nils-herrmann/clean_scirepeval huggingface dataset:
PENGARUH GAYA BELAJAR DAN KECERDASAN LOGIKA MATEMATIKA TERHADAP PRESTASI BELAJAR MATEMATIKA
Year: 2020

Tujuan penelitian adalah untuk menganalisa apakah terdapat pengaruh gaya belajar dan kecerdasan logika matematika terhadap prestasi belajar matematika di Kecamatan Jatinegara. Sampel dalam penelitian ini adalah 60 peserta didik. Metode survei dengan teknik simple random sampling. Uji validitas kedua datanya menandakan rhitung rtabel (0,396) maka soal dikatakan valid. Reliabilitas untuk Gaya Belajar adalah 0,92 dan Kecerdasan Logika Matematika adalah 0,86. Selanjutnya uji chi kuadrat, ketiga data menandakan X2hitung X2tabel, yaitu Gaya Belajar (2,13 12,592) Kecerdasan Logika (10,25 12,592) dan Prestasi Belajar (10,41 12,592) maka ketiga datanya berdistribusi normal. Uji variabel bebas secara parsial terhadap variabel terikat, 2,39 2,0042) maka H0 ditolak, dan disimpulkan terdapat pengaruh yang signifikan gaya belajar terhadap prestasi belajar matematika. 7,18 2,0042) maka H0 ditolak, dan disimpulkan terdapat pengaruh yang signifikan Kecerdasan Logika Matematika terhadap Prestasi Belajar Matematika. Uji korelasi ganda dengan 0,05 maka db1 2 dan db2 57 diperoleh Ftabel =3,17 dan Fhitung 607,33; maka H0 ditolak dan disimpulkan bahwa terdapat pengaruh yang signifikan Gaya Belajar dan Kecerdasan Logika Matematika secara bersama sama terhadap Prestasi Belajar Matematika.
ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations
Venue: ArXiv
Year: 2019

Learning from demonstrations is a popular tool for accelerating and reducing the exploration requirements of reinforcement learning. When providing expert demonstrations to human students, we know that the demonstrations must fall within a particular range of difficulties called the "Zone of Proximal Development (ZPD)" If they are too easy the student learns nothing, but if they are too difficult the student is unable to follow along. This raises the question: Given a set of potential demonstrators, which among them is best suited for teaching any particular learner? Prior work, such as the popular Deep Q learning from Demonstrations (DQfD) algorithm has generally focused on single demonstrators. In this work we consider the problem of choosing among multiple demonstrators of varying skill levels. Our results align with intuition from human learners: it is not always the best policy to draw demonstrations from the best performing demonstrator (in terms of reward) We show that careful selection of teaching strategies can result in sample efficiency gains in the learner's environment across nine Atari games
In Briefs
Venue: American journal of health promotion AJHP
Year: 2021

Paul E. Terry 893 Editorial A Bowl of Vegetables with Someone you Love" Faith, Health and Workplace Well being Worksite health and well being initiatives will ideally be integrated with employers' efforts to address diversity, equity and inclusion issues. Social Determinants of Health (SDOH) include race, class, community health, income and other variables that companies can play a role in ameliorating. As much as spirituality is commonly espoused as a component of a holistic approach to health promotion, making space to discuss faith and health remains an uncommon strategy in the workplace wellness movement. Recognizing the value on investment (VOI) in wellness has eclipsed a return on investment as a driver of an employer's well being strategy. This editorial argues that making space for learning about faith and health will intersect in vital ways with anti racism work, diversity programs and similar efforts to eliminate health inequities, address SDOH and bolster the VOI of worksite well being initiatives. A fictional dialogue between executives is used to review these issues and related literature.
Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non small cell lung cancer from 18F FDG PET/CT images
Venue: EJNMMI Research
Year: 2017

BackgroundThis study aimed to compare one state of the art deep learning method and four classical machine learning methods for classifying mediastinal lymph node metastasis of non small cell lung cancer (NSCLC) from 18F FDG PET/CT images. Another objective was to compare the discriminative power of the recently popular PET/CT texture features with the widely used diagnostic features such as tumor size, CT value, SUV, image contrast, and intensity standard deviation. The four classical machine learning methods included random forests, support vector machines, adaptive boosting, and artificial neural network. The deep learning method was the convolutional neural networks (CNN) The five methods were evaluated using 1397 lymph nodes collected from PET/CT images of 168 patients, with corresponding pathology analysis results as gold standard. The comparison was conducted using 10 times 10 fold cross validation based on the criterion of sensitivity, specificity, accuracy (ACC) and area under the ROC curve (AUC) For each classical method, different input features were compared to select the optimal feature set. Based on the optimal feature set, the classical methods were compared with CNN, as well as with human doctors from our institute.ResultsFor the classical methods, the diagnostic features resulted in 81~85% ACC and 0.87~0.92 AUC, which were significantly higher than the results of texture features. CNN's sensitivity, specificity, ACC, and AUC were 84, 88, 86, and 0.91, respectively. There was no significant difference between the results of CNN and the best classical method. The sensitivity, specificity, and ACC of human doctors were 73, 90, and 82, respectively. All the five machine learning methods had higher sensitivities but lower specificities than human doctors. present study shows that the performance of CNN is not significantly different from the best classical methods and human doctors for classifying mediastinal lymph node metastasis of NSCLC from PET/CT images. Because CNN does not need tumor segmentation or feature calculation, it is more convenient and more objective than the classical methods. However, CNN does not make use of the import diagnostic features, which have been proved more discriminative than the texture features for classifying small sized lymph nodes. Therefore, incorporating the diagnostic features into CNN is a promising direction for future research.
Precipitation of Ordered Dolomite via Simultaneous Dissolution of Calcite and Magnesite: New Experimental Insights into an Old Precipitation Enigma
Year: 2014

In the present study, we demonstrate that ordered dolomite can be precipitated via simultaneous dissolution of calcite and magnesite under hydrothermal conditions (from 100 to 200 degC) The temperature and high carbonate alkalinity have significantly copromoted the dolomite formation. For example, when high purity water was initially used as interacting fluid, only a small proportion of disordered dolomite was identified at 200 degC from XRD patterns and FESEM observations. Conversely, a higher proportion of ordered dolomite, i.e. clear identification of superstructure ordering reflections in XRD patterns, was determined when high carbonate alkalinity solution was initially used in our system at the same durations of reaction. For this latter case, the dolomite formation is favorable therefrom 100 degC and two kinetic steps were identified: (1) protodolomite formation after about 5 days of reaction, characterized by rounded submicrometric particles from FESEM observations and by the absence of superstructure
WEDL NIDS: Improving Network Intrusion Detection Using Word Embedding Based Deep Learning Method
Venue: MDAI
Year: 2018

A Network Intrusion Detection System (NIDS) helps system administrators to detect security breaches in their organization. Current research focus on machine learning based network intrusion detection method. However, as numerous complicated attack types have growingly appeared and evolved in recent years, obtaining high detection rates is increasingly difficult. Also, the performance of a NIDS is highly dependent on feature design, while a feature set that can accurately characterize network traffic is still manually designed and usually costs lots of time. In this paper, we propose an improved NIDS using word embedding based deep learning (WEDL NIDS) which has the ability of dimension reduction and learning features from data with sophisticated structure. The experimental results show that the proposed method outperforms previous methods in terms of accuracy and false alarm rate, which successfully demonstrates its effectiveness in both dimension reduction and practical detection ability.
Comp 7720 Online Algorithms Assignment 1 Introduction Searching List Update
Year: 2017

All problems are written problems. There are six problems with a total of 74 marks plus 108 bonus marks! If you feel the assignment is too hard (or too simple) do not panic! To some extent, this assignment serves to indicate how easy/hard the future assignments/exam should be. More importantly, the assignment is designed to raise a group discussion. I would love to see a discussion on Piazza and when you are confused drop a hint about a problem. Think of the assignment as a project that you need to work on together on Piazza. If you are not active on Piazza, you will miss the hints that I 'plan' to drop.
Rough and tumble play as a window on animal communication
Venue: Biological reviews of the Cambridge Philosophical Society
Year: 2016

Rough and tumble play (RT) is a widespread phenomenon in mammals. Since it involves competition, whereby one animal attempts to gain advantage over another, RT runs the risk of escalation to serious fighting. Competition is typically curtailed by some degree of cooperation and different signals help negotiate potential mishaps during RT. This review provides a framework for such signals, showing that they range along two dimensions: one from signals borrowed from other functional contexts to those that are unique to play, and the other from purely emotional expressions to highly cognitive (intentional) constructions. Some animal taxa have exaggerated the emotional and cognitive interplay aspects of play signals, yielding admixtures of communication that have led to complex forms of RT. This complexity has been further exaggerated in some lineages by the development of specific novel gestures that can be used to negotiate playful mood and entice reluctant partners. Play derived gestures may provide new mechanisms by which more sophisticated communication forms can evolve. Therefore, RT and playful communication provide a window into the study of social cognition, emotional regulation and the evolution of communication systems.
Synthetic biology open language visual (SBOL visual) version 2.2
Venue: J. Integr. Bioinform.
Year: 2020

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.2 of SBOL Visual, which builds on the prior SBOL Visual 2.1 in several ways. First, the grounding of molecular species glyphs is changed from BioPAX to SBO, aligning with the use of SBO terms for interaction glyphs. Second, new glyphs are added for proteins, introns, and polypeptide regions (e. g. protein domains) the prior recommended macromolecule glyph is deprecated in favor of its alternative, and small polygons are introduced as alternative glyphs for simple chemicals.
A block Chebyshev Davidson method for linear response eigenvalue problems
Venue: Adv. Comput. Math.
Year: 2016

We present a Chebyshev Davidson method to compute a few smallest positive eigenvalues and corresponding eigenvectors of linear response eigenvalue problems. The method is applicable to more general linear response eigenvalue problems where some purely imaginary eigenvalues may exist. For the Chebyshev filter, a tight upper bound is obtained by a computable bound estimator that is provably correct under a reasonable condition. When the condition fails, the estimated upper bound may not be a true one. To overcome that, we develop an adaptive strategy for updating the estimated upper bound to guarantee the effectiveness of our new Chebyshev Davidson method. We also obtain an estimate of the rate of convergence for the Ritz values by our algorithm. Finally, we present numerical results to demonstrate the performance of the proposed Chebyshev Davidson method.
Intestinal tuberculosis and secondary liver abscess.
Venue: The Mount Sinai journal of medicine, New York
Year: 2006

The incidence of intestinal tuberculosis (ITB) has been increasing in the West, due to the AIDS epidemic, transglobal immigration, IV drug abuse, an aging population, and an increase in the number of immunocompromised patients. Obstruction and perforation of the intestine are the most common and serious complications of ITB. Another complication, tuberculous liver abscess (TLA) is rare and usually associated with foci of infection in the lung or gastrointestinal tract. We report a case of a 17 year old boy with Down syndrome who presented with multiple TLAs secondary to obstructive and multiple perforated ileal tuberculosis.
The Impact of an Aging Population in the Workplace
Venue: Workplace health safety
Year: 2018

According to the Centers for Disease Control and Prevention, the number of people 65 years of age or older living in the United States is projected to double by 2030 to 72 million adults, representing 20% of the total U.S. population. Evidence suggests that older Americans are working longer and spending more time on the job than their peers did in previous years. The increased number of older adults working longer is observed not only in the Unites States but also worldwide. There are numerous ramifications associated with the changing demographics and the expanding prevalence of an aging population in the workforce. Dynamics that arise include stereotyping and discrimination, longevity and on site expert knowledge, variances in workplace behavior, a multigenerational employee pool, chronic disease management, occupational safety, and the application of adaptive strategies to reduce injury occurrences. Occupational health nurses play a pivotal role in implementing best practices for an aging friendly workplace.
Cell death: a review of the major forms of apoptosis, necrosis and autophagy
Venue: Cell biology international
Year: 2019

Cell death was once believed to be the result of one of two distinct processes, apoptosis (also known as programmed cell death) or necrosis (uncontrolled cell death) in recent years, however, several other forms of cell death have been discovered highlighting that a cell can die via a number of differing pathways. Apoptosis is characterised by a number of characteristic morphological changes in the structure of the cell, together with a number of enzyme dependent biochemical processes. The result being the clearance of cells from the body, with minimal damage to surrounding tissues. Necrosis, however, is generally characterised to be the uncontrolled death of the cell, usually following a severe insult, resulting in spillage of the contents of the cell into surrounding tissues and subsequent damage thereof. Failure of apoptosis and the resultant accumulation of damaged cells in the body can result in various forms of cancer. An understanding of the pathways is therefore important in developing efficient chemotherapeutics. It has recently become clear that there exists a number of subtypes of apoptosis and that there is an overlap between apoptosis, necrosis and autophagy. The goal of this review is to provide a general overview of the current knowledge relating to the various forms of cell death, including apoptosis, necrosis, oncosis, pyroptosis and autophagy. This will provide researchers with a summary of the major forms of cell death and allow them to compare and contrast between them.
Adolescent alcohol, nuts, and fiber: combined effects on benign breast disease risk in young women
Venue: NPJ breast cancer
Year: 2020

Adolescent drinking is associated with higher risks of proliferative benign breast disease (BBD) and invasive breast cancer (BC) Furthermore, adolescent nut and fiber consumptions are associated with lower risks of benign lesions and premenopausal BC. We hypothesize that diet (nuts, fiber) may mitigate the elevated BBD risk associated with alcohol. A prospective cohort of 9031 females, 9 15 years at baseline, completed questionnaires in 1996 2001, 2003, 2005, 2007, 2010, 2013, and 2014. Participants completed food frequency questionnaires in 1996 2001. In 2005, participants =18 years) began reporting biopsy confirmed BBD N 173 cases) Multivariable logistic regression estimated associations between BBD and cross classified intakes (14 17 years) of alcohol and peanut butter/nuts (separately, total dietary fiber) Only 19% of participants drank in high school; drinking was associated with elevated BBD risk (OR 1.75, 95% CI: 1.20 2.56; p 0.004) compared to nondrinkers. Participants consuming any nuts/butter had lower BBD risk (OR 0.64, 95% CI: 0.45 0.90; p 0.01) compared to those consuming none. Participants in top 75% fiber intake had lower risk (OR 0.57, 95% CI: 0.40 0.81; p 0.002) compared to bottom quartile. Testing our hypothesis that consuming nuts/butter mitigates the elevated alcohol risk, analyzing alcohol and nuts combined found that those who consumed both had lower risk (RR 0.47, 95% CI: 0.24 0.89; p 0.02) compared to drinkers eating no nuts. Our analysis of alcohol and fiber together did not demonstrate risk mitigation by fiber. For high school females who drink, their BBD risk may be attenuated by consuming nuts. Due to modest numbers, future studies need to replicate our findings in adolescent/adult females. However, high school students may be encouraged to eat nuts and fiber, and to avoid alcohol, to reduce risk of BBD and for general health benefits.
The Value of Software Architecture Recovery for Maintenance
Venue: ISEC
Year: 2019

In order to maintain a system, it is beneficial to know its software architecture. In the common case that this architecture is unavailable, architecture recovery provides a way to recover an architectural view of the system. Many different methods and tools exist to provide such a view. While there have been taxonomies of different recovery methods and surveys of their results along with measurements of how these results conform to expert's opinions on the systems, there has not been a survey that goes beyond a simple automatic comparison. Instead, this paper seeks to answer questions about the viability of individual methods in given situations, the quality of their results and whether these results can be used to indicate and measure the quality and quantity of architectural changes. For our case study, we look at the results of recoveries of versions of Android, Apache Hadoop and Apache Chukwa obtained by running PKG, ACDC and ARC.
Humor and camera view on mobile short form video apps influence user experience and technology adoption intent, an example of TikTok (DouYin)
Venue: Comput. Hum. Behav.
Year: 2020

Mobile short form videos on social media apps are increasingly popular. Human Computer Interaction (HCI) theories may be extended to short form video apps to understand and improve app user experience, as well as to persuade new technology adoption. The present study examined the psychological responses and persuasive outcomes associated with short form videos on a mobile social media app. In a 2 (low V.S. high level humor) X 2 (first V.S. third person view) between subject experimental design, participants (N 81) were randomly assigned one of the four sets of videos about smart homes; post viewing, they filled out an online questionnaire. Results of ANCOVA demonstrated significant effects of videos' humor and camera view on the viewer perceptions of Immersion, Social Presence and Entertainment but not on Spatial Presence and Perceptual  Humor had mixed effects on the interaction between users and the mobile app; the first person camera view elevated viewers' Immersion, Social Presence, Entertainment. As a PROCESS mediation test showed, Social Presence mediated (by 56.78% the indirect link between the level of humor getting from a video and the viewers' post viewing intent to adopt the technology depicted in the video. The study demonstrated values of extending HCI theories to mobile short form video apps. Implications were discussed in terms of using appropriate humor and camera view for improving user experience and persuading serious agenda.
GiantMIDI Piano: A large scale MIDI dataset for classical piano music
Venue: ArXiv
Year: 2020

Symbolic music datasets are important for music information retrieval and musical analysis. However, there is a lack of large scale symbolic dataset for classical piano music. In this article, we create a GiantMIDI Piano dataset containing 10,854 unique piano solo pieces composed by 2,786 composers. The dataset is collected as follows, we extract music piece names and composer names from the International Music Score Library Project (IMSLP) We search and download their corresponding audio recordings from the internet. We apply a convolutional neural network to detect piano solo pieces. Then, we transcribe those piano solo recordings to Musical Instrument Digital Interface (MIDI) files using our recently proposed high resolution piano transcription system. Each transcribed MIDI file contains onset, offset, pitch and velocity attributes of piano notes, and onset and offset attributes of sustain pedals. GiantMIDI Piano contains 34,504,873 transcribed notes, and contains metadata information of each music piece. To our knowledge, GiantMIDI Piano is the largest classical piano MIDI dataset so far. We analyses the statistics of GiantMIDI Piano including the nationalities, the number and duration of works of composers. We show the chroma, interval, trichord and tetrachord frequencies of six composers from different eras to show that GiantMIDI Piano can be used for musical analysis. Our piano solo detection system achieves an accuracy of 89\ and the piano note transcription achieves an onset F1 of 96.72\ evaluated on the MAESTRO dataset. GiantMIDI Piano achieves an alignment error rate (ER) of 0.154 to the manually input MIDI files, comparing to MAESTRO with an alignment ER of 0.061 to the manually input MIDI files. We release the source code of acquiring the GiantMIDI Piano dataset at this https URL.