nils-herrmann/clean_scirepeval huggingface dataset:
Personality and Intelligence : Gender , the Big Five , Self-Estimated and Psychometric Intelligence

This paper reports on two studies that investigated the relationship between the Big Five personality traits, self-estimates of intelligence (SEI), and scores on two psychometrically validated intelligence tests. In study 1 a total of 100 participants completed the NEOPI-R, the Wonderlic Personnel Test and the Baddeley Reasoning Test, and estimated their own intelligence on a normal distribution curve. Multiple regression showed that psychometric intelligence was predicted by Conscientiousness and SEI, while SEI was predicted by gender, Neuroticism (notably anxiety) and Agreeableness (notablymodesty). Personality was a better predictor of SEI than of psychometric intelligence itself. Study 2 attempted to explore the relationship between SEI and psychometric intelligence. A total of 130 participants completed the NEO-PI-R, the Baddeley Reasoning Test, and the S & M Spatial intelligence test. In addition, SEI and participants conceptions of intelligence were also examined. In combination with gender and previous IQ test experience, these variables were found to predict about 11% of the variance in SEI. SEI was the only significant predictor of psychometrically measured intelligence. Inconsistencies between results of the two studies, theoretical and applied implications, and limitations of this work are discussed.
A conceptual model for IT Governance: A case study research

The purpose of this paper is to explore the importance of Information Technology (IT) Governance models for public organizations and presenting an IT Governance model that can be adopted by both practitioners and researchers. A review of the literature in IT Governance has been initiated to shape the intended theoretical background of this study. The systematic literature review formalizes a richer context for the IT Governance concept. An empirical survey, using a questionnaire based on COBIT 4.1 maturity model used to investigate IT Governance practice in multiple case studies from Kingdom of Bahrain. This method enabled the researcher to gain insights to evaluate IT Governance practices. The results of this research will enable public sector organizations to adopt an IT Governance model in a simple and dynamic manner. The model provides a basic structure of a concept; for instance, this allows organizations to gain a better perspective on IT Governance processes and provides a clear focus for decision-making attention. IT Governance model also forms as a basis for further research in IT Governance adoption models and bridges the gap between conceptual frameworks, real life and functioning governance.
An empirical comparison of rhythm in language and music

Musicologists and linguists have often suggested that the prosody of a culture's spoken language can influence the structure of its instrumental music. However, empirical data supporting this idea have been lacking. This has been partly due to the difficulty of developing and applying comparable quantitative measures to melody and rhythm in speech and music. This study uses a recently-developed measure for the study of speech rhythm to compare rhythmic patterns in English and French language and classical music. We find that English and French musical themes are significantly different in this measure of rhythm, which also differentiates the rhythm of spoken English and French. Thus, there is an empirical basis for the claim that spoken prosody leaves an imprint on the music of a culture.
A 1–4 In-Phase Power Divider for 5G Wireless Communication System

A wide band power divider using modified Wilkinson design is presented. It is designed to operate at 5G wireless communication band of China. This power divider using wide band Wilkinson design method can be used as the feeding network of antenna array. The presented design can operate over a wide bandwidth covering 36.5GHz-44GHz which covers the 5G wireless communication band of China. The simulated and verified results show good agreement that the input return loss (S11) and the output return losses (S22, S33, S44, S55) are all under -12dB from 37GHz-42GHz. The insertion losses (including division loss) are within 7.2dB and the isolation between any two output ports are all under -10dB.
EMG pattern classification to control a hand orthosis for functional grasp assistance after stroke

Wearable orthoses can function both as assistive devices, which allow the user to live independently, and as rehabilitation devices, which allow the user to regain use of an impaired limb. To be fully wearable, such devices must have intuitive controls, and to improve quality of life, the device should enable the user to perform Activities of Daily Living. In this context, we explore the feasibility of using electromyography (EMG) signals to control a wearable exotendon device to enable pick and place tasks. We use an easy to don, commodity forearm EMG band with 8 sensors to create an EMG pattern classification control for an exotendon device. With this control, we are able to detect a user's intent to open, and can thus enable extension and pick and place tasks. In experiments with stroke survivors, we explore the accuracy of this control in both non-functional and functional tasks. Our results support the feasibility of developing wearable devices with intuitive controls which provide a functional context for rehabilitation.
The importance of conventional radiography in the mutational analysis of skeletal dysplasias (the TRPV4 mutational family)

The spondylo and spondylometaphyseal dysplasias (SMDs) are characterized by vertebral changes and metaphyseal abnormalities of the tubular bones, which produce a phenotypic spectrum of disorders from the mild autosomal-dominant brachyolmia to SMD Kozlowski to autosomal-dominant metatropic dysplasia. Investigations have recently drawn on the similar radiographic features of those conditions to define a new family of skeletal dysplasias caused by mutations in the transient receptor potential cation channel vanilloid 4 (TRPV4). This review demonstrates the significance of radiography in the discovery of a new bone dysplasia family due to mutations in a single gene.
Multiple-Parameter Discrete Fractional Transform and its Applications

In recent years, several special multiple-parameter discrete fractional transforms (MPDFRTs) have been proposed, and their advantages have been demonstrated in the fields of communication systems and information security. However, the general theoretical framework of MPDFRTs has not yet been established. In this paper, we propose two separate theoretical frameworks called the type I and II MPDFRT that can include existing multiple-parameter transforms as special cases. The properties of the type I and II MPDFRT have been analyzed in detail and their high-dimensional operators have been defined. Under the theoretical frameworks, we can construct new types of transforms that may be useful in signal processing and information security. Finally, we perform two applications about image encryption and image feature extraction in the type I and II MPDFRT domain. The simulation results demonstrate that the typical transforms constructed under the proposed theoretical frameworks yield promising results in these applications.
Holoprosencephaly and midline facial anomalies: redefining classification and management.

Holoprosencephaly encompasses a series of midline defects of the brain and face. Most cases are associated with severe malformations of the brain which are incompatible with life. At the other end of the spectrum, however, are patients with midline facial defects and normal or near-normal brain development. Although some are mentally retarded, others have the potential for achieving near-normal mentality and a full life expectancy. The latter patients do not fit clearly into the previously defined classification system. Proposed is a new classification focusing on those patients with normal or lobar brain morphology but with a wide range of facial anomalies. The classification aids in planning treatment. Coupled with CT scan findings of the brain and a period of observation, patients unlikely to thrive can be distinguished from those who will benefit from surgical intervention. Repair of the false median cleft lip and palate may suffice in patients with moderate mental retardation. Patients exhibiting normal or near-normal mentality with hypotelorbitism and nasomaxillary hypoplasia can be treated with a simultaneous midface advancement, facial bipartition expansion, and nasal reconstruction.
Clitoral and penile sizes of full term newborns in two different ethnic groups.

Standards of penile and clitoral sizes are useful for diagnosis of genital abnormalities. In order to verify whether ethnicity has an effect on the size of external genitalia in newborns, 570 full term infants, Jews (221) and Bedouins (349), at the neonatal department of the Soroka Medical Center were examined. Clitoral length, the distance between the center of the anus to the fourchette (AF) and the distance between the center of the anus and the base of the clitoris (AC) were measured, and the AF/AC ratio was calculated for the females. Penile length was measured in the males. Significant differences in clitoral length (12.6%) between the Jewish group (5.87 +/- 1.48 mm) and the Bedouin group (6.61 +/- 1.72 mm) (p < 0.01) and in the ratio of AF to AC between the two ethnic groups (p < 0.01) were found. To the best of our knowledge, our study is the first to report ethnic differences in genital sizes of newborns.
Fortune Teller: Predicting Your Career Path

People go to fortune tellers in hopes of learning things about their future. A future career path is one of the topics most frequently discussed. But rather than rely on “black arts” to make predictions, in this work we scientifically and systematically study the feasibility of career path prediction from social network data. In particular, we seamlessly fuse information from multiple social networks to comprehensively describe a user and characterize progressive properties of his or her career path. This is accomplished via a multisource learning framework with fused lasso penalty, which jointly regularizes the source and career-stage relatedness. Extensive experiments on real-world data confirm the accuracy of our model.
16 Acceleration Analysis of 3-RPS Parallel Manipulators by Means of Screw Theory

According to the notation proposed by the International Federation for the Theory of Mechanisms and Machines IFToMM (Ionescu, 2003); a parallel manipulator is a mechanism where the motion of the end-effector, namely the moving or movable platform, is controlled by means of at least two kinematic chains. If each kinematic chain, also known popularly as limb or leg, has a single active joint, then the mechanism is called a fully-parallel mechanism, in which clearly the nominal degree of freedom equates the number of limbs. Tire-testing machines (Gough & Whitehall, 1962) and flight simulators (Stewart, 1965), appear to be the first transcendental applications of these complex mechanisms. Parallel manipulators, and in general mechanisms with parallel kinematic architectures, due to benefits --over their serial counterparts-such as higher stiffness and accuracy, have found interesting applications such as walking machines, pointing devices, multi-axis machine tools, micro manipulators, and so on. The pioneering contributions of Gough and Stewart, mainly the theoretical paper of Stewart (1965), influenced strongly the development of parallel manipulators giving birth to an intensive research field. In that way, recently several parallel mechanisms for industrial purposes have been constructed using the, now, classical hexapod as a base mechanism: Octahedral Hexapod HOH-600 (Ingersoll), HEXAPODE CMW 300 (CMW), Cosmo Center PM-600 (Okuma), F-200i (FANUC) and so on. On the other hand one cannot ignore that this kind of parallel kinematic structures have a limited and complex-shaped workspace. Furthermore, their rotation and position capabilities are highly coupled and therefore the control and calibration of them are rather complicated. It is well known that many industrial applications do not require the six degrees of freedom of a parallel manipulator. Thus in order to simplify the kinematics, mechanical assembly and control of parallel manipulators, an interesting trend is the development of the so called defective parallel manipulators, in other words, spatial parallel manipulators with fewer than six degrees of freedom. Special mention deserves the Delta robot, invented by Clavel (1991); which proved that parallel robotic manipulators are an excellent option for industrial applications where the accuracy and stiffness are fundamental characteristics. Consider for instance that the Adept Quattro robot, an application of the Delta robot, developed by Francois Pierrot in collaboration with Fatronik (Int. patent appl. WO/2006/087399), has a
Curriculum Learning for Depth Estimation with Deep Convolutional Neural Networks

Curriculum learning is a machine learning technique adapted from the way humans acquire knowledge and skills, initially mastering simple tasks and progressing to more complex tasks. The work explores curriculum training by creating multiple levels of dataset with increasing complexity on which the trainings are performed. The experiments demonstrated that there is an average of 12% improvement test loss when compared to a non-curriculum approach. The experiment also demonstrates the advantage of creating synthetic dataset and how it aids in the overall improvement of accuracy. An improvement of 26% is attained on the test error loss when curriculum trained model was compared to training on a limited real world dataset. The work also goes onto propose a novel learning approach, the Self Paced Learning approach with Error-Diversity (SPL-ED) An overall reduction of 32% in the test loss is observed when compared to the non-curriculum training limited to real-world dataset.
Application of hybrid heuristic optimization algorithms for solving optimal regional dispatch of energy and reserve considering the social welfare of the participating markets

Market integration allows increasing the social welfare of a given society. In most markets, integration also raises the social welfare of the participating markets (partakers). However, electricity markets have complexities such as transmission network congestion and requirements of power reserve that could lead to a decrease in the social welfare of some partakers. The social welfare reduction of partakers, if it occurs, would surely be a hindrance to the development of regional markets, since participants are usually national systems. This paper shows a new model for the regional dispatch of energy and reserve, and proposes as constraints that the social welfare of partakers does not decrease with respect to that obtained from the isolated optimal operation. These social welfare constraints are characterized by their stochastic nature and their dependence on the energy price of different operating states. The problem is solved by the combination of two optimization models (hybrid optimization): A linear model embedded within a meta-heuristic algorithm, which is known as the swarm version of the Means Variance Mapping Optimization (MVMOS). MVMOS allows incorporating the stochastic nature of social welfare constraints through a dynamic penalty scheme, which considers the fulfillment degree along with the dynamics of the search process. & 2016
Frame rate analysis of video synthetic aperture radar (ViSAR)

Video Synthetic Aperture Radar (ViSAR) is the new application of SAR technique. Through reasonable system parameter design, ViSAR system can obtain the SAR image at a faster image rates (also referred to herein as frame rate) which permit the detection of dynamic changes that are occurring in the target scene. Therefore, frame rate as one of the core parameters of ViSAR system should be carefully studied.
End-to-end detection-segmentation network with ROI convolution

We propose an end-to-end neural network that improves the segmentation accuracy of fully convolutional networks by incorporating a localization unit. This network performs object localization first, which is then used as a cue to guide the training of the segmentation network. We test the proposed method on a segmentation task of small objects on a clinical dataset of ultrasound images. We show that by jointly learning for detection and segmentation, the proposed network is able to improve the segmentation accuracy compared to only learning for segmentation.
Immersion of rohu fingerlings in clove oil reduced handling and confinement stress and mortality

The use of anaesthetics becomes essential in the transportation medium for mitigating physiological stress and reducing metabolic rates. Clove oil is now emerging as safe, eco-friendly, effective, and economic fish anaesthetic. We tested the efficacy of clove oil as an anaesthetic for the handling and transportation of rohu, Labeo rohita (Hamilton-Buchnan) fingerlings. The lowest effective dose of clove oil that produced induction (≤3 min) and recovery (≤5 min) found was 50μl L-1.The induction times decreased and recovery times increased with increased in the concentrations of clove oil. The effective sedative dose at 5μl L-1 of clove oil was found suitable for transportation in plastic bags with pure oxygen up to 12h. The mortality rate (%) of fingerlings was significantly higher (14.4±1.14%) in the control (without sedative) than sedative doses of clove oil (P<0.05). The dose at 5μl L-1 of clove oil was found to mitigate stress responses with lower glucose level and reduce the deterioration of water quality in comparison to control. The present findings revealed that clove oil is promising to be used as anaesthetic and sedative for handling and transportation of rohu fingerlings. Clove oil is feasible to use in the commercial fish seed transportation due its merits like cheap and safe anaesthetic.
Combining TMS-EEG with transcranial direct current stimulation language treatment in aphasia.

Despite the fact that different studies have been performed using transcranial direct current stimulation (tDCS) in aphasia, so far, to what extent the stimulation of a cerebral region may affect the activity of anatomically connected regions remains unclear. The authors used a combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to explore brain areas' excitability modulation before and after active and sham tDCS. Six chronic aphasics underwent 3 weeks of language training coupled with tDCS over the right inferior frontal gyrus. To measure the changes induced by tDCS, TMS-EEG closed to the area stimulated with tDCS were calculated. A significant improvement after tDCS stimulation was found which was accompained by a modification of the EEG over the stimulated region.
Engineering Secure Software and Systems

Policy-based access control is a technology that achieves separation of concerns through evaluating an externalized policy at each access attempt. While this approach has been well-established for request-response applications, it is not supported for database queries of data-driven applications, especially for attribute-based policies. In particular, search operations for such applications involve poor scalability with regard to the data set size for this approach, because they are influenced by dynamic runtime conditions. This paper proposes a scalable application-level middleware solution that performs runtime injection of the appropriate rules into the original search query, so that the result set of the search includes only items to which the subject is entitled. Our evaluation shows that our method scales far better than current state of practice approach that supports policy-based access control.
Transfer Learning for Melanoma Detection: Participation in ISIC 2017 Skin Lesion Classification Challenge

This manuscript describes our participation in the International Skin Imaging Collaboration’s 2017 Skin Lesion Analysis Towards Melanoma Detection competition. We participated in Part 3: Lesion Classification. The two stated goals of this binary image classification challenge were to distinguish between (a) melanoma and (b) nevus and seborrheic keratosis, followed by distinguishing between (a) seborrheic keratosis and (b) nevus and melanoma. We chose a deep neural network approach with a transfer learning strategy, using a pre-trained Inception V3 network as both a feature extractor to provide input for a multi-layer perceptron as well as fine-tuning an augmented Inception network. This approach yielded validation set AUC’s of 0.84 on the second task and 0.76 on the first task, for an average AUC of 0.80. We joined the competition unfortunately late, and we look forward to improving on these results. transfer learning; melanoma; seborrheic keratosis; nevus;
A GRAPH ORIENTED MODEL FOR ONTOLOGY TRANSFORMATION INTO CONCEPTUAL DATA MODEL

The paper analyses graph oriented method for ontology transformation into conceptual data model. A number of methods were proposed to develop conceptual data models, but only few deals with knowledge reuse. In this paper we present an approach for knowledge represented by ontology automatic transformation into conceptual data model. The graph transformation language is presented and adapted for formal transformation of ontology into conceptual model. Details and examples of proposed ontology transformation into conceptual data model are presented also.
Exploring and Interacting with Virtual Museums

Traditional exhibilions in muséums provide limited possibililies of interaction tiehveen llie visitor and tlieir artefacts. Usually, interaction is confined to reading labels with little information on the exhibits, shop booklets, and audio guided tours. These forms of interaction provide minimal information, and do not respond to a visitor's personalized information preferences. As a result, there is no direct involvement between the visitor and the exhibit. This paper expands on a presentation metaphor, the virtual museum, which through the use of technologies such as Web/X3D, VR and AR offers to the visitor the possibility of exploring a virtual museum, interacting with virtual exhibits in real-time and visualising the.'se exhibits in contexts such as 3D gallery spaces. We offer a 'potpouri 'of novel and cost effective interaction and visualisation techniques that can be integrated into web based virtual museians. In our virtual museums, the exhibit is a digital representation of the cultural artefact, repre.<:ented in various multimedia formats such as text, images, videos and 3D modeh/scenes that can be placed inside virtual galleiy spaces. Such spaces can be explored, interacted with, and visualised on museum web pages using standard VRML browsers. The interactions provided within our system allow a museum web visitor to: participate in education quizzes about the exhibits: examine them from differem perspectives in VR environments: 'pick-up 'andfreely observe the exhibits in indoor AR environments; and finally interact with an artefacts replica through a safe multimodal interface
Biofouling: lessons from nature.

Biofouling is generally undesirable for many applications. An overview of the medical, marine and industrial fields susceptible to fouling is presented. Two types of fouling include biofouling from organism colonization and inorganic fouling from non-living particles. Nature offers many solutions to control fouling through various physical and chemical control mechanisms. Examples include low drag, low adhesion, wettability (water repellency and attraction), microtexture, grooming, sloughing, various miscellaneous behaviours and chemical secretions. A survey of nature's flora and fauna was taken in order to discover new antifouling methods that could be mimicked for engineering applications. Antifouling methods currently employed, ranging from coatings to cleaning techniques, are described. New antifouling methods will presumably incorporate a combination of physical and chemical controls.