nils-herrmann/clean_scirepeval huggingface dataset:
Multilingual bottle-neck features and its application for under-resourced languages

In this paper we present our latest investigation on multilingual bottle-neck (BN) features and its application to rapid language adaptation to new languages. We show that the overall performance of a Multilayer Perceptron (MLP) network improves significantly by initializing it with a multilingual MLP. Furthermore, ASR performance increases on both, on those languages which were used for multilingual MLP training, and on a new language. We propose a new strategy called “open target language” MLP to train more flexible models for language adaptation, which is particularly suited for small amounts of training data. The final results on the Vietnamese GlobalPhone database gave 15.8% relative improvement in terms of Syllable Error Rate (SyllER) for the ASR system trained with 22.5h data and 16.9% relative gains for the system trained with only 2h data.
Towards integrated safety analysis and design

There are currently many problems with the development and assessment of software intensive safety-critical systems. In this paper we describe the problems, and introduce a novel approach to their solution, based around goal-structuring concepts, which we believe will ameliorate some of the difficulties. We discuss the use of modified and new forms of safety assessment notations to provide evidence of safety, and the use of data derived from such notations as a means of providing quantified input into the design assessment process. We then show how the design assessment can be partially automated, and from this develop some ideas on how we might move from analytical to synthetic approaches, using safety criteria and evidence as a fitness function for comparing alternative automatically-generated designs.
Android permissions: a perspective combining risks and benefits

The phenomenal growth of the Android platform in the past few years has made it a lucrative target of malicious application (app) developers. There are numerous instances of malware apps that send premium rate SMS messages, track users' private data, or apps that, even if not characterized as malware, conduct questionable actions affecting the user's privacy or costing them money. In this paper, we investigate the feasibility of using both the permissions an app requests, the category of the app, and what permissions are requested by other apps in the same category to better inform users whether the risks of installing an app is commensurate with its expected benefit. Existing approaches consider only the risks of the permissions requested by an app and ignore both the benefits and what permissions are requested by other apps, thus having a limited effect. We propose several risk signals that and evaluate them using two datasets, one consists of 158,062 Android apps from the Android Market, and another consists of 121 malicious apps. We demonstrate the effectiveness of our proposal through extensive data analysis.
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth

When integrating computational tools, such as automatic segmentation, into clinical practice, it is of utmost importance to be able to assess the level of accuracy on new data and, in particular, to detect when an automatic method fails. However, this is difficult to achieve due to the absence of ground truth. Segmentation accuracy on clinical data might be different from what is found through cross validation, because validation data are often used during incremental method development, which can lead to overfitting and unrealistic performance expectations. Before deployment, performance is quantified using different metrics, for which the predicted segmentation is compared with a reference segmentation, often obtained manually by an expert. But little is known about the real performance after deployment when a reference is unavailable. In this paper, we introduce the concept of reverse classification accuracy (RCA) as a framework for predicting the performance of a segmentation method on new data. In RCA, we take the predicted segmentation from a new image to train a reverse classifier, which is evaluated on a set of reference images with available ground truth. The hypothesis is that if the predicted segmentation is of good quality, then the reverse classifier will perform well on at least some of the reference images. We validate our approach on multi-organ segmentation with different classifiers and segmentation methods. Our results indicate that it is indeed possible to predict the quality of individual segmentations, in the absence of ground truth. Thus, RCA is ideal for integration into automatic processing pipelines in clinical routine and as a part of large-scale image analysis studies.
Personality and Psychological Aspects of Cosmetic Surgery

In recent years, cosmetic surgery in Iran, which is provided almost entirely by the private sector, has gained popularity despite evidence of its potential risks. In most cases, cosmetic surgeries are done to increase self-satisfaction and self-esteem, thus seeking cosmetic surgery potentially shows an individual’s psychological profile. Current evidence needs studies on the psychological profile of Asian cosmetic surgery patients. The present study investigates psychological profile and personality traits of people seeking cosmetic surgery in Iran. The present prospective observational study was conducted with a sample of 274 randomly selected persons seeking cosmetic surgery (rhinoplasty, blepharoplasty, face/jaw implant, mammoplasty, and liposuction). All participants completed the validated and reliable the Global Severity Index (GSI)—Symptom Checklist-90-Revised (SCL-90-R)—and the short Neuroticism-Extraversion-Openness Five-Factor Inventory (NEO-FFI). The prevalence rate of psychiatric problems based on the GSI cut-off point (>63) of SCL-90-R was about 51 %, and interpersonal sensitivity and psychosis were the highest and lowest endorsed syndromes among the subjects, respectively. Openness had the lowest mean score; agreeableness and extroversion had the highest mean. The current study shows that understanding and psychological evaluation prior to surgery is necessary and screening can reduce the number of unnecessary surgeries and may enhance satisfaction with surgical results. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
Quantifying the total wetted surface area of the world fleet: a first step in determining the potential extent of ships’ biofouling

Ships’ hulls can transport aquatic nuisance species, but there is little quantitative information about the magnitude of vessel biofouling on a global or regional scale. There does not exist a robust method to estimate the wetted surface area (WSA) of a particular fleet of ships, especially across the diversity of possible vessel types. An estimate of the total WSA of ship arrivals into a port or region is essential to determine the potential scope of biofouling and to inform management strategies to reduce the future invasions. Multiple statistical models were developed so commonly available ships’ parameters could be used to estimate the WSA for a given set of fleet data. Using individual ship characteristics and publicly available data from  ~120,000 active commercial ships in the world fleet, the method results in a total global minimum WSA estimate of approximately 325 × 106 m2. The size of the global fleet employed here is greater than the commonly cited vessel number of approximately 80,000–90,000, as we include ships <100 gross tons. Over 190,000 vessels were initially identified, representing a WSA of 571 × 106 m2, but active status of only 120,000 vessels could be confirmed. Reliable data were unavailable on the operating status of many additional and especially smaller vessels. This approach, along with a contemporary and comprehensive estimate of global WSA, when combined with knowledge of the different operational profiles of ships that may reduce biofouling (port residence times, steaming speeds, extent of antifouling coatings, cleaning frequency, etc.), can inform current numerical models and risk assessments of bioinvasions.
Preliminary experimental study on the sensing performance of a capacitive tactile sensor array mounted on curved surfaces

In real applications, the capacitive tactile sensor array usually needs to be mounted on curved surfaces. To study the effect of curved surfaces on the sensing performance of the sensor array, we have fabricated the sensor array with 4 × 4 sensor units. Four types of rigid and flexible curved surfaces are selected to mount the sensor array, with radius of curvature of +∞, 40 mm, 30 mm, and 20 mm. The initial capacitances of the sensor array increase as the radius of the surfaces decrease. By applying normal and shear forces to the sensor unit mounted on the curved surfaces, we have found that as the radius of the surface decrease, the capacitance increases faster when the sensor is mounted on 40 mm curved surfaces, and increases slower on 30 mm and 20 mm curved surfaces. The shear forces in the x- and y-axes cause symmetric and asymmetric capacitance changes to the sensor unit, respectively. The flexible curved surfaces can induce larger capacitance changes to the sensor unit, compared with the rigid ones.
OPRM1 and EGFR contribute to skin pigmentation differences between Indigenous Americans and Europeans

Contemporary variation in skin pigmentation is the result of hundreds of thousands years of human evolution in new and changing environments. Previous studies have identified several genes involved in skin pigmentation differences among African, Asian, and European populations. However, none have examined skin pigmentation variation among Indigenous American populations, creating a critical gap in our understanding of skin pigmentation variation. This study investigates signatures of selection at 76 pigmentation candidate genes that may contribute to skin pigmentation differences between Indigenous Americans and Europeans. Analysis was performed on two samples of Indigenous Americans genotyped on genome-wide SNP arrays. Using four tests for natural selection—locus-specific branch length (LSBL), ratio of heterozygosities (lnRH), Tajima’s D difference, and extended haplotype homozygosity (EHH)—we identified 14 selection-nominated candidate genes (SNCGs). SNPs in each of the SNCGs were tested for association with skin pigmentation in 515 admixed Indigenous American and European individuals from regions of the Americas with high ground-level ultraviolet radiation. In addition to SLC24A5 and SLC45A2, genes previously associated with European/non-European differences in skin pigmentation, OPRM1 and EGFR were associated with variation in skin pigmentation in New World populations for the first time.
Variational Recurrent Auto-Encoders

In this paper we propose a model that combines the strengths of RNNs and SGVB: the Variational Recurrent Auto-Encoder (VRAE). Such a model can be used for efficient, large scale unsupervised learning on time series data, mapping the time series data to a latent vector representation. The model is generative, such that data can be generated from samples of the latent space. An important contribution of this work is that the model can make use of unlabeled data in order to facilitate supervised training of RNNs by initialising the weights and network state.
Visualizing Change over Time Using Dynamic Hierarchies: TreeVersity2 and the StemView

To analyze data such as the US Federal Budget or characteristics of the student population of a University it is common to look for changes over time. This task can be made easier and more fruitful if the analysis is performed by grouping by attributes, such as by Agencies, Bureaus and Accounts for the Budget, or Ethnicity, Gender and Major in a University. We present TreeVersity2, a web based interactive data visualization tool that allows users to analyze change in datasets by creating dynamic hierarchies based on the data attributes. TreeVersity2 introduces a novel space filling visualization (StemView) to represent change in trees at multiple levels - not just at the leaf level. With this visualization users can explore absolute and relative changes, created and removed nodes, and each node's actual values, while maintaining the context of the tree. In addition, TreeVersity2 provides overviews of change over the entire time period, and a reporting tool that lists outliers in textual form, which helps users identify the major changes in the data without having to manually setup filters. We validated TreeVersity2 with 12 case studies with organizations as diverse as the National Cancer Institute, Federal Drug Administration, Department of Transportation, Office of the Bursar of the University of Maryland, or eBay. Our case studies demonstrated that TreeVersity2 is flexible enough to be used in different domains and provide useful insights for the data owners. A TreeVersity2 demo can be found at https://treeversity.cattlab.umd.edu.
A voxel-based octree construction approach for procedural cave generation

Procedural content generation is becoming an increasingly popular research area as a means of algorithmically generating scene content for virtual environments. The automated generation of such content avoids the manual labour typically associated with creating scene content, and is extremely useful in application areas such as computer graphics, movie production and video games. While virtual 3D caves are commonly featured in these virtual environment applications, procedural cave generation is not an area that has received much attention among researchers to date. This paper presents a procedural approach to generating 3D cave structures. Other than the development of a method to effectively automate the generation of visually believable 3D cave models, this paper also investigates how to efficiently construct and store this spatial information using a voxel-based octree data structure. In addition, the proposed approach demonstrates that caves with different characteristics can be generated by adjusting certain parameters in order to facilitate the creation of diverse cave structures.
Adoption of Mobile Internet Services: An Exploratory Study of Mobile Commerce Early Adopters

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Record linkage software in the public domain: a comparison of Link Plus, The Link King, and a 'basic' deterministic algorithm

The study objective was to compare the accuracy of a deterministic record linkage algorithm and two public domain software applications for record linkage (The Link King and Link Plus). The three algorithms were used to unduplicate an administrative database containing personal identifiers for over 500,000 clients. Subsequently, a random sample of linked records was submitted to four research staff for blinded clerical review. Using reviewers' decisions as the 'gold standard', sensitivity and positive predictive values (PPVs) were estimated. Optimally, sensitivity and PPVs in the mid 90s could be obtained from both The Link King and Link Plus. Sensitivity and PPVs using a basic deterministic algorithm were 79 and 98 per cent respectively. Thus the full feature set of The Link King makes it an attractive option for SAS users. Link Plus is a good choice for non-SAS users as long as necessary programming resources are available for processing record pairs identified by Link Plus.
Dilemmas in a General Theory of Planning *

The search for scientific bases for confronting problems of social policy is bound to fail, because of the nature of these problems. They are "wicked" problems, whereas science has developed to deal with "tame" problems. Policy problems cannot be definitively described. Moreover, in a pluralistic society there is nothing like the undisputable public good; there is no objective definition of equity; policies that respond to social problems cannot be meaningfully correct or false; and it makes no sense to talk about "optinaal solutions" to social probIems unless severe qualifications are imposed first. Even worse, there are no "solutions" in the sense of definitive and objective answers. George Bernard Shaw diagnosed the case several years ago; in more recent times popular protest may have already become a social movement . Shaw averred that "every profession is a conspiracy against the laity." The contemporary publics are responding as though they have made the same discovery. Few o f the modern professionals seem to be immune f rom the popular a t t a c k whether they be social workers, educators, housers, public health officials, policemen, city planners, highway engineers or physicians. Our restive clients have been telling us that they don ' t like the educational programs that schoolmen have been offering, the redevelopment projects urban renewal agencies have been proposing, the lawenforcement styles o f the police, the administrative behavior o f the welfare agencies, the locations o f the highways, and so on. In the courts, the streets, and the political campaigns, we've been hearing ever-louder public protests against the professions' diagnoses o f the clients' problems, against professionally designed governmental programs, against professionally certified standards for the public services. It does seem odd that this attack should be coming just when professionals in * This is a modification of a paper presented to the Panel on Policy Sciences, American Association for the Advancement of Science, Boston, December 1969.
Context-Aware Movie Recommendations: An Empirical Comparison of Pre-filtering, Post-filtering and Contextual Modeling Approaches

Context-aware recommender systems have been proven to improve the performance of recommendations in a wide array of domains and applications. Despite individual improvements, little work has been done on comparing different approaches, in order to determine which of them outperform the others, and under what circumstances. In this paper we address this issue by conducting an empirical comparison of several pre-filtering, post-filtering and contextual modeling approaches on the movie recommendation domain. To acquire confident contextual information, we performed a user study where participants were asked to rate movies, stating the time and social companion with which they preferred to watch the rated movies. The results of our evaluation show that there is neither a clear superior contextualization approach nor an always best contextual signal, and that achieved improvements depend on the recommendation algorithm used together with each contextualization approach. Nonetheless, we conclude with a number of cues and advices about which particular combinations of contextualization approaches and recommendation algorithms could be better suited for the movie recommendation domain.
Topic Model for Identifying Suicidal Ideation in Chinese Microblog

Suicide is one of major public health problems worldwide. Traditionally, suicidal ideation is assessed by surveys or interviews, which lacks of a real-time assessment of personal mental state. Online social networks, with large amount of user-generated data, offer opportunities to gain insights of suicide assessment and prevention. In this paper, we explore potentiality to identify and monitor suicide expressed in microblog on social networks. First, we identify users who have committed suicide and collect millions of microblogs from social networks. Second, we build suicide psychological lexicon by psychological standards and word embedding technique. Third, by leveraging both language styles and online behaviors, we employ Topic Model and other machine learning algorithms to identify suicidal ideation. Our approach achieves the best results on topic-500, yielding F1 − measure of 80.0%, Precision of 87.1%, Recall of 73.9%, and Accuracy of 93.2%. Furthermore, a prototype system for monitoring suicidal ideation on several social networks is deployed.
Biometric authentication on a mobile device: a study of user effort, error and task disruption

We examine three biometric authentication modalities -- voice, face and gesture -- as well as password entry, on a mobile device, to explore the relative demands on user time, effort, error and task disruption. Our laboratory study provided observations of user actions, strategies, and reactions to the authentication methods. Face and voice biometrics conditions were faster than password entry. Speaking a PIN was the fastest for biometric sample entry, but short-term memory recall was better in the face verification condition. None of the authentication conditions were considered very usable. In conditions that combined two biometric entry methods, the time to acquire the biometric samples was shorter than if acquired separately but they were very unpopular and had high memory task error rates. These quantitative results demonstrate cognitive and motor differences between biometric authentication modalities, and inform policy decisions in selecting authentication methods.
Real-Time Ray Tracing with CUDA

The graphics processors (GPUs) have recently emerged as a low-cost alternative for parallel programming. Since modern GPUs have great computational power as well as high memory bandwidth, running ray tracing on them has been an active field of research in computer graphics in recent years. Furthermore, the introduction of CUDA, a novel GPGPU architecture, has removed several limitations that the traditional GPU-based ray tracing suffered. In this paper, an implementation of high performance CUDA ray tracing is demonstrated. We focus on the performance and show how our design choices in various optimization lead to an implementation that outperforms the previous works. For reasonably complex scenes with simple shading, our implementation achieves the performance of 30 to 43 million traced rays per second. Our implementation also includes the effects of recursive specular reflection and refraction, which were less discussed in previous GPU-based ray tracing works.