Reviewerly/exHarmony huggingface dataset:
Jurisprudence of Tolerance: Hate Speech, Article 17 and Theory of Democracy in the European Convention on Human Rights

What does the protection or prohibition of a speech tell us about the tripartite relationship between political power, democracy and rights? This question has somehow underscored the jurisprudence of the European Court of Human Rights in hate speech cases for more than a half century. We argue that this question has invariably placed the Court in an uneasy position, which is, choosing between a democracy empowered by unlimited freedom of speech, but with recurrent social tensions, and a democracy with rather strict hate speech laws, but at ease with different segments of population. That said, the jurisprudence of the European Court outlines a pattern by which to identify a specific direction for the evolution of rights and democracy. This article considers this pattern. Not only does this article, examine the pattern in the Court’s and the Commission’s jurisprudence, but it also argues that this pattern unfolds a subtle presence of Hobbesian and Lockean theories of political power and the limits in its midst. By invoking this presence, we indicate how the debate in the jurisprudence of the European Court has shifted from the language of protecting democracy to that of rights.
Semantic Language Model for Tunisian Dialect

In this paper, we describe the process of creating a statistical Language Model (LM) for the Tunisian Dialect.Indeed, this work is part of the realization of Automatic Speech Recognition (ASR) system for the Tunisian Railway Transport Network.Since our field of work has been limited, there are several words with similar behaviors (semantic for example) but they do not have the same appearance probability; their class groupings will therefore be possible.For these reasons, we propose to build an n-class LM that is based mainly on the integration of purely semantic data.Indeed, each class represents an abstraction of similar labels.In order to improve the sequence labeling task, we proposed to use a discriminative algorithm based on the Conditional Random Field (CRF) model.To better judge our choice of creating an n-class word model, we compared the created model with the 3-gram type model on the same test corpus of evaluation.Additionally, to assess the impact of using the CRF model to perform the semantic labelling task in order to construct semantic classes, we compared the n-class created model with using the CRF in the semantic labelling task and the n-class model without using the CRF in the semantic labelling task.The drawn comparison of the predictive power of the n-class model obtained by applying the CRF model in the semantic labelling is that it is better than the other two models presenting the highest value of its perplexity.
Computational Decomposition of Style for Controllable and Enhanced Style Transfer

Neural style transfer has been demonstrated to be powerful in creating artistic images with help of Convolutional Neural Networks (CNN), but continuously controllable transfer is still a challenging task. This paper provides a computational decomposition of the style into basic factors, which aim to be factorized, interpretable representations of the artistic styles. We propose to decompose the style by not only spectrum based methods including Fast Fourier Transform and Discrete Cosine Transform, but also latent variable models such as Principal Component Analysis, Independent Component Analysis, and so on. Such decomposition induces various ways of controlling the style factors to generate enhanced, diversified styled images. We mix or intervene the style basis from more than one styles so that compound style or new style could be generated to produce styled images. To implement our method, we derive a simple, effective computational module, which can be embedded into state-of-the-art style transfer algorithms. Experiments demonstrate the effectiveness of our method on not only painting style transfer but also other possible applications such as picture-to-sketch problems.
High-Performance I/O Programming Models for Exascale Computing

The success of the exascale supercomputer is largely dependent on novel breakthroughs that overcome the increasing demands for high-performance I/O on HPC. Scientists are aggressively taking advant ...
Data first: turning the digital library "inside out"

At Caltech a variety of systems--Invenio, EPrints, Islandora, ArchivesSpace--are used to manage various components of what would ideally be an integrated Digital Library. Given limited resources and very demanding partners we focus on data first, integration and manipulation tools second, and de-emphasize development within any of our repository environments. Instead, data is harvested nightly from all our repositories and made available through a variety of data feeds and web services, structured data files, as well as through traditional web environments. Our aim is to maintain separate systems insofar as they are useful, but to present a wide variety of services that are data- and user-centric, rather than bound to services defined within a specific system’s set of features. Our approach is to focus on data as the central concern, and to think of nightly metadata harvesting and normalization as “continuous migration.” Our second focus is on tools developments. These are typically lightweight, usually command line tools that enable and encourage our users to engage with the data in ways that are specific to their needs. When needed we are moving to providing traditional web-based access through generic content management systems rather than our underlying repositories.The presentation includes some examples of strategies and services to illustrate the benefits of this approach, including a workflow for an international research group that integrates their specific workflow along with normalizing, publishing and preserving data through the Library, and strategies for automatically enriching locally managed data from external sources.
A Study on the Expression Method of Interaction for Expanding the Publicness of Socially Engaged Art

With the development of new media technology, art has continually expanded the way of expression, and the way of expressing interaction with the audience has also developed in various forms. However, the study of various expression methods rests only on the interaction between the subjective world of the artist and the audience. An artist should not only focus on personal ideas but also share his subjective interests with his social responsibility toward his society, and with the artistic responsibility and role to understand and share the contemporary society with the audience. However, the efforts of artists to expand their social responsibility and the publicity of arts have been passive compared to the artists' efforts to expand their subjective expression. From this point of view, ‘Socially Engaged Art' based on the interaction between art and society is the most appropriate category for art to fulfill its social responsibilities and exert its influence. This study attempts to classify the concept and expression method of 'Socially Engaged Art'. In addition, this study proposes 'Socially Engaged Art' as an alternative to overcome the limitations of the existing public art and analyzes the interaction with the audience according to the expression method of the work. Based on the research results, we tried to use AR-based interactive new media contents appropriately for audience, work, and interaction with society. <FINE DINING> is an interactive work that make audience to sympathize the artist's intended message about social issues. This study seeks to expand the expression method of 'Socially Engaged Art' from the perspective of the audience, the work, and the interaction with society through the interaction work <FINE DINING> appropriately utilizing AR-based interactive new media contents.
The Effectiveness Of Using Reading Connection To Improve Students’ Reading Comprehension On Biography Text (Quasi Experimental Research at the Tenth Grade of SMAN 3 Pandeglang)

AgniyaChoirunnisa. 152301862. 2019. “The Effectiveness Of Using Reading Connection To Improve Students’ Reading Comprehension On Biography Text (Quasi Experimental Research at the Tenth Grade of SMAN 3 Pandeglang). Advisers: Dra. H. Fitri Hilmiyati, M. Ed, Drs. H. Busthomi Ibrahim, M.Ag. This research conducted based on the statement of problems 1). How is students’ reading comprehension on recount text? 2). How is the effectiveness of reading connection in teaching reading comprehension on biography text at the tenth grade of SMAN 3 Pandeglang? The objectives of this research are 1). To find out the students’ reading comprehension on recount text. 2). To find out the effectiveness of reading connections in teaching reading comprehension on biography text at the tenth grade of SMAN 3 Pandeglang. The method used in this research is quasi experimental. The research conducted in the tenth grade of SMAN 3 Pandeglang as the sample and class X MIA 1 consist of 35 students and X MIA 2 consist of 35 stdents. The result of this research shows that using reading connections technique has significant effect on students’ reading comprehension. It can be seen from the result that researcher has got the mean of pre-test score is 54.85 and post-test score is 71.77 from the experimental class and the pre-test of control class is 41.94 and post-test score is 55.08. The writer got t0 = 7.35 df = 68, ttable 5% = 1,99. It means Ha (alternative hypothesis) of the research is accepted that there is a significant improvement of using reading connection to improve students’ reading comprehension on recount text of biography. From the result of the test, it can be concluded that the reading connection technique has effect to improve students’ reading comprehension on biography text and also can be applied in teaching learning process to improve students’ reading comprehension. Keywords: Reading Connections, reading comprehension, recount text of biography.
Scene matching areas classification based on PCANet and MLP

Scene matching aided navigation is mainly used in autonomous navigation of aircraft. In scene matching field, scene matching areas selecting is a great challenge. The traditional methods focus on extracting image features and building a model to fit the relationship between image features and matching suitability indicators. We propose a new method combing principal component analysis network (PCANet) and multi-layer perception (MLP) to select scene matching areas for the first time. Firstly, we built a dataset based on images captured by TerraSAR-X satellite. Secondly, we extract information of each image by PCANet and generate label based on matching probability. Finally, MLP is used to automatically fit the mapping relation between image and matching suitability. The proposed method avoids the steps of extracting features manually and improves the performance in different task. The method proposed in this paper performs better than convolutional neural network (CNN).
Level Set Model driven by function of Signed Pressure Force For image segmentation

Segmentation is an extremely active field of research since it represents one of the more difficult stages for relevant parameters extraction from images. In this work, we study. A New robust Level Set image segmentation model is developed by function of Signed Pressure Force (SPF). The advantages of this method are Firstly, the signed pressure function can effectively stop contours on weak or fuzzy edges. Secondly, the inner and outer limits can be detected regardless of the starting point of the initial contour. We compare this method with Chan Vese (C-V) method and Geodesic Active Contours (GAC). The performance of each method can be evaluated either visually, or from similarity measurements between the results of the segmentation and a reference. Through the results, we have shown that the better results are obtained with the proposed method.
ANALISIS SISTEM INFORMASI AKUNTANSI PENJUALAN LISTRIK UNTUK PERENCANAAN DAN PENGENDALIAN BISNIS DI PT. PLN (PERSERO) CABANG MANADO SELATAN

Every company always needs a sales accounting information system because sales are a major activity in the company. A good sales accounting information system must be accompanied by effective business planning and control. With the existence of business planning and control in the company PT.PLN can make the company more focused in conducting the electricity sales process to get profit. The research aims to analyze the electricity sales accounting information system for business planning and control at PT. PLN (Persero) Branch of South Manado whether it has been effective or not. The method used in this research is descriptive analysis with a qualitative approach. The data taken in this study is the report on the results of electricity sales in January-December 2018. The electricity sales information system from planning to being realized has been effective then it can be concluded that the electricity sales accounting information system for business planning and control is running well and has been running well according to company needs.
LibGuides: SMARTR Goal Package: Strategies for success

Package SMARTR goal starter kitLibrary standard, POG skill, links to resources, strategies for successDemonstrate how SMARTR goal is aligned to SIIP and FCPS strategic plan
Survey on text-to-speech Kannada using Neural Networks

In this paper, we have explained the different approaches of text-to-speech conversion for Kannada language using Neural Networks. Text-to-speech conversion (TTS) has a wide variety of applications like it serves as an effective aid to the visually impaired by offering a computer-generated spoken voice that would “read” text to the user. TTS can also be used as an interactive educational appliance, as an assistant, etc. The application field of synthetic speech is expanding fast while the quality of the TTS system is also increasing steadily. Text-To-Speech conversion using Neural Networks is found to be more accurate when compared to many other methods like Concatenation, Digital Signal Processing, Articulatory Synthesis, etc. The different approaches of neural networks that we have mentioned in this paper explain its own methodologies, its applications and also its pros and cons.
Architecture to Design Booking Appointment Applications for the Smart Personal Assistant Alexa

The intelligent smart assistants are becoming more interactive and helpful for everyday tasks. The Amazon Echo has potential for advanced voice interactions and as a tool for conducting complex tasks. The potential of the Amazon Echo in the area of booking appointments is not being fully exploited by developers. A flexible architecture for developing appointment booking applications for the Amazon Echo was proposed. The architecture serves as guide for developers without experience working with Voice User Interfaces and saves development time by abstracting the complexity of voice interactions. A prototype skill was developed following the architecture principles and evaluated by a group of users. The skill successfully defines how an appointment booking skill should be.
Intelligent Multi-agent Coordination and Learning

We present a hierarchical neural-fuzzy system for precision coordination of multiple mobile agents for simultaneous arrival at their destination positions in a cluttered urban environment. We assume that each agent is equipped with a 2D scanning LiDAR to make movement decisions based on local distance and bearing information. Two solution approaches are considered and compared. Both of them are structured around a hierarchical arrangement of controller modules to enable synchronisation of the agents arrival times while avoiding collision with obstacles. The first approach is based on cascading SONFIN (Self-Organizing Neural Fuzzy Inference Network) controllers, and the second approach considers the use of an LSTM (Long ShortTerm Memory) recurrent neural network module alongside SONFIN modules. Parameters of all the controllers are optimised using the Particle Swarm optimization algorithm. A physics-based simulator, Webots, is used as a training and testing environment for the two learning models to facilitate the deployment of codes to hardware which will follow in the next phase of our research.
Aviation English Listening and Repeating Task for Native English Speaker and Non-Native English Speaker Pilots

Aviation English, based on a coded jargon from World War II, is a mandatory form of communication for pilots and controllers in international airspace. The International Civil Aviation Organization also requires proficiency in Conversational English, for use in non-standard communication. However, our past research indicates that Aviation English and Conversational English are distinct varieties of English, suggesting that assumptions about native English speaker proficiency and additive learning for non-native English speakers may be false. To establish how different these language varieties are, we present a study of Aviation English intelligibility for non-native and native English speaking pilots. Results suggest that non-native English speaking pilots exhibit high proficiency in Aviation English without parallel proficiency in Conversational English. Non-native English speaking Aviation English users suffer the unfair burden of having to learn and maintain proficiency in two language varieties. The impact on learning, training and testing of Aviation English is discussed.
Formal Analysis of MaTRU Cryptosystem

Security analysis of cryptosystems is a significant area due to the effects on the real world. There are main ways for security analysis: the first one is resistance to the attacks and the second one is on the hardness of computationally hard problems. To provide mathematically correctness of the cryptosystem, formal analysis is used. In this study, by following formal analysis of NTRUEncrypt, th formal analysis components of MaTRU, a matrix variant of NTRU, are given.
Who's afraid of free speech?

It is a growing crisis we can't ignore: free speech has been taking a battering in our Western countries recently.
The effectiveness of wordless Picture Books on Writing Skill

Ariyana Fitriani. 142301624. 2018. “The effectiveness of wordless Picture Books on Writing Skill” (Undergraduate Research Paper, English Education Departement, Education and Teacher Training Faculty, State Islamic University Sultan Maulana Hasanuddin Banten) Adviser : Prof. Dr. H. Ilzamudin Ma’mur, M.A. and Dr. Hj. Anita, S.S., M.Pd. ABSTRACT This research investigates the effectiveness of wordless picture media on writing skill at the second grade students of SMP Negeri 3 Gunungsari. This research conducted based main problems: 1) How is the students’ writing ability in narrative text at the second grade of SMP Negeri 3 Gunungsari, 2) How is the effect of wordless picture on students’ writing skill at the second grade at SMP Negeri 3 Gunungsari. The aims this research are: 1) To know the students’ writing ability in narrative text at the second grade of SMP SMP Negeri 3 Gunungsari, 2) To explain the effectiveness of using wordless picture books on students’ writing skill of SMP Negeri 3 Gunungsari. To answer the research questions, the writer collect data from 63 students’ as a sample in two classes, one class as the experiment class and another class as the control class. By applying the experimental research method, the population are 128 students at the second grade of SMP Negeri 3 Gunungsari. That consists of four classes, VIII A, VIII B, VIII C, VIII D. Each class consists of 31, 33, 32 and 32 students. The writers choose two classes as a sample while VIII A as experiment class and VIII C as control class. Since the writer uses quasi experimental research method, the data gathered through pretest and posttest. iii The result of the research shows that the hypothesis, that the null hypothesis is that null hypothesis is rejected its shown from statistical value that significant 5% = 1,99, significant 1% = 2,65 and the result of to = 8,54. Based on calculating the data of ttest, so the effectiveness of wordless picture books in teaching writing narrative text has positive effect. Keywords: Wordless Picture Books, Writing, Narrative Text.
Algorithms for Complex Systems Reliability Analysis Based on Bayesian Network

This work was supported by the National Natural Science Foundation of China (No.51675525 and 11725211).
Implementasi Manajemen Keuangan Sekolah Berbasis Rapbs (Rencana Anggaran Pendapatan & Belanja Sekolah) Di Smk Muhammadiyah 2 Klaten

This study aims to find out how the implementation of school financial management systems, to find out how the planning and preparation proces in school financial manajement, and how much realization of the use of the budget planning in SMK Muhammadiyah 2 Klaten. This type of research is to use a combination method (mixed method) with an unbalanced mixed research design (concurrent embedded design). The research in This study was SMK Muhammadiyah 2 Klaten. Data collection techniques using observation, interviews, and document review. The sample in this study includes people who truly understand the situation of financial management at school. The qualitative data analysis technique used is trianggulation, while the quantitative data analysis technique uses descriptive statistical analysis. Based on the research results, it shows that the process of preparing the RAPBS in each year and the beginning of learning. Budget planning and realization in managing shool financial management in SMK Muhammadiyah 2 Klaten has been carried out effectively and efficiently by complying with applicable regulations. For the Muhammadiyah 2 Vocational School in Klaten, not all planning can be realized yet.
Threshold Rainfall Ranges for Landslide Occurrence in Matara District and Findings of a Social Survey on Emergency Preparedness

Matara district has faced several devastating landslide events within past few decades. Impacts of those landslide events would have been reduced if the threats had been identified early enough and the early warnings were disseminated at the right time. The objectives of this research were (a) to identify the effects of antecedent rainfall on the probability of landslide occurrence and (b) to analyse the knowledge of the community on landslide response, preparedness and landslide warning signs in general. During this study the major landslide events occurred in 2003 and 2017 were studied for the rainfall impact. The landslide locations were collected and the rainfall relevant to each and every landslide location was extracted by using a GIS-based interpolation method. Simultaneously a social survey was conducted to achieve the second objective described above. Starting from the daily rainfall of two days prior to landslide event (i.e. Day 3) till the daily rainfall of landslide day (Day 1), there was an identifiable pattern. There is more than 90 percent chance for a landslide to occur, when the rainfall of the day of the landslide event is close to 300 mm (in our case 290 mm) or above with a rainfall of ~80 mm or above on the previous day (Day 2). The majority of the events (over 94 percent) had a daily rainfall of ~80 mm or above on Day 3. The cumulative rainfall of the landslide day up to three days prior to the landslide event shows a significant pattern (Day 1-Day 4). There is more than 94% chance for a landslide to occur when the total rainfall received on Day 1 and Day 2 exceeds 375 mm. Overall, when there is a rainfall event of ~80 mm or over, people need to be warned/cautions about a potential landslide within the next three days, if the rainfall continues to be high. Social survey shows that during 2017 event/s people were more prepared for landslides compared to 2003, but still there are many steps to be taken in terms of response, preparedness and early warnings. Keywords: Landslides, Rainfall pattern, Early warnings, Community preparedness