Miracle-dz/UniFAR-FTUs huggingface dataset:
On the boosting ability of top-down decision tree learning algorithms

We analyze the performance of top? down algorithms for decision tree learning, such as those employed by the widely used C4.5 and CART software packages. Our main result is a proof that such algorithms areboostingalgorithms. By this we mean that if the functions that label the internal nodes of the decision tree can weakly approximate the unknown target function, then the top? down algorithms we study will amplify this weaks advantage to build a tree achieving any desired level of accuracy. The bounds we obtain for this amplification show an interesting dependence on thesplitting criterionused by the top? down algorithm. More precisely, if the functions used to label the internal nodes have error 1/2? as approximations to the target function, then for the splitting criteria used by CART and C4.5, trees of size (1/? )O(1/? 2? 2)and (1/? )O(log(1/? )/? 2)(respectively) suffice to drive the error below? Thus (for example), a small constant advantage over random guessing is amplified to any larger constant advantage with trees of constant size. For a new splitting criterion suggested by our analysis, the much stronger bound of (1/? )O(1/? 2)which is polynomial in 1/? ) is obtained, which is provably optimal for decision tree algorithms. The differing bounds have a natured explanation in terms of concavity properties of the splitting criterion. The primary contribution of this work is in proving that some popular and empirically successful heuristics that are base on first principles meet the criteria of an independently motivated theoretical model.
A system of research dissemination for clinical and counselling psychology

This thesis integrates the reflective components of action research, appreciative inquiry and autobiographical methods. Through the thesis, a model of dissemination of research in the fields of clinical and counselling psychology is presented. Its key components include collaboration and collaborative/relational reflection, appreciative inquiry and the researcher-practitioner/reflective-practitioner framework. Other important elements include collaborations that link research, practice and reflection, the identifying and supporting the development of potential leaders, leading research projects and training and conferences. Public Works such as the “Up Skilling the Specialist Mental Health Workforce in Psychological Practice Skills” and The European Journal of Counselling Psychology are used as foundations for this model. The thesis concludes with action planning for the future as part of the action research and appreciative inquiry forward spirals of planning, action, reflection, planning; this includes developments in the field of independent practice of clinical and counselling psychology.
Diagnosing High-Quality Statistical Machine Translation Using Traces of Post-Edition Operations

This paper proposes a fine-grained flexible analysis methodology to reveal the residual difficulties of a high-quality Statistical Machine Translation (SMT) system. This proposal is motivated by the fact that the traditional automated metrics are not enough informative to indicate the nature and reasons of those residual difficulties. Their resolution is however a key point towards improving the high-quality output. The novelty of our approach consists in diagnosing Machine Translation (MT) performance by making a connection between errors, the characteristics of source sentences and some internal parameters of the system, using traces of Post-Edition (PE) operations as well as Quality Estimation (QE) techniques. Our methodology is illustrated on a SMT system adapted to the medical domain, based on a high quality English-French parallel corpus of Cochrane systematic review abstracts. Our experimental results show that the main difficulties that the system faces are in the domains of term precision and source language syntactic and stylistic peculiarities. We furthermore provide general information regarding the corpus structure and its specificities, including internal stylistic varieties characteristic of this sub-genre.
In Band Full Duplex PLC: The role of the hybrid coupler

In Band Full Duplexing (IBFD) has recently become attractive for power line communications (PLC). In this paper we analyze the role of the first stage of a PLC-IBFD modem: the hybrid coupler. An analytical analysis of its influence on the signal transfer function is performed and some simulations using a measurement database are also included. Possible hardware implementation of a PLC hybrid coupler are finally discussed.
Non-compact topological branes on conifold

We consider non-compact branes in topological string theories on a class of Calabi-Yau spaces including the resolved conifold and its mirror. We compute the amplitudes of the insertion of non-compact Lagrangian branes in the A-model on the resolved conifold in the context of the topological vertex as well as the melting crystal picture. They all agree with each other and also agree with the results from Chern-Simons theory, supporting the large N duality. We find that they obey the Schrodinger equation confirming the wavefunction behavior of the amplitudes. We also compute the amplitudes of the non-compact B-branes in the DV matrix model which arises as a B-model open string field theory on the mirror manifold of the deformed conifold. We take the large N duality to consider the B-model on the mirror of the resolved conifold and confirm the wave function behavior of this amplitude. We find appropriate descriptions of non-compact branes in each model, which give complete agreements among those amplitudes and clarify the salient features including the role of symmetries toward these agreements.
Consensus of Multi-Agent Systems: A Relative-Input-Output Approach

Abstract This paper studies the multi-agent consensus problem of complex networks consisting of general homogeneous continuous linear time-invariant systems with controls under a time-invariant directional communication topology. A new approach based on relative-input-output is proposed to solve the problem. In contrast to a popular method where each agent is equipped with an observer, and hence involving heavy observer dynamics, the proposed approach is static and utilizes relative-input and relative-output eliminating the observers aforementioned, therefore is practically much simpler and easier to implement significantly reducing computational and communicational burdens and costs. Extension of the framework is then made to tackle a dual problem: consensus of distributed filtering without controls. Two numerical examples are provided to validate the proposed approach.
Towards Automatic Registration Of Range Maps

The range map registration (or alignment) phase is the main bottleneck in the 3D scanning pipeline due to the amount of user intervention required. The standard approach to registration consists of an initial rough alignment followed by an automatic refining technique (ICP). Automatic registration is an active research area, since it is the missing component to fully automatise the scanning process. Although many efforts have been made in order to avoid the manual placement, none of the existing technologies seems to be adequately accurate and flexible. This paper addresses the problem of providing a good initial guess to the ICP algorithm, by tracking the 3D-scanner motion using well known (and low cost) computer vision techniques. The proposed technique is shown to be effective and to generate sufficiently accurate guesses in the majority of the possible configurations.
Software architecture design: evaluation and transformation

Since the architecture of a software system constrains the quality attributes, the decisions taken during architectural design have a large impact on the resulting system. An architectural design method is presented that employs iterative evaluation and transformation of the software architecture in order to satisfy the quality requirements. Architecture evaluation is performed by using scenarios, simulation, mathematical modelling and experience-based reasoning. The architecture can be transformed by imposing an architectural style, imposing an architectural pattern, using a design pattern, converting a quality requirement to functionality and by distributing quality requirements. The method has evolved through its application in several industrial projects.
Analysis of Correlation between ICI and Desired Carrier Power in OFDM Systems over Frequency-Selective Ricean Fading Channels under the Influence of Doppler Spread

For data detection in orthogonal frequency division multiplexing (OFDM) systems over mobile wireless channels, the inter-carrier interference (ICI) term arising from Doppler spread is correlated with the desired carrier term. In this paper, we carry out detailed analysis on the power correlation between the ICI and the desired signal term. Explicit closed-form expression for the covariance function of the ICI and the desired carrier power is derived for frequency-selective Ricean fading channels. This expression shows that, in the normal Doppler spread range corresponding to practical vehicular speeds, the ICI power is appreciably correlated with the desired carrier power.
Showcase: A database for standards and patents

Disclosure of essential patents at standard-setting organizations provides a rich source of information that can be used for various research questions related to standards and innovation. Yet this data also has some limitations and its compilation and preparation create challenges. This paper summarizes a number of recent studies using this type of data and discusses recent efforts to create an open database.
Online Fuzzy Self-Adaptive PID Attitude Control of a Sub Mini Fixed-Wing Air Vehicle

An online fuzzy self-adaptive Proportional Integral Derivative (PID) controller is proposed to control the attitude of a sub miniature fixed-wing unmanned air vehicle (SUAV). The vehicle is a complex dynamic system with three rotational DOFs (degrees of freedom) and three translational DOFs. It is the three rotational DOFs that determine the air vehicle attitude in the air. The attitude control is based on the conventional PID control combined with an online fuzzy self-adaptive PID gains regulator which regulates three PID gains according to input error and the change in error, and the controller is realized on MCU system. Simulation and test flights show that the proposed controller enhanced the attitude control performance of the SUAV, such as rapidity, stability, and anti-disturbance.
Building a modular service oriented workflow engine

Current workflow engines, often based on WS-BPEL, are monolithic programs to orchestrate a business process or take part in choreography between partners. They cover aspects like the execution of the workflow description derived from the business process, the communication with external services, and the handling of errors. Both, the communication with services as well as basic error handling are covered by static and internal APIs [S. Modafferi, E. Mussi, and B. Pernici (2006)], and thus provide only simple strictly internal means of interaction with running workflows. Introducing new repair algorithms or self-healing behavior require detailed monitoring and modification of all aspects of a workflow execution thus requiring a modularization of the workflow engine itself. In this paper we will present a modular and service oriented workflow engine. Modularity and service-orientedness are realized by integrating a workflow execution engine with means of logging, repair and possibility to invoke external services through simple Web-based APIs.
Model based RGBD SLAM

In this paper we propose to improve the localization and the 3D mapping provided by an RGBD SLAM algorithm, using a prior knowledge of the 3D model of the environment. The proposed solution relies on an feature-based RGBD SLAM algorithm to localize the camera and update the 3D map of the scene. To improve the accuracy and the robustness of the localization, we propose to combine in a local bundle adjustment process, geometric information provided by a prior coarse 3D model of the scene (e.g. generated from the 2D plan of the building) with RGBD data. The proposed approach is evaluated on a public benchmark dataset as well as on a real scene acquired by a Kinect sensor.
Quantum Coherence in Photosynthetic Light Harvesting

Recent two-dimensional (2D) electronic spectroscopic experiments revealed that electronic energy transfer in photosynthetic light harvesting involves long-lived quantum coherence among electronic excitations of pigments. These findings have led to the suggestion that quantum coherence might play a role in achieving the remarkable quantum efficiency of photosynthetic light harvesting. Further, this speculation has led to much effort being devoted to elucidation of the quantum mechanisms of the photosynthetic excitation energy transfer (EET). In this review, we provide an overview of recent experimental and theoretical investigations of photosynthetic electronic energy transfer, specifically addressing underlying mechanisms of the observed long-lived coherence and its potential roles in photosynthetic light harvesting. We close with some thoughts on directions for future developments in this area.
Robust Speech Recognition: The case for restoring missing features

Speech recognition systems perform poorly in the presence of corrupting noise. Missing feature methods attempt to compensate for the noise by removing unreliable noise corrupted components of a spectrographic representation of the noisy speech and performing recognition with the remaining reliable components. Conventional classifier compensation methods modify the recognition system to work with the incomplete representation so obtained. This constrains them to perform recognition using spectrographic features which are known to be suboptimal to cepstra. In previous work we have proposed an alternative feature-compensation approach whereby the unreliable components are replaced by estimates derived from the reliable components and the known statistics of clean speech. In this paper we perform a detailed comparison of various aspects of classifier -based and feature-based compensation methods. We show that although the classifier -based compensation methods are superior when recognition is performed with spectrographic features, feature-based compensation methods provide better recognition performance overall, since cepstra derived from the reconstructed spectrogram can now be used for recognition. In addition, they have the added advantages of being computationally less expensive and not requiring modificati on of the recognizer.
On the dynamics of parallel manipulators

Studies the dynamics of parallel manipulators. We first have a brief review and discussion on different dynamics formulations in the literature (Newton-Euler, direct Lagrangian, and Lagrange-D'Alembert formulation on the reduced system). Then we show the equivalence of these methods. Based on the concepts from differential manifolds, we prove that away from configuration singularity, there exists a projection from the joint space to parameterize the configuration space. The fact that the dynamics is well defined even at actuators singularity, end-effector singularity and other kinds of parameterization singularity is highlighted. For the method of reduced systems, there are two main drawbacks. Firstly the joints being cut for forming the tree system are presumed to have no external torque. Secondly the force and torque applied to other links of the manipulator is not considered. We propose two methods to remedy the situation. Firstly by cutting a link instead of a joint, all the joints torque can be incorporated into our equations of motion. This is useful not only for the case of actuating all the joints, but also if we consider compensating the joints friction. Secondly we propose a concept of transforming force to the generalized force space so that all the other forces and torque can be considered.
Based on Forward Reference Object Transaction Identification Algorithm on Web Mining

This paper puts forward a new transaction identification algorithm (TIFRO) in web mining, which is based on forward reference object. Firstly, TIFRO uses the maximal forward reference algorithm (MFR) to get the forward reference path, and then join a final object of the forward reference path to transaction set. Secondly, TIFRO starts a new transaction by judging the reference length (RL) in case of RL is longer than the maximal reference length(TMAX). So TIFRO can find the object set but not the path set of MFR. Thirdly, TIFRO uses SPADE algorithm to discovery frequency patterns. Finally, we compare TIFRO with MFR in performance.
Role of L-arginine in the biological effects of blue light

Arginine, a semi-essential amino acid, and metabolites of arginine exert multiple biological effects. It has been known that arginine causes the release of various hormones such as insulin, glucagon, growth hormone, prolactin, and adrenal catecholamines. Arginine infusion also produces vasodilation, and in the kidney increased plasma flow accompanied by increases in glomerular filtration rate (GFR). Recent studies have showed that blue and red light irradiation in vitro and in vivo can increase production of nitric oxide (NO), superoxide anion, and related reactive oxygen species (ROS). These then can modulate the production and secretion of several cytokines and other mediators and play an important role as regulatory mediators in signaling processes which can then modulate the production, mobilization and homing of stem cells. It is proposed that some of the therapeutic effects of light can be considered to be due to the changes in the metabolism of L-arginine. The regulation of L-arginine turnover by the use of light at blue wavelengths between 400nm and 510nm can be the explanation for some of the observed effects of blue light: lowering of blood pressure, pain killing effect, regulating insulin production, anti-inflammatory action, and possible effects on the release and homing of stem cells.
A Secure Hybrid Routing Protocol to Combat Malicious Packet Dropping in a MANET

Mobile ad hoc network is based upon multi-hop communication wherein the nodes themselves act as routers as well as source. The inherent characteristics of a MANET make it vulnerable to a variety of insider as well as outsider attacks. Most of the secure routing protocols do not focus on the insider attacks wherein certain adversarial nodes may launch a number of attacks on the routing protocol as well as on the data transmission by simply dropping the packets without forwarding them. We propose a secure hybrid routing protocol which combats the packet dropping attack carried on by an individual / colluding adversaries. It forms routes based upon a metric assigned to each node called weight / cost which indicates it’s good / bad behaviour. A least cost route has to be formed by including those nodes with least weight representing good packet forwarding behaviour. The protocol monitors the ongoing data transmission in the form of acknowledgements from destination, detects the adversarial nodes on the path through a mechanism based upon bloom filters used as node behavioural proofs , adjusts the weight of the adversarial nodes and propagates the information so that the proactive routing tables involving the adversarial node update their appropriate routing table entries. The result of these activities is the establishment of a route including those nodes with good packet forwarding behaviour.
Using Dynamic Adaptive Systems in Safety-Critical Domains

The development of safety-critical Cyber-Physical Systems (CPS) is expanding due to the Internet of Things' promise to make high-integrity applications and services part of everyday life. This expansion is seen in the dependencies some connected vehicles have on cloud services that provide guidance and accident avoidance / detection features. Such systems are safety-critical since failure could result in serious injury or death. Due to the severe consequences of failure, fault-tolerance, reliability and dependability should be primary driving qualities in the design and development of these systems. However, the cost of the analysis, evaluation and certification activities needed to ensure that the possibility of failure has been sufficiently mitigated is significantly higher than the cost of developing traditional software. Our group is exploring the addition of dynamic adaptive capabilities to safety-critical systems. We postulate that dynamic adaptivity could provide several enhancements to safety-critical systems. It would allow systems to reason about the environment within which they are sited and about their internal operation enabling decision making that is context-specific and appropriately prioritized. However, the addition of adaptivity with the associated overhead of reasoning is not without drawbacks particularly when hard real-time safety-critical systems are involved. In this brief position paper, we explore some of the questions and concerns that are raised when dynamic adaptive behavior is introduced into safety-critical systems as well as ways that the Architecture Analysis \& Design Language (AADL) can be used to model / analyze such systems.
Comparing one and two-stage acoustic modeling in the recognition of emotion in speech

In the search for a standard unit for use in recognition of emotion in speech, a whole turn, that is the full section of speech by one person in a conversation, is common. Within applications such turns often seem favorable. Yet, high effectiveness of sub-turn entities is known. In this respect a two-stage approach is investigated to provide higher temporal resolution by chunking of speech-turns according to acoustic properties, and multi-instance learning for turn-mapping after individual chunk analysis. For chunking fast pre-segmentation into emotionally quasi-stationary segments by one-pass Viterbi beam search with token passing basing on MFCC is used. Chunk analysis is realized by brute-force large feature space construction with subsequent subset selection, SVM classification, and speaker normalization. Extensive tests reveal differences compared to one-stage processing. Alternatively, syllables are used for chunking.
GraspZoom: zooming and scrolling control model for single-handed mobile interaction

A pressure sensing based single-handed interaction model is presented in this paper. Unlike traditional desktop GUI model, mobile UI model has not been established yet. For example, Apple iPhone proposed "Pinch" operation, which use two fingers to zoom-in and zoom-out objects. However, in a today's hand-held situation, manipulation methods using two fingers are not always good solution because they require two hands in order to hold the device itself in most cases. We propose a single-handed UI scheme "GraspZoom": multi-state input model using pressure sensing. Force Sensitive Resistor (FSR) attached on backside of a mobile phone was employed in order to evaluate effectiveness of pressure based control model. We also describe example applications which enable intuitive and continuous zooming and scrolling. By using tiny thumb gesture input along with this pressure sensing method, bi-directional operations (e.g., zoom-in and -out) are also achieved.