Reviewerly/exHarmony huggingface dataset:
Self Intelligence with Human Activities Recognition based on Convolutional Neural Networks

In the presented paper, we propose a strategy related to activity recognition of human from profundity maps as well as sequences stance information using convolutional neural systems. Two information descriptors will be utilized for activity portrayal. The main information is a depth movement picture which will store back to back depth motion images of a human activity, whilst the subsequent data is the proposed moving joint description feature which conveys the movement of joints after time instants. To boost highlight extraction for precise activity arrangement, we will use three networked channels prepared with different inputs along with hypothesis verification. The activity results produced from those channels are intertwined for last activity characterization. Here, we suggest a few combination score based tasks to amplify the weightage of the correct activity. The experiments reveal the aftereffects of intertwining the yield of those channels along with the hypothesis are superior to utilizing a single channel or intertwining more than one channel in particular. The technique was assessed on two open databases which are Microsoft activity dataset and the second one is taken from University of Texas . The results demonstrate that our method beats the vast majority of existing cutting edge techniques, for example, histogram of arranged 4-D normal in datasets. Albeit DHA dataset has high number of activities (38 activities) contrasted with existing activity datasets, our paper outperforms a cutting edge strategy on the dataset by 6.9%.
The Students Perception on the Use of E-Book as Learning Sources at The Sixth Semester Students of English Education Study Program of Baturaja University

The purpose of this study was to find out the students perceptions on the use of e-book as learning sources at the sixth semester students of English Education Study Program of Baturaja University.The population of the research was 22 students majoring in English study program. The writer took 22 students by using total sampling.This study used descriptive qualitative method and the data was collected by using questionaire. The questionnaire consists of 20 items in the form of five likert scale. The result of the study showed that 92.90% students had positive response and support e book as learning sources. It indicated that e book was easy to use. By using e book the both students and lecturers can improve their creativity.
Analysis of Items with Item Response Theory (IRT) Approach on Final Assessment for Al-Quran Hadith Subjects

Measurement in the field of education, especially the teaching and learning process can be done with measuring tools in the form of tests and non-tests. Islamic Religious Education is considered the same as other subjects. to realize student success is also measured through evaluation, which is a systematic process to obtain information about the effectiveness of teaching and learning activities. In addition, it can also assist teachers in achieving learning objectives and describe student achievement in accordance with predetermined criteria. This study aims to analyze the Year-End Assessment of MAN 2 Bantul for the 2020/2021 academic year consisting of 25 multiple-choice questions. The items analyzed in the report have a total number of responses of 265 students. Item analysis using analysis with modern test theory ( Item Response Theory ). The results showed that the results of the model fit test showed that the instrument fit on the 2 PL model (Logistics parameter) with the lowest AIC value, namely 4874.85. The results of the parameter analysis of the level of difficulty indicate that there are 4 questions that are categorized as very easy, 4 easy questions, 15 moderate questions, 1 difficult question, and 1 very difficult question. This shows that the distribution of the difficulty level parameters is quite balanced. The results of the analysis of the different power parameters show that there are 23 good questions, 1 fairly good question, and 1 bad question. This shows that the different power level parameters are quite good. The results of the estimation of students' abilities with the MLE estimator showed that there were no students who had abilities below -4. There are 15 students with abilities above 2.00. There are 165 students who fall into the good category (ability -2 to 2 and 9 students who have abilities below -2. Based on the plot of the information function, it can be concluded that the optimal test if given to individuals with low abilities is around -1.2. Accurate questions to measure students' abilities with a range of -2.5 to 1.2.
Pengembangan Media Focusky pada Pembelajaran Teks Iklan di Kelas VIII SMP

This study aims to: (1) describe and develop focusky media on ad text learning in grade VIII and (2) describe the feasibility of focusky media development on ad text learning in class VIII.  This type of research is research and development (R&D). The model used is Borg &Gall with 10 stages of development but only up to the feasibility due to the Covid-19 pandemic, then into 4 stages of development. The 4 stages consist of (1) conducting research and data collection, (2) planning, (3) product development, and (4) early stage field trials. The subject of this study was a grade VIII junior high school student.  Based on the 4 stages of the study, validation results were obtained to experts. Based on the results of validation tests to media experts, obtained as much as 66.3% with the category Valid (before revision) and as much as 72% with the category Valid (after revision). Based on validation tests to material experts, obtained as many as 89.58% with category Very Valid. Based on the trial to students, obtained as much as 92.27% with the category Very Valid.  Based on the results of the validation test, focusky media development worth using.
Integration of Geological, Geochemical, Mineralogical and Remote Sensing Data for Studying Zeolite Deposits of Al-Ahyuq-Taiz, Yemen

Abstract: Zeolite deposits crop out at Al-Ahyuq area, and lies at about 89 km southwest of Taiz city. It is one of the most important zeolite localities in Yemen. The study area is covered by the Yemen volcanic group. X-Ray Diffraction (XRD) analyses showed that clinoptilolite is the major type of Al-Ahyuq zeolites with high purity. Chemical analysis shows that the studied zeolitic tuff samples have silica content ranging from 63.10 wt% - 71.1wt% with an average 68.69 wt%, Fe2O3 [as total iron] with an average 2.38wt%, MgO with an average 0.44 wt% and TiO2 with an average 0.17wt%. These chemical properties of Al-Ahyuq zeolite deposits are with low impurities content such as CaO and MgO, compared to those deposits found in other countries around the world. The chemical and mineralogical studies support that the zeolite minerals of the Al-Ahyuq area formed by subaerial hydrothermal alteration of the parent volcanic glass. The ASTER bands as false colour composite (1-R, 2-G, 3-B), and band ratios 3/9 and 4/6 highlighted area of zeolite deposits dominated as bright pixels. The band ratio combination 4/6-R, 2/1-G and 3/2-B is effective in mapping of Al-Ahyuq zeolitic tuffs. Spectra after being resampled to ASTER VNIR+SWIR bands of the study area comparing with the USGS library spectra of zeolite – clinoptilolite shows almost identical and confirmed that clinoptilolite is the major of zeolite deposits in Al-Ahyuq area. Chemical and mineralogical investigation of the Al-Ahyuq zeolite (clinoptilolite) deposits recommends many important agricultural, environmental, and industrial applications. Keyword: Zeolitic tuff; clinoptilolite; XDR; XRFS; ASTER data; band ratio
Bi-RDNet: Performance Enhancement for Remote Sensing Scene Classification with Rotational Duplicate Layers

We propose compact and effective network layer Rotational Duplicate Layer (RDLayer) that takes the place of regular convolution layer resulting up to 128\(\times \) in memory saving. Along with network accuracy, memory and power constraints affect design choices of computer vision tasks performed on resource-limited devices such as FPGAs (Field Programmable Gate Array). To overcome this limited availability, RDLayers are trained in a way that whole layer parameters are obtained from duplication and rotation of smaller learned kernel. Additionally, we speed up the forward pass via partial decompression methodology for data compressed with JPEG(Joint Photograpic Expert Group)2000. Our experiments on remote sensing scene classification showed that our network achieves \(\sim \)4\(\times \) reduction in model size in exchange of \(\sim \)4.5\(\%\) drop in accuracy, \(\sim \)27\(\times \) reduction with the cost of \(\sim \)10\(\%\) drop in accuracy, along with \(\sim \)2.6\(\times \) faster evaluation time on test samples.
Quantum for Social Good : Ethical Qubits and the Regulatory State

For this panel on the ethics of quantum technologies, I offer provocations that imagine the future of policy and governance, specifically regulation. In this talk I ask : How will we evaluate quantum computing outcomes in social contexts? Regulatory and policy regimes rely on stable measurements that quantum technologies destabilize. Governments create many such boundaries that separate legal from illegal based on quantitative thresholds, like a speed limit. Society is alerted to problems through measurements that allow for common statistical and mathematical methods to make comparisons. Quantum technology outcomes are not reducible to their inputs which seriously limits the ability of governments to identify ethical or operational problems. If we are going to have quantum for social good, I suggest that we push our thinking and vocabulary further. My second provocation calls for a theoretical leap into this new realm with an ethical qubit, or quantum bit. This could move beyond binary thinking linked to Newtonian physics and limits to moral imaginations. If a bit is based on 1s and 0s, and a quantum bit is the probability of 1s and 0s, could we imagine probabilistic assessment of the potentiality of beneficence? Maybe a quantum ethical turn dispels the governing compulsion to control through binary categories. Quantum for the social good is waiting for developments in social theory.
Insurance for Social Media Liability

Whether a claim involves “bodily injury” or “property damage” is a threshold issue for coverage under Coverage A of the standard comprehensive general liability (CGL) policy and homeowners policy. Social media-related claims that allege pure emotional distress, without corresponding physical manifestations, or that allege damage to intangible property, such as intellectual property rights, may not fall within the insuring agreements of these policies. Social media claims often allege intentional conduct, if not intentional harm, which raises the threshold issue of whether the claim alleges an “occurrence” such that coverage is triggered. To the extent a social media claim falls within the policies’ insuring agreements, the next issue is whether the policies contain exclusions that might apply. Exclusions for expected or intended injury, employer’s liability, and electronic data may limit coverage for social media claims. Likewise, exclusions in homeowners policies for “bodily injury” or “property damage” arising from a home business, professional services, or physical or mental abuse may apply to common social media claims.
Fuzzy inference: rule based and relational approaches

A fuzzy modeling system or a fuzzy controller can be implemented by understanding sampled valued variables, translated from the real-life world into a fuzzy domain. The model or the controller will estimate an output, either for a decision-making action or to impose a set-point in a closed-loop control system. Those processes are defined as “fuzzification,” i.e., going through the membership functions of the input data into fuzzy sets and their corresponding pertinence degrees to those sets, through a “fuzzy processing” or also called inference engine; and “defuzzification,” i.e., it is a transformation from such a fuzzy evaluation into crispy variables, ready for control, or modeling analysis (Yen, 1999). Such a methodology could be compared to have a phasor domain analysis, or a Laplace domain analysis. Fuzzy data processing requires to be done in the fuzzy domain with proper direct and inverse transformations.
MINING SIMILAR PATTERN WITH ATTRIBUTEORIENTED INDUCTION HIGH LEVEL EMERGINGPATTERN (AOI-HEP) DATA MINING TECHNIQUE

AOI-HEP (Attribute Oriented Induction High Emerging Pattern) as new data mining technique has been success to minefrequent pattern and is extended to mine similar patterns. AOI-HEP is success to mine 3 and 1 similar patterns from IPUMSand breast cancer UCI machine learning datasets respectively. Meanwhile, the experiments showed that there was nofinding similar patterns on adult and census UCI machine learning datasets. The experiments showed that finding AOI-HEPsimilar pattern in dataset is influenced by learning on chosen high level concept attribute i n concept hierarchy and it isapplied to AOI-HEP frequent pattern in previous research as well. The experiments chosed high level concept attributessuch as workclass, clump thickness, means and marts for adult, breast cancer, census and IPUMS datasets respectively. Inorder to proof that the chosen high level concept attribute will influences the AOI-HEP similar pattern in dataset, thenextended experiments were carried on and the finding were census dataset which had been none AOI -HEP similar pattern,had AOI-HEP similar pattern when learned on high level concept in marital attribute. Meanwhile, Breast cancer which hadbeen had 1 AOI-HEP similar pattern, had none AOI-HEP similar pattern when learned on high level concept in attributessuch as cell size, cell shape and bare nuclei. The 2 of 3 finding Similar patterns in IPUMS dataset have strong discriminantrule since having large growth rates such as 1.53% and 3.47%, and having large supports in target dataset such as 4.54%and 5.45 respectively. Moreover, there have small supports in contrasting dataset such as 2.96% and 1.57% respectively.
Glimpse-Attend-and-Explore: Self-Attention for Active Visual Exploration

Active visual exploration aims to assist an agent with a limited field of view to understand its environment based on partial observations made by choosing the best viewing directions in the scene. Recent methods have tried to address this problem either by using reinforcement learning, which is difficult to train, or by uncertainty maps, which are task-specific and can only be implemented for dense prediction tasks. In this paper, we propose the Glimpse-Attend-and-Explore model which: (a) employs self-attention to guide the visual exploration instead of task-specific uncertainty maps; (b) can be used for both dense and sparse prediction tasks; and (c) uses a contrastive stream to further improve the representations learned. Unlike previous works, we show the application of our model on multiple tasks like reconstruction, segmentation and classification. Our model provides encouraging results while being less dependent on dataset bias in driving the exploration. We further perform an ablation study to investigate the features and attention learned by our model. Finally, we show that our self-attention module learns to attend different regions of the scene by minimizing the loss on the downstream task. Code: this https URL.
AS CRIPTOMOEDAS COMO VETOR DE DESENVOLVIMENTO ECONÔMICO E TECNOLÓGICO DAS CIDADES LOCALIZADAS NA REGIÃO DO MEIO OESTE CATARINENSE

The advancement of technology present in social, cultural and industrial areas has also arrivedin the economic area. As technology seeks solutions to major existing problems,the newest invention for the economic and financial industry is cryptocurrencies. For that,the following research aims to develop a study on how cryptocurrencies can generatea positive development on the economy and technology of Midwestern citiesSanta Catarina. For this, the following research first presents a reviewbibliographical, where through books, articles and texts published by experienced authors,the writers of this article sought to acquire and expand knowledge related todigital coins in order to conceptualize and explain the main topics andcryptocurrency issues. As a subsequent step, there is the development ofresearch, which presents the entire process that was developed and improved throughoutof time, covering issues related to the construction and application of the questionnaireinterviewees. After the application of the first questionnaire, the dissemination of theknowledge, where through an explanatory video, the authors of this researchconveyed to the participants the main concepts involving cryptocurrencies.Having, this time, a greater knowledge about digital currencies, the intervieweeswere able to answer the same questionnaire again, with this, the authors were able tomeasure the degree of knowledge acquired through the dissemination of knowledge made.for them. Following this research, the results obtained with thestudy, being exposed through graphics and images that prove the veracity of thesearch. The results were discussed in the penultimate part of the article, where it waspresented the evolution of knowledge of the inhabitants of the Midwest of Santa Catarina towith the cryptocurrencies. Finally, the conclusion of the work was presented, which provedthat the methodologies used in the research are adequate for comparisonof the study related to cryptocurrencies.
Revisiting consistency of a recursive estimator of mixing distributions

Estimation of the mixing distribution under a general mixture model is a very difficult problem, especially when the mixing distribution is assumed to have a density. Predictive recursion (PR) is a fast, recursive algorithm for nonparametric estimation of a mixing distribution/density in general mixture models. However, the existing PR consistency results make rather strong assumptions, some of which fail for practically relevant mixture models. In this paper, we first develop new consistency results for PR under weaker conditions and then we apply this theory in the important case of mixtures of scaled uniform kernels.
Bad Smells in Javascript - A Mapping Study

Javascript is one of the most famous mainstream programming languages nowadays. It has gained considerable practical relevance over the last years, with applications in several areas, such as games, 3D rendering, and, mainly, web development. Like any other software system, systems developed in Javascript need to keep their ability to evolve to remain useful and relevant over time. Empirical evidence has shown that bad smells are possible indicators of problems hindering software evolvability. In this context, this paper presents a mapping study investigating if and to what extent bad smells have been defined for the Javascript language and how the interest in this topic has evolved. Our study identified 26 different types of bad smells investigated in the context of Javascript in 8 different works published between 2013 and 2020. This result suggests that although Javascript has gained practical relevance in recent years, there is still room for further empirical studies defining and evaluating the impact of bad smells on Javascript-based software systems.
On computations with Double Schubert Automaton and stable maps of multivariate cryptography

AbstractÐThe families of bijective transformations Gn of affine space K n over general commutative ring K of increasing order with the property of stability will be constructed.Stability means that maximal degree of elements of cyclic subgroup generated by the transformation of degree d is bounded by d.In the case K = Fq these transformations of K n can be of an exponential order.We introduce large groups formed by quadratic transformations and numerical encryption algorithm protected by secure protocol of Noncommutative Cryptography.The construction of transformations is presented in terms of walks on Double Schubert Graphs.
Overview of Sql Injection

SQL Injection is a major injection technique, which is used to attack data-driven Applications.Procedures and functions that use dynamic SQL queries by concatenating the text inputs to the dynamic SQL are prone to SQL Injection attack as someone can provide extra commands/malicious text through the input parameter and when executed can result in the unexpected results.
Digital Transformation and Educational Innovation in Latin America in the Framework of Covid-19

A documentary review is carried out regarding the production of scientific publications on the variables Digital Transformation and Educational Innovation in the framework of Covid-19, in order to know the main characteristics of the volume of publications indexed in Scopus database with a total of 164 documents, platform through which the survey of data that allow through the distribution by year of publication, country of origin, area of knowledge and type of publication, highlight relevant aspects as well as identify some examples to know the position of different authors against the proposed topic. The methodology used corresponds to a quantitative analysis of the data on the volume of scientific production, with a bibliometric study, and qualitative analysis of the research works cited in the body of this document. Among the main findings, it is highlighted that in terms of research on Digital Transformation and Educational Innovation in the context of the pandemic generated by Covid-19 in the educational field, Brazil is the Latin American country with the highest number of publications, registering a total of 55 documents. The area of knowledge with the highest number of contributions to publications was Social Sciences with 101 publications, and of the total number of research papers identified, 70% correspond to Journal Articles.
Blockchain and Darwin

Innovative forces are constantly colliding within the blockchain ecosystem (Section 1). As a result, one may observe two distinct types of blockchains: monocentric and platform ones. The second type allows three different applications, cryptocurrency, smart contracts, and others. It all results in a very dynamic Darwinian ecosystem that has already revealed some competitive trends (Section 2). For that reason, I must start by addressing his findings.
投影辅助的数字剪切散斑干涉扫描检测技术

Digital shearography has been widely used in non-destructive testing of composite materials. But the conventional detection area is limited and the defect detection of large-size composite materials is difficult to achieve. A digital shearography assisted with projection scanning detection for large-size composite materials was introduced. Based on digital shearography and the auxiliary projection which could project additional surface features, global matching and coordinate unification of the sub-view original images and the speckle interferograms were calculated by the homography matrix of the corresponding projection images to realize the multi-field scanning and matching stitching of projection, origin, and interferogram images. At the same time, a 4f optical path and an ultra-wide-angle lens were imported for the one detection to expand the detection area. Experimental results show that the scanning detection system can achieve more accurate measurement of the defect position and size. The root mean square error of location positioning is 7.0 mm, and the root mean square value of dimension measurement error is 4.9 mm. At a working distance of 1.2 m, the single detection area can reach 600 mm×500 mm and the global scanning detection area can reach 3.5 m×4.0 m. This method has the advantages of strong resistance to rigid body displacement interference and high sensitivity of defect detection, which is suitable for non-destructive testing of large-size and high performance composite materials.