Miracle-dz/UniFAR-FTUs huggingface dataset:
A Conceptual Model for Representation of Taxi Trajectories

The large-scale capture of data about the motion of moving objects has enabled the development of geospatial tools to analyze and present the characteristics of these objects' behavior in many different fields. Intelligent Transportation Systems, for instance, make intensive use of data collected from embedded in-vehicle devices to analyze and monitor roads conditions and the flow of vehicles and passengers of the public transportation system. The taxi fleet is an important transport modality complementary to the public transportation system. Thus, analysis of taxis' movements can be used to capture information about the condition of the traffic and to understand at a finer level of granularity the movement of people in an urban environment. This paper addresses the problem of mapping taxi raw trajectory data onto a more abstract and structured data model. The proposed data model aims to create an infrastructure to facilitate the implementation of algorithms for data mining and knowledge discovery about taxi movements and people's behavior using this means of transport. Intelligent Transportation Systems (ITS) encompass new kind of applications designed to incorporate information and communication technologies to the transportation infrastructure. The main goal of such applications is to allow users to become more acquainted with the system functioning and to provide innovative services to enhance the system's coordination and maintenance. ITS make intensive use of data collected from sensors placed along the transportation network or embedded in-vehicle devices to analyze and monitor roads conditions and the flow of vehicles and users of the public transportation system. Although the taxi fleet cannot be considered as a component of the public transportation system, it is an important and complementary Proceedings XIII GEOINFO, November 25-27, 2012, Campos do Jord~ao, Brazil. p 96-107.
Semantic Analysis using Dependency-based Grammars and Upper-Level Ontologies

Semantic analysis of texts is a key issue for the n atural language processing community. However, this analysi s i generally based on a deeply-intertwined syntactic an d semantic process, which makes it not easily adaptable and reu sable from a practical point of view. This represents an obstac le to the wide development, use and update of semantic analyze rs. This paper presents a modular semantic analysis pipeline that aims at extracting logical representations from free tex t based on dependency grammars and assigning semantic roles to the logical representation elements using an upper-leve l ontology. An evaluation is conducted, where a comparison of o ur system with a baseline system shows preliminary results.
Classification Using Linguistic Analysis : A Supervised Deep Learning Approach

A vast amount of unstructured text that contains valuable information is available over the web. This text is changing and proliferating, making it hard for people to process, read, and remember. Data mining and information extraction algorithms are used to develop new automation techniques to process the unstructured text. Among this publicly available text, there are a considerable amount of online medical articles, which provides valuable information about diseases, symptoms, operations, treatments, drugs, etc. Automatic unstructured text classification offers practical information management that does not depend on the subjective criteria of classification. It also provides useful information by obtaining and correlating relevant data present in documents. It also classifies, identifies and presents all sources of knowledge and reduces the time for retrieving information by simplifying access to content. Therefore, medical information needs to be classified into their respected categories (such as Diabetes, Cancer, Depression, Pediatrics, etc.). In this paper, we propose to use a deep learning approach for unstructured medical text classification at the document level. In our classification model we used two types of features: (i) content-based features (stylistic and complexity), and (ii) health domain-specific features. Moreover, rather than dealing with binary classification, this work handles multiclasses medical articles classification. This classification is done based on linguistic features that are extracted from the text, it also incorporates medical domain-specific terms/keywords as part of the classification feature set. These domain-specific features are extracted by applying topic modeling technique to spot the most probable terms for each medical class. Our experiments shows a reasonable classification accuracy for such a large number of classes.
Text-independent Speaker Identification in Emotional and Whispered Speech Environments

This paper describes challenging task of closed set text-independent speaker identification in emotional and whispered speech environments. In the first phase of the work, speaker identification system is developed using neutral speech and tested using speech samples comprising of six basic emotions of anger, happiness, sadness, disgust, neutral and fear. The performance is analyzed using Mel frequency cepstral coefficients (MFCC), Line spectral frequencies (LSF), and temporal energy of subband cepstral coefficients (TESBCC) feature sets. The second phase of work involves the process of speaker identification system in whispered speech environment. The performance of the speaker identification system degrades drastically for whisper speech utterances. A new feature called temporal Teager energy based subband cepstral coefficients (TTESBCC) is proposed. The comparison of the performance of MFCC, TESBCC, weighted instantaneous frequency (WIF) and TTESBCC feature sets is done for this process. A novel classifiers fusion technique is developed and its performance is compared with that of the individual classifiers. Two databases with speech utterances of thirty
Modelling the Sectoral Allocation of Labour in Open Economy Models

Indivisible labour is not the only type of nonconvexity affecting labour supply decisions. Another type of nonconvexity arises in economies with sectors whenever individuals can work in only one sector at a time. I introduce this restriction into an open economy model with a tradeable and a nontradeable sector, and I use lotteries to convexify the consumption possibilities set. This approach implies that the aggregate elasticity of labour supply becomes infinite. I compare the performance of the model with an analogous model in which the labour supply elasticity is finite. I find that the infinite labour supply elasticity helps explain the persistence of net exports. However, all the other consequences of the labour supply elasticity for the model-implied second-order moments depend on whether the pricing assumption is Producer Currency Pricing (PCP) or Local Currency Pricing (LCP).
Utilising inkjet printed paraffin wax for cell patterning applications

We describe a method to prepare patterned environments for eukaryotic cells by inkjet printing paraffin wax onto glass. This technique bypasses the requirement to create a master mould, typically required with the use of polydimethylsiloxane techniques and the printed structure could be immediately used to guide cell proliferation. In a space of 2-3 hours, the desired pattern could be created with computer assisted design, printed and have cells seeded onto the scaffold, which could reduce the cycle time of prototyping micropattern designs. Human dermal fibroblasts and RN22 Schwann cells were seen to proliferate within the fabricated patterns and survive for more than 7 days. Additionally, the wax constructs could be readily removed from the substrate at any stage after cell seeding with the cells continuing to proliferate. Thus, we report on a simple but novel approach for the controlled physical positioning of live cells by wax inkjet printing.
Review of models for large scale manufacturing networks

Productive4.0 is a large-scale research project, which aims at using Industry 4.0 ideas and technologies to improve the design, manufacturing and distribution of high-tech products. Within this project, two work-packages provide models, which shall be used to design, optimize and control large supply chains, which consist of manufacturing and distribution elements. In our contribution, we give an overview about the current state of the usage and usability of stochastic, especially queueing models for the above mentioned purpose.
Modular PCA Face Recognition Based on Weighted Average

This paper presents an improved modular PCA approach, that is, modular PCA algorithm based on weighted average. This algorithm extracts weighted average for every sub-block of every training sample in each type of training sample, and normally operates the corresponding sub-block in training sample using weighted average, then all standardized sub-blocks constitute the overall scatter matrix, and thus the optimal projective matrix is obtained; From the middle value of sub-blocks in training set, and normally projecting sub-blocks of training samples and test samples to the projective matrix, then we can get identified characteristics; At last, use the recent distance classifier to class. The test results in the ORL face database show that the proposed method in identifying performance is superior to ordinary modular PCA approach.
Molecular Basis of Cold Resistance: the role of Frost and Muc68E

Ectotherms are affected by environmental temperature, as it impacts their physiology. Small cosmopolitan flies from the Drosophila genus are not capable of regulating their body temperature, so they present different kinds of behaviour in order to avoid thermal stress. In particular, geographical distribution limits of Drosophila and many other insects, have been linked to their physiological and fitness responses to low temperatures. Chill coma recovery has been used in genetic analysis as a measure of cold resistance in Drosophila. Here, we relate the expression after chill coma of two genes that encode proteins with similar features, Frost and Muc68E, with the cold response. Frost is overexpressed around fifty times after cold exposure, and it has been shown to be involved in the responses to other types of stress although to a lesser extent. However, we suggest that Frost is actually responding to desiccation. Since Muc68E is a poorly studied gene, we started by analysing its structure and evolution and discovered that it is only present in the Sophophora subgenus – meaning that even if it is involved in cold response it is not associated with a genus-wide mechanism. We also performed phenotypical comparisons between a Muc68E mutant strain and its control in chill coma and a variety of other stresses in order to grasp other possible functions of this gene.
Multilayer piezoelectric energy harvesting using single supply pre-biasing for maximum power generation

This paper studies the method of increasing output power of multilayer piezoelectric energy harvesters using Single Supply Pre-biasing (SSPB). In SSPB, it is important that the pre-biasing voltage be applied at the right moment. Multilayer piezoelectric energy harvesters are well suited SSPB as there is no phase lag between piezoelectric charge displacement on each layer and one layer can therefore be used for switch timing control. Compared to previously reported SSPB circuits, the power consumption of the circuit has been significantly reduced. Experimentally, the output power of a bimorph single-layer energy harvester using SSPB has been increased by a factor of three compared to that using a bridge rectifier. Furthermore, the possibility of implementing SSPB in bimorph double-layer energy harvesters has also been investigated.
Study on Roll Motion Characteristics of a Rectangular Floating Structure in Regular Waves

This study focused on the roll motion characteristics of a two-dimensional (2D) rectangular floating structure under regular beam sea conditions. An experiment was conducted in a 2D wave tank for a roll free decay test in calm water and the roll motion in a range of regular waves with and without heave motion to investigate the motion response and heave influence on the roll motion. A numerical study was carried out using Reynolds-averaged Navier Stokes (RANS)-based CFD simulations. A grid convergence test was conducted to accurately capture the wave condition on the free surface based on the overset mesh and wave forcing method. It was found in the roll free decay test that the numerical results agreed well with the experimental results for the natural roll period and roll damping coefficient. It was also observed that the heave motion had an impact on the roll motion, and the responses of the heave and roll motion from the CFD simulations were in reasonable agreement with those from the experiment. Received 24 January 2019, revised 20 March 2019, accepted 11 April 2019 Corresponding author Kwang-Hyo Jung: +82-51-510-2343, kjung@pusan.ac. kr ORCID: https://orcid.org/0000-0002-8229-6655 c 2019, The Korean Society of Ocean Engineers This is an open access article distributed under the terms of the creative commons attribution non-commercial license (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
MULTI-OBJECTIVE OPTIMIZATION METHODOLOGY FOR EFFICIENT CMOS OPERATIONAL AMPLIFIER IN THE DESIGN OF LOW POWER 2 ND ORDER DT SIGMA DELTA MODULATOR

The aim of this work is to design an efficient operational amplifier for the DT sigma delta modulator. For a designer it is very time taking process to design an operational amplifier with the required specifications, so the present work will reduces the design time as well as increases the efficiency and accuracy. This work is categorized into two parts they are, getting optimal dimensions of the transistor by multi objective optimization algorithm in MATLAB and by using them operational amplifier was designed and utilized it in the proposed sigma delta modulator architecture using CADENCE Virtuoso Spectre circuit simulator. For designing the efficient operational amplifier, desired specifications like Gain (Av), Unity gain frequency (UGF), Phase Margin (PM), Power consumption (Pc) were given to the optimization algorithm and the resultant optimal dimensions were generated. Using these dimensions an op-amp is designed which is used in Sigma Delta modulator for achieving high performance measures of Signal-tonoise Ratio (SNR) max, Dynamic Range (DR), Effective Number of Bits (ENOB) are International Journal of Pure and Applied Mathematics Volume 114 No. 1
A Novel Approach for Agriculturists on Mobile Platform for Soybean Leaf Disease Detection and Classification Using Proximal Support Vector Machine

Agriculture production increases the Indian Economy and vice-versa is also true. An expert system in the agricultural field can be a better option to increase agriculture production. Today, use of smart phones is very common by everyone, including the farmers. Introduction of Information and Communication Technologies (ICT) has seen a keen role in daily life of farmers. For effective diseases identification, an existing system used histogram equalization and Support vector machine for preprocessing and classification respectively. However Support vector machine is does not possible for large data set and the existing system is not capable of removing the noise from the diseased leaf images efficiently. To overcome this problem, the proposed system uses proximal support vector machine (PSVM) for diseases classification and median filter algorithm for removing the noise effectively. In proposed system, the captured leaf image is first preprocessed and then it will be converted to binary values. Finally it is passed to centralized server, in which classification process is achieved by using PSVM. Finally the classification result is sent back to mobile devices. The experiment is done in Soybean data set. The proposed system achieves high performance compared with the existing system.
The biplot graphic display of matrices with application to principal component analysis

SUMMARY Any matrix of rank two can be displayed as a biplot which consists of a vector for each row and a vector for each column, chosen so that any element of the matrix is exactly the inner product of the vectors corresponding to its row and to its column. If a matrix is of higher rank, one may display it approximately by a biplot of a matrix of rank two which approximates the original matrix. The biplot provides a useful tool of data analysis and allows the visual appraisal of the structure of large data matrices. It is especially revealing in principal component analysis, where the biplot can show inter-unit distances and indicate clustering of units as well as display variances and correlations of the variables. Any matrix may be represented by a vector for each row and another vector for each column, so chosen that the elements of the matrix are the inner products of the vectors representing the corresponding rows and columns. This is conceptually helpful in understanding properties of matrices. When the matrix is of rank 2 or 3, or can be closely approximated by a matrix of such rank, the vectors may be plotted or modelled and the matrix representation inspected physically. This is of obvious practical interest for the analysis of large matrices. Any n x m matrix Y of rank r can be factorized as
Utilization of ANC and PNC services in Nepal : A multivariate analysis based on Nepal Demographic Health Survey 2001 and 2006

Background: Maternal Mortality is a public health problem in Nepal, which was highest in 1990 among the South Asian countries. Associated factors of maternal mortality are various; among them maternal health services such as antenatal (ANC) and postnatal care (PNC) services are the main. Methods: A multivariate secondary data analysis out based on Nepal Demographic Health Surveys 2001 and 2006. Logistic regression models was performed to compare the utilization of the ANC and PNC services, with background characteristics of women aged between 15 to 49 years old. Results: A total of 8913 reproductive aged groups (15-49) women were taken for analysis and the mean age was 28.59±7.040 years. Logistic regression analysis revealed that health facility delivery (AOR=1.297, 95% CI=1.135-1.481), PNC check-up at health facility (AOD=4.442, 95% CI=2.815-7.011) and PNC service with a skilled health worker (AOD=4.533, 95% CI=2.753-7.465) utilized more in 2006 compared to 2001. This study also found that highly educated women had (AOD, 95% CI=10.823-22.968) more utilized the heath facility during pregnancy and (AOD, 95% CI=2.194-16.950) more likely during a PNC check-up, whereas, educated women were less (AOR=0.043, 95% CI=0.007-0.254) likely consult with a skilled professional. Similarly, antenatal care (ANC) visits (4 or more than four) and ANC visit in the first trimester were increased (95% CI=1.137-1.518) and (AOD=1.041, 95% CI=0.924-1.173) respectively. This study found that educated women, those who were living in urban areas, were more likely to use maternal health services compared to other regions. Conclusion: Increased in utilization of the ANC and PNC services through skilled health workers in a health facility among cohorts of educated women. However, the improvements were not equally distributed across the all regions in the country. This utilization of maternal health services is not sufficient to achieve the MDG goal. Because, health facility delivery is poor and counterpart home delivery is still high in Nepal.
Redshift Surveys and Cosmology: A Summary of the Dunk Island Conference

Abstract Redshift surveys constitute one of the prime tools of observational cosmology. Imaging surveys of the whole sky are now available at a wide range of wavelengths, and provide a basis for the new generation of massive redshift surveys currently in progress. The very large datasets produced by these surveys call for new and sophisticated approaches to the analysis of large-scale structure and the galaxy population. These issues, and some preliminary results from the new redshift surveys, were discussed at the second Coral Sea Cosmology Conference, held at Dunk Island on 24–28 August 1999. This is a summary of the conference; the full conference proceedings are on the WWW at http://www.mso. anu.edu. au/DunkIsland/Proceedings.
Marine productivity estimates from continuous O2/Ar ratio measurements by membrane inlet mass spectrometry

Dissolved oxygen/argon (O2/Ar) ratios in the oceanic mixed layer are indicative of net community production (NCP) because O2 and Ar share similar physical solubility properties, but only O2 is biologically produced and consumed. We describe a membrane inlet mass spectrometer (MIMS) that allows continuous high‐precision shipboard analysis of O2/Ar ratios and eventually other gases, calibrated with discrete samples analyzed in the laboratory. We also present O2/Ar data from the eastern equatorial Pacific. Short‐term reproducibilities of 0.05% were achieved. Meridional gradients and small‐scale phenomena were clearly resolved. O2/Ar undersaturations around the equator reflect the interaction of biological and physical forcings. Mixed‐layer NCP estimated from wind speed‐gas exchange parameterizations was near zero north of 2.75°N, and about 12 mmol m−2 d−1 south of 6.75°S. Ar supersaturations, calculated from MIMS O2/Ar measurements and accompanying O2 concentration measurements, ranged from −0.8 to +3.0%.
Epidemiological survey of dermatophytosis in meat rabbits with alopecia in Portugal

An epidemiological dermatophytosis survey was carried out in farmed rabbits with alopecia in Northern and Central Portugal. Between August and October 2008, samples from suspected clinical cases of alopecia in meat rabbits on industrial farms were collected and cultured by conventional methods. Effects on the prevalence of several variables, such as breed, age, month of sample collection, configuration of the lesions and presence of concomitant infections in the rabbitries were evaluated using a logistic regression model. The overall prevalence of dermatophytes species was 82.7% (95% CI: 80.1-85.3%). Two dermatophytes species were isolated: Trichophyton mentagrophytes (91.9%) and Microsporum canis (8.1%). Five variables were associated with dermatophyte isolation in univariate analysis. The multivariate logistic regression model identified configuration of lesions (OR=3.15; 95% CI: 1.39-7.15%) and the presence of concomitant infections on the farms (OR=2.71; 95% CI: 1.03-7.12%) as risk factors. Considering the paucity of epidemiological reports in this country, these results could make a useful contribution towards the diagnosis and prevention of rabbit dermatophytosis.