nils-herrmann/clean_scirepeval huggingface dataset:
Research of automatic recognition of car license plates based on deep learning for convergence traffic control system
Year: 2021

The technology that can recognize the license plates of vehicles in real time and manage them automatically is a key element of building an intelligent transportation system. License plate recognition is the most important technique in vehicle image processing used to identify a vehicle. Object recognition using a camera is greatly influenced by environmental factors in which the camera is installed. When the vehicle image is acquired, the image is distorted due to the tilting of the license plate, reflection of light, lighting effects, rainy weather, and nighttime, so that it is difficult to accurately recognize the license plate. In addition, when the geometric distortion of the license plate image or the degradation of the image quality is intensified, it may be more difficult to automatically recognize the license plate image. Therefore, in this paper, we propose a deep learning based vehicles' license plate recognition method to detect license plate and recognize characters accurately in complex and diverse environments. As a deep learning model, the YOLO model can be used to detect robust license plates in a variety of environments and to recognize characters quickly and accurately. It can also be seen that the license plate accurately recognizes the license plate with geometric distortion.
Form and Function in Human Song
Venue: Current Biology
Year: 2018

Humans use music for a variety of social functions: we sing to accompany dance, to soothe babies, to heal illness, to communicate love, and so on. Across animal taxa, vocalization forms are shaped by their functions, including in humans. Here, we show that vocal music exhibits recurrent, distinct, and cross culturally robust form function relations that are detectable by listeners across the globe. In Experiment 1, internet users (n 750) in 60 countries listened to brief excerpts of songs, rating each song's function on six dimensions (e.g. "used to soothe a baby" Excerpts were drawn from a geographically stratified pseudorandom sample of dance songs, lullabies, healing songs, and love songs recorded in 86 mostly small scale societies, including hunter gatherers, pastoralists, and subsistence farmers. Experiment 1 and its analysis plan were pre registered. Despite participants' unfamiliarity with the societies represented, the random sampling of each excerpt, their very short duration (14 s) and the enormous diversity of this music, the ratings demonstrated accurate and cross culturally reliable inferences about song functions on the basis of song forms alone. In Experiment 2, internet users (n 1,000) in the United States and India rated three contextual features (e.g. gender of singer) and seven musical features (e.g. melodic complexity) of each excerpt. The songs' contextual features were predictive of Experiment 1 function ratings, but musical features and the songs' actual functions explained unique variance in function ratings. These findings are consistent with the existence of universal links between form and function in vocal music.
How to Measure Intraocular Pressure: An Updated Review of Various Tonometers
Venue: Journal of clinical medicine
Year: 2021

Intraocular pressure (IOP) is an important measurement that needs to be taken during ophthalmic examinations, especially in ocular hypertension subjects, glaucoma patients and in patients with risk factors for developing glaucoma. The gold standard technique in measuring IOP is still Goldmann applanation tonometry (GAT) however, this procedure requires local anesthetics, can be difficult in patients with scarce compliance, surgical patients and children, and is influenced by several corneal parameters. Numerous tonometers have been proposed in the past to address the problems related to GAT. The authors review the various devices currently in use for the measurement of intraocular pressure (IOP) highlighting the main advantages and limits of the various tools. The continuous monitoring of IOP, which is still under evaluation, will be an important step for a more complete and reliable management of patients affected by glaucoma.
Significados de la politica en la Grecia clasica
Year: 2011

La experiencia de la Grecia antigua creo el concepto de politica y sistematizo alrededor de el una concepcion profunda de su significado. Los tres pensadores clasicos de la filosofia politica (Socrates aunque no produjo escritos propios; Platon quien solamente enfatizo la politica ideal, y Aristoteles con su estudio de las constituciones de las ciudades estado) propusieron la dialectica entre la realidad y los modelos ideales con el fin de proponer estrategias de accion para los gobiernos y para el ciudadano. Este articulo trata de ofrecer un panorama del surgimiento del pensamiento politico en la Grecia antigua desde los escritos de Homero y Hesiodo, pasando por la formacion de las ciudades estado y los pensadores presocraticos hasta el siglo IV a.C. con la aparicion de la filosofia sistematica para concluir que lo fundamental de su vision sigue siendo marco del debate sobre el devenir de la politica y del modelo democratico en las sociedades contemporaneas.
Structural transformation, inequality, and inclusive growth in China
Year: 2020

In this paper, we analyse the relationship between China's structural transformation and the inclusiveness of its economic growth. China's economy has undergone significant structural changes since it initiated the economic reforms in 1978. Economic activities have shifted from the low productivity agricultural sector to the high productivity industrial sector and, more recently, the tertiary sector, with a large portion of the labour force moving from rural to urban areas, from inland to coastal regions, and from the public to the private sectors.
PROGRAM SIMULASI DELIVERY ORDER DENGAN MENGGUNAKAN MODEL NEXT EVENT TIME ADVANCE STUDI KASUS PADA PT. NINGRAT MANDIRI
Year: 2009

Sistem simulasi delivery order merupakan suatu sistem yang mampu memberikan keputusan kepada pihak pihak yang berkepentingan dengan cara memberikan suatu prediksi jumlah pegawai yang harus berada di tempat kerja pada tiap segmen waktu sehingga nantinnya efisiensi, efektifitas dan produktifitas pegawai dapat meningkat. Permasalahan dari penelitian Tugas Akhir ini adalah tidak adanya sistem yang dapat membuat keputusan yang tepat dalam menentukan jumlah pegawai delivery order yang dibutuhkan dalam pengiriman makanan kepada konsumen. Prediksi jumlah pegawai diperlukan agar tingkat efisiensi, efektifitas dan produktifitas pegawai dapat terjaga pada level terbaik. Pada Tugas Akhir ini penulis menggunakan metode next event time advance dimana yang mendekat pada waktu kejadian berikutnya yang paling dekat (diutamakan) sebagai event selanjutnya, yang menunjuk keadaan sistem yang diperbaruhi untuk menjelaskan fakta bahwa suatu kejadian telah berlangsung secara kontinyu dan hal tersebut berlangsung secara terus menerus pada segmen waktu. Hasil dari proses simulasi ini akan memberikan saran keputusan yang lebih baik yang digunakan untuk menentukan jumlah pegawai delivery order pada tiap harinya. Setelah semua kejadian dan data data yang bersangkutan mulai dari kedatangan telepon, lama telepon, jumlah pesanan hingga tujuan pesanan telah diinputkan ke sistem simulasi. Hasil akhir yang didapatkan berupa laporan yang menunjukkan hasil proses simulasi.
NADPH from the oxidative pentose phosphate pathway drives the operation of cyclic electron flow around photosystem I in high intertidal macroalgae under severe salt stress.
Venue: Physiologia plantarum
Year: 2016

Pyropia yezoensis (Bangiales, Rhodophyta) is a representative species of high intertidal macroalgae, whose blades can tolerate extreme stresses, such as salt stress and desiccation. In this study, the photosystem (PS) responses of P. yezoensis blades under salt stress were studied. Our results showed that when the effective photochemical quantum yield of PS (Y) II decreased to almost zero under high salt stress, YI still had a relatively high activity rate. PSII was therefore more sensitive to salt stress than PSI. Furthermore, in the presence of 3 (3' 4' dichlorophenyl) 1,1 dimethylurea (DCMU) YI rose as salinity increased. The YI values for DCMU treated thalli decreased in the presence of glucose 6 phosphate dehydrogenase (EC 1.1.1.49, G6PDH) inhibitor (glucosamine, Glucm) The YI values were ~0.09 in the presence of methyl viologen (MV) and almost zero in the presence of dibromothymoquinone (DBMIB) These results demonstrated that under severe salt stress (120%0 salinity) PSI activity was driven from a source other than PSII, and that stromal reductants probably supported the operation of PSI. Under salt stress, the starch content decreased and soluble sugar levels increased. The G6PDH and 6 phosphogluconate dehydrogenase (EC 1.1.1.44) activities increased, but cytosolic glyceraldehyde 3 phosphate dehydrogenase (EC 1.2.1.12) activity decreased. Furthermore, the NADPH content increased, but NADH decreased, which suggested that soluble sugar entered the oxidative pentose phosphate pathway (OPPP) All these results suggested that NADPH from OPPP increases the cyclic electron flow around PSI in high intertidal macroalgae under severe salt stress.
Degraded Document Analysis and Extraction of Original Text Document: An Approach without Optical Character Recognition
Year: 2017

Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.  Grayscale image format, image fusing, SURF detection, YCbCr image format.
Hashing Nets for Hashing: A Quantized Deep Learning to Hash Framework for Remote Sensing Image Retrieval
Venue: IEEE Transactions on Geoscience and Remote Sensing
Year: 2020

Fast and accurate remote sensing image retrieval from large data archives has been an important research topic in the remote sensing research literature. Recently, hashing based remote sensing image retrieval has attracted extreme attention because of its efficient search capabilities. Especially, deep remote sensing image hashing algorithms have been developed based on convolutional neural networks (CNNs) and have shown effective retrieval performance. However, implementing a deep hashing network tends to be highly expensive in terms of storage space and computing resources to be suitable for on orbit remote sensing image retrieval, which usually operates on resource limited devices such as satellites and unmanned aerial vehicles (UAVs) To address this limitation, we propose to hash a deep network that in turn hashes remote sensing images. Specifically, we develop a quantized deep learning to hash (QDLH) framework for large scale remote sensing image retrieval. The weights and activation functions in the QDLH framework are binarized to low bit representations, which require comparatively much less storage space and computing resources. The QDLH results in a lightweight deep neural network for effective remote sensing image hashing. We conduct extensive experiments on two public remote sensing image data sets by incorporating several state of the art network architectures into our QDLH methodology for remote sensing image hashing. The experimental results demonstrate that the proposed QDLH is effective in saving hardware resources in terms of both storage and computation. Moreover, superior remote sensing image retrieval performance is also achieved by our QDLH, compared with state of the art deep remote sensing image hashing methods.
Legislating on Violence Against Women: A Critical Analysis of Nigeria's Recent Violence Against Persons (Prohibition) Act, 2015
Year: 2016

In many African countries, as in other countries around the world, women suffer violence on the basis of their gender. Unfortunately, many countries lack legislation that provide effective protections against gender based violence. Evidence from Nigeria, including the passage of new legislation at federal and state levels, suggests some progress. How effective such laws will be is yet to be seen. This paper begins the process of investigating the potential for the effectiveness of these new laws by conducting an in depth analysis of Nigeria's recently enacted Violence Against Persons (Prohibition) Act, 2015. This examines the relevance of the Act and its significance for issues around violence against women. This critique investigates the provisions of the Act alongside internationally accepted best practices and standards on legislation against gender based violence. From this analysis, the article identifies gaps within the provisions articulated in the Act. It also examines the place of the VAPP Act amongst the pantheon of extant laws addressing violence against women. It argues that, by itself, the law will have only a limited impact, in part because of its limited geographical reach. This impact can only be moderated by intensive advocacy to ensure that this legislation is adopted by all States in the federation. The paper suggests the next steps after enactment to ensure effective implementation. The article concludes that the enactment of the Act is a positive step, which has the potential to provide effective protections for women against gender based violence. However, gaps exist in the legislation, which will need to be remedied. Finally, specific actions will need to be taken to move the law from words on paper to active implementation and protection of women from gender based violence in Nigeria.
The Use of a Bar Model Drawing to Teach Word Problem Solving to Students With Mathematics Difficulties
Year: 2017

For students with mathematics difficulties (MD) math word problem solving is especially challenging. The purpose of this study was to examine the effects of a problem solving strategy, bar model drawing, on the mathematical problem solving skills of students with MD. The study extended previous research that suggested that schematic based instruction (SBI) and cognitive strategy instruction (CSI) delivered within an explicit instruction framework can be effective in teaching various math skills related to word problem solving. A multiple baseline design replicated across groups was used to evaluate the effects of the intervention of bar model drawing on math problem solving performance of students with MD. Student achievement was measured in terms of increased correct use of cognitive strategies and overall accuracy of math word problem solving. Results showed that bar modeling drawing is an effective strategy for increasing elementary students' accuracy in solving math word problems and their ability to use cognitive strategies to solve the problems.
Challenges Encountering in E Commerce Fiscal Imposition of Digital Multinational Companies
Year: 2021

Despite its advantages, the borderless nature of electronic commerce poses serious challenges to governments worldwide regarding taxation. Where the goods or services are deliverable digitally (such as software or music) it is difficult to trace their origin for the purpose of taxation. Attempts have been made to seek solution to the challenges posed by electronic commerce to tax administration. The United States, Britain and other large, rich nations reached a landmark deal on June 6, 2021 to squeeze more money out of multinational companies such as Amazon and Google and reduce their incentive to shift profits to low tax offshore havens. Hundreds of billions of dollars could flow into the coffers of governments left cash strapped by the COVID 19 pandemic after the Group of Seven (G7) advanced economies agreed to back a minimum global corporate tax rate of at least 15% <br><br>This article is based on on the literature review of two PhD thesis requirements, namely Mr. Eloi Vincent De Paul Bekombo Ndedi and Ms. Koumemb Carole Danette. In this regard, this article will review recent moves to impose taxes on digital multinational companies.
Fast Implementation of Rainbow Signatures via Efficient Arithmetic over a Finite Field
Year: 2011

An efficient hardware implementation of Rainbow signature scheme is presented in this paper. It introduces an effective way to accelerate the generation of multivariate signatures by using optimized arithmetics including multiplication, multiplicative inverse and Gaussian elimination over finite fields. Not only the speed but also the area are considered in the design. 27 parallel multipliers are adopted and the design has been fully implemented on a low cost Field Programmable Gate Array. Compared with other public key implementations, the proposed implementation with 15490 gate equivalents and 2570 clock cycles has better performance. The cycle area product of this implementation shows that it is suitable for fast multivariate signature generation in the resource limited environments, e.g.smart cards.
Learning to Coordinate via Multiple Graph Neural Networks
Venue: ArXiv
Year: 2021

The collaboration between agents has gradually become an important topic in multi agent systems. The key is how to efficiently solve the credit assignment problems. This paper introduces MGAN for collaborative multi agent reinforcement learning, a new algorithm that combines graph convolutional networks and value decomposition methods. MGAN learns the representation of agents from different perspectives through multiple graph networks, and realizes the proper allocation of attention between all agents. We show the amazing ability of the graph network in representation learning by visualizing the output of the graph network, and therefore improve interpretability for the actions of each agent in the multi agent system.
A Frequency Control Method for Regulating Wireless Power to Implantable Devices
Venue: IEEE Transactions on Biomedical Circuits and Systems
Year: 2008

This paper presents a method to regulate the power transferred over a wireless link by adjusting the resonant operating frequency of the primary converter. A significant advantage of this method is that effective power regulation is maintained under variations in load, coupling and circuit parameters. This is particularly important when the wireless supply is used to power implanted medical devices where substantial coupling variations between internal and external systems is expected. The operating frequency is changed dynamically by altering the effective tuning capacitance through soft switched phase control. A thorough analysis of the proposed system has been undertaken, and experimental results verify its functionality.
Robust Automated Assessment of Human Blastocyst Quality using Deep Learning
Year: 2018

Morphology assessment has become the standard method for evaluation of embryo quality and selecting human blastocysts for transfer in in vitro fertilization (IVF) This process is highly subjective for some embryos and thus prone to human bias. As a result, morphological assessment results may vary extensively between embryologists and in some cases may fail to accurately predict embryo implantation and live birth potential. Here we postulated that an artificial intelligence (AI) approach trained on thousands of embryos can reliably predict embryo quality without human intervention. To test this hypothesis, we implemented an AI approach based on deep neural networks (DNNs) Our approach called STORK accurately predicts the morphological quality of blastocysts based on raw digital images of embryos with 98% accuracy. These results indicate that a DNN can automatically and accurately grade embryos based on raw images. Using clinical data for 2,182 embryos, we then created a decision tree that integrates clinical parameters such as embryo quality and patient age to identify scenarios associated with increased or decreased pregnancy chance. This IVF data driven analysis shows that the chance of pregnancy varies from 13.8% to 66.3% In conclusion, our AI driven approach provides a novel way to assess embryo quality and uncovers new, potentially personalized strategies to select embryos with an improved likelihood of pregnancy outcome.
Health literacy and crisis: Public relations in the 2010 egg recall
Year: 2016

This study examines instructional messages and constraints of health literacy in communicating messages of self protection in a crisis. Specifically, the identifiable public relations strategies of the FDA, CDC, and other prominent spokespersons were assessed and a content analysis of television coverage during the first week of the 2010 Salmonella egg recall was performed to determine the ability of the accountable agencies and organizations to communicate messages of self protection through the media. This study contends that practitioners must take health literacy into consideration when developing messages that must first pass through media gatekeepers. Implications are provided for improving media relations in a crisis that increases health risks and expanding the scope of crisis communication research.
La influencia de la red social facebook en el lenguaje escrito de los estudiantes del grado octavo del Colegio Jaime Garzon de Cucuta
Year: 2017

En el presente proyecto de investigacion, es un estudio cualitativo de tipo interpretativo, que tiene con objetivo el analizar la escritura de los estudiantes del Colegio Jaime Garzon de Cucuta en la red social Facebook, su relacion con el lenguaje moderno y la escritura escolar. Para esto, se toman diferentes captures o tomas de fotografias de las conversaciones y publicaciones que realizan estos jovenes en la red social ya mencionada, ademas de que es aplicada una encuesta de opinion tanto a los estudiantes como a dos docentes de lengua castellana, siendo uno de ellos, el docente que lleva el proceso de ensenanza aprendizaje de los educandos. Es asi, que la muestra seleccionada son 10 estudiantes de la educacion basica precisamente en el grado octavo, sus edades oscilan entre los 13 a 15 anos de edad. Se evidencia en este estudio que los estudiantes construyen nuevas formas de expresion escrita en la red social, siendo influenciada por el medio, por moda, por pertenecer a un grupo de amigos, por la rapidez, por la pereza que de una u otra forma crean modificaciones en la escritura escolar, donde se logra comprender y establecer que los estudiantes son conocedores de todas las reglas gramaticales y ortograficas, pero que al escribir en esta red social lo hacen de manera voluntaria e intencional modificando todos los vocablos. De igual manera, los educando han encontrado en la red social Facebook un espacio para la continua comunicacion sin ninguna barrera, donde les otorga libertad para recrear un nuevo lenguaje, donde utilizando diferentes procedimientos linguisticos para llegar a una escritura utilizada en estos medios virtuales, pues no solo esta escritura es vista en esta red sino en otras como el correo electronico, whatsapp, intagram, entre otras. Para finalizar, los docentes y los estudiantes afirman que este uso continuo de la red social con esta escritura tambien afecta la escritura escolar.