Interactive Computer Research Articles

LVC/MM: A Hybrid Linear Vibronic Coupling/Molecular Mechanics Model with Distributed Multipole-Based Electrostatic Embedding for Highly Efficient Surface Hopping Dynamics in Solution.

We present a theoretical framework for a hybrid linear vibronic coupling model electrostatically embedded into a molecular mechanics environment, termed the linear vibronic coupling/molecular mechanics (LVC/MM) method, for the surface hopping including arbitrary coupling (SHARC) molecular dynamics package. Electrostatic embedding is realized through the computation of interactions between environment point charges and distributed multipole expansions (DMEs, up to quadrupoles) that represent each electronic state and transition densities in the diabatic basis. The DME parameters are obtained through a restrained electrostatic potential (RESP) fit, which we extended to yield higher-order multipoles. We also implemented in SHARC a scheme for achieving roto-translational invariance of LVC models as well as a general quantum mechanics/molecular mechanics (QM/MM) interface, an OpenMM interface, and restraining potentials for simulating liquid droplets. Using thioformaldehyde in water as a test case, we demonstrate that LVC/MM can accurately reproduce the solvation structure and energetics of rigid solutes, with errors on the order of 1-2 kcal/mol compared to a BP86/MM reference. The implementation in SHARC is shown to be very efficient, enabling the simulation of trajectories on the nanosecond time scale in a matter of days.

인터랙티브 컴퓨터 음악에 대한 분류 방식 연구

Advances in science and technology have brought about great changes in music creation and performance, and in particular, interactive computer music provides new approaches to creators and receivers. The purpose of this study is to analyze the characteristics and applications of two sampling models for an in-depth understanding of the creation and performance of interactive computer music. As a research method, a new classification method based on a sampling model is proposed through a literature review of existing classification methods by Robert Rowe, Todd Winkler, etc. Through a comparative analysis and characteristics of the two models, focusing on the preset sampling model and the real-time sampling model, we examine how the two sampling models affect the creation and expression of interactive computer music. This study provides an interpretation of the possibilities and applications of interactive computer music, and is expected to contribute to research and practice in this field.

Visual results and subjective satisfaction after implantation of two different trifocal diffractive intraocular lenses models (AcrySof IQ PanOptix and AT LISA tri 839 MP).

This study aimed to compare visual results following the implantation of two distinct diffractive trifocal IOLs utilizing various vision evaluation techniques and subjective satisfaction. The study included 32 eyes receiving AcrySof IQ PanOptix implantation and 32 receiving AT LISA tri 839 MP. Post-operative examination at one year included uncorrected visual acuity (UCVA), distance-corrected visual acuity (DCVA) at 4 m, 80 cm, 60 cm, and 40 cm, Contrast sensitivity under photopic and mesopic conditions, and a questionnaire on subjective quality of vision, optical phenomena, and spectacle independence. The two groups were similar in baseline demographics, pre-operative visual, biometric data (except for axial length), and surgical paraments. The PanOptix outperformed the AT LISA tri in the intermediate range when using the standard visual acuity testing (UCVA: 0.23 ± 0.14 logMAR vs. 0.31 ± 0.17 logMAR, p = 0.04; BCVA: 0.21 ± 0.12 vs. 0.28 ± 0.14, p = 0.03) and in the intermediate and far range when using the interactive computer program (intermediate: UNVA "E" optotype test: 0.05 ± 0.12 vs. 0.12 ± 0.13, p = 0.03; Far: UNVA "E" optotype: 0.07 ± 0.12 vs. 0.13 ± 0.10, p = 0.05). In addition, the PanOptix group had higher contrast sensitivity under photopic and mesopic conditions with and without glare at all spatial frequencies. There was no difference in subjective outcomes between the groups. Patients who received PanOptix IOL had better visual outcomes for intermediate and far with higher contrast sensitivity under various conditions. Based on patients ' needs and demands, these results could support discussion when tailoring the optimal multifocal IOl.

Joint UV Optimization and Texture Baking

Level of detail has been widely used in interactive computer graphics. In current industrial 3D modeling pipelines, artists rely on commercial software to generate highly detailed models with UV maps and then bake textures for low-poly counterparts. In these pipelines, each step is performed separately, leading to unsatisfactory visual appearances for low polygon count models. Moreover, existing texture baking techniques assume the low-poly mesh has a small geometric difference from the high-poly, which is often not true in practice, especially with extremely low poly count models. To alleviate the visual discrepancy of the low-poly mesh, we propose to jointly optimize UV mappings during texture baking, allowing for low-poly models to faithfully replicate the appearance of the high-poly even with large geometric differences. We formulate the optimization within a differentiable rendering framework, allowing the automatic adjustment of texture regions to encode appearance information. To compensate for view parallax when two meshes have large geometric differences, we introduce a spherical harmonic parallax mapping, which uses spherical harmonic functions to modulate per-texel UV coordinates based on the view direction. We evaluate the effectiveness and robustness of our approach on a dataset composed of online downloaded models, with varying complexities and geometric discrepancies. Our method achieves superior quality over state-of-the-art techniques and commercial solutions.

Exchange correlation potentials from full configuration interaction in a Slater orbital basis.

Ryabinkin-Kohut-Staroverov (RKS) theory builds a bridge between wave function theory and density functional theory by using quantities from the former to produce accurate exchange-correlation potentials needed by the latter. In this work, the RKS method is developed and tested alongside Slater atomic orbital basis functions for the first time. To evaluate this approach, full configuration interaction computations in the Slater orbital basis are employed to give quality input to RKS, allowing full correlation to be present along with correct nuclei cusps and asymptotic decay of the wavefunction. SlaterRKS is shown to be an efficient algorithm to arrive at exchange-correlation potentials without unphysical artifacts in moderately-sized basis sets. Furthermore, enforcement of the nuclear cusp conditions will be shown to be vital for the success of the Slater-basis RKS method. Examples of weakly and strongly correlated molecular systems will demonstrate the main features of SlaterRKS.

Crowdsensing Intelligence: Advancing Trustworthy, Intelligent, Interactive, and Cooperative Sensing and Computing for Transportation 5.0

Crowdsensing Intelligence: Advancing Trustworthy, Intelligent, Interactive, and Cooperative Sensing and Computing for Transportation 5.0

Fintech Agents: Technologies and Theories

Many financial technology (fintech) applications have incorporated interactive computer agents to act as mediators between the user and the fintech system. This paper provides a comprehensive review of interactive fintech agents from technological and social science perspectives. First, we explain the general fintech landscape and define interactive fintech agents. Next, we review the major technologies involved in creating fintech: (1) artificial intelligence and machine learning, (2) big data, (3) cloud computing, and (4) blockchain; as well as the specific key technologies enabling the following aspects of interactive fintech agents: (1) intelligence, (2) understanding of users, and (3) manifestation as social actors. Following the technology review, we examine issues and theories related to human-fintech agent interaction in the following areas: (1) agents’ understanding of users, (2) agents’ manifestation as social actors (via embodiment, emotion, and personality), and (3) users’ social interaction with agents. Finally, we suggest directions for future research on fintech agents.

Providing Reproducibility and objective control in computer measurement of fusion reserves

As is known, the main indicators of the stable functioning of fusion mechanisms – the physiological basis of binocular perception – are the fusion reserves (FR), an accurate assessment of which is still problematic. To measure the FR, a small mismatch between the accommodation and vergence systems is introduced and gradually increasing to reach certain critical angles at which the fusion mechanisms cease to function, as judged by the subjective sensations of the subjects reporting the break of the binocular image into two monocular ones. The subjectivity of such assessments of FR, as well as poorly studied dependence of FR on the parameters of test objects and measurement procedures, make it difficult to determine standard values and to create databases on RF. To overcome these shortcomings inherent in traditional methods of measuring RF, at the end of the last century, attempts were made to use computer methods (Rozhkova et al., 1996 ab, 1998). This article presents the results of a critical evaluation of the computer method for measuring FR using the author’s interactive computer program FUZIYA (Bolshakov, Rozhkova, 2013), which provides for the generation of variable test images on a special display designed for the polarization method of separating the left and right channels of test object presentation. The purpose of this study was to evaluate the accuracy and reproducibility of the measurement results, as well as to test the effectiveness of the previously proposed method to programmatically provide objective control of the binocular image break. The data obtained confirm the prospects of the approach used and make it possible to clarify the specific forms of its rational application.

Surface defect detection and classification of steel using an efficient Swin Transformer

Detecting steel-surface defects is a crucial phase in steel manufacturing; however, accurately completing the detection task is challenging. The Swin Transformer, a self-attention-based model, has shown strong performance in the field of computer vision to enhance the adaptability of the Swin Transformer to the task of steel-surface defect detection, and a new network architecture called the LSwin Transformer is proposed in this study. First, in the downsampling process, we propose a convolutional embedding module and an attention patch merging module, which simultaneously strengthen the connections between the feature map channels, reduce the resolution, and increase image information retention. Second, we propose an effective window shift strategy and a convenient computation approach to make a complete defect between patches have more opportunity to obtain interactive computing. Finally, to combine the feature extraction capability of convolutional neural networks with the global dependency building capability of the Swin Transformer, we propose a depth multilayer perceptron module. Numerous experiments were conducted on a steel-surface defect dataset. The results demonstrated that the detection effect of our model outperformed competing methods, with a mean average precision of 81.2 %. In the ablation study, we verified the effectiveness of each module and initialized the parameters of the model through transfer learning to accelerate the convergence of the model. Therefore, the proposed LSwin Transformer has significant potential for detecting steel-surface defects.

La enseñanza de la radiología en los programas docentes integrados

Radiology is a medical discipline, an area of transversal knowledge integrated into any clinical situation. The optimal training of learning knowledge, skills and aptitudes in Radiology in the Degree in Medicine requires the integration of any imaging modality in the different areas of knowledge; from the basic subjects to any clinical subject of the Degree. This article describes the integration of Radiology teaching into the curriculum throughout the Medicine Degree at the University of Girona (UdG), describing the different radiology teaching activities that are taught. The specific activities of the subject «Radiology» are detailed; through workshops, seminars, practices, interactive computer game; and describing the characteristics of the main teaching methodological activity of the UdG, Problem-Based Learning.

PACMHCI - Engineering Interactive Computing Systems, June 2023: Editorial Introduction

Welcome to this issue of the Proceedings of the ACM on Human-Computer Interaction, bringing together contributions from the community on Engineering Interactive Computing Systems (EICS). The EICS track of the PACM-HCI is the primary venue for research contributions at the intersection of Human-Computer Interaction (HCI) and Software Engineering. This year, over the three rounds of submissions, for the issue of PACM-HCI we received 68 valid submissions (out of 90 submissions in total), of which we carefully selected 19 papers, bringing our acceptance rate to 27.9%. The result of this selection process is presented in this issue of the Proceedings of the ACM.

Density Functional Theory Computation and Machine Learning Studies of Interaction between Au3 Clusters and 20 Natural Amino Acid Molecules.

The optimal adsorption sites and the binding energies of neutral Au3 clusters with 20 natural amino acids under the gas phase and water solvation were systematically investigated based on density functional theory (DFT) calculations. The calculation results showed that in the gas phase Au3 tends to bind with N atoms of amino groups in amino acids, except methionine, which tends to bind with Au3 through S atoms. Under water solvation, Au3 clusters tended to bind to N atoms of amino groups and N atoms of side chain amino groups in amino acids. However, methionine and cysteine bind more strongly to the gold atom through the S atom. Based on the binding energy data of Au3 clusters and 20 natural amino acids under water solvation calculated by DFT, a machine learning model (gradient boosted decision tree) was proposed to predict the optimal binding Gibbs free energy (ΔG) of the interaction between Au3 clusters and amino acids. The main factors affecting the strength of the interaction between Au3 and amino acids were uncovered by the feature importance analysis.

Surface Functionalization of Sulflower with Superhalogens Doping to Achieve Robustly Large Nonlinear Optical Response: Interactive Design Computation of New NLO Materials for Modern Electro-Optic Applications

Developing highly effective nonlinear optical (NLO) materials is a cutting-edge field of study. The desirability of promising NLO materials for optoelectronic and electronic applications drove us to investigate the sulflower (C18S9) doped complexes for developing highly efficient NLO materials. A successful computational design technique for superhalogens (BeF3, MgF3, CaF3, CaCl3) doping is employed on sulflower, and eight stable isomers (BeF3@SF-5M, BeF3@SF-9M, MgF3@SF-5M, MgF3@SF-9M, CaF3@SF-5M, CaF3@SF-9M, CaCl3@ SF-5M, CaCl3@SF-9M) are proposed for NLO properties. DFT and TD-DFT simulations confirm the potential use of superhalogen-doped sulflower complexes for NLO response applications by evaluating NLO response properties, photophysical aspects, frontier molecular orbital (FMO), natural bond orbitals (NBO), non-covalent interaction (NCI), vertical ionization energies (VIE), interaction energies (E int), molecular electrostatic potential (MEP) and density of state (DOS) analysis. The Eint (−28.37 to −53.86 kcal/mol) and VIE (7.0-7.4 eV) findings suggest that superhalogens-doped sulflower complexes are thermodynamically stable and show durable interaction among sulflower and doped superhalogens. Superhalogens doping on sulflower effectively shorten the energy gap from 4.46 eV (pure sulflower) to 4.17 eV in CaCl3@SF-5M isomer. Superhalogens doping causes a change in the dipole moment from 0 D of pure sulflower to 12.57 D in the CaCl3@SF-5M isomer. Proficient intermolecular charge transfers between sulflower and doped superhalogens were established by NCI and NBO analyses. UV-Vis investigation revealed that all superhalogen-doped sulflower complexes are adequately transparent in the near-infrared and visible wavelength ranges. Augmentation in polarizability value from 333.86 a.u.−569.98 a.u and in first hyperpolarizability from 0.00 a.u to 6.6 × 104 a.u. is achieved upon superhalogens doping. A striking NLO response (β 0 = 6.6 × 104 a.u) is exhibited by CaCl3@SF-5M isomer. This report provides an efficient superhalogens doping technique for creating highly effective future NLO systems and recommends superhalogens-doped sulflower complexes as ideal entrants for future NLO applications.

Interactive IoT Cloud Deep Learning Model for Research Development in Universities for the Educational Think Tank

The construction of university education think tanks using the interactive service platform enables the sharing of research resources, encourages cross-disciplinary research collaboration, and fosters innovation in education. It also helps to build a stronger relationship between academia and industry by enabling practitioners to participate in research activities. The Internet of Things (IoT) can be used to collect and analyze data from various sources, including sensors and other connected devices, to provide insights into education-related issues. The integration of these technologies in university education thinks tanks can help to enhance the efficiency and effectiveness of research, decision-making, and collaboration processes. Hence, this paper constructed an Interactive IoT Cloud Computing Platform (IIoTCC). With IIoTCC model the innovative idea about research and other ideas are collected and stored in a Cloud environment. Within the environment, information collected is stored in the stacked architecture model with the voting-based model. Through the stacked model, information is processed and evaluated for academic activities. The IoT environment is implemented through IIoTCC for the information process in a deep learning environment for academic-related issues. Simulation analysis expressed that IIoTCC model achieves a higher accuracy rate of 99.34% which is significantly higher than conventional classifiers.

Development and Validation of a Wearable Device to Provide Rich Somatosensory Stimulation for Rehabilitation After Sensorimotor Impairment.

Training sensory discrimination of the skin has the potential to reduce chronic pain due to sensorimotor impairments and increase sensorimotor function. Currently, there is no such device that can systematically provide rich skin stimulation suitable for a training protocol for individuals with amputation or major sensory impairment. This study describes the development and validation of a non-invasive wearable device meant to repeatedly and safely deliver somatosensory stimulations. The development was guided by a structured design control process to ensure the verifiability and validity of the design outcomes. Two sub-systems were designed: 1) a tactile display for touch and vibration sensations, and 2) a set of bands for sliding, pressure, and strain sensations. The device was designed with a versatile structure that allows for its application on different body parts. We designed a device-paired interactive computer program to enable structured sensory training sessions. Validation was performed with 11 individuals with intact limbs whose upper arm tactile sensitivity was measured over 5 training sessions. Tactile discrimination and perception threshold were measured using the standard 2-point discrimination and Semmes-Weinstein monofilament tests, respectively. The results of the monofilament test showed a significant improvement (p = 0.011), but the improvement was not significant for the 2-point discrimination test(p = 0.141). These promising results confirm the potential of the proposed training to increase the sensory acuity in the upper arms of individuals with intact limbs. Further studies will be conducted to determine how to transfer the findings of this work to improve the pain and/or functional rehabilitation in individuals with sensorimotor impairments.

A computer-vision based hand rehabilitation assessment suite

Post-stroke patients very commonly present upper limb deficits, while their rehabilitation comprises regular monitoring and kinematic assessments to evaluate motor recovery. The Box and Block Test (BBT), as well as the Sollerman Hand function Test (SHT), are two of the most used and recommended tools to objectively measure upper limb dexterity, in addition to evaluating the rehabilitation of fine motor skills in patients. However, the tests themselves require the use of very specific equipment, along with the physical attendance of a therapist, making the whole procedure time consuming and clinic dependent. This paper proposes a computer vision hand rehabilitation assessment suite, which stands as a virtual alternative to the real-world scenarios. Our application integrates all the original tests’ guidelines and procedures into an interactive computer vision experience that utilizes bleeding edge technologies such as MediaPipe Hands for hand and finger tracking. This innovative tool requires neither any additional computer peripherals (smart gloves, VR headsets) nor any kind of extra physical equipment (wooden box, blocks), but works instead with just a mid-range PC and a camera. Our system can be deployed in residential spaces via modern 5G/6G or FTTx networks, and the test results can be sent remotely to any physician or rehabilitation expert. Finally, we shortly discuss some technical issues of our approach, as well as present some future directions regarding our tool’s score normalization and feature expansion.

UmetaFlow: an untargeted metabolomics workflow for high-throughput data processing and analysis

Metabolomics experiments generate highly complex datasets, which are time and work-intensive, sometimes even error-prone if inspected manually. Therefore, new methods for automated, fast, reproducible, and accurate data processing and dereplication are required. Here, we present UmetaFlow, a computational workflow for untargeted metabolomics that combines algorithms for data pre-processing, spectral matching, molecular formula and structural predictions, and an integration to the GNPS workflows Feature-Based Molecular Networking and Ion Identity Molecular Networking for downstream analysis. UmetaFlow is implemented as a Snakemake workflow, making it easy to use, scalable, and reproducible. For more interactive computing, visualization, as well as development, the workflow is also implemented in Jupyter notebooks using the Python programming language and a set of Python bindings to the OpenMS algorithms (pyOpenMS). Finally, UmetaFlow is also offered as a web-based Graphical User Interface for parameter optimization and processing of smaller-sized datasets. UmetaFlow was validated with in-house LC–MS/MS datasets of actinomycetes producing known secondary metabolites, as well as commercial standards, and it detected all expected features and accurately annotated 76% of the molecular formulas and 65% of the structures. As a more generic validation, the publicly available MTBLS733 and MTBLS736 datasets were used for benchmarking, and UmetaFlow detected more than 90% of all ground truth features and performed exceptionally well in quantification and discriminating marker selection. We anticipate that UmetaFlow will provide a useful platform for the interpretation of large metabolomics datasets.Graphical

“Reject the Offer”: The Asymmetric Impact of Defense Attorneys’ Plea Recommendations

In two studies, we examined the impact of defense attorney recommendation on defendant plea decision-making. Community members and college students participated in a 2 (guilt status: innocent or guilty) × 2 (defense attorney recommendation: accept or reject offer) between-subjects factorial design study. The plea scenario was conveyed via an interactive computer simulation. In both studies (Study 1, n = 106; Study 2, n = 282), guilty participants were more likely to plead guilty than innocent participants. In Study 2, participants advised to accept the plea were more likely to plead guilty than those advised to reject the plea. Furthermore, being advised to reject the plea resulted in larger changes in willingness to accept a plea (WTAP) than being advised to accept the plea. This asymmetric effect was driven by those participants who were initially inclined to plead guilty but then received advice inconsistent with that inclination.

Topos of Noise

This paper focuses on the significance of the concept of noise for cognition and computation. The concept of noise was massively transformed in the twentieth century with the advent of information theory, cybernetics, and computer science, all of which provide formal accounts of information and noise centrally concerned with contingency. We show how the concept has changed from these classical formulations, through developments in mathematics (topology and topos theory), computing (interactive computing and univalent foundations), and cognitive science (predictive processing and cognitive morphodynamics). Ultimately it argues for the central importance of noise not only within a topological conception of cognition and computation, but also in the transcendental-empirical torsion of image schemata and the social interactive elaboration of freedom.

Penerapan Metode MOOSRA dan ROC dalam Penentuan Guru Terbaik

The best teacher is a teacher who is given appreciation because he has a high achievement value. There are several specific criteria in selecting the best teacher, namely in terms of achievement, skills possessed, morals/manners, and discipline. To improve quality in the world of education, of course, a teacher is needed who will interact directly with students in the learning process which can indirectly improve the quality of education. With the interaction in the learning process, it is hoped that it will become a resource in improving the quality of education. There is also something the government is doing that is in a way to advance education, namely by empowering teachers and giving an award, especially for those who are entitled to get the title of the best teacher with achievements. Based on the results of interviews and research related to SMK Negeri 2 Medan, in determining the best teacher the assessment is still in a subjective way. This is based only on the opinion of each teacher and does not start with certain criteria, this will affect social events because the method used is not in an objective way and ends in an unfair feeling caused by subjective methods among fellow teachers who teach at the school. Therefore, it is recommended that schools must determine and agree on certain criteria in determining outstanding teachers, even though the assessment in the final process is still carried out by voting from those who have voting rights in determining the outstanding/best teachers, which of course is also carried out by teachers. The system for determining the best teacher is always a problem every year because it can create injustice among fellow teachers. Therefore, to facilitate and eliminate this unfair attitude, a decision support system (SPK) is needed which can facilitate the determination of the best teacher at SMK Negeri 2 Medan. A decision support system is an interactive computer system that can assist decision making by utilizing existing data to solve unstructured and semi-structured problems. In this SPK there are several methods, one of which is the Moosra Method (Multiobjective Optimization on the Basis of Simple Ratio Analysis) and the ROC (Rank Order Centroid) Method. The result of ROC and MOOSRA method calculation showed that Halimah (A10) obtained the highest final preference value of 14.599, making her selected as the best teacher.