nils-herrmann/clean_scirepeval huggingface dataset:
Neighbor predictive adaptive handoff algorithm for improving mobility management in VANETs
Venue: Comput. Networks
Year: 2019

A vehicular ad hoc network (VANET) was employed in commercial, road safety, and entertainment applications due to its accessibility. Applications and services were shared with the service providers (SP) over mobile nodes to any destination without special infrastructure. The mobility pattern of the nodes was independent, and the acceleration remained unpredictable, which led to service failures and information drop outs. Resuming communication requires the flooding of additional control messages, which exploits the network resource in a shorter period. This paper introduces the neighbor predictive adaptive handoff (NPAH) algorithm for ensuring seamless communication, regardless of the application service time. NPAH discovers weak communication links in the service, which persist through the least resource dependent distance based neighbor discovery. The selected neighbors are characterized by distance and minimum cost exploitation using the Q learning technique. The process of learning decides the handoff of a vehicle based on storage utilization and cost factors. The results demonstrated the effectiveness of the NPAH algorithm by achieving less packet loss, shorter outage times, and improving the delivery factor.
Impacts of domestic load and electric vehicles on domestic consumption in UK
Venue: 2016 51st International Universities Power Engineering Conference (UPEC)
Year: 2016

This paper highlights domestic consumption of electricity in UK and effect of electric vehicles on the domestic demands. Also, consider the trends and growth of domestic electricity demand and the implication of using the electric vehicles. One challenging factor is the management of the domestic load electricity demand on the electric vehicles. To this end, this paper investigates new management technology technique that can be used in domestic sector. The key point to tackle this problem is to outline pattern shape of the electricity usage per individual household. However, lack of information on individual usage per consumer is complicating the path to the new solutions. Data were collected from daily energy consumption and energy peak demands from UK electricity industries. In additional the research explores the effect of recently introduced UK energy plan to reduce the CO2 emission and how this affects usage of the electric vehicle. The proposal in the new solutions includes the use of renewable energy sources such as solar panels and batteries banks for domestic supply. This would go a long way to reducing electricity demand as well as reduce CO2 emission from domestic sector.
Student perceptions of distance learning strategies during COVID 19
Venue: Journal of dental education
Year: 2020

In March 2020, the COVID 19 pandemic necessitated the immediate closure of in person dental education to comply with social regulations. Dental schools faced the challenge of effectively engaging students over virtual learning platforms.1,2 Historically, there have been 2 approaches to distance learning: synchronous and asynchronous. Synchronous learning involves students learning together in live environments like lectures, which allows greater engagement and sense of community at the cost of scheduling and technological issues. Conversely, asynchronous learning allows students to learn material on their own and discuss it together in forums like emails or discussion boards, which provides time for material synthesis at the cost of community engagement.3,4 Initially, theHarvard School of DentalMedicine decided to continue virtual learning via a synchronous, live lecture format. However, students perceived their dental education worsening with the transition to virtual learning, with increased burnout and decreased retention and engagement in course material.
Contact isn't enough: attitudes towards and misunderstandings about undocumented immigrants among a diverse college population
Venue: Ethnic and Racial Studies
Year: 2019

Ample evidence exists of bipartisan positive attitudes towards undocumented immigrants receiving a path to citizenship, and of a lack of US residents' knowledge about undocumented immigration, but it is not yet clear whether individuals in the same sampling frame may exhibit both favourable attitudes towards and ignorance about undocumented immigrants. We used open and closed ended survey questions (N 231) to probe perceptions of immigrants and knowledge about US immigration procedures in a cohort of demographically and ideologically diverse college students. Our findings confirmed largely favourable attitudes towards undocumented immigrants, but also misconceptions about undocumented immigrants' rights and options with respect to citizenship. That this lack of understanding exists even in a diverse population with direct contact with undocumented immigrants suggests that such ignorance is pervasive, and not only likely to occur in areas where few undocumented immigrants live or where a conservative political climate creates a culture of exclusion.
Study on the Diversification Trend and Countermeasures of Juvenile Crime
Year: 2010

stability and the economic construction. Based on the survey and research of above problem, the characters, forms, causes, and countermeasures of juvenile crime are discussed in detail in this article. The research result of this article is hoped to mobilize the power of the whole society to participate in the comprehensive treatment of juvenile crime, even minor crime, prevent and reduce the juvenile crime, maintain the stability of the society, protect young people's legal rights and interests, and promote their healthy growth.
Perception of User Criteria in the Context of Sustainability of Modern Methods of Construction Based on Wood
Year: 2018

Recent developments in the construction industry have brought more efficient and sustainable technologies, technological procedures, and materials. An example of this are modern methods of construction, which offer larger production volumes with a higher quality and shorter procurement time. The goal of those methods is to improve construction sustainability through quality improvement, customer satisfaction, shortened construction time, and reduced environmental impact. The main goal of this research is to demonstrate, by means of theoretical assumptions, surveys, and analyses, the sustainability of modern methods of construction based on wood. The work focuses on identifying the user criteria for construction sustainability. Selected user criteria of construction sustainability are applied in a socio economic survey whose purpose is to determine how users perceive the efficiency of selected construction systems. We evaluate certain user parameters in the context of sustainability by relying on the users of buildings (family houses) which have already been built and compare the results with declared design parameters.
Evaluation of the long term effect of biochar on properties of temperate agricultural soil at pre industrial charcoal kiln sites in Wallonia, Belgium
Year: 2017

Research on biochar has increased, but its long term effect on the fertility of temperate agricultural soil remains unclear. In Wallonia, Belgium, pre industrial charcoal production affected former forested areas that were cleared for cultivation in the nineteenth century. The sites of traditional charcoal kilns, largely enriched in charcoal residues, are similar to soil amended with hardwood biochar more than 150 years ago. We sampled 17 charcoal kiln sites to characterize their effect on soil properties compared with adjacent reference soils. Charcoal C content was estimated by differential scanning calorimetry. The kiln soil contains from 1.8 to 33.1 g kg 1 of charcoal C, which markedly increases organic C:N and C:P ratios. It also contains slightly more uncharred soil organic carbon (SOC) than the reference soil, which accords with larger total N content. We measured a small increase in nitrates in the kiln soil that might relate to greater mineralization and nitrification of organic N. Frequent application of lime raised the pH to values close to neutral, which offset the residual effect of charcoal production on soil acidity. A cation exchange capacity (CEC) of 414 cmolc kg 1 was estimated for charcoal C, whereas that of uncharred SOC was 213 cmolc kg 1. Despite the large CEC of the kiln soil, exchangeable K+ content was no different from the adjacent soil, whereas exchangeable Ca2+ and Mg2+ contents were considerably larger. Charcoal enrichment has little effect on available, inorganic and total P, but it can form strong complexes with Cu, which reduces the availability of the metal. Biochar is very persistent in soil; therefore, long term implications should not be overlooked. Highlights Charcoal kiln soil contains from 1.8 to 33.1 g kg 1 of charcoal C, which raises C:N and C:P ratios. Charcoal C content was estimated by differential scanning calorimetry. We estimated a CEC of 414 cmolc kg 1 for charcoal C and 213 cmolc kg 1 for uncharred SOC. Retention of exchangeable K+ remained unaffected by charcoal but that of Ca2+ and Mg2+ increased.
Antisymmetric boundary condition for small disturbance CFD
Venue: Journal of Fluids and Structures
Year: 2019

The class of small disturbance CFD methods, also referred to as linearized CFD methods, is an efficient and accurate means for the prediction of unsteady aerodynamics. Small disturbance CFD methods are successfully used for the computation of generalized aerodynamic forces that can be directly utilized in aeroelastic analyses. Although small disturbance CFD does not achieve the performance of established linear potential theory based methods in terms of computational efficiency and memory requirements, it provides superior fidelity for transonic flows and geometrically complex configurations. To further improve the applicability towards industrial investigations, a novel boundary condition for small disturbance CFD is introduced, which allows to exploit the properties of antisymmetry in the case of antisymmetric modal deflections. Thus, by means of the novel antisymmetric boundary condition all simulation cases without sideslip angle can be treated with a half model of the configuration. The approach reduces both the required memory and the computational effort for small disturbance CFD based simulations by a factor of approximately two. The antisymmetric boundary condition is successfully validated based on the AGARD 445.6 wing and the Common Research Model.
Inter Cluster Thread to Core Mapping and DVFS on Heterogeneous Multi Cores
Venue: IEEE Transactions on Multi Scale Computing Systems
Year: 2018

Heterogeneous multi core platforms that contain different types of cores, organized as clusters, are emerging, e.g. ARM's big.LITTLE architecture. These platforms often need to deal with multiple applications, having different performance requirements, executing concurrently. This leads to the generation of varying and mixed workloads (e.g. compute and memory intensive) due to resource sharing. Run time management is required for adapting to such performance requirements and workload variabilities and to achieve energy efficiency. Moreover, the management becomes challenging when the applications are multi threaded and the heterogeneity needs to be exploited. The existing run time management approaches do not efficiently exploit cores situated in different clusters simultaneously (referred to as inter cluster exploitation) and DVFS potential of cores, which is the aim of this paper. Such exploitation might help to satisfy the performance requirement while achieving energy savings at the same time. Therefore, in this paper, we propose a run time management approach that first selects thread to core mapping based on the performance requirements and resource availability. Then, it applies online adaptation by adjusting the voltage frequency (V f) levels to achieve energy optimization, without trading off application performance. For thread to core mapping, offline profiled results are used, which contain performance and energy characteristics of applications when executed on the heterogeneous platform by using different types of cores in various possible combinations. For an application, thread to core mapping process defines the number of used cores and their type, which are situated in different clusters. The online adaptation process classifies the inherent workload characteristics of concurrently executing applications, incurring a lower overhead than existing learning based approaches as demonstrated in this paper. The classification of workload is performed using the metric Memory Reads Per Instruction (MRPI) The adaptation process pro actively selects an appropriate V f pair for a predicted workload. Subsequently, it monitors the workload prediction error and performance loss, quantified by instructions per second (IPS) and adjusts the chosen V f to compensate. We validate the proposed run time management approach on a hardware platform, the Odroid XU3, with various combinations of multi threaded applications from PARSEC and SPLASH benchmarks. Results show an average improvement in energy efficiency up to 33 percent compared to existing approaches while meeting the performance requirements.
Age differences in loneliness from late adolescence to oldest old age.
Venue: Developmental psychology
Year: 2016

Contrary to common stereotypes, loneliness is not restricted to old age but can occur at any life stage. In this study, we used data from a large, nationally representative German study (N 16,132) to describe and explain age differences in loneliness from late adolescence to oldest old age. The age distribution of loneliness followed a complex nonlinear trajectory, with elevated loneliness levels among young adults and among the oldest old. The late life increase in loneliness could be explained by lower income levels, higher prevalence of functional limitations, and higher proportion of singles in this age group. Consistent with an age normative perspective, the association of income, relationship status, household size, and work status with loneliness differed between different age groups. In contrast, indicators of the quantity of social relationships (social engagement, number of friends, contact frequency) were universally associated with loneliness regardless of age. Overall, these findings show that sources of loneliness in older adults are well understood. Future research should focus on understanding the specific sources of loneliness in middle aged adults.
Understanding the barriers and facilitators to safe infant sleep for mothers of preterm infants
Venue: Journal of Perinatology
Year: 2020

To identify barriers and facilitators to adherence to safe sleep practices (SSP) among mothers of preterm infants using qualitative methodology. We conducted 23 in depth interviews in English or Spanish with mothers of preterm infants who were recently discharged from four hospitals, utilizing a grounded theory approach and framework of the Theory of Planned Behavior (attitudes, perceived control, social norms) For attitudes, mothers' fear about their infants' vulnerable preterm state related to suffocation, apnea of prematurity, and reflux influenced infant sleep practices. For social norms, education received in the NICU and advice from other health care providers, family, friends, and media impacted their choices. For perceived control, mothers adapted infant sleep practices to meet their own needs and address the perceived safety and comfort of infants. Factors identified that influence maternal decision making about infant sleep practices can inform interventions to address sudden unexpected infant death reduction in preterm infants.
Logistic Analytic Hierarchy Process based Gymnastics Development Influence on Human Physical and Psychological Health
Year: 2016

Gymnastics as a kind of sports leisure event, it not only is able to relief fatigue, build up one's body, but also is helpful for strengthening physique. However, no matter athletes that go in for gymnastics, or civil that regard gymnastics as a kind of leisure event, all the number of people significant change. The paper by Logistic regression analysis, in horizontal view of gymnastics athlete's numbers changes, utilizes obtained data to make exact analysis, and further vertically makes comparative study with total number of athletes, and then analyzes recent years' Chinese gymnastics development trend. Utilize analytic hierarchy process to study gymnastics influence on human psychological health, by analyzing gymnastics and chemical medicines curative effects on depressive disorder, anxiety disorder, phobia and obsessive compulsive disorder these main mental illnesses, it makes quantitative analysis of gymnastics important impacts on human psychological health treatment. It gets conclusion: Chinese gymnastics development is relative slower; gymnasts' numbers are little, especially for international level gymnasts and sports masters. In order to better propel to gymnastics development, give its impacts on human psychological health into play, it should positive encourage teenager and broad civil to take gymnastics exercises, expand gymnastics impacts among public, let gymnastics to develop towards stronger orientations and better serve to public.
A weighted rough set based method developed for class imbalance learning
Venue: Inf. Sci.
Year: 2008

In this paper, we introduce weights into Pawlak rough set model to balance the class distribution of a data set and develop a weighted rough set based method to deal with the class imbalance problem. In order to develop the weighted rough set based method, we design first a weighted attribute reduction algorithm by introducing and extending Guiasu weighted entropy to measure the significance of an attribute, then a weighted rule extraction algorithm by introducing a weighted heuristic strategy into LEM2 algorithm, and finally a weighted decision algorithm by introducing several weighted factors to evaluate extracted rules. Furthermore, in order to estimate the performance of the developed method, we compare the weighted rough set based method with several popular methods used for class imbalance learning by conducting experiments with twenty UCI data sets. Comparative studies indicate that in terms of AUC and minority class accuracy, the weighted rough set based method is better than the re sampling and filtering based methods, and is comparable to the decision tree and SVM based methods. It is therefore concluded that the weighted rough set based method is effective for class imbalance learning.
A Deep Learning Approach to Automatic Caption Generation for News Images
Year: 2019

Automatic caption generation of images has gained significant interest. It gives rise to a lot of interesting image related applications. For example, it could help in image/video retrieval and management of vast amount of multimedia data available on the Internet. It could also help in development of tools that can aid visually impaired individuals in accessing multimedia content. In this paper, we particularly focus on news images and propose a methodology for automatically generating captions for news paper articles consisting of a text paragraph and an image. We propose several deep neural network architectures built upon Recurrent Neural Networks. Results on a BBC News dataset show that our proposed approach outperforms a traditional method based on Latent Dirichlet Allocation using both automatic evaluation based on BLEU scores and human evaluation.
Opioid Crisis: No Easy Fix to Its Social and Economic Determinants.
Venue: American journal of public health
Year: 2018

The accepted wisdom about the US overdose crisis singles out prescribing as the causative vector. Although drug supply is a key factor, we posit that the crisis is fundamentally fueled by economic and social upheaval, its etiology closely linked to the role of opioids as a refuge from physical and psychological trauma, concentrated disadvantage, isolation, and hopelessness. Overreliance on opioid medications is emblematic of a health care system that incentivizes quick, simplistic answers to complex physical and mental health needs. In an analogous way, simplistic measures to cut access to opioids offer illusory solutions to this multidimensional societal challenge. We trace the crisis' trajectory through the intertwined use of opioid analgesics, heroin, and fentanyl analogs, and we urge engaging the structural determinants lens to address this formidable public health emergency. A broad focus on suffering should guide both patient and community level interventions.
Layered shape grammars
Venue: Comput. Aided Des.
Year: 2014

In this article we propose a computer aided conceptual design system to assist modelling at the early stages of design. More precisely, we address the problem of providing the designer with design alternatives that can be used as starting points of the design process. To guide the generation of such alternatives according to a given set of design requirements, the designer can express both visual knowledge in the form of basic geometric transformation rules, and also logic constraints that guide the modelling process. Our approach is based on the formalism of shape grammars, and supplements the basic algorithms with procedures that integrate logic design constraints and goals. Additionally, we introduce a layered scheme for shape grammars that can greatly reduce the computational cost of shape generation. Shape grammars, constraints, goals and layers can be handled through a graphic environment. We illustrate the functionalities of ShaDe through two use cases taken from the architectural design and video games domains, and also evaluate the performance of the system.
Interfaces to Scripting Languages in Visual Analytics Applications
Year: 2020

The need to use data visualization and visual analysis in various fields has led to the development of featurerich standalone applications such as Tableau and MS Power BI. These applications provide ready to use functionality for loading, analyzing and visualizing data, even for users who are not familiar with programming and scripting. Meanwhile, data scientists have to combine many different tools and techniques in their daily work, since no standalone application can yet cover the entire workflow. As a result, a rich landscape of open source libraries is available today, covering various tasks from data analysis to modeling and visualization. To combine the best of two worlds, interfaces for scripting languages have been integrated into standalone applications in recent years. We analyzed which interfaces to six common scripting languages are offered. The interfaces offer different levels of integration and therefore support different steps of the data science workflow. In this paper we investigated the integration levels of script languages in standalone applications and divided them into four groups. We used this classification to evaluate 13 standalone visual analysis applications currently available on the market. We then analyzed which groups of applications best support which steps in the data science workflow. We found that a tight integration of scripting languages can especially support the explorative analysis and modeling phase of the data science workflow. We also discuss our results in the light of visual analysis research and give suggestions for future research directions.