Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmental Effects on the Accentual Phrase in Korean

The Accentual Phrase (AP) in Korean is said to be conditioned by the glottal status in the AP-initial segments, with the canonical shape of THLH. T is realized a H when the initial segment of the AP bears [+stiff vocal cords] and L when it bears [-stiff vocal cords]. The paper raises the question of whether the binary categorical distinction for the AP initial T is reflected upon phonetic realization of F0 (in semitone). The question is pursued by analyzing pitch contour shapes of canonical APs over word-like chunks in Korean reading-style corpus. The initial segments are divided into three groups of fortis obstruents, lenis obstruents, and sonorants. The results showed that the F0 is affected not only by the laryngeal status but also by the sonority difference between lenis obstruents and sonorants. The research raises an empirical question regarding the binary distinction of categorical prosodic events in the Tone and Break Indices (ToBI) system.
The beat the news system: Forecasting social disruption via modelling of online behaviours

Law enforcement agencies and intelligence professionals commonly use labour intensive (often ad-hoc) processes to monitor online behaviours that help detect civil unrest events. These processes are reactive and non-exhaustive. This paper presents the “Beat the News” System, developed at the Data to Decision Cooperative Research Centre (D2D CRC), as a mechanism to address this problem. Beat the News is an automatic analytical system for forecasting and early detection of civil unrest events. This system has been providing continuous forecasts for the past 12 months, and has successfully detected events such as rallies, protests and strikes up to six weeks before they occurred. The system is currently undergoing trials by multiple Australian law enforcement agencies and intelligence professionals. In this paper, the scalable ingestion and enrichment pipeline mechanisms used to support the forecasting and modelling aspects of the Beat the News system are discussed. Also, the cognitive computing techniques, such as natural language processing and automatic pattern recognition, used by the Beat the News system, to extract predictive signals from social media data are explored. The multiple models used to build forecasts, and how they are analysed and evaluated against a record of ground truth data, collected over the last two years, will be discussed. These evaluations are used to demonstrate how social media activity is predictive of realworld activities linked to civil unrest. Finally, some examples of forecasts made by the system are provided.
Alternator : Fault-tolerant state sharing for IoT networks

Applications in the realm of The Internet of Things often depend on the cooperation between devices with different resources at their disposition. For example, devices in this kind of heterogeneous networks may have exclusive access to large disks, powerful CPUs and GPUs, sensors, actuators, etc. Additionally, IoT networks are often subject to constant node failures, unreliable network channels and network partitions. Distributed applications looking to take maximum advantage of the features of each node require precise control of the data flow throughout the network while preserving fault-tolerance and availability. Alternator provides a fault-tolerant, highly available solution to the problem state-sharing for distributed applications in heterogeneous networks. The Alternator key-value store achieves this by using a consistent-hashing scheme, much like Chord[4], as a bottom layer to store metadata for each entry in the system. In order to provide full control of the data flow in the system Alternator allows users to specify the nodes in the system that will replicate each entry. This offers complete granular control of data-flow in the system while also preserving all of the virtues of consistent-hashing schemes: speed and fault-tolerance.
The results of phacoemulsification with intraocular lens (IOL) implantation in Songklanagarind Hospital

Objective: To study the results of phacoemulsification with intraocular lens implantation, including the incidence of perioperative and postoperative complications. Design: Retrospective descriptive study Materials and methods: We reviewed the medical records of 243 cataract eyes (213 patients) who had had phacoemulsification with intraocular lens implantation at Songklanagarind Hospital between 1 January and 31 December, 2002, noting the patient's demographic characteristics, uncorrected visual acuity before and post-surgery and the incidence of perioperative and postoperative complications. Results: There were 143 females and 100 males with an average age of 67.2 years (range 42-93 years). Most patients (68.7%) had uncorrected visual acuity (UCVA) from better than counting finger (CF) to less than 20/70 before surgery. At 4 weeks post-surgery, 157 patients (64.6%) had a UCVA of 20/30 or better, 222 patients (91.4%) had a UCVA of 20/70 o r better. At 3 months post-surgery, there were 158 follow-up patients (65%); 73 patients (46.3%) had stable UCVA and the UCVA of 31 patients (19.6%) had decreased due to posterior capsule opacity. There were 10 cases of perioperative complication. The most common intraoperative complication was the tearing of the anterior lens capsule (50%). Other complications included a subsequent change to an unplanned extracapsular cataract extraction in 1 patient and a ruptured posterior lens capsule with vitreous loss in 1 patient. Five patients (50%) with perioperative complications had a UCVA of 20/30 or better. No statistically significant difference in visual outcome was observed between the patients with and without perioperative complications. There were 8 cases of postoperative complication, but none was serious. After treatment all showed improved visual acuities. Conclusions: We are satisfied with the results of phacoemulsification and intraocular lens implantation in Songklanagarind Hospital. The complication rates were acceptable when compared to other studies.
UvA-DARE ( Digital Academic Repository ) Explorations in Homeomorphic Variational Auto-Encoding

The manifold hypothesis states that many kinds of high-dimensional data are concentrated near a low-dimensional manifold. If the topology of this data manifold is non-trivial, a continuous encoder network cannot embed it in a one-to-one manner without creating holes of low density in the latent space. This is at odds with the Gaussian prior assumption typically made in Variational Auto-Encoders (VAEs), because the density of a Gaussian concentrates near a blob-like manifold. In this paper we investigate the use of manifoldvalued latent variables. Specifically, we focus on the important case of continuously differentiable symmetry groups (Lie groups), such as the group of 3D rotations SO(3). We show how a VAE with SO(3)-valued latent variables can be constructed, by extending the reparameterization trick to compact connected Lie groups. Our experiments show that choosing manifold-valued latent variables that match the topology of the latent data manifold, is crucial to preserve the topological structure and learn a well-behaved latent space.
IMAGE SEGMENTATION : DETERMINATION OF JOINT SPACE AREA INHAND RADIOGRAPHS

This paper is an attempt to investigate the possibility of automating assessment of joint damage in hand radiographs. The goal is to design a segmentation algorithm to obtain the area which is an object, the joint space. Image segmentation is the process of partitioning a digital image into several segments. For this study has collected 46 hands radiographic images. Pre-processing done using adaptive threshold and morphological gradient concept, then do segmentation with watershed transformation. Analysis results of segmentation based on the level of accuracy, sensitivity and specificity using the ROC. Results of segmentation with pre-processing, produces images that are not over-segmentation and produces a clearer image with accuracy value of 95.75%, sensitivity of 70.51% and specificity of 96.99% in a high percentage.
Technique on managing maternal anxiety during pregnancy : integrative review

Summary: This article describes the importance of the Guided Imagery Technique for the management of maternity associated anxiety during pregnancy. Goal: To understand the scientific evidence regarding the Guided Imagery Technique for the management of maternity associated anxiety during pregnancy. Method: Integrative revision of the literature from the Cochrane Library database, using the platform EBSCO Host. From a total of 30 articles on the subject, 10 were included on this article Results/Discussion: The scientific evidence analysis translates on the following topics: anxiety, stress management and physiological impact; relaxation and well-being; adherence to the Guided Imagery Technique; positive perception of the pregnancy; difficulties to its use. Conclusion: The Guided Imagery Technique seems to promote the relaxation and well being of the women and also, aids with the reduction of anxiety levels and perceived discomfort during pregnancy Key-words: Anxiety, stress, pregnancy, images.
Real-time Textureless Object Detection and Recognition Based on an Edge-based Hierarchical Template Matching Algorithm

Textureless object recognition is a difficult task in computer vision because the object-ofinterest (OOI) may not have enough texture information for extracting object features. To address this problem, this paper presents a textureless object recognition method based on the existing Line2D algorithm. The proposed method employs an edge-based hierarchical template matching method to detect and identify a wide variety of textureless objects. Given a reference template image of an OOI, a hierarchical edge-template database containing different 2D poses of the OOI was firstly created by applying affine transformation with different rotating and scaling settings to the reference template image. Next, an edge-based template matching process is performed to detect and recognize the OOI by searching matches between the hierarchical edge-template database and the input image. Finally, the position and angle posture of the OOI can be determined by the best match having the highest similarity measure. Experimental results show that the proposed method not only can efficiently recognize the type, quantity, position, and angle information of various textureless objects in the image, but also can achieve real-time performance about 24 frames per second (fps) in processing 640x480 images. Therefore, the proposed algorithm has the potential to be used in many computer vision applications.
1 FULL-SCALE TESTING AND NUMERICAL ANALYSIS OF A PRECAST FIBRE REINFORCED SELF-COMPACTING CONCRETE SLAB PRE-STRESSED WITH BASALT FIBRE REINFORCED POLYMER BARS

Steel-free pre-stressed reinforced concrete may be used in aggressive environments to increase the durability of structural elements and to limit the carbon footprint by replacing steel with high-strength fibre composites. The design of a 10-m long steel-free precast fibre-reinforced concrete slab, pre-stressed with basalt-fibre reinforced polymer (BFRP) bars and shear-reinforced with glass-fibre reinforced polymer bars, is presented in this paper. Non-linear viscoelastic and elastic-plastic models have been employed for the prediction of the service and ultimate limit state flexural behaviour, respectively. Preliminary tests on the employed materials and a 3-point load test on the slab element are presented, together with indications on its manufacturing process. The proposed numerical analysis is validated against the experimental results.
Systematization , Implementation and Analysis of the Overall Throughput Effectiveness Calculation for the Finishing Processes after Weaving

For the sustainability of continuous improvement, the importance of acquiring as much data as possible from the production field is indisputable. However, converting these data into key performance indicators in a lean production system is much more important. This paper focuses on the finishing processes of the weaving industry in a real production plant. In the study, roll of fabric based traceability is first provided by a radio frequency identification (RFID) and programmable logic controller (PLC) automation structure. In the next step, the calculation of the overall equipment effectiveness (OEE) for each process is provided, and a method of converting these OEE values to the unique indicator as the overall throughput effectiveness (OTE) is proposed. In the last phase of the paper, after getting OTE value automatically, it was aimed to reveal the relationship between the production environment parameters and the OTE indicator. A revised hybrid genetic algorithm was proposed to determine the most important production environment parameters that affect OTE results. Multiple linear regression was utilized to verify the result of the developed algorithm. ARTICLE HISTORY Received: 04.09. 2018 Accepted: 02.04. 2019
A 04 – 01 POLICY AND GOVERNANCE countability for empowerment : Dilemmas facing non-governmental organisations

A recurring theme in modern development discourse is the role that Non-Governmental Organizations (NGOs) play in providing mechanisms for strengthening civil society and with it local governance to lift marginalised communities in developing countries out of poverty through empowerment. Empowerment can result in the greater participation of the poor and marginalised in the economic, social, and civic domains within their communities. NGOs are seen to be ideally placed to perform this task, given their relatively closer proximity to the poor communities they serve however their accountability, particularly the ‘downward’ accountability to their constituents the beneficiaries of their work can affect their role as empowerment. The dilemma that NGOs face is that first, they are generally not required by law or under their governance rules to be accountable to their constituents, and as a consequence there is a risk that any processes of accountability they adopt would not provide their constituency the necessary control that is required for genuine accountability. Second, the ’required’ accountability the NGO has to other stakeholders such as Government and supporters affects the ‘strength’ of the accountability relationship they can have with their constituents. Generally NGOs are guided by staff and self-appointed Boards, and see their role as promoting their values in advancing what they see as a broader community interests. A weakness of NGOs’ and their public benefit role is that they lack a defined accountability path to their constituency that a representative structure would provide. That is, while NGOs purport to represent the interests of their constituency, at a broader level there is no clearly defined path by which they can be held to account by that constituency in representing those interests. The first part of the paper looks at the accountability of NGOs, and the second part will look at the evidence from a number of case studies from NGO programs with poor women in India. Finally the paper identifies ways in which NGOs can strengthen their ‘downward accountability’ to their constituents and therefore improve their empowerment outcomes with poor and marginalised groups.
Towards Safe Navigation of Quadcopter Amongst Uncertain Dynamic Obstacles

In a last few years, there has been a surge of interest in the field of autonomous navigation and exploration using drones. While there have been many advances made in the field, there has been various challenges, yet to be tackled, for a safe navigation of Quad-copters amidst uncertain dynamic obstacles. In this work, we attempt to tackle this problem by incorporating positional uncertainties of drone and moving obstacles into a joint trajectory optimization framework. In this thesis, we formulate a novel trajectory optimization scheme that takes into consideration the state uncertainty of the robot and obstacle into its collision avoidance routine. The collision avoidance under uncertainty is modeled here as an overlap between two distributions that represent the state of the robot and obstacle respectively. Our framework is a generic framework and the idea proposed here can be used to for any sets of distributions with characterizable overlap. In the scope of this thesis, we model these distributions as Gaussian distributions. We adopt the minmax procedure to characterize the area of overlap between two Gaussian distributions, and compare it with the method of Bhattacharyya distance. Bhattacharyya distance is an approximate closed form characterization of overlap between two Gaussian distribution. The Bhattacharyya distance is generalizable to other distributions too, if their overlap can be characterized through some analytical closed form solution. In this work, We provide closed form expressions that can characterize the overlap as a function of control. We establish that our closed form approximations to characterize overlap is less erroneous when compared with entropic distances like Bhattacharyya distance. Our proposed algorithm can avoid overlapping uncertainty distributions in two possible ways. Firstly when a prescribed overlapping area that needs to be avoided is posed as a confidence contour lower bound, control commands are accordingly realized through a MPC framework such that these bounds are respected. Secondly in tight spaces control commands are computed such that the overlapping distribution respects a prescribed range of overlap characterized by lower and upper bounds of the confidence contours. We test our proposal with extensive set of simulations carried out under various constrained environmental configurations. We show usefulness of proposal under tight spaces where finding control maneuvers with minimal risk behavior becomes an inevitable task.
Scoring System Using Semantic Similarity Approach

Essay Scoring System provides a systematic checking of essay based on the similarity of its meaning to the model as implied on the content. This study automatically score essays and give feedback to the students about their score. Besides, the system uses algorithms that analyse the lexical semantics of the words to get the similarity between the model and student essay which includes the Common Term Frequency (CTF), Longest Common Subsequence (LCS), and Semantic Distance (SD). The two essay will undergo the Text Processing Phase which includes the process of Tokenization, Stop words removal, Stemming and Parts-of-Speech (POS) tagging. It uses the WorldNet database for word synonymy and semantic references. Word Sense Disambiguation is also implemented in the study to identify the meaning of the word used in the context and also to solve the ambiguity of meaning particularly on homonyms. The scoring follows the predefined criteria for content relevance, spelling, and grammar. Furthermore, the study conducted tests to the actual users of the system including teachers. Based on these tests, the computed percentage differences between the teacher and the system score is 18.03% with an accuracy of 82.18%. The accuracy shows a close similarity of the system’s score to the teachers’ given score to the essays. Developing the system faces a challenge in the implementation of the semantic algorithms. Since the SMCC Higher Education Research Journal ISSN Print: 2449-4402 · ISSN Online: 2467-6322 Volume 5 · August 2018 SMCC Higher Education Research Journal 2 study is more capable of evaluating semantic similarity based on word occurrences, it is best to further the system’s capability of checking the semantic similarity based on the context of the essay.
Author ' s personal copy Symmetric mortality and asymmetric suicide cycles

In this investigation, tests were performed to determine whether mortality cycles are asymmetric. Results from an asymmetry test of U.S. time-series data from 1951 to 2005 provide no evidence that allcause mortality or mortality caused by disease causes asymmetric cycles. However, the rate of fatalities from suicide exhibits the pattern of an asymmetric cycle. The evidence for asymmetric suicide cycles is statistically significant for men and working-age groups but not for women and non-working-age
From geological interpretation and 3 D modelling to the characterization of the deep seated EGS reservoir of Soultz ( France )

This study presents a 3D interpretation of the geophysical logs run after the drill of three wells at 5 km depth in the framework of the Soultz European EGS (Enhanced Geothermal Systems) project. The major fracture zones encountered in these wells are characterized through examination of borehole image logs, classical geophysical well logs and cutting samples. In the open holes of the granite massif, the flow logs and temperature profiles allow to distinguish natural flowing fractures. These large-scale fracture zones are characterized by sealed core and an around damage zone that is highly fractured and therefore highly permeable. The fractures are identified and measured in orientation and in dip by borehole imagery techniques. The major issue for reconstructing the 3D geometry of the Soultz fracture network is the question of the fracture extension. In a first approach, we define and correlate the fracture extensions according to the importance of flow observed on flow log runs during the injection and stimulation tests in the wells. A maximal fracture extension of 600 m length is proposed, excepted for the most important fault zone that extends to 2000 m. This geometry seems to be in agreement with the development of microseismicity within these fracture planes during the 1997-2003 hydraulic stimulation phases at Soultz. The model is enclosed in a 3D regular grid. The grid axes fit on the directions of the maximal anisotropy of the microseismic cloud (N170°E). The main fractures are modeled by planar discs centered on the wells respecting the fracture orientations and widths. Moreover, each plane is characterized by a property corresponding to its permeability assumed as proportional to the importance of the flow developed in the vicinity of the fracture zones. Storage capacities and types of permeability are quantified. They are similar for the production wells but strongly different for the injection well. The 3D well connectivity is modeled and discussed. This geological model could be used as a geometrical basis for fracture quantification of fracture porosity and permeability in the EGS reservoir.
FOR THE PRESENTATION OF FOREGROUND AND BACKGROUND ITEMS IN AUDITORY DISPLAYS

This work forms a part of a wider project, in which one of the authors is developing a system to sonify images (and other material) via sets of audio (and tactile) effects. The main contribution of this paper is to describe the design, and examine the effectiveness, of “multi-talker focus effects” in directing the user's attention to particular items, while at the same time making them aware of other co-located (or separate) items. Additionally, the paper describes approaches to presenting and navigating multi-level representations of visual scenes, and of non-visual and non-spatial information and entities. It describes how external client application-generated (or manually produced) material can be submitted to the system, and considers several interaction methods, including using multiple taps on parts of images to command the system. Initial results are reported from informal assessment sessions with a totally blind person, and a sighted person.