Reviewerly/exHarmony huggingface dataset:
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection

We investigate the adversarial robustness of CNNs from the perspective of channel-wise activations. By comparing \textit{non-robust} (normally trained) and \textit{robustified} (adversarially trained) models, we observe that adversarial training (AT) robustifies CNNs by aligning the channel-wise activations of adversarial data with those of their natural counterparts. However, the channels that are \textit{negatively-relevant} (NR) to predictions are still over-activated when processing adversarial data. Besides, we also observe that AT does not result in similar robustness for all classes. For the robust classes, channels with larger activation magnitudes are usually more \textit{positively-relevant} (PR) to predictions, but this alignment does not hold for the non-robust classes. Given these observations, we hypothesize that suppressing NR channels and aligning PR ones with their relevances further enhances the robustness of CNNs under AT. To examine this hypothesis, we introduce a novel mechanism, i.e., \underline{C}hannel-wise \underline{I}mportance-based \underline{F}eature \underline{S}election (CIFS). The CIFS manipulates channels' activations of certain layers by generating non-negative multipliers to these channels based on their relevances to predictions. Extensive experiments on benchmark datasets including CIFAR10 and SVHN clearly verify the hypothesis and CIFS's effectiveness of robustifying CNNs.
A Combined Traffic and Workload-aware Optimized Virtual Machine Migration in Cloud Computing

In cloud computing paradigm, Virtual Machine (VM) migration strategies play a vital role in reducing the Energy Consumption (EC) and balancing the workloads in the cloud servers. From this viewpoint, an Osmotic Hybrid artificial Bee and Ant Colony with Future Utilization Prediction and Multipath Traffic Routing (OH-BAC-FUP-MTR) strategy was designed to accomplish effective load-balancing and minimize the chance of traffic congestion during VM migration in data centres. But, the tradeoffs among workload efficiency and power-gain in heterogeneous cloud servers were not analyzed. Hence in this article, a VM consolidation strategy is proposed with OH-BAC-FUP-MTR to switch the idle Physical Machines (PMs) into hibernation mode, resulting in very less EC. In this strategy, the VM migration is targeted at consolidating the VMs depending on the workload to the smaller number of PMs for reducing the power use and encouraging green computing. Initially, the PMs are split into various groups depending on their workload levels and then a new Merge-and-Split-based Coalitional Game-theoretic (MSCG) method is applied to select associates from these groups to create efficient coalitions. After that, OH-BAC-FUP-MTR is performed amongst the coalition associate for maximizing the reward of each coalition and PMs are maintained to operate in the maximum power-efficient condition. Finally, the investigational outcomes exhibit the OH-BAC-FUP-MTR-MSCG achieves a mean EC of 60.63KWh which is 28.87% less than all other classical VM migration strategies.
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Utilización de plataformas digitales en educación

espanolTratamos de reflexionar lo concerniente al uso de plataformas digitales, concretamente de E-Learning, en el proceso educativo, aplicable a diferentes niveles educativos. De este modo, una vez conseguido nuestro objetivo: como preparar un proyecto de formacion autonoma del profesorado, en nuestro centro de referencia, nuestra finalidad seria, que todo el profesorado pueda aplicarlo a su materia en el aula. EnglishWe try to reflect on the use of digital platforms, specifically E-Learning, in the educational process, applicable to different educational levels. In this way, once we achieve our objective: how to prepare an autonomous teacher training project, in our reference center, our aim would be that all the teachers are able to apply it to their subject in the classroom.
Language Learning and Processing in People and Machines

The goal of this tutorial is to bring the fields of computational linguistics and computational cognitive science closer: we will introduce different stages of language acquisition and their parallel problems in NLP. As an example, one of the early challenges children face is mapping the meaning of word labels (such as “cat”) to their referents (the furry animal in the living room). Word learning is similar to the word alignment problem in machine translation. We explain the current computational models of language acquisition, their limitations, and how the insights from these models can be incorporated into NLP applications. Moreover, we discuss how we can take advantage of the cognitive science of language in computational linguistics: for example, by designing cognitively-motivated evaluations task or buildings language-learning inductive biases into our models.
Methodology of Scientific Activity and Art Education in the System of Media Communications

Currently, the priority of the dynamic development of the university is the integration of science and education on the basis of an interdisciplinary approach. The potential of art history as a scientific discipline is in demand at all levels of higher liberal arts education. The art history perspective of the scientific and educational activities of the university in the field of media communications and world art culture is becoming increasingly obvious, which provides for a certain organization of the educational process.
iClean / Muhammad Afiq Aiman Mohd Zamari … [et al.]

iClean is a company that specializes in health and sanitary products. Our company is located in Seksyen 7, Shah Alam in Selangor. Our company’s business commenced on 19th of October and registered on 3rd of November. Our main product, Pocket Soap, is the staple of iClean. The Pocket Soap is a unique one of a kind soap product that is easy to use and easy to carry around in day to day life. The product is a packet with multiple sheets of usable soap that dissolves in water, it is also light and small enough to put in your pocket. Thus, the name Pocket Soap. Our product, the Pocket Soap, offers unique features that are not found in even other soap brands. Those features are a cheap price, fresh design as well as a social media presence. When compared to famous soap brand Remy soap, we can match the brand’s advertisement as we will pay other famous celebrities to promote our product as well as sell it at a lower price. Another famous soap brand is Dittol, which we will have an advantage due to our unique product design as well as a strong social media presence. Furthermore, other soap brands are mostly liquid in form so carrying around in a bag or in our pockets is quite difficult since the liquid may spill out. But for the Pocket Soap that would not be a problem since our product is solid in form and will dissolve to soap form only when it comes to contact with water. The purpose of this Business Model Canvas is to help create a guideline to develop and refine our business as well as describe our intentions and proposal to interested parties. Customer Segment is the process of dividing customers into groups based on common characteristics and choosing which groups our product will be for. Value propositions refers to the value our company’s promise to deliver to customers. Distribution Channels are ways our products are bought and delivered to our customers. Customer relationships are methods to earn customer loyalty. Revenue streams are various ways our company receives income or profit. Key resources are required to offer and deliver the value of products and prices. Key activities are the main activities the company will partake to grow our business. Key partners are other brands or companies who we will keep in close touch to help each other grow. Cost structure is the main cost that is needed to perform our duties.
Blockchain in AI

In recent times, the two technologies, artificial intelligence (AI) and blockchain, are the most trending and disruptive in all technologies. Undoubtedly both technologies are covering all the areas of engineering and science with an exceptional rate. These technologies offer various degrees of technological complexity and multi-dimensional business implications. Blockchain is an open, distributed ledger technology that records all the transactions done. These distributed ledger technologies have disrupted the evolving technology sector. Blockchain can authorize and automate payment transactions in cryptocurrency. Also, blockchain has provided access to a shared ledger (block) of data, digital transactions, and logs in an environment that is decentralized, secure, and trusted. Blockchain governs the interactions among distributed participants with the capability of no intermediary or a trusted third party. Blockchain technology is evolving day by day with a fast-passed pace. Now, it is possible to integrate blockchain with many other evolving technologies like robotics with AI services. AI provides intelligence and decision-making capabilities like humans to machines. Data is the main constituent to develop AI and machine learning. Now, AI has a wide variety of uses from finance (stock trading) to web (chatbots) to advanced technology (self-driving cars). Before the advent of big data, AI was a conceptual model. Artificial intelligence (AI) works significantly as a strong analytic tool to analyze big data in a scalable, accurate, and real-time. By using artificial intelligence, the design and development of tools for big data analysis has certain issues like centralized architecture, security, privacy, resource constraints, and lack of enough training data. There is rarely today any human activity, machine control, and business logic that is not considered artificial intelligence in future years and decades. On the contrary, blockchain considers decentralized architecture as an emerging technology. Among the various distributed nodes of the IoT network, secure sharing of data and resources is provided by the blockchain. It is expected to remove centralized control and may overcome the other existing challenges in AI. In this chapter, we consider, emphasize, and analyze how blockchain implementation is supported or enhanced via various AI techniques. We will further review how artificial intelligence may be exploited to achieve the goal of blockchain 2.0. There seem to be numerous possibilities in the alliance of AI and blockchain in Industry 4.0.
NH-CIL: A Nested Hierarchy Algorithm for Class Incremental Learning

Class incremental learning is widely applied in the classification scenarios as the number of classes is usually dynamically changing. However, the existing algorithms increase computational cost to implement class incremental learning in order to increase classification quality. In this paper, we propose a nested hierarchy algorithm based on OCSVM for class incremental learning, called NH-CIL. We reuse support vectors to eliminate redundant instances and catch the key ones to replace the whole model because of the generalization ability of OCSVM. When a new class arrives, NH-CIL adopts OCSVM on the new class and the old classes respectively to get the corresponding sketching supports vectors. Then NH-CIL reuses these two kinds of sketching support vectors to build a binary sub-classifier. These two steps are repeatedly nested to form a hierarchy classification model in a bottom-up manner while the number of classes increases. On the contrary, the testing phase is in a top-down manner. NH-CIL can be used as a flexible approach in the classification scenarios during the collaborative information processing. We conduct the experiments on 8 real-world benchmark datasets to compare NH-CIL with some other class incremental learning algorithms, e.g. SD-CIL, HS-CIL and OP-CIL. The experiment results show that NH-CIL averagely achieves more than 5.1%, 8.6% and 11.6% accuracy improvement and 39.8%, 24.7% and 12.6% efficiency improvement over SD-CIL, HS-CIL and OP-CIL, respectively.
PROJECT WAY FOR SUBJECTNESS DEVELOPMENT

The article shows some attitudes between subjectness, activity and free choice. Subjectness is ability to awareness of choices for taking decision and doing. Activity is ability to act on the basis of individual goals, senses and intentions. Choice is the volitional action of making a decision to choose a course of action from a certain range of those that are conscious. The choice can be difficult to implement given the similarity of options, or awareness of the complexity of practical implementation and the likelihood of negative outcomes and consequences. A particular complication is that choosing any option usually leads to the abandonment of other options that may also be attractive. There is conception of individual development in general as development of thinking and doing ways. The main way to develop is the organization of reflection, including prospective. There is a review of concept, structure and process of professional group development training that built as individual reflection and projects designs. Also some experimental study results and discussion about it.
Effectiveness of the Regional School Operational Assistance Program for Madrasas in Bekasi Municipal Government in the Decentralization Era: A Case Study of Madrasah Ibtidaiyah Negeri Bekasi Municipality and Madrasah Tsanawiyah Negeri 1 Bekasi Municipality

Recently, Indonesia prioritized education for everyone to reach the United Nation's sustainable development goals (SDGs).Generally, central and regional governments have the authority to implement education to achieve fair and inclusive education nationwide.To enhance the overall quality of education, regional governments are implementing the Regional School Operational Assistance (Bantuan Operasional Sekolah Daerah, BOSDA) program.This program is a school operational assistance program that provides middle and elementary schools with funds from the regional budget for operational expenses.Hence, Bekasi municipal government decided to make BOSDA available to both public schools and madrasas.Local governments rarely support madrasas through BOSDA because madrasas are considered the concern of the central government.This study uses a postpositivist descriptive approach to analyze the effectiveness of this BOSDA program in education in madrasas in the Bekasi Municipality.The results of this study showed that the BOSDA program implemented in Madrasah Ibtidaiyah Negeri Bekasi Municipality and Madrasah Tsanawiyah Negeri 1 Bekasi Municipality is fairly effective in helping madrasas develop their infrastructure and human resources.This study is expected to encourage other regions to take part in developing madrasas, thereby contributing to enhancing the overall access to education and achieving comprehensive education equality throughout Indonesia.
Las Tecnologías de la Información y la Comunicación en apoyo a la asignatura de metabolismo nutrición

Introduction: the university is the institution responsible for promoting knowledge with a creative character, stimulating the development of science through research and technological development to train young generations with a humanistic approach and an important social task. Aim: to elaborate a complementary material containing a system of teaching tasks that give an output to the first-year program of the medical career of the Metabolism-Nutrition subject in times of pandemic with the creation of WhatsApp groups for clarification of doubts. Method: development research was carried out in the field of learning resources in the Faculty of Medical Sciences of Granma from March 2020 to August 2020. The study universe was composed of 83 students. Results: 100% of students and teachers considered the complementary materials and the WhatsApp group useful to clarify doubts and make teaching consultations, while 98.79% considered them useful for the acquisition of contents. Conclusions: the complementary materials and the use of a WhatsApp group allow improving the educational strategy in the 21st century, with good acceptance by students and teachers.
Digital Reality As A Synergistic Paradigm Of Xxi Century Education

The article dwells on the problems of present-day education, particularly, the problem of digitalization, its strengths and weaknesses in the context of the economic crisis, as well as the analysis of its impact on the educational paradigm of the XXI century.Special attention is paid to the difficulties that the educational process participants are forced to face nowadays; various scenarios for overcoming existing contradictions are considered.Education generally promotes learning in the form of knowledge and skills transfer.It dates back to prehistoric times when knowledge was transferred through imitation.It is known that schools existed in ancient Egypt, and the education system was developed along with literacy, culture and science.As a rule, the educational process includes a teacher, a student and certain means to transmit knowledge from a teacher to a student.If you remove the real (not virtual) teacher from this process, there will be an abrupt transition to the system of self-education.This synergistic paradigm of present-day education is a reality reflection; however, it is worth noting that at this stage the education system still needs a teacher as a source of knowledge.
SISTEM INFORMASI PENJUALAN PADA CV.PUTRA BATANGHARI

Information systems have become an urgent need in various fields of life including in the business field, CV. Putra Batanghari is a company engaged in the sale of stones. Sales information system is needed by CV. Putra Batanghari, because it has a role to facilitate the activities or business activities, especially in sales activities. One information system that can be used is Visual Basic. Net is a simple programming which is expected to make it easier for the CV. Putra Batanghari to prevent errors in inputting sales data and avoid misunderstanding between consumers The design built includes consumer data, item data, transaction data, and report data to produce reports in the form of goods and sales transaction data reports in order to help and process data more effectively and efficiency.
COVID Manifesto (2020)

Previous articleNext article No AccessAnother IdeaCOVID Manifesto (2020)Cauleen SmithCauleen SmithCalifornia Institute of the Arts, Los Angeles, California, USA Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Portable Gray Volume 4, Number 1Spring 2021Another Idea: Exhibition Catalogue Published for the Gray Center for Arts and Inquiry Article DOIhttps://doi.org/10.1086/715570 Views: 74Total views on this site © 2021 The University of Chicago. All rights reserved.PDF download Crossref reports no articles citing this article.
qxoRef 1.0: A coreference corpus and mention-pair baseline for coreference resolution in Conchucos Quechua

This paper introduces qxoRef 1.0, the first coreference corpus to be developed for a Quechuan language, and describes a baseline mention-pair coreference resolution system developed for this corpus.The evaluation of this system will illustrate that earlier steps in the NLP pipeline, in particular syntactic parsing, should be in place before a complex task like coreference resolution can truly succeed.
New digital signature algorithm based on ECC and its application in bitcoin and IoT

Elliptic curve digital signature algorithm (ECDSA) is the simulation of digital signature algorithm (DSA) algorithm on elliptic curve. Compared with DSA, ECDSA has higher security and is the only widely accepted ECDSA, which has been adopted by many standardisation organisations. Based on the study of the original ECDSA scheme, this paper attempts to propose a new improved scheme. The proposed scheme has one main improvement. That is, considering that the original scheme has a finite field inversion process in the signature equation, the time-consuming inversion operation is completely avoided in the design. The proposed scheme has faster computation speed and reduces the ratio of verifying signature to signature generation time. The algorithm has certain significance for improving the efficiency of elliptic curve cryptography. Our simulation results show that the scheme runs faster and has higher signature and verification efficiency than that of the original scheme without compromising security. What's more, we also explore its application in bitcoin and Internet of Things (IoT).
Texture Segmentation by Morphological Probabilistic Hierarchies

A general methodology is introduced for probabilistic texture segmentation in binary, scalar, or multispectral images. Textural information is obtained from morphological operations on images. Starting from a fine partition of the image in regions, hierarchical segmentations are set up in a probabilistic framework by means of probabilistic distances conveying the textural or morphological information, and of random markers accounting for the morphological content of the regions and of their spatial arrangement. The probabilistic hierarchies are built from binary or multiple fusion of regions.
The "Blooming" of English Poetry in the Middle School Classroom---Take “When You are Old” as an Example

The poetry teaching in this class aims at cultivating the students’ core literacy in the English subject, training students’ language ability, learning ability, cultural character, and thinking quality as the end point, adopts the "target step by step" teaching model and the narrative research method. Students made perception, recitation, appreciation, imitation and comparison of “When You are Old”. The teaching results found that English poetry has a certain significance and value for the cultivation of English core literacy.
The joint discriminative and generative learning for person re-identification of deep dual attention

In the task of person re-identification, there are problems such as difficulty in labeling datasets, small sample size, and detail feature missing after feature extraction. The joint discriminative and generative learning for person re-identification of the deep dual attention is proposed against the above issues. Firstly, the author constructs a joint learning framework and embeds the discriminative module into the generative module to realize the end-to-end training of image generative and discriminative. Then, the generated pictures are sent to the discriminative module to optimize the generative module and the discriminative module simultaneously. Secondly, according to the connection between the channels of the attention modules and the connection between the attention modules in spaces, it merges all the channel features and spatial features and constructs a deep dual attention module. By embedding the models in the teacher model, the model can better extract the fine-grained features of the objects and improve the recognition ability. The experimental results show that the algorithm has better robustness and discriminative capability on the Market-1501 and the DukeMTMC-ReID datasets.