Reviewerly/exHarmony huggingface dataset:
Kearifan Lokal Masyarakat Penambang Minyak Tradisional dalam Bahasa dan Budaya Jawa di Desa Wonocolo Kabupaten Bojonegoro

This study aims to identify and describe the cognition system (cognition system) and local wisdom (local wisdom) in oil mining which is traditionally managed by the people of Wonocolo Village, Bojonegoro Regency.&#x0D; This study used a descriptive qualitative which is studied ethnolinguistically with ethnoscience model. The data in this study were oral data obtained when the researcher observed the participants by using interview and filled note techniques in order to obtain the data classified from predrilling process and drilling process to find out cognition system and local wisdom of it.&#x0D; Key Wordsi: Traditional Oil Mining, Local Wisdom, Ethnolinguistics
Linear-time Erasure List-decoding of Expander Codes.

We give a linear-time erasure list-decoding algorithm for expander codes. More precisely, let $r > 0$ be any integer. Given an inner code ${\mathcal {C}}_{0}$ of length $d$ , and a $d$ -regular bipartite expander graph $G$ with $n$ vertices on each side, we give an algorithm to list-decode the code ${\mathcal {C}}= {\mathcal {C}}(G, {\mathcal {C}}_{0})$ of length $nd$ from approximately $\delta \delta _{r} nd$ erasures in time $n \cdot \mathrm {poly} (d2^{r} / \delta)$ , where $\delta $ and $\delta _{r}$ are the relative distance and the $r$ ’th generalized relative distance of ${\mathcal {C}}_{0}$ , respectively. To the best of our knowledge, this is the first linear-time algorithm that can list-decode expander codes from erasures beyond their (designed) distance of approximately $\delta ^{2}~nd$ . To obtain our results, we show that an approach similar to that of (Hemenway and Wootters, Information and Computation , 2018) can be used to obtain such an erasure-list-decoding algorithm with an exponentially worse dependence of the running time on $r$ and $\delta $ ; then we show how to improve the dependence of the running time on these parameters.
Augmenting Intelligent Tutoring Systems With Intelligent Tutors

Intelligent Tutoring Systems (ITS) technology has been advertised as being one effective way of reinforcing instruction in procedural skills at the workplace. These systems offer individualized curricula with fine-grained feedback and analysis of student problems. They have been used effectively in a number of domains, from introductory programming to electronics diagnosis and repair. Distance-learning techniques offer a means of remote access to an instructor and an alternative way of delivering declarative instruction. Distance learning generally refers to remote links between an instructor and students. If the action is correct, the code appears on the screen. If the action is incorrect, error feedback is presented in the lower Interactor window. (ITS) such as Grace have generally been used to reinforce classroom or textual knowledge. One problem with these tutors is that when a student encounters difficulties on a problem or is lacking a piece of prerequisite information, the tutor cannot offer the flexible help normally available through an instructor.
MATHEMATICAL CONEPTS AND COMPUTATIONS IN REVERSIBLE EMBEDDING MECHANISMS: A THEORETICAL STUDY

Adv. Math. Sci. J. Vol. 9, No. 9 Open Access MATHEMATICAL CONEPTS AND COMPUTATIONS IN REVERSIBLE EMBEDDING MECHANISMS: A THEORETICAL STUDY G.C.P. Latha, S.S. Banu, T. Karthikeyan and N. Yuvaraj DOI: https://doi.org/10.37418/amsj.9.9.32 Full Text Abstract Abstract In the health, military, and legal sectors, the reversible watermark becomes more common. The following are considered … page AMSJ9-N9-32 Read More »
Timing Attack on Random Forests for Generating Adversarial Examples

The threat of implementation attacks to machine learning has become an issue recently. These attacks include side-channel attacks that use information acquired from implemented devices and fault attacks that inject faults into implemented devices using external tools such as lasers. Thus far, these attacks have targeted mainly deep neural networks; however, other popular methods such as random forests can also be targets. In this paper, we investigate the threat of implementation attacks to random forests. Specifically, we propose a novel timing attack that generates adversarial examples, and experimentally evaluate its attack success rate. The proposed attack exploits a fundamental property of random forests: the response time from the input to the output depends on the number of conditional branches invoked during prediction. More precisely, we generate adversarial examples by optimizing the response time. This optimization affects predictions because changes in the response time imply changes in the results of the conditional branches. For the optimization, we use an evolution strategy that tolerates measurement error in the response time. Experiments are conducted in a black-box setting where attackers can use only prediction labels and response times. Experimental results show that the proposed attack generates adversarial examples with higher probability than a state-of-the-art attack that uses only predicted labels. This suggests the attacker motivation for implementation attacks on random forests.
Moving Object in Two Dimensional Plane using Hand Gesture Recognition

This paper gives the simple technique which can be used to move anelectronic device in the 2D plane by means of the hand gesture withgood accuracy in the movement. It uses Haar Cascade method of handgesture detection which gives us a good idea of the placement of thehand using which we can move the object. It requires a simple webcamera that is needed to connect to the computer.
Justice in the genomic and digital era: a ‘different world’ requiring ‘different law’

Discoveries in the last two decades have created a ‘different world’, which requires ‘different’ laws. They have created a world where: enormous in- formation on people’s past, present and future can be extracted from DNA alone; the DNA of millions of people has already been sequenced; the cost of sequencing is around 30 million times less than in 2003; additional detailed personal information is collected from numerous sources, such as mobile phones, hospitals, bank cards; this information is shared internationally among numerous powerful private and State organisations; and use of this information can be highly profitable for these organisations. Under these conditions, current law is unable to fully protect rights such as that of data protection, privacy, a fair trial, and non-discrimination on genetics and other basis – rights valued by societies. For the law to serve its key purpose, it now must adapt (evolve) to this fast and fundamental change in the ‘environment’. In relation to protection from data misuses, as privacy (genetic and other) is not possible, laws are required which can minimise negative impact of data misuses. Key stakeholders (e.g. judges, policymakers) would need to understand how genes work and how genetic information is used in order to appreciate the urgency of updating laws and to build effective protection.
Cryptocurrencies, Eonomic and Legal Aspects (Criptomonedas, Economía y Derecho)

English Abstract: This article suggests that, while the state of the art in the Civil Law tradition is incapable of producing a coherent and transversal answer to address the regulation of cryptocurrencies, and in general, virtual goods, drafters and lawmakers should aim to produce the rules necessary to achieve narrowly defined and explicit policy goals. In the article I show the shortcomings of using the existing legal concepts to regulate cryptocurrencies, and additionally show that in practice and financially, they have not yet achieved the necessary importance to force traditional concepts used to regulate currency upon them. The argument goes in line with previous literature that claims that current suggestions to regulate cryptocurrencies do not risk inhibiting their develop- ment, but risk shallow and ineffective regulation that might damage particular actors like early-adopters or those willing to experiment with newer technologies.Spanish Abstract: En este articulo sugiero que mientras el derecho tradicional no sea capaz de generar una respuesta coherente y transversal para regular las criptomonedas, y en general, para regular los bienes virtuales, la regulacion que busque evitar su mal uso debiera ser la minima necesaria para cumplir con el objetivo de politica estrictamente definido. Todavia no hemos desarrollado las categorias conceptuales adecuadas para regular un fenomeno tan nuevo y, ademas, desde un punto de vista practico y financiero, las criptomonedas no han alcanzado importancia suficiente para justificar el esfuerzo regulatorio que las monedas tradicionales demandan. Mi argumento se suma a otras voces que han advertido que las sugerencias por regular las criptomonedas, mas que in- hibir su desarrollo, corren el riesgo de introducir regulaciones inefectivas y superficiales, que sin embargo pueden danar a actores particulares, como los nuevos adoptantes y los que quieran experimentar con las tecnologias relacionadas.
Corrections to “Non-Stationary Representation for Continuity Aware Head Pose Estimation via Deep Neural Decision Trees”

In the above article <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , the affiliation for the first author Jiang Wang needs to be corrected.
Sherlock 2: An Intelligent Tutoring System Built on the LRDC Tutor Framework

The Sherlock story began about a decade ago when our research and development team responded to the US Air Force’s need for an efficient training technology. Budget cutbacks across the armed services, as well as a shrinking pool of enlisted soldiers prompted the Air Force to look to Intelligent Tutoring Systems as a tool for training avionics technicians expediently in the skills needed to do their jobs, namely, diagnosing faults in, and repairing, faulty aircraft and the systems used to maintain them. Perhaps most importantly, the student can ask for advice at any point while troubleshooting. Sherlock provides advice at both the circuit path and individual component levels of investigation. The design of Sherlock 2 was also driven by the principles of apprenticeship learning upon which its predecessor, Sherlock, was based, that is, modeling of expert troubleshooting behavior, student-initiated coaching on the most difficult parts of the task, gradual fading of support as expertise is acquired.
Uno stacko: a game to increase the elderly cognitive function

The elderly experience physical, mental, and social decline gradually, one of which is a decline in cognitive function. Efforts to improve the cognitive function in the elderly can given by Uno Stacko game intervention. This study aimed to determine the effect of the Uno Stacko game on improving cognitive function in the elderly. This research used a quasy-experiment pre-post-test with a control group design. The sampling technique used in this study is purposive sampling. The samples in this study were 36 respondents who were divided into two groups; the treatment group (n=18) and the control group (n=18). The independent variable was the uno stacko game. The dependent variable was the cognitive function. The instrument in this study was the mini-mental state exam (MMSE) questionnaire. The data were analyzed using paired t-test dan independent t-test (α=0.05). Data analysis by paired T-test in the treatment group obtained p=0.000, which means there was an increase in cognitive function before and after the intervention of the uno stacko game, while in the control group p= 0.542, which means there was no change in cognitive function in the elderly. Independent T-test statistical test results obtained p= 0.000. Namely, there was a significant difference between the post-test of the treatment and the control group. The results of the study are an influence of the uno stacko game on the improvement of cognitive function in the elderly. Uno stacko game has powers that can stimulate aspects of cognitive function in the elderly. Nurses can apply the game as a non-pharmacological alternative therapy to improve the cognitive function of the elderly who live in nursing homes.
The Kazakh terminology recognition system in the IT field

Abstract The design and development of the Kazakh language terminology recognition platform in IT field is one of the important means for more effective use of term resources in the field. Used a conditional random field (CRF) and manual modification method in the platform and based on the characteristics of the Kazakh language itself, this paper analyzes the rules of terminology formation and related terminology identification methods as well as describes the basic framework of the term recognition platform and the workflow and main functions of the training corpus, terminology recognition, feature template and term extraction in the system.
Improvement of Co-training Based Recommender System with Machine Learning

Recommender system (RS) is an application of information filtering to recommend information or items that users like according their data. Collaborative filtering algorithm is a famous algorithm in recommender system. However, the proportion of users willing to rate is very small, which causes data sparsity and cold start problem. In this paper, machine learning (ML) technology is integrated to an existed recommendation algorithm to get a more accurate predictions during filling in the user-item matrix, which can enrich data and then alleviate data sparsity and cold start problems. Follow that a new reliable confidence measure is applied in the process of enrich data to filter noisy. The experimental result of real data shows that the accuracy of the modified algorithm is better than the original.
Preparing for a Workshop

Now that you understand how Design Thinking became an important tool in identifying problems to be solved and uncovering possible solutions, you are likely ready to use the methodology in strategy development. While some might associate Design Thinking workshops primarily with user experience (UX) design in software projects, these workshops are now also commonly used to define the full scope of the business solutions to be provided in comprehensive software and AI development projects. Your role in a Design Thinking workshop might include leading, sponsoring, or simply taking part in the workshop.
Fine-Grained Error Analysis on English-to-Japanese Machine Translation in the Medical Domain

We performed a detailed error analysis in domain-specific neural machine translation (NMT) for the English and Japanese language pair with fine-grained manual annotation. Despite its importance for advancing NMT technologies, research on the performance of domain-specific NMT and non-European languages has been limited. In this study, we designed an error typology based on the error types that were typically generated by NMT systems and might cause significant impact in technical translations: “Addition,” “Omission,” “Mistranslation,” “Grammar,” and “Terminology.” The error annotation was targeted to the medical domain and was performed by experienced professional translators specialized in medicine under careful quality control. The annotation detected 4,912 errors on 2,480 sentences, and the frequency and distribution of errors were analyzed. We found that the major errors in NMT were “Mistranslation” and “Terminology” rather than “Addition” and “Omission,” which have been reported as typical problems of NMT. Interestingly, more errors occurred in documents for professionals compared with those for the general public. The results of our annotation work will be published as a parallel corpus with error labels, which are expected to contribute to developing better NMT models, automatic evaluation metrics, and quality estimation models.
Custom datasets from 0.-A brief discussion on how to acquire and prepare data for training deep learning neural networks. Whether for sorting, recognizing objects or targeting.

A quick chat about creating custom datasets from absolute 0.  The true path between the stones. (Focusing on data acquisition and preparation. Without going into details of neural network training). A summary of what I wish someone had talked to me when I was starting ... It will be addressed from the collection of images. Criteria for image acquisition, such as ambient light control, dark areas in the image. Existence of hotspots. The importance of highlighting the points of the scene with really relevant data. Possible improvements in the quality of images collected using optical filters to alleviate major problems. Such as eliminating light reflections, enhancing or eliminating colors. What are the main filters that should always be in our toolbox? Imaging from special cameras such as infrared cameras, multispectral cameras and thermal cameras. The least I need to know about DICOMS. Do I need special and expensive software to deal with dicoms? Quantities of images to train a network. - Why do I need two thousand images if I trained my network with only one image?. Data Standardization (Microsoft COCO, Pascal VOC). Main tools (free and paid) to annotate images for object recognition and segmentation. Ok. I prepared my dataset. And now? How do I do to train? Some frameworks for network training. Image classification classification, recognition and segmentation of objects in images. Gpus. What is this? Do I need this to train? And after training? Is it mandatory to use gpus to run my project? Now I know how to train a network! I already know everything! Am I ready for the market? Only not ....
DIRECTIONS OF INNOVATIVE DEVELOPMENT OF HIGHER EDUCATION INSTITUTIONS AT THE PRESENT STAGE

In the article the author analyzes the socio-economic problems of development of innovative activity of higher educational institutions. The necessity of implementing innovative directions of the University at the present stage is shown. It is noted that in countries that have a positive development dynamics to date, a bet was made on the implementation of innovative activities and the development of high-tech technologies based on the education system. The research focuses on innovative activities of Samara University and suggests the creation of a University innovation center based on cluster development of the region. It is noted that in the context of the development of the knowledge economy, the priority task is to integrate science, industry and education on the basis of research universities. The results of integration and networking of economic entities in the region are the development of innovative activities of the university. The article also notes and analyzes such important fundamental components of modern processes as transformation, the formation of university centers for innovative development as well as many others. Particular attention is paid to the participation of Samara University in the socio-economic development of the region and federal priority development projects, such as Universities as centers for innovations creation Samara University wins the right to participate in priority projects on a competitive basis.
Computing Sentence Embedding by Merging Syntactic Parsing Tree and Word Embedding

Recent progress in using deep learning for training word embedding has motivated us to explore the research of semantic representation in long texts, such as sentences, paragraphs and chapters. The existing methods typically use word weights and word vectors to calculate sentence embedding. However, these methods lose the word order and the syntactic structure information of sentences. This paper proposes a method for sentence embedding based on the results of syntactic parsing tree and word vectors. We propose the SynTree-WordVec method for deriving sentence embedding, which merges word vectors and the syntactic structure from the Stanford parser. The experimental results show the potential to solve the shortcomings of existing methods. Compared to the traditional sentence embedding weighting method, our method achieves better or comparable performance on various text similarity tasks, especially with the low dimension of the data set.
Guide A Robot Using An Automatic Programming Technique

Artificial intelligence as a branch of computer science is related with producing applicable strategies to make computational machines intelligent. Automatic programming is an interesting research area of artificial intelligence that concerned with writing executable computer programs automatically. In this context, Genetic Programming is one of the most promising techniques, which aims to achieve the goal of automatic programming by mimicking the evolution process in nature. Among many robot navigation behaviors, the obstacle avoidance behavior is strongly desirable to make a robot able to navigate safely and smoothly in its environment. In this research, we interested in examining the ability of genetic programming to evolve a successful computer program that helps a simulator robot to avoid obstacles randomly placed in a room. The evaluation of proposed programs will include execute, observe and analysis of the robot's performance based on the applied strategy.
Constraint-Logic Object-Oriented Programming with Free Arrays

Constraint-logic object-oriented programming provides a useful symbiosis between object-oriented programming and constraint-logic search. The ability to use logic variables, constraints, non-deterministic search, and object-oriented programming in an integrated way facilitates the combination of search-related program parts and other business logic in object-oriented applications. With this work we add array-typed logic variables (“free arrays”), thus completing the set of types that logic variables can assume in constraint-logic object-oriented programming. Free arrays exhibit interesting properties, such as indeterminate lengths and non-deterministic accesses to array elements.
IMPROVING STUDENTS’ COMPREHENSION IN READING DESCRIPTIVE TEXT USING STUDENT TEAM ACHIEVEMENT DIVISIONS (STAD) TECHNIQUE

The purpose of this research is to find out how STAD technique did improve students comprehension in reading descriptive text. The action hypothesis in this research was stated that teaching reading descriptive text using Student Team Achievement Divisions (STAD) technique can improve the achievement of the eighth grade students of MTSN 2 Pontianak. Classroom action research was used in conducting this research in two cycles. The data were divided measurement test, observation checklist, and field note. The result of the implementation shows that after the researcher conducted the actions, the students reading comprehension improved as shown in the result of both the observation on the students activities during the actions and their individual quizzes mean scores. From the reading comprehension test, the mean score of the individual quiz 1 was 48.57 and the mean score of the individual quiz 2 was 75.75. Student Team Achievement Divisions technique can improve reading comprehension of main idea, details, reference and inference.