Reviewerly/exHarmony huggingface dataset:
Concrete Analysis of Quantum Lattice Enumeration

Lattice reduction algorithms such as BKZ (Block-Korkine-Zolotarev) play a central role in estimating the security of lattice-based cryptography. The subroutine in BKZ which finds the shortest vector in a projected sublattice can be instantiated with enumeration algorithms. The enumeration procedure can be seen as a depth-first search on some “enumeration tree” whose nodes denote a partial assignment of the coefficients, corresponding to lattice points as a linear combination of the lattice basis with the coefficients. This work provides a concrete analysis for the cost of quantum lattice enumeration based on Montanaro’s quantum tree backtracking algorithm. More precisely, we give a concrete implementation in the quantum circuit model. We also show how to optimize the circuit depth by parallelizing the components. Based on the circuit designed, we discuss the concrete quantum resource estimates required for lattice enumeration.
Correlation Cube Attack Revisited

In this paper, we improve the cube attack by exploiting low-degree factors of the superpoly w.r.t. certain “special” index set of cube (ISoC). This can be viewed as a special case of the correlation cube attack proposed at Eurocrypt 2018, but under our framework more beneficial equations on the key variables can be obtained in the key-recovery phase. To mount our attack, one has two challenging problems: (1) effectively recover algebraic normal form of the superpoly and extract out its low-degree factors; and (2) efficiently search a large quantity of good ISoCs. We bring in new techniques to solve both of them. First, we propose the variable substitution technique for middle rounds of a cipher, in which polynomials on the key variables in the algebraic expressions of internal states are substituted by new variables. This will improve computational complexity of the superpoly recovery and promise more compact superpolys that can be easily decomposed with respect to the new variables. Second, we propose the vector numeric mapping technique, which seeks out a tradeoff between efficiency of the numeric mapping technique (Crypto 2019) and accuracy of the monomial prediction technique (Asiacrypt 2020) in degree evaluation of superpolys. Combining with this technique, a fast pruning method is given and modeled by MILP to filter good ISoCs of which the algebraic degree satisfies some fixed threshold. Thanks to automated MILP solvers, it becomes practical to comprehensively search for good cubes across the entire search space. To illustrate the power of our techniques, we apply all of them to Trivium stream cipher. As a result, we have recovered the superpolys of three cubes given by Kesarwani et al. in 2020, only to find they do not have zero-sum property up to 842 rounds as claimed in their paper. To our knowledge, the previous best practical key recovery attack was on 820-round Trivium with complexity $$2^{53.17}$$ . We put forward 820-, 825- and 830-round practical key-recovery attacks, in which there are $$\mathbf {2^{80}\times 87.8\%}$$ , $$\mathbf {2^{80}\times 83\%}$$ and $$\mathbf {2^{80}\times 65.7\%}$$ keys that could be practically recovered, respectively, if we consider $$\mathbf {2^{60}}$$ as the upper bound for practical computational complexity. Besides, even for computers with computational power not exceeding $$\mathbf {2^{52}}$$ (resp. $$\mathbf {2^{55}}$$ ), we can still recover $$\mathbf {58\%}$$ (resp. $$\mathbf {46.6\%}$$ ) of the keys in the key space for 820 rounds (resp. 830 rounds). Our attacks have led 10 rounds more than the previous best practical attack.
More Insight on Deep Learning-Aided Cryptanalysis

In CRYPTO 2019, Gohr showed that well-trained neural networks could perform cryptanalytic distinguishing tasks superior to differential distribution table (DDT)-based distinguishers. This suggests that the differential-neural distinguisher ( $$\mathcal {N}\mathcal {D}$$ ) may use additional information besides pure ciphertext differences. However, the explicit knowledge beyond differential distribution is still unclear. In this work, we provide explicit rules that can be used alongside DDTs to enhance the effectiveness of distinguishers compared to pure DDT-based distinguishers. These rules are based on strong correlations between bit values in right pairs of XOR-differential propagation through addition modulo $$2^n$$ . Interestingly, they can be closely linked to the earlier study of the multi-bit constraints and the recent study of the fixed-key differential probability. In contrast, combining these rules does not improve the $$\mathcal {N}\mathcal {D}$$ s’ performance. This suggests that these rules or their equivalent form have already been exploited by $$\mathcal {N}\mathcal {D}$$ s, highlighting the power of neural networks in cryptanalysis. In addition, we find that to enhance the differential-neural distinguisher’s accuracy and the number of rounds, regulating the differential propagation is imperative. Introducing differences into the keys is typically believed to help eliminate differences in encryption states, resulting in stronger differential propagations. However, differential-neural attacks differ from traditional ones as they don’t specify output differences or follow a single differential trail. This questions the usefulness of introducing differences in a key in differential-neural attacks and the resistance of Speck against such attacks in the related-key setting. This work shows that the power of differential-neural cryptanalysis in the related-key setting can exceed that in the single-key setting by successfully conducting a 14-round key recovery attack on Speck32/64 .
FORMATION OF PORTFOLIOS OF SOCIAL PROJECTS IN ORGANIZATION

The topicality of the topic is determined by the need for improvement and further development of scientific and methodological support for the management of social programs in the organization, carried out with the direct participation of its employees, under the conditions of the introduction of portfolio-oriented management in this field. The purpose of the study is to improve and further develop the scientific and methodological support for the management of social programs of the organization based on the interpretation of the measures of these programs as projects that make up the relevant portfolios (sub-portfolios). Research tasks: 1) analyze approaches to the formation and classification of social programs in the organization; 2) to adapt the concept of forming portfolios of public participation projects to the conditions of forming portfolios of projects of social programs of internal direction of the organization, which provide for the direct participation of the organization's employees in the specified formation. Research methodology. The method of scientific identification was used when forming the conceptual basis of the study; when analyzing approaches to the formation and classification of social programs in the organization - the method of comparative analysis; to adapt the concept of forming portfolios of public participation projects to the conditions of forming portfolios of projects of social programs of the organization's internal direction, which involve the participation of the organization's employees - the method of analogies.
Towards Compressed Permutation Oracles

Compressed oracles (Zhandry, Crypto 2019) are a powerful technique to reason about quantum random oracles, enabling a sort of lazy sampling in the presence of superposition queries. A long-standing open question is whether a similar technique can also be used to reason about random (efficiently invertible) permutations. In this work, we make a step towards answering this question. We first define the compressed permutation oracle and illustrate its use. While the soundness of this technique (i.e., the indistinguishability from a random permutation) remains a conjecture, we show a curious 2-for-1 theorem: If we use the compressed permutation oracle methodology to show that some construction (e.g., Luby-Rackoff) implements a random permutation (or strong qPRP), then we get the fact that this methodology is actually sound for free.
Design of Online Certificate Legalisation Information System at Indramayu State Polytechnic

An information system is a collection of interconnected elements that form a unity in integrating data, processing, storing and distributing information. Legalization is an attestation process by providing an original stamp and signature from the authorities on a photocopy of a diploma or grade transcript as proof that the photocopy matches the original diploma or grade transcript. The legalization process at the Indramayu State Polytechnic which is currently running is still done manually. This mechanism requires alumni who wish to legalize their diplomas or transcripts to come directly to campus. The legalization service system that is currently running at the Indramayu State Polytechnic is considered to be less effective because it takes a long time for alumni to process the application. Based on the problems above, the researcher aims to design a website-based information system for legalizing diplomas and transcripts. The legalization system is designed to focus on the needs of alumni and those from the academic department who are responsible for ratifying documents for legalizing diplomas and transcripts. The result of this research is a website platform for submitting online legalization requests which can help the academic section of the Indramayu State Polytechnic in managing legalization applications and make it easier for alumni to submit legalization applications.
A Model Proposal for Scaling the Productivity Increase in Agile Project Management Methodology

Project management in the software industry is the process of successfully planning, managing, and completing software development projects. Software projects can often be complex, constantly changing, and full of uncertainties, so project management is of particular importance in the software industry. There are two basic approaches to the execution of software projects. In the waterfall model, the project stages are operated in the determined order and after each stage is completed, the next stage is passed, while in the agile approach, the project is divided into small and priority parts, and the work processes are repeated at regular intervals and improvements are made depending on the feedback received. Recently, there has been a trend towards managing software projects with agile methodologies, as it provides flexibility and adaptability. However, there is no quantitative evaluation of the benefits of agile structuring both in the literature and in the sector, and this benefit is expressed with verbal expressions referring to the formation of a dynamic culture. For this reason, the productivity increase brought by the agile project approach cannot be measured and the benefit it provides cannot be scaled. In this study, a model that takes linguistic uncertainty into account is proposed to quantitatively scale the productivity increase provided by agile project structuring. The proposed model has been applied in a business where enterprise resource planning solutions have been developed and the effect of the transition from waterfall model to agile methodology on the productivity of the project has been investigated. Within the framework of the procedure proposed by the model, expert evaluations were taken in line with the determined quantitative and qualitative criteria, these criteria were listed with the fuzzy SWARA method, and the productivity increase provided by agile methodology was calculated using this information. The findings also allowed us to get an idea of the point of scaling the increase in productivity across the industry.
On the Promotion of Comprehensive Practical Training in Economics and Management in Universities based on VBSE System

With the rapid development of the market economy, enterprises and society have increasingly high requirements for the professional abilities and comprehensive qualities of various types of college graduates. Most universities have carried out education and teaching reforms based on this reason, in order to improve the employment competitiveness of graduates. Practical teaching is a key direction of higher education reform, and schools hope to provide graduates with a more systematic, comprehensive, and three-dimensional knowledge application system through practical teaching. The VBSE system is a simulation training platform that simulates the commercial and social environment. By building a simulated commercial and social environment on campus, students participating in the training course can engage in different jobs through role-playing, thereby understanding the functions and structures of each position, improving their professional abilities and comprehensive qualities in practice, and enhancing communication and teamwork skills among classmates in operation. This article will start from the current teaching situation in universities, analyze the necessity, advantages and disadvantages of introducing comprehensive management training in universities, and explore the specific trial plan of training courses.
Fluent in English with Social Media Platforms during the Covid-19 Pandemic

This study is conducted to provide a very enjoyable teaching reference in order to improve English learning outcomes, especially in the speaking skills of English Department students at Universitas Muhammadiyah Lampung. The purpose of this study is to provide a fun learning solution through the social media platform Instagram so that students can be motivated to continue to carry out distance learning during the COVID-19 pandemic so that there is an increase in learning outcomes to speak. This study puts forward a quantitative approach using the Quasi Experimental design method. The steps taken include: 1) giving a pre-test several times; 2) provide treatment; 3) give a pot-test several times. This research shows that Instagram can be an effective speaking learning media. This is evidenced by the acceptance of Ha in this study. Learning English during the pandemic is indeed a challenge for teachers and students. The boredom of studying at home is one of the causes of decreased learning achievement. The use of social media can be a solution to this problem. Instagram can be used as a fun learning medium (Fidian, 2017). Instagram provides learning motivation for students (Rohim, 2020). By using this social media, students' desire to learn increases. They can play while doing the teaching and learning process, especially learning English.
Advances in CUDA for computational physics

Advances in the graphics processing unit (GPU) development led to the opportunity for software developers to increase the execution speed for their programs by massive parallelization of the algorithms using GPU programming. NVIDIA company developed an arhitecture for parallel computing named Compute Unified Device Architecture (CUDA) which includes a set of CUDA instructions and the hardware for parallel computing. Computational Physics is an interdisciplinary field which is in continuous progress and which studies, develops and optimizes numerical algorithms and computational techniques for their application in solving various physics problems. Computational Physics has applicability in all sub-branches of physics and related fields such as: biophysics, astrophysics, plasma physics, biomechanics, fluid physics, etc. Moreover, with the evolution of technology in the last few decades, this relatively new field has helped to quickly obtain results in these fields, facilitating the connection between theoretical and experimental physics. In this paper, some of the latest researches and results obtained in computational physics by using GPU computing with CUDA architecture are reviewed.
A Novel Information Extraction Approach Employing Hierarchical Clustering Techniques with A Focus on Attribute Similarity Values

Data mining technique developed in vast manner. It mainly used over in information retrieval, information filtering, Data retrieval techniques. In scientific world data mining techniques used over in hospital management, Schools, colleges, public libraries, shopping complexes, space research foundation. Data Mining refers to extracting the information. Many Algorithms are used over in Data mining area. Agglomerative hierarchical technique uses top down approach. Certain arrangements are made over in this algorithm in hierarchical manner. Hierarchical algorithm mainly used for time consuming process.
A State of the Art Review on Natural Language Processing applied to the Malagasy Language

Based on the growing mass of information of all kinds to be processed and to facilitate human/machine dialogue, research teams and language industries are still developing applications integrating automatic natural language processing techniques. Natural Language Processing (NLP) is a discipline on the border of linguistics and computer science that concerns the application of computer programs and techniques to all aspects of human language. NLP is an area of research that is still open. It has extended its applications in various fields and applied them in several languages worldwide. This paper will review the NLP methods and resources that have been performed on the Malagasy language only. Recently, work on the automatic processing of the Malagasy language occurs even if the language is part of the group of under-endowed languages. This will allow researchers who are interested in the Malagasy language to update themselves in terms of the work already carried out, and the challenges that may be envisaged in future.
Errors in The Acquisition of Various Grammar Items by Vietnamese Students at Elementary Level

This article uses test papers from students at Ho Chi Minh University of Banking (HUB) in Vietnam as the interlanguage corpus. According to the "Chinese Proficiency Grading Standards for International Chinese Language Education" (New Standads), we find out the grammatical items in which learners make errors and count their error rates, compared with Vietnamese expressions, analyze the cause of the error. The results show that in the band 1 grammar items of the “New Standard”, the proportion of Vietnamese students' errors in the total number of grammar items is relatively low: HSK1 class students have a total of 9 errors, accounting for 18.7% of the total grammar items in the band 1. In HSK2-3 class, Except for demonstrative pronouns, the error rate of these items decreased significantly, with 3 items having zero error rates. At the same time, 2 new error items appeared with the acquisition of new grammar points in this stage. The students in HSK1 class have a high error rate mainly due to the structural auxiliary word "的", the preposition "和" and "跟", the preposition "在" and the adverbial indicating the time. The high error rate among students in HSK2-3 class is mainly reflected in the special sentence structures of "了1、了2. The types of errors are mostly out of sequence or missing components. Therefore, when training Chinese to Vietnamese students, it is necessary to strengthen their expression order of "subject- time- object- location- action", which can solve multiple word order errors. In addition, for the teaching of "tenses", it is necessary to increase the repetition rate of learning materials and repeatedly practice using context, which can greatly improve students' bias situation.
Analysis of Generic Structure and Grammatical Problem of Students in Writing English Paragraphs in Online Learning at Muhammadiyah University of Riau

The purpose of this research is to find out the generic structure and grammatical problems encountered by the non-English students at Muhammadiyah University of Riau. The data was obtained through students writing task namely writing English paragraphs of descriptive text. The writing task was given through Learning System Management (LSM) of the university named Sikuli. The participants of this research were the Non-English students taking the English subject in the first semester in academic year of 2021/2022 at Muhammadiyah University of Riau. The samples of this research were 4 classes consisting of a number of students for each class taken randomly spreading in eight faculties. They were from Computer Science faculty (40), Communication Science faculty (28), Natural Science and Health faculty (45), and Teacher Training and Education faculty (25). The total number of students are 138. The researchers applied the theory of Gerot and Wignel (1994) and Halliday et al. (2014) from the perspective of systemic functional linguistics. In generic structure, the appropriateness and inappropriateness in formulating identification and descriptions in descriptive text were described. While, in grammatical case, the writing students were analyzed based on the theory proposed by Yarber and Yarber (2010) and Dye (2005). After the data was analyzed, the results were obtained. It was showed that the non-English students at Muhammadiyah University of Riau in writing English paragraphs of descriptive text got serious problem on writing identification (115/83%) as one of the generic structure in descriptive text. In addition, they also encountered grammatical problems such as noun, pronoun, verb, adjective, adverb, preposition, conjunction, parallelism, modifiers, subject-verb agreement, punctuation, and capitalization. Based on the numbers and the percentage of the grammatical problems above, it showed that the non-English students at Muhammadiyah University of Riau got serious problem on subject-verb agreement (129 / 14,16%).&#x0D; Keywords: Generic structure, Grammatical problems, Writing English paragraphs, Online learning
q-Deformed and λ-parametrized A-generalized logistic function based Banach space valued ordinary and fractional neural network approximation

Here we research the univariate quantitative approximation, ordinary and fractional, of Banach space valued continuous functions on a compact interval or all the real line by quasi-interpolation Banach space valued neural network operators. These approximations are derived by establishing Jackson type inequalities involving the modulus of continuity of the engaged function or its Banach space valued high order derivative of fractional derivatives. Our operators are defined by using a density function generated by a q-deformed and λ-parametrized A-generalized logistic function, which is a sigmoid function. The approximations are pointwise and of the uniform norm. The related Banach space valued feed-forward neural networks are with one hidden layer.
Session Introduction: Artificial Intelligence in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface

Artificial Intelligence (AI) models are substantially enhancing the capability to analyze complex and multi-dimensional datasets. Generative AI and deep learning models have demonstrated significant advancements in extracting knowledge from unstructured text, imaging as well as structured and tabular data. This recent breakthrough in AI has inspired research in medicine, leading to the development of numerous tools for creating clinical decision support systems, monitoring tools, image interpretation, and triaging capabilities. Nevertheless, comprehensive research is imperative to evaluate the potential impact and implications of AI systems in healthcare. At the 2024 Pacific Symposium on Biocomputing (PSB) session entitled "Artificial Intelligence in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface", we spotlight research that develops and applies AI algorithms to solve real-world problems in healthcare.