Miracle-dz/UniFAR-FTUs huggingface dataset:
Parsing with Sparse Annotated Resources

This thesis focuses on algorithms for parsing within the context of sparse annotated resources. Despite recent progress in parsing techniques, existing methods require significant resources for training. Therefore, current technology is limited when it comes to parsing sentences in new languages or new grammars. We propose methods for parsing when annotated resources are limited. In the first scenario, we explore an automatic method for mapping language-specific partof-speech (POS) tags into a universal tagset. Universal tagsets play a crucial role in cross-lingual syntactic transfer of multilingual dependency parsers. Our central assumption is that a high-quality mapping yields POS annotations with coherent linguistic properties which are consistent across source and target languages. We encode this intuition in an objective function. Given the exponential size of the mapping space, we propose a novel method for optimizing the objective over mappings. Our results demonstrate that automatically induced mappings rival their manually designed counterparts when evaluated in the context of multilingual parsing. In the second scenario, we consider the problem of cross-formalism transfer in parsing. We are interested in parsing constituency-based grammars such as HPSG and CCG using a small amount of data annotated in the target formalisms and a large quantity of coarse CFG annotations from the Penn Treebank. While the trees annotated in all of the target formalisms share a similar basic syntactic structure with the Penn Treebank CFG, they also encode additional constraints and semantic features. To handle this apparent difference, we design a probabilistic model that jointly generates CFG and target formalism parses. The model includes features of both parses, enabling transfer between the formalisms, and preserves parsing efficiency. Experimental results show that across a range of formalisms, our model benefits from the coarse annotations. Thesis Supervisor: Regina Barzilay Title: Professor
A Word Embedding based Method for Question Retrieval in Community Question Answering

Community Question Answering (cQA) continues to gain momentum owing to the unceasing rise of user-generated content that dominates the web. CQA are platforms that enable people with different backgrounds to share knowledge by freely asking and answering each other. In this paper, we focus on question retrieval which is deemed to be a key task in cQA. It aims at finding similar archived questions given a new query, assuming that the answers to the similar questions should also answer the new one. This is known to be a challenging task due to the ver-boseness in natural language and the word mismatch between the questions. Most traditional methods measure the similarity between questions based on the bag-of-words (BOWs) representation capturing no semantics between words. In this paper , we rely on word representation to capture the words semantic information in language vector space. Questions are then ranked using cosine similarity based on the vector-based word representation for each question. Experiments conducted on large-scale cQA data show that our method gives promising results.
Effect of Delaying School Start Time on Sleep Quality, Emotions, and Performance in Korean Adolescents

Background and ObjectiveaaThe purpose of this study was to investigate the effect of delaying school start time on sleep quality, emotions, and performance in Korean adolescents. MethodsaaData were collected in two months and 12 months after delaying school time, each using self-administered questionnaires for 238 students at a middle school in Gyeonggi province. Questionnaires consisted of demographic data and various sleep and emotion related scales, including the Pittsburgh Sleep Quality Index (PSQI). Students were divided into two groups, of increased or decreased total sleep time (TST). ResultsaaIn both groups, sleep duration, global PSQI score, and sleep efficiency significantly improved in 12 months, compared to two months’ data. There was significant improvement in depression, stress, behavioral aggression, and verbal aggression in the increased TST group. The increased TST group showed advancement in subjective feeling of happiness, and number of times students are late for school, between baseline and 12 months. The decreased TST group showed significant differences between baseline and 12 months in seven categories of subjective life quality/ emotions in school, including subjective feeling of happiness, concentrating in classes, and anger. ConclusionsaaAfter school start time was delayed, many adolescent’s TST relatively decreased on school nights. However, students whose TST increased, showed reduction in depression, stress, and behavioral/verbal aggression. Students whose TST decreased also reported reduced negative affect, and significant improvement in subjective emotions and school performance. Delaying school start time may be beneficial, in improving mental health and quality of life of students. Sleep Med Res 2019;10(1):1-7
Toward a UI Adaptation Approach Driven by User Emotions

With the advent of ubiquitous computing, HumanComputer Interfaces must now be able to dynamically adapt to changes which may occur in their context of use while preserving usability. In this perspective, previous research evidences the need to adapt User interfaces (UIs) by taking into account dynamic user features like emotions at design time. To go one step further, this paper proposes an architecture to adapt the UI driven by user emotions at runtime. It is based on an existing adaptation approach which is extended to consider emotions. Hence, this proposition relies on three main components: the inferring engine, the adaptation engine and the Interactive System. We show an ongoing prototype to evaluate the feasibility of the approach for which we describe its implementation.
Content based Feature Combination Method for Face Image Retrieval using Neural Network and SVM Classifier for Face Recognition

Objectives: To propose a CBIR based face image retrieval and identification model. Method/Analysis: A model of hybrid face recognition system based on CBIR and SVM is proposed. The feature vectors from the face image database are generated by using Gabor wavelet (GW), wavelet Transformation (WT), and Principal Component Analysis (PCA). For the face image retrieval purpose, Artificial Neural Network (ANN) is adopted and its performance on the retrieval process is evaluated with PCA, WT, GW and their fusion as a feature vector. The query image is recognized from the faces returned by retrieval process by using Support Vector Machine (SVM). The experimental results indicate that the fusion of PCA, WT and GW features as a feature vector performs reasonably well for retrieval and recognition process. The experimental results also demonstrate the efficiency of the proposed approach for face recognition over existing methods when considering different performance measures such as system running time, Receiver Operating Characteristic (ROC) curve and recognition accuracy. The proposed model was evaluated with two face databases viz. Unconstrained Facial Image (UFI) and Oracle Research Laboratory (ORL) face database with a recognition accuracy of 95.42% and 98.75% respectively. Finding: The proposed system has been tested for retrieval and recognition and found with reasonable retrieval time and high recognition rate. Novelty/Improvement: The conventional model-based face recognition systems are limited in several aspects, like (1) It is usually time-consuming and expensive to collect a large amount of training facial images, (2) It is usually difficult to generalize the models when new training data or new persons are added, in which an intensive retraining process is usually required and (3) The recognition performance often scales poorly when the number of persons/ classes are very large. The proposed CBIR based retrieval and the recognition system is intended to take care of the above limitation.
Modelling and Simulation of Electric Vehicle Drive Through SAEJ227 & EUDC Cycles

The conventional method of transportation is the custom of I.C engines which uses fossil fuels like petrol, diesel, etc., these commercial resources are depleting day by day. Moreover, these fuels cause pollution and atmospheric deviations like global warming. In recent years the significance and development of electric vehicles have rapidly increased as it is pollution-free and more reliable. The MATLAB/SIMULINK is a key tool that facilitates design and requirements to reduce the cost of product development. In this paper electric vehicle drive is modelled, simulation is done by giving SAEJ227 (Society of Automotive Engineers), a Japanese driving cycle, and EUDC (Extra Urban Driving Cycle), a European driving cycle as input signals. After the simulation, motor voltage, motor current, motor power curves, and battery voltage, current, power, and SOC (State Of Charge) curves plotted. The model can be used to assess the electric drive's energy flow and capability for different driving cycles.
Parallel game architectures with tardiness policy and workload balance

Computer games are real-time applications that create interactive virtual environments, usually as discrete time-stepped simulations. These simulations may have predefined time step sizes or may use variable time step sizes. These approaches are common in games, but not flexible. In the first approach, when the game runs on a machine with abundant resources, the game does not use the extra capacity to improve simulation quality (task results or presentation). The second approach usually runs the simulation as fast as possible, using the time elapsed between consecutive time steps to scale all computations, so as the simulation runs in real-time. However, this approach wastes processor time and energy and in multi-core hardware scenarios (e.g., GPUs and clusters), the problem of wasting computing resources becomes more severe. In this paper, we propose a parallel and adaptive architecture that employs workload balance, precedence of game tasks and tardiness policy in multi-core hardware to handle the aforementioned issues. The architecture uses tardiness policy to monitor and change task behavior according to the current conditions of he host hardware. On more powerful computers, the architecture is able to improve task quality if there is spare time available. On less powerful computers, the architecture restricts task functionality so that tasks are able to complete on time. We provide two examples to demonstrate how the architecture works.
Control Strategies for Robot Therapy

The patients hit by stroke have primary concerns of upper and lower limb weakness. To recover from these disorders patients, undergo a process known as rehabilitation. Robotic devices have the potential to address this area as noted by the previous studies. The purpose of this technology is build such devices which serves individuals motor impairments to practice the movement without the supervision of therapist. Formerly several devices were developed but such resources are limited. Studying and improving the devices used in therapy maximises the potential of restoration and provides greater means of access to cost effective healthcare devices. Control strategies play a substantial role in the success of these type of robotic devices. The purpose of this study is to document a review of control strategies which have been implemented previously on the rehabilitation robotic devices assisting either upper or lower limb in order to facilitate the development of new and improved strategies.
GR@PPA event generator

The history and the present status of the GR@PPA event generator are briefly reviewed. The development of GR@PPA started in 2000 in order to provide a framework of NLO event generators for hadron collision interactions. After the first release of the package (GR@PPA\_4b) in 2002, which supported four bottom quark production processes, many multi-particle production processes have been added to the package: GR@PPA\_ALL in 2004 and GR@PPA 2.7 in 2006. Now we are going to release a new package (GR@PPA 2.8), which supports single and double weak-boson production processes with an initial-state jet matching. Though the matrix elements presently included are still at the tree level, this new release is an important step towards constructing consistent NLO event generators.
Controlling the correctness of physical exercises performance

This document contains the description of the program for the control of the correct physical exercises performance implementation using Microsoft Kinect, the method of the comparison between live motions performed by the user and recorded motions, description of the testing of the program and also information about different approaches for gesture recognition. Keywords—Physical exercises, Microsoft Kinect, motion comparison, production rule system, gesture recognition
ANALISIS SENTIMEN DENGAN MENGGUNAKAN METODEKLASIFIKASI LAZY K-STAR

Analisis Sentimen merupakan cabang ilmu dari text mining yang sudah mulai banyak dimanfaatkan dalam berbagai bidang, misalnya dalam bidang politik, bidang pemasaran produk, bidang jasa, bidang perhotelan dan lain lain. Contoh analisis sentimen dalam dunia bisnis yaitu digunakan untukmenganalisis secara otomatis opini pelanggan tentang produk dan pelayanannya. Dalambidang politik, analisis sentimendigunakan untukmenampungaspirasimasyarakatmengenai kinerjapemerintahanmaupunmanajemenreputasi tokoh tertentu.Dalambidang pendidikan, termasuk dalampenelitian ini, dengan melakukan analisis sentimen mahasiswa terhadap sebuah Universitas atauPerguruan Tinggi, dapatmenjadi evaluasiPerguruanTinggi tersebutdalammeningkatkankualitas pembelajarannya. Penelitian ini menggunakan data primary yang berasal dari mahasiswa yang minimal sudah melakukan pembelajaran minimal setahun di Universitas PGRI Yogyakarta, data yang didapat, akan dilakukan normalisasi kata terlebih dahulu, sehingga kata yang tidak baku menjadi baku. Kemudian penelitianinimenggunakanWordTokenizerdenganmenggunakanmetode klasifikasi LazyK-Star. Hasil klasifikasimenggunakanmetode Lazy K-Star tidak sebaik denganmenggunakanmetode Naive Bayes dan SVMdengan persentase sebesar 79,2952%, sehingga perlu adanya improvisasi atau pembelajaran tambahan yang dilakukan gunamendapatkan hasil akurasi yang lebih baik.
Design of Hybrid Wireless and Power Line Sensor Networks With Dual-Interface Relay in IoT

The hybrid wireless and power line communication (HWPLC) networks address the problem that mobile wireless sensors and power line communication (PLC) sensors cannot communicate with each other within an Internet of Things (IoT) network. In this paper, we design a relay equipped with a dual wireless and PLC interface, which connects both the PLC and wireless sensors into an IoT network. Furthermore, the dual-interface relay forwards messages by adaptively selecting a interface according to the channel state. A general mathematical probability model of the dual-interface relaying system is presented. The probability density function of the output signal-to-noise ratio (SNR) is developed, which is based on explicit closed-form expressions derived from the statistics character of the PLC and wireless channel. Furthermore, the average capacity, bit-error rate (BER) expressions, and the outage probability formulas are derived. Numerical results show that the HPLWC relaying system with the dual-interface can significantly improve the performance of capacity, BER, and outage probability by adaptively selecting the interface with the optimal received SNR.
Adaptive reuse and repurposing of industrial buildings to residential dwellings in Auckland City

Auckland is currently facing a housing crisis in which demand for living space has exceeded what is being provided. The ad hoc demolition of older buildings, driven by proactive property developers in hope of meeting the ever-increasing housing demand, often does not take into consideration the economic, environmental and social benefits that existing buildings can offer. Auckland City has at its disposal existing building stock that is often underutilised, with building owners usually opting for demolition as opposed to adaptation, due to a stigma attached that it is both a complicated and costly process. The study utilises a case study approach that focuses on a conversion project, the Ford Factory Lofts, situated in Parnell, one of Auckland’ s CBD fringe areas. Semi-structured in-depth interviews were carried out with the property developer, architect, structural engineer, planner and marketing manager. Fieldwork and documentary research complemented the interviews with the aim to understand the potential that adaptive reuse has in the context of Auckland City. The findings indicate that for a developer to consider adaptive reuse as a viable alternative to demolition, a clear set of financial incentives must be identified. Although the undertaking was not attractive in terms of cost and risk related to buildability, marketability and the potential for return on investment played an important role and ultimately validated the process, allowing the developer to capitalise on the building’s character. Other drivers, associated with sustainable building practices, were not considered and were instead a bi-product of the adaptive reuse process.
Reverberation Suppression of Noisy Speech Signal

This paper presents an enhancement of noisy reverberant speech signal by linear prediction analysis and spectral subtraction. The linear prediction analysis is used to suppress the short term reverberation. In general, the equalized impulse response has two detrimental effects, late impulses and pre-echo. These late impulses and pre-echo are suppressed by spectral subtraction. In LP analysis, the SNR value is improved and also the LP parameters are calculated accurately by flattering the spectral components.
Reduced Ecological Footprints of Modern Facilities Introducing the Implementation of Advanced Wireless Technologies, and Human Resources’ Benefits

The necessity of lowering the mean power consumption of various facilities, due to the lack of their enormous future energy needs, led to an ongoing advance of various technologies. These technologies have been oriented towards the concept of a Reduced Ecological Footprint. Massive structures (such as building complexes and hospitals) have been redesigned and upgraded; many interior designs have been dramatically altered while new electronic devices are constantly being produced in order to revolutionize a long term perspective towards a “Green Planet” while they exhibit astonishing signal processing. Consequently, an enormous technology already exists which needs to be properly combined to a proposed methodology and to new ideas relevant to systems’ administration through automatic wireless control. This paper intends to reduce the gap between design and realization of the aforementioned research. Consequently, the primary contribution of this research is the proposal of a complete design protocol with minimized defects relevant to Reduced Ecological Footprints of Facilities (REFF) along with its beneficial advantages relevant to providing a healthy and productive work environment. This protocol consists of four main parts which are 1) the main key points-guidelines, 2) its objectives, 3) the know-how methodology for implementation in existing installations and 4) the description of the imminent benefits in workforce/human resources.
Clinical comparison of different cardiovascular risk scores for cardiovascular risk prediction in Indian patients

Background: Cardiovascular diseases (CVD) are the main cause of mortality and disability in India. Early and sustained exposure to behavioral risk factors leads to development of CVD. The present study was conducted to compare different cardiovascular calculators for CVD risk assessment models in young Indian patients presenting with myocardial infarction.Methods: This study included 85 patients with myocardial infarction (MI). Their predicted 10-year risk of CVD was calculated using three clinically most relevant risk assessment models viz. Framingham Risk score (RiskFRS), American College of Cardiology/American Heart Association (RiskACC/AHA) and the 3rd Joint British Societies risk calculator (RiskJBS). Results: RiskFRS recognized the highest number of patients (15.4%) at high CVD risk while RiskACC/AHA and RiskJBS calculators provided inferior risk assessment but statistically significant relationship. RiskFRS and RiskACC/AHA (Pearson's r 0.870, p<0.001). Conclusions: RiskFRS seems to be as most useful CVD risk assessment model in young Indian patients. RiskFRS is likely to identify the number of patients at ‘high-risk’ as compared to RiskJBS and RiskACC/AHA.
Grenzen und Widersprüche der Entwicklung und Anwendung ,Autonomer Systeme‘

Derzeit überrollt uns nach drei Jahrzehnten relativer Stille erneut eine Sturzflut von Meldungen über Projekte vermeintlicher ›künstlicher Intelligenz‹ (KI, engl. AI für ›artificial intelligence‹). Die Spannweite der Meldungen reicht von Heilsversprechen über Erfolgsgeschichten bis zu Szenarien der Apokalypse. Als kleine Auswahl aus dem gesamten Spektrum vermitteln die nachstehenden Äußerungen einen Eindruck:
No . 197 Games with the Total Bandwagon Property

We consider the class of two-player symmetric n × n games with the total bandwagon property (TBP) introduced by Kandori and Rob (1998). We show that a game has TBP if and only if the game has 2n−1 symmetric Nash equilibria. We extend this result to bimatrix games by introducing the generalized TBP. This sheds light on the (wrong) conjecture of Quint and Shubik (1997) that any n × n bimatrix game has at most 2n − 1 Nash equilibria. As for an equilibrium selection criterion, I show the existence of a 1/2–dominant equilibrium for two subclasses of games with TBP: (i) supermodular games; (ii) potential games. As an application, we consider the minimum-effort game, which does not satisfy TBP, but is a limit case of TBP. JEL Classification: C62; C72; C73
Gargalos e demandas da insfraestrutura portuária e os investimentos do PAC

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