Reviewerly/exHarmony huggingface dataset:
Analysis of humanoid robotics for nuclear disaster management incorporated with biomechanics

The humanoid is investigated for the mechanical and physical aspect in the nuclear disaster, especially for a severe accident, which includes the core melting. There are some mechanical studies of the leg and hand of the humanoid in which the human mimicking features are described. The management of the task is accomplished by the three regional preparations. The robot is made of the radiation-resistance substance. Therefore, it could work on the normal task of a human for the removal of the broken debris in a collapsed building. However, there is a limitation for the use in the reactor core building due to very high temperature of the nuclear fuel. The regional classification of the site is studied for the practical purposes. The post-accident analysis is accompanied with multidisciplinary research for the humanoid development in the nuclear industry.
A Survey of State-of-the-Art GAN-based Approaches to Image Synthesis

In the past few years, Generative Adversarial Networks (GANs) have received immense attention by researchers in a variety of application domains.This new field of deep learning has been growing rapidly and has provided a way to learn deep representations without extensive use of annotated training data.Their achievements may be used in a variety of applications, including speech synthesis, image and video generation, semantic image editing, and style transfer.Image synthesis is an important component of expert systems and it attracted much attention since the introduction of GANs.However, GANs are known to be difficult to train especially when they try to generate high resolution images.This paper gives a thorough overview of the state-of-the-art GANs-based approaches in four applicable areas of image generation including Text-to-Image-Synthesis, Image-to-Image-Translation, Face Aging, and 3D Image Synthesis.Experimental results show state-of-the-art performance using GANs compared to traditional approaches in the fields of image processing and machine vision.
Adaptive Component Embedding for Unsupervised Domain Adaptation

Domain adaptation has obtained considerable interest from the literatures of multimedia, especially in cross-domain knowledge transfer problems. In this paper, we propose an effective yet time-saving approach, named Adaptive Component Embedding (ACE), for unsupervised domain adaptation. Specifically, ACE learns adaptive components across domains to embed all data in a shared subspace where the distribution divergence is mitigated and the underlying geometric structures in the local manifold are preserved. Then, an adaptive classifier is learned by using Representer Theorem in the Reproducing Kernel Hilbert Space (RKHS). The objective of our method can be efficiently solved in a closed form. Comprehensive experiments on both standard and large-scale datasets verify that ACE significantly outperforms previous state-of-the-art methods in terms of the classification accuracy and training time.
Querying NoSQL with Deep Learning to Answer Natural Language Questions

Almost all of today’s knowledge is stored in databases and thus can only be accessed with the help of domain specific query languages, strongly limiting the number of people which can access the data. In this work, we demonstrate an end-to-end trainable question answering (QA) system that allows a user to query an external NoSQL database by using natural language. A major challenge of such a system is the non-differentiability of database operations which we overcome by applying policy-based reinforcement learning. We evaluate our approach on Facebook’s bAbI Movie Dialog dataset and achieve a competitive score of 84.2% compared to several benchmark models. We conclude that our approach excels with regard to real-world scenarios where knowledge resides in external databases and intermediate labels are too costly to gather for non-end-to-end trainable QA systems.
Using relative von Neumann and Shannon entropies for feature fusion

This paper develops a new quantum inspired feature fusion method based on relative von Neumann entropy. The motivation is to more effectively reduce data redundancy and further improve the completeness and conciseness of the existing feature data. Regarding this, we quantise the source dataset into the collection of basic quantum states and constructed a weighted linking network to calculate the relative von Neumann entropies between feature samples. Thus, the detection and fusion of the duplicate feature samples in a subset is turned to the computation of the average relative von Neumann entropy and the measurement probabilities of the quantised feature samples. In parallel, the classical feature fusion method based on relative Shannon entropy is also proposed following similar idea. The experimental results show that the proposed feature fusion methods perform better in their completeness, conciseness, and stability.
Studying, designing and 3d-printing an operational model of the Antikythera Mechanism

3D printing technology is an established industrial practice for rapid prototyping and manufacturing across a range of products, components and commercial sectors and at the same time possesses great potential for every-day life applications to be invented, explored and developed by the coming generations of scientists and engineers. A 3D printer installed in a school setting and complemented by well-designed educational activities can: stimulate the interest and curiosity of students; engage and motivate them into studying science, technology, engineering and mathematics (STEM) subjects, that they may choose or consider as career options; give the opportunity to teachers to achieve content and concept learning in an innovative way. In this paper we present an interdisciplinary science course that was developed for high school students and was implemented in an actual science classroom. The objectives of the course were both to spark the interest and creativity of students and teach them certain curriculum units the content knowledge of which is reached or utilized in an unconventional way. Students are gradually introduced into the 3D printing technology, its application and potential and are assigned a challenging collaborative project in which they have to study, analyse, design and build, using the 3D printer of their school, an operational model of a renown ancient artefact, the so-called Antikythera Mechanism. The mechanism is a 2100-year-old computer and is internationally known as an artefact of unprecedented human ingenuity and scientific, historic and symbolic value. The course involves the teaching of STEM curriculum domains of physics, astronomy, mathematics/geometry, informatics and technology related content and also non-STEM subjects like history and Greek language, both ancient and modern. We give an overview of the course, discuss its various phases and highlight its outcomes.
Supervised Consistent and Specific Hashing

Most existing methods seek for the common semantics using different projections for different modalities, which isolates the intrinsic relationships among different modalities. Besides, to avoid the large quantization error, some of them adopt the discrete cyclic coordinate descent schemes which are usually time-consuming. To address these issues, we present a novel hashing method, namely Supervised Consistent and Specific Hashing (SCSH), for cross-modal retrieval. We explicitly decompose the mapping matrices into consistent part and modality-specific ones. Specifically, consistency excavates the semantic shared by different modalities, whereas specificity captures private properties for each modality. Different from prior works, SCSH can discover the intrinsic semantic shared among different modalities more accurately. Moreover, by regressing the semantic labels to hash codes, SCSH can further promote the discriminative power of hash codes and significantly accelerate the hashing learning process. Extensive experiments on three widely used datasets demonstrate that the proposed SCSH outperforms other state-of-the-art methods.
Sistem Informasi Inventarisasi Sumberdaya Perikanan Kabupaten Maluku Tenggara Dengan Metode Rapid Application Development Berbasis Web

- Southeast Moluccas Regency is a districts in Moluccas Province that is rich in marine fisheries resources, especially pelagic fish, seaweed, and demersal fish. Knowledge of information fisheries resources by fishermen and the community in general in the regions is still low, because the unavailability of easy information media to access information about fisheries resources in this area. The research aims to design an information system of fisheries resources inventory to improve the performance of the Southeast Moluccas Regency Government to inform and process data on fisheries resources. System design method uses RAD (Rapid Application Development). System design tools use UML (Unified Modeling Language), to make applications using the PHP(Hypertext Preprocessor) programming language, and MySQL as the database. Information System for Fisheries Resources has been tested using the blackbox method, the results show the system runs as expected. This system can display information on Southeast Moluccas Regency Fisheries Resources informally to the public and can be used as a tool for local governments to improve performance for presentation and processing of data and information in the marine and fisheries sector. Keywords: Information Systems,Inventory, Fisheries, RAD, UML
Multi-Agent Path Finding on Ozobots

Multi-agent path finding (MAPF) is the problem to find collision-free paths for a set of agents (mobile robots) moving on a graph. There exists several abstract models describing the problem with various types of constraints. The demo presents software to evaluate the abstract models when the plans are executed on Ozobots, small mobile robots developed for teaching programming. The software allows users to design the grid-like maps, to specify initial and goal locations of robots, to generate plans using various abstract models implemented in the Picat programming language, to simulate and to visualise execution of these plans, and to translate the plans to command sequences for Ozobots.
User-Centred Design in Content Management System Development: The Case of EMasters

Including users in design and development of an interactive product is crucial to achieve high level of usability. Content management systems have two categories of users, content creators and content consumers, and designers of these systems have to considers the needs of both user groups. In design of interactive learning systems, special attention has to be given to the process of learning, which means that functional, accessible and usable interface has to serve the purpose of knowledge acquisition. Designing for mobile learning brings additional challenges due to the small screens of mobile devices. The paper describes the process of utilization of user-centred design in development of a simple content management system for learning called EMasters. The aim of the EMasters is to enable teachers to easily create and organize courses which will be delivered to students to facilitate web-based and mobile learning. According to the user-centred design approach, teachers and students are involved in iterative process of design, implementation and evaluation of EMasters. Evaluation study used complementary methods and provided quantitative and qualitative feedback. The usability score reached good level and the guidelines for redesign of the system interface are drown. According to the obtained results, proposed framework is confirmed to be applicable in user-centred design of content management systems in general. In addition, the directions for adjustment of the framework for specific cases are provided.
Light Field Image Encryption Based on Pixel Substitution and Double Random Phase Encoding

In this paper, a light field image (LFI) encryption scheme based on pixel substitution and double random phase encoding (DRPE) is presented. The LFI includes the direction and intensity information of the light in the propagation process. Firstly, we employ an angular domain plane to represent the multi-view image of the LFI. Furthermore, pixel substitution processing based on rows and columns for a single view LFI. Finally, by the Fourier transform based on DRPE to obtain a encrypted image. Experimental results show that proposed scheme can be reliable and has a better immunity to noise and higher execution efficiency.
Verifiable dynamic searchable encryption

Using regular encryption schemes to protect the privacy of the outsourced data implies that the client should sacrifice functionality for security. Searchable symmetric encryption (SSE) schemes encrypt the data in a way that the client can later search and selectively retrieve the required data. Many SSE schemes have been proposed, starting with static constructions, and then dynamic and adaptively secure constructions but usually in the honest-but-curious model. We propose a verifiable dynamic SSE scheme that is adaptively secure against malicious adversaries. Our scheme supports file modification, which is essential for efficiently working with large files, in addition to the ability to add/delete files. While our main construction is proven secure in the random oracle model (ROM), we also present a solution secure in the standard model with full security proof. Our experiments show that our scheme in the ROM performs a search within a few milliseconds, verifies the result in another few milliseconds, and has a proof overhead of 0:01% only. Our standard model solution, while being asymptotically slower, is still practical, requiring only a small client memory (e.g., $\simeq$488 KB) even for a large file collection (e.g., $\simeq$10 GB), and necessitates small tokens (e.g., $\simeq$156 KB for search and $\simeq$362 KB for file operations).
Applying Geo-Encryption and Attribute Based Encryption to Implement Secure Access Control in the Cloud

Cloud computing is utility-based computing provides many benefits to its clients but security is one aspect which is delaying its adoptions.Security challenges include data security, network security and infrastructure security.Data security can be achieved using Cryptography.If we include location information in the encryption and decryption process then we can bind access to data with the location so that data can be accessed only from the specified locations.In this paper, we propose a method based on the symmetric cryptography, location-based cryptography and ciphertext policy -Attribute-based encryption (CP-ABE) to implements secure access control to the outsourced data.The Symmetric key is used to encrypt that data whereas CP-ABE is used to encrypt the secret key and the location lock value before uploading on the server.User will download encrypted data and the symmetric secret key XORed with the Location Lock value, using his attributes based secret key he can obtain first XORed value of Symmetric secret key and location lock value.Using anti-spoof GPS Location lock value can be obtained which can be used to retrieve the symmetric secret key.We have adopted Massage Authentication Code (MAC) to ensure Integrity and Availability of the data.This protocol can be used in the Bank, government organization, military services or any other industry those are having their offices/work location at a fixed place, so data access can be bounded to that location.
Public Private Partnership as a Tool for the Development of Educational Infrastructure

Purpose: The national project Education defines the vector of the development of the Russian education system for 2019-2024. In order to achieve its goals, tasks and indicators, it is necessary to attract investments and competencies of the private sector on the basis of public-private partnership. Design/Methodology/Approach: In the course of the study, there were used methods of system analysis, methods of scientific analysis, induction and deduction, comparison and grouping as tools of scientific research. Findings: The article proves that the Russian regions need additional investments to create a modern educational infrastructure and its maintenance. This is connected with the predominant financing of current costs from the consolidated budgets of the subjects of the Russian Federation on pre-school, general and vocational education, the demographic situation and the differentiated level of socio-economic development of the regions. Practical Implications: Authors proposed an activity contributing to the development of public-private partnerships in the subjects of the Russian Federation, providing the formation of a modern educational infrastructure. Originality/Value: The study presents the original approach in development of public-private partnership in the context of modern legal incentives in Russia.
Guarantees for Sound Abstractions for Generalized Planning

Generalized planning is about finding plans that solve collections of planning instances, often infinite collections, rather than single instances. Recently it has been shown how to reduce the planning problem for generalized planning to the planning problem for a qualitative numerical problem; the latter being a reformulation that simultaneously captures all the instances in the collection. An important thread of research thus consists in finding such reformulations, or abstractions, automatically. A recent proposal learns the abstractions inductively from a finite and small sample of transitions from instances in the collection. However, as in all inductive processes, the learned abstraction is not guaranteed to be correct for the whole collection. In this work we address this limitation by performing an analysis of the abstraction with respect to the collection, and show how to obtain formal guarantees for generalization. These guarantees, in the form of first-order formulas, may be used to 1) define subcollections of instances on which the abstraction is guaranteed to be sound, 2) obtain necessary conditions for generalization under certain assumptions, and 3) do automated synthesis of complex invariants for planning problems. Our framework is general, it can be extended or combined with other approaches, and it has applications that go beyond generalized planning.
Reciprocal Influences Between Proof Theory and Logic Programming

The topics of structural proof theory and logic programming have influenced each other for more than three decades. Proof theory has contributed the notion of sequent calculus, linear logic, and higher-order quantification. Logic programming has introduced new normal forms of proofs and forced the examination of logic-based approaches to the treatment of bindings. As a result, proof theory has responded by developing an approach to proof search based on focused proof systems in which introduction rules are organized into two alternating phases of rule application. Since the logic programming community can generate many examples and many design goals (e.g., modularity of specifications and higher-order programming), the close connections with proof theory have helped to keep proof theory relevant to the general topic of computational logic.
Enumerating Potential Maximal Cliques via SAT and ASP

The Bouchitté-Todinca algorithm (BT), operating dynamic programming over the so-called potential maximal cliques (PMCs), yields a practically efficient approach to treewidth and generalized hypertreewidth. The enumeration of PMCs is a scalability bottleneck for BT in practice. We propose the use of declarative solvers for PMC enumeration as a substitute for the specialized PMC enumeration algorithms employed in current BT implementations. The presented Boolean satisfiability (SAT) and answer set programming (ASP) based PMC enumeration approaches open up new possibilities for improving the efficiency of BT in practice.
Improving Reading Comprehension of the Second Grade Students by Using Graphic Organizer

Abstract The preliminary research of this research showed that the students had problems with reading comprehension known from their score. The students got 55 as their reading comprehension score where as the score of the student’s report card was 68. Therefore, this present study employed Classroom Action Research (CAR) which involves four stages of research. They were (1) Planning, (2) Implementing, (3) Observing, and (4) Reflecting. The instruments used to collect data in this research are field note, observation checklist, and reading comprehension test. This research was done in one cycle which consists of three meeting and it set score 63 in average as the criterion of success based on the researcher and the English teacher discussion. This criterion of success considered the students’ reading comprehension ability and the classroom circumstance. The result of this study above draws us into the conclusion that the graphic organizer Method improves the student’s reading comprehension. This proved by the increasing of their score and behavior during the implementation of the method. Thus, graphic organizer method is an effective method in improving student’s reading comprehension. Keywords: Reading comprehension, graphic organizer method, classroom action research AbstrakStudi pendahuluan dari penelitian ini menunjukkan bahwa siswa memiliki masalah dengan kemampuan membaca yang diketahui dari skor mereka. Para siswa mendapat 55 sebagai skor pemahaman bacaan mereka sedangkan skor kartu laporan siswa adalah 68. Oleh karena itu, penelitian ini menggunakan Penelitian Tindakan Kelas (PTK) yang melibatkan empat tahap penelitian. Mereka adalah (1) Perencanaan, (2) Implementing, (3) Observing, dan (4) Reflecting. Instrumen yang digunakan untuk mengumpulkan data dalam penelitian ini adalah catatan lapangan, daftar observasi, dan tes membaca pemahaman. Penelitian ini dilakukan dalam satu siklus yang terdiri dari tiga pertemuan dan menetapkan skor rata-rata 63 sebagai kriteria keberhasilan berdasarkan pada peneliti dan diskusi guru bahasa Inggris. Kriteria keberhasilan ini mempertimbangkan kemampuan pemahaman membaca siswa dan keadaan kelas. Hasil penelitian ini di atas menarik kita ke kesimpulan bahwa Metode grafik organizer meningkatkan pemahaman membaca siswa. Ini dibuktikan dengan meningkatnya skor dan perilaku mereka selama implementasi metode. Dengan demikian, metode grafik organizer adalah metode yang efektif dalam meningkatkan pemahaman membaca siswa. Kata kunci: Pemahaman membaca, metode grafik organizer, penelitian tindakan kelas
Penerapan Metode Pewarnaan Graf Untuk Penjadwalan Mata Kuliah

Scheduling courses is a routine agenda every semester carried out by the study program, in the manufacturing process it often experiences difficulties such as frequent clashes between courses, lecturers and other times in one period of the lecture schedule. The graph coloring method used is a simple row coloring algorithm on the side. This algorithm can be used in scheduling so that there is no overlap between courses, lecturers, room and time. The system design tool used is a flowchart. The results of this study are in the form of applications that are made automatically without any conflicting schedules. Users can enter the initial scheduling data according to their needs, then the application will follow scheduling using a simple line coloring algorithm on the side, and the output results will display the scheduling results. testing using black box, this test will test in detail the plus button and process button, the expected result is a success