Instruments Assessing Problematic Use of the Internet and Their Associations with Psychological Distress among Ghanaian University Students

Background:The present study evaluated the psychometric properties of Problematic Internet Use(PIU)instruments and their correlation with psychological distress and time spent on Internet activities among university students in Ghana.Methods:In the present cross-sectional survey design study,520 participants(35.96% female)were recruited with a mean age of 19.55 years(SD=1.94)from several university departments(i.e.,Behavioral Sciences,Materials Engineering,Nursing and Midwifery,and Biochemistry and Biotechnology)of Kwame Nkrumah University of Science and Technology(KNUST)between 19 July and 04 August,2023.Participants completed a survey that included the following measures:the Gaming Disorder Test(GDT),Gaming Disorder Scale for Adolescents(GADIS-A),Internet Gaming Disorder Scale-Short Form(IGDS9-SF),Bergen Social Media Addiction Scale(BSMAS),Smartphone Application Based Addiction Scale(SABAS),Nomophobia Questionnaire(NMP-Q),and the external criterion measure:Depression Anxiety Stress Scale-21(DASS-21).Confirmatory factor analysis(CFA)was carried out to evaluate the structure of the instruments.Cronbach’s α,McDonald’s ω,and composite reliability were used to evaluate internal consistency.Pearson correlation was used to examine the associations between the scores of instruments assessing PIU,time spent on Internet activities,and the level of psychological distress.Results:Model fits confirmed the(i)unidimensional structure of the GDT,BSMAS,SABAS,IGDS9-SF,(ii)two-factor structure of the GADIS-A,and(iii)four-factor structure of the NMP-Q.Additionally,the study found that different types of PIU were significantly associated with psychological distress and time spent on related Internet activities.Conclusion:The six instruments validated in the present study demonstrated very good to excellent psychometric properties when applied to university students in Ghana.The significant associations between Internet-related disorders,time spent on Internet-related activities,and psychological distress highlight the importance of addressing issues of PIU among this population.

The Existing Problems and Optimization Paths of Digital Textbooks Under Background of Internet

With the rapid development of information technology,the combination of terminal technology,big data and mobile Internet and textbooks has become an irresistible trend in the modern education field.Under the context of the Internet,carrying out education and teaching activities based on digital textbooks can give full play to the rich media,openness and interaction of digital textbooks,broaden students′horizon,enrich students′knowledge,and promote the improvement of students′ability and all-round development.However,in the specific teaching practice,there are also problems such as old compilation ideas,single compilation mode and low efficiency of personalized learning.Therefore,schools and teachers need to constantly innovate the presentation and arrangement of digital textbooks,strengthen technical support,deepen students′understanding of the teaching content of digital textbooks,promote the comprehensive development of students and improve the effectiveness of digital textbook teaching.

Study on Problems and Countermeasures of English Hidden Curriculum Construction in Higher Vocational Colleges in the Era of “Internet Plus”

As the extension and supplement of explicit curriculum,the English hidden curriculum in higher vocational colleges plays animportant role in cultivating students' behaviors,stimulate their interest and arouse their enthusiasm,initiative and creativity in learningEnglish.This paper analyzes the problems of English hidden curriculum construction in higher vocational colleges under the back-ground o"fInternet plus",and puts forward some corresponding countermeasures to bring the role of college English hidden curriculuminto full play.

Internet addiction and problematic Internet use: A systematic review of clinical research

AIM: To provide a comprehensive overview of clinical studies on the clinical picture of Internet-use related addictions from a holistic perspective. A literature search was conducted using the database Web of Science.METHODS: Over the last 15 years, the number of Internet users has increased by 1000%, and at the same time, research on addictive Internet use has proliferated. Internet addiction has not yet been understood very well, and research on its etiology and natural history is still in its infancy. In 2013, the American Psychiatric Association included Internet Gaming Disorder in the appendix of the updated version of the Diagnostic and Statistical Manual for Mental Disorders(DSM-5) as condition that requires further research prior to official inclusion in the main manual, with important repercussions for research and treatment. To date, reviews have focused on clinical and treatment studies of Internet addiction and Internet Gaming Disorder. This arguably limits the analysis to a specific diagnosis of a potential disorder that has not yet been officially recognised in the Western world, rather than a comprehensive and inclusive investigation of Internet-use related addictions(including problematic Internet use) more generally. RESULTS: The systematic literature review identified a total of 46 relevant studies. The included studies used clinical samples, and focused on characteristics of treatment seekers and online addiction treatment. Four main types of clinical research studies were identified, namely research involving(1) treatment seeker characteristics;(2) psychopharmacotherapy;(3) psychological therapy; and(4) combined treatment. CONCLUSION: A consensus regarding diagnostic criteria and measures is needed to improve reliability across studies and to develop effective and efficient treatment approaches for treatment seekers.

Comparisons of temperament and character between problematic internet users and problematic drug users in Korean adolescents

Objective: It has been suggested that some internet users spend so much time on the internet that their personal and/or professional lives suffer. This study compared the temperament and character of problematic internet users (PIU) with that of problematic drug users (PDU) among Korean adolescents and aimed to examine the personality characteristics of adolescents with internet use problems. Method: We enrolled participants from high schools (n = 487), internet cafés (n = 89), and an adolescent-substance abuse consultation office (n = 45). All subjects were assessed using the Korean Internet Addiction Scale (KIAS), the Korean Adolescent Drug Addiction Screening Test-2 (KOADAST-2), and the Korean version of the Temperament and Character Inventory (K-TCI). Subjects were classified into the following four groups based on the KIAS and KOADAST-2 results: normal controls, pure PIUs, pure PDUs, and dual problematic users. Differences in the subscale scores on the K-TCI were analyzed by group. Results: Scores for Reward dependence (RD) were significantly lower in pure PIUs than in pure PDUs (13.85 ± 4.07 versus 15.44 ± 3.56, p < 0.05). Scores for Self-Directedness (SD) were lower in pure PIUs (18.21 ± 6.90) and pure PDUs (18.22 ± 6.03) than in normal controls (20.88 ± 6.60), although the scores did not differ significantly between pure PIUs and pure PDUs. Scores for Cooperativeness (C) were lower in pure PIUs than in normal controls (23.97 ± 7.02 versus 26.57 ± 6.67, p < 0.05). Conclusions: The results of this study suggest that PIUs are more socially insensitive and that they may experience more inter-personal problems than PDUs.

Neurobiological risk factors for problematic social media use as a specific form of Internet addiction:A narrative review

Problematic social media use(PSMU)is a behavioral addiction,a specific form of problematic Internet use associated with the uncontrolled use of social networks.It is typical mostly for modern adolescents and young adults,which are the first generations fully grown up in the era of total digitalization of society.The modern biopsychosocial model of the formation of behavioral addictions,postulating the impact of a large number of biological,psychological,and social factors on addictive behavior formation,may be quite applicable to PSMU.In this narrative review,we discussed neurobiological risk factors for Internet addiction with a focus on current evidence on the association between PSMU and structural/functional characteristics of the brain and autonomic nervous system,neurochemical correlations,and genetic features.A review of the literature shows that the vast majority of the mentioned neurobiological studies were focused on computer games addiction and generalized Internet addiction(without taking into account the consumed content).Even though a certain number of neuroimaging studies have been conducted for PSMU,there is practically no research on neuropeptide and genetic associations for PSMU to date.This fact points to the extremely high relevance of such studies.

A Summary of the Main Contents and Existing Problems in the Study of Multi-Energy Coupling in Energy Internet

Multi-energy flow (MEF) coupling is one of the key features of the energy Internet and integrated energy systems that are different from smart grids. With the increasing coupling of heterogeneous energy flow, the system characteristics of coupling are becoming more and more obvious and more complicated. The modeling, analysis and control methods of traditional single flow systems have not been applied directly. Therefore, it is necessary to study the modeling of multi-energy flow coupling, the power flow analysis, optimization and control method of heterogeneous energy flow, which plays the role of multi-energy flow synergy to avoid the adverse effects of coupling. This paper summarizes the current research situation of energy Internet at home and abroad from the aspects of modeling of multi-energy flow, power flow calculation and optimal dispatching, and analyzes the existing problems in the research of these aspects.

Analysis on the Implicit Internet Attitude of the Internet Addicts and the Intervene Problems

Implicit Internet attitude refers to the implicit, automatic psychological tendency of an individual toward the Internet. A study found that Internet addicts held an implicit attitude and positive evaluation toward the Intemet, and this type of evaluations could be effectively changed through subliminal evaluative conditioning technology. An investigation on IAT effect showed the implicit attitude of the Intemet addicts was stable and variable, and AIA （ambivalence of implicit attitudes） might be an integrated perspective to solve the problem.

From the empty nest elderly to explore the era of Internet ＋ in Shanghai community enctowment problems at home

At present, China＇s population aging of unprecedented increase, empty older family question discussion and solve the problem of pension, is the urgent needs of the population aging in our country. Compared with the traditional family endowment, institution endowment and community endowment that occupy the home can guarantee the old man in his own enjoy the professional care services in the community, its unique advantage by relevant government departments, institutions and community in favor of people. At the same time, the rapid development of science and technology will we＇re in a new era of big data, set offa wave of intelligent city, the era of Internet ＋ city community home endowment also ushered in the new opportunities and challenges, ＂community O2O＂ pension mode is more and more clear, the Internet information technology will be in the development of urban community endowment that occupy the home is very imoortant.

Current Situation and Problems of College Students’Financial Management in the Era of Internet Finance and the Countermeasures

With the rapid development of information technology,internet financial products have been continuously launched,and many college students have joined the internet financial team.By investigating the current situation of college students’financial management,this study found several problems and deficiencies in college students’financial management and proposed countermeasures to these problems for colleges and universities to cultivate students’internet financial literacy as well as guide them to establish the correct concept of financial management under the internet financial environment,learn financial management knowledge,improve financial management capabilities and risk awareness,as well as choose appropriate internet financial management products.

Enhancing Critical Path Problem in Neutrosophic Environment Using Python

In the real world,one of the most common problems in project management is the unpredictability of resources and timelines.An efficient way to resolve uncertainty problems and overcome such obstacles is through an extended fuzzy approach,often known as neutrosophic logic.Our rigorous proposed model has led to the creation of an advanced technique for computing the triangular single-valued neutrosophic number.This innovative approach evaluates the inherent uncertainty in project durations of the planning phase,which enhances the potential significance of the decision-making process in the project.Our proposed method,for the first time in the neutrosophic set literature,not only solves existing problems but also introduces a new set of problems not yet explored in previous research.A comparative study using Python programming was conducted to examine the effectiveness of responsive and adaptive planning,as well as their differences from other existing models such as the classical critical path problem and the fuzzy critical path problem.The study highlights the use of neutrosophic logic in handling complex projects by illustrating an innovative dynamic programming framework that is robust and flexible,according to the derived results,and sets the stage for future discussions on its scalability and application across different industries.

A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as industry,automotive,construction,machinery,and interdisciplinary research.However,there are established optimization techniques that have shown effectiveness in addressing these types of issues.This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues.The algorithms used in the study are listed as:transient search optimization(TSO),equilibrium optimizer(EO),grey wolf optimizer(GWO),moth-flame optimization(MFO),whale optimization algorithm(WOA),slimemould algorithm(SMA),harris hawks optimization(HHO),chimp optimization algorithm(COA),coot optimization algorithm(COOT),multi-verse optimization(MVO),arithmetic optimization algorithm(AOA),aquila optimizer(AO),sine cosine algorithm(SCA),smell agent optimization(SAO),and seagull optimization algorithm(SOA),pelican optimization algorithm(POA),and coati optimization algorithm(CA).As far as we know,there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems.Hence,a remarkable research guideline is presented in the study for researchersworking in the fields of engineering and artificial intelligence,especiallywhen applying the optimization methods that have emerged recently.Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.

An Effective Meshless Approach for Inverse Cauchy Problems in 2D and 3D Electroelastic Piezoelectric Structures

In the past decade,notable progress has been achieved in the development of the generalized finite difference method(GFDM).The underlying principle of GFDM involves dividing the domain into multiple sub-domains.Within each sub-domain,explicit formulas for the necessary partial derivatives of the partial differential equations(PDEs)can be obtained through the application of Taylor series expansion and moving-least square approximation methods.Consequently,the method generates a sparse coefficient matrix,exhibiting a banded structure,making it highly advantageous for large-scale engineering computations.In this study,we present the application of the GFDM to numerically solve inverse Cauchy problems in two-and three-dimensional piezoelectric structures.Through our preliminary numerical experiments,we demonstrate that the proposed GFDMapproach shows great promise for accurately simulating coupled electroelastic equations in inverse problems,even with 3%errors added to the input data.

Efficient Inverse Analysis for Solving a Coupled Conduction,Convection and Radiation Problem Involving Non⁃gray Participating Media

The presence of non-gray radiative properties in a reheating furnace’s medium that absorbs,emits,and involves non-gray creates more complex radiative heat transfer problems.Furthermore,it adds difficulty to solving the coupled conduction,convection,and radiation problem,leading to suboptimal efficiency that fails to meet real-time control demands.To overcome this difficulty,comparable gray radiative properties of non-gray media are proposed and estimated by solving an inverse problem.However,the required iteration numbers by using a least-squares method are too many and resulted in a very low inverse efficiency.It is necessary to present an efficient method for the equivalence.The Levenberg-Marquardt algorithm is utilized to solve the inverse problem of coupled heat transfer,and the gray-equivalent radiative characteristics are successfully recovered.It is our intention that the issue of low inverse efficiency,which has been observed when the least-squares method is employed,will be resolved.To enhance the performance of the Levenberg-Marquardt algorithm,a modification is implemented for determining the damping factor.Detailed investigations are also conducted to evaluate its accuracy,stability of convergence,efficiency,and robustness of the algorithm.Subsequently,a comparison is made between the results achieved using each method.

Clarifications for the Published Article: “A Solution to the Famous Twin’s Problem” in the APM of SCIRP at 24 September of 2019

This article B is almost autonomous because it can be read independently from the first published article A [1] using only a few parts of the article A. Be-low are given instructions so to need the reader study only on few places of the article A. Also, in the part A of Introduction, here, you will find simple and useful definitions and the strategy we are going to follow as well useful new theorems (also and in Section 5, which have been produced in this solution). So the published solution of twin’s problem can now be easily understood. The inequalities (4.17), (4.18) of Article A are proved here in Section 4 by a new clear method, without the possible ambiguity of the text between the relations (4.14), (4.16) of the Article A. Also we complete the proof for the twin’s distri-bution which we use. At the end here are presented the Conclusions, the No-menclatures and the numerical control of the proof, which is probably useful as well in coding methods. For a general and convincing picture is sufficient, a study from the beginning of this article B until the end of the part A of the In-troduction here as well a general glance on the Section 5 and on the Conclu-sions below.

ResNeSt-biGRU: An Intrusion Detection Model Based on Internet of Things

The rapid expansion of Internet of Things (IoT) devices across various sectors is driven by steadily increasingdemands for interconnected and smart technologies. Nevertheless, the surge in the number of IoT device hascaught the attention of cyber hackers, as it provides them with expanded avenues to access valuable data. Thishas resulted in a myriad of security challenges, including information leakage, malware propagation, and financialloss, among others. Consequently, developing an intrusion detection system to identify both active and potentialintrusion traffic in IoT networks is of paramount importance. In this paper, we propose ResNeSt-biGRU, a practicalintrusion detection model that combines the strengths of ResNeSt, a variant of Residual Neural Network, andbidirectionalGated RecurrentUnitNetwork (biGRU).Our ResNeSt-biGRUframework diverges fromconventionalintrusion detection systems (IDS) by employing this dual-layeredmechanism that exploits the temporal continuityand spatial feature within network data streams, a methodological innovation that enhances detection accuracy.In conjunction with this, we introduce the PreIoT dataset, a compilation of prevalent IoT network behaviors, totrain and evaluate IDSmodels with a focus on identifying potential intrusion traffics. The effectiveness of proposedscheme is demonstrated through testing, wherein it achieved an average accuracy of 99.90% on theN-BaIoT datasetas well as on the PreIoT dataset and 94.45% on UNSW-NB15 dataset. The outcomes of this research reveal thepotential of ResNeSt-biGRU to bolster security measures, diminish intrusion-related vulnerabilities, and preservethe overall security of IoT ecosystems.

Highly Accurate Golden Section Search Algorithms and Fictitious Time Integration Method for Solving Nonlinear Eigenvalue Problems

This study sets up two new merit functions,which are minimized for the detection of real eigenvalue and complex eigenvalue to address nonlinear eigenvalue problems.For each eigen-parameter the vector variable is solved from a nonhomogeneous linear system obtained by reducing the number of eigen-equation one less,where one of the nonzero components of the eigenvector is normalized to the unit and moves the column containing that component to the right-hand side as a nonzero input vector.1D and 2D golden section search algorithms are employed to minimize the merit functions to locate real and complex eigenvalues.Simultaneously,the real and complex eigenvectors can be computed very accurately.A simpler approach to the nonlinear eigenvalue problems is proposed,which implements a normalization condition for the uniqueness of the eigenvector into the eigenequation directly.The real eigenvalues can be computed by the fictitious time integration method(FTIM),which saves computational costs compared to the one-dimensional golden section search algorithm(1D GSSA).The simpler method is also combined with the Newton iterationmethod,which is convergent very fast.All the proposed methods are easily programmed to compute the eigenvalue and eigenvector with high accuracy and efficiency.

Linking 24-h Movement Behavior Guidelines to Cognitive Difficulties,Internalizing and Externalizing Problems in Preterm Youth

Background:Given the heightened risk of developmental challenges associated with preterm birth,it is crucial to explore interventions that may ameliorate potential adverse outcomes.This study aimed to examine whether meeting the 24-h movement behavior(24-HMB)guidelines,which include recommendations on physical activity(PA),screen time(ST),and sleep(SL),is related to indicators of cognitive difficulties,internalizing problems(e.g.,depression and anxiety),and externalizing problems(e.g.,difficulties in making friends and arguing)in a sample of preterm youth(children and adolescents born preterm).Methods:In this cross-sectional study,data from 3410 preterm youth(aged 6 to 17 years)were included for data analyses.Multivariable logistic regression was used to investigate associations between meeting the 24-HMB guidelines and the above-mentioned health outcomes,while controlling for sociodemographic and health-related factors.Results:The prevalence of meeting 24-HMB guidelines varied across independent and integrated components of the 24-HMB guidelines.Meeting the ST guideline alone(p<0.05)and integrated guidelines(i.e.,ST+SL and ST+SL+PA)were associated with fewer cognitive difficulties and reduced internalizing and externalizing problems(p<0.05).Specifically,meeting the SL guideline alone and integrated guidelines(i.e.,SL+ST)were associated with lower odds of depression and anxiety(p<0.01).Additionally,meeting independent,and integrated(PA and/or ST)guidelines were associated with less pronounced difficulties in making friends and arguing(p<0.05).Meeting 24-HMB guidelines in an isolated and integrated manner are linked to better cognitive performance and fewer internalizing and externalizing problems in preterm youth.Conclusion:Results suggest that advocating for the implementation of the 24-HMB guidelines may reduce cognitive challenges and behavioral issues,which is of high relevance for improving public health.Future longitudinal studies in preterm youth should investigate how modifying specific 24-HMB behaviors,especially ST,influence cognitive difficulties,internalizing and externalizing problems in this vulnerable population.

Deep Transfer Learning Techniques in Intrusion Detection System-Internet of Vehicles: A State-of-the-Art Review

The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)technology.The functional advantages of IoV include online communication services,accident prevention,cost reduction,and enhanced traffic regularity.Despite these benefits,IoV technology is susceptible to cyber-attacks,which can exploit vulnerabilities in the vehicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and vehicle immobilization.This paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of Vehicles(IDS-IoV)based on anomaly detection.IDS-IoV leverages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by cyber-attacks.These systems can autonomously create specific models based on network data to differentiate between regular traffic and cyber-attacks.Among these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational complexity.We evaluate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and stability.This review highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-IoV systems.By examining recent advancements,we provide insights into how DTL can effectively address cyber-attack challenges in IoV environments,ensuring safer and more efficient transportation networks.

Optimal Shape Factor and Fictitious Radius in the MQ-RBF:Solving Ill-Posed Laplacian Problems

To solve the Laplacian problems,we adopt a meshless method with the multiquadric radial basis function(MQRBF)as a basis whose center is distributed inside a circle with a fictitious radius.A maximal projection technique is developed to identify the optimal shape factor and fictitious radius by minimizing a merit function.A sample function is interpolated by theMQ-RBF to provide a trial coefficient vector to compute the merit function.We can quickly determine the optimal values of the parameters within a preferred rage using the golden section search algorithm.The novel method provides the optimal values of parameters and,hence,an optimal MQ-RBF;the performance of the method is validated in numerical examples.Moreover,nonharmonic problems are transformed to the Poisson equation endowed with a homogeneous boundary condition;this can overcome the problem of these problems being ill-posed.The optimal MQ-RBF is extremely accurate.We further propose a novel optimal polynomial method to solve the nonharmonic problems,which achieves high precision up to an order of 10^(−11).