Reviewerly/exHarmony huggingface dataset:
AN ANALYSIS OF DISTRIBUTION AND DIFFICULTY LEVELS OF LINGUISTIC QUESTIONS ON COGNITIVE DOMAIN IN INDONESIAN SUBJECT AT GRADE EIGHT OF SMP 1 TAKENGON

This study aims (1) to describe the distribution of linguistic questions of cognitive domain on the second semester final exam year 2013/2014 in Indonesian subject at Grade Eight of SMP 1 Takengon and (2) to describe the difficulty levels of linguistic questions of cognitive domain on the second semester final exam year 2013/2014 in Indonesian subject at Grade Eight of SMP 1 Takengon. The method used in this research is a quantitative descriptive. Data were obtained through documentation techniques. The results of this study show that (1) there are several levels the distribution of linguistic questions of cognitive domain on the second semester final exam year 2013/2014 in Indonesian subject at Grade Eight of SMP 1 Takengon i.e. C1 level items at 54% classified as unbalanced, C2 level items at 23% classified as unbalanced, C3 level items at 17% classified as unbalanced, and C4 level items at 6% classified as unbalanced and (2) there are the difficulty levels of linguistic questions of cognitive domain on the second semester final exam year 2013/2014 in Indonesian subject at Grade Eight of SMP 1 Takengon i.e. category of the easy items at 57% classified as unbalanced, category of the medium items at 37% classified as unbalanced, and category of the difficult items at 6% classified as unbalanced. From results of this study proved that (1) the distribution of linguistic questions on cognitive domain not balanced by the percentage proportion balancing of the items for grade of the SMP and (2) the difficulty levels of linguistic questions on cognitive domain not balanced by the percentage proportion balancing for amount of the items. Thus, an evaluation of distribution and difficulty levels of linguistic questions on cognitive domain on the second semester final exam year 2013/2014 in Indonesian subject at Grade Eight of SMP 1 Takengon still require adjustments in the future.
Present Status of Age Determination in Geology

Like most other fields of physical and chemical research which depend on the advance of authors knowledge of radioactivity and other nuclear processes, the matter of radioactive age determination has made tremendous strides in the last decade. Therefore it would seem desirable to briefly summarize the various radioactive methods that are presently recognized as having value in geologic age determination and to indicate their limitations. These are enumerated for each method followed by an estimate of the potential effective range, and finally the geologic conditions in which the particular method may be used. Uranium minerals might be useful in this method for very young rocks to the present but older minerals would certainly be severely shattered and a large fraction of their helium lost. A great potential advantage of this method in contrast to the preceding ones is that the accuracy of the age determination is independent of the age of the deposit.
Intelligent information system for predicting the phase stability of solid solutions

This research work is devoted to solving the actual problem of predicting the phase stability of solid solutions based on determining the limits of substitutions by the crystal-chemical method in systems of solid solutions with isostructural components in the approximation of regular solid solutions
MCLS (Midwest Collaborative for Library Services) E-Resources 2021 Meeting <i>Reporter: Joseph Badics, Eastern Michigan University</i>

"MCLS (Midwest Collaborative for Library Services) E-Resources 2021 Meeting Reporter: Joseph Badics, Eastern Michigan University." Journal of Electronic Resources Librarianship, 33(3), pp. 229–230
A quantum computer architecture perspective: executing quantum applications on real quantum processors

Building a quantum computer is not only about having qubits or quantum processors, analogously to classical computers are not only based on transistors or integrated circuits. Accordingly, in the very recent times, a few unique research groups in academia and companies have been exploring and proposing high-level and low-level programming languages, compilers, microarchitecture and instruction set architectures for quantum computation as well as different computer architecture approaches. In other words, developing a quantum computer requires bridging quantum applications and quantum devices. This talk will address the main challenges of building a scalable full-stack quantum computing system followed by a discussion on its architecture focusing on fault tolerance and compilation of quantum algorithms on NISQ devices. I will also provide my vision on how the research community could accelerate the process towards building such a scalable quantum machine, potentially through vertical cross-layer co-design structured methodologies.
Quantum-dot Controlled Electronic Block Triggering a Quantum Computation Procedure: A Recent Study

The works that have been devoted to the topic of quantum computer design have been examined. The main issues surrounding the development of a quantum computer are explored. The “up to bottom” concept has been presented and supported as a fundamentally novel way to solve the problem of building a really quantum computer. The technique can be accomplished by using nanotriggers made of two-dimensional materials, such as graphene, to visualise the quantum states of qubits in advance. This refers to the visualisation (materialisation) of all states, including entangled states, which primarily determine the quantum computer's theoretically large mathematical resource. The proposal is for an electronic device block diagram based on “a priory” quantum states of q-bits. It is demonstrated that each realised (visualised) Shor's cell should correspond to an element of the electronic system for the execution of quantum computation procedures. A block containing at least 1010 nanotriggers that act as q-bits in quantum computation and are generated using graphene nanoribbons and controlled by a specific element is included in the device. The latter is a self-organizing quantum dot with two essentially different magnetic states. This quantum dot is made from a compound whose molecules are distinguished by intramolular rearrangement. Nanotriggers are used to create reversible logic gates or blocks. Three triggers are included in each gate to perform logical operations. The offered device is an additional electronic unit implanted in a digital computer that allows the computational process to be implemented in accordance with the requirements of quantum physics.
GOVT_EXAM ONTOLOGY IN SEMANTIC WEB FOR QUERY RETRIEVAL

The World wide web is growing day by day exponentially and it becomes difficult to find the relevant information even using efficient search engines. Search results always give lots of irrelevant data which often misled to actual needed information. One solution of this problem is semantic web which was proposed by Sir Tim Berner’s Lee. Semantic web is an extended version of World Wide Web that has opened the new doors for efficient information retrieval process. Ontology is one of the methodologies to implement the semantic web. In this paper govt exam ontology is created with the help of protégé ontology creation tool. In the given ontology various relationship between different govt exams of central and state level is provided and also the general information about these exams like exam type, subject level of exam and institutes for coaching is given. This domain specific ontology can help the potential information seeker to get the accurate information which can help to crack the exam.
Search guidance from the relative arrangement between objects

Objects do not exist in isolation; they exist in relation to each other. Recognizing that a printed Journal of Vision article is below a desk lamp is thought to require a focal shift of attention between objects (Franconeri, et al., 2012). Relatedly, target object pairs produce highly inefficient search slopes when distractors only differ by their relative arrangement (X above Y, vs. X below Y), suggesting a serial process and no attentional guidance (Logan, 1994). Rather than searching for an article below a lamp, observers might search for the features of an article and/or a lamp, then check their relative arrangement. We tested these hypotheses across two experiments that recorded eye movements and used previewed random pairs of trial-unique real-world objects. Experiment 1 asked participants to search for object pairs that only differed from distractors in their relative arrangement, preventing target-feature guidance from individual objects; guidance would rather require a holistic representation that captures the relative arrangement. Experiment 2 asked participants to search for target pairs among heterogeneous pairs of distractors, which allows target-feature guidance from individual objects. The targets relative arrangement was swapped on half of the trials (indicating target absence). Above chance search guidance in Experiment 1, and significantly more guidance for matched relative to swapped targets in Experiment 2, argues for small but significant search guidance based on the relative arrangement of objects (operationalized as the proportion of trials where the target pair was fixated first, and the number of distractors fixated before the target; all p < .05). We conclude that the computation of relative object arrangement may not be strictly serial, and that it is possible to extract and use a relative-object-arrangement feature to guide search. Future work will explore related features that generate small amounts of guidance in other highly inefficient searches.
Preferred Explanations of Algorithmic Decision-Making Systems in the Dutch Property & Casualty Insurance Industry

There are multiple challenges relating to the explainability of algorithmic decision-making (ADM) systems, such as that there is not a clear consensus on what a ‘good’ explanation is and what sort of explanation fit the different types of ADM-systems. Therefore, in this research, the Delphi-method was used to study which explanation would fit the different types of ADM-systems best. This was done in the Dutch property & casualty insurance industry. This report will show that often the data that is used to reach a decision should be included in the explanation because of the privacy perspective. Also, for most ADM-systems in this study, can be said that the general idea behind the algorithm and/or data should be included in the explanation. The main conclusion, however, is that there is not a one-size-fits-all explanation for ADM-systems and that it depends on the type of ADM-system, for what it is used and in which social context.
Accurate Intrusion Detection Based On Feature Optimization Using Plant Grow Algorithm

The process of features reduction enhanced the performance of the intrusion detection system. Nowadays used various features reduction algorithms are used for static as well as dynamic features reduction. The feature reduction technique behaves in dual mode. The reduction of features cannot have fixed how many features are reducing for the better detection process of intrusion. The process of features reduction used plant grow optimization algorithm and classification using support vector machine algorithm.
A Comparative Analysis of NAEA English Reading Passages for Middle and High School Students Using Coh-Metrix

This study aims to identify differences of English reading passages in the National Assessment of Educational Achievement (NAEA) for middle and high school students. For this study, 208 NAEA English reading passages from the five consecutive years from 2015 to 2019 were extracted. The two research questions consider the differences of two tests, and correlations among the selected Coh-Metrix indices such as descriptive measures, lexical characteristics, syntactic complexity, discourse patterns, and readability level. The extracted reading passages were analyzed based on 17 selected Coh-Metrix indices related to each selected index. As for the differences of two tests, descriptive measures, lexical difficulty and readability level showed clear differences, whereas lexical diversity, syntactic complexity, and discourse patterns did not present critical gaps between the two tests. As for the correlations, the positive correlations between readability level and descriptive measures were inevitable in that the way to estimate the Flesch Reading Ease score and the Flesch-Kincaid Grade Level is based on the average number of syllables per word and words per sentence. Lexical diversity was negatively correlated to all the indices of discourse patterns. The implications and limitations of the current study are included.
A Dynamic Topic Identification and Labeling Approach for COVID-19 Tweets

This paper formulates the problem of dynamically identifying key topics with proper labels from COVID-19 Tweets to provide an overview of wider public opinion. Nowadays, social media is one of the best ways to connect people through Internet technology, which is also considered an essential part of our daily lives. In late December 2019, an outbreak of the novel coronavirus, COVID-19 was reported, and the World Health Organization declared an emergency due to its rapid spread all over the world. The COVID-19 epidemic has affected the use of social media by many people across the globe. Twitter is one of the most influential social media services, which has seen a dramatic increase in its use from the epidemic. Thus dynamic extraction of specific topics with labels from tweets of COVID-19 is a challenging issue for highlighting conversation instead of manual topic labeling approach. In this paper, we propose a framework that automatically identifies the key topics with labels from the tweets using the top Unigram feature of aspect terms cluster from Latent Dirichlet Allocation (LDA) generated topics. Our experiment result shows that this dynamic topic identification and labeling approach is effective having the accuracy of 85.48\% with respect to the manual static approach.
A computational investigation of the relationship between lexical sophistication and writing competence using the automatic analysis of lexical sophistication program

This study explores the relationship between newly developed indices of lexical sophistication and essay scores written by Asian college students. The study employs the Tool for the Automatic Analysis of Lexical Sophistication(TAALES) program. A total of 440 essays written by EFL students from Korea, China, Japan, Thailand, Taiwan, and Indonesia were selected from the ICNALE(International Corpus Network of Asian Learners of English) corpus. The following two research questions were addressed. First, what is the best lexical sophistication predictor of essay scores? Second, what are differentiating lexical sophistication indices among high-, mid-, and low-level EFL students? Two statistical analyses such as the stepwise regression analysis and the discriminant function analysis were performed using the SPSS version 26.0. Results showed that ‘age of acquisition content words’ turned out the best predictor of essay score, indicating that essays with content words that on average are perceived to be learned later received higher scores. Also, two multiword units such as ‘COCA magazine trigram strength of directional association’ and ‘COCA magazine bigram mutual information’ contributed to distinguishing among EFL students with different English proficiency levels. Therefore, EFL students who produced two-word and three-word phrases with stronger associations were classified as the high proficiency group, hence judged to be more proficient in writing.
Securing Logins in Electronic Examination Systems for Tertiary Institutions Using Quick Response Code (QR) Technology and Multiple Hashing Algorithms

This work is aimed at adding an extra layer of security to the login process of an electronic examination system as security has been identified as one of the critical success factors in the management of such exams. It proposes to secure the login process of an e-exam system through authentication and encryption to control access and avoid impersonation. A model of the e-exam system with Quick Response (QR) code generation capability was designed where a student’s matriculation number is accepted as input which is then converted into a two-dimensional bar code using a QR generator. Outputs from the QR code generator are then secured by encryption using MD5 and SHA-224 encryption algorithms. MD5 algorithm produces a 32-bit hash value which is further encrypted using SHA-224 that produces a resulting 56-bit hash value that is then saved in the password column of the user table in the database. This research resulted in a secure and web-based electronic examination authentication system implemented and tested on a client-server architecture. Performance evaluation of the developed system revealed that it is fast and effective, capable of authenticating students in an average of 0.624 seconds when the smartphone flashlight is off, and 0.318 seconds with flashlight turned on and consequently, resistant to brute force attacks. This paper fulfils an identified need to develop an electronic exam system that not only secures the question bank but equally ensures the security of the login process as well as the login details using a combination of two security techniques.
Determining Minimal Cost of Action for Task Allocation Within Mobile Robot Swarm in Production Environments

This paper describes the continuation of a series of research in which human behavior, in the form of models and algorithms, endeavor to be mapped into the field of mobile robotics, all with the aim of more efficient path prediction with collision detection in a dynamic obstacle environment. In our latest research [] we proposed a new approach called Sliding Holt (SH) algorithm which is used for calculation of future spatiotemporal state of dynamic obstacle. Besides SH algorithm we also proposed method for (non)collaborative collision detection with dynamic obstacles in 2D and 3D space which ensures full de-centralization of the collision detection process. Research described in this paper focuses on the application of Computer Vision for detecting the position and movement direction of mobile robots in order to create assumptions for collision detection and path planning with within the production environment. We propose a new approach for detecting mobile robot direction based on triangular shape and use of Cost of Action in order to allocate tasks within robotic swarm.
Wolf Optimization Based Web Page Prediction Using Weblog and Web Content Feature

Website depends on user visits. To increase the user engagement on site web portals are working on page prediction algorithms. Many of researchers are working on this issue from last two decades. This paper has proposed a web page prediction model using web log feature. Raw weblog feature was pre-processed by applying Markova model with hierarchical structure. Markov model gives web page pattern with support value. User next web page prediction was done by wolf optimization genetic algorithm. Web mining known weblog and web content feature were used for obtaining the probability density value of web pages. This feature help algorithm to identify page having high opening probability. Wolf algorithm fitness function highly depends on this probability density function for selection of good chromosome in current population. Experiment was done on real weblog dataset. Results were compared with existing model on different evaluation parameters.
Large-scale quantum photonic processors: photonics for AI and AI for photonics

Photons play a central role in many areas of quantum information science, either as qubit themselves or to mediate interactions between long-lived matter based qubits. Techniques for (1) high-fidelity generation, (2) precise manipulation and (3) ultra-efficient detection of quantum states of light are therefore a prerequisite for virtually all quantum technologies. A quantum photonics processor is the union of these three core technologies into a single system, and, bolstered by advances in integrated photonics, promises to be a versatile platform for quantum information science. In this talk we present recent progress towards large-scale quantum photonic processors, leveraging the platform of silicon photonics. We demonstrate how quantum photonic processors can accelerate both quantum and classical machine learning, and how optimization techniques can enhance large-scale quantum control.
Neural Machine Translation in Low-Resource Setting: a Case Study in English-Marathi Pair

In this paper and we explore different techniques of overcoming the challenges of low-resource in Neural Machine Translation (NMT) and specifically focusing on the case of English-Marathi NMT. NMT systems require a large amount of parallel corpora to obtain good quality translations. We try to mitigate the low-resource problem by augmenting parallel corpora or by using transfer learning. Techniques such as Phrase Table Injection (PTI) and back-translation and mixing of language corpora are used for enhancing the parallel data; whereas pivoting and multilingual embeddings are used to leverage transfer learning. For pivoting and Hindi comes in as assisting language for English-Marathi translation. Compared to baseline transformer model and a significant improvement trend in BLEU score is observed across various techniques. We have done extensive manual and automatic and qualitative evaluation of our systems. Since the trend in Machine Translation (MT) today is post-editing and measuring of Human Effort Reduction (HER) and we have given our preliminary observations on Translation Edit Rate (TER) vs. BLEU score study and where TER is regarded as a measure of HER.
About the unification type of $\mathbf {K}+\square \square \bot $

The unification problem in a propositional logic is to determine, given a formula φ, whether there exists a substitution σ such that σ(φ) is in that logic. In that case, σ is a unifier of φ. When a unifiable formula has minimal complete sets of unifiers, it is either infinitary, finitary, or unitary, depending on the cardinality of its minimal complete sets of unifiers. Otherwise, it is nullary. In this paper, we prove that in modal logic $\mathbf {K}+\square \square \bot $ , unifiable formulas are either finitary, or unitary.
Digital Literation in Increasing Reading Interest and Overcoming Hoax News from Social Media in Basic School Students

Digital literacy is one of the reading movements that elementary school students must have in the 21st century. Social media allows students to be actively involved in increasing the reading interest of elementary school students to obtain new information. The role of digital use in today's modern era is very effective and efficient to increase reading interest, but in the context of language learning, teachers still have to be guided by using social media facilities so that students don't fall into consuming hoax or fake news. From the hoax news that is spread, researchers suspect that increasing reading interest from social media through digital literacy has a very big effect. This study aims to determine and analyze the relationship between digital literacy and reading interest from social media in dealing with hoax stories of elementary school students. The method used in this research is literature study or literature study. The results showed that in general, the application of digital literacy was able to increase reading interest in overcoming hoax news from social media. Furthermore, suggestions from researchers so that students have good reading interests need to be trained continuously by applying digital literacy in elementary schools.