Reviewerly/exHarmony huggingface dataset:
Improving Machine Learning Based Color Optimization Efficiency by Using a New Image Restoration Technique

In the past ten years, neural network is playing an important role of solving computer vision problems. One reason is due to the improvement of machine learning algorithms. The other reason is due to the hardware acceleration from GPUs and TPUs. However, researchers and developers are still having a hard time to deal with high resolution images. While the image size increases, the computational time of neural network models may increase quadratically. In this paper, we introduced a new image restoration method which successfully improves the efficiency of image color optimization task. For any input image size, this method could reduce the computational time of the autoencoder to a constant time.
The Impact of Creativity in the Growth and Value of Petrochemical Companies Listed on the Stock Markets of the Gulf Cooperation Council Countries "An Analytical Study": أثر الإبداع في نمو وقيمة الشركات البتروكيماوية المدرجة ‏في الأسواق المالية لدول مجلس التعاون الخليجي " دراسة تحليلية"

This study aimed to study the effect of the relationship between innovation methods represented in “research and development, training, information technology, and advertising” on the growth and value of petrochemical companies listed in the financial markets of the Gulf Cooperation Council countries, as well as the impact of the age and size of the company on this relationship. The study was conducted on a representative sample of 16 companies from the Gulf Cooperation Council countries, and multiple linear regression was used in conducting the statistical analysis based on the E views program. The study concluded with several results, the most important of which are: 1- The results showed a statistically significant effect at the level (α ≥ 0.05) of creativity methods represented in “research and development, training, information technology, and advertising” on the value of the companies under study, as well as the presence of this effect for both research and development, and information technology. and advertising” on the growth of these companies, while the results showed that the training is not moral and has no effect on the growth of these companies. 2- The results showed an impact of the age and size of the company on the relationship between “research, development and training” and the growth of the companies under study, while the results showed the absence of this effect on the relationship between “information technology and advertising” and the growth of these companies. The study recommended the necessity of consolidating the conviction of the importance of research and development among these companies, by establishing a specialized department in this field in each company, as well as preparing modern programs and evaluating them periodically to ensure their effectiveness, and allocating a percentage of these companies’ revenues to be able to provide innovative products that satisfy consumers. Attention to creative ideas to improve current products and create new products that lead to an increase in growth rates for these companies. The study also recommended the need to pay attention to information technology, training, and advertising to open new markets at the regional and international levels, which contributes to the growth rates of these companies and improve their financial position.
Conducting sentiment analysis: Lei L. &amp; Liu D. Elements in Corpus Linguistics, CUP

Sentiment analysis is an important task in corpus linguistics and natural language processing. Based on statistical and machine-learning algorithms, texts’ subjective evaluations and emotional states can be detected, extracted, and classified. Sentiment analysis results are significant to the development of many different industries in the financial, political, medical, and entertainment domains. They are beneficial to make relevant stakeholders have a good command of public attitudes to products, policies, medical treatment, and services in order to make appropriate adjustments. Lei and Liu provide a comprehensive and concise introduction to sentiment analysis to assist students and academics in understanding the theoretical aspects and the application of sentiment analysis.
My Voice Assistant Using Python

Abstract: In the current situation of technology development within the field of augmented reading and voice assistant systems development, many researchers are writing in this regard for the development of new and effective technologies. The voice assistant are software package agents that may interpret human speech &amp; responds via synthesized voices apple siri, microsoft cortana &amp; google assistant are the foremost common voice assistant &amp; embedded in smartphones .Today the technological advancement is increasing day by day. with the assistance of computer system in which we are able to do solely few task however currently artificial intelligence ,machine learning and few a lot of technologies have created computer system so advance that we are able to implement any type of task. In the present paper, The thought of speech technology extremely encompasses 2 technologies: Synthesizer and recognizer. A speech synthesizer takes as input and produces an audio stream as output. A speech recognizer on the opposite hand does opposite. It takes an audio stream as input and thus turns it into text transcription. The voice may be a signal of infinite information. for this reason, we have got created our own virtual personal assistant just for windows using python 3.6 that is ready to right to use on any windows explorer such as windows 7,8,10.we will use python as a programming language as a result of it have a major libraries which is use to implement command. Index Term: Artificial Intelligence, Desktop Assistant, Python, Text to Speech, Virtual Assistant, Voice Recognition.
An integrated approach of block chain technology with machine learning and cloud computing for handling healthcare data

Healthcare industry has become one of the world's important sectors. It is one of the quickestand persistently growing industries. Healthcare Technology focuses mainly on patient's empowerment. Blockchain technology is offering healthier scope for accessing medical records privately. Patient confidentiality can be maintained more effectively using block chain. It is very difficult to hack the data because blockchain makes use of decentralized data storage. Nowadays machine learning is used for understanding the data and for analysing and making decisions in various sectors. It is one of the prominent techniques that are being applied in an extensive range of applications to solve a variety of complex problems. Machine learning plays a vital role in healthcare sector, by offering effective methods by saving time, effort and money. Convergence of blockchain technology with machine learning and cloud computing provides extremelyenriched functionalities and services which enables the healthcare industry to revolutionize with substantial results for medical professionals. For experimental results, Ethereum is used. In the proposed work, the patients can also get the disease details using machine learningconcept by providing their symptoms.
Investigating the Construct Validity of an ESL Test for Young Learners

This study investigated the construct validity and reliability of the GEPT-Kids, which is composed of 25 listening items and 30 reading items. Data were collected from 742 test takers from Grades 5 and 6 from eight Chinese-speaking schools in Beijing, Shanghai, Guangzhou, Hong Kong, Macau, Taipei, Taichung, and Kaohsiung. Two CFA models (Model 1: a one-factor model with a general language proficiency construct; Model 2: a two-factor model with listening and reading constructs based on the test design) were proposed and analyzed using AMOS 24.0 to reveal whether the internal structure of the test reflected the test developers’ design for the test. The results showed Model 1 provided an adequate explanation of the data as most of the model fit indices were acceptable, and Model 2 showed that there was a lack of discriminant validity between listening and reading because they were too highly correlated although the fit indices were high. While both models can be considered acceptable based on fit indices, and Model 1 is more parsimonious than Model 2. To sum, the main finding was that GEPT-Kids is valid in terms of score interpretation of young learners’ overall language ability but may lack discrimination in terms of assessing subskills of English language proficiency. Therefore, findings from this study suggest that GEPT-Kids is acceptable as a general language proficiency test but should be used with caveats while using test scores in terms of listening and reading in the classroom teaching-learning context.
CloudConsumerism: A Consumer-Centric Ranking Model for Efficient Service Mapping in Cloud

In cloud, service providers and consumers are primary stakeholders that maintain a business liaison. Cloud service providers (CSPs) offer the services, and consumer uses the services on a payment basis. From a business perspective, the selection of a service based on mutual evaluation benefits both the CSPs and consumers. This paper presents an efficient CloudConsumerism model where the multicriteria decision-making method (MCDM) method, TOPSIS, is used for evaluating the performance of CSPs and consumers. For performance evaluation of CSPs, the performance attributes defined by Cloud Service Measurement Initiative Consortium (CSMIC) are exploited. For evaluating the consumers, this paper is the first approach towards identifying the behavioral attributes for evaluating the cloud consumers analogous to the business models. A service mapping algorithm is proposed for efficient (less overhead and higher robustness) mapping. Extensive simulation experiments are conducted; the results show that the proposed framework can be used for the online cloud-based platform due to limited overhead and high robustness.
Unavailability of Python Tool Which Can Perform Various Hacking Activities

Abstract: Multi Technique Hacking is implemented with all three functions in a single interface, that is, Http Packet Credential Harvesting, IP Spoofing and Packet Modification and There is no existing system in which all the functions have been used together. It describes how the process is done and how they go about helping their customers find and plug up security holes. The hacking process is explained, along with many of the challenges and opportunities in the field of ethical hacking. This hacking technique is done using scapy library which is a very big library with plenty of functions available for use. To understand the working of the library firstly the practice has to be done using the library and then try to implement it in the code. Ethical hacking, also known as penetration testing, penetration testing, or the red team, has become a major concern for businesses and governments. Companies are concerned about the possibility of being hacked and prospects are concerned about managing their personal information. This Paper describes how the process works and helps customers find and close security gaps. The hacking process is described with many challenges and opportunities in the field of ethical hacking Keywords: Scapy, IP Spoofing, Credential Harvesting, Packet Modification.
EFFECTIVENESS OF USING LEARNING MEDIACARD-BASED READING SKILLS QUESTIONS EXPOSITION TEXT FOR CLASS VIII STUDENTS MTS AR-ROUDHOH JABUNG, INDONESIA IN THE ACADEMIC YEAR 2021/2022

This research is motivated by learning Indonesian in conventional schools. Observations show the minimal use of learning media at MTs Ar-Roudhoh Jabung, Indonesia. This is what underlies the researcher to determine the effectiveness of using question card-based learning media with exposition text material for class VIII. The research method used is a pre-experimental design with one group pretest-posttest design. The research location is MTs Ar-Roudhoh Jabung. Collecting data was done by using a validation questionnaire for media expert lecturers, material expert lecturers, linguists, and class VIII students. The research instrument consists of five aspects, namely aspects of content feasibility, presentation aspects, graphic aspects, language aspects, and learning design aspects. The results of this study are: (a) The validity and effectiveness of the media have been well tested. Expert validation test results: (1) Media Experts are 91.25% with "Valid" criteria; (2) Material Expert by 94.4% with "Valid" criteria; (3) linguists 98.75% with "Valid" criteria; (4) Students are 96.22% with "Valid" criteria. (b) Student learning outcomes show that student scores have increased and meet the minimum final score of KKM (Minimum Completeness Criteria). Thus, the results of the validation of the four respondents indicate that the question card-based learning media is effectively used for learning exposition texts for class VIII MTs students. To improve student motivation and learning outcomes, Indonesian language teachers should be able to develop learning media in terms of more complete material. The material presented does not only contain exposition text material, but can be developed with other materials in class VIII learning. Teachers pay attention to the learning model used when implementing learning media and schools should further improve facilities for the use of learning media.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0937/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
PROJECT-BASED LEARNING DALAM PEMBELAJARAN BAHASA INGGRIS PADA PROGRAM STUDI PARIWISATA

Learning English, especially in the tourism study program, is very important to emphasize. However, the process of learning English in fact still faces various obstacles. One of the obstacles that are often faced in the process of learning English is that lecturers tend to apply a one-way learning process from lecturer to student using the lecture method. For this reason, it is necessary to further analyze the model or learning approach that is more possible and has the potential to effectively assist students in the English learning process. One model of English learning that has the potential to effectively help students in tourism study programs is to apply a project-based learning model. Therefore, the present study utilizes a qualitative descriptive approach using library research methods aiming at analyzing the concept of project-based learning to be implemented in English learning environments in tourism study programs. This library research approach, according to Lin (2009) involves reading and categorizing materials to solve a problem. Thus, from the result of the study it was found that the use of project-based learning in learning English in the tourism study program is assumed to be able to help students prepare for the future well in terms of English skills and at the same time help lecturers to prepare a more meaningful English learning process.
Primary school teachers knowledge towards management of students with T1DM

A descriptive cross-sectional study is conducted in Wasit Governorate, Numaniyah District. Out of 60 teachers were selected from 30 schools for each school 2 teachers, who were tested in a questionnaire related to type 1DM. The reliability of the questionnaire was achieved through a pilot study and then presented to experts to prove its validity. The total number of items included in the questionnaire was 30-items. The data was collected by using the self-report method and analyzed by applying a descriptive and inferential statistical data analysis approach .Out of 60 primary school teachers the mean age is 42.15±9.221, (53.3%) were female, (78.3%) were diploma graduated, (41.7%) had less than 5 years of experience, (81.7%) were exhibit no trained. The results of the study indicated that the (78.3%) of school teachers expressed deficit knowledge. There were significant differences in teachers knowledge with regards age groups, years of experience and training sessions (p&lt; 0.05).
Instilling Type Knowledge in Language Models via Multi-Task QA

Understanding human language often necessitates understanding entities and their place in a taxonomy of knowledge-their types.Previous methods to learn entity types rely on training classifiers on datasets with coarse, noisy, and incomplete labels.We introduce a method to instill fine-grained type knowledge in language models with text-to-text pre-training on type-centric questions leveraging knowledge base documents and knowledge graphs.We create the WikiWiki dataset: entities and passages from 10M Wikipedia articles linked to the Wikidata knowledge graph with 41K types.Models trained on WikiWiki achieve state-ofthe-art performance in zero-shot dialog state tracking benchmarks, accurately infer entity types in Wikipedia articles, and can discover new types deemed useful by human judges.
THE IMPLEMENTATION OF COMMUNICATIVE LANGUAGE TEACHING IN THE CONTEXT OF ONLINE LEARNING: A LITERATURE REVIEW

With the occurrence of the COVID-19 crisis, there has been dramatically growth and adoption of online education. As a consequence of the epidemic, institutes have been compulsory to close, and teaching and learning have changed fully to home studying. As a result, numerous educational institutions have adopted online teaching and learning on a massive scale. To combine the Communicative Language Teaching (CLT) approach with a framework of computer-assisted language learning seems to be the best strategy during a coronavirus outbreak. This study offers a survey of the literature on Communicative Language Teaching in the situation of online teaching and studying. This paper begins with an overview, definition, and characteristics of CLT. It then examines how CLT can be beneficial in a virtual classroom: advantages and disadvantages. Besides, it discusses the approaches to using CLT in online teaching and learning. This paper's goal is to provide an effective overview that can be used for online language instruction. The study will add to our understanding of Communicative Language Teaching and its use in an online setting.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0947/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
Certified Robustness via Randomized Smoothing over Multiplicative Parameters of Input Transformations

Currently the most popular method of providing robustness certificates is randomized smoothing where an input is smoothed via some probability distribution. We propose a novel approach to randomized smoothing over multiplicative parameters. Using this method we construct certifiably robust classifiers with respect to a gamma correction perturbation and compare the result with classifiers obtained via other smoothing distributions (Gaussian, Laplace, uniform). The experiments show that asymmetrical Rayleigh distribution allows to obtain better certificates for some values of perturbation parameters. To the best of our knowledge it is the first work concerning certified robustness against the multiplicative gamma correction transformation and the first to study effects of asymmetrical distributions in randomized smoothing.
An improved liver tumor image segmentation method based on mixed domain attention mechanism

This paper proposes a new liver tumor segmentation method based on mixed domain attention mechanism. Firstly, by combining the well-known SENet with channel attention architecture, cross channels are interacted at their Excitations by using multiple one-dimensional convolution kernels. Then, multiple dilation convolution is used to increase the receptive field in the spatial attention module of BAM. After then, the channel and spatial attention feature maps are fused to recorrect the original feature map. Finally, a gating mechanism is introduced at the sampling skip connection on the decoder to filter important features. The experimental results show that in many evaluation indexes, the accuracy of this method is higher than the relevant segmentation methods, and thus the introduced segmentation method can provide some guidance in clinical diagnosis for liver tumor.
Cybernetic suit for interaction with virtual reality

The study in the field of the structure of the processing architecture of a cybernetic suit for working with virtual reality was conducted. Nowadays it is relevant to use such a systems to implement various scenarios of rehabilitationfor people, as well as to conduct possible training sessions for operators of mechanized devices and so on. The goal is to achieve the highest possibleaccura-cy in repetition of the operator's movements, i.e. motion capture, at the lowest financial cost. The initial variant ofthe suit was creat-ed on the basis of Arduino and Unity 3D for visualization. 3D human model based on quaternion is built in Unity 3D which repeats all the real person twists and turns. But the first architecture had problems with performance and accuracy.A series of experiments was carried out to improve the effectiveness of the cybernetic suit prototypes. Thanks to the introduction of the proposed new type of architecture, namely the “controller-sensor”, it ispossible to completely get rid of the inaccuracy of the received data from the sen-sors. Also it allows removing the unauthorized change in the position of the body parts of the 3D model and increasingthe overall resistance and noise immunity of the product. Softwarebased on the algorithm for processing data from gyroscope and accelerometer sensors is presented, and the possibility of upgrading the design of the hardware part of the suit, aimed at optimizing the output char-acteristics, is described. To achieve the goal the most stable and noise-resistant transmission of primary data from cybernetic suit to a 3D model with the minimum possible number of errors in the data transmission buses was obtained. As a result, the modernization of the cybernetic suit for interaction with virtual reality has increased the accuracy of data from 66 % to 94.5 % and reduced the amount of interference from 40.59 % to 5.5 %.
Monitoring Videocolonoscopy Examinations in Real-Time via Internet

Computational technologies have promoted several benefits for medicine, such as improvements in medical data storage, transmission, and analysis. They also have the potential to support the establishment of collaboration networks among professionals in medical centers, clinics, and hospitals, notably after the advent and expansion of the Internet. In particular, these networks could allow experts in dif-ferent locations to monitor and discuss medical procedures in real time, as well as to collect, store, and share multimedia data associated with these procedures. This chapter presents an innovative method in telemedicine and a computational system that allows experts to interact in real time by text, audio, and video. The proposal also allows experts to perform real-time gathering and sharing of videocolonoscopic images and videos with authorized users connected to the system through the Internet. These multimedia data are stored and published into a centralized server implemented with security techniques. The presented method was experimentally evaluated in a simulation of a real environment in which the system could be applied. As a result, the system met the requirements of the telemedicine method and was able to collect, store, and share videocolonoscopic multimedia data securely in real time. This finding confirms the proposal as an alternative to support collaboration among experts and institutions that offer videocolonoscopy or other types of video-based examinations and medical procedures to patients.