Miracle-dz/UniFAR-FTUs huggingface dataset:
Preference learning from qualitative partial derivatives

We address the problem of learning preference models from data containing implicit preference information. The information about preferences is expressed as a result of a decision or action in a given state in context of other attributes. We propose an algorithm that observes the change of probability of a target class (desired result) w.r. t. the change in the values of the attribute describing the decision or action. We generalize the notion of a partial derivative by defining the probabilistic discrete qualitative partial derivative (PDQ PD). PDQ PD is a qualitative relation between the target class c and a discrete attribute, given as a sequence of attribute values ai in the order of P (c|ai) in a local neighbourhood of the reference point. In a two stage learning process we first compute PDQ PD for all examples in the training data, and then generalize over the entire data set using an appropriate machine learning algorithm (e.g. a decision tree). The induced preference model explains the influence of the attribute values on the target class in different subspaces of the attribute space.
Equivariant quantum cohomology of homogeneous spaces.

We prove a Chevalley formula for the equivariant quantum multiplication of two Schubert classes in the homogeneous variety X=G/P. As in the case when X is a Grassmannian, studied by the author in a previous paper, this formula implies an effective algorithm to compute the structure constants of the equivariant quantum cohomology algebra of X.
Framing futures through notions of a particular 'Community of Practice': what TAFE teachers said

This paper was initialised by a request from a group of Technical and Further Education (TAFE) teachers for support in the development of what they called 'a community of practice'. In an effort to explore this localised encounter with the concept of learning as a social phenomenon, this paper explores the question, 'If a group of TAFE teachers described a community of practice, how might it look? '
Long-Term Effects of Famine on Life Expectancy: A Re-Analysis of the Great Finnish Famine of 1866-1868

Famines are extreme cases of environmental stress, and have been used by a series of studies to explore the long-term consequences of the fetal or childhood environment. Results are inconsistent and do not support negative long-term effects on mortality. The authors test the hypothesis that selection during famine changes the frailty distributions of cohorts and may hide negative long-term effects. They use death counts from age 60+ from the Human Mortality Data Base for the birth cohorts 1850-1854, 1855-1859, 1860-1865, 1866-1868, 1869-1874, 1875-1879, 1880-1884 and 1885-1889 to explore the effect of being born during the Great Finnish Famine 1866-1868. Swedish cohorts without famine exposure are analysed as a control group. Cohorts born in Finland during the Great Finnish Famine are highly heterogeneous in their distribution of deaths after age 60. By contrast, cohorts born in the years immediately after the famine are particularly homogeneous. Accounting for these differences results into a lower remaining life expectancy at age 60 for cohorts born during the famine. Statistically, long-term effects of famine on mortality become only visible when changes in the frailty distribution of cohorts are explicitly considered.
Exposure to Air Pollution : the Quantified Self

The purpose of this paper is to apply recent developments in the areas of the ‘Quantified Self’ and the ‘Internet of Things’ in order to explore the use of low-cost sensors for the collection of a variety of spatially-referenced biometric and environmental data from participants. This is achieved using a specially designed application on the Android mobile platform, which has been developed for this project in order to log serial sensor data via USB against GPS location and timestamp, allowing the spatio-temporal mapping of a variety of personal data. In this case, traffic pollution data is collected and compared with a measures of nasal airflow, permitting an estimate of exposure to traffic pollution for an individual on a given journey. These data will be fed back to individuals in order to assess the level of correlation with their reported perception of exposure to pollution, as well the extent to which this influences subsequent behaviour; such as whether or not an individual will modify their route for a given journey based upon their new knowledge of pollution levels. In this way, personal pollution exposure can be empirically monitored at the individual level, allowing for a more in-depth understanding of these issues than has so far been possible.
CLUSTERED SPATIAL ASSOCIATION RULE TO EXPLORE LARGE VOLUMES OF GEOREFERENCED CRIME TO CRIME DATA

The studies of this paper which zeal to integrate a large volume of data sets into useful information by adopting a various information techniques in the hottest technology world. The adopted approaches of Single variate Association Rule for Crime to Crime based on the knowledge discovery techniques such as, clustering and association-rule mining. It reveals with an inherent of patterns of information into a fruitful exploratory tool for the discovery of spatio-temporal patterns. This tool is an autonomous pattern detector to reveal plausible cause-effect associations between layers of point and area data. We present REPA, VBEA and TEA algorithms with an exploratory analysis for the effectively explore geo-referenced data. The present study of this paper was focuses through the real crime dataset by using various algorithms. We demonstrate our approach to a new type of analysis of the spatio-temporal dimensions of records of criminal events. We hope this will lead to new approaches in the exploration of large volumes of spatio-temporal data.
The effects of career planning on self-concept and academic achievement of at-risk middle school students in an urban public school environment

approved: Kenneth M. Ahrendt The purpose of this study was to determine the effects of a six-week career planning dropout prevention program on the self-concepts and academic achievement of at-risk middle school students in an inner-city public school environment. The research population consisted of 1,434 students (grades seven, eight and nine) attending an inner city public junior high school in south-central Los Angeles, California. The selection of the research site and sample was based on the assumption that the student population met the criteria and demographic profile of at-risk students: Students are from low-income and/or single parent families; have low achievement scores in reading and mathematics; exhibit a high incidence of truancy, absenteeism and teenage pregnancy; have low career aspirations and plans; and exhibit other related characteristics of at-risk students. The study was conducted from September, 1993 to January, 1994 (fall semester, 1993). All students were selected by random procedure from grades seven, eight and nine. The experimental group consisted of 195 students enrolled in a woodworking class. The control group consisted of 1,239 students who were not enrolled in a woodworking class but were enrolled in other elective
Modelling and optimization of traffic loads of the radio access network

This article presents a methodology for modelling and optimization of radio interfaces of 2G, 3G and 4G access networks. The basics for modelling of interfaces with embedded traffic management mechanisms are described and discussed. A particular attention is given to the problems stemming from the introduction of the IP technology to the 3G and 4G radio access networks.
UNCONSCIOUS CONTRIBUTIONS Applying a connectionist model to design knowledge exchange

The distributed cognition approach, and by extension the domain of social intelligence design, attempts to integrate three until recently separate realms: mind, society, and matter. The field offers a heterogeneous collection of ideas, observations, and case studies, yet lacks a solid, coherent theoretical framework for building models of concrete systems and processes. Despite the intrinsic complexity of integrating individual, social and technologically-supported intelligence, the paper proposes a relatively simple "connectionist" framework for conceptualizing a distributed cognitive system. This framework represents shared information sources (documents) as nodes connected by links or associations of variable strength. The link strength increases interactively with the number of “co-activations” or co-occurrences of documents in the patterns of their usage. This connectionist learning procedure captures the implicit knowledge of its community of users and uses it to help them find relevant information, thus supporting an unconscious form of exchange. The principles are illustrated by an envisaged application to a concrete problem domain: the dynamic sharing of design knowledge among a multitude of architects by means of a database of associatively connected building projects.
Area Spt in the Human Planum Temporale Supports Sensory-motor Integration for Speech Processing Establishing the Existence of Distinct Sen- Sory versus Motor Activation Patterns Would Establish That

Area Spt in the human planum temporale supports sensory-motor integration for speech processing. Processing incoming sensory information and transforming this input into appropriate motor responses is a critical and ongoing aspect of our moment-to-moment interaction with the environment. While the neural mechanisms in the posterior parietal cortex (PPC) that support the transformation of sensory inputs into simple eye or limb movements has received a great deal of empirical attention—in part because these processes are easy to study in nonhuman primates—little work has been done on sensory-motor transformations in the domain of speech. Here we used functional magnetic resonance imaging and multivariate analysis techniques to demonstrate that a region of the planum temporale (Spt) shows distinct spatial activation patterns during sensory and motor aspects of a speech task. This result suggests that just as the PPC supports sensorimotor integration for eye and limb movements, area Spt forms part of a sensory-motor integration circuit for the vocal tract. Although most research on sensory-motor integration has focused on the neural mechanisms in posterior parietal cortex (PPC) that support interactions between vision and motor behaviors such as reaching and eye movements (Andersen 1997; Colby and Goldberg 1999; Cui and Andersen 2007), sensory-motor interactions are also critically important for speech-related behaviors including aspects of speech develop-A region in the left posterior planum temporale (PT) in humans, area Spt, has been proposed as a critical node in a network that supports sensory-motor integration for speech and other vocal tract behaviors (Buchs-baum et al. has sensory-motor response properties, activating both during the auditory perception and covert production of speech (Buchsbaum et al. 2001, 2005b; Hickok et al. 2003; Okada and Hickok 2006). Second, Spt appears to be selective for the vocal tract effector system (Pa and Hickok 2008). Third, although Spt activates during speech functions, it is not speech selective: it responds to other vocal-tract related behaviors such as the perception and covert production (humming) of melodies (Hickok et al. 2003; Pa and Hickok 2008). Fourth, while Spt is responsive to speech stimulation, it is not critical for speech recognition (Hickok and Poeppel 2000, 2004, 2007), just as PPC sensory-motor areas are not critical for object recognition (Milner and Goodale 1995; Ungerleider and Mishkin 1982). Fifth, human cytoarchitectonic studies (Galaburda and Sanides 1980) and comparative studies in monkeys (Smiley et al. 2007) indicate that the posterior PT region is not part of unimodal auditory cortex. Finally, the …
Students' Reflections on Industry Placement: Comparing Four Undergraduate Work-Integrated Learning Streams.

This paper compares four work-integrated learning (WIL) streams embedded in a professional Development course for tourism, hospitality and event management students. Leximancer was used to analyze key themes emerging from reflective portfolios completed by the 137 students in the course. Results highlight that student learning outcomes and experiences differed depending on the WIL stream chosen. Aristotle's notions of episteme, techne and phronesis are used as a broad framework for situating the key themes that emerge from students' reflections.
Self-reported aggressive and antisocial behaviors in Moroccan high school students

The aims of the present study were to map the level and distribution of aggressive and antisocial behaviors in a sample of Moroccan high school students and to define the level of these behaviors in adolescents who reported parental alcohol use problems and/or experienced abuse. In total, 375 high school students completed the ? Mental and Somatic Health without borders (MeSHe)? survey that includes the Life History of Aggression scale. Male students had significantly higher scores for aggression and antisocial behaviors than female. The students who reported experience of abuse or parental alcohol use problems scored significantly higher for aggression, self-directed aggression, and antisocial behaviors compared to students not reporting these negative psychosocial factors. Previously shown gender-specific patterns in aggressive and antisocial behaviors, but not in self-harm behaviors were confirmed in these Moroccan high school students. Reported experience of abuse and/or parental alcohol use problems were associated with increased frequency of aggressive and antisocial behaviors.
Smart Video Hosting and Processing Platform for Internet-of-Things

Due to the rapid improvement in resolution and codec, the number of video sensing device grows fast in the recent years. Tremendous data need to be stored and processed. To meet such a need, we developed a video hosting and processing platform for near-real time applications. An intelligent device can obtain connection-less upload function from our client-side SDK. Video data are sliced into pieces, distributed over cloud-of-clouds and can be processed in parallel once stored. Various video processing algorithms can be mounted together and processed by multiple CPU cores. Performance evaluations show that our platform has the ability to host and process large-scale video data.
Genome-Wide Transcriptional Profiling to Elucidate Key Candidates Involved in Bud Burst and Rattling Growth in a Subtropical Bamboo (Dendrocalamus hamiltonii)

Bamboo, one of the fastest growing plants, can be a promising model system to understand growth. The study provides an insight into the complex interplay between environmental signaling and cellular machineries governing initiation and persistence of growth in a subtropical bamboo (Dendrocalamus hamiltonii). Phenological and spatio-temporal transcriptome analysis of rhizome and shoot during the major vegetative developmental transitions of D. hamiltonii was performed to dissect factors governing growth. Our work signifies the role of environmental cues, predominantly rainfall, decreasing day length, and high humidity for activating dormant bud to produce new shoot, possibly through complex molecular interactions among phosphatidylinositol, calcium signaling pathways, phytohormones, circadian rhythm, and humidity responses. We found the coordinated regulation of auxin, cytokinin, brassinosteroid signaling and cell cycle modulators; facilitating cell proliferation, cell expansion, and cell wall biogenesis supporting persistent growth of emerging shoot. Putative master regulators among these candidates were identified using predetermined Arabidopsis thaliana protein-protein interaction network. We got clues that the growth signaling begins far back in rhizome even before it emerges out as new shoot. Putative growth candidates identified in our study can serve in devising strategies to engineer bamboos and timber trees with enhanced growth and biomass potentials.
Less Regret via Online Conditioning

We analyze and evaluate an online gradient descent algorithm with adaptive per-coordinate adjustment of learning rates. Our algorithm can be thought of as an online version of batch gradient descent with a diagonal preconditioner. This approach leads to regret bounds that are stronger than those of standard online gradient descent for general online convex optimization problems. Experimentally, we show that our algorithm is competitive with state-of-the-art algorithms for large scale machine learning problems.
On the Probe Complexity of Local Computation Algorithms

The Local Computation Algorithms (LCA) model is a computational model aimed at problem instances with huge inputs and output. For graph problems, the input graph is accessed using probes: strong probes (SP) specify a vertex $v$ and receive as a reply a list of $v$'s neighbors, and weak probes (WP) specify a vertex $v$ and a port number $i$ and receive as a reply $v$'s $i^{th}$ neighbor. Given a local query (e.g., "is a certain vertex in the vertex cover of the input graph? "), an LCA should compute the corresponding local output (e.g., "yes" or "no") while making only a small number of probes, with the requirement that all local outputs form a single global solution (e.g., a legal vertex cover). We study the probe complexity of LCAs that are required to work on graphs that may have arbitrarily large degrees. In particular, such LCAs are expected to probe the graph a number of times that is significantly smaller than the maximum, average, or even minimum degree. For weak probes, we focus on the weak coloring problem. Among our results we show a separation between weak 3-coloring and weak 2-coloring for deterministic LCAs: $\log^* n + O(1)$ weak probes suffice for weak 3-coloring, but $\Omega\left(\frac{\log n}{\log\log n}\right)$ weak probes are required for weak 2-coloring. For strong probes, we consider randomized LCAs for vertex cover and maximal/maximum matching. Our negative results include showing that there are graphs for which finding a \emph{maximal} matching requires $\Omega(\sqrt{n})$ strong probes. On the positive side, we design a randomized LCA that finds a $(1-\epsilon)$ approximation to \emph{maximum} matching in regular graphs, and uses $\frac{1}{\epsilon }^{O\left( \frac{1}{\epsilon ^2}\right)}$ probes, independently of the number of vertices and of their degrees.
A study of 2 D features for 3 D visual SLAM

— The use of 2D features in computer vision has had a great impact in lots of applications. For example, the combination of those features together with 3D data has helped to solve the Simultaneous Location And Mapping (SLAM) problem in real time. Nowadays, there are several interesting feature detectors and descriptors with different characteristics: processing time, robustness against lightning conditions, changes in point of view, scale, etc., and every day it appears more and more. In this paper, a deeper study about several of these detectors and descriptors is done. Several interesting graphs where we can separate distances with respect to axis and angles have been analysed. This study helps to make decisions about which are better for a given application. The study has been done with a low cost sensor as Kinect installed on robotics arm to control the movements with accuracy. Furthermore, finally, real scenario reconstruction is shown using Kinect camera and the visual features analysed in the study.
A SAW-less CDMA receiver front-end with single-ended LNA and single-balanced mixer with 25% duty-cycle LO in 65nm CMOS

A fully integrated SAW-less direct conversion CDMA receiver with single-ended LNA and modified single-balanced passive mixer is manufactured in a 65 nm digital CMOS process. The measured receiver gain at 1.96 GHz was 37 dB, NF was 3 dB, IIP2 was +62 dBm, and cross-modulation triple beat (TB) was 65 dB.
A fault-tolerant integrated navigation method for land vehicle

A fault-tolerant integrated navigation method for land vehicle is researched in this paper, which is based on inertial measurement unit (IMU), global positioning system (GPS) and dead reckoning system (DRS). Firstly, position and velocity outputs of IMU and GPS are taken to construct measurements of IMU/GPS integrated navigation, and IMU/GPS Kalman filtering algorithm is deduced and designed. At the same time, position outputs of IMU and DRS are taken to construct measurements of IMU/DRS integrated navigation, and its Kalman filtering algorithm is also designed. Then IMU/GPS/DRS federated filter frame is designed, and the global optimal fusion algorithm of the master filter is researched. Thus estimations of system states from IMU/GPS and IMU/DRS local filters are sent to the master filter independently. Consequently global optimal estimations of system states are given in the master filter. Lastly, based on the federated filter frame, the fault detection and isolation algorithm for IMU/GPS/DRS integrated navigation system is designed. Simulation results show that, position accuracy of this integrated navigation method reaches ±4.8m, and velocity accuracy reaches ± 0.09m/s. And simulation results also show that, this integrated navigation method has strong fault-tolerance, and it can keep high accuracy when GPS or DRS is out of order.
AN EXPERIENCEMODELINGCRITICAL REQUIREMENTS

Previous work at NRL demonstrated the benefits of a security modeling approach for building high assurance systems for particular application domains. This paper1 introduces an application domain called selective bypass that is prominent in certain network security solutions. We present a parameterized modeling framework for the domain and then instantiate a confidentiality model for a particular application, called the External COMSEC Adaptor (ECA), within the framework. We conclude with lessons we learned from modeling, implementing and verifying the ECA. Our experience supports the use of the applicationbased security modeling approach for high assurance systems.
Structural Induction and Coinduction in a Fibrational Setting

We present a categorical logic formulation of induction and coinduction principles for reasoning about inductively and coinductively defined types. Our main results provide sufficient criteria for the validity of such principles: in the presence of comprehension, the induction principle for initial algebras is admissible, and dually, in the presence of quotient types, the coinduction principle for terminal coalgebras is admissible. After giving an alternative formulation of induction in terms of binary relations, we combine both principles and obtain a mixed induction/coinduction principle which allows us to reason about minimal solutionsX? (X) whereXmay occur both positively and negatively in the type constructor ? We further strengthen these logical principles to deal with contexts and prove that such strengthening is valid when the (abstract) logic we consider is contextually/functionally complete. All the main results follow from a basic result about adjunctions between “categories of algebras” (inserters).
Multivalued Trust Routing Based on Topology Level for Wireless Sensor Networks

In wireless sensor network (WSN), many low cost sensor nodes are deployed over a geographically limited area without well-established infrastructure. They accomplish the task together. Malicious sensor nodes are well disguised in sensor nodes, so they can attack the whole network using the natural cooperation of WSN. In order to detect malicious nodes and enhance the security of network, this paper presents a novel multivalued trust routing protocol, called MTR, which is based on the concept of sensor's trust and level in topology structure of network. Protocol MTR employs sensor's trust and the number of hops from sensor nodes to Base Station (BS) to ensure the stability of the net. The simulation results show that protocol MTR significantly improves the reliability data transmission to BS and the time to live in the present of compromise nodes.