nils-herrmann/clean_scirepeval huggingface dataset:
TiO2 Nanotube Array Sensor for Detecting the SF6 Decomposition Product SO2
Venue: Sensors
Year: 2012

The detection of partial discharge through analysis of SF6 gas components in gas insulated switchgear, is significant for the diagnosis and assessment of the operating state of power equipment. The present study proposes the use of a TiO2 nanotube array sensor for detecting the SF6 decomposition product SO2, and the application of the anodic oxidation method for the directional growth of highly ordered TiO2 nanotube arrays. The sensor response of 10 50 ppm SO2 gas is tested, and the sensitive response mechanism is discussed. The test results show that the TiO2 nanotube sensor array has good response to SO2 gas, and by ultraviolet radiation, the sensor can remove attached components very efficiently, shorten recovery time, reduce chemical poisoning, and prolong the life of the components.
A comparative analysis of the performance of LHTES systems case study: Cylindrical exchanger with and without annular fins
Year: 2019

The Thermal Energy Storage (TES) occupied an important role in the reasonable use of energy, because it allows the decoupling between the production and the energy demand in the applications with intermittent energy production. In recent years, many researchers have highlighted the use of Latent Heat Thermal Energy Storage (LHTES) systems, this is especially because the high energy density can be stored during phase change. Notwithstanding this great potential, the feasibility of LHTES with PCM is still limited, mainly due to a low thermal conductivity. In this sense, the exchanger with fins is the most effective proposal which is based on the increase of the exchange surface. After a review of recent advances in LHS systems with a focus on methods for improving the thermal conductivity of MCPs, and a selection methodology (Exchanger PCM) adequate. The main objective of this paper is to develop, perform and compare a numerical study of a new finned exchanger (double pipe with Longitudinal fins on the external pipe, Phase Change Material in the annular space between the two pipes and HTF in the inner pipe) with a classic exchanger without fins. This comparative study was done according to the process of heat transfer during melting (charging) at average temperature (180 280 degC) In addition, the results obtained were adapted for an implementation of Fresnel solar power installed at Green Energy Park (1 MWe) in Morocco. This study has shown that the first exchanger has a good compactness, can store enough latent energy, and significantly overcome the problem of low thermal conductivity related to the second heat exchanger.The Thermal Energy Storage (TES) occupied an important role in the reasonable use of energy, because it allows the decoupling between the production and the energy demand in the applications with intermittent energy production. In recent years, many researchers have highlighted the use of Latent Heat Thermal Energy Storage (LHTES) systems, this is especially because the high energy density can be stored during phase change. Notwithstanding this great potential, the feasibility of LHTES with PCM is still limited, mainly due to a low thermal conductivity. In this sense, the exchanger with fins is the most effective proposal which is based on the increase of the exchange surface. After a review of recent advances in LHS systems with a focus on methods for improving the thermal conductivity of MCPs, and a selection methodology (Exchanger PCM) adequate. The main objective of this paper is to develop, perform and compare a numerical study of a new finned exchanger (double pipe with Longitudinal fins on the ex.
Instrumentation hyperfrequence pour l'etude de cinetiques de reactions biochimiques en presence d'un champ electromagnetique de forte intensite interpretation physique des resultats
Year: 2011

Cette etude a pour objectif de mettre en place une instrumentation pour la caracterisation de l'evolution d'une cinetique biochimique soumise a un champ electromagnetique d'amplitude continue a 2. 45 GHz et sous champ impulsionnel a tres court temps de montee et a tres fort potentiel. Elle porte plus particulierement sur l'observation d'effets induits par ces champs electromagnetiques sans elevation de temperature de la solution reactionnelle. La mesure de la solution electrolytique s'effectue via un protocole de caracterisation dielectrique de materiaux et de liquides sur une tres large bande (40 Hz 18 GHz) Le substrat est place dans une discontinuite coaxiale reliee au reseau. La mesure de son impedance permet de determiner sa permittivite complexe via un algorithme base sur le raccordement des modes de propagations entre le support coaxial et le guide circulaire contenant l'echantillon. La reaction etudiee porte sur l'hydrolyse de l'acetylcholine par l'acetylcholine esterase. Le premier etant le principal neurotransmetteur du corps humain et la seconde l'enzyme le catalysant. L'objectif consiste a observer si les ondes electromagnetiques auxquelles est soumise la reaction ont un effet inhibiteur et le cas echeant, de determiner le seuil de puissance ou d'energie y conduisant. L'evaluation des mesures porte sur le pouvoir adsorbant des reactifs et produits en solution aqueuse sur une electrode doree, celle ci etant l'ame centrale de la cellule de caracterisation de liquide. L'analyse des resultats se base sur les theories electrocinetiques et de spectroscopie d'impedance electrochimique en vigueur, soit l'observation et l'interpretation des changements d'impedance survenant a la surface de l'electrode de mesure.
Partial discharges and noise classification under HVDC using unsupervised and semi supervised learning
Year: 2020

This paper tackles the problem of the classification of partial discharge (PD) and noise signals by applying unsupervised and semi supervised learning methods. The first step in the proposed methodology is to prepare a set of classification features from the statistical moments of the distribution of the Wavelet detail coefficients extracted from a dataset of signals acquired from a test cell under 40 kVDC. In a second step, an unsupervised learning framework that implements the k means algorithm is applied to reduce the dimensionality of this initial feature set. The Silhouette index is used to evaluate the number of natural clusters in the dataset while the Dunn index is used to determine which subset of features produces the best clustering quality. Since the unsupervised learning does not provide any method for result validation, then the third step in the methodology of this paper consists of applying a semi supervised learning framework that implements Transductive Support Vector Machines. The labeling of the test set that is required in this framework for the result validation is carried out by visual checking of the signal waveforms assisted by GUI tools such as the software PDflex. The results using this methodology showed a high classification accuracy and proved that both learning frameworks can be combined to optimize the selection of classification features.
The impact of financial dollarization on the banking system of Ukraine
Year: 2014

5. Rediscovering Social Innovation [Electronic resource] A. James, Jr. Phills, K. Deiglmeier, Dale T. Miller Stanford Social Innovation Review.  Let's hear those ideas [Electronic resource] The Economist. August 12. 2010 what it is, why it Matters, how it can be Accelerated Mulgan, Ali, Tucker Said Business School.  The Guide to Social Innovation [Electronic resource] Belgium. European Commission. 2013
Efficient LiDAR Odometry for Autonomous Driving
Venue: IEEE Robotics and Automation Letters
Year: 2021

LiDAR odometry plays an important role in self localization and mapping for autonomous navigation, which is usually treated as a scan registration problem. Although having achieved promising performance on the KITTI odometry benchmark, the conventional tree based neighbor search still has the difficulty in dealing with the large scale point cloud efficiently. The recent spherical range image based method enjoys the merits of fast nearest neighbor search by spherical mapping. However, it is not very effective to deal with the ground points nearly parallel to LiDAR beams. To address these issues, we propose a novel efficient LiDAR odometry approach by taking advantage of both non ground spherical range images and bird's eye view maps for ground points. Moreover, a range adaptive method is introduced to robustly estimate the local surface normal. Additionally, a very fast and memory efficient model update scheme is proposed to fuse the points and their corresponding normals at different time stamps. We have conducted extensive experiments on the KITTI odometry benchmark and UrbanLoco dataset, whose promising results demonstrate that our proposed approach is effective.
Truth Tampering Through Social Media: Malaysia's Approach in Fighting Disinformation Misinformation
Year: 2019

Though poorly defined and highly politicized, the term 'Fake News' has been popularized by the Trump administration in recent years. Scholars prefer to use terms such as Information Disorder, in particular Disinformation and Misinformation, to discuss this global concern. The dissemination of disinformation and misinformation is not new. However, the penetration of social media and messaging applications today enable such information to spread much faster, deeper and wider. Further, social media and messaging applications have become the public's source of primary information. These platforms are fast becoming a birthplace of the manipulation of truth and the influencing of public opinion. The advancement of technology has also been manipulated to create false information and add to the severity of the problem. The impact of disinformation and misinformation varies: from financial difficulties faced by businesses to influencing the outcome of elections to physical violence triggered by racial and religious tensions. This paper aims to explore: 1) How information disorder, in particular, disinformation and misinformation, are being disseminated through social media and instant messaging platforms to influence public opinion; 2)How states respond to disinformation and misinformation; 3) Malaysia's disinformation and misinformation landscape and 4) Key areas for Malaysia to improve on, namely enhancing its current legal responses, developing digital literacy, heightening the accountability of social media platforms and strengthening the fact checking mechanism.
ZEST: Zero shot Learning from Text Descriptions using Textual Similarity and Visual Summarization
Venue: FINDINGS
Year: 2020

We study the problem of recognizing visual entities from the textual descriptions of their classes. Specifically, given birds' images with free text descriptions of their species, we learn to classify images of previously unseen species based on specie descriptions. This setup has been studied in the vision community under the name zero shot learning from text, focusing on learning to transfer knowledge about visual aspects of birds from seen classes to previously unseen ones. Here, we suggest focusing on the textual description and distilling from the description the most relevant information to effectively match visual features to the parts of the text that discuss them. Specifically, (1) we propose to leverage the similarity between species, reflected in the similarity between text descriptions of the species. (2) we derive visual summaries of the texts, i.e. extractive summaries that focus on the visual features that tend to be reflected in images. We propose a simple attention based model augmented with the similarity and visual summaries components. Our empirical results consistently and significantly outperform the state of the art on the largest benchmarks for text based zero shot learning, illustrating the critical importance of texts for zero shot image recognition.
Development and Assessment of a Machine Learning Model to Help Predict Survival Among Patients With Oral Squamous Cell Carcinoma.
Venue: JAMA otolaryngology head neck surgery
Year: 2019

Predicting survival of oral squamous cell carcinoma through the use of prediction modeling has been underused, and the development of prediction models would augment clinicians' ability to provide absolute risk estimates for individual patients.  To develop a prediction model using machine learning for 5 year overall survival among patients with oral squamous cell carcinoma and compare this model with a prediction model created from the TNM (Tumor, Node, Metastasis) clinical and pathologic stage.  A retrospective cohort study was conducted of 33 065 patients with oral squamous cell carcinoma from the National Cancer Data Base between January 1, 2004, and December 31, 2011. Patients were excluded if the treatment was considered palliative, staging demonstrated T0 or Tis, or survival or staging data were missing. Patient, tumor, treatment, and outcome information were obtained from the National Cancer Data Base. The data were split into a distribution of 80% for training and 20% for testing. The model was created using 2 class decision forest architecture. Permutation feature importance scores were used to determine the variables that were used in the model's prediction and their order of significance. Statistical analysis was conducted from August 1, 2018, to January 10, 2019.  Ability to predict 5 year overall survival assessed through area under the curve, accuracy, precision, and recall.  Among the 33 065 patients in the study, the mean (SD) age was 64.6 (14.0) years, 19 791 were men (59.9% 13 274 were women (40.1% and 29 783 (90.1% were white. At 60 months, there were 16 745 deaths (50.6% The median time of follow up was 56.8 months (range, 0 155.6 months) Age, pathologic T stage, positive margins at the time of surgery, lymph node size, and institutional identification were identified among the most significant variables. The calculated area under the curve for this machine learning model was 0.80 (95% CI, 0.79 0.81) accuracy was 71% precision was 71% and recall was 68% In comparison, the calculated area under the curve of the TNM staging system was 0.68 (95% CI, 0.67 0.70) accuracy was 65% precision was 69% and recall was 52% Conclusions and Relevance Using machine learning algorithms, a prediction model was created based on patient social, demographic, clinical, and pathologic features. The developed prediction model proved to be better than a prediction model that exclusively used TNM pathologic and clinical stage according to all performance metrics. This study highlights the role that machine learning may play in individual patient risk estimation in the era of big data.
GAME PENGENALAN HURUF HIJAIYAH UNTUK ANAK AUTIS DENGAN PENERPAN PENDEKATAN EDUKASI MULTISENSORI
Year: 2018

Autis merupakan suatu kelainan dengan ciri perkembangan yang terlambat atau yang abnormal dari hubungan sosial dan bahasa. Anak yang mengalami hambatan khusus atau kebutuhan khusus sering mengalami hambatan dalam proses pembelajaran. salah satunya yaitu belajar Al Quran khususnya mengenal huruf hijaiyahah. Agar anak autis fokus dan antusias belajar maka dikembangkan aplikasi game pengenalan huruf hijjaiyah. Pada game yang akan dikembangkan menrepakan pendekatan edukasi multisensori. Pendekatan multisensori merupakan pendekatan pembelajaran dengan melibatkan audio, visual dan kinestetik. Metode pengembangan sistem yang digunakan pada penelitian ini adalah Multimedia Development Life Cycle (MDLC) yang dikembangkan oleh Luther Soetopo. Metodologi pengembangan multimedia terdiri dari enam tahap, yaitu concept (pengonsepan) design (pendisainan) material collecting (pengumpulan materi) assembly (pembuatan) testing (pengujian) dan ditribution (pendistribusian) Pada penelitian ini menghasilkan game pembelajaran huruf hijaiyah untuk mebantu anak autis dalam belajar huruf hijaiyah dengan memiliki fitur yang terdiri dari bermain dan belajar serta menerapkan pendekatan edukasi multisensori yang melibatkan audio, visual dan kinestetik anak. Kata kunci: autis game edukasi, multisensori.
Investigations of laser induced plasma in air by Thomson and Rayleigh scattering
Venue: Spectrochimica Acta Part B: Atomic Spectroscopy
Year: 2019

Laser Thomson scattering and Rayleigh scattering methods were applied to investigate the dynamics of laser induced plasmas in atmospheric air. Laser induced plasma was generated by a 1064 nm, 200 mJ Nd: YAG laser. Another nanosecond Nd: YAG laser (532 nm, 50 mJ) was used as the probe laser. The temporally and spatially resolved electron number density and temperature distributions of the laser induced plasma were determined from the Thomson scattering spectra. From 1 ms to 21 ms after plasma generation, the electron number density around the centre of the plasma decreased from 4.96 x 1023m 3 to approximately 1.1 x 1021m 3, while the electron temperature dropped from approximately 51,500 K to 6900 K. The plasma images and the measured distribution of the electron number density and temperature indicated the formation of a toroidal structure approximately 18 ms after plasma generation. The Rayleigh scattering results show that the Taylor Sedov model cannot well describe the early evolution of the shockwave in radial directions.
The Depressed Female Characters From Their Intimidated Surrounding as Seen in The Yellow Wallpaper By Charlotte Perkin Gilman's, A Rose For Emily By William Faulkner's, and The Story of an Hour By Kate Chopin
Venue: Jurnal Ilmiah Langue and Parole
Year: 2019

In writing this thesis, the writer discusses the depression of women because of patriarchal traditions, even though they already know about women's rights and freedoms. This patriarchal tradition is that men hold full power over anything and women must always obey the rules of men. The women are required not to do any activities, in terms of education and employment. Women are only allowed to do homework. This applies to all women, both single and married. This began in the 90s, especially in the United States. In writing the thesis, the writer uses psychological and feminist theories according to Sigmund Freud and Maggie Humm, who will explore the psychological side of women who are oppressed by the existence of this patriarchal custom. The purposes of this paper are: (1) To describe psychological feminist cases in female characters (2) To analyze psychological feminists in depressed female characters (3) To explain the psychological feminist influence with female characters in the short story of The Yellow Wallpaper from Charlotte Perkins Gilman, A Rose For Emily from William Faulkner, The Story Of An Hour by Kate Chopin. The author uses descriptive qualitative methods in processing data. Through analysis of several existing sources and data. Based on available data, the writer discover how the psychology of depressed female characters from their environment is intimidated based on the short story. In fact women can become depressed because their freedom of expression is hampered and prohibited by tradition. With the writing of this thesis, it is hoped that the public can find out what exactly the meaning of women's emancipation is without having to put down women or men.
Exploratory Study of knowledge and experience of Polycystic Ovary Syndrome (PCOS) among PCOS diagnosed Bangladeshi women
Year: 2020

To explore the perceived experience of polycystic ovary syndrome (PCOS) among PCOS diagnosed Bangladeshi women with examination of the influence of culture.  This qualitative study included 25 Bangladeshi women who had been diagnosed with PCOS. The qualitative interviews were completed via Skype and/ or phone between December 2017 to March 2018. Transcriptions of recorded, deidentified responses were analyzed using qualitative manual coding and thematic analysis.  Three overarching themes were identified from the narratives: PCOS diagnosis experience, PCOS knowledge, and role of religion and culture in relation to PCOS. The women expressed an unsatisfactory experience with their PCOS diagnosis including having to change healthcare professionals, inadequate access to resources, and concerns related to infertility and pregnancy complications. Lack of available evidence based information was associated with limited knowledge of PCOS among the PCOS diagnosed Bangladeshi women and their families. The respondents perceived that culture influenced refraining from sharing of information about PCOS thereby limiting knowledge, muting women's health experience, and contributing to a negative perception on PCOS and related conditions. Participants felt that cultural expectations and emphasis on childbearing placed constant pressure on women and stigmatized PCOS.  Bangladeshi women with PCOS perceive various challenges and limited access to information and resources. To minimize some of the challenges associated with PCOS, public health efforts should focus on increasing awareness, education, and resources for women and their families.
The neural basis for human syntax: Broca's area and beyond
Venue: Current Opinion in Behavioral Sciences
Year: 2018

Language is a uniquely human cognitive system which is biologically grounded in the human brain. Recent studies have shown that syntax processing in humans can be separated from sequence processing, a cognitive ability also present in non human primates. Syntactic processing as the core of human language is subserved specifically by BA 44 located in the posterior portion of Broca's area in the left inferior frontal gyrus and its white matter connection to the posterior temporal cortex. It is only when this fronto temporal system has emerged that full syntactic abilities are present both in phylogeny and ontogeny.
The Polyvagal Theory: Neurophysiological Foundations of Emotions, Attachment, Communication, and Self regulation
Year: 2011

This book compiles, for the first time, Stephen W. Porges's decades of research. A leading expert in developmental psychophysiology and developmental behavioral neuroscience, Porges is the mind behind the groundbreaking Polyvagal Theory, which has startling implications for the treatment of anxiety, depression, trauma, and autism. Adopted by clinicians around the world, the Polyvagal Theory has provided exciting new insights into the way our autonomic nervous system unconsciously mediates social engagement, trust, and intimacy.
LASER CLADDING OF HOT WORK TOOL STEEL (H13) WITH NANO TIC PARTICLES
Year: 2019

In this study, nano titanium carbide particles are coated on the surfaces of X40CrMoV51 (H13) hot work tool steel to improve the tribological properties of steel surface by laser coating method. Nano TiC having average size of 10 nm are used as coating material and two stage laser cladding method was employed for coating processes. In the first stage, nano TiC powder is mixed in the phonelic resin and then precoated at 50 um thickness on the surface of steels under vacuum. After that laser beam melted the surface of steels and hard coating layer obtained. The effect of laser power on the coating layers were examined using a 2000 W CO 2 laser which operated at continuous wave mode. The morphological structures and phase structures were examined by scanning electron microscopy X ray spectroscopy and optic microscope, respectively. The hardness of coating layers and bonding strength to substrate were defined with microhardness tests and scratch test. The thickness of the coatings layers were measured in the range of 15 130 um according to laser powers It is seen that c rack free, smooth and homogenous coating layers can be obtained at 235 W laser power. According to hardness and micro scratch tests results, hardness was improved significantly and all coating layers had a good metallurgical strength to substrate.