nils-herrmann/clean_scirepeval huggingface dataset:
A Componential Analysis of the Bamboo Fans' Names in Thailand: an Ethnosemantic Study
Year: 2016

Bamboo fans are a unique Thai handicraft made of bamboo strips plaited into various patterns and colors. They have been made in Banphraek district, Phra Nakorn Si Ayutthaya province, Thailand for over 80 years. Apart from being local products which contributes to a number of income, they are served as the district cultural heritage identity for the district. Unfortunately, it is unlikely to find new generation who want to carry on this local wisdom and it will be disappeared very soon. Several attempts have concerned with folklores but there has been no study on their names and how to make them thoroughly and systematically. In this linguistic study, the meanings of the names of traditional Thai bamboo fans were analyzed by employed ethnosemantic approach in order to discover the system of naming of the Thai bamboo fans according to their patterns in order to reveal people's thoughts and worldviews reflected on the fans' names. The data was elicited from handful elderly fan makers in the village. The results show that there are 17 traditional names of bamboo fan patterns. Each pattern is distinguished from one another by seven dimensions of contrast, as follows: (1) the shape of cross, (2) the shape of square, (3) the shape of triangle, (4) the shape of circle, (5) the shape of heart, (6) the shape of asterisk, and (7) the shape of spot. In conclusion, this ethnosemantic study can reflect that the villagers are closely connected to nature and the objects around them. It also reveals people's rich imagination of constructing and combining such simple geometrical forms into various shapes and lines
Description of a CAD Protocol for the Simulation of Dental Treatment of Amelogenesis Imperfecta
Year: 2018

Amelogenesis imperfecta (AI) is an inherited disorder of development that primarily affects dental enamel. The etiology of this pathology is the mutation or the expression alteration of 13 genes  The tissues of both dentitions being reached, the aesthetics of the smile is lost from childhood. The psychosocial impact of AI imposes a relatively young functional and aesthetic care  The difficulty of the reconstruction of tooth tissues in definitive dentition is based on two elements: the associated dento facial dysmorphosis and the difficulties of bonding due to the alteration of the adhesive bond to the affected enamel. Management with the best prognosis is therefore based on a treatment combining orthodontics and indirect reconstructions  We propose here, the analysis of a case then and the simulation of the treatment by CAD. The interest of this approach is to be able to perform the simulation of the wax up to offer a coherent therapeutic proposal, both functional and aesthetic.
THE DYNAMICS IN THE RECOGNITION OF CUSTOMARY JUSTICE IN THE POLITICS OF LAW OF THE JUDICIARY IN INDONESIA
Year: 2014

This study aims at discussing the dynamics of the legal recognition of customary justice in politics of law of the judicial power in Indonesia. In accordance with the nature of the analysis, namely, the normative legal analysis, the approach used in this study is the statute approach completed with historical and futuristic approach of the law. The study results show that the recognition of customary justice in the politics of law in Indonesia has been dynamic along with the change of government. In the colonial time of the Dutch East Indies government, there were two forms of customary justice formally recognized, namely, the indigenous justice inheemsche rechtspraak and the village justice dorpjustitie .These conditions remained prevailing at the time of the Japanese occupation and in the early days of Indonesian independence. In 1951, the existence of customary courts were abolished gradually and brought an end in 1970 in which the existence of the formal justice system of out of the state court settlement was not allowed anymore. The customary courts abolished in 1951 were indigenous justice (inheemsche rechtspraak) while the existence of village justice (dorpjustitie) continued to berecognized. In the Judicial Power Act of 2009 applied at present, there is no provision which gives recognition of customary justice, but in the laws governing special autonomy for Papua Province a province in eastern Indonesia the existence of customary court is explicitly recognized From the program of national legislation in the House of Representatives of the Republic of Indonesia, it is known that in the future it seems customary justice will be recognized nationally by legislation governing the unity of customary law society Keywords: customary justice, the unity of customary law society, politics of law.
isletmelerin Sermaye Yapilari ve Firma Degerleri Arasindaki Iliski BIST Sinai Endeksinde Bir Uygulama1 (The Relationship Between Capital Structures and Company Values of Companies An Application in the BIST Industrial Index)
Year: 2020

Enstitusu tarafindan kabul edilen yuksek lisans tez calismasindan turetilmistir. Onerilen Atif/ Suggested Citation Sisman, M. E. Comlekci, I. (2019) Isletmelerin Sermaye Yapilari ve Firma Degerleri Arasindaki Iliski BIST Sinai Endeksinde Bir Uygulama, Isletme Arastirmalari Dergisi, 11 (4) 3086 3103 ISLETME ARASTIRMALARI DERGISI JOURNAL OF BUSINESS RESEARCH TURK 2019, 11(4) 3086 3103
Object Guided Remote Sensing Image Scene Classification Based on Joint Use of Deep Learning Classifier and Detector
Venue: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2020

Due to the extremely complex composition of remote sensing scenes, REmote Sensing Image Scene Classification (RESISC) is still a challenging task. To further improve classification accuracy, this article introduces a deep learning detector into RESISC and proposes to classify remote sensing images according to the detected class specific signature objects. Inspired by the classification procedure of human vision system, we design a classification framework that utilizes class specific signature objects of scene classes to guide scene classification. When performing image classification, the proposed framework first adopts a deep learning classifier to create an initial judgment of the scene class for an image and then determines the scene class based on the class specific signature objects detected from the image. The proposed method can compete with the state of the art methods on three RESISC benchmark datasets, including NWPU RESISC45, AID, and OPTIMAL 31.
Small Energy Masking for Improved Neural Network Training for End To End Speech Recognition
Venue: ICASSP 2020 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2020

In this paper, we present a Small Energy Masking (SEM) algorithm, which masks inputs having values below a certain threshold. More specifically, a time frequency bin is masked if the filterbank energy in this bin is less than a certain energy threshold. A uniform distribution is employed to randomly generate the ratio of this energy threshold to the peak filterbank energy of each utterance in decibels. The unmasked feature elements are scaled so that the total sum of the feature values remain the same through this masking procedure. This very simple algorithm shows relatively 11.2% and 13.5% Word Error Rate (WER) improvements on the standard LibriSpeech test clean and test other sets over the baseline end to end speech recognition system. Additionally, compared to the input dropout algorithm, SEM algorithm shows relatively 7.7% and 11.6% improvements on the same LibriSpeech test clean and test other sets. With a modified shallow fusion technique with a Transformer LM, we obtained a 2.62% WER on the Lib riSpeech test clean set and a 7.87% WER on the LibriSpeech test other set.
Iterative Differential Characteristic of TRIFLE BC
Venue: IACR Cryptol. ePrint Arch.
Year: 2019

TRIFLE is a Round 1 candidate of the NIST Lightweight Cryptography Standardization process. In this paper, we present an interesting 1 round iterative differential characteristic of the underlying block cipher TRIFLE BC used in TRIFLE, which holds with probability of (2^ 3} Consequently, it allows to mount distinguishing attack on TRIFLE BC for up to 43 (out of 50) rounds with data complexity (2^{124} and time complexity (2^{124} Most importantly, with such an iterative differential characteristic, the forgery attack on TRIFLE can reach up to 21 (out of 50) rounds with data complexity (2^{63} and time complexity (2^{63} Finally, to achieve key recovery attack on reduced TRIFLE, we construct a differential characteristic covering three blocks by carefully choosing the positions of the iterative differential characteristic. As a result, we can mount key recovery attack on TRIFLE for up to 11 rounds with data complexity (2^{63} and time complexity (2^{104} Although the result in this paper cannot threaten the security margin of TRIFLE, we hope it can help further understand the security of TRIFLE.
Adaptive Neural Network Dynamic Surface Control Algorithm for Pneumatic Servo System
Year: 2019

Pneumatic servo system is widely applied in many industries, which has advantages comparing with electromechanical and hydraulic system because of its fast response, high performance quality and low cost. However, the servo control methods for pneumatic system still have some inevitable drawbacks and problems remaining to be researched. In this paper, a position feedback dynamic surface control is designed which is based on our pneumatic actuator model. More importantly, in order to overcome model uncertainties, noise interference and external force disturbance, an adaptive neural network dynamic surface controller is proposed to overcome the negative effects. Besides, the stability of the pneumatic system is substantiated by Lyapunov stability theorem. Finally, the results of simulation experiment also prove that the adaptive neural network dynamic surface controller has more advantages than the traditional controllers in pneumatic position servo control.
PTU 135 How Much Gluten is the General Population Consuming and Does It Relate to Symptoms?
Year: 2016

Gluten is a ubiquitous part of a western diet. It is implicated for causing an array of disorders, which have both intestinal and/or extraintestinal manifestations. Our understanding of this heterogeneous group of gluten related disorders is advancing, however uncertainty exists as to how much gluten the general population is consuming. This study aims to address this knowledge gap and also assess the prevalence of self reported gluten sensitivity within the general population.  Between September and October 2015 a population based survey was undertaken in Sheffield, UK. Members of the general public, all over the age of 16 years, were invited to complete a modified version of a previously validated written questionnaire. This questionnaire assessed demographic information, GI conditions and also determined the presence of gluten sensitivity (GS) In addition, total gluten consumption was calculated using a food frequency questionnaire. Participants were asked about their use of a gluten free diet (GFD) and whether they had seen a healthcare professional for their symptoms. A diagnosis of coeliac disease (CD) was determined if individuals had a doctor diagnosis of CD, and were also taking a GFD.  1003 adults completed the population based survey (59% female, median age 31 years (16 86 years) The mean consumption of gluten per day for this group was 13.2 g (s.d =9.2 g) The self reported prevalence of GS was 32.5% (326/1003, female 70% [P 0.0001] age range 17 82, median age 35 yrs) with 3.7% (38/1003) on a GFD and 1.1% (12/1003) having CD. The proportion of GS individuals who had seen a doctor for their symptoms was 18.3% (65/326) Individuals with GS had an increased prevalence of fulfilling the Rome III criteria for irritable bowel syndrome, in comparison with those without GS (31.3% vs. 5.61% odds ratio 7.66, p 0.0001) In addition, mean daily consumption of gluten was considerably lower in this GS group compared to the non GS group (10.8 g vs. 14.4 g, p 0.0001)  This is the first study assessing gluten consumption in a UK population. Findings from our work highlight that sensitivity to gluten based products is common, and that affected individuals have a higher prevalence of IBS. Although only a minority of individuals maintained a gluten free diet, individuals with gluten related symptoms evidently were electing to reduce their gluten consumption. Disclosure of Interest None Declared
Gelato: Feedback driven and Guided Security Analysis of Client side Web Applications
Venue: ArXiv
Year: 2020

Even though a lot of effort has been invested in analyzing client side web applications during the past decade, the existing tools often fail to deal with the complexity of modern JavaScript applications. However, from an attacker point of view, the client side of such web applications can reveal invaluable information about the server side. In this paper, first we study the existing tools and enumerate the most crucial features a security aware client side analysis should be supporting. Next, we propose GELATO to detect vulnerabilities in modern client side JavaScript applications that are built upon complex libraries and frameworks. In particular, we take the first step in closing the gap between state aware crawling and client side security analysis by proposing a feedback driven security aware guided crawler that is able to analyze complex frameworks automatically, and increase the coverage of security sensitive parts of the program efficiently. Moreover, we propose a new lightweight client side taint analysis that outperforms the start of the art tools, requires no modification to browsers, and reports non trivial taint flows on modern JavaScript applications.
Worker Flows and Wage Growth Over the Life Cycle: A Cross Country Analysis
Year: 2017

Using panel data for 1990 2014 from 12 OECD countries, I document three facts about cross country labor market outcomes. First, worker flows and life cycle wage growth differ substantially across countries. Second, the fluidity of a country's labor market covaries positively with life cycle wage growth of its workers. Third, the direct effect of job shopping accounts for only a quarter of this. I build an equilibrium life cycle model of the labor market that features search and human capital accumulation, and show that a faster rate of climbing the job ladder increases incentives to accumulate human capital. A calibrated version of the model suggests that differences in the cost to firms of hiring may account for all of the empirical covariation between fluidity, on the one hand, and wage growth and output per capita, on the other, and 43 45 percent of the overall variation in these measures.
REABILITACAO ESTETICA COM COROAS DE CERAMICA LIVRES DE METAL RELATO DE CASO
Year: 2019

A Odontologia restauradora vem desenvolvendo, ano apos ano, novos materiais para recuperacao dos tecidos dentarios perdidos. Sabe se que um dos materiais mais utiliza dos em reabilitacoes esteticas e a metaloceramica, vantajoso por aliar a alta transluci dez e variedade de matizes das porcelanas feldspaticas a resistencia mecanica dos me tais, usados como infra estrutura. Entretanto, acompanhamentos clinicos longitudinais revelam retracoes gengivais e percepcao visual do metal, mesmo coberto pela porcela na. Ja as ceramicas a base de oxido de zirconia apresentam alta resistencia a flexao, opacidade e cor semelhante aos tecidos dentarios. Tais caracteristicas as indicam como infra estrutura para coroas totais estratificadas livres de metal, principalmente em dentes anteriores, como alternativas as coroas metaloceramicas. No presente trabalho, e des crito um caso clinico no qual foram realizadas restauracoes indiretas com infra estrutura em zirconia na regiao antero superior. Alem disso, sao discutidas as propriedades opti cas e mecanicas do material, contextualizando com o caso relatado.
SEMI SUPERVISED LEARNING WITH MULTI CLASS SIMPLE RECYCLED SELECTION USING SEQUENTIAL FORWARD SELECTION
Year: 2015

In semi supervised learning, one frequent problem is how to find useful unlabeled data to join labeled data in building classification models. Simple Recycled Selection (SRS) is a method to rank unlabeled data based on confidence levels to build an ensemble of weak classifiers, working with two class datasets. Sequential Forward Selection (SFS) is a greedy deterministic search strategy usually applied to feature selection, that make use of a wrapper method to inquire the best feature subset to train a model. The objective of the present work is to modify the SFS search strategy to help SRS ensembles in the classification of multi class datasets using the one versus all approach. SRS ensembles of support vector machines, decision trees and nearest neighbors classifiers are trained and tested using the proposed algorithm. Regular versions of support vector machines with SFS, decision trees and nearest neighbors classifiers are used as comparison. Benchmark datasets are used as training and test for the algorithms. Results show that the error rates of SRS ensembles are lower for most two class and multi class datasets.  Semi supervised learning, SRS, SFS, Multi class, Cascade classifier.
[Clinical examination for patellofemoral problems]
Venue: Der Orthopade
Year: 2008

Patellofemoral pain and instability account for 25% of all sports related knee problems. However, definitive analysis seems to be difficult. Descriptive findings like "anterior knee pain" "patellofemoral pain syndrome" or "chondromalacia" are used instead of diagnosis. One reason may be the complex pathomechanics of the patellofemoral joint which is suspended between the pelvis, the femur, and the tibia and subsequently is influenced by the whole lower extremity from the hip down to the foot. On the other hand, different signs and functional tests are in use with at times lack of quantification and ambiguous interpretation. The current manuscript reviews the commonly used signs and functional tests, analyzes them based on the current literature, and arranges them in a practical manner for physical examination. A MEDLINE literature search and special textbooks regarding patellofemoral disorders were used; 43 signs and tests were found. The examiner can quantify 18 of these findings on a nominal and 15 on an ordinal scale. Thus, this manuscript provides a standardized algorithm for physical examination with a collection of quantifiable findings, which are of growing importance to justify adequate diagnostics and treatment.
Novel targeted therapies in peripheral T cell lymphoma.
Venue: Discovery medicine
Year: 2013

Peripheral T cell lymphomas (PTCL) non Hodgkin lymphomas characterized by having features of T cells that have matured in the thymus, are a heterogeneous group of clinical entities. Compared with B cell lymphomas, they are less common, more difficult to diagnose and classify, more aggressive, and have inferior outcomes with current treatment paradigms. They are also less completely understood in terms of how different PTCL types correspond to normal T cell development, and in identifying cell signaling pathways as targets for new therapies. Recent studies with novel targeted therapies as single agents or in combination with other drugs have illustrated promising outcomes both for relapsed and frontline PTCL. We first briefly review classification, prognostic indices, and results of initial therapy of various T cell lymphomas. We then review recent studies of chemotherapy, monoclonal antibody based therapy directed at cell surface targets, small molecule inhibitors of intracellular targets such as histone deacetylases and the proteasome, and agents that disrupt stromal interactions. Investigations that enhance our knowledge of T cell molecular biology and integrate novel targeted agents into the treatment algorithm for PTCL will be keys to improved outcomes for patients with PTCL.
Deep Learning Based Low light Enhancement and Noise Suppression in USV Imaging System
Venue: ICRAI
Year: 2020

With the rapid development of artificial intelligence technology and autonomous navigation technology, the unmanned surface vessel (USV) industry has developed accordingly, and it has played an important role in the fields of water quality monitoring, maritime inspection, and maritime safety assurance. However, USV is easily affected by the external lighting environment. In the case of insufficient lighting, the collected images have the characteristics of low brightness, low contrast and low resolution, and are extremely susceptible to external noise interference, making USV difficult obtain input requirements that meet the visual tasks such as target recognition and semantic segmentation. In this paper, we propose a deep learning based low light image enhancement and noise suppression method (LENet) Specifically, LENet is used to map the low light image to the normal light image through a deep Unet network, and CBM3D further suppresses the interference noise in the image to achieve the enhancement of the low light image. We enhance the generalization ability and robustness of the deep network by embedding dilated convolutions and dense blocks in the deep Unet network. Structural similarity (SSIM) and norm are used as the loss function to further improve the quality of the enhanced image. The experimental results show that the deep network proposed in this paper improves the brightness and contrast of the images collected by the USV under insufficient lighting conditions, which can meet the input requirements of the USV visual task.
Ensemble Coordination Approach in Multi AGV Systems Applied to Industrial Warehouses
Venue: IEEE Transactions on Automation Science and Engineering
Year: 2015

This paper deals with a holistic approach to coordinate a fleet of automated guided vehicles (AGVs) in an industrial environment. We propose an ensemble approach based on a two layer control architecture and on an automatic algorithm for the definition of the roadmap. The roadmap is built by considering the path planning algorithm implemented on the hierarchical architecture and vice versa. In this way, we want to manage the coordination of the whole system in order to increase the flexibility and the global efficiency. Furthermore, the roadmap is computed in order to maximize the redundancy, the coverage and the connectivity. The architecture is composed of two layers. The low level represents the roadmap itself. The high level describes the topological relationship among different areas of the environment. The path planning algorithm works on both these levels and the subsequent coordination among AGVs is obtained exploiting shared resource (i.e. centralized information) and local negotiation (i.e. decentralized coordination) The proposed approach is validated by means of simulations and comparison using real plants. Note to Practitioners The motivation of this work grows from the need to increase the flexibility and efficiency of current multi AGV systems. In particular, in the current state of the art the AGVs are guided through a manually defined roadmap with ad hoc strategies for coordination. This is translated into high setup time requested for installation and the impossibility to easily respond to dynamic changes of the environment. The proposed method aims at managing all the design, setup and control process in an automatic manner, decreasing the time for setup and installation. The flexibility is also increased by considering a coordination strategy for the fleet of AGVs not based on manual ad hoc rules. Simulations are performed in order to compare the proposed approach to the current industrial one. In the future, industrial aspects, as the warehouse management system, will be integrated in order to achieve a real and complete industrial functionality.