Reviewerly/exHarmony huggingface dataset:
A Secure Access Policies Based Data Deduplication SystemA Secure Access Policies Based Data Deduplication System

Attribute-based encryption (ABE) has been widely used in cloud computing where a data provider outsources his/her encrypted data to a cloud service provider, and can share the data with users possessing specific credentials (or attributes). However, the standard ABE system does not support secure deduplication, which is crucial for eliminating duplicate copies of identical data in order to save storage space and network bandwidth. In this paper, we present an attribute-based storage system with secure deduplication in a hybrid cloud setting, where a private cloud is responsible for duplicate detection and a public cloud manages the storage. Compared with the prior data deduplication systems, our system has two advantages. Firstly, it can be used to confidentially share data with users by specifying access policies rather than sharing decryption keys. Secondly, it achieves the standard notion of semantic security for data confidentiality while existing systems only achieve it by defining a weaker security notion. In addition, we put forth a methodology to modify a ciphertext over one access policy into ciphertexts of the same plaintext but under other access policies without revealing the underlying plaintext. The main aim of this project is to achieve new distributed de-duplication systems. we present an attribute-based storage system with deduplication in a cloud setting with higher Trusty and security. In this Deduplication, techniques are most widely employed to backup data and minimize network and storage overhead by detecting and eliminating redundancy among data.I.
MulCode: A Multiplicative Multi-way Model for Compressing Neural Language Model

It is challenging to deploy deep neural nets on memory-constrained devices due to the explosion of numbers of parameters.Especially, the input embedding layer and Softmax layer usually dominate the memory usage in an RNNbased language model.For example, input embedding and Softmax matrices in IWSLT-2014 German-to-English data set account for more than 80% of the total model parameters.To compress these embedding layers, we propose MulCode, a novel multi-way multiplicative neural compressor.MulCode learns an adaptively created matrix and its multiplicative compositions.Together with a prior weighted loss, MulCode is more effective than the state-of-the-art compression methods.On the IWSLT-2014 machine translation data set, MulCode achieved 17 times compression rate for the embedding and Softmax matrices, and when combined with quantization technique, our method can achieve 41.38 times compression rate with very little loss in performance.
Comparative Study ofConvolutional Neural Network with Word Embedding Technique for Text Classification

This paper presents an investigation of the convolutional neural network (CNN) with Word2Vec word embedding technique for text classification.Performance of CNN is tested on seven benchmark datasets with a different number of classes, training and testing samples.Test classification results obtained from proposed CNN are compared with results of CNN models and other classifiers reported in the literature.Investigation shows that CNN models are better suitable for text classification than other techniques.The main objective of the paper is to identify best-fitted parameter values batch size, epochs, activation function, dropout rates and feature maps values.Results of proposed CNN are better than many other classification techniques reported in the literature for Yelp Review Polarity dataset and Amazon Review Polarity dataset.For all the seven datasets, accuracy obtained by proposed CNN is close to the best-known results from the literature.
Application of an Automatic Plagiarism Detection System in a Large-scale Assessment of English Speaking Proficiency

This study aims to build an automatic system for the detection of plagiarized spoken responses in the context of an assessment of English speaking proficiency for non-native speakers.Classification models were trained to distinguish between plagiarized and nonplagiarized responses with two different types of features: text-to-text content similarity measures, which are commonly used in the task of plagiarism detection for written documents, and speaking proficiency measures, which were specifically designed for spontaneous speech and extracted using an automated speech scoring system.The experiments were first conducted on a large data set drawn from an operational English proficiency assessment across multiple years, and the best classifier on this heavily imbalanced data set resulted in an F1-score of 0.761 on the plagiarized class.This system was then validated on operational responses collected from a single administration of the assessment and achieved a recall of 0.897.The results indicate that the proposed system can potentially be used to improve the validity of both human and automated assessment of non-native spoken English.
Communicating User Insights with Travel Mindsets and Experience Personas in Intra-city Bus Context

Design of attractive services for the bus travel context is important because of the aim to increase the usage of sustainable travel modes of public transportation. In bus travel, both user experience of the digital services and the broader service design context of the public transportation need to be addressed. Experience-Driven Design (EDD) can be used to take the passengers’ needs and experiences in the core of the design process. This paper presents a qualitative diary and interview study on bus travel experience with 20 passengers in two major cities in Finland. The aim of this study was to identify and communicate frequent bus passengers’ needs, experiences, values and activities as user insights to support experience-driven service design in the public transportation context. Based on the data analysis, we derived ten Travel Mindsets: Abstracted, Efficient, Enjoyer, In-control, Isolation, Observer, Off-line, Relaxed, Sensitive, and Social. To communicate the study findings on bus passengers’ travel experience, Travel Experience Personas were created. The personas include primary and secondary travel mindsets, specific needs related to bus travel, insights on mobile device usage, and target user experience (UX) goals that could enhance the personas’ travel experience. We also discuss how the personas can be used as a communicative design tool that supports EDD of novel services in the bus context.
MTD Techniques for Memory Protection Against Zero-Day Attacks

During the past 25 years, the arms race between attacks exploiting memory corruption and memory protection techniques has drawn tremendous attention. This book chapter seeks to give an in-depth review of the newest research progress made on applying the MTD methodology to protect memory corruption exploits. The new research progress also represents the current phase of the arms race in the MTD perspective. In particular, on one hand, at the frontier of defending against control-hijacking attacks, we will give an in-depth review on the shift of defense strategy from static ASLR to dynamic ASLR. On the other hand, at the frontier of defending against data-oriented attacks, we will give an in-depth review on the shift of defense strategy from static DSLR to dynamic DSLR.
SEAGLE: A Platform for Comparative Evaluation of Semantic Encoders for Information Retrieval

We introduce SEAGLE, 1 a platform for comparative evaluation of semantic text encoding models on information retrieval (IR) tasks.SEAGLE implements (1) word embedding aggregators, which represent texts as algebraic aggregations of pretrained word embeddings and (2) pretrained semantic encoders, and allows for their comparative evaluation on arbitrary (monolingual and cross-lingual) IR collections.We benchmark SEAGLE's models on monolingual document retrieval and crosslingual sentence retrieval.SEAGLE functionality can be exploited via an easy-to-use web interface and its modular backend (microservice architecture) can easily be extended with additional semantic search models.
NL2pSQL: Generating Pseudo-SQL Queries from Under-Specified Natural Language Questions

Generating SQL codes from natural language questions (NL2SQL) is an emerging research area.Existing studies have mainly focused on clear scenarios where specified information is fully given to generate a SQL query.However, in developer forums such as Stack Overflow, 1 questions cover more diverse tasks including table manipulation or performance issues, where a table is not specified.The SQL query posted in Stack Overflow, Pseudo-SQL (pSQL), does not usually contain table schemas and is not necessarily executable, is sufficient to guide developers.Here we describe a new NL2pSQL task to generate pSQL codes from natural language questions on under-specified database issues, in short, NL2pSQL.In addition, we define two new metrics suitable for the proposed NL2pSQL task, Canonical-BLEU and SQL-BLEU, instead of the conventional BLEU.With a baseline model using sequence-to-sequence architecture integrated with denoising autoencoder, we confirm the validity of our task.Experiments show that the proposed NL2pSQL approach yields well-formed queries (up to 43% more than a standard Seq2Seq model).Our code and datasets are publicly available at
A Stylometry Toolkit for Latin Literature

Computational stylometry has become an increasingly important aspect of literary criticism, but many humanists lack the technical expertise or language-specific NLP resources required to exploit computational methods.We demonstrate a stylometry toolkit for analysis of Latin literary texts, which is freely available at www.qcrit.org/stylometry.Our toolkit generates data for a diverse range of literary features and has an intuitive pointand-click interface.The features included have proven effective for multiple literary studies and are calculated using custom heuristics without the need for syntactic parsing.As such, the toolkit models one approach to the user-friendly generation of stylometric data, which could be extended to other premodern and non-English languages underserved by standard NLP resources.
Proposed System for Education Augmented Reality Self English Learning

The AR Self Learning Application is an educational project that base on augmented reality using AR Foundation package which is combination between ARkit and ARCore, the main idea of project is self-learning without needing any tutor as it show in front of user a 3D character which will be user’s private tutor, it introduce each section and start teaching user names of every object in that section and show him animated 3d object which make it easier for user to memorize name of each object.
Kesalahan Penerapan Kaidah Bahasa Indonesia dalam Karya Tulis Mahasiswa pada Mata Kuliah Bahasa Indonesia di Universitas PGRI Semarang

&lt;p&gt;Several errors in spelling and grammar were found in the students' writing on Indonesian language courses. The errors affect the quality of students' academic works. Based on the findings, this study was aimed at (1) describing the forms of misapplication of Indonesian rules and writing in the students’ writing, and (2) defining the aspects behind the application of Indonesian rules and writing in the students’ writing. The approach used in this research is descriptive qualitative. This research was carried out in data collection, data classification, data analysis, and informal data analysis presentation. There are two results in this study. First, language errors were found at three levels, namely errors in aspects of letter writing, elements of paper and use of words, and writing sentences. Second, there are some factors behind this error, both internally and externally.&lt;/p&gt;
Nature of bibliophiles. Reflections inspired by the book of Alexander Yu. Samarin and Leonid I. Fursenko “Bibliophiles-bibliographers of the late XIX – early XX century”

In the analyzed book, the cause of the emergence and support of the phenomenon of bibliophilia is installs. The idea is that the effect of book selection belongs to the sphere of irrational, but thanks to its characteristic property libraries are enriched with the most valuable cultural heritage of different times. The main content of the publication is to assess the information about the contribution to the book culture of famous bibliophiles XIX-early XX centurynot only indicated in the subtitle of the book. Pavel K. Simoni carefully examined the Izbornik Svyatoslav (1076), a Word about Igor's regiment, monuments of old Russian folklore. In the history of book culture returned significant strokes from the biography of Dmitry V. Ulyaninsky, which allowed to recreate an objective description of his life. A lot of information about the life and work of Nikolai N. Orlov during prison and exile, as well as in the post-rehabilitation period. The value of this information is increased by the fact that Nikolai N. Orlov is known not only as a bibliophile, the author of dozens of publications in the professional press, but also as the Director of the Moscow higher technical school. Nikolai E. Bauman (now MSTU im. Nikolai E. Bauman). In General, the publication is evaluated as a good and in form and content.
Towards a Custom Designed Mechanism for Indexing and Retrieving Video Transcripts

Finding appropriate e-Learning resources within a repository of videos represents a critical aspect for students. Given that transcripts are available for the entire set of videos, the problem reduces to obtaining a ranked list of video transcripts for a particular query. The paper presents a custom approach for searching the 16.012 available video transcripts from https://media.upv.es/ at Universitat Politècnica de València. An inherent difficulty of the problem comes from the fact that transcripts are in the Spanish language. The proposed solution embeds all the transcripts using feed-forward Neural-Net Language Models, clusters the embedded transcripts and builds a Latent Dirichlet Allocation (LDA) model for each cluster. We can then process a new query and find the transcripts that have the LDA results closest to the LDA results for our query.
UNSUPERVISED PEDESTRIAN SAMPLE EXTRACTION FOR MODEL TRAINING

Many researches on pedestrian detection use benchmarking datasets such as INRIA for model training.However, models trained with standard video database do not usually obtain satisfying performance in real-life conditions.Hence, supervised training through manually labelled instances is often required to help achieving better detection result.In this research, an innovative unsupervised training approach is proposed.By analyzing the histogram of adjacent pixels modelled from the video sequences, separated pedestrians can be extracted without manual intervention.Experiments have shown consistent performance that is superior over the state-of-the-art methods.
IMMERSION DURING DIGITALMEDIAMULTITASKING

In terms of digital media usage, immersion refers to user involvement in and focus on a single activity.It is easy to assume that individuals can only be immersed in one media at any moment, but the commonalty of multi-tasking raises questions regarding whether one media source should be considered the true locus of immersion.Self-report questionnaires and eye trackers were used to measure the immersive experiences of a sample consisting of students (ranging from undergraduate to doctoral candidates) from two universities while playing video games and watching a television program at the same time.Their data were compared with those for a similar group of individuals playing games or watching television only.While we found evidence of immersion across the two activities while multitasking, some immersion dimensions were significantly weaker.We also noted that immersion experiences from multiple media might be cumulative.A possible explanation for our results is that the act of switching between two media compensated for any down time-users could abandon a less attractive medium and switch to the other, resulting in an impression of continuous immersion in the overall multitasking experience.
An Airborne Geophysical Survey System Based on CH3-UAV Platform(iUAGSS) and it's Applications

Summary As an emerging airborne geophysical platform,unmanned aerial vehicle (UAV),provides a new way to host high-efficiency resource explorations.In recent years,some achievements have been made in the research and development of UAV aerogeophysical platforms all over the world.In this paper,we will introduce an airborne geophysical survey system based on UAV-CH3 platform,leading R&amp;D by Institute of Geophysical and Geochemical Exploration(so we call it ‘iUAGSS’) ,and some applications in northern and western China.By comparing with the datas measured by manned aerial geophysical survey system in same areas,we summarize the advantages and disadvantages of this UAV aerial geophysical survey system.
Readability of HIV/AIDS information manuals in Ghana

This paper examined the readability of some medical information documents for HIV/AIDS patients in Ghana.The SMOG readability formula was used to determine the reading levels of the documents which were obtained through convenience sampling technique.One sample T-test was used to determine whether there were statistically significant differences in the readability of the sampled HIV/AIDS literature compared to a standard 8th grade recommended for public documents.The bootstrapping technique was employed in this evaluation to ensure robust estimates of significant or p-value, standard errors and the confident intervals.The study revealed that the leaflets were generally difficult to comprehend when compared to the standard readability score of public reading materials.The study concluded that it is prudent such documents are written in plane language in order that the target readers would benefit from the information carried by these documents.
What Kind of Grid Formations and Password Formats are Useful for Password Authentication with Eye-Gaze-Based Input?

This study investigates which grid formations and password formats are useful for password authentication by means of eye-gazebased input. Sixteen grid formations were made, in between 3×3 to 6×6 cells (columns-by-rows), for three password formats. The formats were an alphanumeric format, a pattern format, and a picture format. The participants were asked to memorize a 4-object or a 6-object password and register (Task 1), confirm (Task 2), and log in (Task 4) the password on each of the 16 grids with eye-gaze-based input. In Task 3, the participants evaluated each grid with a rating scale. The results showed that task-completion time was mostly shorter for the alphanumeric password format than for the pattern or picture format. Task-completion time of 4-object or 6-object passwords generally increased as the grid density increased, while the task-success rate at the first attempt decreased when the grid density increased. Task-completion time often was longer for grids with more rows than columns (vertical formations, e.g., 3×4 cells) than for grids with more columns than rows (horizontal formations, e.g., 4×3 cells). These results suggest that password authentication with eye-gaze-based input is best performed on horizontal grids with relatively few cells and a traditional (alphanumeric) format.
Don’t Just Scratch the Surface: Enhancing Word Representations for Korean with Hanja

We propose a simple yet effective approach for improving Korean word representations using additional linguistic annotation (i.e.Hanja).We employ cross-lingual transfer learning in training word representations by leveraging the fact that Hanja is closely related to Chinese.We evaluate the intrinsic quality of representations learned through our approach using the word analogy and similarity tests.In addition, we demonstrate their effectiveness on several downstream tasks, including a novel Korean news headline generation task.* Equal contribution. 1 Hanja and traditional Chinese characters are very similar but not completely identical.Some differences in strokes and language-exclusive characters exist.
Simple But Not Naïve: Fine-Grained Arabic Dialect Identification Using Only N-Grams

This paper presents the participation of Qatar University team in MADAR shared task, which addresses the problem of sentence-level fine-grained Arabic Dialect Identification over 25 different Arabic dialects in addition to the Modern Standard Arabic.Arabic Dialect Identification is not a trivial task since different dialects share some features, e.g., utilizing the same character set and some vocabularies.We opted to adopt a very simple approach in terms of extracted features and classification models; we only utilize word and character ngrams as features, and Naïve Bayes models as classifiers.Surprisingly, the simple approach achieved non-naïve performance.The official results, reported on a held-out testing set, show that the dialect of a given sentence can be identified at an accuracy of 64.58% by our best submitted run.
Hubungan Pola Asuh Orang Tua Terhadap Minat Baca Siswa Sekolah Dasar

This reserch aims to find out the correlation of parenting to reading interest g. In this study the researcher uses a simple paradigm research model which only has one independent variable / parental parenting pattern and one dependent variable or dependent yaituminat read students. The indicators used in reading interest in this study were attention, feelings of pleasure, teacher motivation and parents' motivation. This type of research correlates with a quantitative approach that analyzes data with the help of statistical tools in the form of numbers.This research is a correlation research. The approach used in this study is a quantitative approach that analyzes data with the aid of statistical tools in the form of numbers. Samples used students as many as 86 students using simple random sampling method. The sample of this study was tested with SPSS version 23 using correlation regression analysis getting sig results 0.270 indicates that there is a significant relationship in parenting parenting of reading interest but the level of correlation of variable X to variable Y is fairly low. This conclusion is obtained from the interpretation scale table that sig range from 0.200 to sig 0.399 is low, sig &lt;0.199 is classified is lower.
Query-focused Scenario Construction

The news coverage of events often contains not one but multiple incompatible accounts of what happened.We develop a query-based system that extracts compatible sets of events (scenarios) from such data, formulated as oneclass clustering.Our system incrementally evaluates each event's compatibility with already selected events, taking order into account.We use synthetic data consisting of article mixtures for scalable training and evaluate our model on a new human-curated dataset of scenarios about real-world news topics.Stronger neural network models and harder synthetic training settings are both important to achieve high performance, and our final scenario construction system substantially outperforms baselines based on prior work.Query: Jamal Khashoggi was murdered.Jamal Khashoggi entered the consulate of Saudi Arabia consulate in Istambul.He exited the Saudi consulate after a few minutes.The team wanted to arrest Khashoggi but botched