Reviewerly/exHarmony huggingface dataset:
Batch Photo Editor | Downloads | converts images in a post-editing phase in a batch (bulk, massive) way.

Batch Photo Editor | Downloads | converts images in a post-editing phase in a batch (bulk, massive) way. Allows to quantize images (color reduction) in a professional way, for responsive web pages
Determining the Domain of Postproverbials in Human Language Development Theories and Stages

Abstract Language acquisition is a fundamental phenomenon in the linguistic enterprise. Chomsky claims that, “the human brain provides an array of capacities that enter into the use and understanding of Language (the language faculty ( FL ))”. Using the descriptive approach, this paper explores, justifies, and determines the place of the human linguistic capacity to articulate and engage postproverbials vis-a-vis Chomsky’s model of grammar and few scholarly positions. This article aims at providing evidence that, compared to others; Chomsky’s idea of linguistic competence is the most appropriate account for the use and understanding of postproverbials. The study revealed that the first sentences/the intermediate proficiency stage presents humans with the capacity to develop, use, and understand postproverbials, and this attains full development at the advanced fluency stage to establish postproverbial as one of the capacities that the human brain provides, located in the FL , and that its use and understanding is consciously employed.
Survey On Dual Axis Sun Solar Tracker

In this paper, a performance analysis of dual axis solar tracker contains photovoltaic (PV) system is conducted, to evaluate the performance based on field data measurement. A dual-axis tracker with an algorithm named as maximum light detection which effectively applied on the solar energy generation system is being used. In a tropicalized country there has a massive cloud cover throughout the year, the sky condition is categorized as sunny, intermittent and gloomy. The relative results show that the system with dual axis tracker improved the energy generation significantly in possibly all sky conditions respectively.
Uncertainty-aware INVASE: Enhanced Breast Cancer Diagnosis Feature Selection

In this paper, we present an uncertainty-aware INVASE to quantify predictive confidence of healthcare problem. By introducing learnable Gaussian distributions, we lever-age their variances to measure the degree of uncertainty. Based on the vanilla INVASE, two additional modules are proposed, i.e., an uncertainty quantification module in the predictor, and a reward shaping module in the selector. We conduct extensive experiments on UCI-WDBC dataset. Notably, our method eliminates almost all predictive bias with only about 20% queries, while the uncertainty-agnostic counterpart requires nearly 100% queries. The open-source implementation with a detailed tutorial is available at https://github.com/jx-zhong-for-academic-purpose/Uncertainty-aware-INVASE/blob/main/tutorialinvase%2B.ipynb.
MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains

Given the often enormous effort required to train GANs, both computationally as well as in dataset collection, the re-use of pretrained GANs largely increases the potential impact of generative models. Therefore, we propose a novel knowledge transfer method for generative models based on mining the knowledge that is most beneficial to a specific target domain, either from a single or multiple pretrained GANs. This is done using a miner network that identifies which part of the generative distribution of each pretrained GAN outputs samples closest to the target domain. Mining effectively steers GAN sampling towards suitable regions of the latent space, which facilitates the posterior finetuning and avoids pathologies of other methods, such as mode collapse and lack of flexibility. Furthermore, to prevent overfitting on small target domains, we introduce sparse subnetwork selection, that restricts the set of trainable neurons to those that are relevant for the target dataset. We perform comprehensive experiments on several challenging datasets using various GAN architectures (BigGAN, Progressive GAN, and StyleGAN) and show that the proposed method, called MineGAN, effectively transfers knowledge to domains with few target images, outperforming existing methods. In addition, MineGAN can successfully transfer knowledge from multiple pretrained GANs. MineGAN .
Internet of Things (IOT)-A Smart Solution To Run The college Management Information System

The Internet of Things (IoT) is a collection of interconnected physical devices that can monitor, report on and send and exchange data. IoT devices are typically connected to computer systems via data or Wi-Fi networks.This is paper is emphasis on the college management information system.Now a days almost all the education institute are maintaining software to maintain the big data of the institute for the implementation of e-governance in areas of operation like, planning and development, Administration, human Resource management system, finance and accounts, students admission and support, examination and Library management. The Internet of things is play major role to maintain such kind of system in effective manner.
HOW TO STILL RECOGNIZE THE PERIODIC TABLE OF ELEMENTS: THE PROPOSALS OF DIDACTIC AND METHODOLOGICAL PLANNING

The methodical approach presents the proposals of didactic-methodological planning of curriculum password "Fields in the periodic system" for the needs of the key components of teaching &amp; learning process. The didactic-methodological proposal of each of the current macro-didactic components of the learning process includes the following didactic elements: chemical terms, method / method’s password, didactic tool, didactic material. For each macro-didactic component, it is planned to use one of the methods from the author's "methodic hexaplet", defined by the didactic formula ADDGPS: Analogy-Drama-Dance-Game-Pantomime-Socratic dialogue. The dance method is used to acquire the concepts of atomic orbitals and electronic configurations of the elements. The macro-component repeating involves the role-play method used to implement the Expeditionary Visit of PTE by using the Identity card of the element. Both methods of quiz conversation method according to Socrates and the Small PTE cells are used for evaluation. The use of all the mentioned methods is evaluated in terms of the competencies that must be mastered by the teacher, as well as the competencies that the student acquires when performing an individual method. Keywords: Periodic table of elements; chemical terms; ADDGPS methods (Analogy-Drama–Dance-Game-Pantomime-Socratic dialogue)
Document Forgery Detection for Admission Process using CNN Algorithm

The recent advancement in technology in the usage of image processing tools and applications has led to increased criminal activities in fraudulent and forging documents and digitally manipulating them. The use of tools like Adobe Photoshop, GNU Gimp to create manipulated fraud documents is a major concern for the government in this digital era. It is extremely crucial to detect image forgery and manipulation done by computer in these documents. This proposed system focusses on the use of image processing techniques and algorithms along with machine learning to detect the forgery and image manipulation done in a admission document which is used for admission in most states. A Convolutional Neural Network (CNN) is being adopted to extract the features from the image of the document to analyse it further and classify it. The image of the document extracts features like brightness of pixel and the font format and the resolution of image. These features provide us with details to analyse the similarity between the digital forged images and enable us to develop an algorithm to detect and manipulation in digital images and tampering in documents.I.
Coupling purposes with status-functions in artificial institutions

In multi-agent systems, the agents may have goals that depend on a social, shared interpretation about the facts occurring in the system. These are the so-called social goals. Artificial institutions provide such a social interpretation by assigning statuses to the concrete elements that compose the system. These statuses are supposed to enable the assignee element to perform functions that are not exclusively inherent to their design features. However, the enabled functions are not explicit in the existing models of artificial institutions. As a consequence, (i) agents may have difficulties to reasoning about how to achieve their own social goals with the help of artificial institutions and (ii) these institutions are not well instrumented to receive incoming agents, in the case of open systems. Considering those problems, this paper proposes a model to express the functions -- or the purposes -- associated with the status-functions helping the agents to reason about their social goals and the institution. We evaluate the model by using it in some scenarios, showing how the agents can use purposes to reason about the satisfaction of their social goals in institutional contexts and how the institution can be flexible enough to support new agents operating in the system.
El Covid-19 y la escuela en casa

The human being faces a global threat, COVID 19, for which, until today, there is no vaccine, which has forced people who work in nonessential activities to seclude themselves in a confinement at their home. School authorities implemented The School at Home Program, which brought unprecedented situations and problems to solve.
Convert PDF to Audiobook using OCR (Optical Character Recognition) and Machine Learning

Reading stories or essays or any text can be onerous, however an audio reading of the text is convenient and doesn’t require as much concentration as reading requires. And here comes the talking book known audiobook. An audiobook allows a person to listen to a recording of the text of the book, rather than read the text of the book. Audiobooks have traditionally been used in schools by teachers of second-language learners, learning-disabled students, and struggling readers or nonreaders. In many cases, audiobooks have proven successful in providing a way for these students to access literature and enjoy books. While these have dramatically risen in popularity over the last few years alone, they’re not exactly new. Audiobooks, or “talking books, as they were often referred to in the past, emerged during the 1930s. Unlike the digital versions we enjoy today, however, they often came in the physical form of a cassette tape or vinyl record. LOCUAS it’s one of such power to create such taking book. LOCUAS is one of the few contributions to AI community.
The effect of remote learning after COVID-19 on self-directed learning ability and learning motivation of students majoring in police administration

이 연구에서는 경찰행정전공 학생들을 대상으로 코로나19로 시행된 원격수업의 만족도가 학생들의 자기주도 학습역량 및 학습동기부여에 미친 영향을 검증하였다. 분석결과 첫째, 원격수업의 만족도가 높은 학생일수록 원격수업 후 자기주도 학습역량이 높아진 것으로 나타나 가설1이 지지되었다. 둘째, 원격수업의 높은 만족도가 학생들의 학습에 대한 동기부여에 긍정적인 영향을 미친 것으로 나타나 가설2가 지지되었다. 셋째, 원격수업의 만족도와 자기주도 학습역량 간의 관계에서 학습태도는 조절효과를 나타내어 가설3 또한 지지되었다. 즉 원격수업에 만족할수록 자기주도 학습역량이 향상되었는데, 이는 원격수업 만족도와 학습태도가 상호작용할 때 자기주도 학습역량이 더욱 향상될 수 있는 것으로 해석된다. 넷째, 원격수업의 만족도와 학습동기부여 간의 관계에서 학습태도는 조절효과를 나타내지 못하였다. 결과적으로 위 분석결과를 통해 만족도가 높은 원격수업은 학습자의 자기주도 학습역량 및 학습동기부여에 긍정적인 영향을 미치므로 원격수업이 효과적인 교수법임은 분명해졌다. 따라서 앞으로 대학에서는 온라인 기반의 강의 비중을 높여 학생들이 다양한 강좌를 접하고 그로 인해 학습효과를 높일 수 있는 방안을 마련해야 한다. 특히 경찰채용시험을 준비하는 경찰행정전공 학생들을 위해 학습의 편의성과 반복 학습 등 온라인강의의 장점을 활용하여 채용시험 관련 전공교과목에 대한 온라인강의 비중을 높이고 이를 지속적으로 관리한다면 학습효과는 상당할 것이다. 그러나 주의해야 할 것은 온라인강의의 개설에만 치중하다보면 강의콘텐츠의 질적 문제가 소홀해질 수 있다. 학생들 입장에서 오프라인강의보다 더 학습효과가 높다는 평가를 받기 위해서는 온라인강의 콘텐츠 개발을 위해 교수자들의 노력이 필요하다. 그리고 이러한 준비과정에서 온라인강의의 수요자인 학생들의 다양성까지 고려하여 개발되어야 한다. 무엇보다 오프라인강의의 높은 만족도, 오프라인상 교수와 학생간의 원활한 상호작용 등이 갖추어졌을 때 온라인강의의 효과가 나타남을 명심해야 한다.This study analyzed the effect of remote learning on self-directed learning ability and learning motivation of students majoring in police administration. The analysis results are as follows. First, it was found that the higher the satisfaction with remote learning, self-directed learning ability increases. Second, it was found that the higher the satisfaction with remote learning, it has a positive effect on motivation to learn. Third, the moderating effect of learning attitude was found in the relationship between the satisfaction of remote learning and self-directed learning abilities. It is interpreted that the higher the satisfaction with remote learning, the better the self-directed learning ability, and it is further improved when the satisfaction with remote learning and learning attitude interact. Fourth, there was no moderating effect of learning attitude in the relationship between satisfaction of remote learning and learning motivation. As a result of the analysis, it was found that remote learning is an effective teaching method that increases learner satisfaction and motivates learners to self-directed learning. Therefore, universities should come up with a plan to increase the learning effect by increasing the rate of online classes so that students can access various lectures. In particular, if you increase the percentage of online lectures on test subjects for police administration majors preparing for the police exam, the learning effect will increase. It should be developed taking into account the diversity of students in online classes. In the case of remote learning, offline class checks and offline exchanges between professors and students must be conducted first. For smooth distance lessons, the inspection of offline lessons and the interaction between professors and students in offline should be prepared first.
Meta-learning using privileged information for dynamics

Neural ODE Processes approach the problem of meta-learning for dynamics using a latent variable model, which permits a flexible aggregation of contextual information. This flexibility is inherited from the Neural Process framework and allows the model to aggregate sets of context observations of arbitrary size into a fixed-length representation. In the physical sciences, we often have access to structured knowledge in addition to raw observations of a system, such as the value of a conserved quantity or a description of an understood component. Taking advantage of the aggregation flexibility, we extend the Neural ODE Process model to use additional information within the Learning Using Privileged Information setting, and we validate our extension with experiments showing improved accuracy and calibration on simulated dynamics tasks.
국어과 연계 융합교육 프로그램의 현황과 개선 방향

The purpose of this study way to analyze convergence education programs linked to the Korean language subject operated in schools, and to explore directions for the development of convergence education in the Korean language. As a theoretical foundation, the study examined prior research trends in convergence education, and analyzed 33 programs in middle schools for the contents, methods, and forms of convergence education linked to the Korean language. The results showed that, Korean-language-linked convergence education programs were biased toward multi-disciplinary convergence centered on themes or topics, and writing was most frequently linked among the five areas of the Korean language. Activity elements associated with the Korean language were used as tools to understand the contents of other subjects. It was not possible to find a convergence education program that addressed the core educational content of the Korean language. In some cases, Korean language achievement standards were used as linked achievement standards without accurately understanding the focus of the achievement standards. To solve these problems, it will be necessary to properly set Big Ideas as mediating elements of convergence and promote interdisciplinary convergence. It is also important to pay more attention to program designs that focus on the Korean language. The scope of understanding of other subjects would be expanded by providing opportunities for mutual communication between subjects.
A Literature Survey of Virtual Currency

Money is maybe the best-recognized but at the same time less-understood economic metric. Throughout the development of a monetary science starting in the eighteenth century and fundamental works on such issues as true nature and the key functions of currency, the method and theories of monetary science have changed dramatically to the point of not entering the final state. The twenty-first century can be characterized by massive technological advancement and increased internet use, which greatly resulted in the growth of a monetary system that implemented a new trend-virtual currencies. Though remaining somewhat illusive, both legislative authorities and practitioners have widely noted the virtual currencies. In addition, prime authorities such as the Securities and Exchange Commission, S Treasury and European Central Bank expressed their reservations regarding this new form of currency as well. The suggested subject deserves extra attention because of the increasing popularity of virtual currencies, particularly the cryptocurrencies. Given the various possibilities virtual currencies could bring, it is very difficult to disregard the related risks-virtual currencies, representing a form of unregulated, digital money could support higher risks such as money laundering, financing illegal activity, etc. The focus of this paper addresses the overall analysis and evaluation of risks associated with the future production of virtual currencies and the inadequate, not comprehensive regulation. The paper's main findings suggest that virtual currencies nonetheless have a strong potential for further development, the development of a global or at least regional legislative base should take precedence.
Sistem Pakar Diagnosa Virus Corona Dengan Metode Naïve Bayes

Humans being are faced with non-natural disasters which have bad effect for population on the world. This non-natural disaster is called Corona Virus Disease (COVID-19). This COVID-19 will become a pandemic in 2020. This types of COVID-19 is coming from the Orthocronavirinae. It belongs to the Coronaviridae and the Nidovirales. This type of that virus has caused some disease to birds, mammals and also human being. Therefore, the research was conducted. The result of this research will give the information about system which related the classification human being according to their transmission to the body. This research used naïve bayes method. The result of this research is diagnostic system with the level of accuracy 94%. Thus, COVID-19 diagnostic expert system used to know the level of COVID -19 infections to human being. It can help the user knowing the next treatment.Keywords : Expert System, Naïve Bayes, Coronavirus, Covid-19
Extraction and Evaluation of Software Components from Object-Oriented Artifacts

A doctoral thesis is summarized in this paper that focuses on strengthening the Component-Based Software Development (CBSD) approach by proposing an efficient approach for extracting and evaluating reusable software components from an Object Oriented (OO) software by utilizing its various artifacts. The carried out research work mainly consists of two main steps: (1) extracting a possible set of components by utilizing optimal software artifacts and clustering techniques; (2) identifying reusable components by evaluating the quality of different components using the proposed reusability metric suite. The carried out research work significantly helps in identifying and extracting the reusable components for the CBSD environment and the proposed metric suite helps in evaluating the quality of all components.
LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search

Object tracking has achieved significant progress over the past few years. However, state-of-the-art trackers become increasingly heavy and expensive, which limits their deployments in resource-constrained applications. In this work, we present LightTrack, which uses neural architecture search (NAS) to design more lightweight and efficient object trackers. Comprehensive experiments show that our LightTrack is effective. It can find trackers that achieve superior performance compared to handcrafted SOTA trackers, such as SiamRPN++ and Ocean, while using much fewer model Flops and parameters. Moreover, when deployed on resource-constrained mobile chipsets, the discovered trackers run much faster. For example, on Snapdragon 845 Adreno GPU, LightTrack runs $12\times$ faster than Ocean, while using $13\times$ fewer parameters and $38\times$ fewer Flops. Such improvements might narrow the gap between academic models and industrial deployments in object tracking task. LightTrack is released at https://github.com/researchmm/LightTrack.
Transport of formaldehyde in water unsaturated laboratory columns packed with quartz sand: Effect of colloid-sized clay particles.

&amp;lt;p&amp;gt;Colloid-sized clay particles are in great abundance in the unsaturated or vadose zone and are capable of binding a variety of contaminants, which in turn either facilitate or hinder their migration in the subsurface. Also, FA has relatively strong affinity for kaolinite colloid particles (Fountouli et al., 2019). This study examines the effects of two representative colloid-sized clay particles (kaolinite, montmorillonite) on the transport of formaldehyde (FA) in unsaturated porous media. Transport experiments were performed in columns packed with quartz sand, under unsaturated conditions. The transport of FA was examined with and without the presence of suspended clay particles under various flow rates and various levels of saturation. DLVO interaction energies and the capillary potential energy associated with colloid retention at air-water and solid-water interfaces were calculated. The experimental results clearly suggested that the presence of suspended clay particles hindered the transport of FA in unsaturated packed columns. Moreover, as expected, it was shown that clay particle retention in the packed column increased with decreasing level of water saturation.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Reference&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Fountouli, T.V., C.V. Chrysikopoulos, and I.K. Tsanis, Effect of salinity on formaldehyde interaction with quartz sand and kaolinite colloid particles: batch and column experiments. Environmental Earth Sciences 78, 152, 2019.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;
Passive Voices Used in Reading Comprehension on the TOEFL

This study was aimed to find out the frequency of passive voice identified and to describe the types and frequencies of passive voices in reading comprehension texts in TOEFL. This study was applied descriptive qualitative design in analyzing the data. The source of the data was five kinds of selected reading comprehension text in TOEFL. The data used in this study were all of the reading texts consisting the passive voice. The instrument used to collect the data in this study was the researchers as the main instrument and supported by the secondary instrument called a reading test of complete one in TOEFL and table analysis. After analyzing the data, first, there were three types of passive voices called: simple present, past tense and present perfect tense. Second, it was shown: (1) there were 6 times of passive voices in the first reading text containing 1 type in simple present tense and 5 times in past tense; (2) in second reading text, there were 7 times of passive voices found consisting 1 type in simple present, 4 in past tense, 2 types in present perfect tense; (3) there were 2 times of passive voices which was only in present tense; (4) there was 1 time passive voice in simple present; and (5) there were 2 times passive voices in the type of simple present.