Reviewerly/exHarmony huggingface dataset:
Recovering AES Keys with a Deep Cold Boot Attack

Cold boot attacks inspect the corrupted random access memory soon after the power has been shut down. While most of the bits have been corrupted, many bits, at random locations, have not. Since the keys in many encryption schemes are being expanded in memory into longer keys with fixed redundancies, the keys can often be restored. In this work, we combine a novel cryptographic variant of a deep error correcting code technique with a modified SAT solver scheme to apply the attack on AES keys. Even though AES consists of Rijndael S-box elements, that are specifically designed to be resistant to linear and differential cryptanalysis, our method provides a novel formalization of the AES key scheduling as a computational graph, which is implemented by a neural message passing network. Our results show that our methods outperform the state of the art attack methods by a very large margin.
The Effectivenes of Technopreneurship with Cooperative Learning for Technopreneur in SMK (CLTSMK)

This research aims to reveal: 1) effectiveness of technopreneurshipin SMK for the survival skills of students, 2) aspects of motivation to learn, 3) aspects of thinking creativy, and 4) aspects of the student’s managerial of class XI students majoring in Mechanical Light Vehicle on the competence of the electrical system at SMKN 2 Depok and SMK Muhammadiyah 1 Playen. This research is a quasi experimental. The study design refers to the model developed by Donald Ary et.al. This study consisted of classroom control using conventional teaching methods and classroom experiments using model CLTSMK. The results of the research are as follows: (1) Application of CLTSMK effective learning model for the development of survival skills students (2) Aspects of motivation to learn of the control A the qualification Less while the experimental class the qualification Very Good. motivation to learn the control class B the qualification Enough  while the experimental class the qualification Very Good. (3) Aspects of thinking creativity of the control class A the qualification Enough   while the experimental class the qualification Very Good. Thinking creativity of the control class B the qualification Enough while the experimental class the qualification Very Good. (4) Aspects of student’s managerial in the control class Athe qualification Enough while the experimental class the qualification Very Good. Student’s managerial in the control class B the qualification Enough while the experimental class the qualification Very Good.
Approaching a DoS attack using change and risk management methods

The Information Technology security threats are emerging with each day passing by. The implementation of the technology into every field of society brings changes. Finding a way to manage these changes would be a success, and, by doing so, it would mitigate the risks they bring. Data transmission nowadays is unsecure like never before. Challenging is the way that should be found to cope with these kinds of evolutionary changes. Among the top threats in networks lies the DoS attack. It has been a long time since this kind of attack is around, but that doesn’t reduce the fact that this type of attacks is still dangerous and devastating. In order to cope with this kind of attack, we need to know how to manage risks and changes during a DoS attack. Because of this, it is very important that defensive mechanisms are implemented and integrated so that unauthorized access would be prevented from accessing your network or data. This refers to individuals and everyone else working in companies that are working in the field of IT, because at some point, we all share the same thing-devices (mobile phones, personal computers, devices at work, etc.). The base of the IT foundation is knowing how to protect yourself and your data. Due to this, we need to work hard and exploit every possible threat and attack from the inside out. Not only to reduce or mitigate the already occurred impact, but also to prevent these types of failures from happening in the future.
Pattern of malaria parasitaemia in a high transmission setting of Oba-Ile, Akure North, southwestern Nigeria

Malaria is an infectious disease of major public health importance worldwide. This study was carried out to investigate the malaria parasitaemia in a high transmission setting of Oba-Ile, Akure North Local Government Area (LGA), Ondo State, Nigeria. Thick and thin blood smeared slides were prepared and examined under the light microscope. Out of 210 individuals examined, 148(70.50 %) were positive for malaria infection. The infection pattern among age groups revealed that the highest (84.61 %) and the lowest (66.67 %) infection rate were observed among age group 6 – 10 years and 5 years and below respectively. No significant difference (p>0.05) occurred between age-related malaria infection. Additionally, male had the highest (75.89 %) prevalence of infection compared to their female counterpart (64.28 %) though significant difference (p>0.05) did not occur. Parasite densities vary significantly (p<0.05) across age group and sex. The highest (4428 parasite/µl of blood) and lowest (824 parasite/µl of blood) parasite density was recorded among age group ≥ 21 years and ≤ 5 years respectively. Similarly, male significantly (p<0.05) had the highest parasite density (6484 parasite/µl  of blood) compared to their female counterpart (4316 parasite/µl of blood). Furthermore, prevalence of malaria infection varied significantly (p<0.05) with respect to occupation and income. This study revealed that malaria is prevalent in Oba-Ile. Thus, appropriate intervention programme should be designed to curtail the disease.Keyword: Malaria, Parasite density, Parasitaemia, Plasmodium  falciparum, Oba-Ile, Nigeria
Questions of formation of readiness of the future teacher to ensure continuity of preschool and primary mathematical education

The article deals with the problem of the future teacher’s readiness to implement the continuity of preschool and primary mathematical education. The authors define the philosophical, psychological, and pedagogical essence of continuity as a pedagogical phenomenon. Continuity is defined as the General and specific goal of education, the construction of a single content line that provides effective progressive development of the child, his successful transition to the next stage of education. The article analyzes the typical curriculum of preschool education and training and the curriculum of the 1st grade to determine the continuity of preschool and primary mathematical education. The authors substantiate the structure of the future teacher’s readiness to implement the continuity of preschool and primary mathematical education, highlighting: motivational, cognitive, activity and reflexive components. The criteria, indicators and levels (low, medium, high) of the future teacher’s readiness to implement the continuity of preschool and primary mathematical education and the results of experimental work are presented. The article was published through grant funding «The best teacher of the university in 2019».
Learning to Optimize Domain Specific Normalization with Domain Augmentation for Domain Generalization

We propose a simple but effective multi-source domain generalizationtechnique based on deep neural networks by incorporating optimizednormalization layers specific to individual domains. Our approach employsmultiple normalization methods while learning a separate affine parameter perdomain. For each domain, the activations are normalized by a weighted averageof multiple normalization statistics. The normalization statistics are kepttrack of separately for each normalization type if necessary. Specifically, weemploy batch and instance normalizations in our implementation and attempt toidentify the best combination of two normalization methods in each domain andnormalization layer. In addition, we augment new domains through thecombinations of multiple existing domains to increase the diversity of sourcedomains available during training. The optimized normalization layers and thedomain augmentation are effective to enhance the generalizability of thelearned model. We demonstrate the state-ofthe-art accuracy of our algorithm inthe standard benchmark datasets.
한일 고등학교 영어교과서의 시간 형용사에 대한 코퍼스 기반 비교 분석

The purpose of this paper is to investigate and compare the use of three time adjectives new/old/young in high school textbooks of Korea and Japan. The main findings of the study are as follows. First, while the order(high to low) of frequency in the use of time adjectives such as new:135/231: old: 125/188 and young 73/100 is consistent between Korean and Japanese textbooks, the frequency of the three adjectives used is higher in Japanese textbooks than in Korean textbooks. Second, the proportion of time adjective+noun expressions out of all common combined nouns in both textbooks is as low as 30%, hence it is reasonable to state that there is more commonality than difference in combined nouns of adjective+noun expressions of Korean and Japanese textbooks. Third, the proportion of common time adjective+noun expressions between COCA(top 20) and Korean/Japanese textbooks is just approximately 55% and 52%, respectively. These results strongly suggest that we should consult native English speakers’ corpus when we write and publish English textbooks.
DeLib Guides: Publication Services: Visual Assets Review and Consultation

This Guide provides an overview of the publication services offered by the Distributed eLibrary. This guide provides details on our visual asset consultation services.
AN ANALYSIS OF SARCASM ON HATE SPEECH UTTERANCES ON JUST JARED INSTAGRAM ACCOUNT

This research focuses on how sarcasm on hate speech is used by the followers of Just Jared’s account on Instagram. The purposes are to investigate what maxims are violated in the sarcastic comments made by the IG followers, which violation of maxim is the most dominant, and what factors cause hate speech in the comment. There were 50 comments collected as the primary source of data. The comments were those from the October 2019 to May 2020’s posts. Grice’s theory of maxims that classifies the rules of conversation into the maxims of quality, quantity, manner, and relevance was used to decide whether the comments violated the maxims or not. The results show that the analyzed data were proven to contain violation of the Gricean maxims that included violations of: the maxim of manner (17 comments), the maxim of quality (11 comments), the maxim of relevance (8 comments), and the maxim of quantity (4 comments). Besides single violation, some comments contain mixed violations that included the combinations of: the maxim of quantity and relevance (3 comments), the maxims of manner and relevance (3 comments), the maxim of quality and relevance (2 comments), and the maxim of quality and manner (2 comments). While violation of the maxim of manner records the highest (34%) in the data, combinations of violation of the maxim of quality-relevance and the maxim of quality-manner record the lowest (4.0%). Factors that motivate people to these violations are mostly due to the absence of providing brief, clear, and orderly information in the comments, the cultural value in the western countries that gives people the right and privilege to speak freely, the exaggeration for seeking other people’s attention, and the ego that enhances self-importance among individuals while at the same time diminishing others’.
LibGuides: Diverse Reads: The Why, How, and Where: Articles

A resource for youth services librarians and teachers on diverse read selections and programming.
Cyberbullying detection in Roman Urdu language using lexicon based approach

Nowadays, online social networks (OSNs) have become integral part of our daily life and online users of social media are massively growing. The increasing use of OSNs by users leads to large amount of user communication data. This study focuses on OSNs users who communicate in Roman Urdu (Urdu language written in English alphabets). Pakistan alone has over 44 million OSNs users who communicate in Roman Urdu. In this paper, we addressed the issue of cyberbullying behavior on Twitter platform, where users use Roman Urdu as medium of their communication. To the best of our knowledge, this is the first study addressing cyberbullying behavior in Roman Urdu. To address this issue, we developed supervised machine learning method and proposed a lexicon-based model with set of features derived from Twitter. An evaluation model shows that the developed model attained results with area under receiver operating characteristics curve (AUC) of 0.986 and f-measure of 0.984. These results indicate that the proposed lexicon-based method gives feasible solution for detecting cyberbullying behavior in Roman Urdu in OSNs. Finally, we compared results achieved with our proposed lexicon-based method and the results obtained from other well-known models. The comparison results show the significance of our proposed model.
시청각 자료 중심 방법과 문맥 중심 방법의 아랍어 어휘 학습 비교 연구

The purpose of this research was to investigate the effects of listening-visual based teaching and context based teaching on Korean AFL learners’ vocabulary learning in a classroom. To accomplish the goal of this study, 24 Arabic intermediate learners participated in the experiment for 8 classes. They were divided into two groups: listening-visual based teaching and context based teaching groups.The effectiveness of vocabulary teaching has been measured in the following dimensions: how it affects long-term memory and how it affects application of memorized vocabulary in various contexts.The results of this study were as follows: First, the outcome of the experiment indicates that listening-visual based teaching was more effective than context based teaching for learners to infer the meaning of the target words. Also, in the 8 tests for Arabic vocabulary there were significant differences between the two groups. It showed that listening-visual based teaching was effective in learning vocabulary. Secondly, listening-visual based teaching helped increase the retention of vocabulary in learners’ long-term memory.
Habilidades esenciales para el siglo XXI a través de la educación STEM

espanolEl presente trabajo tiene como objetivo describir un proceso de ensenanza y aprendizaje de la Fisica mediado por simulaciones basadas en la educacion STEM. La investigacion se llevo a cabo en un grupo de estudiantes de pregrado en matematicas que estaban cursando la disciplina de electricidad y magnetismo. El montaje de los circuitos electricos se realizo en un laboratorio virtual en la modalidad de ensenanza a distancia con la ayuda del software Thinkercad. El enfoque educativo STEM sirvio para fomentar el desarrollo de habilidades esenciales para el siglo XXI que son: pensamiento critico, trabajo colaborativo, creatividad e innovacion, resolucion de problemas. Creemos que el uso de simulaciones en laboratorios virtuales de electricidad contribuye al desarrollo de habilidades esenciales para el siglo XXI desde la educacion STEM. EnglishThe present work aims to describe a process of teaching and learning of Physics mediated by simulations based on STEM education. The research was carried out on a group of undergraduate mathematics students who were studying the discipline of electricity and magnetism. The assembly of the electrical circuits was carried out in a virtual laboratory in distance learning mode with the help of the Thinkercad software. The STEM educational approach served to promote the development of essential skills for the 21st century that are: critical thinking, collaborative work, creativity and innovation, problem solving. We believe that the use of simulations in virtual electricity laboratories contributes to the development of essential skills for the 21st century from STEM education
Field Service Technician of 2025: Empower Your Team with Technology

How to leverage todays technology to empower your future field service team [row] [column md=6] [/column] [column md=6]We recently ...
Coded-InvNet for Resilient Prediction Serving Systems

Inspired by a new coded computation algorithm for invertible functions, we propose Coded-InvNet a new approach to design resilient prediction serving systems that can gracefully handle stragglers or node failures. Coded-InvNet leverages recent findings in the deep learning literature such as invertible neural networks, Manifold Mixup, and domain translation algorithms, identifying interesting research directions that span across machine learning and systems. Our experimental results show that Coded-InvNet can outperform existing approaches, especially when the compute resource overhead is as low as 10%. For instance, without knowing which of the ten workers is going to fail, our algorithm can design a backup task so that it can correctly recover the missing prediction result with an accuracy of 85.9%, significantly outperforming the previous SOTA by 32.5%.
A Graph based Data Integration and Aggregation Technique for Big Data

Data integration is a vital issue in the conditions of heterogeneous data sources. As of now, the in advance of referenced heterogeneity is getting boundless. In view of different data sources, in the event that we need to acquire valuable information and knowledge, we should take care of data integration issues to apply suitable insightful techniques to extensive and uniform data. All the more especially, we propose a novel engineering for instance matching that considers the particularities of this heterogeneous and conveyed setting. Rather than expecting that instances share a similar schema, the proposed technique works in any event, when there is no cover between schema, aside from a key name that matching instances should share. In addition, we have thought about the conveyed idea of the Semantic Web to propose another design for general data integration. The arrangement consolidates ETL innovation and a wrapper layer known from intervened frameworks. It additionally gives semantic integration through association component between data components. The outcomes accomplished in this work are especially intriguing for the Semantic Web and Data Integration people group.
교원학습공동체를 통한 가상현실 기반의 음악교육 콘텐츠 개발 및 효용성에 관한 논의

This study aimed to examine the evaluation and implementation of educational technology of online-based singing education programs and non-contact performance contents developed by the teachers' learning community in Seoul. This study describes the process of eight teachers creating their own content, evaluates its final results, and explores teachers' experiences and practices that have emerged in the course of its development. As a feature of the developed content, first, it can be used as a useful content for modeling and feedback on online teaching environments. Second, teaching environments leveraging virtual reality expanded the concept of time and space, providing a one-on-one teaching environment that was difficult in traditional classrooms. Third, by providing cloud-based mobile textbooks, content has been constructed to help students learn on their own initiative. In addition, if this is discussed about the experiences and practices of teachers in the process of developing contents through the teacher learning community, it is as follows. First, in the process of producing the contents of learning, teachers were found to grow through trial and error and reflection. Second, sharing was practiced through official documents and various channels after the production of the educational contents and as teachers, they felt rewarded and proud. Third, the teachers’ willingness and sharing of a vision played a positive role in the participation of learning to produce content.
Asymmetric Information in High-Value Low-Frequency Transactions: Mitigation in Real Estate Using Blockchain

The saying ‘buyer be aware’ has been used as an excuse from a seller’s perspective to withhold information that could negatively impact a transaction. This asymmetric information is especially prevalent in high–value, low-frequency assets. Using New Zealand real estate as an exemplar to understand the difﬁculties faced in such a transaction, we delve into the characteristics of the transaction and speciﬁcally the asymmetric information that is predominant in the real estate industry. Understanding the processes and stakeholders involved gives us the possibility to introduce blockchain as a system to mitigate asymmetric information. We identify the bottlenecks in the current processes and suggest possible solutions that capitalize on the blockchain characteristics.
Two-qubit non-locality interacting time-dependently with a parametric amplifier cavity with Stark-shift nonlinearity

We have explored the non-locality of two qubits interacting time-dependently with a nondegenerate parametric amplifier cavity fields in the presence of the Stark shift interaction term. The time-dependent two-qubit reduced density matrix is calculated numerically when the cavity fields are initially in two entangled coherent states. We investigate the non-locality via local Fisher information and negativity. It is shown that, the generated non-locality depends on the time-dependent two-qubit location, the Stark shift interaction, the difference between the mean photon numbers of the two cavity fields as well as the initial intensity coherent fields. The agreement of the generated correlations presented by the local Fisher information and the negativity depends on the physical parameters. The Stark shift non-linearity and the difference between the mean photon numbers leads to reducing the generated correlations. The local Fisher information is more robust against the Stark shift interaction than the negativity.
Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks

In contrast to traditional weight optimization in a continuous space, we demonstrate the existence of effective random networks whose weights are never updated. By selecting a weight among a fixed set of random values for each individual connection, our method uncovers combinations of random weights that match the performance of trained networks of the same capacity. We refer to our networks as ``slot machines'' where each reel (connection) contains a fixed set of symbols (random values). Our backpropagation algorithm ``spins'' the reels to seek ``winning'' combinations, i.e., selections of random weight values that minimize the given loss. Quite surprisingly, we find that allocating just a few random values to each connection (e.g., 8 values per connection) yields highly competitive combinations despite being dramatically more constrained compared to traditionally learned weights. Moreover, finetuning these combinations often improves performance over the trained baselines. A randomly initialized VGG-19 with 8 values per connection contains a combination that achieves 90% test accuracy on CIFAR-10. Our method also achieves an impressive performance of 98.1% on MNIST for neural networks containing only random weights.
Uma história não contada: arquivos de organizações privadas no periódico Arquivo & Administração

This research sought to identify the interest caused by the archives of private organizations in the journal Arquivo & Administracao (1972-2014). By means of a historical approach, copies of this journal were analyzed, as well as other publications that deal with the subject. We seek to explore how private archives’ theme has emerged since the 1970s in the theoretical field of archival science in Brazil.
Lexicalized Reordering Models for English-Myanmar Phrase-based Statistical Machine Translation

This work is partly supported by the Asian-MT“Network-based ASEAN Languages TranslationPublic Service” and the ASEAN IVO Project “OpenCollaboration for Developing and Using AsianLanguage Treebank”.