Reviewerly/exHarmony huggingface dataset:
Providing more than 'just' reachability through semantic networking

The Internet has been constantly evolving beyond its original purpose to ensure the reachability between endpoints wherever they may be located. The many technologies developed in Standard Developing Organizations (SDOs) and through proprietary solutions bear witness to this continuous evolution, often driven through specifying and implementing new communication protocols or design practises. Parts of those solutions may overload, amend, or extend packet header semantics at the risk of endangering inter-operability of the solutions that make up the Internet system. This discussion paper advocates the Semantic Networking vision, explicitly exposing communication semantics as the essential abstraction for its runtime realization. We present an architecture for Semantic Networking and discuss key design considerations that may inform future research and development work, eventually leading to a new Internet architecture.
How to Backdoor (Classic) McEliece and How to Guard Against Backdoors

We show how to backdoor the McEliece cryptosystem such that a backdoored public key is indistinguishable from a usual public key, but allows to efficiently retrieve the underlying secret key. For good cryptographic reasons, McEliece uses a small random seed $$\boldsymbol{\delta }$$ that generates via some pseudo random generator (PRG) the randomness that determines the secret key. Our backdoor mechanism works by encoding an encryption of $$\boldsymbol{\delta }$$ into the public key. Retrieving $$\boldsymbol{\delta }$$ then allows to efficiently recover the (backdoored) secret key. Interestingly, McEliece can be used itself to encrypt $$\boldsymbol{\delta }$$ , thereby protecting our backdoor mechanism with strong post-quantum security guarantees. Our construction also works for the current Classic McEliece NIST standard proposal for non-compressed secret keys, and therefore opens the door for widespread maliciously backdoored implementations. Fortunately, our backdoor mechanism can be detected by the owner of the (backdoored) secret key if $$\boldsymbol{\delta }$$ is stored after key generation as specified by the Classic McEliece proposal. Thus, our results provide strong advice for implementers to store $$\boldsymbol{\delta }$$ inside the secret key and use $$\boldsymbol{\delta }$$ to guard against backdoor mechanisms.
Estimating the Hidden Overheads in the BDGL Lattice Sieving Algorithm

The lattice sieving algorithm based on list-decoding of Becker-Ducas-Gama-Laarhoven (SODA 2016) is currently at the center of cryptanalysis cost estimates of candidate lattice schemes for post-quantum standardization. Yet, only an idealized version of this algorithm has been carefully modelled, i.e. given an efficient list-decoding oracle for a perfectly random spherical code. In this work, we propose an experimental analysis of the actual algorithm. The difficulty lies in estimating the probabilistic defect with respect to perfectly random spherical codes for the task at hand. While it should be in principle infeasible to run the algorithm in cryptographically relevant dimensions, a few tricks allow to nevertheless measure experimentally the relevant quantity. Concretely, we conclude on an overhead factor of about $$2^{6}$$ on the number of gates in the RAM model compared to the idealized model for dimensions around 380 after an appropriate re-parametrization. Part of this overhead can be traded for extra memory, at a costly rate. We also clarify that these overheads apply to an internal routine, and discuss how they can be partially mitigated in the whole attack.
Post-quantum Plaintext-Awareness

In this paper, we formalize the plaintext-awareness notion in the superposition access model in which a quantum adversary may implement the encryption oracle in a quantum device and make superposition queries to the decryption oracle. Due to various possible ways an adversary can access the decryption oracles, we present six security definitions to capture the plaintext-awareness notion with respect to each way of access. We study the relationships between these definitions and present various implications and non-implications. Classically, the strongest plaintext-awareness notion (PA2) accompanied by the indistinguishability under chosen-plaintext attack (IND-CPA) notion yields the indistinguishability under chosen-ciphertext attack (IND-CCA) notion. We show that the PA2 notion is not sufficient to show the above relation when targeting the IND-qCCA notion (Boneh-Zhandry definition, Crypto 2013). However, our proposed post-quantum PA2 notion with superposition decryption queries fulfils this implication.
Attack on SHealS and HealS: The Second Wave of GPST

We cryptanalyse the isogeny-based public key encryption schemes SHealS and HealS, and the key exchange scheme HealSIDH of Fouotsa and Petit from Asiacrypt 2021.
On Quantum Ciphertext Indistinguishability, Recoverability, and OAEP

The qINDqCPA security notion for public-key encryption schemes by Gagliardoni et al. (PQCrypto’21) models security against adversaries which are able to obtain ciphertexts in superposition. Defining this security notion requires a special type of quantum operator. Known constructions differ in which keys are necessary to construct this operator, depending on properties of the encryption scheme. We argue—for the typical setting of securing communication between Alice and Bob—that in order to apply the notion, the quantum operator should be realizable for challengers knowing only the public key. This is already known to be the case for a wide range of public-key encryption schemes, in particular, those exhibiting the so-called recoverability property which allows to recover the message from a ciphertext using the randomness instead of the secret key. The open question is whether there are real-world public-key encryption schemes for which the notion is not applicable, considering the aforementioned observation on the keys known by the challenger. We answer this question in the affirmative by showing that applying the qINDqCPA security notion to the OAEP construction requires the challenger to know the secret key. We conclude that the qINDqCPA security notion might need to be refined to eventually yield a universally applicable PKE notion of quantum security with a quantum indistinguishability phase.
BettyLanteigne, ChristineCoombe, &amp; James DeanBrown. 2021. <i>Challenges in Language Testing around the World: Insights for language test users</i>. Singapore: Springer, 2021, 129.99 € (hardcover), ISBN 978‐981‐33‐4232‐3 (eBook). xxiii + 553 pp. https://doi.org/10.1007/978‐981‐33‐4232‐3

Journal of Educational MeasurementVolume 59, Issue 4 p. 536-544 Book Review Betty Lanteigne, Christine Coombe, & James Dean Brown. 2021. Challenges in Language Testing around the World: Insights for language test users. Singapore: Springer, 2021, 129.99 € (hardcover), ISBN 978-981-33-4232-3 (eBook). xxiii + 553 pp. https://doi.org/10.1007/978-981-33-4232-3 Bahram Kazemian, Bahram Kazemian orcid.org/0000-0001-8957-821X Islamic Azad UniversitySearch for more papers by this authorShafigeh Mohammadian, Shafigeh Mohammadian Independent ResearcherSearch for more papers by this author Bahram Kazemian, Bahram Kazemian orcid.org/0000-0001-8957-821X Islamic Azad UniversitySearch for more papers by this authorShafigeh Mohammadian, Shafigeh Mohammadian Independent ResearcherSearch for more papers by this author First published: 25 September 2022 https://doi.org/10.1111/jedm.12343Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL References Arksey, H., & O'Malley, L. (2005). Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology, 8(1), 19– 32. Fulcher, G. (2012). Assessment literacy for the language classroom. Language Assessment Quarterly, 9(2), 113– 132. https://doi.org/10.1080/15434303.2011.642041 Kane, M. (2010). Validity and fairness. Language Testing, 27(2), 177– 182. Volume59, Issue4Winter 2022Pages 536-544 ReferencesRelatedInformation
How to Move? Control, Navigation and Path Planning for Mobile Robots

Controllers and control techniques used in robotics, including the PID controller.
Performance Comparison of Neural Network-Based Models in the Classification of Polycystic Ovary Syndrome Disease

In this study, it was aimed to compare the performances of the above mentioned ANN, MLP and deep learning methods to determine polycystic ovary syndrome (PCOS) risk factors and predict PCOS diagnosis. In this study, the data set “Polycystic ovary syndrome” was used to determine PCOS risk factors and to compare the performances of ANN, MLP and deep learning methods for PCOS diagnosis prediction. The performance of the models was evaluated with accuracy, sensitivity, specificity, positive/negative predictive values. Factors associated with PCOS were estimated from the deep learning model that has the best performance. Accuracy, sensitivity, specificity, positive predictive value and negative predictive value obtained from the MLP method were 87.25%, 79.66%, 90.93%, 81.03%, and 90.19%. Accuracy, sensitivity, specificity, positive predictive value and negative predictive value obtained from the Neural Network method were 87.80%, 79.10%, 92.03%, 82.84%, and 90.05%. Accuracy, sensitivity, specificity, positive predictive value and negative predictive value obtained from the Deep Learning method were 89.09%, 81.92%, 92.58%, 84.30%, and 91.33%. According to the findings obtained from this study, the best classification result according to the performance metrics obtained from the artificial neural networks, MLP and deep learning methods used for the PCOS data set used in the study belongs to the deep learning method. As a result, PCOS was successfully classified in the light of the findings obtained from the study, and clinical findings were tried to be revealed by giving the risk factors associated with PCOS.
Hybrid model with optimization tactics for software defect prediction

Defects are frequent in software systems, and they can cause a lot of issues for users. Despite the fact that many studies have been conducted on employing software product metrics to determine defect-prone modules, defect prediction techniques are still worth investigating. Hence, the aim of this work is to provide a unique Software Defect Prediction (SDP) approach that includes four steps like “(a) pre-processing, (b) feature extraction, (c) feature selection and (d) detection.” At first, the input data are given to the pre-processing step, as well as in the feature extraction step; the “statistical features, raw features, higher-order statistical features as well as proposed entropy features” are extracted from the pre-processed data. In addition, the retrieved features are sent into a feature selection step, wherein the appropriate features are selected utilizing a modified chi-square scheme. In the detection step, a hybrid Long Short-Term Memory (LSTM) and Deep Belief Network (DBN) classifiers are used to predict the defects. To provide a more accurate detection, the weights of both DBN and LSTM are optimally tuned via a Self Improved Social Ski-Driver Optimization (SISSDO) algorithm. This proposed SDP model is a beneficial practice for enhancing software quality and reliability. Moreover, the results of the adopted technique are assessed to traditional techniques on the basis of various measures. In particular, the accuracy of the suggested approach for dataset 3 is 5.80%, 6.52%, 5.07%, 7.97%, 5.80%, 9.42%, 9.42%, 10.15%, 2.17%, and 3.62% better than the extant HC[Formula: see text]+[Formula: see text]ALO, HC[Formula: see text]+[Formula: see text]SMO, HC[Formula: see text]+[Formula: see text]CMBO, HC[Formula: see text]+[Formula: see text]SSD, RNN, CNN, NN, Bi-LSTM, HC+SPFCNN, and HC[Formula: see text]+[Formula: see text]CWAR approaches, correspondingly. Moreover, the computation time of the suggested approach is 17.05%, 5.78%, 1.31%, and 50.53% better than the existing HC[Formula: see text]+[Formula: see text]ALO, HC[Formula: see text]+[Formula: see text]SMO, HC[Formula: see text]+[Formula: see text]CMBO, and HC[Formula: see text]+[Formula: see text]SSD approaches, correspondingly.
Study on Optimizing Feature Selection in Hate Speech Using Evolutionary Algorithms

Hate speech is an important problem while dealing with user-generated content on online social media platforms. The huge amount of data generated makes it nearly impossible to manually moderate hate speech content and take appropriate measures. In this paper, we utilize various optimization algorithms to enhance the feature extraction and vectorization, of various techniques like TF-IDF, Word2Vec, and Bag of Words and appertain on the machine learning models for two-fold classification. We gauge and visualize the conclusion of the propounded methodology of the hate speech problem about Twitter tweets. We examine our suggested technique on three datasets; out of which, two of the datasets were highly unbalanced, and SMOTE was used for class balance. Our experiments indicate the random behavior of particle swarm optimization and genetic algorithm and the decrease in accuracy when applied individually to the experiments. The results also indicate that the accuracy can be achieved back by applying particle swarm optimization and genetic algorithm parallels, countering their random behavior.
Review of Toolkit to Build Automatic Speech Recognition Models

Speech is one of the most significant types of communication between human beings. It is beginning to be a preferred means for communication between machines and humans. The mechanism of transforming human speech into its equivalent textual format is known as speech recognition. Various toolkits are being used to automate the process of speech-to-text conversion, and this process is referred to as automatic speech recognition (ASR). The usage of the ASR system is becoming prevalent with the implementation of human–machine interaction. Numerous speech-based assistive systems are available today used in several different areas. This paper provides insight into the ASR domain and toolkit used in ASR system—HTK, CMU Sphinx, Kaldi, and Julius with their comparative analysis in terms of installation, ease of use, and accuracy assessment.
Color Image Retrieval with a Weighted Adjacent Structure Model

In recent days, content-based image retrieval (CBIR) is a burning research area in image processing. The retrieval accuracy of CBIR further can be improved by a method that combines soft hypergraph and weighted adjacent structure (WAS) in the retrieving process. This method includes calculation of similarities between images and constructs a similarity matrix by combining color difference histogram and micro-structure descriptor methods. Retrieval precision can further be enhanced using a modern WAS and a soft hypergraph. The proposed method is projected as good by comparing with different methods and datasets. With the help of experimental results, this paper presents a clear understanding of performance and effectiveness of the proposed method.
Custom Handloom Mobile Application

Custom handloom mobile application is an application between the customers and the makers. In this application, only handmade products are available for the customers to buy. The main feature of this application is customers and can customize the products according to their needs. The customer can buy the product which is already available in the application. Or in case a customer has an idea of a design for the product, the customer can contact or chat with the maker or a designer to make a specific product as they wish. After completing the product, they can buy it by paying through online mode or cash on delivery.
Automated Real-Time Face Detection and Generated Mail System for Border Security

This paper focuses on face recognition and automatic mail generated system for observations by using a solitary camera. The application is created for detection and capturing the face, which can be applicable in surveillance system at border gateway. The camera is fixed for human face identification. A framework that perceives human information is handled in a second and an email alert is produced for security reasons. The key regions for examination of face detection have taken as consideration in scenario. After applying in real-time state Viola–Jones algorithm is used for face detection from different angles. The better pixels based image is used for sending emails. The performance has been checked and analyzed after repeating iterations of experiments through simulation.
Enhancement of Low-Resolution Images Using Deep Convolutional GAN

Neural networks have expanded the scope of machine learning to unlock new opportunities across industrial dimensions. Convolutional GAN is a recent technique which has achieved promising results in the areas of image enhancement and classification. In this paper, deep convolutional GAN (DCGAN) is implemented, and the network is trained on the fashion-MNIST dataset. The implementation of DCGAN is done using leaky ReLU activation functions and sequential modeling. The proposed implementation has resulted in successful data retrieval from grayscale images for relevant apparel categories. The collective PSNR and SSIM results achieved in this work are better when compared with the other contemporary image enhancement techniques available in literature.
Philosophical Results I: A Protocol-Theoretic Logic of Epistemic Deontics, Procedural Knowledge, and Norm Application

This chapter presents a penultimate layer of elaborations of PLEN. First, a protocol-theoretic logic of epistemic deontics is built into the Revised PLEN framework of Chaps. 4 , 5 , 6 , and 7 . The deontic logic is defended from several different directions. First, a number of immediate philosophical arguments, drawing on ideas from the inception of deontic logic, show the greater plausibility of protocol-theoretic deontics as compared to the intensional operators of standard deontic logic or even the merely dynamic operators of dynamic deontic logic. Second, the chapter observes, drawing on Chap. 6 , that protocols are hyperintensional objects; indeed, protocol graph isomorphism equivalence is a form of hyperintensional equivalence. This draws a broad and formally important consonance between the protocol-theoretic analysis of epistemic norms and arguments for the hyperintensionality of normative concepts in general. Third, the chapter shows that the protocol-theoretic logic solves a wide array of paradoxes of deontic logic. The second system added by this chapter is a logic of procedural knowledge and norm application. Procedural knowledge is knowledge of the procedural requirements of a system of norms or rules, and this notion is built into the logic of norm application, per the analysis of the regulative role of norms in prior chapters. The latter additions are given a much less extensive defense, as their primary notions are derived from prior considerations raised about the regulative role of epistemic norms. Both systems are only minimally explored from a technical perspective, as they serve primarily to extend the expressive power of PLEN in order to capture some of the principles of epistemic proceduralism.
The Revised PLEN Framework III: An Adaptable Protocol Logic

The prior chapters developed a theory of protocol equivalence that bound the syntax of protocols to well-known and novel process equivalence relations (bisimulation, isomorphism, protocol graph isomorphism) over dynamic process models (Kripke frames, graphs, LTSs, EDGs). The result was a novel and fine-grained protocol equivalence relation defined in terms of protocol graph isomorphism. The resulting theory of protocol equivalence was built into a revised derivation system for PLEN. This chapter shows that, conditional on the correctness of protocols as representations of procedural epistemic norms, the revised derivation system provides a formally regimented system for reasoning about epistemic norms and a framework for comparing different formal approaches for representing and reasoning about epistemic norms. On the basis of this system, it is shown that different philosophical orientations to modeling epistemic dynamics and epistemic norms can be formalized and qualitatively compared. This is a result of the relative independence of the protocol logic, the propositional and modal logics, and the properties of the contents of epistemic states in PLEN. As a result, PLEN is a sort of modular, formal laboratory in which sublogics encoding different theories of procedural epistemic norms can be built and studied.
Epistemic Proceduralism Defended II

Epistemic proceduralism is spelled out by clusters of principles characterizing the structure, function, and logic of procedural epistemic norms, norms that define restrictions on epistemic actions, processes, and procedures. With the content of epistemic norms regimented by means of norm-kernels and restrictions on epistemic dynamics, this chapter completes the defense of epistemic proceduralism. It articulates and defends the cluster, D3, along with its subclauses and corollaries, D3C1, D3C2, and D3C3. Roughly, this cluster of principles identifies the core forms of reasoning with and about epistemic rationality norms required by their first-order use in deliberate, ante hoc regulation (i.e., epistemic planning and control) and by their second-order use as objects of epistemological and logical analysis. Reasoning about norm equivalence, dependence, and independence relations as well as interactions between these logical properties and their normative verdicts prove to be of central importance, as does reasoning about their connections to deontic operators and the logical decomposition of ante hoc regulation. In the context of the book, the clusters of principles articulating these results stand as theoretical criteria or tests applicable to formal frameworks for representing and reasoning about epistemic norms. The chapter closes with two exercises helpful for framing the rest of the book. The first is a pair of brief arguments for the claim that the clusters of principles, D1–D3C3, are criteria on formal frameworks for the logic of epistemic norms. The second is an application of D1-D3C3 to other formal frameworks, which serves to highlight the main ideas of PLEN by contrast.
Evaluating a typology of signals for automatic detection of complementarity

In a cluster of news texts on the same event, two sentences from different documents might express different multi-document phenomena (redundancy, complementarity, and contradiction). Cross-Document Structure Theory (CST) provides labels to explicitly represent these phenomena. The automatic identification of the multi-document phenomena and their correspondent CST relations is definitely handy for Automatic Multi-Document Summarization since it helps computers understand text meaning. In this paper, we evaluated a typology of (textual) signals for the automatic detection of the CST relations of complementarity (i.e., Historical background, Follow-up and Elaboration) in a multi-document corpus of news texts in Brazilian Portuguese. Using algorithms from different machine-learning paradigms, we obtained classifiers that achieved high general accuracy (higher than 90%), indicating the potential of the signals.