Reviewerly/exHarmony huggingface dataset:
Methodological strategies for the development of multiple intelligences in tenth year students

The application of effective methodological strategies based on the theory of multiple intelligences is the fundamental objective of research to determine and verify the potential of students at different levels of learning, according to academic tasks and activities, both theoretically and practically. The type of research is argumentative, with scientific strategies developed by various authors. It was necessary to apply analytical, synthetic, comparative methods and a bibliographic review in information sources, through documents, scientific articles, journals, among other research instruments, to identify different teaching-learning models of a pedagogical and educational nature. high impact, in addition to methodological strategies that allowed to argue the theoretical basis of the authors, the systematic they proposed, for which each of their arguments and explanations were analyzed. The different types of skills were compared through the comparative method to contrast each of the methodologies and strategies exposed by the researchers, highlighting what is based on each of them and how they differ from one to the other, as well as the advantages and disadvantages possessed by each of the models taken, generating a cluster of ideas that continued to choose the best methodological strategy to apply in the classroom.
Can’t Touch This: Inertial HSMs Thwart Advanced Physical Attacks

In this paper, we introduce a novel countermeasure against physical attacks: Inertial Hardware Security Modules (IHSMs). Conventional systems have in common that their security requires the crafting of fine sensor structures that respond to minute manipulations of the monitored security boundary or volume. Our approach is novel in that we reduce the sensitivity requirement of security meshes and other sensors and increase the complexity of any manipulations by rotating the security mesh or sensor at high speed—thereby presenting a moving target to an attacker. Attempts to stop the rotation are easily monitored with commercial MEMS accelerometers and gyroscopes. Our approach leads to an HSM that can easily be built from off-the-shelf parts by any university electronics lab, yet offers a level of security that is comparable to commercial HSMs. We have built a proof-of-concept hardware prototype that demonstrates solutions to the concept’s main engineering challenges. As part of this proof-of-concept, we have found that a system using a coarse security mesh made from commercial printed circuit boards and an automotive high-g-force accelerometer already provides a useful level of security.
Hybrid Machine Learning: A Tool to Detect Phishing Attacks in Communication Networks

Phishing is a cyber-attack that uses disguised email as a weapon and has been on the rise in recent times. Innocent Internet user if peradventure clicking on a fraudulent link may cause him to fall victim of divulging his personal information such as credit card pin, login credentials, banking information and other sensitive information. There are many ways in which the attackers can trick victims to reveal their personal information. In this article, we select important phishing URLs features that can be used by attacker to trick Internet users into taking the attacker’s desired action. We use two machine learning techniques to accurately classify our data sets. We compare the performance of other related techniques with our scheme. The results of the experiments show that the approach is highly effective in detecting phishing URLs and attained an accuracy of 97.8% with 1.06% false positive rate, 0.5% false negative rate, and an error rate of 0.3%. The proposed scheme performs better compared to other selected related work. This shows that our approach can be used for real-time application in detecting phishing URLs.
Analysing the Potential of Blockchain for the Accounting Field in Indonesia

This research aims to identify and analyze the potential of blockchain technology for the accounting field in Indonesia. This research was conducted at the Indonesian Blockchain Association. This research uses qualitative methods with the case study approach and analysis of making explanation strategies. The result of this study indicates that blockchain is applicable in Indonesia without having to use cryptocurrency as a payment tool. The result finds that blockchain can be used as a technology for Accounting Information System. One of the reasons is that all accounting transactions have the potential to be traceable with the blockchain. The data in this technology can be considered as relevant information due to the nature of blockchain as a technology that records and stores data that cannot be changed and manipulated. Blockchain will be used as a database and data procession will still be carried out by using the Accounting Information System. Blockchain is unable to automatically process data into information that may be needed in accounting. This research is expected to strengthen the theory related to blockchain as one of the accounting technologies, also to be an initial step in improving the concept of triple-entry accounting that is usable in Indonesia by using Blockchain which is supported by other platforms such as ERP and uses Token as the representative of assets or financial in recording transactions.
Model-Agnostic Post-Processing Based on Recursive Feedback for Medical Image Segmentation

In medical image segmentation, post-processing can effectively improve the performance of a segmentation model. Existing post-processing methods generally require additional training of a post-processing model using training data or designing a post-processing procedure based on a high level of domain knowledge. Their application is limited in many real-world situations due to the lack of prerequisites. In this study, we present a post-processing method that can be applied to any existing segmentation model without requiring the use of training data or domain knowledge. Given a segmentation model of any type, the proposed method improves its prediction based on the recursive feedback mechanism. For a query image, we first obtain its prediction mask by using the segmentation model. Based on the prediction mask, we modify the original image by selectively blurring the area in which the target object is expected to be absent. Subsequently, the modified image is fed again into the model to acquire a refined prediction mask. We repeat this process to obtain multiple prediction masks, which are then combined to yield the final prediction. We verified the effectiveness of the proposed method through experiments using real-world medical datasets.
Interactive E-Module for Science Learning Content: Validity and Feasibility

Lack of use and development of teaching materials, especially in science content, which causes learning activities not to run optimally. This study aims to develop an interactive e-module with science content that has been tested for validity. This development research uses the ADDIE development model which consists of five stages, namely analysis, design, development, implementation, and evaluation. However, this research was only carried out until the development stage, the implementation and evaluation stages were not carried out due to time, resource and financial limitations caused by the current pandemic conditions. The subject in this study was an interactive e-module with science content, while the object in this study was the validity of an interactive e-module with science. This development research uses a questionnaire method by distributing assessment sheets to respondents, namely, material experts, media experts, and practitioners. The results of the validity test of the interactive e-module on the IPA content are in the form of numbers that are calculated as the average score then categorized into the five scale guideline table. The assessment of two material expert lecturers obtained an average score of 4.5 with very good qualifications. The assessment of two media expert lecturers obtained an average score of 4.8 with very good qualifications and the results of the practitioner's assessment consisting of two homeroom teachers in grade V SD obtained an average score of 4.9 with very good qualifications. Based on the results of the analysis obtained, it can be concluded that the interactive e-module with science content is very good qualifications.
OSCAR: A Low-Cost, Open-Source Robotic Platform Design for Cognitive Research

Research in cognitive robotics has been traditionally carried out in high-end research robots. This poses a barrier to many research institutions that cannot handle the costs associated with purchasing and operating this type of robot. In this paper, the design of a low-cost and open-source robot called OSCAR is presented. This robot was purposely designed to adapt to manipulation tasks in the context of cognitive robotics. The morphology, sensors equipped and software architecture of the robot are explained. Moreover, an initial implementation based in the Gazebo simulator is used to carry out an experiment involving a manipulation task using the Multilevel Darwinist Brain cognitive architecture. Results show that OSCAR is capable of learning a task and to obtain general information of its environment when paired with a cognitive architecture.
Factors Inducing Literature Anxiety for Students Studying Literature in English

Students have been plagued with various types of anxieties in the educational context, hence we propose to introduce the concept of literature anxiety in this study. This study investigates the possible factors inducing literature anxiety from the perspectives of university students studying Literature in English at tertiary level, and records their emotional experiences during their learning encounters with Literature in English. The study also presents how these students make sense of their Literature in English learning and how their knowledge and perceptions of Literature in English have influenced or affected their experience of literature anxiety. SPSS analysis of the data procured through the Literature Anxiety Scale (LITAS) provided evidence concerning students’ literature anxiety and the factors they perceive inducing literature anxiety for them. The literature anxiety-inducing factors were identified as situational, dispositional, and environmental factors. The findings obtained showed that students’ literature anxiety does debilitate their studying of Literature in English. The implications are that educators should teach more attentively and be sensitized to learners’ possible experience of anxiety.
SMART EDUCATORS FOR DIGITAL AGE STUDENTS

The purpose of this study was to review the shifting paradigm of educators that should be adjusted to the development and needs of the current generations or in other words educators must be smart to digital age students. This study was conducted by previous studies and associated with the facts that occur at this time or also known as a literature study. The data analysis method used in this study is descriptive analysis method. Results showed that the root reason to shift the old paradigm in education system is not just about technology, but it tends to the needs of â€˜new environmentâ€™ in learning process for digital age students. Having good skill in technology is a must, but smart educators have greater challange to interprate that skill to create an interesting learning process to absorb the best result from the education system. That is why educators have to shift the old paradigm in education system. Educators have to improve their creativity to create an enjoyable class to attract studentsâ€™ attention.
Optimization of multiplier in reversible logic

Reversible logic is leading area in power consumption.Based on its application, its emerging trend in power consumption.In ideal situations, reversible circuit yield nil power.Different methods of multiplier optimized in this paper.Like quantum computers, multipliers required to develop computational units.In the paper, two different methods of multiplier developed with very large bit width.Based on partial products hierarchical method is developed.Another method is Karatsuba's algorithm developed based on divide and conquers method.Finally, we compare the results of both two methods.The projected reversible multipliers are enhanced in terms of quantum cost, number of constant inputs, number of garbage outputs and complexity in hardware.In nanotechnology applications this multiplier can be used to construct complex system.
Aplikasi Penilaian Lomba Burung Murai Batu Berbasis Android

This research aims to design and build an Android-based Magpie Batu race evaluation app. The appraisal application is one of the media used in the judging process for judges to participants in the bird competition. Based on the results of observations on Saturday's cheerful contest. It was found that the current system was still manual using paper, pen and flag media to determine the results of the race and the process the calculation of the value after the end time is also still manually with counting the total number of values ​​obtained can only be known which bird won, so it was less effective in the assessment of the Magpie Stone race. The system development method in this application uses the Luther method which consists of several stages, namely concept, design, material collecting, assembly, testing, distribution. To measure the success of this application, alpha testing is done to test the validity of the product to design experts, material experts, linguists and media experts. The results expected in this study are in the form of an Android-based appraisal of the Magpie Stone contest as a media for the Magpie Stone race in Pagar Alam City.
A Hybrid of two Homomorphic Encryption Schemes for Cloud Enterprise Resource Planning (ERP) Data

Data confidentiality and privacy has been one of the major challenges in cloud Enterprise Resource Planning (ERP) deployment.There are different techniques to help provide enhanced security and data confidentiality.In this paper, a hybrid of two different Homomorphic encryption schemes is proposed to further enhance security and data confidentiality of ERP data.The Paillier and RSA Cryptosystems are modified and applied to form a two-layer encryption scheme.A successful implementation of the proposed hybrid of two homomorphic encryption scheme without sharing keys with the cloud is realised.The security of the Cloud ERP Data is enhanced by the modification of the Paillier Cryptosystem with the introduction of a new parameter g f to the Paillier Cryptosystem.The scheme also introduced a random parameter r g to help generate the value of g f .The simulation results reveals that the proposed scheme achieved improvement in the encryption time, decryption time and better throughput when compared with other schemes.The proposed scheme achieved six (6) percent improvement on encryption time,about thirty-two (32) percent improvement in decryption time as well as seven (7) percent improvement on throughput.
Perceptual hashing method for video content authentication with maximized robustness

Abstract Perceptual video hashing represents video perceptual content by compact hash. The binary hash is sensitive to content distortion manipulations, but robust to perceptual content preserving operations. Currently, boundary between sensitivity and robustness is often ambiguous and it is decided by an empirically defined threshold. This may result in large false positive rates when received video is to be judged similar or dissimilar in some circumstances, e.g., video content authentication. In this paper, we propose a novel perceptual hashing method for video content authentication based on maximized robustness. The developed idea of maximized robustness means that robustness is maximized on condition that security requirement of hash is first met. We formulate the video hashing as a constrained optimization problem, in which coefficients of features offset and robustness are to be learned. Then we adopt a stochastic optimization method to solve the optimization. Experimental results show that the proposed hashing is quite suitable for video content authentication in terms of security and robustness.
A Semantic Agent-Based Safety Model for Alzheimer’sPatients for Driving

Alzheimer’s disease drastically affects the human neurological system, causing the death of neurons and synapses in cerebral cortex and other regions. Consequently, patients with Alzheimer’s disease require 24/7 care and assistance with daily life activities. This study uses an ontology-based semantic model to assist the Alzheimer’s patients through activity recognition in the focused scenario of driving. The safety model presented in this paper alerts the user if anything dangerous is about to happen when they enter a car or during driving. It should be noted that the model is specifically designed for the patients suffering from a mild form of Alzheimer’s disease. We have used semantics to define the objects and environment for the patients. After proper monitoring and evaluation, our model suggests a proper course of action based on semantic reasoning.
Secure Symmetric Keyword Search with Keyword Privacy for Cloud Storage Services

As Internet services are widely used in various mobile devices, the amount of data produced by users steadily increases. Meanwhile, the storage capacity of the various devices is limited to cover the increasing amount of data. Therefore, the importance of Internet-connected storage that can be accessed anytime and anywhere is steadily increasing in terms of storing and utilizing a huge amount of data. To use remote storage, data to be stored need to be encrypted for privacy. The storage manager also should be granted the ability to search the data without decrypting them in response to a query. Contrary to the traditional environment, the query to Internet-connected storage is conveyed through an open channel and hence its secrecy should be guaranteed. We propose a secure symmetric keyword search scheme that provides query privacy and is tailored to the equality test on encrypted data. The proposed scheme is efficient since it is based on prime order bilinear groups. We formally prove that our construction satisfies ciphertext confidentiality and keyword privacy based on the hardness of the bilinear Diffie–Hellman (DH) assumption and the decisional 3-party DH assumption.
Improving Abstractive Summarization with Commonsense Knowledge

Large scale pretrained models have demonstrated strong performances on several natural language generation and understanding benchmarks.However, introducing commonsense into them to generate more realistic text remains a challenge.Inspired from previous work on commonsense knowledge generation and generative commonsense reasoning, we introduce two methods to add commonsense reasoning skills and knowledge into abstractive summarization models.Both methods beat the baseline on ROUGE scores, demonstrating the superiority of our models over the baseline.Human evaluation results suggest that summaries generated by our methods are more realistic and have fewer commonsensical errors.
Cognitive Interest As An Activator For The Development Of Teacher Leadership Qualities

The article dwells on constructing more effective forms, models, ways, and conditions for teaching and fostering the desire for learning.New approaches to teaching require new criteria for a teacher personality thus forming a new-generation teacher, with a new type of thinking.A cognitive interest may be a contributing factor to this process.First of all we have to motivate students' interest in learning which is based primarily on scientifically oriented higher education content components.As any psychic process and even as a personality orientation, a cognitive interest is formed in the course of activities.Against the background of a positive attitude towards learning, learning activities and persons and objects involved therein, the learning process organized by a teacher leader also allows developing leadership qualities among students through a cognitive interest.The efforts involved in developing teacher leadership skills through a cognitive interest is worthy in all respects -it improves knowledge, favors a teacher personal development, helps to overcome difficulties, affects the entire nature of work improving the ways of working, favors further education and self-education, and improves a high-school teacher's personality as a whole.According to the author, it has a positive impact on the students and allows improving the quality of education.
The effect of REACT strategy assisted by GeoGebra software on students' mathematical representation ability

This study was conducted to determine the effect of REACT strategy assisted by GeoGebra software on students' mathematical representation ability. This study was quasi-experimental with a quantitative approach. The design used in this study was The Nonequivalent Posttest Only Control Group Design. Four posttest questions were given to 25 students of Class VIII A and 25 students of Class VIII B at SMP Negeri Arun Lhokseumawe (public middle school). The data obtained from the posttest results were analyzed by data normality test and data homogeneity test, then hypotheses were tested using a t-test to see the effect of REACT strategy assisted by GeoGebra software on students' mathematical representation ability. The results of the data analysis of the posttest score tested using the t-test, the sig value was obtained. (2-tailed) of 0.000 &gt; 0.05. This showed that there was a significant effect of using the REACT strategy assisted by GeoGebra software on students' mathematical representation ability.
The Strategic Goals of -Using Service Oriented Architecture Principles

Organizations use heterogonous systems and legacy systems, they are implemented at different platforms, different databases, and different language programs. These systems need to exchange information and reuse the same functionality to achieve integration between these systems. Many Software companies failed to achieve information follow and reuse the same functionality. This paper introduces guidelines introduces Service-Oriented Architecture Principles guidelines and rules to help Applications developers to achieve information integrations and reuse the same functionality, SOA principles providing rules and guidelines that specify exactly how solution logic should be decomposed and molded into technology solutions