nils-herrmann/clean_scirepeval huggingface dataset:
Neural correlates of superior intelligence: Stronger recruitment of posterior parietal cortex

General intelligence (g) is a common factor in diverse cognitive abilities and a major influence on life outcomes. Neuroimaging studies in adults suggest that the lateral prefrontal and parietal cortices play a crucial role in related cognitive activities including fluid reasoning, the control of attention, and working memory. Here, we investigated the neural bases for intellectual giftedness (superior-g) in adolescents, using fMRI. The participants consisted of a superior-g group (n = 18, mean RAPM = 33.9 +/- 0.8, >99%) from the national academy for gifted adolescents and the control group (n = 18, mean RAPM = 22.8 +/- 1.6, 60%) from local high schools in Korea (mean age = 16.5 +/- 0.8). fMRI data were acquired while they performed two reasoning tasks with high and low g-loadings. In both groups, the high g-loaded tasks specifically increased regional activity in the bilateral fronto-parietal network including the lateral prefrontal, anterior cingulate, and posterior parietal cortices. However, the regional activations of the superior-g group were significantly stronger than those of the control group, especially in the posterior parietal cortex. Moreover, regression analysis revealed that activity of the superior and intraparietal cortices (BA 7/40) strongly covaried with individual differences in g (r = 0.71 to 0.81). A correlated vectors analysis implicated bilateral posterior parietal areas in g. These results suggest that superior-g may not be due to the recruitment of additional brain regions but to the functional facilitation of the fronto-parietal network particularly driven by the posterior parietal activation.
Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures

In recent years, hesitant fuzzy linguistic term sets (HFLTSs) have been studied by many scholars and are becoming gradually mature. However, some shortcomings of HFLTS also emerged. To describe the complex linguistic terms or linguistic term sets more accurately and reasonably, in this paper, we introduce the novel concepts named double hierarchy linguistic term set (DHLTS) and double hierarchy hesitant fuzzy linguistic term set (DHHFLTS). The operational laws and properties of the DHHFLTSs are developed as well. Afterwards, we investigate the multiple criteria decision making model with double hierarchy hesitant fuzzy linguistic information. We develop a double hierarchy hesitant fuzzy linguistic MULTIMOORA (DHHFL-MULTIMOORA) method to solve it. Furthermore, we apply the DHHFL-MULTIMOORA method to deal with a practical case about selecting the optimal city in China by evaluating the implementation status of haze controlling measures. Some comparisons between the DHHFL-MULTIMOORA method and the hesitant fuzzy linguistic TOPSIS method are provided to show the advantages of the proposed method.
Malton: Towards On-Device Non-Invasive Mobile Malware Analysis for ART

It’s an essential step to understand malware’s behaviors for developing effective solutions. Though a number of systems have been proposed to analyze Android malware, they have been limited by incomplete view of inspection on a single layer. What’s worse, various new techniques (e.g., packing, anti-emulator, etc.) employed by the latest malware samples further make these systems ineffective. In this paper, we propose Malton, a novel on-device non-invasive analysis platform for the new Android runtime (i.e., the ART runtime). As a dynamic analysis tool, Malton runs on real mobile devices and provides a comprehensive view of malware’s behaviors by conducting multi-layer monitoring and information flow tracking, as well as efficient path exploration. We have carefully evaluated Malton using real-world malware samples. The experimental results showed that Malton is more effective than existing tools, with the capability to analyze sophisticated malware samples and provide a comprehensive view of malicious behaviors of these samples.
Model-Driven ERP Implementation

Enterprise Resource Planning (ERP) implementations are very complex. To obtain a fair level of understanding of the system, it is then necessary to model the supported business processes. However, the problem is the accuracy of the mapping between this model and the actual technical implementation. A solution is to make use of the OMG’s Model-Driven Architecture (MDA) framework. In fact, this framework lets the developer model his system at a high abstraction level and allows the MDA tool to generate the implementation details. This paper presents our results in applying the MDA framework to ERP implementation based on a high level model of the business processes. Then, we show how our prototype is structured and implemented in the IBM/Rational XDE environment
Intelligent Car Braking System with Collision Avoidance and ABS

This paper provides an efficient way to design an automatic car braking system using Fuzzy Logic. The system could avoid accidents caused by the delays in driver reaction times at critical situations. The proposed Fuzzy Logic Controller is able to brake a car when the car approaches for an obstacle in the very near range. Collision avoidance is achieved by steering the car if the obstacle is in the tolerable range and hence there is no necessity to apply the brakes. Another FLC (which is cascaded with the first FLC for collision avoidance) implements the Anti-lock Braking capability during heavy braking condition. Thus the system is made intelligent since it could take decisions automatically depending upon the inputs from ultrasonic sensors. A simulative study is done using MATLAB and LabVIEW software. The results obtained by the simulation model are compared with the existing system and the proposed model conveys a satisfactory result which has high consumer acceptance. ATMega controller is used for implementation of the proposed system.
Hypovitaminosis D in developing countries—prevalence, risk factors and outcomes

Hypovitaminosis D is a prevalent disorder in developing countries. Clinical manifestations of hypovitaminosis D include musculoskeletal disorders, such as nonspecific muscle pain, poor muscle strength and low BMD, as well as nonmusculoskeletal disorders, such as an increased risk of respiratory infections, diabetes mellitus and possibly cardiovascular diseases. In developing countries, the prevalence of hypovitaminosis D varies widely by and within regions; prevalence ranges between 30–90%, according to the cut-off value used within specific regions, and is independent of latitude. A high prevalence of the disorder exists in China and Mongolia, especially in children, of whom up to 50% are reported to have serum 25-hydroxyvitamin D levels <12.5 nmol/l. Despite ample sunshine throughout the year, one-third to one-half of individuals living in Sub-Saharan Africa and the Middle East have serum 25-hydroxyvitamin D levels <25 nmol/l, according to studies published in the past decade. Hypovitaminosis D is also prevalent in children and the elderly living in Latin America. Risk factors for hypovitaminosis D in developing countries are similar to those reported in Western countries and include extremes of age, female sex, winter season, dark skin pigmentation, malnutrition, lack of sun exposure, a covered clothing style and obesity. Clinical trials to assess the effect of vitamin D supplementation on classical and nonclassical clinical outcomes in developing countries are needed.
Event Detection with Hybrid Neural Architecture

Event detection from clinical notes has been traditionally solved with rule based and statistical natural language processing (NLP) approaches that require extensive domain knowledge and feature engineering. In this paper, we have explored the feasibility of approaching this task with recurrent neural networks, clinical word embeddings and introduced a hybrid architecture to improve detection for entities with smaller representation in the dataset. A comparative analysis is also done which reveals the complementary behavior of neural networks and conditional random fields in clinical entity detection.
An Automatic Approach for Accurate Edge Detection of Concrete Crack Utilizing 2D Geometric Features of Crack

The automatic edge detection of cracks on concrete structures plays an important role in the damage assessment process for cracked structures. In this paper, we proposed an automatic method for accurate edge detection of concrete cracks from real 2D images of concrete surfaces containing noisy and unintended objects. In the 2D image of a damaged concrete surface, cracks are usually observed as tree-like topology dark objects of which the branches are line-like and have local symmetry across their center axes. We utilize these two geometric properties of cracks to detect crack edges and discriminate them with edges of other unintended objects. The novel automatic crack edge detection is composed of two sequential stages. In the first stage, cracks are enhanced by a novel phase symmetry-based crack enhancement filter (PSCEF) based on their symmetric and line-like properties while non-crack objects are removed. Estimated crack centerlines are then obtained by thresholding the filtered images and applying morphological thinning algorithm to the binary image. In the second stage, the estimated center lines of the detected cracks are fitted by cubic splines and the pixel intensity profiles in the directions perpendicular to the splines are used to determine the edge points. The edge points are linked together to form the desired continuous crack edges. Various experiments of real concrete crack images are used to demonstrate the excellent performance of the proposed method. Keyword Crack detection . Edge detection . Phase symmetry . Line enhancement filter . Non-destructive evaluation
Predicting food nutrition facts using pocket-size near-infrared sensor

Diet monitoring is one of the most important aspects in preventative health care that aims to reduce various health risks. Manual recording has been a prevalence among all approaches yet it is tedious and often end up with a low adherence rate. Several existing techniques that have been developed to monitor food intake suffer too with accuracy, efficiency, and user acceptance rate. In this paper we propose a novel approach on measuring food nutrition facts, through a pocket-size non-intrusive near-infrared (NIR) scanner. We build efficient regression models that can make quantitative prediction on food nutrition contents, such as energy and carbohydrate. Our extensive experiments on off-the-shelf liquid foods demonstrates the accuracy of these regression models and proves the applicability of using NIR spectra that are collected by small hand-held scanner, on food nutrition prediction.
Projected texture stereo

Passive stereo vision is widely used as a range sensing technology in robots, but suffers from dropouts: areas of low texture where stereo matching fails. By supplementing a stereo system with a strong texture projector, dropouts can be eliminated or reduced. This paper develops a practical stereo projector system, first by finding good patterns to project in the ideal case, then by analyzing the effects of system blur and phase noise on these patterns, and finally by designing a compact projector that is capable of good performance out to 3m in indoor scenes. The system has been implemented and has excellent depth precision and resolution, especially in the range out to 1.5m.
Design and Performance Evaluation of Overcurrent Protection Schemes for Silicon Carbide (SiC) Power MOSFETs

Overcurrent protection of silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFETs) remains a challenge due to lack of practical knowledge. This paper presents three overcurrent protection methods to improve the reliability and overall cost of SiC MOSFET-based converters. First, a solid-state circuit breaker (SSCB) composed primarily by a Si IGBT and a commercial gate driver IC is connected in series with the dc bus to detect and clear overcurrent faults. Second, the desaturation technique using a sensing diode to detect the drain-source voltage under overcurrent faults is implemented as well. Third, a novel active overcurrent protection scheme through dynamic evaluation of fault current level is proposed. The design considerations and potential issues of the protection methods are described and analyzed in detail. A phase-leg configuration-based step-down converter is built to evaluate the performance of the protection schemes under various conditions, considering variation of fault type, decoupling capacitance, protection circuit parameters, etc. Finally, a comparison is made in terms of fault response time, temperature-dependent characteristics, and applications to help designers select a proper protection method.
State of the science in health professional education: effective feedback.

Effective feedback may be defined as feedback in which information about previous performance is used to promote positive and desirable development. This can be challenging as educators must acknowledge the psychosocial needs of the recipient while ensuring that feedback is both honest and accurate. Current feedback models remain reductionist in their approach. They are embedded in the hierarchical, diagnostic endeavours of the health professions. Even when it acknowledges the importance of two-way interactions, feedback often remains an educator-driven, one-way process.


LESSONS FROM THE LITERATURE
An understanding of the various types of feedback and an ability to actively seek an appropriate approach may support feedback effectiveness. Facilitative rather than directive feedback enhances learning for high achievers. High-achieving recipients undertaking complex tasks may benefit from delayed feedback. It is hypothesised that such learners are supported by reducing interruptions during the task. If we accept that medical students and doctors are high achievers, we can draw on some guiding principles from a complex and rarely conclusive literature. Feedback should focus on the task rather than the individual and should be specific. It should be directly linked to personal goals. Self-assessment as a means to identify personal learning requirements has no theoretical basis. Motivated recipients benefit from challenging facilitated feedback from external sources.


A NEW MODEL
To achieve truly effective feedback, the health professions must nurture recipient reflection-in-action. This builds on self-monitoring informed by external feedback. An integrated approach must be developed to support a feedback culture. Early training and experience such as peer feedback may over time support the required cultural change. Opportunities to provide feedback must not be missed, including those to impart potentially powerful feedback from high-stakes assessments. Feedback must be conceptualised as a supported sequential process rather than a series of unrelated events. Only this sustained approach will maximise any effect.
Behavioral anomaly detection of malware on home routers

The Internet of Things (IoT) introduced new targets and attack vectors for malicious actors who infect insecure devices with malware in order to form large botnets that can launch distributed denial of service (DDoS) attacks. These botnets comprise various infected devices such as Internet-connected cameras and home routers. This paper focuses on the unsolved problem of creating robust malware detection to secure home routers. This research compares the effectiveness of three different approaches to behavioral malware detection on home endpoint routers through the observation of kernel-level system calls on these routers: i) principal component analysis (PCA), ii) one-class support vector machines, and iii) a naive anomaly detector based on unseen n-grams.
Secure Fine-Grained Access Control and Data Sharing for Dynamic Groups in the Cloud

Cloud computing is an emerging computing paradigm that enables users to store their data in a cloud server to enjoy scalable and on-demand services. Nevertheless, it also brings many security issues, since cloud service providers (CSPs) are not in the same trusted domain as users. To protect data privacy against untrusted CSPs, existing solutions apply cryptographic methods (e.g., encryption mechanisms) and provide decryption keys only to authorized users. However, sharing cloud data among authorized users at a fine-grained level is still a challenging issue, especially when dealing with dynamic user groups. In this paper, we propose a secure and efficient fine-grained access control and data sharing scheme for dynamic user groups by: 1) defining and enforcing access policies based on the attributes of the data; 2) permitting the key generation center to efficiently update user credentials for dynamic user groups; and 3) allowing some expensive computation tasks to be performed by untrusted CSPs without requiring any delegation key. Specifically, we first design an efficient revocable attribute-based encryption (ABE) scheme with the property of ciphertext delegation by exploiting and uniquely combining techniques of identity-based encryption, ABE, subset-cover framework, and ciphertext encoding mechanism. We then present a fine-grained access control and data sharing system for on-demand services with dynamic user groups in the cloud. The experimental data show that our proposed scheme is more efficient and scalable than the state-of-the-art solution.
Attacking Deterministic Signature Schemes Using Fault Attacks

Many digital signature schemes rely on random numbers that are unique and non-predictable per signature. Failures of random number generators may have catastrophic effects such as compromising private signature keys. In recent years, many widely-used cryptographic technologies adopted deterministic signature schemes because they are presumed to be safer to implement. In this paper, we analyze the security of deterministic ECDSA and EdDSA signature schemes and show that the elimination of random number generators in these schemes enables new kinds of fault attacks. We formalize these attacks and introduce practical attack scenarios against EdDSA using the Rowhammer fault attack. EdDSA is used in many widely used protocols such as TLS, SSH, and IPSec, and we show that these protocols are not vulnerable to our attack. We formalize the necessary requirements of protocols using these deterministic signature schemes to be vulnerable, and discuss mitigation strategies and their effect on fault attacks against deterministic signature schemes.
A NETWORK ANALYSIS OF TOURISM RESEARCH

This paper uses network analysis to identify the pioneering scholars and seminal works which have influenced recent papers in leading journals. The analysis extends beyond rankings of scholars by using co-citation networks to visualize the relationships between the most influential scholars and works and to uncover the disciplinary contributions which have supported the emergence of tourism as a field of academic study. The networks of scholars and works illuminate invisible colleges, tribes and territories in tourism research and indicate that while the social sciences have been most influential, business-related citations are increasing. The findings contribute to the discourse about the epistemology of tourism research by using bibliometric techniques to offer insights into the interdisciplinary structure of tourism research.
Using the Delphi method

The reliability and validity of the selected research method are subjects to which every researcher is bound to address himself when representing the findings and conclusions of his/her work. In this study we will discuss the reliability, validity and philosophical aspects of the Delphi method, first with a small literature review and then by representing two different surveys conducted using the Delphi method. The point of view in our report is the usability of Delphi in collecting qualitative data for software engineering research. The most significant features of the Delphi method are its recursion and the possibility to get immediate feedback and evaluate one's own answer. Although there are many forms of Delphi techniques, these features exist in one form or the other in all Delphi variations. In Delphi-based surveys, the minimum number of participants is smaller and participants are not selected at random but because of their particular expertise. Among the traditional research methods this is seen to cause the risk of bias and endangering both reliability and validity. In the Delphi method, the recursion produced by three or more rounds, the expertise and - in most cases - anonymity of participants, and the opportunity to evaluate and argue one's own answer after having seen the other opinions and arguments are thought to guarantee the quality of well-planned and well-conducted research.
An Information Retrieval System for Quranic Texts: A Proposed System Design

This project proposed a system design for retrieving Quranic texts and any knowledge that derived or cites al-Quran. The objectives were to survey the Websites offering access to Quranic texts on their structure and linkages, and to propose a system design for retrieving Quranic texts. A total of 125 Websites offering access to Quranic texts were examined. Findings revealed that the Websites offer texts and translation, recitation, excerpt of exegesis, and link to other Websites consisting of news, events, and related topics. A standard structure was not implemented by these Websites. The proposed system design focuses on texts, translation, recitation, exegesis, al-Hadith, its topics and themes like stories of the prophets and places mentioned in al-Quran, and search feature
Web Service Composition: A Survey of Techniques and Tools

Web services are a consolidated reality of the modern Web with tremendous, increasing impact on everyday computing tasks. They turned the Web into the largest, most accepted, and most vivid distributed computing platform ever. Yet, the use and integration of Web services into composite services or applications, which is a highly sensible and conceptually non-trivial task, is still not unleashing its full magnitude of power. A consolidated analysis framework that advances the fundamental understanding of Web service composition building blocks in terms of concepts, models, languages, productivity support techniques, and tools is required. This framework is necessary to enable effective exploration, understanding, assessing, comparing, and selecting service composition models, languages, techniques, platforms, and tools. This article establishes such a framework and reviews the state of the art in service composition from an unprecedented, holistic perspective.
Analysis and design of proximity fuze based on waveguide discontinuity

In order to satisfy the special requirement of antenna directivity base on proximity Fuze, the concept of the waveguide discontinuity was introduced which could be a method of designing antenna. The beam of radiation should deviate from axis direction of bomb in a certain angle The frequency was between 24 GHz and 25 GHz.Circular waveguide was connected to coaxial waveguide. This form could inspire high model in discontinuity place. Electric field of coupling model could lead to a oblique radiation pattern. In the meanwhile, two symmetrical metal column was loaded in waveguide in purpose of changing impedance of antenna. The test results demonstrated the veracity of the analysis.