nils-herrmann/clean_scirepeval huggingface dataset:
Age diversity , age discrimination climate and performance consequences — a cross organizational study

This paper deals with the emergence of perceived age discrimination climate on the company level and its performance consequences. In this new approach to the field of diversity research, we investigated (a) the effect of organizational level age diversity on collective perceptions of age discrimination climate that (b) in turn should influence the collective affective commit ment of employees, which is (c) an important trigger for overall company performance. In a large scale study that included 128 companies, a total of 8,651 employees provided data on their perceptions of age discrimination and affective commitment on the company level. Information on firm level performance was collected from key informants. We tested the proposed model using structural equation modeling (SEM) procedures and, overall, found support for all hypothesized relationships. The findings demonstrated that age diversity seems to be related to the emergence of an age discrimination climate in companies, which negatively impacts overall firm performance through the mediation of affective commitment. These results make valuable contributions to the diversity and discrimination literature by establish ing perceived age discrimination on the company level as a decisive mediator in the age diversity/performance link. The results also suggest important practical implications for the effective management of an increasingly age diverse workforce.
A Brief History of Serious Games

Serious Games are now an established field of study. In this field most would attribute the rise of Serious Games to Clark C Abt’s creation of the term in 1970, or indeed Ben Sawyer’s popularization of it in 2002. However, consid‐ ering the rich history of purposing non-digital games, itself preceded by discus‐ sions of purposing play that are traceable to the work of Plato, it can be said that Serious Games is a contemporary manifestation of centuries old theories and practices. In this chapter, we explore the pre-history of Serious Games, beginning with the suggested purpose, and purposing of play. Throughout this historical review we identify key in research and practice that are apparent in the contem‐ porary Serious Games field.
Data Readiness Levels

Application of models to data is fraught. Data-generating collaborators often only have a very basic understanding of the complications of collating, processing and curating data. Challenges include: poor data collection practices, missing values, inconvenient storage mechanisms, intellectual property, security and privacy. All these aspects obstruct the sharing and interconnection of data, and the eventual interpretation of data through machine learning or other approaches. In project reporting, a major challenge is in encapsulating these problems and enabling goals to be built around the processing of data. Project overruns can occur due to failure to account for the amount of time required to curate and collate. But to understand these failures we need to have a common language for assessing the readiness of a particular data set. This position paper proposes the use of data readiness levels: it gives a rough outline of three stages of data preparedness and speculates on how formalisation of these levels into a common language for data readiness could facilitate project management.
Identifying emerging research fields: a longitudinal latent semantic keyword analysis

This study aims to gain insights into emerging research fields in the area of marketing and tourism. It provides support for the use of quantitative techniques to facilitate content analysis. The authors present a longitudinal latent semantic analysis of keywords. The proposed method is illustrated by two different examples: a scholarly journal (International Marketing Review) and conference proceedings (ENTER eTourism Conference). The methodology reveals an understanding of the current state of the art of marketing research and e-tourism by identifying neglected, popular or upcoming thematic research foci. The outcomes are compared with former results generated by traditional content analysis techniques. Findings confirm that the proposed methodology has the potential to complement qualitative content analysis, as the semantic analysis produces similar outcomes to qualitative content analysis to some extent. This paper reviews a journal’s content over a period of nearly three decades. The authors argue that the suggested methodology facilitates the analysis dramatically and can thus be simply applied on a regular basis in order to monitor topic development within a specific research domain.
SCADA system security: Complexity, history and new developments

Over the last decade, efforts from industries and research communities have been made in addressing the security of Supervisory Control and Data Acquisition (SCADA) systems. However, the SCADA security deployed for critical infrastructures is still a challenging issue today. This paper gives an overview of the complexity of SCADA security. Products and applications in control network security are reviewed. Furthermore, new developments in SCADA security, especially the trend in technical and theoretical studies are presented. Some important topics on SCADA security are identified and highlighted and this can be served as the guide for future works in this area.
Higher-order Coreference Resolution with Coarse-to-fine Inference

We introduce a fully differentiable approximation to higher-order inference for coreference resolution. Our approach uses the antecedent distribution from a span-ranking architecture as an attention mechanism to iteratively refine span representations. This enables the model to softly consider multiple hops in the predicted clusters. To alleviate the computational cost of this iterative process, we introduce a coarse-to-fine approach that incorporates a less accurate but more efficient bilinear factor, enabling more aggressive pruning without hurting accuracy. Compared to the existing state-of-the-art span-ranking approach, our model significantly improves accuracy on the English OntoNotes benchmark, while being far more computationally efficient.
Performance analysis of image segmentation for breast ultrasound images

Breast cancer is one of the main causes of women mortality worldwide. Ultrasonography (USG) is other modalities than mammography that capable to support radiologists in diagnosing breast cancer. However, the diagnosis may come with different interpretation depending on the radiologists experience. Therefore, Computer-Aided Diagnosis (CAD) is developed as a tool for radiologist's second opinion. CAD is built based on digital image processing of ultrasound (US) images which consists of several stages. Lesion segmentation is an important step in CAD system because it contains many important features for classification process related to lesion characteristics. This study provides a performance analysis and comparison of image segmentation for breast USG images. In this paper, several methods are presented such as a comprehensive comparison of adaptive thresholding, fuzzy C-Means (FCM), Fast Global Minimization for Active Contour (FGMAC) and Active Contours Without Edges (ACWE). The performance of these methods are evaluated with evaluation metrics Dice coefficient, Jaccard coefficient, FPR, FNR, Hausdorff distance, PSNR and MSSD parameters. Morphological operation is able to increase the performance of each segmentation methods. Overall, ACWE with morphological operation gives the best performance compare to the other methods with the similarity level of more than 90%.
L EARNING HOW TO EXPLAIN NEURAL NETWORKS : P ATTERN N ET AND P ATTERN A TTRIBUTION

DeConvNet, Guided BackProp, LRP, were invented to better understand deep neural networks. We show that these methods do not produce the theoretically correct explanation for a linear model. Yet they are used on multi-layer networks with millions of parameters. This is a cause for concern since linear models are simple neural networks. We argue that explanation methods for neural nets should work reliably in the limit of simplicity, the linear models. Based on our analysis of linear models we propose a generalization that yields two explanation techniques (PatternNet and PatternAttribution) that are theoretically sound for linear models and produce improved explanations for deep networks.
Improvements in Functional Safety of Automotive IP Through ISO 26262: 2018 Part 11

In early 2018, the second edition of ISO 26262:2018[1] automotive functional safety standard, is due for release. At the time of writing, the draft international standard (DIS) version is out for comment and review. One significant change over the original version of the ISO 26262:2011[2] standard is part 11, which brings detailed information to support semiconductor manufacturers develop ISO 26262 compliant intellectual property (IP). In the original version, information available to semiconductor companies was limited, this forthcoming release will bring significantly more information to support semiconductor and silicon IP suppliers. In the areas of digital and analogue components, programmable logic devices (PLD), multi-core processors and sensors. Tips, recommendations and practical examples are illustrated. However, there are certain areas that still not well represented, diagnostic coverage for analogue components for example is not defined in detail and there is a shortage of supporting information. Part 11 could also provide more worked examples to give design and functional safety teams a better insight into estimation techniques. The final draft international standard (FDIS) is due for publication in autumn 2017, and certain aspects of part 11 will be enhanced.
Palm oil versus hydrogenated soybean oil: effects on serum lipids and plasma haemostatic variables.

The purpose of this study was to test if replacement of trans fatty acids by palmitic acid in an experimental margarine results in unfavourable effects on serum lipids and haemostatic factors. We have compared the effects of three different margarines, one based on palm oil (PALM-margarine), one based on partially hydrogenated soybean oil (TRANS- margarine) and one with a high content of polyunsaturated fatty acids (PUFA-margarine), on serum lipids in 27 young women. In nine of the participants fasting levels and diurnal postprandial levels of haemostatic variables on the 3 diets were compared. The sum of 12:0, 14:0, 16:0 provided 11% of energy (E%) in the PALM diet, the same as the sum of 12:0, 14:0, 16:0 and trans fatty acids in the TRANS-diet. Oleic acid provided 10-11E% in all three diets, while PUFA provided 5.7, 5.5 and 10.2 E%, respectively. Total fat provided 30-31% and the test margarines 26% of total energy in all three diets. Each of the diets was consumed for 17 days in a crossover design. There were no significant differences in total cholesterol, LDL-cholesterol and apoB between the TRANS- and the PALM-diet. HDL-cholesterol and apoA-I were significantly higher on the PALM-diet compared to the TRANS-diet while the ratio of LDL- to HDL-cholesterol was lower, although not significantly (P = 0.077) on the PALM-diet. Total cholesterol, LDL-cholesterol and apoB were significantly lower on the PUFA-diet compared to the two other diets. HDL-cholesterol was not different on the PALM- and the PUFA-diet while it was significantly lower on the TRANS-diet compared to the PUFA-diet. Triglycerides and Lp(a) were not different among the three diets. The diurnal postprandial state level of tissue plasminogen activator (t-PA) activity was significantly decreased on the TRANS-diet compared to the PALM-diet. t-PA activity was also decreased on the PUFA-diet compared to PALM-diet although not significantly (P=0.07). There were no significant differences in neither fasting levels or in circadian variation of t-PA antigen, PAI-1 activity, PAI-1 antigen, factor VII coagulant activity or fibrinogen between the three diets. Our results suggest that dietary palm oil may have a more favourable effect on the fibrinolytic system compared to partially hydrogenated soybean oil. We conclude that from a nutritional point of view, palmitic acid from palm oil may be a reasonable alternative to trans fatty acids from partially hydrogenated soybean oil in margarine if the aim is to avoid trans fatty acids. A palm oil based margarine is, however, less favourable than one based on a more polyunsaturated vegetable oil.
Compact UHF RFID Handheld Reader Antenna and Array Based on Resonant Quadrifilar Spiral Structure

In this paper, a compact circularly polarized antenna based on a resonant quadrifilar spiral structure for the application of UHF RFID handheld reader is proposed and demonstrated experimentally. To reduce antenna size and improve impedance matching, the original resonant arms are revised by bending inverted-F structures and printing them on dielectric substrates, and the four arms are fed by a four-way phase shift network. Such an antenna indicates stable circular polarization performance and wide beamwidth. The gain bandwidth (> 2 dBic) can cover the frequency band from 902 MHz to 928 MHz, which is suitable for most of the popular UHF RFID systems in the world. Moreover, the 1×4 array and 2×2 array based on previously demonstrated antenna unit are numerically investigated. The array performances, including the gain, beam scanning and low side-lobe are discussed.
Scaffolding Deep Comprehension Strategies Through Point & Query , AutoTutor , and iSTART

It is well-documented that most students do not have adequate proficiencies in inquiry and metacognition, particularly at deeper levels of comprehension that require explanatory reasoning. The proficiencies are not routinely provided by teachers and normal tutors so it is worthwhile to turn to computer-based learning environments. This article describes some of our recent computer systems that were designed to facilitate explanation-centered learning through strategies of inquiry and metacognition while students learn science and technology content. Point&Query augments hypertext, hypermedia, and other learning environments with question–answer facilities that are under the learner control. AutoTutor and iSTART use animated conversational agents to scaffold strategies of inquiry, metacognition, and explanation construction. AutoTutor coaches students in generating answers to questions that require explanations (e.g., why, what-if, how) by holding a mixed-initiative dialogue in natural language. iSTART models and coaches students in constructing self-explanations and in applying other metacomprehension strategies while reading text. These systems have shown promising results in tests of learning gains and learning strategies.
The Omniglot Challenge: A 3-Year Progress Report

Three years ago, we released the Omniglot dataset for developing more human-like learning algorithms. Omniglot is a one-shot learning challenge, inspired by how people can learn a new concept from just one or a few examples. Along with the dataset, we proposed a suite of five challenge tasks and a computational model based on probabilistic program induction that addresses them. The computational model, although powerful, was not meant to be the final word on Omniglot; we hoped that the machine learning community would both build on our work and develop novel approaches to tackling the challenge. In the time since, we have been pleased to see the wide adoption of Omniglot and notable technical progress. There has been genuine progress on one-shot classification, but it has been difficult to measure since researchers have adopted different splits and training procedures that make the task easier. The other four tasks, while essential components of human conceptual understanding, have received considerably less attention. We review the progress so far and conclude that neural networks are still far from human-like concept learning on Omniglot, a challenge that requires performing all of the tasks with a single model. We also discuss new tasks to stimulate further progress.
PATTERN GENERATION FOR TWO-DIMENSIONAL CUTTING STOCK PROBLEM WITH LOCATION

Selection of feasible cutting patterns in order to minimize the raw material wastage which is known as cutting stock problem has become a key factor of the success in today’s competitive manufacturing industries. In this paper, solving a rectangular shape medium size two-dimensional cutting stock problem is discussed. Our study is restricted to raw materials (main sheets) in a rectangular shape with fixed sizes, and cutting items are also considered as rectangular shape with known dimensions and location of each feasible cutting pattern inside the main sheet is given in Cartesian Coordinate Plane. The Branch and Bound approach in solving integer programming problems is used to solve the problem.
DT_Team at SemEval-2017 Task 1: Semantic Similarity Using Alignments, Sentence-Level Embeddings and Gaussian Mixture Model Output

We describe our system (DT Team) submitted at SemEval-2017 Task 1, Semantic Textual Similarity (STS) challenge for English (Track 5). We developed three different models with various features including similarity scores calculated using word and chunk alignments, word/sentence embeddings, and Gaussian Mixture Model (GMM). The correlation between our system’s output and the human judgments were up to 0.8536, which is more than 10% above baseline, and almost as good as the best performing system which was at 0.8547 correlation (the difference is just about 0.1%). Also, our system produced leading results when evaluated with a separate STS benchmark dataset. The word alignment and sentence embeddings based features were found to be very effective.
Soil beneficial bacteria and their role in plant growth promotion: a review

Soil bacteria are very important in biogeochemical cycles and have been used for crop production for decades. Plant–bacterial interactions in the rhizosphere are the determinants of plant health and soil fertility. Free-living soil bacteria beneficial to plant growth, usually referred to as plant growth promoting rhizobacteria (PGPR), are capable of promoting plant growth by colonizing the plant root. PGPR are also termed plant health promoting rhizobacteria (PHPR) or nodule promoting rhizobacteria (NPR). These are associated with the rhizosphere, which is an important soil ecological environment for plant–microbe interactions. Symbiotic nitrogen-fixing bacteria include the cyanobacteria of the genera Rhizobium, Bradyrhizobium, Azorhizobium, Allorhizobium, Sinorhizobium and Mesorhizobium. Free-living nitrogen-fixing bacteria or associative nitrogen fixers, for example bacteria belonging to the species Azospirillum, Enterobacter, Klebsiella and Pseudomonas, have been shown to attach to the root and efficiently colonize root surfaces. PGPR have the potential to contribute to sustainable plant growth promotion. Generally, PGPR function in three different ways: synthesizing particular compounds for the plants, facilitating the uptake of certain nutrients from the soil, and lessening or preventing the plants from diseases. Plant growth promotion and development can be facilitated both directly and indirectly. Indirect plant growth promotion includes the prevention of the deleterious effects of phytopathogenic organisms. This can be achieved by the production of siderophores, i.e. small metal-binding molecules. Biological control of soil-borne plant pathogens and the synthesis of antibiotics have also been reported in several bacterial species. Another mechanism by which PGPR can inhibit phytopathogens is the production of hydrogen cyanide (HCN) and/or fungal cell wall degrading enzymes, e.g., chitinase and ß-1,3-glucanase. Direct plant growth promotion includes symbiotic and non-symbiotic PGPR which function through production of plant hormones such as auxins, cytokinins, gibberellins, ethylene and abscisic acid. Production of indole-3-ethanol or indole-3-acetic acid (IAA), the compounds belonging to auxins, have been reported for several bacterial genera. Some PGPR function as a sink for 1-aminocyclopropane-1-carboxylate (ACC), the immediate precursor of ethylene in higher plants, by hydrolyzing it into α-ketobutyrate and ammonia, and in this way promote root growth by lowering indigenous ethylene levels in the micro-rhizo environment. PGPR also help in solubilization of mineral phosphates and other nutrients, enhance resistance to stress, stabilize soil aggregates, and improve soil structure and organic matter content. PGPR retain more soil organic N, and other nutrients in the plant–soil system, thus reducing the need for fertilizer N and P and enhancing release of the nutrients.
Integrating Blockchain with ERP for a Transparent Supply Chain

Supply chain is complex today. Multi-echelon, highly disjointed, and geographically spread are some of the cornerstones of today’s supply chain. All these together with different governmental policies and human behavior make it almost impossible to probe incidents and trace events in case of supply chain disruptions. In effect, an end-to-end supply chain, from the most basic raw material to the final product in a customer’s possession, is opaque. The inherent cost involved in managing supply chain intermediaries, their reliability, traceability, and transparency further complicate the supply chain. The solution to such complicated problems lies in improving supply chain transparency. This is now possible with the concept of blockchain. The usage of blockchain in a financial transaction is well known. This paper reviews blockchain technology, which is changing the face of supply chain and bringing in transparency and authenticity. This paper first discusses the history and evolution of blockchain from the bitcoin network, and goes on to explore the protocols. The author takes a deep dive into the design of blockchain, exploring its five pillars and three-layered architecture, which enables most of the blockchains today. With the architecture, the author focuses on the applications, use cases, road map, and challenges for blockchain in the supply chain domain as well as the synergy of blockchain with enterprise applications. It analyzes the integration of the enterprise resource planning (ERP) system of the supply chain domain with blockchain. It also explores the three distinct growth areas: ERP-blockchain supply chain use cases, the middleware for connecting the blockchain with ERP, and blockchain as a service (BaaS). The paper ends with a brief conclusion and a discussion.
Planning walking patterns for a biped robot

Biped robots have better mobility than conventional wheeled robots, but they tend to tip over easily. To be able to walk stably in various environments, such as on rough terrain, up and down slopes, or in regions containing obstacles, it is necessary for the robot to adapt to the ground conditions with a foot motion, and maintain its stability with a torso motion. When the ground conditions and stability constraint are satisfied, it is desirable to select a walking pattern that requires small torque and velocity of the joint actuators. In this paper, we first formulate the constraints of the foot motion parameters. By varying the values of the constraint parameters, we can produce different types of foot motion to adapt to ground conditions. We then propose a method for formulating the problem of the smooth hip motion with the largest stability margin using only two parameters, and derive the hip trajectory by iterative computation. Finally, the correlation between the actuator specifications and the walking patterns is described through simulation studies, and the effectiveness of the proposed methods is confirmed by simulation examples and experimental results.