Measuring Semantic Similarity of Documents by Using Named Entity Recognition Methods

The work presented in this thesis was born from the desire to map documents with similar semantic concepts between them. We decided to address this problem as a named entity recognition task, where we have identified key concepts in the texts we use, and we have categorized them. So, we can apply named entity recognition techniques and automatically recognize these key concepts inside other documents. However, we propose the use of a classification method based on the recognition of named entities or key phrases, where the method can detect similarities between key concepts of the texts to be analyzed, and through the use of Poincaré embeddings, the model can associate the existing relationship between these concepts. Thanks to the Poincaré Embeddings’ ability to capture relationships between words, we were able to implement this feature in our classifier. Consequently for each word in a text we check if there are words close to it that are also close to the words that make up the key phrases that we use as Gold Standard. Therefore when detecting potential close words that make up a named entity, the classifier then applies a series of characteristics to classify it. The methodology used performed better than when we only considered the POS structure of the named entities and their n-grams. However, determining the POS structure and the n-grams were important to improve the recognition of named entities in our research. By improving time to recognize similar key phrases between documents, some common tasks in large companies can have a notorious benefit. An important example is the evaluation of resumes, to determine the best professional for a specific position. This task is characterized by consuming a lot of time to find the best profiles for a position, but our contribution in this research work considerably reduces that time, finding the best profiles for a job. Here the experiments are shown considering job descriptions and real resumes, and the methodology used to determine the representation of each of these documents through their key phrases is explained

Laser crystallization of silicon and study by finite element modelling

Laser crystallization of amorphous or microcrystalline silicon films to obtain high-quality polycrystalline films is one of the most promising methods for diminishing costs in the microelectronic and solar cells sectors. During a laser crystallization process light is partially absorbed by the amorphous silicon, heating the sample and, if the temperature rises high enough, causing the reorganization of the film structure into a crystalline one. In this work we show results on the crystallization of non-hydrogenated silicon thin-films by a continuous wave infrared laser, as well as a study of the process with a simple finite elements method (FEM) numerical model based in the dimensional non-linear heat transfer equation with a steady heat source

Finite element method modeling applied to laser crystallization of amorphous silicon

The crystallization by laser of amorphous or microcrystalline silicon films allows to obtain thin, high-quality, polycrystalline Si films, being a very promising method for diminishing costs in the microelectronic and solar cells sectors. During a laser crystallization process, light is partially absorbed in the amorphous silicon film, heating the sample and, if the temperature rises high enough, causing the reorganization of the film structure into a crys- talline one. In this work we show both experimental results on the crystallization of non-hydrogenated silicon thin-films performed by a continuous wave infrared laser are included, as well as a study of the process with a simple finite elements (FEM) numerical model based in the dimensional non-linear heat transfer equation with a steady heat source

Free form metallization of solar cells using Laser Induced Forward Transfer

Front metallization is an expensive, fundamental step in the fabrication of solar cells. Laser additive direct writing techniques, such as Laser Induced Forward Transfer (LIFT), can be used for printing optimized metallization patterns or free form personalized designs with applications in building integrated photovoltaics. In this work, metallic fingers and busbars have been printed onto different rigid and flexible photovoltaic materials using commercial, high viscosity, micron-sized particles, silver-based pastes. Printed lines show very large aspect ratios, low electrical resistivity and good adherence to the substrate. Functional test cells have been metallized from unfinished CIGS flexible solar cells

PERBANDINGAN MODEL PEMBELAJARAN CORE (CONNECTING, ORGANIZING, REFLECTING AND EXTENDING) DAN DISCOVERY LEARNING DALAM PEMBELAJARAN MATEMATIKA TERHADAP KEMAMPUAN PEMECAHAN MASALAH MATEMATIS DAN SELF-REGULATED LEARNING SISWA SMA

Pada pelaksanaan proses pembelajaran dengan menggunakan model pembelajaran Discovery Learning terlihat bahwa interaksi antar siswa masih sangat kurang. Selama proses diskusi, sebagian besar kelompok belum melibatkan setiap anggotanya karena anggotanya mengerjakan LKS secara individu, sehingga diskusi didominasi oleh beberapa siswa saja. Akibatnya, ketika dihadapkan dengan persoalan matematika siswa kurang mampu untuk menyelesaikannya. Salah satu upaya untuk mengatasi masalah tersebut adalah dengan menggunakan model pembelajaran inovatif lainnya. Salah satunya dengan penggunaan model pembelajaran CORE (Connecting, Organizing, Reflecting, dan Extending). Model pembelajaran CORE merupakan model pembelajaran dengan metode diskusi dengan menghubungkan informasi lama dengan informasi baru, mengorganisasikan sejumlah materi yang bervariasi, merefleksikan segala sesuatu yang peserta didik pelajari, dan mengembangkan lingkungan belajar. Tujuan dari penelitian ini adalah mengkaji perbedaan kemampuan pemecahan masalah matematis dan Self-Regulated Learning siswa yang menggunakan model pembelajaran CORE dengan siswa yang menggunakan model pembelajaran Discovery Learning dalam pembelajaran. Adapun metode penelitian yang digunakan adalah kuantitatif eksperimen, dengan desain kuasi eksperimen. Populasi dalam penelitian ini adalah seluruh siswa SMAN 13 Bandung. Dua dari tiga belas kelas XI yang ada dipilih sebagai sampel penelitian. Instrumen yang digunakan adalah tes dan angket. Analisis data yang digunakan adalah uji kesamaan dua rerata dengan uji-t dua pihak menggunakan Independent Sample T-Test. Berdasarkan analisis pada keseluruhan tahapan penelitian dapat disimmpulkan bahwa: 1) Kemampuan pemecahan masalah matematis siswa SMA yang memperoleh model pembelajaran CORE tidak lebih baik dari kemampuan pemecahan masalah matematis siswa SMA yang memperoleh model pembelajaran Discovery Learning, 2) Self-Regulated Learning siswa yang dalam pembelajaran matematikanya menggunakan model pembelajaran CORE lebih baik daripada siswa yang menggunakan model pembelajaran Discovery Learning. Kata Kunci: CORE (Connecting, Organizing, Reflecting, and Extending), Discovery Learning, Model Pembelajaran, Pemecahan Masalah Matematis, Self-Regulated Learning

COLLABORATIVE WEB-BASED TAGGER FOR NAMED ENTITIES IN THE TASK OF INFORMATION EXTRACTION (ETIQUETADOR COLABORATIVO BASADO EN WEB PARA ENTIDADES NOMBRADAS EN LA TAREA DE EXTRACCIÓN DE LA INFORMACIÓN)

AbstracNowadays, there exists a huge amount of information on the World Wide Web and since every day is mainly generated a lot of text data, the problem of information overload arise. In this way, the task of extracting meaningful information from text has gained the significant attention of researchers. In this paper, we propose a collaborative tagging system to help users in the task of highlighting important information in plain text files. Additionally, it allows converting tagged texts into a structured format. The web-based system is proposed in order to exploit the relevant content information provided by tagger users, since actual collaborative tagging systems suffer from issues such as tag scarcity or ambiguous labeling. Approaches such as the proposed here can facilitate to obtain better quality in tags and in any domain, allowing to achieve significant improvements in information extraction through named entities extraction, avoiding the noise of information overload.ResumenHoy en día existe una gran cantidad de información en Internet y ya que cada día se genera mucha información principalmente en forma de texto, el problema de sobrecarga de información se hace presente. En este sentido, la tarea de extraer información significativa de los textos ha ganado la atención de investigadores. En este artículo, proponemos un sistema de etiquetamiento colaborativo para ayudar a los usuarios en la tarea de resaltar información importante en archivos de texto plano. Adicionalmente, el sistema permite convertir textos etiquetados a un formato estructurado. El sistema basado en web es propuesto con el fin de explotar el contenido relevante de la información proporcionada por los usuarios etiquetadores, ya que los sistemas de etiquetamiento colaborativos actuales sufren de algunos problemas tales como la escasez de etiquetas o el etiquetado ambiguo. Enfoques como el propuesto aquí pueden facilitar la obtención de etiquetas con mejor calidad y en cualquier dominio, permitiendo lograr mejoras significativas en la extracción de información a través de la extracción de entidades nombradas, evitando el ruido en la sobrecarga de información

Perfil de responsabilidad social empresarial para las entidades promotoras de salud - régimen contributivo de Bucaramanga y su área metropolitana

Introducción: Este proyecto busca determinar el perfil y el análisis de las prácticas actuales de responsabilidad social empresarial en las entidades promotoras de servicios de salud de Bucaramanga y su área metropolitana, a partir del análisis cualitativo y cuantitativo de variables, estableciendo como estas entidades promueven el desarrollo integral de la salud. Materiales y Métodos: El estudio contempló un enfoque cuantitativo de tipo analítico, en el cual se realizó un censo en el cual participaron 11 Entidades Promotoras de Salud (EPS) en cada una de ellas se midieron un total de 72 variables, a partir de ello seformula una metodología cualitativa para medir el nivel de gestión en Responsabilidad Social Empresarial (RSE) también una valoración cuantitativa mediante un análisis multivariado con el programa Numerical Taxonomy System (NTSYS) que permitiera determinar perfiles en Responsabilidad Social Empresarial. Resultados y Discusión: A partir de los resultados se pudo observar cómo se encontraban las empresas del sector respecto a Responsabilidad Social Empresarial, así como identificar el nivel de gestión que cuentan las EPS en el tema de Responsabilidad Social Empresarial, adicional a esto se determinó que no existe un Perfil dominante en el Sector en materia de Responsabilidad Social Empresarial. Conclusiones: Se ha establecido que las Entidades Promotoras de Salud, tienen un modelo de responsabilidad social reactivo, cada una lleva a cabo diversas acciones las entidades que no son suficientes para consolidar una estrategia del sector para el desarrollo de un modelo integral de salud que contribuyen a la dimensión social del desarrollo sostenible. Palabras clave: Atención Integral de Salud, Ética Institucional, Instituciones de Salud, Responsabilidad Social. (Fuente: DeCS BIREME).Cómo citar este artículo: Morales Méndez JD, Galeano Barrera CJ, Muñoz Ospina JF. Perfil de responsabilidad social empresarial para las entidades promotoras de salud - régimen contributivo de Bucaramanga y su área metropolitana. Rev Cuid. 2014; 5(1): 633-43.

Laser functionalization of surfaces

The treatment of surfaces by physical or chemical methods is a very usual way to change their original properties. Although the most common use of a surface functionalization is for tribology aims, modifications of the topography that leads to changes in the surface roughness, its hydrophilicity or hydrophobicity, its light scattering behavior, biocompatibility or even aesthetic changes are possible. In this field, laser sources have proven to be a most versatile and useful tool, being a clean and fast way to achieve any of those objectives. In this work we show the results of functionalization by laser texturing of four different materials

Gb3/cd77 Is a Predictive Marker and Promising Therapeutic Target for Head and Neck Cancer

Head and neck squamous cell carcinoma is the sixth leading cancer in the world. This cancer is difficult to treat and is characterized by recurrences that are often fatal. This cancer is generally removed surgically, but it often regrows from the edges of the lesion from where most recurrences reappear. In this study, we have investigated if the expression of GB3 in human cell lines, tissues from patient biopsies, and a murine animal model could be used as an early and determinant marker of HNC. We found that in all the investigated systems, this marker appears in neoplastic cells from the very early stages of their malignant transformation. Our conclusions support the hypothesis that GB3 is a reliable and independent target for HNC identification and selective delivery of treatments. Furthermore, we show that the level of expression of this marker correlates with the degree of malignancy of the tumor. These studies suggest that GB3 may provide the basis for the early identification and new targeted therapies for head and neck cancer.Funding: This research was funded by ISCIII Projects ref. PI19/00349, DTS19/00033, co-funded by ERDF/ESF, “Investing in your future”; NanoBioApp Research Network (MINECO-17-MAT2016-81955-REDT), COST action Nano2Clinic CA17140, and IDIVAL for the INNVAL 19/12 and INNVAL20/13 projects