Mixed Strategy Research Articles

A domain adaptation framework for cross-modality SAR 3D reconstruction point clouds segmentation utilizing LiDAR data

Synthetic aperture radar (SAR) 3D point clouds reconstruction can eliminate the problems of layover in 2D SAR image projections, the recognition of the reconstructed point cloud can significantly enhance target identification and information extraction. Current SAR 3D point cloud segmentation methods, based on traditional machine learning clustering approaches, suffer from poor automation and accuracy. However, the absence of publicly labeled SAR datasets impedes the progress of deep learning-based SAR 3D point cloud segmentation methods. To tackle the aforementioned challenges, we introduce, for the first time, an alternative training approach for SAR 3D point cloud segmentation using LiDAR annotated data, which offers a more abundant sample pool, thus alleviating the lack of training sets. Nevertheless, a segmentation model trained on LiDAR point clouds exhibits a significant decline in performance when directly applied to SAR 3D reconstructed point clouds due to the cross-domain discrepancy. This research presents a pioneering domain adaptation 3D semantic segmentation framework to implement cross-modal learning for SAR point clouds. In our scheme, a simple yet effective technique is developed to achieve segmentation of SAR double-bounce scattering regions called SARDBS-Mix, which employs a mixing strategy, to capture the distinctive reflection characteristics of SAR data. Furthermore, we implement approaches including center alignment and normalization, local augmentation, and weighted cross entropy to mitigate LiDAR and SAR domain gap and class imbalances. The experimental results validate the feasibility and effectiveness of the proposed method for SAR 3D reconstructed point cloud segmentation.

Pengaruh Strategi Bauran Pemasaran Digital Terhadap Kinerja Pemasaran melalui Manajemen Hubungan Pelanggan di Objek Wisata Pantai Randusanga Indah Brebes

This study aims to determine the effect of digital marketing mix strategy on marketing performance through customer relationship management at Randusanga Indah Brebes Beach tourist attraction. Using quantitative and qualitative approaches, this research sample involved 203 respondents who were beach visitors who were taken using purposive sampling techniques. Data analysis was conducted using the Structural Equation Modeling (SEM) model with the AMOS program. The results showed that the digital marketing mix strategy had a significant effect on customer relationship management with a CR value of 11.252 (CR ≥1.96) and a probability value ≤ 0.05. However, the digital marketing mix strategy has no significant effect on marketing performance with a CR value of -,434 (CR ≥1.96) and a probability value of 0.664 (p ≤ 0.05). Similarly, customer relationship management also has no significant effect on marketing performance with a value of CR 1,261 (CR ≥1.96) and a probability value of 0.207 (p ≤ 0.05).

A novel importance measure considering multi-constraints for RAP optimization of 1-out-of-n subsystems with mixed redundancy strategy

Intelligent optimization algorithms are the mainstream approach to solving redundancy allocation problems (RAP) with challenging features. Since importance measures (IM) can identify critical components, the combination of IM-based local optimization and intelligent algorithms has wide applications in various optimization problems; however, it is less studied in RAP. Existing IMs also failed to address both the objective function and multiple constraints like cost and weight; this may result in an imprecise identification of critical subsystems for RAP optimization. This paper considers a RAP with a mixed strategy, i.e., active and standby strategies can be applied to a subsystem simultaneously. Two novel IMs are proposed based on a Lagrangian function: cost-centric RAP-based importance (CRI) and weight-centric RAP-based importance (WRI). CRI (WRI) reveals the comprehensive effect of cost (weight) consumption on the system reliability and other resources. A local optimization algorithm guided alternately by CRI and WRI is presented to adjust the redundancy level of subsystems; then, this algorithm is introduced into a genetic algorithm (GA) to determine the component types and redundancy level of all subsystems. Compared with other algorithms and previous studies, the superiority of the proposed hybrid GA is demonstrated via numerical experiments and a well-known benchmark example.

Prediction for Global Whipping Responses of a Large Cruise Ship Under Unprecedented Sea Conditions Using an LSTM-Based Encoder–Decoder Model

Abstract Global whipping responses contribute to a significant increase in vertical bending moments (VBM), making their accurate prediction crucial for ship safety. In this study, a long short-term memory (LSTM)-based encoder–decoder model is established to predict the whipping responses under varying sea states. The model is trained on a comprehensive dataset, which includes motion data and VBM history of a cruise ship under various sea conditions. This dataset is established via numerical simulation, ensuring a wide range of scenarios for the model to learn from. The efficacy of the LSTM encoder–decoder model in capturing global whipping responses is initially verified under a single sea condition case. This step confirms the model's ability to accurately predict vertical bending moments under known conditions. Subsequently, the model's performance under unprecedented sea conditions is examined. Given that the distribution of training data significantly influences the model's performance and the data from diverse sea conditions typically exhibit distinct data distribution, a mixed data training strategy is employed during the training process in this scenario. The results indicate that the LSTM encoder–decoder model effectively captures whipping responses. Furthermore, the mixed data training strategy significantly improves the model's prediction accuracy for global whipping responses under unprecedented sea conditions.

An improved intrusion detection method for IIoT using attention mechanisms, BiGRU, and Inception-CNN

In the field of Industrial Internet of Things (IIoT), existing intrusion detection models face challenges in three main areas: low accuracy in detecting attack traffic, feature redundancy when dealing with high-dimensional and complex attack traffic, making it difficult to capture critical information, and a tendency to favor learning common categories while neglecting rare categories when handling imbalanced data. To tackle these challenges, this study introduces an intrusion detection method that combines an attention mechanism, Bidirectional Gated Recurrent Units (BiGRU), and Inception Convolutional Neural Network (Inception-CNN) to enhance the model’s detection rate. Simultaneously, the method employs a mixed sampling strategy for data resampling to address the bias learning issue caused by data imbalance. Additionally, the method employs a hybrid sampling strategy for data resampling to address the bias learning issue caused by data imbalance. It also incorporates denoising techniques to handle potential dataset noise introduced by hybrid sampling. Furthermore, a feature selection method combining Pearson correlation coefficient and Random Forest is applied to eliminate feature redundancy, enhancing the model’s ability to capture crucial information from high-dimensional attack traffic. Experimental validation on internationally recognized datasets (Edge-IIoTset, CIC-IDS2017, and CIC IoT 2023) affirms the reliability of the proposed intrusion detection method. This approach underscores the significance of intrusion detection in the security of Industrial IoT and showcases its potential in addressing pertinent challenges in network security.

Investigations of magnetic and thermal expansion properties of two cobalt(II) metal-organic frameworks constructed by mixed bipyridyl-tetracarboxylate strategy

We report the syntheses, crystal structures, adsorption behavior, thermal expansion behavior, and magnetic properties of two cobalt(II) metal-organic frameworks (MOFs), {[Co(btca)1/2(bpe)(H2O)2]·bpe}n (1) and {Co(btca)1/2(bpe)(DMF)}n (2, H4btca = 1,2,4,5-benzenetetracarboxylic acid; bpe = 1,2-di(4-pyridyl)ethane), constructed using mixed bipyridyl and tetracarboxylate ligands. Single-crystal X-ray diffraction (SC-XRD) indicates that the change of synthetic solvents leads to a significant tuning of structural dimensionality from 2D to 3D framework. Temperature-dependent SC-XRD reveals anisotropically negative and positive thermal expansion of the compounds identified along different crystallographic axes within the frameworks over a 120–400 K temperature range. N2 adsorption measurements indicate a nonporous and ultramicroporous framework for 1 and 2, respectively. Magnetic measurements indicate an easy-plane magnetic anisotropy of the Co2+ ions in the MOFs, with experimental D values of 63.1 and 87.1 cm−1. The ac susceptibility measurements of 1 and 2 show field-induced slow magnetic relaxation below 6 K through different relaxation dynamics. This work not only provides two new cobalt(II) SIM-MOFs, but also presents an effective bipyridyl-tetracarboxylate strategy for designing and building framework materials with interesting magnetic and mechanical properties.

To what Extent is the Best Specific Marketing Strategy from Push, Pull, or Direct

This study investigates the effectiveness of three distinct fundraising strategies—push, pull, and direct marketing—in non-profit organizations, with a focus on entities based in Washington D.C. A literature review highlights the significance of these strategies, noting that push marketing is often favored for generating initial awareness, while direct marketing excels in targeted outreach, and pull marketing is beneficial for building long-term engagement. To empirically assess these methods, a survey was conducted with 25 non-profit organizations to examine the prevalence and success of each strategy. The chi-squared test revealed that push marketing, often combined with direct methods, was the most prevalent and effective approach among the organizations surveyed, aligning with previous research indicating its superior efficacy in fundraising. The findings suggest that nonprofits in Washington D.C. prefer a mixed strategy approach to maximize fundraising success. This study contributes to the understanding of fundraising tactics, demonstrating the importance of selecting and combining marketing strategies based on organizational goals and target audiences.

Techno-economic analysis of deploying a short or mixed energy storage strategy in a 100 % green power grid

A fully decarbonised electricity grid with extensively deployed renewable systems is a fundamental step in transitioning to a net-zero world. Unlike fossil energy, renewable energy systems are subject to meteorological intermittency. However, few studies have investigated the techno-economic performance of integrating short- and promising long-duration energy storage into a 100 % renewable energy grid to balance short-term and inter-seasonal demand.This research developed an economic model to investigate the techno-economic performance of standalone and combined energy storage solutions for a fully green grid in three defined scenarios. Lithium-ion batteries (Li-ion), hydrogen, and electrical thermal energy storage (ETES) were selected as promising storage technologies due to their maturity, commercial availability, and scalability. The three examined scenarios are: 1) Li-ion battery only, 2) Li-ion battery with ETES, and 3) Li-ion battery with hydrogen. The research aims to determine whether combining long-duration energy storage (e.g., ETES and hydrogen) with Li-ion batteries offers greater economic and technical benefits, resulting in a more affordable, resilient, and secure power supply.The results show that the Li-ion battery only scenario (Scenario 1) requires a capacity of 234,956 MWh. Adding ETES and hydrogen reduces this capacity to 53,304 MWh (Scenario 2) and 7020 MWh (Scenario 3). The addition of ETES and hydrogen improves power supply flexibility, increasing the proportion of generated electricity used to meet demand from 32.7 % in Scenario 1 to 41.2 % and 52.3 % in Scenarios 2 and 3, respectively. These technologies also help avoid electricity deficits, reduce the loss of power probability (LOPP), and lower the cost of electricity supply losses from $8365 million in Scenario 1 to $1793 million in Scenario 2 and only $4 million in Scenario 3. Power delivery costs decrease from $99.5/MWh in Scenario 1 to $77.6/MWh and $76.6/MWh in Scenarios 2 and 3, respectively. The research concludes with four policy recommendations to advance long-duration energy storage and transition to a fully green power supply system.

Strategi Bauran Pemasaran dalam Meningkatkan Penjualan Wedding Package di The Anvaya Beach Resort Bali

The sales target for wedding packages at The Anvaya Beach Resort Bali in 2020, 2021 and 2023 cannot be achieved. This research aims to identify a marketing mix strategy to increase sales of wedding packages at The Anvaya Beach Resort Bali. This research uses qualitative descriptive data analysis techniques which will be analyzed using SWOT analysis with the 7P marketing mix (Product, Price, Place, Promotion, People, Process and Physical Evidence). SWOT Matrix Analysis groups internal and external factors to produce four specific strategies, namely SO, ST, WO, and WT. In the research results, there are four marketing mix strategies in increasing sales of wedding packages at The Anvaya Beach Resort Bali, namely the SO (Strength Opportunities) strategy of having a wedding venue location which is a strategy to facilitate access in holding weddings, the ST (Strength Threats) strategy of utilizing the wedding venue by promoting The beauty of each wedding location that is owned, the WO (Weakness Opportunities) strategy improves weaknesses by utilizing the potential of social media which provides information about wedding packages to companies, and the WT (Weakness Threats) strategy maximizes ecommerce to expand the reach of the target market.

PENERAPAN STRATEGI MARKETING MIX PADA PERUSAHAAN FOREX STUDI KASUS : PT INTERNATIONAL BUSINESS FUTURE

Business development in Indonesia continues to increase, one of these businesses is the trading business on the foreign exchange market. The 7P marketing mix is a method to introduce the most effective forex business. PT International Business Future is a company that operates in the forex business sector. The purpose of this study is to determine the assessment and response of investors to the marketing mix at PT IBF. The research is descriptive qualitative with the research method used was a case study at PT IBF Bandung branch at Mohammad Rhamdan. The research used an interview system and distributed questionnaires. The Results show that the product and promotion variables show a very positive response from investors, which means these two variables have succeeded in becoming a good marketing mix strategy. Meanwhile, the lowest but still positive variables are in the place variable, especially the company image and in the people variable, sales professionalism in explaining the product. Variables that show a positive response can continue to be improved while the lowest variables can be made stronger changes or improvements. The results of the cross-tabulation show that respondents with higher education tend not to agree with the promotion, which means that PT IBF needs to provide a new marketing strategy.

Analisis Strategi Pemasaran untuk Meningkatkan Penjualan UMKM Ayam Geprek Melotot di Kota Jambi

Melotot Geprek Chicken Shop which is located at Jl. Sk Syahbudin, Ruko Puri Mayang, Mayang Mangurai, Jambi city. This Geprek Chicken Shop not only provides Geprek Chicken, but also provides toppings such as omelettes, liver gizzards, quail eggs, tofu-tempeh, perkedel, fried petai and others. The phenomenon or event that can be felt directly by researchers is, the Geprek Melotot Chicken Shop with a simple and not luxurious building design, ordinary service, and product sales that only use a word of mouth strategy, resulting in a lack of turnover as expected and what has been achieved. planned. So the aim of this research is to find out what marketing strategies are to increase sales, what obstacles are faced and what are the solutions in dealing with marketing strategies. The discussion of this research is related to the theory of increasing sales, MSMEs, Marketing Strategy, Halal Labeling, and Constraints in MSME Development. This research is a type of Qualitative research with a descriptive approach, using primary data sources and secondary data. The subjects of the research are Shop Owners and Consumers. Data collection techniques are observation, interviews and documentation. The results of this study indicate that the strategy implemented by Toko Ayam Geprek Melotot in increasing sales is by using the 9P marketing mix strategy (product, price, place, promotion, people, process, physical evidence, payment, packaging), namely product strategy, price, location, promotion, people, process, physical evidence, payment, and packaging.

A terbium coordination polymer based on mixed rigid and flexible organic ligands as a luminescent sensor for the convenient visual detection of ascorbic acid

Ascorbic acid (AA) is an essential antioxidant in the human body, whose detection is of significance in many fields. In this study, a two-dimensional terbium coordination polymer [Tb (dlba) (phen)]n (Tb-CP) based on a rigid 1,10-phenanthroline (phen) and a flexible 2-(3,5-dicarboxybenzyloxy) benzoic acid unit (H3dlba) was prepared under the hydrothermal conditions and characterized by Powder X-ray diffraction, elemental analysis, thermogravimetric analysis, infrared spectroscopy and single crystal X-ray diffraction. The Tb-CP synthesized via the mixed ligand strategy exhibits excellent water stability and acid-alkali resistance. As a luminescent sensor, the Tb-CP showed bright green luminescence characteristics of Tb3+, which was quenched after the addition of AA, with a quenching efficiency of 95.3 %. Additionally, the sensor shows high sensitivity and a rapid response time of 30 s. The detection limit is as low as 55.4 nM. In the actual sample test, the recovery rate of AA was 95–105 % (RSD< 1 %), indicating that the sensor has the potential for practical application. Furthermore, an integrated system based on Tb-CP and a smartphone can be employed for the visual detection of AA.

Examining the methods of converting the threats caused by sanctions on Iran’s petrochemical industry to economic opportunities and investigating the growth rate of Iran’s petrochemical industry during sanction

PurposeThis study aims to examine the methods of converting the threats caused by sanctions on Iran’s petrochemical industry to economic opportunities and investigating the growth rate of Iran’s petrochemical industry during sanctions.Design/methodology/approachThe present research was descriptive-exploratory and the research method was based on a mixed research strategy. In the qualitative part, two methods of content analysis and semistructured interview were used and in the quantitative part, the survey method was used. The participants of the qualitative part were the content of all related published researches that have been published in the past 20 years and to conduct a semistructured interview with experts that were selected by nonprobability sampling method. In the quantitative part, the statistical population, there were including managers, supervisors and experts active in the Iran’s petrochemical industry (especially in Asaluyeh area of Iran), the sampling method was nonprobability of the type available.FindingsThe findings of the research showed that the potential risks resulting from the sanctions on Iran’s petrochemical industry from the review of the selected researches include 5 main risks (marketing, financial, supply and procurement, technological and production) and 26 related subrisks. Also, the ranking of the mentioned risks showed that among the main risks, the highest rank is related to the financial risk and among the subrisks, the increase in transaction costs and disruption in the implementation of contractual obligations have the highest rank.Research limitations/implicationsThe investigation of the growth rate of Iran’s petrochemical industry during the sanctions in terms of performance (production, export and foreign exchange) showed that the amount of production has gone through a growing trend during the period under review (it has grown by more than 68%). Also, the amount of exports in the investigated time period has been growing (it has grown by more than 70%) and finally, the amount of foreign exchange in this time period has experienced growth (more than 58% growth).Originality/valueIntroducing and examining methods of turning threats into economic opportunities in Iran’s petrochemical industry under the shadow of sanctions, which can be used in other active industries under sanctions in the energy field.

Prey targeted by lactating Weddell seals (Leptonychotes weddellii) in Erebus Bay, Antarctica

AbstractFemale Weddell seals (Leptonychotes weddellii) display a mixed capital-income breeding strategy, losing up to 40% of their body mass between birthing and weaning their pups. How and when they regain energy stores, however, remains to be fully explored. To better understand the foraging by lactating Weddell seals, we fitted time-depth recorders and head-mounted cameras on 26 seals in Erebus Bay, Ross Sea, for ~ 5 days in November and December 2018 and 2019. We aimed to (1) identify prey species and foraging depth and (2) investigate relationships between seal physiology and demographics and probability of foraging. We recorded 2782 dives, 903 of which were &gt; 50 m, maximum depth was 449.3 m and maximum duration was 31.1 min. Pup age likely contributes to the probability of a lactating Weddell seal foraging (Est. = 1.21 (SD = 0.61), z = 1.97, p = 0.0484). Among 846 prey encounters, the most frequent prey items were crustaceans (46.2%) and Antarctic silverfish (Pleuragramma antarcticum, 19.0%); two encounters were observed with juvenile Antarctic toothfish (Dissostichus mawsoni, 0.2%). We identified substantial variability in foraging behaviour, individually and between locations, and found that lactating seals target many species and some may specialise on certain prey groups.

A novel evolutionary strategy optimization algorithm for reliability redundancy allocation problem with heterogeneous components

The reliability-redundancy allocation problem (RRAP) is an optimization problem that maximizes system reliability under some constraints. In most studies on the RRAP, either active redundant components or cold standby components are used in a subsystem. This paper presents a new model for the RRAP of a system with a mixed redundancy strategy, in which all components can be heterogeneous. This formulation leads to a more precise solution for the problem; however, RRAP is an np-hard problem, and the new mixed heterogeneous model will be more complicated to solve. After formulating the issue, a novel design of an evolutionary strategy optimization algorithm is proposed to solve that. The problem consists of discrete and continuous variables, and different mutation strategies are designed for each. The new formulation of the problem and the new method for solving it lead to better results than those reported in other recent papers. We implement the new suggested heterogeneous model with the PSO and SPSO algorithms to better compare the proposed algorithm. Results show improvement in both system reliability and fitness evaluation count.

Nickel-Based Metal-Organic Framework Materials with Mixed Ferrocene-Based Ligands As Anodic Catalysts for Water Electrolysis and Urea Electrolysis

Water electrolysis is a highly promising technology for hydrogen production, generating green hydrogen with no greenhouse gas emissions. The water electrolysis reaction involves two half-reactions: hydrogen evolution and oxygen evolution. While oxygen evolution in water electrolysis involves a four-electron transfer requiring higher overpotential and thus leading to energy consumption. Urea electrolysis offers lower theoretical energy consumption than water electrolysis, making them a key technology in future electrolytic hydrogen production processes. Conventional anodic catalysts, such as Ir and Ru, exhibit good performance in oxygen evolution, but being precious metals, they face limitations due to high cost and limited abundance. Its is crucial to find an active, durable and cost-effective anode catalyst for realistic application.Metal-organic framework (MOF) materials, due to their high porosity, large surface area, and unique structural features, have emerged as promising materials for water electrolysis. However, their relatively poor stability is a drawback that needs to be overcome. In herein, we design the mixed ligand strategy for synthesizing the MOF materials. Ferrocene-based ligands, ferrocenedicarboxylic acid (Fd), combing with terephthalic acid (H2BDC) as the mixed ligands for this study. The MOF catalysts, namely Ni-BDC and Ni-BDC-Fd, was synthesized using a simple one-step hydrothermal method with ferrocenedicarboxylic acid and terephthalic acid.Raman spectra revealed the presence of Fe-O, originating from the iron in Fd, demonstrating a structural transformation during the hydrothermal process. XRD analysis also confirmed the existence of FeO. The SEM images showed nanosheets and nanoneedles morphologies for Ni-BDC, while a dense nanofiber structure for Ni-BDC-Fd demonstrating the effect of 2nd ligand on the MOF structure.Electrochemical tests were conducted in 1 M KOH electrolyte and 1 M KOH + 0.5 M urea electrolyte, including oxygen evolution reaction (OER), urea oxidation reaction (UOR). The overall reaction comprising the same catalysts for the anode and the cathode side is performed to examine the real electrolysis performance.Results showed that the addition of Fd enhanced OER and UOR activity in alkaline and urea electrolytes. Ni-BDC-Fd achieved 1.483 V vs. RHE and 1.386 V vs. RHE at 65 mA/cm-2 driving potential for OER and UOR, respectively, requiring a smaller potential than Ni-BDC to achieve the same current density. To verify that the performance improvement was not solely due to iron, NiFe-BDC was synthesized by adding iron nitrate, showing inferior UOR performance compared to Ni-BDC-Fd but superior OER performance to NiFe-BDC. This indicated that the performance improvement resulted from structural changes rather than just the presence of iron atoms. Ni-BDC-Fd exhibited the lowest Tafel slope in OER, indicating a faster reaction rate due to the increased active surface area during OER. After continuous catalysis for 80 hours in the alkaline water electrolysis cell and urea electrolysis cell, a significant improvement in the loss of potential was observed.These results suggest that the addition of ferrocene dicarboxylic acid altered the structure of Ni-BDC, maintaining an appropriate interlayer distance. This not only enhanced its catalytic performance but also improved its catalytic stability, demonstrating a promising strategy for preparing metal-organic framework materials for electrocatalysis applications. Figure 1

Ethnic ecotourism: an alternative for the environmental sustainability of the Rancheria River delta, La Guajira

This study examined sustainable eco-ethno-tourism in the Ranchería River Delta Integrated Management District (DMI) as an environmental management tool to conserve and protect environmental and cultural aspects of the protected area. A mixed methodological strategy was implemented, combining documentary and descriptive research. On the other hand, the descriptive research involved unstructured interviews with experts to understand the conceptions and concepts related to the empowerment of eco-ethno-tourism for the sustainability of the Ranchería river delta, La Guajira. Aspects such as the characteristics of the Wayuu people, their social organization, ancestral history, governance, clans, myths, legends, customs, social fabric and fishing were addressed. The results obtained could serve as a tool for the management and planning of eco-etnotourism projects, thus strengthening conservation actions, sustainable use and management of mangroves and the adaptive capacity of coastal communities

Use of Nash equilibrium in finding game theoretic robust security bound on quantum bit error rate

Nash equilibrium is employed to find a game theoretic robust security bound on quantum bit error rate (QBER) for DL04 protocol which is a scheme for quantum secure direct communication that has been experimentally realized recently. The receiver, sender and eavesdropper (Eve) are considered to be quantum players (players having the capability to perform quantum operations). Specifically, Eve is considered to have the capability of performing quantum attacks (e.g., Wójcik’s original attack, Wójcik’s symmetrized attack and Pavičić attack) and classical intercept and resend attack. Game theoretic analysis of the security of DL04 protocol in the above scenario is performed by considering several game scenarios. The analysis revealed the absence of a Pareto optimal Nash equilibrium point within these game scenarios. Consequently, mixed strategy Nash equilibrium points are identified and employed to establish both upper and lower bounds for QBER. Further, the vulnerability of the DL04 protocol to Pavičić attack in the message mode is established. In addition, it is observed that the quantum attacks performed by Eve are more powerful than the classical attack, as the QBER value and the probability of detecting Eve’s presence are found to be lower in quantum attacks compared to classical ones.

Research on the effect of mixed teaching strategies on students' ambidextrous innovation

Mixed teaching strategies have caused a fierce debate about teaching quality in China's higher education. Based on theories of constructivism and self-regulation, we examine the impact of mixed teaching strategies on learners' ambidextrous innovation capacities. Utilizing a questionnaire survey of 412 undergraduate and graduate students from 36 Chinese higher education institutions, this research demonstrates that combining metacognitive strategies with motivational and collaborative approaches enhances exploratory innovation ability, while the pairing of metacognitive and collaborative strategies promotes exploitative innovation. Furthermore, the study identifies significant differences in the effectiveness of mixed teaching strategies based on students' self-efficacy and teaching acceptance levels. These findings highlight the importance of tailoring mixed teaching strategies to individual characteristics for optimal learning outcomes and fostering students' innovative potential. This research contributes to the discourse on effective teaching practices in Chinese higher education by proposing a mixed teaching strategies matrix informed by self-efficacy and teaching acceptance, offering valuable guidance for educators seeking to cultivate students' innovative abilities.

Multi-granular spatial-temporal synchronous graph convolutional network for robust action recognition

Graph Convolutional Networks (GCNs) have shown great potential in skeleton-based human action recognition. However, due to the diversity and complexity, modeling human actions as general graphs and capturing discriminative spatial–temporal motion patterns is challenging. Besides, the inevitable interference, especially occlusion, impairs the robustness of existing methods that depend on complete skeletons. To solve these problems, we propose a Multi-Granular Spatial-Temporal Synchronous Graph Convolutional Network (MSS-GCN). Firstly, we investigate three partition strategies: attribute, activity, and mixed partition strategy to optimize the weight-sharing mechanism of GCNs, which facilitates the novel Extended Adaptive Graph Convolution (EAGC) module. Secondly, we elaborate on a Multi-sliced Spatial–temporal Graph (MSTG) for multi-granular action modeling. Thirdly, we present a Synchronized Slice Encoder (Syn-STE) to simultaneously embed spatial and temporal action patterns. Then, we design Multi-granular Spatial–temporal Encoders (Multi-STE) with multi-branch Syn-STE to generate multi-granular context. The extensive experiments verified that MSS-GCN is more robust and outperforms benchmarks on NTU-RGB+D, NTU-RGB+D 120, and NW-UCLA datasets.