nils-herrmann/clean_scirepeval huggingface dataset:
Articulated body deformation from range scan data

This paper presents an example-based method for calculating skeleton-driven body deformations. Our example data consists of range scans of a human body in a variety of poses. Using markers captured during range scanning, we construct a kinematic skeleton and identify the pose of each scan. We then construct a mutually consistent parameterization of all the scans using a posable subdivision surface template. The detail deformations are represented as displacements from this surface, and holes are filled smoothly within the displacement maps. Finally, we combine the range scans using k-nearest neighbor interpolation in pose space. We demonstrate results for a human upper body with controllable pose, kinematics, and underlying surface shape.
Low-transition-temperature mixtures (LTTMs): a new generation of designer solvents.

A new generation of designer solvents emerged in the last decade as promising green media for multiple applications, including separation processes: the low-transition-temperature mixtures (LTTMs). They can be prepared by mixing natural high-melting-point starting materials, which form a liquid by hydrogen-bond interactions. Among them, deep-eutectic solvents (DESs) were presented as promising alternatives to conventional ionic liquids (ILs). Some limitations of ILs are overcome by LTTMs, which are cheap and easy to prepare from natural and readily available starting materials, biodegradable, and renewable.
Block Truncation Coding-based Audio Compression Technique

There have been an increasing utilization and consumption of audio files in various applications across different desktop and mobile devices. Thus, audio data compression has been beneficial in reducing the bandwidth and disk space requirements of such data. Block Truncation Coding (BTC), a well-known data compression technique for digital images, was used as the underlying algorithm in encoding audio data. A new encoding technique for audio data was proposed with the following components: (1) quadtree for audio block segmentation, (2) AMBTC for computation of representative values, and (3) Huffman Coding for lossless data representation. The performance of the proposed encoding technique was benchmarked and measured using Peak Signal-to-Noise Ratio (PSNR) and compression rate.
Constrained Model Predictive Control Implementation for a Heavy-Duty Gas Turbine Power Plant

In this paper, model predictive control (MPC) strategy is implemented to a GE9001E gas turbine power plant. A linear model is developed for the gas turbine using conventional mathematical models and ARX identification procedure. Also a process control model is identified for system outputs prediction. The controller is designed in order to adjust the exhaust gas temperature and the rotor speed by compressor inlet guide vane (IGV) position and fuel signals. The proposed system is simulated under load demand disturbances. It is shown that MPC controller can maintain the rotor speed and exhaust gas temperature more accurately in comprehension with both SpeedTronicTM control system and conventional PID control.  Gas turbine, Identification, ARX, Predictive control, Power plant, Modeling, Multivariable control, PID
MSP-IMPROV: An Acted Corpus of Dyadic Interactions to Study Emotion Perception

We present the MSP-IMPROV corpus, a multimodal emotional database, where the goal is to have control over lexical content and emotion while also promoting naturalness in the recordings. Studies on emotion perception often require stimuli with fixed lexical content, but that convey different emotions. These stimuli can also serve as an instrument to understand how emotion modulates speech at the phoneme level, in a manner that controls for coarticulation. Such audiovisual data are not easily available from natural recordings. A common solution is to record actors reading sentences that portray different emotions, which may not produce natural behaviors. We propose an alternative approach in which we define hypothetical scenarios for each sentence that are carefully designed to elicit a particular emotion. Two actors improvise these emotion-specific situations, leading them to utter contextualized, non-read renditions of sentences that have fixed lexical content and convey different emotions. We describe the context in which this corpus was recorded, the key features of the corpus, the areas in which this corpus can be useful, and the emotional content of the recordings. The paper also provides the performance for speech and facial emotion classifiers. The analysis brings novel classification evaluations where we study the performance in terms of inter-evaluator agreement and naturalness perception, leveraging the large size of the audiovisual database.
Serotonin, serotonin receptors and their actions in insects

Serotonin is an ancient monoamine neurotransmitter, biochemically derived from tryptophan. It is most abundant in the gastrointestinal tract, but is also present throughout the rest of the body of animals and can even be found in plants and fungi. Serotonin is especially famous for its contributions to feelings of well-being and happiness. More specifically it is involved in learning and memory processes and is hence crucial for certain behaviors throughout the animal kingdom. This brief review will focus on the metabolism, biological role and mode-of-action of serotonin in insects. First, some general aspects of biosynthesis and break-down of serotonin in insects will be discussed, followed by an overview of the functions of serotonin, serotonin receptors and their pharmacology. Throughout this review comparisons are made with the vertebrate serotonergic system. Last but not least, possible applications of pharmacological adjustments of serotonin signaling in insects are discussed.
Hardware Implementation for the Echo Canceller System based Subband Technique using TMS320C6713 DSP Kit

The acoustic echo cancellation system is very important in the communication applications that are used these days; in view of this importance we have implemented this system practically by using DSP TMS320C6713 Starter Kit (DSK). The acoustic echo cancellation system was implemented based on 8 subbands techniques using Least Mean Square (LMS) algorithm and Normalized Least Mean Square (NLMS) algorithm. The system was evaluated by measuring the performance according to Echo Return Loss Enhancement (ERLE) factor and Mean Square Error (MSE) factor. Acoustic echo canceller; Least Mean Square (LMS); Normalized Least Mean Square (NLMS); TMS320C6713; 8 subbands adaptive filter
Typed Lua: An Optional Type System for Lua

Dynamically typed languages trade flexibility and ease of use for safety, while statically typed languages prioritize the early detection of bugs, and provide a better framework for structure large programs. The idea of optional typing is to combine the two approaches in the same language: the programmer can begin development with dynamic types, and migrate to static types as the program matures. The challenge is designing a type system that feels natural to the programmer that is used to programming in a dynamic language.
 This paper presents the initial design of Typed Lua, an optionally-typed extension of the Lua scripting language. Lua is an imperative scripting language with first class functions and lightweight metaprogramming mechanisms. The design of Typed Lua's type system has a novel combination of features that preserves some of the idioms that Lua programmers are used to, while bringing static type safety to them. We show how the major features of the type system type these idioms with some examples, and discuss some of the design issues we faced.
Accompanying Depression with FINE - A Smartphone-Based Approach

Major depression is the most prevalent mental disorder and one of the main reasons for disability. To be successful in treating depression, it is necessary to have early identification and intervention. Therefore, it is important to design more objective and more efficient depression screening techniques. Such interventions provided by mobile apps shows promise due to their capabilities to support people in their everyday lives. Until very recently, the design of mental health apps that works effectively in the context of diagnostics had not been widely explored. For this reason, we have investigated potentially significant depression-correlated parameters derived from self reports, smartphone usage pattern and sensor data to specify our concept. Following the results of the requirement analysis, we developed the Android app 'Fine'. A feasibility check with a specific target audience has shown that the app can record most of the selected parameters reliably. It has also shown that the overall concept has been accepted positively with the target audience. Further work is planned to improve the functionalities and to adapt specific needs for depression attendance.
Data mining and machine learning in computational creativity

Creative machines are an old idea, but only recently has computational creativity established itself as a research field with its own identity and research agenda. The goal of computational creativity research is to model, simulate or enhance creativity using computational methods. Data mining and machine learning can be used in a number of ways to help computers learn how to be creative, such as learning to generate new artefacts or to evaluate various qualities of newly generated arfefacts. In this review paper we give an overview of research in computational creativity with a focus on the roles that data mining and machine learning have had and could have in creative systems.
Anonymization of Set-Valued Data via Top-Down, Local Generalization

Set-valued data, in which a set of values are associated with an individual, is common in databases ranging from market basket data, to medical databases of patients’ symptoms and behaviors, to query engine search logs. Anonymizing this data is important if we are to reconcile the conflicting demands arising from the desire to release the data for study and the desire to protect the privacy of individuals represented in the data. Unfortunately, the bulk of existing anonymization techniques, which were developed for scenarios in which each individual is associated with only one sensitive value, are not well-suited for set-valued data. In this paper we propose a top-down, partition-based approach to anonymizing set-valued data that scales linearly with the input size and scores well on an information-loss data quality metric. We further note that our technique can be applied to anonymize the infamous AOL query logs, and discuss the merits and challenges in anonymizing query logs using our approach.
Convolutional Simplex Projection Network for Weakly Supervised Semantic Segmentation

Weakly supervised semantic segmentation has been a subject of increased interest due to the scarcity of fully annotated images. We introduce a new approach for solving weakly supervised semantic segmentation with deep Convolutional Neural Networks (CNNs). The method introduces a novel layer which applies simplex projection on the output of a neural network using area constraints of class objects. The proposed method is general and can be seamlessly integrated into any CNN architecture. Moreover, the projection layer allows strongly supervised models to be adapted to weakly supervised models effortlessly by substituting ground truth labels. Our experiments have shown that applying such an operation on the output of a CNN improves the accuracy of semantic segmentation in a weakly supervised setting with image-level labels.
Understanding Web Archiving Services and Their (Mis)Use on Social Media

Either by ensuring the continuing availability of information, or by deliberately caching content that might get deleted or removed, Web archiving services play an increasingly important role in today’s information ecosystem. Among these, the Wayback Machine has been proactively archiving, since 2001, versions of a large number of Web pages, while newer services like archive.is allow users to create on-demand snapshots of specific Web pages, which serve as time capsules that can be shared across the Web. In this paper, we present a large-scale analysis of Web archiving services and their use on social media, aiming to shed light on the actors involved in this ecosystem, the content that gets archived, and how it is shared. To this end, we crawl and study: 1) 21M URLs, spanning almost two years, from archive.is; and 2) 356K archive.is plus 391K Wayback Machine URLs that were shared on four social networks: Reddit, Twitter, Gab, and 4chan’s Politically Incorrect board (/pol/) over 14 months. We observe that news and social media posts are the most common types of content archived, likely due to their perceived ephemeral and/or controversial nature. Moreover, URLs of archiving services are extensively shared on “fringe” communities within Reddit and 4chan to preserve possibly contentious content. Lastly, we find evidence of moderators nudging or even forcing users to use archives, instead of direct links, for news sources with opposing ideologies, potentially depriving them of ad revenue.
A max-norm constrained minimization approach to 1-bit matrix completion

We consider in this paper the problem of noisy 1-bit matrix completion under a general non-uniform sampling distribution using the max-norm as a convex relaxation for the rank. A max-norm constrained maximum likelihood estimate is introduced and studied. The rate of convergence for the estimate is obtained. Information-theoretical methods are used to establish a minimax lower bound under the general sampling model. The minimax upper and lower bounds together yield the optimal rate of convergence for the Frobenius norm loss. Computational algorithms and numerical performance are also discussed.
Interaction of physical activity, mental health, health locus of control and quality of life : a study on university students in Pakistan

Bazila Akbar Kahn, 2013. Interaction of Physical Activity, Mental Health, Health Locus of Control and Quality of Life: A Study on University Students in Pakistan. Department of Sport Sciences. University of Jyväskylä. Master’s Thesis of Sport and Exercise Psychology. 66 pages Physical activity involvement is considered as beneficial both for physiological and psychological health. In Pakistani society an elevated level of physical inactivity has been identified lately. Nevertheless, studies examining the association between physical activity and psychological health are limited to the young population of university students in Pakistan. University students are considered to be at a risk stage due to academic stress and physiological changes Therefore, the purpose of this study was to explore the associations between physical activity, quality of life and psychological health related variables to university students in Pakistan. Participants (N=378) of the current study were from seven universities in Pakistan (265 female, 112 males). General Health Questionnaire, SF-36 quality of life matrix, multidimensional health locus of control and international physical activity questionnaire were administered. Results reveal a large number of students as physically inactive (37.6%). t-Test revealed male students were more active and having a better quality of life in comparison to the female. The high prevalence of psychological distress (25%) has also been identified by using correlation. Results indicated a linear positive relationship of physical activity with mental component summary and a negative association with psychological distress. Conversely, psychological distress was negatively related overall health related quality of life and PA. Results also demonstrated that students with a better internal locus of control were discovered to be more physically active. Findings were discussed in comparison with studies from other countries e.g. US, UK, Norway, Poland, Turkey and Australia However, the results suggest the replication of the study with a larger sample size. Additionally, it is also imperative to explore the barriers to PA among the student population in Pakistan.  Physical activity, mental health, health locus of control, psychological distress, university students in Pakistan.
Scalable network traffic visualization using compressed graphs

The visualization of complex network traffic involving a large number of communication devices is a common yet challenging task. Traditional layout methods create the network graph with overwhelming visual clutter, which hinders the network understanding and traffic analysis tasks. The existing graph simplification algorithms (e.g. community-based clustering) can effectively reduce the visual complexity, but lead to less meaningful traffic representations. In this paper, we introduce a new method to the traffic monitoring and anomaly analysis of large networks, namely Structural Equivalence Grouping (SEG). Based on the intrinsic nature of the computer network traffic, SEG condenses the graph by more than 20 times while preserving the critical connectivity information. Computationally, SEG has a linear time complexity and supports undirected, directed and weighted traffic graphs up to a million nodes. We have built a Network Security and Anomaly Visualization (NSAV) tool based on SEG and conducted case studies in several real-world scenarios to show the effectiveness of our technique.
The Right to Be Forgotten: Towards Machine Learning on Perturbed Knowledge Bases

Today’s increasingly complex information infrastructures represent the basis of any data-driven industries which are rapidly becoming the 21st century’s economic backbone. The sensitivity of those infrastructures to disturbances in their knowledge bases is therefore of crucial interest for companies, organizations, customers and regulating bodies. This holds true with respect to the direct provisioning of such information in crucial applications like clinical settings or the energy industry, but also when considering additional insights, predictions and personalized services that are enabled by the automatic processing of those data. In the light of new EU Data Protection regulations applying from 2018 onwards which give customers the right to have their data deleted on request, information processing bodies will have to react to these changing jurisdictional (and therefore economic) conditions. Their choices include a re-design of their data infrastructure as well as preventive actions like anonymization of databases per default. Therefore, insights into the effects of perturbed/anonymized knowledge bases on the quality of machine learning results are a crucial basis for successfully facing those future challenges. In this paper we introduce a series of experiments we conducted on applying four different classifiers to an established dataset, as well as several distorted versions of it and present our initial results.
Sucking and swallowing in infants and diagnostic tools

Preterm infants often have difficulties in learning how to suckle from the breast or how to drink from a bottle. As yet, it is unclear whether this is part of their prematurity or whether it is caused by neurological problems. Is it possible to decide on the basis of how an infant learns to suckle or drink whether it needs help and if so, what kind of help? In addition, can any predictions be made regarding the relationship between these difficulties and later neurodevelopmental outcome? We searched the literature for recent insights into the development of sucking and the factors that play a role in acquiring this skill. Our aim was to find a diagnostic tool that focuses on the readiness for feeding or that provides guidelines for interventions. At the same time, we searched for studies on the relationship between early sucking behavior and developmental outcome. It appeared that there is a great need for a reliable, user-friendly and noninvasive diagnostic tool to study sucking in preterm and full-term infants.
Helical rim advancement flaps for reconstruction.

Principles of reconstruction dictate a number of critical points for successful repair. To achieve aesthetic and functional goals, the dermatologic surgeon should avoid deviation of anatomical landmarks and free margins, maintain shape and symmetry, and repair with skin of similar characteristics. Reconstruction of the ear presents a number of unique challenges based on the limited amount of adjacent lax tissue within the cosmetic unit and the structure of the auricle, which consists of a relatively thin skin surface and flexible cartilaginous framework.
A Unity-Gain Buffer with Reduced Offset and Gain Error

A unity-gain buffer has been fabricated in 0.35-mum CMOS technology. The circuit uses feed forward and local feedback in a cascaded source follower circuit as well as two global feedback loops: one to reduce the output resistance, gain error, and offset and a second loop to further reduce gain error. The buffer consumes 3.7 mW at 3.3 V and has a bandwidth of 92 MHz when driving a 13-pF capacitive load
A Markovian Decision Process Analysis of Experienced Agents Joining Ad-Hoc Teams

As the number of agents grows in a multi-agent system, it is very impractical to have a team that is preprogrammed to share a cooperation protocol. In this situation experienced agents that have been trained to cooperate with different teams come in handy. In this paper based on some UAV teams, we investigate the behavior of an experienced agent which we call ad-hoc agent. First, we train the ad-hoc agent to cooperate with different teams and in different environmental situations. This training is based on an approximated version of MDP which is very fast. Then the ad-hoc agent joins the teams and tries to cooperate with them in a Persistent Surveillance Mission(PSM). Our experiment for the ad-hoc agent starts with joining different fixed strategy teams and ends with joining a fully cooperative team. The results of the simulation show that the performance of a team having an ad-hoc agent is even comparable to a team that has completely trained together.
From Cultural Exchange to Transculturation : A Review and Reconceptualization of Cultural Appropriation

Cultural appropriation is often mentioned but undertheorized in critical rhetorical and media studies. Defined as the use of a culture’s symbols, artifacts, genres, rituals, or technologies by members of another culture, cultural appropriation can be placed into 4 categories: exchange, dominance, exploitation, and transculturation. Although each of these types can be understood as relevant to particular contexts or eras, transculturation questions the bounded and proprietary view of culture embedded in other types of appropriation. Transculturation posits culture as a relational phenomenon constituted by acts of appropriation, not an entity that merely participates in appropriation. Tensions exist between the need to challenge essentialism and the use of essentialist notions such as ownership and degradation to criticize the exploitation of colonized cultures.