The use of remote sensing data for drought assessment and monitoring in southwest Asia

Drought / Monitoring / Indicators / Assessment / Remote sensing / Asia

Restaurant style prediction using Word2vec and support vector machine.

Natural Language Processing represents a quantum leap for governance and industries. It enables them to have an insight into hidden patterns and information within their data. In this thesis, we have worked on an important field in Natural Language Processing, which is Text Classification. Our goal is to help restaurant owners to find which dishes customers like more. To do that we have used a dataset from Yelp.com that has 150,000 restaurant reviews, then count the most frequent dishes mentioned. However, this way is not effective except if these reviews are categorized into different restaurants-styles. For this reason, we have used Word2vec with Support Vector Machine algorithms to classify these reviews into four restaurant-style categories (Mediterranean, Indian, Mexican, and Japanese). The experimental result shows that this methodology has successfully achieved a classification accuracy of 87.2%, which shows that the methodology is effective in classifying reviews datasets

INFORM scientific and technical improvements in 2017: Missing values imputation and IT developments

The JRC is the technical and scientific leader of the INFORM model, and responsible for methodological improvements, and their implementation. This publication describe the INFORM methodological and technical improvements implemented by JRC in the 2017. On despite the indicators have been selected on be base of their reliability, consistency continuity and completeness, most of the them don’t cover all the countries for all the year. This results in a significant number of missing values, irregularly distributed among countries, time and indicators. This report describes an innovative approach for predicting missing values using advanced statistical technics. We also present the IT developments in support to the INFORM model, including the web platform for managing the INFORM Subnational models and the improvements in the API.JRC.E.1-Disaster Risk Managemen

Missing values imputation in Arabic datasets using enhanced robust association rules

Missing value (MV) is one form of data completeness problem in massive datasets. To deal with missing values, data imputation methods were proposed with the aim to improve the completeness of the datasets concerned. Data imputation's accuracy is a common indicator of a data imputation technique's efficiency. However, the efficiency of data imputation can be affected by the nature of the language in which the dataset is written. To overcome this problem, it is necessary to normalize the data, especially in non-Latin languages such as the Arabic language. This paper proposes a method that will address the challenge inherent in Arabic datasets by extending the enhanced robust association rules (ERAR) method with Arabic detection and correction functions. Iterative and Decision Tree methods were used to evaluate the proposed method in an experiment. Experiment results show that the proposed method offers a higher data imputation accuracy than the Iterative and decision tree methods

Reactive web templates

Dissertação para obtenção do Grau de Mestre em Engenharia Informática e de ComputadoresTécnicas de renderização otimistas no lado do servidor (SSR) requerem uma thread dedicada por pedido HTTP, limitando assim o número de pedidos concurrentes às threads do servidor disponíveis. Além disso, essa abordagem mostra-se impraticável para servidores modernos com um baixo número de threads, como WebFlux, VertX e Express Node.js. Para alcançar renderização progressiva, modelos de dados assíncronos fornecidos por APIs não bloqueantes devem ser utilizados. No entanto, este método pode introduzir uma sobreposição indesejável entre o processamento de visualização do modelo e o acesso a dados, potencialmente resultando em documentos HTML malformados. Alguns template engines oferecem remédios parciais tirando partido de dialetos específicos, mas enfrentam duas limitações. Em primeiro lugar, a sua compatibilidade é restrita a tipos específicos de APIs assíncronas, como a API reativa Publisher. Em segundo lugar, geralmente suportam apenas um modelo de dados assíncrono. Nesta pesquisa, propomos uma abordagem alternativa de templates web que abrange qualquer API assíncrona (por exemplo, Publisher, promessas, funções de suspensão, flux, etc.) e permite várias fontes de dados assíncronos. A Nossa abordagem é implementada usando como base o HtmlFlow, uma DSL (Linguagem de Domínio Específica) baseada em Java para escrever HTML usando forte tipificação de tipos. Foi avaliado em servidores reativos de última geração, especificamente o WebFlux, e comparamos com idiomas populares de templating, como Thymeleaf e KotlinX.html. Nossa proposta supera as limitações das abordagens existentes.Naive server-side rendering (SSR) techniques require a dedicated server thread per HTTP request, thereby limiting the number of concurrent requests to the available server threads. Furthermore, this approach proves impractical for modern low-thread servers likeWebFlux, VertX, and Express Node.js. To achieve progressive rendering, asynchronous data models provided by non-blocking APIs must be utilized. Nevertheless, this method can introduce undesirable interleaving between template view processing and data access, potentially resulting in malformed HTML documents. Some template engines offer partial remedies through specific templating dialects, but they encounter two limitations. Firstly, their compatibility is confined to specific types of asynchronous APIs, such as the reactive stream Publisher API. Secondly, they typically support only a single asynchronous data model at a time. In this research, we propose an alternative web templating approach that embraces any asynchronous API (e.g., Publisher, promises, suspend functions, flow, etc.) and allows for multiple asynchronous data sources. Our approach is implemented on top of HtmlFlow, a Javabased DSL for writing type-safe HTML. We evaluated against state-of-the-art reactive servers, specifically WebFlux, and compared it with popular templating idioms like Thymeleaf and KotlinX.html. Our proposal effectively overcomes the limitations of existing approaches.N/

Explication of Extrinsic Forearm Muscles On the Classification of Thumb Position Using High-Density Surface Electromyogram

Muscles for hand functions and movements play a major role in basic daily activities such as writing and lifting objects. The main digit of the finger in differentiating the hand gesture is the thumb and its main muscles are intrinsic muscles. However, for transradial amputees, despite the loss of access to the intrinsic muscles, any information from the extrinsic muscles would be paramount and non-negotiable in creating a perfect hand prosthesis. As such, the research is dedicated to studying the relationship between extrinsic muscles located at the human’s forearm to characterize the actual thumb attitudes. A 64-channel HD-sEMG recording device together with a thumb force measuring platform was utilized to collect the required signals from 17 participants at several thumb angle positions namely zero-degrees, thirty-degree, sixty-degrees, and ninety-degree. For each position, the participants were required to place their thumbs on top of a load cell at relaxing (no force at all) and contact (30% of their individual Maximum Voluntary Contraction or known as MVC) conditions repetitively by following a designated trajectory. Feature extraction was performed by calculating the Root Mean Square (RMS) values of the HD-sEMG data collected from each channel. Six different classifiers have been used to classify the relationship between the forearm HD-sEMG and the corresponding thumb positions. As a result, LazyIBK obtained the highest correctly classified instances with 81.05%. The finding is significant in developing a dedicated control framework for a prosthetic hand for tansradial amputees that can operate as closely as normal

Explication of Extrinsic Forearm Muscles On the Classification of Thumb Position Using High-Density Surface Electromyogram

Muscles for hand functions and movements play a major role in basic daily activities such as writing and lifting objects. The main digit of the finger in differentiating the hand gesture is the thumb and its main muscles are intrinsic muscles. However, for transradial amputees, despite the loss of access to the intrinsic muscles, any information from the extrinsic muscles would be paramount and non-negotiable in creating a perfect hand prosthesis. As such, the research is dedicated to studying the relationship between extrinsic muscles located at the human’s forearm to characterize the actual thumb attitudes. A 64-channel HD-sEMG recording device together with a thumb force measuring platform was utilized to collect the required signals from 17 participants at several thumb angle positions namely zero-degrees, thirty-degree, sixty-degrees, and ninety-degree. For each position, the participants were required to place their thumbs on top of a load cell at relaxing (no force at all) and contact (30% of their individual Maximum Voluntary Contraction or known as MVC) conditions repetitively by following a designated trajectory. Feature extraction was performed by calculating the Root Mean Square (RMS) values of the HD-sEMG data collected from each channel. Six different classifiers have been used to classify the relationship between the forearm HD-sEMG and the corresponding thumb positions. As a result, LazyIBK obtained the highest correctly classified instances with 81.05%. The finding is significant in developing a dedicated control framework for a prosthetic hand for tansradial amputees that can operate as closely as normal