Reviewerly/exHarmony huggingface dataset:
Çok Katmanlı Derin Sinir Ağlarını Hibrit Algoritmalarla Eğiterek Ağlara İzinsiz Girişi Tespit Etmek

One of the challenges facing security analysts and administrators is to enable intrusion detection in network systems, preventing intruders from entering the network.Network intrusion detection is usually signature-based and plays an effective role in detecting only known attacks.However, there are concerns about unknown attacks and the difficulty arises here.Which requires creating a model that can detect network attacks by discovering anomalies in the network.Therefore, in this article, an approach to detecting attacks is presented by monitoring the behavior of data and training it to distinguish between network traffic, which is normal traffic, and traffic that is classified as an attack on the network.The known database was used NSL-KDD, a dataset that monitors network traffic including various types of network attacks and detects normal traffic, it also contains numerous patterns and features.It includes 41 features for each traffic and is divided into five classifications.The four types are classified as types of network attacks and the fifth as normal traffic.One of the difficulties and problems is the existence of a wide variety of features.This requires finding a way to extract features that can have a significant impact on the results to achieve greater accuracy in classifying the type of attack.For this reason, principal component analysis PCA technology has been used to reduce feature sizes.Six models were created which are hybrid algorithms to optimize the performance of a multi-layer neural network by training their weights to classify the attack type in the network.A two hidden layer deep neural network was designed, and their weights were trained by designing six hybrid models.These models are hybrid algorithms based on four optimization algorithms which are Genetic Algorithm, Artificial bee colony algorithm, firefly algorithm, and Jaya algorithm.Several metrics were used to evaluate the performance of the proposed models.This paper contributed to finding an effective network intrusion detection methodology and developing a deep neural network by building effective optimization algorithms.Where the proposed algorithms performed well with accuracy ranging from 77.177% to 85.077%.The proposed algorithms also achieved a low MSE loss rate close to zero with an MSE value of 9.99868e-05.Also, precision values range from 82 to 97%, and most of the proposed algorithms achieved high rates when calculating the sensitivity and specificity.The proposed models have contributed to finding a high-performance methodology for detecting intrusion on the network and contributed to proving that the hybrid algorithms used are effective and help to the optimization can be used in other studies.
The Correlation Between Students Achievement In Vocabulary And Speaking Ability at Grade 8 Junior High School Students

This research aimed to find out the correlation between students’ vocabulary mastery and speaking ability at grade 8 of SMP Negeri. This research was quantitative research which used correlational technique design. The sample of the research was 30 students of grade eight selected by clustering sampling. The instruments used in the research were vocabulary test and speaking test. Vocabulary test consisted of 50 questions of multiple choices, and speaking test in the form of role play. The research data were in the form of interpretation of students’ vocabulary and speaking test results, and their correlation. Based on data analysis, it was found that students’ vocabulary mastery and speaking ability were fair. They were proved by the mean score 65 for vocabulary mastery and 68 for speaking ability. Moreover, there was strong correlation between students’ vocabulary mastery and speaking ability. It was shown by the rvalue = 0,703 . Keywords:Students’ Achievement, Vocabulary, Speaking
Pengembangan bahan ajar e-book akuntansi keuangan kelas XII SMK pada materi aset tetap berwujud berbasis pendekatan saintifik

In 21st century education, the use of information technology is needed to facilitate learning activities, especially in the development of learning materials. For example, the use of electronic teaching materials in the form of e-books. The research was carried out with the aim of developing and analyzing the feasibility of the financial accounting e-book teaching material for class XII SMK in the material of tangible fixed assets based on a scientific approach as well as knowing the responses of students after being given e-book teaching materials. The 4D model by Thiagarajan, Semmel and Semmel is used in this research and development (R&amp;D) research. The steps taken are define, design, develop, while disseminate was not carried out. The research data were analyzed using quantitative descriptive analysis techniques. Obtaining the feasibility of the results of this study revealed that the validity of the material, language, and graphics were categorized as very feasible. A total of 20 students from class XII AKL SMK Rajasa Surabaya gave their responses to the e-book teaching material as a limited trial implementation that obtained a very well-understood interpretation. Thus, the e-book teaching materials for Financial Accounting class XII SMK on tangible fixed assets based on a scientific approach can be used in the learning process
MADE: Exploration via Maximizing Deviation from Explored Regions

In online reinforcement learning (RL), efficient exploration remains particularly challenging in high-dimensional environments with sparse rewards. In low-dimensional environments, where tabular parameterization is possible, count-based upper confidence bound (UCB) exploration methods achieve minimax near-optimal rates. However, it remains unclear how to efficiently implement UCB in realistic RL tasks that involve non-linear function approximation. To address this, we propose a new exploration approach via \textit{maximizing} the deviation of the occupancy of the next policy from the explored regions. We add this term as an adaptive regularizer to the standard RL objective to balance exploration vs. exploitation. We pair the new objective with a provably convergent algorithm, giving rise to a new intrinsic reward that adjusts existing bonuses. The proposed intrinsic reward is easy to implement and combine with other existing RL algorithms to conduct exploration. As a proof of concept, we evaluate the new intrinsic reward on tabular examples across a variety of model-based and model-free algorithms, showing improvements over count-only exploration strategies. When tested on navigation and locomotion tasks from MiniGrid and DeepMind Control Suite benchmarks, our approach significantly improves sample efficiency over state-of-the-art methods. Our code is available at this https URL.
Computerized or Automated Object Recognition and Analysis of Pattern Matching in Runways Using Surface Track Data

In today’s world, accurate and fast information is vital for safe aircraft landings. The purpose of an EMAS (Engineered Materials Arresting System) is to prevent an aeroplane from overrunning with no human injury and minimal damage to the aircraft. Although various algorithms for object detection analysis have been developed, only a few researchers have examined image analysis as a landing assist. Image intensity edges are employed in one system to detect the sides of a runway in an image sequence, allowing the runway’s 3-dimensional position and orientation to be approximated. A fuzzy network system is used to improve object detection and extraction from aerial images. In another system, multi-scale, multiplatform imagery is used to combine physiologically and geometrically inspired algorithms for recognizing objects from hyper spectral and/or multispectral (HS/MS) imagery. However, the similarity in the top view of runways, buildings, highways, and other objects is a disadvantage of these methods. We propose a new method for detecting and tracking the runway based on pattern matching and texture analysis of digital images captured by aircraft cameras. Edge detection techniques are used to recognize runways from aerial images. The edge detection algorithms employed in this paper are the Hough Transform, Canny Filter, and Sobel Filter algorithms, which result in efficient detection.
Play &amp; Fun Portal to Support “Steam” Learning Method in Early Childhood

The Covid-19 pandemic has forced learning to change.As stipulated by the government, students of all levels of education, from early childhood to higher education, must eventually study from home through online learning.The online learning process would be effective if it is supported by media and applications that suit the needs of the students.Currently, the e-learning portals seem to be relatively limited, such as Rumah Belajar, sekolah.mu,Zenius, and Ruang Guru.Online learning particularly for early childhood is unique because in this period children learn new things that will shape themselves.One of the most popular and important methods to apply is the STEAM method (Science, Technology, Engineering, Art, and Mathematics).This method aims to stimulate these five aspects in children.Within this framework, a learning portal that is specifically used for early childhood was made.The output of this research is a learning portal specially used for early age children named the "Play & Fun" portal.In this portal, two main contents are intended to support STEAM learning, namely learning videos of scientific themes and animation-based learning media applications.
Increasing Students' Ability In Writing Procedure Text Through Learning Model Pictures And Pictures

This study investigated increasing students' ability to write procedure text through learning model pictures and pictures in ninth grade at SMPN 4 Takengon. The study used the quantitative method with experimental design. To collect the data, the writer uses the test (pre-test and post-test). The population in this research is all students of the ninth grade in SMPN 4 Takengon, which consists of 196 students. The writer uses purposive sampling to take the sample in this research. A first group is an experimental group, which amounts to 37 students, and the second group is the control group which amounts to 37 students. The writer uses the t-test formula to analyze data in this research. The result of tscore is 5,71. Compared with the ttable, the tscore is higher, i.e., 5,71, than ttable is 1,99. It can be concluded that learning model pictures and pictures can increase students' ability in writing procedure text. The writer suggests that students try to write in English as habitual because it can help add more vocabulary and make the students have good writing.
An Event Diminishment Model to Optimize Cloud Environment

Cloud computing is to compute a task assigned to a set of connections, software and services that can be utilized by the user over a network. The trending need of Cloud infrastructure has drastically scale up the energy need of data centers, which has become a critical issue. In the row also lead to high carbon emission which is not environment friendly so there is a need of energy efficient approach in cloud computing The research paper aims to reach a theoretical notion of sustainable development with proposing an incentive for reducing global warming through effective clustering techniques and methods. This paper aims to reduce cloud events by applying map reduce on large event clusters formed in cloud. The purpose of the paper is to develop a better methodology for handling the events of cloud computing and possibly clustering and reducing the similar types of events. This approach might lead to the reduction of carbon-dioxide gas (which is a greenhouse gas) by less usage of servers in cloud data centers. With the advent of IT services in cloud computing energy consumption it is necessary for the developing technology to progress towards sustainable development rather thrashing and harnessing energy from every possible means.
Legal Aspects of Evidence Collected by Modern Devices: A Case Study

This paper is a qualitative research of different case laws dealing with modern technological evidence.Courts were required to adopt new methods, techniques and devices obtained through advancement of science without affecting the original intention of law.Because of modern technology, a benefit could be taken from said technology to preserve evidences and to assist proceedings of the Court in the dispensation of justice in modern times.Owing to the scientific and technological advancements the admissibility of audio and visual proofs has grown doubtful.No doubt modern evidence assist the court in reaching out to the just decision but at the same time certain criteria need to be laid down which must be satisfied to consider such evidence admissible.Different Case laws are discussed here to show how the cases were resolved on the basis of technological evidence and when and why such evidence have been rejected by the court, if it did.Moreover, legal practices developed in various countries allow our Courts to record evidence through video conferencing.The Honorable Supreme Court of Pakistan directed that in appropriate cases statement of juvenile rape victims and other cases of sensitive nature must be recorded through video conferencing to avoid inconvenience for them to come to the Court.Nevertheless, it has some problems.The most important among them is the identification of the witness and an assurance that he is not being prompted when his statement is recorded.In this paper protocols that are necessary to follow while examining witness through video link are discussed
Comparative Study of Different SDLC Models

Abstract: The Software Development Life Cycle (SDLC) refers to a methodology with clearly defined processes for creating highquality software which are cost effective and reliable. This method of software developing process is quite systematic and structural. SDLC defines the framework that has different activities and tasks to be administered during the software development process. Software development process is quite complex, and to do it without any proper planning would be inefficient. So, we use these SDLC models to make the Software development process simple and systematic. There are various software development life cycle models that are used in the software development process, all having their own advantages and limitations. In this paper, we have included six of these SDLC models - Waterfall Model, Spiral Model, V Model, Agile Model, Iterative Model and Rapid Application Development (RAD) Model. These Software Development processes have their own Advantages and Disadvantages, and the main purpose of this paper is to explain these models and know the difference between them. Keywords: Software Development life cycle, Models, Risk Analysis, Framework, SRS.
Discourse-Driven Integrated Dialogue Development Environment for Open-Domain Dialogue Systems

Development environments for spoken dialogue systems are popular today because they enable rapid creation of the dialogue systems in times when usage of the voice AI Assistants is constantly growing.We describe a graphical Discourse-Driven Integrated Dialogue Development Environment (DD-IDDE) for spoken open-domain dialogue systems.The DD-IDDE allows dialogue architects to interactively define dialogue flows of their skills/chatbots with the aid of the discourse-driven recommendation system, enhance these flows in the Python-based DSL, deploy, and then further improve based on the skills/chatbots usage statistics.We show how these skills/chatbots can be specified through a graphical user interface within the VS Code Extension, and then run on top of the Dialog Flow Framework (DFF).
Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain

Multimedia data in various forms is now readily available because of the widespread usage of Internet technology. Unauthorized individuals abuse multimedia material, for which they should not have access to, by disseminating it over several web pages, to defraud the original copyright owners. Numerous patient records have been compromised during the surge in COVID-19 incidents. Adding a watermark to any medical or defense documents is recommended since it protects the integrity of the information. This proposed work is recognized as a new unique method since an innovative technique is being implemented. The resilience of the watermarked picture is quite crucial in the context of steganography. As a result, the emphasis of this research study is on the resilience of watermarked picture methods. Moreover, the two-stage authentication for watermarking is built with key generation in the section on robust improvement. The Fast Fourier transform (FFT) is used in the entire execution process of the suggested framework in order to make computing more straightforward. With the Singular Value Decomposition (SVD) accumulation of processes, the overall suggested architecture becomes more resilient and efficient. A numerous quality metrics are utilized to find out how well the created technique is performing in terms of evaluation. In addition, several signal processing attacks are used to assess the effectiveness of the watermarking strategy.
Kontribusi Media Pembelajaran Daring terhadap Minat Belajar Siswa

This study aims to determine the contribution of online learning media to students' interest in learning in network service technology subjects for class XI Smk Negeri 8 Padang. The type of this research is correlational quantitative, the sampling is done using the Proportion Random Sampling technique. Total 66 people. The instrument used in data collection in this study was a questionnaire compiled according to the Likert scale model. Data analysis was performed using SPSS 20 and Microsoft Excel. Based on the results of the study, the value of rcount -0.212 while the value of rtable is 0.250 because the value of rcount is smaller than the value of rtable is 0.212 &lt; 0.250) it can be concluded that there is no significant relationship between online learning media and student interest in learning, with a contribution value of 4.5% which means that online learning contributes to students' interest in learning in network service technology subjects is very low. which means that online learning contributes to students' interest in learning in network service technology subjects is very low.
The Students Difficulties in Understanding of Active to Passive Voice at X Tm1 SMKN 2 Panyabungan

Grammar is a study about how to make and arrange the sentence. It is an integral part of languagesand is very important for the learner. Moreover, the active and passive voice form should bestudied to improve our English skills. However, presently students' are sometimes uninterested inthe concept of active and passive voice form. This study aims to determine the high substantial thestudents' obstacle in transforming active to passive voice form at X TM1 SMKN 2 Panyabungan.This research conducted a qualitative way, the source taken at X1 TM SMKN 2 Panyabungan. Datacollection is observation, interviews, and documentation techniques. The analysis results reveal thehigh dominant students' obstacles in determining the subject, using verb3, putting verb be, andobstacles found in the past continuous form. Based on this research finding, the researcher decidesthat few students' have an adequate understanding of passive voice. However, more studentsrequire extra effort to learn and practice grammar to be master and capable of active and passivevoice form.
Identifying the structure and coordinates of the curriculum of indigenous arts in the second elementary school of sistan region

Identifying the structure and coordinates of the curriculum of indigenous arts in the second elementary school of sistan region
Updating of educational programs based on the results of an independent assessment of the level of training of university graduates

Introduction. Unemployment among young professionals, low competitiveness in the labor market, work not in the specialty are indicators of the quality of education of both individual higher educational institutions and the entire higher education system. Currently, there are already obvious contradictions between the requirements for the development of higher education programs and the requirements of employers. Employment of graduates is a complex problem that should be solved not only by young specialists, but also by universities and employers. The purpose of the study: to develop measures to improve the efficiency of training students of technical universities by updating the basic educational programs (OPOP) in accordance with the requirements of employers. Materials and methods. The analysis of scientific sources in the field of compliance of the level of training of graduates with the requirements of the labor market is applied. The study analyzes the results of professional and public accreditation of 9 bachelor's degree programs implemented at 9 departments of electrical engineering, chemical technology, mechanical technology and humanities faculties of PNRPU. 611 graduates and 222 representatives of employers took part in the survey. The main disadvantages of the programs according to experts are summarized and presented. Compliance with the level of training of graduates was assessed by the level of professional knowledge, skills, as well as by the presence of personal skills ("soft skills"). The results of a survey of working graduates are presented, their satisfaction with the results of training is on average 96.5%, career development-86%. Of the 611 graduates surveyed, only 73.85% work in their specialty. A set of measures aimed at increasing the demand and competitiveness of graduates with higher education in the labor market is proposed. The practical significance lies in identifying the points of growth of higher educational institutions in terms of interaction with employers and improving the level of training of young specialists. The results of the study can be useful and applicable in improving the organization of the educational process in other universities of the country. In the future, it is planned to repeat the research in order to evaluate the recommendations.
The effect of letter (c) modelling on developing the skills of handwriting performance among learners of Arabic speaking other languages

&#x0D; This study aimed at identifying the effectiveness of letter (c) modelling in developing the writing skills performance of Arabic learners speaking other languages and the number of views required for the line visual to develop their writing skills performance. The study sample consisted of 15 learners who were studying the Arabic language for the first time and were chosen by the convenience sampling method. The female students did not take a pre-test as they did not know Arabic before. The students were trained on the attached Arabic calligraphy visual, which included all the Arabic language alphabets. The training period lasted for 8 weeks, with two lessons per week, and each session lasted for 40 minutes. The students then underwent a post-test that was checked for validity and reliability. The analysis results showed a clear ability to draw the Arabic letter due to the visualisation of the calligraphy presented by the researcher, which relied on modelling the letter (c) in all Arabic letters. In light of the findings, the study recommended applying the teaching method based on the calligraphy visualisation devised in teaching non-Arabic speakers.&#x0D; &#x0D; Keywords: Handwritten performance, development, letter (c) modelling, learners of Arabic speaking other languages.&#x0D;