Reviewerly/exHarmony huggingface dataset:
A Bionic Optimization Technique with Cockroach Biological Behavior

Many practical engineering problems can be abstracted as corresponding function optimization problems. During the last few decades, many bionic algorithms have been proposed for this problem. However, when optimizing for large scale problems, such as 1000 dimensions, many existing search techniques may no longer perform well. Inspired by the social model of cockroaches, this paper presents a novel search technique called Cooperation cockroach colony optimization (CCCO). In the CCCO algorithm, two kinds of special biological behavior of cockroach, wall-following and nest-leaving, are simulated and the whole population is divided into wall-following and nest-leaving populations. By the collaboration of the two populations, CCCO accomplishes the computation of global optimization. The crucial parameters of CCCO are set by the self-adaptive method. Moreover, a discussion on group model design is provided in this paper. The CCCO algorithm is evaluated with shifted test functions (1000 dimensions). Three state-of-the-art cockroach-inspired algorithms are used for the comparative experiments. Furthermore, CCCO is applied to a real-world optimization problem concerning spread spectrum radar poly-phase. Experiment results show that the CCCO algorithm can be applied to optimize large-scale problems with the good performance.
Income Analysis of Social Users Based on Multi-features

Text classification is an important technology of mining text hidden information. It is a process to determining the category of text based on analyzing the content of text. Nowadays, Twitter is one of the most popular social networks with the largest number of users in the world, so we can analyze a lot of potential information of users from their tweets. This paper mainly predicts the income level of users through their tweets and personal information. Based on machine learning algorithm, this paper mainly includes five processes: data acquisition, text preprocessing, feature extraction, classifier training, and classification. In feature extraction, we use sensitive thesaurus and sentiment classification to obtain coarse-grained features of users and use TF-IDF algorithm and LDA topic extraction model to obtain fine-grained features of users. In the training stage, naive Bayes, K-nearest neighbor, logistic regression, and support vector machine were used to evaluate and compare, and the final results were obtained. The final experimental results show that the income analysis based on multi-features can achieve a good result.
3D Surface Detail Enhancement

In 3D surface reconstruction, the sampling and quantization in the process of digitization limits the surface details obtained by the visual sensor. Obtaining a fine-grained 3D surface at lower cost remains a difficult problem. In our work, we have introduced a new method for enhancing 3D surface details reconstructed from single normal map without the support of hardware and reflection models. Using the new measurement of angle profile to infer microstructures hidden from existing surfaces. In addition, discrete geometry processing (DGP) can be used to further improve inference results. Numerous simulation results show that our method has achieved significant improvements on both subjective visual evaluation and objective quality metrics.
The Blockchain That Matters: A Comparative Analysis of Bitcoin's Fundamentally Unique and Irreplicable Properties

The crypto industry comprises thousands of cryptocurrencies offering different versions of blockchain-based decentralization – a concept that was described originally in the Bitcoin Whitepaper in 2008. What is Bitcoin’s value proposition in this confusing landscape? Bitcoin is a monetary asset that achieves immutability through a decentralized governance protocol. Such immutability is, in theory, the primary reason behind blockchain technology in the first place. However, besides Bitcoin, what we see across the industry are blockchain-based tokens offering diluted or spurious decentralization, thereby contradicting and defeating the purpose of immutability altogether. This paper highlights these ‘blockchain-fallacies’ through a comparative analysis against Bitcoin’s unique and irreplicable decentralized governance mechanism.
Improvement in Ranking Relevancy of Retrieved Results from Google Search Using Feature Score Computation Algorithm

Websites with a higher position in search engine ranking result; directly and positively affect visitors’ number to such sites. Search engine optimization (SEO) has become a promoting business that attempts to improve websites’ ranking. Sometimes, search engine results may contain undeserving websites at top rank due to SEO techniques in an unethical way. It misleads the search engine, and thereby it will increase the page rank of unfit websites. Due to this, such results downgrade the performance of search engines and frustrate the users. These irrelevant pages must be moved top-down from the search results to improve search engine quality. This paper analyzes Google results and proposes a novel approach to move down the top-ranking irrelevant Google search engine results. A ‘feature Score computation’ algorithm was presented here to compute scores based on features found in pages, and using the score, the pages are re-ranked to move down irrelevant results and uplift the relevant products. The accuracy of the corpus results’ relevancy was 88%, and after applying the algorithm, it was improved to 99%. This work improved the ranking of relevant products efficiently.
Dedications and autographs on the rare stock books of the Central Scientific Library of the Irkutsk Scientific Center of SB RAS

Today it is widely practiced to exhibit autographs, inscriptions at exhibitions in museums, institutions of science, education and culture. This is due to the increased interest in the history of scientific research, personal and official relation-ships of people, and testifies to the urgency of the problem, that requires the attention of specialists. According to Brockhaus and Efron, «the autographs of famous scientists, writers and poets constitute the true treasure of libraries ...» (Encyclopedic Dictionary of Brockhaus and Efron, St. Petersburg, 1890. T. 1, p. 123). Autographs, inscriptions on books can serve as an additional source of information about any author’s life, era, scientific or cultural phenomenon. In the libraries of the Academy of Sciences, one can find literature with autographs, donation inscriptions of scientists, various notes. The purpose of the article is to bring to the readers some autographs, inscripts, their content, handwriting of prominent Russian scientists on books from the library stock of the Central Scientific Library of the Irkutsk Scientific Center SB RAS (СSL ISC SB RAS) (previously – the library of the East-Siberian Branch of the USSR Academy of Sciences), to tell about these books and their authors destinies. Responses to the article will help to determine the authorship of unidentified inscriptions. In the course of the work, there were exposed and identified de visu books with autographs, donations (inscriptions) to the library from authors, to scientists from colleagues and owner’s inscriptions; the analysis of library materials was carried out, an attempt was made to systematize written sources with autographs and donations. At the second stage of the work, an electronic database was being compiled - the Catalog of Rare Books in EC IRBIS, which can be found on the library website.
A Language with Type-Dependent Equality

In soft type systems terms and types exist independently and typing is a binary relation between them. That allows the same term to have multiple types, which is in particular the case in the presence of subtyping. Thus, a soft type system may define equality in such a way that two terms can be equal at one type but unequal at another type. We explore the design of soft type systems with such a type-dependent equality. The most promising application is that it yields a more natural treatment of quotient types: if two terms can be different at the base type but equal at the quotient type, we can use the same representation in both types without incurring the cost of using equivalence classes. That can help formalize mathematics, where the official definition of quotients uses equivalence classes but practical notations usually do not. The main drawback of such a system is that the substitution of equals by equals becomes more complex as it now depends on the type with which the equal terms are used. We analyze the general problem, show examples from major soft-typed proof assistants, and then present a simple language that allows studying type-dependent equality in a simple rigorous setting.
Online Teaching as an Important Means of Technogenic Society Development During the Pandemic

The article is devoted to the problems that have arisen during the students’ education of non-language institutes to distance learning due to the pandemic of 2020. The relevance of the research topic is due, on the one hand, to modern requirements for the digitalization of education in general and higher vocational education in particular cases. On the other hand, the organisation to distance learning of students at the Siberian Federal University carried out with the use of various digital resources, which had a number of positive results; it was accompanied by a number of difficulties, the analysis of some of these problems are presented in this article. In the article you also can find the most effective digital methods of teaching students that were identified, taking into account direction of the student and acquisition of unqualified competencies in accordance with the discipline program, all these findings were based on the analysis fulfilled by the authors. Other digital resources considered in the article by the authors can be applied additionally, according to their advantages and disadvantages. The practical significance of the article lay in the justification of the feasibility of combining the resources under consideration in the organization of distant study of students in the course “Foreign language” as an example of the work organized during the pandemic. #CSOC1120
Boolean Polynomials, BDDs and CRHS Equations - Connecting the Dots with CryptaPath

When new symmetric-key ciphers and hash functions are proposed they are expected to document resilience against a number of known attacks. Good, easy to use tools may help designers in this process and give improved cryptanalysis. In this paper we introduce CryptaPath, a tool for doing algebraic cryptanalysis which utilizes Compressed Right-Hand Side (CRHS) equations to attack SPN ciphers and sponge constructions. It requires no previous knowledge of CRHS equations to be used, only a reference implementation of a primitive. The connections between CRHS equations, binary decision diagrams and Boolean polynomials have not been described earlier in literature. A comprehensive treatment of these relationships is made before we explain how CryptaPath works. We then describe the process of solving CRHS equation systems while introducing a new operation, dropping variables.
The Use of Authentic Materials in Teaching Reading to Secondary School Students in Malaysia: A Literature Review

English language has been used globally.In Malaysia, to strengthen the English proficiency among the Malaysian students, English language is introduced as a compulsory subject at both primary and secondary schools and administered under the language education policy.Students in secondary school must learn the language for the sake of their future endeavours.As teachers, it is their role to grab the students' attention to learn English language through reading.However, most of the students nowadays never show the interest to read.Various kinds of authentic materials could be used to help the students in their language acquisition and to bridge the gap between classroom knowledge and students' capacity to participate in the real-world situation.Prior to this, the researcher finds that authentic materials are useful in enhancing the secondary school students to read and help the students to explore more knowledge from this borderless world.In accordance to encourage the students in secondary school to read, this review will expose the readers to the use of authentic materials in teaching reading, the roles of authentic materials in developing the reading skill among the secondary students, and the teachers' role in teaching reading by using the authentic materials.Most of the findings have shown that authentic materials give positive impacts to the secondary school students to improve their reading skill.In short, the more materials the students read, the more knowledgeable they will become.
A Computer Control for Electronics Actions of Smart Voice Interactive Devices

Smart devices have evolved through voice control. They are permanently connected to the internet to provide information interactively. The electronic services offered are based on actions towards devices interconnected through wireless communication channels. They can be smart plugs, smart bulbs or any electronic device compatible with the smart audio system. Remote control via the Internet of these interconnected devices is possible. The advantages of these technologies are certain for various monitoring and services. The system proposed in this paper is able to monitor the predefined operation with online remote control. Especially for off-line situations, it intervenes through a local strategy to ensure a predictable functionality. Included here are emergencies, when power consumers are connected or there is critical assistance for certain remote services.
OctaNLP: A Benchmark for Evaluating Multitask Generalization of Transformer-Based Pre-trained Language Models

Kaddari, Zakaria Mellah, Youssef Berrich, Jamal Belkasmi, Mohammed G. Bouchentouf, Toumi In the last decade, deep learning based Natural Language Processing (NLP) models achieved remarkable performance on the majority of NLP tasks, especially, in machine translation, question answering and dialogue. NLP language models shifted from uncontextualized vector space models like word2vec and Glove in 2013, and 2014, to contextualized LSTM-based model like ELMO and ULMFit in 2018, to contextualized transformer-based models like BERT. Transformer-based language models are already trained to perform very well on individual NLP tasks. However, when applied to many tasks simultaneously, their performance drops considerably. In this paper, we overview NLP evaluation metrics, multitask benchmarks, and the recent transformer-based language models. We discuss the limitations of the current multitask benchmarks, and we propose our octaNLP benchmark for comparing the generalization capabilities of the transformer-based pre-trained language models on multiple downstream NLP tasks simultaneously.
Employee Awareness Model to Enhance Awareness of Social Engineering Threats in the Saudi Public Sector

The increase in social-engineering threats within the Saudi public sector has changed awareness and training methods. However, due to employees' lack of awareness, social engineering could lead to a breach whereby attackers identify vulnerabilities and subsequently launch their attacks. A social-engineering attack is a high risk to the Saudi public sector and may significantly affect its security measures. Thus, the benefits of adopting awareness-enhancement tools in the public sector are undeniable. This study proposes a conceptual awareness model designed to enhance employee awareness in the Saudi public sector to address this issue. This study reviews seven main factors of social engineering risk: phishing, baiting, pretexting, quid pro quo, tailgating, related security policies, and the ability to identify attacks and respond to threats. Additionally, this research examines one public sector actor in Saudi Arabia as a case study. The findings led to a model creation comprising of five components: a situation-awareness model for phishing, an information-security awareness tool, a power-knowledge-practice triangle, Saudi public sector follow-up metrics, and implementation phases. As a result, an a priori model was successfully developed, tested, and applied in the subsequent stage by the case study participants, the employees.
Learning-To-Ensemble by Contextual Rank Aggregation in E-Commerce

Ensemble models in E-commerce combine predictions from multiple sub-models for ranking and revenue improvement. Industrial ensemble models are typically deep neural networks, following the supervised learning paradigm to infer conversion rate given inputs from sub-models. However, this process has the following two problems. Firstly, the point-wise scoring approach disregards the relationships between items and leads to homogeneous displayed results, while diversified display benefits user experience and revenue. Secondly, the learning paradigm focuses on the ranking metrics and does not directly optimize the revenue. In our work, we propose a new Learning-To-Ensemble (LTE) framework RA-EGO, which replaces the ensemble model with a contextual Rank Aggregator (RA) and explores the best weights of sub-models by the Evaluator-Generator Optimization (EGO). To achieve the best online performance, we propose a new rank aggregation algorithm TournamentGreedy as a refinement of classic rank aggregators, which also produces the best average weighted Kendall Tau Distance (KTD) amongst all the considered algorithms with quadratic time complexity. Under the assumption that the best output list should be Pareto Optimal on the KTD metric for sub-models, we show that our RA algorithm has higher efficiency and coverage in exploring the optimal weights. Combined with the idea of Bayesian Optimization and gradient descent, we solve the online contextual Black-Box Optimization task that finds the optimal weights for sub-models given a chosen RA model. RA-EGO has been deployed in our online system and has improved the revenue significantly.
Heuristic Evaluation of Android-Based Applications with Multiple Screen Sizes Support: A Case Study

In recent years, mobile devices have become one of the main tools for communication and now represent a unique opportunity to reach great numbers of users. Also, Google’s Android OS is the one that has grown into a first choice for developing applications. This situation has a diversity of challenges, one of them being ensuring a rich and engaging user experience. One of the most restrictive and unique aspects of mobile development is the diversity in support for screen sizes and/or resolutions. This characteristic can mean different user experiences for users with the same application and has become increasingly important to consider when evaluating usability. In view of this, a proposal was made of an adaptation for the Heuristic Evaluation method, targeting applications that could be used in a range of devices with multiple screen sizes. To validate the proposal, a case study was conducted, evaluating a well-known banking application in Peru, using the proposed adaptation of the method described by Nielsen. This validation consisted of two groups of evaluators, one using traditional Nielsen heuristics, and a second group using context specific heuristics. As a result of the validation, the second group found more issues related with screen size. The proposed adaptation showed positive results, especially if a predefined set of devices, representative of the most common sizes sub-groups is used. As conclusion to the study, the evaluation conducted is an indication that careful consideration should be taken when building applications for a broad range of users, and devices.
A Preliminary Study of Confusable Words in L2 Chinese Textbooks

The present study adopts a corpus-based method to investigate the effectiveness and reliability of the confusable word sets listed in the L2 Chinese textbooks. Through the quantitative analysis based on the interlanguage corpus, we have found that, among 134 sets of words listed in the textbooks, only 50 sets have met the criterion we had set for “confusable words”. We hence provide a suggested word list based on the results of the analysis, a list of the sets that do not meet the criteria but are found in the corpus with more obvious mistaken usage, as well as a list of the sets that meet the criteria but are not the most typical ones. Through the preliminary research, it is hoped to provide teachers and textbooks editors with a more scientific method of selecting confusable words to improve the efficiency of teaching and learning.
Formally Verified a Front-End of the Trusted Code Generator for Safety I&amp;C Software of NPPs

In nuclear power plant embedded software control area, graphical control algorithms are described by Lustre program and designed with graphical editors of engineering station. After they are translated into C programs through a code generator, then the C programs are downloaded to the embedded platform software of NASPIC. The correctness of the code generator will directly determine the credibility and safety of NASPIC. Therefore, it’s important to ensure the correctness of the code generator translation process. Formally verified the correctness of a code generator, which has been studied for many years and becomes a most effective approach to develop a trusted code generator. This article is based on the requirements of nuclear safety-level I&C (Instrumentation & Control) system and mainly presents the development of a formally verified code generator front-end. The front-end translates Lustre source program into S_Lustre (a sequential intermediate language). And it is programmed and proved in Coq (Auxiliary Theorem Prover). During the development of the front-end, two key technical challenges have been resolved. The first is to ensure every id which appeared in the Lustre program has been defined. The second is to implement the casualty analysis and determine the evaluation order of user-defined types and equations based on the dependencies.
Empirical Evidence in Early Stage Software Effort Estimation Using Data Flow Diagram

Software effort estimation in a very early stage of the application development lifecycle is always a challenge for project managers. Many researchers have proposed different methods. They have certain advantages and limitations. This study proposed an approach called Early Effort Estimation from the data flow diagram with a complexity tag added that could estimate the effort estimation in a very early stage of the software development cycle. This method can be obtained by evaluating the customized data flow diagram, a data flow diagram with specific tag values. We also proposed a tool that implemented this method.
Performance analysis of AES encryption operation modes for IoT devices

Daily activities have been increasingly supported by intelligent devices and applications. Smart devices are constantly communicating through the Internet of Things (IoT) networks, either by sending collected data and notifying the actions taken or by receiving instructions for actions to be taken. Most of this communication requires the confidentiality of data through the usage of encryption algorithms, being the Advanced Encryption Standard (AES) algorithm one of the most used. However, how do the operation modes of AES algorithm perform in a resource-constraint device? This paper aims to evaluate the impact on the time to encrypt and decrypt different sized messages in IoT devices when using each one of the five AES modes of operation and the three key sizes defined. The test scenario was implemented using two programming languages, running on a Raspberry Pi device. The results achieved infers that Python was quicker and had a more homogeneous result set than JavaScript implementation in most AES operation modes. These results help to understand the trade-off between IoT devices' security needs and delays in communication caused by the selection of the AES algorithm operation mode.