Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Physical Design for XML Databases

Database systems employ physical structures such as indexes and materialized views to improve query performance, potentially by orders of magnitude. It is therefore important for a database administrator to choose the appropriate configuration of these physical structures (i.e., the appropriate physical design) for a given database. Deciding on the physical design of a database is not an easy task, and a considerable amount of research exists on automatic physical design tools for relational databases. Recently, XML database systems are increasingly being used for managing highly structured XML data, and support for XML data is being added to commercial relational database systems. This raises the important question of how to choose the appropriate physical design (i.e., the appropriate set of physical structures) for an XML database. Relational automatic physical design tools are not adequate, so new research is needed in this area. In this thesis, we address the problem of automatic physical design for XML databases, which is the process of automatically selecting the best set of physical structures for a given database and a given query workload representing the client application’s usage patterns of this data. We focus on recommending two types of physical structures: XML indexes and relational materialized views of XML data. For each of these structures, we study the recommendation process and present a design advisor that automatically recommends a configuration of physical structures given an XML database and a workload of XML queries. The recommendation process is divided into four main phases: (1) enumerating candidate physical structures, (2) generalizing candidate structures in order to generate more candidates that are useful to queries that are not seen in the given workload but similar to the workload queries, (3) estimating the benefit of various candidate structures, and (4) selecting the best set of candidate structures for the given database and workload. We present a design advisor for recommending XML indexes, one for recommending materialized views, and an integrated design advisor that recommends both indexes and materialized views. A key characteristic of our advisors is that they are tightly coupled with the query optimizer of the database system,
Curve length estimation using vertix chain code

Most of the applications in image analysis are based on Freeman chain code. In this paper, for the first time, vertex chain code (VCC) proposed by Bribiesca is applied to improve length estimation of the 2D digitized curve. The chain code has some preferences such as stable in shifting, turning, mirroring movement of image and has normalized starting point. Due to the variety of length estimator methods, we focused on the three specific techniques. First, the way Bribiesca proposed which is based on counting links between vertices; second, based on maximum length digital straight segments (DSSs) and lastly local metrics. The results of these length estimators with the real perimeter are compared. Results thus obtained exhibits that length estimation using VCC is nearest to the actual length.
Fusion of Video and Multi-Waveform FMCW Radar for Traffic Surveillance

Gale, Nicholas. Ph.D., Engineering Ph.D. Program, Wright State University, 2011. Fusion of Video and Multi-Waveform FMCW Radar for Traffic Surveillance. Modern frequency modulated continuous wave (FMCW) radar technology provides the ability to modify the system transmission frequency as a function of time, which in turn provides the ability to generate multiple output waveforms from a single radar unit. Current low-power multi-waveform FMCW radar techniques lack the ability to reliably associate measurements from the various waveform sections in the presence of multiple targets and multiple false detections within the field-of-view. Two approaches are developed here to address this problem. The first approach takes advantage of the relationships between the waveform segments to generate a weighting function for candidate combinations of measurements from the waveform sections. This weighting function is then used to choose the best candidate combinations to form polar-coordinate measurements. Simulations show that this approach provides a ten to twenty percent increase in the probability of correct association over the current approach while reducing the number of false alarms in generated in the process, but still fails to form a measurement if a detection form a waveform section is missing. The second approach models the multi-waveform FMCW radar as a set of independent sensors and uses distributed data fusion to fuse estimates from those individual sensors within a tracking structure. Tracking in this approach is performed directly with the raw frequency and angle measurements from the waveform segments. This removes the need for data association between the measurements from the individual waveform segments. A distributed data fusion model is used again to modify the radar tracking systems to include a video sensor to provide additional angular and identification information into the system. The combination of the radar and vision sensors, as an end result, provides an enhanced roadside tracking system.
Automatic Detection of Face and Facial Features from Images of Neutral and Expressive Faces

Automated analysis of faces showing different expressions has been recently studied to improve the quality of human-computer interaction. In this framework, the expression-invariant face segmentation is a crucial step for any vision-based interaction scheme. A method for detecting facial landmarks from neutral and expressive facial images was proposed. In present study, a particular emphasis was given to handling expressions of happiness and disgust. The impact of these expressions on the developed method was tested using dataset including neutral, happiness and disgust images. The results demonstrated a high accuracy in detecting landmarks from neutral images. However, the expressions of happiness and disgust had a deteriorating effect on the landmark detection.
Adaptive filtering implemented over TMS320c6713 DSP platform for system identification

This paper presents the experimental development of software and hardware configuration to implement two adaptive algorithms: LMS (Least Mean Square) and RLS (Recursive Least Square), using TMS320C6713 DSP platform of Texas Instruments, for unknown systems identification. Methodology for implementation and validation analysis for the adaptive algorithms is described in detail for real-time systems identification applications, and the experimental results were evaluated in terms of performance criterions in time domain, frequency domain, computational complexity, and accuracy.
Extracting Features in Opinion Miningusing Inter Dependent Domain Relevance

Opinion mining is the task of extraction and analyzes the user comments and classifies the reviews, documents into Positive or Negative. It analyzes the user view on several domains such as product, movie, news media, social blogs etc. The automatic extraction of opinion from the old user reviews is more prominent to new users and developer. Normally the opinion mining is carried out in single domain. In multi domain, the extraction of relevant features from the reviews is more difficult. The Inter Dependent Domain Relevance (IDDR) mechanism is extracting the relevant and contrast domain features using domain relevance score. The features are extracted with the help of the Part-Of-Speech (POS) tagging tool. The tool generates the POS of each word in the reviews and the Noun (NN) is considered as Feature. The domain relevance score is used to predict the relevance of those features in the domain. Domain relevance score is calculates with the help of the Dispersion and Deviation. The domain relevance score is greater than the threshold value then the features are selected. The common feature is extracted and important features in that domain are also extracted. The performance of Inter Dependent Domain Relevance is evaluated using two real word domains like Canon S100 and iPod over intrinsic domain relevance and extrinsic domain relevance algorithm.
Towards Robust Visual-Controlled Flight of Single and Multiple UAVs in GPS-Denied Indoor Environments

Having had its origins in the minds of science fiction authors, mobile robot hardware has become reality many years ago. However, most envisioned applications have yet remained fictional—a fact that is likely to be caused by the lack of sufficient perception systems. In particular, mobile robots need to be aware of their own location with respect to their environment at all times to act in a reasonable manner. Nevertheless, a promising application for mobile robots in the near future could be, e.g., search and rescue tasks on disaster sites. Here, small and agile flying robots are an ideal tool to effectively create an overview of the scene since they are largely unaffected by unstructured environments and blocked passageways. In this respect, this thesis first explores the problem of ego-motion estimation for quadrotor Unmanned Aerial Vehicles (UAVs) based entirely on onboard sensing and processing hardware. To this end, cameras are an ideal choice as the major sensory modality. They are light, cheap, and provide a dense amount of information on the environment. While the literature provides camera-based algorithms to estimate and track the pose of UAVs over time, these solutions lack the robustness required for many real-world applications due to their inability to recover a loss of tracking fast. Therefore, in the first part of this thesis, a robust algorithm to estimate the velocity of a quadrotor UAV based on optical flow is presented. Additionally, the influence of the incorporated measurements from an Inertia Measurement Unit (IMU) on the precision of the velocity estimates is discussed and experimentally validated. Finally, we introduce a novel nonlinear observation scheme to recover the metric scale factor of the state estimate through fusion with acceleration measurements. This nonlinear model allows now to predict the convergence behavior of the presented filtering approach. All findings are experimentally evaluated, including the first presented human-controlled closed-loop flights based entirely on onboard velocity estimation. In the second part of this thesis, we address the problem of collaborative multi robot operations based on onboard visual perception. For instances of a direct line-of-sight between the robots, we propose a distributed formation control based on ego-motion detection and visually detected bearing angles between the members of the formation. To overcome the limited field of view of real cameras, we add an artificial yaw-rotation to track robots that would be invisible to static cameras. Afterwards, without the need for direct visual detections, we present a novel contribution to the mutual localization problem. In particular, we demonstrate a precise global localization of a monocular camera with respect to a dense 3D map. To this end, we propose an iterative algorithm that aims to estimate the location of the camera for which the photometric error between a synthesized view of the dense map and the real camera image is minimal.
The slice-timing problem in event-related fMRI

The desiderata for functional neuroimaging are high spatial and high temporal resolution. Recent developments in rapid echo-planar functional resonance imaging (fMRI) and event-related analyses [1,2] combine a spatial resolution of millimetres with a temporal resolution of seconds. A fundamental trade-off remains however: large brain coverage at high spatial resolution requires many, thin image planes (slices), resulting in a longer interscan interval (TR) and hence poorer temporal resolution. Though staggering stimulus times relative to scan times allows a higher effective sampling rate, existing volume-based analysis techniques such as SPM [2] assume simultaneous sampling of all slices. We show that this assumption can result in poor model fits and hence type II errors. Two popular solutions are compared: the use of multiple regressors and the interpolation of data in time.
THE ABDUS SALAM INTERNATIONAL CENTRE FOR THEORETICAL PHYSICS RARE SEGMENTS IN TEMPORAL SIGNALS AND VIDEO RECORDINGS

We can regard temporal record of bio-electrical signal and video as a geometrical object with one more dimension taking into account the temporal evolution of the signal. In this case the video can be regarded as a three dimensional object while the temporal recording of an electrical signal can be regarded as one dimensional geometrical object. One interesting practical and theoretical problem is to find the parts of these figures that differ significantly from all the common parts of the recordings. The deterministic approach for the location of the unusual parts inside the signals and recordings is not feasible, as it needs an exhaustive search in all the parametric space. In this paper we show that by using a modification of our previously developed probabilistic method to find the most unusual part of a 3D digital image, we can find the temporal intervals and areas of interest of the signals/video and mark the corresponding objects that behave in an unusual way. Due to the different dynamics along the temporal and the spatial axes, namely the prevalence of the cylinder-like objects in the video and the pseudo-periodic slowly changing spectral characteristics of the bio-electrical signals, an additional step is needed to treat the temporal axis.
Wall-bounded turbulence at high Reynolds numbers

Measurements are reported that give new insight into the behavior of turbulent wallbounded flows at high Reynolds number. Turbulent pipe and boundary layer flows are examined experimentally over a wide range of Reynolds numbers – up to Reτ = 100, 000 (ReD = 6× 10) in pipe flow, and up to Reτ = 73, 000 (Reθ = 235× 10) in a flat plate zero pressure gradient boundary layer. A Nano-Scale Thermal Anemometry Probe (NSTAP) was developed for very high spatial and temporal resolution measurements. Sensors with wire lengths 30 and 60 μm were fabricated, tested and validated in known flows, and then used to obtain single-point measurements at high Reynolds numbers in pipe and boundary layers. The mean velocity data together with data from previous studies and extensive error analysis showed that the von Kármán’s constant in the log-law is κ = 0.40±0.02. It was shown that the streamwise Reynolds stress exhibits a logarithmic behavior in the inertial sublayer for Reτ ≥ 20, 000, in both pipes and boundary layers. Variances as well as higher order even moments were compared for pipes and boundary layers and it was shown that all even moments have a logarithmic behavior in the inertial sublayer, suggesting a true scale separation. Streamwise turbulent spectra showed a clear k region for up to two decades in wavenumber. No k region was found to be present in any of the cases in the pipe or the boundary layer. The location of the outer spectral peak, associated with very large scale motions, was found to have only a weak dependence on Reynolds number. The loci of these peak occur at the same wall-normal distance where the streamwise stresses establish a logarithmic behavior and where the amplitude modulation coefficient has a zero value. This suggests that with Reynolds number increasing to infinity most of the energy is contained within a diminishing wall-layer in physical coordinates.
The Cycle Time Stochastic Distributions in Simulation of Manufacturing Systems

The paper presents a theme of research through the analysis of flows' modelling and simulation in a flexible manufacturing system. It is studied the simulation with discrete events of a real manufacturing line with the software Delmia Quest. The objectives of this paper are to modelling and simulate the manufacturing system and to choose the properly probability distributions of a cycle time of each machine from this layout. A comparison of three distributions is presented and SCL implemented program will automatically display the values resulting from the manufacturing system simulation.
TCL and the TK Toolkit (Addison-Wesley Professional Computing)

Ousterhout's Tcl and the Tk Toolkit was one of the first books on Tcl (tool command language) and Tk (toolkit) and has become one of the classics in the field. Written by the developer of Tcl and Tk, the text takes a no-nonsense approach to the language, describing the elements of Tcl and Tk in programming-reference-style detail. If you are already familiar with a C-like language and want a just-the-facts introduction to Tcl and Tk, this is the book for you. The manual is divided into four sections: a description of the Tcl language, an introduction to Tk, a discussion of the Tcl/C interface, and information about the Tk/C interface. Although there are no fully worked out programs, code snippets illustrate how to use control structures and data types. Written in 1994, the book is based on Tcl 7.3 and Tk 3.6 and does not cover the most recent versions of Tcl and Tk.
An Influence: Vendor Locking in Meta Cloud

Cost and scalability benefits of Cloud storage services are apparent. However, selecting a single storage service provider limits availability and scalability to the selected provider and may further cause a vendor lock-in effect. In this paper, we present Meta Storage, a federated Cloud storage system that can integrate diverse Cloud storage providers. Meta Storage is a highly available and scalable distributed hash table that replicates data on top of diverse storage services. Meta Storage reuses mechanisms from Amazon's Dynamo for cross-provider replication and hence introduces a novel approach to manage consistency-latency tradeoffs by extending the traditional quorum (N; R; W) configurations to an (NP; R; W) scheme that includes different providers as an additional dimension. With MetaStorage, new means to control consistency-latency tradeoffs are introduced.
Mobile Computing with WirelessLAN and its Modes Ad hoc Network with Challenges

In this paper, we summarized Mobile computing with WirelessLAN and its modes Ad hoc network and infrastructure. We define the operational model of our mobile computing environment, where we plan to demonstrate our proposed solutions. Mobile cloud computing is the combination of both cloud computing and mobile networks to bring benefits for mobile users, network operators, as well as cloud computing providers. In the present mobile communication environment, lot of research is going on, to improve the performance of issues like handoffs, routing etc. Security is another key issue that needs to be considered, when the setup of communication channel is to be set. Wireless local area network (WLAN) security are inherently weak and do not provide adequate security. Newer, more robust, wireless security technologies are being developed but have not had widespread acceptance within corporate information infrastructures. An ad hoc network is a collection of mobile nodes equipped with wireless communication adapters; these nodes dynamically form a temporary network without the need of any existing network infrastructure. Earlier studies on ad hoc networks aimed to propose solutions to some fundamental problems, such as routing, coping with the new challenges caused by network's and nodes' features without taking the security issues into account.
Harmonization and merging of two Italian dependency treebanks

The paper describes the methodology which is currently being defined for the construction of a “Merged Italian Dependency Treebank” (MIDT) starting from already existing resources. In particular, it reports the results of a case study carried out on two available dependency treebanks, i.e. TUT and ISST–TANL. The issues raised during the comparison of the annotation schemes underlying the two treebanks are discussed and investigated with a particular emphasis on the definition of a set of linguistic categories to be used as a “bridge” between the specific schemes. As an encoding format, the CoNLL de facto standard is used.
Enhancing Students' Motivation to Learn Programming by Using Direct Visual Feedback

In several new approaches to interdisciplinary engineering education, students often see the technical subjects such as mathematics and programming as problematic to learn. These technical subjects of concern here are within programming, and image-processing algorithms are used as a means to provide direct visual feedback for learning basic C/C++. The pedagogical approach is within a Problem Based Learning (PBL) framework and is based on dialogue and collaborative learning. At the same time, the intention was to establish a community of practice among the students and the teachers. A direct visual feedback and a higher level of merging between the artistic, creative and technical lectures have been the focus of motivation, as well as a complete restructuring of elements of the technical lectures. The paper will present test results based on over 400 students, gathered over a period of five years. The paper will explain different steps of the new programming courses in detail, and relate students’ test data to each of the initiatives causing the leaps of improvement. Furthermore, the students’ technical abilities and the enhanced balance between the interdisciplinary disciplines of the study are analysed. The conclusion is that the technical courses have attained a higher status for the students. Students now see them as a very important basis for their further study, and their learning results have improved to a satisfactory level from the study board’s point of view.
Physical layer attacks on sensor nodes

The goal of this thesis was to evaluate different academic implementations of cryptographic algorithms for the Mica2 and TelosB sensor nodes and test their resilience against simple and differential power analysis. Weaknesses in physical implementation are exploited in several software packages including TinyPK, EccM and TinyECC. These include a Diffie Helmann key exchange with RSA, an elliptic curve implementation of the same key exchange, and an optimized Elliptic Curve Digital Signature algorithm, respectively. In addition, various modifications of TinyPK and EccM were enacted and evaluated. The results show that providing an implementation secure against this particular class of side channel attack is easy to ensure while maintaining similar performance statistics to the original implementations.