nils-herrmann/clean_scirepeval huggingface dataset:
Performance Characterization of DNN Training using TensorFlow and PyTorch on Modern Clusters
Venue: 2019 IEEE International Conference on Cluster Computing (CLUSTER)
Year: 2019

The recent surge of Deep Learning (DL) models and applications can be attributed to the rise in computational resources, availability of large scale datasets, and accessible DL frameworks such as TensorFlow and PyTorch. Because these frameworks have been heavily optimized for NVIDIA GPUs, several performance characterization studies exist for GPU based Deep Neural Network (DNN) training. However, there exist very few research studies that focus on CPU based DNN training. In this paper, we provide an in depth performance characterization of state of the art DNNs such as ResNet(s) and Inception v3/v4 on multiple CPU architectures including Intel Xeon Broadwell, three variants of the Intel Xeon Skylake, AMD EPYC, and NVIDIA GPUs like K80, P100, and V100. We provide three key insights: 1) Multi process (MP) training should be used even for a single node, because the single process (SP) approach cannot fully exploit all the cores, 2) Performance of both SP and MP depend on various features such as the number of cores, the processes per node (ppn) and DNN architecture, and 3) There is a non linear and complex relationship between CPU/system characteristics (core count, ppn, hyper threading, etc) and DNN specifications such as inherent parallelism between layers. We further provide a comparative analysis for CPU and GPU based training and profiling analysis for Horovod. The fastest Skylake we had access to is up to 2.35x better than a K80 GPU but up to 3.32x slower than a V100 GPU. For ResNet 152 training, we observed that MP is up to 1.47x faster than SP and achieves 125x speedup on 128 Skylake nodes.
Photodegradation performance of g C3N4 fabricated by directly heating melamine.
Venue: Langmuir the ACS journal of surfaces and colloids
Year: 2009

The g C(3)N(4) photocatalyst was synthesized by directly heating the low cost melamine. The methyl orange dye (MO) was selected as a photodegrading goal to evaluate the photocatalytic activity of as prepared g C(3)N(4) The comparison experiments indicate that the photocatalytic activity of g C(3)N(4) can be largely improved by the Ag loading. The strong acid radical ion (SO(4)(2 or NO(3) can promote the degrading rate of MO for g C(3)N(4) photocatalysis system. The MO degradation over the g C(3)N(4) is mainly attributed to the photoreduction process induced by the photogenerated electrons. Our results clearly indicate that the metal free g C(3)N(4) has good performance in photodegradation of organic pollutant.
Rigorous analysis of Pareto fronts in sustainability studies based on bilevel optimization: Application to the redesign of the UK electricity mix
Year: 2017

Multi objective optimization (MOO) is at present widely used in the design and planning of sustainable systems where economic, environmental and social aspects must be considered simultaneously. The solution of a multi objective model is given by a set of Pareto optimal points that feature the property that they cannot be improved in one objective without necessarily worsening at least another one. Identifying the best Pareto solution from this set is challenging, particularly when many objectives and decision makers are involved in the analysis. In this work, we propose the first rigorous method (to the authors' knowledge) based on bilevel optimization to explore Pareto points that allows to: (i) identify in a systematic manner non dominated solutions which are particularly appealing for decision makers; (ii) quantify the distance between any (suboptimal) feasible point of a MOO model and its Pareto front (i.e. project suboptimal points onto the Pareto frontier) and (iii) establish improvement targets for suboptimal solutions of a MOO (through projection onto the Pareto front) that if attained would make them optimal. Overall, our method allows analysing Pareto fronts and selecting a final Pareto point to be implemented in practice without the need to define subjective weights in an explicit manner. We illustrate the capabilities of our approach through its application to the optimization of the UK electricity mix according to several economic, environmental and social indicators.
An Enterprise Control Methodology for the Techno Economic Assessment of the Energy Water Nexus
Venue: ArXiv
Year: 2019

In recent years, the energy water nexus literature has recognized that the electricity and water infrastructure that enable the production, distribution, and consumption of these two commodities is fundamentally intertwined. Electric power is used to produce, treat, distribute, and recycle water while water is used to generate and consume electricity. In the meantime, significant attention has been given to renewable energy integration within the context of global climate change. While these two issues may seem unrelated, their resolution is potentially synergistic in that renewable energy technologies not only present low CO2 emissions but also low water intensities. Furthermore, because water is readily stored, it has the potential to act as a flexible energy resource on both the supply and the demand side of the electricity grid. Despite these synergies, the renewable energy integration and energy water nexus literature have yet to methodologically converge to systematically address potential synergies. This paper advances an enterprise control methodology as a means of assessing the techno economic performance of the energy water nexus. The enterprise control methodology has been developed in recent years to advance the methodological state of the art of renewable energy integration studies and used recently to carry out a full scale study for the Independent System Operator (ISO) New England system. The methodology quantifies day ahead and real time energy market production costs, dispatched energy mixes, required operating reserves, levels of curtailment, and grid imbalances. This energy water nexus methodological extension now includes flexible water energy resources within the grid's energy resource portfolio and quantifies the amounts of water withdrawn and consumed. The simulation methodology is demonstrated on a modified version of the RTS 96 (RTS GMLC) test case.
Black Women and the Media in Britain
Year: 2020

This chapter outlines media developments and key matters concerning the on screen depiction of Black women in Britain in recent decades. It draws on material accessed at the Black Cultural Archives (BCA) in Brixton, London and the Spare Rib digital archive at the British Library. This chapter discusses self representing and organising in relation to Black women and the media. The discussion explores the politics of representation in connection with superficiality, conceptualisations of Black women's media experiences and television representations, as well as the influence of variations regarding regionality and rurality. This chapter emphasises that due to the geo culturally and socio politically specific setting of Britain and its consititutive nations work focused on the lives of Black women (t)here demands a critical lens that is sensitive to this context's various characteristics.
The Impact of Product Portfolio Strategy on Financial Performance: The Roles of Product Development and Market Entry Decisions
Year: 2014

Innovation is one of the most important issues facing business today. The major difficulty in managing innovation is that managers must do so against a constantly shifting backdrop as technologies, competitors, and markets constantly evolve. Managers determine the product portfolio through key decisions about product development and market entry. Key strategic questions are what portfolio strategies provide the greatest reward. The purpose of this study is to understand the relative financial values of each component of a product portfolio. Specifically, the paper examines the short term and long term financial impacts of product development strategy and market entry strategy. These strategies reflect two critical tensions that must be balanced in product portfolio decision making and essentially determine a firm's product portfolio. In doing so, the paper also investigates how a firm's capabilities drive each component of a product portfolio. From the empirical analyses in the context of the biomedical device industry, the paper found important insights regarding product portfolio strategies. First, a large product portfolio helps a firm's financial performance. In particular, the pioneering new products have strongest impacts on short term performances, and nonpioneering mature products do not provide significant contribution. Second, the results indicate a persistent first mover advantage. The first to market new products yield not only an immediate effect, but also persistent long term effects, suggesting that it is important to be first in the market even though there may be short term losses. Third, the results suggest the need to balance between "mature" and "new" products. Also, firms need to balance "first to market" and "late entered" products. Because a new or pioneering product requires more resource, it may hurt other products in the portfolio. Thus, without support from mature or follower products, new products and pioneering products alone may not increase firm sales or profit. Fourth, from a long term perspective, the paper found that the financial market only rewards a firm's overall capability to deliver new products first in the marketplace. Thus, short term performance is mainly driven by product level innovativeness, whereas firm level innovativeness enhances forward looking long term performance. Fifth, the paper also found that pioneering new products are driven by integrating both primary and complementary technological capabilities. And nonpioneering new products are mainly driven by the capabilities in primary technology domain. These results provide important insight into the relative value and timing of return on investment in radical versus incremental innovation and alternative market entry strategies. By understanding the performance trade offs of these different factors in the short and long term, one can develop better guidelines for optimizing innovation strategies, and their dependence on both external and internal environmental conditions.
Speed Control of Asymmetrical Six Phase Induction Motor based Fuzzy Logic Controller
Year: 2020

1Assistance Lecturer, Dept. of Mechatronics Engineering, University of Mosul, Mosul Iraq 2Assistance Professor , Dept. University of Mosul, Mosul Iraq.  Ac electric drives for both synchronous and induction take great interests by researchers and industrialist especially last type due to there is effortlessness for speed regulation, ruggedness, and high power to weight ratio etc..three phase drives was the conventional types that covered wide range of industrial and transmitting application .but with rising power demand and development in power electronics device and control schemes conventional induction motor drives could not be able to overcome all requirements in different fields that's leads to think to create an other types of drivers having more than three phase five, six ,seven and nine etc. .six phase induction motor drive become one of these type used for many application instead of three phase type rising systems dependability, efficiency and flexibility in control process
Inflation Dynamics During the Financial Crisis
Year: 2016

Using confidential product level price data underlying the U.S. Producer Price Index (PPI) this paper analyzes the effect of changes in firms' financial conditions on their price setting behavior during the "Great Recession" that surrounds the financial crisis. The evidence indicates that during the height of the crisis in late 2008, firms with "weak" balance sheets increased prices significantly relative to industry averages, whereas firms with "strong" balance sheets lowered prices, a response consistent with an adverse demand shock. These stark differences in price setting behavior are consistent with the notion that financial frictions may significantly influence the response of aggregate inflation to macroeconomic shocks. We explore the implications of these empirical findings within a general equilibrium framework that allows for customer markets and departures from the frictionless financial markets. In the model, firms have an incentive to set a low price to invest in market share, though when financial distortions are severe, firms forgo these investment opportunities and maintain high prices in an effort to preserve their balance sheet capacity. Consistent with our empirical findings, the model with financial distortions relative to the baseline model without such distortions implies a substantial attenuation of price dynamics in response to contractionary demand shocks.
Definition, necessity, and Nansen: Efficacy of dialogue in peacebuilding
Year: 2012

In international conflict resolution the term dialogue is used frequently while lacking specificity. When examined in practice, dialogue is revealed as a specific, efficacious method for conflict management and peacebuilding. This article defines dialogue specifically through description of eight characteristics: coexistence; movement; encountering the "other" assumption; creativity and flexibility; sharing; holistic; and multigenerational. In defining dialogue, a parameter is drawn and a method clarified. The case of Macedonia and the Nansen Dialogue Network (NDN) is drawn upon to illustrate these traits and the success of the method in long term conflict management and peacebuilding. NDN has used its dialogic approach in Macedonia, leading to integrated schooling. As integrated schooling has continued success with NDN as an ongoing dialogue facilitator, as of 2011 the Macedonia government is considering it as an educational model. As evidence of further success, this dialogue work has led to continued funding as well as peace related awards and nominations to NDN. Understanding the nature and success of dialogue as practiced is an essential, though often overlooked, aspect of international relations work.
Epileptic Seizure Prediction in Scalp EEG Using an Improved HIVE COTE Model
Venue: 2020 39th Chinese Control Conference (CCC)
Year: 2020

Epileptic seizures occur as a result of a disorder of brain waves. In this study, we aim at a patient specific model for predicting the risk of seizure paroxysm by extracting the in depth features from continuous scalp electroencephalographic(EEG) signals. Unfortunately, the false warning rates of generalized regression prediction algorithms are relatively high on account of the complexity of the cerebral time series. Hence we set the seizure forecast problem as a time series classification(TSC) problem and a cutting edge TSC algorithm:the Hierarchical Vote Collective of Transformation based Ensembles(HIVE COTE) is introduced to address the issue at the first time. In addition, we improve the structure of HIVE COTE using a channel selection module. With the improved HIVE COTE model, an oncoming seizure could be detected by a collective of machine learning classifiers that identify the accurate pattern(inter ictal or pre ictal) of the cerebral signals. Based on 15 patients in CHB MIT dataset, the proposed improved HIVE COTE model achieves a sensitivity of 87.4% an AUC of 0.859, which is a promising result. Our work significantly outperform a random predictor and other TSC algorithms.
THE RELATION BETWEEN BODY MASS INDEX AND DIETARY HABITS, PHYSICAL ACTIVITY AND DURATION SPEND ON ELECTRONIC DEVICES IN CHILDREN (2 18) YEARS OLD IN ALMADINAH ALMUNWARRAH
Year: 2020

Walaa Alhazmi, Omar Abduldaem, Sondos Albukhari, Abdulrahman Aldhalan and Mahmoud Alkhayat Manuscript Info Abstract Manuscript History Received: 25 November 2019  27 December 2019  January 2020 Childhood obesity is one of the most serious public health challenges of the 21st century. type 2 diabetes mellitus, hypertension, and hypercholesterolemia are becoming more common among obese children. This study aimed to estimate the relation between body mass index and the dietary habits, physical activity and the duration spend on electronic devices among children in Almadinah, KSA.  A community based Analytical cross sectional study was conducted during the event of "Your Health is Your Life 6 th
AI Grand Challenges for Education
Venue: AI Mag.
Year: 2013

This article focuses on contributions that AI can make to address long term educational goals. It describes five challenges that would support: (1) mentors for every learner; (2) learning twenty first century skills; (3) interaction data to support learning; (4) universal access to global classrooms; and (5) lifelong and life wide learning. A vision and brief research agenda are described for each challenge along with goals that lead to access to global educational resources and the reuse and sharing of digital educational resources. Instructional systems with AI technology are described that currently support richer experiences for learners and supply researchers with new opportunities to analyze vast data sets of instructional behavior from big databases, containing elements of learning, affect, motivation, and social interaction. Personalized learning is described using computational tools that enhance student and group experience, reflection, and analysis, and supply data for development of novel theory development.
Eigengene networks for studying the relationships between co expression modules
Venue: BMC Systems Biology
Year: 2007

BackgroundThere is evidence that genes and their protein products are organized into functional modules according to cellular processes and pathways. Gene co expression networks have been used to describe the relationships between gene transcripts. Ample literature exists on how to detect biologically meaningful modules in networks but there is a need for methods that allow one to study the relationships between modules.ResultsWe show that network methods can also be used to describe the relationships between co expression modules and present the following methodology. First, we describe several methods for detecting modules that are shared by two or more networks (referred to as consensus modules) We represent the gene expression profiles of each module by an eigengene. Second, we propose a method for constructing an eigengene network, where the edges are undirected but maintain information on the sign of the co expression information. Third, we propose methods for differential eigengene network analysis that allow one to assess the preservation of network properties across different data sets. We illustrate the value of eigengene networks in studying the relationships between consensus modules in human and chimpanzee brains; the relationships between consensus modules in brain, muscle, liver, and adipose mouse tissues; and the relationships between male female mouse consensus modules and clinical traits. In some applications, we find that module eigengenes can be organized into higher level clusters which we refer to as meta modules.ConclusionEigengene networks can be effective and biologically meaningful tools for studying the relationships between modules of a gene co expression network. The proposed methods may reveal a higher order organization of the transcriptome. R software tutorials, the data, and supplementary material can be found at the following webpage: http:/www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/EigengeneNetwork.
The Long Term Effects of Bullying, Victimization, and Bystander Behavior on Emotion Regulation and Its Physiological Correlates.
Venue: Journal of interpersonal violence
Year: 2020

Bullying at school is a serious social problem that influences the wellbeing of everyone involved, that is, victims, perpetrators, and bystanders. Among the many health and psychological problems that these individuals may develop, emotion dysregulation appears to be a common marker. To date, however, it remains unclear whether bullying experienced during the school years is associated with emotion dysregulation also in adulthood. In this study, by adopting a retrospective approach, we investigated whether involvement in bullying at school either as a bully, victim, or bystander could put these individuals at risk of presenting deficits in emotion regulation in adulthood, as assessed with behavioral (explicit) and physiological (implicit) indexes (i.e. skin conductance) and whether the association between the involvement in bullying and emotion regulation was direct or mediated by other factors, such as somatic complaints and sensation seeking. A total of 58 young adults were asked to control their emotional reactions in front of images with strong emotional content, and to explicitly evaluate them with ratings, while their arousal was measured through skin conductance. They also responded to questionnaires about retrospective involvement in bullying, somatic complaints, and sensation seeking. Results revealed that victimization and bystander behavior were directly and negatively associated with emotion regulation as assessed with skin conductance, whereas bullying was positively associated with implicit emotion regulation through the mediation of sensation seeking. Interestingly, emotion regulation as assessed with explicit ratings was not associated with any of the characteristics of the participants. Our study suggests that being directly (as victim) but also indirectly (as bystander) involved in bullying at school time is associated with difficulties in emotional wellbeing in adulthood. Furthermore, it reveals that behavioral and physiological indexes associated with emotion regulation dissociate, suggesting that subtle physiological changes may remain hidden from explicit behavior.
A Review of 40 Years of Cognitive Architecture Research: Focus on Perception, Attention, Learning and Applications
Venue: ArXiv
Year: 2016

In this paper we present a broad overview of the last 40 years of research on cognitive architectures. Although the number of existing architectures is nearing several hundred, most of the existing surveys do not reflect this growth and focus on a handful of well established architectures. While their contributions are undeniable, they represent only a part of the research in the field. Thus, in this survey we wanted to shift the focus towards a more inclusive and high level overview of the research in cognitive architectures. Our final set of 86 architectures includes 55 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience. To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, learning and memory structure. To assess the breadth of practical applications of cognitive architectures we gathered information on over 700 practical projects implemented using the cognitive architectures in our list. We use various visualization techniques to highlight overall trends in the development of the field. For instance, our data confirms that the hybrid approach to cognitive modeling already dominates the field and will likely continue to do so in the future. Our analysis of practical applications shows that most architectures are very narrowly focused on a particular application domain. Furthermore, there is an apparent gap between general research in robotics and computer vision and research in these areas within the cognitive architectures field. It is very clear that biologically inspired models do not have the same range and efficiency compared to the systems based on engineering principles and heuristics. Another observation is related to a general lack of collaboration, which is surprising to see in the inherently interdisciplinary area of cognitive architectures. Several factors hinder communication, among which are the closed nature of the individual projects (only one third of the reviewed here architectures are open source) and terminological differences.