Communication Design Research Articles

Development of Chatbot-Based Oral Health Care for Young Children and Evaluation of its Effectiveness, Usability, and Acceptability: Mixed Methods Study.

Chatbots are increasingly accepted in public health for their ability to replicate human-like communication and provide scalable, 24/7 services. The high prevalence of dental caries in children underscores the need for early and effective intervention. This study aimed to develop the 30-Day FunDee chatbot and evaluate its effectiveness, usability, and acceptability in delivering oral health education to caregivers of children aged 6 to 36 months. The chatbot was created using the artificial intelligence (AI) chatbot behavior change model, integrating behavioral change theories into content designed for 3-5 minutes of daily use over 30 days. A pre-post experimental study was conducted from December 2021 to February 2022 in Hat Yai District, Songkhla Province, and Maelan District, Pattani Province, Thailand. Fifty-eight caregivers completed a web-based structured questionnaire at baseline and 2 months post baseline to evaluate knowledge, protection motivation theory-based perceptions, and tooth-brushing practices. Usability was assessed via chatbot logfiles and a web-based questionnaire at 2 months post baseline. Acceptability was evaluated through three methods: (1) open-ended chatbot interactions on day 30, (2) a web-based structured questionnaire at 2 months post baseline, and (3) semistructured telephone interviews with 15 participants 2 weeks post intervention. Participants for interviews were stratified by adherence levels and randomly selected from Hatyai and Maelan districts. All self-reported variables were measured on a 5-point Likert scale (1=lowest, 5=highest). The chatbot was successfully developed based on the 4 components of the AI chatbot behavior change model. Participants had a mean age of 34.5 (SD 8.6) years. The frequency of tooth brushing among caregivers significantly improved, increasing from 72.4% at baseline to 93.1% two months post baseline (P=.006). Protection motivation theory-based perceptions also showed significant improvement, with mean scores rising from 4.0 (SD 0.6) at baseline to 4.5 (SD 0.6) two months post baseline (P<.001). The chatbot received high ratings for satisfaction (4.7/5, SD 0.6) and usability (4.7/5, SD 0.5). Participants engaged with the chatbot for an average of 24.7 (SD 7.2) days out of 30. Caregivers praised the chatbot's content quality, empathetic communication, and multimedia design, but noted the intervention's lengthy duration and messaging system as limitations. The 30-Day FunDee chatbot effectively enhanced caregivers' perceptions of oral health care and improved tooth-brushing practices for children aged 6-36 months. High user satisfaction and engagement demonstrate its potential as an innovative tool for oral health education. These findings warrant further validation through large-scale, randomized controlled trials.

The Octagonal-Cross-By-Pass-Mesh Topology Design for the On-Chip-Communication

This article presents the novel Octagonal-Cross-By-Pass-Mesh (Octa-CBP-Mesh) network topology design for on-chip communication. We have recently presented the cross-by-pass mesh (CBP-Mesh) topology, which outperformed its classed competitors like modified 2-Diamesional-meshes. The effectiveness of the Cross-by-pass links in the CBP-Mesh played a vital role in enhancing the capabilities of the network characteristics and the overall performance of the topology from its competitors. In this study, keeping in view the weaknesses of the CBP-Mesh network, we proposed the Octa-CBP-Mesh network topology, which further improved compared to state-of-the-art predecessors and competitors. The addition of intelligent CBP-Links in Octa-CBP-Mesh design reduces network diameter and improves other network parameters like increasing the bisection-width, path diversity, fault tolerance, and reduces the average number of hops. The synthetic and embedded application traffic traces were applied to the proposed Octa-CBP-Mesh, its predecessors, and its competitor topologies. The simulation results showed that the Octa-CBP-Mesh performed better in terms of network latency and throughput than state-of-the-art topologies with a negligible increase in network energy and power consumption than CBP-Mesh topology only.

Optimal Beamforming for Covert Communication in MIMO Relay Systems

ABSTRACTThis paper investigates the optimal beamforming design for covert communication in a multiple‐input multiple‐output (MIMO) relay system consisting of source, destination, relay and warden. For both scenarios when each transmitting node knows the perfect or partial warden's channel state information (CSI), we first develop theoretical models to depict the inherent relationship between the beamforming matrices at source/relay and end‐to‐end covert performance of the system regard the minimum detection error probability and covert capacity. Based on these models, we then formulate the optimal beamforming for covert capacity maximization under perfect and partial CSI as linear non‐convex (LNC) and non‐linear non‐convex (NLNC) optimization problems, respectively. We then apply Lagrangian and Hadamard inequality methods to solve the LNC optimization problem to determine the closed‐form expressions for the optimal beamforming matrices at source/relay, based on which a stochastic gradient descent algorithm is developed to evaluate the maximum covert capacity. For the complicated NLNC problem, we propose an efficient search algorithm based on S‐procedure lemma and interior point methods to identify the optimal beamforming matrices to reach the maximum covert capacity. Finally, we provide extensive numerical results to illustrate the covert performance enhancement from adopting the optimal beamforming in MIMO relay systems.

A Machine Learning-Based Approach to Cross-Application of Computer Vision and Visual Communication Design for Automatic Labelling and Classification

A Machine Learning-Based Approach to Cross-Application of Computer Vision and Visual Communication Design for Automatic Labelling and Classification

A biomechanics-oriented study on the impact of AIGC on user interaction and ergonomics in visual communication design

This study investigates the biomechanical implications and ergonomic impacts of AI-generated content (AIGC) integration in visual communication design workflows. Through a comprehensive analysis of 23 professional designers in Chengdu, China, we examined the physical stress patterns, user interaction dynamics, and overall ergonomic outcomes when transitioning from traditional to AIGC-assisted design processes. The research employed a mixed-method approach combining quantitative biomechanical measurements with qualitative user experience assessments over 12 weeks. Results revealed significant reductions in muscle activity across key muscle groups, with the upper trapezius showing the most significant decrease (−3.6% MVC, p &lt; 0.001) during AIGC-assisted tasks. This change in muscle activity can be further linked to alterations in the body's postural stability and load distribution, which are core considerations in biomechanics. Movement efficiency metrics, which are inherently related to biomechanical performance, demonstrated a 27.9% reduction in task completion time (p &lt; 0.001) and a 33.3% decrease in design iterations. Quality assessment scores improved across all dimensions, with Creative Innovation showing the highest enhancement (+1.8 points, p &lt; 0.001). User satisfaction metrics indicated significant improvements, with consistent gains of 1.1 points (on a 5-point scale) across all measured dimensions (p &lt; 0.001). Notably, the study identified distinct adaptation patterns between novice and experienced users in terms of their biomechanical responses. Experienced users demonstrated significantly faster response times in AIGC prompt input (8.94 ± 1.87 s vs 18.62 ± 3.15 s, p &lt; 0.001), which can be associated with differences in their neuromuscular coordination and motor learning abilities. While AIGC integration initially increased certain types of errors (+51.2% in input errors), it led to substantial reductions in tool misuse (−40.4%) and design revisions (−39.9%). These findings suggest that AIGC integration can significantly reduce physical stress while improving design efficiency and quality outcomes, all of which are intertwined with the biomechanical functioning of the body during the design process. The research provides evidence-based recommendations for optimizing AIGC implementation in professional design workflows, taking into account the biomechanical and ergonomic factors that contribute to the overall well-being and creative productivity. This study has important implications for software development, workplace health policies, and the future direction of AI-assisted creative work, as it highlights the significance of considering biomechanics in the integration of advanced technologies within creative domains.

The Integration of Artificial Intelligence in Communication Design. Case Studies from the Polytechnic of Milan: from Digital Culture to Sociology of Media

L’INTEGRAZIONE DELL’INTELLIGENZA ARTIFICIALE NEL DESIGN DELLA COMUNICAZIONE. CASI DI STUDIO DEL POLITECNICO DI MILANO: DALLA CULTURA DIGITALE ALLA SOCIOLOGIA DEI MEDIA Abstract The advent of Artificial Intelligence (AI), particularly Generative AI (GenAI), has catalyzed a transformative shift in educational methodologies, bridging traditional pedagogy with advanced digital technologies. This article presents a comparative analysis of two case studies conducted within the Communication Design Program at Polytechnic of Milan, exploring the integration of GenAI as a collaborative tool in Digital Culture and Sociology of Media courses. By examining the implications, challenges, and outcomes of embedding GenAI within these educational frameworks, we aim to highlight the role of AI as a «co-pilot» in learning processes, offering innovative approaches to knowledge creation and problem-solving. The case studies underscore common themes, such as the democratization of creative tools through AI, the necessity for critical AI literacy, and the exploration of AI as a facilitator of innovative content generation. Simultaneously, the article delves into the differences between the two courses, including participant numbers, course structures, and project aspects, providing a comprehensive understanding of GenAI’s impact on educational experiences and students’ problem-solving skills.

Comparing the Impacts of Different Risk Communication Policy Designs on Public Risk Perceptions: An Experiment in a Nuclear Power Plant Siting Scenario

Policy design of risk communication is crucial for informing the public about potential hazards. This study compares the impacts of different risk communication policy designs on public perceptions regarding the siting of a new nuclear power plant in China. Using a 2 × 2 factorial survey experiment, the behavioural effects of two policy goals (reinforcing benefits and allaying threats) and two policy instruments (science popularization and public engagement) were investigated. The results showed that science popularization is more effective in allaying threats, while public engagement is better at reinforcing benefits. These insights help inform goal-instrument coherence in risk communication policy design.

Citizen Worry and Adherence in Response to Government Restrictions in Switzerland During the COVID-19 Pandemic: Repeated Cross-Sectional Online Surveys.

Good communication between health authorities and citizens is crucial for adherence to preventive measures during a pandemic. Crisis communication often appeals to worries about negative consequences for oneself or others. While worry can motivate protective behavior, it can also be overwhelming and lead to irrational choices or become a mental health problem. Also, the levels and consequences of worry can differ between different groups of citizens. Little is known about the evolution of worries during the pandemic and adherence to measures in distinct groups. This study aimed to evaluate worries in the Swiss population as well as associations between worry levels and citizens' adherence to government restrictions during different phases of the COVID-19 pandemic. We carried out an observational study with 4 cross-sectional online surveys of adults in the Canton of Vaud, Switzerland. Questionnaires were distributed through social media and websites during 4 periods: survey 1: April 17 to May 14, 2020; survey 2: May 15 to June 22, 2020; survey 3: October 30 to December 12, 2020; and survey 4: June 18 to December 30, 2021. On visual analog scales from 0 to 100, participants reported worry, self-adherence to pandemic restrictions, and their perceived adherence to others. We used multivariable linear regression, adjusting for age, gender, health literacy, and education to assess associations between self-reported worry, adherence, and study periods. We collected 7106 responses. After excluding 2377 questionnaires (incomplete, age <18 years, residence outside Vaud), 4729 (66.55%) were analyzed (mean age 47, SD 15.6 years, 63.96% women). Mean worry across the 4 periods was 42/100, significantly higher in women (44.25/100, vs 37.98/100; P<.001) and young people (43.77/100 in those aged 18-39 years, vs 41.69/100; P=.005; in those aged 40-64 years and 39.16/100; P=.002; in those aged >64 years). Worries were higher during survey 1 and survey 3 (52.41/100 and 56.32/100 vs 38.93/100, P<.001; and 35.71/100, P<.001) than during survey 2 and survey 4, respectively. This corresponds to pandemic peaks during which federal restrictions were better followed with self-reported adherence of 84.80/100 and 89.59/100 in survey 1 and survey 3 versus 78.69/100 (P<.001) and 78.64/100 (P<.001) in survey 2 and survey 4. A 2.9-point increase in worry score, adjusted for the pandemic period, gender, age, education, and health literacy, was associated with a 10-point increase in personal adherence score (95% CI 2.5-3.2; P<.001). Worries were higher in women, young people, and during the peak of the COVID-19 pandemic. Higher worry levels were associated with increased self-reported adherence to federal restrictions. Authorities should consider population worry levels and population subgroups in the planning and design of pandemic communication.

A Low-profile EBG Based Corrugated 5G Antenna Design for WLAN Communication

A Low-profile EBG Based Corrugated 5G Antenna Design for WLAN Communication

Dual-Function Beamforming Design for Multi-Target Localization and Reliable Communications

Dual-Function Beamforming Design for Multi-Target Localization and Reliable Communications

Low-Complexity Beamforming Design for MU-MIMO Optical Wireless Communications

Low-Complexity Beamforming Design for MU-MIMO Optical Wireless Communications

Dynamic Hybrid Beamforming Designs for ELAA Near-Field Communications

Dynamic Hybrid Beamforming Designs for ELAA Near-Field Communications

Design and Performance of Resonant Beam Communications—Part I: Quasi-Static Scenario

Design and Performance of Resonant Beam Communications—Part I: Quasi-Static Scenario

Codebook Design for SCMA-Assisted Visible Light Communication With Shot Noise

Codebook Design for SCMA-Assisted Visible Light Communication With Shot Noise

Soliton and rogue wave excitations in the Chen-Lee-Liu derivative nonlinear Schrödinger equation with two complex PT-symmetric potentials.

We demonstrate that fundamental nonlinear localized modes can exist in the Chen-Lee-Liu equation modified by several parity-time (PT) symmetric complex potentials. The explicit formula of analytical solitons is derived from the physically interesting Scarf-II potential, and families of spatial solitons in internal modes are numerically captured under the optical lattice potential. By the spectral analysis of linear stability, we observe that these bright solitons can remain stable across a broad scope of potential parameters, despite the breaking of the corresponding linear PT-symmetric phases. When these bright spatial solitons interact with external incident waves, they can always maintain their original shape, while the external incident wave may remain unchanged or may generate a reflected wave after the interaction. Then, the adiabatic switching of potential parameters is carried out in a way that allows these bright solitons to be excited from one unstable bound state to another alternative stable bound state. Many other intriguing properties associated with these nonlinear localized modes including the lateral power flow are further analyzed meticulously. Various high-order rogue waves induced by modulation instability in these PT-symmetric systems are generated too. These results may be useful to construct novel optical soliton communication schemes or design related optical materials.

Artificial Intelligence based Automated Sign Gesture Recognition Solutions for Visually Challenged People

Gesture recognition is employed in human-machine communications, enhancing human life with impairments or who depend on non-verbal instructions. Hand gestures role an important role in the field of assistive technology for persons with visual impairments, whereas an optimum user communication design is of major importance. Many authors with substantial development for gesture recognition modeled several methods by using deep learning (DL) methods. This article introduces a Robust Gesture Sign Language Recognition Using Chicken Earthworm Optimization with Deep Learning (RSLR-CEWODL) approach. The projected RSLR-CEWODL algorithm majorly focuses on the recognition and classification of sign language. To accomplish this, the presented RSLR-CEWODL technique utilizes a residual network (ResNet-101) model for feature extraction. For optimal hyper parameter tuning process, the presented RSLR-CEWODL algorithm exploits the CEWO algorithm. Besides, the RSLR-CEWODL technique uses a whale optimization algorithm (WOA) with deep belief network (DBN) method for the sign language recognition method. The simulation result of the RSLR-CEWODL algorithm is tested using sign language datasets and the outcome was measured under various measures. The simulation values demonstrated the enhancements of the RSLR-CEWODL technique over other methodologies.

Computer multimedia art pattern and visual communication design integrating virtual reality technology and big data image processing

Computer multimedia art pattern and visual communication design integrating virtual reality technology and big data image processing

16-Elements Ring Shaped MIMO Antenna Design for 5G Wireless Communication

The most popular area of study in wireless communication is Fifth Generation (5G). In this paper, a 5G MIMO antenna with a wide bandwidth, large gain, and compact structure is designed. The suggested design has two input and two output ports, with eight octagonal randomly shaped patches designed with Rogers RT5880 substrate in a building from the front and stripped from the bottom sort of arrangement. On CST-Microwave Studio, the entire designing and simulation process is carried out. Several characteristic parameters have been determined in this research using CST software. Broadband from 32GHz to 35 GHz and -43.62 return losses achieved at 33.56 GHz frequency with the proposed design. More than 9.6 dBi gain is also achieved with the proposed antenna. The antenna is broadband, very compact, with high gain and efficiency.

HARNESSING AI IMAGE GENERATOR PROMPT ENGINEERING FOR ACADEMIC EXCELLENCE

This study explores the role of prompt engineering in visual communication design education, specifically examining its application with AI image generators. With the rise of AI technologies, prompt engineering has become an essential skill for creative professionals to maximize the potential of AI tools in generating high-quality visuals. The purpose of this research is to assess the effectiveness of prompt engineering skills among visual communication design students and identify factors that contribute to successful prompt formulation. Research methods include case study analysis, surveys, prompt formulation experiments, interviews, and visual output analysis using AI tools such as DALL-E, MidJourney, and Stable Diffusion. Findings show that students’ prompt engineering proficiency varies widely, with language skills, creativity, and technological understanding being key determinants. Effective prompt engineering significantly enhances the quality and creativity of generated visuals. The study concludes that integrating prompt engineering into design curricula can improve students' technical skills and creative problem-solving. Educators should focus on practical applications and provide training in AI tools to ensure that students are prepared for the evolving design landscape.

“SOSIOLOGI SASTRA PENGANTAR RINGKAS” COVER DESIGN BY 369 IN SCHLEIERMACHER'S HERMENEUTIC PERSPECTIVE

This study aims to investigate the process of role-changing taken by the author, who designs his book covers using the pseudonym “369”. The author's knowledge and experiences in self-publishing showed how his process relates to what is now known as visual communication design democratization. Schleiermacher's hermeneutic perspective is used to comprehend the process of the roles-changing and thoughts of the designer/author in exploring knowledge of visual communication design, which may be understood through other perspectives held by 369. By using an empathetic and divinatory approach, as Schleiermacher suggested, this study finds the transtextual relationship between the book cover design as text and the text of the book's contents, as well as other texts from the same author. This transtextual relationship becomes a way to re-reflect on the democratization of visual communication design.