Reviewerly/exHarmony huggingface dataset:
UPAYA PENINGKATAN KEMAMPUAN MEMBACA DINI MURID TK MELALUI METODE CANTOL ROUDHOH

In childhood, you cannot really learn words, your skills develop rapidly, and in childhood you begin to understand and understand the meaning of words and what adults say one by one. Children can not only communicate with adults, but also with their peers. It is one of the preparations for kindergarten children to read simple words and know how to write and the meaning of words. Reading from an early age can have a positive impact on children's language development for the next level of education. Early reading is reading that is taught in the program to preschool children. The purpose of this study was to determine the early reading ability of children in the experimental group and the control group at Kartini 3 Nagrak Sukabumi Kindergarten and the implementation of early reading skills. Children through cantol roudhoh as well as supporting factors and inhibiting the implementation of children's early reading skills through cantol roudhoh. This study uses a quantitative approach, the method used is a quasi-experimental method. This research shows that there is a significant effect on the use of the cantol roudhoh method in early reading learning at TK Kartini 3 Nagrak. This is evident from the increased early reading ability of children before and after treatment. In other words, the use of the cantol roudhoh method is effective and can improve children's early reading skills.
The Effect of Organizational Safety on Turnover Intention Through The Moderation Role of Career Commitment: A Proposed Framework

Employee turnover is an international phenomenon that is deliberated as a tough challenge to organisations, as it is tiring and costly. Thus, there is an obligation for conducting more research to support the academicians, practitioners, and decision-makers with a better understanding of this dilemma and clarify more on the factors affecting these phenomena in different settings and contexts of research, particularly in the non-western perspectives such as Algeria which is facing a big challenge toward the employees’ turnover in many sectors. Therefore, the purpose of this conceptual paper is to determine the moderating effect of career commitment (CC) on the relationship between organizational safety (OS) and turnover intention (TI). Due to that, this study proposed framework to study the effect of organizational safety on turnover intention through the moderation role of (CC). In addition, the direct effect between the variables has been discussed. Hence this paper is expected to fill the research gap and contribute to the body of knowledge in this area of research.
DEVELOPMENT OF A MODULAR EDUCATIONAL APPLICATION USING THE FLEXIBLE ARCHITECTURE OF DOCKER CONTAINERS

Each educational discipline involve enough deep theoretical and scientific context, which require a lot of experience and calculation for learning. However, scientific work is often in several disciplines. So there is demand for experts and software applications, which can improve the educational process. This article is about creating a system for students-ecologists, tutors, software developers in air quality and ecology domains, which helps use formulas, calculated by students from math modeling faculties.
A Study on Awareness of Fake News Proliferation in Social Media and its Cognitive Impact

Emergence of social media has given the right to all and sundry to post any content according to their ideology and preferences. Undoubtedly that can be fabricated, with no variable facts, or sources. Today, when people observe something fishy, they don’t bother to cross check the content at all, because they have developed the tendency to just ignore the news/content and move further. It has become increasingly prevalent over the last few years, because of numerous incorrect articles and rumours on social media. We are always suggested and informed to think critically on fishy content we come across and should think twice and thrice if any doubt emerges regarding any material. Also, before forwarding any message cross checking should be done to the hilt. But by referring to it, as a wastage of time and effort people do not check the content and start believing that content must be true/false. Now people are well aware of fake contents. Therefore rather than focusing on how to make people aware about it, the study focuses on how this awareness of fake content creates other issues. Whilst, there is another aspect of this, i.e., people are also losing their interest and faith from reality as well. Because not posting and not believing is easier than cross checking. So, a need arises to study the nature, content, effect, and remedy of this at a large.
Handling Errors

This chapter will look at different types of errors that occur in AI systems and strategies for handling them.
FAKE LOGO DETECTION

This project aims to find fake logos by matching and detecting them against the original logo. This is accomplished by dividing the logo picture into rows and columns and assigning an index value to each cell. The values in each cell are referred as pixels which can be compared with logo image to classify whether it’s a fake logo or original logo. To say whether the logo is fake or the original by looking at the relationship between the pixel values of both the original and the logo in training dataset. The original logo is determined by the pixel values of all cells exactly matching the genuine logo otherwise its fake logo. The convolution neural network algorithm is used for detecting and classifying the logo.
Bayesian Network Model

This chapter describes the Bayesian network model (BNM; e.g., Pearl, 1988; Jensen & Nielsen, 2007; Darwiche, 2009; Koski & Noble, 2009; Ueno, 2013; Scutari & Denis, 2014), which has been widely used in many fields, including engineering, marketing, behavioral sciences, and cognitive psychology. Almond et al. (2007, 2009, 2015) applied the model to educational measurements, and Culbertson (2016) and Reichenberg (2018) provided quality reviews of its application.
Hemorrhagic Transformation in Patients with Large-Artery Atherosclerotic Stroke is Associated with Gut Microbiota and LPS-TLR4 Signaling Pathway

Objective: Hemorrhagic transformation (HT) is a major complication of ischemic stroke that worsens outcomes and increases mortality. we aimed to study the relationship between gut microbiota and HT of large-artery atherosclerotic stroke.Methods: From May-2020 through September-2021, the blood and fecal samples in patients with acute first-ever ischemic stroke and not undergoing intravenous thrombolysis or endovascular were obtained on admission, and gut microbiota was assessed by 16s ribosomal ribonucleic acid (rRNA) sequence. Stroke that developed HT (n=15) were compared to those without HT (n=17) and healthy controls (n=16). We also examined the key components of lipopolysaccharide (LPS) pathway: LPS, LPS-binding protein (LBP), and solube CD14 (sCD14). The role of gut microbiota in HT was evaluated using experimental stroke model.Results: We observed that bacterial diversity was decreased in both HT and non-HT group compared to the healthy controls. The concentrations of LPS, LBP and sCD14 were associated with increased abundance of Enterobacteriaceae. In experimental study, the antibiotics treatment diminished HT-induced increase in the levels of LPS and LBP as well as upregulated expression of Toll-like receptor 4 (TLR4) and NF-κB in colon tissue. Transplant of microbiota from HT rats triggered higher level of LPS, LBP and sCD14 in plasma and increased expression of TLR4 and NF-κB in colon tissue.Conclusion: Stroke patients who developed with HT exhibit an obvious change in gut microbiota and LPS-induced inflammatory response. This suggests that maintaining a balance of gut microbiota may be an important factor in preventing HT after stroke.
A Method for Catastrophic Forgetting Prevention during Multitasking Reinforcement Learning

Reinforcement learning is based on a principle of an agent interacting with an environment in order to maximize the amount of reward. Reinforcement learning shows amazing results in solving various control problems. However, the attempts to train a multitasking agent suffer from the problem of so-called "catastrophic forgetting": the knowledge gained by the agent about one task is erased during developing the correct strategy to solve another task. One of the methods to fight catastrophic forgetting during multitask learning assumes storing previously encountered states in, the so-called, experience replay buffer. We developed the method allowing a student agent to exchange an experience with teacher agents using an experience replay buffer. The procedure of experience exchange allowed the student to behave effectively in several environments simultaneously. The experience exchange was based on knowledge distillation that allowed to reduce the off-policy reinforcement learning problem to the supervised learning task. We tested several combinations of loss functions and output transforming functions. Distillation of knowledge requires a massive experience replay buffer. Several solutions to the problems of optimizing the size of the experience replay buffer are suggested. The first approach is based on the use of a subset of the whole buffer; the second approach uses the autoencoder as a tool to convert states to the latent space. Although our methods can be applied to a wide range of problems, we use Atari games as a testing environment to demonstrate the methods.
Face Recognition for Secure Online Payment with Proxy Detection Using Face Net Classifier

In most online transactions, in addition to the user's password, an OTP is used to authenticate the user. OTP is primarily used to improve security and prevent fraudulent actions such as identity theft. In some situations, OTPs aren't very secure. The most significant downside of utilizing OTP is that it may be readily stolen and exploited by someone who knows the concerned user's bank details, including access to the registered mobile phone, allowing money to be transferred without the account holder's awareness. To address this flaw, we suggest a system that employs the account holder's face as a form of authentication and verification. During the initial process, the account holder's face is taken. To extract facial traits, we employ the Face Net algorithm. SVM will be used to classify each person's facial features. The trained face model is compared to the face recognized during the online payment procedure. Payment will be processed successfully if no proxy is discovered and the detected face matches the trained face.
Research on fast video mapping method of borehole in front view

Camera borehole technology is widely used in borehole engineering, which can obtain the structure of deep-buried rock mass. However, when people recognise these images, there will be problems such as heavy workload, low efficiency and easy recognition errors. In order to solve these problems, this paper proposes a fast unfolding mosaic and fusion method of looped image in the forward view video. This paper proposes a borehole image expansion method with autonomous positioning of the borehole centre and adaptive adjustment of the expansion radius to achieve rapid and automatic image expansion. On this basis, an adaptive adjustment algorithm of image stitching points based on grey difference registration is proposed, which solves the defect of determining stitching points by artificial experience. The practical results show that the image mosaic technology is simple, the processing is flexible and efficient and the forward view borehole expansion map obtained has an ideal effect.
English E-Book as Supporting Learning Media for X Grade Students

The objective of this research is to develop an English E-book as supporting learning media for students at X grade. This learning media consist of some materials in which each materials are completed by some exercises and quiz. The materials in this E-Book are based on senior high school syllabus of curriculum K13. This is a developmental research which adopt Developmental model in research procedures. This model have several steps, those are; 1) Analysis, 2) Design, 3) Development, 4) Implementation, and 5) Evaluation. The result of this research showed from the media validation result got 4,4 score it was in “very good” category, and the material validation got 4,5 score it was in “very good” category. By having those result, this English E-Book is feasible to be used as supporting learning media for X grade students. Furthermore the result of this research can be used as reference for other researchers in exploring and developing English learning media in different level of students.
Remotely preparing optical Schrödinger cat states via homodyne detection in nondegenerate triple-photon spontaneous downconversion

Abstract Optical downconversion is a key resource for generating nonclassical states. Very recently, direct nondegenerate triple-photon spontaneous downconversion (NTPSD) with bright photon triplets and strong third-order correlations has been demonstrated in a superconducting device (2020 Phys. Rev. X 10 011011). Besides, linear and nonlinear tripartite entanglement in this process have also been predicted (2018 Phys. Rev. Lett . 120 043601; 2020 Phys. Rev. Lett. 125 020502). In this paper, we consider the generation of nonclassical optical quantum superpositions and investigate nonlinear quantum steering effects in NTPSD. We find that large-size Schrödinger cat states of one downconverted mode can be achieved when the other two modes are subjected to homodyne detection. Also, a two-photon Bell entangled state can be generated when only one mode is homodyned. We further reveal that such ability of remote state steering originates from nonlinear quantum steerable correlations among the triplets. This is specifically embodied by the seeming violation of the Heisenberg uncertainty relation for the inferred variances of two noncommutating higher-order quadratures of downconverted modes, based on the outcomes of homodyne detection on the other mode, i.e., nonlinear quantum steering, compared to original Einstein–Podolsky–Rosen steering. Our results demonstrate non-Gaussian nonclassical features in NTPSD and would be useful for the fundamental tests of quantum physics and implementations of optical quantum technologies.
Modelling and testing multi-qubit universal control gate developed for quantum computing systems

Quantum gates are building blocks of quantum circuits and they are used to carry out corresponding operations on quantum bits or qubits. The distinguishing feature of multi-qubit quantum control-gates is that they act on target qubits according to the state of control qubit(s). In this sense, there exist 2- and 3-qubit quantum gates such as Controlled-NOT, Toffoli (Controlled-Controlled-NOT), Controlled-Hadamard, Controlled-Swap and so on. In order to make complex quantum circuits easier and control more qubits, it is necessary to work out mathematical models of new control gates acting on more than three qubits depending on the state of control qubit. Therefore, in this work, mathematical model of multi-qubit universal control gate is worked out and some control gates are formulated in accordance with the proposed model, moreover the tests of these novel control gates are carried out using online open resource or virtual laboratory that is called “Quirk”. Existing 2- and 3-qubit control gates can also be derived using this model. Matrix representations of Controlled-NOT-NOT, Controlled-Hadamard-Hadamard, Controlled-NOT-NOT-Hadamard, Controlled-Hadamard-Swap and Controlled-Hadamard-SWAP-NOT gates are derived using the proposed mathematical model. These quantum gates are unitary and reversible gates. Using the proposed model and novel quantum gates will help to reduce complexity of quantum circuits and develop new cryptographic algorithms.
A Keen Study on Quantum Information Systems

Each computer is essentially an actual framework, and any calculation is only an actual cycle gone through by this framework. Quantum physics is the most dependable approach to depicting actual frameworks and their overall conduct. Encoding information into quantum frameworks and processing it as indicated by the laws of quantum physics brings about new elements which don’t exist in the old-style calculation. Quantum information processing is a cross-disciplinary field and is critical from, both, a crucial as well as an innovative viewpoint. According to the crucial viewpoint, we have developed how we might interpret the connection between physics, information, and calculation as a general rule, and have additionally acquired a more profound comprehension of the principal parts of the quantum hypothesis—non-area and entanglement specifically. According to the mechanical point of view, we have controlled increasingly large quantum frameworks and acquired strong down to earth applications in the area of correspondence and cryptography like the unequivocally solid quantum cryptography (key trade) and quantum instant transportation The more prominent capability of the quantum computer was first acknowledged by Feynman, who noticed that quantum frameworks give off an impression of being dramatically difficult to recreate with traditional computers and expressed that quantum computers might actually be significantly more remarkable than their old-style partners. The improvement of quantum information science (QIS) has been driven by hypothetical work of researchers dealing with the limit between Physics, Computer Science, Mathematics, and Information Theory. In the beginning phases of this turn of events, hypothetical work has regularly been a long way in front of test acknowledgement of these thoughts. Simultaneously, the hypothesis has given various propositions of how to execute fundamental thoughts and ideas from quantum information in explicit actual frameworks.
Ghost Attention Efficient Network for Crowd Counting

Despite the great success of crowd counting networks on various applications, the redundant structure and excessive parameters still limit the deployment of counting models on mobile or embedded devices. In order to address this problem, we propose a lightweight density estimation architecture named Ghost Attention Efficient Network (GAEnet) for high-accuracy and real-time crowd counting. Firstly, the lightweight but powerful Ghost Extraction Network (GEN) are introduced to extract multi-level features. Meanwhile, we design the Cross-order Ghost Attention Module (CGAM) which is based on the Parameter-Sharing mechanism. CGAM aims at capturing higher-order discriminative information and obtaining wider receptive fields. In addition, the Weight-sharing Mask Density Producer (WMDP) are proposed to alleviate the influence of complex background on counting accuracy. Finally, we conduct extensive experiments on multiple crowd counting datasets. The experimental results have demonstrated the effectiveness of our GAEnet.
Blockchain Technology in Cryptocurrency: A Review

A blockchain is a public ledger to which everyone has access but which is not controlled by a central authority. It is a technology that enables individuals and industries to interact with confidence and transparency. This paper provides an overview of blockchain technology in cryptocurrency. The purpose of this research is to examine the popularity of blockchain and to investigate the growth and development of this modern-day hotspot based on blockchain-based smart contracts. Blockchain technology is becoming more common in the IT business. It is more likely than any other technology in our economy to have a larger influence on business and society. Most contemporary blockchain technology research focuses on its application in cryptocurrencies such as Bitcoin and Ethereum, which are among the most popular and the most well-known uses of blockchain, although many additional applications are feasible.
Power Consumption and Hardware Utilization for Traffic Signs Recognition Models through FPGA Implementation

In this paper, the sequence of MATLAB/Simulink models required for the recognition of the speed-based traffic sign images have been discussed. The resources utilized by all the models along with their dynamic power consumption, when implemented on a Spartan 3E FPGA at 50MHz frequency, have been discussed and compared with the existing literature. Here, the images of traffic signs-30km/h and 50km/h speed limits have been taken. The images have been clicked in real-time environment, with different illumination levels and are of 32 x 32 and 256 x 256 resolution. Four MATLAB/Simulink models for RGB to Gray conversion, Median filtering, Segmentation, and Edge detection have been implemented and the resource utilization as well as the dynamic power consumption of these models have been found using Xilinx ISE EDA platform, when implemented on Spartan 3E hardware. Both the resource utilization and the dynamic power for all the models have been investigated and compared with the existing available literature, to ensure and validate the efficiency and applicability of the present work. The percentage contribution of different models-RGB to Gray, Median filtering, Segmentation, and Edge detection in a total of 156mW dynamic power consumption is found to be 21&#x0025;, 32&#x0025;, 2&#x0025;, and 45&#x0025;, respectively.
Equivalence of Product Ciphers to Substitution Ciphers and their Security Implications

Product/Compound ciphers composed of multi-byte permutations and substitutions are generally considered to be more secure than their standalone individual component-cipher counterparts (i.e., substitution (S) and permutation (P) ciphers). In this paper, we show that a permutation-substitution-permutation (PSP) cipher that uses any form of regular byte-block boundaries, along with a regular encoding (such as ASCII), is no more secure than a multi-byte S cipher. In addition, we also show that, under certain conditions, a PSP cipher can be reduced to an S cipher. In addition to introducing the concept of isomorphic cipher reduction, we show that our theoretical findings translate into practical means by using a plaintext attack. In doing so, we shed light on the problems of encryption security that arise due to employing a product cipher in conjunction with any form of regular byte-block boundaries, and propose appropriate countermeasures.
Environmental sustainability and its impact on the mental status an exploratory study of the opinions of a sample of agents for mineral water companies in the city center of Kirkuk

The research aims to determine the impact of environmental sustainability on the mental status. An exploratory study of the opinions of a sample of customers in mineral water companies in the city center of Kirkuk. A sample of (120) customers was selected and statistical methods were used, including the descriptive approach in data analysis and extraction of results using the SPSS statistical program. To the most important conclusions that there is no correlation and impact with a statistically significant significance between the environmental sustainability variable and the dependent variable mental status. He also reached the most important proposal for the surveyed organizations to continuously pay attention to environmental aspects in all production processes within the company, and this contributes greatly to preserving the environment for the customer after achieving satisfaction and loyalty.