Reviewerly/exHarmony huggingface dataset:
WITHDRAWN: An effective low power halftoning based authentication and self-recovery of tampered images

For the reason, that the need for image safekeeping is crucial to address the prerequisites of the two safety and non-wellbeing in many areas of the developments in PC-based communications and well-being administrations for many decades. Techniques for confirmation and self-recuperation of altered data in advanced pictures have been in steady improvement during recent years. This paper suggests another LU decomposed halftoning plan for picture verification and self-recuperation for clinical applications. The projected pattern pinpoints picture tampering over and above recuperates the first picture. A picture is cut into 4 × 4 blocks and LU is operated to sort off the change in the inventive picture. At that instant creates the validation watermarks, established on XOR operations on non-covering blocks, consequently, by exploiting a halftoning procedure the recuperation watermark is produced. The proposed method is implemented in MATLAB. The suggested halftoning strategy was coded in Verilog and actualized in SPARTAN to screening the drop multifaceted nature and low force picture handling competence of the recommended structure. To assess the feature of the acquired pictures, the substantive criteria of PSNR and Tampering ratio is exploited. The tentative outcomes viewing the adequacy of our technique in correlation with different plans revealed in the writing, where the physiognomies of the watermarked pictures, the aspect of the remaking pictures, and the reclamation rate of each plan were evaluated.
Ontology-Based Framework For Automatic Generation Of SQL Assessment

Assessment measures learner progresses in acquisition of knowledge and skills. It helps teachers to refine their teaching strategies and better deliver knowledge and skills. Likewise, It makes it possible not only to simulate learners’ thinking but to measure the value or quality of their work.
Quo Vadis, AI?

Research Question: This article reflects on currently popular topics and future development and application of AI. Motivation: AI has become a key technology in many areas – from business and services, to science engineering and engineering, natural language processing and news, publishing and writing, human resource management and education, medicine and healthcare, transportation and aviation, government, military and agriculture. Idea: As the field advances and expands at an unprecedented pace, it becomes more and more difficult to distinguish between AI and other fields. Data: The article is based on a qualitative analysis of relevant literature and direct insights into the field of AI during the last 35 years. Tools: The article uses direct observation and content analysis to derive conclusions. Findings: Just like any other technology, AI has both its bright and its dark sides. There is a number of expectations, hopes and promises of AI that still remain to be fulfilled, yet new avenues for further development open day after day. Contribution: The article attempts to put AI developments in different contexts and shed different lights on AI applications in general, AI applications in business, in particular, and current limitations, trends and challenges in the field.
Analysis on the Implementation Path of Mathematics Education and Teaching Guided by Scientific and Technological Thinking

In the era of science and technology with the rapid development of Internet, we should pay attention to students' innovative spirit and thinking mode in the process of mathematics education and teaching. In order to cultivate students' innovative spirit and improve their mathematical accomplishment and quality, we should instill knowledge into them, but more importantly, we should make them understand the creative process of mathematics. Cultivating students' mathematical modeling literacy is an important embodiment of improving students' application ability and practical ability, and also an important way to cultivate high-quality talents. Therefore, in mathematics teaching, the first thing to determine is the development goal and influencing factors of mathematical modeling literacy, and then to guide students to find accurate information, analyze information, and use information to establish models, so as to achieve good results in mathematics teaching.
Bare bones mayfly optimization algorithm

Although individuals in the mayfly optimization (MO) swarms would have a chance to dance around the current positions, most of them would still perform exploration according to their best historical trajectories and the global best candidates, which was quite similar to the behavior performed by individuals in the particle swarm optimization (PSO) algorithm. Therefore, there would also exist the stochastic Gauss distribution among the exploration, exploitation for individuals in MO swarms. In this paper, the bare bones MO algorithm was proposed and simulation experiments were carried out. Results verified that the bare bones MO algorithm would perform better than before.
Analysis of Computer Technology on Sports Technical Movement Characteristics of Model Test Research

Exercise can enhance our physical function, so we have been taking the course of physical education since we went to school. In order to make sports action more standardized and improve people’s sports level, this paper uses the image processing technology and multimedia database technology in computer technology to conduct quantitative research on the movement characteristics of sports technology, and establish the action feature model. This paper discusses the application of digital motion simulation technology in sports training, including the application of digital motion simulation technology in sports training. The research shows that the establishment of the digital model of human movement structure can make use of the analysis and comparison between the standard movements in the labeled action library and the technical movements made by the athletes, so as to find out the gap between them, so as to make a set of good improvement scheme for the athletes.
Towards a Biology-Based Approach to Support Software Process Line Evolution

Considering the fact that the process by which software is developed influences the final product quality, companies are concerned with their process definitions. However, defining a software process is a complex activity, as well as a risky one. In this scenario, different software process reuse techniques have been proposed in the literature, such as Software Process Line (SPrL). SPrL provides a systematic way to support software process reuse, aiming to increase the reuse potential, risk reduction, among other benefits. However, SPrL is not being widely used in industry yet, mainly due to the lack of support, e.g., SPrL evolution support. SPrL evolution research topic investigates the modifications (e.g., maintenance, improvement, tailoring) performed during the SPrL lifecycle and helps to understand and manage them. Although it has not been appropriately explored by previous studies, it is important to support SPrL useful life extension through enabling practices and technologies. Aware that engineers often try to learn from their natural counterparts to solve problems following approaches in nature, this paper analyzes four theories of biological evolution aiming at interpreting its concepts and terms within the SPrL evolution context. Different SPrL evolution’s open research points were observed. It is expected that this work supports future investigations to propose a biology-based approach to support SPrL evolution.
On the Adoption and Supply of Bitcoin: An Empirical Analysis

With no central authority backing Bitcoin and other major cryptocurrencies, technological progress in an open-source setting and decentralized consensus mechanisms such as Proof-of-Work (PoW) governing the production side are the essential elements for the operation of most cryptocurrencies. While studies have largely focused on speculation as a key driver of demand, we examine how technological advances in the cryptocurrency codebases impact demand and returns. On the supply side, a higher hashrate, i.e., the amount of computing power used, enhances the security of PoW systems by increasing the cost of attacks, which may positively impact user perceptions and demand. However, increasing hashrate is also correlated with substantial carbon emissions and the emergence of large mining pools, which may negatively affect the demand. We hypothesize technological development activities on GitHub and hashrate to be significant demand and returns drivers, albeit in opposite directions. We create a comprehensive dataset for five dominant cryptocurrencies using the PoW consensus and demonstrate that GitHub developments are associated with higher demand and returns. Contrary to common wisdom, we demonstrate that hashrate has a significantly negative effect on the demand and returns of these major cryptocurrencies. In exploring plausible mechanisms, we perform sentiment analysis on user conversations and demonstrate that technological advances are associated with positive sentiments. Higher hashrate and the presence of large mining pools are associated with negative sentiments. Overall, we establish a unique set of relationships between supply, demand, and returns, and underscore the critical role of continuous technological progress, more efficient mechanisms, and user communication in driving cryptocurrency demand. Our study provides policy implications for cryptocurrency development communities. Given the low immunity to centralization and the detrimental environmental effects of the PoW mechanism, which negatively impact user perceptions, demand, and returns, cryptocurrency developer communities should consider switching to a superior eco-friendly mechanism.
Accuracy and Stability for Optimum Performance of Digital Fringe Profilometry Method

Abstract Various method was developed for the acquisition of the three-dimensional surface of an object. One of the more popular methods used is the structured light profilometry method. It can capture a high-resolution three-dimensional object in real-time. Not only that, but this method is also non-invasive, which is very suitable for the measurement of fragile samples. This paper discusses the accuracy and stability of a structured light profilometry method that is used to obtain a 3D measurement. The experiment is done by using a calibrated camera and projector. A light pattern is then projected onto the sample and captured by the camera. The accuracy of the system is investigated by capturing a flat plate with an increment of 50 µm from 0 µm to 1000 µm. The result has shown a maximum percentage error of this system is 15.76% which is 9.3511 µm, and the minimum percentage error is 0.15% which is 0.7339 µm. For the stability test, the plate was captured thirty times at the same location, and the data obtained shows the consistency of the system has a minimum and maximum standard deviation of 2.4991 µm and 6.8886 µm, which is within 7 µm. The test on the feeler gauge shows a maximum percentage error of 2.12% which is 2.1671 µm.
Smart Attendance System Using Deep Transfer Learning

Automatic face recognition technologies have made numerous enhancement in the changing world. Smart attendance using face recognition is a solution that comes with everyday activities of taking care of the student attendance system. Transfer learning in convolutional neural networks has shown an efficient alternative method for solving the tasks in recognition rather than designing and training new neural networks from scratch. In this paper, we present a smart attendance system by transfer learning deep pretrained CNN. Our proposed system will be able to find and perceive human faces fast and precisely in images or videos that are being captured. The experimental result shows excellent performance in recognition of the student's face under varying distance and resulting conditions mostly applicable in mobile IP webcam.
A-MnasNet and Image Classification on NXP Bluebox 2.0

Computer Vision is a domain which deals with the challenge of enabling technology with vision capabilities.This goal is accomplished with the use of Convolutional Neural Networks.They are the backbone of implementing vision applications on embedded systems.They are complex but highly efficient in extracting features, thus, enabling embedded systems to perform computer vision applications.After AlexNet won the ImageNet Large Scale Visual Recognition Challenge in 2012, there was a drastic increase in research on Convolutional Neural Networks.The convolutional neural networks were made deeper and wider, in order to make them more efficient.They were able to extract features efficiently, but the computational complexity and the computational cost of those networks also increased.It became very challenging to deploy such networks on embedded hardware.Since embedded systems have limited resources like power, speed and computational capabilities, researchers got more inclined towards the goal of making convolutional neural networks more compact, with efficiency of extracting features similar to that of the novel architectures.This research has a similar goal of proposing a convolutional neural network with enhanced efficiency and further using it for a vision application like Image Classification on NXP Bluebox 2.0, an autonomous driving platform by NXP Semiconductors.This paper gives an insight on the Design Space Exploration technique used to propose A-MnasNet (Augmented MnasNet) architecture, with enhanced capabilities, from MnasNet architecture.Furthermore, it explains the implementation of A-MnasNet on Bluebox 2.0 for Image Classification.
Design and Performance Optimization of WebGIS Front End Class Library Based on HTML5

With the development of Internet and mobile Internet technology, especially the maturity of HTML5 technology, WebGIS Application development has been changed from server to client. The front-end development has become the focus of WebGIS and mobile Internet GIS application development. In this paper, a lightweight WebGIS front-end class library (GMap V3.0) based on HTML5 is designed and implemented for the WebGIS platform software ECNU GeoServer developed by ECNU spatial web laboratory. At the same time, the web front-end storage technology, mashup technology, browser compatibility and front-end performance optimization are discussed.
Optimization Strategy of Supply Chain Financial Platform Based on Blockchain

The traditional supply chain financial platform is faced with the problems of logistics information supervision, cumbersome and inefficient financing process, and information asymmetry, which cannot meet the financing needs of small and medium-sized enterprises. This article applies the blockchain technology to the supply chain financial platform, and optimizes the design of the supply chain financial platform based on the blockchain from three aspects: the demand of the supply chain financial platform, the architecture design of the decentralized supply chain financial platform and the design of privacy protection, so as to promote the supply chain finance to break the traditional bottleneck and realize the innovation and development.
Chapter 14. Technological context

This study investigated the impact of technological devices on Kuwaiti youths as creators of a technological context with its own pragmatic parameters. To the youth, a parallel communicative world is in action when they engage in any communicative repertoire using mobile devices. I conducted a survey at the Gulf University for Science and Technology in Kuwait to investigate the existence of such a contextual realm and whether it has its own regulatory factors. A majority of my respondents emphasized that when talking with any person using a mobile device, they are indeed engaged in a communicative environment, the context of which has its own regulatory parameters, such as emoticons, pictures, sound files, text files, tweets, and so on. A majority of the respondents insisted that they feel more secure when using their mobile devices, implying that they become different individuals when doing so, and that this sudden role change occurs due to the contextual environment in which they are engaged. This study emphasizes that the technological context is the product of instant collaboration between two or more communicators in a real-time situation. I argue that technological meanings are produced solely in a technological context and, thus, their facilitating environments differ from those found in the real world.
Dynamics of flows of a substance in a channel with a branch

A model of flow of a substance in a part of a network that consists of a channel and a branch of this channel is discussed. In general this model can be based on differential or difference equations. In this text a difference equations model is considered and studied and it describes how amounts of a substance are distributed along the cells that form the studied part of the network. For the stationary case of motion of the substance a class of long-tail probability distributions is obtained. This class contains famous discrete probability distributions as particular cases. The discussed research has many applications. Several notes about the case of application of the model to channels of human migration are presented.
Research and Practice on Reform of Teaching Content of Digital Technology Course

In the era of science and technology with the rapid development of Internet, we should pay attention to students' innovative spirit and thinking mode in the process of mathematics education and teaching. In order to cultivate students' innovative spirit and improve their mathematical accomplishment and quality, we should instill knowledge into them, but more importantly, we should make them understand the creative process of mathematics. Cultivating students' mathematical modeling literacy is an important embodiment of improving students' application ability and practical ability, and also an important way to cultivate high-quality talents. Therefore, in mathematics teaching, the first thing to determine is the development goal and influencing factors of mathematical modeling literacy, and then to guide students to find accurate information, analyze information, and use information to establish models, so as to achieve good results in mathematics teaching.
Blackjack: A Las Vegas Fairy Tale

In gambling casinos, blackjack is considered the game with the best odds. It is even maintained that there exist strategies that make it possible for the player to beat the house. The goal of blackjack is to draw cards until one has as high a sum of card points as possible that does not exceed 21. In casinos, blackjack is a game played against the bank. Blackjack is practically symmetric for the players and the bank, and is therefore more or less a fair game. A mathematical analysis of blackjack should begin with the bank, whose results can be determined in the form of a probability distribution. The average loss at blackjack can be reduced if one splits and doubles. Depending on the variant of the rules, then, the average loss at blackjack can be brought down to the range 0.64% to 0.88% of the initial wager.
The Influence on Mobile Learning: Mobile Learning Contents, Higher Education Institutes, and Communication Technology

In the present era, mobile learning has secured a better position in modern technology base learning paradigms. It surpasses other conventional learning methods because of ubiquity, mobility, attractive content, facilitated connectivity, and institutional engagements. The main objective of this study is to identify how mobile learning content, higher education institute, and communication technology factors influence learners and teachers when using sustainable mobile learning in higher education. Through the literature review, we developed three separate impact models i.e. mobile learning content, higher education institute, and communication technology with separate impact factors. We used pre and post usage survey questionnaires of 60 teachers and 60 learners to evaluate these models. Primarily, they were asked to fill the pre-usage questionnaire with their initial mobile learning experience. Then, they were allowed to use the modified Moodle mobile app and asked to fill the post-usage questionnaire. The results reveal that the most significant influencing factors are, ease of use in mobile learning content, and facilitating conditions for higher education institutes and communication technology models. Finally, we can conclude that users prefer to have easy to use mobile learning content with better service facilities in higher education institutes and communication technologies.
heSRPT

Modern data centers serve workloads which can exploit parallelism. When a job parallelizes across multiple servers it completes more quickly. However, it is unclear how to share a limited number of servers between many parallelizable jobs. In this paper we consider a typical scenario where a data center composed of N servers will be tasked with completing a set of M parallelizable jobs. Typically, M is much smaller than N. In our scenario, each job consists of some amount of inherent work which we refer to as a job's size. We assume that job sizes are known up front to the system, and each job can utilize any number of servers at any moment in time. These assumptions are reasonable for many parallelizable workloads such as training neural networks using TensorFlow [2]. Our goal in this paper is to allocate servers to jobs so as to minimize the mean slowdown across all jobs, where the slowdown of a job is the job's completion time divided by its running time if given exclusive access to all N servers. Slowdown measures how a job was interfered with by other jobs in the system, and is often the metric of interest in the theoretical parallel scheduling literature (where it is also called stretch), as well as the HPC community (where it is called expansion factor).
Glass Bottle Bottom Segmentation Based on Improved Snake Model

The Snake active contour model converts the image segmentation problem into solving the energy functional minimum problem, and uses curve evolution to locate the edge of the target. But the disadvantage is that it depends on the position of the initial contour. In order to improve the defect that the initial contour of the traditional Snake active model is difficult to locate when it is applied and the inaccurate extraction results when the initialization curve is far away from the target edge, follow the steps below:The initial curve is determined by the inscribed circle generated by the Hough transform algorithm in the area where the target is located; According to the different area where the point on the curve located and the point's neighborhood characteristics, the direction of the point movement on the curve and the automatically changed Step size. The above steps can improve the defect of inaccurate extraction results when the initialization curve is far away from the target edge. The results obtained by the above method are compared with the traditional Snake model segmentation results to verify the feasibility and accuracy of the improved algorithm.