Process Strategies Research Articles

Contextual analysis to find implementation strategies for an interprofessional process to improve medication safety in primary care – the P3S study

Contextual analysis to find implementation strategies for an interprofessional process to improve medication safety in primary care – the P3S study

Online Topological Mapping on a Quadcopter with Fast Growing Neural Gas

This paper presents an online topological mapping method on a quadcopter with fast-growing neural gas. Recently, perceiving the real world in 3D space has become increasingly important, and robotics is no exception. Quadcopters are the most common type of robot working in 3D space. The ability to perceive 3D space is even required in order to enable real-time autonomous control. Dense maps are simply unpractical, while sparse maps are not suitable due to a lack of appropriate information. Topological maps then offer a balance between computational cost and accuracy. One of the most well-known unsupervised learning methods for topological mapping is growing neural gas (GNG). Unfortunately, it is difficult to increase the learning speed due to the traditional iterative method. Consequently, we propose a new method for topological mapping, called simplified multi-scale batch-learning GNG, by applying a mini-batch strategy in the learning process. The proposed method has been implemented on a quadcopter for indoor mapping applications. In addition, the topological maps are also combined with the tracking data of the quadcopter to generate a new global map. The combination is simple yet robust, based on rotation and translation strategies. Thus, the quadcopter is able to run the algorithms in real-time and maintain its performance above 30 fps.

Marketing Strategy for Savings Fund Collection Products at PT. BPRS Lantabur Tebuireng Gresik Branch

This study aims to identify the marketing strategies used by BPRS Lantabur Tebuireng, Gresik Branch in promoting savings fund collection products, and to understand the role of these strategies in the marketing process of these products. This research uses a qualitative methodology that applies a descriptive approach, where the research findings are presented in depth in narrative form to facilitate understanding. For data collection, researchers utilize various techniques, including observation, documentation, and interviews. The informants of this study consisted of funding officer staff of BPRS Lantabur Tebuireng, Gresik Branch and savings customers at the branch. The problem experienced by BPRS Lantabur Tebuireng, Gresik Branch is what marketing strategy is used by BPRS Lantabur Tebuireng, Gresik Branch in marketing Savings Fund Collection Products. The first finding shows the ball pick-up strategy used by BPRS Lantabur Tebuireng, Gresik Branch. The second finding shows what obstacles occur during the implementation of the ball pick-up strategy. The third finding shows which Savings products are most in demand by customers. According to the results of the discussion, the outreach strategy has proven successful in marketing savings products.

Utilizing multiple intelligences as a means to improving claim performance outcomes in project-based organizations

PurposeProject claim performance is often poor with negative consequences for project-based organizations (PBOs). Conflict and emotion are reported to impact organizational claim performance outcomes, yet remains unexplored. This study investigates the multiple intelligence (MI) context from the viewpoint of the claim management office (CMO), with the intent of identifying pathways to improving the emotion-based claim performance of PBOs.Design/methodology/approachThe study utilizes an autoethnographic case study involving a PBO-based general contractor (GC). Multiple intelligence theory (MIT) is applied as the theoretical lens. Method of framework analysis is used in analyzing the data, with reference to claim management office (RFCMO) theory as a main source in making “analytic generalization”.FindingsMultifaceted complexities of MIs are identified, including ambidexterity, actions and relations, stress and conflict, cultural differences and universals, meta-strategic thinking and team diversity. The holistic emotion-based strategies model identifies how PBOs can improve claim performance, specifically by adopting theories confection remedy and controlling emotion outcomes strategies in a closed-loop process. Further, the coherent emotions governance (CEG) framework enables CMOs' to upgrade maturity levels, by integrating the strategies, general and specific measures for improving emotion-based organizational claim performance.Originality/valueThis is a pioneering study in unveiling the complexities of organizational emotions engagement and the application of confection remedy, specifically in a project management context. The antecedents of RFCMO theory are here enriched with MIT and the pool of the supporting people-centered theories, augmented by an autoethnographic case study, in which the linkage between emotion and conflict complexity is laid bare. Further, this study identifies how conflicts in construction industry can be mitigated by way of a discrete three-category theories confection remedy.

The Principal's Strategy in Implementing the Value of Religious Moderation in the Pancasila Student Profile Strengthening Project

The issue of intolerance and radicalism among students must be taken seriously by school principals, who play a crucial role in managing the learning process, including in the P5 program. This research analyses the principal’s strategy in implementing the value of religious moderation in P5 and its implications for student character and school culture. This study is a qualitative research project using a case study method. Data collection methods included interviews, observations, and documentation, and the data were analyzed through reduction, presentation, and conclusion. Data verification was achieved through triangulation of sources and methods. The research results show that the principal's strategy for implementing the value of religious moderation in P5 involves three main approaches: process, program, and culture strategies. The process strategy includes planning, implementation, evaluation, and follow-up. The program strategy encompasses structuring P5 activities based on teamwork and partnerships with external parties. Meanwhile, the cultural strategy utilizes habituation activities to support the values and meaning of moderation within P5. The strategy implemented has had implications for student character, fostering awareness, tolerance, care, love for the country, and teamwork. Additionally, they have promoted a disciplined and collaborative school culture.

Rumor detection model with weighted GraphSAGE focusing on node location

While social media platforms promote people’s information exchange and dissemination, they also make rumors spread rapidly on online platforms. Therefore, how to detect rumors quickly, timely and accurately has become a hot topic for scholars in related fields. Traditional deep learning models ignore the relationship and topology between nodes in the rumor detection task and use fixed weights or mean aggregation strategies in the feature aggregation process, which fail to capture the complex interactions between nodes and the dynamics of information propagation, limiting the accuracy and robustness of the rumor detection model. To address these problems, we propose a location-aware weighted GraphSAGE rumor detection model GSMA. We first introduce an attention mechanism that dynamically assigns different attention weights to different neighboring nodes for different degrees of aggregation, improving GraphSAGE’s strategy of using mean-value aggregation for all neighboring nodes during the aggregation process; second, we introduce a modulated position encoding into the model and encode the position information of nodes into the features to improve the model’s ability to perceive the relative position and order of nodes; finally, the post text sentiment is incorporated into the features to provide additional semantic information for the model as a way to achieve rumor detection in microblogging platforms. Experiments show that the accuracy of the GSMA model on Ma-Weibo and Weibo23 reaches 97.43% and 97.55%, which is an improvement of 1.11% and 0.77% compared to the benchmark GraphSAGE, and all the evaluation metrics are also improved compared to other optimal rumor detection models.

An improved face attributes editing method based on DDIM

The main advantage of DDIM is that it guarantees the quality of the generated images while increasing the efficiency of the generation by modifying the sampling strategy in the diffusion process. DiffusionRig, which addresses the problem of maintaining identity consistency by learning the person-specific facial prior in a tiny personalized dataset, is a successful representation of the DDIM strategy. Based on DiffusionRig, in this article, we propose an improved face attributes editing method based on DDIM to improve naturalness and accuracy of editing results in complex face attribute editing tasks and the generalization ability. Our method combines DDIM and DECA together and use two-stage training strategy. To reduce DiffusionRig’s limitations in handling face attribute editing tasks that require nonlinear understanding and fine-tuning, our method also introduces a channel attention mechanism and a depth-separable convolution technique in the training model. In the first stage we trained our model on the open FFHQ dataset, which consists of 30,000 high-resolution face image. In the second stage, the model was refined by using a tiny personalized dataset. Face attribute editing experiments,comparative experiment with DiffusionRig, and a series of ablation experiments have been performed. Then, the validity of our improved method is verified by qualitative and quantitative analysis.

Synthesis of SrTiO3 nanoparticles for photocatalytic applications

Due to the heightened emphasis on environmental protection and the escalating demand for renewable energy sources, the potential applications of strontium titanate (SrTiO3) nanoparticles in photocatalysis have shown remarkable promise. With rapid advancements in technological capabilities, the standards for SrTiO3 photocatalytic materials have soared. Researchers have relentlessly delved into and innovated techniques for preparing strontium titanate powders, striving to yield nanocrystalline SrTiO3 that exhibits specific morphologies, high purity, superior dispersibility, and exceptional photocatalytic efficiency, while continually refining the properties of these powders. The paper encapsulates the advancements in preparation methodologies and photocatalytic attributes of perovskite SrTiO3 nanoparticles, encompassing diverse synthetic routes such as hydrothermal synthesis, sol-gel process, chemical precipitation, solid-state reaction, sonochemical technique, and composite modification strategies. The characteristics, merits, demerits, and prevailing challenges associated with each synthesis technique are thoroughly and analyzed. Ultimately, this review serves as a valuable reference and foundation for the synthesis, modification, and application of SrTiO3 nanoparticle photocatalysts, fostering their development and practical implementation in environmental remediation and renewable energy technologies.

Information Propagation in Hypergraph-Based Social Networks.

Social networks, functioning as core platforms for modern information dissemination, manifest distinctive user clustering behaviors and state transition mechanisms, thereby presenting new challenges to traditional information propagation models. Based on hypergraph theory, this paper augments the traditional SEIR model by introducing a novel hypernetwork information dissemination SSEIR model specifically designed for online social networks. This model accurately represents complex, multi-user, high-order interactions. It transforms the traditional single susceptible state (S) into active (Sa) and inactive (Si) states. Additionally, it enhances traditional information dissemination mechanisms through reaction process strategies (RP strategies) and formulates refined differential dynamical equations, effectively simulating the dissemination and diffusion processes in online social networks. Employing mean field theory, this paper conducts a comprehensive theoretical derivation of the dissemination mechanisms within the SSEIR model. The effectiveness of the model in various network structures was verified through simulation experiments, and its practicality was further validated by its application on real network datasets. The results show that the SSEIR model excels in data fitting and illustrating the internal mechanisms of information dissemination within hypernetwork structures, further clarifying the dynamic evolutionary patterns of information dissemination in online social hypernetworks. This study not only enriches the theoretical framework of information dissemination but also provides a scientific theoretical foundation for practical applications such as news dissemination, public opinion management, and rumor monitoring in online social networks.

Raw Material Management Strategy in The Production Process of Tos-Tos Tortilla Chips (Case Study at PT Dua Kelinci)

PT Dua Kelinci is a company based in Pati that operates in the food industry. The purpose of this study is to analyze the raw material management strategy in the production process within PT Dua Kelinci’s Tos-tos Tortilla Chips division. The focus of this study is the role of the production supervisor in managing raw materials and ensuring efficient processes. This study employed a qualitative descriptive method, utilizing primary data collected through interviews. The data was then analyzed through data reduction, data presentation, and conclusion drawing. The findings of the study indicate that PT Dua Kelinci implements its raw material management strategy by (1) following a production process in accordance with work guidelines that outline monthly food orders, (2) recording input and output materials for accurate tracking, and (3) sourcing materials based on the quantity and variety of food orders, ensuring timely procurement of required flavors. This approach ensures a smooth production process, helps maintain product quality, and fulfills customer demands. Efficient management of raw materials not only reduces the likelihood of production delays but also ensures operational stability and cost control. The study concludes that strategic raw material management is essential for sustaining production efficiency and product quality at PT Dua Kelinci.

Analisis Pengaruh Manajemen Operasi Dalam Perusahaan

Operational management is part of the work process, implementation, organization, or overall management in an organization or company. Our country has experienced difficulties since the implementation of PSBB. This also has an impact on the economy in Indonesia. Every company will compete to be at the forefront to meet consumer needs in the market in order to survive in the midst of competition. The type of research conducted in the discussion of this article is by using literature studies or literature reviews, The data sources used in this study are secondary data which are types of data that come from documents or other secondary sources Several supporting aspects for the company, Project Management, Process Strategy, Quality Management, Forecasting Management, and Strategic Location.

Dynamic Simulation and Optimization for Load Regulation Strategies of the Green Ammonia Synthesis Process

Dynamic Simulation and Optimization for Load Regulation Strategies of the Green Ammonia Synthesis Process

Subcritical water hydrolysis of soybean hulls pretreated by steam explosion: High pressure integrated process strategy

Steam explosion (SE) pretreatment and sequentially subcritical water hydrolysis (SWH) was studied. Industrially, there is an advantage in using this process strategy, since it uses the same equipment and instrumentation, without the need to transport the raw material in separate stages. The influence of severity factors (SF) (2.75, 3.05, and 3.35) and solvent used (distilled water and 0.5 % w/w of H2SO4) were evaluated in the SE efficiency. SWH was perform in integrated processing using the best pre-treatment conditions. The influence of temperature (230 and 260 °C) and the solvent/feed ratio (40 and 80) were considered. The integrated system resulted in a FS yield of 19.19 ± 0.49 g/ 100 g SH, for a condition Integrated 230 °C, S/F-40, a FS yield 3.3 times greater than that obtained in the same condition with untreated soybean hulls, demonstrating the advantage of perform the process under this operating strategy (SE + SWH)

Ideologies Underlying Chinese-English News Translation Strategies: A Critical Discourse Analysis of An Example from China Daily

With the aim of revealing the interplay between ideologies and translation strategies in the English translation process of Chinese political discourses, this research delves into the critical discourse analysis (CDA) of the English translation of the 2024 New Year Message by Chinese President Xi in China Daily. By examining the translation strategies like domestication, foreignization, addition, literal translation, and free translation, the study uncovers that these translation strategies are adopted in order to portray China as a nation developing with promising prospects. The primary research findings reveal how these strategies align with key ideologies including modernization and progress, stability and long-term planning, China’s global role and commitment to cooperation, cultural heritage and national pride, and people-centered development. Through the critical analysis of how these strategies reflect and reinforce these ideological narratives in shaping the international perceptions of the status quo and future direction of China’s growth, this research provides insights into the complex relations between translation choices and ideologies.

Beyond viability: Advancing CHO cell culture process strategies to modulate host cell protein levels

Chinese Hamster Ovary (CHO) cells are widely utilized in bioprocessing industry for monoclonal antibody (mAb) production. In many instances, challenges persist in achieving sufficient clearance of Host Cell Proteins (HCPs) in the final drug substance. While purification strategies usually offer substantial HCP clearance, certain "problematic" HCPs, particularly lipases, continue to pose significant challenges. This study investigates the accumulation of various "problematic" HCPs in CHO cell culture using transcriptomics, revealing correations between cell culture parameters and HCP level. Contrary to conventional assumptions, viability alone does not reliably predict HCP levels, with factors such as clone selection, host cell line choice, media and feed compositions significantly influencing HCP accumulation. Leveraging transcriptomics-based approaches, we demonstrate the potential of upstream process control strategies to mitigate HCP presence and improve biologic product quality. Our findings underscore the importance of considering diverse cell culture parameters in bioprocess optimization to ensure product stability and quality. While promising, further research is needed to elucidate the mechanisms underlying HCP release and propagation through downstream processing stages, emphasizing the necessity of a comprehensive integrated approach to HCP control in biologics production.

Density‐Aware Diffusion Model for Efficient Image Dehazing

AbstractExisting image dehazing methods have made remarkable progress. However, they generally perform poorly on images with dense haze, and often suffer from unsatisfactory results with detail degradation or color distortion. In this paper, we propose a density‐aware diffusion model (DADM) for image dehazing. Guided by the haze density, our DADM can handle images with dense haze and complex environments. Specifically, we introduce a density‐aware dehazing network (DADNet) in the reverse diffusion process, which can help DADM gradually recover a clear haze‐free image from a haze image. To improve the performance of the network, we design a cross‐feature density extraction module (CDEModule) to extract the haze density for the image and a density‐guided feature fusion block (DFFBlock) to learn the effective contextual features. Furthermore, we introduce an indirect sampling strategy in the test sampling process, which not only suppresses the accumulation of errors but also ensures the stability of the results. Extensive experiments on popular benchmarks validate the superior performance of the proposed method. The code is released in https://github.com/benchacha/DADM.

Repair of heat load damaged plasma–facing material using the wire-based laser metal deposition process

Due to its unique properties tungsten is a promising candidate as plasma-facing-material (PFM) in future nuclear fusion reactors. Tungsten features an exceptionally high melting point, high thermal conductivity, low tritium inventory and comparatively low erosion rate under plasma loading [1]. But given the extreme loads on the PFM during operation of a fusion reactor, the lifetime of plasma-facing components (PFC)s is limited. Currently, it is planned to replace damaged PFCs when they reach the end of their service life. However, the lifetime of PFCs could be increased by in situ repair using additive manufacturing technology (AM) in the form of direct-energy-deposition (DED). The wire–based laser metal deposition process (LMD-w) meets several necessary conditions for operation in the vessel and could be used for performing such in situ repairs.It was investigated if the LMD-w process is able to heal thermal induced surface cracks and roughening by remelting the substrate during deposition of tungsten. For this purpose, tungsten samples of 12 × 12 × 5mm3, which later served as substrate plates for the LMD-w experiments, were treated with combined steady-state and transient thermal loads in the electron beam facility JUDITH 2. These samples were brazed to a copper cooling structure and exposed to 105 thermal shocks of 0.5 ms duration and an intensity of Labs = 0.55 GW m−2 (FHF = 12 MW s0.5 m−2) at a base temperature of Tbase = 700 °C. This way, edge localized mode (ELM) like thermal load damage was induced on the tungsten samples. On these samples, different LMD-w and laser remelting process strategies were performed. Subsequently, these samples were analyzed, and it was examined that the healing of the pre-damaged substrate material was successful. In parallel, the laser remelting process was modeled in a thermal transient finite element method(FEM) simulation in order to gain an insight into the temperatures prevailing in the material during the process.

Multi-level discriminator based contrastive learning for multiplex networks

Graph embedding is a technique for obtaining low-dimensional representations of nodes across diverse networks, which may then be used for various downstream tasks and applications. When it applies to heterogeneous networks, it is hard to handle heterogeneous networks because they usually contain different types of nodes and edges with more semantic and structural information. Recently, contrastive learning has developed as the preferred strategy for dealing with unsupervised heterogeneous graph embedding to reduce the cost of human label annotation. However, most multi-view contrastive learning approaches calculate the model’s loss only based on the mutual dependence between the node representation and graph representation. These approaches ignore that both node attributes and node clustering contain discriminative content. To solve this issue, we propose a model called Multi-Level Discriminator-based Contrastive Learning for Multiplex Networks (MLDCL). This model adopts a multi-level multi-discriminator-based approach that can simultaneously learn the global-level structural information, node-level attribute information, and local-level clustering information. Moreover, an augmentation strategy in the contrast learning process from the spectral domain is proposed to improve the representation and discriminative ability of MLDCL. Numerous tests with node clustering and classification tasks on widely used datasets demonstrate the efficacy of the proposed approach.

The Application of Social Media in Digital Marketing

Social media can quickly share and communicate while building personal and community online identities and interactive platforms. It can reach almost everyone and effectively pro-mote brands, products, and services, attract potential customers, and encourage sales. It accelerates changes in the environment shared by enterprises and consumers and shapes market behavior. Through a literature review combined with the digital marketing research framework, we classify and synthesize the relevant literature research results, analyze the critical touch points where social media has or may have a significant impact on the marketing process and marketing strategy, and propose the role of social media in the field of digital marketing—existing future research directions.

New routing method based on sticky bacteria algorithm and link stability for VANET

With the rapid development of Telematics, the role of edge computing (Mobile Edge Computing, MEC) is becoming more and more significant. Mobile users can obtain massive computing and storage resources in a local way, thus effectively solving the congestion problem of the core network. However, in general urban edge network scenarios of VANET (Vehicular Ad-hoc Network), due to low node density and poor connectivity, there are few chances to encounter suitable forwarding nodes. In order to avoid the above situation and adapt to sparse scenarios, we propose new link-stabilized routing method & protocol based on sticky bacteria algorithm in this paper. The new idea and the significant findings of this proposed algorithm in enhancing the routing protocol is as follows: five factors affecting routing decision are identified: evaluation distance, deflection angle, number of neighboring nodes, rate difference, and the traffic of the road section at which it is located, and then these five factors are comprehensively evaluated by using the our designed Analytic Hierarchy Process (AHP) strategy, so as to determine the score of each node and the candidate routing paths; And the best routing path between two communicating nodes is found through the stronger global exploration capability of the sticky bacteria algorithm. Our experiments (that are based on our developed C++ programs) have proved that the method proposed in this paper has stronger link stability and the highest packet delivery rate. And the experiments and their results has enhanced our new method credibility in the field of ad hoc networks.