Miracle-dz/UniFAR-FTUs huggingface dataset:
Noise robust goodness of pronunciation measures using teacher's utterance

In the applications of computer-aided pronunciation training (CAPT), evaluation of second language learner’s pronunciation is an important task. For this task, goodness of pronunciation (GoP) is shown to be effective and is typically computed under clean speech conditions. However, in real scenarios, CAPT systems often need to deal with noisy conditions, which could degrade the effectiveness of GoP. We analyze the variations in GoP performance under noisy conditions by adding three types of noises namely, babble, white and f-16 at 20 dB, 10 dB and 0 dB signal-to-noise ratio (SNR) conditions. We hypothesize that the use of phonemes uttered by a teacher would make GoP score more robust and mimic the human rating closely, based on which we propose a modiﬁcation to the typical lexicon based GoP (LGoP). The proposed scheme is referred as teacher ut-terance based GoP (TGoP). In addition, GoP of learner’s and teacher’s utterances are combined to propose a GoP like (GL) score based on the difference between the two. Correlation co-efﬁcient between the GoPs and the teacher’s ratings is used as the performance metric. Experiments conducted on the speech data collected from Indian English learners reveal that, although the performance of different GoP schemes drops with additive noise, TGoP performs better than LGoP in both clean and noisy conditions. In low SNR conditions, GL performs better than both TGoP and LGoP.
Optimization of Annealing Temperature , Concentration of Primer , and Genome DNA for Amplification of Disease Resistance Gene Markers on Tiger Shrimp ( Penaeus monodon )

Identification of the molecular basis of disease-resistant shrimp with PCR technique is one of the initial steps in Assembly of tiger shrimp Penaeus monodon strains resistant to the disease.This study aims to optimize the PCR process in order to obtain the corresponding target genes and increases the amplification products. Isolation of genomic DNA was conducted by using phenol-chloroform method. Amplification of microsatellite fragments using RTG-PCR beads kit with specific primers MsatPm-F and MsatPm-R. Optimization of annealing temperature is set at 50, 52, 54, and 56 oC. Optimization of primer concentration is done with a concentration of 0,5 μM; 1,0 μM; 1,5 μM; dan 2,0 μM forward and reverse primer, and genomic DNA were used as templates, respectively 0.5; 1.0; 1,5; and 2.0 μg/μL. The results showed that the conditions of the PCR reaction largely determine the amplification process for the identification disease resistance gene marker of tiger shrimp, where annealing temperature 54 oC, the concentration 1 μM of Primer MsatPm-F and MsatPm-R, and genomic DNA as much as 1 μg/μL provide best amplification because it produces the corresponding target, thick ribbon, and not occur mispriming.
Quality PREDICTING SOIL ORGANIC CARBON IN AGROECOSYSTEMS UNDER CLIMATE CHANGE SPECIAL SECTION Core Ideas

Grazing lands support the livelihoods of millions of people across nearly one-half of the globe. Soils are the backbone of stability and resilience in these systems. To determine livestock grazing impacts on soil health, we conducted a global meta-analysis of soil organic carbon (SOC), total N, C/N ratio, and bulk density responses to grazing strategies (continuous, rotational, and no grazing) and intensities (heavy, moderate, and light grazing) from 64 studies around the world. Across all studies and grazing intensities, continuous grazing significantly reduced SOC, C/N, and total N compared with no grazing. Soil compaction (i.e., increased bulk density) was greater under both continuous and rotational grazing compared with no grazing; however, rotational grazing had lower bulk density than continuous grazing. Rotational grazing had greater SOC than continuous grazing and was not different from no grazing. The positive responses of SOC to rotational grazing could create climate change mitigation opportunities. Grazing strategy comparisons were minimally conditioned by aridity class (i.e., arid, subhumid, and humid); however, complete observations were notably limited or missing for many rotational grazing comparisons. For continuous and no grazing strategy comparisons, we found that grazing management can significantly influence soil function and health outcomes; however, site-specific environmental factors play important moderating roles. Greater coordination across regional, national, and global efforts, as well as consistent guidelines for soil health evaluation, would help overcome these knowledge gaps and vastly improve our collective understanding of grazing impacts on soil health, providing greater management and policy impacts. A Global Meta-Analysis of Grazing Impacts on Soil Health Indicators
Segregation , Race , and Bias : The Role of the US Census : Comments of

Issue: The US Bureau of the Census has requested commentary upon the utility of measures of segregation used in the 2002 report on residential segregation, “Racial and Ethnic Segregation in the United States: 1980-2000. " Daniel Weinberg and John Iceland are noted as the principal analysts for this report. The purpose of the following is to comment on general issues regarding race and segregation measurement tools, to offer some thoughts on the technical adequacy of segregation analyses, and then to provide reference to research in the allied issue of housing integration.
Reducing methane emissions in dairy cows

Methane is produced in the rumen (called enteric methane, CH4) as part of the normal process of feed digestion. Typically, about 6 to 10% of the total gross energy consumed by the dairy cow is converted to CH4 and released via the breath. Thus, methane losses can be considered an inefficiency in converting feed energy to milk. In addition, CH4 is a potent greenhouse gas (GHG) that contributes to global warming. Reducing CH4 losses is an environmentally sound practice that can improve production efficiency. Our review presents some nutritional approaches that can reduce enteric CH4 emissions from dairy cows.
Clustering Phenomena in Dropout

Despite its prevalence, Dropout lacks a conclusive explanation behind its regularization effects. In this paper, we verify that applying Dropout is akin to training a stochastic neural network. We then analyze the variance across models to quantify the regularization properties of Dropout and explain the observed trends from the stochastic perspective. Subsequently, we propose that the network produces similar nodes to adapt to the stochastic training process, resulting in a clustering phenomenon that reduces model complexity. Our experiments culminate in a compression scheme that converts the trained stochastic network into a smaller, deterministic network for prediction.
Mobile Ad Hoc Networks for Ubiquitous Computing : Review

The term “ubiquitous computing” refers to making many computing devices available throughout the physical environment, while making them effectively invisible to the user and its aims to create surroundings, transparent to the user, where devices with communication and processing capacity (cellular phones, PDA, sensors, electrical appliances, electronic books, etc.) can cooperate in an intelligent and context-aware manner. Communication plays a fundamental role in this field and in particular mobile ad hoc networks (MANETs) can provide flexibility to the access. This paper presents the concept of experiment relative to the use of the Bluetooth and IEEE 802.11 wireless technology to build a MANET which provides network support to a context-aware application.
UNDERDETERMINED BLIND SEPARATION FOR SPEECH IN REAL ENVIRONMENTS WITH F 0 ADAPTIVE COMB FILTERING

This paper proposes a method for separating speech signals when there are more signals than sensors. The underdetermined scenario has already been investigated, exploiting the sparseness of speech signals. These methods employ binary masks to extract the signals, and therefore, the extracted signals contain loud musical noise. To mitigate this side effect, a combined continuous mask approach and post processing scheme is proposed here. First, the time-frequency points at which each source is active are estimated based on the sparseness assumption. These values are used to design continuous masks, instead of conventional binary masks, to extract target speakers. Then, using the fundamental frequency (F0) estimated from each separated speaker, F0 adaptive comb filters are tuned and used to further enhance the separation performance and sound quality of the output. Experimental results show that the proposed combination of a continuous mask and F0 adaptive comb filtering reduces the detrimental musical noise effect under both anechoic and reverberant conditions with TR=130 ms.
Biologically-Inspired Deep Reinforcement Learning of Modular Control for a Six-Legged Robot

Deep Reinforcement Learning (DRL) has been applied successfully in an increasing number of areas, ranging from computer games towards robotic control [1]. While such Deep Learning approaches have shown to produce viable solutions, these are still struggling when we try to scale them up towards complex bodies or when these approaches should be applied in more natural contexts that require behavioral flexibility. In these areas, there is still a major discrepancy between current state-of-the-art DRL approaches and biological systems [5] that excel at adaptive behavior. Therefore, insights on the structure of biological control systems appears as a promising approach for guiding DRL approaches [2]. Our goal is to address as an example the complex control problem of a six-legged walking agent. Such a problem is difficult, as there are many coupled degrees of freedom that have to be controlled in a coordinated way. Such a problem appears difficult to solve through a basic DRL approach as the space for exploration is growing way too large. Therefore, we will take a modular and hierarchical control approach for locomotion that is inspired by the structure of walking control as found in animals [6]: First, the complete control problem is divided into smaller sub-problems. Research on insects have found a decentralized control approach that suggests as a basic building block a division into individual leg controllers. Secondly, this induces a hierarchy. There is a higher level that selects a particular behavior to perform. A lower level takes care of motor control on the joint level. We will introduce such a modular structure into a neural network controller and train this system using reinforcement learning. The modularity of this approach and in particular the decentralized aspect set this apart from other current hierarchical DRL approaches [4]. Each module only has to control, on the lower level, a small number of coupled degrees of freedom (this is comparable to an approach as are motor synergies and which we applied in a DRL approach in [3]). On the higher level that deals with selection of motor behaviors, a form of coordination is required. In the presented approach, we will use a fixed form of coordination and analyze learning performance. In the future, we want to extend this towards a research project that is also taking concurrency on the higher
RECOGNITION OF EMOTION AND ADULT ATTACHMENT

The main aim of this study was to examine the relationship between affective attachment and accuracy in decoding of facial expressions of basic emotions (anger, contempt, disgust, fear, happiness, sadness and surprise). It was expected that with the higher level of dimensions (anxiety and avoidance), the level of success in identifying facial expressions of emotions would get lower. The sample of respondents included 249 students of different professional orientations at the Faculty of Philosophy, University of Niš, Serbia. The gender structure consisted of 59 (23.7%) males and 190 (76.3%) females. The average age was 22.13 (SD = 1.596) years. Instruments. As a stimulus, we have used a collection of photos, »Matsumoto and Ekman’s Japanese and Caucasian Facial Expressions of Emotion« (Matsumoto and Ekman, 1988). Also, we have used the ECR-rQuestionnaire for the evaluation of the pattern of affective attachment (Fraley, Waller and Brennan, 2000). The hypothesis on the connection of dimensions of affective attachment (avoidance and anxiety) and the success in identifying basic emotions (anger, contempt, disgust, fear, happiness, sadness, surprise) has been confirmed. The dimensions of af1 Professor Tatjana Stefanović Stanojević, psychologist, e-mail:sstanja63@ gmail.com 2 Professor Aleksandra Kostić, psychologist, e-mail: aleksandrakost@gmail. com 3 Professor Howard Steele, psychologist, e-mail:steeleh@newschool.edu 4 Associate Professor Jasmina Nedeljković, psychologist, e-mail: jasmina. nedeljkovic@gmail.com Ljetopis socijalnog rada 2019. , 26 (1), 39-60. 40 articles fective attachment (avoidance and anxiety) are negatively connected with the subjects’ success in identifying facial expressions of emotions.
Comparing the Effect of Output vs . Input Instruction on Iranian EFL Learners ' Learning of Resumptives

This study aimed at comparing the effect of input and output instruction on learning Resumptives by Iranian EFL learners. To this end, 50 individuals (all females) who were all native speakers of Persian and their age ranged from 18 to 28 were chosen through convenient sampling. They were divided into two experimental groups, 25 people each. Before the treatment, in order to take up initial differences between the groups, the participants were given the writing section of a TOEFL test. Then the participants in the first group attended five 90-minute input based grammar instruction sessions while the second group participated in five 90-minute output based grammar instruction sessions. At the end of the treatment period, the participants were given a researcher made grammar test to compare their knowledge of resumptives. The data collected from the pre-test and the post-test were then analyzed through independent samples t-test which showed the output practice can be more beneficial than the input practice.
Immersive Applications for Informal and Interactive Learning for Earth Sciences

Immersive technologies provide novel ways to integrate data with their context. This integration has brought tremendous opportunities to blur the distinction between classroom-based formal learning and informal learning in the outside world. Additionally, the ability for virtual navigation to real world sites has converged space and time. To further the understanding of such opportunities, this paper presents an ongoing project that integrates heterogeneous datasets (i.e., tabular data, 360° photos, and videos) with the 3D photorealistic model of a real-word object in a comprehensive suite of immersive applications (i.e., virtual and augmented reality, collectively known as xR). Our xR prototype provides an immersive analytical environment that supports interactive data visualization and virtual navigation in a natural environment. This work-in-progress project can provide an interactive immersive learning platform (specifically, for K-12 and introductory level geosciences students) where learning process is enhanced through seamless navigation between 3D data space and physical space.
AUTOMATIC 2 D VIRTUAL FACE GENERATION BY 3 D MODEL TRANSFORMATION TECHNIQUES

A system for automatic generation of talking cartoon faces is proposed, which includes four processes: cartoon face creation, speech analysis, facial expression and lip movement synthesis, and animation generation. A face model of 72 facial feature points is adopted. A method for construction of a 3D local coordinate system for the cartoon face is proposed, and a transformation between the global and the local coordinate systems is conducted. A new 3D rotation technique is applied to the cartoon face model with some additional points to draw the face in different poses. A concept of assigning control points is applied to animate the cartoon face with different facial expressions. A statistical method is proposed to simulate the timing information in simulating various facial expressions. For lip synchronization, a sentence utterance segmentation algorithm is proposed and a syllable alignment technique is applied. Twelve basic mouth shapes for Mandarin speaking are defined to synthesize lip movements. Finally, an editable and opened vectorbased XML language Scalable Vector Graphics (SVG) is used for rendering and synchronizing the cartoon face with speech. Experimental results showing the feasibility of the proposed methods are included.
Proceedings Targeting the Resistance in Multiple Myeloma †

Multiple myeloma is a hematological cancer characterized by the clonal proliferation of malignant plasma cells in the bone marrow. That disease has a rather low incidence but displays a high rate of relapse and resistance to conventional therapies. It is therefore necessary to find new therapeutic strategies to overcome this resistance, which is partly attributed to a subpopulation of cells known as cancer stem cells. Withanolides and HDAC6 selective inhibitors were identified as promising compounds in various resistant multiple
, 2018 K 2141 b : A 5M ⊕ super-Earth transiting a K 7 V star every 6 . 7 hours ?

We report on the discovery of K2-141 b (EPIC 246393474 b), an ultra-short-period super-Earth on a 6.7-hour orbit transiting an active K7 V star based on data from K2 campaign 12. We confirmed the planet’s existence and measured its mass with a series of follow-up observations: seeing-limited MuSCAT imaging, NESSI high-resolution speckle observations, and FIES and HARPS high-precision radial-velocity monitoring. K2-141 b has a mass of 5.31 ± 0.46 M⊕ and radius of 1.54+0.10 −0.09 R⊕, yielding a mean density of 8.00+1.83 −1.45 g cm−3and suggesting a rocky-iron composition. Models indicate that iron cannot exceed ∼70% of the total mass. With an orbital period of only 6.7 hours, K2-141 b is the shortest-period planet known to date with a precisely determined mass.
Phenotypic and production performance of indigenous zebu cattle ( Bos indicus ) under hot and humid temperature in Mymensingh district

How to cite this article: Hossain MA, Khan MAS and Hashem MA (2017). Phenotypic and production performance of indigenous zebu cattle (Bos indicus) under hot and humid temperature in Mymensingh district. International Journal of Natural and Social Sciences, 4(3): 49-57. Phenotypic and production performance of indigenous zebu cattle (Bos indicus) under hot and humid temperature in Mymensingh district
A Super-Resolution-Assisted Fingerprinting Method Based on Channel Impulse Response Measurement for Indoor Positioning

The channel impulse response (CIR), which characterizes the multipath channel between a transmitter and a receiver, can serve as a received position signature for indoor position fingerprinting (FP). Since it takes large system bandwidth to distinguish individual paths along which the signal waves travel in an indoor environment, a small bandwidth may yield an unsatisfactory performance of FP based on mere CIR. In this paper, we apply the multiple signal classification (MUSIC) algorithm, a super-resolution method, to unveil the path-delay signatures covered by bandwidth-limited CIRs. With the pseudospectrum evaluated with MUSIC, we resolve and identify the arrival times of the individual paths at a sub-sample precision. We further propose a super-resolution-aided fingerprinting (SFP) algorithm to estimate the receiver's position by taking the averaged positions of the reference points (RPs) of similar FP signatures with weights evaluated by the difference in pseudospectrum and received power. Experiments in an indoor environment show that SFP reduces the positioning error compared to the FP based on conventional channel state information (CSI), and that demands fewer infrastructures and less protocol complexity than CIR-based FP does to achieve similar performance.
Query Optimization Properties of Modified Valuation-Based Systems

Valuation-Based System can represent knowledge in different domains including probability theory, Dempster-Shafer theory and possibility theory. More recent studies show that the framework of VBS is also appropriate for representing and solving Bayesian decision problems and optimization problems. In this paper after introducing the valuation based system (VBS) framework, we present Markov-like properties of VBS and a method for resolving queries to VBS.
A survey of Record Deduplication Techniques

Record Deduplication refers to the task of finding and deleting records in a data set that refer to the same entity across different data sources. Record Deduplication is necessary when joining data sets based on entities that may or may not share a common identifier, as may be the case due to differences in record shape, storage location, and/or curator style or preference. In this paper, we present the detailed analysis of deduplicating the data. We have discussed the different deduplication techniques and analysed the same. For non duplicate set, the two cooperating classifiers, a Weighted Component Similarity Summing Classifier (WCSS) and Support Vector Machine (SVM) are used to iteratively identify the duplicate records from the non duplicate record and a genetic programming (GP) approach to record deduplication. The GP-based approach is also able to automatically find effective deduplication functions.
WCBEM 2012 Leadership in the 21 st century : challenges in the public versus the private system

Major role in differentiating performance organizations from those who register failures is determined by the presence of a dynamic, efficient and flexible leadership. For multiple reasons, researchers presented various forms, theories and models, phenomena of leadership and management style are studied relevant, in relation to their influence on organizations, as expressed by the effectiveness, efficiency and sustainability.Article refers to the exercise of leadership differentiated into two organizational systems with different features: the public and private. Perceived differently at the company level, service users or consumers of goods, it attracts a lot of controversies caused by the processes taking place in the environment and organizational culture. This study defines precisely the differences of perception that leaders of the two systems show in relation to the needs expressed and reflected in the list of recommendations made by the researchers to suggest they change leadership style in the 21st century.
Making Trading Great Again : Trump-based Stock Predictions via doc 2 vec Embeddings Computer Science

References Problem • One of the first seminal papers using Twitter to predict stock movements focused on relatively coarse categories of sentiment [1] • More recent advancements in NLP and NLU have given rise to distributed representations (word2vec, doc2vec) [2, 3] • On January 20th 2017, Donald Trump is inaugurated as President • President Trump uses Twitter as his singular platform. His tweets and policies have been known to shake financial markets.
Recognition of Normal and Whispered Speech Based on RASTA Filtering and DTW Algorithm

This paper presents the results of normal and whispered speech recognition using RASTA (Relative Spectral) filtering applied on PLP (Perceptual Linear Prediction) feature. It is used for a front-end while the DTW (Dynamic Time Warping) algorithm is used for a back-end of ASR system. All isolated words in these experiments are from the Whi-Spe database. In the experiments four training/test scenarios are analyzed: normal/normal, whispered/whispered, normal/whispered and whispered/normal. The speaker dependent mode is used with 10 speakers. The results confirm a good improvement in recognition when RASTA filtering is applied, especially in the mismatch scenarios.