Reviewerly/exHarmony huggingface dataset:
Subvert KEM to Break DEM: Practical Algorithm-Substitution Attacks on Public-Key Encryption.

Motivated by the currently widespread concern about mass surveillance of encrypted communications, Bellare et al. introduced at CRYPTO 2014 the notion of Algorithm-Substitution Attack (ASA) where the legitimate encryption algorithm is replaced by a subverted one that aims to undetectably exfiltrate the secret key via ciphertexts. Practically implementable ASAs on various cryptographic primitives (Bellare et al., CRYPTO’14 & ACM CCS’15; Ateniese et al., ACM CCS’15; Berndt and Liśkiewicz, ACM CCS’17) have been constructed and analyzed, leaking the secret key successfully. Nevertheless, in spite of much progress, the practical impact of ASAs (formulated originally for symmetric key cryptography) on public-key (PKE) encryption operations remains unclear, primarily since the encryption operation of PKE does not involve the secret key, and also previously known ASAs become relatively inefficient for leaking the plaintext due to the logarithmic upper bound of exfiltration rate (Berndt and Liśkiewicz, ACM CCS’17).
Face Recognition Technology Adoption In Pharmacies in Lebanon

The pace and evolution of information technology solutions has impacted every profession, but its impact on the ones in direct exposure to clients, has been particularly dramatic. Nevertheless, pharmacies all over the world have aggressively embarked on adopting new technologies that play an increasing role in sales, marketing, and surprisingly customer service positions. Face recognition is one of those technologies whose purpose is to integrate customer relationship management (CRM) systems, in the purpose of analyzing data related to clients and building customer loyalty. Pharmacies in Lebanon today know that what’s working now may need refining tomorrow. Thus, they must be ready to invest in this latest technology to grow and sustain in the ever changing markets. This paper aims at exploring and assessing face recognition in Lebanon and overviewing its design and modeling. Moreover, a critical examination of the productivity, acceptability, and the assessment on the readiness of pharmacists in Lebanon to “face recognition tools” shows that they are still in the early stages. Major advances in the system design level have been discussed, as well as the current issues facing pharmacies will be identified. Nowadays, the pharmacy should be much more than a shop selling medicines; It should make people feel better from the moment they step in; starting from how it handles its products leading to how it treats its visitors. And to take care of people’s health, it should take advantage of cognitive solutions oriented towards customer care.
Real-time Opinion Extraction and Classification for Vietnamese Posts on Social Networks

The growth of social networks changes the way people communicate and interact with each other. People have a tendency to give their thoughts and feelings on social networks. Thus, opinion mining posts on social networks is meaningful for companies and governments in terms of business and management. In this research, we propose a new approach for real-time extraction and classification for Vietnamese posts on social networks. There is an integration of Apache Kafka and Spark Streaming for large scale data collecting and processing. We use statistical methods for opinion extraction and classification. Experiments were conducted on a Spark cluster with real-time data stream collected from Facebook.
109 COCATOO: a cohort comparison tool for GOSH clinical researchers

<h3></h3> When faced with large amounts of data, it can be a challenging and lengthy process for a researcher to identify key differences and trends between different sets of patients. The development of a reporting tool which can be easily adapted to any speciality and patient selection would be advantageous in highlighting and presenting patient group comparisons in a clinical research environment. By developing standard, reproducible analytics from the core datasets provided by the Digital Research Environment (DRE) team at GOSH, the researcher is able to identify differences in hospital (hospital admissions, ward stays) and clinical (patient laboratory results, demographics and vital signs) trends between user defined cohort-control patient groups which can accelerate their clinical understanding. Herein, we introduce COCATOO, a cohort comparison tool that compares and reports distinct sets of patient groups based on defined specifications which are controlled by the researcher. By utilising generalisable analytics developed in R, the tool is able to display a set of predefined exploratory data analytics (EDA) which have the ability to be adapted to any hospital department by incorporating project specific rules. We present here an example with Chronic Kidney Disease (CKD) comparing stage 5 to stages 1–4. The output report gives an overview of the disease and highlights significant cohort-control differences via the predefined EDA.
Discussion on the Teaching Problems and Countermeasures of Ancient Chinese Literature Under the New Education Concept

Ancient Chinese literature is an important part of Chinese language and literature. However, due to the lack of professional quality and teaching experience of most ancient Chinese literature teachers in China, there are many problems in the teaching of ancient Chinese literature, which hinders the improvement of students' comprehensive quality. In this regard, this paper discusses the teaching problems and coping strategies of ancient Chinese Literature under the new education concept, hoping to help improve the teaching quality of ancient Chinese literature in China.
A Multi-class Approach - Building a Visual Classifier based on Textual Descriptions using Zero-Shot Learning.

Machine Learning (ML) techniques for image classification routinely require many labelled images for training the model and while testing, we ought to use images belonging to the same domain as those used for training. In this paper, we overcome the two main hurdles of ML, i.e. scarcity of data and constrained prediction of the classification model. We do this by introducing a visual classifier which uses a concept of transfer learning, namely Zero-Shot Learning (ZSL), and standard Natural Language Processing techniques. We train a classifier by mapping labelled images to their textual description instead of training it for specific classes. Transfer learning involves transferring knowledge across domains that are similar. ZSL intelligently applies the knowledge learned while training for future recognition tasks. ZSL differentiates classes as two types: seen and unseen classes. Seen classes are the classes upon which we have trained our model and unseen classes are the classes upon which we test our model. The examples from unseen classes have not been encountered in the training phase. Earlier research in this domain focused on developing a binary classifier but, in this paper, we present a multi-class classifier with a Zero-Shot Learning approach.
Selected tools for Java class and bytecode inspection in the educational environment

Abstract Java is not only a modern, powerful, and frequently used programming language, but together with Java Virtual Machine it represents a novel dynamic approach of writing and executing computer programs. The fact that Java programs are executed in a controlled environment has several important implications that define the nature of the language and makes it different from the traditional C-like languages. Knowing the detailed differences between the two types of languages and execution environments is a part of the holistic education of a computer engineer. In this paper, we present some behind-the-scene details about the Java Virtual Machine and we show how these details could be used in the educational process to demonstrate the differences and to emphasise the advantages of the dynamic programming approach when compared to the static one. After presenting some information about class files and about the internal structure and operation of the Java Virtual Machine we demonstrate the usage of public domain programs that could be used in the educational process to put these theoretical concepts into practice.
RESULTS OF THE PEDAGOGICAL EXPERIMENT OF FORMATION OF BASIC PROFESSIONAL COMPETENCE IN FUTURE BACHELORS OF MECHANICAL BUILDING SPECIALTIES

the article deals with the organization and results of pedagogical experiment on formation of basic professional competence of future bachelors of mechanical engineering specialties in the process of scientific and natural preparation. Scientific works on methodology and methods of pedagogical researches were offered for research, methods of mathematical statistics in pedagogy were used. It is determined that the results of the experiment confirmed the statistical validity of the influence of the developed pedagogical conditions of forming the basic professional competence of future bachelors of mechanical engineering specialties. It is found that the analysis of the results, carried out at the end of the experiment, showed significant positive changes by all criteria of motivational, cognitive, activity, and personal.
Predictive analysis of two bijectively related families of functions in L2, which are expressed as tuple pairs

This article proposes a method of function image prediction calculation by its preimage. This method is based on regression analysis of function image and preimage pairs in L 2 . The prediction model application procedure is described. The algorithm pseudocod are given.
PAC Learning of Deterministic One-Clock Timed Automata

We study the problem of learning deterministic one-clock timed automata in the framework of PAC (probably approximately correct) learning. The use of PAC learning relaxes the assumption of having a teacher that can answer equivalence queries exactly, replacing it with approximate answers from testing on a set of samples. The framework provides correctness guarantees in terms of error and confidence parameters. We further discuss several improvements to the basic PAC algorithm. This includes a special sampling method, and the use of comparator and counterexample minimization to reduce the number of equivalence queries. We implemented a prototype for our learning algorithm, and conducted experiments on learning the TCP protocol as well as a number of randomly generated automata. The results demonstrate the effectiveness of our approach, as well as the importance of the various improvements for learning complex models.
Secure Optical Communication based on Synchronous Chaotic Phase Scrambling-Induced Wavelength-Aliasing

We propose a physical-layer encryption scheme that is compatible with conventional WDM transmission system in virtue of private chaos synchronization and phase-modulation-induced wavelength-aliasing, and experimentally demonstrate a 4×12.5Gbps secure WDM transmission to confirm the feasibility.
Searching for Controllable Image Restoration Networks

Diverse user preferences over images have recently led to a great amount of interest in controlling the imagery effects for image restoration tasks. However, existing methods require separate inference through the entire network per each output, which hinders users from readily comparing multiple imagery effects due to long latency. To this end, we propose a novel framework based on a neural architecture search technique that enables efficient generation of multiple imagery effects via two stages of pruning: task-agnostic and task-specific pruning. Specifically, task-specific pruning learns to adaptively remove the irrelevant network parameters for each task, while task-agnostic pruning learns to find an efficient architecture by sharing the early layers of the network across different tasks. Since the shared layers allow for feature reuse, only a single inference of the task-agnostic layers is needed to generate multiple imagery effects from the input image. Using the proposed task-agnostic and task-specific pruning schemes together significantly reduces the FLOPs and the actual latency of inference compared to the baseline. We reduce 95.7% of the FLOPs when generating 27 imagery effects, and make the GPU latency 73.0% faster on 4K-resolution images.
Geochemistry and mineral chemistry of quartz mica schists within Iseyin-Oyan Schist Belt, Southwestern Nigeria

Background/Objectives: The Iseyin-Oyan schist belt is made up metasedimentary rocks, gneisses, granites and pegmatite intrusions. The study was aimed at identifying the schist within this belt and assess their metamorphism, geochemical characteristics and tectonic origin. Methods: Detailed geologic field mapping was undertaken where rocks were located, studied in-situ and identified. Samples of the schist were prepared for petrographic studies. Mineralogical contents were determined using X-Ray Diffraction technique. Polished sections were studied for mineral chemistry using Scanning Electron Microscope-Energy Dispersive Spectroscopy. Rock samples were analysed using X-Ray Fluorescence Spectroscopy and Inductively Coupled Plasma Emission Spectrometry. Geochemical data were elucidated using diverse geochemical discrimination diagrams. Findings: The schists are quartz mica schists and occur in close association with amphibolites, intrusive granitoids and pegmatites. The Mineral assemblage indicates upper (at the western part) to lower (at the central part) amphibolite facies grade metamorphism in the area. Pyrope-almandine garnets occur in quartz mica schist at the western parts reinforcing higher pressure-temperature metamorphic conditions. The concentration (in %) of SiO2 ranged from 56.4-71.6; Al2O3, 13.7-21.1; Fe2O3, 2-8; MgO, 0.7-2.4; and K2O, 2.1-5.5 supporting the evidence for differential degrees of metamorphism. Large iron lithophile and high field strength elements are similar to the average upper continental crust. Pronounced negative Europium anomaly pointed to the major roles played by feldspars during the geological processes. Plagioclase ranged from albite-oligoclase and oligoclase- andesine. The precursors of the quartz mica schist are possibly arkosic and greywacke sands deposited within the active continental margins. Evidence of uplift and overturning suggested for the differential metamorphism may be due to these events usually associated with active continental margins. Applications: This study has identified the once named undifferentiated schist in the study area to be quartz mica schist with details in their grades of metamorphism elucidated. Keywords: Quartz mica schist; geochemistry; mineral chemistry; Iseyin-Oyan schist belt; precambrian basement complex
Virtual Environmental Monitoring Laboratory. Using Robotic Systems

This article presents the developed ecomontoring system. In this article you will find the concept of the developed ecomontoring system and its prototype. The problem was posed by the lack of effective environmental monitoring systems. The development of the concept and structure was made taking into account modern technologies and the fast pace of their development. In the process of working on the project, it has been investigated factors that have an adverse effect on the environment, such as the air condition, it has been made a model of an intelligent system for monitoring the state of the environment with the use of cloud technologies, the Internet of things, measuring robotic systems for the collection / control / analysis of climatic parameters, such as temperature, relative humidity and the level of carbon dioxide in the air. Software is developed and modularity and adaptability of the system is provided. The effectiveness of developed ecomontoring system is verified through the use of mathematical method and making experiments on each component of the system.
Prospects for the Development of Digital Healthcare Sector through Patent Analysis

In recent years, the healthcare information system based on big data has been growing rapidly and is being adapted to medical information to derive important health trends and support timely preventive care.This study analyzes patents to grasp the latest technological trends and core competencies in the digital healthcare field in Korea, by identifying which fields have numerous patent applications, and which fields have few patent applications.The technology classification system for patent analysis is divided into health information measurement technology (A), healthcare platform technology (B), and healthcare teleservice technology (C) for digital healthcare.Korea is confirmed to have high patented technology in the field of biometric measurement technology and health information building, sharing, and utilization technology.In the field of life information pattern measurement technology, the patent activity rate is high, while the market retention rate is very low.As a result of OS Matrix analysis, in the field of Korean healthcare, technology development using wearable devices or toilet seats for identification, diagnosis, and treatment of users, and patient pattern analysis using big data were found to be areas with relatively low concentration of R&D or patent applications.And it seems that there is a need for technology development and patent application in these fields in the future.
Decision Analytic Pricing with Constant Price Elasticities

This article introduces a new pricing model which uses decision analysis and isoelastic demand functions. Using the methodologies discussed here will enable companies to choose prices that will maximize the profit of a given product based on the state of the economy. An exponential utility function is used to incorporate the risk attitude of the company. The use of the model is demonstrated through a case study on 2018 Chevrolet Malibus. The proper use of the model will “take the guesswork out” of the pricing decision and help companies make pricing decisions using the best available data. Keywords: Pricing, Decision Analysis, Elasticity, Utility.
PELAKSANAAN KEGIATAN PELAYANAN KELILING PEREKAMAN E-KTP DI KECAMATAN TANJUNG LAGO KABUPATEN BANYUASIN

This study discusses the implementation of Mobile Recording E-Identity Card Service Activities in Tanjung Lago District, One of which supports the implementation of the E-Identity Card is a printing press. The regions do not yet have permission to choose their own E-Identity Card because the current authority is still at the Center. On the basis of the above problems, a special government apparatus in Tanjung Lago Subdistrict, Banyuasin District, did a recording of the E-Identity Card to help and facilitate the community in the process. This study uses a qualitative method with observation techniques and direct interviews with informants. The conclusion of this study is that there are still people who do not have an E-Identity Card because the people in Tanjung Lago District are happy to record e-ID Card and related printing machines that are still at the center and there are still responses to the government that are less friendly from the government apparatus in Tanjung District, For this reason, infrastructure facilities to support the e-ID card recording process in Tanjung Lago Subdistrict are provided by the central government.
Algorithm for recognizing text commands for constructing an arbitrary form of data input

The article proposes a solution to the problem of processing requests recorded in Russian to building data entry forms. Lexeme and syntactic analyzes stages request with examples are described. In the end of article, there is link to working project and repository with source code in Kotlin language.
Active Annotation of Informative Overlapping Frames in Video Mosaicking Applications

Video mosaicking requires the registration of overlapping frames located at distant timepoints in the sequence to ensure global consistency of the reconstructed scene. However, fully automated registration of such long-range pairs is (i) challenging when the registration of images itself is difficult; and (ii) computationally expensive for long sequences due to the large number of candidate pairs for registration. In this paper, we introduce an efficient framework for the active annotation of long-range pairwise correspondences in a sequence. Our framework suggests pairs of images that are sought to be informative to an oracle agent (e.g., a human user, or a reliable matching algorithm) who provides visual correspondences on each suggested pair. Informative pairs are retrieved according to an iterative strategy based on a principled annotation reward coupled with two complementary and online adaptable models of frame overlap. In addition to the efficient construction of a mosaic, our framework provides, as a by-product, ground truth landmark correspondences which can be used for evaluation or learning purposes. We evaluate our approach in both automated and interactive scenarios via experiments on synthetic sequences, on a publicly available dataset for aerial imaging and on a clinical dataset for placenta mosaicking during fetal surgery.
Omni-Zernike Algorithm for Template Matching in Catadioptric System

Image descriptor have been widely applied in many computer visions and image understanding applications including pattern recognition, robotic, video surveillance, camera calibration and image retrieval, etc. Invariants features are robust when apply several transformations of photometry (illumination, blur, noise, JPEG compression) and transformations of geometry (scaling, rotation, translation and viewpoint change).In this study, we present representation and matching region descriptors.Consequently, a set of region used provided by catadioptric system for evaluation of the performance.These regions are normalized by unit circle form with form and size change.In this contribution, the image descriptors of regions used is Moment's Zernike.They are most suitable invariants in omnidirectional context thanks to the polar coordinates used both omnidirectional geometry and Zernike Moments formulation.The aim is realize a robust matching between object's block by using a measure of distance between Zernike's moment descriptors for optimal similarity.Results shown clearly demonstrate the performance of our method and powerful than most important region descriptors (GLOH, SIFT, PCA-SIFT, complex moments and steerable filters) in term of the ROC curve or precision-recall criterion.
Sentiment Analysis on Gujarati Text: A Survey

Internet is a source of huge amount of information generated from blog, social websites, and forums and so on by user. In today’s world information available on the internet plays an important role in human’s life. To analyze a huge amount of information it’s require an automated method to classify this type of information. High usage of web and mobile technologies, user generated content in Guajarati is increasing on the web is motivation behind sentiment analysis. Emotion analysis is the process of identifying user’s opinion in section of text. This opinion helps to carry out decisions. Now a day’s a new source of opinion for users are web documents. Sentiment analysis is natural language processing task that extract information from various sources such as news, social networking site, blog, forums and classify them into positive, negative or neutral on the basis of their polarity. Lots of research is done in English language but it’s also important to perform sentiment analysis in Gujarati language as it is 6th official language in India. This paper gives an overview how sentiment analysis can be performed in Gujarati Language.