Reviewerly/exHarmony huggingface dataset:
A Proposed Technique for Simultaneously Detecting DDoS and SQL Injection Attacks

As people's reliance on the internet grows, they reveal their data without realizing the implications of a cyberattack.A cyberattack is any form of attack against one or more computers or networks to cause damage.These attacks have the potential to compromise network access, confidentiality, and data integrity.The most popular and powerful attacks to destroy an enterprise, server, or host are distributed denial-ofservice (DDoS) and Structured Query Language injection (SQLi).A distributed denial-of-service (DDoS) attack can freeze an entire website with an intention to ransomware or push viruses.On the other hand, with a successful Structured Query Language injection (SQLi) attack, hackers can access the secret information of a legit user.To deal with DDoS and SQL injection attacks, a variety of techniques have been developed.However, hackers use different techniques to breach security mechanisms, many of which are undetectable by most intrusion detection systems because of their unpredictability.In this paper proposal of a system is given that can detect DDoS and SQL injection attacks simultaneously.Right now, there is no such system that can detect both attacks at the same time.A secure way of browsing the internet and sharing information can be ensured with this system.Webservers will be more secured.
Towards a Reliability Prediction Model based on Internal Structure and Post-Release Defects Using Neural Networks

Reliability is one of the most important quality attributes of a software system, addressing the system’s ability to perform the required functionalities under stated conditions, for a stated period of time. Nowadays, a system failure could threaten the safety of human life. Thus, assessing reliability became one of the software engineering‘s holy grails. Our approach wants to establish based on what project’s characteristics we obtain the best bug-oriented reliability prediction model. The pillars on which we base our approach are the metric introduced to estimate one aspect of reliability using bugs, and the Chidamber and Kemerer (CK) metrics to assess reliability in the early stages of development. The methodology used for prediction is a feed-forward neural network with back-propagation learning. Five different projects are used to validate the proposed approach for reliability prediction. The results indicate that CK metrics are promising in predicting reliability using a neural network model. The experiments also analyze if the type of project used in the development of the prediction model influences the quality of the prediction. As a result of the operated experiments using both within-project and cross-project validation, the best prediction model was obtained using PDE (PlugIn characteristic) for MY project (Task characteristic).
Research on University-enterprise Cooperation Practical Education of New Engineering Majors under the Background of Integration of Industry and Education

With the implementation of the national strategy of “transportation power”, the transportation major is facing the transformation of new engineering majors. Practical education is an important link in the training of new engineering majors in application-oriented universities and plays a vital role in the quality of talent training. The transformation and upgrading of traditional majors has promoted the transformation of traditional school-enterprise cooperation to the integration of industry and education. Under the background of the integration of industry and education, the author puts forward some viewpoints, such as the precise orientation of talent training, the improvement of the system construction of practical education base, and the broadening of the practical education forms of the integration of industry and education. Taking Anhui Sanlian University as an example, This paper analyzes the practice and achievement of university-enterprise cooperative practical education construction for new engineering majors under the background of the integration of industry and education.
PERANCANGAN DAN PEMBUATAN MEDIA PEMBELAJARAN AUGMENTED REALITY PADA PENGAJARAN TEKNIK ELEKTRONIKA

This study aims to produce learning media for electronic components using Augmented Reality technology by knowing the performance and magnitude of the feasibility value of learning media for electronic components using the Augmented Reality technology. Designing and making applications using the steps of the waterfall method include: 1) Designing, 2) Architectural Design and Interfaces, 3) Encoding / Programming, and 4) Testing. Application programs are made with laptops that have Intel®core ™ i3 CPU@2.00GHz processor specifications, 4.00GB RAM, Intel® HD Graphics520, 1TB hard drive, with a Windows 10 Pro 64-bit X64 operating system. Integrated Development Environment (IDE) in making this application is Unity 2018.3.6f1 with the marked based tracking method. Based on the results of the feasibility test conducted by two material experts as well as two media experts, that in the aspect of application material got an average value of a total score of 63 out of 68. In the media aspect the application got an average score of 84.5 from the total score of 96 Both of these scores give interpretation that the application of Augmented Reality learning media in teaching electronic engineering is very feasible to be used as a learning media.Keywords: Augmented Reality, Learning Media, Electronic Engineering, Unity 3D
CRYPTOCURRENCIES, COVID-19 PANDEMIC AND THE FINANCIAL BUBBLES: THE CASE OF TOP FIVE DIGITAL ASSETS

This study explores the bubble behavior in the prices of top five cryptocurrencies (i.e., Bitcoin, Ethereum, Ripple, Stellar, and Tether) using daily data of the closing level at the COVID-19 pandemic, covering the period from January 2, 2020 to January 2, 2021. The testing procedure of the bubble behavior in selected cryptocurrencies prices is investigated by two methodologies. Those covers the test statistics originated by the Supremum Augmented Dickey-Fuller (SADF) (Phillips et al., 2011) and Generalized Supremum Augmented Dickey-Fuller (GSADF) (Phillips et al., 2015) to define several bubble periods. The empirical results emphasize that bubble behavior is not a diverse and stable feature of Bitcoin, Ethereum, Ripple, and Stellar prices, except the Tether prices, which point out the emergence of a potential crisis in the digital assets market through an increasing degree of financial instability.
Sentiment Analysis Algorithms: Classifiers and Their Comparison

If consumers want something today, the manufacturer cannot let them wait until tomorrow. All businesses need to stay updated on opinion fluctuations over existing products or services so that they can improve upon and can stay ahead in this tough competition. This field of market research is called sentiment analysis and requires structuring of unstructured online text data on a vast scale. Various techniques have already been put forward for this. In this paper, we will study the performance of broadly four such techniques—K nearest neighbours, logistic regression, support vector machine and Naive Bayes, when they are applied on a large dataset of 8500 movie reviews. The comparison and conclusion will be drawn out on the basis of accuracy, precision score, training and testing time.
CREATIVE WRITING IN FOREIGN LANGUAGE TEACHING

The article is an attempt to reveal the role of creative writing in the process of foreign language teaching/learning at higher school. Approaches to teaching creative writing to students, who learn English as a first foreign language at the classes of business English, history of the English literature and practical course of the first foreign language are discussed. The effectiveness of creative writing assignments as independent work is proven.
Multi-scale methods for reconstructing collective shapes of digital diasporas

Abstract The ICT revolution has impacted the way diasporic groups and individuals communicate and interact with one another. Diasporas are now fueled by unlimited flows of digital contents generated by daily activities or sudden historical events. As a natural result, the science of migration has evolved just as much as its own subject of research. Thus, dedicated branches of research like digital diasporas emerge at the crossroad between fields of social and computational sciences. Thereupon, new types of multi-scale reconstruction methods are developed to investigate the collective shapes of digital diasporas. They allow the researchers to focus on individual interactions before visualizing their global structures and dynamics. In this paper, we present three different multi-scale reconstruction methods applied to reveal the scientific landscape of digital diasporas and to explore the history of an extinct online collective of Moroccan migrants.
Parallel impelementation of RC6 algorithm

Data security is very important in the field of Computer Science. In this paper the encryption algorithm called RC6 will be analyzed and its standard and parallel implementation will be done.&#x0D; First the field of Cryptology is discussed in general terms, then the classification of encryption algorithms according to operation and techniques is explained.&#x0D; RC6 is a symmetric block algorithm derived from the RC5 algorithm. RC6 operates on 128-bit blocks and accepts 128, 192, 256-bit keys until 2040 bytes. In the Advanced Encryption Standard (AES) competition, RC6 managed to rank among the five finalists.&#x0D; The structure of the RC6 algorithm will be analyzed also the encryption and decryption methods. The comparison between standard and parallel implementation will be made.
RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract)

Training agents to learn efficiently in multi-agent environments can benefit from the explicit modelling of other agent's beliefs, especially in complex limited-information games such as the Hanabi card game. However, generalization is also highly relevant to performance in these games, though model comparisons at large training timescales can be difficult. In this work, we address this by introducing a novel model trained using a sleep metaphor on a reduced complexity version of the Hanabi game. This sleep metaphor consists an altered training regiment, as well as an information-theoretic constraint on the agent's policy. Results from experimentation demonstrate improved performance through this sleep-metaphor method, and provide a promising motivation for using similar techniques in more complex methods that incorporate explicit models of other agent's beliefs.
Exploiting Cyclic Dependencies in Landmark Heuristics

Landmarks of a planning task denote properties that must be satisfied by all plans. Existing landmark heuristics exploit that each landmark must be achieved at least once. However, if the orderings between the landmarks induce cyclic dependencies, one of the landmarks in each cycle must be achieved an additional time. We propose two novel heuristics for cost-optimal planning that consider cyclic dependencies between landmarks in addition to the cost for achieving all landmarks once. We show that our heuristics dominate the minimum hitting set solution over any set of landmarks as well as h+ if all delete-relaxation landmarks are considered. An experimental evaluation on benchmarks from the International Planning Competition shows that exploiting cyclic dependencies can lead to improved heuristics.
PROSPECTS OF THE MOBILE APPLICATIONS USE IN THE PROFESSIONAL TRAINING OF FUTURE TEACHERS OF MATHEMATICS

The relevance of the problem under consideration. The use of modern developments in the field of mobile digital technologies will intensify the process of teaching professional disciplines in the system of pedagogical education of future teachers of mathematics, which encourages the study of the specifics of using mobile applications in the training of future teachers of mathematics. The purpose of the study is to reveal the possibilities of introducing mobile applications in the process of teaching mathematical disciplines to future mathematics teachers. Research methods. Theoretical (analysis, systematization and generalization of pedagogical and psychological research, curricula for future teachers of mathematics) and empirical (pedagogical observation of the educational process, questionnaires) methods. Results of the research. By mobile learning we mean the process of creating a mobile educational environment with the use of mobile technologies for access to educational resources, implemented in face-to-face and distance forms. Active use of mobile educational applications leads to changes in the content of education, learning technology and in the relations between the participants of the educational process, allows to individualize learning, make it more adequate to the abilities of students. According to the survey results, the least attention in the study of mathematical disciplines is paid to applied mobile applications for mathematical calculations, but specialized programs and applications installed on mobile devices make them real assistants to teachers of mathematical disciplines and students of mathematical specialties. Our survey shows that the mobile application PhotoMath is the most popular among students when studying mathematical disciplines. We analyzed the possibilities of using the mobile application PhotoMath in the study of mathematical analysis by students of pedagogical universities.
A Novel Discrete Particle Swarm Optimization Algorithm for the Travelling Salesman Problems

There are Optimization Problems that are too complex to be solved efficiently by deterministic methods. For these problems, where deterministic methods have proven to be inefficient, if not completely unusable, it is common to use approximate methods, that is, optimization methods that solve the problems quickly, regardless of their size or complexity, even if they do not guarantee optimal solutions. In other words, methods that find “acceptable” solutions, efficiently. One particular type of approximate method, which is particularly effective in complex problems, are metaheuristics. Particle Swarm Optimization is a population-based metaheuristic, which has been particularly successful. In order to broaden the application and overcome the limitation of Particle Swarm Optimization, a discrete version of the metaheuristics is proposed. The Discrete Particle Swarm Optimization, DPSO, will change the PSO algorithm so it can be applied to discrete optimization problems. This alteration will focus on the velocity update equation. The DPSO was tested in an instance of the Traveling Salesman Problem, att48, 48 points problems proposed by Padberg and Rinaldi, which showed some promising results.
Densely connected Siamese network visual tracking.

Visual object tracking plays a significant role in intelligent robot systems. This study aims to focus on unlocking the tracking performance potential of the deep network and presenting a dynamic template update strategy for the Siamese trackers.,This paper presents a novel and efficient Siamese architecture for visual object tracking which introduces densely connected convolutional layers and a dynamic template update strategy into Siamese tracker.,The most advanced performance can be achieved by introducing densely connected convolutional neural networks that have not yet been applied to the tracking task into SiamRPN. By using the proposed architecture, the experimental results demonstrate that the performance of the proposed tracker is 5.8% (area under curve), 5.4% expected average overlap (EAO) and 3.5% (EAO) higher than the baseline on the OTB100, VOT2016 and VOT2018 data sets and achieves an excellent EAO score of 0.292 on the VOT2019 data set.,This study explores a deeper backbone network with each convolutional network layer densely connected. In response to tracking errors caused by templates that are not updated, this study proposes a dynamic template update strategy.
Distributed Training of Embeddings using Graph Analytics

Many applications today, such as natural language processing, network and code analysis, rely on semantically embedding objects into low-dimensional fixed-length vectors. Such embeddings naturally provide a way to perform useful downstream tasks, such as identifying relations among objects and predicting objects for a given context. Unfortunately, training accurate embeddings is usually computationally intensive and requires processing large amounts of data. This paper presents a distributed training framework for a class of applications that use Skip-gram-like models to generate embeddings. We call this class Any2Vec and it includes Word2Vec (Gensim), and Vertex2Vec (DeepWalk and Node2Vec) among others. We first formulate Any2Vec training algorithm as a graph application. We then adapt the state-of-the-art distributed graph analytics framework, D-Galois, to support dynamic graph generation and re-partitioning, and incorporate novel communication optimizations. We show that on a cluster of 3248-core hosts our framework GraphAny2Vec matches the accuracy of the state-of-the-art shared-memory implementations of Word2Vec and Vertex2Vec, and gives geo-mean speedups of 12 x and 5 x respectively. Furthermore, GraphAny2Vec is on average 2 x faster than DMTK, the state-of-the-art distributed Word2Vec implementation, on 32 hosts while yielding much better accuracy.
The Study of Privacy Protection of Scientific Data Sharing Based on Data Life Cycle

Abstract Scientific data sharing has become an important activity to promote modern research findings in which helps to reduce costs and save time for data collection, but it also brings certain privacy issues when using scientific data. First, based the network and literature survey method to described the basic conceptual of scientific data sharing, and discussed the issues of privacy violation in scientific data sharing during the data lifecycle. Second, tried to propose a privacy protection model and framework to prevent privacy violation. Finally, provided some suggestions for the current privacy protection in scientific data sharing from different perspectives. The study contributes to the scientific data sharing by shedding light on how to protect privacy of scientific data sharing through the privacy protection model and framework.
Privacy-Preserving Algorithm for Decoupling of Multi-Agent Plans with Uncertainty

The execution of multi-agent plans often requires communication between agents in order to synchronize their tasks. In cases where communication is unreliable or undesirable, temporal decoupling algorithms allow agents to find a distributed execution strategy beforehand without requiring perfect communication on the fly. The state-of-the-art Multi-Agent Simple Temporal Network with Uncertainty (MaSTNU) framework extends the decoupling problem for Multi-Agent Simple Temporal Network (MaSTN) to allow the modeling of uncertain durations and allow agents to communicate when certain events occur and communication is available. However, the existing approach assumes centralized knowledge of the MaSTNU, whereas in the multi-agent context, privacy is an important concern. In this paper, we propose a distributed, privacy-preserving algorithm for finding distributed execution strategies for MaSTNU. Experiments also showed significant speed-up of the proposed algorithm when the multi-agent plan is loosely coupled and mostly private.
REKAYASA SISTEM INFORMASI PROMOSI DAN PENGELOLAAN JASA STUDIO FOTO BERBASIS WEB

The information system appear give support and advantages in all areas of life. One of them is on economic. Photo studio is a part of economic field. Photo studio that offer photography and video recording service have a broad target market. Photo studio still use manual system and have not utilized the information system optimally in promote and manage it system that can causes many problems. For example, the problem in inform service packages, problem in booking that has impact to report. The purpose of information system is to minimize mistakes and optimize the promotion that offer by provider photograph services (photo studio, photographer and freelance videographer). Show detail information such as : portfolio and art gallery. So, customers can order easily. Information system also can give order report in periodic time for provider services. Information systems designed by waterfall method. Developed with php language, laravel framework and Mysql database.Keywords : Information systems, Photo Studio, Management, Laravel Framework.
Student’s Grammar Mastery of Simple Present Tense by Using Egra (Exposure, Generalization, Reinforcement, And Application) Method

Nowadays English send to be the crucial language in the world. The existence of English subject should be focus on the grammar. Because grammar stated as the complicated thing in English. This study focused on simple present tense, teaching English subject especially in simple present tense generally make students felt bored because they did not feel confidence and felt difficult in understanding the material. Here, EGRA method to be alternative of the problem in which the EGRA method can make make students more enthusiastically in learning and confident in simple present tense. EGRA is an acronym of four major learning styles for student’s confidence and confidence, namely Exposure, Generalization, Reinforcement, and Application. Many researcher found that teaching by using EGRA method give well understanding for students in learning a new language. It can be shown that students become more creative, active and communicative in the class. The success of learning also depend on the method used by the teacher. Here the EGRA method used to fulfill the needed of student.
PENGEMBANGAN E-COMIC BERBASIS ANDROID SEBAGAI MEDIA PEMBELAJARAN PADA MATERI KEBIJAKAN MONETER DAN KEBIJAKAN FISKAL KELAS XI SMA PARAMARTA 1 SEPUTIH BANYAK

Instructional media playing an important role in the communication process between teachers and students optimally established. However, it has not fully met the needs of students in the learning process. In the development of science and technology and the existence of the 4.0 industrial revolution, it increasingly encourages various offorts to take advantage of technology, this can encourage the implementation of learning to be more varied oan innovative. The purpose of this development is to produce an Android-based E-comic media as instructional media on monetary and fiscal policy instructional material of xi grade of Paramarta 1 Senior High School, which is valid and practical. This research was conducted using R&amp;D (Research and Development) or development research with the 4D development model (Define, Design, Development, Disseminate). The process for developing E-comics begins with a validation stage by two media experts and one material experts. The e-comic was also tested in small groups to see the responses of Xl graders at Paramarta 1 Senior High School of Seputih Banyak. The results of the study show an increase, this is indicated by the results of the validation of the instructional media experts with a percentage of 91.2% with very strong criteria, the results of assessments by material experts with a rate of 91.4% with very strong criteria, and the results of online testing with small groups, ten from thirty students with a percentage of 88% included in the Very Strong standards. Based on the percentage obtained, e-comic is declared valid and practical to be used as instructional media.Keywords: Android, E-comics, Instructional Media, Technology