree or mesh structure. During the study of CEMR performance, the CEMR tested along with On-Demand Multicast Routing Protocol where simulation results proved that CEMR raises the performance of ODMRP in order of magnitude.
Twitter Based Earthquake Alert System

Twitter, a popular microblogging service, has received much attention recently. We investigate the real-time interaction of events such as earthquakes. Propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features such as the keywords in a tweet, the number of words, and their context. we produce a probabilistic spatiotemporal model for the target event that can find the center and the trajectory of the event location. We consider each Twitter user as a sensor and apply Kalman filtering and particle filtering. The particle filter works better than other compared methods in estimating the centers of earthquakes and the trajectories of typhoons. As an application, we construct an earthquake reporting system in Japan. Our system detects earthquakes promptly and sends e-mails and SMS alerts to registered users. Notification is delivered much faster than the announcements that are broadcast by the JMA.
Construction Of Lyapunov Functions For Some Fourth Order Nonlinear Ordinary Differential Equations By Method Of Integration

In giving adequate attention to some qualitative properties of solutions in ordinary differential equations, Lyapunov functions is quite indispensable. The process of tackling some problems in the application is the construction of appropriate Lyapunov functions for some nonlinear fourth order differential equation. Our focus is finding V(x), a quadratic form and positive definite also finding U(x) which is positive definite such that the derivative of V with respect to time would be equal to the negative value of U(x) In this work, we adopted the pre-multiplication of the given differential equation by x and thereafter we integrated with respect to t form 0 t  to t T  . We obtained a Lyapunov function candidate for a fourth order differential equation or its scalar equation.
Design of a Wireless Fingerprint Authentication Service Platform Using the SOPC Technology

Fingerprint authentication is becoming an important security requirement in various embedded systems. While traditional identification method, user ID plus password cannot satisfy users’ needs due to various defects, they are increasingly being replaced by biometric technologies such as fingerprint, face, and voice recognition, which are known to provide higher levels of security for user authentication. In this paper, an effective wireless fingerprint authentication system is presented. We designed the wireless fingerprint authentication based on Altera's Nios II processor. The whole system design includes real-time fingerprint image collection, image preprocessing, feature extraction, matching processes, a database and wireless transmission.
User Review Sentiment Classification and Aspect Extraction

Online User reviews is a great platform for collecting large volume of information for sentiment analysis. Here we propose an system which classifies the user reviews into two main categories: Positive and Negative reviews. The Classification algorithm uses only the overall review scores to understand sentiment behind each review and extract the important aspects about the product. We developed an efficient classifier model to classify the provided review is either a positive review or negative review by analysing the performance of various classification algorithm on the review data corpus. Clustering techniques are then used to identify key sentiment characteristics to provide them to the users, which helps the user to understand the aspects of the products/service they wish to buy or experience.
Syllable-based Korean POS Tagging Based on Combining a Pre-analyzed Dictionary with Machine Learning

This study is directed toward the design of a hybrid algorithm for syllable-based Korean POS tagging. Previous syllable-based works on Korean POS tagging have relied on a sequence labeling method and mostly used only a machine learning method. We present a new algorithm integrating a machine learning method and a pre-analyzed dictionary. We used a Sejong tagged corpus for training and evaluation. While the machine learning engine achieved eojeol precision of 0.964, the proposed hybrid engine achieved eojeol precision of 0.990. In a Quiz domain test, the machine learning engine and the proposed hybrid engine obtained 0.961 and 0.972, respectively. This result indicates our method to be effective for Korean POS tagging.
optimization of vehicle routing on road network

The optimization of vehicle routing is a process of restricting the total traveling time in a time window constraint and is also accountable for restricting the total cost due to the total traveling distance. In order to get an optimized route, an efficient algorithm is devised known as GSA (Graph Search Algorithm). The various queries have been employed in locationbased systems such as KNN, Path Query and Keyword-based KNN. The role of fuzzy logic is to calculate the distance of available routes and dynamically adjust the crossover rate and mutation rate occurring in the road network. The use of genetic algorithm escalates in selecting the best possible route among various available routes by taking into consideration the road and traffic conditions. A number of benchmark problems are scrutinized for their search performance to demonstrate the potency of the algorithms used. Also, various search methods are acquired in order to compare with the GSA such as branch and bound, standard GSA, simulated annealing and tabu search. The overall comparison is done over randomly selected data sets. The results if the simulation reveals clearly that GSA outperforms other search methods.
Perceptual graphic rendering and quality evaluation

Computer graphics are widely used in various areas nowadays, such as entertainment, industry design, education, architecture and scientific visualization. Graphic rendering is the process of displaying 3D models visually as 2D images. An important issue in graphic rendering is to improve the rendering efficiency. Since the ultimate evaluator of the realistically rendered images is the human visual system (HVS), it is meaningful to substantially decrease computational, storage and transmission cost by exploiting perceptual properties of the HVS without degradation of perceived rendering quality. To design a perceptual rendering system, we need to consider two processes: one is how to build computational models of the characteristics of the HVS; the other is how to incorporate these models into the rendering process. In this work, we explore both the two processes for three schemes in graphic rendering. Firstly, we propose a new visual saliency based perceptual rendering scheme. In general, a scene has one or more salient objects, and the visual attention of observers is attracted by the salient objects. This property of the HVS allows us to decrease computational resources in non-salient objects without degrading the perceived rendering quality. Different from existing work in saliency-based perceptual rendering which use visual saliency as the
Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing

2014 has been another incredible year for Ubiquitous Computing, as body worn, mobile, sensor rich technologies pervade every aspect of our daily lives and the augment the infrastructures and environments we inhabit, and instigates changes in our societies. Such technologies both enable new practices and behaviours, but also challenge us to consider the role and impact of such technologies are having on our lives, and even to question our very rights and entitlements. This year's program reflects the full gamut of these endeavours, from fundamental techniques in sensing, activity recognition, and security on mobiles, to focused interventions in healthcare and for specialist applications. We are particularly delighted to welcome our keynote, Gaetano Borriello, who's work on Open Data Kit is leading to new Applications of Mobile Devices in the Developing World, inspiring us to think how we might transform lives using ubiquitous technologies within our own work.
An Approximate Differentiation Method of Inverse Simulation based on a Continuous System Simulation Approach

Inverse simulation techniques allow inverse solutions to be found for a range of problems involving dynamic systems described by sets of linear or nonlinear ordinary differential equations. Techniques in common use generally involve iterative solutions based on discretised descriptions but continuous system simulation tools can also provide solutions and are often simpler to apply and computationally more efficient. This paper presents a method of inverse simulation which involves use of a very simple, but effective, approximation for derivative terms within the model. Discussion of results for linear and non-linear examples leads to the conclusion that this technique can be applied to a wide range of dynamic models that are of practical importance for engineering applications.
NuSTAR Observations of the Accreting Atolls GX 3+1, 4U 1702-429, 4U 0614+091, and 4U 1746-371

Atoll sources are accreting neutron star (NS) low-mass X-ray binaries. We present a spectral analysis of four persistent atoll sources (GX 3+1, 4U 1702−429, 4U 0614+091, and 4U 1746−371) observed for ∼20 ks each with NuSTAR to determine the extent of the inner accretion disk. These sources range from an apparent luminosity of 0.006–0.11 of the Eddington limit (assuming the empirical limit of 3.8 × 1038 erg s−1). Broad Fe emission features shaped by Doppler and relativistic effects close to the NS were firmly detected in three of these sources. The position of the disk appears to be close to the innermost stable circular orbit (ISCO) in each case. For GX 3+1, we determine (90% confidence level) and an inclination of 27°–31°. For 4U 1702−429, we find a and inclination of 53°–64°. For 4U 0614+091, the disk has a position of and inclination of 50°–62°. If the disk does not extend to the innermost stable circular orbit, we can place conservative limits on the magnetic field strength in these systems in the event that the disk is truncated at the Alfvén radius. This provides the limit at the poles of B ≤ 6.7 × 108 G, 3.3 × 108 G, and 14.5 × 108 G for GX 3+1, 4U 1702−429, and 4U 0614+091, respectively. For 4U 1746−371, we argue that the most plausible explanation for the lack of reflection features is a combination of source geometry and strong Comptonization. We place these sources among the larger sample of NSs that have been observed with NuSTAR.
Quantization issues in signal processing & control system design

Abstract Many interesting design problems encountered in signal processing and control turn out to depend on a set of decision variables that can only take a finite number of values, i.e., they are quantized. For example, in power distribution networks there are only a finite number (typically small) of generators and possible transmission options. Other examples abound in many fields, e.g., on-off control problems, quantization of audio signals for CD-production, filter banks for audio and video compression, switch-mode power supplies used, e.g., in laptop computers, and so on. All of these problems share the common feature that the decision space is quantized. The associated design problems require special attention since they are inherently “nonconvex” in a technical sense. This paper gives an overview of quantization issues in signal processing and control and points to recent research aimed at providing designs that can be utilized in practice
Spyder: a reconfigurable VLIW processor using FPGAs

A processor with multiple reconfigurable execution units has been designed and implemented. The reconfigurable execution units are implemented using reprogrammable field programmable gate array (FPGA) chips. The architecture and implementation of this processor are described in detail. An example shows that this reconfigurable processor is able to compute the new state of 100'000'000 cells of Conway's game of life per second with a clock speed of 6.25 MHz. <<ETX>>
The representation of association semantics with annotations in a biodiversity informatics system

A specialized variation of associations for biodiversity data is defined and developed that makes the capture and discovery of information about biological images easier and more efficient. Biodiversity is the study of the diversity of plants and animals within a given region. Storing, understanding, and retrieving biodiversity data is a complex problem. Biodiversity experts disagree on the structure and the basic ontologies. Much of the knowledge on this subject is contained in private collections, paper notebooks, and the minds biologists. Collaboration among scientists is still problematic because of the logistics involved in sharing collections. This research adds value to image repositories by collecting and publishing semantically rich user specified associations among images and other objects. Current database and annotation techniques rely on structured data sets and ontologies to make storing, associating, and retrieving data efficient and reliable. A problem with biodiversity data is that the information is usually stored as ad-hoc text associated with non-standardized schemas and ontologies. This research developed a method that allows the storage of ad-hoc semantic associations through a complex relationship of working sets, phylogenetic character states, and image annotations. MorphBank is a collaborative research project supported by an NSF BDI grant (0446224 - $2,249,530.00) titled " Web Image Database Technology for Comparative Morphology and Biodiversity Research". MorphBank is an on-line museum-quality collection of biological images that facilitates the collaboration of biologists from around the world. This research proves the viability of using association semantics through annotations of biodiversity informatics for storing and discovery of new information.
Finding people, papers, and posts: Vertical search algorithms and evaluation

There is a growing diversity of information access applications. While general web search has been dominant in the past few decades, a wide variety of so-called vertical search tasks and applications have come to the fore. Vertical search is an often used term for search that targets specific content. Examples include YouTube video search, Facebook graph search, Spotify music recommendation, product search, expertise retrieval, and scientific literature search. In a vertical search application, typically, some background knowledge is available about the context in which search is taking place. We may know something about the user population, about the tasks they wish to perform, about their information needs, and about the information objects in the collection we make available to them. This knowledge can inform adaptation of retrieval algorithms and evaluation methodology, to provide a better ranking of information objects, or to organize search results more effectively. This dissertation showcases the need, as well as many opportunities, to leverage background knowledge in three vertical search scenarios: finding people, finding scientific papers, and finding microblog posts. Its five research chapters provide pointers on how background knowledge may be used to help understand user information needs, organize search results, evaluate retrieval algorithms, and automatically generate ground truth.
Uniform repeater insertion in RC trees

Repeater insertion can be used to overcome the quadratic increase in the time required for a signal to propagate through an RC interconnect. A new timing model, based on short-channel I-V equations, has been developed to characterize the signal delay through a resistive line. These analytical expressions provide the foundation for algorithms used to insert uniform repeaters into RC tree structures. Both local and global optimization algorithms for repeater insertion are presented. While the local optimization algorithm provides a computationally fast solution to the repeater insertion problem, the resulting circuit implementation is less power, area, and speed efficient than applying global optimization techniques. The global optimization algorithm for repeater insertion is achieved through the downhill simplex method. The circuit equations, algorithms, and software implementation of this repeater insertion system are presented in this paper. Results from these insertion methodologies improve delay from 25% to 60% versus typical cascaded buffer methodologies. Global repeater insertion further decreases delay times by up to 22% over the local repeater insertion method. The accuracy of the timing model characterizing the repeater insertion process as compared to SPICE simulations is generally within 10%. Applications of these algorithms for minimizing the signal delay through an RC tree, such as in data paths, and targeting signal delays through an RC tree, such as in clock distribution networks, are also discussed.
Addressing security in safety projects – experiences from the industry

Security and cybersecurity has become familiar to everyone. Nevertheless, security is still something that often denoted as not applicable when companies are developing or operating programmable electronic safety systems. In this fast abstract we try to point of some of the reasons to why it is like that, and discuss the problems by both believing there are no reasonable foreseeable security threats, and by believing that every thinkable attack can hit you. We also describe how we as consultancy try to address security in safety projects, and how guidance address the challenge. Finally, we point to the role of system owners that manage to set up clear expectations to include and integrate both safety and security.
The Impact of the Pattern-Growth Ordering on the Performances of Pattern Growth-Based Sequential Pattern Mining Algorithms

Sequential Pattern Mining is an efficient technique for discovering recurring structures or patterns from very large datasetwidely addressed by the data mining community, with a very large field of applications, such as cross-marketing, DNA analysis, web log analysis,user behavior, sensor data, etc. The sequence pattern mining aims at extractinga set of attributes, shared across time among a large number of objects in a given database. Previous studies have developed two major classes of sequential pattern mining methods, namely, the candidate generation-and-test approach based on either vertical or horizontal data formats represented respectively by GSP and SPADE, and the pattern-growth approach represented by FreeSpan and PrefixSpan.In this paper, we are interested in the study of the impact of the pattern-growthordering on the performances of pattern growth-based sequential pattern mining algorithms.To this end, we introduce a class of pattern-growth orderings, called linear orderings, for which patterns are grown by making grow either the currentpattern prefix or the current pattern suffix from the same position at eachgrowth-step.We study the problem of pruning and partitioning the search space followinglinear orderings. Experimentations show that the order in which patternsgrow has a significant influence on the performances.