Miracle-dz/UniFAR-FTUs huggingface dataset:
Samaniego “ Entry , Exit and Investment-Specific Technical Change ” PIER Working Paper 08-013

Across industries, this paper finds that the rate of investment-specific technical change (ISTC) is positively related to rates of entry and exit. This finding is consistent with industry dynamics along the balanced growth path of a general equilibrium, multi-industry model of the plant lifecycle, in which technology adoption is costly and the rate of ISTC varies across industries. Results are robust to allowing for structural change induced by technological progress. The model also generates lumpy investment as a result of technology adoption by incumbents. JEL Codes: L16, O33, O41.
Toward High-Level Dynamic Camera Control An Integrated Qualitative-Probabilistic Approach

Spatial assistance systems designed to empower people in smart environments need to perceive their operational environment, recognize activities performed in the environment, and reason about the observed information in order to plan a course of action. Integrated commonsense reasoning and learning-centred methods provide the means to reason about uncertainties that arise when dealing with partially observable, noise-prone, dynamic environments; especially, qualitative spatial abstractions (e.g., via formal spatial calculi) can be used to model environmental spatio-temporal phenomena. We propose a high-level commonsense reasoning driven dynamic camera controller that combines qualitative models of space with a basic approach to reason about action and change that is grounded in the Situation Calculus formalism. We illustrate our work with a work-in-progress smart meeting scenario, a domain of long-term interest for our project; this paper focusses on one of the system sub-components concerned with dynamic control of co-ordinating Pan-Tilt-Zoom capable cameras toward creating a unified recording of meeting dynamics.
TRANSLATION OF DIVISION ALGORITHM INTO VERILOG HDL

This paper deals with the design of sixteen bit division algorithms, programmed by using Xilinx ISE 14.4 software for translating the arithmetic operation for division operation. In recent, many researchers have proposed the algorithms to carry out the computation task in hardware instead of software, with the aim to increase the performance of computation. We explained and translated the non-restoring method for division operation. This method is simple to implement since it requires only adder or subtractor in each iteration. Hence, it does not require any other hardware components such as multipliers and multiplexers. The algorithm is translated into Verilog Hardware Description Language that simulated using Integrated Synthesis Environment (ISE) Simulator and then synthesized using Synopsys Design Compiler. The system will only process unsigned binary division hence producing in fixed point value.
Linked Bibliographic Data : An Approach to Integrating Bibliographic Data with External Datasets from the Web

Digital libraries share their catalogue services to expand access to their collections. Currently MAchineReadable Catalogue (MARC) format is much used as a standard in sharing bibliographic records among libraries . However, this standard is limited to bibliographic data interchange among libraries. It cannot exploit data available on the Web. This paper presents an approach to enrich bibliographic data with related information from the Web. The approach develops linked bibliographic data by integrating an existing bibliographic system with external data sources on the Web. The approach consists of three steps, i.e. (i) analyse the bibliographic system’s data structure; (ii) develop a linked bibliographic data model; and (iii) incorporate the resulted linked data into the existing system. To illustrate the approach, we conduct a case study in which we in tegrate an open source library management system, called SLiMS, with datasets from the Web, i.e. DBpedia, VIAF, and WorldCat. In the case study, bibliographic subjects are enriched with abstracts and labels; authors data are enriched with information related to the authors, including their other collections. Information about collections availability is made accessible so it can be linked to other libraries that implement this approach.
The Application of Class Structure to Classification Tasks

Abstract This article presents an approach in bioinformatics data analysis and exploration that improves classification accuracy by learning the inner structure of the data. The diseases studied in bioinformatics (diagnostic, prognostic etc. studies) often have the known or yet undiscovered subtypes that can be used while solving bioinformatics tasks providing more information and knowledge. This study deals with the problem above by studying inner class structures (probable disease subtypes) using a cluster analysis to find classification subclasses and applying it in classification tasks. The study also analyses possible cluster merges that would best describe classes. Evaluation is carried out using four classification methods that can be successfully used in bioinformatics: Naïve Bayes classifiers, C4.5, Random Forests and Support Vector Machines.
Time series mixture model considering dependence to multiple topics

This paper proposes a mixture model that considers dependence to multiple topics. In time series documents such as news, blog articles, and SNS user posts, topics evolve with depending on one another, and they can die out, be born, merge, or split at any time. The conventional models cannot model the evolution of all of the above aspects because they assume that each topic depends on only one previous topic. In this paper, we propose a new mixture model which assumes that a topic depends on previous multiple topics. This paper shows that the proposed model can capture the topic evolution of death, birth, merger, and split and can model time series documents more adequately than the conventional models.
Speaker identification using hidden Markov models

In this study, we show that the use of hidden Markov models (HMMs) significantly enhances the success rate of speaker identification over time. The segment boundary information derived from HMMs provides a means of normalizing the formant patterns obtained from a digital cochlear filter, which we also describe. The use of the digital cochlear filter and HMMs in our study was motivated by two well-known problems in speech recognition generally, i.e. phonetic tempo variability and variability over temporal units of a given length, typically days. We show how these problems can be minimized to achieve more robust speaker identification.
Visual Navigation using Deep Reinforcement Learning

Deep reinforcement learning (RL) has been successfully applied to a variety of game-like environments. However, the application of deep RL to visual navigation with realistic 3D environments is a challenging task. We propose a novel learning architecture capable of navigating an agent to a target given by an image. To achieve this, we have extended batched advantage actor-critic (A2C) algorithm with auxiliary tasks designed to improve visual navigation performance. We propose three additional auxiliary tasks for the prediction of the depth map, of the observation image segmentation and of the target image segmentation. These tasks enable the use of supervised learning to pre-train a major part of the network and to substantially reduce the number of training steps. The training performance can be further improved by increasing the environment complexity gradually over time. An efficient neural network structure is proposed, which is capable of learning for multiple targets in multiple environments. Our method navigates in continuous state spaces and on the AI2-THOR environment simulator surpasses the performance of state-of-the-art goal-oriented visual navigation methods from the literature.
The η ′ mass on 2 + 1 flavor DWF lattices

The large η ′ mass depends on the topological properties of the QCD gauge fields and an accurate measurement requires an ensemble that well samples the possible topologies of the gauge fields. In this proceedings, we present our analysis of the RBC-UKQCD 243×64×24 physical coarse DWF ensemble. The evolution of the global topological charge is measured using the 5-loop improved method [1] after cooling via Wilson flow. The results for closed quark loops, which are sensitive to the topology on the original (unflowed) configurations, are shown to have long autocorrelations. Several eigenvectors with small eigenvalues are calculated for one specific configuration and topological fluctuations are found. Preliminary calculation of the η and η ′ mass is done. Our results show that good sampling of the global topological charge (measured after the Wilson flow) does not necessarily mean rapid evolution of local topological fluctuations.
Understanding tax morale of SMEs : A qualitative study

This article investigates the factors that influence Small and Medium-Sized enterprises’ (SMEs) tax morale and focuses on the factors that stem from concerns of SME owner-managers about their company’s wellbeing that may influence tax morale. Prior literature suggests that there are six relevant factors/constructs that influence SMEs’ tax morale, namely: compliance costs, professionalism, tax advisors’ effect, company structure, size of economic obligation and risk aversion. Drawing on a conceptual model of tax morale, we utilise an exploratory qualitative methodology and provide findings based on a thematic analysis of twenty semi-structured interviews with SMEs owners-managers in Turkey. Our study contributes to the literature by explaining the six constructs and by being one of the very few research studies of tax morale in SMEs in a non-western country.
T 2 WSN : TITIVATED TWO-TIRED CHORD OVERLAY AIDING ROBUSTNESS AND DELIVERY RATIO FOR WIRELESS SENSOR NETWORKS 1

Wireless Sensor Network (WSN) is the embryonic field of research in the past few years due to its appealing applications in need of mobility. The efficiency of message transfer gets a noteworthy amendment if mobility is assimilated in certain applications. Bettering some performance metrics improves applicability of the applications in several sporadic scenarios like military and disaster surveillance, industrial product line monitoring, agricultural and wildlife observation and health care. In this article, the subsisting C2WSN for static nodes is amended with a periodic light weighted CREIDO packet to improve the robustness and packet delivery ratio in the two-tiered chord overlay for wireless sensor networks. The simulated experiments also show that an improvement in robustness leads to increase in packet delivery ratio.
A modified fast laser-Doppler flowmetry to measure the pulsatile microcirculation in rats

A fast laser-Doppler flowmetry (LDF) is modified from a commercial one to measure the pulsatile microcirculation in rats. The time constant (TC) of the integrator in the analogue circuit of the LDF was modified; the frequency response of the modification was simulated by PSPICE to estimate the high 3 dB frequency. The coefficients of variance of 32 2-second ensembles of flux in the calibration standard measured by the commercial LDF and the modified one were less than 2%. The animal tests also clearly demonstrated the pulsatile microcirculation on the renal cortex in the rat.
I.1 Overview of Haploidy

The term haploid sporophyte is generally used to designate sporophytes having the gametic chromosome number, and although the first haploids in flowering plants were identified over 80 years ago (Belling and Blakeslee 1922), it was not until Guha and Maheshwari (1964) reported the first in vitro culture anther-derived haploids from Datura that their potential for crop improvement was seriously contemplated as the value of quickly achieving homozygous lines was recognized. Since then, haploids and doubled haploids have been reported in a vast number of species and several cultivars have been developed using doubled haploids (Maluszynski et al. 2003a; Thomas et al. 2003). Consequently, the use of germplasm collection, classical plant breeding methods and genetic engineering for crop improvement can be supplemented with doubled haploid technology (Baenzinger 1996; Khush and Virmani 1996; Gepts 2002). Here we present a brief overview of the occurrence and experimental induction of haploidy.
Contemporary Issues in Crime and Justice Number 104 October 2006 The economic and social factors underpinning Indigenous contact with the justice system : Results from the 2002 NATSISS survey

This study uses the 2002 National Aboriginal and Torres Strait Islander Social Survey (NATSISS) to examine the economic and social factors that underpin Indigenous contact with the criminal justice system. The analysis shows that the Indigenous respondents to the NATSISS were far more likely to have been charged with, or imprisoned for, an offence if they abused drugs or alcohol, failed to complete Year 12 or were unemployed. Participating in the Commonwealth Development Employment Scheme (CDEP) appears to reduce the risk of being charged (compared with being unemployed). Other factors that increase the risk of being charged or imprisoned include: experiencing financial stress, living in a crowded household and being a member of the ‘stolen generation’.
Stacking Bagged and Boosted Forests for E ective Automated Classification Online Appendix ∗

1.1 Topic Categorization In order to evaluate the methods under the topic categorization seing, we explored the following datasets: 20 Newsgroups (20NG) a classical textual dataset with roughly 20, 000 labeled documents gathered from newsgroups. Each document is classied into one of 20 categories. Each category has approximately 1, 000 examples. 4Universities (4UNI) (akaWEBKB) this dataset contains Web pages collected from Computer Science departments of four universities by the Carnegie Mellon University (CMU) text learning group. ere is a total of 8, 277 web pages, classied into 7 categories (such as student, faculty, course and project web pages). Reuters (REUT) this is a classical text collection, composed by news articles collected and annotated by Carnegie Group, Inc. and Reuters, Ltd. We consider here a set of 13, 327 articles, classied into 90 categories. ACM-DL (ACM) a subset of the ACM Digital Library with 24, 897 documents containing articles related to Computer Science. We considered only the rst level of the taxonomy adopted by ACM, whereas each document is assigned to one of 11 classes. Spambase (SPAM) is a collection of spam e-mails collected by Hewle-Packard Labs. It contains 1, 813 e-mails labeled as spam and 2, 788 non-spam personal e-mails. MEDLINE (ML) a subset of the MedLine dataset, with 861, 454 documents classied into 7 distinct classes related to Medicine. is collection was obtained from [2]. In that work the authors considered the rst level of the taxonomy so that each document article is classied under only one category, avoiding dealing with multilabel cases.
Deep Learning based Retinal Image Analysis for evaluation of Glaucoma

Glaucoma is one of the commonly occurring ocular diseases which could potentially lead to permanent loss in vision. Color fundus imaging is one of the most common modalities used for imaging the retina. Using the color fundus images, the assessment of glaucoma is performed by the examination of the optic nerve head and the region around it. For the computer aided diagnosis of glaucoma, we propose a deep learning based framework for three major tasks localization of optic nerve head, image based classification for glaucoma, semantic segmentation of optic disc and cup. In our approach, we transform the fundus images with cropped region of interest using various operations. We propose a novel method for glaucoma classification in which we employ multiple pretrained deep networks and retrain the networks for glaucoma classification.During the prediction stage, we perform ensembling of multiple classifiers, each of which are trained with different networks and different kinds of input images. For the task of semantic segmentation, we employ a fully convolutional network for joint segmentation of optic disc and cup. On the validation set of the REFUGE challenge, we obtain an area under the curve (AUC) 0.9635 and reference sensitivity of 0.975, for the task of classification and dice scores for 0.8964 for optic disc and 0.7744 for optic cup and cup-to-disc ratio (CDR) error of 0.0974 for the task of semantic segmentation.
High stress and Self-assessment : Assumption of Systematic Overestimation

The use of questionnaires for self-assessment of stress is broadly applied within the scientific community, often complemented with physiological measurements. A few cases of over-estimation of perceived stress using such questionnaires with healthy adult subjects were reported; most of the time, this point is never questioned in the articles. It thus appeared interesting to undertake experiments in the aim of characterizing the possible deviation regarding self-assessment through questionnaires. Peritraumatic Distress Inventory (PDI) questionnaire was used for self-assessment of short term mental stress for two cohorts of subjects (N=19) (residents in anesthesiology working in hospital and charter engineers working on an industrial plant) having experienced stressful situations during which mean heart rate was measured. The PDI scores obtained were compared to expected values using the Fauquet-Alekhine et al.’s model for HR response under mental stress. The resulting significant deviation observed was confronted to four assumptions which led to conclude for an effective over-estimation due to the subjects’ perception occurring for high level of
LIPASE-CATALYSED ACYL TRANSFER IN DEOXYSUGARS : A COMPUTATIONAL STUDY

CALB-catalyzed acyl transfer from vinyl acetate to bromoand ester-derivatives of tri-and tetradeoxysugars has been studied by Amber biomolecular simulation packet. In comparison to the experimental data the best results have been obtained via an analysis of catalytically essential hydrogen bonds.
Some Biofertilizers Application in Relation to Growth , Chemical Constituents and Yield of Snap Bean Plants

Two field experiments were carried out during two successive seasons of 2009 and 2010 on snap bean to study the effect of biofertilizers shus as amino green, effective microorganisms (EM) and terra sorb on growth, chemical constituents and yield along with its components. Using amino green, EM and terra sorb caused significant increases in plant height, number of branches, number of leaves, fresh and dry weight of roots, leaves and stems, total chlorophyll, total carbohydrates, peroxidase, N, P and K% in leaves. Also there were significant increases in P%, K%, protein%, total carbohydrates in seeds due to applied treatments. Besides, number of pods / plant, green pods weight, early yield and total yield were also positively responded to applied biofertilizers. In addition, using these biofertilizers decreased NO3 accumulation in pods. It can be recommended that using biofertilizers especially amino green and EM with half amount of N fertilizers to get a good quality and quantity of yield.
MODELLING AND ANALYZING DYNAMIC SOURCE ROUTING PROTOCOL WITH GENERAL DISTRIBUTIONS

In this paper, we present an integrated algebraic model of the dynamic source routing protocol used in ad hoc networks. Algebraic description of this protocol has been realized by means of powerful operators of Extended Markovian Process Algebra EMPA and by exploiting value passing feature in order to express activities execution delay with general distribution. Afterwards, functional properties of the model are formally verified using µ-calculus/CTL model checking formulas and performance parameters are assessed via simulation through the EMPA software tool.
Secure Bootstrapping for 6 LoWPAN Networks to Prevent Vampire Attacks in the Internet of Things

The Internet of Things (IoT) and its vision of connecting every device to one another and to the Internet presents an opportunity to create large information sharing networks. However, intruders can capture IoT devices and take advantage of their constrained nature to disrupt these networks and launch a wide range of attacks on its nodes. In our work we address this security concern from a power-aware perspective, because typical devices have limited power available and they need to judiciously decide what to do with it. This work identified the relation between security and resource consumption. To achieve this objective we do a thorough analysis of the existing protocols, attacks and mitigation strategies, combining that information into our proposed bootstrapping and network management system – AutoStrap – evaluated on a Smart Campus scenario. Furthermore, we perform energy, space and time profiling of the network devices to provide future users with the knowledge of what kind of physical resources to deploy based on the desired application security level.
Unequal Impact II : Māori and Non-Māori Cancer Statistics

The new chart book includes contextual information, analyses of selected findings and a series of detailed data tables based on Māori and non-Māori cancer outcomes, area deprivation and rural-urban status. This report is available on the Māori Health website www.maorihealth. govt.nz or in hardcopy by emailing moh@wickliffe.co.nz or calling 04 496 2277 quoting HP number 5173 Tënä koutou, tënä koutou, tënä tätou katoa Nau mai ki tenei Tirohanga hou Hauora Māori. He rangahau tuhi hou e paa ana ki nga hau ora a ki te oratanga o te Māori. No reira noho ora mai raa i o koutou waahi noho a waahi mahi hoki. Noho ora mai. Matire Greetings Welcome to this issue of the Māori Health Review. Each issue attempts to bring you research relevant to the health and wellbeing of Māori. I welcome feedback and suggestions for papers/research to include in future issues and I’m pleased to hear and read about the excellent work being undertaken in Hauora Māori. Stay well, regards Matire Dr Matire Harwood matire@maorihealthreview.co.nz Maori Health Review