Tweeting Behaviour during Train Disruptions within a City

In a smart city environment, citizens use social media for communicating and reporting events. Existing work has shown that social media tools, such as Twitter and Facebook, can be used as social sensors to monitor events in real-time as they happen (e.g. riots, natural disasters and sport events). In this paper, we study the reactions of citizens in social media towards train disruptions within a city. Our study using 30 days of tweets in a large city shows that citizens react differently to train disruptions by, for instance, displaying unique behaviours in tweeting depending on the time of the disruption. Specifically, for working days, tweets related to train disruptions are typically generated during rush hour periods. In contrast, during weekends, urban citizens tended to tweet about train disruptions during late evenings. Using these insights, we develop a supervised approach to predict whether a train disruption tweet will be retweeted and propagated on the social network, by using features, such as time, user, and the content of tweets. Our experimental results show that we can effectively predict when a train disruption tweet is retweeted by using such features

Topic-centric Classification of Twitter User's Political Orientation

In the recent Scottish Independence Referendum (hereafter, IndyRef), Twitter offered a broad platform for people to express their opinions, with millions of IndyRef tweets posted over the campaign period. In this paper, we aim to classify people's voting intentions by the content of their tweets---their short messages communicated on Twitter. By observing tweets related to the IndyRef, we find that people not only discussed the vote, but raised topics related to an independent Scotland including oil reserves, currency, nuclear weapons, and national debt. We show that the views communicated on these topics can inform us of the individuals' voting intentions ("Yes"--in favour of Independence vs. "No"--Opposed). In particular, we argue that an accurate classifier can be designed by leveraging the differences in the features' usage across different topics related to voting intentions. We demonstrate improvements upon a Naive Bayesian classifier using the topics enrichment method. Our new classifier identifies the closest topic for each unseen tweet, based on those topics identified in the training data. Our experiments show that our Topics-Based Naive Bayesian classifier improves accuracy by 7.8% over the classical Naive Bayesian baseline

Online Website Builder for Non-Programmers

Developing a website is not simple. One must have some basic knowledge in programming to build a website from scratch. That is why the author has developed an Online Website Builder for Non-Programmers to help non-programmer to develop website on their own. The objectives of this project is to develop a system that can really help in building a website with less programming knowledge and website development skills. This system is using basic approach where the user will follow a step-by-step method in developing their website. The system is to be used by any level of society from who do not have the basic in programming. This will also stimulate the numbers of websites in the internet when every one no matter with programming knowledge or not can develop website on their own. The author used 4 major phases in development methodology. The phases are Planning and Analysis, Designing, Coding and Development and Delivery. As the result, an online system has been built to help the people with no programming background to build their own website besides encouraging Malaysian business people to build a static website that will help them in terms of their business marketing. The system has some limitation and a few future enhancements could be done to make this system more reliable

Normalising Medical Concepts in Social Media Texts by Learning Semantic Representation

Automatically recognising medical con- cepts mentioned in social media messages (e.g. tweets) enables several applications for enhancing health quality of people in a community, e.g. real-time monitoring of infectious diseases in population. How- ever, the discrepancy between the type of language used in social media and med- ical ontologies poses a major challenge. Existing studies deal with this challenge by employing techniques, such as lexi- cal term matching and statistical machine translation. In this work, we handle the medical concept normalisation at the se- mantic level. We investigate the use of neural networks to learn the transition be- tween layman’s language used in social media messages and formal medical lan- guage used in the descriptions of medi- cal concepts in a standard ontology. We evaluate our approaches using three differ- ent datasets, where social media texts are extracted from Twitter messages and blog posts. Our experimental results show that our proposed approaches significantly and consistently outperform existing effective baselines, which achieved state-of-the-art performance on several medical concept normalisation tasks, by up to 44%

Mondo et le Ciapacan : J.M.G. Le Clézio et le rapport au monde Mondo and le Ciapacan : J.M.G. Le Clézio and the Relation to the World

Résumé Cet article porte sur Mondo, la nouvelle de 68 pages (6 chapitres) qui ouvre le recueil Mondo et autres histoires, publié en 1978, par Jean-Marie Gustave Le Clézio. Mondo est une histoire reprenant les thèmes chers à l’auteur, tels que, le voyage, la ville et la nature, la marginalité, l’enfant en quête d’un sens à la vie, etc. Nous cherchons dans cet article à montrer en quoi Mondo est le personnage porte-parole de l’auteur. Et quel est le rapport que l’auteur entretient avec la politique et la société moderne ? Mots-clés : Jean-Marie Gustave Le Clézio, Mondo et autre histoires, Mondo.   Abstract This article focuses on Mondo, the 68 pages (and 6 chapters) short story which is the first one in the collection Mondo et autres histoires, published in 1978 by Jean-Marie Gustave Le Clézio. Mondo typically deals with the favorite themes of the author, like traveling, city and nature, people living on the fringes of society, children in search of the meaning of life, etc. In this article, we will try to show why Mondo can be considered as the spokesman character of the author and we will also study the relationships of the author with politics and modern society. Keywords: Jean-Marie Gustave Le Clézio, Mondo et autre histoires, Mondo

A framework for enhancing the query and medical record representations for patient search

Electronic medical records (EMRs) are digital documents stored by medical institutions that detail the observed symptoms, the conducted diagnostic tests, the identified diagnoses and the prescribed treatments. These EMRs are being increasingly used worldwide to improve healthcare services. For example, when a doctor compiles the possible treatments for a patient showing some particular symptoms, it is advantageous to consult the information about patients who were previously treated for those same symptoms. However, finding patients with particular medical conditions is challenging, due to the implicit knowledge inherent within the patients' medical records and queries - such knowledge may be known by medical practitioners, but may be hidden from an information retrieval (IR) system. For instance, the mention of a treatment such as a drug may indicate to a practitioner that a particular diagnosis has been made for the patient, but this diagnosis may not be explicitly mentioned in the patient's medical records. Moreover, the use of negated language (e.g.\ `without', `no') to describe a medical condition of a patient (e.g.\ the patient has no fever) may cause a search system to erroneously retrieve that patient for a query when searching for patients with that medical condition (e.g.\ find patients with fever). This thesis focuses on enhancing the search of EMRs, with the aim of identifying patients with medical histories relevant to the medical conditions stated in a text query. During retrieval, a healthcare practitioner indicates a number of inclusion criteria describing the medical conditions of the patients of interest. To attain effective retrieval performance, we hypothesise that, in a patient search system, both the information needs and patients' histories should be represented based upon \emph{the medical decision process}. In particular, this thesis argues that since the medical decision process typically encompasses four aspects (symptom, diagnostic test, diagnosis and treatment), a patient search system should take into account these aspects and apply inferences to recover the possible implicit knowledge. We postulate that considering these aspects and their derived implicit knowledge at three different levels of the retrieval process (namely, sentence, medical record and inter-record levels) enhances the retrieval performance. Indeed, we propose a novel framework that can gain insights from EMRs and queries, by modelling and reasoning upon information during retrieval in terms of the four aforementioned aspects at the three levels of the retrieval process, and can use these insights to enhance patient search. Firstly, at the sentence level, we extract the medical conditions in the medical records and queries. In particular, we propose to represent only the medical conditions related to the four medical aspects in order to improve the accuracy of our search system. In addition, we identify the context (negative/positive) of terms, which leads to an accurate representation of the medical conditions both in the EMRs and queries. In particular, we aim to prevent patients whose EMRs state the medical conditions in the contexts different from the query from being ranked highly. For example, preventing patients whose EMRs state ``no history of dementia'' from being retrieved for a query searching for patients with dementia. Secondly, at the medical record level, using external knowledge-based resources (e.g.\ ontologies and health-related websites), we leverage the relationships between medical terms to infer the wider medical history of the patient in terms of the four medical aspects. In particular, we estimate the relevance of a patient to the query by exploiting association rules that we extract from the semantic relationships between medical terms using the four aspects of the medical process. For example, patients with a medical history involving a \emph{CABG surgery} (treatment) can be inferred as relevant to a query searching for a patient suffering from \emph{heart disease} (diagnosis), since a CABG surgery is a treatment of heart disease. Thirdly, at the inter-record level, we enhance the retrieval of patients in two different manners. First, we exploit knowledge about how the four medical aspects are handled by different hospital departments to gain a better understanding about the appropriateness of EMRs created by different departments for a given query. We propose to aggregate EMRs at the department level (i.e.\ inter-record level) to extract implicit knowledge (i.e.\ the expertise of each department) and model this department's expertise, while ranking patients. For instance, patients having EMRs from the cardiology department are likely to be relevant to a query searching for patients who suffered from a heart attack. Second, as a medical query typically contains several medical conditions that the relevant patients should satisfy, we propose to explicitly model the relevance towards multiple query medical conditions in the EMRs related to a particular patient during retrieval. In particular, we rank highly those patients that match all the stated medical conditions in the query by adapting coverage-based diversification approaches originally proposed for the web search domain. Finally, we examine the combination of our aforementioned approaches that exploit the implicit knowledge at the three levels of the retrieval process to further improve the retrieval performance by adapting techniques from the fields of data fusion and machine learning. In particular, data fusion techniques, such as CombSUM and CombMNZ, are used to combine the relevance scores computed by the different approaches of the proposed framework. On the other hand, we deploy state-of-the-art learning to rank approaches (e.g.\ LambdaMART and AdaRank) to learn from a set of training data an effective combination of the relevance scores computed by the approaches of the framework. In addition, we introduce a novel selective ranking approach that uses a classifier to effectively apply one of the approaches of the framework on a per-query basis. This thesis draws insights from a thorough evaluation and analysis of the proposed framework using a standard test collection provided by the TREC Medical Records track. The experimental results show the effectiveness of the framework. In particular, the results demonstrate the importance of dealing with the implicit knowledge in patient search by focusing on the medical decision criteria aspects at the three levels of the retrieval process

Bioekologi Ikan Glodok (Mudskipper) Berdasarkan Tingkat Kerapatan Mangrove di Kawasan Ekosistem Esensial (KEE) Muara Kali Ijo, Kabupaten Kebumen

Ekosistem mangrove merupakan ekosistem tinggi produktivitas yang memberi kontribusi penting bagi ekosistem pesisir. Hutan mangrove menjadi kunci utama penyedia makanan bagi organisme yang tinggal di sekitar seperti ikan glodok. Ikan glodok hidup di daerah muara sungai sampai pinggiran pantai dan mencari makanan di daerah mangrove sehingga kawasan hutan mangrove sangat berperan penting bagi kelimpahan ikan glodok. Tujuan dari penelitian ini adalah untuk mengetahui tingkat kerapatan mangrove, bioekologi ikan glodok dilihat dari pola pertumbuhan dan faktor kondisi, serta hubungan tingkat kerapatan mangrove dengan kelimpahan ikan glodok di KEE Muara Kali Ijo Kabupaten Kebumen. Pengambilan data pada penelitian ini menggunakan metode purposive random sampling dan data dianalisis dengan analisis korelasi dan regresi. Berdasarkan hasil penelitian, tingkat kerapatan mangrove masuk dalam kategori kerapatan sangat padat dengan tingkat kerapatan berkisar antara 1800-3800, Pola pertumbuhan ikan glodok adalah allometrik negatif dengan nilai b berkisar antara antara 2,33-2,8 dan nilai faktor kondisi berkisar antara 1,00-1,02 yang menunjukkan bahwa ikan tidak gemuk. Hasil uji regresi didapatkan bahwa terdapat hubungan kuat antara kerapatan mangrove dengan kelimpahan ikan glodok di Muara Kali Ijo (r=0,75591). Hubungan antara kerapatan mangrove dengan kelimpahan ikan glodok bersifat berbanding terbalik

Influencia De Los Factores De Motivación En El Desempeño Laboral De Los Trabajadores De La Empresa Silar Peru S.A.C. Año 2017

En estos tiempos, por la gran competencia que existe en el mercado, las organizaciones están centradas en producir más destrezas, habilidades, y conocimientos en el empleado y trabajador que tiene a su cargo. Ante los diversos desafíos que se enfrentan todos los días, las organizaciones necesitan cambiar sus planes de trabajo. Por lo tanto, para las empresas, es necesario generar nuevas tecnologías desde la perspectiva de las ocupaciones y los clientes, de alguna manera consistentemente con la calidad del capital humano. De acuerdo a lo anterior, para la mejora de las capacidades del trabajador es necesario poner en práctica nuevas estrategias organizacionales. Por eso mismo, la motivación influye en el día a día de las personas, como una herramienta con la cual se alcanza metas y objetivos. Por eso, la motivación representa un hecho de carácter universal y además es un factor sustancioso del comportamiento organizacional, pues se enfoca directamente en el esfuerzo, el ánimo y el comportamiento del trabajador, produciendo en este un sentimiento de satisfacción con respecto a lo que realiza; también, incentivando a que trabaje más por la importancia que realiza y ejerce en la organización. Como se mencionó anteriormente, este trabajo de investigación se centra en el valor de los talentos en la organización, ya que muestran algunos factores que determinan la motivación laboral y cómo estos factores afectan su desempeño. Se cree que, al implementar políticas que beneficien a los empleados de la organización, es posible hacer que su trabajo se sienta completo, aumentando así la productividad de la organización.Trabajo de suficiencia profesiona

The first records of Red-legged Crake Rallina fasciata for Cambodia

First paragraph: The Red-legged Crake Rallina fasciata is a little-known rallid, listed as Least Concern by BirdLife International (2015), with a range extending across most of South-East Asia (Robson 2008, Taylor 2015). However, the species has been rarely recorded, with the exception of a few locations in Singapore and Thailand (Li 2009, Wong 2011, Pierce et al. 2013), partly because of its skulking nature; it is seldom flushed or observed, and very rarely encountered as camera-trap by-catch during wildlife surveys, indicating that it may indeed be genuinely scarce. This note is a compilation of the only three confirmed Redlegged Crake records from Cambodia. Two are new records, whilst the third has been previously reported (Goes 2013) but is presented here with documentary evidence. These records confirm the species’s presence in three protected areas in widely separated parts of the country, and offer limited but important information on its ecology and likely status

PENGARUH KUALITAS PELAYANAN TERHADAP KEPUASAN SERTA DAMPAKNYA PADA KEPERCAYAAN (Suatu Survei Pada Pasien di Instalasi Rawat Jalan Rumah Sakit Mitra Husada Lampung)

Penelitian ini bertujuan untuk menganalisis dan mengetahui pengaruh pengaruh kualitas pelayanan terhadap kepuasan serta dampaknya pada pasien di Instalasi Rawat Jalan Rumah Sakit Mitra Husada Lampung. Hasil penelitian ini diharapkan dapat menjadi bahan masukan bagi Rumah Sakit Mitra Husada Lampung dalam menyelenggarakan pelayanan kesehatan khususnya di Unit Rawat Jalan. Metode penelitian yang digunakan adalah analisis deskriptif dan verifikatif. Pengumpulan data yang digunakan adalah wawancara dengan menggunakan kuesioner disertai dengan teknik observasi dan kepustakaan, teknik pengambilan sampel menggunakan consecutive sampling. Pengumpulan data di lapangan dilaksanakan pada tahun 2022. Teknik analisis data menggunakan Analisis Jalur. Hasil penelitian menunjukan bahwa secara umum persepsi pasien di Instalasi Rawat Jalan Rumah Sakit Mitra Husada Lampung tentang kualitas pelayanan, kepuasan, dan kepercayaan pasien relatif cukup baik. Kualitas pelayanan berpengaruh terhadap kepuasan pasien baik secara parsial maupun simultan. Kepuasan berpengaruh terhadap kepercayaan pasien, dan kualitas pelayanan berpengaruh terhadap kepercayaan pasien melalui kepuasan di Instalasi Rawat Jalan Rumah Sakit Mitra Husada Lampung. Kata Kunci : Kualitas Pelayanan Kesehatan, Kepuasan Pasien, Kepercayaan Pasie