Reviewerly/exHarmony huggingface dataset:
Reducing catastrophic forgetting problem in streaming data by Hybrid Shark Smell with Jaya Optimization-based Deep Neural Networks

Catastrophic forgetting is a well-known characteristic of diverse parameterized supervised learning models. Artificial Neural Networks (ANN) face severe catastrophic forgetting or catastrophic interference in the sequential learning of information that is intolerable to both engineering applications and the human memory model. This problem can be solved through the machine learning community. The main intent of this paper is to implement a novel continuous learning model that could overcome the problem of catastrophic forgetting. The stream data from diverse benchmark sources are used for experimenting. The proposed model adopts the Deep Neural Network (DNN) with testing weight updates. When new data are given, the hybrid meta-heuristic algorithm helps to update the weight that manages to prevent the learning from catastrophic forgetting. The weight update strategy for solving the catastrophic forgetting is done by the hybridization of Shark Smell Optimization (SSO) and Jaya Algorithm (JA) that is named as Hybrid Shark Smell with Jaya Optimization (HSS-JO). A multi-objective function concerning the parameters associated with catastrophic forgetting like accuracy and remembering is used for framing the proposed continuous learning. The proof of the proposed model over conventional models on three publicly available datasets is given for final validation. From the analysis, in Table 3, the accuracy of the proposed HSS-JO-DNN is 38%, 0.5%, 0.55%, 0.14%, 0.98%, and 0.5% superior to DT, NB, KNN, SVM, NN, and RNN, respectively. For dataset 2, the FNR of the proposed HSS-JO-DNN is 90% superior to DT, 89% improved than NB, KNN, and NN, 94% improved than SVM, and 24% improved than RNN. Similarly, the proposed HSS-JO performance is higher in all the results. Thus, the proposed HSS-JO performs better than all the other traditional methods.
Klasifikasi Physical Activity Berbasis Sensor Accelorometer, Gyroscope, dan Gravity menggunakan Algoritma Multi-class Ensemble GradientBoost

The current generation of smartphones is increasingly sophisticated, equipped with several sensors such as accelerometer, gravity sensor, and gyroscope that can be used to recognize human activities such as going up stairs, going down stairs, running and walking. To get information, the data will be grouped using statistical methods. The performance of statistical methods has shortcomings in classifying data because of the procedures that must be met. To cover this shortcoming, the ensemble technique is used. In this paper, we propose to apply the Multi-Class Ensemble Gradientboost algorithm to improve the performance of the logistic regression method in classifying such as climbing stairs, descending stairs, running and walking. The process of taking data using a smartphone by designing an Android-based .apk system. Then, the entire dataset was separated into training data and test data with a comparison percentage of 70:30. The results obtained show that the Multi-Class Ensemble Gradientboost algorithm succeeded in increasing the logistic regression performance by 27.93%
HIGHLY DELICATE PIN ACCESSIBILITY FOR ATM USING HUMAN BODY COMMUNICATION

Frauds happening in ATM have increased over a period of time. With the evolution of Mobile Technology and Smartphones, wireless devices can be used for PIN authentication and transmission but they require network connectivity and only an active user can perform successful transactions though they provide security. Researchers are striving hard to eradicate the frauds happening by coming up with new technologies. In this paper, we use face and fingerprint recognition combined with Red- tacton technology which will provide additional security and minimize the chances of frauds happening in ATM. Here a body based communication is performed. A system for secure transactions in an ATM machine is proposed. These processes are used to reduce processing time for identification and identification processes. Here we are using a new technology called RED-TACTON, which has a transmitter and receiver section that communicates information through the human body. At first the client should put place a fingerprint to get to the ATM, and when the client touches the ATM, the client can touch the transmitter module where the password is put away, implying that the receiver will naturally send the information (password). In this system, hacking is not possible, security is high and it reduces fraudulent transactions.
Understanding the Impact of Development Efforts in Code Quality

Today, there is no company that does not attempt to control or assure software quality in a greater or lesser extent. Software quality has been mainly studied from the perspectives of the software product and the software process. However, there is no thorough research about how code quality is affected by the software development projects&amp;rsquo; contexts. This study analyses how the evolution of the development effort (i.e., the number of developers and their contributions) influences the code quality (i.e., the number of bugs, code smells, cloning, etc). This paper presents a multiple case study that analyses 13 open-source projects from GitHub and SonarCloud, and retrieves more than 95,000 commits and more than 25,000 quality measures. The insights are that more developers or higher number of commits does not necessary influence worse quality levels. After applying a clustering algorithm, it is detected an inverse correlation in some cases where specific efforts were made to improve code quality. The size of commits and the relative weight of developers in their teams might also affect measures like complexity or cloning. Project managers can therefore understand the mentioned relationships and consequently make better decisions based on the information retrieved from code repositories.
Portfolio of Compositions

Author(s): de Filippo, Stephen | Advisor(s): Reynolds, Roger | Abstract: The music composition portfolio consists of three works presented in three chapters. The first chapter titled “Casuarina-salvaged Dreaming” includes a work for eight performers plus electronics, lasting for approximately 10 minutes. This composition was premiered by the graduate students of UC San Diego’s Department of Music, and conducted by Steve Schick. The work is presented in a semi-flexible time-banned system whereby the conductor can assert some agency in the duration of the composition. The electronics utilise sound sources that are localised within the Southwest of Australia, and these samples are drawn randomly from different categorised pools with differing durations, and cast across the 4 channels of the concert hall. Then, the ensemble reacts, replicates, and maneuvers around these electronics.The second chapter consists of a 6-minute composition for a small chamber ensemble entitled “a moment exposed”. Through this work I focus on creating a extensive introduction, a dialogue between the clarinet and violin. The two instruments paired together, performing in a sort of chaotic unity where the two instruments interact and replicate each other's gestures in a raucous opening — acting together, but vocal in insisting on their own instrumental identity. Often, the clarinet sits above the violin’s register, with the violin utilising more of its lower register — the 4th string is also tuned lower to ground the violin further. Out of the pair’s final explosion emerges the rest of the ensemble. The two low strings are in their upper register, and the piano vamps soft chords — acting as a cloud which sits underneath the interjections of the clarinet and violin.Chapter three is entitled “Star Picc” for amplified piccolo, vocoder, tape, and a big drum. This work features live processing of the piccolo using pitch shifter. The shifter has 6 independent lines, one for each channel. The speakers are separated with the left channel next to the performer, and the right channel behind the audience — becoming more present in the latter half of the work. The piece explores contemporary performance practice, contrasted against kitsch robotic sounds in the fixed media and electronic pitch bending in its processing.
Crisis management in small and medium scale enterprises: a systematic literature review

The study presents the findings of a systematic literature review of crisis management in Small and Medium Scale Enterprises (SMEs) referring to recent literature. Crisis management studies have received significant attention in academic research. This can also be observed in organizational crisis management. Compared to larger organizations, the attention received for SMEs was inadequate. Recognizing the dearth of SME crisis management studies in the existing literature of crisis management, this systematic literature review on SMEs aims to recognize the issues around academic research on SME crisis management and to identify the strategies applied by small business entrepreneurs against crisis vulnerability. Thus, two questions are addressed: what has been done in SME crisis management research, and what trends have marked this phenomenon in research arenas. This review considered 181 research articles published on SME crisis management since 2000. Exploring the existing SME crisis management literature identified three major themes: Crisis preparedness measures, Crisis impact on SMEs, and SMEs' strategic approach. Following the identification of gaps in the literature, the findings suggest future research areas of SME crisis management with organizational perspective, crisis experience towards crisis learning, crisis learning as a strategic approach, and networking as a social coping strategy. The synthesis action also directed future research in the field.
ANALISIS RESPON SISWA PADA PEMBELAJARAN MENGGUNAKAN MEDIA BERBASIS E-LEARNING

Abstract: The purpose of this study was to determine student responses to learning using e-learning based media. The research approach was quantitative descriptive with the research subjects being 20 students in SMPN 3 Sape. The research data was collected through a Likert scale questionnaire with 10 items with four alternative answers, namely strongly agree, agree, disagree and strongly disagree. The results showed that of 20 students had a positive response to the use of e-learning based media in the world of education. Students' responses to the use of e-learning based media were seen from several aspects namely; 1) Interactive aspects; and 2) Aspects of utilization. The interactive aspect got an average score of 2.97 and was included in the good category and there were a number of items that had an average score of 1.6 and 1.85 with a less good category found in items three and five. The utilization aspect gained an average score of 2.68 in both categories. Aspects of utilization there are several items that obtain an average score of 3.45 and 3.6 with very good categories contained in items seven, eight and nine.Keywords: mathematics learning, e-learning.
Dynamic way of remediating product & item attributes for ecom or stores

Product Attributes are key to the Ecom Sales; As Customers may search based on any Attributes of a Product like Brand, Color, Gender, style etc of a Category; Search results of Products could be from different Departments & Categories with same Attributes and would be challenging in determining which Product the Customers are interested in. Also challenges of incomplete Product attributes in the Catalog & inaccurate Taxonomy and its relationships. How to handle these Product & Item Challenges? Also addressing Data Quality issues of Item & Product. How to handle Product attributes if they are Not same on Omni channel like Stores, Ecometc.
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning

Behavioral cloning has proven to be effective for learning sequential decision-making policies from expert demonstrations. However, behavioral cloning often suffers from the causal confusion problem where a policy relies on the noticeable effect of expert actions due to the strong correlation but not the cause we desire. This paper presents Object-aware REgularizatiOn (OREO), a simple technique that regularizes an imitation policy in an object-aware manner. Our main idea is to encourage a policy to uniformly attend to all semantic objects, in order to prevent the policy from exploiting nuisance variables strongly correlated with expert actions. To this end, we introduce a two-stage approach: (a) we extract semantic objects from images by utilizing discrete codes from a vector-quantized variational autoencoder, and (b) we randomly drop the units that share the same discrete code together, i.e., masking out semantic objects. Our experiments demonstrate that OREO significantly improves the performance of behavioral cloning, outperforming various other regularization and causality-based methods on a variety of Atari environments and a self-driving CARLA environment. We also show that our method even outperforms inverse reinforcement learning methods trained with a considerable amount of environment interaction.
A Research Road Map for Building Secure and Resilient Software-Intensive Systems

Poor software engineering processes can result in insecure and brittle software-intensive systems. A new U.S. agenda addresses this by advancing development and architectural paradigms, and by providing concrete research and development recommendations. We propose that the security community works closely with the software engineering community to realize secure, resilient software-intensive systems.
IMAGE QUALITY IMPROVEMENT BY ARTIFICIAL INTELLIGENCE

Today, the generally accepted resolution standard is 4K, and we are moving towards 8K screens. Youtube started supporting 4K for video downloads back in 2010 — then many manufacturers began to produce inexpensive cameras in this format. Since then, displays and smart TVs with 4K support have dropped significantly in price and gained popularity. Despite the fact that the human eye can hardly physically notice the difference in a picture with a quality over 4K, the race for higher resolution continues. Owners of Ultra HD displays can most fully experience the capabilities of their screens when viewing native 4K content. And videos with a lower resolution have to be stretched to the whole screen, because, for example, images in 1080p (Full HD) contain only a quarter of the pixels of a 4K picture. You can scale the image immediately on a smart TV, in a media player, or use special programs to improve the video quality
The Use of Environmentally and Online-Based Media and Its Effect on PAI Learning Outcomes

Learning media has an important position for the achievement of learning outcomes, theoretically there are various types of media that are commonly used, therefore, researchers want to analyze the implementation of PAI learning using environmental-based and online-based learning media and their effect on PAI learning outcomes in state elementary schools. The collected data is analyzed using SPSS Version 20.0 through the Classical Assumption Test, Percentage Descriptive Analysis, T (partial) and F (simultaneous) Test. The results showed pai learning using Environmental-Based Media and Online supports the effective implementation of learning. This is evident from the percentage of respondents' answers of 90.83% for environmentally based media and 90.14% for online-based media. Based on the constant value of PAI Learning Media Based Environment and Online Based which amounted to 81,289. This constant value means, if there is no Environmentally Based and Online-Based PAI Learning Media, then a consistent value of Learners' Learning Outcomes of 81,289 will not appear.
The Effectiveness of Reading Strategies Training to Teach Reading Comprehension

This study investigated the effect of reading strategies training technique on the students’ reading skill in literal and inferential comprehension. The training techniques were modified from the procedure developed by Brown and Palincsar (1984), which involved three concrete reading strategies: predicting, text mapping, and summarizing. To achieve the purpose of this study, the quasi experimental design was conducted with the experimental group was given reading strategies training technique and the control group was conventional technique. The subjects were two classes of office administration tenth grade students of SMKN 1 Sooko. The instrument of this study was test that used to compare the students achievement which used reading strategies training technique. The test for the post-test was constructed in multiple choices. In this study mid-test score is a covariate, it is used to know the students’ average score both experimental and control group before giving the treatment. The experimental data were subjected to descriptive statistics of mid-test score and post-test score, and both the analysis of covariance (ANCOVA) of post-test score in literal and inferential comprehension. Furthermore, the increase of the mean score of teaching reading comprehension by using strategies training technique is higher than the conventional technique group. It means that two groups both of experimental and control group differ significantly in literal and inferential comprehension.
Vokal improvisation : En studie i att sjunga med och mot harmoniken

In this bachelor thesis, I explored vocal improvisation and the terms “out playing” and “in playing”. My ambition was to find new ways of exploring and developing my approach to improvisation, depe ...
EOSC-SYNERGY EU Milestone: M2.1 Roadmap for infrastructure integration

EOSC-SYNERGY receives funding from the European Union’s Horizon 2020 researchand innovation programme under grant agreement No. 857647.
Sign Language to Text and Speech Conversion

Sign language is one of the oldest and most natural forms of language for communication. Since most people do not know sign language and interpreters are very difficult to come by, we have come up with a real-time method using Convolution Neural Network(CNN) for fingerspelling based American sign language(ASL). In our method, the hand is first passed through a filter and after the filter has applied the hand is passed through a classifier that predicts the class of the hand gestures.
Education Of Moral Culture Of Student Youth In The Conditions Of Polycultural Space

Problems of morality have not lost significance in all times of human existence, but contained different accents in social manifestations. Modern anthropocentric tendencies of social life have also changed value orientations, because material values, human self-presentation in society, the desire for recognition as a manifestation of self-worth, somewhat level the spiritual, moral and ethical, cultural values. Therefore, consideration of the tasks of educating the moral culture of in a multicultural space is significant, especially today. The education of the moral culture of student youth in the spirit of universal ideals begins in early childhood, which is an important stage in human development. After all, at this time the necessary skills begin to form, such as: thinking, conscious perception of the world around and one’s own place in it, communication with other people. The task of moral culture of student youth in a multicultural space is to build a process of transformation of socially significant norms, principles governing relationships, universal moral values into individual qualities and the formation on this basis of children’s views and beliefs. The main attention is paid to emphasizing the importance of educating the moral culture of youth at the university in a multicultural space. The paper analyzes the scientific literature on the need for the process of educating the moral culture of youth at the university in a multicultural space. Methodical recommendations on successful education of moral culture of youth at the university in multicultural space are offered. It is concluded that the education of moral culture of student youth in a multicultural space is an organic part of the inner world of man and the world around him. This process determines the ethical, aesthetic, ideological values and norms, traditions, habits of the individual. It is manifested in lifestyle, behavior, thinking, attitude to work, the environment. Education of moral culture of student youth in the conditions of multicultural space in education is called to prevent formation of the one-dimensional person.
REVIEW OF ANOMALY DETECTION IN INDUSTRIAL IOT

Over recent years, IoT has evolved into a paramount technology of the modern era. The data we share every day over this personified platform exposes one to a huge list of benefits. Now that it is possible to connect objects like home appliances, cars etc. to the internet, communication is possible between humans and things. The Internet has given us the comfort to control/automate the entire work whilst sitting in any part of the world. This network of “things” operates on huge amounts of real-time data. The data so collected is processed and is then used to make certain modelled decisions. This technology gives a vast implementation opportunity to all kinds of industries whether it be a product, service, or even security-based system. Although IoT technology can benefit humans in many possible ways, the risks involved cannot be ignored. The majority of risks involved are associated with the privacy and security of data. In this review paper, we discuss and deliver an organized literature review of the anomaly detection system with machine learning and deep learning models that help carry out the IoT process securely. On the basis of our study, academics and scholars can familiarize themselves with various methods and can use them to solve anomaly detection problem by developing novel techniques for predicting and detecting anomalies in Industrial IoT.
Information technology-based innovative teaching methods and entrepreneurship education: a literature perspective

The main objective of this paper is to provide the literature support for implementing innovative teaching methods with the help of information technology (IT) in entrepreneurship education (EE). A...
Aspect-Based and Multi-Level Sentiment Information Applying Contrast Dictionary

The customer feedbacks provide alternative and important sources to discover knowledge supporting the marketers and customers to make better decisions. However, the manual process to extract useful information depends on domain experts. This paper focuses on improving the performance of the automatic sentiment information extraction from customer feedbacks. The article proposes a new extraction method that consider multiple dimensions of feedback information, aspect, word, contrast, sentence or phrase, and document levels. The aspect-based sentiment extraction uses a named entity recognition technique to extract the desired aspects of a target product. The aspect-based sentiment combines with sentiment information from multiple levels of feedback contexts resulting in the fused sentiment information improves the extraction performance. We validate the effectiveness by measuring the accuracy of the sentiment and aspect recognition methods comparing with SentiStrength and Word-Count. This information gives some insights on customer satisfaction and can be applied in an alarming tool.
VỀ MỘT PHƯƠNG PHÁP ĐẢM BẢO AN TOÀN TRUY CẬP TÀI NGUYÊN ĐÁM MÂY

Cloud computing today is not only popular with business customers but also with educational customers. When all the owner's data is put on the cloud, the problem of secure access becomes more urgent than ever. This paper proposes a quantified role-based access control model for the cloud, providing an effective authorization solution and flexible permission adjustment when there are unauthorized accesses. The proposed solution againsts privilege escalation attacks based on the authorization mechanism for each role in each session of each different object. The analysis results are tested by the application in the IaaS cloud.