Miracle-dz/UniFAR-FTUs huggingface dataset:
Features selection for primitives estimation on emotional speech

This paper examines the importance of different groups of speech acoustic features in the estimation of emotional primitives which define a three-dimensional continuous model of emotions. A set of proposed features is extracted from a database of German spontaneous emotional speech. This features set tries to represent several aspects of emotional content in speech that have been discussed separately in other works. Features selection and dimensionality reduction techniques are applied to find the features subsets that best estimate the emotional primitives Valence, Activation and Dominance. Finally, the emotional primitives are estimated using different classifiers based on the proposed features getting better results than the ones previously reported on related works.
Protein sequence motif patterns using adaptive Fuzzy C-Means granular computing model

Data Mining is the process to extract hidden predictive information from large databases. In Bioinformatics, data mining enables researchers to meet the challenge of mining large amount of biomolecular data to discover real knowledge. Major research efforts done in the area of bioinformatics involves sequence analysis, protein structure prediction and gene finding. Proteins are said to be prominent molecules in our cells. They involve virtually in all cell functions. The activities and functions of proteins can be determined by protein sequence motifs. These protein motifs are identified from the segments of protein sequences. All segments may not be important to produce good motif patterns. The generated sequence segments do not have classes or labels. Hence, unsupervised segment selection technique is adopted to select significant segments. Therefore Singular Value Decomposition (SVD) entropy method is adopted to select significant sequence segments. In this proposed work, weighted K-Means and Adaptive Fuzzy C-Means have been applied to the selected segments to generate granules, since large amount of segments cannot be grouped or clustered as such. Each granules generated by weighted K-Means algorithm are further clustered by using the K-Means algorithm and granules generated by Adaptive Fuzzy C-Means algorithm are clustered by using Weighted K-Means. The two proposed models are compared with K-Means granular computing model. The experimental results show that Adaptive Fuzzy C-Means with Weighted K-Means technique produces better results than K-Means and weighted K-Means granular computing methods.
Free head motion eye gaze tracking using a single camera and multiple light sources

One of the main limitations of current remote eye gaze tracking (REGT) techniques is that the user's head must remain within a very limited area in front of the monitor screen. In this paper, we present a free head motion REGT technique. By projecting a known rectangular pattern of lights, the technique estimates the gaze position relative to this rectangle using an invariant property of projective geometry. We carry extensive analysis of similar methods using an eye model to compare their accuracy. Based on these results, we propose a new estimation procedure that compensates the angular difference between the eye visual axis and optical axis. We have developed a real time (30 fps) prototype using a single camera and 5 light sources to generate the light pattern. Experimental results shows that the accuracy of the system is about 1deg of visual angle
Learning-based depth estimation from 2D images using GIST and saliency

Although there has been a significant proliferation of 3D displays in the last decade, the availability of 3D content is still scant compared to the volume of 2D data. To fill this gap, automatic 2D to 3D conversion algorithms are needed. In this paper, we present an automatic approach, inspired by machine learning principles, for estimating the depth of a 2D image. The depth of a query image is inferred from a dataset of color and depth images by searching this repository for images that are photometrically similar to the query. We measure the photometric similarity between two images by comparing their GIST descriptors. Since not all regions in the query image require the same visual attention, we give more weight in the GIST-descriptor comparison to regions with high saliency. Subsequently, we fuse the depths of the most similar images and adaptively filter the result to obtain a depth estimate. Our experimental results indicate that the proposed algorithm outperforms other state-of-the-art approaches on the commonly-used Kinect-NYU dataset.
An empirical assessment of the use of foundational ontologies in ontology development

There is an assumption that ontology developers will use a top-down approach by using a foundational ontology, because it purportedly speeds up ontology development and improves quality and interoperability of the domain ontology. Informal assessment of these assumptions reveals ambiguous results that are not only open to different interpretations but also such that foundational ontology usage is not foreseen in most methodologies. Therefore, we investigated these assumptions in a controlled experiment. After a lecture about DOLCE, BFO, and partwhole relations, one-third chose to start domain ontology development with an OWLized foundational ontology (6 out of 18 ontologies developed by 52 participants). On average, those who commenced with a foundational ontology added more new classes and class axioms, and significantly less object properties than those who started from scratch. The comprehensive results show that the ‘cost’ incurred in spending time getting acquainted with a foundational ontology—in casu, DOLCE and a taxonomy of part-whole relations—compared to starting from scratch was more than made up for in size, understandability, and interoperability already within the limited time frame of the experiment.
ECNU: Leveraging on Ensemble of Heterogeneous Features and Information Enrichment for Cross Level Semantic Similarity Estimation

This paper reports our submissions to the Cross Level Semantic Similarity (CLSS) task in SemEval 2014. We submitted one Random Forest regression system on each cross level text pair, i.e., Paragraph to Sentence (P-S), Sentence to Phrase (SPh), Phrase to Word (Ph-W) and Word to Sense (W-Se). For text pairs on P-S level and S-Ph level, we consider them as sentences and extract heterogeneous types of similarity features, i.e., string features, knowledge based features, corpus based features, syntactic features, machine translation based features, multi-level text features, etc. For text pairs on Ph-W level and W-Se level, due to lack of information, most of these features are not applicable or available. To overcome this problem, we propose several information enrichment methods using WordNet synonym and definition. Our systems rank the 2nd out of 18 teams both on Pearson correlation (official rank) and Spearman rank correlation. Specifically, our systems take the second place on P-S level, S-Ph level and Ph-W level and the 4th place on W-Se level in terms of Pearson correlation.
Health of Children Classified as Underweight by CDC Reference but Normal by WHO Standard

OBJECTIVE: To ascertain measures of health status among 6- to 24-month-old children classified as below normal weight-for-age (underweight) by the Centers for Disease Control and Prevention (CDC) 2000 growth reference but as normal weight-for-age by the World Health Organization (WHO) 2006 standard. METHODS: Data were gathered from children and primary caregivers at emergency departments and primary care clinics in 7 US cities. Outcome measures included caregiver rating of child health, parental evaluation of developmental status, history of hospitalizations, and admission to hospital at the time of visit. Children were classified as (1) not underweight by either CDC 2000 or WHO 2006 criteria, (2) underweight by CDC 2000 but not by WHO 2006 criteria, or (3) underweight by both criteria. Associations between these categories and health outcome measures were assessed by using multiple logistic regression analysis. RESULTS: Data were available for 18 420 children. For each health outcome measure, children classified as underweight by CDC 2000 but normal by WHO 2006 had higher adjusted odds ratios (aORs) of adverse health outcomes than children not classified as underweight by either; children classified as underweight by both had the highest aORs of adverse outcomes. For example, compared with children not underweight by either criteria, the aORs for fair/poor health rating were 2.54 (95% confidence interval: 2.20–2.93) among children underweight by CDC but not WHO and 3.76 (3.13–4.51) among children underweight by both. CONCLUSIONS: Children who are reclassified from underweight to normal weight in changing from CDC 2000 to WHO 2006 growth charts may still be affected by morbidities associated with underweight.
Learning, Negotiating, and Surviving in Child Welfare: Social Capitalization Among Recently Hired Workers

ABSTRACT In the child welfare workplace, accessible relationships and support, although understudied, are vital to worker success. Using telephone interviews with a statewide sample of recently hired, frontline workers (N = 38), this study applied a social capital framework to consider support functionality or capitalization. Findings highlight that, although nearly all workers recognized the importance of instrumental and expressive support, many workers did not capitalize on support. Agencies may benefit from an atmosphere focused on collective interests rather than individual survival. Policy can promote supportive atmospheres through providing agencies with the ability and time to foster recently hired workers’ skills.
Pure agnosia for mirror stimuli after right inferior parietal lesion.

This study reports the experimental investigation of G.R. , a patient suffering from a highly specific disorder in discriminating mirror stimuli following a right temporoparietal cerebrovascular accident. G.R. showed intact perceptual, attentional, mnestic, linguistic and executive abilities. Object recognition was accurate even under unusual viewing conditions. He was highly accurate in defining the canonical orientation of common objects and in discriminating misoriented objects among identical distracters. However, he was severely impaired in tasks requiring mirror-stimulus discrimination, a deficit that persisted even when the object's coordinates were systematically misaligned with respect to his body. The disorder was also dependent upon the frame of reference (allocentric versus egocentric) activated on the basis of task demands. These results demonstrate the existence of a highly specific disorder in discriminating mirror stimuli defined in object-based coordinates, suggesting a failure in processing the directionality of an object's intrinsic x-axis.
Professional Career Opportunities for Rural College Students—An Empirical Analysis Based on the Chinese General Social Survey

Abstract Rural college students are an important, integral part of the current urban labor force. This article uses a group comparison perspective to study the professional career opportunities and their impacting factors of rural college students and other related groups. Analysis of 2010 Chinese General Social Survey data shows the following: (1) college students who transfer from agricultural to nonagricultural status and urban college students have the same opportunities to enter party and government organs and state-owned enterprises, have the same opportunities to obtain elite professional status, and have about the same economic incomes; (2) even if they have received college degrees, if they have not achieved the transition from agricultural to nonagricultural status, rural household registration status will decrease the professional career opportunities of rural college students, and their work unit status, professional status, and income levels will be lower than those of urban college students; (3) in non–college student groups, transitioning from agricultural to nonagricultural status will also increase the aforementioned professional career opportunities for the urban labor force with rural backgrounds. The article presents views on six social groups in the current urban labor force, and through empirical analysis lays out the nature and extent of the impact of household registration status and higher education on professional career opportunities.
A study on repetitiveness of code completion operations

In current software development, code completion is necessary to enhance productivity of our programming tasks. However, how developers use code completion tools on integrated development environments is still not elucidated completely. Aiming to improve such tools, we performed an investigation in terms of code completion use. We investigated developers' operation histories on an integrated development environment and found that code completion operations inserting the same text tend to be repetitively performed in a short time period. We also propose new code completion strategies to reduce such repetitive code completion.
Introduction to the Special Issue on Child Welfare Literature Reviews: Literature Reviews, Systematic Reviews and Meta-Analyses—How Can Child Welfare Administrators, Practitioners and Researchers Determine What We Know?

Just over a decade ago, the Journal of Public Child Welfare (JPCW) was established to fulfill the need for a forum for publication of research directly related to publicly funded child welfare. Founding Editors Drs. Katharine Briar Lawson, and Martin Feit recognized that although existing scholarly journals were publishing child welfare-related work, the emerging volume of research in this area necessitated a focused publication to serve as a resource to the field. Under the leadership of Editor Emeritus, Dr. Alberta Ellett, the journal has worked to serve in this capacity, publishing a wide range of research to inform child welfare policy and practice. Over many years we have seen repeated calls for the use of research evidence in child welfare policy and practice (Lindsey & Shlonsky, 2008; Testa & Poertner, 2010), while simultaneously acknowledging that the evidence base in this field was early in development compared with other fields (Barth, 2008; Usher & Wildfire, 2003). Concurrently, the evidence-based practice movement has progressed, beginning in medicine (Sackett, Richardson, Rosenberg, & Haynes, 1997), and later promoted in social work (Gibbs, 2003; Gibbs & Gambrill, 2002). In 2008, Barth warned,
Practical experiment of balancing for a hopping humanoid biped against various disturbances

This paper discusses balancing for a hopping humanoid biped against various disturbances. Contrary to other studies, the present work focuses on the practical experiment with a real humanoid biped, HUBO2. Also, hopping is focused on among various types of locomotion since hopping is simple movement but more dynamic rather than walking. Two control strategies are proposed according to the magnitude of the disturbances. The one is the posture balance control for small disturbance, which uses the ankle torque of the stance leg. The other is to use the posture balancing control and the landing position control together for large disturbance. The landing position controller changes the landing position of the swing foot to maintain stability. The closed form solution of the landing position controller is addressed with the simplified model. As this simplification, both controllers are used together since the landing position controller cannot maintain a perfect balance alone. To this end, practical experiments with HUBO2 are conducted. In the experiments, HUBO2 maintains a balance against not only small disturbance but also large disturbance such as pushing through the proposed control strategies.
Sexual orientation and health: comparisons in the women's health initiative sample.

CONTEXT Little is known about older lesbian and bisexual women. Existing research rarely compares characteristics of these women with comparable heterosexual women. OBJECTIVE To compare heterosexual and nonheterosexual women 50 to 79 years on specific demographic characteristics, psychosocial risk factors, screening practices, and other health-related behaviors associated with increased risk for developing particular diseases or disease outcomes. DESIGN Analysis of data from 93,311 participants in the Women's Health Initiative (WHI) study of health in postmenopausal women, comparing characteristics of 5 groups: heterosexuals, bisexuals, lifetime lesbians, adult lesbians, and those who never had sex as an adult. SETTING Subjects were recruited at 40 WHI study centers nationwide representing a range of geographic and ethnic diversity. PARTICIPANTS Postmenopausal women aged 50 to 79 years who met WHI eligibility criteria, signed an informed consent to participate in the WHI clinical trial(s) or observational study, and responded to the baseline questions on sexual orientation. MAIN OUTCOME MEASURES Demographic characteristics, psychosocial risk factors, recency of screening tests, and other health-related behaviors as assessed on the WHI baseline questionnaire. RESULTS Although of higher socioeconomic status than the heterosexuals, the lesbian and bisexual women more often used alcohol and cigarettes, exhibited other risk factors for reproductive cancers and cardiovascular disease, and scored lower on measures of mental health and social support. Notable is the 35% of lesbians and 81% of bisexual women who have been pregnant. Women reporting that they never had sex as an adult had lower rates of Papanicolaou screening and hormone replacement therapy use than other groups. CONCLUSIONS This sample of older lesbian and bisexual women from WHI shows many of the same health behaviors, demographic, and psychosocial risk factors reported in the literature for their younger counterparts, despite their higher socioeconomic status and access to health care. The lower rates of recommended screening services and higher prevalence of obesity, smoking, alcohol use, and lower intake of fruit and vegetables among these women compared with heterosexual women indicate unmet needs that require effective interactions between care providers and nonheterosexual women.
Turning maneuvers and mediolateral reaction forces in a quadruped robot

In this paper we address the turning maneuver technique for a quadruped robot with only the hip pitch and the knee pitch for each leg, and explore characteristics of the mediolateral reaction forces experienced by the robot legs during the stance phase. We propose a turning strategy based on the translation of the hip-knee joint space towards the deepest flexion point. Such a translation can cause the robot body inclination in the roll plane, and consequently, result in the changes of the mediolateral reaction forces. In particular, we investigate the mediolateral reaction forces during straight walking and turning. Simulation results reveal that the lateral and medial reaction forces during turning differ strongly from those during straight walking in terms of the frequency used and peak force magnitude. That is, the dominance of the lateral or medial reaction forces in frequency and magnitude contributes forces and torques requisite for the turning maneuver.
Implementation Approach for Network Coding using External Devices in IP Multicast

Network coding is a novel technique to improve network throughput and performance by efficient encoding over the intermediate nodes in the network and works particularly well in multicasting. We expect that network coding will reduce the bandwidth utilization of IP broadcasting services that provide multichannel services and high quality videos using IP multicast. However, it is difficult to apply network coding to commercial networks because the routers actually used have no coding functions. In this paper, we propose a scheme that achieves network coding for IP multicast. It works by attaching external devices to routers instead of replacing them with network coding routers and can be applied to gigabit network by avoiding packet transmission excluding the target multicast.
INTELLIGENT ANALYSIS OF MANUFACTURING DATA

The article discusses the data analysis conducted for a company of the glass industry. The first part of the paper introduces the examined production process and presents the descriptive statistics used to analyze the manufacturing data. The dataset was collected from measuring points in the process of quality control of products in a given period. In the second part, another dataset is presented. This data was used as a training set for artificial neural networks. Finally, the paper describes the results of research on the possible use of the neural networks for the automatic classification of defects in finished products.
A Novel Maximum Entropy Markov Model for Human Facial Expression Recognition

Research in video based FER systems has exploded in the past decade. However, most of the previous methods work well when they are trained and tested on the same dataset. Illumination settings, image resolution, camera angle, and physical characteristics of the people differ from one dataset to another. Considering a single dataset keeps the variance, which results from differences, to a minimum. Having a robust FER system, which can work across several datasets, is thus highly desirable. The aim of this work is to design, implement, and validate such a system using different datasets. In this regard, the major contribution is made at the recognition module which uses the maximum entropy Markov model (MEMM) for expression recognition. In this model, the states of the human expressions are modeled as the states of an MEMM, by considering the video-sensor observations as the observations of MEMM. A modified Viterbi is utilized to generate the most probable expression state sequence based on such observations. Lastly, an algorithm is designed which predicts the expression state from the generated state sequence. Performance is compared against several existing state-of-the-art FER systems on six publicly available datasets. A weighted average accuracy of 97% is achieved across all datasets.
Myeloid Hematopoietic Progenitor Cells Oncoprotein Causes Polyploidy and Cell Death in FDC-P 1 Forced Expression of the Interferon Regulatory Factor 2 Updated

The IFN regulatory factor-2 (IRF-2) oncoprotein controls the cell cycledependent expression of histone H4 genes during S phase and may function as a component of an E2F-independent mechanism to regulate cell growth. To investigate the role of IRF-2 in control of cell proliferation, we have constructed a stable FDC-P1 cell line (F2) in which expression of IRF-2 is doxycycline (DOX)-inducible, and a control cell line (F0). Both the F2 and F0 cell lines were synchronized in the G1 phase by isoleucine deprivation, and IRF-2 was induced by DOX on release of cells from the cell cycle block. Flow cytometric analyses indicated that forced expression of IRF-2 has limited effects on cell cycle progression before the first mitosis. However, continued cell growth in the presence of elevated IRF-2 levels results in polyploidy (>4n) or genomic disintegration (<2n) and cell death. Western blot analyses revealed that the levels of the cell cycle regulatory proteins cyclin B1 and the cyclin-dependent kinase (CDK)inhibitory protein p27 are selectively increased. These changes occur concomitant with a significant elevation in the levels of the FAS-L protein, which is the ligand of the FAS (Apo1/CD95) receptor. We also found a subtle change in the ratio of the apoptosis-promoting Bax protein and the antiapoptotic Bcl-2 protein. Hence, IRF-2 induces a cell death response involving the Fas/FasL apoptotic pathway in FDC-P1 cells. Our data suggest that the IRF-2 oncoprotein regulates a critical cell cycle checkpoint that controls progression through G2 and mitosis in FDC-P1 hematopoietic progenitor cells.