nils-herrmann/clean_scirepeval huggingface dataset:
SCAFFOLDING PARENTS TO ACCEPT ADULT CHILDREN'S INTERVENTION
Venue: Innovation in Aging
Year: 2019

Guided by social cognitive domain specific theory (Smetana, 1997) this study explored the issue of role reversal in the aging parent adult child relation when parents are experiencing age related functional limitations. Data was collected from adult children (N=16, Mage=53.06, SD=6.08) with a living parent of 70 years old or older who participated in a focus group and were analyzed by a directed analysis (Potter Levine Donnerstein, 1999) Participants legitimated their intervention into parents' autonomy when they perceived a potential risk of parents' health and safety and involvement of those and of others. Eight types of intervention emerged: (1) monitoring and talking with potential risk with parent (2) convincing parents under the name of super power or an authority figure (3) scaffolding parent's task by teaching skills, (4) scaffolding by sharing role, (5) scaffolding by optimizing environment, (5) overriding parents' autonomy behind parents, (6) forcefully overriding, (7) giving up parents' behavioral modification by accepting parents' lifestyle, and (8) giving up because of discomfort of talking about the issue (i.e. potential risks of parent's sexual intercourse, parents' death preparation) Thus, adult children changed their strategies of intervention from monitoring their parents' behaviors to overriding parents' autonomy, depending on their appraisal of potential harms of parents' prudential and moral domains of life and of their own work/family conditions from monitoring to overriding. Adult children's possible ways of scaffolding in helping their parents accept their children's interventions as letting parents maintain their psychological autonomy, including communication skills to discuss uncomfortable topics is discussed.
Demonstration of Asymmetric Wavelength Selective Switch Based on LCoS SLM for Optical Access Network
Venue: 2019 21st International Conference on Transparent Optical Networks (ICTON)
Year: 2019

In this research, an asymmetric wavelength selective switch (WSS) based on 4 by 16 switching architecture using Liquid Crystal on Silicon (LCoS) Spatial Light Modulator (SLM) which offers simultaneously multicast transmission and power equalization, for application in optical access network is reported and experimentally demonstrated. A dynamic spectrum equalizer through the design of LCoS SLM was proposed to improve the power uniformity of transmitted wavelengths, and the system multicast transmission was achieved through an efficient design of computer generated holograms based on GS algorithm. According to the experimental measurements, the system light loss of the switching system were analyzed and the results shown that depending on different wavelength selection scenario with/without multicast transmissions, the switching system has a light loss of 21 dB 26 dB and the crosstalk were measured to be less than 30 dB. Digital transmission tests were performed at a data transmission rate beyond 2.5 Gbps and the performance evaluation of each wavelength received at the output fiber ports of the switching system estimated from the measured Q factor of eye diagrams were all regarded as error free.
Classification Preprocessing IC Topics As Keywords Federated IC Search Engine Enterprise Information Repository Internet Custom Search Semantic
Year: 2015

One of the greatest challenges of an enterprise's service center is to ensure that their engineers and customers are provided with the right information in a timely fashion. For this purpose, modern organizations operate a wide range of information support systems to assist customers with critical service requests and to provide proactive monitoring, where possible, to prevent service requests from occurring in the first place. It is often the case that relevant information is scattered over the Internet and/or maintained on disparate systems, buried in large amount of noisy data, and in heterogeneous formats, thereby complicating the access to reusable knowledge and extending the response time to reach a resolution. To address these challenges, in this paper we propose an effective knowledge mining solution to improve the quality of service request resolution. We model the service resolution problem as an online search and classification problem, and use domain knowledge in the form of ontology to guide effective machine learning. Our proposed solution has been extensively evaluated with experiments and has been used in a real enterprise customer center.
Effects of micronized and nano copper azole on marine benthic communities.
Venue: Environmental toxicology and chemistry
Year: 2018

The widespread use of copper nanomaterials (CuNMs) as antibacterial and antifouling agents in consumer products increases the risk for metal contamination and adverse effects in aquatic environments. Information gaps exist on the potential toxicity of CuNMs in marine environments. We exposed field collected marine meio and macrobenthic communities to sediments spiked with micronized copper azole (MCA) using a novel method that brings intact benthic cores into the laboratory and exposes the organisms via surface application of sediments. Treatments included field and laboratory controls, 3 spiked sediments: low MCA (51.9 mg/kg sediment) high MCA (519 mg/kg sediment) and CuSO4 (519 mg/kg sediment) In addition, single species acute testing was performed with both MCA and CuSO4. Our results indicate that meio and macrofaunal assemblages exposed to High MCA and CuSO4 treatments differed significantly from both the laboratory control and the low MCA treatments. Differences in macrofauna were driven by decreases in 3 Podocopa ostracod species, the bivalve Gemma gemma, and the polychaetes Exogone verugera and Prionospio heterobranchia relative to the laboratory control. Differences in the meiofaunal community are largely driven by nematodes. The benthic community test results were more sensitive than the single species test results. Findings of this investigation indicate that CuNMs represent a source of risk to marine benthic communities comparable to that of dissolved Cu.
The study of relationship between intellectual capital and its growth rate with earning management in accepted companies in Tehran Stock Exchange
Year: 2014

Since the intellectual capital provide a new and perfect model to observation of organizations real value, therefore, the tendency to evaluation of intangible assets true value of intellectual capital has increased in companies, shareholders (investors) and other stakeholders. This study investigates the relationship between the intellectual capital and its growth rate with earning management in accepted companies in the Tehran Stock Exchange. The statistical society of study includes all Tehran Stock Exchange firms after put of certain conditions sampling was undertaken. Finally, during the period 2006 to 2013, 121 companies selected.The methodology of research is descriptive. Using a modified Jones discretionary accruals calculated as a measure to detect earnings management and then placed in the regression model defined earnings management, Hypotheses were tested. With the use of regression analysis the research hypotheses have been carried out. Also a number of control variables consist of Size and M/B have been used. The results of this study show that there is a significant relationship between intellectual capital and earnings management but there is a significant relationship between intellectual capital growth and earnings management.
Learning Disentangled Semantic Representation for Domain Adaptation
Venue: IJCAI
Year: 2019

Domain adaptation is an important but challenging task. Most of the existing domain adaptation methods struggle to extract the domain invariant representation on the feature space with entangling domain information and semantic information. Different from previous efforts on the entangled feature space, we aim to extract the domain invariant semantic information in the latent disentangled semantic representation (DSR) of the data. In DSR, we assume the data generation process is controlled by two independent sets of variables, i.e. the semantic latent variables and the domain latent variables. Under the above assumption, we employ a variational auto encoder to reconstruct the semantic latent variables and domain latent variables behind the data. We further devise a dual adversarial network to disentangle these two sets of reconstructed latent variables. The disentangled semantic latent variables are finally adapted across the domains. Experimental studies testify that our model yields state of the art performance on several domain adaptation benchmark datasets.
An exploration of the strategic antecedents of firm supply chain agility: The role of a firm's orientations
Year: 2016

Agility has been identified as one of the most salient issues of contemporary supply chain management (Lee, 2004) Despite its importance, there has been limited theory development in supply chain agility at the firm level. The antecedents of firm supply chain agility are understood even less as they have been primarily addressed at an operational level. Gligor and Holcomb (2012b) emphasized that more research is needed to identify the firm supply chain agility strategic level antecedents. Gligor et al. (2015) specifically called for future research to investigate the role of market orientation and supply chain orientation in achieving supply chain agility. We address this call and expand on the work of Braunscheidel and Suresh (2009) who explored the role of different managerial orientations in achieving supply chain agility. The current research hypothesizes that market orientation has a direct impact on firm supply chain agility. Further, it is not enough to be market oriented to achieve a high level of supply chain agility; rather, a supply chain orientation also needs to be developed. In order to increase the explanatory power of our model we account for the impact of environmental uncertainty (Dess and Beard, 1984) Important theoretical and managerial implications are put forth as well.
A novel feature subspace selection method in random forests for high dimensional data
Venue: 2016 International Joint Conference on Neural Networks (IJCNN)
Year: 2016

Random forests are a class of ensemble methods for classification and regression with randomizing mechanism in bagging instances and selecting feature subspace. For high dimensional data, the performance of random forests degenerates because of the random sampling feature subspace for each node in the construction of decision trees. To address the issue, in this paper, we propose a new Principal Component Analysis and Stratified Sampling based method, called PCA SS, for feature subspace selection in random forests with high dimensional data. For each decision tree in the forests, we firstly create the training data by bagging instances and partition the feature set into several feature subsets. Principal Component Analysis (PCA) is applied on each feature subset to obtain transformed features. All the principal components are retained in order to preserve the variability information of the data. Secondly, depending on a certain principal components principle, the transformed features are partitioned into informative and less informative parts. When constructing each node of decision trees, a feature subspace is selected by stratified sampling method from the two parts. The PCA SS based Random Forests algorithm, named PSRF, ensures enough informative features for each tree node, and it also increases the diversity between the trees to a certain extent. Experimental results demonstrate that the proposed PSRF significantly improves the performance of random forests when dealing with high dimensional data, compared with the state of the art random forests algorithms.
Deep Architecture for High Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning
Venue: IEEE Transactions on Instrumentation and Measurement
Year: 2019

The insulator is an important catenary component that maintains the insulation between the catenary and earth. Due to the long term impact of railway vehicles and the environment, defects in the insulator are inevitable. Recently, automatic catenary inspection using computer vision and pattern recognition has been introduced to improve the safety of railway operation. However, achieving full automation of insulator defect detection is still very challenging due to the visual complexity of defects and the small number of defective insulators. To overcome these problems, this paper proposes a novel insulator surface defect detection system using a deep convolutional neural network (CNN) The proposed system consists of two stages. First, a Faster R CNN network is adopted to localize the key catenary components, and the image areas that contain the insulators are obtained. Then, the classification score and anomaly score are determined from a deep multitask neural network that is composed of a deep material classifier and a deep denoising autoencoder. The defect state is determined by analyzing the classification score and anomaly score. Experiments of the catenary insulator defect detection along the Hefei Fuzhou high speed railway line indicate that the system can achieve high detection accuracy.
Optimasi Sistem Pembangkit Listrik Tenaga Angin Dan Pembangkit Listrik Tenaga Diesel Berbasis Fuzzy Logic
Venue: PROtek Jurnal Ilmiah Teknik Elektro
Year: 2019

Penelitian ini bertujuan untuk mengetahui potensi energi angin di Kabupaten Pangkep, kapasitas daya yang mampu tenaga angin, simulasi logika Fuzzy sistem hibrida dalam melayani beban, dan mengetahui sistem operasi ekonomis Hybrid Wind Power dan Solar Power. Untuk mengetahui kapasitas daya mampu kemudian melakukan tes dengan memberikan beban mulai dari beban rendah, menengah, dan tinggi pada angin pembangkit listrik simulasi fuzzy logic. digunakan untuk sistem Hybrid menggabungkan tenaga angin dan Genset dalam sistem bekerja sama dalam pelayanan beban. Sedangkan hasil perhitungan harga ekonomis kWh yang diperoleh pada sistem hibrida tenaga angin dan tenaga diesel Rp 2.076/kWh lebih mahal daripada harga tenaga angin Rp 773/kWh tapi lebih murah dibanding rupiah. Genset 2240/kWh. Dengan kombinasi sistem hibrida angin powerand diesel Power maka dapat mengurangi biaya operasi, yaitu bahan bakar selain mampu memberikan pasokan tenaga listrik yang berkesinambungan
Ding Editionen. Vom archaologischen (Be )Fund ubers Corpus ins Netz
Year: 2019

Corpora, thing editions, are a central epistemic instrument of knowledge generation for archaeology. Due to digitisation attention has turned once more to various strategies and the politics of representation, and in the course of the debate on (post )factualism and cultures of knowledge and data we are striving to render the production of knowledge more visible and comprehensible. Following B. Latour's concept of circulating reference, editions are products of a praxeological connection between the world and representations. This is a report on the ongoing discussion of central questions and objectives for digital corpora and research data management following the FAIR (findable, accessible, inter operable, re usable) principle.
The role of radio frequency identification (RFID) technologies in improving garment manufacturing operations
Year: 2014

A growing number of organisations are using radio frequency identification (RFID) technology to improve their manufacturing processes. A case study approach is used to explore the development of an RFID based manufacturing process management system in a garment factory in China. The results indicate that both technology push and need pull factors influence the garment factory's intention to adopt RFID technology. We identify eight factors for the successful implementation of an RFID based manufacturing process management system, namely, vendor selection, organisational motivation, cost/benefit evaluation, top management support, user involvement, the extent of progress supervision, staff competence and training, and policy, structure and operating process compatibility. This in depth case study details the organisation's experience and identifies the challenges it faces and important issues in the development and implementation of the system. Implications for academics and practitioners are discussed.
BanglaLekha Isolated: A multi purpose comprehensive dataset of Handwritten Bangla Isolated characters
Venue: Data in brief
Year: 2017

BanglaLekha Isolated, a Bangla handwritten isolated character dataset is presented in this article. This dataset contains 84 different characters comprising of 50 Bangla basic characters, 10 Bangla numerals and 24 selected compound characters. 2000 handwriting samples for each of the 84 characters were collected, digitized and pre processed. After discarding mistakes and scribbles, 1,66,105 handwritten character images were included in the final dataset. The dataset also includes labels indicating the age and the gender of the subjects from whom the samples were collected. This dataset could be used not only for optical handwriting recognition research but also to explore the influence of gender and age on handwriting. The dataset is publicly available at https:/data.mendeley.com/datasets/hf6sf8zrkc/2.
Sex/Gender Differences and Autism: Setting the Scene for Future Research
Venue: Journal of the American Academy of Child and Adolescent Psychiatry
Year: 2015

The relationship between sex/gender differences and autism has attracted a variety of research ranging from clinical and neurobiological to etiological, stimulated by the male bias in autism prevalence. Findings are complex and do not always relate to each other in a straightforward manner. Distinct but interlinked questions on the relationship between sex/gender differences and autism remain underaddressed. To better understand the implications from existing research and to help design future studies, we propose a 4 level conceptual framework to clarify the embedded themes.  We searched PubMed for publications before September 2014 using search terms "'sex OR gender OR females' AND autism." A total of 1,906 articles were screened for relevance, along with publications identified via additional literature reviews, resulting in 329 articles that were reviewed.  1, "Nosological and diagnostic challenges," concerns the question, "How should autism be defined and diagnosed in males and females?" Level 2, "Sex/gender independent and sex/gender dependent characteristics," addresses the question, "What are the similarities and differences between males and females with autism?" Level 3, "General models of etiology: liability and threshold," asks the question, "How is the liability for developing autism linked to sex/gender?" Level 4, "Specific etiological developmental mechanisms," focuses on the question, "What etiological developmental mechanisms of autism are implicated by sex/gender and/or sexual/gender differentiation?"  Using this conceptual framework, findings can be more clearly summarized, and the implications of the links between findings from different levels can become clearer. Based on this 4 level framework, we suggest future research directions, methodology, and specific topics in sex/gender differences and autism.
Understanding e Justice and Open Justice Through the Assessment of Judicial Websites: Toward a Conceptual Framework
Year: 2020

The pressure to adopt information technologies has clearly reached the judicial branch of government. General trends toward greater transparency and more openness in the public sector have pushed judges, ministers, and lawyers to use emergent technologies and to provide more information online. In fact, judicial agencies have created their own websites with diverse levels of technological sophistication and functionality, often with the intention of opening their processes and interacting with multiple stakeholders. In contrast to the executive branch, however, little is known about the structure, usability, content, and impacts of these websites. There is also no clear understanding of how judicial websites could be used to better understand and assess electronic justice and open justice efforts. Using a longitudinal mixed method research design, this study analyzes the functionality of judicial websites and proposes a comprehensive assessment framework that not only evaluates the availability of information but also the participatory mechanisms related to e justice and open justice. We started with an exploratory research project, followed by a pilot evaluation, and ended with an assessment of the 32 state judicial websites in Mexico in 2014 and 2016. Based on the results of these empirical efforts, this article proposes a framework to understand e justice and open justice through the assessment of judicial websites.
Modeling confidence judgments, response times, and multiple choices in decision making: recognition memory and motion discrimination.
Venue: Psychological review
Year: 2013

Confidence in judgments is a fundamental aspect of decision making, and tasks that collect confidence judgments are an instantiation of multiple choice decision making. We present a model for confidence judgments in recognition memory tasks that uses a multiple choice diffusion decision process with separate accumulators of evidence for the different confidence choices. The accumulator that first reaches its decision boundary determines which choice is made. Five algorithms for accumulating evidence were compared, and one of them produced proportions of responses for each of the choices and full response time distributions for each choice that closely matched empirical data. With this algorithm, an increase in the evidence in one accumulator is accompanied by a decrease in the others so that the total amount of evidence in the system is constant. Application of the model to the data from an earlier experiment (Ratcliff, McKoon, Tindall, 1994) uncovered a relationship between the shapes of z transformed receiver operating characteristics and the behavior of response time distributions. Both are explained in the model by the behavior of the decision boundaries. For generality, we also applied the decision model to a 3 choice motion discrimination task and found it accounted for data better than a competing class of models. The confidence model presents a coherent account of confidence judgments and response time that cannot be explained with currently popular signal detection theory analyses or dual process models of recognition.
CuSAPO 5Fen Zi Shai De He Cheng Biao Zheng Ji Dui Jia Ben Xi Fu Xing Neng
Year: 2016

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