Miracle-dz/UniFAR-FTUs huggingface dataset:
Programming of Intelligent Service Robots with the Process Model “FRIEND::Process” and Configurable Task-Knowledge

In Alex Proyas’s science fiction movie “I, Robot” (2004) a detective suspects a robot as murderer. This robot is a representative of a new generation of personal assistants that help and entertain people during daily life activities. In opposition to the public opinion the detective proclaimed that the robot is able to follow his own will and is not forced to Isaac Asimov’s three main rules of robotics (Asimov, 1991). In the end this assumption turned out to be the truth. Even though the technological part of this story is still far beyond realization, the idea of a personal robotic assistant is still requested. Experts predicted robotic solutions to be ready to break through in domestic and other non-industrial domains (Engelberger, 1989) within the next years. But up to now, only rather simple robotic assistants like lawn mowers and vacuum cleaners are available on the market. As stated in (Grafe & Bischoff, 2003), all these systems have in common that they only show traces of intelligence and are specialists, designed for mostly a particular task. Robots being able to solve more complex tasks have not yet left the prototypical status. This is due to the large number of scientific and technical challenges that have to be coped with in the domain of robots acting and interacting in human environments (Kemp et al., 2007). The focus of this paper is to describe a tool based process model, called the “FRIEND::Process”1, which supports the development of intelligent robots in the domain of personal assistants. The paper concentrates on the interaction and close relation between the FRIEND::Process and configurable task-knowledge, the so called process-structures. Process-structures are embedded in different layers of abstraction within the layered control architecture MASSiVE2 (Martens et al., 2007). Even though the usage of layered control architectures for service robots is not a novel idea and has been proposed earlier (Schlegel &
Influences of Different Calcinations Ambience on Phase Composition and Morphologies of Ceramic Coatings on Ti Alloy by Micro-Arc Oxidation

Compound ceramic coatings with the main crystalline of Al2TiO5 (as-coated samples) were prepared in situ on the surface Ti-6Al-4V alloy by means of pulsed bi-polar micro-arc oxidation (MAO) in a NaAlO2 solution. The coated samples were calcined in argon and air at 1000 oC, respectively. The phase composition, surface morphology of the ceramic coatings were investigated by XRD, SEM and XRF. The samples were treated in argon and the as-coated ones were calcined in air at 1000 oC to study the anti-oxidation properties of the samples. The results show that Al2TiO5 was decomposed very soon and transformed into α-Al2O3 and rutile TiO2 in air. However, Al2TiO5 was decomposed very slowly in argon and the final coating surface was completely α-Al2O3. Also, the morphology of the ceramic coatings after the calcination was different. The coatings calcined in argon were fined; grains and pores were smaller than those in air. High temperature oxidation occurred very strongly in the TC4 substrate, the weight gains of the as-coated ceramic coatings and the treated ones in argon were nearly changing in the form of parabola, and the weight gains of the coated samples treated in argon were comparatively lower than those of the as-coated samples.
Exploiting Textons Distributions on Spatial Hierarchy for Scene Classification

This paper proposes a method to recognize scene categories using bags of visual words obtained by hierarchically partitioning into subregion the input images. Specifically, for each subregion the Textons distribution and the extension of the corresponding subregion are taken into account. The bags of visual words computed on the subregions are weighted and used to represent the whole scene. The classification of scenes is carried out by discriminative methods (i.e., SVM, KNN). A similarity measure based on Bhattacharyya coefficient is proposed to establish similarities between images, represented as hierarchy of bags of visual words. Experimental tests, using fifteen different scene categories, show that the proposed approach achieves good performances with respect to the state-of-the-art methods.
Topological insulator growth and characterization

viii CHAPTER 1. FUNDAMENTALS OF TOPOLOGICAL INSULATORS . 1 1.
Model of a Sensorless Induction Drive

The paper deals with modeling, simulation and analysis of speed observer for induction drive. Mathematical model of observer is presented and its computer model is elaborated. Speed measurement results are compared with those obtained during simulations with induction motor model. Development and implementation of speed observer requires measurement of motor current and supply voltage. Simulated values of current and voltage are used in the proposed observer model instead of the real ones. Model of induction motor is developed on the basis of motor equations in stationary reference frame. Model of observer relies on nonlinear differential equations, describing performance of induction motor, additionally making use of the space-vector theory. The speed observer developed by means of direct synthesis from state equations is robust with respect to parameter and load variations.
Robust Face Recognition with Deep Multi-View Representation Learning

This paper describes our proposed method targeting at the MSR Image Recognition Challenge MS-Celeb-1M. The challenge is to recognize one million celebrities from their face images captured in the real world. The challenge provides a large scale dataset crawled from the Web, which contains a large number of celebrities with many images for each subject. Given a new testing image, the challenge requires an identify for the image and the corresponding confidence score. To complete the challenge, we propose a two-stage approach consisting of data cleaning and multi-view deep representation learning. The data cleaning can effectively reduce the noise level of training data and thus improves the performance of deep learning based face recognition models. The multi-view representation learning enables the learned face representations to be more specific and discriminative. Thus the difficulties of recognizing faces out of a huge number of subjects are substantially relieved. Our proposed method achieves a coverage of 46.1% at 95% precision on the random set and a coverage of 33.0% at 95% precision on the hard set of this challenge.
Accurate and Efficient Object Tracking Based on Passive RFID

RFID technology has been widely used for object tracking in indoor environment due to their low cost and convenience for deployment. In this paper, we consider RFID reader tracking which refers to continuously locating a mobile object by attaching it with a RFID reader that communicates with passive RFID tags deployed in the environment. One difficulty is that the RFID readings gathered from the environment are often noisy. Existing approaches for tracking with noisy RFID readings are mostly based on using Particle Filter (PF). However, continuous execution of PF has extremely high computational cost, and may be difficult to be done on mostly resource constrained mobile RFID devices. In this paper, we propose a hybrid method which combines PF with Weighted Centroid Localization (WCL) to achieve high accuracy and low computational cost. Our observation is that WCL has the same accuracy with PF with much lower cost if the object's velocity is low. Our method has two critical features. The first feature is adaptive switching between using WCL and PF based on the estimated velocity of the mobile object. The second feature is the further reduction of computational cost by offloading costly PF algorithm onto nearby servers. We evaluate the performance of our method through extensive simulations and experiments in two real world applications, namely, indoor wheelchair navigation and in-station Light Rail Vehicle (LRV) tracking at one of Hong Kong MTR depots. The result shows that our proposed approach has significantly less computational cost than existing PF based methods, while being as accurate as them.
Recent Developments in Robocasting of Ceramics and Multimaterial Deposition

Robocasting is a freeform fabrication technique for dense ceramics and composites that is based on layer-wise deposition of highly loaded colloidal slurries. The process is essentially binderless with less than 1% organics and parts can be fabricated, dried, and completely sintered in less than 24 hours. This overview will highlight recent materials developments for structural applications and modeling of slurry flow. Fabrication of preforms for alumina/metal composites will be discussed as well as techniques for multimaterial deposition in both graded structures and discrete placement of fugitive materials.
Study of Substrate Induced Deep Level Defects in Bulk GaN Layers Grown by Molecular Beam Epitaxy Using Deep Level Transient Spectroscopy

In this paper we have investigated the substrate-induced deep level defects in bulk GaN layers grown on p-silicon by molecular beam epitaxy. Representative deep level transient spectroscopy (DLTS) performed on Au-GaN/Si/Al devices displayed only one electron trap E1 at 0.23 eV below the conduction band. Owing to out-diffusion mechanism; silicon diffuses into GaN layer from Si substrate maintained at 1050°C, E1 level is therefore, attributed to the silicon-related defect. This argument is supported by growth of SiC on Si substrate maintained at 1050°C in MBE chamber using fullerene as a single evaporation source.
Conformance checking of service behavior

A service-oriented system is composed of independent software units, namely services, that interact with one another exclusively through message exchanges. The proper functioning of such system depends on whether or not each individual service behaves as the other services expect it to behave. Since services may be developed and operated independently, it is unrealistic to assume that this is always the case. This article addresses the problem of checking and quantifying how much the actual behavior of a service, as recorded in message logs, conforms to the expected behavior as specified in a process model. We consider the case where the expected behavior is defined using the BPEL industry standard (Business Process Execution Language for Web Services). BPEL process definitions are translated into Petri nets and Petri net-based conformance checking techniques are applied to derive two complementary indicators of conformance: fitness and appropriateness. The approach has been implemented in a toolset for business process analysis and mining, namely ProM, and has been tested in an environment comprising multiple Oracle BPEL servers.
Regulation of DNA Repair Process by the Pro-Inflammatory NF-κB Pathway

Skin is the largest organ of the body. It is organized into three main layers, epidermis, der‐ mis and subcutaneous layer. The epidermis, an outermost avascular layer, is formed by ker‐ atinocytes at the epidermal basal layer that differentiate into corneocytes at the outer layer of the epidermis. The dermis lies below the epidermis separated by a basement membrane and is composed mainly of fibroblasts. The primary function of skin is to constitute an effi‐ cient barrier to protect the organism both from water evaporation and from external aggres‐ sions. Skin is an excellent organ system to study DNA damage and repair since skin is routinely exposed to external and internal aggressors which can induce DNA damage. Sun‐ light is the primary environmental inducer of damage in the skin. In particular ultraviolet radiations (UVR) are known to induce damage on DNA bases by direct absorption of pho‐ tons. Typical damages from the direct effect of UVR are the cyclobutane pyrimidine dimers (CPD) or the 6-4 photoproducts formation both created by dimerization of contiguous pyri‐ midines on the DNA [1]. Sunlight also induces significant damage to skin cells through the generation of Reactive Oxygen Species (ROS) which damage DNA nucleobases and the sug‐ ar phosphate backbone. Depending on the attacking ROS (singlet oxygen and hydroxyl radi‐ cals through the formation of superoxide radicals), different modifications are generated to DNA such as bulky (8-oxoguanosine, as guanine is the most easily oxidized base, thymi‐ dine and cytosine glycol) and non bulky (cyclo purine and etheno adducts) base modifica‐ tions, spontaneous hydrolysis of a normal or damaged nucleobase leading to an abasic site, (See review [2]). Finally ROS may also generate other forms of DNA damage such as single strand breaks (SSB) or double strand breaks (DSB) when the free radical attack is located on the polydeoxyribose chain. Other external aggressors, such as cigarette smoke and pollu‐
The Usage of Association Rule Mining to Identify Influencing Factors on Deafness After Birth

Background: Providing complete and high quality health care services has very important role to enable people to understand the factors related to personal and social health and to make decision regarding choice of suitable healthy behaviors in order to achieve healthy life. For this reason, demographic and clinical data of person are collecting, this huge volume of data can be known as a valuable resource for analyzing, exploring and discovering valuable information and communication. This study using forum rules techniques in the data mining has tried to identify the affecting factors on hearing loss after birth in Iran. Materials and Methods: The survey is kind of data oriented study. The population of the study is contained questionnaires in several provinces of the country. First, all data of questionnaire was implemented in the form of information table in Software SQL Server and followed by Data Entry using written software of C # . Net, then algorithm Association in SQL Server Data Tools software and Clementine software was implemented to determine the rules and hidden patterns in the gathered data. Findings: Two factors of number of deaf brothers and the degree of consanguinity of the parents have a significant impact on severity of deafness of individuals. Also, when the severity of hearing loss is greater than or equal to moderately severe hearing loss, people use hearing aids and Men are also less interested in the use of hearing aids. Conclusion: In fact, it can be said that in families with consanguineous marriage of parents that are from first degree (girl/boy cousins) and 2nd degree relatives (girl/boy cousins) and especially from first degree, the number of people with severe hearing loss or deafness are more and in the use of hearing aids, gender of the patient is more important than the severity of the hearing loss.
Role of dietary restriction in Haemoccult® screening for colorectal cancer

The aim of this study was to investigate the effect of dietary restrictions on the positivity rate and yield of neoplasia during a study based on Haemoccult® screening for colorectal neoplasia. Of 18925 participants who completed Haemoccult tests on a normal diet, 647 (3·4 per cent) were positive. All repeated the test with dietary restrictions: 251 remained positive and underwent further investigations which revealed 35 carcinomas and 169 adenomas in 129 subjects. The remaining 396 were sent a further Haemoccult test at 3 months. Of these, 317 (80·1 per cent) completed the test: 31 (9·8 per cent) were positive. Further investigation of the 31 positive subjects revealed four carcinomas and 20 adenomas. Retesting with dietary restriction will reduce the false positive rate of Haemoccult when used for colonic cancer screening. However, if the retest is negative a further test should be performed. To minimize the adverse effect this may have on compliance, we have allowed an interval of 3 months to elapse before this retest is requested.
NAP: practical fault-tolerance for itinerant computations

One use of mobile agents is support for itinerant computation (D. Chess et al., 1995). An itinerant computation is a program that moves from host to host in a network. Which hosts the program visits is determined by the program. The program can have a pre-defined itinerary or can dynamically compute the next host to visit as it visits each successive host; it can visit the same host repeatedly or it can even create multiple concurrent copies of itself on a single host. Itinerant computations are susceptible to processor failures, communications failures, and crashes due to program bugs. NAP is a protocol for supporting fault tolerance in itinerant computations. It employs a form of failure detection and recovery, and it generalizes the primary backup approach to a new computational model. The guarantees offered by NAP as well as an implementation for NAP in TACOMA are discussed.
An algorithm for map enumeration

Bauer and Itzykson showed that associated to each labeled map embedded on an oriented Riemann surface there was a group generated by a pair of permutations. From this result an algorithm may be constructed for enumerating labeled maps, and this construction is easily augmented to bin the numbers by the genus of the surface the map is embedded in. The results agree with the calculations of Harer and Zagier of 1-vertex maps; with those of Bessis, Itzykson, and Zuber of 4-valent maps; and with those of Ercolani, McLaughlin, and Pierce for $2\nu$-valent maps. We then modify this algorithm to one which counts unoriented maps or Mobius graphs. The results in this case agree with the calculation of Goulden and Jackson on 1-vertex unoriented maps.
GPR Signal Characterization for Automated Landmine and UXO Detection Based on Machine Learning Techniques

Landmine clearance is an ongoing problem that currently affects millions of people around the world. This study evaluates the effectiveness of ground penetrating radar (GPR) in demining and unexploded ordnance detection using 2.3-GHz and 1-GHz high-frequency antennas. An automated detection tool based on machine learning techniques is also presented with the aim of automatically detecting underground explosive artifacts. A GPR survey was conducted on a designed scenario that included the most commonly buried items in historic battle fields, such as mines, projectiles and mortar grenades. The buried targets were identified using both frequencies, although the higher vertical resolution provided by the 2.3-GHz antenna allowed for better recognition of the reflection patterns. The targets were also detected automatically using machine learning techniques. Neural networks and logistic regression algorithms were shown to be able to discriminate between potential targets and clutter. The neural network had the most success, with accuracies ranging from 89% to 92% for the 1-GHz and 2.3-GHz antennas, respectively.
Raman microscopy : developments and applications

G. Turrell, The Raman Effect. G. Turrell, M. Delhaye, and P. Dhamelincourt, Characteristics of Raman Microscopy. M. Delhaye, J. Barbillat, J. Aubard, M. Bridoux, and E. Da Silva, Instrumentation. J. Barbillat, Raman Imaging. M. Truchet, J.-C. Merlin, and G. Turrell, Raman Microscopy and Other Local-Analysis Techniques. P. Dhamelincourt and S-I. Nakashima, Applications to Materials Science. P.F. McMillan, J. Dubessy, and R. Hemley, Applications in Earth, Planetary and Environmental Sciences. M. Truchet, Biological Applications. M. Manfait and I. Nabiev, Applications in Medicine. C. Coupry and D. Brissaud, Applications in Art, Jewelry and Forensic Science. Subject Index. G. Turrell, The Raman Effect: History of the Raman Effect. Mechanim of the Raman Effect. Electromagnetic Radiation and Classical Light Scattering. Molecular Vibrations. The Scattering Tensor. Polarization in Gases and Liquids. Polarication in Crystals. Raman Bandshapes. Resonance Raman Scattering and Fluorescence. Postlog. G. Turrell, M. Delhaye, and P. Dhamelincourt, Characteristics of Raman Microscopy: Excitation Focusing. Collection Optics. Absorbing Samples. Mocroscope-Spectrometer Coupling. Confocal Raman Microscopy. The Confocal Effect. Conclusion. M. Delhaye, J. Barbillat, J. Aubard, M. Bridoux, and E. da Silva, Instrumentation: Characteristics of Laser Sources. Microscope Objectives. Spectral Analyzers. Photoelectric Detectors. Fluorescent Samples. Fiber Optics. A Brief Survey of Digital Signal Processing. J. Barbillat, Raman Imaging: Direct Imaging. Series Imaging. Signal-to-Noise Ratio (S/N) and Collection Time. Hadamard Imaging versus Global Illumination and Line Scanning. Examples of Applications. M. Truchet, J.-C. Merlin, and G. Turrel, Raman Micriscopy and Other Local-Analysis Techniques: Electron Microscopy. Coupling of Raman and electron Microscopies. X-Ray and Raman Microscopy Coupling. Coupling of Secondary Ion Mass and Raman Spectroscopies. Coupling of Laser Mass Spectrometry (LMS, LAMM, LPMS) with the Raman Microprobe. Summary of Coupling with Electron, Ion and X-Ray Microscopies. Microchromatography and Other Separation Methods. Optical Waveguides: Raman Spectra of Films and Adsorbed Species. P. Dhamelincourt and S-I. Nakashima, Applications to Materials Science: Inorganic Solids. Microelectronics and Semiconductors. Polumers and Fibers. P.F. McMillan, J. Dubessy, and R. Hemley, Applications in Earth, Planetary and Environmental Sciences: Practical Aspects. Mineralogy and Petrology. Geochemistry. M. Truchet, Biological Applications: From Histology to Cistology. From Morphology to Analysis. Raman Microanalysis Applied to Bioaccumulations. Trends in Raman Microscopy as Applied to Cells and Tissues. M.Manfait and I. Nabiev, Applications in Medicine: Experimental Conditions for the Raman Microprobe Analysis of Biomedical Samples. Raman Microscopy of Living Cellsa and Chromosomes. Raman Microscopy of Ocular Lenses. Surgace-Enhanced Raman Scattering (SERS) Microscopy. Summary. C. Coupry and D. Brissaud, Applications in Art, Jewelry and Forensic Science: Art Objects. Jewellery. Forensic Science. Subject Index.
The costs of child poverty for individuals and society

• health: physical and mental health, public health issues; • education: including low educational attainment and skill levels; • employment: low status and precarious employment, worklessness and low levels of employability; • behaviour: inhibiting and anti-social behaviour including crime, smoking, substance misuse and suicide; • financial: income, assets and material hardship; • family and personal relationships: including family difficulties, child abuse, local authority care, friendships and social isolation, future relationships and family formation; • subjective well-being: shame, stigma, lack of autonomy and low self-esteem.
Deterministic & Adaptive Non-Submodular Maximization via the Primal Curvature

While greedy algorithms have long been observed to perform well on a wide variety of problems, up to now approximation ratios have only been known for their application to problems having submodular objective functions $f$. Since many practical problems have non-submodular $f$, there is a critical need to devise new techniques to bound the performance of greedy algorithms in the case of non-submodularity. Our primary contribution is the introduction of a novel technique for estimating the approximation ratio of the greedy algorithm for maximization of monotone non-decreasing functions based on the curvature of $f$ without relying on the submodularity constraint. We show that this technique reduces to the classical $(1 - 1/e)$ ratio for submodular functions. Furthermore, we develop an extension of this ratio to the adaptive greedy algorithm, which allows applications to non-submodular stochastic maximization problems. This notably extends support to applications modeling incomplete data with uncertainty.