Miracle-dz/UniFAR-FTUs huggingface dataset:
Workflow Patterns for Modeling Computer Aided Engineering Iterations

Worfklow languages are typically used for modelling business processes since it is very natural to think of business processess as being workflows. But we should not limit workflow languages to business processes only. Any logical flow of tasks can in theory be modelled by a workflow language. It might be that this flow of tasks, or process, is a complex one and that as a result current workflow approaches might need adaptation or added functionality. One such complex flow is found in Computer Aided Engineering (CAE) and Multi-Disciplinary Optimization (MDO). Applications in these domains differ in complexity from applications in other domains in such a way that they cannot be built using today’s workflow languages. This complexity has been studied by SSEL (Software and Systems Engineering Lab, VUB). The first outcome of this study was the recognition of three main requirements: modularization of crosscutting concerns, advanced data support and advanced iteration support. A second outcome was the proposal of a conceptual workflow language meeting the first two requirements. This thesis contributes to the framework support for the third and final requirement of supporting iterations. Iterations are algorithms such as optimization methods, Monte-Carlo methods and many more. In a first step we will define these iterations by making a classification. In a second step we propose workflow patterns that fit into the existing approach and that allow to implement the classified iterations. The result of this thesis makes the conceptual workflow language meet all requirements. This means that a first implementation of the language can start. For the first time MDO applications can be developed using a real workflow language where they gain all direct benefits from workflow languages: evolution and reuse, customizability, collaboration and distributive computation.
Toric Varieties of Brick Polytopes , Associahedra and Operad Structures

In this project, we examine realizations of certain classes of toric varieties as brick manifolds, defined by Escobar. To do so, we use the language of subword complexes, introduced by Knutson and Miller. Pilaud and Stump realized certain subword complexes as dual to a convex polytope. In particular, for certain complexes, and their corresponding varieties, in the work of Escobar, we find that this convex polytope is a realization of the associahedron. Escobar provides a realization as the Loday associahedron, while we will provide a realization as the ChapotonFomin-Zelevinsky associahedron of type An. We also give a stratification of the corresponding variety in terms of binary tree. In addition, we describe the operad of varieties defined by Dotsenko, Shadrin and Vallette, before discussing why we believe an analogous operad does not exist. Finally, we conjecture possible realizations of the Chapoton-Fomin-Zelevinsky associahedron of type Bn, along with the existence of an operad containing that of Dotsenko, Shadrin and Vallette, along with the analogous structure we wished to define.
Biosignal Monitoring Platform Using Wearable IoT

Thanks to the IoT technology advancement and wearable devices, the healthcare industry is shifting ahead to a brighter future. In this paper, we present a Wi-Fi and battery powered wearable IoT system to monitor patient's Biosignal from anywhere at any time through an IP based network. The system is unique as it is composed of a 2 or/and 8 channel electrodes to measure ECG and EMG signals with a sampling frequency fixed at 1 KHz, an analog front-end (AFE) compliant with the IEEE standard, a microcontroller for data processing and transmission, and a power management unit. The prototype operates at 2.4 GHz, 3.3v. The transceiver consumes very low power in arrange of 9mW, has a communication range between 20m and 100m, a data-rate of 128 kB/s, a latency of 1.2ms, equipped with Advanced Encryption Standard (AES) for real- time data encryption and has a high common-mode rejection ratio (CMRR). Experimental test result demonstrates that our developed prototype has a better performance than state of the art systems.
Classification of electrocardiogram using hidden Markov models

The objective of this project is to develop models for the characterization of electrocardiogram (EGG). A fast and reliable QRS detection algorithm based on a one-pole filter has been developed. Automatic ECG classification using hidden Markov models (HMMs) is investigated. Models representing various types of beat are trained using the American Heart Association (AHA) ventricular arrhythmia ECG data. The types of beat being selected in the study are: normal (N), premature ventricular contraction (V), and fusion of ventricular and normal beats (F). Artificial ECG generated from the model shows that each model truly characterizes that particular type of beat. In the testing phase, ECG signals are classified using the trained models. The average classification accuracy is 93% for N beat, 65.55% for V beat, and 56.38% for F beat respectively.
Transport of gigabit/sec data packets over SONET/ATM networks

A scheme is proposed to convert the data formats between the HIPPI (high performance parallel interface) and ATM (asynchronous transfer mode) protocols. A possible method of implementing the HIPPI broadband terminal adaptor (HIPPI-BTA), which interfaces multiple HIPPI channels to the SONET (synchronous optical network)/ATM network, is also presented. A preliminary study indicated that the HIPPI interface of the high performance computer hosts and the SONET/ATM standards of the future broadband communication networks have a high potential to work well with each other. <<ETX>>
L3-Net: Towards Learning Based LiDAR Localization for Autonomous Driving

We present L3-Net - a novel learning-based LiDAR localization system that achieves centimeter-level localization accuracy, comparable to prior state-of-the-art systems with hand-crafted pipelines. Rather than relying on these hand-crafted modules, we innovatively implement the use of various deep neural network structures to establish a learning-based approach. L3-Net learns local descriptors specifically optimized for matching in different real-world driving scenarios. 3D convolutions over a cost volume built in the solution space significantly boosts the localization accuracy. RNNs are demonstrated to be effective in modeling the vehicle's dynamics, yielding better temporal smoothness and accuracy. We comprehensively validate the effectiveness of our approach using freshly collected datasets. Multiple trials of repetitive data collection over the same road and areas make our dataset ideal for testing localization systems. The SunnyvaleBigLoop sequences, with a year's time interval between the collected mapping and testing data, made it quite challenging, but the low localization error of our method in these datasets demonstrates its maturity for real industrial implementation.
Investigating the effect of drugs consumption on survival outcome of Heart Failure patients using joint models : a case study based on regional administrative data

In this work, we propose an innovative approach for investigating the effect of drugs consumption on survival outcomes of patients affected by Hearth Failure (HF), a widespread chronic heart disease. In order to achieve this goal, we consider Joint Models approach [7] on administrative dataset of Lombardia Region. In this database several information is collected about patients’ pharmacological history, which can be used to recover time-dependent data concerning drug assumptions over time. Through the application of this data, we are able to study the influence of longitudinal processes given by pharmacological treatments consumptions on patients’ survival outcomes. Abstract In questo lavoro proponiamo un approccio innovativo per indagare l’effetto del consumo di farmaci sulla probabilità di sopravvivenza dei pazienti affetti da Scompenso Cardiaco. A tal fine, consideriamo l’approccio dei modelli congiunti [7] applicandolo al dataset amministrativo di Regione Lombardia. Questo database raccoglie diverse informazioni sulla storia farmacologica dei pazienti, le quali possono essere utilizzate per risalire a variabili tempo-dipendenti rigurdanti il consumo del farmaco nel tempo. Attraverso l’uso di questi dati, siamo in grado di studiare l’influenza del processo longitudinale dato dai trattamenti farmacologici sugli esiti di sopravvivenza dei pazienti. Marta Spreafico MOX, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, e-mail: marta1.spreafico@mail.polimi.it Francesca Gasperoni MOX, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, e-mail: francesca.gasperoni@polimi.it Francesca Ieva MOX, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, e-mail: francesca.ieva@polimi.it
Loss of b-Catenin Impairs the Renewal of Normal and CML Stem Cells In Vivo

A key characteristic of stem cells and cancer cells is their ability to self-renew. To test if Wnt signaling can regulate the self-renewal of both stem cells and cancer cells in the hematopoietic system, we developed mice that lack b-catenin in their hematopoietic cells. Here we show that b-catenin-deficient mice can form HSCs, but that these cells are deficient in long-term growth and maintenance. Moreover, b-catenin deletion causes a profound reduction in the ability of mice to develop BCRABL-induced chronic myelogenous leukemia (CML), while allowing progression of acute lymphocytic leukemia (ALL). These studies demonstrate that Wnt signaling is required for the self-renewal of normal and neoplastic stem cells in the hematopoietic system.
Separation and bearing estimation of co-channel signals

The authors describe a technique for simultaneously estimating the bearing of and separating (copying) multiple cochannel signals received by a multielement antenna array. The method uses a combination of adaptive beamformers and signal cancelers to sequentially lock onto and remove emitters one by one from the element signals. Inherent to the technique is the generation of a direction vector for each of the isolated emitters. The technique requires neither prior knowledge of emitter bearings nor array calibration is required only to map direction vectors into bearing estimates. The technique is computationally simple and easily amenable to hardware implementation. For reasonably narrowband signals (<50 kHz), the method is simple enough to make real-time implementation using programmable digital signal processing hardware possible. Computer simulations are presented to demonstrate the technique's operation and robustness. <<ETX>>
ANTIPARASITIC PLANTS USED BY THE KANTARURÉ-BATIDA INDIGENOUS COMMUNITY (NE-BRAZIL): ETHNOBOTANY AND LOCAL KNOWLEDGE-EROSION RISKS

Abstract Indigenous people have an intrinsic relationship with the flora used in healing systems. However, data about plants used to treat intestinal parasitosis, which are one of the main morbidity and mortality causes among indigenous peoples, remain scarce. Thus, the aim of the current study is to survey antiparasitic plants used by the Kantaruré-Batida community and to investigate whether their ethno-medico-botanical knowledge is spread. Therefore, it adopted interviews and free lists. Thirty-one (31) indigenous individuals were interviewed and they mentioned 21 plant species. Most respondents (91%) acquired the traditional knowledge through hereditary transmission and spread it (77%) in the same way. Only 35% of the respondents adopt medicinal plants as the first cure resource, besides associating the decrease of such use to their proximity to health care services. Thus, it is worth taking actions to help preserving the local knowledge and biodiversity in order to avoid the loss of indigenous therapeutic treatments.
COST OPTIMIZATION OF ALLOCATING VIRTUAL NETWORK FUNCTIONS WITH PRECEDENCE IN MULTICAST NETWORKS

In the past few years, Network Function Virtualization (NFV) has been widely used to reduce the operational and capital costs of implementing network functions with better performance and easier network management. NFV is a network architecture completely built relying on Virtual Network Functions (VNFs). Quite a few developments have been done for the optimization of resource allocation to implement VNFs in various networks. In this report, an algorithm for reducing the cost of placing the VNFs within a Multicast network along with a choice of selecting the precedence of the VNFs is presented. The proposed approach is formulated as a Mixed Integer Linear Programming (MILP) model based on a main objective of minimizing the cost of resource allocation with Precedence in Multicast Networks. Finally, we evaluate the algorithm through simulations in CPLEX and demonstrate the results.
A multiple model multiple hypothesis filter for systems with possibly erroneous measurements

In this paper a novel method to deal with possibly erroneous measurements is presented. In target tracking applications it may be the case that measurements that are obtained are incorrect in the sense that they do not comply with the measurement model. Examples in (radar) target tracking are: Glint, Multipath, Ambiguous Doppler, etc. The method that we present here is able to detect these non-normalities and modifies the measurement model in such a way that these non-normalities do not blur the track filter output. The method is based on a multi hypothesis assumption w.r. t. to the correctness of the measurement model. This new method is also shown to outperform classical methods for dealing with possibly erroneous measurements. We demonstrate our method by an extensive example of a surveillance radar tracking system with unreliable (or sometimes false) Doppler measurements.
Is the Hawkes Graph Approach Applicable for Examining the Bankruptcy Risk Dependence Structure? An Empirical Analysis of Firms' Bankruptcies in Japan

In this research, we examine the types of bankruptcy risk dependence structures of Japanese firms. For this purpose, we classify bankruptcy events observed in Japan into multiple event types based on industry type and firm size and then use a multidimensional Hawkes process that has been drawing attention recently in the field of finance research so as to model the self-exciting and/or mutually exciting properties of bankruptcy among the event types. As for estimation of the intensity processes associated with the multidimensional Hawkes process, we attempt a new approach using a nonparametric estimation for piece-wise constant kernel functions, introduced by Embrechts and Kirchner (2) to effectively obtain a weighted directed graph representing the estimation result called the Hawkes graph, as well as a conventional maximum likelihood estimation for an exponentially decaying kernel function. We compare and consider the estimation results of the two specifications via visualization with Hawkes graph representations to find that the Embrechts and Kirchner's estimation is applicable for examination of bankruptcy risk contagion.
Protocol Analysis of a Federated Search Tool: Designing for Users

SUMMARY Librarians at Springfield College conducted usability testing of Endeavor's federated search tool, ENCompass for Resource Access. The purpose of the testing was to make informed decisions prior to customizing the look and function of the software's interface in order to make the product more usable for their patrons. Protocol, or think-aloud, analysis was selected as a testing and analysis method. Subjects from the general college community were recruited and given a list of tasks to perform on ENCompass, and they were asked to speak all of their thoughts out loud as they worked. Upon analyzing the test results, researchers found that subjects' problems fell into certain categories, such as unfamiliarity with terms or navigation from screen to screen. The researchers were able to use their findings to recommend extensive revisions to the interface, which improved usability for this library's patrons.
Adverse Infarct Remodeling 92 a Promotes Angiogenesis and − Single Intracoronary Injection of Encapsulated

del Gonzalez-Alujas, Jordi Pérez-Rodon, Marielle Esteves, Carla Fonseca, Nuria Toran, Bruno Garcia Neus Bellera, Ignasi Barba, Antonio Rodriguez-Sinovas, Eulalia Ferret, Miguel Angel Asín, MaTeresa Prevents Adverse Infarct Remodeling 92a Promotes Angiogenesis and − Single Intracoronary Injection of Encapsulated Antagomir Online ISSN: 2047-9980 Dallas, TX 75231 is published by the American Heart Association, 7272 Greenville Avenue, Journal of the American Heart Association The doi: 10.1161/JAHA.114. 000946 2014;3:e000946; originally published September 19, 2014; J Am Heart Assoc. http://jaha.ahajournals. org/content/3/5/e000946 World Wide Web at: The online version of this article, along with updated information and services, is located on the
1 Ricin : an ancient story for a timeless plant toxin 2

The castor plant (Ricinus communis L.) has been known since time immemorial in 11 traditional medicine in the pharmacopeia of Mediterranean and eastern ancient cultures. Moreover, 12 it is still used in folk medicine worldwide. Castor bean has been mainly recommended as anti‐ 13 inflammatory, anthelmintic, anti‐bacterial, laxative, abortifacient, for wounds, ulcers, and many 14 other indications. Many cases of human intoxication occurred accidentally or voluntarily with the 15 ingestion of castor seeds or derivatives. Ricinus toxicity depends on several molecules, among them 16 the most important is ricin, a protein belonging to the family of ribosome‐inactivating proteins. Ricin 17 is the most studied of this category of proteins and it is also known to the general public, having 18 been used for biocrimes in several cases. Here, the main steps of ricin research are reported with 19 particular regards to its enzymatic activity, structure and cytotoxicity. Moreover, we discuss ricin 20 toxicity for animals and humans, as well as the relation amongst bioterrorism and ricin and its 21 impact on environmental toxicity. Ricin has also been of great utility to develop a number of 22 immunotoxins specific for the elimination of unwanted cells, mainly cancer cells; some of these 23 immunotoxins gave promising results also in clinical trials. 24
Using Natural Language Processing and Discourse Features to Identify Understanding Errors in a Spoken Dialogue System

While it has recently become possible to build spoken dialogue systems that interact with users in real-time in a range of domains, systems that support conversational natural language are still subject to a large number of spoken language understanding (SLU) errors. Endowing such systems with the ability to reliably distinguish SLU errors from correctly understood utterances might allow them to correct some errors automatically or to interact with users to repair them, thereby improving the system’s overall performance. We report experiments on learning to automatically distinguish SLU errors in 11,787 spoken utterances collected in a field trial of AT&T’s How May I Help Yousystem interacting with live customer traffic. We apply the automatic classifier RIPPER (Cohen 96) to train an SLU classifier using features that are automatically obtainable in real-time. The classifer achieves 86% accuracy on this task, an improvement of 23% over the majority class baseline. We show that the most important features are those that the natural language understanding module can compute, suggesting that integrating the trained classifier into the NLU module of the How May I Help You system should be straightforward.
TRANSLATION ERROR SPOTTING FROM A USER'S POINT OF VIEW

The evaluation of errors made by Machine Translation (MT) systems still needs human effort despite the fact that there are automated MT evaluation tools, such as the BLEU metric. Moreover, assuming that there would be tools that support humans in this translation quality checking task, for example by automatically marking some errors found in the MT system output, there is no guarantee that this actually helps to achieve a more correct or faster human evaluation. The paper presents a user study which found statistically significant interaction effects for the task of finding MT errors under the conditions of non-annotated and automatically pre-annotated errors, in terms of the time needed to complete the task and the number of correctly found errors.
Influence of the local defect distribution on vibration characteristics of ball bearings

Local defects in ball bearings may occur at the center line of raceway and its surrounding areas. However, most current studies were concentrated in studying the influence of the local defect located at the centerline of raceway on the bearing vibrations, where the effects of local defects surround the centerline were ignored. To overcome this problem, based on Hertzian point contact theory and multi-body dynamic algorithm, a multi-body dynamic model considering the offset and angular distributions for a ball bearing with a local defect on its outer raceway is established. The influences of offset distance and skew angle between the geometric center of local defect and the centerline of outer raceway on the bearing vibrations are investigated. The relationship between the offset distance and the impulse waveform characteristics is obtained, as well as that between the skew angle and the impulse waveform characteristics. The results show that the offset distance and skew angle of the local defect have a great influence on the time-domain impulse waveform characteristics of the bearing accelerations. This paper can provide a useful guidance for the accurate diagnosis of early local fault in the ball bearings.
Asymptotic output tracking of fully input-output linearizable systems via output feedback

We study the asymptotic output tracking control of fully input-output linearizable nonlinear systems in a case where the full state of the system is not available. The main purpose of the paper is to show the following two facts : 1) if a single-input single-output (SISO) nonlinear system has relative degree n, then there always exists a state observer for the given nonlinear system which guarantees the observation error converges to zero exponentially; and 2) if a SISO nonlinear system has relative degree n, then there always exists an output feedback controller which guarantees the tracking error is less than the prescribed bound and converges to zero asymptotically.