On new results on Extremal Graph Theory, Theory of Algebraic Graphs and their applications in Cryptography and Coding Theory.

New explicit constructions of infinite families of finite small world graphs of large girth with well defined projective limits which is an infinite tree are described. The applications of these objects to constructions of LDPC codes and cryptographic algorithms are shortly observed. We define families of homogeneous algebraic graphs of large girth over commutative ring K. For each commutative integrity ring K with |K|>2 we introduce a family of bipartite homogeneous algebraic graphs of large girth over K formed by graphs with sets of points and lines isomorphic K^n, n>1 and cycle indicator ≥ 2n+2 such that their projective limit is well defined and isomorphic to an infinite forest

If Animals Are Like Our Children Let Us Treat Them Alike: Creating Tests of an Animal\u27s Intelligence for Determinations of Legal Personhood

The notion that animals could be granted rights under the law was once ridiculed, but now courts and legislatures have begun to move towards granting animals greater protections from cruelty and emotional trauma. Animal law as a course of study was not available in law schools until the early 1970\u27s. It has since grown into a field of debate and study that has drawn in experts from around the world. The rules of law that treat animals as property have been fought by animal rights advocates as being archaic similarly to the laws that once allowed for slavery. Animal owners are now being treated as guardians of animals rather than property owners who may benefit from their animals, but who must also ensure their health. Due to a lack of legal personhood under the law, when animals are injured or their wellbeing is threatened, advocates and owners are often barred from bringing claims on the behalf of animals because of the lack of legal standing to argue for the animals they are attempting to aid. Children have been seen by philosophers and the law as property that are under the control of their parents. Examining the relationship between children and their caregivers has been likened to examining the relationship between other sentient animals and their owners. The earliest anti-child abuse laws stemmed from efforts to end animal cruelty and sought to protect children not only from abusive guardians, but also from exploitation through labor and medical experimentation. Inspired by anti-child cruelty laws, reforms were made to address medical research abuses, availability of education, eugenics, and a variety of other social problems. Interestingly, such reforms were often backed by arguments comparing the legal status of animals and children. The current state of the law is a hodgepodge of common law, statues, and agency regulations which makes it difficult to determine what, if any, choices a child can make and what protections from harm they have

The Role of Artificial Intelligence and Information Technology in Promoting Knowledge Management in Business Firms: A Review

Knowledge Management appears to be more advanced and sophisticated in the twenty-first century, as a result of the advancement of information technology and artificial intelligence technologies. Several academic and commercial scholars have been studying, exploring, and discussing knowledge management for a long time, owing to the importance of this topic for the success of companies in both the public and private sectors. In addition, many prominent firms throughout the world have used a variety of knowledge management methods to ensure that they remain one step ahead of their competitors in today's highly competitive business environment, including businesses that are constantly looking for methods to improve their knowledge management strategies. There have been some studies undertaken to gain a more in-depth grasp of the most recent research trend in knowledge management procedures and best practices in businesses. This subject, on the other hand, demands deeper examination from a variety of angles. The impact of using Artificial Intelligence (AI) and Information Technology (IT) concepts and techniques on the efficiency of knowledge management in modern businesses, particularly has been overlooked by many prior studies. The current study reviews the role of artificial intelligence and information technology in promoting knowledge management in business firms

Про застосування алгебраїчної комбінаторики до проблем кодування та криптографії

У статті подано короткий огляд вітчизняних досліджень із застосувань алгебраїчної комбінаторики до захисту інформації. Розроблена теорія дала змогу побудувати нові нелінійні алгоритми захисту інформації, які можуть бути використані в задачах електронного бізнесу, управління та комерції. Параметри одного з потокових алгоритмів представлено у таблицях. Описано його специфічні властивості. Головною метою статті є огляд застосувань з прикладної алгебраїчної комбінаторики до постквантової криптографії – напрямку, який виник у зв’язку з надіями на появу квантового комп’ютера.В статье представлен краткий обзор отечественных исследований по применению алгебраической комбинаторики к защите информации. Разработанная теория позволила построить новые нелинейные алгоритмы защиты информации, которые могут быть использованы в задачах электронного бизнеса, управления и коммерции. Параметры одного из потоковых алгоритмов представлены в таблицах. Описаны его специфические свойства.This article provides a brief overview domestic research on applications of algebraic combinatorics to information security. The theory made it possible to build new nonlinear algorithms for protection of information which can be used in problems of e-business, management and commerce. Parameters of a streaming algorithms presented in the tables. The specific properties are described

On the family of cubical multivariate cryptosystems based on the algebraic graph over finite commutative rings of characteristic 2

The family of algebraic graphs A(n;K) defined over the finite commutative ring K were used for the design of different multivariate cryptographical algorithms (private and public keys, key exchange protocols). The encryption map corresponds to a special walk on this graph. We expand the class of encryption maps via the use of an automorphism group of A(n;K). In the case of characteristic 2 the encryption transformation is a Boolean map. We change finite field for the commutative ring of characteristic 2 and consider some modifications of algorithm which allow to hide a ground commutative ring

Fuzzy logic controller parameter optimization using metaheuristic Cuckoo search algorithm for a magnetic levitation system

The main benefits of fuzzy logic control (FLC) allow a qualitative knowledge of the desired system’s behavior to be included as IF-THEN linguistic rules for the control of dynamical systems where either an analytic model is not available or is too complex due, for instance, to the presence of nonlinear terms. The computational structure requires the definition of the FLC parameters namely, membership functions (MF) and a rule base (RB) defining the desired control policy. However, the optimization of the FLC parameters is generally carried out by means of a trial and error procedure or, more recently by using metaheuristic nature-inspired algorithms, for instance, particle swarm optimization, genetic algorithms, ant colony optimization, cuckoo search, etc. In this regard, the cuckoo search (CS) algorithm as one of the most promising and relatively recent developed nature-inspired algorithms, has been used to optimize FLC parameters in a limited variety of applications to determine the optimum FLC parameters of only the MF but not to the RB, as an extensive search in the literature has shown. In this paper, an optimization procedure based on the CS algorithm is presented to optimize all the parameters of the FLC, including the RB, and it is applied to a nonlinear magnetic levitation system. Comparative simulation results are provided to validate the features improvement of such an approach which can be extended to other FLC based control systems.Peer ReviewedPostprint (published version

On semigroups of multivariate transformations constructed in terms of time dependent linguistic graphs and solutions of Post Quantum Multivariate Cryptography.

Time dependent linguistic graphs over abelian group H are introduced. In the case $H=K*$ such bipartite graph with point set $P=H^n$ can be used for generation of Eulerian transformation of $(K*)^n$, i.e. the endomorphism of $K[x_1, x_2,… , x_n]$ sending each variable to a monomial term. Subsemigroups of such endomorphisms together with their special homomorphic images are used as platforms of cryptographic protocols of noncommutative cryptography. The security of these protocol is evaluated via complexity of hard problem of decomposition of Eulerian transformation into the product of known generators of the semigroup. Nowadays the problem is intractable one in the Postquantum setting. The symbiotic combination of such protocols with special graph based stream ciphers working with plaintext space of kind $K^m$ where $m=n^t$ for arbitrarily chosen parameter $t$ is proposed. This way we obtained a cryptosystem with encryption/decryption procedure of complexity $O(m^{1+2/t})$

On affine Cremona semigroups, corresponding protocols of Non-commutative Cryptography and encryption with several nonlinear multivariate transformations on secure Eulerian mode.

We suggest new applications of protocols of Non-commutative cryptography defined in terms of subsemigroups of Affine Cremona Semigroups over finite commutative rings and their homomorphic images to the constructions of possible instruments of Post Quantum Cryptography. This approach allows to define cryptosystems which are not public keys. When extended protocol is finished correspondents have the collision multivariate transformation on affine space K ^n or variety (K*)^n where K is a finite commutative ring and K* is nontrivial multiplicative subgroup of K . The security of such protocol rests on the complexity of word problem to decompose element of Affine Cremona Semigroup given in its standard form into composition of given generators. The collision map can serve for the safe delivery of several bijective multivariate maps F_i (generators) on K^n (or (K*)^n) from one correspondent to another. So asymmetric cryptosystem with nonpublic multivariate generators where one side (Alice) knows inverses of F_i but other does not have such a knowledge is possible. We consider the usage of single protocol or combinations of two protocols with platforms of different nature. The usage of two protocols with the collision spaces K^n and (K*)^n allows safe delivery of two sets of generators of different nature. In terms of such sets we define an asymmetric encryption scheme with the plainspace (K*)^n, cipherspace K^n and multivariate non-bijective encryption map of unbounded degree O(n) and polynomial density on K^n with injective restriction on (K*)^n. Algebraic cryptanalysis faces the problem to interpolate a natural decryption transformation which is not a map of polynomial density

Towards More Robust Natural Language Understanding

Natural Language Understanding (NLU) is a branch of Natural Language Processing (NLP) that uses intelligent computer software to understand texts that encode human knowledge. Recent years have witnessed notable progress across various NLU tasks with deep learning techniques, especially with pretrained language models. Besides proposing more advanced model architectures, constructing more reliable and trustworthy datasets also plays a huge role in improving NLU systems, without which it would be impossible to train a decent NLU model. It's worth noting that the human ability of understanding natural language is flexible and robust. On the contrary, most of existing NLU systems fail to achieve desirable performance on out-of-domain data or struggle on handling challenging items (e.g., inherently ambiguous items, adversarial items) in the real world. Therefore, in order to have NLU models understand human language more effectively, it is expected to prioritize the study on robust natural language understanding. In this thesis, we deem that NLU systems are consisting of two components: NLU models and NLU datasets. As such, we argue that, to achieve robust NLU, the model architecture/training and the dataset are equally important. Specifically, we will focus on three NLU tasks to illustrate the robustness problem in different NLU tasks and our contributions (i.e., novel models and new datasets) to help achieve more robust natural language understanding. The major technical contributions of this thesis are: (1) We study how to utilize diversity boosters (e.g., beam search & QPP) to help neural question generator synthesize diverse QA pairs, upon which a Question Answering (QA) system is trained to improve the generalization on the unseen target domain. It's worth mentioning that our proposed QPP (question phrase prediction) module, which predicts a set of valid question phrases given an answer evidence, plays an important role in improving the cross-domain generalizability for QA systems. Besides, a target-domain test set is constructed and approved by the community to help evaluate the model robustness under the cross-domain generalization setting. (2) We investigate inherently ambiguous items in Natural Language Inference, for which annotators don't agree on the label. Ambiguous items are overlooked in the literature but often occurring in the real world. We build an ensemble model, AAs (Artificial Annotators), that simulates underlying annotation distribution to effectively identify such inherently ambiguous items. Our AAs are better at handling inherently ambiguous items since the model design captures the essence of the problem better than vanilla model architectures. (3) We follow a standard practice to build a robust dataset for FAQ retrieval task, COUGH. In our dataset analysis, we show how COUGH better reflects the challenge of FAQ retrieval in the real situation than its counterparts. The imposed challenge will push forward the boundary of research on FAQ retrieval in real scenarios. Moving forward, the ultimate goal for robust natural language understanding is to build NLU models which can behave humanly. That is, it's expected that robust NLU systems are capable to transfer the knowledge from training corpus to unseen documents more reliably and survive when encountering challenging items even if the system doesn't know a priori of users' inputs.No embargoAcademic Major: Computer Science and EngineeringAcademic Major: Industrial and Systems Engineerin