The necessity of green construction technologies is currently a fundamental requirement in India. Although not a novel technology, an examination of Indian statistics reveals a limited number of green-rated projects or buildings. A fundamental benefit of any green building is the reduction in electricity usage, reliance on underground water resources, and the need for air conditioning. The occupants of green buildings experience a noticeable disparity in comfort and energy conservation compared to conventional structures. Within this academic study, the analysis of a residential projects in Bhopal named Sagar Green Hills (SGH), Sage Golden Spring (SGS), Sage Milestone, Sage Suncity and Prime Square, Indore is presented, assessed against the 34 criteria of Green Rating for Integrated Habitat Assessment (GRIHA), emphasizing key findings on achieving a minimum 1-star evaluation. This investigation aims to inspire developers in Tier II cities like Bhopal and Indore to undertake green residential projects and encourage potential residents, or clients, to choose environmentally-friendly initiatives. The evaluation of the project follows the GRIHA guidelines, outlining essential actions required to fulfill mandatory criteria.

Mobile Adhoc Networks (MANETs) have emerged as a popular technology because of their wide application and independent mobility. Nevertheless, communication through MANETs can be effective because of their inherent nature of high mobility, which in turn results in a higher rate of data loss and delay. Therefore, for effective communication to be achieved, the MANETs’ routing performance must be enhanced. Some extant routing protocols like AOMDV can yield moderate Routing Overhead (RO) during communication. The review of previous studies shows that there is a need for improvement in the following areas: Computational E2E delay: the proposed Genetic Algorithm- Ant Colony Optimization (GA-ACO) was unable to reduce the computational E2E delay that occurs during communication. RO: The schemes that were proposed failed to minimize the RO in the network. Energy consumption: the reduction energy consumed by the network was reduced, however, high throughput and PDR could not be achieved by the method. On the contrary, the EHO-based AOMDV routing protocol achieved low E2E delay and RO but was unable to decrease the energy consumed by the network. Throughput and PDR: The protocol proposed failed to achieve high Quality of Services (QoS). Consequently, this paper aims to provide a solution to this communication problem by proposing a Hybrid Optimization-based Effective Path Selection and Multipath routing (HOEPSM) approach for MANETs. The proposed approach, which is HOEPSM is made up of two parts: Elephant Herding Optimization (EHO)-based AOMDV routing protocol, which makes use of EHO for the identification of the shortest path from the source to the destination. The second part which is the Hybrid optimization using Genetic Ant Optimization (GAO) algorithm, involves finding the best solution through the use of a GAO-based hybrid optimization algorithm. The results of the study revealed that the use of the HOEPSM causes a significant decrease in routing RO while enhancing the network’s Quality of Forwarding (QoF) of the network. Also, the simulation of the proposed approach was carried out in NS2, and afterward, compared with earlier proposed methods like DRARP and MDRARP. Based on the simulation results, the HOEPSM outperformed the other methods, with high Energy Efficiency (EE) (91%), Packet Delivery Ratio (PDR) (95%), RO (155), and End to End (E2E delay) (102ms). These results can be attributed to the HOEPSM’s choice of the best and steady route from the source nodes and destination nodes.

The acceptance of technology at the higher educational level has been a significant discussion, with little attention on the gender dynamics on the acceptance of artificial intelligence (AI ) tools by senior lecturers. This study delved into a detailed analysis of the gender dynamics in the discussion of technology acceptance mainly AI tools, in foreign language (FL) education. Quantitative study approach was adopted in the process, and survey design was implemented. Data was collected using structured digital questionnaire, based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. A total of ninety-five (95) male senior lecturers and one hundred and three (103) female senior lecturers participated in the study. Analysis was conducted using relevant statistical measures. The results showed disparities in the attitudes and views of senior lecturers towards artificial intelligence (AI) technologies in the context of FL education, greatly influenced by gender. In relation to usage, male senior lecturers have higher positive reactions (61.06%) in comparison to their female counterparts (46.6%). However, in relation to the assumption that AI technologies improve the performance of learners, 69% of male senior lecturers agree with this notion, but a substantially greater percentage of 72.81% of female senior lecturers hold the same perspective. Moreover, there exists a little disparity in the level of proficiency in using AI technologies across genders. Specifically, 56.84% of male senior lecturers see it as uncomplicated, while 61.16% of their female counterparts share the same sentiment. The gender discrepancy that is most notable pertains to the perceived level of ease in using artificial intelligence (AI) technologies during foreign language (FL) lessons. The data reveals that a majority of male senior lecturers, calculated as 69.48%, see the use of these tools very easy. In contrast, a much higher proportion of female senior lecturers, 86.41%, share the same perception. This discrepancy highlights a notable disparity in confidence levels between the two genders. These results together emphasise the changing gender dynamics in the acceptance of technology, interrogating conventional assumptions and underscoring the need for customised support systems to guarantee fair and efficient integration of artificial intelligence (AI) technologies in foreign language instruction among senior lecturers.

Helping college students to establish the concept of employment in line with the socialist core values is of great significance for cultivating high-quality employment talents and conveying excellent main force for the construction of socialism with Chinese characteristics. This paper puts forward the integration path of college students’ employment education and ideological education based on the idea of “goal-system-variable”. It also designs a questionnaire based on the influence mechanism of integrated education on college students’ employability to investigate the implementation effect of the integrated education path. The reliability test of the questionnaire is completed by Cronbach’s α and retest reliability method, and the validity test of the questionnaire is realized by using KMO test and Bartlett’s globular test method. It was found that 194 students strongly agreed with the question “The implementation of the integrated education pathway in schools is very effective”, which indicates that the implementation of the pathway in this paper has achieved good results. Most of the students think that after integrated education, they have improved their self-management ability and are able to make reasonable employment plans, which greatly helps to improve their employability. At the same time, the analysis found that the students’ view of big employment has changed significantly, and the score of the students’ view of employment goal planning after the implementation of the path reaches 4.51 points. The integration education path designed in this paper provides an effective reference for colleges and universities to improve the employment ability of college students.

With the continuous expansion of enrollment, the overall level of students in various types of colleges and universities is mixed, which brings unprecedented difficulty to the teaching of linear algebra courses, and the hierarchical teaching of linear algebra courses is imperative. In this paper, in the teaching practice of university linear algebra, the mathematical statements provided by matlab software are used to draw graphs in the linear algebra class to help students effectively understand and master the concepts, definitions, theorems and corollaries that are more difficult and abstract in the teaching of university mathematics. And through the experimental layered design, the linear algebra course is divided into four modes: student layered, teaching layered, tutoring layered and assessment layered. The results show that after the implementation of tiered teaching, the passing rate of linear algebra of students increased by 16.7936 percentage points and the good rate increased by 21.1439 percentage points. Meanwhile, applying matlab to the visualization teaching of linear algebra can improve classroom efficiency, promote students’ understanding of concepts, and cultivate students’ mathematical literacy and information technology literacy.

The traditional media industry is facing a turnaround and challenges, and at the same time there are many opportunities for development in the new era, which will have many impacts on the mainstream media, and the innovation of mainstream media is imminent. The SECI model is the communication model of mainstream media, and its view on the continuous transformation of mainstream media is consistent with the transformation of mainstream media. This paper tries to combine the theoretical framework of SECI model with the existing communication strategy of mainstream media, to find the theoretical support of communication, to find the key link of mainstream media communication, and to propose new communication strategy of mainstream media, hoping that after the discussion of this paper, it can help the practitioners to do their work better.

The construction of civil service legal system is an important element of civil service management, and strengthening the onstruction of civil service legal system is an objective requirement for maintaining the advanced nature of the Party is a practical need to consolidate the party’s ruling base, is the problem of style itself stubborn and recurring requirements. It is the key to cope with the complex international competition and build a moderately prosperous society. In the new era, China,s civil service legal system construction mainly takes measures in three aspects: First, strengthen the ideological education and lay a firm ideological foundation for the construction of the civil service legal system. The second is to improve the institutional mechanism to ensure the standard operation of the civil service legal construction of the fundamental; third is to strengthen supervision and inspection to ensure that the civil service legal construction of the key to achieve effective results. Based on this, this paper considers the strategies and directions of the legal construction of civil service based on data fusion under the perspective of administrative law, and combines case studies to demonstrate the effectiveness and superiority of the proposed scheme.

A teaching platform community for innovation, entrepreneurship, and moral education is being developed in colleges and universities against the backdrop of a multimedia network. This platform will aid in the formation of a multi-subject collaborative education mechanism and the joint cultivation of innovative and entrepreneurial talents, thereby promoting the high-quality development of innovation and entrepreneurship education in colleges and universities. Given the widespread use of neural networks, we address the utility of this technology in cross-modal multimedia retrieval from the following three perspectives using a depth-limited Boltzmann machine pre-trained sparse neural network model. The integration of moral education into the teaching platform allows for the realisation of quantitative and qualitative evaluation from theory to practise. Experiments demonstrate that our model can perform significantly better than a single model’s baseline performance.

Early administrative jurisprudence generally experienced a shift from administrative science to legal science, while modern administrative jurisprudence has shifted from judicial review to administrative process centered. In this paper, we introduce feature engineering technology into the construction model of administrative law based on data mining. The prior knowledge is introduced into the model through the artificially constructed effective features, and the neural network method can automatically extract features such as abstract features from the original input text. We propose a deep feature engineering method to combine the advantages of both in the study of relation extraction tasks. Experiments show that our method provides a powerful legal analysis tool, which helps to innovate the conceptual framework and theoretical system of traditional administrative law and establish a modern administrative law system that can explain the real-world administrative process.