nils-herrmann/clean_scirepeval huggingface dataset:
Craving Facebook? Behavioral addiction to online social networking and its association with emotion regulation deficits.

To assess disordered online social networking use via modified diagnostic criteria for substance dependence, and to examine its association with difficulties with emotion regulation and substance use.



Cross-sectional survey study targeting undergraduate students. Associations between disordered online social networking use, internet addiction, deficits in emotion regulation and alcohol use problems were examined using univariate and multivariate analyses of covariance.



A large University in the Northeastern United States.



Undergraduate students (n = 253, 62.8% female, 60.9% white, age mean = 19.68, standard deviation = 2.85), largely representative of the target population. The response rate was 100%.



Disordered online social networking use, determined via modified measures of alcohol abuse and dependence, including DSM-IV-TR diagnostic criteria for alcohol dependence, the Penn Alcohol Craving Scale and the Cut-down, Annoyed, Guilt, Eye-opener (CAGE) screen, along with the Young Internet Addiction Test, Alcohol Use Disorders Identification Test, Acceptance and Action Questionnaire-II, White Bear Suppression Inventory and Difficulties in Emotion Regulation Scale.



Disordered online social networking use was present in 9.7% [n = 23; 95% confidence interval (5.9, 13.4)] of the sample surveyed, and significantly and positively associated with scores on the Young Internet Addiction Test (P < 0.001), greater difficulties with emotion regulation (P = 0.003) and problem drinking (P = 0.03).



The use of online social networking sites is potentially addictive. Modified measures of substance abuse and dependence are suitable in assessing disordered online social networking use. Disordered online social networking use seems to arise as part of a cluster of symptoms of poor emotion regulation skills and heightened susceptibility to both substance and non-substance addiction.
Mining spatio-temporal information on microblogging streams using a density-based online clustering method

0957-4174/$ see front matter 2012  E-mail address: leechung@mail.ee.kuas.edu.tw Social networks have been regarded as a timely and cost-effective source of spatio-temporal information for many fields of application. However, while some research groups have successfully developed topic detection methods from the text streams for a while, and even some popular microblogging services such as Twitter did provide information of top trending topics for selection, it is still unable to fully support users for picking up all of the real-time event topics with a comprehensive spatio-temporal viewpoint to satisfy their information needs. This paper aims to investigate how microblogging social networks (i.e. Twitter) can be used as a reliable information source of emerging events by extracting their spatio-temporal features from the messages to enhance event awareness. In this work, we applied a density-based online clustering method for mining microblogging text streams, in order to obtain temporal and geospatial features of real-world events. By analyzing the events detected by our system, the temporal and spatial impacts of the emerging events can be estimated, for achieving the goals of situational awareness and risk management.
EMPress: Practical Hand Gesture Classification with Wrist-Mounted EMG and Pressure Sensing

Practical wearable gesture tracking requires that sensors align with existing ergonomic device forms. We show that combining EMG and pressure data sensed only at the wrist can support accurate classification of hand gestures. A pilot study with unintended EMG electrode pressure variability led to exploration of the approach in greater depth. The EMPress technique senses both finger movements and rotations around the wrist and forearm, covering a wide range of gestures, with an overall 10-fold cross validation classification accuracy of 96%. We show that EMG is especially suited to sensing finger movements, that pressure is suited to sensing wrist and forearm rotations, and their combination is significantly more accurate for a range of gestures than either technique alone. The technique is well suited to existing wearable device forms such as smart watches that are already mounted on the wrist.
Bone Ingrowth to Ti Fibre Knit Block with High Deformability

The objective of this study is to develop a Ti fibre knit block without sintering, and to evaluate its deformability and new bone formation in vivo.



A Ti fibre with a diameter of 150 μm was knitted to fabricate a Ti mesh tube. The mesh tube was compressed in a metal mould to fabricate porous Ti fibre knit blocks with three different porosities of 88%, 69%, and 50%. The elastic modulus and deformability were evaluated using a compression test. The knit block was implanted into bone defects of a rabbit's hind limb, and new bone formation was evaluated using micro computed tomography (micro-CT) analysis and histological analysis.



The knit blocks with 88% porosity showed excellent deformability, indicating potential appropriateness for bone defect filling. Although the porosities of the knit block were different, they indicated similar elastic modulus smaller than 1 GPa. The elastic modulus after deformation increased linearly as the applied compression stress increased. The micro-CT analysis indicated that in the block with 50% porosity new bone filled nearly all of the pore volume four weeks after implantation. In contrast, in the block with 88% porosity, new bone filled less than half of the pore volume even 12 weeks after implantation. The histological analysis also indicated new bone formation in the block.



The titanium fibre knit block with high porosity is potentially appropriate for bone defect filling, indicating good bone ingrowth after porosity reduction with applied compression.
Smart Icing Systems for Aircraft Icing Safety

1 Professor and Head, Department of Aeronautical and Astronautical Engineering, Associate Fellow AIAA. 2 Professor, Department of Electrical and Computer Engineering and the Coordinated Science Laboratory. 3 Associate Professor, Department of Aeronautical and Astronautical Engineering, Senior Member AIAA. 4 Associate Professor, Dept. of Aero. and Astro. Eng. and the Coordinated Science Lab., Member AIAA. 5 Graduate Research Assistant, Dept. of Elec. and Comp. Eng. and the Coordinated Science Laboratory. 6 Assistant Professor, Industrial and Systems Engineering, The Ohio State University.
Speech compression and decompression using DWT and DCT

speech compression is the digital signal which is compressed by using various techniques for transmission. This paper explains a transform methodology for compression of the speech signal. In this paper speech is compressed by discrete wavelet transform technique afterward compressed signal is again compressed by discrete cosine transform afterward compressed signal is decompressed by discrete wavelet transform. The performance of speech signal is measure on the basis of peak signal to noise ratio (PSNR) and mean square error (MSE) by using different filters of wavelet family.  DCT, DWT, SPEECH COMPRESSION AND DECOMPRESSION
RULE -BASED SENTIMENT ANALYSIS OF UKRAINIAN REVIEWS

Last decade witnessed a lot of research in the field of sentiment analysis. Understanding the attitude and the emotions that people express in written text proved to be really important and helpful in sociology, political science, psychology, market research, and, of course, artificial intelligence. This paper demonstrates a rule-based approach to clause-level sentiment analysis of reviews in Ukrainian. The general architecture of the implemented sentiment analysis system is presented, the current stage of research is described and further work is explained. The main emphasis is made on the design of rules for computing sentiments.
Unbiased Estimation of the Value of an Optimized Policy

Randomized trials, also known as A/B tests, are used to select between two policies: a control and a treatment. Given a corresponding set of features, we can ideally learn an optimized policy P that maps the A/B test data features to action space and optimizes reward. However, although A/B testing provides an unbiased estimator for the value of deploying B (i.e., switching from policy A to B), direct application of those samples to learn the the optimized policy P generally does not provide an unbiased estimator of the value of P as the samples were observed when constructing P. In situations where the cost and risks associated of deploying a policy are high, such an unbiased estimator is highly desirable. We present a procedure for learning optimized policies and getting unbiased estimates for the value of deploying them. We wrap any policy learning procedure with a bagging process and obtain out-of-bag policy inclusion decisions for each sample. We then prove that inverse-propensity-weighting effect estimator is unbiased when applied to the optimized subset. Likewise, we apply the same idea to obtain out-of-bag unbiased per-sample value estimate of the measurement that is independent of the randomized treatment, and use these estimates to build an unbiased doubly-robust effect estimator. Lastly, we empirically shown that even when the average treatment effect is negative we can find a positive optimized policy.
Design of applying FlexRay-bus to federated archiectecture for triple redundant reliable UAV flight control system

For an Unmanned Aerial Vehicle (UAV) performing a mission, any failure of the flight control system can result in fatal disaster. Therefore, reliability requirement for UAV flight control system becomes increasingly important and then the redundancy technology is considered as a solution to enhance system reliability. This paper studies the designs of reliability, system architecture, and redundancy management logic for UAV flight control system. Therefore, a reliable federated architecture design for triple redundant UAV flight control system is introduced, in which the distributed hardware design combined with centralized software framework was adopted as well. The number of subsystems in the case study is more than that of centralized architecture and less for distributed architecture. Next, the fault detection and fault tolerant design can be achieved, and simultaneously the design problems associated with distributed software framework was reduced. Furthermore, by using the distributed hardware, system's reliability requirement of single hardware module was decreased. Consequently, the goal of high reliability for the entire system reached. Finally, FlexRay bus with time-trigger mechanism was chosen to simulate the communication of such a federated architecture designed. The experimental results show that the design is reasonable and satisfy the high reliability, high performance-price ratio and high expandability requirements of UAV flight control system.
Attendee-Sourcing: Exploring The Design Space of Community-Informed Conference Scheduling

Constructing a good conference schedule for a large multi-track conference needs to take into account the preferences and constraints of organizers, authors, and attendees. Creating a schedule which has fewer conflicts for authors and attendees, and thematically coherent sessions is a challenging task. Cobi introduced an alternative approach to conference scheduling by engaging the community to play an active role in the planning process. The current Cobi pipeline consists of committee-sourcing and author-sourcing to plan a conference schedule. We further explore the design space of communitysourcing by introducing attendee-sourcing – a process that collects input from conference attendees and encodes them as preferences and constraints for creating sessions and schedule. For CHI 2014, a large multitrack conference in human-computer interaction with more than 3,000 attendees and 1,000 authors, we collected attendees’ preferences by making available all the accepted papers at the conference on a paper recommendation tool we built called Confer, for a period of 45 days before announcing the conference program (sessions and schedule). We compare the preferences marked on Confer with the preferences collected from Cobi’s author-sourcing approach. We show that attendee-sourcing can provide insights beyond what can be discovered by authorsourcing. For CHI 2014, the results show value in the method and attendees’ participation. It produces data that provides more alternatives in scheduling and complements data collected from other methods for creating coherent sessions and reducing conflicts.
Multiple algorithms for fraud detection

This paper describes an application of Case-Based Reasonin g to the problem of reducing the number of final-line fraud investigation s i the credit approval process. The performance of a suite of algorithms whi ch are applied in combination to determine a diagnosis from a set of retriev ed cases is reported. An adaptive diagnosis algorithm combining several neighbourhoodbased and probabilistic algorithms was found to have the bes t performance, and these results indicate that an adaptive solution can pro vide fraud filtering and case ordering functions for reducing the number of fin al-li e fraud investigations necessary.
25 Challenges of Semantic Process Modeling

Process modeling has become an essential part of many organizations for documenting, analyzing and redesigning their business operations and to support them with suitable information systems. In order to serve this purpose, it is important for process models to be well grounded in formal and precise semantics. While behavioural semantics of process models are well understood, there is a considerable gap of research into the semantic aspects of their text labels and natural language descriptions. The aim of this paper is to make this research gap more transparent. To this end, we clarify the role of textual content in process models and the challenges that are associated with the interpretation, analysis, and improvement of their natural language parts. More specifically, we discuss particular use cases of semantic process modeling to identify 25 challenges. For each challenge, we identify prior research and discuss directions for addressing them.
Distributed Representations of Geographically Situated Language

We introduce a model for incorporating contextual information (such as geography) in learning vector-space representations of situated language. In contrast to approaches to multimodal representation learning that have used properties of the object being described (such as its color), our model includes information about the subject (i.e., the speaker), allowing us to learn the contours of a word’s meaning that are shaped by the context in which it is uttered. In a quantitative evaluation on the task of judging geographically informed semantic similarity between representations learned from 1.1 billion words of geo-located tweets, our joint model outperforms comparable independent models that learn meaning in isolation.
Leveraging prior ratings for recommender systems in e-commerce

User ratings are the essence of recommender systems in e-commerce. Lack of motivation to provide ratings and eligibility to rate generally only after purchase restrain the effectiveness of such systems and contribute to the well-known data sparsity and cold start problems. This article proposes a new information source for recommender systems, called prior ratings. Prior ratings are based on users’ experiences of virtual products in a mediated environment, and they can be submitted prior to purchase. A conceptual model of prior ratings is proposed, integrating the environmental factor presence whose effects on product evaluation have not been studied previously. A user study conducted in website and virtual store modalities demonstrates the validity of the conceptual model, in that users are more willing and confident to provide prior ratings in virtual environments. A method is proposed to show how to leverage prior ratings in collaborative filtering. Experimental results indicate the effectiveness of prior ratings in improving predictive performance.
MODELING WATER QUALITY USING TERRA / MODIS 500 M SATELLITE IMAGES

A study was conducted in Hong Kong with the aim of deriving algorithms for the retrieval of turbidity, chlorophyII a and suspended solids concentrations from Terra/MODIS 500m level 1B reflectance data. Rigorous atmospheric correction using Radiative Transfer Model coupled with the inputs of AERONET data and MODIS atmospheric products was carried out for deriving the water leaving reflectances. The in-situ measurements were compared with coincident water leaving reflectances using different sets of empirical algorithms. Due to the high variation of water quality in Hong Kong, the in-situ data were divided into three groups based on the spatial locations of the measurements: east zone (similar to case I water), west zone (similar to case II water) and harbour zone (in between case I and case II water). Significant correlations were observed between water-leaving reflectances and in-situ marine data on the three zones while only moderate correlations can be found on those with the entire dataset. These suggest the single empirical algorithm may not be applicable on the areas with high variation of water quality and MODIS 500m data are feasible for water quality retrieval in a local scale.   Man Sing Wong, email: m.wong06@fulbrightweb.org;
Prospects and Challenges in Algal Biotechnology

In this chapter, event-based control approaches for microalgae culture in industrial reactors are evaluated. Those control systems are applied to regulate the microalgae culture growth conditions such as pH and dissolved oxygen concentration. The analyzed event-based control systems deal with sensor and actuator deadbands approaches in order to provide the desired properties of the controller. Additionally, a selective event-based scheme is evaluated for simultaneous control of pH and dissolved oxygen. In such configurations, the event-based approach provides the possibility to adapt the control system actions to the dynamic state of the controlled bioprocess. In such a way, the event-based control algorithm allows to establish a tradeoff between control performance and number of process update actions. This fact can be directly related with reduction of CO2 injection times, what is also reflected in CO2 losses. The application of selective event-based scheme allows the improved biomass productivity, since the controlled variables are kept within the limits for an optimal photosynthesis rate. Moreover, such a control scheme allows effective CO2 utilization and aeration system energy minimization. The analyzed control system configurations are evaluated for both tubular and raceway photobioreactors to proove its viability for different reactor configurations as well as control system objectives. Additionally, control performance indexes have been used to show the efficiency of the event-based control approaches. The obtained results demonA. Pawlowski (✉) ⋅ S. Dormido Department of Computer Science and Automatic Control, UNED, Madrid, Spain e-mail: a.pawlowski@dia.uned.es S. Dormido e-mail: sdormido@dia.uned.es J.L. Guzmán ⋅ M. Berenguel Department of Informatics, University of Almería, ceiA3, CIESOL, Almería, Spain e-mail: joseluis.guzman@ual.es
Deriving a Large-Scale Taxonomy from Wikipedia

We take the category system in Wikipedia as a conceptual network. We label the semantic relations between categories using methods based on connectivity in the network and lexicosyntactic matching. As a result we are able to derive a large scale taxonomy containing a large amount of subsumption, i.e. isa, relations. We evaluate the quality of the created resource by comparing it with ResearchCyc, one of the largest manually annotated ontologies, as well as computing semantic similarity between words in benchmarking datasets.
The aircraft ground routing problem: Analysis of industry punctuality indicators in a sustainable perspective

The ground routing problem consists in scheduling the movements of aircraft on the ground between runways and parking positions while respecting operational and safety requirements in the most efficient way. We present a Mixed Integer Programming (MIP) formulation for routing aircraft along a predetermined path. This formulation is generalized to allow several possible paths. Our model takes into account the classical performance indicators of the literature (the average taxi and completion times) but also the main punctuality indicators of the air traffic industry (the average delay and the on time performance). Then we investigate their relationship through experiments based on real data from Copenhagen airport (CPH). We show that the industry punctuality indicators are in contradiction with the objective of reducing taxi times and therefore pollution emissions. We propose new indicators that are more sustainable, but also more relevant for stakeholders. We also show that the runway is the main bottleneck of CPH airport and that alternate paths cannot improve the performance indicators.
Effects of a mindfulness-based intervention during pregnancy on prenatal stress and mood: results of a pilot study

Stress and negative mood during pregnancy increase risk for poor childbirth outcomes and postnatal mood problems and may interfere with mother–infant attachment and child development. However, relatively little research has focused on the efficacy of psychosocial interventions to reduce stress and negative mood during pregnancy. In this study, we developed and pilot tested an eight-week mindfulness-based intervention directed toward reducing stress and improving mood in pregnancy and early postpartum. We then conducted a small randomized trial (n = 31) comparing women who received the intervention during the last half of their pregnancy to a wait-list control group. Measures of perceived stress, positive and negative affect, depressed and anxious mood, and affect regulation were collected prior to, immediately following, and three months after the intervention (postpartum). Mothers who received the intervention showed significantly reduced anxiety (effect size, 0.89; p < 0.05) and negative affect (effect size, 0.83; p < 0.05) during the third trimester in comparison to those who did not receive the intervention. The brief and nonpharmaceutical nature of this intervention makes it a promising candidate for use during pregnancy.
Parental Control vs. Teen Self-Regulation: Is there a middle ground for mobile online safety?

We conducted a structured, qualitative feature analysis of 75 Android mobile apps designed for the purpose of promoting adolescent online safety. Through this analysis we identified 42 unique features that mapped to a theoretically derived conceptual framework of teen online safety strategies balanced between parental control strategies (through monitoring, restriction, and active mediation) and teen self-regulation strategies (through self-monitoring, impulse control, and risk-coping). We found that the apps strongly favored features that promote parental control through monitoring and restricting teens' online behaviors over teen self-regulation or more communicative and collaborative practices between parents and teens. We use the lens of value sensitive design to discuss the implications of our results and identify opportunities for designing mobile apps for online safety that embed more positive family values.