Population Density-based Hospital Recommendation with Mobile LBS Big Data

The difficulty of getting medical treatment is one of major livelihood issues in China. Since patients lack prior knowledge about the spatial distribution and the capacity of hospitals, some hospitals have abnormally high or sporadic population densities. This paper presents a new model for estimating the spatiotemporal population density in each hospital based on location-based service (LBS) big data, which would be beneficial to guiding and dispersing outpatients. To improve the estimation accuracy, several approaches are proposed to denoise the LBS data and classify people by detecting their various behaviors. In addition, a long short-term memory (LSTM) based deep learning is presented to predict the trend of population density. By using Baidu large-scale LBS logs database, we apply the proposed model to 113 hospitals in Beijing, P. R. China, and constructed an online hospital recommendation system which can provide users with a hospital rank list basing the real-time population density information and the hospitals' basic information such as hospitals' levels and their distances. We also mine several interesting patterns from these LBS logs by using our proposed system

New and Existing Approaches Reviewing of Big Data Analysis with Hadoop Tools

             الجميع متصل بوسائل التواصل الاجتماعي مثل) الفيس بوك وتويتر ولنكدان والانستغرام ...الخ) , التي تتولد من خلالها كميات هائلة من البيانات لا تستطيع التطبيقات التقليدية من معالجتها , حيث تعتبر وسائل التواصل الاجتماعي منصة مهمة لتبادل المعلومات والآراء والمعرفة التي يجريها العديد من المشتركين ,على الرغم من هذه السمات الأساسية ، تساهم البيانات الضخمة أيضًا في العديد من المشكلات ، مثل جمع البيانات ، والتخزين ، والنقل ، والتحديث ، والمراجعة ، والنشر ، والمسح الضوئي ، والتصور ، وحماية البيانات ... إلخ. للتعامل مع كل هذه المشاكل، ظهرت الحاجة إلى نظام مناسب لا يقوم فقط بإعداد التفاصيل، بل يوفر أيضًا تحليلًا ذا مغزى للاستفادة من المواقف الصعبة، سواء ذات الصلة بالأعمال التجارية، أو القرار المناسب، أو الصحة، أو وسائل التواصل الاجتماعي، أو العلوم، الاتصالات، البيئة... إلخ.يلاحظ المؤلفون من خلال قراءة الدراسات السابقة أن هناك تحليلات مختلفة من خلال Hadoop وأدواته المختلفة مثل المشاعر في الوقت الفعلي وغيرها. ومع ذلك، فإن التعامل مع هذه البيانات الضخمة يعد مهمة صعبة. لذلك فإن هذا النوع من التحليل يكون بكفاءه أكثر أكثر كفاءة فقط من خلال نظام Hadoop البيئي.، الغرض من هذه الورقة هو تحليل الأدبيات المتعلقة بتحليل البيانات الضخمة لوسائل التواصل الاجتماعي باستخدام إطار Hadoop لمعرفة أدوات التحليل تقريبًا الموجودة في العالم تحت مظلة Hadoop وتوجهاتها بالإضافة إلى الصعوبات والأساليب الحديثة لها للتغلب على تحديات البيانات الضخمة في المعالجة غير المتصلة وفي الوقت الفعلي. تعمل التحليلات في الوقت الفعلي على تسريع عملية اتخاذ القرار إلى جانب توفير الوصول إلى مقاييس الأعمال وإعداد التقارير. كما تم توضيح المقارنة بين Hadoop و spark.Everybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, science, telecommunications, the environment, etc. Authors notice through reading of previous studies that there are different analyzes through HADOOP and its various tools such as the sentiment in real-time and others. However, dealing with this Big data is a challenging task. Therefore, such type of analysis is more efficiently possible only through the Hadoop Ecosystem. The purpose of this paper is to analyze literature related analysis of big data of social media using the Hadoop framework for knowing almost analysis tools existing in the world under the Hadoop umbrella and its orientations in addition to difficulties and modern methods of them to overcome challenges of big data in offline and real –time processing. Real-time Analytics accelerates decision-making along with providing access to business metrics and reporting. Comparison between Hadoop and spark has been also illustrated

Migration in the 20th Century with Emphasis on Spain

This research reflects the most important aspects of migration as it pertains to Spain. This includes migration to the country, from the country, and within the country. Historical analysis previous to the 20th century is included as well as analysis of more contemporary migration. At the end there is an interview comparison with a modern immigrant that lives in the United States, which allows for a comparison of a normal migrant story with a real life example

State College Times, December 6, 1933

Volume 22, Issue 42https://scholarworks.sjsu.edu/spartandaily/12936/thumbnail.jp

The Daily Texan

Texas Student Medi

Towards Operational Research Infrastructures with FAIR Data and Services

Environmental research infrastructures aim to provide scientists with facilities, resources and services to enable scientists to effectively perform advanced research. When addressing societal challenges such as climate change and pollution, scientists usually need data, models and methods from different domains to tackle the complexity of the complete environmental system. Research infrastructures are thus required to enable all data, including services, products, and virtual research environments is FAIR for research communities: Findable, Accessible, Interoperable and Reusable. In this last chapter, we conclude and identify future challenges in research infrastructure operation, user support, interoperability, and future evolution

Scaling out Big Data Distributed Pricing in Gaming Industry

Game companies have millions of customers, billions of transactions and petabytes of other data related to game events. The vast volume and complexity of this data make it practically impossible to process and analyze it using traditional relational database models (RDBMs). This kind of data can be identified as Big Data, and in order to handle it in efficient manner, multiple issues have to be taken into account. It is more straightforward to answer to these problems when developing completely new system, that can be implemented with all the new techniques and platforms to support big data handling. However, if it is needed to modify an existing system to accommodate data volumes of big data, there are more issues to be taken into account. This thesis starts with the clarification of the definition 'big data'. Scalability and parallelism are key factors for handling big data, thus they will be explained and some of the conventions to do them will be reviewed. Next, different tools and platforms that do parallel programming, are presented. The relevance of big data in gaming industry is briefly explained, as well as the different monetization models that games have. Furthermore, price elasticity of demand is explained to give better understanding of a Dynamic Pricing Engine and what does it do. In this thesis, I solve a bottleneck that emerges in data transfer and processing when introducing big data to an existing system, a Dynamic Pricing Engine, by using parallel programming in order to scale the system. Spark will be used to deal with fetching and processing distributed data. The main focus is in the impact of using parallel programming in comparison to the current solution, which is done with PHP and MySQL. Furthermore, Spark implementations are done against different data storage solutions, such as MySQL, Hadoop and HDFS, and their performance is also compared. The results for utilizing Spark for the implementation show significant improvement in performance time for processing the data. However, the importance of choosing the right data storage for fetching the data can't be understated, as the speed for fetching the data can widely variate.Peliyhtiöillä on miljoonia asiakkaita, miljardeja maksutapahtumia ja petatavuja pelin tapahtumiin liittyvää dataa. Tämän datan suuri määrä ja kompleksisuus tekevät sen prosessoimisesta sekä analysoimisesta lähes mahdotonta tavallisilla relaatiotietokannoilla. Tällaista dataa voidaan kutsua Big Dataksi, ja jotta sen käsittely olisi tehokasta, useita asioita on otettava huomioon. Uuden järjestelmän toteutuksessa näihin ongelmiin pystytään vastaamaan melko johdonmukaisesti, sillä uusimmat tekniikat ja alustat voidaan ottaa tällöin helposti käyttöön. Jos kyseessä on jo olemassa oleva järjestelmä, jota halutaan muuttaa vastaamaan big datamaisiin datamääriin, huomioon otettavien asioden määrä kasvaa. Tämän diplomityön aluksi selitetään termi 'Big Data'. Big Datan kanssa työskentelyyn tarvitaan skaalautuvuutta ja rinnakkaisuutta, joten nämä termit, sekä näiden yleisimmät käytännöt käydään läpi. Seuraavaksi esitellään työkaluja ja alustoja, joilla on mahdollista tehdä rinnakkaisohjelmointia. Big Datan merkitys peliteollisuudessa selitetään lyhyesti, kuten myös eri monetisaatiomallit, joita peliyritykset käyttävät. Lisäksi kysynnän hintajousto käydään läpi, jotta lukijalle olisi helpompaa ymmärtää, mikä seuraavaksi esitelty Apprien on ja mihin sitä käytetään. Tässä diplomityössä etsin ratkaisua Big Datan siirrossa ja prosessoinnissa ilmenevään ongelmaan jo olemassa olevalle järjestelmälle, Apprienille. Tämä pullonkaula ratkaistaan käyttämällä rinnakkaisohjelmointia Sparkin avulla. Pääasiallinen painopiste on selvittää rinnakkaisohjelmoinnilla saavutettu hyöty verrattuna nykyiseen ratkaisuun, joka on toteutettu PHP:llä ja MySQL:llä. Tämän lisäksi, Spark toteusta hyödynnetään eri datan säilytysmalleilla (MySQL, Hadoop+HDFS), ja niiden suorityskykyä vertaillaan. Tulokset, jotka saatiin Spark toteutusta hyödyntämällä, osoittavat merkittävän parannuksen suoritusajassa datan prosessoimisessa. Oikean tietomallin valitsemisen tärkeyttä ei pidä aliarvioida, sillä datan siirtämiseen käytetty aika vaihtelee myös huomattavasti alustasta riippuen

A list of websites and reading materials on strategy & complexity

The list has been developed based on a broad interpretation of the subject of ‘strategy & complexity’. Resources will therefore more, or less directly relate to ‘being strategic in the face of complexity’. Many of the articles and reports referred to in the attached bibliography can be accessed and downloaded from the internet. Most books can be found at amazon.com where you will often find a number of book reviews and summaries as well. Sometimes, reading the reviews will suffice and will give you the essence of the contents of the book after which you do not need to buy it. If the book looks interesting enough, buying options are easy

The Call of the Wild —— An Eco-critical Reading of The Old Man and the Sea

Under the circumstances of the severe ecological crisis, ecocriticism has become a hot topic. In recent years, the natural world in Hemingway’s works has come into the view of the ecocritics. This paper is, according to the theory of ecocriticism, to interpret Hemingway’s masterpiece The Old Man and the Sea from the perspective of anti-ecology, which is often neglected by traditional literary critics. Through thorough analysis of the text, the author claims that the novella has presented the protagonist, Santiago’s anti-ecological-consciousness. At the same time, it further reflects the ambivalent attitude of Hemingway himself towards nature: reverence for nature and desire to conquer nature. Key words: Anti-ecological-consciousness; Ecocriticism; Ernest Hemingway Résumé: Dans les circonstances d'une grave crise écologique, l'écocriticisme est devenu un sujet brûlant. Ces dernières années, le monde naturel dans les oeuvres d'Hemingway est entré dans la vue de l'écocritiques. Cet article est, selon la théorie de l'écocriticisme, d'interpréter le chef d'oeuvre de Hemingway "Le Vieil Homme et la mer" du point de vue anti-écologique, qui est souvent négligée par les critiques littéraires traditionnels. Grace à une analyse approfondie du texte, l'auteur affirme que le roman a présenté la consicence anti-écologique du protagoniste, Santiago. En même temps, il reflète en outre l'attitude ambivalente de Hemingway lui-même envers la nature: le respect de la nature et le désir de conquérir la nature. Mots-clés: Conscience anti écologique; Écocritisme; Ernest Hemingwa

Volume 35 - Issue 5 - January, 1926

https://scholar.rose-hulman.edu/technic/1314/thumbnail.jp