Reviewerly/exHarmony huggingface dataset:
DP-Eclat:A Vertical Frequent Itemset Mining Algorithm Based on Differential Privacy

Frequent itemset mining has been a focused theme in the field of data mining, which is widely used in business decision making, economics, medicine, bioinformatics and other fields. Frequent itemset mining can provide a lot of valuable information when making decisions, but it may bring the risk of privacy disclosure when mining and publishing frequent itemsets. In order to solve the privacy leakage problem, most of the existing solutions are using horizontal mining method to mine frequent itemsets under differential privacy. However, these solutions generally suffer from complex support computation and poor accuracy due to large candidate sets. In this paper, we propose a new vertical frequent itemset mining algorithm based on differential privacy, which is referred to as DP-Eclat. In DP-Eclat, a new privacy budget allocation strategy is proposed to rationalize the privacy budget allocation, which allows privacy budget to be used more fully. In addition, we devise a multiple pruning strategy to further improve the data utility by prune before and after the generation of candidate itemsets. Through privacy analysis, we prove that DP-Eclat satisfies E -differential privacy. Extensive experiment results on multiple real datasets show that DP-Eclat significantly outperforms state-of-the-art algorithms in terms of data utility.
Towards an Overall QoE Model for 360-Degree Video

Although 360-degree video is becoming more and more popular on the Internet, understanding of Quality of Experience (QoE) of 360-degree video is still limited. In this paper, we aim to investigate for the first time the impacts of two QoE aspects, namely perceptual quality and presence, on the overall QoE of 360-degree video. By using a subjective dataset, statistical analysis shows that the overall QoE is significantly affected by the perceptual quality and presence. In addition, we make the first attempt to model the overall QoE of 360-degree video taking into account the impacts of the QoE aspects. In particular, two approaches are investigated to predict the overall QoE. The result shows that one of the approaches is applicable to predict the overall QoE of 360-degree video over different videos and rendering device sets.
Forecasting Error Pattern-Based Anomaly Detection in Multivariate Time Series

The advent of Industry 4.0, partly characterized by the development of cyber-physical systems (CPSs), naturally entails the need for reliable security schemes. In particular, accurate detection of anomalies is of paramount importance, as even a small number of anomalous instances can trigger a catastrophic failure, often leading to a cascading one, throughout the CPS due to its interconnectivity. In this work, we aim to contribute to the body of literature on the application of anomaly detection techniques in CPSs. We propose novel Functional Data Analysis (FDA) and Autoencoder-based approaches for anomaly detection in the Secure Water Treatment (SWaT) dataset, which realistically represents a scaled-down industrial water treatment plant. We demonstrate that our methods can capture the underlying forecasting error patterns of the SWaT dataset generated by Mixture Density Networks (MDNs). We evaluate our detection performances using the \(F_1\) score and show that our methods empirically outperform the baseline approaches—cumulative sum (CUSUM) and static thresholding. We also provide a comparative analysis of our methods to discuss their abilities as well as limitations.
How Would Do that? An Agile Elicitation Technique to Explore Users’ Spontaneous Gestural Commands

Hand gestures are an essential component of our behavior and are often considered a valuable way for Ambient Assisted Living solutions. Gestural commands are particularly helpful in hectic home environments, like the kitchen, where we often have greasy hands. Yet, gestures can be challenging to learn and recall especially for non-tech savvy users. The adoption of a user-centered approach to select the gestural commands typically allows to generate postures and moves that are easier to perform and remember. Following this approach, we report on an agile and cost-effective elicitation study based on a virtual prototype that was conducted to design a set of gestural commands to operate the lighting system embedded into an extraction hood. Spontaneous gestures by 30 participants were video recorded and categorized through computer-supported structured video analysis. Our findings indicate the feasibility of the proposed approach with able-bodied users and open to the involvement of physically and cognitively challenged individuals.
Research on the Influence of Computer Electronic Media on Higher Education in Mother Language

Abstract The rapid development of computer technology has brought about the rapid popularization and application of electronic media in the field of education, and has also caused an impact on traditional education. This paper discusses the influence of computer electronic media on Chinese education in higher education in China from many aspects by using statistical data and theoretical analysis. The purpose of this study is to guide the implementation of higher Chinese education in the use of electronic media.
Technology of spacecraft on-board equipment design support

Abstract The Technology is shown that combines knowledge bases, information and graphic resources into a set of automated software tools. Technology includes the methods of intellectual models’ building and the tools of scenario creation for measurement, data transmission, test results’ control and visualization. It is implemented in the software-mathematical model of the on-board equipment control system and the software of the testing equipment. Software is integrated into a technological platform for the design and testing of technical systems. Application of Technology reduces the time of the on-board equipment design and production, reduces import dependency of Russian space development and increases its competitiveness in the space systems’ market.
Study on the Application of LSTM in Meteorological Element Prediction based on Computer Software

Abstract The 21st century is the era of big data. With the rapid development of computer technology, we can store more meteorological data, which increases the meteorological data. As people put forward higher requirements for meteorological information, we need to collect and forecast abundant meteorological laws. With the rapid development of computer technology, deep learning has opened a new era of artificial intelligence. Deep learning technology has brought opportunities to the development of meteorological forecasting technology, which has played an important role in basic weather forecast, economic activities and disaster prevention in China. First of all, this paper analyzes the important role of meteorological elements prediction. Then, this paper analyzes the deep learning LSTM algorithm. Finally, this paper makes an empirical analysis.
Agriculture Multispectral Uav Image Registration Using Salient Features and Mutual Information

Multimodal image registration has been studied for a long time as a necessary pre-processing step to extract relevant information from the studied images. In this direction, agriculture remote sensing has evolved to use multispectral sensors and faces challenges since the application of classic solutions is not suitable. This paper preliminarily explores the benefits of applying Mutual Information (MI) based on SIFT points for image registration to agriculture remote sensing multi-spectral evaluated on a self-developed public database of images through a fixed-wing Unmanned Aerial Vehicle (UAV) equipped with a multispectral sensor operating within parameters that would apply to crops inspection in real life. Our preliminary results have shown a marginal improvement of MI after registration highlighting that we may apply it to improve the registration of agriculture remotely sensed images. This small variation of MI shows that there is room for improvement.
Incremental Mining Method of Spatial Co-Location Pattern based on Genetic Algorithm

In the traditional incremental mining under the spatial co-location mode, parallel computing is often used for obstacle clustering, which causes the running time of the mining method to be greatly affected by the conditional parameters. Therefore, an incremental mining method of spatial co-location pattern based on genetic algorithm is proposed. Obstacles are divided by Euclidean distance and thresholds are set, genetic algorithms are used to cluster the obstacles, the fitness function of the obstacles is established, and the frequent clustering increment method is used to increase the clustering set. Based on the IULEP clustering set incremental mining algorithm, the calculation is performed to complete the incremental mining. In order to verify the effectiveness of the designed method, a simulation experiment is designed, and the experimental results prove that the running time of the designed incremental mining method is less affected by the conditional parameters, and the mining time is shorter, which is feasible.
A Novel Approach to Multi-authority Attribute-Based Encryption Using Quadratic Residues with Tree Access Policy

Attribute-based encryption has been a trend in the security field due to its higher efficiency and its compatibility with cloud computing, mobile ad hoc systems and the recent computing advancements like fog computing, social networking, IoT, etc. The attribute-based encryption (ABE) can be defined as a type of public key encryption in which keys are directly linked to the attributes of the user. These attributes can be anything like the place of access, the email address of the user, or the position of the user, or the type of subscription the user has taken. This obviously limits the user access, but it reduces the excess overhead and also secures the system to higher efficiency. Sahai and Waters put on the light the vulnerabilities of a single authority ABE scheme and further gave a proposition of a multi-authority ABE scheme. After that, some very useful techniques were given to cope up with the limitations in the existing techniques. There are three major schemes for ABE, i.e., the bilinear pairings, the quadratic residues and the lattices. All these three have certain advantages and limitations in some or the other proposals. One such focus for the implementation of the ABE is the Quadratic Residues (QR). The proposed scheme extends this implementation to a multi-authority attribute-based encryption scheme. A tree-based access approach is utilized to diminish the reliance on the central authority. Thus, the proposed scheme considers three major models of cryptography, namely multi-authority, tree-based policy and the quadratic residues to reduce the limitations of the existing models.
Stranger Dungeons: 2d6 Variant Rules for Swords &amp;amp; Wizardry

During the 2020 Corona virus crisis in Lombardy a "stranger time," the Game Design Workshop at Bocconi University studied the implementation of the algorithms proposed by Maccheroni (2020, SSRN paper 3622663) for digital play using only six-sided dice.Swords & Wizardry by Finch (2011, Frog God Games) is a popular restatement of the Original Dungeons & Dragons Game by Gygax and Arneson (1974, Tactical Studies Rules).A case study, the present paper presents an implementation of the aforementioned algorithms for this game.
Allocating Limited Sensing Resources to Accurately Map Dynamic Environments

This work addresses the problem of learning a model of a dynamic environment using many independent Hidden Markov Models (HMMs) with a limited number of observations available per iteration. Many techniques exist to model dynamic environments, but do not consider how to deploy robots to build this model. Additionally, there are many techniques for exploring environments that do not consider how to prioritize regions when resources, in terms of robots to deploy and deployment durations, are limited. Here, we consider an environment model consisting of a series of HMMs that evolve over time independently and can be directly observed. At each iteration, we must determine which HMMs to observe in order to maximize the gain in model accuracy. We present a utility measure that balances a Pearson's χ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> goodness-of-fit of the dynamics model with Mutual Information (MI) to ensure that observations are allocated to maximize the convergence rate of all HMMs, resulting in a faster convergence to higher steady-state model confidence and accuracy than either χ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> or MI alone.
Argument Identification in Indonesian Tweets on the Issue of Moving the Indonesian Capital

Last October 2019, Indonesian Twitter community is busy discussing the issue of moving the capital city, and people are very eager to share their opinion in various expressions. This form of expression was alleged as a form of society expressing their opinions and arguments. This research uses a dataset from online discussions about moving Indonesian capital on Twitter. The goal of this study aims to identify whether a tweet contains argument or not. In this experiment, we use Multi-Class Support Vector Machine (SVM), and Multinomial Naïve Bayes (MNB) as the classifier and TF-IDF as feature extraction. Variation of Twitter data characters that have a lot of noise will be a challenge in this study so that some preprocessing processes will be carried out to overcome this problem. This research will investigate several combinations of preprocessing to discover the best result. We classify each tweet information such as argument, non-argument, and unknown. The best results with an accuracy of 71.42% were obtained by performing SVM with only a unigram feature. This study shows that the stopwords feature has effectiveness depends on which feature combination is implemented in the model.
Interpolation of Geochemical Data with Aster Images Based on AlexNet Convolution Neural Network

Being an important geological information source, geochemical data is widely used in mineral exploration, environmental protection, pollution monitoring, etc. However, geochemical data with extensive coverage and fine resolution has become inaccessible, especially in some unreachable and remote areas. Remote sensing data with fast and efficient ability to collect geology related geoinformation has long been employed in many of geological studies. Joint utilization of geochemical and remote sensing data, as well as other sources of geo-data can consequently assist in geological applications such as mineral exploration In recent decades, methodology to integrate remote sensing and geochemical data have significantly improved. During the integration, geochemical data are often interpolated or resampled to finer resolution for match that of remote sensing images but without notable improvement in geo-information quality containedwith. This study proposeda new integration method that uses the AlexNet convolution neural network to interpolate geochemical data with ASTER images. The interpolated geochemical data presents not only with a higher spatial resolution, but also with geological information from remote sensing images.
Operational limitation of Indonesian traditional wooden boat in the framework of second generation intact stability criteria

Abstract Recently, the International Maritime Organization (IMO) developed the second generation intact stability criteria for all possible capsizing scenario in seaways with performance based approach. This paper presents application of the criteria to investgate operational limitation of an Indonesian traditional woooden boat for dead ship condition. The hydrodynamic characteristics of the ship are determined by model experiment except the effective wave slope coefficient is calculated using the simplified Froude-Krylov assumption of roll exciting moment and the formula of weather criterion. The wave characteristics are described by JONSWAP spectrum based on the wave statistic of Flores sea and the gusty wind is calculated by Davenport spectrum. The results show that the Indonesian traditional wooden boat comply with the criteria when the downflooding angle is larger than 25.0 degrees. The vulnerability criteria level 1 and the vulnerability criteria level 2 of the criteria are not consistent when the effective wave slope coefficient is calculated using the formula of weather criterion but it is consistent when the simplified Froude-Krylov assumption is used. The inconsistency could appear due to the geometry characteristics of Indonesian traditional wooden boats which are different from the geometry characteristics of ships used to develop the weather criterion as the level 1 of vulnerability criteria.
Practical application of the fuzzy logic apparatus in solving the problem of orientation of solar batteries

The paper considers the possibility of using a new approach - fuzzy logic when solving the problem of solar batteries orientation. During the study, a fuzzy regulator was constructed, which forms the control impact on the engine based on external factors: the angle of deviation from the orientation on the Sun, harmful impact from the Sun, and position in orbit. For simplification, a model of the satellite’s orbital motion has been adopted in which the orientation of the panel around a single axis can be considered. The output parameter of the regulator is the control action applied to the engine. The regulator’s input and output factors are formalized by appropriate linguistic variables for which the themos and their accessory functions have been designed. According to the proposed logic, the fuzzy regulator provides tracking of the Sun with zero angle of deviation in case the degree of the harmful impact of the Sun does not exceed some threshold. If there is a danger of accelerated degradation of photovoltaic cells due to harmful impact, the solar panel is oriented in such a way that the panel track the Sun with some displacement angle, which is more than zero by the module. The value of this angle is calculated by a fuzzy system based on the intensity of harmful impacts. To check the possibility of applying the proposed approach, modeling was carried out for cases of absence and presence of harmful impact. The analysis of results has shown the possibility of application of the offered approach for solving the problems of the orientation of solar batteries.
A state of the art fuzzy based healthcare risk management for health information exchange

The Today health-care organizations and physicians use several processes and instruments to exchange data about the private health of patients electronically. The main aims of the different methods of information (HIE) exchange on health are to reduce healthcare costs, to minimize medical errors and to better coordinate health services. Risks of information assets have a complex nature and different approaches address risk management of information security in medial field. The objective of this paper is to create the state-of - the-art information security risk management. In order to accomplish this, a Fuzzy based Healthcare Risk Management is suggested. This research aimed at exploring the core importance of the Fuzzy based Healthcare Risk Management (FHRM) from the views of health care consumers in the health sector. The result shows that the views of patients on multiple mechanisms for exchanging data about patient privacy, trust in competence and integrity and readiness to share data are significantly different.
Optimized Data Hiding for the Image Steganography Using HVS Characteristics

Steganography algorithms used to secure sensitive data on the Internet. It hides the secret data in the cover image and provides imperceptibility to the attacker. The least significant bit (LSB) is the most preferred data hiding technique in the steganography. In this technique, the least significant bit of the cover image pixel replaced with data bits. In the literature, the data hiding achieved without considering the human visual system (HVS) characteristics that degrade the visual quality of the image. In this paper, the optimized data hiding has done while considering the HVS characteristics. The colour image contains three planes known as the red–green–blue plane. The green plane is the most sensitive, and blue is less sensitive to the human eyes. Thus, in the proposed technique, the green plane used as a reference plane for data hiding in the red and blue planes. In the optimized data hiding technique, the secret data bits match with the cover pixel bits. If the bits match, then the corresponding optimal index determines, else data hiding done in the LSB bits of the cover pixel. After that, the optimal indexes hide in the cover image using a 2-bit LSB technique. In the proposed technique, image smooth and edge region characteristics explored before data hiding. There is a high correlation between the consecutive pixels in the smooth region and the minimum correlation on the edges. Thus, we have matched the secret data bits with the cover pixel bits in the smooth region and hide the optimal indexes on the edges. The experimental results performed on the standard dataset images downloaded from the USC-SIPI image database. The experimental results show that the proposed technique provides better visual quality as compared to the existing techniques.
Revocation of Emirati citizenship due to committing cybercrimes

Information technology has become a tangible and influential reality in various areas of our scientific and practical lives. Its multiple uses carry out beneficial acts while harmful behaviours can also occur. Unfortunately, such harmful behaviours can be classified as crimes that lead to an ‘original’ penalty of a fine in excess of one thousand Dirhams, and /or temporary/life imprisonment. Committing some of those crimes, however, can also result in the revocation or withdrawal of the nationality from its perpetrator as an accessory penalty imposed by force of law. This research dealt with such inquiry in the context of United Arab Emirates. The study concluded that cybercrimes that may result in the withdrawal of nationality from a naturalized or affiliated citizen but not the citizen by law, are those cybercrimes stipulated in the law on combating cybercrimes related to honour and trust, and fall into eleven cybercrimes. The study also found that emerging cybercrimes that cannot be imagined to be committed without electronic means and that its commission may result in the revocation or withdrawal of nationality for everyone who holds it (citizen by operation of law, by naturalization, or by affiliation) fall into eight crimes.