Reviewerly/exHarmony huggingface dataset:
Testing the systems with fuzzy discrete components

Modern complex systems are build based on heterogeneous components with various interrela tionships, fuzziness, and uncertainty of the laws of functioning of the components and the system. An important class of such systems comprises hybrid intelligent systems, where the components are represented by analytical models of fuzzy objects, artifi cial neural networks, expert systems, etc. The article considers fuzzy discrete devices being, for example, part of hybrid systems. Fuzzy linear automata (FLA) introduced in the article are used as a mathematical model of such components. The problem of test synthesis for FLA used to detect faults in them is discussed. Normal single-stuck faults are permissible faults in FLA. The faults originating from the replacement of some elements of the FLA characteristic matrices with others (from a given set of alternative ones) are also permissible. Test synthesis methods for FLA belonging to the class of m-deterministic and synchronized automata, as well as arbitrary linear automata have been developed. The fi rst two methods are based on reducing the considered problem of solving systems of linear algebraic equations. It should be noted that there is a well-developed mathematical apparatus applying a few eff ective methods for searching for such solutions. The tests synthesized by these methods for m-deterministic and synchronized FLA are sufficiently short and do not exceed the memory depth of the corresponding automata. It is shown that the conditions for an FLA referring to the two fi rst classes mentioned above are not too strict. It is noted that the known methods of test synthesis for linear automata require compliance with much more stringent requirements. The synthesis method for arbitrary FLA also builds short tests
On Finality in Blockchains

This paper focuses on blockchain finality, which refers to the time when it becomes impossible to remove a block that has previously been appended to the blockchain. Blockchain finality can be deterministic or probabilistic, immediate or eventual. To favor availability against consistency in the face of partitions, most blockchains only offer probabilistic eventual finality: blocks may be revoked after being appended to the blockchain, yet with decreasing probability as they sink deeper into the chain. Other blockchains favor consistency by leveraging the immediate finality of Consensus - a block appended is never revoked - at the cost of additional synchronization. In this paper, we focus on necessary and sufficient conditions to implement a blockchain with deterministic eventual finality, which ensures that selected main chains at different processes share a common increasing prefix. This is a much weaker form of finality that allows us to provide a solution in an asynchronous system subject to unlimited number of Byzantine failures. We also show that the classical selection mechanism, such as in Bitcoin, that appends blocks at the longest chain is not compliant with a solution to eventual finality. We then study stronger forms of eventual finality strengthened with bounded revocation. By founded revocation we mean that the number of blocks that can be revoked from the current blockchain is bounded. This problem reduces to consensus or eventual consensus depending on whether the bound is known or not. We finally provide the first solution for unknown bounded revocation eventual finality with Byzantine processes.
Resampling Strategy for Mitigating Unfairness in Face Attribute Classification

With the widespread success of artificial intelligence (AI) systems, various applications based on the systems are being applied to our daily life. However, AI systems also raise societal problems since it is highly dependent on training datasets with bias. Consequently, concerning about trustworthiness in AI systems becomes a popular research topic, and recent studies reveal unfairness in developed models. In this paper, we propose a new batch sampling strategy considering fairness among demographic groups. Unlike conventional batch sampling methods such as under-sampling or oversampling, we reflect the notion of fairness directly to estimate the batch sampling probability of data. We empirically demonstrate that our batch sampling method achieves fairer results compared to prior methods in image classification tasks on CelebA and UTKFace datasets.
“My Grades Are Always Equal to Standardized Critetria” : Discovering EFL Learners’ Motivation Outside Formal Classroom

Motivation in language mastery is a crucial aspect that supports learner success especially in non-formal education. This study explores the motivation of English language learners in non-formal education as well as their perceived difficulties. Employing a qualitative approach with in-depth-interviews in the data collection, the study involved eight learners from a language course institution in Yogyakarta. The transcribed data were analyzed, interpreted, and categorised based on types of motivation and difficulties. The results show that most of the English learners possess instrumental motivation in learning foreign languages, but some tend to have integrative motivation. The instrumental motivation is mainly linked to efforts to pass the exam or tests with good grades. Their integrative motivation is related to recognizing the culture of the target language speech community and desire to communicate with the target community. Despite their motivation, they faced some difficulties related to language skills, especially reading and listening. In addition, they perceived vocabulary as hindrance in all the four skills. Further research to overcome the difficulties is recommended to maximize the learning achievement.
Secure I-voting system using QR code and biometric authentication

The Estonian i–voting system uses the PIN of the national ID card for the authentication of the voter. The vote modification malware, re-voting malware, and self-voting malware can easily record the PIN and change the vote or secretly cast a vote. The bad verification attack can easily change the encrypted ballot sent to the verification application because the public key of the server encrypts it. This study presents a secure internet voting and verification protocol that conquers the malware in the internet voting system. The proposed method uses the QR code and fingerprint biometric authentication provided by the Aadhaar card in India. The use of a parameter q modifies the voting and verification protocol. Only the parameter q display on the screen for verification, thereby, conserves the vote’s secrecy. The parameter q provides a second level of authentication in the voting protocol. The fingerprint biometric authentication exhibits better security against the vote modification malware, re-voting malware, and self-voting malware. The parameter q is digitally signed using the server’s private key before it is sent to the verification application to defend against the bad verification attack.
Sentiment analysis of mass rapid transit jakarta using naïve bayes classifier and rule-based opinion target detection on Twitter

Jakarta Mass Rapid Transit (MRT) is a national project in Indonesia that has been operated since the beginning of 2019 for phase 1 and still under further development. People's opinions posted on Twitter concerning Jakarta MRT could become an evaluation material, viewed from the sentiment score and object of the opinion. To analyze the sentiment score, opinion sentiment classified using the naive Bayes classifier, followed by rule-based target opinion detection. The classification process is using bag of words (BoW) features and lexicon-based features. In the weighting process of the Lexicon-based features and detection of the target opinion, POS tagging is employed to get the word class. In determining the target opinion object, the POS tagging result is used to do chunking that has specific rules, specific to noun-phrase (NP) tags. Therefore, the obtained sentiment class and object become the target in the opinion. Using Naïve Bayes with the bag of words features and lexicon-based, we achieve precision 0,92, recall 1,0, f-measure 0,95, and accuracy 0,92. The results of the rule-based target opinion detection are 0.78, 0.85, 0.79, and 0.75 for precision, recall, f-measure, and accuracy, respectively.
Database Integration Based on the Selection of Preliminary Knowledge Using a Semantic Network

It is proposed to use a semantic search system to solve the problem of the inadequacy of the key-based data discovery mechanism due to the extraction of a large amount of irrelevant information. An algorithm for detecting knowledge in the semantic network at the stage of selecting the appropriate preliminary knowledge using associated open data to interpret relational databases and unstructured data is presented. A comparative analysis of the results of the used algorithm in traditional methods is performed.
Campur Kode dalam Proses Pembelajaran Bahasa Indonesia di SMA Negeri 1 Rantepao

This research aims to describe the form of the use of code interfering in the Indonesian language learning process at SMA Negeri 1 Rantepao, North Toraja.The research is a qualitative descriptive research type. The Data in this research is the code of mixed teachers and students in the learning process of Bahasa Indonesia class XI language SMA Negeri 1 Rantepao. Data is collected with observation, record, and record techniques.The form of code is derived from the Indonesian language learning process in SMA Negeri 1 Rantepao in the form of insertion of elements in the form of (1) words, (2) phrases, and (3) sentences. Mix the code found aimed at knowing, informing, asserting, as well as explaining something.
Separability as Channeling: A Cautionary Tale

One of the most prominent themes in Annette Kur’s influential scholarship has to do with cumulation of intellectual property rights, especially in relation to design. Professor Kur is much more comfortable with that cumulation than I have been, at least in part because she is less confident that subject matter can neatly be separated.2
Android Musical Puzzle Game “Music Puzzle”

Abstract “Music Puzzle” is a musical puzzle game for Android. Player will try to arrange the puzzle piece by listening to the music in each puzzle and correct the order of the music. This game use classical music as the theme of the game. This game is developed by Unity game engine with C# as the programming language. Testing has been done with Black Box Testing, Alpha Testing by lecturer and Beta Testing by survey to 30 respondents. The results show that the “Music Puzzle” is an interesting game to play and encourage respondents to interest in classical music.
pRnR: A Parallel Record-Replay Framework for Virtual Machines

The record and replay(RnR) technology of virtual machine(VM) provides the ability to reproduce the past execution of a VM deterministically. It has many promising applications in the cloud environment, including fault tolerance, security analysis, and failure diagnosis. Existing studies in this area pay more effort in optimizing the record method, such as reducing performance penalty and storage costs. However, considering that many practical applications follow the record once, replay many mode, the optimization for the replay is more critical, especially for efficiency. In this paper, we propose pRnR, a novel parallel RnR framework, to support efficient replay. By combining the native RnR framework with an improved continuous snapshots mechanism, pRnR divides the full execution into many independent and complete slices, each of which supports arbitrary replay. In addition, it supports two replay modes to improve replay efficiency, i.e., multi-slice parallel replay and multi-dimension parallel replay. Moreover, we apply our pRnR framework to syscall-based diagnosis to demonstrate its usability. The experimental results show that pRnR is more efficient than existing RnR frameworks.
МЕТОДОЛОГІЧНІ АСПЕКТИ ДОСЛІДЖЕННЯ ПАНДЕМІЧНОГО ОБРАЗУ СВІТУ

Possibilities of research of a pandemic image of the world were theoretically reviewed on the methodological basis of the psychosemantic approach. The pandemic image of the world is positioned as a product and a significant outcome of pandemic consciousness. Pandemic consciousness is a state of mass everyday consciousness that finds its expression in the indirect reflection of everyday life, the essence and content of which is to meet the interests and needs of a given society related to physical and economic survival during a mass pandemic. It is concluded that the content of the pandemic image of the world is formed by activating the following socio-psychological phenomena, mechanisms and coping strategies: stereotyping of mass consciousness, escape into denial, avoidance of an unfavourable reality, infodemia, magical thinking, revival of conspiracy theories and enemy archetypes, creation of new simulacra, increasing alarmism, anxiety about the near future, the search for new meanings of life.
Application of GIS in Oilfield Power System

This paper discusses the use of GIS in oilfield power system, combined with the basic concept and advantages of GIS, combined with the characteristics of the oilfield power system, put forward the overall design system of the oilfield power system, ensure the stability of the power system operation, give full play to the role of GIS.
Actual Trends of Cloud Computing and Technologies in Optimization of Data Storage

The purpose of the article is to investigate and consider the general trends, problems and prospects of using cloud computing and technologies in data processing, in particular optimization of their storage.The research methodology consists of semantic analysis methods of the basic concepts of the considered subject area (cloud computing and cloud technologies). The article discusses approaches to storing data (including multimedia) in modern systems that support cloud computing and technologies.The scientific novelty of the research is the analysis of cloud computing use and cloud technologies for data storage optimizing.The conclusions of the research conducted in the article are as follows: the paper considered various aspects related to cloud computing and cloud technologies, including various advantages and disadvantages; cloud computing and cloud technologies can offer numerous benefits to various stakeholders; cloud computing and cloud technologies have some problems; it is noteworthy that by supporting the cloud computing and cloud technologies deployment and maintenance models, problems can be either minimized or eliminated since the dynamic characteristics of cloud computing and cloud technologies can always support users.
A Quantified Cloud Base Polio Vaccination Management Information System (QCloudMIS)

Polio Supplemental Immunization Activities (SIAs) are components of the global polio initiative set out by the world health assembly (WHA) in 1988. While the strategy has helped to interrupt the transmission of wild poliovirus in most countries. The Percentage of positive change needs to be improved upon. Polio and immunization reporting in Africa, Nigeria has traditionally been paper- based. This study assessed the existing polio immunization coverage and proposed a cloud-based framework to enhance quality of data, report and documentation including tracking rural health workers. The proposed solution is a cloud-based health information management system designed specifically for health workers in remote and challenging areas, it allows Health workers to register beneficiaries into health programs like polio vaccination, screen them for high-risk infection, submit stock reports of vaccination and report disease outbreaks as against the manual system. which delayed and lack adequate data quality. QCloudMIS technology also helps to track field exercise and reporting using offline cloud mobile cloud. While the existing technological solution depends on Standalone local server or device memory for storage, this study uncovers their limitations and proposed that cloud-based HMIS can improve health care service delivery and enhance the administration of Vaccines in rural communities.
A Striping Removal Method Based on Spectral Correlation in MODIS Data

Modis imagery suffers from nonlinear striping in many bands. The nonlinear stripes make great difficulties for conventional linear statistical destriping methods. This paper presents a two-step method for nonlinear stripe removing. Both steps depend on the correlation information between defective band and its reference normal band. First stripes in defective band are divided into different portions with the aid of its high correlation spectrum by GA algorithm automatically and moment matching destriping is performed in each portion independently. Then the residual noise is eliminated by PCA transform and low pass filtering of two high correlation spectrums. Experiment results demonstrate that the proposed algorithm can effectively reduce nonlinear striping in MODIS data.
Quantum Information Processing Framework

This chapter gives an overview of a quantum information processing framework. You will see how a quantum information processing framework is applied in real life. Code examples are presented for the quantum algorithms discussed. In addition, this chapter discusses quantum circuits in detail.
Iteration in ACL2.

Iterative algorithms are traditionally expressed in ACL2 using recursion. On the other hand, Common Lisp provides a construct, loop, which -- like most programming languages -- provides direct support for iteration. We describe an ACL2 analogue loop$ of loop that supports efficient ACL2 programming and reasoning with iteration.
UAV solutions based on wireless communications

Summary form only given. The complete presentation was not made available for publication as part of the conference proceedings. In this talk an introduction to unmanned aerial vehicles will be made, detailing their operation, main uses, and main research challenges. Next, different applications and systems developed in our research group will be discussed, showing how wireless communications can be used to achieve advanced features such as swarm creation and collision avoidance.Regarding collision avoidance, the Mission Based Collision Avoidance Protocol (MBCAP) is presented. MBCAP is a novel UAV collision avoidance protocol applicable to all types of multicopters flying autonomously. It relies on wireless communications in order to detect nearby UAVs, and to negotiate the procedure to avoid any potential collision. Experiments show that MBCAP is very effective at impeding collisions, while introducing a flight time overhead that is typically in the range from 15 to 40 seconds.Concerning swarm creation, the Mission-based UAV Swarm Coordination Protocol (MUSCOP) is presented. It allows multiple UAVs to perfectly coordinate their flight when performing planned missions. Experimental results show that the proposed protocol is able to achieve a high degree of swarm cohesion independently of the swarm formation adopted, being resilient to channel losses, and introducing a low synchronization time overhead.
Performance evaluation of common lightweight ciphers against AES : Evaluating code size, memory usage, execution time, and energy consumption of common lightweight ciphers used in 8 – bit AVR microcontrollers against AES-128

The increased use of low resource devices that are dependent on robust security solutions demands new cryptographic methods to optimize resource usage to allow devices to increase the workload. Rec ...
Morphological convergence as on-line lexical analogy: Supplementary materials

In this supplementary information, we detail (1) the structure of our nonce verb stimuli, (2) the setup of the Generalized Context Model (GCM) and (3) the Minimal Generalization Learner (MGL), and (4) how these models compare.We illustrate the models using fits on our baseline data.We also discuss model selection in analysing our regression data (5), how the two learning models compare on our baseline data (6), and how they compare on our ESP post-test data (7).Sections ( 2) and (3) also appear in the main text of Rácz et al. ( 2020), as Appendices A and B. However, this material is included here so that this Supplement can serve as a standalone document for readers who are interested in the technical details of our study.Additional material is reproduced from the main text, revisiting specific regression model summaries and additional methods we used to investigate contributions from the GCM and MGL.The source file for this SI, along with the data and the code for the paper, are hosted at https://github.com/petyaracz/RaczHayPierrehumbert2019. Regular and irregular verbs in EnglishFour irregular verb classes were defined for our stimuli, based on the vowel alternation and affixation processes that apply to the stem:
Integration and Participation of Parents in Educational System

The objective of the article is to inform the relevance and importance of the family when getting involved as a beneficiary factor in the study of young people; more importantly, the father in his contribution to the education of his sons and daughters. After decades and with the passing of the years this bond so transcendental between parents and children has been weakened, so that the results today are so visible that it is increasingly less important for the young person to study and move forward in their professional future life; going to another extreme as it also hurts to overprotect a lot in your student preparation life, without letting it be defended only that it constitutes another current concern since there is no effort to achieve its goals, knowing that someone who seeks Always solution to your problems.
Ciphertext Sorting Search Scheme Based on B+ Tree Index Structure on Blockchain

In order to overcome the problem that cloud storage is not trusted and the low efficiency of ciphertext retrieval in cloud storage, a searchable ciphertext sorting encryption scheme based on B+ tree on the block chain is proposed. Combined with the blockchain technology, the problem of establishing reliable trust in multiple parties that do not understand each other is solved. A vector space model is used to reduce the complexity of the text and an efficient text retrieval system is implemented. The index structure of the B+ tree is used to improve the retrieval of ciphertext transactions on the blockchain. The ranking of multi-keyword query results is realized by the Term Frequency–Inverse Document Frequency (TF-IDF) algorithm. Under the random oracle model, it is proved that the scheme is adaptive and indistinguishable. Through the comparative analysis of efficiency, it is shown that the scheme achieves efficient ciphertext retrieval on the blockchain.
TEACHING ENGLISH TO YOUNG LEARNERS THROUGH WORD-WEBBING

Teaching English to young learners commonly uses various method s and technique s . One is to use word-webbing media in teaching vocabulary. The researcher creates the word-webbing media that is made of wood and has a different color which contains vocabular y that is related to the theme. To express a different way in teaching vocabulary process , this media is helpful. The way to use word-webbing is simple. The teacher only brings a word-webbing media and a box of cards contains an alphabet. Then , the teacher lets the learners choose the color and letter randomly. The letter will be opened, so the learners will arrange some letters based on the vocabulary . Th ese media ha ve been examined to young learners. They are so excited to enjoy this media because it is not only to build their comprehension of English but also their critical thinking as well.
ON THE IMPORTANCE OF INNOVATION IN THE EDUCATIONAL PROCESS OF A MODERN UNIVERSITY

The article presents an analysis of innovative processes in the educational process of a modern Univer-sity. The author's interpretation of such definitions as «innovation», «information technology» and their in-volvement in the educational process is given.