Miracle-dz/UniFAR-FTUs huggingface dataset:
northward density shift of bird species in boreal protected areas due to climate change

Species ranges are expected to move latitudinally poleward because of the warming climate. We asked whether northward patterns are observable also in population densities of land birds in Finnish protected areas such that temporal population changes would be most pronounced toward species range boundaries. We compared population changes of northern species, southern species, and species distributed over the whole country from 1981– 1999 to 2000–2009 in 96 protected areas. Northern species showed the greatest decrease in southern Finnish protected areas, and southern birds increased most in northern Finnish protected areas. Among species distributed over the whole country, there were population density shifts toward northern Finnish protected areas. Two thirds of the species that decreased most were northern, whereas many of the species showing the greatest increase were southern habitat generalists. The results show that there are already northward density shifts occurring that probably precede future species range shifts.
HDT-UD: A very large Universal Dependencies Treebank for German

We report on the conversion of the Hamburg Dependency Treebank (Foth et al., 2014) to Universal Dependencies. The HDT consists of more than 200.000 sentences annotated with dependency structure, making every attempt at manual conversion or manual post-processing extremely costly. The conversion employs an unranked tree transducer. This formalism allows to express transformation rules in a concise way, guarantees the well-formedness of the output and is predictable to the rule writers. Together with the release of a converted subset of the HDT spanning 3 million tokens, we release an interactive workbench for writing and reﬁning tree transducer rules. Our conversion achieves a very high labeled accuracy with respect to a manually converted gold standard of 97.3%. Up to now, the conversion effort took about 1000 hours of work.
A Conceptual Model of Benchmarking Data and its Implications for Data Mapping in the Data Economy

Digitalization of the economy requires enterprises from all industries to revisit their current business models and prepare their organizations for the digital age. One task is the (re-)design of hybrid and digital products and services. The foundation builds the improved interchangeability of data and the availability of external data sources through data markets and platforms. This leads to the requirement of a structured decision-making while mapping data sources to digital products. In order to successfully transform their business and develop valuable new products, companies require methodological help. This paper proposes a high-level conceptual model for the assessment of data sources value. It consists of an approach for comparing data sources based on a common description of data and individual metrics definition enable a benchmark process. The development of the model and its practicability has been validated in a case study with an industrial partner.
Sınavı, Zaman Serisi Model, Matematik PREDICTION OF NUMBERS QUESTION MATHEMATICS IN THE UNIVERSITY ENTRANCE EXAM BY TOPICS WITH LSTM-BASED DEEP NEURAL NETWORK

In this study, we proposed a model for estimating the number of questions in the long short term memory (LSTM) deep neural network (DNN) and the mathematics test in the university entrance exam. The data set of the model consists of 931 questions divided according to 16 subjects of the mathematics test for the years 1981-2018. The data set is divided into 80% for the training of the model and 20% for the test. Hypercritical parameters have been determined to provide high accuracy in time series estimation problems in the LSTM model. The number of questions for each subject group has been trained one by one in the time series model. As a result of the study, the average accuracy was 98.42% and the average accuracy was 96.82% in the test. The data set was compared with machine learning algorithms to measure the accuracy of the DNN algorithm used and LSTM DSA achieved the highest performance. As a result of study, the future studies will provide the development of robots to predict because of the high accuracy of the model.
A Secret Key Information Hiding in Digital Images Protocol based on Steganographic Methods in Image Frequency Domain

In this paper, we present and evaluate experimentally a stego-key steganographic method operating in the frequency domain of digital images and an information hiding protocol based on this method. According to this protocol, the two communicating parties share a set of candidate cover images and a secret key, which is divided into two subkeys needed by the stego-key steganographic method. The first one is used for hiding the hidden message size while the second one is used to guide the message hiding process. After the selection of the cover image, the message embedding method can utilize one of three schemes for the collection of appropriate image blocks, based on the Discrete Cosine Transform coefficients, in which the message can be hidden with minimal visual image distortion. The recovery of the hidden message is possible even if the cover image is subjected to the JPEG (lossy) image encoding standard. The use of the keys in the embedding process makes the method especially robust as the attacker has two challenges to overcome in order to extract the hidden message, i.e. the extraction of the message size and, then, the extraction of the hidden message itself. We provide experimental evidence demonstrating the efficiency of the proposed cover block selection schemes of the embedding and disembedding methods both in terms of image distortion as well as robustness under image compression. A Secret Key Information Hiding in Digital Images Protocol based on Steganographic Methods in Image Frequency Domain Publication History: Received: October 31, 2016 Accepted: June 28, 2017 Published: June 30, 2017
The Effect of Four-Week Period of Aerobic Exercise with Cinnamon Consumption on Lipoprotein Indicates and Blood sugar in Diabetic Female Patients (Type 2)

Introduction: Cinnamon as an herbal medicine has the ability to reduce blood glucose and lipoproteins in diabetic patients. Based on the positive effects of exercise on diabetic patients, the present study was conducted to investigate the effect of Four weeks Period aerobic exercise alongside using cinnamon on lipoprotein parameters and blood glucose in women with type 2 diabetes. Methods: Thirty diabetic women were voluntarily selected and were randomly divided into three groups: 1) aerobic exercise group; 2) aerobic exercise alongside using cinnamon; and 3) control group. Aerobic exercise took four weeks with 60 percent of maximum heart rate. Blood samples were collected at the beginning and end of the study. Results: Blood glucose, the fat percentage and HDL, and the ratio of LDL to HDL in the first group significantly decreased and in the second group increased (P<0.05). Also the first group showed a significant reduction in triglyceride. The only significant change observed in the control group was a significant increase in the level of LDL. Comparing the first and second group, it was observed that in the second group the level of total cholesterol decreased and the ratio of LDL to HDL increased (P<0.05). Conclusion: Using cinnamon alongside aerobic exercise is likely to be beneficial in regulating the concentration of blood glucose and lipids in diabetic patients.
48o CONGRESO ESPAÑOL DE ACÚSTICA ENCUENTRO IBÉRICO DE ACÚSTICA EUROPEAN SYMPOSIUM ON UNDERWATER ACOUSTICS APPLICATIONS EUROPEAN SYMPOSIUM ON SUSTAINABLE BUILDING ACOUSTICS

The Internet of Things is being used in several application domains and is identified as one of the key enablers of the Smart City paradigm. Notwithstanding some efforts have been carried out to advance in the adoption of Web standards and Cloud and Fog computing technologies, developing a Smart City IoT platform remains a challenge. This paper describes our experience building a Smart City Internet of Things platform framed on the SusCity project. The proposed platform allows the gathering, processing, and visualization of typical gauges in Smart City scenarios, such as water and air quality, temperature, humidity, mobility, and noise levels. The data is standardly collected from different sources and then displayed in a dashboard to the final users.
THE SNAPSHOT OF NANOSECOND DEVELOPMENT OF HIGH POWER MICROWAVE VACUUM WINDOW BREAKDOWN

Breakdown at the vacuum/dielectric interface is triggered by multipactor and finally realized by plasma avalanche in the ambient desorbed or evaporated gas layer above the dielectric. We have theoretically and experimentally demonstrated that the periodic surface profiles and external resonant magnetic field can prominently increase the high power microwave (HPM) breakdown thresholds. The recent experiments of diagnosing the snapshot of nanosecond development of vacuum window breakdown are reported in this paper. For a flat-surface window, the light emission from the local plasma is focused in a thin layer above the surface during the HPM pulse, and the light emission lasts much longer than the HPM pulse, the thickness increases and the light weakens. The periodic surface could effectively suppress multipactor demonstrated by a much weaker light emission compared with flat surface.
The Role of Academic Self-Efficacy in Improving Students’ Metacognitive Learning Strategies

Introduction: Metacognitive strategies play an essential role in students’ learning and achievement; therefore, identifying their antecedents should be considered. This study indicated how self-efficacy, as motivational beliefs, affects the meta-cognitive strategies of medical students using a SEM approach. Method: The present study was a quantitative cross-sectional research design, using a Smart-PLS 3 approach in which 225 medical students at Shiraz University of Medical Sciences were selected, using simple random sampling. Pintrich and De Groot’s (1990) students’ self-efficacy for learning and performance questionnaire and metacognitive learning strategies questionnaire developed by Dowson and McInerney (2004) were used to collect data. The collected data were analyzed using SPSS 21 and PLS 3 software. Results: The validity and reliability of research questionnaires were confirmed by confirmatory factor analysis. The results showed self-efficacy had a positive and significant relationship with planning (r=0.24, p<0.001), monitoring (r=0.30, p<0.001) and regulating (r=0.31, p<0.001). Furthermore, self-efficacy had direct, positive and statistically significant effect on metacognitive learning strategies (β=0.42, p<0.001). Conclusion: The findings suggest students who believe they are capable to learn and to do their academic tasks are more effective in adopting meta-cognitive strategies to achieve learning objectives than students who do not maintain such optimistic beliefs. Therefore, it is recommended that the officials of Shiraz University of Medical Sciences provide opportunities for strengthening the students’ self-efficacy and metacognitive learning strategies through providing training courses. In these courses students should be explicitly instructed how a specific learning strategy is adopted, why it is important and when and how it applies to the specific task.
PROPOSED THERMAL MODEL OF SILICON-ON-INSULATOR ( SOI ) INTEGRATED CIRCUITS

The Silicon-on-insulator (SOI) metal oxide semiconductor field effect transistor (MOSFET) structure with a layer of buried silicon oxide added to isolate the device body and the silicon substrate can significantly cut down source and drain depletion capacitances and can reduce the effect of short channel. Though, the low thermal conductivity of the buried oxide (BOX) can cause local heating, changed electrical properties, altered heat flow down interconnects, and failure of thermal devices. The current thermal models that are presently used in simulation of a circuit to account for thermal effects do not accurately capture the heat flow in the devices. However, accurate models rely on large network circuits or arithmetic simulations which does not execute speedily enough for large scale integrated circuit (LSIC) simulation. The drive of this research work is to advance a method that is efficient balance between accuracy, adaptability and speed and can be used in large scale simulation. The approach will integrate efficient SOI device thermal model and communicate thermal model into integrated circuit (IC) simulation, and will offer accurate, effective and efficient electro-thermal simulation tool for large scale SOI integrated circuit structure.
THE PROJECTION SPHERE

In this paper we show a way of viewing normal surfaces in a onevertex triangulation of a three-manifold using the unique vertex-linking two sphere and projections of the normal surface. 1. Normal Surface Theory Let M be a three-manifold with a triangulation T . A normal surface in M is a properly embedded surface such that the intersection of the surface with each 3-simplex of M is a collection of properly embedded disjoint disks with either three or four edges that span three or four distinct faces of the 3-simplex. A disk with three edges is called a t-disk, and a disk with four edges is called a q-disk. A normal isotopy of M is an isotopy that leaves the simplicies of T invariant. Up to normal isotopy, there are four distinct t-disks and three distinct q-disks in each 3-simplex. We refer to t-disks and q-disks as elementary disks. A normal surface can consist of any combination of the four t-disk types but can have at most one q-disk type in each tetrahedron. Figure 1 illustrates the t-disks and the q-disks. An arc type is the normal isotopy class of an arc in which an elementary disk meets a 2-face of a 3-simplex of T . A normal arc is made up of a union of arcs from given arc types. Corresponding to a triangulation T is a set of matching equations. The elementary disk types relative to T are arbitrarily assigned labels (a1, a2, a3, ., a7t), where t is the number of tetrahedra in T . We then can assign to a normal surface F a 7t-tuple ~ F = (x1, x2, x3, ., x7t), called the normal coordinates of F , where xi denotes the number of elementary disks in F of type ai . A 7t-tuple of non-negative integers ~x = (x1, x2, x3, ., x7t) corresponds to a normal surface if it satisfies two constraints. The first constraint is that there can be only one q-disk type in each tetrahedron. The second constraint concerns the matching of elementary disks that meet along an interior 2-simplex of M . In a tetrahedron there are two elementary disk types that meet a face in a given arc type. In two tetrahedra that meet along a common 2-face there are three matching equations; one for each arc type. Each equation is of the form: xh + xi = xj + xk. The system of matching equations, subject to the constraints that there can be only one q-disk type in each tetrahedron and all the variables are nonnegative, has a solution space in which each integral solution corresponds to a normal surface. Projecting that solution space onto the unit sphere gives us the projective solution space. Thus the Projective Solution Space is the solution space to the system we get by adding the additional equation x1 + x2 + . + x7t = 1 Date: September 1, 2007.
Nonlinear Auto-Regressive with eXogenous (NARX) input model for Liquid-Gas Dehydration and control Systems: Data Driven Modelling Approach

The operation and management of dehydration systems for the determination of liquid and gas dew points is becoming increasingly complex. Several methods for prediction of the liquid and gas dew points have been developed by researchers. These methods differ in the available inputs, their classification and the horizon of the prediction. In this paper, a nonlinear auto-Regressive with eXogenous (NARX) input model has been proposed. The data driven modelling approach was adopted in the proposed model with System Identification toolbox in MATLAB software. Implementation and simulation of the model which was achieved by feeding the measured input data into the developed model shows that the model is able to reproduce the dew-point (measured output) of the dehydrator bed, and hence gives a good prediction of it.
Spatial release from masking in bilateral cochlear implant users listening to the Temporal Limits Encoder strategy

Binaural hearing benefits with bilateral cochlear implants (CI) are usually smaller than with normal hearing (NH) in the same tasks. This gap in performance has typically been attributed to a lack of coordinated stimulation between ears and the high stimulation rates used in clinical processors. These factors hinder sensitivity to interaural timing differences (ITDs); an important binaural cue for NH listeners. The Temporal Limits Encoder (TLE) strategy was originally designed to encode unilateral low-frequency temporal fine structure pitch cues into the signal envelope of CIs. However, TLE also lowers the stimulation rate on some channels which may potentially provide useable ITD cues. Here, we measured spatial release from masking (SRM) in bilateral CI users listening to TLE vs Advanced Combinational Encoder (ACE) strategy to determine if TLE provides a benefit. The CCiMobile research platform was used for testing. Results from eight listeners showed comparable word recognition performance in quiet and co-located conditions for TLE and ACE, even with a short acclimatization period with TLE. In the spatially-separated condition, performance across the group was more similar with TLE than ACE, and more listeners showed SRM. These results indicate that TLE has the potential for improving binaural hearing benefits for CI users.
Kobe University and Kindai University at TRECVID 2018 AVS Task

—This paper presents our system developed for Ad-hoc Video Search (AVS) task (manually-assisted) in TRECVID 2018. Our system adopts a concept-based approach using the ﬁve sources of training data, 1) collaborative annotations for Semantic INdexing (SIN) in TRECVID 2013 [1], 2) ImageNet [2], 3) Places365 dataset [3], 4) Sports1M dataset [4] and 5) MS COCO dataset [5]. The following four runs were submitted:
Image registration with structuralized Mutual Information: application to CEST

Synopsis In image registration, mutual information (MI) has proved to be an effective I i i i , l i i ( I ) i s imilarity measure and is widely used for medical image registration. However, the i i l i i i l i l i i i . , MI algorithm does not consider spatial dependencies of voxels and introduces I l i i i l i l i s ignificant errors when registering images with large intensity changes, l ike in Zi i i i i i l i i , l i i spectral images of CEST-MRI. This abstract shows that by the incorporation of l i I . i i i structural information the SMI algorithm demonstrates robust performance l i i I l i registering Z-spectral images with large and complex intensity variat ions. i i l i i l l i i i i .
An Integrated Architecture for Corrosion Monitoring and Testing, Data mining, Modeling and Diagnostics/Prognostics

It has been established that corrosion is one of the most important factors causing deterioration and decreased performance and reliability in critical aerospace and industrial systems. Corrosion monitoring, detection, and quantification are recognized as key enabling technologies to reduce the impact of corrosion on the integrity of aircraft and industrial assets. Accurate and reliable detection of corrosion initiation and propagation, with specified false alarm rates, requires novel tools and methods, including verifiable simulation and modeling methods. This paper reports an experimental investigation of the detection and quantification of pitting corrosion on aluminum alloy panels using 3D surface metrology methods and image processing techniques. Panel surfaces were evaluated by laser microscopy and stylus-based profilometry to characterize global and local surface features. Promising imaging and texture features were extracted and compared between coated and uncoated aluminum panels at different exposure times under accelerated corrosion conditions. Image processing, information processing, and data mining techniques were utilized to evaluate the presence and extent of pitting corrosion. A new modeling framework for corrosion stages is introduced that emphasizes the representation of pitting corrosion and ultimately the crack formation process. Detection and prediction of the evolution of corrosion stages relies on data, a particle filtering method, and the corrosion propagation model. Results from these experimental studies demonstrate the efficacy of this proposed methodology.
Is an intratympanic injection of corticosteroids effective in the treatment of otitis media with effusion?

Abstract Objectives Chronic otitis media with effusion (OME) is a worldwide major health problem for both children and adults. The aim of this study is to test the effectiveness of intratympanic injection of corticosteroid in the treatment of chronic OME. Study The study was applied on 14 patients (24 ears) who had failed medical treatment and had recurrence after surgery or patients who refused surgical treatment. Methods These patients received 4 intratympanic injections of dexamethasone. Approximately 0.5 ml of dexamethasone was injected in each time. Subjective assessment for symptomatic improvement was done and objective assessment was done by pure tone audiometry and tympanometry 3 months after the last injection. Results At the end of follow up period, no patient had noticeable improvement in hearing, aural fullness nor tinnitus. Also, pure tone audiometry and tympanometry revealed no noticeable improvement in any patient. Conclusion It was found that intratympanic injection of dexamethasone is not effective in management of chronic OME.