nils-herrmann/clean_scirepeval huggingface dataset:
Training Deep Bidirectional LSTM Acoustic Model for LVCSR by a Context Sensitive Chunk BPTT Approach
Venue: IEEE/ACM Transactions on Audio, Speech, and Language Processing

This paper presents a study of using deep bidirectional long short term memory (DBLSTM) recurrent neural network as acoustic model for DBLSTM HMM based large vocabulary continuous speech recognition (LVCSR) where a context sensitive chunk (CSC) back propagation through time (BPTT) approach is used to train DBLSTM by splitting each training sequence into chunks with appended contextual observations, and a CSC based decoding method with possibly overlapped CSCs is used for recognition. Our approach makes mini batch based training on GPU more efficient and reduces the latency of DBLSTM based LVCSR from a whole utterance to a short chunk. Evaluations have been made on Switchboard I benchmark task. In comparison with epoch wise BPTT training, our method can achieve more than three times speedup on a single GPU card without degrading recognition accuracy. In comparison with a highly optimized DNN HMM system trained by a frame level cross entropy (CE) criterion, our CE trained DBLSTM HMM system achieves relative word error rate reductions of 9% and 5% on Eval2000 and RT03S testing sets, respectively. Furthermore, by running model averaging based parallel training of DBLSTM on a cluster of GPUs, CSC BPTT incurs less accuracy degradation than epoch wise BPTT while achieves a linear speedup.
Fast view based 3D model retrieval via unsupervised multiple feature fusion and online projection learning
Venue: Signal Process.

Since each visual feature only reflects a unique characteristic about a 3 dimensional (3D) model and different visual features have diverse discriminative power in model representation, it would be beneficial to fuse multiple visual features in 3D model retrieval. To this end, we propose a fast view based 3D model retrieval framework in this article. This framework comprises two parts: the first one is an Unsupervised Multiple Feature Fusion algorithm (UMFF) which is used to learn a compact yet discriminative feature representation from the original multiple visual features; and the second one is an efficient Online Projection Learning algorithm (OPL) which is designed to fast transfer the input multiple visual features of a newcome model into its corresponding low dimensional feature representation. In this framework, many existing ranking algorithms such as the simple distance based ranking method can be directly adopted for sorting all 3D models in the database using the learned new feature representation and returning the top ranked models to the user. Extensive experiments on two public 3D model databases demonstrate the efficiency and the effectiveness of the proposed approach over its competitors. The proposed framework cannot only dramatically improve the retrieval performance but also reduce the computational cost in dealing with the newcome models. HighlightsAn Unsupervised Multiple Feature Fusion (UMFF) algorithm is proposed to fuse multiple features for 3D model representation.The 1 graph method is used to learn roust and datum adaptive graph to preserve local geometric structure information.An efficient Online Projection Learning (OPL) algorithm is designed to solve the out of sample problem.
Why Does Positive Mental Health Buffer Against Psychopathology? An Exploratory Study on Self Compassion as a Resilience Mechanism and Adaptive Emotion Regulation Strategy
Venue: Cognitive Therapy and Research

Growing evidence suggests that positive mental health or wellbeing protects against psychopathology. How and why those who flourish derive these resilient outcomes is, however, unknown. This exploratory study investigated if self compassion, as it continuously provides a friendly, accepting and situational context for negative experiences, functions as a resilience mechanism and adaptive emotion regulation strategy that protects against psychopathology for those with high levels of positive mental health. Participants from the general population (n 349) provided measures at one time point on positive mental health (MHC SF) self compassion (SCS SF) psychopathology (HADS) and negative affect (mDES) Self compassion significantly mediated the negative relationship between positive mental health and psychopathology. Furthermore, higher levels of self compassion attenuated the relationship between state negative affect and psychopathology. Findings suggest that especially individuals with high levels of positive mental health possess self compassion skills that promote resilience against psychopathology. These might function as an adaptive emotion regulation strategy and protect against the activation of schema related to psychopathology following state negative affective experiences. Enhancing self compassion is a promising positive intervention for clinical practice. It will not only impact psychopathology through reducing factors like rumination and self criticism, but also improve positive mental health by enhancing factors such as kindness and positive emotions. This may reduce the future risk of psychopathology.
Executive Function and Emotion Regulation Strategy Use in Adolescents
Venue: Applied neuropsychology. Child

Development of emotion regulation strategy use involves a transition from reliance on suppression during childhood to greater use of reappraisal in adolescence and adulthood a transition that parallels developmental changes in executive functions. We evaluated the relationship between emotion regulation strategy use and executive functioning in the everyday life of 70 typically developing adolescents who completed the Emotion Regulation Questionnaire for Youth and the Behavior Rating Inventory of Executive Function Self Report. Results indicated that greater reliance on reappraisal was associated with better executive functions, while reliance on suppression was related to poorer executive functions. Findings suggest that adolescents who rely on reappraisal may have more cognitive resources to help them remain attentive and well regulated in their daily lives. On the other hand, if better executive functions facilitate the use of reappraisal, adolescents' ability to regulate their emotions could potentially be enhanced via supports for executive functions.
The impact of malicious nodes positioning on vehicular alert messaging system
Venue: Ad Hoc Networks

ICT components of vehicular and transportation systems have a crucial role in ensuring passengers' safety, particularly in the scenario of vehicular networks. Hence, security concerns should not be overlooked, since a malicious vehicle might inject false information into the intervehicle wireless links, leading to life and money losses. This is even more critical when considering applications specifically aimed at improving people's safety, such as accident warning systems. To assess the scenario of such type of applications in a vehicular network, we have performed a thorough evaluation of accident warning systems under a position cheating attack. As one of the main contributions of this paper, we determine the impact of a different number of malicious vehicles on delaying the alert warning messages. In particular, we study the impact of the position of malicious vehicles on delaying alert messages. We identify the most effective strategies that could be used by malicious vehicles in order to maximize the delay of the alert message, and thus strengthen the impact of the attacker. Finally, we pinpoint that even with a small number of malicious vehicles, the positioning cheating attack can significantly increase the delay of the alert message when compared to a scenario without attack.
Observer based hybrid control algorithm for semi active suspension systems

In order to improve ride comfort and handling performance of the vehicle, an adaptive hybrid control algorithm is proposed for semi active suspension systems. The virtues of sky hook is combined with ground hook control strategies and a more suitable compromise for the suspension systems is chosen. The hybrid coefficient is tuned according to the longitudinal and lateral acceleration so as to improve the vehicle stability especially in high speed conditions. Damping continuous adjustable absorber is used to continuously control the damping force so as to eliminate the damping force jerk instead of traditional on off control policy. Based on suspension stroke measured by sensors, unscented Kalman filter is designed to estimate the suspension states in real time for the realization of hybrid control, which improves the robustness of the control strategy and is adaptive to different types of road profiles. Finally, the proposed control algorithm is validated under the following two typical road profiles: half sine speed bump road and the random road. The simulation results indicate that the hybrid control algorithm could offer a good coordination between ride comfort and handling of the vehicle.
Social and Traditional Mainstream Media of Communication: Synergy and Variance Perspective

Social media are computer mediated tools that allow people to create, share or exchange information, ideas, pictures/videos in implicit communities and networks such as Facebook, Twitter, Baddo, Instagram among others. Whereas Traditional Media refer to those media that communicates identical messages in a one way route to very large mass audiences, which are assumed to be homogeneous. Social media is at variance with Traditional media in production of media content; whereby social media content have now become more generally dispersed throughout the population, rather than restricted to media professionals, and there is more accessibility, quality and interactivity. Social media and the Traditional media share a relationship in advertisement, entertainment and news among others. The study postulates that although social media have come to stay, the traditional media will continue to strive in complimenting the social media.  Social Media, Facebook, Twitter, Traditional Media, Synergy, Variance
Arabic Cross Language Information Retrieval
Venue: ACM Trans. Asian Low Resour. Lang. Inf. Process.

Cross language information retrieval (CLIR) deals with retrieving relevant documents in one language using queries expressed in another language. As CLIR tools rely on translation techniques, they are challenged by the properties of highly derivational and flexional languages like Arabic. Much work has been done on CLIR for different languages including Arabic. In this article, we introduce the reader to the motivations for solving some problems related to Arabic CLIR approaches. The evaluation of these approaches is discussed starting from the 2001 and 2002 TREC Arabic CLIR tracks, which aim to objectively evaluate CLIR systems. We also study many other research works to highlight the unresolved problems or those that require further investigation. These works are discussed in the light of a deep study of the specificities and the tasks of Arabic information retrieval (IR) Particular attention is given to translation techniques and CLIR resources, which are key issues challenging Arabic CLIR. To push research in this field, we discuss how a new standard collection can improve Arabic IR and CLIR tracks.
Extracting translations from comparable corpora for Cross Language Information Retrieval using the language modeling framework
Venue: Inf. Process. Manag.

Proposing a language modeling method to extract translations from comparable corpora.Comparing two similarity functions for deriving bilingual word correlations.Improving translation quality by integrating co occurrence relations into word models.Comparing different estimations of translation probabilities from word correlations.Showing the significant impact of probability estimation methods on CLIR performance. A main challenge in Cross Language Information Retrieval (CLIR) is to estimate a proper translation model from available translation resources, since translation quality directly affects the retrieval performance. Among different translation resources, we focus on obtaining translation models from comparable corpora, because they provide appropriate translations for both languages and domains with limited linguistic resources. In this paper, we employ a two step approach to build an effective translation model from comparable corpora, without requiring any additional linguistic resources, for the CLIR task. In the first step, translations are extracted by deriving correlations between sourcetarget word pairs. These correlations are used to estimate word translation probabilities in the second step. We propose a language modeling approach for the first step, where modeling based on probability distribution provides two key advantages. First, our approach can be tuned easier in comparison with heuristically adjusted previous work. Second, it provides a principled basis for integrating additional lexical and translational relations to improve the accuracy of translations from comparable corpora. As an indication, we integrate monolingual relations of word co occurrences into the process of translation extraction, which helps to extract more reliable translations for low frequency words in a comparable corpus. Experimental results on an EnglishPersian comparable corpus show that our method outperforms the previous approaches in terms of both translation quality and the performance of CLIR. Indeed, the proposed method is naturally applicable to any comparable corpus, regardless of its languages. In addition, we demonstrate the significant impact of word translation probabilities, estimated in the second step of our approach, on the performance of CLIR.
A study of user profile representation for personalized cross language information retrieval
Venue: Aslib J. Inf. Manag.

With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross language information retrieval (CLIR) systems through the means of personalized query expansion.  The user profiles consist of weighted terms computed by using frequency based methods such as tf idf and BM25, as well as various latent semantic models trained on monolingual documents and cross lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods.  Experimental results suggest that latent semantic weighted user profile representation techniques are superior to frequency based methods, and are particularly suita.
Studying the effect and treatment of misspelled queries in Cross Language Information Retrieval
Venue: Inf. Process. Manag.

We study the effects of misspelled queries on the performance of CLIR systems.Word based approaches (as both indexing and translation units) are highly sensitive to the presence of misspellings.The use of correction mechanisms can significantly reduce their negative effects.Classical techniques are suitable for shorter queries while context based corrections are suitable for longer queries.Our approach based on character n grams (as both indexing and translation units) shows remarkable strength. In contrast with their monolingual counterparts, little attention has been paid to the effects that misspelled queries have on the performance of Cross Language Information Retrieval (CLIR) systems. The present work makes a first attempt to fill this gap by extending our previous work on monolingual retrieval in order to study the impact that the progressive addition of misspellings to input queries has, this time, on the output of CLIR systems. Two approaches for dealing with this problem are analyzed in this paper. Firstly, the use of automatic spelling correction techniques for which, in turn, we consider two algorithms: the first one for the correction of isolated words and the second one for a correction based on the linguistic context of the misspelled word. The second approach to be studied is the use of character n grams both as index terms and translation units, seeking to take advantage of their inherent robustness and language independence. All these approaches have been tested on a from Spanish to English CLIR system, that is, Spanish queries on English documents. Real, user generated spelling errors have been used under a methodology that allows us to study the effectiveness of the different approaches to be tested and their behavior when confronted with different error rates. The results obtained show the great sensitiveness of classic word based approaches to misspelled queries, although spelling correction techniques can mitigate such negative effects. On the other hand, the use of character n grams provides great robustness against misspellings.
Using Word Embeddings for Query Translation for Hindi to English Cross Language Information Retrieval
Venue: Computacion y Sistemas

Cross Language Information Retrieval (CLIR) has become an important problem to solve in the recent years due to the growth of content in multiple languages in the Web. One of the standard methods is to use query translation from source to target language. In this paper, we propose an approach based on word embeddings, a method that captures contextual clues for a particular word in the source language and gives those words as translations that occur in a similar context in the target language. Once we obtain the word embeddings of the source and target language pairs, we learn a projection from source to target word embeddings, making use of a dictionary with word translation pairs. We then propose various methods of query translation and aggregation. The advantage of this approach is that it does not require the corpora to be aligned (which is difficult to obtain for resource scarce languages) a dictionary with word translation pairs is enough to train the word vectors for translation. We experiment with Forum for Information Retrieval and Evaluation (FIRE) 2008 and 2012 datasets for Hindi to English CLIR. The proposed word embedding based approach outperforms the basic dictionary based approach by 70% and when the word embeddings are combined with the dictionary, the hybrid approach beats the baseline dictionary based method by 77% It outperforms the English monolingual baseline by 15% when combined with the translations obtained from Google Translate and Dictionary.
Unconditional government social cash transfer in Africa does not increase fertility
Venue: Journal of population economics

Among policymakers, a common perception surrounding the effects of cash transfer programmes, particularly unconditional programmes targeted to families with children, is that they induce increased fertility. We evaluate the Zambian Child Grant Programme, a government unconditional cash transfer targeted to families with a child under the age of 5 and examine impacts on fertility and household composition. The evaluation was a cluster randomized control trial, with data collected over 4 years from 2010 to 2014. Our results indicate that there are no programme impacts on overall fertility. Our results contribute to a small evidence base demonstrating that there are no unintended incentives related to fertility due to cash transfers.
Invasive alien birds in Denmark

Dansk Orn. Foren. Tidsskr. 109 (2015) 193 205  A new European Union Regulation on Invasive Alien Species implemented in January 2015 establishes a framework for actions to combat alien species, which requires Member States to prevent the spread of alien species, provide early warning and rapid responses to their presence and management of established alien species where they occur. We show the importance of mechanisms such as DOF's (Dansk Ornitologisk Forening, BirdLife Denmark) Atlas project, Common Bird Census (breeding and wintering species) and DOFbasen to contribute data on the current geographical and numerical distribution of the few serious alien avian species already present in Denmark. We review the status, abundance and distribution of seven critical IAS that do, or have, occurred in Denmark in the last 10 years and conclude that none of these pose a major threat as things stand at the present, although breeding Egyptian Geese Alopochen aegyptiaca and Canada Geese Branta canadensis potentially give cause for future concern. We underline the need for continued surveillance of all avian IAS through data collection via DOF's monitoring programmes and Aarhus University's mid winter waterbird census, hunting bag and wing surveys. These programmes are essential if we are to continue to effectively monitor the extent and nature of the problems constituted by IAS in support of the Danish Nature Agency in their direct management of alien species problems in this country.
Surgeon design interface for patient specific concentric tube robots
Venue: 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)

Concentric tube robots have potential for use in a wide variety of surgical procedures due to their small size, dexterity, and ability to move in highly curved paths. Unlike most existing clinical robots, the design of these robots can be developed and manufactured on a patient and procedure specific basis. The design of concentric tube robots typically requires significant computation and optimization, and it remains unclear how the surgeon should be involved. We propose to use a virtual reality based design environment for surgeons to easily and intuitively visualize and design a set of concentric tube robots for a specific patient and procedure. In this paper, we describe a novel patient specific design process in the context of the virtual reality interface. We also show a resulting concentric tube robot design, created by a pediatric urologist to access a kidney stone in a pediatric patient.
PTNet: A parameterizable data center network
Venue: 2016 IEEE Wireless Communications and Networking Conference

This paper presents PTNet, a new data center topology that is specifically designed to offer a high and parameterized scalability with just one layer architecture. Furthermore, despite its high scalability, PTNet grants a reduced latency and a high performance in terms of capacity and fault tolerance. Consequently, compared to widely known data center networks, our new topology shows better capacity, robustness, cost effectiveness and less power consumption. Conducted experiments and theoretical analyses illustrate the performance of the novel system.