Characteristics Of Technology Research Articles

Performance analysis of different control models for smart demand–supply energy management system

Several features of innovative grid technologies can be deployed to improve the overall performance of the power system environment. This can be seen from the generation to the consumption of energy. The two-way communication of smart metering introduces the novel functionalities of the energy management system. This paper presents a practical implementation of using the intelligent metering system. It consists of implementing a nanogrid that optimally coordinates the energy from the solar panel, battery storage and utility grid to supply the end user. The developed model is validated with an optimal value of the state of charge of the distributed energy storage to maximise energy from the solar panel and battery storage while minimising the power received from the utility grid. A demand response scheme is employed to formulate the performance index of the energy management system using three optimal control models: adaptive open-loop control, adaptive closed-loop control and model predictive control schemes. The formulation of the performance index of each approach is a function of the energy flow from different resources depending on the power consumption. The three models have given different insights into the performance of the smart nanogrid, which may be used to the advantage of the grid owner or end user. Through the performance of the optimal strategies, it can be observed that energy management is ensured, and real-time monitoring of the entire system is guaranteed. The performance models facilitate the minimisation of the power from the utility, resulting in savings between 23.7% and 39.240% of the total energy demand from the end user. Besides, the system design is validated by an electrical system to form a real-world innovative nanogrid application in residential environments.

B-LPoET: A middleware lightweight Proof-of-Elapsed Time (PoET) for efficient distributed transaction execution and security on Blockchain using multithreading technology

A private permissioned chain is typically considered a fully protected authorized blockchain. The concept of a permissioned chain has become better single-entity control operation over the network and allows entry only to selected nodes, which most probably supports different small-medium enterprises and government officials. It is one of the prominent features of blockchain technology that maintains transaction integrity and security throughout the deliverance. This paper initially highlights the benefits of a permissioned private chain. Present the current issues of the Proof-of-Elapsed Time consensus mechanism for the distributed applicational environment. In order to make blockchain systems more adaptive for private chains, this paper proposes a middleware lightweight consensus based on PoET, named “B-LPoET”. Objecting to being improved as a lightweight PoET from the predefined PoET in terms of verifying transactions and creating more blocks, to decide the mining right, and participants allows to acknowledge their identities before joining. The design of B-LPoET reduces the cost of multi-node efficiency by establishing a lightweight topology for selecting and waiting time of winning node using multithreading, which affects positively by increasing systems scalability. The experimental results of the B-LPoET illustrate that it performs better as compared with the existing PoET and other state-of-the-art consensus.

Cloud Computing and Mobile Technologies as a Marketing Strategy towards Innovation and Business Growth among Small Tourism Enterprises

This study examined the impact of Cloud Computing and Mobile Technologies as marketing strategy towards innovation, business growth among small tourism enterprises (STEs). Mobile commerce is viewed as next generation, e-commerce refers to any transactions, either direct or indirect, via mobile devices, such as phones or personal digital assistants (PDAs). Most significant features of mobile technology are mobility and portability. Ability to access services ubiquitously, on the move, through wireless networks, various devices. The study highlights business risk of being left behind and gives a contemporary research gap, how frequent businesses are engaging with mobile technologies and innovation marketing strategies. Positivist Paradigm- Targeted population were Southern African border countries players in STEs. Data analysis utilised SMARTPLS, Tested CFA, Model Fit, Reliability and Validity, Path Modelling and hypothesis. Raosoft calculator was used to calculate sample size. Calculation considered population of approximately 350 STEs officially registered with Southern Africa Tourism Services Association (SATSA), a 5% margin of error, 90% confidence interval & recommended 50% distribution, and returned a minimum sample size of 184 respondents. Findings revealed transactions can be business to business applications (targeted to other firms, business to consumer applications (targeted to final customers, e.g. advertisements based on SMS/ MMS) e- catalogues on what the small tourism enterprise offers and networking regionally and at global level. Keywords: cloud computing, innovation, mobile technology, tourism enterprise, marketing strategy, business growth

Problems and Opportunities in the use of Bioelectrical Impedance Analysis for Assessing Body Composition During Ketogenic Diets: A Scoping Review.

The use of bioelectrical impedance analysis (BIA) for monitoring body composition during the ketogenic diet has experienced a rapid surge. This scoping review aimed to assess the validity of procedures applying BIA in the ketogenic diet and to suggest best practices for optimizing its utilization. We conducted a systematic scoping review of peer-reviewed literature involving BIA for assessing body composition in individuals adhering to a ketogenic diet. Searches of international databases yielded 1609 unique records, 72 of which met the inclusion criteria and were reviewed. Thirty-five studies used foot-to-hand technology, 34 used standing position technology, while 3 did not declare the technology used. Raw bioelectrical parameters were reported in 21 studies. A total of 196 body mass components were estimated, but predictive equations were reported in only four cases. Most research on BIA during ketogenic diets did not report the equations used for predicting body composition, making it impossible to assess the validity of BIA outputs. Furthermore, the exceedingly low percentage of studies reporting and analyzing raw data makes it challenging to replicate methodologies in future studies, highlighting that BIA is not being utilized to its full potential. There is a need for more precise technology and device characteristics descriptions, full report of raw bioelectrical data, and predictive equations utilized. Moreover, evaluating raw data through vectorial analysis is strongly recommended. Eventually, we suggest best practices to enhance BIA outcomes during ketogenic diets.

A Two-Stage co-Design Process of Battleship-AST Persuasive Game for Active School Transportation in Northern Sweden

This research delves into the dynamics of active school transport (AST) by utilizing a two-stage co-design process and leveraging persuasive technology within a game for promoting AST called Battleship-AST. The primary aim of this research is to thoroughly investigate the two-stage game co-design process employed in creating a Battleship-AST game. Moreover, our research aims to evaluate participants’ perceptions regarding the motivating and engaging potential of the persuasive technology and gamification features embedded within the final iteration of the game. This evaluation aims to understand how these features influence participants’ motivation to increase their usage of AST through gameplay. In pursuit of these objectives, the research builds upon the existing Battleship-AST prototype and actively engages school children in a collaborative two-stage co-design process. Their valuable insights and preferences were harnessed in refining the game, which was subsequently tested during a tech event in Skellefteå, Sweden. The findings shed light on various aspects of the game’s impact, from its reception to the gamification features integrated within. Notably, the research highlights the positive impact of the co-design process, with increased motivation and engagement observed among the participants. Their involvement in shaping the game’s design resulted in a more engaging and enjoyable experience. The persuasive technology features, encompassing competition, collaboration, auditory cues, a virtual reward system, and an emphasis on similarity, played a pivotal role in sustaining engagement and motivating players. Elements such as rewards, leaderboard progression, and badges proved highly effective in encouraging continued participation and fostering a positive feedback loop. However, the study also identifies areas for potential improvement, including the need to measure real-life progress and refine the game’s levelling system. The research indicates that refining feedback mechanisms and tailoring game content to individual preferences could create an even more engaging experience. Additionally, long-term playtesting is proposed to assess the game’s extended impact. The findings offer promising avenues for enhancing motivation and engagement in AST, which can contribute to the promotion of healthier and more sustainable transportation choices among school children.

Effects of Social Media on Branding ——The Rise of Creative Advertising Marketing

In the Web2.0 era, social media has developed into the most compelling area in the global media industry and brought online users a fresher experience and more creative network communication application models. Both its social impact and economic development have become the new engine and growth point of the media industry. More and more brands and companies put their advertising budgets on social media advertising, because social media advertising is not only affordable but also able to accurately target the consumer group. The Internet word of mouth formed by social media is reshaping the relationship between brands and consumers. At the same time, the way audiences receive and disseminate information has undergone tremendous changes, and advertising creative communication is also facing huge challenges. This article will analyze the development process and trends of social media from the perspective of its core technology and communication characteristics, and then explore the social-psychological impact and cultural value of social media brought to brand communication.

Research on emergency logistics information traceability model and resource optimization allocation strategies based on consortium blockchain.

In response to increasingly complex social emergencies, this study realizes the optimization of logistics information flow and resource allocation by constructing the Emergency logistics information Traceability model (ELITM-CBT) based on alliance blockchain technology. Using the decentralized, data immutable and transparent characteristics of alliance blockchain technology, this research breaks through the limitations of traditional emergency logistics models and improves the accuracy and efficiency of information management. Combined with the hybrid genetic simulated Annealing algorithm (HGASA), the improved model shows significant advantages in emergency logistics scenarios, especially in terms of total transportation time, total cost, and fairness of resource allocation. The simulation results verify the high efficiency of the model in terms of timeliness of emergency response and accuracy of resource allocation, and provide innovative theoretical support and practical scheme for the field of emergency logistics. Future research will explore more efficient consensus mechanisms, and combine big data and artificial intelligence technology to further improve the performance and adaptability of emergency logistics systems.

Creativity in a music composition community: an analysis of online comments

ABSTRACT Scholars have often highlighted the intrinsic features of technology to support the generation and sharing of ideas (Craft 2011). By studying user interactions within informal online communities, researcher can elucidate the ways technology impacts creativity and learning within these groups. This qualitative content analysis (Hsieh and Shannon 2005) used a systems-based approach to creativity (Csikszentmihalyi 1999) to examine the interactions within an online community (Noteflight) focused on Western standard music notation-based composition. One popular, publicly available, original musical score was selected. Online comments were collected and analysed. Findings highlight the diversity and abundance of feedback given to the composer as well as the many ways users engaged with domain knowledge. This online community allows individuals to share knowledge, learn about the social norms associated with giving feedback, and explore creative ideas regarding music composition. Implications from this study highlight the ways music educators and technology designers can develop web-based music learning environments that support creativity and life-long engagement.

Review on Semi Active Suspension System for Ride Comfort

This review article provides a thorough examination of the function and influence of semi active suspension systems in improving the level of comfort experienced during rides in the automobile sector. The paper explores the core concepts, types, and features of semi-active suspension technology, while also highlighting their differences and similarities with passive and fully active suspension systems. This study also examines the measures used to assess the level of comfort experienced during a ride, incorporating both objective and subjective factors. The research examines many components that impact ride comfort in semi-active suspensions, such as control algorithms, sensor technologies, and the effects of important vehicle and ambient variables. Moreover, it offers valuable information on performance assessment via both laboratory and field testing, as well as comparison studies with alternative systems. It also covers current improvements and the integration of the system with other vehicle systems. The study finishes by succinctly summarizing crucial ideas, emphasizing the importance of these technologies in augmenting both ride comfort and safety. Additionally, it solicits additional investigation and underscores the ramifications for the automobile sector, establishing the foundation for future progress and use in the realm of semi-active suspension systems.

On the Use of an Online Polling Platform for Enhancing Student Engagement in an Engineering Module

Students’ engagement is a fundamental challenge in large classrooms in higher education. In recent years, innovative technologies such as electronic learning and online polling platforms have made learning more engaging, effective, and interactive. By using these platforms, educators can create more inclusive and enriching learning environments. This paper presents a novel approach in which an online technology is employed to enhance students’ learning experience. In this approach, features of an online polling platform, i.e., Slido, are employed to enhance students’ engagement in an engineering module, i.e., ‘Mechanics of Solids’, which is recognised as a fundamentally challenging module with difficult subjects. This study investigates how the interactive features of such technologies, such as real-time polls, question and answer (Q&A) sessions, and quizzes, can provide a more active and practical learning environment by improving student engagement in the classroom. In total, six online polls were designed: one for ice-breaking, two on the topics of shear forces and bending moment, two on stresses, and one on deflection. Each poll was presented to the students, and they participated in them by scanning a QR code or typing the poll’s code online. The rate of students’ participation in polls is extensively discussed to show the effectiveness of the proposed method. The findings of this study show a significant increase in student participation in classroom activities compared to traditional methods. Student feedback also indicates a positive learning experience with the use of the proposed approach. It is shown that the proposed approach has the potential to transform the way engineering students engage with challenging subjects, leading to enhanced learning outcomes and a more positive learning experience.

A survey on social network’s anomalous behavior detection

AbstractThe onset of Web 3.0 has catalyzed the rapid advancement of social networking, transforming platforms into essential elements deeply embedded within the fabric of daily life. Researchers have proposed several methods for detecting anomalous behaviors in various scenarios. This article provides a comprehensive review of current research and the latest developments in anomalous behavior detection within social networks. We present a hierarchical three-layer categorization scheme based on the distinct characteristics of base-level detection technologies and various datasets. First, anomaly detection based on user behavioral characteristics can intuitively reflect deviations in individual behavior. However, it may overlook the overall network structure’s impact. Second, detecting anomalies within a network’s topological structure highlights structural significance, but may overlook the subtle nuances of individual behavior. Finally, the coordinated fusion method, which blends individual behavioral characteristics and the network’s topological structure, addresses the multifaceted nature of anomalies, yielding a more thorough and accurate anomaly detection strategy. This paper provides an overview and assesses the performance of three anomaly detection methods. Furthermore, we explore the challenges associated with social network anomaly detection and the potential pathways for further research.

(Why) Do We Trust AI?: A Case of AI-based Health Chatbots

Automated chatbots powered by artificial intelligence (AI) can act as a ubiquitous point of contact, improving access to healthcare and empowering users to make effective decisions. However, despite the potential benefits, emerging literature suggests that apprehensions linked to the distinctive features of AI technology and the specific context of use (healthcare) could undermine consumer trust and hinder widespread adoption. Although the role of trust is considered pivotal to the acceptance of healthcare technologies, a dearth of research exists that focuses on the contextual factors that drive trust in such AI-based Chatbots for Self-Diagnosis (AICSD). Accordingly, a contextual model based on the trust-in-technology framework was developed to understand the determinants of consumers’ trust in AICSD and its behavioral consequences. It was validated using a free simulation experiment study in India (N = 202). Perceived anthropomorphism, perceived information quality, perceived explainability, disposition to trust technology, and perceived service quality influence consumers’ trust in AICSD. In turn, trust, privacy risk, health risk, and gender determine the intention to use. The research contributes by developing and validating a context-specific model for explaining trust in AICSD that could aid developers and marketers in enhancing consumers’ trust in and adoption of AICSD.

Investigating the international corporate tax revenue efficiency under the digital economy: multiple case study of MNES operating in India

Purpose The purpose of this paper is to validate the theoretical finding that digital MNEs avoid physical presence norms of permanent establishment and royalty characterization rules for business and royalty taxation, respectively, to escape tax incidence in the market economy, using information, communication and technology features and transfer pricing (TP) manipulations. Design/methodology/approach Multiple case studies of MNEs from technology sector, based on judicial decisions in 141 cases, over taxability of profits earned from Indian economic activities. Additional in-depth case study of the Uber Group to study the tax avoidance structures under platform economy, by routing of Indian profits through The Netherlands, a tax haven. Findings The study finds a significant number of digital MNEs earning profits from India and avoiding tax by defying physical presence and royalty characterization. In majority of the cases, demand-side business activities are discharged through incorporating and remunerating affiliates at cost plus low markup, thus avoiding tax incidence, using TP manipulations under the arm’s length principle applied by governments for benchmarking the intragroup transactions of the MNEs. Research limitations/implications The research findings validate the view that digital features promote tax avoidance in the market economy. Originality/value The originality of the study lies in the validation of profit shifting through digital features from the developing market economy and portending that digital MNEs defy physical presence to avoid business taxation through TP manipulations.

A digital twin model of the axial temperature field of a DC cable for millisecond calculations

The most important features of digital twin technology for transmission and transformation equipment are symbiotic evolution and state prediction. In constructing the digital twin model for DC cables, the transient and steady-state temperature fields need to be considered comprehensively in the modeling process to consider the multi-physical field coupling, mathematical model, operational data, and environmental conditions in specific cases, which makes it difficult to satisfy the real-time requirements of the digital twin. To solve this problem, in this paper, a digital twin technology architecture for DC cables is proposed, and a neural network learning model is constructed to minimize the latency due to the complexity of the model simulation. Moreover, an efficient digital twin model that is based on the model-driven approach is developed for the fast computation of the axial temperature field of DC cables. The use of the Sequence-to-Sequence residual neural network algorithm for the reduced-order multi-physics field coupling modeling reduces the computational time and ensures as much accuracy as possible up to the finite element model simulation. The simulation results show that the use of the digital twin model reduces the simulation time from 275 s to 0.56 s, and the relative error between the accuracy of the digital twin model and the finite element model for the axial temperature field of the DC cable is 0.46 %. Finally, verification of the reasonableness and feasibility of the proposed method is carried out via an experimental platform according to the standard of CIGRE TB496. In particular, the maximum value of the DC cable temperature is verified to have a small error compared with the result of the Sequence-to-Sequence calculation under specific working conditions.

МЕТОД КОДУВАННЯ ВІДЕОДАНИХ В СПЕКТРАЛЬНО- ПАРАМЕТРИЧНОМУ ПРОСТОРІ

It is shown that the development of modern infocommunication systems is followed by the trend of widespread use of wireless technologies. The level of intellectualization of the protocols of their functioning is increasing. Accordingly, the characteristics of wireless infocommunication technologies for data transmission are increasing. This contributes to their use for data transmission from remote robotic platforms in the process of information support for the functioning of critical infrastructure. It is substantiated that the transmission of video data with the required level of bit intensity on the basis of existing on-board telecommunication technologies is organized under conditions of significant time delays. Consequently, the level of efficiency of information delivery is lost. On the other hand, there are losses in the reliability of video information. It is argued that the option for solving the problem lies in the further development of technologies for encoding video information streams. The most common platform is the JPEG format. However, the city has disadvantages. They refer to the loss of compression levels in the event of a reduction in the potential for detecting psychovisual addictions. The article substantiates an approach for improvement, which consists in the use of an adapted coding technology in the spectral-parametric space. This approach consists in detecting subbands in spectral arrays and their subsequent parameterization with the formation of structural components at a significant level and length. Further processing is proposed to be carried out taking into account the informativeness of segments and reducing the amount of structural redundancy. An approach for constructing a technology for compression of spectral arrays with the detection of spectral sub-bands is substantiated. A model has been created to find the amount of information for transformed segments in the spectral-parametric space. This takes into account the available amount of redundancy, which is established by determining the constraints on the values of structural components. A method for encoding segments in spectral-parametric description has been developed. The main basic components of the method relate to the processing of sets of two-component structural-parametric components, taking into account the peculiarities of their content depending on the presence of quantization processes.

General characteristics of technologies, innovations in intellectual property law

In this work, we consider technologies, innovations and intellectual property rights. In the context of modern development of all spheres of human life, the concepts of «technology», «innovation» and «innovative technologies» are an integral aspect of the present. They play an important and key role in the competitiveness of not only individual enterprises and organizations, but also in law and economics in general, since innovative technologies are the basis for the positive development of society and the legal relations that arise in this regard, including legal relations in the field of intellectual property rights. Intellectual property is the result of intellectual and creative activity, which is formalized and grants the author or a person who is granted the right of ownership of the result by law, which is acquired, exercised and protected in accordance with the established procedure, rules and legally defined norms. It is the objects of intellectual property rights that are in clear interaction with technology and innovation. Detailed attention is paid to the essence and content of innovations and technologies in the field of intellectual activity, in particular in the production and change of characteristics of the relevant objects of intellectual property rights. The author focuses on the conceptual apparatus of such concepts as «innovation», «technology», «intellectual property», «intellectual property rights», and technology transfer. The modern national and foreign literature is analyzed with a view to defining the basic concepts of the study and their legislative consolidation. The author analyzes the features of technology transfer, in particular, it is established that innovative technologies are endowed with novelty, revolutionary nature, irreplaceability, uniqueness, and inevitability. The author establishes the interconnectedness of the content of «innovations» and «technologies» in relation to intellectual property rights, namely, directly to intellectual property objects, which are manifested by applying know-how or an invention to a specific result of intellectual activity in the production process.

Feature of technology in therapeutic education of diabetes patient: 61 cases

Feature of technology in therapeutic education of diabetes patient: 61 cases

Neural Technologies for Objects Classification with Mobile Applications

This paper is related to the study of the features of the neural technologies’ application, in particular, ResNet neural networks for the classification of objects in photographs. The work aims to increase the accuracy of recognition and classification of objects in photographs by using various models of the ResNet neural network. The paper analyzes the features of the application of the corresponding models in comparison with other architectures of deep neural networks and evaluates their efficiency and accuracy in the classification of objects in photographs. The process of data formation for training neural networks, their processing and sorting is described. A web application and a mobile application for recognizing and classifying objects in a photo were also developed. A system for classifying objects, in particular airplanes in photographs, was developed using neural network technologies. It gives a recognition and classification accuracy of about 95%. Research results of ResNet models are of great practical importance, as they can improve the classification accuracy of various images. Features of ResNet, such as the use of skip connections or residual connections, make it effective in the relevant tasks. The results of the study will help to implement ResNet in various fields, including medicine, automatic pattern recognition and other areas where the classification of objects in photographs is an important task.

Digital contact tracing technology in the COVID-19 pandemic: a systematic review

Abstract Introduction The COVID-19 pandemic prompted public health teams across the world to emphasize case identification, contact tracing, and isolation in outbreak management strategies. Contact tracing was advanced by global access to mobile phones to develop and implement digital contact tracing (DCT) technology with the objective of increasing the rate of contact tracing while reducing the resources required. Purpose This study aimed to describe the DCT technology used during the COVID-19 pandemic across the world, and to identify differences and similarities between characteristics and uses. Methods This review followed the PRISMA (2020) guidelines for systematic reviews. Literature searches were conducted using Embase, MEDLINE, and PubMed and were restricted to English studies published between 2019 to 2023. Studies were excluded if they did not report findings for DCT during COVID-19, did not provide data for technology characteristics or outcomes, or were a study design listed for exclusion. Results Sixty one studies were included in the review producing results for 147 digital contact tracing technologies across 83 countries. The majority of digital contact tracing (DCT) technologies are government-owned (75.6%), primarily developed for COVID-19 tracing (96.4%). Bluetooth is the most favored technology (70%) used in their development, followed by GPS (30%) and QR codes (22%). Applications are the preferred platform (90.9%), with a few using applets (6.3%) and wearable devices (1.4%). Only 2 DCT technologies have achieved over 100 million downloads or uses (3.1%). Most DCTs fall into the 1–9.99 million downloads range (27.7%) and 10,000–99,999 downloads (20%). The majority of DCTs are voluntarily used by the population (63.6%), while 27.3% are mandated for use. Conclusions Digital contact tracing technologies were developed and implemented globally as a strategy in emergency outbreak management to reduce the spread of disease. This review describes the use of DCT across the world by identifying key features and characteristics that will serve as a lesson learned for improvement of existing DCT technologies for other emergency response outbreak management.

Farmland transfer contract performance and green production technology adoption among farmers: evidence from a survey of four provinces in China.

The popularization and use of green production technology is the key to promoting the sustainable development of agriculture. Exploring the path of promoting farmers' adoption of green production technology has important theoretical and practical significance for promoting the green transformation of agriculture and realizing the high-quality development of agriculture. This study examined the impact of contract performance on the adoption of green production technology in the farmland transfer market based on the characteristics of green production technology. An empirical test was conducted using survey data from Heilongjiang, Henan, Zhejiang, and Sichuan Provinces, which differ in agricultural resource endowment and economic development. The results demonstrated that farmland area was positively associated with the number of green production technologies adopted by farmers and use of straw returning, subsoiling, and soil testing for formula fertilization technology. Moreover, improving the performance rates of farmland transfer contracts strengthened the promotional effect of operation scale on green production technology adoption. Using either contract execution or dispute resolution rates to measure contract performance promoted the adoption of green production technology, particularly for large-scale farmers. Therefore, in the publicity and promotion of agricultural green production technology, the government should not only formulate differentiated promotion strategies and support policies based on resource endowment, but also focus on the construction of rural legal systems, which are helpful for building and maintaining a good farmland market order and performance environment, and create conditions for the durability and stability of technology adoption.