nils-herrmann/clean_scirepeval huggingface dataset:
Feature based Fruit Quality Grading System using Support Vector Machine
Venue: 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information Communication Technology (RTEICT)
Year: 2018

The conventional post harvesting process of horticultural fruit and vegetables is exorbitant and highly subjective which susceptible to errors. This process is extremely unreliable in terms of accuracy, throughput, speed and cost. An automated fruit grading approach is desirable to reduce the manual efforts and increase the efficiency. In this paper, we are developing a computer vision based an image acquisition and classification system for fruit grading. This system is divided into three modules image pre processing, image segmentation and Classifier. In the first phase, we are extracting the image features such as image quality, area, perimeter, mean, variance, color, intensity. Next Otsu algorithm works on automatic threshold calculation and image binarization part. In the second phase k means clustering is used for image segmentation. In last phase the vectors of color, intensity, segments, and image quality feature were utilized for training of the support vector machine structure. The image k means clustering approach is embedded with support vector machine classifier to improve the speed and accuracy of the classifier. As a result, the system will be able to classify the fruit into three different categories. The proposed algorithm is implemented with an example of tomato fruit grading. The experiments consider real tomato image dataset of 200 samples.75% of the total dataset is used for training and remaining 25% used for testing purpose. Training dataset is distinguished into three categories depending on the maturity of tomato.
The relationship between platelet size and the B' infrared peak of natural diamonds revisited
Year: 2017

Platelets in diamond are extended planar defects that are thought to be generated during the nitrogen aggregation process in type Ia diamonds. They were subjected to intensive research during the 1980s and 1990s but the techniques used for observation of defects in diamond have improved since that time and new insights can be gained by further study. This study combines high resolution Fourier Transform Infrared (FTIR) analysis, with an emphasis on the main platelet peak, and transmission electron microscopic (TEM) imaging. By performing TEM and FTIR analyses on volumes of diamond that were closely spatially related it is shown that the average platelet diameter, D, follows the relationship D a x b where x is the position of the platelet peak in the infrared spectrum, a is a constant and b is the minimum position of the platelet peak. The best fit to the data is obtained if a value of b 1360 cm 1 is used, giving a fitted value of a 221. The observed variation in infrared (IR) peak width can also be explained in terms of this relationship. Additionally, platelet morphology was found to vary according to diameter with large platelets being more elongated. The tendency to become more elongated can be described by the empirical equation A R 11.9 D 19.6 0.4 where AR is the aspect ratio. Using the relationships established here, it will be possible to study platelet abundance and size as a function of parameters such as nitrogen concentration, nitrogen aggregation and diamond residence time in the mantle. This work therefore will open up new methods for constraining the geological history of diamonds of different parageneses and from different localities.
Multifunctional 25D metastructures enabled by adjoint optimization
Year: 2020

Optical metasurfaces are two dimensional arrays of meta atoms that modify different characteristics of light such as phase, amplitude, and polarization. One intriguing feature that distinguishes them from conventional optical components is their multifunctional capability. However, multifunctional metasurfaces with efficiencies approaching those of their single functional counterparts require more degrees of freedom. Here we show that 2.5D metastructures, which are stacked layers of interacting metasurface layers, provide sufficient degrees of freedom to implement efficient multifunctional devices. The large number of design parameters and their intricate intercoupling make the design of multifunctional 2.5D metastructures a complex task, and unit cell approaches to metasurface design produce suboptimal devices. We address this issue by designing 2.5D metastructures using the adjoint optimization technique. Instead of designing unit cells individually, our technique considers the structure as a whole, accurately accounting for inter post and inter layer coupling. As proof of concept, we experimentally demonstrate a double wavelength metastructure, designed using adjoint optimization, that has significantly higher efficiencies than a similar device designed with a simplified approach conventionally used in metasurface design. The 2.5D metastructure architecture empowered by the optimization based design technique is a general platform for realizing high performance multifunctional components and systems.
Analisis Algoritma Naive Bayes Classifier untuk Klasifikasi Tweet Pelecehan Seksual dengan #MeToo
Year: 2020

Pelecehan seksual adalah perilaku yang ditandai oleh ketika seseorang membuat komentar seksual yang tidak diinginkan dan tidak pantas atau menyentuh secara fisik di tempat kerja atau situasi profesional atau situasi sosial. Permasalahan terhadap tweets yang mengandung curhatan para korban pelecehan seksual menjadi hal penting untuk dikaji sebagai pemrosesan teks. Analisis sentimen dapat digunakan sebagai solusi untuk mengidentifikasi tweets pelecehan seksual berdasarkan jenisnya dengan metode klasifikasi menggunakan algoritma Naive Bayes Classifier. Naive Bayes Classifier menggunakan metode probabilitas dan statistik setiap kelas dalam pembelajaran klasifikasinya, sehingga jarak perbedaan antar kelas tidak besar. Tujuan penelitian ini yaitu untuk mengklasifikasikan data tweets berdasarkan kelas quid pro quo dan hostile work environment Pengujian pada penelitian ini dilakukan dengan empat skenario yang berbeda menggunakan bahasa pemrograman R dan tools RStudio yang kemudian dievaluasi menggunakan confusion matrix untuk menentukan model klasifikasi terbaik. Hasil evaluasi dengan confusion matrix didapatkan bahwa model klasifikasi terbaik adalah skenario dengan pembagian data training dan data testing 80:20. Skenario ini menghasilkan nilai akurasi sebesar 88.55% dengan recall 96.50% precision 90.78% dan f measure 93.55% Sexual harassment is behavior that is characterized by when someone makes an unwanted and inappropriate sexual comment or physical advances at work or a professional or social situation. The issue of tweets containing the experience of victims of sexual harassment becomes important to be examined as text processing. Sentiment analysis can be used as a solution to identify sexual harassment tweets by type by classification method using the Naive Bayes Classifier algorithm. Naive Bayes Classifier uses the probability and statistical methods of each class in its classification learning, so that the difference between classes is not large. The purpose of this study is to classify tweets data based on quid pro quo and hostile work environment classes. Testing in this study was carried out with four different scenarios using the R programming language and RStudio tools which were then evaluated using a confusion matrix to determine the best classification model. The results of the evaluation with the confusion matrix found that the best classification model is a scenario with the distribution of training data and testing data 70:30. This scenario produces an accuracy value of 88.55% with a recall 96.50% precision 90.78% and f measure 93.55%
Fruit and vegetable consumption, Helicobacter pylori antibodies, and gastric cancer risk: A pooled analysis of prospective studies in China, Japan, and Korea
Venue: International journal of cancer
Year: 2017

Epidemiological findings on the association between fruit and vegetable consumption and gastric cancer risk remain inconsistent. The present analysis included 810 prospectively ascertained non cardia gastric cancer cases and 1,160 matched controls from the Helicobacter pylori Biomarker Cohort Consortium, which collected blood samples, demographic, lifestyle, and dietary data at baseline. Conditional logistic regression adjusting for total energy intake, smoking, and H. pylori status, was applied to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for gastric cancer risk across cohort and sex specific quartiles of fruit and vegetable intake. Increasing fruit intake was associated with decreasing risk of non cardia gastric cancer (OR 0.71, 95% CI: 0.52 0.95, p trend 0.02) Compared to low fruit consumers infected with CagA positive H. pylori, high fruit consumers without evidence of H. pylori antibodies had the lowest odds for gastric cancer incidence (OR 0.12, 95% CI: 0.06 0.25) whereby the inverse association with high fruit consumption was attenuated among individuals infected with CagA positive H. pylori (OR 0.82, 95% CI: 0.66 1.03) To note, the small number of H. pylori negative individuals does influence this finding. We observed a weaker, nondose response suggestion of an inverse association of vegetable intake with non cardia gastric cancer risk. High fruit intake may play a role in decreasing risk of non cardia gastric cancer in Asia.
The Ethics of Cyber Attack: Pursuing Legitimate Security and the Common Good in Contemporary Conflict Scenarios
Year: 2020

Cyber attack against Critical National Infrastructure is a developing capability in state arsenals. The onset of this new instrument in national security has implications for conflict thresholds and military ethics. To serve as a legitimate tool of policy, cyber attack must operate in accordance with moral concerns. To test the viability of cyber attack, this paper provides a new perspective on cyber ethics. Cyber attack is tested against the criteria of the common good. This involves identifying the four core components of the common good from a conflict perspective: respect for the person; social wellbeing; peace and security; and solidarity. The fate of these components is assessed in relation to the six key characteristics of cyber attack from a moral standpoint: security; the role or absence of violence; discrimination; proportionality; cyberharm; and the threshold of conflict. It is concluded that the common good must be incorporated into developing state cyber strategies.
Literature, Theory, and the Politics of Criticism in Contemporary Thailand
Venue: PMLA/Publications of the Modern Language Association of America
Year: 2011

In the aftermath of Britain's Nuptial Extravaganza celebrating the Union of Prince William and Kate Middleton, comparisons between that event and the profile of the monarchy in Thailand have emerged. Occupying a central and highly visible position in the public domain, Thailand's King Bhumibol Adulyadej (Rama IX, r. 1946 present) is widely held in great esteem. Yet the silencing of republican sentiment in the run up to the royal wedding in London echoes the measures deployed with increasing regularity and rigor in Thailand under article 112 of the country's penal code, a law against lese majeste that effectively suppresses all open criticism of the Thai monarchy. In 2009 an all time high of 164 lese majeste cases were tried in Thailand's Court of First Instance "Article 112" The Thai historian and public intellectual Somsak Jeamteerasakul, among others, has argued that these measures create a climate of fear around the discussion of the place and role of the monarchy in contemporary Thailand. This climate also has a bearing on the production and study of literature, on literary analysis, and on approaches to literary and cultural theory in Thailand.
Krisenmanagement
Venue: Vernetztes Betriebssicherheitsmanagement
Year: 2019

Zusammenfassung Erfolgreiche Unternehmen und Organisationen entwickeln ein umfassendes Bewusstsein fur mogliche Krisen, sie betreiben professionelle Krisenpravention. Das Rezept fur eine dauerhafte und erfolgreiche Krisenpravention lautet: Jeden Tag nach vorne schauen, Risiken wahrnehmen, richtig abschatzen und moglichst neutralisieren. Systematische Verfahren zur Fruherkennung von Warnsignalen spielen dabei eine wichtige Rolle. Krisenpotenziale erkennen und antizipieren, Infrastrukturen schaffen, Ablaufe einuben und Mitarbeiter schulen sind gute Voraussetzungen, um in krisenhaften Situationen souveran zu agieren, statt in einen Schockzustand zu verfallen. Leider sind noch zu viele Unternehmen und Organisationen von diesem Ideal weit entfernt. Krisen gefahrden ausserdem immer das Image und die Reputation eines Unternehmens. In diesem Zusammenhang darf das mediale Interesse nicht unterschatzt werden. Die Mediengesellschaft, in der wir leben, liebt und produziert deswegen unentwegt grosse und kleine Krisen, indem sie schlicht jede Gelegenheit zur Berichterstattung nutzt. Schliesslich ist die Krise mehr noch als die bloss schlechte Nachricht ein hervorragend verkaufliches Gut (Morle 2004) Leider verfugen noch zu wenig Unternehmen uber professionelle Konzepte, die auch den Aspekt der Krisenkommunikation hinreichend berucksichtigen. Auch ist einzelnen Studien zu entnehmen, dass das Bewusstsein in Deutschland fur das Thema Krisenpravention und bewaltigung in einigen Branchen noch nicht hinreichend ausgepragt ist.
Les capacites verbales et visuo spatiales en memoire de travail d'enfants sourds munis d'un implant cochleaire compares a leurs pairs entendants
Year: 2014

professeure specialisee aupres d'enfants sourds, centre charlotte blouin a angers et doctorante en psychologie, Laboratoire de psychologie des pays de la Loire, universite d'angers, unam. email stephanie.pouyat houee@mfam49 53.fr mcu en psychologie du developpement cognitif de l'enfant, Laboratoire de psychologie des pays de la Loire, universite d'angers, unam. professeure emerite en psychologie, Laboratoire de psychologie des pays de la Loire, universite d'angers, unam.
Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations
Venue: ArXiv
Year: 2017

How can we learn a classifier that is "fair" for a protected or sensitive group, when we do not know if the input to the classifier belongs to the protected group? How can we train such a classifier when data on the protected group is difficult to attain? In many settings, finding out the sensitive input attribute can be prohibitively expensive even during model training, and sometimes impossible during model serving. For example, in recommender systems, if we want to predict if a user will click on a given recommendation, we often do not know many attributes of the user, e.g. race or age, and many attributes of the content are hard to determine, e.g. the language or topic. Thus, it is not feasible to use a different classifier calibrated based on knowledge of the sensitive attribute. Here, we use an adversarial training procedure to remove information about the sensitive attribute from the latent representation learned by a neural network. In particular, we study how the choice of data for the adversarial training effects the resulting fairness properties. We find two interesting results: a small amount of data is needed to train these adversarial models, and the data distribution empirically drives the adversary's notion of fairness.
Pharmacological screening technologies for venom peptide discovery
Venue: Neuropharmacology
Year: 2017

Venomous animals occupy one of the most successful evolutionary niches and occur on nearly every continent. They deliver venoms via biting and stinging apparatuses with the aim to rapidly incapacitate prey and deter predators. This has led to the evolution of venom components that act at a number of biological targets including ion channels, G protein coupled receptors, transporters and enzymes with exquisite selectivity and potency, making venom derived components attractive pharmacological tool compounds and drug leads. In recent years, plate based pharmacological screening approaches have been introduced to accelerate venom derived drug discovery. A range of assays are amenable to this purpose, including high throughput electrophysiology, fluorescence based functional and binding assays. However, despite these technological advances, the traditional activity guided fractionation approach is time consuming and resource intensive. The combination of screening techniques suitable for miniaturization with sequence based discovery approaches supported by advanced proteomics, mass spectrometry, chromatography as well as synthesis and expression techniques promises to further improve venom peptide discovery. Here, we discuss practical aspects of establishing a pipeline for venom peptide drug discovery with a particular emphasis on pharmacology and pharmacological screening approaches. This article is part of the Special Issue entitled 'Venom derived Peptides as Pharmacological Tools. HIGHLIGHTSVenom peptides are a rich source of bioactives with therapeutic potential.Pharmacological screening is a validated venom peptide drug discovery approach.Assay guided fractionation is particularly powerful combined with transcriptomics and proteomics.
The motivational push factor for visiting reenactment site
Year: 2015

The research conducted here examines the satisfaction for visiting reenactment site in the context of the motivational push factor education, leisure, exploration and relaxation. This research analyzed the relationship of satisfaction and four motivational push factors. Through a review of existing literature and data case study, the research seeking to bring together in a motivation traveler in historical reenactment and allows tourist to share their satisfaction toward history site. The objective of this research was to determine the relationship satisfaction of visitor towards motivation to visit history site. The early literature focused on what the tourism was about and all the information about the research all about. The study was conducted by using the survey method of questionnaire collected by 322 respondents at Sungai Lembing, Kuantan Pahang. The analysis was carried out by using SPSS to interpret data and determine the relationship of satisfaction and four motivation push factors. The results determined significantly correlated factors, including four push travel motivations. The results reveal that there are significant relationship between satisfaction and four motivational push factors
A systematic review and meta analysis of long term studies (five or more years) assessing maxillary sinus floor augmentation.
Venue: International journal of oral and maxillofacial surgery
Year: 2018

The objective was to test the hypothesis of no difference in long term =5 years) implant treatment outcomes after maxillary sinus floor augmentation (MSFA) with autogenous bone graft compared to a mixture of autogenous bone graft and bone substitutes or bone substitutes alone. A MEDLINE (PubMed) Embase, and Cochrane Library search in combination with a hand search of relevant journals was conducted. Human studies published in English between January 1, 1990 and October 1, 2016 were included. Nine studies fulfilled the inclusion criteria. The survival of suprastructures has never been compared within the same study. The 5 year implant survival after MSFA with autogenous bone graft was 97% compared to 95% for Bio Oss; the reduction in vertical height of the augmented sinus was equivalent with the two treatment modalities. Non comparative studies demonstrated high survival rates for suprastructures and implants regardless of the grafting material used. Meta analysis revealed an overall estimated patient based implant survival of 95% (confidence interval 0.92 0.96) High implant stability quotient values, high patient satisfaction, and limited peri implant marginal bone loss were revealed in non comparative studies. No long term randomized controlled trial comparing the different treatment modalities was identified. Hence, the conclusions drawn from the results of this systematic review should be interpreted with caution.
Unscented Kalman Filtering for Nonlinear State Estimation with Correlated Noises and Missing Measurements
Year: 2018

The unscented Kalman filtering problem is investigated for a class of nonlinear discrete stochastic systems subject to correlated noises and missing measurements. Here, a random variable obeying Bernoulli distribution with known conditional probability is introduced to depict the phenomenon of missing measurements occurring in a stochastic way. Due to taking the correlation of noises into account, a one step predictor is designed by applying the innovative analysis and unscented transformation approach. And then, based on one step predictor and the minimum mean square error principle, a new unscented Kalman filtering algorithm is proposed such that, for the correlated noises and missing measurements, the filtering error is minimized. By solving the recursive matrix equation, the filter gain matrices and the error covariance matrices can be obtained and the proposed results can be easily verified by using the standard numerical software. We finally provide a numerical example to show the performance of the proposed approach.
The framing of decisions
Year: 2017

In the Theory of Rational Decision Making the psychological aspects are set aside. This contribution seeks to point out the relevance of psychology into economic decisions. The essay treats the "framing of decisions" which is a pillar of Kahneman's behavioral theory. Framing must be considered a special case of the more general phenomenon of dependency from the representation. The best known risky choice framing problem, i.e. the "Asian Disease Problem" is shown where an essential aspect of rationality: invariance, is violated. In addition, the contribution explains Kahneman and Tversky's Prospect Theory and illustrates their value function. Finally, it discusses the reversals of preference in framing and framing of contingencies. The framing manipulation is viewed as a public tool for influencing the decision maker's private framing of the problem in terms of gains or losses, which determines the decision maker's evaluation of the options. In conclusion, the psychology of choice is relevant both for the descriptive question of how decisions are made and for the normative question of how decisions ought to be made.