International Journal of Quantum Chemistry

As brain diseases become more prevalent, early assessment of brain function is increasingly vital. This study introduces a piano sight-reading data collection and processing system, along with a quantitative evaluation method for brain health based on spatiotemporal dimensions. The system demonstrated effective data storage and analysis, with speed and ability scores improving over time. At the highest difficulty (D), the right hand outperformed the left in both speed (7% advantage) and ability (8.6% higher score). Over time, Speed scores peaked at 90 for the left hand and 73 for the right, while ability scores reached 96 and 92, respectively. The method showed high sensitivity (92%) and specificity (90%), with positive and negative predictive values of 90.2% and 91.8%, confirming its reliability for detecting cognitive improvement and decline. These findings highlight the potential of musical training for early cognitive assessment and brain health promotion.

In recent years, in the process of creating modern material civilization, problems such as ecological environment imbalance and deterioration, resource and energy crisis, environmental pollution, and population expansion have emerged. With the development of social economy, in order to meet people's higher consumption needs, green marketing has gradually developed into a typical new concept marketing model in the era of people-oriented marketing. In order to achieve marketing success in fierce market competition, enterprises must adapt to new situations, keep up with the times in marketing concepts and methods, and apply new marketing methods in order to achieve sustainable development. Therefore, this article conducts corresponding research and analysis on e-commerce and traditional markets based on the ecological environment. The research in this article has laid a certain foundation for future research on e-commerce and traditional markets under the mechanism of ecological environment protection.

In the context of smart tourism, this paper delves into the intricate process of constructing tourism destination images. It examines how factors such as tourism demand and supply dynamics influence the formation and perception of these images. Using Xi'an as a case study, the research employs statistical methods including factor analysis, correlation analysis, and ANOVA to analyze data on tourism resources and tourist perceptions. The study identifies a pronounced imbalance in online service provision across different tourism sectors, with accommodations showing robust online presence while scenic spots lag behind. Additionally, the article validates a predictive model for destination selection in smart tourism, underscoring its efficacy. Despite these advancements, the study calls for deeper exploration into tourists' motivations and behaviors to refine image construction strategies further. This research contributes to a nuanced understanding of how smart tourism frameworks can enhance the systematic development and communication of tourism destination images.

In the actual production of smart home products, it is difficult to complete the matching design in specific stages. Therefore, the design workload at different stages will have a certain time gap. For the first time in this paper, user groups are divided into two categories, namely users, controllers, buyers and Experiencers. A new smart home system model is designed. Its innovation lies in the integrated system of Internet of things and smart home. Connect the home appliances to the network through the gateway, and communicate with mobile phones and computers. Through analyzing and comparing its characteristics, it is concluded that the controller is the most active response group of smart home products. The effectiveness of the protocol implementation is verified by writing corresponding simulation scenario scripts and general trace file processing scripts. The verification results show that the implementation of the protocol is effective. ZBR algorithm is the complementary advantage of the two routing algorithms.

Traditional libraries often suffer from outdated facilities and limited space, impacting learning comfort. This study proposes integrating 5G and mobile intelligent devices to enhance library learning spaces. Results show that the 5G network achieves high efficiency in data transmission, with 95% efficiency at a data volume of 1000 and 96% at a distance of 100 meters. The mobile device system also accurately monitors temperature and humidity, with less than 7% error compared to instruments. This method significantly shortens data transmission time and improves planning efficiency, offering a reliable solution for modernizing library environments.

The traditional evaluation mechanism of ideological education in universities faces many challenges. How to improve the quality of knowledge service work in the university and enhance instructors' skill level and effectiveness is the main problem facing the sustainable development of higher education in the new century. This article studies the innovation and expansion of the evaluation and management mechanism for university teachers based on the neural system in order to achieve effective scientific and systematic teaching methods. The experimental results show that the improvement rate of higher education academic performance under neural system learning is 75.12%, which is 17.34% higher than traditional Blended Open Learning(BOP) learning methods. Therefore, the improvement rate using the neural system learning is higher. This article targets different groups responsible for university-level teaching, thereby greatly improving the learning of college students.

Traditional probabilistic tide calculation methods often fall short in capturing the dynamic nature of these systems, leading to discrepancies between calculated and actual data. To address this, a dynamic probabilistic tide calculation model is proposed in this study, incorporating a wind farm probabilistic model enhanced by the CATTSTS model. This integration aims to optimize prediction accuracy by improving feature focusing and data fitting, thereby reducing prediction errors and providing more reliable data for power system adjustments and optimizations. Experimental results demonstrate that the model's predictions for wind speed series in multi-wind farm distribution networks closely match actual conditions, underscoring its practical applicability and reliability in real-world settings. Furthermore, the study highlights the impact of spatial and temporal correlations on model performance. This research contributes to advancing the management of renewable energy integration in power systems, offering insights for more informed decision-making and operational efficiency.

COVID-19 caused a global public disaster as well as an economic crisis, and other challenges. The fifth-generation network, or 5G, connects practically every machine, person, and thing on the planet. We can analyse the public's opinions and sentiments connected to COVID-19 from 5G user-generated content on social media, which will eventually aid in promoting health intervention strategies and designing successful projects based on public perceptions. The BERT language model is first used to preprocess data that has been obtained from Sina Weibo. Following that, the features of the preprocessed data are chosen using a class-wise information technique. Finally, a capsule network (CapsNet) approach is used to identify the 5G user perception and experience optimization. Dynamic routing algorithm is used for optimizing the capsule network. By comparing the suggested framework's performance with certain existing approaches, its effectiveness is evaluated. Simulation results show that the proposed method is more accurate than previous approaches at identifying 5G user experiences.

This article presents a proposal of a reconfigurable FIR filter capable of covering the most common wireless communication standards on software-defined radio applications. The filter was implemented using a low-cost field programmable gate array, Cyclone IV EP4CE22F17C6 model from Altera®. System design is presented together with simulation results. Validation is done for a 500 kHz base-band noisy signal. The synthesized design uses 5,259 logic elements of which 4,778 were used for combinational logic blocks and 513 for dedicated logic registers, which represents 22% of total used FPGA capacity. The maximum sampling frequency supported by the architecture is 23.24 MHz.

Orthogonal frequency division multiplexing (OFDM) expects the subcarriers to be orthogonal. However, the factors, such as residual carrier frequency, offset time variations due to Doppler shift or phase noise leads to a loss in the orthogonality between subcarriers and results in inter-carrier interference (ICI). Further developing the parallel cancellation (PC) scheme to mitigate the ICI of OFDM systems, the authors expand this OFDM symbol-based PC scheme into a space-time (ST) coded system. This simple space-time parallel cancellation (STPC) scheme is a technique that combines the useful properties of ST and PC schemes together. Computer simulations indicate that OFDM systems using the STPC scheme outperform the regular PC and ST systems in slow and fast frequency selective fading channels, specifically at a high signal-noise ratio (SNR). Furthermore, the error floor of the STPC-OFDM system is significantly lower than that of the regular ST systems without increasing computational load.

To connect agricultural wireless sensor networks (WSNs) to web services and applications, the agricultural WSNs/WoT gateway is empowered with local data management and network maintenance functions for downstream WSNs in addition to traditional upstream data collection. This work demonstrates a low-cost, highly scalable, rapidly deployable web of things (WoT) gateway with edge computing capabilities. First, an agricultural WSNs/WoT topology is architected, connecting a ZigBee WSNs to the Web for remote monitoring the local environmental and agronomical information, and simultaneously for managing the solar-powered WSNs for a prolonged lifespan according to the instant data scrawled from the cloud. Second, a WSNs/WoT gateway is designed with the hardware platform Raspberry Pi 3, which serves multiple needs for bidirectional information exchange and local WSNs management. Finally, experimentation demonstrates the proposed hardware platform and architecture can perform edge computing, and efficiently realize the up and down transmission and distribution of data stream.

Position accuracy at any point in time has been a thing of great concern around the globe. Solution has been provided through radio devices with location estimation capabilities. Results have shown that the available location estimation algorithm has recorded improvement in terms of location accuracy and reliability. However, improving location accuracy should be a continuous process as security of life, and properties ought to be given a high priority. For this reason, currently, many localization algorithms are available. This work investigated two localization algorithms that were formulated based on the principle of multiple linear regression, namely weighted multiple linear regression (WMLR) and improved weighted multiple linear regression (iWMLR) algorithms, in order to suggest a better terminal localization algorithm. Location accuracy, range of errors, and R2 scores are the basis on which the aforementioned algorithms are evaluated. Finally, localization algorithm with high location estimation accuracy is proposed.

A zone walking attack is to get all existing domain information from a secured DNS server. NSEC3 protocol was proposed to defend against zone walking attacks in a secured DNS server, although NSEC3 uses more CPU time. In this paper, the authors have proposed two novel solutions to defend against the zone walking attack by addressing the efficiency issue of secure DNS protocol. They have simulated the proposed solution and analyzed it with different scenarios of the secure DNS server and attackers. The result of the experiment shows that the proposed solution Low Profiling can be effective against zone walking attacks for up to certain server-side and client-side parameters. The work can help researchers to understand how a new approach in the DNSSEC server can defend against zone walking attacks.

Cooperative-intelligent transport systems (C-ITS) are a solution for the manifold challenges of traffic as well as a major competitive stepping stone for the European automotive and tele-communication industry. However, against the backdrop of far-reaching COVID-19 impacts, the management of such complex C-ITS megaprojects needs to be adapted. Insights from most recent research contributions on megaproject management and the unexpected have shown that fostering a common sense of action, intense and efficient communication, and a strong organizational culture can help C-ITS projects to cope with the unprecedented situation. The institutional role model has proven to be an effective implementation framework for employing such project management methods in the C-ITS context. By combining different strands of research in an analysis of the intersection between recent C-ITS findings and theory on megaproject management and the unexpected, this article contributes to a holistic understanding of the impact of COVID-19 on C-ITS.

Multipath transmission control protocol (MPTCP) has been proposed for devices with multiple network interfaces. This idea seems to be impossible for user implementation at the beginning of its proposal. However, the emergence of smartphones with multiple network access allows this idea to be implemented. This paper provides both theoretical and empirical throughput analysis of MPTCP under long term evolution (LTE) and Wi-Fi networks. First, a new modified congestion control is presented as an enhancement of standard TCP Reno using logarithmic function. Second, the existing MPTCP approaches like linked increase algorithm (LIA) and balanced LIA (BALIA) are discussed briefly. Finally, the experimental results under long term evolution (LTE) and Wi-Fi under software defined wireless networking (SDWN) are given along with the analysis. The experimental result shows that the proposed congestion control achieves higher average congestion window size. The BALIA MPTCP is shown to have higher throughput than that of the LIA MPTCP.