Reviewerly/exHarmony huggingface dataset:
Towards a Taxonomy of Technological Innovations in Higher Education

The process of innovation within Higher Education is complex and is limited by internal structural hinderances, lack of knowledge on various technological innovations and their use. Academics in this field have suggested that the limitation stems from lack of comprehension of the fundamental characteristics of the different innovations. The study aims to build towards addressing this problem through the development of a taxonomy to provide distinguishing characteristics of the various innovations available. To develop the taxonomy, the taxonomy development method by Nickerson, Varshney and Muntermann [1] was adopted. A systematic literature review was conducted to discover the dimensions for the conceptual-to-empirical approach and an empirical analysis on a sample of innovations that are said to have a disruptive potential was done to discover additional dimensions. The resulting taxonomy has seven different dimensions with two to three characteristics in each. The findings yielded different categorization of innovations according to disruptive, sustaining or efficiency innovation. The taxonomy should be of value for any scholar interested in innovation in Higher Education.
Influence and Optimization of Power Grid ERP System Permission Management on Enterprise Internal Control

To further explore the impact of ERP (Enterprise Resource Planning, ERP) system authority management on the internal management control of power grid enterprises, further standardize the internal management processes and standards of power grid enterprises, improve the internal production and management efficiency of power grid enterprises, and ensure the security of important data information in the ERP system of power grid enterprises. This paper first analyzes the influence of authority management of power grid ERP system on the internal management control of enterprises based on the background of authority management of Hunan Xiangtan Power Grid ERP system, then put forward feasible suggestions for enterprise automation optimization from the aspects of building enterprise internal control system, asset life-cycle management, internal control environment construction, supply chain cost management, improving personnel’s awareness of internal control, and improving power grid ERP system authority management scheme under the power grid EPR system environment. Introduce ERP system to power grid company and related industry enterprises to participate in the modern management of enterprises, and improve the production management efficiency of enterprises, at the same time, provide reference opinions to ensure the security of important data information of enterprises.
Cybersecurity Considerations for Deep Renovation

Abstract Deep renovation efforts to improve the energy performance of buildings are of paramount importance for the overall energy reduction of nations. Like other construction projects, deep renovation ones are affected by the digital transformation of the construction industry. While this transformation involves the increasing utilisation of new technologies to optimise cost, time and quality at every stage, concerns emerge about how to maintain robust cybersecurity. This chapter summarises the cybersecurity research related to each deep renovation phase and provides an overview of relevant cybersecurity frameworks, standards, guidelines and codes of practice. The chapter also discusses the need for a contingency approach in deep renovation cybersecurity due to the varying requirements of each project and organisation.
Yet Another Parallelism Within the “Hobby Time Training”

The Hobby Time Training (HTT) concept is part of the Developer’s point of view (DPV) learning approach. It is described as “perceive the very solution to the problem as a game,” that is the decision-making process itself becomes a game. Moreover, is assumed the usage of conventional development environments. Thus, following the constructivism, making transition to a next level of gamification in comparison to the more primitive perception of gamification as “make the hard stuff fun.” The HTT assumes solving of small, apparently simple problems, which encapsulates deeply hidden potential that could be find out only during the problem solving. The problem decision is made in the student’s free time, at his discretion. In the area of computer architectures, when viewed as an interface between the high-level languages (HLL) and the raw machine, the bitwise algorithms are a good choice of problem set. Bitwise operations contain the sought-after hidden creative potential, mainly due to the limited support both at the high and low levels. Besides that, bitwise algorithms suppose usage of special techniques as word-level parallelism, unrolling loops and branch elimination. As an illustration of the hidden deep inner content of the bitwise problems, we are going to focus on the computing of bit set problem, or namely the Population Count problem.
Coping with the Business Ethics Issues in the Era of the Internet of Things

The advancement of technology has brought society to the Internet of Things industry. Businesses become more efficient due the technology development via innovation and creativity. New business model creation due to the Internet has changed employment and transaction practices. The emergence of new business models and efficiency has created ethical issues and challenges such as sharing economy employment sustainability, inequality, robot, artificial intelligence in the workplace, and unemployment due to technological advancement. Business ethics is not an exclusive norm developed by business players. Society has its social standards, which will be applied to every aspect of human life, including business. What is right and wrong in the community will be perceived similarly to business practices. Hence, people will not evaluate the business practice based on company perception but on their norms. Consequently, with the radical changes in business models and practices, a new consensus of business ethics between companies and society may be developed to accommodate and balance between companies and society norms.
Prescribing Algorithmic Discrimination

In response to America’s escalating drug poisoning crisis, the federal government has funded, incentivized, and mandated that states adopt and implement prescription drug monitoring programs (PDMPs) to electronically surveil controlled substances and other “drugs of concern.” State PDMPs utilize proprietary, predictive software platforms that deploy algorithms to determine whether a patient is at risk for drug misuse, drug diversion, doctor shopping, or substance use disorder. PDMPs have never been validated by a federal agency or peer review, yet states have mandated their use throughout the health care delivery system. Research demonstrates that clinical overreliance on the risk scores generated by PDMP algorithms motivates clinicians to refuse to treat—or to inappropriately treat—marginalized and stigmatized patient populations, including individuals with or perceived of suffering from substance use disorder and patients with chronic, complex disabilities. This article provides a framework for challenging such PDMP algorithmic discrimination as disability discrimination. It contends that Section 504 of the Rehabilitation Act, the Americans with Disabilities Act, and Section 1557 of the Accountable Care Act can be engaged to protect vulnerable patients from PDMP-related algorithmic discrimination and provides recommendations to strengthen the 2022 Section 1557 proposed rule concerned with clinical-decision algorithmic discrimination, to harmonize new and existing antidiscrimination protections, and to improve implementation and enforcement efforts in this context.
Virtual Training System for the Autonomous Navigation of an Omnidirectional Traction Robot

This paper presents the development of a virtual environment for the training of autonomous omnidirectional drive vehicle control. The virtual system considers the virtualization of structured and unstructured environments. Therefore, the virtual environment considers mathematical models of the omnidirectional robot in order to simulate more realistically the behavior and motion constraints of the robot. The integration of the control schemes is considered in the MATLAB software, for which a communication between the Unity3D graphic engine and MATLAB is considered through the use of DLL libraries. For the validation of the control algorithms on the virtual training environment, the construction of an omnidirectional traction vehicle with mecanum configuration. In addition, the constructed prototype will be used for the identification and validation of the mathematical models that represent its behavior. Finally, a usability analysis of the developed training system is presented.
Preserving Filipino Native Dishes Using Android-Based Application: A Heritage Cooking Tutorial

As a result of contemporary cooking methods, many of the local cuisines in the Philippines are starting to be forgotten. Today, some restaurants have begun to serve native dishes, but in small quantities. In some restaurants, the serving of native dishes is primarily centered on the most popular. With that, the vast majority of historical foods that shaped Philippine culture are now considered endangered and might be lost forever. Cooking tutorials using mobile devices are popular nowadays. Applications such as this help individuals easily learn how to cook certain dishes. In this study, the researchers developed a cooking tutorial mobile application that can preserve Filipino historical cuisines to help Filipino get used to different dishes that are part of their heritage. The goal of the study to provide instructions on how to properly prepare traditional dishes using actual cooking time and voice guide was achieved. To successfully develop the application tutorial, the researchers made use of the unified method, since this model focuses on the exchange of ideas and messages taking place between the user and the application. Moreover, statistical analysis of data revealed that the application was helpful and effective for people who wanted to learn how to cook native dishes. Users appreciated the application because it could explain the step-by-step process on cooking Filipino native dishes. Additionally, the application offers information on each recipe's historical significance. People who enjoy cooking will find the application highly helpful, user-friendly, and simple to use.
Higher Education and Skills for the Future(s) of Work

Abstract This chapter takes a macro-level approach to explore key skills required for the future(s) of work in a digital era. It will explore how the future skills highlighted both impact on, and can be co-created and nurtured through, formal yet flexible higher education. Our focus is purposefully on skills for the future (not of the future) and on futures (plural). A key underpinning to our argument is the need for a narrative that moves away from a technical focus on skill development to a more holistic view of human-centred development. This is discussed with respect to the human aspects of digitalisation in virtual and real dimensions, the slow movement and elevated well-being. In providing an infrastructure which balances reflection and action while locating digital disruption in its socio-economic context, higher education can ultimately provide a platform for greater certainty and progress in an age of digital disruption and uncertainty.
Creating a Happy Life Through Body Sensations

The World 1.0, the world of the industrial society, is getting close to its ceiling and many issues are emerging, such as decreasing labor force due to decreasing childbirth and aging population. And although AI is expected to contribute to the next generation, it consumes 10,000 times more energy than that of a human brain. So, although AI is indeed wonderful, we need to pinpoint the applications, which cannot be solved otherwise. Thus, it is time now to develop another world for the next generation. We make our life happy by “self-sustaining” and “self-satisfying”. Then, we can reduce the burden to the “society” to the minimum. Still, we can enjoy the maximum happiness and the feeling of achievement. To achieve this, we need to pay attention to our “instinct” and utilize it to the maximum. In short, we should pay attention to the body sensations and make the most of our proprioception.
1001 Games a Night—Continuous Evaluation of an Intelligent Multi-agent-Based System

The goal of the presented approach is to improve the stability of our RoboCup team code by providing an improved continuous integration software engineering process. As big and even small changes in our code base cannot be judged by just a couple of games, roughly 1000 games were run each night to have a good feeling whether changes were for the better or for worse. In addition, it is now possible to analyze the output to gain even deeper understanding of different approaches and parameters. This is supported by interactive visualization techniques. As a brute force approach will collect way too much data every night, it is necessary to condense the output and keep just a very small fraction of the detailed log data for further analysis. To decide which log files to keep different outlier detection algorithms are compared and optimized.
Real-Time Hand Action Detection and Classification Based on YOLOv7 from Egocentric Videos

Hand detection and classification still exists many challenges when detecting and classifying the hands-on data received from the first-person camera/egocentric vision, because the data of the hand is obscured by the viewpoint or other objects. On this dataset, the fingers are almost completely obscured, and only the data area of the hand palm is visible. In this paper, we propose to apply YOLOv7 and its variations for fine-tuning the hand action detection, and classification model on the RGB image of egocentric vision dataset as First-Person Hand Action Benchmark (FPHAB) dataset, HOI4D dataset. We have prepared the ground-truth data of the hand action by manual operation for the hand action detection evaluation on the FPHAB and HOI4D datasets. The results are compared with different YOLO variations (YOLOv7, YOLOv7-w6, YOLOv7-X) and Mediapipe on the FPHAB and HOI4D datasets. We did a very diverse evaluation with two configurations (Conf. #123, Conf. #213) of data on the FPHAB and a configuration of the HOI4D dataset. YOLOv7 and its variants are more than 95% accurate across all evaluation configurations with an IOU threshold of 0.95.
Traffic Sign Recognition Based on Improved VGG-16 Model

Traffic sign recognition technology is very important in intelligent transportation systems. Aiming at the problem that the imbalance of existing traffic sign data sets affects the recognition accuracy. Firstly, this paper introduces the Weighted-Hybrid loss function in VGG-16 to enhance the feature extraction ability of the model. The model can reduce the contribution of easy-to-classify samples to the decline of the loss function. Then, we introduce the HDC-VGG lightweight model to ensure the accuracy of model recognition on the basis of reducing model parameters. Finally, the experiment results show that the recognition accuracy of the proposed model can reach 98.2%.
Towards Prototyping Single-modal and Multimodal Interactions in Mixed Reality Games

Mixed reality (MR) blends the physical and digital environments using natural interactions. In MR, users experience computer-generated content in the physical world by wearing a head-mounted display unit. MR domain is still in its infancy with several open questions on immersion, comfort, user interactions, and user experience. Specifically, game user experience in MR is new to the research in game design and human-computer interaction. To understand the effective interaction modes with new technology such as MR, user experience analysis and interaction patterns need to be deeply explored. In this paper, we aim to explore novel ways in which we can effectively play games in an MR environment by analyzing different interaction modalities and user experience factors. This paper explains the prototypical process involved in developing 5 games in MR that include single-modal and multimodal interactions.
Distance Education Opportunities for the Elderly in Thailand: Opportunity to Access Distance Education and Factors Affecting Such Opportunity

The aim of this study was to investigate the present situation of lifelong learning of the elderly as well as factors impacting the opportunity and accessibility of distance education for the elderly. This study was divided into two stages. This article presents only the results of the first stage, which is a quantitative study that used a printed survey and an online survey to collect data from 791 participants. In this survey, the questionnaires were distributed to samples from all five geographical regions in Thailand. It was found that nearly all the elders were married and lived with a small family. Their education varied, but mostly they had completed elementary school education, and most did not work anymore. Their average income was most commonly between 1000 and 5000 Thai Baht that came from elderly welfare given by the government. They mostly did have electronic devices, that included televisions and smartphones, and mostly they learned for self-development and used their devices to get access to social media such as Line and YouTube, and tended to spend less than 3 h in the morning for their learning. They reported learning mostly for easing their loneliness and maintaining their ability, perception, and memory. The people who influenced their decisions to learn were mainly just themselves. Moreover, they indicated having little knowledge about the topics of law in daily life and elderly people’s rights. They were mostly interested in learning more about physical exercise, the use of Line application, music, and rights protection for the elderly. Most said they were likely to use the opportunity to participate in distance learning at only a medium level because of the lack of accessibility, internet network, health problems, vision problems, insufficiency of study time due to agriculture job, lack of advisors, and poor-quality devices.
An Experimental Analysis of Benchmarking Tools for Smart Contract-Based Blockchain Application

Blockchain is an emerging technology that can merge with various business sectors. However, the blockchain is nevertheless in the early stage, and there are concerns regarding its acceptability. One of the primary bottlenecks is the low-performance issue. Thus, it is necessary to assess the multi-blockchain ecosystem’s performance in different use case scenarios. This paper presents experimental insights on the smart contract-based blockchain using Hyperledger caliper and manual benchmarking. It monitors and simulates benchmarking tools for varying workloads. Thus, this work analyzes Hyperledger caliper and manual benchmarking on scalable and adaptable networks. It also presents a graphical analysis of the performance evaluation metrics such as transaction rate, throughput, and average read or write latency. It also gives a proper understanding of the relative parameters such as success rate, availability, consistency, and scalability. The proposed approaches will help researchers benchmark and make correct decisions in developing blockchain systems.
Neural Network Models for Time Series Analysis and Estimation

This paper focuses on time series and regression modeling using neural networks. Based on the recent results of least squares estimation of nonlinear time series, the research proposed a comprehensive and straightforward methodology for parameter estimation (learning process) and model selection (structure selection). This research presents a solution to the problem of pruning in a multi-layer perceptron by means of a step-by-step method using the Schwarz information criterion (SIC) type standard in which can be demonstrate its consistency. In more concise words, this paper deals with neural network modeling for time series and regression analysis based on recent results of least square estimation for nonlinear time series, the work proposed a complete and feasible methodology for parameter estimation (learning process) and model selection (structure selection). This work has solved the pruning problem of multi-layered cognition models using a gradient search method using the SIC criterion which has been shown to be consistent.
Sorting and Searching

In computer science, a sorting algorithm is an algorithm that puts elements of a list into an order. The most frequently used orders are numerical order and lexicographical order, and either ascending or descending. This chapter studies some of the sorting algorithms and their C implementations.
System Models of a Single Information Space of Digital Twins

The paper considers a systematic approach to modeling a single system-information space of virtual digital production. The terms system information, information norm, and information measure introduced in the work correspond to the generally accepted classical definition of the concept of “information”. An analysis of system-information models of processes and systems was carried out, and a definition of the term system information was proposed as a proportional ratio of a general attribute to its particular value, that is, information about the proportion of an information measure is subject to transmission. A methodology for system-information modeling of the information space is proposed. An example of calculating equivalent system information is given and an analysis of methods for solving production problems using system-information models is carried out. The analysis of methods for solving production problems, based on system-information models, showed additional possibilities for processing information in single information space of virtual digital industries, which are based on the developed terms of system information, information norm, and information measures.
Solving Class Imbalance Problem in Target Detection with a Squared Cross Entropy Based Method

The foreground-background class imbalance in target detection is inevitable, which is caused by the training data set. Specifically, the number of targets contained in any image of the training data set is generally very small, that is, the number of positive examples is small, while the number of the negative examples from the background is large. Therefore, the ability of the algorithm to detect the negatives is stronger than that of positive examples. The Focal Loss algorithm solves this problem by improving the classification loss function. However, Focal Loss brings additional hyper-parameters, which remains to be further adjusted. This paper refers to the idea of Focal Loss from the classification loss function, and proposes new a classification loss function SCE that is similar to Focal Loss but does not contain any extra hyper-parameters. Experiments in the paper prove that SCE can obtain performance equivalent to Focal Loss without introducing hyper-parameters.