nils-herrmann/clean_scirepeval huggingface dataset:
The impact of business analytics on supply chain performance

a r t i c l e i n f o Keywords: Supply chain management Analytical capabilities Information systems Business process management Performance SCOR The paper investigates the relationship between analytical capabilities in the plan, source, make and deliver area of the supply chain and its performance using information system support and business process orientation as moderators. Structural equation modeling employs a sample of 310 companies from different industries from the USA, Europe, Canada, Brazil and China. The findings suggest the existence of a statistically significant relationship between analytical capabilities and performance. The moderation effect of information systems support is considerably stronger than the effect of business process orientation. The results provide a better understanding of the areas where the impact of business analytics may be the strongest. In the modern world competition is no longer between organizations , but among supply chains ('SCs'). Effective supply chain management ('SCM') has therefore become a potentially valuable way of securing a competitive advantage and improving organizational performance [47,79]. However, the understanding of the why and how SCM affects firm performance, which areas are especially important and which are the important moderator effects is still incomplete. This paper thus analyses the impact of business analytics ('BA') in a SC on the improvement of SC performance. The topic is important since enhancing the effectiveness and efficiency of SC analytics is a critical component of a chain's ability to achieve its competitive advantage . BA have been identified as an important " tool " for SCM [44] and optimization techniques have become an integral part of organizational business processes [80]. A correct relevant business decision based on bundles of very large volumes of both internal and external data is only possible with BA [68]. It is therefore not surprising that research interest in BA use has been increasing [43]. However, despite certain anecdotic evidence (see for instance the examples given in ) or optimistic reports of return-on-investment exceeding 100% (see e.g. ) a systematic and structured analysis of the impact of BA use on SC performance has not yet been conducted. Accordingly, the main contribution of our paper is its analysis of the impact of the use of BA in different areas of the SC (based on the Supply Chain Operations Reference ('SCOR') model) on the performance of the chain. Further, the mediating effects of two important constructs, namely information systems ('IS') support and business …
Using Data Mining for Predicting Relationships between Online Question Theme and Final Grade

As higher education diversifies its delivery modes, our ability to use the predictive and analytical power of educational data mining (EDM) to understand students’ learning experiences is a critical step forward. The adoption of EDM by higher education as an analytical and decision making tool is offering new opportunities to exploit the untapped data generated by various student information systems (SIS) and learning management systems (LMS). This paper describes a hybrid approach which uses EDM and regression analysis to analyse live video streaming (LVS) students’ online learning behaviours and their performance in their courses. Students’ participation and login frequency, as well as the number of chat messages and questions that they submit to their instructors, were analysed, along with students’ final grades. Results of the study show a considerable variability in students’ questions and chat messages. Unlike previous studies, this study suggests no correlation between students’ number of questions / chat messages / login times and students’ success. However, our case study reveals that combining EDM with traditional statistical analysis provides a strong and coherent analytical framework capable of enabling a deeper and richer understanding of students’ learning behaviours and experiences.
Video Question Answering via Attribute-Augmented Attention Network Learning

Video Question Answering is a challenging problem in visual information retrieval, which provides the answer to the referenced video content according to the question. However, the existing visual question answering approaches mainly tackle the problem of static image question, which may be ineffectively for video question answering due to the insufficiency of modeling the temporal dynamics of video contents. In this paper, we study the problem of video question answering by modeling its temporal dynamics with frame-level attention mechanism. We propose the attribute-augmented attention network learning framework that enables the joint frame-level attribute detection and unified video representation learning for video question answering. We then incorporate the multi-step reasoning process for our proposed attention network to further improve the performance. We construct a large-scale video question answering dataset. We conduct the experiments on both multiple-choice and open-ended video question answering tasks to show the effectiveness of the proposed method.
Noninvasive and Nonocclusive Blood Pressure Estimation Via a Chest Sensor

The clinical demand for a device to monitor blood pressure (BP) in ambulatory scenarios with minimal use of inflation cuffs is increasing. Based on the so-called pulse wave velocity (PWV) principle, this paper introduces and evaluates a novel concept of BP monitor that can be fully integrated within a chest sensor. After a preliminary calibration, the sensor provides nonocclusive beat-by-beat estimations of mean arterial pressure (MAP) by measuring the pulse transit time (PTT) of arterial pressure pulses travelling from the ascending aorta toward the subcutaneous vasculature of the chest. In a cohort of 15 healthy male subjects, a total of 462 simultaneous readings consisting of reference MAP and chest PTT were acquired. Each subject was recorded at three different days: D, D+3, and D+14. Overall, the implemented protocol induced MAP values to range from 80 ± 6 mmHg in baseline, to 107 ± 9 mmHg during isometric handgrip maneuvers. Agreement between reference and chest-sensor MAP values was tested by using intraclass correlation coefficient (ICC = 0.78) and Bland-Altman analysis (mean error = 0.7 mmHg, standard deviation = 5.1 mmHg). The cumulative percentage of MAP values provided by the chest sensor falling within a range of ±5 mmHg compared to reference MAP readings was of 70%, within ±10 mmHg was of 91%, and within ±15 mmHg was of 98%. These results point at the fact that the chest sensor complies with the British Hypertension Society requirements of Grade A BP monitors, when applied to MAP readings. Grade A performance was maintained even two weeks after having performed the initial subject-dependent calibration. In conclusion, this paper introduces a sensor and a calibration strategy to perform MAP measurements at the chest. The encouraging performance of the presented technique paves the way toward an ambulatory compliant, continuous, and nonocclusive BP monitoring system.
Tangible products: redressing the balance between appearance and action

Over the past decade, our group has approached interaction design from an industrial design point of view. In doing so, we focus on a branch of design called “formgiving” Whilst formgiving is somewhat of a neologism in English, many other European languages do have a separate word for form-related design, including German (Gestaltung), Danish (formgivnin), Swedish (formgivning) and Dutch (vormgeving). . Traditionally, formgiving has been concerned with such aspects of objects as form, colour, texture and material. In the context of interaction design, we have come to see formgiving as the way in which objects appeal to our senses and motor skills. In this paper, we first describe our approach to interaction design of electronic products. We start with how we have been first inspired and then disappointed by the Gibsonian perception movement , how we have come to see both appearance and actions as carriers of meaning, and how we see usability and aesthetics as inextricably linked. We then show a number of interaction concepts for consumer electronics with both our initial thinking and what we learnt from them. Finally, we discuss the relevance of all this for tangible interaction. We argue that, in addition to a data-centred view, it is also possible to take a perceptual-motor-centred view on tangible interaction. In this view, it is the rich opportunities for differentiation in appearance and action possibilities that make physical objects open up new avenues to meaning and aesthetics in interaction design. Whilst formgiving is somewhat of a neologism in English, many other European languages do have a separate word for form-related design, including German (Gestaltung), Danish (formgivnin), Swedish (formgivning) and Dutch (vormgeving).
Utilizing IOMMUs for Virtualization in Linux and Xen Muli

IOMMUs are hardware devices that translate device DMA addresses to proper machine physical addresses. IOMMUs have long been used for RAS (prohibiting devices from DMA’ing into the wrong memory) and for performance optimization (avoiding bounce buffers and simplifying scatter/gather). With the increasing emphasis on virtualization, IOMMUs from IBM, Intel, and AMD are being used and re-designed in new ways, e.g., to enforce isolation between multiple operating systems with direct device access. These new IOMMUs and their usage scenarios have a profound impact on some of the OS and hypervisor abstractions and implementation. We describe the issues and design alternatives of kernel and hypervisor support for new IOMMU designs. We present the design and implementation of the changes made to Linux (some of which have already been merged into the mainline kernel) and Xen, as well as our proposed roadmap. We discuss how the interfaces and implementation can adapt to upcoming IOMMU designs and to tune performance for different workload/reliability/security scenarios. We conclude with a description of some of the key research and development challenges new IOMMUs present.
Multimodal Interfaces That Process What Comes Naturally

During natural multimodal communication, we speak, gesture, gaze and move in a powerful flow of communication that bears little resemblance to the discrete keyboard and mouse clicks entered sequentially in a graphical user interface (GUI). A profound shift is occurring toward embracing users’ natural behavior as the c nter of the humancomputer interface. Multimodal interfaces are being developed that permit our highly skilled and coordinated communicative behaviors to control system interactions in a more transparent interface experience than ever before. Our voice, hands, and whole body together, once augmented by sensors such as microphones and cameras, now are the ultimate transparent and mobile multimodal input devices.
A Hybrid Approach for Efficient Privacy-Preserving Authentication in VANET

A vehicular ad hoc network (VANET) serves as an application of the intelligent transportation system that improves traffic safety as well as efficiency. Vehicles in a VANET broadcast traffic and safety-related information used by road safety applications, such as an emergency electronic brake light. The broadcast of these messages in an open-access environment makes security and privacy critical and challenging issues in the VANET. A misuse of this information may lead to a traffic accident and loss of human lives atworse and, therefore, vehicle authentication is a necessary requirement. During authentication, a vehicle’s privacy-related data, such as identity and location information, must be kept private. This paper presents an approach for privacy-preserving authentication in a VANET. Our hybrid approach combines the useful features of both the pseudonym-based approaches and the group signature-based approaches to preclude their respective drawbacks. The proposed approach neither requires a vehicle to manage a certificate revocation list, nor indulges vehicles in any group management. The proposed approach utilizes efficient and lightweight pseudonyms that are not only used for message authentication, but also serve as a trapdoor in order to provide conditional anonymity. We present various attack scenarios that show the resilience of the proposed approach against various security and privacy threats. We also provide analysis of computational and communication overhead to show the efficiency of the proposed technique. In addition, we carry out extensive simulations in order to present a detailed network performance analysis. The results show the feasibility of our proposed approach in terms of end-to-end delay and packet delivery ratio.
Internet use, videogame playing and cell phone use as predictors of children's body mass index (BMI), body weight, academic performance, and social and overall self-esteem

0747-5632/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.chb.2010.10.019 ⇑ Corresponding author.  E-mail address: jackso67@msu.edu (L.A. Jackson). In this research we examined the prediction of children’s body mass index (BMI), body weight, academic performance, social self-esteem and overall self-esteem from their IT (information technology) use, specifically, their Internet use, cell phone use and videogame playing, after controlling for the effects of gender, race, age and household income on these measures. Participants were 482 children whose average age was 12 years old. One-third was African American and two-thirds were Caucasian American. Results indicated that IT use did not predict BMI or body weight, contrary to one previous survey and the widespread belief that screen time is responsible for the obesity epidemic among our nation’s children. Instead, BMI and body weight were higher for African Americans, older children and children from lower income households. The sole and strong positive predictor of visual–spatial skills was videogame playing, which also predicted lower grade point averages (GPAs). Gender and Internet use predicted standardized test scores in reading skills. Females and children who used the Internet more had better reading skills than did males and children who used the Internet less, respectively. Implications of these findings for future research on the benefits and liabilities of IT use are discussed.
Online Feature Selection and Its Applications

Feature selection is an important technique for data mining. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of online feature selection (OFS) in which an online learner is only allowed to maintain a classifier involved only a small and fixed number of features. The key challenge of online feature selection is how to make accurate prediction for an instance using a small number of active features. This is in contrast to the classical setup of online learning where all the features can be used for prediction. We attempt to tackle this challenge by studying sparsity regularization and truncation techniques. Specifically, this article addresses two different tasks of online feature selection: 1) learning with full input, where an learner is allowed to access all the features to decide the subset of active features, and 2) learning with partial input, where only a limited number of features is allowed to be accessed for each instance by the learner. We present novel algorithms to solve each of the two problems and give their performance analysis. We evaluate the performance of the proposed algorithms for online feature selection on several public data sets, and demonstrate their applications to real-world problems including image classification in computer vision and microarray gene expression analysis in bioinformatics. The encouraging results of our experiments validate the efficacy and efficiency of the proposed techniques.
SAPIENS DIGITAL : FROM DIGITAL IMMIGRANTS AND DIGITAL NATIVES TO DIGITAL WISDOM

This is the translation of a paper by Marc Prensky, the originator of the famous metaphor digital natives digital immigrants. Here, ten years after the birth of that successful metaphor, Prensky outlines that, while the distinction between digital natives and immigrants will progressively become less important, new concepts will be needed to represent the continuous evolution of the relationship between man and digital technologies. In this paper Prensky introduces the concept of digital wisdom, a human quality which develops as a result of the empowerment that the natural human skills can receive through a creative and clever use of digital technologies.  Digital natives, digital immigrants, digital wisdom, digital empowerment. Prensky M. (2010). H. Sapiens Digitale: dagli Immigrati digitali e nativi digitali alla saggezza digitale. TD-Tecnologie Didattiche, 50, pp. 17-24 17 I problemi del mondo d’oggi non possono essere risolti facendo ricorso allo stesso tipo di pensiero che li ha creati
The human sexual response cycle: Brain imaging evidence linking sex to other pleasures

Sexual behavior is critical to species survival, yet comparatively little is known about the neural mechanisms in the human brain. Here we systematically review the existing human brain imaging literature on sexual behavior and show that the functional neuroanatomy of sexual behavior is comparable to that involved in processing other rewarding stimuli. Sexual behavior clearly follows the established principles and phases for wanting, liking and satiety involved in the pleasure cycle of other rewards. The studies have uncovered the brain networks involved in sexual wanting or motivation/anticipation, as well as sexual liking or arousal/consummation, while there is very little data on sexual satiety or post-orgasmic refractory period. Human sexual behavior also interacts with other pleasures, most notably social interaction and high arousal states. We discuss the changes in the underlying brain networks supporting sexual behavior in the context of the pleasure cycle, the changes to this cycle over the individual's life-time and the interactions between them. Overall, it is clear from the data that the functional neuroanatomy of sex is very similar to that of other pleasures and that it is unlikely that there is anything special about the brain mechanisms and networks underlying sex.
A Novel Pattern Diversity Reflector Antenna Using Reconfigurable Frequency Selective Reflectors

A radiation pattern diversity reflector antenna is investigated. Novel switchable frequency selective reflectors are designed and developed to construct a square corner reflector antenna. By controlling a switching device on the frequency selective reflector, one can make it opaque or transparent to a vertically polarized incident wave. This antenna is fed by a monopole. By configuring the switch states of the frequency selective reflectors, various beam shapes can be formed and steered. Measured results of the antenna show good agreement with the calculated ones.
The fundamental matrix: Theory, algorithms, and stability analysis

In this paper we analyze in some detail the geometry of a pair of cameras, i.e., a stereo rig. Contrarily to what has been done in the past and is still done currently, for example in stereo or motion analysis, we do not assume that the intrinsic parameters of the cameras are known (coordinates of the principal points, pixels aspect ratio and focal lengths). This is important for two reasons. First, it is more realistic in applications where these parameters may vary according to the task (active vision). Second, the general case considered here, captures all the relevant information that is necessary for establishing correspondences between two pairs of images. This information is fundamentally projective and is hidden in a confusing manner in the commonly used formalism of the Essential matrix introduced by Longuet-Higgins (1981). This paper clarifies the projective nature of the correspondence problem in stereo and shows that the epipolar geometry can be summarized in one 3×3 matrix of rank 2 which we propose to call the Fundamental matrix. After this theoretical analysis, we embark on the task of estimating the Fundamental matrix from point correspondences, a task which is of practical importance. We analyze theoretically, and compare experimentally using synthetic and real data, several methods of estimation. The problem of the stability of the estimation is studied from two complementary viewpoints. First we show that there is an interesting relationship between the Fundamental matrix and three-dimensional planes which induce homographies between the images and create unstabilities in the estimation procedures. Second, we point to a deep relation between the unstability of the estimation procedure and the presence in the scene of so-called critical surfaces which have been studied in the context of motion analysis. Finally we conclude by stressing the fact that we believe that the Fundamental matrix will play a crucial role in future applications of three-dimensional Computer Vision by greatly increasing its versatility, robustness and hence applicability to real difficult problems.
An evaluation of Convolutional Neural Networks for music classification using spectrograms

Music genre recognition based on visual representation has been successfully explored over the last years. Classifiers trained with textural descriptors (e.g., Local Binary Patterns, Local Phase Quantization, and Gabor filters) extracted from the spectrograms have achieved state-of-the-art results on several music datasets. In this work, though, we argue that we can go further with the time-frequency analysis through the use of representation learning. To show that, we compare the results obtained with a Convolutional Neural Network (CNN) with the results obtained by using handcrafted features and SVM classifiers. In addition, we have performed experiments fusing the results obtained with learned features and handcrafted features to assess the complementarity between these representations for the music classification task. Experiments were conducted on three music databases with distinct characteristics, specifically a western music collection largely used in research benchmarks (ISMIR 2004 Database), a collection of Latin American music (LMD database), and a collection of field recordings of ethnic African music. Our experiments show that the CNN compares favorably to other classifiers in several scenarios, hence, it is a very interesting alternative for music genre recognition. Considering the African database, the CNN surpassed the handcrafted representations and also the state-of-the-art by a margin. In the case of the LMD database, the combination of CNN and Robust Local Binary Pattern achieved a recognition rate of 92%, which to the best of our knowledge, is the best result (using an artist filter) on this dataset so far. On the ISMIR 2004 dataset, although the CNN did not improve the state of the art, it performed better than the classifiers based individually on other kind of features.