Miracle-dz/UniFAR-FTUs huggingface dataset:
Family Influence on Career Trajectories among High School Students in Midlands Province, Zimbabwe

Abstract The study was aimed at finding the parental influence on their children’s career trajectories. The study was informed by the quantitative research approach. A survey design was used in the current study. Data was collected through questionnaires. Data was analysed using descriptive statistics. Results of the study revealed that parents had tremendous influence to their children’s career trajectories. Parental influence was in the form of their direct and indirect involvement in their children’s education. Results also revealed that siblings and other extended family members had also an influence to a lesser extent. The study recommended that schools involve parents in their career development activities as they were found to be an important factor in the children’s careers. The study also recommended a similar study be carried out at national level to enable generalisation of the findings.
La definición sinonímica en la sexta edición del Diccionario de la lengua castellana de la Real Academia Española

espanolLa sexta edicion del Diccionario de la lengua castellana de la Real Academia Espanola se publico en 1822, solamente cinco anos despues de la inmediatamente anterior de 1817, con la urgencia de resolver la ausencia en el mercado de ejemplares. En su redaccion se mantuvieron los mismos criterios acordados para la edicion precedente, lo que demuestra la continuidad entre ambas. Sin embargo, en la practica existen ciertas diferencias que apuntan a una mejora en la precision de la tecnica lexicografica. Una de estas diferencias destacable es la que afecta a la coherencia entre las definiciones sinonimicas y la remision. Por ello, el objetivo de este trabajo es el estudio de su relacion en el diccionario academico, asi como el analisis de las modificaciones que experimentan las definiciones sinonimicas en la edicion de 1822. Dicho estudio ha llevado a constatar que, en la sexta edicion del diccionario, la Academia establecio una distincion entre las definiciones sinonimicas compuestas por varios equivalentes y las compuestas por un solo equivalente, haciendo uso, en este ultimo caso, del recurso lexicografico de la remision para concentrar la definicion en una sola entrada (la mas «usual»), suprimiendo asi definiciones repetidas. EnglishThe sixth edition of the Diccionario de la lengua castellana was urgently published in 1822 by the Real Academia Espanola, due to the lack of copies of the previous edition that had only been published five years before, in 1817. The same criteria that had been applied in the elaboration of precedent edition were followed, thus demonstrating continuity between both editions. However, in practice there are differences that point at an improvement in the accuracy of the lexicographic technique. One of these differences concerns the coherence between the synonymic definitions and the cross-reference. For this reason, this paper aims to evaluate their relation in the academic dictionary, as well as to analyse the modifications that the synonymic definitions experience in the 1822 edition. This study has led to confirm that in the sixth edition of the dictionary the Academia distinguished between synonymic definitions comprising various equivalents and those that were composed of one equivalent, making use in this case of the cross-reference, a lexicographic resource that concentrated the definition in a single entry (the most common one). By doing so, duplicated definitions were suppressed.
Data as Social Capital and the Gift Culture in Research

The value of making research data available is broadly accepted. Policies concerning the open access to research data try to implement new norms calling for researchers to make their data more openly available. These policies either appeal to the common good or focus on publication and citation as an incentive to bring about a cultural change in how researchers share their data with their peers. But when we compare the total number of publications in the fields of science, technology and medicine with the number data publications from the same time period, the number of openly available datasets is rather small. This indicates that current policies on data sharing are not effective in changing behaviours and bringing about the wanted cultural change. By looking at research communities that are more open to data sharing we can study the social patterns that influence data sharing and point us to possible points for intervention and change.
Discrete Dynamic Programming

Dynamic programming is an approach that transforms a multi variable optimization problem into a sequence of single variable optimization problems. Discrete dynamic programming requires us to define and limit ourselves to using only discrete values of the decision variables. It requires us to look at a problem as a network of nodes and links. The nodes represent discrete states of the system and the links from each node represent decisions that can be made, i.e., that are feasible, given the state of the system. A decision based on an initial state value in any stage results in a final state value of that stage, which is an initial state value for the next stage. Converting an optimization problem into a discrete network of nodes and links is the main challenge in using dynamic programming. Solving it once a network is constructed is relatively easy, especially using spreadsheets.
An Effectual Load Distribution Approach based on Transmission Power and Topology Controlled Clustered Environment in Mobile Ad Hoc Network

Mobile ad-hoc networks (MANETs) are demanding considerable improvement in energy efficiency, as their applications are being developed continuously and consistently which also includes high level performance oriented application. In MANET the mobile nodes are dynamic in nature. It also suffers from other two constraints which are Limited Processing capability and Limited Power Supply. Energy Consumption in the nodes takes place mainly during the communication process between the nodes. One of the approaches to improve the efficiency in energy is by applying Transmission Power Control (TPC) technique to adjust the transmission power in communication between nodes. Another approach is, distributing the loads within the network and also maintaining clusters in this uncertain network. Therefore, we investigate different effects of TPC on two load distribution approaches like Localized Energy Aware Routing (LEAR) and Conditional Max-Min Battery Capacity Routing (CMMBCR) protocols for MANETs, in a restricted customized environment by forming clusters within the nodes. This improves the network scalability and also decreases the probability of the network failure. This topology control focuses on the clustering of the nodes in a particular formation and communicates with the nodes according to the status of them in the clusters. The experimental results show a noticeable effect of TPC implementation technique on MANETs in respect to transmission energy consumption and packet received ratio at low node mobility.
A Perceptual Colour Separation Methodology for Automated Quantification of Ki67 and Hematoxylin Stained Digital Histopathology Images

A PERCEPTUAL COLOUR SEPARATION METHODOLOGY FOR AUTOMATED QUANTIFICATION OF KI67 AND HEMATOXYLIN STAINED DIGITAL HISTOPATHOLOGY IMAGES Peter Morreale Advisor: Dr. Robert Dony University of Guelph, 2018 Co-Advisor: Dr. April Khademi This thesis is focussed on the development of a colour separation methodology for quantification of histopathology stains Ki67 and hematoxylin. Traditional methods require tedious manual evaluations prone to inter and intra-observer variability due to inherent subjectivity. Automatic algorithms have been proposed as the solution to manual challenges, however many algorithms are sensitive to wide staining variability common among histopathology images. This thesis proposes a perceptual colour separation framework that models colour information in a way that mimics the human visual systems ability to identify colour content. It is an automatic framework that was evaluated against 30 manually labelled canine mammary TMA core images. The average difference between manual and automatic PI estimates was 3.25%, with a Kappa similarity statistic of 0.86 across four Ki67 cut-off levels, and a linear correlation coefficient of 0.93. Validation studies show the colour separation framework achieves robust results across various Ki67 staining levels.
Building More Expressive Structured Models

Building More Expressive Structured Models Yujia Li Doctor of Philosophy Graduate Department of Computer Science University of Toronto 2017 Structured data and structured problems are common in machine learning, and they appear in many applications from computer vision, natural language understanding, information retrieval, computational biology, and many more. Compared to unstructured problems, where the input data is represented as a vector of independent feature values and output is a scalar prediction like a class label or regression value, both the input and output for structured problems may be objects with internal structure, like sequences, grids, trees or general graphs. Effectively exploiting the structure in the problems can help build efficient prediction models that significantly improve performance. The complexity of the structures requires expressive models that have enough representation capabilities. However, increased model complexity usually leads to increased inference complexity. A key challenge in building more expressive structured models is therefore to balance the model complexity and inference complexity, and explore models that are both expressive enough and have efficient inference. In this thesis, I present our work in the direction of building more expressive structured models, from developing more expressive structured output models, to semi-supervised learning of structured models, and then structured neural network models. The first technical part of the thesis describes a model that uses a new family of expressive high order pattern potentials, for which we characterized the theoretical properties and developed efficient inference and learning algorithms. Next we study semi-supervised learning algorithms for structured prediction problems that can help improve prediction performance by using unlabeled data. Motivated by our observation that standard structured models with iterative inference algorithms can be converted to neural networks, we study in particular structured neural network models for structured problems, and propose a new model that can handle prediction problems on graphs. Discussions about promising future directions are presented at the end of each technical chapter as well as at the end of the thesis.
Optimal Optotype Structure for Monitoring Visual Acuity

Abstract To date, there are no generally accepted optotypes for monitoring visual acuity. All common optotypes are not completely suitable for some reasons. The tasks requiring visual monitoring - investigation of visual development, early diagnostics, assessment of treatment - impose heavy demands on the test stimuli. They must be: (1) suitable for patients of any age; (2) convenient for repeatable examinations; and (3) accurate enough for revealing the smallest physiologically significant changes of visual acuity. From theoretical consideration, one could conclude that the optotypes for monitoring visual acuity should be designed for measuring visual resolution but not recognition, unlike most popular optotypes. The best optotypes for visual resolution are gratinglike stimuli whose recognition could only be based on the high frequency part of the Fourier spectrum around the characteristic frequency (not on the low-frequency components). On the basis of theoretical analysis we elaborated modified 3-bar optotypes, which minimise the possibility of using low-frequency cues for stimulus recognition. In this paper we present the results of theoretical and experimental comparison of these optotypes with the two widely used ones: tumbling-E and standard 3-bar targets. According to the data obtained, our modified optotypes seem to be better than other investigated ones for monitoring visual acuity.
Revisiting the distinction between accomplishments and achievements

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Revisiting the Distinction between Accomplishments and Achievements Fabienne Martin
Rethinking Alternative Data in Institutional Investment

As alternative data steadily become mainstream in finance, institutional investors may benefit from rethinking how they engage with alternative datasets. Specifically, they could gain from rethinking (1) alternative data’s value proposition, (2) how they characterize alternative data, and (3) how they access alternative data. Rethinking their approaches to alternative data in these ways can help investors select alternative datasets that better align with their organizational resources and contexts. Such rethinking offers the greatest advantages when it focuses on building defensive and defensible strategies around alternative data, rather than prioritizing quicker exploitation of short-lived opportunities. Rethinking alternative data will require institutional investors to investigate new partnering possibilities, which should help them weather (and even thrive during) the escalating arms race among financial-market participants for alternative data. Building capacity for alternative data in these ways could also help investors accelerate innovation.
2016 Ieee International Conference on Big Data (big Data) Human Network Usage Patterns Revealed by Telecom Data

—Call detail records (CDRs) collected at telecommuni-cation networks have been well studied to reveal human behaviors such as voice service usage, contact regularities and mobility patterns. With the advances in big data technology, carriers can now collect, store and analyze more data, such as records of user mobile web activities, at scales much larger than CDRs. In this paper, we study 14 features extracted from both call and web records through statistical modeling. We also analyze the impact of locations on voice usage, and examine the correlations between the usage of voice and web services. The results can be used in user profiling, service usage prediction, and network dimensioning.
SPIN Protokolünde Gönderilen Paket Sayısının Azaltılması

Algilayici dugumler sinirli miktarda enerjiye sahiptirler. Bu nedenle algilayici aglar icin enerji tuketimi onemli bir arastirma konusudur. Algilayici dugumler iletisim islemleri esnasinda diger islemlere nazaran daha cok enerji harcarlar. Boylece iletimin azaltilmasi enerji korunumu icin baslica hedeftir. SPIN, algilayici aglarda kullanilan bir veri dagitim protokoludur. Bu protokol uc cesit paket kullanir. Bunlar ADV, REQ ve DATA olarak adlandirilir. SPIN’de kullanilan paket sayisi algilayici agda kullanilan algilayici dugum sayisi ile dogru orantili olarak artar. Bu makalede biz SPIN protokolunde veri yaymak icin kullanilan paket sayisini azaltarak enerji tuketiminde tasarruf yapmak uzere yeni bir duzenleme onerdik. Basarim degerlendirmemiz, bizim duzenlememiz kullanildigi taktirde SPIN protokolunu ilk veri dagitimindan sonra kulllanmanin gerekli olmadigini gosterdi. Ayrica bizim duzenlememizin agdaki paket sayisini ve dolayisi ile tuketilen enerji miktarini azalttigini tespit ettik.
Comprehensive Classification for Blood Test Data to Extract Prediction Factor Candidates

The electric medical record of hospitals stores a huge amount of blood test results and it is expected to estimate the effect of treatments and the cause of diseases by analyzing the results. We have proposed a method to analyze blood test data using Linear Discriminant Analysis (LDA) with a variable selection by non-parametric test. But this method is inconsistent because LDA assumes the data comes from a normal distribution and non-parametric test assumes that the data do not come from any distributions. In this paper, we propose a method to comprehensively analyze blood test data using general machine learning methods. This method includes a new sampling method and a new cross-validation method in a stepwise variable selection method without nonparametric test. We show the experimental results for blood test data and confirm the effectiveness.
Educar en igualdad: prevención de la violencia de género en la adolescencia.

espanolEl presente articulo plantea el tema de la educacion en igualdad y la prevencion de la violencia de genero en la adolescencia. El objetivo de la investigacion es evidenciar el papel crucial que desempenan las instituciones educativas en la superacion de esta problematica generalizada en la sociedad actual, ademas de recalcar la urgente necesidad de una transformacion generacional respecto a la perspectiva de genero, impulsada desde el ambito educativo. La metodologia empleada se fundamenta en el analisis de la productividad cientifica del fenomeno a partir de la revision de los principales contenidos presentes en publicaciones cientificas de impacto, en un periodo comprendido entre 2013 y 2018. Los datos obtenidos permiten realizar una aproximacion al estado del fenomeno y su evolucion. En este trabajo de investigacion se definen los conceptos de sexo, genero y violencia de genero, se describen las caracteristicas y los tipos de violencia de genero, se muestran diversos aspectos del acoso escolar y del maltrato entre iguales y sus implicaciones, desde una perspectiva de genero, y se determinan una serie de medidas educativas que pueden contribuir a mejorar la convivencia en la escuela y prevenir la violencia de genero. Entre las principales conclusiones destaca la importancia de los contextos educativos como espacios para la educacion y el fomento de valores y actitudes sociales deseables. En este sentido, educar en igualdad es fundamental para prevenir la violencia de genero y construir una sociedad mas igualitaria. EnglishThe present article raises the issue of equality education and the prevention of gender violence in adolescence. The objective of the research is to demonstrate the crucial role played by educational institutions in overcoming this generalized problem in today's society, as well as to emphasize the urgent need for a generational transformation with respect to the gender perspective, promoted from the educational field. The methodology used is based on the analysis of the scientific productivity of the phenomenon based on the revision of the main contents present in impact scientific publications, in a period between 2013 and 2018. The data obtained allow an approximation to the state of the phenomenon and its evolution. In this research work, the concepts of sex, gender and gender violence are defined, the characteristics and types of gender violence are described, various aspects of school bullying and peer abuse and their implications are shown, from a gender perspective, and a series of educational measures are determined that can contribute to improving coexistence in school and preventing gender violence. Among the main conclusions highlights the importance of educational contexts as spaces for education and the promotion of values and desirable social attitudes. In this sense, educating in equality is fundamental to prevent gender violence and build a more egalitarian society.
Implementation of parallel k-means algorithm for two-phase method biclustering in Carcinoma tumor gene expression data

Tumor is an abnormal growth of cells that serves no purpose. Carcinoma is a tumor that grows from the top of the cell membrane. In the field of molecular biology, the development of microarray technology is used in data store of disease genetic expression. For each of microarray gene, an amount of information is stored for each trait or condition. In gene expression data clustering can be done with a bicluster algorithm, that’s clustering method not only the objects to be clustered, but also the properties or condition of the object. This research proposed a two-phase method for finding a bicluster. In the first phase, a parallel k-means algorithm is applied to the gene expression data. Then, in the second phase, Cheng and Church biclustering algorithm as one of biclustering method is performed to find biclusters. In this study, we discuss the implementation of two-phase method using biclustering of Cheng and Church and parallel k-means algorithm in Carcinoma tumor gene expression data. From the experimen.
Isosurface Visualization Using Augmented Reality for Improving Tumor Resection Outcomes

Isosurface Visualization Using Augmented Reality for Improving Tumor Resection Outcomes Niveditha Kalavakonda Chair of the Supervisory Committee: Professor Blake Hannaford Electrical Engineering Tumor resection techniques have significantly improved survival rates in cancer patients. However, these require chemotherapy or radiation as follow-up procedures. With the advent of Mixed Reality technology, a wide range of possibilities have opened for the field of surgery. This work explores the use of mixed reality for maximizing tumor margin removed during surgical procedures. An isosurface reconstruction algorithm was integrated with the Microsoft HoloLens, a self-contained holographic computer, to enable visualization of Computed Tomography (CT) imaging superimposed in 3D on the patient. The results suggest that though the device has limitations at its current stage, the Microsoft HoloLens could be used for planning and overlaying the imaging information on the patient for excision of lesions in real-time. The modules developed could also be extended to other types of surgery involving visualization of Digital Imaging and Communication in Medicine (DICOM) files.
IMPLEMENTASI TEKNOLOGI WEB SEMANTIK DALAM APLIKASI PENCARIAN KATALOG ONLINE PERPUSTAKAAN UNIVERSITAS BINA DARMA

Abstract: The online catalog is a catalog of the library system that uses a computer, a catalog can provide a collection of bibliographic information. Catalogs are typically designed to simplify the user. In this research will be made a prototype online library catalog search application that utilizes semantic web technologies. Semantic web technologies allow describing objects and repositories in the form of ontology. Ontology represents semantic levels for knowledge ontology containing semantic entities instead of words. The application was built using JSP (Java Server Page) web based programming. Application of semantic web technologies in the study was able to provide results to the user with the information presented richer. Keywords: Semantic Web,Catalog, JSP