Reviewerly/exHarmony huggingface dataset:
Towards interpreting deep learning models for industry 4.0 with gated mixture of experts

In this work, we propose to use the Gated Mixture of Experts to interpret a deep learning model trained on industrial data. Unlike monolithic deep learning models, gated modular neural networks enable to decompose parts of the models in a way that may potentially be interpreted by domain experts or users. We first propose to transform a model that gives state-of-the-art performances on a standard industrial benchmark according to this paradigm. The model aims at predicting the remaining useful life of an asset in the field of prognostics and health management for industry 4.0. Then, we experimentally validate that the performances of the transformed model are not degraded and that the resulting model segments and clusters the data streams according to an emerging concept that reflects previously published analyses by experts on this dataset, even though such a concept has never been introduced at training time. This work thus confirms the interpretable properties of the Gated Mixture of Experts in a new domain. We further study some potential weaknesses of this paradigm, in particular the excessive variability of the resulting decomposition across experiments, and we propose to modify the loss with a new knowledge-based constraint term that encodes a known prior distribution of latent concepts in the data. We show that this term enables greater control over the Gated Mixture of Experts that results in a decomposition of significantly better quality on our benchmark.
Features of International and Legal protection of cinematographic works

In his article, the author analyzes international legal law for the protection of copyright in general and cinematographic works.The author notes that as a result of a long diplomatic conference in year 1886, was adopted the first multilateral convention – the BerneConvention for the Protection of Literary and Artistic Works, which was revised several times: in Paris (1896), Berlin (1908), Rome(1928), Brussels (1948), Stockholm (1967) and Paris (1971). Ukraine ratified this convention on October 25, 1995. According to thisconvention for the first time was provided the possibility of protection of non-property rights of the author, although no specific meansof protection were enshrined.TheAuthor attention to the fact that the Convention is based on three main principles: the principle of “national regime”, the principleof “automatic protection”, the principle of “independence of the protection”. By this Convention, cinematographic works were forthe first time classified as copyrighted works. During the conference, it was France that proposed that the protection provided by theConvention be extended to cinematographic works. An important provision was the adoption of a general rule, according to which theterm of protection of any work applies to the entire duration of the entire life of the author and fifty years after his death.The author analyzes that in general by the end of the 80’s the basics of international law were created and agreed in terms of legalregulation of creation and use of cinematographic (audiovisual) works, which became the basis for appropriate changes in copyrightlaw of European law, including Ukrainian law. The author draws attention to the concept that copyright arises at the time of creationand does not require registration.The author notes that international protection in the field of copyright and related rights is currently developing dynamically. Therapid growth of digital technology, in particular global networks, necessitates constant attention in terms of protection, enforcement andenforcement of copyright.
A secure and decentralized SSI authentication protocol with privacy protection and fine-grained access control based on federated blockchain

Self-sovereign identity authentication protocol is an active research topic in the field of identity authentication and management. However, the current SSI authentication protocols pay little attention to privacy protection and the fine-grained access control. Therefore, a secure and decentralized SSI authentication protocol with privacy protection and fine-grained access control is proposed. Firstly, the formal model of SSI including the SDPP-SSI identity model and management model is presented. And then, based on the federated blockchain, the distributed identifier is used as a global identifier for users in the decentralized domain. Finally, the verifiable statement is encapsulated using a policy control signature supporting privacy protection to develop the user's access control for identity registration in the centralized domain. Compared with the related work (Lin 2018, Zhu 2018, Stokkink 2018, Hammudoglu 2017, Othman 2017, Abraham 2018, Guan 2019, Lin 2019) from controllability, security, flexibility, privacy protection, authentication and fine-grained access control, the proposed SSI authentication protocol not only meets controllability, authentication, and flexibility, but also supports privacy protection and fine-grained access control.
Key Interpretation Challenges for Wastewater-Based Epidemiology of Illicit Drugs: A Norwegian Three-City Case Study

Wastewater-based epidemiology (WBE) has emerged as a timely, non-invasive, and cost-effective indicator of illicit drug consumption. It is increasingly used by international organizations as a proxy measure for estimates of drug prevalence and related trends. Nevertheless, the literature exploring the limitations of WBE remains limited. This paper aims to shed further light on important shortcomings of WBE with recommendations on moving forward.Utilizing case study and statistical analysis, the paper critically reviews methodological challenges associated with WBE results related to (i) levels, (ii) trends, and (iii) between-city comparisons of drug use. Data from raw influent wastewater samples from wastewater plants in the cities of Oslo, Bergen and Stavanger/Sandnes were analysed for amphetamine, methamphetamine, MDMA, and cocaine (benzoylecgonine) over a 3-year period. Normalized population loads were calculated and variation in daily loads analysed with plots and estimation of means, confidence intervals, and coefficient of variation. Linear regression models examined trends and between-city differences.Plots and statistical analyses revealed extensive variation in daily loads, with min/max values of 6.1/453.9 mg/day per 1,000 inhabitants 15-64 years for amphetamine and correspondingly 9.4/675.9 mg for methamphetamine. Substantial differences in load levels and patterns across time and plants were also observed. A carefully designed sampling procedure and a relatively large number of daily samples are required to obtain estimates of sufficient precision for determining trends in space or time. Cross-referencing with alternative trend variables can improve the interpretation of WBE trend indicators. Finally, when using mean load levels for different wastewater-treatment plants to assess spatial variation in drug use, the representativeness of the catchment area should be evaluated before interpreting observed changes as city differences.Although WBE is a useful supplementary indicator of illicit drug consumption, important methodological issues and potential shortcomings should be taken into account when designing sampling procedures and interpreting the analytical results.
Secure access control using updateable attribute keys

In the era of cloud computing, the technique of access control is vital to protect the confidentiality and integrity of cloud data. From the perspective of servers, they should only allow authenticated clients to gain the access of data. Specifically, the server will share a communication channel with the client by generating a common session key. It is thus regarded as a symmetric key for encrypting data in the current channel. An access control mechanism using attribute-based encryptions is most flexible, since the decryption privilege can be granted to the ones who have sufficient attributes. In the paper, the authors propose a secure access control consisting of the attributed-based mutual authentication and the attribute-based encryption. The most appealing property of our system is that the attribute keys associated with each user is periodically updatable. Moreover, we will also show that our system fulfills the security of fuzzy selective-ID assuming the hardness of Decisional Modified Bilinear Diffie-Hellman (DMBDH) problem.
Optimal Bernoulli point estimation with applications

This paper develops optimal procedures for point estimation with Bernoulli filters. These filters are of interest to radar and sonar surveillance because they are designed for stochastic targets that can enter and exit the surveillance region at random instances. Because of this property they are not served by the minimum mean square estimator, which is the most widely used approach to optimal point estimation. Instead of the squared error loss, this paper proposes an application-oriented loss function that is compatible with Bernoulli filters, and it develops two significant practical estimators: the minimum probability of error estimate (which is based on the rule of ideal observer), and the minimum mean operational loss estimate (which models a simple defence scenario).
Virtual private network (VPN) model for AIS real time monitoring

Abstract The need for a ship monitoring system based on Automatic Identification System (AIS) has been developed and provides many broad benefits for the maritime world in Indonesia. The system can become an early warning system (EWS) for ship operators, port operators, and even ship owners for tracking a movement of their ships. By internet connection based Virtual Private Network (VPN) can connect several remote base stations (RBS), VPN technology can integrate many RBS from several remote places into one AIS monitoring system. VPN-based internet connection is used to guarantee a secure network, private internet connection, and can access a network remotely. VPN technology encrypts data exchange even before data transmission reaches the public network. Connecting to the internet using a VPN connection is like accessing the internet using a special tunnel, not in the main internet network. Thus the use of a VPN-based internet connection in the AIS monitoring system can ensure the security of data transmission from RBS to the AIS monitoring server.
Hydraulic Stability of BPPT – lock on Breakwater Head

Abstract Breakwater is one of the coastal buildings built by humans to protect coastal areas such as ports, settlements, and tourist attractions from wave attacks. This test aims to determine the condition damage of BPPT – lock in one- and two-layers placements in the head of the rubble mound breakwater. The method used to conduct this research was physical model test and carried out at laboratory of Balai Teknologi Infrastruktur Pelabuhan dan Dinamika Pantai (BTIPDP) Yogyakarta – Indonesia. The armour unit model used BPPT–locks were 66.048 grams or equivalent to 2.268 tons in prototype and tested in various wave heights, starting from 7.5 cm, 9.2 cm, and 11.4 cm with period 1.5 S or equal to 4 meters of wave height in the prototype. Based on the laboratory results of testing, installing a double armour layer was recommended because the percentage of damage of the double armour layer was lower, and the coefficient of damage was higher.
Solving Shape-From-Shading problem through shape and depth joint optimization

Shape-From-Shading (SFS) is one unique and long-standing problem aiming to reconstruct shape/depth from only one image. The SFS problem can be regarded as an inverse process of image rendering, i.e., solving the Bi-directional Reflection Distribution Function (BRDF) model with the given image. Among various BRDF models, physically based perspective Cook-Torrance BRDF model is generally used because of its universality. However, the solution of Cook-Torrance BRDF model based SFS problem has not been properly addressed because the model is very complicated and non-convex. In this paper, we present a shape and depth joint optimization method under the neural network framework to solve this kind of SFS problem. Our method has three aspects of contributions. Firstly, we remove the unrealistic surface smoothness constraint imposed on the solution of SFS. Secondly, the design of shape and depth joint optimization provides the method with a higher probability of bypassing local optimum and finding the global optimum. Thirdly, the neural network framework enables our method with the ability of performing point-wise optimization, that is, the optimization does not subject to the approximation on the discrete domain. Through experiments, we prove that our method can solve Cook-Torrance BRDF model based SFS problem with good accuracy. The maximum Mean Absolute Error, Mean Relative Error and Root-mean-square error of depth results are 0.8 mm, 1.0% and 1.23 mm respectively, which outperforms related methods.
The relationship between soil microbial diversity and angelica planting based on network big data

Angelica sinensis is a kind of traditional Chinese medicine with very good blood nourishing effect, and it is cultivated in many regions of China. But with the increasingly severe climate, angelica cultivation has become a big problem. Therefore, this paper starts from the soil microorganisms of angelica planting, and studies the influence of soil biodiversity and angelica planting in the context of big data. This paper proposes a Hadoop system for big data analysis, combining the biocommunity characteristics and metagenomes of soil microorganisms. It then calculates the distance between samples and generates a dissimilarity matrix. Finally, this paper proposes a soil optimization method for angelica planting based on big data analysis of soil microorganisms. In order to optimize the Angelica planting soil designed in this paper, a soil microbial genome comparison experiment and a big data concurrent control test experiment were designed in this paper. It then analyzes the data obtained from the experiment, and the results of the analysis are used to optimize the soil for angelica planting. It finally compares the soil method of Angelica planting designed in this paper with the traditional Angelica planting method. The experimental results show that the survival rate of Angelica sinensis planted by the soil optimization method based on big data analysis of soil microorganisms has increased by 16.09% compared with the traditional Angelica sinensis planting site. The growth rate of Angelica sinensis planted by the soil optimization method based on big data analysis of soil microorganisms increased by 9.64% compared with the traditional Angelica sinensis planting area.
Ex Libris

Free AccessEx LibrisE. HauschildtE. HauschildtSearch for more papers by this authorPublished Online:Sep 2022https://doi.org/10.13109/path.2022.111.9.412SectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail About Previous article FiguresReferencesRelatedDetails Download book coverVolume 111Issue 9September 2022 ISSN: 0720-6259eISSN: 2197-0831HistoryPublished online:September 2022 PDF download
Geodesic Gramian denoising applied to the images contaminated with noise sampled from diverse probability distributions

As quotidian use of sophisticated cameras surges, people in modern society are more interested in capturing fine-quality images. However, the quality of the images might be inferior to people's expectations due to the noise contamination in the images. Thus, filtering out the noise while preserving vital image features is an essential requirement. Existing denoising methods have assumptions, on the probability distribution in which the contaminated noise is sampled, for the method to attain its expected denoising performance. In this paper, the recent Gramian-based filtering scheme to remove noise sampled from five prominent probability distributions from selected images is utilized. This method preserves image smoothness by adopting patches partitioned from the image, rather than pixels, and retains vital image features by performing denoising on the manifold underlying the patch space rather than in the image domain. Its denoising performance is validated, using six benchmark computer vision test images applied to two state-of-the-art denoising methods, namely BM3D and K-SVD.
Disjunctive Rule Lists

In this study, we present an interpretable model, disjunctive rule list (DisRL) for regression. This research is motivated by the increasing need for model interpretability, especially in high-stakes decisions such as medicine, where decisions are made on or related to humans. DisRL is a generalized form of rule lists. A DisRL model consists of a list of disjunctive rules embedded in an if-else logic structure that stratifies the data space. Compared with traditional decision trees and other rule list models in the literature that stratify the feature space with single itemsets (an itemset is a conjunction of conditions), each disjunctive rule in DisRL uses a set of itemsets to collectively cover a subregion in the feature space. In addition, a DisRL model is constructed under a global objective that balances the predictive performance and model complexity. To train a DisRL model, we devise a hierarchical stochastic local search algorithm that exploits the properties of DisRL’s unique structure to improve search efficiency. The algorithm adopts the main structure of simulated annealing and customizes the proposing strategy for faster convergence. Meanwhile, the algorithm uses a prefix bound to locate a subset of the search area, effectively pruning the search space at each iteration. An ablation study shows the effectiveness of this strategy in pruning the search space. Experiments on public benchmark datasets demonstrate that DisRL outperforms baseline interpretable models, including decision trees and other rule-based regressors. History: Accepted by J. Paul Brooks, Area Editor for Applications in Biology, Medicine, &amp; Healthcare. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplementary Information [ https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.1242 ] or is available from the IJOC GitHub software repository ( https://github.com/INFORMSJoC ) at [ http://dx.doi.org/10.5281/zenodo.6954927 ].
A Performance Comparison of Post-Quantum Algorithms in Blockchain

Blockchain and other Distributed Ledger Technologies have triggered widespread research and interest.This is due to their ability to create redundant, transparent, and accountable connections in various application domains while utilising asymmetric cryptography, digital signature, and hash functions.However, the current blockchain system exhibits vulnerability to attacks, especially those staged and actualised using quantum computers leveraging Grover's and Shor's algorithms.There is a need to examine the various algorithms of digital signatures, post-quantum generations of public-key cryptography, and their performance to gain insights into the most suitable way to address the issue.In our review, we examine the performance of different post-quantum public-key generation and digital signature algorithms in blockchain and provide a performance comparison of computing time and memory usage.The research presented here includes application domains where post-quantum blockchain may be used.
Tris Pharma, Inc. v. Actavis Lab'ys FL, Inc.

Biotechnology Law ReportVol. 41, No. 5 Tris Pharma, Inc. v. Actavis Lab'ys FL, Inc.United States Court of Appeals of the Federal Circuit, 2022 No. 2021-1495, 2022 WL 2525318 (non-precedential)Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMANEdited for Biotechnology Law Report by CHRISTOPHER M. HOLMANChristopher M. Holman is a Professor of Law at the University of Missouri–Kansas City School of Law; a Senior Scholar at the Center for the Protection of Intellectual Property at the Antonin Scalia Law School, George Mason University; and the Executive Editor of Biotechnology Law Report.*The synopsis is original content and the decision itself has been condensed for ease of readability.Search for more papers by this authorPublished Online:11 Oct 2022https://doi.org/10.1089/blr.2022.29284.cipAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 41Issue 5Oct 2022 InformationCopyright 2022, Mary Ann Liebert, Inc., publishersTo cite this article:Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN.Tris Pharma, Inc. v. Actavis Lab'ys FL, Inc..Biotechnology Law Report.Oct 2022.262-266.http://doi.org/10.1089/blr.2022.29284.cipPublished in Volume: 41 Issue 5: October 11, 2022Online Ahead of Print:September 23, 2022PDF download
How Is Walden Georgic?

Whereas twentieth-century American ecocriticism tended to associate Thoreau’s Walden (1854) with the elastic category of ‘pastoral’, critics in this century have increasingly proposed georgic, pastoral’s counterpart, as an alternative category in which to situate Thoreau. This essay argues that it is a mistake to cast pastoral and georgic as opposite categories, and that Walden is more sensitively read by responding to the freedom with which Thoreau (often mockingly) inflects a broader continuum of genres, including the Virgilian triad of pastoral, georgic, and epic. The key quality Walden shares with Virgil’s Georgics is not the promotion of an ethos, but the difficult and rewarding burden of interpretation each work places on the reader and citizen.
(Non-)visitors in Quantitative Terms

The results of our study are divided into two parts: first, the analysis of the questionnaires in this chapter and, second, the analysis of the interviews (Chap. 4 ).
Cryptographic Key Management Using Elliptic Curve X448 for Multiuser Environment

Key management is very essential part in the cryptographic field where the key must be maintained very secure so that the problem of maintaining of the key is important.The proposed method elaborates the much enhanced and actual key management system along with improved speed and less storage of the key.The policy of managing the key is mandatory for producing a key and required to take care to the storage as well as processing of it in the cloud scenario where security of the data is up most important thing when number cloud users are more in the network to use several applications.Making use of several algorithms by considering Diffie Hellman by combing with the Elliptic Curve will provide most effective in managing of the keys with much lesser key size.In this paper key exchange and shared key generation with Curve 448 is considered the practical results shows that effective key generation and exchange of the shared key.It obtains a 224-bit security level which delivers increased security over Curve 25519, and which has a 255-bit prime number.The proposed elliptic curves which are quicker and simpler to implement than other prime-order curves which are applicable for most of the applications.Hamburg chose the Solinas trinomial prime base p=2 448 -2 224 -1 which provides faster Karatsuba multiplication.