Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated alignment of chromatographic data

This paper focuses on the practical aspects and implications of preprocessing chromatographic data to correct for undesirable time‐shifts. An approach to automate the alignment of chromatographic data based on peak alignment or warping is proposed. This approach deals with selection of the required parameters including selection of reference sample to warp towards, and chooses warping settings based on a new evaluation criterion for goodness of correction. The new criterion aims at quantifying goodness of alignment while at the same time penalising significant shape or area‐changes in the warped peaks. The entire selection procedure is automated using a discrete‐coordinates simplex‐like optimisation routine. Examples with simulated chromatographic data, GC‐FID and HPLC‐Fluorescence measurement series illustrate the potential of using this automated alignment tool. Copyright © 2007 John Wiley & Sons, Ltd.
Identifying and interpreting context on the Web : an application-driven approach

This work describes the use of contextual information in Web document processing. Contextual information is defined as the contents of a ‘context set’ of a document of interest on the Web. The context set of a document is determined by the hyperlink structure of the Web around the document of interest. This thesis suggests that, as in other text media, contextual information on the Web is a vital component of the information content of a document, and should be taken into account when interpreting or processing that information. Most existing hypertext document processing applications either ignore hyperlinks, or use them in a restrictive manner, to identify a particular form of contextual information. For example, many information retrieval applications use hyperlinks as indicators of document prestige or authority, conferred by the referring document to the referred document. Others use them to locate (or help to locate) similar content in order to augment a document index or provide additional information about a document’s relevance. A related method is the clustering of Web documents, using the Web hyperlink structure to identify clusters of related documents, either to generate an aggregate that can be used in document indexing, or to simplify a visual representation of the graph structure in order to aid browsing. These approaches typically apply the information provided by hyperlinks to a particular application, such as information retrieval, or Web browsing. In contrast, this thesis proposes a flexible method for the inclusion of hypertext contextual information in a number of document processing applications, based on an adaptation of the TF×IDF term weighting measure. The resultant non-linear measure can be incorporated into Web applications using a probabilistic model trained on pre-annotated data suitable for the domain of the application. In this work, the measure is implemented and evaluated on a number of Web document content processing applications. Specifically, three applications are presented: an adaptation of an existing automatic keyphrase extraction application, a Web document retrieval ranking algorithm, and a document collection homogeneity measure with a related homogeneous corpus generation application. Each of these applications is evaluated against the state of the art in the application domains. Contextual information on the Web is found to provide valuable additional information in each of the applications, demonstrating that the method described in this thesis is both a flexible and effective approach to the question of context on the Web.
AN RGB-D DATA PROCESSING FRAMEWORK BASED ON ENVIRONMENT CONSTRAINTS FOR MAPPING INDOOR ENVIRONMENTS

Abstract. The adoption of RGB and depth (RGB-D) sensors for surveying applications (i.e., building information modeling [BIM], indoor navigation, and three-dimensional [3D] models) to replace expensive and time-consuming methods (e.g., stereo cameras, laser scanners) has recently attracted great attention. Due to the distinctive structure and scalability of indoor environments, the depth quality produced from RGB-D cameras and the simultaneous localization and mapping (SLAM) system responsible for the cameras pose estimation are substantial problems with existing RGB-D mapping systems. This study introduces a new RGB-D data processing framework that adopts two-dimensional and 3D features from RGB and depth images. To overcome the self-repetitive structure of indoor environments, the proposed framework uses novel description functions for both line and plane features extracted from RGB and depth images for further matching between successive RGB-D frame features. Also, the framework estimates the camera pose by minimizing the combined geometric distance of both two-dimensional and 3D features. Using the previously known structure of the indoor environment, the framework leverages the structural constraints to enhance 3D model precision. The framework also adopts a graph-based optimization technique to distribute the closure error to the graphs nodes and edges when a loop closure is detected. The visual RGB-D SLAM system and the default sensor tracking system (SensorFusion) were used to assess the performance of the proposed framework. The results show that the proposed framework can achieve significant improvement in 3D model accuracy.
Entropy-based regularization of AdaBoost

In this study, we introduce an entropy-based method to regularize the AdaBoost algorithm. The AdaBoost algorithm is a well-known algorithm used to create aggregated classifiers. In many real-world classification problems in addition to paying special attention classification accuracy of the final classifier, great focus is placed on tuning the number of the so-called weak learners, which are aggregated by the final (strong) classifier. The proposed method is able to improve the AdaBoost algorithm in terms of both criteria. While many approaches to the regularization of boosting algorithms can be complicated, the proposed method is straightforward and easy to implement. We compare the results of the proposed method (En- tropyAdaBoost) with the original AdaBoost and also with its regularized version, ǫ-AdaBoost on several classification problems. It is shown that the proposed methods of EntropyAdaBoost and ǫ-AdaBoost are strongly complementary when the improvement of AdaBoost is considered.
Firmware Replacement for AR Drone Quadrotor enabling camera sensor fusion for on-board Autonomous Hover and Flight Control

This paper involves the development of on-board customised software to enable the vision based autonomous hover and control of the Parrot Company’s AR Drone. The software connects a computer via WLAN to the drone enabling file transfers to the drone also gives direct access to the sensors and motors. The software enables the ability to use the drone’s processor and ventral camera to calculate optic flow and snapshot for fusion with the on-board inertial navigation sensors. Sensor fusion of the ultrasonic sonar altimeter and z-axis accelerometer is used to improve height estimations for vertical stability and a suitable PID control method is selected for optimal response. Optic Flow velocities are calculated on-board the drone and used for inner loop control without the need for ground station computations. Other capabilities developed are video and data recording on the AR drone whilst in flight for off-line analysis.
P11.03: Diagnostic accuracy of transvaginal sonogarphy in infertile patients with endometrial polyp

Background: To evaluate the diagnostic accuracy of transvaginal sonography (TVS) in infertile patients and compare its results with hysteroscopy, as the gold standard. Materials and Methods: A total of 679 infertile women who underwent both TVS and diagnostic hysteroscopy were retrospectively investigated. TVS was performed in the mid-follicular phase (days 5-8) of their cycles. Sensitivity, specificity, and positive and negative predictive values were calculated for TVS. Results: Hysteroscopy diagnosed endometrial polyps in 197 out of 679 cases (24.5%). TVS confirmed the hysteroscopy findings in 174 of 197 (88.3%) cases. The sensitivity, specificity, and positive and negative predictive values of TVS compared to hysteroscopy in the detection of endometrial polyps were 88.3%, 91.9%, 81.6% and 90.8%, respectively. Conclusion: TVS is both a cost-effective and non-invasive method for the diagnosis of intrauterine lesions such as polyps. When used in conjunction with a saline infusion, it can be a proper alternative for diagnostic hysteroscopy that saves time and enables the surgeon to perform the operative hystroscopy procedure with greater accuracy.
Sales Analysis Using the Forecasting Method

Sales Analysis Using Forecasting Method aims to improve effectiveness and efficiency that facilitates companies in business transaction processes, improve the delivery of information quickly, accurately, and transaction data well and minimize errors. The method used in the presentation of this scientific work is by using a forecasting method which helps determine the approximate stock of goods to come. With 3 forecasting modules are: Moving Average, Weighted Moving Average, Trend Projection is used to perform the forecasting process of the upcoming stock of goods. Can solve problems that exist in the current system so that it can help in improving its services by calculating the stock and helping by determining the average data that has been linked to the forecasting module whose results can be concluded through reports per period. It can be concluded that the results of implementing this new system can help companies in recording each transaction that occurs becomes more efficient and effective, so that it can overcome the problems that exist in the current system. With this we can predict the current flow of goods that have been calculated based on 3 (three) modules that have connections with the system
ANALISIS PERBANDINGAN ALGORITMA NAIVE BAYES DAN SUPPORT VECTOR MACHINE DALAM MENGKLASIFIKASIKAN JUMLAH PEMBACA ARTIKEL ONLINE

PT. Linktone Indonesia merupakan salah satu perusahaan yang bergerak dalam bidang portal berita online. Semakin banyaknya portal berita online di Indonesia, para penulis yang ada di PT. Linktone Indonesia harus dapat bersaing, agar artikel yang mereka publish mendapatkan jumlah pembaca yang maksimal. Jumlah pembaca pada sebuah artikel tidaklah menentu, dan sulit untuk diprediksi. Banyaknya jumlah artikel yang dimiliki, maka dapat dilakukan penelitian data mining untuk mengklasifikasi jumlah pembaca artikel. Terdapat beberapa algoritma dalam teknik klasifikasi, akan tetapi tidak semua algoritma memiliki kinerja dan tingkat keakuratan yang baik dalam mengklasifikasi jumlah pembaca artikel. Penelitian ini membandingkan dua algoritma klasifikasi antara Naive Bayes, Support Vector Machine dan Bagging pada tiap algoritma. Peneliti membagi menjadi 5 dataset dan menggunakan tools WEKA dengan tools options K-Folds Cross Validation dan Confussion Matrix. Hasil penelitian ini, dengan jumlah dataset 7111 record. Bagging kurang memperbaiki hasil klasifikasi dengan jumlah dataset yang besar dan memerlukan waktu pembuatan model yang sangat lama dengan klasifikasi Support Vector Machine. Sementara itu Naive Bayes dalam segi waktu pembuatan model mendapatkan waktu yang paling cepat.
Quantitative Measurement of Oxygen Extraction Fraction (OEF) Using Respiratory Modulated Perfusion MRI

Background: Measurement of oxygen consumption can give useful information of brain functionality in health and disease. To have a better understanding of normal physiology in all conditions (rest or functional tasks), development of accurate brain oxygen mapping is essential. This mapping could also be a great help in managing pathological conditions with disturbance in oxygen supply. One of the most important hemodynamic parameters of the brain is oxygen extraction fraction (OEF). By development of blood oxygen level dependent magnetic resonance imaging (BOLD MRI) in imaging, several methods have been proposed for measuring this parameter. The latest methods are mostly based on hypercapnic and hyperoxic stimulus. Objectives: Here, we presented a new method with hypercapnic and hyperoxic stimulus and using BOLD and dynamic susceptibility contrast (DSC) perfusion imaging instead of arterial spin labelling (ASL). Materials and Methods: A 3T Siemens Trio Tim Scanner was used for imaging five patients (three males and two females) who were recruited for this experiment. Four set of T1 data, BOLD data and two DSC-perfusions (two injections) were applied to each subject. Gas manipulation was applied while acquiring BOLD data and one of the DSC-perfusion was done in hyperoxic condition. Gas manipulation was a combination of hypercapnic, hyperoxic and normoxic conditions in a total of 13 minutes. The DSC data was analyzed using PMA (ASIST) software to calculate cerebral blood flow (CBF) and using its results with the BOLD data, OEF was calculated by MATLAB coding. All preprocessing was done with the SPM12 (MATLAB). Results: Comparable results were acquired for OEF with previous studies. The mean value of estimated OEF for gray matter (GM), white matter (WM) and whole brain is 0.46, 0.37, and 0.44, respectively which are within the expected range of normal condition. Conclusion: As the proposed method for OEF measurement uses a combination of hyperoxic and hypercapnic stimulus with BOLD and DSC-perfusion imaging, it could be considered the most available one in all MRI scanners and being a voxel wise method, it could give OEF value for any requested ROI.
Citation Extraction Based on Hidden Markov Model

This paper puts forward a method of HMM structure learning which is based on the extraction of tokens' features, uses a variation of Viterbi algorithm to extract citation. For evaluating the method, it introduces two standards: Macro-averaging and Mico-averaging in addition to commonly used Precision, Recall and F.
Phased Compliance Control with Virtual Force for Six-Legged Walking Robot

Decreasing impact force between the foot and the terrain when the foot lifting and landing, is one of the most important problems for the walking robot on the irregular terrain and the bumpy road, because it negatively affects the body stability and sometimes destroys robot mechanical parts. Therefore this paper a proposed phased compliance control using virtual compliance force for multi-legged walking robot, which can reduce the impact force when the robot walks. The effectiveness of the proposed method is verified by the computer simulation using a 3D-CAD dynamic model of a six-legged walking robot.
Average Partial Power Spectrum Density Approach to Feature Extraction for EEG-based Motor Imagery Classification

Brain Computer Interface (BCI) has attracted many researchers in recent years, in which one of non-invasive techniques for the BCI issue is Electroencephalography (EEG). This EEG technique can allow to investigate human brain related to muscle for diagnosis and rehabilitation. In this paper, we proposed an Average Partial Power Spectrum Density (APPSD) approach and a bandpass filter to classify mental tasks using an EGG system with 24 channels, in which the relevant mental tasks are: left hand movement, right hand movement and rest. The proposed approach is the combination of the 2 Hz bandpass filter and the APPSD algorithm in the specific frequency ranges to find out features of imagery for classification. For the accuracy of the feature extraction, outliers which sparsely appear in the range of the PSD are removed. From the obtained features of movements, an Artificial Neuron Network (ANN) model was used to classify imagery status. Experiments were performed on 2 subjects with 200 runs per one subject to illustrate the effectiveness of the proposed method.
Emoticonos y multimodalidad. El uso del pulgar hacia arriba en WhatsApp

espanolEl presente trabajo propone una aproximacion multimodal al estudio de los emoticonos a traves del analisis del uso del emoji del pulgar hacia arriba en un corpus de mensajes de WhatsApp. Ademas de contribuir a superar la idea, todavia muy arraigada, de que los emoticonos sirven para expresar emociones en el discurso digital, el trabajo toma en consideracion algunos aspectos tradicionalmente obviados en el estudio sobre estas pequenas caras, en concreto, la historia que hay detras de estos recursos semioticos, la sofisticada relacion entre imagen y texto y la interaccion entre los usuarios en la vida real y en la pantalla. EnglishIn the present paper a multimodal approach to the study of emoticons is proposed by analyzing the use of the thumbs-up emoji in a corpus of WhatsApp messages. One of the main aims of the paper is to overcome the idea, still deeply rooted, that emoticons are used to express emotions in digital communication. Moreover, this study takes into account some aspects traditionally overlooked in the research on emoticons, namely the history of these semiotic resources, the sophisticated relations between image and text and the interaction among users in real life and on screen.
Essentials of business statistics

What is statistics? Graphical descriptive methods Numerical descriptive measures Probability Probability distributions Sampling and sampling distributions Statistical inference: Introduction Estimation: Describing a single population Estimation: comparing two populations Hypothesis testing: Describing a single population Hypotheses testing: Comparing two populations Statistical inference: A review of Chapters 8 through 11 Analysis of variance Chi-square tests Simple linear regression and correlation Multiple regression Time series analysis and forecasting Nonparametric statistics Statistical process control Statistical inference.
INDOOR SCENE REGISTRATION BASED ON SIAMESE NETWORK AND POINTNET

Abstract. This paper presents a deep learning feature-based method for registration of indoor mobile LiDAR data. Our method is to input point cloud directly, which is more robust to noise than traditional algorithms. The proposed method involves three steps. We first extract the key points by Harris3D algorithm and get their local patches by our sampling method. Second, a Siamese network is trained to describe the patches as local descriptors. Finally, we obtain the final matching pairs depends on the distance which is between two descriptors, and then solve the transformation matrix. The accuracy of registration is within 6 cm when the overlap is greater than 35%. In order to improve the registration accuracy, the ICP algorithm is used to fine-tuning the registration results. And the final registration accuracy is within 3.5 cm. The experiments show that our method applied to the registration of indoor mobile LiDAR data robustly and accurately.
Delayed presentation of displaced neck of femur fractures in patients under sixty years of age- A prospective functional outcome assessment study after osteosynthesis

Introduction: An intracapsular fracture of the neck of the femur in the young adult is a difficult injury to manage. Although internal fixation is the standard treatment for young adults, controversy remains concerning the mode of fixation, the approach to be used (closed vs open), method of reduction, time to fixation, post-operative protocols. Avascular necrosis can occur following this injury because of disruption of the femoral head blood supply. Some believe that emergent fracture reduction is necessary to minimize the risk of avascular necrosis. Objective: In a developing country like ours with many cases presenting late to the hospital after injury, there are very few studies assessing the outcome in such cases. So we did a prospective study to assess the functional outcome in patients with neck of femur fractures presenting after 48hrs to the hospital. Methods: This is a prospective study with patients below the age of sixty years with displaced neck of femur fractures (Garden’s grade 3 and 4) presenting after 48 hrs treated with closed reduction and fixation with cannulated cancellous screws. Patients were followed up periodically for a minimum period of 3 years. Results: 28 patients participated in the study of which 18 were males and 10 female patients. Average time to surgery was 2.5days +/-0.3days. Time to union is 15.8 +/4.2 weeks. AVN developed in 4(14.2%) and non-union in 3 (10.7%) cases. Functional outcome with Harris Hip score was excellentgood in 22 (78.5%) cases. Conclusion: Accurate reduction with establishment of the smooth curve between the head and neck of femur and accurate placement of screws in the neck with guarded weight bearing protocols in cases with posterior comminution can give good results with this fracture irrespective of the delay in surgery.
The Journal of the Civil War Era et l’approche transnationale de la Guerre de Sécession

La Guerre de Secession, evenement central du recit national americain s’il en est, est bien evidemment presente dans toutes les revues generalistes et regionales, d’autant plus lorsqu’entre 2011 et 2015 il a fallu en celebrer le cent-cinquantieme anniversaire. Mais seule Civil War History s’etait constituee depuis plus de soixante ans en reference incontournable, unique periodique scientifique consacre entierement a ces annees-la. S’il ne peut etre question de mettre en cause la qualite des t.
The Muscular System

Introduction Muscular Anatomy and Physiology Anatomy of the Musculature System Muscle Contraction Muscles in Exercise Development of the Muscular System Historic Perspectives Early Discoveries in Muscular Anatomy Current Approaches to Understanding the Musculature System Medical Information Muscular Injuries Muscular Dystrophy Diseases of the Cardiac Muscle Disease of the Muscular Enzymes References Glossary Medical Organizations Fact Sheet
The future in brain/neural computer interaction: Horizon 2020

The main objective of this roadmap is to provide a global perspective on the BCI field now and in the future. For readers not familiar with BCIs, we introduce basic terminology and concepts. We discuss what BCIs are, what BCIs can do, and who can benefit from BCIs. We illustrate our arguments with use cases to support the main messages. After reading this roadmap you will have a clear picture of the potential benefits and challenges of BCIs, the steps necessary to bridge the gap between current and future applications, and the potential impact of BCIs on society in the next decade and beyond.
Software Product Lines Composition through Partial Derivation

Software product line approach has been successfully adopted in various software domains. In some fields, single SPLs are no longer sufficient to fulfill their requirements due to the large variability amount they include. Consequently, a set of separated SPLs is built to handle this issue and construct what is known by Multi Product Lines (MPL). However, the emergence of MPLs results in several challenges, namely: managing the reuse between SPLs, structuring the MPL model and distributed derivation. In this paper, we propose a new approach for SPLs composition. Our approach relies on two main concepts: the separation of concerns and the partial derivation. It is validated in the context of an eLearning MPL and an illustration is explained throughout the paper. The results show that our approach helps systemizing reuse within MPLs and structuring the MPL model. Moreover, SPLs are integrated early in the development process avoiding thus the distributed derivation challenges.