Threefold Optimized Forecasting of Electricity Consumption in Higher Education Institutions

Energy management benefits both consumers and utility companiesalike. Utility companies remain interested in identifying and reducing energywaste and theft, whereas consumers’ interest remain in lowering their energyexpenses. A large supply-demand gap of over 6 GW exists in Pakistan asreported in 2018. Reducing this gap from the supply side is an expensiveand complex task. However, efficient energy management and distributionon demand side has potential to reduce this gap economically. Electricityload forecasting models are increasingly used by energy managers in takingreal-time tactical decisions to ensure efficient use of resources. Advancementin Machine-learning (ML) technology has enabled accurate forecasting ofelectricity consumption. However, the impact of computation cost affordedby these ML models is often ignored in favour of accuracy. This studyconsiders both accuracy and computation cost as concurrently significantfactors because together they shape the technology environment as well ascreate economic impact. Thus, a three-fold optimized load forecasting modelis proposed which includes (1) application specific parameters selection, (2)impact of different dataset granularities and (3) implementation of specificdata preparation. It deploys and compares the widely used back-propagationArtificial Neural Network (ANN) and Random Forest (RF) models for theprediction of electricity consumption of buildings within a university. In addition to the temporal and historical power consumption date as input parameters, the study also embeds weather data as well as university operationalcalendars resulting in improved performance. The outcomes are indicativethat the granularity i.e. the scale of details in data, and set of reduced and fullinput parameters impact performance accuracies differently for ANN and RFmodels. Experimental results show that overall RF model performed betterboth in terms of accuracy as well as computational time for a 1-min, 15-minand 1-h dataset granularities with the mean absolute percentage error (MAPE)of 2.42, 3.70 and 4.62 in 11.1 s, 1.14 s and 0.3 s respectively, thus well suitedfor a real-time energy monitoring application.

A Study on the Management of Career Development of Young Teachers in Higher Education Institutions from the Perspective of Career Anchors

In January 2021,six departments in China,including the Ministry of Education jointly issued the Guiding Opinions on Strengthening Reform in HEI Teacher Capacity Building for the New Era which emphasizes support for career development of young teachers.From the perspective of the career anchor theory,this paper takes human resource management as a tool to analyze organizational environment at the macro and micro levels to find out how to facilitate career development of young teachers in higher education institutions.

Empirical Research on the Status Quo of Teachers of Common Required Courses in Vocational Higher Education Institutions

In order to build a high-quality team of teachers in vocational higher education institutions, and investigate the current situation of teachers of common required courses in vocational higher education institutions of Hainan Province, an empirical research is conducted. A questionnaire survey was carried out in aspects of satisfaction of teaching and scientific research, professional quality, work saturation and teacher’s job satisfaction. The research results shows that the professional quality of teachers of common required courses cannot significantly influence the satisfaction of teaching and scientific research;Job saturation can positively influence teaching and research satisfaction;teaching and research satisfaction can positively influence teachers’ job satisfaction.

Coping Strategies of Nigeria Higher Education Institutions during COVID-19 Lockdown

Beginning at the end of the year 2019,the novel coronavirus(COVID-19)has drowned the world into uncertainty and has threatened the continuity of traditional classroom learning that is the backbone and,in many cases,the main method of learning in most countries.This paper seeks to ascertain how Higher Institutions of learning in Nigeria have thrived during the lockdown period,based on the National policy document that spells out the guidelines for school reopening.Official documents such as newspaper reports university bulletins are used to corroborate in order to ascertain the implementation of the provisions of the policy guideline document as well as assess the efficacy of the measures on students’quality of learning.

Determinants of Satisfaction at Work and Its Reflections on Performance

This study examines the relationship between job satisfaction and performance,investigating personality traits and satisfaction aspects among employees of a Federal Higher Education Institution.A questionnaire was administered to 658 participants,using structural equation modeling for analysis.Results highlighted that challenging work,neuroticism,and self-esteem significantly influenced overall workplace satisfaction,while general satisfaction,self-efficacy,and lack of attention were key determinants of work performance.This emphasizes the importance for managers to prioritize factors enhancing employee satisfaction,as it positively correlates with job performance.

Valorization of Solid Waste Recovery in an Institution of Higher Education

One of the biggest challenges for organizations, cities and countries is waste management. Currently, 1.3 million tons of solid wastes are generated in the cities and by 2025 it is estimated that this volume will increase up to 2.2 billion tons. Considering this, it is clear that strategies for the reduction of waste generation are needed. In order to achieve this arduous and critic task changes in education, culture and public policy are required and one of the strategies that emerge as one of the most effective is the “zero waste” programs. This paper shows the foundation of a zero waste program based on previous and successful experiences in institutions of higher education. It presents the characterization and quantification of waste, as well as the valorization of it and potential environmental and economic benefits of the implementation of this kind of programs in higher education institutions. Results show that reduction and valorization of waste generation is possible in academic sectors while other outcomes emerge, such as the generation of human capital for the implementation of this kind of programs in different sectors of society and, in that way, contribute in the transition towards sustainable development.

Development and construction of China's higher education libraries

Libraries in China's higher education institutions have been developing in keeping pace with the flourishing development of China's higher education. This article aims to make an introduction to the construction of China's higher education libraries, especially the recent three decades' achievements since China's reform and opening-up in 1978. In this article, the authors draw a general picture of the development of libraries in China's higher education institutions, covering such eight aspects as management, types and positioning,organizational structure and personnel, expenditure and buildings, reader service, building and sharing of resources as well as automation system.

New Features and Trends of Higher Education during the Epidemic Period

The epidemic that ravaged the world has had impact on every element of human endeavors,including education.This devastation was evident in the speed with which several countries'ministries of education shut down school activities and halted academic sessions.In the wake of the epidemic,several trends and features has emerged in the higher education sector as higher education institutions tries to create methods to offset the disruptive impacts of the COVID-19 epidemic on their activities and operations.The trends that will shape the future of the higher education industry are not new.However,the epidemic on the other hand has hastened their progress.It has become evident over the last year what the post-epidemic higher education institutions will look like.The rapid speed of change that has already begun will continue.It is in tandem to this that this paper identifies and discusses some of the emerging trends and new features of higher education in the epidemic period.

Enlightenment of the Talent Training Mode of Japan's Colleges and Universities to China's five-year Higher Vocational Education

Since Jimei navigation College of Fujian Province started five-year junior college education in 1984,five-year higher vocational education has become one of the important forms of Higher Vocational Education in China.In the 1960s,with the rapid development of Japan's economy,there was a shortage of technical personnel.In order to cultivate a large number of technical personnel in a short period of time,Japan's specialized colleges and universities recruited junior high school graduates,studied in school for five years,and obtained an associate's degree after graduation,which provided a large number of technical personnel for the development of Japan's basic industry manufacturing industry.By combing the development process of Japan's colleges and universities,this paper studies Japan's colleges and universities from the aspects of school running subjects,talent training objectives,training methods and evaluation methods.It can provide the basis and implementation methods for China to better promote the convergence of secondary and higher vocational education,strengthen the training of secondary and higher vocational education,and provide theoretical basis and practical experience for improving the quality of five-year higher vocational education.

The mechanism of enterprise-university-esearch institute binding to promote higher education and protection measures——For example Tianjin

The Mechanism of Enterprise-university-research institute (EURI) Binding is a market-oriented strategic alliance as the government and industry associations and intermediary organs for auxiliary forces complement, in which enterprises play the leading role and which combines the efforts of enterprises, universities and research institutes. It is the advanced development of enterprise- university-research institute binding cooperation. The development of technology and social economy continue to offer new challenges for higher education. Under this situation, many universities in Tianjin area actively develop their superiority and cooperate with enterprise and research department, trying their best to explore various enterprise- university-research institute binding ways to quicken the pace of technology innovation and transfer in order to make the school's track wider and wider. According to the situation of Tianjin area, this text introduces the cases of mechanism of enterprise-university- research binding about this area's universities and comes up with safeguard measures on the base of analyzing other areas' mechanism of enterprise-university-research institute binding, combining with educational economy and management theory.

Sustainability in Higher Education Institutions(HEI):Merging the Study Systematic Review,Analysis Content and Bibliometrics

This study aims to explore how the topic of sustainability in Higher Education Institutions(HEI)has been addressed in the scientific literature.It presents a systematic literature review of peer-reviewed journal articles published between 1975 and 2019.After that,bibliometric and content analyses were performed in order to identify the behavior and evolution of the literature and identify the frequency with which they appear in the text,making it possible to raise replicable and valid inferences to the data.The results of this study indicate that the theme is emerging since the year 2010 and with a strong focus on qualitative studies,focused on critical theory.The results indicate that although studies involve the tripod environment,economy,and society,there is still a gap in studies that deal with specific issues to solve practical problems and that analyze the impacts from a more holistic perspective.The combination of methods made it possible to identify and interpret the articles in the selected sample,but based on results reported by other authors,with little room for quality control and integrity.

Artificial Intelligence Techniques Based Learner Authentication in Cybersecurity Higher Education Institutions

Education 4.0 is being authorized more and more by the design of artificial intelligence(AI)techniques.Higher education institutions(HEI)have started to utilize Internet technologies to improve the quality of the service and boost knowledge.Due to the unavailability of information technology(IT)infrastructures,HEI is vulnerable to cyberattacks.Biometric authentication can be used to authenticate a person based on biological features such as face,fingerprint,iris,and so on.This study designs a novel search and rescue optimization with deep learning based learning authentication technique for cybersecurity in higher education institutions,named SRODLLAC technique.The proposed SRODL-LAC technique aims to authenticate the learner/student in HEI using fingerprint biometrics.Besides,the SRODLLACtechnique designs a median filtering(MF)based preprocessing approach to improving the quality of the image.In addition,the Densely Connected Networks(DenseNet-77)model is applied for the extraction of features.Moreover,search and rescue optimization(SRO)algorithm with deep neural network(DNN)model is utilized for the classification process.Lastly,template matching process is done for fingerprint identification.A wide range of simulation analyses is carried out and the results are inspected under several aspects.The experimental results reported the effective performance of the SRODL-LAC technique over the other methodologies.

Enhanced Artificial Intelligence-based Cybersecurity Intrusion Detection for Higher Education Institutions

As higher education institutions(HEIs)go online,several benefits are attained,and also it is vulnerable to several kinds of attacks.To accomplish security,this paper presents artificial intelligence based cybersecurity intrusion detection models to accomplish security.The incorporation of the strategies into business is a tendency among several distinct industries,comprising education,have recognized as game changer.Consequently,the HEIs are highly related to the requirement and knowledge of the learner,making the education procedure highly effective.Thus,artificial intelligence(AI)and machine learning(ML)models have shown significant interest in HEIs.This study designs a novel Artificial Intelligence based Cybersecurity Intrusion Detection Model for Higher Education Institutions named AICIDHEI technique.The goal of the AICID-HEI technique is to determine the occurrence of distinct kinds of intrusions in higher education institutes.The AICID-HEI technique encompassesmin-max normalization approach to preprocess the data.Besides,the AICID-HEI technique involves the design of improved differential evolution algorithm based feature selection(IDEA-FS)technique is applied to choose the feature subsets.Moreover,the bidirectional long short-term memory(BiLSTM)model is utilized for the detection and classification of intrusions in the network.Furthermore,the Adam optimizer is applied for hyperparameter tuning to properly adjust the hyperparameters in higher educational institutions.In order to validate the experimental results of the proposed AICID-HEI technique,the simulation results of the AICIDHEI technique take place by the use of benchmark dataset.The experimental results reported the betterment of the AICID-HEI technique over the other methods interms of different measures.

Total Quality Management at Algerian Higher Education Institutions to Promote Our Roles in Comprehensive Development

The aims this study to know the reality of the role for Total Quality Management(TQM)to need of Algerian Higher Education Institutions(AHEI)in apply the Total Quality Management(TQM)to promote the Comprehensive Development(CD),and this approach to enhance their roles in the comprehensive development,the efficiency of the training process,global changes and their needs to adopt a new educational policy in line with the global transformation competition,and the requirements of sustainable development,in this study was used a questionnaire composed of(75)items distributed on(08)areas,This is for confirmation the need to adopt philosophy of Total Quality Management(TQM)as a strategy imposed by the nature and the stage experienced for Algerian Higher Education Institutions(AHEI),And deal with the nature of the changes and challenges imposed by certain factors such as Globalization and the knowledge revolution,through all this inevitably to apply the Total Quality Management(TQM)in our Algerian Higher Education Institutions(AHEI).

Exploring the Potentialities of Automatic Extraction of University Webometric Information

Purpose:The main objective of this work is to show the potentialities of recently developed approaches for automatic knowledge extraction directly from the universities’websites.The information automatically extracted can be potentially updated with a frequency higher than once per year,and be safe from manipulations or misinterpretations.Moreover,this approach allows us flexibility in collecting indicators about the efficiency of universities’websites and their effectiveness in disseminating key contents.These new indicators can complement traditional indicators of scientific research(e.g.number of articles and number of citations)and teaching(e.g.number of students and graduates)by introducing further dimensions to allow new insights for“profiling”the analyzed universities.Design/methodology/approach:Webometrics relies on web mining methods and techniques to perform quantitative analyses of the web.This study implements an advanced application of the webometric approach,exploiting all the three categories of web mining:web content mining;web structure mining;web usage mining.The information to compute our indicators has been extracted from the universities’websites by using web scraping and text mining techniques.The scraped information has been stored in a NoSQL DB according to a semistructured form to allow for retrieving information efficiently by text mining techniques.This provides increased flexibility in the design of new indicators,opening the door to new types of analyses.Some data have also been collected by means of batch interrogations of search engines(Bing,www.bing.com)or from a leading provider of Web analytics(SimilarWeb,http://www.similarweb.com).The information extracted from the Web has been combined with the University structural information taken from the European Tertiary Education Register(https://eter.joanneum.at/#/home),a database collecting information on Higher Education Institutions(HEIs)at European level.All the above was used to perform a clusterization of 79 Italian universities based on structural and digital indicators.Findings:The main findings of this study concern the evaluation of the potential in digitalization of universities,in particular by presenting techniques for the automatic extraction of information from the web to build indicators of quality and impact of universities’websites.These indicators can complement traditional indicators and can be used to identify groups of universities with common features using clustering techniques working with the above indicators.Research limitations:The results reported in this study refers to Italian universities only,but the approach could be extended to other university systems abroad.Practical implications:The approach proposed in this study and its illustration on Italian universities show the usefulness of recently introduced automatic data extraction and web scraping approaches and its practical relevance for characterizing and profiling the activities of universities on the basis of their websites.The approach could be applied to other university systems.Originality/value:This work applies for the first time to university websites some recently introduced techniques for automatic knowledge extraction based on web scraping,optical character recognition and nontrivial text mining operations(Bruni&Bianchi,2020).