Miracle-dz/UniFAR-FTUs huggingface dataset:
A system for image-based modeling and photo editing

Traditionally in computer graphics, a scene is represented by geometric primitives composed of various materials and a collection of lights. Recently, techniques for modeling and rendering scenes from a set of pre-acquired images have emerged as an alternative approach, known as image-based modeling and rendering. Much of the research in this field has focused on reconstructing and re-rendering from a set of photographs, while little work has been done to address the problem of editing and modifying these scenes. On the other hand, photo-editing systems, such as Adobe Photoshop, provide a powerful, intuitive, and practical means to edit images. However, these systems are limited by their two-dimensional nature. In this thesis, we present a system that extends photo editing to 3D. Starting from a single input image, the system enables the user to reconstruct a 3D representation of the captured scene, and edit it with the ease and versatility of 2D photo editing. The scene is represented as layers of images with depth, where each layer is an image that encodes both color and depth. A suite of user-assisted tools are employed, based on a painting metaphor, to extract layers and assign depths. The system enables editing from different viewpoints, extracting and grouping of image-based objects, and modifying the shape, color, and illumination of these objects. As part of the system, we introduce three powerful new editing tools. These include two new clone brushing tools: the non-distorted clone brush and the structure-preserving clone brush. They permit copying of parts of an image to another via a brush interface, but alleviate distortions due to perspective foreshortening and object geometry. The non-distorted clone brush works on arbitrary 3D geometry, while the structure-preserving clone brush, a 2D version, assumes a planar surface, but has the added advantage of working directly in 2D photo-editing systems that lack depth information. The third tool, a texture-illuminance decoupling filter, discounts the effect of illumination on uniformly textured areas by decoupling large- and small-scale features via bilateral filtering. This tool is crucial for relighting and changing the materials of the scene. There are many applications for such a system, for example architectural, lighting and landscape design, entertainment and special effects, games, and virtual TV sets. The system allows the user to superimpose scaled architectural models into real environments, or to quickly paint a desired lighting scheme of an interior, while being able to navigate within the scene for a fully immersive 3D experience. We present examples and results of complex architectural scenes, 360-degree panoramas, and even paintings, where the user can change viewpoints, edit the geometry and materials, and relight the environment. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Cerebrospinal fluid levels of total‐tau, phospho‐tau and Aβ42 predicts development of Alzheimer's disease in patients with mild cognitive impairment

Cerebrospinal fluid (CSF) biochemical diagnostic markers may be valuable to help in the diagnosis early in the course of Alzheimer's disease (AD), especially in the phase before clinically overt dementia, i.e. in patients with mild cognitive impairment (MCI). We studied 44 patients with MCI who, at 1‐year follow‐up investigation, had progressed to AD with dementia, and 32 controls. Three CSF biomarkers related to the central pathogenic processes in AD were analysed, including CSF total‐tau (T‐tau) (as a marker for neuronal degeneration), CSF phospho‐tau (P‐tau) (as a marker for hyperphosphorylation of tau and possibly for the formation of neurofibrillary tangles), and CSF Aβ42 (as a marker for Aβ metabolism, and possibly for the formation of senile plaques). At baseline, 35/44 (79.5%) of the MCI patients had high CSF T‐tau, 31/44 (70.4%) high CSF P‐tau, while 34/44 (77.3%) had low CSF‐Aβ42 levels. The positive likelihood ratio was 8.45 for CSF T‐tau, 7.49 for CSF P‐tau and 8.20 for CSF Aβ42. These findings suggest that these CSF‐markers are abnormal before the onset of clinical dementia, and that they may help to identify MCI patients that will progress to AD. CSF diagnostic markers will be especially important when drugs with potential effects on the progression of AD (e.g. γ‐secretase inhibitors) will reach the clinical phase.
A Secured Storage using AES Algorithm and Role Based Access in Cloud

Cloud computing provides lot of advantages such as on demand service, cost effectiveness, elasticity, scalable, pay per use . One of the main drawback of cloud computing is data security . when data migrate to the cloud , is fully controlled by cloud service provider not by the data owner . As a result user data is not secure at the server side.The main contribution of this paper to designed a prototype which uses a encryption technique to store data and Retrieve data using access control . Instead of applying encryption technique to the whole dataset, we are applying attribute based encryption to only any confidential data in the database and the same encrypted data sent to cloud server. Accessing of data by authorized users via access control methods and polices. Finally achieve data confidentiality and integrity in cloud computing.
The Static Eccentricity Fault Diagnosis in Time Domain at Line Start Permanent Magnet Synchronous Motor

Recently, Line Start Permanent Magnet Synchronous Motor have been commonly utilized in industrial areas because of their high efficiency. Motor faults during operation cause losses of production and high maintenance and repair expenditures. In this study, the effect of static eccentricity fault on line start permanent magnet synchronous motor was investigated. The simulation models of motor belonging to healthy and fault status were formed via Finite Elements Method. The analyses in time domain of motor currents under different load conditions were carried out by using these models. When the results of the analyses were investigated, the motor fault was successfully diagnosed via the recommended method.
Pattern recognition of UAV flight data based on semi-supervised clustering

UAV is an unmanned aerial vehicle controlled by a remote radio signal or a trajectory planning software carried itself. It is widely used in military, civil and scientific research fields. However, due to the lack of real-time decision-making ability, the UAV has high fault rate. The flight quality assessment of UAV and the construction of fault prediction model can be used for debugging and fault-removing to customer’s aircraft, and also to increase the added value of the civilian UAV products. Before building a fault prediction model, a very important step is to identify the pattern of sampled data. For each group of flight data, the efficiency and accuracy rate of manual quality evaluation and fault identification are not acceptable. Based on the UAV flight data accumulated in the big data platform of an UAV production company in Shenyang, Liaoning Province of China, this paper proposes a semi-supervised clustering technique to do automatic pattern recognition for the sampling points. According to the characteristics of UAV flight data, two different methods are designed to choose initial centroids. Meanwhile, we use the existing normal flight data to train distance thresholds to combine some clusters to eliminate the resulting error clustering. Real flight data or flight test data with manually added labels are used to run the proposed algorithms to verify the recognition results. The experimental results show that the proposed methods greatly improve the efficiency and accuracy of adding precise labels to the historical flight data and play a role in assisting the manual recognition of sampling points while strengthening the management and statistics.
Limited Feedforward for Channel Estimation in Massive MIMO With Cascaded Precoding

In this paper, we propose a novel channel estimation technique for frequency-division duplex (FDD)-based massive multiple-input multiple-output (MIMO) systems. Cascaded precoding has been adopted in FDD massive MIMO systems in order to reduce the dimension of physical channels so that the traditional channel estimation can be employed over a low-dimensional effective channel. However, due to the lack of a priori knowledge of the downlink channels, traditional channel estimation approaches can hardly achieve the minimum mean-square-error (MMSE) performance. To this end, we propose a limited feedforward strategy for downlink channel estimation based on the parametric model. In the parametric model, the channel frequency responses are represented by the path delays and the corresponding complex amplitudes. The path delays of uplink channels are first estimated and quantized at the base station, then fed forward to the user equipment (UE) through a dedicated feedforward link. In this way, the UE can obtain the a priori knowledge of the downlink channel under the assumption of the reciprocity between downlink and uplink path delays. Our analysis and simulation results show that the limited feedforward method can achieve near-MMSE performance.
PRE-MIGRATORY BEHAVIOUR OF THE PURPLE HERON IN THE NETHERLANDS COMPORTAMIENTO PRE-MIGRATORIO DE LA GARZA IMPERIAL EN LOS PAÍSES BAJOS

—Birds performing long-distance migration without substantial refuelling en route rely on fat reserves accumulated in the post-breeding, pre-migratory period. In order to fill a knowledge gap in the pre-migratory behaviour of purple herons Ardea purpurea, a species conducting a 3,500-4,000 km migration journey within 5-7 days, 12 adult and four juvenile purple herons were equipped with satellite transmitters in The Netherlands. The birds were followed during and after the breeding period until they departed for their migration. Based on the recorded positions, the location and the size of pre-migratory feeding areas were identified, as well as the duration herons used these sites. In addition, the location of and the distance flown to and from night roosts could also be defined. The results revealed that failed breeders started migration at the same time as successful breeders resulting in a longer pre-migratory period. After fledging, juveniles showed an initial “search period” before settling down at a final premigratory site, which resulted in later departure to Africa compared with adults. Most of the duskand daylight period (amounting altogether to 15-18 hours) was spent at the feeding sites. After breeding, most adults remained to use the same feeding areas but switched from sleeping in the colony to night roosts within feeding areas, likely to minimize the daily flight costs. Based on the daily foraging time, the pre-migratory period seems to be sufficient to deposit reserves for a migration journey of several thousand kilometres. Above this, our results generally highlight the importance of high-quality premigratory feeding areas for long-distance migrants without extensive stop-over periods.
Association between Age of Menarche and Premarital Sexual Behavior of Young Adults in Indonesia: Data Analysis of Health Reproductive Survey Indonesia 2012

One of the most crucial periods in a woman's developmental period is entering the age of puberty marked by menarche. Age of menarche can be associated with sexual behavior in which a person with early menarche is at risk for premarital sexual behavior. The aim of this study is to present the interrelation of trade between menarche and premarital sexual behavior and the factors that have affected premarital sexual behavior. This research is used as crosssectional survey. The study population is women whose ages are over 15-24 years. The number of samples are 7,446 women aged adolescents and adults who are not married. The dependent variable in this research is premarital sexual behavior. The results of this study concluded that the average age of menarche women is 13 years old, intimate sexual behavior shows fewer proportions and the majority are those who live in urban areas. There is a relationship between age, education, domicile, and age of menarche with sexual behavior, where age and higher education have a chance of doing premarital sexual behavior.
Bounded Verification of Software Models: Challenges and Opportunities

Ensuring the absence of bugs in a software system is an important but very challenging problem. Early error detection within the development process reduces the cost of finding and fixing defects. Thus, the analysis of software models can improve its final quality and reduce its development costs. A promising research direction in this field is the use of boolean satisfiability (SAT) or constraint programming (CP) solvers to perform bounded verification. Bounded verification consists in formally checking the absence of errors within a finite space defined as a parameter of the analysis. This type of analysis is usually fast in practice and provides informative feedback. However, it is computationally complex in general and lacks conclusive results outside the verification bounds provided as parameters. In this paper, we discuss recent trends and results in the application of bounded verification to a specific field within software engineering: the analysis of models of a software system. Furthermore, we will discuss promising contributions that can build upon previous work to improve its applicability in practice within the software industry.
Web Services Essentials

From the Publisher: As a developer new to Web Services, how do you make sense of this emerging framework so you can start writing your own services today? This concise book gives programmers both a concrete introduction and a handy reference to XML web services, first by explaining the foundations of this new breed of distributed services, and then by demonstrating quick ways to create services with open-source Java tools. Web Services make it possible for diverse applications to discover each other and exchange data seamlessly via the Internet. For instance, programs written in Java and running on Solaris can find and call code written in C# that run on Windows XP, or programs written in Perl that run on Linux, without any concern about the details of how that service is implemented. A common set of Web Services is at the core of Microsoft's new . NET strategy, Sun Microsystems's Sun One Platform, and the W3C's XML Protocol Activity Group. In this book, author Ethan Cerami explores four key emerging technologies: XML Remote Procedure Calls (XML-RPC) SOAP - The foundation for most commercial Web Services development Universal Discovery, Description and Integration (UDDI) Web Services Description Language (WSDL) For each of these topics, Web Services Essentials provides a quick overview, Java tutorials with sample code, samples of the XML documents underlying the service, and explanations of freely-available Java APIs. Cerami also includes a guide to the current state of Web Services, pointers to open-source tools and a comprehensive glossary of terms. If you want to break through the Web Serviceshype and find useful information on these evolving technologies, look no further than Web Services Essentials.
Highly responsive real time token rings

The real-time communications problem is distinguished from the standard nonreal-time problem by the introduction of time. In the nonreal-time setting, it is sufficient to verify the functional correctness of a communications solution along with some notion of aggregate throughput and/or average delay. In the real-time setting, the individual message-level timing requirements are an integral part of the functional correctness. The current state of the art and predominant practice of using Time Domain Multiplexing (TDM) techniques to insure timing correctness tends to result in ad hoc, handcrafted timing solutions which are very hard to modify, upgrade and extend. Further, the deadlines of synchronous communications are guaranteed by relegating asynchronous class messages to a noninterfering, background status. This approach often results in poor system responsiveness. This thesis develops a novel approach for scheduling the IEEE 802.5 and SAE-9B token ring LANs for hard real-time applications that not only guarantees deadlines for synchronous messages, but also dramatically reduces the asynchronous messages' response times. Highly responsive guaranteed service is introduced for alert class asynchronous messages. This algorithmic-based scheduling approach supports a priori determination of system timing correctness for arbitrary synchronous and asynchronous message sets without the costly time-line development, testing and tuning associated with TDM techniques. This capability allows token rings to support dynamic, adaptive and reconfigurable run-time environments. In addition, a new Enhanced Responsiveness Protocol that directly embeds real-time scheduling theory into the media access protocol is developed that offers higher performance than is possible with standard-based methods. These new approaches introduce guaranteed alert class service, and dramatically enhanced asynchronous class message service to LANs. The result is highly responsive real-time rings that can form the backbone of predictable, stable extensible real-time systems.
Development of Smart Technology for Complex Objects Prediction and Control on the Basis of a Distributed Control System and an Artificial Immune Systems Approach

Article history: Received: 07 February 2019 Accepted: 03 May, 2019 Online: 21 May, 2019 This paper is an extension of work originally presented in 2018 Global Smart Industry Conference (GloSIC). Researches are devoted to the development of Smart technology for complex objects control and prediction on the basis of a distributed Honeywell DCS control system of the TengizChevroil enterprise using the example of a technological process of medium pressure gas cleaning. The article describes how on the basis of the multialgorithm approach there was developed a modified algorithm based on modern artificial intelligence methods in order to select informative features (principal component method, Random Forest algorithm, particle swarm algorithm) and artificial immune systems (clonal selection) solving the image recognition problem and predicting the state of a complex control object. There was conducted a comparative analysis of the simulation results using the example of real production data (daily data of sensors from an average pressure absorber).
Robot-Dependent Maps for Coverage and Perception Task Planning

As different mobile robots may increasingly be used in everyday tasks, it is crucial for path planning to reason about the robots’ physical characteristics. This thesis addresses path planning where robots have to navigate to a destination, either for coverage tasks or perception tasks, which we introduce. For coverage tasks, robots target the destination position, whereas for perception tasks a robot has to reach a point from where a target can be perceived.For complex planning problems with multiple heterogeneous robots, it is essential for planning to run efficiently. This thesis introduces robot-dependent maps, which are map transformations that quickly retrieve information related to the feasibility of coverage and perception tasks. The map transformation depends on properties such as footprint, sensing range and field of view. When dealing with perception tasks, this thesis introduces the concept of perception planning, where paths are calculated not only to minimize motion cost but also to maximize perception quality. In order to find optimal paths for the perception of targets, this work uses an informed heuristic search to determine paths considering both motion and perception. Robot-dependent maps are then used to improve theefficiency of perception planning, by providing dominant heuristics that reduce the number of ray castingoperations and node expansion. The use of robot-dependent maps has a low cost that amortizes over multiple search instances. This thesis also provides a novel technique for multi-robot coverage task planning, with the newrobot-dependent maps used as a pre-processing step. The robot-dependent maps are used to improve theperformance of task allocation when splitting tasks among multiple robots. By using a pre-processing phase, the feasibility of coverage tasks is known for each robot beforehand, and estimates on the cost of each robot executing each task can be quickly computed. This thesis contributes an algorithm to calculate paths for multiple heterogeneous robots that need to perceive multiple regions of interest. Clusters of perception waypoints are determined and heuristically allocated to each robot’s path to minimize overall robot motion and maximize the quality of measures on the regions of interest. Overall, this thesis provides techniques that deal with robot heterogeneity mathematically, modeling the individual characteristics, so that path planning takes into account the perception quality as well. Assuming we have multiple robots with different geometries, ranging from different footprints to differentsensors, the planner accounts for those differences when coordinating the robots. This thesis thus explores algorithms for a planner to dynamically adapt and be able to generate path solutions based on the advantages of each robot. We provide theoretic proofs for some of our contributions and evaluate our algorithms on simulations with a variety of 2D obstacle maps and robots with different physical characteristics.
Size Reduction and Performance Enhancement of Pi Shaped Patch Antenna using Superstrate Configuration

Patch antennas are modern elements of today’s world communication technology. They appear to have unique characteristics and features with their unique power with handling capabilities and lighted structure. This paper focuses on superstrate configuration of patch antenna with defected ground plane and Pi Slotted radiating patch. The three different cases were taken in terms of wavelength distance to observe the performance characteristics of patch structure. The antenna designed in this study can be used for S and C band applications.
Relationship between strength of the trunk and flexibility in healthy subjects

The current study was designed to determine whether alteration of trunk muscles strength caused modification of spinal and lower limb flexibility in healthy subjects. The study was based on the examination of 50 subjects (25 men and 25 women). In women, the extensibility of posterior muscles and ligaments, measured by Schober index or finger to floor distance, was weakly but significantly related to isokinetic strength of flexor muscles of the trunk, and was inversely related to isokinetic strength of the extensor muscle. In men, no such relation was indicated. Consequently, when measuring the concentric strength of the trunk extensors, particularly in women, trunk flexibility is a factor that needs to be taken account of.
Rural Tourism : A Gender Approach

Research on the subject of rural tourism and agritourism in the Netherlands has shown that most of the work in this field is done by women. Moreover, without the consent and initiative of the women, no agritourist activities would have been started. In the paper the position of women in agritourist enterprises is understood within the framework of family enterprises. Findings of research are presented on the position of women in tourism enterprises, of which agritourist enterprises are specific examples. The women's position in the enterprise and in the branch organisation are discussed with help of the power relation theory (Giddens, 1981; Komter, 1985), and the `tokenism' theory of Kanter (1977). The findings indicate that the challenge of the renewal of the countryside, plays a major role in the independency and control rural women face when setting up an own enterprise related to the farm.