nils-herrmann/clean_scirepeval huggingface dataset:
Optimism in Reinforcement Learning with Generalized Linear Function Approximation
Venue: ICLR
Year: 2021

We design a new provably efficient algorithm for episodic reinforcement learning with generalized linear function approximation. We analyze the algorithm under a new expressivity assumption that we call "optimistic closure," which is strictly weaker than assumptions from prior analyses for the linear setting. With optimistic closure, we prove that our algorithm enjoys a regret bound of \tilde{O}\sqrt{d^3 T} where $d$ is the dimensionality of the state action features and $T$ is the number of episodes. This is the first statistically and computationally efficient algorithm for reinforcement learning with generalized linear functions.
Minimal Residual Disease in Acute Lymphoblastic Leukemia: Technical and Clinical Advances
Venue: Front. Oncol.
Year: 2019

Acute lymphoblastic leukemia (ALL) is the first neoplasm where the assessment of early response to therapy by minimal residual disease (MRD) monitoring has proven to be a fundamental tool to guide therapeutic choices. The most standardized methods to study MRD in ALL are multi parametric flow cytometry (MFC) and polymerase chain reaction (PCR) amplification based methods. Emerging technologies hold the promise to improve MRD detection in ALL patients. Moreover, novel therapies, such as monoclonal antibodies, bispecific T cell engagers, and chimeric antigen receptor T cells (CART) represent exciting advancements in the management of B cell precursor (BCP) ALL.  Through a review of the literature and in house data, we analyze the current status of MRD assessment in ALL to better understand how some of its limitations could be overcome by emerging molecular technologies. Furthermore, we highlight the future role of MRD monitoring in the context of personalized protocols, taking into account the genetic complexity in ALL.  Molecular rearrangements (gene fusions and immunoglobulin and T cell receptor IG/TR gene rearrangements) are widely used as targets to detect residual leukemic cells in ALL patients. The advent of novel techniques, namely next generation flow cytometry (NGF) digital droplet PCR (ddPCR) and next generation sequencing (NGS) appear important tools to evaluate MRD in ALL, since they have the potential to overcome the limitations of standard approaches. It is likely that in the forthcoming future these techniques will be incorporated in clinical trials, at least at decisional time points. Finally, the advent of new powerful compounds is further increasing MRD negativity rates, with benefits in long term survival and a potential reduction of therapy related toxicities. However, the prognostic relevance in the setting of novel immunotherapies still needs to be evaluated.
Continuously Improving Model of Road User Movement Patterns using Recurrent Neural Networks at Intersections with Connected Sensors
Venue: VEHITS
Year: 2019

Intersections with connected infrastructure and vehicle sensors allow observing vulnerable road users (VRU) longer and with less occlusion than from a moving vehicle. Furthermore, the connected sensors are providing continuous measurements of VRUs at the intersection. Thus, we propose a data driven prediction model, which benefits of the continuous, local measurements. While most approaches in literature use the most probable path to predict road users, it does not represent the uncertainty in prediction and multiple maneuver options. We propose the use of Recurrent Neural Networks fed with measured trajectories and a variety of contextual information to output the prediction in a local occupancy grid map in polar coordinates. By using polar coordinates, a reliable movement model is learned as base model being insensitive against blind spots in the data. The model is further improved by considering input features containing information about the static and dynamic environment as well as local movement statistics. The model successfully predicts multiple movement options represented in a polar grid map. Besides, the model can continuously improve the prediction accuracy without re training by updating local movement statistics. Finally, the trained model is providing reliable predictions if applied on a different intersection without data from this intersection.
Evaluation of automatic video captioning using direct assessment
Venue: PloS one
Year: 2018

We present Direct Assessment, a method for manually assessing the quality of automatically generated captions for video. Evaluating the accuracy of video captions is particularly difficult because for any given video clip there is no definitive ground truth or correct answer against which to measure. Metrics for comparing automatic video captions against a manual caption such as BLEU and METEOR, drawn from techniques used in evaluating machine translation, were used in the TRECVid video captioning task in 2016 but these are shown to have weaknesses. The work presented here brings human assessment into the evaluation by crowd sourcing how well a caption describes a video. We automatically degrade the quality of some sample captions which are assessed manually and from this we are able to rate the quality of the human assessors, a factor we take into account in the evaluation. Using data from the TRECVid video to text task in 2016, we show how our direct assessment method is replicable and robust and scales to where there are many caption generation techniques to be evaluated including the TRECVid video to text task in 2017.
Optimizing control based on ant colony logic for Quadrotor stabilization
Venue: 2015 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)
Year: 2015

Quadrotor as one type of UAV (Unmanned Aerial Vehicle) have the ability to perform Vertical Take Off and Landing (VTOL) It allows the Quadrotor to be stationary hovering in the air. PID (Proportional Integral Derivative) control system is one of the control methods that are commonly used. It is usually used to optimize the Quadrotor stabilization at least based on the three Eulerian angles (roll, pitch, and yaw) as input parameters for the control system. The three constants of PID can be obtained in various ways or methods. However, to produce a robust control, we need a method that can optimize the PID components. Ant Colony Optimization (ACO) is one of PID controller optimization method which adapted by ant colony ability to find the shortest way from their nest to food. Some ACO parameters are number of ants, parameters, and pheromone constant for pheromone. Pheromones are the values given by the ants when they use the road.
Supply Chain Management Pattern of Pollution free Agricultural Products Based on Precision Marketing
Year: 2015

The paper studies the supply chain management pattern of pollution free agricultural products from the perspective of marketing strategy. Taking Company A for an example, it first introduces the precision marketing strategy of its pollution free agricultural product Brand A local pork. On that basis, it analyses the management pattern of the company's supply chain process that carries out organic integration of marketing, research development, production and distribution. Finally the conclusion is given based on implementation effect of precision marketing strategy.
Multi objective MCTLBO approach to allocate renewable energy system (PV/BESS) in electricity grid: assessing grid benefits
Year: 2020

With the advent of the smart grid paradigm many distribution system operators are making efforts to modernise their power grids through the optimal integration of renewable energy system (RES) such as photovoltaic/battery energy storage system (PV/BESS).This paper presents a novel mathematical model and solution approach for the optimal allocation of RES in radial distribution system (RDS) The optimal allocation of RES is formulated as a problem, and it is solved by multi objective multi course teaching learning based optimisation (MCTLBO) An efficient codification for the allocation of RES allows the multi objective MCTLBO to find the optimal location, capacity and power dispatch of RESs for a given RESs for a given load level with time of use (TOU) pricing. The proposed methodology is tested on the 69 bus RDS. It was found that an appropriate allocation of RESs results techno economic improvement for the system under study.
Ji Yu BERTDe Duan Dao Duan Zhong Wen Pian Zhang Shi Jian Chou Qu (A BERT based End to End Model for Chinese Document level Event Extraction)
Venue: CCL
Year: 2020

Document level event extraction aims at discovering event mentions and extracting events which contain event arguments and their roles from texts. This paper proposes an end to end model for closed domain based on BERT. We introduce the embedding of event type and entity nodes to the subsequent layer for event argument and role identification, which represents the relation between event, arguments and roles and improves the accuracy of classifying multi event arguments. With the title, the quintuple of event, we calculate the master slave structure between multiple events with the embedding presentation. Experimental results show that our model outperforms the state of the art.
A unified framework of deep networks for genre classification using movie trailer
Venue: Appl. Soft Comput.
Year: 2020

Affective video content analysis has emerged as one of the most challenging and essential research tasks as it aims to analyze the emotions elicited by videos automatically. However, little progress has been achieved in this field due to the enigmatic nature of emotions. This widens the gap between the human affective state and the structure of the video. In this paper, we propose a novel deep affect based movie trailer classification framework. We also develop an EmoGDB dataset, which contains 100 Bollywood movie trailers annotated with popular movie genres: Action, Comedy, Drama, Horror, Romance, Thriller, and six different types of induced emotions: Anger, Fear, Happy, Neutral, Sad, Surprise. The affect based features are learned via ILDNet architecture trained on the EmoGDB dataset. Our work aims to analyze the relationship between the emotions elicited by the movie trailers and how they contribute in solving the multi label genre classification problem. The proposed novel framework is validated by performing cross dataset testing on three large scale datasets, namely LMTD 9, MMTF 14K, and ML 25M datasets. Extensive experiments show that the proposed algorithm outperforms all the state of the art methods significantly, as reported by the precision, recall, F1 score, precision recall curves (PRC) and area under the PRC evaluation metrics.
The role of oestrogen and progesterone receptors in gigantomastia
Venue: Archives of Medical Science
Year: 2019

Gigantomastia is a rare condition characterised by excessive breast growth. The pathophysiology of mammary enlargement varies depending on the type of gigantomastia: gestational, juvenile virginal, or idiopathic. The study aimed at examining the receptor status (oestrogen receptor alpha [ERa] and progesterone receptor [PR] of breast tissue in adult women with juvenile or idiopathic gigantomastia.The study involved 70 women who underwent breast reduction due to juvenile or idiopathic gigantomastia. Control breast specimens were obtained from 18 female cadavers. ERa and PR expressions were detected immunohistochemically in breast gland samples.Categorised and uncategorised ERa and PR expression did not differ between women with gigantomastia and control women. It was found that in both groups weak (0 30% ERa and PR expression was the most common. Analysis of categorised data also did not reveal any significant correlations between ERa or PR and the women's age: for the whole group: p 0.795 (ERa) p 0.207 (PR) for women with gigantomastia: p 0.934 (ERa) p 0.43 (PR) and for control women: p 0.638 (ERa) p 0.805 (PR).Gigantomastia is not caused by increased expression of ERa and PR. Analysing abnormal sensitivity of these receptors to hormones may be crucial in establishing the increased risk of breast cancer in women with gigantomastia.
SISTEM INFORMASI PASIEN DI KLINIK DOKTER GIGIBUDI ROCHMAN
Year: 2013

Skripsi dengan judul Sistem Informasi Pasien Di Klinik Dokter Gigi Budi Rochman akan menampilkan informasi pasien dari awal pasien melakukan pendaftaran sampai transaksi pembayaran. Dengan adanya sistem ini maka akan memudahkan para petugas untuk mempermudah pekerjaan yang ada melalui komputer yang sudah terstruktur dengan rapi. Sistem Informasi ini di bangun menggunakan bahasa pemrograman java dan MySQL. Sistem Informasi ini dibuat untuk membantu petugas ataupun bagi pihak manajemen klinik untuk dapat melakukan pengolahan data pasien. Sisteminformasi ini akan menampilkan laporan laporan yang di butuhkan mulai dari laporan pemeriksaa, laporan penerimaan kas dan laporan data pasien. Kata kunci Dokter, Gigi, Java, MySql, Pasien.
Androgynous Fasteners for Robotic Structural Assembly
Venue: 2020 IEEE Aerospace Conference
Year: 2020

We describe the design and analysis of an androgynous fastener for autonomous robotic assembly of high performance structures. The design of these fasteners aims to prioritize ease of assembly through simple actuation with large driver positioning tolerance requirements, while producing a reversible mechanical connection with high strength and stiffness per mass. This can be applied to high strength to weight ratio structural systems, such as discrete building block based systems that offer reconfigurability, scalability, and system lifecycle efficiency. Such periodic structures are suitable for navigation and manipulation by relatively small mobile robots. The integration of fasteners, which are lightweight and can be robotically installed, into a high performance robotically managed structural system is of interest to reduce launch energy requirements, enable higher mission adaptivity, and decrease system life cycle costs.
Correlation measurements on small mobile devices
Venue: 2012 6th European Conference on Antennas and Propagation (EUCAP)
Year: 2012

Here, analysis of the antenna correlation at the design stage is done, with focus on measurement techniques. Various theoretical definitions of correlations are used with the corresponding measured data required. The problems related to the coaxial measurement cables, when calculating correlation through the radiation patterns, are analyzed and an optical solution proposed. It is shown that using optical cable replacement, repeatable and accurate measurements of the envelope correlation coefficient can be made.
Talking heads synthesis from audio with deep neural networks
Venue: 2015 IEEE/SICE International Symposium on System Integration (SII)
Year: 2015

Talking heads synthesis with expressions from speech is proposed in this paper. Talking heads synthesis can be considered as a learning problem of sequence to sequence mapping, which consists of audio as input and video as output. To synthesize talking heads, we use SAVEE database which consists of videos of multiple sentences speeches recorded from front of face. Audiovisual data can be considered as two parallel sequential data of audio and visual features and it is composed of continuous value. Thus, audio and visual features of our dataset are represented by a regression model. In this research, the regression model is trained with long short term memory (LSTM) by minimizing mean squared error (MSE) Then, audio features are used as input and visual features are used as target of LSTM. Thereby, talking heads are synthesized from speech. Our method is proposed to use lower level audio features than phonemes and it enables to synthesize talking heads with expressions while existing researches which use phonemes as audio features only can synthesize neutral expression talking heads. With SAVEE database, we achieved the minimum MSE 17.03 on our testing dataset. In experiment, we use mel frequency cepstral coefficient (MFCC) AMFCC and A2 MFCC with energy as audio feature and active appearance model (AAM) on entire face region as visual feature.
Kelvin Helmholtz Instability in Solar Chromospheric Jets: Theory and Observation
Year: 2016

Using data obtained by the high resolution CRisp Imaging SpectroPolarimeter instrument on the Swedish 1 m Solar Telescope, we investigate the dynamics and stability of quiet Sun chromospheric jets observed at disk center. Small scale features, such as Rapid Redshifted and Blueshifted Excursions, appearing as high speed jets in the wings of the H$\alpha$ line, are characterized by short lifetimes and rapid fading without any descending behavior. To study the theoretical aspects of their stability without considering their formation mechanism, we model chromospheric jets as twisted magnetic flux tubes moving along their axis, and use the ideal linear incompressible magnetohydrodynamic approximation to derive the governing dispersion equation. Analytical solutions of the dispersion equation indicate that this type of jet is unstable to Kelvin Helmholtz instability (KHI) with a very short (few seconds) instability growth time at high upflow speeds. The generated vortices and unresolved turbulent flows associated with the KHI could be observed as broadening of chromospheric spectral lines. Analysis of the H$\alpha$ line profiles shows that the detected structures have enhanced line widths with respect to the background. We also investigate the stability of a larger scale H$\alpha$ jet that was ejected along the line of sight. Vortex like features, rapidly developing around the jet's boundary, are considered as evidence of the KHI. The analysis of the energy equation in the partially ionized plasma shows that the ion neutral collisions may lead to the fast heating of the KH vortices over timescales comparable to the lifetime of chromospheric jets.
Prediction and evaluation of the lipase inhibitory activities of tea polyphenols with 3D QSAR models
Venue: Scientific reports
Year: 2016

The extraordinary hypolipidemic effects of polyphenolic compounds from tea have been confirmed in our previous study. To gain compounds with more potent activities, using the conformations of the most active compound revealed by molecular docking, a 3D QSAR pancreatic lipase inhibitor model with good predictive ability was established and validated by CoMFA and CoMISA methods. With good statistical significance in CoMFA (r2cv 0.622, r2 0.956, F 261.463, SEE 0.096) and CoMISA (r2cv 0.631, r2 0.932, F 75.408, SEE 0.212) model, we summarized the structure activity relationship between polyphenolic compounds and pancreatic lipase inhibitory activities and find the bulky substituents in R2, R4 and R5, hydrophilic substituents in R1 and electron withdrawing groups in R2 are the key factors to enhance the lipase inhibitory activities. Under the guidance of the 3D QSAR results, (2R,3R,2'R,3'R) desgalloyloolongtheanin 3,3' O digallate (DOTD) a potent lipase inhibitor with an IC50 of 0.08 mg/ml, was obtained from EGCG oxidative polymerization catalyzed by crude polyphenol oxidase. Furthermore, DOTD was found to inhibit lipid absorption in olive oil loaded rats, which was related with inhibiting the activities of lipase in the intestinal mucosa and contents.
Grb2 depletion under non stimulated conditions inhibits PTEN, promotes Akt induced tumor formation and contributes to poor prognosis in ovarian cancer
Venue: Oncogene
Year: 2016

In the absence of extracellular stimulation the adaptor protein growth factor receptor bound protein (Grb2) and the phospholipase Plcg1 compete for the same binding site on fibroblast growth factor receptor 2 (FGFR2) Reducing cellular Grb2 results in upregulation of Plcg1 and depletion of the phospholipid PI(4,5)P2. The functional consequences of this event on signaling pathways are unknown. We show that the decrease in PI(4,5)P2 level under non stimulated conditions inhibits PTEN activity leading to the aberrant activation of the oncoprotein Akt. This results in excessive cell proliferation and tumor progression in a xenograft mouse model. As well as defining a novel mechanism of Akt phosphorylation with important therapeutic consequences, we also demonstrate that differential expression levels of FGFR2, Plcg1 and Grb2 correlate with patient survival. Oncogenesis through fluctuation in the expression levels of these proteins negates extracellular stimulation or mutation and defines them as novel prognostic markers in ovarian cancer.
KAJIAN ADAPTASI BEBERAPA VARIETAS UNGGUL JAGUNG DI KABUPATEN MALUKU BARAT DAYA (MBD)
Year: 2016

Adaptation study of hybrid maize varieties and improved varieties do subdistrict Wonreli Southwest Maluku district from September to December 2012. Study using a randomized block design repeated 3 times and farmers as replicates. Varieties tested is the Bima 3, Bima 4, Bima 5, Srikandi kuning, Lamuru, Lagaligo and Lokal MBD as a comparison. Fertilization is done drill, a distance of 5 7 cm from the plant, fertilizer dose of 300 kg urea, 200 kg SP 36, 100 kg of KCl and 1 2 t.ha 1manure. Urea fertilizer done twice, is 100 kg urea and entire SP36 and KCl at the age of 7 10 plants hst and residual urea 200 kg administered at 30 dap. Parameters observed plant height at harvest, High cob, cob diameter, cob length, number of rows/cob, number of grains row, weight of 1000 seeds and Yield per hectare. The results of the study showed that of the varieties tested turned out varieties Bima 5 higher result of (6.7 t.ha 1) and the lowest result is Lokas MBD 5.7 t.ha 1)
THE LITERATURE REVIEW OF TECHNOLOGY ADOPTION MODELS AND THEORIES FOR THE NOVELTY TECHNOLOGY
Year: 2017

This paper contributes to the existing literature b y comprehensively reviewing the concepts, applications and development of technology adoption m dels and theories based on the literature review with the focus on potential application for the novelty technology of single platform Epayment. These included, but were not restricted to the Theory of Diffusion of Innovations (DIT) (Rogers, 1995) the Theory of Reasonable Action (TR A) (Fishbein and Ajzen, 1975) Theory of Planned Behavior (TPB) (Ajzen, 1985, 1991) Decompo sed Theory of Planned Behaviour, (Taylor and Todd, 1995) the Technology Acceptance Model (TAM) (Davis, Bogozzi and Warshaw, 1989, Technology Acceptance Model 2 (TAM2) Venkatesh and Davis (2000) and Technology Acceptance Model 3 (TAM3) Venkatesh and Bala (2008) These reviews will shed some light and potential applications for technolog y applications for future researchers to conceptualize, distinguish and comprehend the under lying technology models and theories that may affect the previous, current and future applica tion of technology adoption.
Multi choice Relational Reasoning for Machine Reading Comprehension
Venue: COLING
Year: 2020

This paper presents our study of cloze style reading comprehension by imitating human reading comprehension, which normally involves tactical comparing and reasoning over candidates while choosing the best answer. We propose a multi choice relational reasoning (McR^2) model with an aim to enable relational reasoning on candidates based on fusion representations of document, query and candidates. For the fusion representations, we develop an efficient encoding architecture by integrating the schemes of bidirectional attention flow, self attention and document gated query reading. Then, comparing and inferring over candidates are executed by a novel relational reasoning network. We conduct extensive experiments on four datasets derived from two public corpora, Children's Book Test and Who DiD What, to verify the validity and advantages of our model. The results show that it outperforms all baseline models significantly on the four benchmark datasets. The effectiveness of its key components is also validated by an ablation study.