Reviewerly/exHarmony huggingface dataset:
Differential Privacy using Fuzzy Convolution Neural Network (DP-FCNN) with Laplace Mechanism and Authenticated Access in Edge Computing

During recent years, mobile edge computing is getting much attention from both academia and industry. However, many found that this emerging architecture needs a proper data privacy protection mechanism at mobile edge nodes against unintended data use by authorized data analysts. Due to the reason, the development of a proper lightweight privacy-preserving data analysis mechanism is of great urgency. Thus, we propose DP-FCNN, a light-weight Differential Privacy (DP) framework using Fuzzy Convolution Neural Network (FCNN) with Laplace Mechanism which injects noise into the personal data before uploading data from users generating the data into the storage so that the data is still useful but data privacy can be properly protected against unauthorized data analysis attempt. We implemented the proposed framework, and tested its performance in terms of scalability, processing time, and accuracy. The result shows that the proposed framework is very practical.
Virtual Machine Placement for Edge and Cloud Computing

So far, the genetic algorithm has been presented for the energy-aware scheduling of virtual machines to minimize the total busy time of servers. However, this algorithm does not consider the criteria for service-level policies on real-time applications. The convergence speed of the genetic algorithm is quite low in solving many of the large hybrid optimization problems. In other similar studies, heuristic algorithms were used to solve the interval scheduling problem. Such algorithms are not able to find nearly optimal solutions to hard problems. Since the optimization of scheduling is part of the hard problems, it is wise to use meta-heuristic algorithms to find nearly optimal solutions. Accordingly, an energy-aware meta-heuristic scheduling algorithm is presented in this paper for real-time virtual machines. The main goal of this algorithm is to minimize the total busy time of the physical machines in an interval without violating the deadline for virtual machines. The results were collected from the genetic algorithm, the smart water drop algorithm, the optimization of the ant colony, and the first possible downward algorithm for comparison and evaluation. The optimization of the ant colony and the smart algorithm of water drops showed better results than did the other two algorithms.
Secure-Reliable Blockchain-Based Data Access Control and Data Integrity Framework in The Environment of Smart City

Abstract The most important concern of smart cities and electronic governments that provide their services through smart applications and modern technology is security, reliability and privacy management. Therefore, it has become an effective research area. The open access environment that the Smart City idea offers suffers from the issue of data access and integrity rights. Encryption, Sequence Detection, and other traditional techniques may be somewhat unable to maintain the required level of security. In this paper, we suggest a practical framework based on blockchain technology and how its positive advantages will be reflected to provide a secure, reliable, integrity and controlled data access system. The main idea presented by the research is to manage access rights and protect privacy according to blockchain strategies. The analytical results showed a high level of protection, decentralization and reliability of the proposal based on blockchain technology and its advantages.
Statistical Tests and Algorithms

Abstract In this chapter statistical tests are performed in R, including the χ2 tests; testing can be started if allele and genotype frequency data match the reader’s expectations. Writing and running algorithms are introduced as functions, specifically working through building an Expectation Maximization function. The function is then used to estimate and update the reader’s inferences of allele frequencies from observed and expected genotypes.
PLACED-BASED LEARNING: THE CONCEPT OF NATURAL LEARNING OVERCOMES THE BOREDOM OF FULL DAY SCHOOL

The full-day program is implemented in increasing educational equality and improving learning services. However, the length of time students learn in a full day school system creates boredom in students when learning. The boredom that students experience when following the teaching and learning process from morning to evening, 7-8 hours a day. The boredom that occurs is influenced by several factors such as length of study time, emotional exhaustion, physical fatigue, cognitive influence, and decreased motivation. The purpose of this study is to determine the forms of student boredom that occur. The research subjects were 4-grade elementary school students. Researchers used random sampling techniques drawn from data from public schools, private schools, and inclusive schools. This study took 50 students from three different schools. Methods for collecting students' boredom data in full-day school use observation, in-depth interviews, and teacher questionnaires. Interviews and questionnaires were used to collect data from sources, namely the principal, teachers, and students. This research uses a qualitative approach that is descriptive in a natural setting. The boredom of learning because the academic emotional impact can be reduced by increasing students' interest and motivation through back to nature. We try to offer learning schemes that can be used in overcoming student boredom in learning that is place-based learning. Students will feel the sensation of learning with the environment as a source of learning with the concept of back to nature.
An Edge Attribute-Wise Partitioning and Distributed Processing of R-GCN Using GPUs

R-GCN (Relational Graph Convolutional Network) is one of GNNs (Graph Neural Networks). The model tries predicting latent information by considering directions and types of edges in graph-structured data, such as knowledge bases. The model builds weight matrices to each edge attribute. Thus, the size of the neural network increases linearly with the number of edge types. Although GPUs can be used for accelerating the R-GCN processing, there is a possibility that the size of weight matrices exceeds GPU device memory. To address this issue, in this paper, an edge attribute-wise partitioning is proposed for R-GCN. The proposed partitioning divides the model and graph data so that R-GCN can be accelerated by using multiple GPUs. Also, the proposed approach can be applied to sequential execution on a single GPU. Both the cases can accelerate the R-GCN processing with large graph data, where the original model cannot be fit into a device memory of a single GPU without partitioning. Experimental results demonstrate that our partitioning method accelerates R-GCN by up to 3.28 times using four GPUs compared to CPU execution for a dataset with more than 1.6 million nodes and 5 million edges. Also, the proposed approach can accelerate the execution even with a single GPU by 1.55 times compared to the CPU execution for a dataset with 0.8 million nodes and 2 million edges.
Construction of Evolving Multi-Agent Systems Based on the Principles of Evolutionary Design

The problem of constructing evolving multi-agent systems based on the principles of evolutionary design and hybrid models are discussed. The principles of construction and organization of multi-agent systems are considered. The concept of an agent and a set of basic properties that an agent should possess are given. An analogy between the basic definitions of agent theory and evolution theory is noted. The use of basic evolutionary models and algorithms for the design of multi-agent systems is proposed. The analysis of existing methods and methodologies for the design of agents and multi-agent systems is carried out. The existing differences in approaches to the design of multi-agent systems are noted. The main types of models are described and their most important characteristics are given. The importance and prospects of using an agent-based approach to the design of multi-agent systems are noted. Various approaches to the evolutionary design of artificial systems are considered. The evolutionary model of the formation of agents and agencies is described. The use of modified evolutionary operators to implement the agent design process is proposed.
Improved Design of IIR filter using Salp Swarm Algorithm

This paper presents an improved design of Infinite Impulse Response (IIR) filter using the Salp Swarm Algorithm (SSA). SSA is a recently developed meta-heuristic algorithm inspired by Salp's the swarming behavior of in the ocean. Because of its high efficiency in solving complex problems, this algorithm has gained widespread acceptance in a variety of fields. To ensure the efficiency of the proposed method, three different types of IIR models are considered here. The simulation results are compared with few other competitor algorithms like Whale Optimization Algorithm and Dragonfly Algorithm which indicated that SSA outperforms Whale Optimization Algorithm and Dragonfly Algorithm.
The dependence of the performance of imaging tasks on the forensic imager interface type

Abstract Forensic research in the investigation of information security incidents, the production of forensic examinations and many other areas of activity related to computer forensics require the maximum possible preservation of the integrity of the investigated data. To do this, write blockers are used - programs or devices that do not allow writing anything to the drive under investigation. The need to use such means comes both from the requirements of procedural legislation (for example, the Criminal Procedure Code of the Russian Federation), and from various recommendations of a methodological and other nature, as well as from standards (for example, STO BR IBBS-1.3-2016). Some aspects of the functioning of write blockers will be discussed in this article. And on the example of the criminalistic lock the question of influence of the used interface for data transmission in tasks of creation of images of data carriers will be considered.
Designing and Developing an Agricultural Product Sales Application Catalog with a Hybrid Application Development Framework

Abstract The use of e-commerce systems continues to increase in Indonesia, but the field facts show that e-commerce in agriculture is still relatively low compared to other fields. The problems faced are limited e-commerce infrastructure, lack of the farmers' knowledge on the benefits of e-commerce, and application design, which is challenging to use. Those problems cause a lack of e-commerce use in this field. Besides, the characteristics of technology users in agriculture also have a considerable influence. In this paper, a mobile-based application is developed to facilitate farmers in promoting agricultural products sales. One of the problems faced in developing mobile applications is the diversity of mobile device platforms. A mobile application can ideally run on multiple platforms. This paper contributes to building an application by using a hybrid method for application development to be used on the Android and IOS platforms. The application built aims to display agricultural products of farmers. The filter feature also makes it easier to find agricultural products in this application. The application is built using the Flutter framework to use one source of the same code on several mobile operating systems at once. There are some slight differences between the output versions of the Android and iOS platforms. Although there are some subtle differences, the similarity rate reaches 90%.
SwissFinder: Identifying Swiss Websites from Unstructured Content

Finding companies' websites is important when building business databases. However, automatically finding a company's website based on its name or its official entry in a registry is challenging, as companies often have similar names, acronyms, or descriptions. In this context, we built a system to evaluate different features and classifiers to automatically identify a company's website from unstructured content.
An Empirical Study of Text Factors and Their Effects on Chinese Writer Identification

In this paper, we analyze the relationship between the performance of the text-independent feature and text factors of the handwriting on Chinese writer identification. Text factors contain two types of information: the number of characters in both query and reference and the number of the same characters in both query and reference. We conclude that the performance increases when the query and reference contain more characters, and the minimum number of needed characters is 50. The number of the same characters in both query and reference has little influence on the identification when the number of characters is more than 50. The conclusions are verified by repeated writer identification tests with different amount of characters on the handwriting document pages.
Information Leakage Through Passive Timing Attacks on RSA Decryption System

A side channel attack is a means of security attacks that tries to restore secret information by analyzing side-information such as electromagnetic wave, heat, electric energy and running time that are unintentionally emitted from a computer system. The side channel attack that focuses on the running time of a cryptosystem is specifically named a “timing attack”. Timing attacks are relatively easy to carry out, and particularly threatening for tiny systems that are used in smart cards and IoT devices because the system is so simple that the processing time would be clearly observed from the outside of the card/device. The threat of timing attacks is especially serious when an attacker actively controls the input to a target program. Countermeasures are studied to deter such active attacks, but the attacker still has the chance to learn something about the concealed information by passively watching the running time of the target program. The risk of passive timing attacks can be measured by the mutual information between the concealed information and the running time. However, the computation of the mutual information is hardly possible except for toy examples. This study focuses on three algorithms for RSA decryption, derives formulas of the mutual information under several assumptions and approximations, and calculates the mutual information numerically for practical security parameters.
MONADIC INTUITIONISTIC AND MODAL LOGICS ADMITTING PROVABILITY INTERPRETATIONS

Abstract The Gödel translation provides an embedding of the intuitionistic logic $\mathsf {IPC}$ into the modal logic $\mathsf {Grz}$ , which then embeds into the modal logic $\mathsf {GL}$ via the splitting translation. Combined with Solovay’s theorem that $\mathsf {GL}$ is the modal logic of the provability predicate of Peano Arithmetic $\mathsf {PA}$ , both $\mathsf {IPC}$ and $\mathsf {Grz}$ admit provability interpretations. When attempting to ‘lift’ these results to the monadic extensions $\mathsf {MIPC}$ , $\mathsf {MGrz}$ , and $\mathsf {MGL}$ of these logics, the same techniques no longer work. Following a conjecture made by Esakia, we add an appropriate version of Casari’s formula to these monadic extensions (denoted by a ‘+’), obtaining that the Gödel translation embeds $\mathsf {M^{+}IPC}$ into $\mathsf {M^{+}Grz}$ and the splitting translation embeds $\mathsf {M^{+}Grz}$ into $\mathsf {MGL}$ . As proven by Japaridze, Solovay’s result extends to the monadic system $\mathsf {MGL}$ , which leads us to a provability interpretation of both $\mathsf {M^{+}IPC}$ and $\mathsf {M^{+}Grz}$ .
Implementation of Open-Source Image Analysis Techniques in Commercial Quality Control Systems

Using image pattern matching techniques, this paper presents the development of an open-source based quality control program that can distinguish between sample pages in a book printing/production environment, intended to enable automatic rejection of incorrect pages from the binding process. Novel adaptations are made to an ORB (Oriented FAST and Rotated Brief) based image matching system that deals with quantifying the confidence of a match to ensure that even identical pages in the incorrect orientation are rejected during book binding operations. The program is subjected to a variety of quantitative tests to evaluate its performance and from these tests the effects of various parameters used in the program are discovered, allowing tuning to be performed. Potential paths for development of the analysis program are discussed, with the implementation of machine learning, highlighted as a possibility, to provide automated parameter tuning, and suggestions for further optimisation of the software are made, with a view to creating an even more bespoke version that retains performance whilst cutting computational overhead to a minimum.
ScalaParBiBit: scaling the binary biclustering in distributed-memory systems

Biclustering is a data mining technique that allows us to find groups of rows and columns that are highly correlated in a 2D dataset. Although there exist several software applications to perform biclustering, most of them suffer from a high computational complexity which prevents their use in large datasets. In this work we present ScalaParBiBit, a parallel tool to find biclusters on binary data, quite common in many research fields such as text mining, marketing or bioinformatics. ScalaParBiBit takes advantage of the special characteristics of these binary datasets, as well as of an efficient parallel implementation and algorithm, to accelerate the biclustering procedure in distributed-memory systems. The experimental evaluation proves that our tool is significantly faster and more scalable that the state-of-the-art tool ParBiBit in a cluster with 32 nodes and 768 cores. Our tool together with its reference manual are freely available at https://github.com/fraguela/ScalaParBiBit .
Innovating instruction of communication theory with machine learning and speech analysis

Foundational work of Claude Shannon in 1950's provided direction for theory of communication for many decades thereafter. Emphasis of research was on development of new coding and decoding techniques in order to make effective use of all available bandwidth. With the advent of Internet, and especially of Internet commerce, security aspects of communication theory became much more important. As research in these questions enters a mature stage, the challenge for teachers of communication theory is to find novel ideas, new applications and new interdisciplinary topics in order to engage students as well as to prepare them to tackle challenges they will encounter in their engineering careers later on. In our paper we propose to apply to teaching emerging connections of information theory with two other scientific disciplines: machine learning and analysis of speech.
Shared Diminished Reality: A New VR Framework for the Study of Embodied Intersubjectivity

Shaping both the environment and the embodiment of the users in that virtual world, VR offers designers and cognitive scientists the unprecedented potential to virtually explore a vast set of interactions between persons, and persons and their environment. By design, VR tools offer a formidable opportunity to revisit the links between body movement and lived experiences, and to experiment with them in a controlled, yet engaging and ecologically valid manner. In our multidisciplinary research-creation project we ask, how can we design (virtual) environments that specifically encourage interactions between multiple persons and that allow designers, scientists, and participants (users or “immersants”) to explore the very process of interaction itself? Building on our combined experience with dance improvisation research and interactive virtual spatial design, we document a multi-user VR experience design approach we name Shared Diminished Reality (SDR), where immersants are co-present and able to move together while their bodies and the environment are represented in a minimalist way. Our working hypothesis is that non-anthropomorphic embodiment of oneself and one’s partner(s), combined with open-ended exploration, focuses the user’s attention on the quality of the interaction and encourages playfulness and creativity. We present the articulations VR platform and its design history, as well as design evaluations of SDR in a laboratory setting and through a mixed reality performance, interrogating the impact of our minimalist approach on user experience and on the quality of the interaction. Our results suggest that minimizing (self and other) representation in Shared Diminished Reality positively impacts relational dynamics, induces playful creativity, and fosters the will to move and improvise together.
Trends and Recent Change in the Syntactic Distribution of Degree Modifiers: Implications for a Usage-based Theory of Word Classes

This paper examines the syntactic distribution of degree modifiers in both spoken and written English. The results of the empirical case studies show that degree modifiers, both amplifiers (e.g., very, extremely) and downtoners (e.g., quite, pretty), are generally more often used in predication than in attribution, a result that is in line with earlier observations of the distribution of individual modifiers. This synchronic trend is also evident in diachronic developments: corpus data show that the recent frequency increase of intensifying this and that has largely taken place in predication, and the adjectivization of a class of -ed participles (e.g., interested, scared) can also be connected to their frequent co-occurrence with degree modifiers after be. Finally, the connection between degree modifiers and predicative usage has recently become stronger for a subset of modifiers (e.g., so, this, that) due to the decline of the “Big Mess” construction (e.g., so good an idea). From a theoretical perspective, this paper promotes a dynamic, usage-based model of word classes where frequency of use plays a role in categorization. The data investigated in the article are mainly discussed from the perspective of usage-based Construction Grammar, and the theoretical implications of the findings are examined both in light of a more traditional Construction Grammar network model of language and some recent ideas of overlapping word classes.
Design of Fringe Projector Illumination System Based on Digital Mircomirror Device

High-speed fringe structured light projection system is one of the key technologies for real-time and efficient measurement of phase three-dimensional topography measurement system. Its function is to generate a modulated fringe pattern for three-dimensional measurement. Digital projectors based on DMD (Digital Mircomirror Device) have been widely used in three-dimensional projection fringe measurement systems due to their advantages such as high contrast, high brightness, high efficiency, and secondary development. This paper designs a high-efficiency and high-uniformity fringe projector illumination system based on DMD, with a light efficiency of 54%, a uniformity of 91.5%, and an illumination beam angle distribution of 10°–38°. The overall system size is 70 mm × 74 mm × 35 mm, which is applied to the phase three-dimensional topography measurement system, has important research significance and practical value.
Effective Tuple-based Anonymization for Massive Streaming Categorical Data

In this poster, we propose a novel, effective tuple-based anonymization technique for categorical data over the Internet. By utilizing a new structure, called Candidate Encoding Sequence with Frequency, and a set of new rules for generating such a sequence for each domain value of the categorical data, we can effectively solve the key limitation of the existing methods. Our experimental results demonstrate the superiority of our method against the existing method in terms of the strength of privacy protection.