Interactive System Research Articles

Research Progress and Prospect on Profile Roll Forming Methods and Equipment

Abstract: In recent years, with the development of aerospace, automotive, rolling stock, shipbuilding, military weapons and other industries, the demand for bent and rolled parts is increasing, and the requirements for roll forming accuracy are growing. With the rapid development of coal power, hydropower, nuclear power, wind power, and petrochemical industries, the design and research on roll bending machine and the profile roll forming methods have come into focus. The purpose of this study is to summarize the classification and characteristics of roll bending equipment, analyze the reasons that affect the accuracy of profile bending, and propose specific solutions. This paper summarizes the research status and patents on the existing roll bending equipment, introduces its structural characteristics, differences, and molding effects, and focuses on the difficulties, optimization, and improvement methods of roll bending molding. In this paper, the mechanical structures of the existing roll forming equipment have been analyzed and compared, the effects of different roll forming equipment on the profile bending results have been determined, and the reasons affecting the bending accuracy have been pointed out. By summarizing the patents and research on profile roll forming methods and equipment, the current situation and future research prospects of roll forming equipment are discussed. The roll forming equipment is divided into a roll bending machine, a CNC roll bending machine, and a flexible roll bending machine. Each design can meet different profile processing needs. From the design point of view, the optimization under the given processing profile can achieve relatively high processing accuracy. However, the processing of different profiles will still produce geometric defects, and there is some space for improvement in the structure of roll forming equipment, the materials of processing rollers, and the NC interactive system. Thus, further research on profile roll forming is needed in the future.

Psudo: Exploring Multi-Channel Biomedical Image Data with Spatially and Perceptually Optimized Pseudocoloring.

Over the past century, multichannel fluorescence imaging has been pivotal in myriad scientific breakthroughs by enabling the spatial visualization of proteins within a biological sample. With the shift to digital methods and visualization software, experts can now flexibly pseudocolor and combine image channels, each corresponding to a different protein, to explore their spatial relationships. We thus propose psudo, an interactive system that allows users to create optimal color palettes for multichannel spatial data. In psudo, a novel optimization method generates palettes that maximize the perceptual differences between channels while mitigating confusing color blending in overlapping channels. We integrate this method into a system that allows users to explore multi-channel image data and compare and evaluate color palettes for their data. An interactive lensing approach provides on-demand feedback on channel overlap and a color confusion metric while giving context to the underlying channel values. Color palettes can be applied globally or, using the lens, to local regions of interest. We evaluate our palette optimization approach using three graphical perception tasks in a crowdsourced user study with 150 participants, showing that users are more accurate at discerning and comparing the underlying data using our approach. Additionally, we showcase psudo in a case study exploring the complex immune responses in cancer tissue data with a biologist.

SARDINE: Simulator for Automated Recommendation in Dynamic and Interactive Environments

Simulators can provide valuable insights for researchers and practitioners who wish to improve recommender systems, because they allow one to easily tweak the experimental setup in which recommender systems operate, and as a result lower the cost of identifying general trends and uncovering novel findings about the candidate methods. A key requirement to enable this accelerated improvement cycle is that the simulator is able to span the various sources of complexity that can be found in the real recommendation environment that it simulates. With the emergence of interactive and data-driven methods—e.g., reinforcement learning or online and counterfactual learning-to-rank—that aim to achieve user-related goals beyond the traditional accuracy-centric objectives, adequate simulators are needed. In particular, such simulators must model the various mechanisms that render the recommendation environment dynamic and interactive, e.g., the effect of recommendations on the user or the effect of biased data on subsequent iterations of the recommender system. We therefore propose SARDINE, a flexible and interpretable recommendation simulator that can help accelerate research in interactive and data-driven recommender systems. We demonstrate its usefulness by studying existing methods within nine diverse environments derived from SARDINE, and even uncover novel insights about them.

Efficacy and safety of undenatured type II collagen in patients with knee osteoarthritis: a multicenter, prospective, double-blind, placebo-controlled, randomized trial

Non-pharmacological treatments based on collagen as a dietary supplement are emerging as a new area of interest to support preventive or therapeutic effects in patients with osteoarthritis (OA). In a multicenter, prospective, double-blind, placebo-controlled, randomized study, to evaluate the effectiveness and safety of the use of the Artneo complex containing undenatured chicken collagen type II in patients with OA of the knee joints. The study enrolled 212 outpatients from 12 centers in the Russian Federation with knee OA, stages II and III according to the Kellgren-Lawrence classification. The participants included 171 women (80.7%) and 41 men (19.3%), with an average age of 60.2±9.0 years (range: 40 to 75 years). The study population was randomly allocated in equal proportions into two groups using an interactive web response system (IWRS). Group 1 (Artneo) consisted of 106 patients who took one capsule of the drug once daily for 180 days. Group 2 (Placebo) also had 106 patients, with the dosage form and regimen identical to Group 1. During the treatment period, the following outcomes were assessed: WOMAC index, KOOS, pain according to VAS, quality of life using the EQ-5D questionnaire, and the need for NSAIDs. All patients underwent a clinical blood test, general urine analysis, biochemical blood test, and ultrasound examination of the affected knee joint. In a prospective, double-blind, placebo-controlled, randomized study, it was demonstrated that the Artneo combination, containing undenatured chicken collagen type II, has a positive effect on all clinical manifestations of OA: it effectively reduces pain, stiffness, and improves the functional state of joints and quality of life. It has a good safety profile and is superior to placebo in all parameters studied. The results of the study confirm the good effectiveness and safety of the Artneo combination in patients with OA of the knee joints.

Voice interactive information metasurface system for simultaneous wireless information transmission and power transfer

Intelligent voice interaction offers a flexible and powerful way to connect individuals with smart devices beyond our expectations. The real-time nature of voice communication enables smart devices to comprehend the user language, execute the corresponding instructions, and facilitate seamless communications, transforming our lives in unprecedented ways. Owing to self-adaptive and reprogrammable functionalities, information metasurface (IMS) opens up a new avenue for smart home and smart cities. To further enhance the intelligence of IMS, we propose an IMS system via intelligent voice interaction and information processing. The voice interaction enables the efficient remote control on the IMS in a flexible, convenient, touchless manner. Leveraging speech recognition, speech synthesis, target detection, and communication technologies, the IMS system achieves automatic beam manipulation capabilities for wireless information transmissions and wireless power transfers. The IMS system is designed to operate in two distinct modes: instruction mode, wherein the user instructs the operations, and autonomous mode, wherein the automatic detections govern the actions, in which seamless mode switching through the voice commands is supported. Users can flexibly achieve precise control over the functions of the intelligent metasurface system through voice interaction at a distance, without the need for close-range manual touch control, which greatly simplifies the operation difficulty and is particularly suitable for remote control and complex application scenarios. A series of experiments, including wireless video transmissions and wireless power transfers are conducted to demonstrate the flexibility and convenience of the IMS system. The incorporation of intelligent voice interaction technology with the IMS presents a novel paradigm for the applications of programmable and information metasurfaces.

System interactive reader using eye-tracker technology in ebook reader

Interest in using ebooks by the academic community is very high. Still, there is a problem when readers are reading through screens, tend to read fast, only scan the necessary parts, and don't focus on paying attention to the content they read, so this reduces the quality of reading because readers don't study the overall meaning of the sentence. Hence, this research aims to build an interactive reader system by integrating eye tracker technology with a webcam which is expected to solve the problem of decreasing the quality of reading through the screen by helping readers stay focused on their reading and providing an interactive system that makes it easier for readers to control the computer while reading. This research adopts the waterfall method and is divided into six stages. The system is designed using class diagrams, use case diagrams, and activity diagrams. Also, the system is built using the Python language with the Django framework. Then, the interactive reader system was tested using black box testing and usability testing methods. Based on the test results, it is shown that the interactive reader system that was built can help improve the quality and concentration when reading activities take place.

Safety and efficacy of inebilizumab for the treatment of neuromyelitis optica spectrum disorder: end-of-study results from the open-label period of the N-MOmentum trial

Inebilizumab, an anti-CD19 B-cell-depleting antibody, demonstrated safety and efficacy in neuromyelitis optica spectrum disorder in the randomised controlled period of the N-MOmentum trial. Here, end-of-study data, including the randomised controlled period and open-label extension period, are reported. In the double-blind, randomised, placebo-controlled, phase 2/3 N-MOmentum trial, adults aged 18 years and older with an neuromyelitis optica spectrum disorder diagnosis, Expanded Disability Status Scale score of 8·0 or less, and history of either at least one acute inflammatory attack requiring rescue therapy in the past year or two attacks requiring rescue therapy in the past 2 years, were recruited from 81 outpatient specialty clinics or hospitals in 24 countries. Eligible participants were randomly assigned (3:1), using a central interactive voice system or interactive web response system, and a permuted block randomisation scheme (block size of 4), to receive intravenous inebilizumab (300 mg) or identical placebo on days 1 and 15 of the randomised period, which lasted up to 197 days. Participants and all study staff were masked to treatment assignment. The primary endpoint of the randomised period of the trial was time to onset of adjudicated neuromyelitis optica spectrum disorder attack on or before day 197. Participants in the randomised controlled period who had an adjudicated attack, completed 197 days in the study, or were in the randomised controlled period when enrolment stopped, could voluntarily enter the open-label period. In the open-label period, participants either initiated inebilizumab if assigned placebo (receiving 300 mg on days 1 and 15 of the open-label period) or continued treatment if assigned inebilizumab (receiving 300 mg on day 1 and placebo on day 15, to maintain B-cell depletion and masking of the randomised controlled period). All participants subsequently received inebilizumab 300 mg every 6 months for a minimum of 2 years. The end-of-study analysis endpoints were time to adjudicated attack and annualised attack rate (assessed in all participants who received inebilizumab at any point during the randomised controlled period or open-label period [any inebilizumab population] and the aquaporin-4 [AQP4]-IgG seropositive subgroup [any inebilizumab-AQP4-IgG seropositive population]) and safety outcomes (in all participants who were exposed to inebilizumab, analysed as-treated). This study is registered with ClinicalTrials.gov, NCT02200770, and is now complete. Between Jan 6, 2015, and Sept 24, 2018, 467 individuals were screened, 231 were randomly assigned, and 230 received at least one dose of inebilizumab (n=174) or placebo (n=56). Between May 19, 2015, and Nov 8, 2018, 165 (95%) of 174 participants in the inebilizumab group and 51 (91%) of 56 in the placebo group entered the open-label period (mean age 42·9 years [SD 12·4], 197 [91%] of 216 were female, 19 [9%] were male, 115 [53%] were White, 45 [21%] were Asian, 19 [9%] were American Indian or Alaskan Native, and 19 [9%] were Black or African American). As of data cutoff for this end of study analysis (Dec 18, 2020; median exposure 1178 days [IQR 856-1538], total exposure of 730 person-years) 225 participants formed the any inebilizumab population, and 208 (92%) participants were AQP4-IgG seropositive. Overall, 63 adjudicated neuromyelitis optica spectrum disorder attacks occurred in 47 (21%) of 225 treated participants (60 attacks occurred in 44 [21%] of 208 in the AQP4-IgG seropositive subgroup); 40 (63%) of 63 attacks occurred in 34 (15%) of 225 treated participants during the first year of treatment. Of individuals who had an adjudicated attack while receiving inebilizumab, 36 (77%) of 47 were subsequently attack-free at the end of 4 years. Annualised attack rates decreased year-on-year, with end-of-study adjusted annualised attack rates being similar in the any inebilizumab-AQP4-IgG seropositive subgroup (0·097 [95% CI 0·070-0·14]) and any inebilizumab populations (0·092 [0·067-0·13]). Overall, 208 (92%) of 225 participants who received any inebilizumab had at least one treatment-emergent adverse event, the most frequent of which were urinary tract infection (59 [26%]), nasopharyngitis (47 [21%]), and arthralgia (39 [17%]). Infection rates did not increase over 4 years. Three (1%) of 225 participants in the any inebilizumab population died during the open-label period (one each due to a CNS event of unknown cause and pneumonia, respiratory insufficiency resulting from an neuromyelitis optica spectrum disorder attack and viral pneumonia related to COVID-19), all of which were deemed to be unrelated to treatment. Data from the end-of-study analysis of the N-MOmentum trial showed continued and sustained clinical benefits of long-term inebilizumab treatment in individuals with neuromyelitis optica spectrum disorder, which supports the role of inebilizumab as a CD19+ B-cell-depleting therapy in neuromyelitis optica spectrum disorder. MedImmune and Viela Bio/Horizon Therapeutics, now part of Amgen.

Preference-Learning Emitters for Mixed-Initiative Quality-Diversity Algorithms

In mixed-initiative co-creation tasks, wherein a human and a machine jointly create items, it is important to provide multiple relevant suggestions to the designer. Quality-diversity algorithms are commonly used for this purpose, as they can provide diverse suggestions that represent salient areas of the solution space, showcasing designs with high fitness and wide variety. Because generated suggestions drive the search process, it is important that they provide inspiration, but also stay aligned with the designer's intentions. Additionally, often many interactions with the system are required before the designer is content with a solution. In this work, we tackle these challenges with an interactive constrained MAP-Elites system that leverages emitters to learn the preferences of the designer and then use them in automated steps. By learning preferences, the generated designs remain aligned with the designer's intent, and by applying automatic steps, we generate more solutions per user interaction, giving a larger number of choices to the designer and thereby speeding up the search. We propose a general framework for preference-learning emitters (PLEs) and apply it to a procedural content generation task in the video game Space Engineers. We built an interactive application for our algorithm and performed a user study with players.

Exploring the Composer-Performer-Teacher Role Complex in Fostering Creativity in Music Education

The article considers the interaction system between the processes of creating a musical composition, performance and pedagogy, which is currently a particularly topical issue. The main purpose of the article is to actualise the attention to this dilemma of representatives of the Ukrainian musical and pedagogical community, including composers, performers, teachers, and to comprehend the importance of the triune role complex. The article analyses the block “composer – performer – teacher” using the methods of historical and interdisciplinary approaches. Data different in nature, directions of musical activity constitute a single whole in real practice. The system of the educational process in various educational institutions, the problems of interaction between the teacher and the student, the specifics of the self-realisation of the individual in the creative musical area were also covered. In the course of the study, it was determined that composer creativity, performance and music education are carried out in the interaction process of such objects as music and pedagogy, teacher and student, various kinds of contacts among employees on creative and educational activities in terms of world and, in particular, Ukrainian culture. The practical significance of the study is to update and expand the scope of the modern educational system through the application of the trinity principles “composer – performer – teacher” in the process of mastering the curriculum. It is designed to make the interaction of professional musicians with the audience and students more effective, to create the conditions necessary for the training of musical personnel of the highest level, and also to form an awareness of the importance and equivalence of each of the components of this triad.

Real-Time Object Detection and Recognition with Computer Vision

Abstract: Object detection, a fundamental aspect of computer vision, is essential for identifying and localizing objects within images or video frames, leveraging advancements in deep learning, particularly convolutional neural networks (CNNs), to enhance precision and speed. Its applications span diverse domains, from autonomous vehicles and surveillance systems to augmented reality and human-computer interaction. Our project focuses on engineering a real-time object detection system, integrating deep learning and computer vision methodologies. Anchored on the robust Single Shot Multibox Detector (SSD) architecture and reinforced by the efficiency and accuracy of the MobileNetV3 backbone, our system utilizes a pre-trained SSD MobileNetV3 model and comprehensive annotations from the COCO dataset to adeptly detect and recognize a wide array of objects within live video streams or archived footage. It seamlessly processes video frames from various sources, annotating detected objects in real-time to provide instant visual feedback. Offering customizable confidence thresholds and support for multiple video sources, our project showcases the transformative potential of deep learning and computer vision, advancing realtime object detection across domains like surveillance and interactive systems. By pushing the boundaries of object detection technology, our project aims to enhance safety, efficiency, and user experiences in various applications, promising to redefine the landscape of computer vision with innovation and advancement.

Enhancing Interactive IVR Using NLP

Abstract: This paper suggests a fresh approach to IVR design by incorporating natural language processing (NLP) techniques, enhancing user experiences. Traditional IVRs often frustrate users due to their rigid menu structures. By integrating NLP, we aim to create dynamic and interactive IVR systems, leading to increased user satisfaction, streamlined interactions, and improved business performance. Our self-deployment and user testing demonstrate the system's effectiveness in providing personalized and responsive support, transforming traditional IVRs into engaging communication channels.

Exploring the gender gap: A nationwide comparative analysis of general surgery residency program leadership

BackgroundThe gender disparity in surgery leadership roles is well-reported. However, the effect of program type and region on mean number of men or women occupying a particular leadership role has yet to be explored. This study aims to investigate the gender disparity of leadership positions in different types of General Surgery Residency Programs (GSRPs). MethodsLeadership roles of the general surgery departments were collected from the Fellowship and Residency Electronic Interactive Database Access System (FREIDA) database. Each GSRP was categorized by region and program type using FRIEDA. Analysis of the mean number of men and women holding various leadership positions by program type and region was conducted using one-way ANOVA with post-hoc tests. ResultsA total of 345 GSRPs were analyzed. The mean number of women occupying various leadership roles was significantly higher at university-based programs when compared to community-based programs. No significant difference in mean number of women leaders was observed by region. ConclusionsWomen consistently occupy a lower number of GSRP leadership positions when compared to men, regardless of program type or region. University-based GSRP leadership positions have significantly greater gender inclusion compared to community-based GSRPs. Key messagesUniversity-based general surgery residency programs had a higher mean number of women in all leadership roles compared to other program types. In comparison, region did not appear to be a significant factor impacting the leadership gender disparity. Improvement is needed in community-based general surgery residency programs to bridge the gender gap in leadership roles.

CPU 병렬 처리를 이용한 SPH 유체와 단일보드 컴퓨터의 실시간 상호작용 시스템 개발

CPU 병렬 처리를 이용한 SPH 유체와 단일보드 컴퓨터의 실시간 상호작용 시스템 개발

Retraction Note: Speech to speech interaction system using Multimedia Tools and Partially Observable Markov Decision Process for visually impaired students

Retraction Note: Speech to speech interaction system using Multimedia Tools and Partially Observable Markov Decision Process for visually impaired students

Research on the interaction between trench material and pipeline under fault displacement

With the large-scale construction of oil and gas pipelines, the safety issues of long-distance buried pipelines in the service and construction have become increasingly prominent. The complex geological and topographical conditions of the special zone will put forwards extremely high requirements on pipe trench laying backfill materials and construction technology. For example, pipelines are inevitable to cross the active fault, while the trench backfilled with soil has limitations in protecting them from failure under the active fault displacement caused by the earthquake. Therefore, it is necessary to study the pipe–soil interaction mechanism, determine the stress state of the pipeline and propose a new backfilling material that can protect the pipeline from failure. Foam concrete (FC) provides a new choice to backfill the buried pipeline trench due to its high-homogeneity, lightweight, controllable-strength, and self-compacting. To further determine the applicability of the FC, the pipe-FC interaction mechanism is studied. Then, a FE model of the FC-pipeline-soil interaction system is established by Abaqus to quantitatively analyze the applicability of the FC based on the experimental data of the mechanical performance of the FC. It proves that using FC as trench backfill material has a noticeable protective effect on the pipeline under the earthquake-induced displacement of the normal fault. Furthermore, FC has a better protective effect on the pipeline subjected to compressive than tensile. Therefore, the reference for applying FC in trench backfilling of pipelines crossing normal fault is provided.

Thermalization and Hydrodynamics in an Interacting Integrable System: The Case of Hard Rods

We consider the relaxation of an initial non-equilibrium state in a one-dimensional fluid of hard rods. Since it is an interacting integrable system, we expect it to reach the Generalized Gibbs Ensemble (GGE) at long times for generic initial conditions. Here we show that there exist initial conditions for which the system does not reach GGE even at very long times and in the thermodynamic limit. In particular, we consider an initial condition of uniformly distributed hard-rods in a box with the left half having particles with a singular velocity distribution (all moving with unit velocity) and the right half particles in thermal equilibrium. We find that the density profile for the singular component does not spread to the full extent of the box and keeps moving with a fixed effective speed at long times. We show that such density profiles can be well described by the solution of the Euler equations almost everywhere except at the location of the shocks, where we observe slight discrepancies due to dissipation arising from the initial fluctuations of the thermal background. To demonstrate this effect of dissipation analytically, we consider a second initial condition with a single particle at the origin with unit velocity in a thermal background. We find that the probability distribution of the position of the unit velocity quasi-particle has diffusive spreading which can be understood from the solution of the Navier–Stokes (NS) equation of the hard rods. Finally, we consider an initial condition with a spread in velocity distribution for which we show convergence to GGE. Our conclusions are based on molecular dynamics simulations supported by analytical arguments.

YOLOv5 driven smart glasses for visually impaired

This project introduces an innovative AI-based interactive shopping assistance system tailored specifically for visually impaired individuals, aiming to enhance their shopping experience and promote inclusivity in retail environments. Leveraging advanced artificial intelligence algorithms, the system provides personalized assistance, navigation support, and seamless interaction for users facing visual challenges. Through intuitive interfaces and adaptive technologies, disabled individuals are empowered to navigate retail spaces with greater independence and confidence. The system utilizes a camera module and YOLO-based deep learning algorithms on a Raspberry Pi 4 for real-time object classification, converting processed information into accessible audio output. In addition to these features, the system incorporates a language customization capability using OCR and gTTS technology, enabling conversion of audio output into multiple languages based on user preference. By prioritizing the needs of visually impaired individuals, this groundbreaking system aims to enhance accessibility and promote an inclusive shopping experience for all.

The development status and trends of automotive interactive systems

Nowadays, as time passes and science and technology improve, the interactive system of autos becomes more common, and there are far-reaching changes from the original. As autonomous driving and other functions become more developed, people are increasingly focusing on the car's interactive system. This study investigates automobile development status and trends via the lens of automobile interaction systems, comparing them between previous and present periods, using BYDs electric vehicle interaction system as an example, and briefly exploring the current automobile interaction system. The development characteristics and influencing elements of some automobile interface systems are summarized, and the future development trend is anticipated using this information. Finally, it is determined that the automobile interaction system is progressing toward giving people a more comfortable and safe driving experience, which is a positive trend, and that more technologies may be merged into it in the future. The research in this paper that the vehicle interaction system is currently in development, and while it is merely a simple physical interaction, with the continual integration of new technologies, it has the potential to make significant progress.

A digital twin-driven human-machine interactive assembly method based on lightweight multi-target detection and assembly feature generation

ABSTRACT In the field of industrial assembly, human-machine interactive assembly methods are frequently used. Lack of virtual and physical mapping, a convoluted guiding system, and low effect precision in the interactive process, a digital twin-driven human-machine interactive assembly method system is proposed as a solution to the mentioned issues. The YOLOv7-tiny lightweight model is used to perform accurate detection of parts. By incorporating attention modules into the backbone network, the feature extraction capability of the model in complicated assembly environments is enhanced. The assembly method proposed is validated using the assembly process of the reducer as an instance. The OpenCV method is employed to produce geometric reference features for parts. The experimental results show that the proposed assembly method can provide visual guidance for the assembly process, improve the traditional list-type assembly component retrieval method, solve the drawbacks of the pre-set assembly guidance in the guidance system that may not be able to adapt to the changes of the assembly results in the actual operation, and can accurately instruct novices how to assemble, which is characterised by easy implementation, low cost and high accuracy, and is of great significance for improving the success rate and assembly efficiency of human-machine interactive assembly.

Multi-scenario application of chitosan emulsions as fat replacers: Based on the regulation of chitosan hydrophobicity and emulsion rheological properties

Excessive intake of saturated fatty acids poses a serious health risk, necessitating the urgent development of healthier plant-based fat replacers. Despite the emulsifying properties of chitosan (CS), it remains a significant challenge to create CS emulsions with minimal CS content and superior rheological properties as fat replacers. In this study, a supramolecular interaction system was constructed with inner hydrophilicity and outer hydrophobicity, enabling tunable rheological properties. This system was utilized to assemble hydrophobically modified CS with sodium alginate through appropriate treatment. As the oil phase fraction in the emulsion of stabilized flaxseed oil in the supramolecular system increases, the viscosity, storage modulus (G′), and loss modulus (G″) of the emulsion also increase. The emulsion transitions to a semi-solid state when the oil phase fraction ≥60 wt%. The supramolecular system (1 mg/g) can stabilize flaxseed oil emulsion with 80 wt% oil phase fraction. There were no significant changes in the morphology and rheological properties of the emulsions following a 60-day storage period at room temperature. In addition, emulsions can be used in several scenarios as fat replacers in food processing due to their tunable rheological properties.