nils-herrmann/clean_scirepeval huggingface dataset:
SELF-SERVICE BUSINESS INTELLIGENCE FOR HIGHER EDUCATION MANAGEMENT

Higher education institution management faces the challenge of improving study process quality and efficiency. Employable graduates are the result every education institution wishes to produce. Graduation rate is therefore crucial key performance indicator (KPI) important in many national models of financing higher education institutions. To achieve performance improvements of institution undergraduate retention rate has to be measured and analysed. Unfinished coursework indicates problems in the study process which management can correct with assignment of extra academic workload to faculty staff. Principles of equity and transparency have to be considered in the academic workload management process. Information technology (IT), in particular self-service business intelligence (BI) can help management with timely and relevant information about study process. In this case study of designing a data warehouse for higher education management the use of different KPI’s is discussed. Dimensional models of proposed BI solution are presented. Future research will include assessment of relative technical efficiency of higher education institution, prediction of undergraduate retention and analysis of obstacle for successful graduation.
Towards Nearly Zero Energy Buildings in Europe : A Focus on Retrofit in Non-Residential Buildings

Buildings are the focus of European (EU) policies aimed at a sustainable and competitive low-carbon economy by 2020. Reducing energy consumption of existing buildings and achieving nearly zero energy buildings (NZEBs) are the core of the Energy Efficiency Directive (EED) and the recast of the Energy Performance of Building Directive (EPBD). To comply with these requirements, Member States have to adopt actions to exploit energy savings from the building sector. This paper describes the differences between deep, major and NZEB renovation and then it provides an overview of best practice policies and measures to target retrofit and investment related to non-residential buildings. Energy requirements defined by Member States for NZEB levels are reported comparing both new and existing residential and non-residential buildings. The paper shows how the attention given to refurbishment of NZEBs increased over the last decade, but the achievement of a comprehensive implementation of retrofit remains one of main challenges that Europe is facing.
A Factorial Mixture Prior for Compositional Deep Generative Models

We assume that a high-dimensional datum, like an image, is a compositional expression of a set of properties, with a complicated non-linear relationship between the datum and its properties. This paper proposes a factorial mixture prior for capturing latent properties, thereby adding structured compositionality to deep generative models. The prior treats a latent vector as belonging to Cartesian product of subspaces, each of which is quantized separately with a Gaussian mixture model. Some mixture components can be set to represent properties as observed random variables whenever labeled properties are present. Through a combination of stochastic variational inference and gradient descent, a method for learning how to infer discrete properties in an unsupervised or semi-supervised way is outlined and empirically evaluated.
A CPW-fed inductively coupled modified bow-tie slot antenna

A CPW-fed inductively coupled bow-tie slot antenna is introduced. Several geometric parameters of the antenna were varied to observe the impedance matching between the CPW-feed and the antenna. The inductively coupled CPW feeding mechanism makes the concept suitable for array applications. The bandwidth reduction for an inductively coupled straight-dipole slot is overcome by utilizing an inductively coupled bow-tie slot. Antenna models for operation at 2.45 and 5.5 GHz were constructed and return loss and radiation pattern results were obtained. The proposed antenna provides bandwidths of 8% and 13% at 2.45 and 5.5 GHz, respectively.
A preliminary study of ecommerce adoption in developing countries

What factors underlie the adoption dynamics of ecommerce technologies among users in developing countries? Even though the internet promised to be the great equalizer, the nuanced variety of conditions and contingencies that shape user adoption of ecommerce technologies has received little scrutiny. Building on previous research on technology adoption, the paper proposes a global information technology (IT) adoption model. The model includes antecedents of performance expectancy, social influence, and technology opportunism and investigates the crucial influence of facilitating conditions. The proposed model is tested using data from 172 technology users from 37 countries, collected over a 1-year period. The findings suggest that in developing countries, facilitating conditions play a critical moderating role in understanding actual ecommerce adoption, especially when in tandem with technological opportunism. Altogether, the paper offers a preliminary scrutiny of the mechanics of ecommerce adoption in developing countries.
The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology

The human orbitofrontal cortex is an important brain region for the processing of rewards and punishments, which is a prerequisite for the complex and flexible emotional and social behaviour which contributes to the evolutionary success of humans. Yet much remains to be discovered about the functions of this key brain region, and new evidence from functional neuroimaging and clinical neuropsychology is affording new insights into the different functions of the human orbitofrontal cortex. We review the neuroanatomical and neuropsychological literature on the human orbitofrontal cortex, and propose two distinct trends of neural activity based on a meta-analysis of neuroimaging studies. One is a mediolateral distinction, whereby medial orbitofrontal cortex activity is related to monitoring the reward value of many different reinforcers, whereas lateral orbitofrontal cortex activity is related to the evaluation of punishers which may lead to a change in ongoing behaviour. The second is a posterior-anterior distinction with more complex or abstract reinforcers (such as monetary gain and loss) represented more anteriorly in the orbitofrontal cortex than simpler reinforcers such as taste or pain. Finally, we propose new neuroimaging methods for obtaining further evidence on the localisation of function in the human orbitofrontal cortex.
A Pragmatic Guide to Geoparsing Evaluation

Empirical methods in geoparsing have thus far lacked a standard evaluation framework describing the task, data and metrics used to establish state-of-the-art systems. Evaluation is further made inconsistent, even unrepresentative of real world usage, by the lack of distinction between the different types of toponyms, which necessitates new guidelines, a consolidation of metrics and a detailed toponym taxonomy with implications for Named Entity Recognition (NER). To address these deficiencies, our manuscript introduces such a framework in three parts. Part 1) Task Definition: clarified via corpus linguistic analysis proposing a fine-grained Pragmatic Taxonomy of Toponyms with new guidelines. Part 2) Evaluation Data: shared via a dataset called GeoWebNews to provide test/train data to enable immediate use of our contributions. In addition to fine-grained Geotagging and Toponym Resolution (Geocoding), this dataset is also suitable for prototyping machine learning NLP models. Part 3) Metrics: discussed and reviewed for a rigorous evaluation with appropriate recommendations for NER/Geoparsing practitioners. We gratefully acknowledge the funding support of the Natural Environment Research Council (NERC) PhD Studentship (Milan Gritta NE/M009009/1), EPSRC (Nigel Collier EP/M005089/1) and MRC (Mohammad Taher Pilehvar MR/M025160/1 for PheneBank). We also acknowledge Cambridge University linguists Mina Frost and Qianchu (Flora) Liu for providing expertise and verification (IAA) during dataset construction/annotation. Milan Gritta E-mail: mg711@cam.ac.uk Mohammad Taher Pilehvar E-mail: mp792@cam.ac.uk Nigel Collier E-mail: nhc30@cam.ac.uk Language Technology Lab (LTL) Department of Theoretical and Applied Linguistics (DTAL) University of Cambridge, 9 West Road, Cambridge CB3 9DP ar X iv :1 81 0. 12 36 8v 2 [ cs .C L ] 2 N ov 2 01 8 2 Milan Gritta et al.
Architecture of the Hyperledger Blockchain Fabric ∗

Overview. A blockchain is best understood in the model of state-machine replication , where a service maintains some state and clients invoke operations that transform the state and generate outputs. A blockchain emulates a “trusted” computing service through a distributed protocol, run by nodes connected over the Internet. The service represents or creates an asset, in which all nodes have some stake. The nodes share the common goal of running the service but do not necessarily trust each other for more. In a “permissionless” blockchain such as the one underlying the Bitcoin cryptocurrency, anyone can operate a node and participate through spending CPU cycles and demonstrating a “proof-of-work.” On the other hand, blockchains in the “permissioned” model control who participates in validation and in the protocol; these nodes typically have established identities and form a consortium. A report of Swanson compares the two models .
Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition

Humans can naturally understand an image in depth with the aid of rich knowledge accumulated from daily lives or professions. For example, to achieve fine-grained image recognition (e.g., categorizing hundreds of subordinate categories of birds) usually requires a comprehensive visual concept organization including category labels and part-level attributes. In this work, we investigate how to unify rich professional knowledge with deep neural network architectures and propose a Knowledge-Embedded Representation Learning (KERL) framework for handling the problem of fine-grained image recognition. Specifically, we organize the rich visual concepts in the form of knowledge graph and employ a Gated Graph Neural Network to propagate node message through the graph for generating the knowledge representation. By introducing a novel gated mechanism, our KERL framework incorporates this knowledge representation into the discriminative image feature learning, i.e., implicitly associating the specific attributes with the feature maps. Compared with existing methods of fine-grained image classification, our KERL framework has several appealing properties: i) The embedded high-level knowledge enhances the feature representation, thus facilitating distinguishing the subtle differences among subordinate categories. ii) Our framework can learn feature maps with a meaningful configuration that the highlighted regions finely accord with the nodes (specific attributes) of the knowledge graph. Extensive experiments on the widely used CaltechUCSD bird dataset demonstrate the superiority of ∗Corresponding author is Liang Lin
Adversarial Robustness Toolbox v0.2.2

Adversarial examples and poisoning attacks have become indisputable threats to the security of modern AI systems based on deep neural networks (DNNs). The Adversarial Robustness Toolbox (ART) is a Python library designed to support researchers and developers in creating novel defence techniques, as well as in deploying practical defences of real-world AI systems. Researchers can use ART to benchmark novel defences against the state-of-the-art. For developers, the library provides interfaces which support the composition of comprehensive defence systems using individual methods as building blocks. The Adversarial Robustness Toolbox supports machine learning models (and deep neural networks (DNNs) specifically) implemented in any of the most popular deep learning frameworks (TensorFlow, Keras, PyTorch and MXNet). Currently, the library is primarily intended to improve the adversarial robustness of visual recognition systems, however, future releases that will comprise adaptations to other data modes (such as speech, text or time series) are envisioned. The ART source code is released (https://github.com/IBM/ adversarial-robustness-toolbox) under an MIT license. The release includes code examples and extensive documentation (http://adversarial-robustness-toolbox.readthedocs.io) to help researchers and developers get quickly started. *maria-irina.nicolae@ibm.com †mathsinn@ie.ibm.com ‡Contributed to ART while doing an internship with IBM Research – Ireland. 1 ar X iv :1 80 7. 01 06 9v 3 [ cs .L G ] 1 1 Ja n 20 19
Automatic calibration for inertial measurement unit

The nine degrees-of-freedom (DOF) inertial measurement units (IMU) are generally composed of three kinds of sensor: accelerometer, gyroscope and magnetometer. The calibration of these sensor suites not only requires turn-table or purpose-built fixture, but also entails a complex and laborious procedure in data sampling. In this paper, we propose a method to calibrate a 9-DOF IMU by using a set of casually sampled raw sensor measurement. Our sampling procedure allows the sensor suite to move by hand and only requires about six minutes of fast and slow arbitrary rotations with intermittent pauses. It requires neither the specially-designed fixture and equipment, nor the strict sequences of sampling steps. At the core of our method are the techniques of data filtering and a hierarchical scheme for calibration. All the raw sensor measurements are preprocessed by a series of band-pass filters before use. And our calibration scheme makes use of the gravity and the ambient magnetic field as references, and hierarchically calibrates the sensor model parameters towards the minimization of the mis-alignment, scaling and bias errors. Moreover, the calibration steps are formulated as a series of function optimization problems and are solved by an evolutionary algorithm. Finally, the performance of our method is experimentally evaluated. The results show that our method can effectively calibrate the sensor model parameters from one set of raw sensor measurement, and yield consistent calibration results.
Intermediation and electronic markets: aggregation and pricing in Internet commerce

The Internet continues to grow as a medium to support commerce. Economic analysis of Internet commerce is still in a nascent stage while Internet technology and use has rapidly advanced. The result is an Internet marketplace brimming with entrepreneurs and major corporations experimenting with business strategies and technology advances even though the economics of Internet commerce is not well understood. This thesis responds to this need by exploring how the Internet reduces the market friction common in physical commerce. The intermediaries who help reduce market friction in physical markets may be eliminated, when suppliers and consumers increasingly rely on the Internet as a transaction medium. An intermediary in any market may reduce transaction costs by performing four roles: aggregation, pricing, search, and trust. The intermediary roles of aggregation and pricing may provide little or no value as the Internet becomes the medium for commerce because the technology, not the intermediary, reduces transaction costs. This thesis examines the possible elimination of aggregation and pricing intermediaries in Internet commerce. It does so by extending the theory of the economics of intermediation and electronic markets; developing a methodology for the analysis of Internet price competition; analyzing exploratory empirical data of the book, compact disc, and software markets to test a subset of this theory; and exploring the public policy implications of Internet price discrimination. The approach is interdisciplinary because this thesis integrates the technology, policy, and economics that underpin the role of aggregation and pricing intermediaries in Internet commerce. The thesis shows that Internet commerce may not reduce market friction because prices are higher when consumers buy homogeneous products on the Internet, and price dispersion for homogenous products among Internet retailers is greater than the price dispersion among physical retailers. Internet retailers—even those selling homogenous goods—can develop pricing strategies to differentiate themselves from their competitors and to price discriminate. The ability for the Internet to become a medium for price discrimination is an area that requires the attention of public policy makers. While self-regulation of Internet price discrimination may be the most appropriate policy, monitoring by the United States government through the Federal Trade Commission and international organizations such as the World Trade Organization helps establish a trusted transaction environment for future Internet commerce growth.  W. McKnight Lecturer, Technology and Policy Program Erik Brynjolfsson Associate Professor, MIT Sloan School of Management David D. Clark Senior Research Scientist, Laboratory for Computer Science
Cognitive impairment in adult ADHD--perspective matters!

The assessment of cognitive functions of adults with attention deficit hyperactivity disorder (ADHD) comprises self-ratings of cognitive functioning (subjective assessment) as well as psychometric testing (objective neuropsychological assessment). The aim of the present study was to explore the utility of these assessment strategies in predicting neuropsychological impairments of adults with ADHD as determined by both approaches.



Fifty-five adults with ADHD and 66 healthy participants were assessed with regard to cognitive functioning in several domains by employing subjective and objective measurement tools. Significance and effect sizes for differences between groups as well as the proportion of patients with impairments were analyzed. Furthermore, logistic regression analyses were carried out in order to explore the validity of subjective and objective cognitive measures in predicting cognitive impairments.



Both subjective and objective assessment tools revealed significant cognitive dysfunctions in adults with ADHD. The majority of patients displayed considerable impairments in all cognitive domains assessed. A comparison of effect sizes, however, showed larger dysfunctions in the subjective assessment than in the objective assessment. Furthermore, logistic regression models indicated that subjective cognitive complaints could not be predicted by objective measures of cognition and vice versa.



Subjective and objective assessment tools were found to be sensitive in revealing cognitive dysfunctions of adults with ADHD. Because of the weak association between subjective and objective measurements, it was concluded that subjective and objective measurements are both important for clinical practice but may provide distinct types of information and capture different aspects of functioning.
A Prospective Study to Compare Routine versus Need Based Change of IV Cannula on Development of Infusion Phlebitis in Adult Surgical Patients

(IV) Intravenous therapy is one of the most commonly performed procedures in hospitalized patients yet phlebitis affects 27% to 70% of all patients receiving IV therapy. The incidence of phlebitis has proved to be a menace in effective care of surgical patients, delaying their recovery and increasing duration of hospital stay and cost. The recommendations for reducing its incidence and severity have been varied and of questionable efficacy. The current study was undertaken to evaluate whether elective change of IV cannula at fixed intervals can have any impact on incidence or severity of phlebitis in surgical patients. All patients admitted to the Department of Surgery, SMIMS undergoing IV cannula insertion, fulfilling the selection criteria and willing to participate in the study, were segregated into two random groups prospectively: Group A wherein cannula was changed electively after 24 hours into a fresh vein preferably on the other upper limb and Group B wherein IV cannula was changed only on development of phlebitis or leak i.e. need-based change. The material/brand and protocol for insertion of IV cannula were standardised for all patients, including skin preparation, insertion, fixation and removal. After cannulation, assessment was made after 6 hours, 12 hours and every 24 hours thereafter at all venepuncture sites. VIP and VAS scales were used to record phlebitis and pain respectively. Upon analysis, though there was a lower VIP score in group A compared to group B (0.89 vs. 1.32), this difference was not statistically significant (p-value = 0.277). Furthermore, the differences in pain, as assessed by VAS, at the site of puncture and along the vein were statistically insignificant (p-value > 0.05). Our results are in contradiction to few other studies which recommend a policy of routine change of cannula. Further we advocate a close and thorough monitoring of the venepuncture site and the length of vein immediately distal to the puncture site, as well as a meticulous standardized protocol for IV access.
Sport-specific nutrition: practical strategies for team sports.

Implementation of a nutrition programme for team sports involves application of scientific research together with the social skills necessary to work with a sports medicine and coaching staff. Both field and court team sports are characterized by intermittent activity requiring a heavy reliance on dietary carbohydrate sources to maintain and replenish glycogen. Energy and substrate demands are high during pre-season training and matches, and moderate during training in the competitive season. Dietary planning must include enough carbohydrate on a moderate energy budget, while also meeting protein needs. Strength and power team sports require muscle-building programmes that must be accompanied by adequate nutrition, and simple anthropometric measurements can help the nutrition practitioner monitor and assess body composition periodically. Use of a body mass scale and a urine specific gravity refractometer can help identify athletes prone to dehydration. Sports beverages and caffeine are the most common supplements, while opinion on the practical effectiveness of creatine is divided. Late-maturing adolescent athletes become concerned about gaining size and muscle, and assessment of maturity status can be carried out with anthropometric procedures. An overriding consideration is that an individual approach is needed to meet each athlete's nutritional needs.
Noninvasive Brain–Computer Interfaces for Augmentative and Alternative Communication

Brain-computer interfaces (BCIs) promise to provide a novel access channel for assistive technologies, including augmentative and alternative communication (AAC) systems, to people with severe speech and physical impairments (SSPI). Research on the subject has been accelerating significantly in the last decade and the research community took great strides toward making BCI-AAC a practical reality to individuals with SSPI. Nevertheless, the end goal has still not been reached and there is much work to be done to produce real-world-worthy systems that can be comfortably, conveniently, and reliably used by individuals with SSPI with help from their families and care givers who will need to maintain, setup, and debug the systems at home. This paper reviews reports in the BCI field that aim at AAC as the application domain with a consideration on both technical and clinical aspects.