Miracle-dz/UniFAR-FTUs huggingface dataset:
Working with trauma : a qualitative and retrospective exploration of the experiences of clinicians who work with trauma

The current study explored the gap in understanding the experiences of clinicians who work with trauma given the interesting intersection of high prevalence of trauma and demonstrated lack of training in working with trauma survivors. To this end, this qualitative and exploratory study sought to gain a retrospective understanding of clinicians’ training and career experiences in an effort to glean what has worked well in preparing skilled clinicians to work with trauma. Findings confirmed that clinicians do not feel prepared to do trauma work upon graduating from their degree programs and that they must seek out training opportunities in order to gain competence in this area. Further findings (i.e. insights regarding supervision experiences and self-care) were discussed in an effort to elucidate the most salient takeaways for academic administrators, clinicians, and students training to work in trauma.
Mental health and conflicts : conceptual framework and approaches

The paper provides an overview of the Bank's role in conflict and development, and explores the links between poverty, social capital and mental and psychosocial disorders in conflict settings. The premise of the paper is that increased understanding and targeted interventions to deal with mental health can play an important role in effective post-conflict reconciliation and reconstruction. It also argues that there are effective approaches that can be adapted to different conflict settings. The paper presents a conceptual framework based on experiences in and outside the Bank that can help guide interventions and approaches to address mental health and psychosocial disorders in conflict-affected countries. The paper briefly examines mental health approaches adopted by the Bank in West Bank and Gaza, Bosnia-Herzegovina, Uganda, Burundi and Afghanistan. These brief country illustrations suggest there are a variety of approaches and a growing body of experience on which Bank country teams can draw. The paper concludes by noting areas where additional research would seem appropriate and presenting suggestions for further Bank analytical and operational work.
Analysis of passwords: Towards understanding of strengths and weaknesses

In this paper, we analyze the passwords’ strength from real-world data; perform an in-depth analysis, and extract useful information related to the millions of usernames and passwords being utilized. This useful information thus represents the millions of minds and the individual behaviors in online and offline passwords based information systems. From the twelve million usernames and passwords, we investigate density, numbers in usernames and passwords, special characters, and strength analysis of the usernames and passwords. To the best of our knowledge, this work is unique based on the selected parameters and the amount of processed data. With the extensive analysis, we seek the weak link in the username and password paradigm. With density analysis, it can be deduced that users like to have (or by chance use) similar character usernames and passwords. From the digits analysis in passwords, it is found that users like to use the first few digits (1, 2, and 3) and the last digits (8, 9, and 0). With the special character analysis, we found that “_” is the most widely used character. With the strength analysis, we determined that it is better to use non-popular English vocabulary words and the inclusion of the special characters, lower, upper and digits are in between different words. Also, if a word can be converted to other languages and used as a password, it will be extremely robust. Most users use their username partly or fully as passwords. This opens doors for hackers. The extensive experimentation and results in the appropriate sections provide useful contributions.
Emotion Detection From Speech Using Mfcc & Gmm

In these years, literature about automatic emotion recognition is growing dramatically due to the development of techniques in computer vision, speech analysis and machine learning. However, automatic recognition on emotions occurring on natural communication setting is a largely unexplored and challenging problem. Speech processing is emerged as one of the important application area of digital signal processing. Various fields for research in speech processing are emotion detection from speech, speech recognition, speaker recognition, speech synthesis, speech coding etc. The objective of automatic emotion detection is to extract, characterize and recognize the information of speaker‘s emotions. Feature extraction is the first step for speaker recognition. Many algorithms are suggested/developed by the researchers for feature extraction. In this report, the Mel Frequency Cepstrum Coefficient (MFCC) feature has been used for designing an automatic emotion detection system. Some modifications to the existing technique of MFCC for feature extraction are also suggested to improve the emotion detection efficiency. This report presents an approach to emotion recognition from speech signals. In this report, the framework to extract features from the speech signal that can be used for the detection of emotional state of the speaker. An essential step in the generation of expressive speech synthesis is the automatic detection and classification of emotions most likely to be present in speech input. Keywords— speech recognition , MFCC ,GMM.
Formulasi Ekstrak Sambiloto (Andrographis paniculata) dan Brotowali (Tinospora crispa) Sebagai Inhibitor α-Glukosidase dan Analisis Sidik Jari Menggunakan Teknik Kromatografi

RONA JUTAMA YONANDA Formulation of Sambiloto (Andrographis paniculata) and Brotowali (Tinospora crispa) Extract as An α-Glucosidase Inhibitor and Fingerprints Analysis Using Chromatography Techniques Supervised by LATIFAH K. DARUSMAN and WULAN TRI WAHYUNI. Two of many potential sources of natural materials as an α-glucosidase inhibitors are sambiloto and brotowali. The aims of the study were to obtain the best formula of sambiloto and brotowali extract with highest α-glucosidase enzyme inhibition including its fingerprint information. Extractions were carried out using maceration and ultrasonication methods with water, ethanol 30%, and 70% as the solvents. Sambiloto ultrasonication extract and brotowali maceration extract using ethanol 70% as solvent showed the lowest IC50 value, respectively 55.36 and 68.28 ppm. Both of extracts were then formulated. Formula of sambiloto and brotowali with the concentration ratio of 2 IC50:1 IC50 was the best formula with inhibition value 28.11%. In thin layer chromatography separation, ethyl acetate was the optimum mobile phase for sambiloto extract and chloroform: ethanol: ethyl acetate (0.487: 0: 0.513) is the optimum mobile phase composition for brotowali extract. Ethyl acetate used as mobile phase in formula separation. Formula analysis using high performance liquid chromatography technique with optimum separation condition of sambiloto extract did not show components from brotowali extract, so the separation condition of the formula still need to be optimized.
Development of Wireless Patient’s Vital Sign Monitor Using Wireless LAN (IEEE.802.11.b/g) Protocol

Vital sign monitor is typical medical instrument for basic physiological measurement. Medical practitioner assesses a patient’s health condition by observing measurement results shown in display. In this research, we designed low cost, wireless, PC-based vital sign monitor. Signals captured in designed vital sign monitor are electrocardiogram (ECG), photoplethysmogram (PPG), and body temperature. Captured data are transmitted via wireless LAN module so that medical practitioner is able to monitor patient’s condition remotely from another room or place. The system worked well for maximum transmission distance about 45 meters for LOS condition and 20 meter for NLOS condition. DOI: http://dx.doi. org/10.11591/ijece.v4i6. 6429
Review of Different Techniques for Ripe Fruit Detection

–Many techniques have been developed for ripe fruit image detection. Such as K-means clustering, fuzzy c mean, color segmentation etc. Segmentation is a technique which partitions the images by similarity or equality etc. Segmentation is most important step in image processing. It is used to distinguish various objects in the image. Different ripe fruit detection techniques have been developed by the researchers to detetct ripe fruits image. In this review paper various techniques for ripe fruit image detection are considered.
User Analysis Mechanisms based Mobile Fitness System

Modern men have health problems caused by lack of exercise than in the past. But most modern people do not know what to do exercise. Mobile systems for fitness to solve this problem have been developed. In this paper, by analyzing the user's BMI (Body Mass Index) Index and BMR (Basal Metabolic Rate) value, the data is made available. The processed data is provided to the user which proposes the right exercise and the appropriate level of exercise intensity, for exercise machines. This is different from detecting the movement, like the existing system, and a fitness value showing the calorie consumption caused. Thus the user is considered to be able to efficiently proceed to a movement based on the provided data.
Etude des transferts de masse et de chaleur dans la grotte de Lascaux: le suivi climatique et le simulateur

L:agrotte de Lascauxd,ecouverte en 1940et situeeenDordognedanslavallee de la Vezere est inscrite au Patrimoine Mondial de l'Unesco.Elleest consideree comme I'une des grottes ornees les plus importantes au monde. Lesvisites qui ont suivisa decouverte ont perturbe I'equilibre de lacaviteet induitsa fermetureen 1963. Depuis,elle a retrouve un etat a peu pres stable, jusqu'en 2001 ou une attaque de micro-organismesa eu lieu. Suite a cette proliferation un comite scientifique international pluridisciplinairea ete cree par le ministre de la Culture et de la Communication.Cecomite a d'emblee souhaite disposer d'une meilleure comprehension des ecoulements presents dans la cavite. Pour repondre a cette demande un nouvel outil a ete cree, le «SimulateurLascaux", basesuruncode de mecanique des fluides numerique. Undes principauxatouts de cette methode est son caractere non intrusif. Deuxconfigurations climatiques ont ete choisiesdans cet article. Enseptembre 1981 la grotte etait dans desconditions« stables": lestemperatures dansla rocheentourant lagrotte suivaient le schema classique augmentant avec la profondeur.Lasecondeconfiguration (endecembre1999)concerneune periode precedant des travaux dans la cavite: les temperatures se sont inverseesse trouvant etre plus elevees a la voute qu'au sol. Cetteinversiona conduit au confinement de la grotte. Finalement, les ecoulements resultant du retrait d'une cloisonont ete apprecies grace au simulateur, et il a ete montre un impact negligeable de ce retrait sur I'equilibre de la cavite.
Pimentão cultivado em ambiente protegido sob diferentes tensões de água no solo

This study aimed to evaluated the effects of different soil water tensions applied in two phenological stages in bell red pepper (Capsicum annuum L.) grown in a greenhouse. The work was carried out in the region of Lavras, Minas Gerais and the crop was irrigated by drip. It was used a completely randomized experimental design in factorial outline 2 x 4, considering two different phenological phases (vegetative and reproductive) at four levels of soil water tensions (15, 30, 60 and 120 kPa) and four replications. The results showed that the culture was more sensitive to soil water tensions applied in the reproductive phase. The greatest total and commercial yield in the vegetative and reproductive phases were obtained for the treatments in that the irrigation was accomplished when the tension of the water in the soil reached 15 kPa.
Path planning for mobile articulated robots based on the improved A* algorithm

Mobile articulated robots system composed of tractor and multiple articulated trailers is a nonlinear and underactuated system subject to nonholonomic constraints. The significant achievements of path planning for mobile robots with single segment are very difficult to be applied to it directly. For resolving this problem, the kinematics model is established for the system with three segments connected by nonstandard connection type, as well as its trajectory. Equivalent size is introduced that includes two parameters: the distance parameter being the size for enlarging obstacles and the curvature parameter being the minimum turning radius of system. The distance parameter is used to enlarge obstacles in the environment to shrink the system to be a particle. The planning path adopted by the improved A* algorithm can ensure itself as a collision-free and feasible path as long as the maximum path curvature is no larger than the curvature parameter in free space. The comparisons of simulation result show that the improved A* algorithm makes the quality of path optimized and more suitable than A* algorithm under the complex environment.
Study of Multiple Multiagent Reinforcement Learning Algorithms in Grid Games

This thesis studies multiagent reinforcement learning algorithms and their implementation; In particular the Minimax-Q algorithm, the Nash-Q algorithm and the WOLF-PHC algorithm. We evaluate their ability to reach a Nash equilibrium and their performance during learning in general-sum game environments. We also testtheir performance when playing against each other. We show the problems with implementing the Nash-Q algorithm and the inconvenience of using it in future research. We fully review the Lemke-Howson Algorithm used in the Nash-Q algorithm to find the Nash equilibrium in bimatrix games. We find that the WOLF-PHC is a more adaptable algorithm and it performs better than the others in a general-sum game environment.
A Linear Systems Primer

Based on a streamlined presentation of the authors' successful work Linear Systems, this textbook provides an introduction to systems theory with an emphasis on control. The material presented is broad enough to give the reader a clear picture of the dynamical behavior of linear systems as well as their advantages and limitations. Fundamental results and topics essential to linear systems theory are emphasized. The emphasis is on time-invariant systems, both continuous- and discrete-time. Key features and topics: * Notes, references, exercises, and a summary and highlights section at the end of each chapter. * Comprehensive index and answers to selected exercises at the end of the book. * Necessary mathematical background material included in an appendix. * Helpful guidelines for the reader in the preface. * Three core chapters guiding the reader to an excellent understanding of the dynamical behavior of systems. * Detailed coverage of internal and external system descriptions, including state variable, impulse response and transfer function, polynomial matrix, and fractional representations. * Explanation of stability, controllability, observability, and realizations with an emphasis on fundamental results. * Detailed discussion of state-feedback, state-estimation, and eigenvalue assignment. * Emphasis on time-invariant systems, both continuous- and discrete-time. For full coverage of time-variant systems, the reader is encouraged to refer to the companion book Linear Systems, which contains more detailed descriptions and additional material, including all the proofs of the results presented here. * Solutions manual available to instructors upon adoption of the text. A Linear Systems Primer is geared towards first-year graduate and senior undergraduate students in a typical one-semester introductory course on systems and control. It may also serve as an excellent reference or self-study guide for electrical, mechanical, chemical, and aerospace engineers, applied mathematicians, and researchers working in control, communications, and signal processing. Also by the authors: Linear Systems, ISBN 978-0-8176-4434-5.
A formal model of ambiguity and its applications in machine translation

Systems that process natural language must cope with and resolve ambiguity. In this dissertation, a model of language processing is advocated in which multiple inputs and multiple analyses of inputs are considered concurrently and a single analysis is only a last resort. Compared to conventional models, this approach can be understood as replacing single-element inputs and outputs with weighted sets of inputs and outputs. Although processing components must deal with sets (rather than individual elements), constraints are imposed on the elements of these sets, and the representations from existing models may be reused. However, to deal efficiently with large (or infinite) sets, compact representations of sets that share structure between elements, such as weighted finite-state transducers and synchronous context-free grammars, are necessary. These representations and algorithms for manipulating them are discussed in depth in depth. To establish the effectiveness and tractability of the proposed processing model, it is applied to several problems in machine translation. Starting with spoken language translation, it is shown that translating a set of transcription hypotheses yields better translations compared to a baseline in which a single (1-best) transcription hypothesis is selected and then translated, independent of the translation model formalism used. More subtle forms of ambiguity that arise even in text-only translation (such as decisions conventionally made during system development about how to preprocess text) are then discussed, and it is shown that the ambiguity-preserving paradigm can be employed in these cases as well, again leading to improved translation quality. A model for supervised learning that learns from training data where sets (rather than single elements) of correct labels are provided for each training instance and use it to learn a model of compound word segmentation is also introduced, which is used as a preprocessing step in machine translation.
A Hybrid Method for Open Information Extraction Based on Shallow and Deep Linguistic Analysis

Open Information Extraction is a relation-independent extraction paradigm that extracts assertions from massive and heterogeneous corpora such as the Web. Light relation extractors focus on eﬃciency by restricting analysis to some shallow linguistic tools such as part-of-speech tagging. Although these methods are fast and scalable, they are unable to deal with complex sentences (such as complicated and long distance relations) due to using only shallow syntactic features. This paper presents two novel hybrid methods, TextRunner-DepOE (TR-DOE) and ReVerb-DepOE (RV-DOE) which combine high-performance subset of shallow Open IE systems with the strengths of a deep Open IE system. We detect the best trade-oﬀ between precision and recall by tuning two combination parameters: sentence length and conﬁdence measure. Since the focus is on using time eﬃciently, we used a fast and robust deep extractor. Experiments indicate that the proposed hybrid methods obtain signiﬁcantly higher performance than their constituent systems. The best result was for TR-DOE which had an F-measure almost twice that of TextRunner.
6D Visual Servoing for Industrial Manipulators applied to Human-Robot Interaction Scenarios (6D Visual Servoing für industrielle Manipulatoren, angewandt in Szenarien der Mensch-Roboter Interaktion)

This thesis presents a novel vision-based control system for industrial manipulators. The primary contribution is an uncalibrated Visual Servoing (VS) based on 6D orthogonal features. These features have good linearization and decoupling properties, leading to a full-rank image Jacobian which allows avoiding classical VS problems such as image space singularities and local minima. By integrating the VS system with the environment and robot model constraints in real world applications using a prioritized multi-constraints control framework, we demonstrate that it can be easily and safely integrated into a variety of robotic systems involving human-robot interaction.
Supporting Development of Energy-Optimised Java Real-Time Systems using TetaSARTS

—This paper presents how the tool TetaSARTS can be used to support the development of embedded hard real-time systems written in Java using the emerging Safety Critical Java (SCJ) proﬁle. TetaSARTS facilitates control-ﬂow sensitive schedulability analysis of a set of real-time tasks, and features a pluggable platform speciﬁcation allowing analysis of systems including the hosting execution environment. This is achieved by approaching the analysis as a model checking problem by modelling the system using the Timed Automata formalism of the model checking tool U PPAAL . The resulting Timed Automata model facilitates easy adjustment of a wide variety of parameters that may be of interest such as processor frequency. This paper demonstrates that TetaSARTS can be used for tuning processor frequency, for conducting control-ﬂow sensitive Worst Case Response Time analysis, and for conducting processor utilisation and idle time analysis.
Channel estimation for time varying channel based on decision directed technique in OFDM mobile systems

A channel estimation method was proposed based on decision directed technique and pilot tracking for OFDM WLANS with mobile terminals. The result of training sequence based estimation was used as the initialization of decision directed technique. With the help of the decision symbols, the statistical characteristics of the transmitted data via the fading channel were applied for the channel estimation. Some reliable estimated results combined with pilot were used to track the change of the fading channel. The simulation results show that the proposed method has better performance than training sequence based or pilots based channel estimation method.
The use of nonparametric item response theory to explore data quality. In: S. P. Reise & D. Revicki (Eds.). Handbook of item response theory modeling: Applications to typical performance assessment.

The aim of this chapter is to provide insight into a number of commonly used nonparametric item response theory (NIRT) methods and to show how these methods can be used to describe and explore the psychometric quality of questionnaires used in patient-reported outcome measurement and, more in general, typical performance measurement (personality, mood, health-related constructs). NIRT is an extremely valuable tool for preliminary data analysis and for evaluating whether item response data are acceptable for parametric IRT modeling. This is in particular useful in the field of typical performance measurement where the construct being measured is often very different than in maximum performance measurement (education, intelligence; see Chapter 1 of this handbook). Our basic premise is that there are no “best tools” or “best models” and that the usefulness of psychometric modeling depends on the specific aims of the instrument (questionnaire, test) that is being used. Most important is, however, that it should be clear for a researcher how sensitive a specific method (for example, DETECT, or Mokken scaling) is to the assumptions that are being investigated. The NIRT literature is not always clear about this, and in this chapter we try to clarify some of these ambiguities.