Reviewerly/exHarmony huggingface dataset:
A Robust Functional Minimization Technique to Protect Image Details from Disturbances

Image capturing using faulty systems or environmental vulnerabilities always degrade the image quality and causes the distortion of true details from the original imaging signals.Thus a robust way of image enhancement and edge preservation is an enormously requirement for smooth imaging operations.Although, many techniques have been deployed in this area during the decades for its betterment.However, the key challenges are remain towards better tradeoff between image enhancement and details protection.Therefore, this study inspects the existing limitations and proposes a robust technique based on functional minimization scheme in variational framework for ensuring better performance in case of image enhancement and details preservation simultaneously.A vigorous way to solve the minimization problem is also develop to make sure the efficiency of the proposed technique than some other traditional techniques.
A Novel Watermarking Approach for Protecting Image Integrity based on a Hybrid Security Technique

Digital Photo images are everywhere around us in journals, on walls, and over the Internet.However we have to be conscious that seeing does not always imply reality.Photo images become a rich subject of manipulations due to the advanced digital cameras as well as photo editing software.Accordingly, image forgery is becoming much easier using the existing tools in terms of time and accuracy, and thus the forensics of detecting an image forgery case is becoming difficult and needs more and more time and techniques to prove the image originality especially as crime evidences and court related cases.In this paper, a framework with associated algorithms and methodologies is proposed to ensure the authenticity of the image and the integrity of the content in addition to protecting the photo image against forgery suspects.The framework depends on developing new generation of certified digital cameras that could produce authenticated and forgery-proof photos.The proposed methodology generates an irreversible hash integrity code from the image content based on color matrix calculations and steganography algorithms.The simulation results proved the capability of the proposed technique to detect image forgery cases in more than 16 scenarios of manipulation.
Educational subjects content formation on the basis of components of educational branches of the state standard

The article deals with the approaches to the formation of the content of educational subjects for institutions of general secondary education on the basis of analysis of normative documents and didactic approaches. The causes of the difficulties that arise at each of the stages of the formation of the content of education are revealed and the ways of overcoming them are offered. In this article, we are dealing with the content of the basic and complete general secondary education, which was in the process of formation during 2010-2017. The normative documents which regulate the formation of the content of education and the requirements for its assimilation are: the state standard of education, in which the state requirements for the level of general education of students and the basic curriculum are described according to the branches of education. Based on the standard, a typical curriculum is developed, which defines the list of subjects and the amount of time provided for their learning. The standard stipulates that an educational subject can realize the content of one or several components of the educational branch. In the case of implementation of several components - this may be an integrated course or course, built on a modular principle, where each module implements the content of the corresponding component of the educational branch determined by the standard. The analysis, conducted by us, of the state standard and curricula showed that by this time there is a traditional list of educational subjects, which was determined in the 90’s of the last century. The developers of curricula are traditionally focused on subject content and proceed from the position that subject is a didactically sound system of knowledge, skills and abilities selected from the corresponding science or art for studying at an educational institution, while forgetting that it should primarily realize the task and content of the educational branch of the state standard. We paid special attention in our study for the analysis of the formation of the content of natural science subjects. We discovered that curricula of some natural science subjects not fully meet the requirements of the state standard. These problems, in our opinion, arise because of the lack of holistic approach to the formation of the content of the field “Natural Science” around the cross-cultural natural science content lines, structuring it between two concentrators, describing possible variants of implementing the content of the branch in educational subjects and courses, clear recommendations for building the curricula. Our analyzes will be useful when developing a new state standard for basic and complete secondary education and new curricula.
Visual Servo System Based on Cubature Kalman Filter and Backpropagation Neural Network

This paper attempts to enhance the estimation accuracy of image Jacobian matrix, despite the impacts from unknown statistical features of process noise and measurement noise.For this purpose, the singular value decomposition aided Cubature Kalman filter (SVDCKF) was coupled with a noise compensator for visual servo systems based on the backpropagation neural network (BPNN).The proposed algorithm improves the accuracy of the Kalman filter and compensates for the two noise covariances through the nonlinear approximation function of the BPNN.The proposed Jacobian matrix estimation algorithm was subjected to a binocular stereo visual servoing experiment on the Motoman UP6 robot experimental platform.The experimental results show that the proposed algorithm is capable of completing servo positioning.
O-Nect: Open Source Interface for Motion Capture using RGB Camera

The use of neural networks for evaluation of Human Pose Estimation has been around for a long time in the field of entertainment , gaming , modeling using Motion Capture systems.However , these systems require expensive hardware installations.Motion capture provides several advantages over traditional animation methods.However,the cost of hardware equipment ,personnel and software makes it highly ineffective for low budget designers to obtain and process the essential data for their projects.Complex movement animations and realistic physical interactions can be easily recreated using our approach with minimal hardware investment.In this paper, we discuss an open source library : O-Nect which can be utilized for Motion Capture using a simple RGB camera.Motion Capture based interactive applications could be potentially beneficial while designing interactive humanoid robots.
Experience Of Creating Innovative And Developmental Environment In Masters’ Professional Training

In modern Russian education there are a lot of reasons that cause the interest to educational processes consideration in terms of innovative activity.Among those there is a tendency to keep the balance between traditions and innovations in the field of education, paying attention to the concept of developmental education and implementation of system and activity approach principles.The aim of the article is to present the activity experience in implementation of innovative and developmental environment in professional training of Master's Degree students studying in the program of professional training 'Innovative primary school' worked out and realised in Surgut State Pedagogical University.The authors have investigated the components of innovative and developmental environment and present the practical experience on their implementation in terms of organisation of practical training of Master's Degree Students for innovative professional activity.Work experience of the professors engaged in Master's Degree Program 'Innovative primary school' allows to state that special attention should be given to possibilities of active cooperation of Master's Degree students with innovative and developmental environment, moreover, to be active participants of that environment on the ground of creative innovative activity.
Standardizing Unstructured Interaction Data in Adaptive Instructional Systems

Standardization of unstructured information such as freely generated verbal responses in adaptive instructional systems poses many challenges. For instance, free responses have no clear delimitation of knowledge components, i.e., basic learning units (BLU), and therefore identifying the BLUs in such responses automatically is a challenge. We will review and exemplify major challenges and solutions and make recommendations for standardization of such unstructured information. Our work will inform student models that rely on student free responses, domain models that are derived from textual sources such as textbooks or general resources such as Wikipedia, the interoperability of adaptive instructional systems with free text inputs, and learning record stores.
The rT − X Family of Distributions induced by V: A New Method for Generating Continuous Distributions with Illustration to Cancer Patients Data

In this short note we introduce a new technique to generate continuous distributions which is partially inspired by [1] and [2]. An illustration to cancer patients data is also given, indicating the new class of distributions will be useful in modeling and forecasting data in various disciplines.
Visual Ontology-Based Query Approach for Data Access in Heterogeneous Expertise Environment: Application in PLM Biomedical Imaging

Computer-Aided Design and Applications is an international journal on the applications of CAD and CAM. It publishes papers in the general domain of CAD plus in emerging fields like bio-CAD, nano-CAD, soft-CAD, garment-CAD, PLM, PDM, CAD data mining, CAD and the internet, CAD education, genetic algorithms and CAD engines. The journal is aimed at all developers and users of CAD technology to ptovide CAD solutions for various stages of design and manufacturing. The journal publishes all about Computer-Aided Design and Computer-Aided technologies.
Design of express delivery equipment based on STM32

Abstract this paper introduces the current situation of campus express service points, points out the problems existing in campus express service points and the working situation of express delivery personnel. Through the design of an automatic courier processor. In the hope of automation as a solution to find ways to improve the efficiency of express delivery and solve the pain points in the development of campus express service points. This scheme not only provides a solution to the low efficiency of express processing in campus express service points, but also improves the automation level of express terminal processing in the express industry
Supervised Quantum State Discrimination

first_page settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing:    Column Width:    Background: Open AccessProceeding Paper Supervised Quantum State Discrimination † by Marco Fanizza *, Andrea Mari and Vittorio Giovannetti NEST, Scuola Normale Superiore, Istituto Nanoscienze-CNR, I-56126 Pisa, Italy * Author to whom correspondence should be addressed. † Presented at the 11th Italian Quantum Information Science conference (IQIS2018), Catania, Italy, 17–20 September 2018. Proceedings 2019, 12(1), 21; https://doi.org/10.3390/proceedings2019012021 Published: 19 July 2019 (This article belongs to the Proceedings of 11th Italian Quantum Information Science conference (IQIS2018)) Download Download PDF Versions Notes Excerpt Note: In lieu of an abstract, this is an excerpt from the first page. Combining machine learning and quantum information. [...] Keywords: quantum machine learning; supervised learning; state discrimination; representation theory quantum machine learning; supervised learning; state discrimination; representation theory Share and Cite MDPI and ACS Style Fanizza, M.; Mari, A.; Giovannetti, V. Supervised Quantum State Discrimination. Proceedings 2019, 12, 21. https://doi.org/10.3390/proceedings2019012021 AMA Style Fanizza M, Mari A, Giovannetti V. Supervised Quantum State Discrimination. Proceedings. 2019; 12(1):21. https://doi.org/10.3390/proceedings2019012021 Chicago/Turabian Style Fanizza, Marco, Andrea Mari, and Vittorio Giovannetti. 2019. "Supervised Quantum State Discrimination" Proceedings 12, no. 1: 21. https://doi.org/10.3390/proceedings2019012021 Find Other Styles Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here. Article Metrics No No Article Access Statistics Multiple requests from the same IP address are counted as one view.
Factors Affecting Classification Algorithms Recommendation: A Survey

A lot of classification algorithms are available in the area of data mining for solving the same kind of problem with a little guidance for recommending the most appropriate algorithm to use which gives best results for the dataset at hand.As a way of optimizing the chances of recommending the most appropriate classification algorithm for a dataset, this paper focuses on the different factors considered by data miners and researchers in different studies when selecting the classification algorithms that will yield desired knowledge for the dataset at hand.The paper divided the factors affecting classification algorithms recommendation into business and technical factors.The technical factors proposed are measurable and can be exploited by recommendation software tools.
No limit: AI poker bot is first to beat professionals at multiplayer game

Triumph over five human opponents at Texas hold’em brings bots closer to solving complicated real-world problems. Triumph over five human opponents at Texas hold’em brings bots closer to solving complicated real-world problems.
Sentiment Analysis on Hate Speech using Twitter

Sentiment analysis is an application of natural language processing.It is also known as emotion extraction or opinion mining.There is a vast growth in use of social networking sites and microblogging websites, by which communication between people from different countries, cultures and psychological and physical backgrounds became more direct, resulting in more and more conflicts about thoughts and speech used between these people.Hate speech can be explained and it can be put into context as the use of aggressive, violent or offensive language, which targets a specific group of people who shares a common property.In India, a lot of hate speech generated posts are placed on social networking sites.So, to block and catch the hate speech generated posts and to avoid necessary conflicts, we thought of introducing a technique using Twitter, as our data source.We will create and analyze datasets that can be used for machine learning.We are going to analyze the negative and positive hate speech tweets which are generated, and use machine learning algorithms to analyze the tweets, to find the correct meaning behind it whether it is offensive or not.In our project we are going to use various techniques such as Stop Words, Lexicon Analysis, Datasets and Machine Learning to Analyze tweets and find out the sentiments behind it.We are also going to use Apache Spark based parallel processing technique to access only the latest tweets and not the old ones which are already being analyzed.
The Influence of Cooperative Intergerative Reading and Composition (CIRC) and Survey, Question, Read, Recite, Review (SQ3R) on Ability Reading Comprehension of Elementary School

The objective of this study is to examine the theory of Cooperative integrated learning&#x0D; and composition (CIRC) and Survey, Question, Read, Recite, Review (SQ3R). This study&#x0D; used eksperiment technique.The study design Nonequivalent Control Group’s pretestposttest&#x0D; Design with two experimental groups and a control group. The population&#x0D; of this study is the fourth grade of Muhammadiyah Gunungpring elemnatary school.&#x0D; Determination of subjects in this study using Simple Random Sampling technique&#x0D; with the subject of research is the fourth grader of Muhammadiyah Gunungpring&#x0D; Muntilan. Technique of collecting data using test. Validity test in this research using&#x0D; grain analysis technique. Measurement of the reliability of research instruments in the&#x0D; form of multiple choice to measure the comprehension of reading comprehension with&#x0D; the cronbach’s alpha formula. Based on the results of the research, the following results&#x0D; are obtained: (1) Is there is a significant difference of influence between Cooperative&#x0D; Integrated Reading and Composition (CIRC) method and control class; (2) Is There is a&#x0D; difference of influence between Survey Question Read Recite Review (SQ3R) learning&#x0D; and Context class in learning comprehension reading skill (3) There is influence of&#x0D; using CIRC and SQ3R method to reading comprehension skill
CHARACTER IMAGE SEGMENTATION OF JAVANESE SCRIPT USING CONNECTED COMPONENT METHOD

Automation of Javanese script translation is needed to make it easier for people to understand the meaning of ancient Javanese script. By using Javanese script image as input, the translation system generally consists of character segmentation, character recognition, and combining the recognized characters as a meaningful word. The segmentation which obtains region of interest of each character, is an important process in the translation system. In the previous research, segmentation using projection profile method can separate each character well. The method can overcome characters overlapping, but it still produces truncated characters. In this study, we proposed a new segmentation to reduce the truncated character. The first step of the proposed method is pre-processing that consists of converting input into binary image and cleaning noises. The next step is to determine the connected component labels, which further perform as candidate of characters. Some of the candidates are still represented by more than one labels, so that we need a process to merge the connected component labels that have centroid distance less than threshold. We evaluate the proposed method using Intersection over Union (IoU). The evaluation shows the best accuracy 93,26%.
PERANCANGAN SISTEM PELAYANAN RESTORAN BERBASIS WEB MOBILE MENGGUNAKAN FRAMEWORK YII2

The increased business needs and rapid technological developments helped to make easier in marketing, ordering, or delivery. Restaurant service that is still manual is only efficient for visitors who are few. With a-based restaurant application it mobile web will make it easier and more efficient for large restaurants with more visitors. With reliable Smartphone, visitors immediately place an order through the waterfall method and database MySQL, so that later it will produce an application that is accessed via a Smartphone customer in handling food menu orders.
Exploring Spatiotemporal Characteristics of Twitter data Using Topic Modelling Techniques

Abstract. This research purpose aims to explore the spatiotemporal aspects of social media data with Twitter data by using topic modelling techniques. The spatiotemporal limits are restricted in two areas of the Republic of Korea: Seoul and Jeju Island. This paper searches the semantics and geographical place characteristics of the Twitter data, and the semantics and place characteristics are regarded as topics in the topic modelling. This paper also discusses the temporal intensity over different spatial areas and visualizes the spatiotemporal patterns with GIS techniques.As Twitter mobility message contains a user’s interests and behavioural patterns in the geo-tagged data corresponding to its location, it is possible to explore geographical locality and the user’s mobility over space by using textual ontological techniques such as topic modelling. Therefore, this paper attempts keywords searching and textural classification to classify the shared spatial activity patterns of the Twitter users. Consequently, two main analysis themes are explored: the tourist activity patterns attracting the visitors in Jeju over time and temporal periodicity for shopping and meal preference in Seoul, respectively.In conclusion, this research represents a potential of the social network data that enables to fill the gap of spatiotemporal patterns of human beings over the online and mobile environment. Furthermore, our study confirms social data analysis techniques as an alternative geographical data source that can complement and replace the roles of spatial data, which could not be analysed in the conventional offline data.
Crypto-Watermarking of Images based on the Permutation on Z/pZ and the Wavelet Decompositions of Legall 5/3

In this work, we are interested in the insertion of the watermarking of digital images in the frequency domain.The algorithm proposed uses the transformed into wavelet Legall 5/3 on an image encrypted by swapping on the Z/pZ field, to perform the watermarking.By consequence, this introduces the concept of keys to the traditional methods of non-blind watermarking.The results of the application of this method on the fixed image (presented in the section: Application and results show well its performance.