nils-herrmann/clean_scirepeval huggingface dataset:
Automatic Speech Recognition Based on Neural Networks
Venue: SPECOM

In automatic speech recognition, as in many areas of machine learning, stochastic modeling relies on neural networks more and more. Both in acoustic and language modeling, neural networks today mark the state of the art for large vocabulary continuous speech recognition, providing huge improvements over former approaches that were solely based on Gaussian mixture hidden markov models and count based language models. We give an overview of current activities in neural network based modeling for automatic speech recognition. This includes discussions of network topologies and cell types, training and optimization, choice of input features, adaptation and normalization, multitask training, as well as neural network based language modeling. Despite the clear progress obtained with neural network modeling in speech recognition, a lot is to be done, yet to obtain a consistent and self contained neural network based modeling approach that ties in with the former state of the art. We will conclude by a discussion of open problems as well as potential future directions w.r.t. to neural network integration into automatic speech recognition systems.
Discriminative sparse subspace learning and its application to unsupervised feature selection.
Venue: ISA transactions

In order to efficiently use the intrinsic data information, in this study a Discriminative Sparse Subspace Learning (DSSL) model has been investigated for unsupervised feature selection. First, the feature selection problem is formulated as a subspace learning problem. In order to efficiently learn the discriminative subspace, we investigate the discriminative information in the subspace learning process. Second, a two step TDSSL algorithm and a joint modeling JDSSL algorithm are developed to incorporate the clusters' assignment as the discriminative information. Then, a convergence analysis of these two algorithms is provided. A kernelized discriminative sparse subspace learning (KDSSL) method is proposed to handle the nonlinear subspace learning problem. Finally, extensive experiments are conducted on real world datasets to show the superiority of the proposed approaches over several state of the art approaches.
Let Me Join Your Tactile Attention: A Sign Language Perspective on the Communicative Togetherness with a Child who is Congenitally Deafblind

This article will describe and discuss how tactile language might develop in a child who is congenitally deafblind (cdb) based on a real world enquiry of a five year old boy. This article is based on the RuG Master Thesis LET ME JOIN YOUR ATTENTION (Brede, 2008) It will draw attention to and give examples on how it looks like, when a teacher sees the child's communicative skills and acts to and answer the child's utterances, accepting it as language. Language development in seeing and hearing children normally happens very fast and is usually uncomplicated. The joint attention and perception of a tactile sign language is much more complicated, and the cdb children's natural gestural manner of being in the world can seem complicated to their communication partners. The children with cdb need competent partners, who need knowledge about features in the early processes to support the development. In this article, video capturing and analyses are presented as a research methodology. The results of this study describe ten steps within a period of 16 months where bodily experiences led to a shared meaningful sign. They describe and discuss joint attention in tactile language development. They also present an interesting path for meaning making, leading to linguistic units, which are influenced both by the culture and by the child himself. The results from a single case study of a boy with cdb may be of interest to the community of deafblindness, and to the augmentative and alternative communication community.
Evolutionary and Holistic Assessment of Green Grey Infrastructure for CSO Reduction

Recent research suggests future alterations in rainfall patterns due to climate variability, affecting public safety and health in urban areas. Urban growth, one of the main drivers of change in the current century, will also affect these conditions. Traditional drainage approaches using grey infrastructure offer low adaptation to an uncertain future. New methodologies of stormwater management focus on decentralized approaches in a long term planning framework, including the use of Green Infrastructure (GI) This work presents a novel methodology to select, evaluate, and place different green grey practices (or measures) for retrofitting urban drainage systems. The methodology uses a hydrodynamic model and multi objective optimization to design solutions at a watershed level. The method proposed in this study was applied in a highly urbanized watershed to evaluate the effect of these measures on Combined Sewer Overflows (CSO) quantity. This approach produced promising results and may become a useful tool for planning and decision making of drainage systems.
Optimal installation of multiple DG units using competitive swarm optimizer (CSO) algorithm
Venue: 2016 IEEE Congress on Evolutionary Computation (CEC)

This paper investigates the optimal installation of multiple distributed generation (DG) units in radial distribution network using competitive swarm optimizer (CSO) algorithm. CSO algorithm is basically evolved from PSO algorithm but conceptually it is very different from PSO algorithm. In CSO algorithm, instead of using local best and global best for particle update, a pairwise competition between particles is introduced, so that the particle which fails in the competition will learn from the winner and update its position accordingly. The DG location and sizing problem is solved by the objective of minimizing total real power loss. Results demonstrate the effectiveness of the proposed method in minimizing total real power loss (Pioss) of the system. The dominance of the proposed method is also proved by comparing the simulation results with other optimization techniques.
New routes to CSO sustainability: the strategic shift to social enterprise and social investment

The issue of sustainability is becoming more important for civil society, as non profits, NGOs, and other civil society organisations (CSOs) face a range of political, regulatory, organisational, and financial challenges. This article focuses on the crucial dimension of financial sustainability and the growing awareness of the importance of accessing alternative sources of funds and developing new funding models. These include accessing social investment, using subsidiary businesses to fund programme work, or developing new social enterprises. The article draws on analysis of the funding environment and specific examples to explore the different dimensions of sustainability, and assess why many CSOs are looking to new funding models and alternative routes to sustainability.
Effect of Behavior Modification on Outcome in Early to Moderate Stage Chronic Kidney Disease: A Cluster Randomized Trial
Venue: PloS one

Owing to recent changes in our understanding of the underlying cause of chronic kidney disease (CKD) the importance of lifestyle modification for preventing the progression of kidney dysfunction and complications has become obvious. In addition, effective cooperation between general physicians (GPs) and nephrologists is essential to ensure a better care system for CKD treatment. In this cluster randomized study, we studied the effect of behavior modification on the outcome of early to moderate stage CKD.  Stratified open cluster randomized trial.  A total of 489 GPs belonging to 49 local medical associations (clusters) in Japan.  A total of 2,379 patients (1,195 in group A (standard intervention) and 1,184 in group B (advanced intervention) aged between 40 and 74 years, who had CKD and were under consultation with GPs.  All patients were managed in accordance with the current CKD guidelines. The group B clusters received three additional interventions: patients received both educational intervention for lifestyle modification and a CKD status letter, attempting to prevent their withdrawal from treatment, and the group B GPs received data sheets to facilitate reducing the gap between target and practice.  The primary outcome measures were 1) the non adherence rate of accepting continuous medical follow up of the patients, 2) the collaboration rate between GPs and nephrologists, and 3) the progression of CKD.  The rate of discontinuous clinical visits was significantly lower in group B (16.2% in group A vs. 11.5% in group B, p 0.01) Significantly higher referral and co treatment rates were observed in group B (p<0.01) The average eGFR deterioration rate tended to be lower in group B (group A: 2.6+ 5.8 ml/min/1.73 m2/year, group B: 2.4+ 5.1 ml/min/1.73 m2/year, p 0.07) A significant difference in eGFR deterioration rate was observed in subjects with Stage 3 CKD (group A: 2.4+ 5.9 ml/min/1.73 m2/year, group B: 1.9+ 4.4 ml/min/1.73 m2/year, p 0.03)  Our care system achieved behavior modification of CKD patients, namely, significantly lower discontinuous clinical visits, and behavior modification of both GPs and nephrologists, namely significantly higher referral and co treatment rates, resulting in the retardation of CKD progression, especially in patients with proteinuric Stage 3 CKD.
Evaluation of a student participatory, low intensity program to improve school wellness environment and students' eating and activity behaviors
Venue: International Journal of Behavioral Nutrition and Physical Activity

BackgroundMost schools have not fully implemented wellness policies, and those that have rarely incorporate meaningful student participation. The aim of the Fuel Up to Play 60 (FUTP60) program is to help schools implement wellness policies by engaging students in activities to improve access to healthful, good tasting food and drinks, and increase the number and type of opportunities for students to be physically active. The aim of this paper is to present initial student level results from an implementation of FUTP60 in 72 schools, grades 6 9.MethodsThe study used a non controlled pretest/posttest with serial cross sectional data. School process data and student level data were collected in fall 2009 (pre intervention) and spring 2010 (post intervention) School wellness practices were captured during a baseline needs assessment survey. Validated self administered questionnaires assessing dietary and physical activity (PA) behaviors were administered to students in grades 6 9 in the 72 pilot schools. Mixed effects logistic regression controlling for clustering of schools and demographics was used to calculate odds ratios and confidence intervals to evaluate changes pre and post intervention.ResultsAll 72 schools implemented FUTP60 during the 2009 2010 school year. Action strategies most frequently chosen by the schools included increasing breakfast participation and new activities before and after school. Positive and significant changes in students' behaviors (n 32,482 at pretest and 29,839 at post test) were noted for dairy, whole grains, fruit, and vegetable consumption and PA levels pre and post intervention (OR 1.05 to 1.27) Students aware of the program at post test were significantly more likely to report healthier eating and PA behaviors than students unaware of the program (OR 1.1 to 1.34).ConclusionsFUTP60 pilot findings indicate that a low intensity program focused on wellness policy implementation is associated with small positive changes in student behaviors, especially when students were aware of the program. Although these initial results are promising, a more rigorous controlled study is warranted as a next step.
Wellness Among Dental Students: An Institutional Study.
Venue: Journal of dental education

The high prevalence of distress among health professionals during their education has fostered increased interest in the study of student well being. The aim of this study was to assess the self perceived wellness of dental students and determine the relationship between factors affecting wellness and demographic variables. An online questionnaire was distributed to 334 first through fourth year dental students at one U.S. dental school. The questionnaire consisted of modified versions of the Perceived Wellness Survey, Medical Outcomes Study Social Support Survey, and Mental Health Inventory and also collected demographic information. The response rate was 78% (N=261) More than 80% of the respondents reported that they were happy all, most, or a good bit of the time. These students exhibited a strong sense of self worth, were positive about their friendships, and perceived they had good social support. Less than 20% of respondents did not view their physical health as excellent and identified a lack of self perceived wellness. First year and single students reported statistically less social support. Students who were parents perceived their wellness less favorably. Hispanic and Asian students were less happy regarding their mental health than white and African American students. These findings suggest that students, especially Hispanic and Asian students, may benefit from programs that promote student well being. Academic programs that encourage students to work together and promote peer to peer involvement may be beneficial, especially for first year and single students.
De La Historia A La Accion

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Adipose Tissue Remodeling: Its Role in Energy Metabolism and Metabolic Disorders
Venue: Front. Endocrinol.

The adipose tissue is a central metabolic organ in the regulation of whole body energy homeostasis. The white adipose tissue functions as a key energy reservoir for other organs, whereas the brown adipose tissue accumulates lipids for cold induced adaptive thermogenesis. Adipose tissues secrete various hormones, cytokines, and metabolites (termed as adipokines) that control systemic energy balance by regulating appetitive signals from the central nerve system as well as metabolic activity in peripheral tissues. In response to changes in the nutritional status, the adipose tissue undergoes dynamic remodeling, including quantitative and qualitative alterations in adipose tissue resident cells. A growing body of evidence indicates that adipose tissue remodeling in obesity is closely associated with adipose tissue function. Changes in the number and size of the adipocytes affect the microenvironment of expanded fat tissues, accompanied by alterations in adipokine secretion, adipocyte death, local hypoxia, and fatty acid fluxes. Concurrently, stromal vascular cells in the adipose tissue, including immune cells, are involved in numerous adaptive processes, such as dead adipocyte clearance, adipogenesis, and angiogenesis, all of which are dysregulated in obese adipose tissue remodeling. Chronic overnutrition triggers uncontrolled inflammatory responses, leading to systemic low grade inflammation and metabolic disorders, such as insulin resistance. This review will discuss current mechanistic understandings of adipose tissue remodeling processes in adaptive energy homeostasis and pathological remodeling of adipose tissue in connection with immune response.
Modelling modal gating of ion channels with hierarchical Markov models
Venue: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences

Many ion channels spontaneously switch between different levels of activity. Although this behaviour known as modal gating has been observed for a long time it is currently not well understood. Despite the fact that appropriately representing activity changes is essential for accurately capturing time course data from ion channels, systematic approaches for modelling modal gating are currently not available. In this paper, we develop a modular approach for building such a model in an iterative process. First, stochastic switching between modes and stochastic opening and closing within modes are represented in separate aggregated Markov models. Second, the continuous time hierarchical Markov model, a new modelling framework proposed here, then enables us to combine these components so that in the integrated model both mode switching as well as the kinetics within modes are appropriately represented. A mathematical analysis reveals that the behaviour of the hierarchical Markov model naturally depends on the properties of its components. We also demonstrate how a hierarchical Markov model can be parametrized using experimental data and show that it provides a better representation than a previous model of the same dataset. Because evidence is increasing that modal gating reflects underlying molecular properties of the channel protein, it is likely that biophysical processes are better captured by our new approach than in earlier models.
A bluetooth based sophisticated home automation system using smartphone
Venue: 2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI)

This paper represents a reliable, compact, fast and low cost smart home automation system, based on Arduino (microcontroller) and Android app. Bluetooth chip has been used with Arduino, thus eliminating the use of personal computers (PCs) Various devices such as lights, DC Servomotors have been incorporated in the designed system to demonstrate the feasibility, reliability and quick operation of the proposed smart home system. The entire designed system has been tested and it is seen capable of running successfully and perform the desired operations, such as switching functionalities, position control of Servomotor, speed control of D.C motor and light intensity control (Via Voltage Regulation)
Android Based Home Automation System Using Bluetooth Voice Command

grown at high speed. Also human lives have become much more dependent on electronic devices and appliances. It has thus led to the idea of developing a home automation system. This paper is about home automation system which would use a smartphone to enable any naive user to operate all the appliances. The system has three components: an Arduino microcontroller for connecting the appliances, a Bluetooth module for signal transfer, and a smartphone running the Android application. The system also supports voice command for naive users with command sensing. It decodes the user's voice command and extracts the exact meaning of his command. The paper focuses on the features and design of the proposed system. The design is based on a standalone Arduino BT board and the appliances are connected to this board using relays. The smartphone interacts with the Arduino via Bluetooth. The main aim of the system development is to be low cost and scalable according to the requirements. Password protection is being used for authentication.
Second derivative of high order accuracy methods for the numerical integration of stiff initial value problems

In Mitsui ( 2010) the author introduced a new class of discrete variable methods known as look ahead linear multistep methods (LALMMs) which consist of a pair of predictor corrector (PC) including a function value at one more step beyond the present step for the numerical solution of ordinary differential equations. Two step family of Look Ahead linear multistep methods of fourth order pair were derived and shown to be A(\theta $th) stable in Mitsui and Yakubu ( 2011) The derived integration methods are of low orders and unfortunately cannot cope with stiff systems of ordinary differential equations. In this paper we extend the concept adopted in Mitsui and Yakubu ( 2011) to construct second derivative of high order accuracy methods with off step points which behave essentially like one step methods. The resulting integration methods are A stable, convergent, with large regions of absolute stability, suitable for stiff systems of ordinary differential equations. Numerical comparisons of the new methods have been made and enormous gains in efficiency are achieved.
Construction of Additive Semi Implicit Runge Kutta Methods with Low Storage Requirements
Venue: J. Sci. Comput.

Space discretization of some time dependent partial differential equations gives rise to systems of ordinary differential equations in additive form whose terms have different stiffness properties. In these cases, implicit methods should be used to integrate the stiff terms while efficient explicit methods can be used for the non stiff part of the problem. However, for systems with a large number of equations, memory storage requirement is also an important issue. When the high dimension of the problem compromises the computer memory capacity, it is important to incorporate low memory usage to some other properties of the scheme. In this paper we consider Additive Semi Implicit Runge Kutta (ASIRK) methods, a class of implicit explicit Runge Kutta methods for additive differential systems. We construct two second order 3 stage ASIRK schemes with low storage requirements. Having in mind problems with stiffness parameters, besides accuracy and stability properties, we also impose stiff accuracy conditions. The numerical experiments done show the advantages of the new methods.
Relationship between class attendance and student performance

We investigate the relationship between university students' class attendance and learning performance. We use data from a course in a university in which attendance to classes is not mandatory. The methods used are cluster analysis and regression analysis. We find that students form three distinct groups: 1) those who drop out before the final exam, 2) those who attend classes as well as the exam, and 3) those who study independently and attend the exam. Most importantly, we find that in group 2, attendance is positively and significantly related to performance, after controlling for the effect of other variables potentially related to performance. We also find that students in group 3 are characterized by compelling reasons for absenteeism and a good ability to proactively search for information and study independently. The results are relevant for teachers and students alike. First and foremost, they can be used as a motivator for students to attend classes and for teachers to bear in mind the relevance of class teaching for learning outcomes.
Relationship between Class Attendance and Student Performance

We investigate the relationship between university students' class attendance and learning performance. We use data from a course in a university in which attendance to classes is not mandatory. The methods used are cluster analysis and regression analysis. We find that students form three distinct groups: 1) those who drop out before the final exam, 2) those who attend classes as well as the exam, and 3) those who study independently and attend the exam. Most importantly, we find that in group 2, attendance is positively and significantly related to performance, after controlling for the effect of other variables potentially related to performance. We also find that students in group 3 are characterized by compelling reasons for absenteeism and a good ability to proactively search for information and study independently. The results are relevant for teachers and students alike. First and foremost, they can be used as a motivator for students to attend classes and for teachers to bear in mind the relevance of class teaching for learning outcomes.