Miracle-dz/UniFAR-FTUs huggingface dataset:
A Bayesian model for mobility prediction in wireless sensor networks

Wireless sensor networks (WSN) have specific features such as low transmission range, stringent energy consumption constraints, limited memory and processing power. For this reason, tailored protocols have been proposed, optimizing network protocols with respect to various assumptions: one commonly exploited property of WSN is the stability of the topology due to permanent installation of sensor nodes. However, in some applications, some of the wireless sensor nodes might be mobile, for instance when they are associated with users. In that case, specific extensions of WSN protocols need to be designed. Then a first step is the characterization of nodes' mobility. This is the focus of this article: we propose a general method of mobility estimation for wireless sensor networks. Namely, using a Bayesian framework, we derive a mobility prediction model to estimate the node velocity (starting from no knowledge) from observed events. In this article, we focus on events represented by the most minimal information: mere observation of link duration with neighbors. Simulations illustrate that, even with such limited information, the mobility can be well inferred, and results show the good performance of the method.
Brave new world: higher education reform in Finland

Finnish universities are about to enter a period of radical change. This paper considers the reforms expected of a new Universities Act currently before parliament and a set of institutional mergers. When passed, the new act will provide universities with independent legal status, change their relationship with the government in several ways, affect university governance arrangements, and alter the relationship between staff and their university employers. Although these reforms will be radical for the university sector itself, many of the changes will be all but invisible to those outside the sector. The change that will be noticed is the creation of the new Aalto University through a merger between three existing institutions. The new university will be highly visible to all as it tries to meet the government’s aspirations for it to become a world-class university. Le meilleur des mondes : Reforme du systeme de l’enseignement superieur en Finlande Les universites finlandaises se trouvent au seuil de changements radicaux. Cet article analyse les reformes decoulant d’un nouveau projet de loi sur l’universite actuellement presente devant le Parlement finlandais et de plusieurs fusions institutionnelles. Une fois adoptee, la nouvelle loi accordera aux universites un statut juridique independant, modifiera leurs relations au gouvernement en plusieurs points, affectera les accords relatifs a la gestion des universites et modifiera les relations entre le personnel et les employeurs universitaires. Bien que le secteur universitaire considere ces reformes comme radicales, la plupart des changements qu’elles vont entrainer seront absolument invisibles aux yeux de l’observateur exterieur pour qui le changement apparent resideradans la creation de la nouvelle Universite de Aalto, fruit d’une fusion entre trois institutions existantes. Cette nouvelle universite occupera en effet le devant de la scene puisqu’elle s’efforcera de repondre aux aspirations du gouvernement qui veut en faire une universite internationale de haut niveau.
An Approach for 3D Reconstruction from Uncalibrated Images

Three-dimensional (3D) reconstruction considering of image sequences is an unresolved and active research topic on the cross-section of computer vision and digital photogrammetry. In this paper, we focus on 3D object shape reconstruction from uncalibrated images and put forward a rapid algorithm to recover the object height. The recovering 3D shape comprises two steps, for the one hand, calculate homography transformation to obtain the outlines, for the other hand calculate the reconstructed object height by reference height proposed by the paper, and then recover the 3D object shape. This method requires no camera calibration or the estimation of the fundamental matrix; hence, it reduces the computational complexity by eliminating the requirement for abundant conjugate points. The experiment shows that the method is much validated and something useful is obtained.
Fast path loss prediction by using virtual source technique for urban microcells

This work proposes a new principle for fast path loss prediction and cell coverage calculations for urban microcells in a high rise building environment. The technique is based on finding a virtual source located in line of sight with the mobile station (MS). This technique maps the out-of-sight propagation prediction problem to a line-of-sight propagation prediction problem. The received power at the MS is given in a closed form expression. Based on a comparison performed with experimental results, it seems that breakpoint is valid in side-street propagation. The proposed virtual source principle opens a door for a new fast computation technique for path loss modeling in the microcellular environment.
Segmenting Long Sentence Pairs for Statistical Machine Translation

In phrase-based statistical machine translation, the knowledge about phrase translation and phrase reordering is learned from the bilingual corpora. However, words may be poorly aligned in long sentence pairs in practice, which will then do harm to the following steps of the translation, such as phrase extraction, etc. A possible solution to this problem is segmenting long sentence pairs into shorter ones. In this paper, we present an effective approach to segmenting sentences based on the modified IBM Translation Model 1. We find that by taking into account the semantics of some words, as well as the length ratio of source and target sentences, the segmentation result is largely improved. We also discuss the effect of length factor to the segmentation result. Experiments show that our approach can improve the BLEU score of a phrase-based translation system by about 0.5 points.
Sparse Coding of Disparity Information

Organopolysiloxanes, which terminally, laterally or both have at least one group of the formula well as at least one acrylate group, linked over a bridge element to this group, is obtained by hydrosilylation of organopolysiloxanes with at least one SiH group by compounds, which have at least two acrylate groups, in equimolar amounts at a temperature of 60 DEG to 130 DEG C. in presence of rhodium catalysts. The rhodium catalysts cause a 1,2 addition to take place during the addition reaction between polyacrylates and hydrogen siloxanes.
Segmentation of cDNA Microarray Spots Using K-means Clustering Algorithm and Mathematical Morphology

Complementary DNA microarray technology is a powerful tool in many areas. Usually a two channel microarray Red–Green (RG) image is obtained. Due to the nature of cDNA microarray technology, a number of impairments affect the cDNA microarray image before the analysis such as identification of differentially expressed genes. Microarray image processing plays a crucial role in the extraction and quantitative analysis of the relative abundance of the DNA product. In this paper, a method combined K-means clustering algorithm and mathematical morphology is presented. Mathematical morphology is a useful tool for extracting image components. K-means clustering algorithm has a good performance in the segmentation of microarray image processing. The result of the experiment shows that the method presented in this paper is accurate, automatic and robust.
Using Business Analytics for Strategic Alignment and Organisational Transformation

Organisations use business analytics BA systems to create value and provide competitive advantage. They frequently use BA systems to respond quickly to market changes and customer demand, and for market differentiation with better customer service and new types of products and services. The authors argue that BA systems can also enable alignment between business strategy and information technology IT strategy and support organisational transformation. The authors use a single case study to explain how a global data warehouse, standardized metrics and sophisticated reporting capabilities supported the strategic transformation of a diversified and multi-layered international mining company into a unified and integrated global organisation. They identify a number of core technology, management, culture, governance and people related capabilities that were crucial to the success of the global transformation initiative. Two important implications of the case study are the importance of BA systems in the alignment of IT and business strategy and the synergistic interaction of BA systems and other organizational resources in achieving benefits.
One-shot learning gesture recognition from RGB-D data using bag of features

For one-shot learning gesture recognition, two important challenges are: how to extract distinctive features and how to learn a discriminative model from only one training sample per gesture class. For feature extraction, a new spatio-temporal feature representation called 3D enhanced motion scale-invariant feature transform (3D EMoSIFT) is proposed, which fuses RGB-D data. Compared with other features, the new feature set is invariant to scale and rotation, and has more compact and richer visual representations. For learning a discriminative model, all features extracted from training samples are clustered with the k-means algorithm to learn a visual codebook. Then, unlike the traditional bag of feature (BoF) models using vector quantization (VQ) to map each feature into a certain visual codeword, a sparse coding method named simulation orthogonal matching pursuit (SOMP) is applied and thus each feature can be represented by some linear combination of a small number of codewords. Compared with VQ, SOMP leads to a much lower reconstruction error and achieves better performance. The proposed approach has been evaluated on ChaLearn gesture database and the result has been ranked amongst the top best performing techniques on ChaLearn gesture challenge (round 2).
A Linearly-Polarized Compact UHF PIFA with Foam Support

Preliminary work on the design of a low-cost linearly-polarized broadband PIFA operating in the UHF band (440 MHz) is presented. Extensive simulations using Ansoft HFSS are performed in order to model and optimize the antenna performance. High-density polystyrene foam is employed as a dielectric substrate/support for all antenna prototypes. The metal sheets are made of copper foil. To minimize the antenna dimensions, a tapered patch with slots and capacitive loading is used. The fabricated antennas have the measured bandwidth of about 60MHz (14%) and are centered at 440 MHz. Change in antenna performance close to the human body is briefly discussed.
Highly Accurate Tree Models Derived from Terrestrial Laser Scan Data: A Method Description

This paper presents a method for fitting cylinders into a point cloud, derived from a terrestrial laser-scanned tree. Utilizing high scan quality data as the input, the resulting models describe the branching structure of the tree, capable of detecting branches with a diameter smaller than a centimeter. The cylinders are stored as a hierarchical tree-like data structure encapsulating parent-child neighbor relations and incorporating the tree’s direction of growth. This structure enables the efficient extraction of tree components, such as the stem or a single branch. The method was validated both by applying a comparison of the resulting cylinder models with ground truth data and by an analysis between the input point clouds and the models. Tree models were accomplished representing more than 99% of the input point cloud, with an average distance from the cylinder model to the point cloud within sub-millimeter accuracy. After validation, the method was applied to build two allometric models based on 24 tree point clouds as an example of the application. Computation terminated successfully within less than 30 min. For the model predicting the total above ground volume, the coefficient of determination was 0.965, showing the high potential of terrestrial laser-scanning for forest inventories.
Threshold-based prediction of schedule overrun in software projects

Risk identification is the first critical task of risk management for planning measures to deal with risks. While, software projects have a high risk of schedule overruns, current practices in risk management mostly rely on high level guidance and the subjective judgements of experts. In this paper, we propose a novel approach to support risk identification using historical data associated with a software project. Specifically, our approach identifies patterns of abnormal behaviours that caused project delays and uses this knowledge to develop an interpretable risk predictive model to predict whether current software tasks (in the form of issues) will cause a schedule overrun. The abnormal behaviour identification is based on a set of configurable threshold-based risk factors. Our approach aims to provide not only predictive models, but also an interpretable outcome that can be inferred as the patterns of the combinations between risk factors. The evaluation results from two case studies (Moodle and Duraspace) demonstrate the effectiveness of our predictive models, achieving 78% precision, 56% recall, 65% F-measure, 84% Area Under the ROC Curve.
Text Line Detection in Corrupted and Damaged Historical Manuscripts

Most of the algorithms proposed for text line detection are designed to process binary images as input. For severely degraded documents, binarization often introduces significant noise and other artifacts. In this work we present a novel method designed to detect text lines directly in gray scale images. The method consists of two stages. Potential characters are detected in the first stage. This is done by analyzing the evolution maps of connected components obtained by a sliding threshold. The detected potential characters are grouped into text lines in the second stage using sweep-line approach. The suggested method is especially powerful when applied to torn and damaged documents that other algorithms are not able to deal with.
Relationship between atmospheric stability and area burned during the 1998 Florida wildfires

During the spring and early summer of 1998, over 2,200 wildfires scorched nearly a half million acres of Florida. Many of these fires rapidly grew to large sizes and threatened and/or damaged private homes (126 were lost). During this period, a strong ridge of high pressure developed over the region and persisted from late April through the first week of July. High temperature records were continuously being set across Florida during the month of June, presenting severe fire weather conditions as these high temperatures contributed to unusually low relative humidity. While these conditions persisted throughout the event, certain days exhibited very dramatic fire growthlactivity that is likely tied to atmospheric stability. This study seeks to examine the relationship between stability and area burned by examining two stability indicators used in wildland fire, the Haines lndex (HI) and the Lavdas Atmospheric Dispersion lndex (ADI). While the HI is widely used across the United States in fire weather forecasts, the AD1 is a smoke management tool that the Florida Division of Forestry has found useful in assessing stability conditions for wildfires. 2. DATA a) Soundings The Haines lndex (HI) was calculated
Automatic 3D Facial Region Retrieval from Multi-pose Facial Datasets

The availability of 3D facial datasets is rapidly growing, mainly as a result of medical and biometric applications. These applications often require the retrieval of specific facial areas (such as the nasal region). The most crucial step in facial region retrieval is the detection of key 3D facial landmarks (e.g., the nose tip). A key advantage of 3D facial data over 2D facial data is their pose invariance. Any landmark detection method must therefore also be pose invariant. In this paper, we present the first 3D facial landmark detection method that works in datasets with pose rotations of up to 80 degree around the y-axis. It is tested on the largest publicly available 3D facial datasets, for which we have created a ground truth by manually annotating the 3D landmarks. Landmarks automatically detected by our method are then used to robustly retrieve facial regions from 3D facial datasets.
Neuroprotective Effects of Isosteviol Sodium Injection on Acute Focal Cerebral Ischemia in Rats

Previous report has indicated that isosteviol has neuroprotective effects. However, isosteviol was administered preventively before ischemia and the inclusion criteria were limited. In the present study, a more soluble and injectable form of isosteviol sodium (STVNA) was administered intravenously hours after transient or permanent middle cerebral artery occlusion (tMCAO or pMCAO) to investigate its neuroprotective effects in rats. The rats were assessed for neurobehavioral deficits 24 hours after ischemia and sacrificed for infarct volume quantification and histology evaluation. STVNA 10 mg·kg−1 can significantly reduce the infarct volumes compared with vehicle in animals subjected to tMCAO and is twice as potent as previously reported. Additionally, the therapeutic window study showed that STVNA could reduce the infarct volume compared with the vehicle group when administered 4 hours after reperfusion. A similar effect was also observed in animals treated 4 hours after pMCAO. Assessment of neurobehavioral deficits after 24 hours showed that STVNA treatment significantly reduced neurobehavioral impairments. The number of restored NeuN-labeled neurons was increased and the number of TUNEL positive cells was reduced in animals that received STVNA treatment compared with vehicle group. All of these findings suggest that STVNA might provide therapeutic benefits against cerebral ischemia-induced injury.
Theoretical Investigations for Strain Relaxation and Growth Mode of InAs Thin Layers on GaAs(110)

The growth mode of InAs/GaAs(110) is systematically investigated using our macroscopic theory with the aid of ab initio calculations that determine the parameter values used in the macroscopic theory. Formations of misfit dislocation and island are employed as strain relaxation mechanisms. The calculated results reveal that the misfit dislocation formation generally leads to two‐dimensional growth of InAs on GaAs(110) because of its small formation energy compared with that on GaAs(001). On the other hand, three‐dimensional growth mode appears with insertion of an In0.25Ga0. 75As strain‐reducing layer between InAs and GaAs, since the strain relaxation induced by the insertion layer reduces the surface energy from 51 to 49 meV Å−2 that prefers the three‐dimensional island formation. These findings are consistent with experimental results.
Laboratory Manual of Biological Chemistry

This new edition of Folin's Manual follows the same general plan of topics treated as that which characterized the earlier editions. The first chapter treats of such fundamental topics as acidimetry, alkalimetry, calibration of apparatus, and nitrogen determination. Some commentators might be disposed to criticize this on the ground that such matters should be considered prerequisite for entrance to a course in biological chemistry. In defense the reviewer suggests that details of entrance requirements cannot always be decided by one instructor, but depend on numerous factors beyond his control, and the first edition of this manual which sets the pattern of the present book, was the result of actual experience in Professor Folin's laboratory over a period of years. Furthermore, in developing the subject of biological chemistry in accordance with the viewpoint of Folin, which conceives as the ideal the treatment of both qualitative and quantitative aspects of the subject without definite separation, it is logical to begin as he has done. Incidentally, it may be added, this first chapter is as condensed and clear a presentation of these fundamental essentials as may be found anywhere, if it is not indeed the best. The importance of acidimetry is emphasized to the student and related in a practical way by titrations of the gastric contents, a presentation which reveals the deep pedagogical insight of the author. This edition differs from the previous ones largely in that it describes newer quantitative methods applicable to blood analysis. The supplement, which is devoted to quantitative methods useful with blood and urine, covers 163 pages as compared with 201 pages for the previous part of the book and constitutes a valuable compendium of the methods developed and in use in the Harvard laboratories. The style of presentation of the material in the first chapter is quite different from that of the later chapters which read more like conventional laboratory manual notes. In the reviewer's opinion, the later sections would be improved by inclusion of informative comments and descriptive matter similar to that presented in the first chapter. However, it might be argued, against this view, that such material belongs more properly to a textbook ; also, that this additional material should be given by the instructor. One of the useful features of the earlier editions has been retained, namely, the use of blank left-hand pages as a place for the student to record important data. …
UWB at SemEval-2016 Task 1: Semantic Textual Similarity using Lexical, Syntactic, and Semantic Information

We present our UWB system for Semantic Textual Similarity (STS) task at SemEval 2016. Given two sentences, the system estimates the degree of their semantic similarity. We use state-of-the-art algorithms for the meaning representation and combine them with the best performing approaches to STS from previous years. These methods beneﬁt from various sources of information, such as lexical, syntactic, and semantic. In the monolingual task, our system achieve mean Pearson correlation 75.7% compared with human annotators. In the cross-lingual task, our system has correlation 86.3% and is ranked ﬁrst among 26 systems.
Process Aware Circuit Design Using Adaptive Body Biasing

The process variation has become inevitable in the present VLSI technology. The IC designed without consideration of process variation fails to do operation correctly Numbers of techniques has proposed to mitigate the effect of process and NBTI effect but have limitation. In this paper Adaptive Body Bias technique is proposed which mitigate the effect of NBTI and process variation. The simulation result shows that proposed method compensate the change in threshold voltage due to process variation/NBTI.
Reliable Communication Network Design with Metaheuristics

involves determining where to place the components and how to connect them. In the design process, the reliability of the network has been one of the critical requirements. In this paper, we propose two metaheuristics (Simulated Annealing and Genetic Algorithm) to find the minimum cost network topology with reliability constraint. This is a NP-hard problem and the exact solution can only be found for small sized networks. In our approaches, various methods are considered in order to incorporate problem-specific operators for searching phase, including Minimum Spanning Tree (MST) heuristics for initial population generation, intelligent variation operators, which comprise problem-specific knowledge, and a repair function. The effectiveness of our approaches is presented by numerical experiments for different sized networks with different costs, link reliabilities and all-terminal reliability requirements. Our algorithms are compared with other algorithms given in the literature.