Design Of Systems Research Articles

E-Gaze: Gaze Estimation With Event Camera.

Near-eye gaze estimation is a task that maps the recording of an eye captured by an adjacent camera to the direction of a person's gaze in space. In contrast to frame-based cameras, event cameras are characterized by high sensing rates, low latency, sparse asynchronous data outputs, and high dynamic range, which are well suited for recording the fast eye movements. However, algorithms and system designs that operate on frame-based cameras are not applicable to event-based data, due to the natural differences in the data characteristics. In this work, we study the pattern of near-eye event-based data streams and extract eye features to estimate gaze. First, by analyzing eye parts and movements, and harnessing the polar, spatial, and temporal distribution of the events, we introduce a real-time pipeline to extract pupil features. Second, we present a recurrent neural network with a proposed coordinate-to-angle loss function to accurately estimate gaze from pupil feature sequence. We demonstrated that our system achieves accurate real-time estimation with angular accuracy of 0.46 ° and update rates of 950 Hz, thus opening up avenues for novel applications. To our knowledge, this is the first system that operates only on event-based data to perform gaze estimation.

Human Versus Machine Intelligence: Assessing Natural Language Generation Models Through Complex Systems Theory.

The introduction of Transformer architectures - with the self-attention mechanism - in automatic Natural Language Generation (NLG) is a breakthrough in solving general task-oriented problems, such as the simple production of long text excerpts that resemble ones written by humans. While the performance of GPT-X architectures is there for all to see, many efforts are underway to penetrate the secrets of these black-boxes in terms of intelligent information processing whose output statistical distributions resemble that of natural language. In this work, through the complexity science framework, a comparative study of the stochastic processes underlying the texts produced by the English version of GPT-2 with respect to texts produced by human beings, notably novels in English and programming codes, is offered. The investigation, of a methodological nature, consists first of all of an analysis phase in which the Multifractal Detrended Fluctuation Analysis and the Recurrence Quantification Analysis - together with Zipf's law and approximate entropy - are adopted to characterize long-term correlations, regularities and recurrences in human and machine-produced texts. Results show several peculiarities and trends in terms of long-range correlations and recurrences in the last case. The synthesis phase, on the other hand, uses the complexity measures to build synthetic text descriptors - hence a suitable text embedding - which serve to constitute the features for feeding a machine learning system designed to operate feature selection through an evolutionary technique. Using multivariate analysis, it is then shown the grouping tendency of the three analyzed text types, allowing to place GTP-2 texts in between natural language texts and computer codes. Similarly, the classification task demonstrates that, given the high accuracy obtained in the automatic discrimination of text classes, the proposed set of complexity measures is highly informative. These interesting results allow us to add another piece to the theoretical understanding of the surprising results obtained by NLG systems based on deep learning and let us to improve the design of new informetrics or text mining systems for text classification, fake news detection, or even plagiarism detection.

Reliability analysis of GAN based transmit modules for active array antenna of phased array radar

Reliability is one of the most important requirements in our day to day life considering consistency, availability and failure free performance of the product over it’s define mission time. As complexity of the system increases, design for reliable systems is a big challenge. The objective of the reliability prediction analysis is to evaluate the predicted reliability of the active transmit receive modules (TRMs) under specified operating conditions, and to demonstrate that the predicted reliability meets the requirements, also to identify any parts present in the design which leads to higher failure rates. The research shows reliability of generative adversarial network (GAN) based TRMs covering from design to finalization of components as early as practicable in today's short product lifecycles. Using the reliability prediction process, we describe a method for providing design engineers with reliability feedback on their decisions. Using a conventional reliability prediction model, the Telcordia (Bellcore) parts stress prediction model, and some standard rules of thumb, we describe an initial implementation of this technique. It provides systematic identification of likely modes of failure, possible effects of each failure, and the criticality of each failure with regard to reliability, system readiness, mission success, and demand for maintenance/logistic support.

Sparse Structure Design for Stochastic Linear Systems via a Linear Matrix Inequality Approach

Sparse Structure Design for Stochastic Linear Systems via a Linear Matrix Inequality Approach

Regulatory sandboxes for trustworthy artificial intelligence – global and Latin American experiences

ABSTRACT This paper explores how regulatory sandboxes can be used to promote the development of trustworthy artificial intelligence (AI) systems. The analysis focus on the experiences of Data Protection Authorities (DPAs) who have been experimenting with sandboxes to foster the implementation of privacy by design principles in AI systems. Throughout bibliographic research, this study (i) highlights privacy-related elements on international AI regulatory frameworks; (ii) explores the concept of privacy by design (PbD) and some of its strategies, patterns and techniques, such as Privacy Enhancing Technologies (PETs); (iii) reflects upon the impact of regulatory sandboxes; and (iv) analyses how regulatory sandboxes are being discussed in the context of AI regulatory frameworks. While this study brings global perspective on regulatory sandboxes, it also does relevant analysis in the Latin American context by presenting different stages of development of initiatives in the region. One of the main findings of this paper is that literature currently lacks an analysis of how privacy by design could be used in the context of AI systems design and governance. It also suggests that regulatory sandboxes may be able to integrate PbD principles to foster the development of trustworthy AI, although further research would be needed on that matter.

What distance learning students want from an AI Digital Assistant

With the release of Generative AI systems such as ChatGPT, an increasing interest in using Artificial Intelligence (AI) has been observed across domains, including higher education. While emerging statistics show the popularity of using AI amongst undergraduate students, little is yet known about students’ perceptions regarding AI including self-reported benefits and concerns from their actual usage, in particular in distance learning contexts. Using a two-step, mixed-methods approach, we examined the perceptions of ten online and distance learning students from diverse disciplines regarding the design of a hypothetical AI Digital Assistant (AIDA). In the first step, we captured students’ perceptions via interviews, while the second step supported the triangulation of data by enabling students to share, compare, and contrast perceptions with those of peers. All participants agreed on the usefulness of such an AI tool while studying and reported benefits from using it for real-time assistance and query resolution, support for academic tasks, personalization and accessibility, together with emotional and social support. Students concerns related to the ethical and social implications of implementing AIDA, data privacy and data use, operational challenges, academic integrity and misuse, and the future of education. Implications for the design of AI-tailored systems are also discussed.

An experimental study on low-temperature plasma tissue ablation and its thermal effect

Low-temperature plasma ablation has been recently used for minimally invasive surgeries. However, more research is still needed on its generation process during tissue ablation and the underlying mechanism of tissue thermal damage. In this paper, high-speed camera footage, voltage–current signal collection, temperature analysis, and histological analysis were used to investigate the dynamic process of plasma tissue ablation and its thermal effect of dual-needle electrodes immersed in normal saline, which were driven by a high-frequency DC power supply with an output voltage ranging from 220 V to 320 V and a squire wave of 100 kHz. Microbubbles occurred around the ground electrode and merged to form a vapor layer that could completely cover the ground electrode. Plasma capable of ablating tissue would occur in the vapor layer between the ground electrode and tissue. The effect of electrical parameters on plasma generation and its thermal effect are analyzed by statistical results. The experimental results indicated that the voltage applied to the electrodes significantly influenced both the generation and stability of plasma, as well as the heat generation and tissue damage around the electrodes. Furthermore, under the same voltage, the existence of biological tissue promotes the formation of a vapor layer around the electrode, thereby facilitating the generation and stability of plasma. Notably, the temperature rise around the ground electrode is much higher than that around the powered electrode. These results have direct application to the design of plasma tissue ablation systems, which could achieve tissue ablation effects with minimal thermal damage.

Analysis of the Covid-19 pandemic on preferences of transport modes

The Covid-19 pandemic has affected the entire world and changed many aspects of daily life, including transportation behaviour and preferences. This study examines the situation of transportation behaviour and preferences before and after the Covid-19 pandemic process through a survey study. A total of 471 people participated in the survey, and 30 questions were posed to participants regarding transportation modes preference, daily usage habits, public transportation usage rate, income status, perceived risk level of transportation systems, preferences before and after the pandemic process, and more. The answers were classified, evaluated and statistically analysed. The results showed that users were significantly affected by the Covid-19 process and changed their transportation mode preferences. The use of buses in urban journeys decreased, and the use of private vehicles significantly increased after the Covid-19 process. Hygiene was the key factor in travel, followed by the vehicle occupancy rate, ventilation, fare and travel time factors. The perceived risk levels of public transportation systems were ranked as metrobus, minibus (paratransit), bus, metro, tram and ferry. The study suggests that future transportation system designs should consider user preferences, as well as changes in education and working conditions, and pandemic conditions.

Studying Cation Exchange in {Cr7Co} Pseudorotaxanes: Preparatory Studies for Making Hybrid Molecular Machines.

In the design of dynamic supramolecular systems used in molecular machines, it is important to understand the binding preferences between the macrocycle and stations along the thread. Here, we apply 1H NMR spectroscopy to investigate the relative stabilities of a series of linear alkylammonium templated pseudorotaxanes with the general formula [H2NRR'][Cr7CoF8(O2CCH2 tBu)16] by exchanging the cation in solution. Our results show that the pseudorotaxanes are able to exchange threads via a dissociative mechanism. The position of equilibrium is dependent upon the ammonium cation and solvent used. Short chain primary ammonium cations are shown to be far less favourable macrocycle stations than secondary ammonium cations. Collision-induced dissociation mass spectrometry (CID-MS) has been used to look at disassembly of the pseudorotaxanes in a solvent-free environment and stability trends compared to those in acetone-d6. The energy needed to induce 50 % of the precursor ion loss (E50) is used and shows a similar trend to the equilibria measured by NMR. The relative stabilities of these hybrid inorganic-organic pseudo-rotaxanes are different to those of host-guest compounds involving crown ethers and this may be valuable for the design of molecular machines.

State Control Design of Ostensible Metzler Linear Systems with Unsigned Input Parameters

This paper deals with the design of a complete state control for input unsigned, rank deficient matrix parameters of a linear system with system dynamics defined by ostensible structures of Metzler matrices. The proposed solution is based on the principle of diagonal stabilization of positive systems and uses a stabilizing additional component over the decomposition of the Metzler matrix in solving the incomplete internal positivity of such linear system structures. The novelty of the proposed approach is the unified representation of the parametric constraints of the Metzler matrix and the structurally constrained system inputs using linear matrix inequalities, which guarantees that the closed-loop system will be asymptotically stable. Despite the complexity of the constraint conditions on this class of linear continuous systems, the design conditions are formulated using sharp linear matrix inequalities only. A detailed design process is presented using a system-linearized mathematical model to verify the superiority and practicality of the proposed method.

Charge Transport Approaches in Photocatalytic Supramolecular Systems Composing of Semiconductor and Molecular Metal Complex for CO2 Reduction.

The design of photocatalytic supramolecular systems composing of semiconductors and molecular metal complexes for CO2 reduction has attracted increasing attention. The supramolecular system combines the structural merits of semiconductors and metal complexes, where the semiconductor harvests light and undertakes the oxidative site, while the metal complex provides activity for CO2 reduction. The intermolecular charge transfer plays crucial role in ensuring photocatalytic performance. Here, we review the progress of photocatalytic supramolecular systems in reduction of CO2 and highlight the interfacial charge transfer pathways, as well as their state-of-the-art characterization methods. The remaining challenges and prospects for further design of supramolecular photocatalysts are also presented.

On the optimal design of peer monitoring systems in capital budgeting

AbstractThis paper considers peer monitoring in a capital budgeting setting with information asymmetry between principal and agents. The paper demonstrates in a two‐agent, two‐project setting that the principal can have each agent reveal their private information on the other agent's project, at an arbitrarily low cost. Next, an examination of monitoring resource allocations is made. Specifically, a comparison is made of broad monitoring, which spreads monitoring resources equally across agents' projects, and focused monitoring, which applies all monitoring resources to a single agent's project. Focused monitoring is preferred within an intermediate range of profitability, above which broad monitoring is preferred and below which neither is preferred. If project profitability is heterogeneous and focused monitoring is preferred, the more profitable project receives the focus. Both of these results occur because there is a threshold of monitoring resources that must be deployed for monitoring to provide any benefit, and the threshold is higher (more resources must be deployed) for lower profitability projects. That is, even if all monitoring resources are devoted to a low profitability project, they may provide no benefit to the principal. A discussion of how peer monitoring can be engineered by the firm is included.

MATHEMATICAL MODELING OF THE AUTONOMOUS HEAT SUPPLY SYSTEM WITH TUBULAR GAS HEATERS IN BUILDING STRUCTURES WHEN OPERATING IN THE CONDENSATION MODE

Problem statement. The application of modern autonomous heat supply systems is one of the directions of reducing the consumption of natural energy resources. There are many different autonomous systems of heat supply of objects. One of the variants of such systems is the system with tubе gas heaters. A tube gas heater consists of a gas burner, a radiating tube and a fan. One of the technical solutions for such heat supply systems is a tubular heater located inside the building structure. Increase of the efficiency of gas equipment can be achieved by operating this equipment in the condensation mode. Therefore, the operation of tubular gas heaters in building structures in the condensation mode is quite interesting in terms of increasing the efficiency of utilisation of the thermal potential of gaseous fuel and ensuring its saving. For research and practical design of autonomous heat supply systems with gas tube heaters in building structures with regard to the condensation mode of operation it is essential to develop a mathematical model for calculating the thermal and hydraulic modes of the system. The purpose of the article is to develop a mathematical model of an autonomous heat supply system with tubular gas heaters in building structures when operating in the condensation mode. Conclusion. The mathematical model of hydraulic and thermal modes of autonomous heat supply system with tubular gas heaters in building structures when operating in the condensation mode was developed. It is presented in the form of differential equations. The model is based on the equations of conservation of mass, motion and energy for the gas-air mixture inside the canal in two-phase flow, the equation of heat transfer inside the building structure, the equation of heat transfer from the external surface of the heater to the environment. The mathematical model of hydraulic and thermal modes of autonomous heat supply system with tubular gas heaters in building structures when operating in the condensation mode will be used to calculate and design such systems.

A review on the magnetorheological materials and applications

Magnetorheological materials refer to field-response smart materials whose properties are controllable with a magnetic field, including fluid, grease, elastomer, and gel. The unique magnetorheological effect exhibited by these smart materials is a physical phenomenon where physics and engineering intersect and has extensive application prospects in modern machinery. In electro-mechanical systems, magnetorheological materials offer a superior design method for mechanical devices used in the fields of transmission, damping, and braking. It is important to control the magnetorheological materials for advancing the design philosophy of modern electro-mechanical devices. Hence, this paper presents a recent progressive review on the fundamentals of magnetorheological materials and numerous applications. Firstly, an introduction to the magnetorheological effect and different types of magnetorheological materials are presented in this review. Then, the individual and coupled effects of sedimentation, temperature, and magnetic field on magnetorheological materials are discussed. Finally, magnetorheological materials-based devices have been extensively reviewed, including actuator, clutch, damper, brake, pump, valve, and robot, thus aiming to provide useful information for facilitating the design of complex electro-mechanical systems.

De novo design of proteins housing excitonically coupled chlorophyll special pairs.

Natural photosystems couple light harvesting to charge separation using a 'special pair' of chlorophyll molecules that accepts excitation energy from the antenna and initiates an electron-transfer cascade. To investigate the photophysics of special pairs independently of the complexities of native photosynthetic proteins, and as a first step toward creating synthetic photosystems for new energy conversion technologies, we designed C2-symmetric proteins that hold two chlorophyll molecules in closely juxtaposed arrangements. X-ray crystallography confirmed that one designed protein binds two chlorophylls in the same orientation as native special pairs, whereas a second designed protein positions them in a previously unseen geometry. Spectroscopy revealed that the chlorophylls are excitonically coupled, and fluorescence lifetime imaging demonstrated energy transfer. The cryo-electron microscopy structure of a designed 24-chlorophyll octahedral nanocage with a special pair on each edge closely matched the design model. The results suggest that the de novo design of artificial photosynthetic systems is within reach of current computational methods.

Recent Advances in the Understanding of Stress Resistance Mechanisms in Probiotics: Relevance for the Design of Functional Food Systems.

In recent years, more and more scientific community, food producers, and food industry show increased interest in functional foods containing probiotics, which is a big challenge. The consumption of probiotics in the context of a balanced diet through the consumption of functional foods or through the intake of pharmaceutical preparations has proven to contribute to the improvement of human health, even contributing to the prevention of diseases. In order for probiotics to be considered suitable for consumption, they must contain a minimum concentration of viable cells, namely, at least 107 colony forming units of beneficial microbes per gram. Ensuring the viability of bacterial cells until the moment of consumption is the overriding priority of functional probiotic food manufacturers. Probiotic bacteria are subject to stress conditions not only during food manufacturing but also during gastrointestinal passage, which limit or even compromise their functionality. This paper first examines all the stressful conditions faced by probiotic cells in their production stages and related to the conditions present in the bioreactor fermentation and drying processes as well as factors related to the food matrix and storage. The stress situations faced by probiotic microorganisms during the gastrointestinal transit especially during stomach and intestinal residence are also analyzed. In order to understand the adaptation mechanisms of probiotic bacteria to gastrointestinal stress, intrinsic and adaptive mechanisms identified in probiotic strains in response to acid stress and to bile and bile acid stress are analyzed. In addition, improvement strategies for multiple stress tolerance of lactic acid bacteria through directions dealing with stress, accumulation of metabolites, use of protectants, and regulation of technological parameters are examined. Finally, the definition of postbiotics, inanimate microorganisms and/or their components conferring health benefits, is also introduced. Postbiotics include cell lysates, enzymes, and cell wall fragments derived from probiotic bacteria and may represent an alternative to the use of probiotics, when they do not tolerate stressful conditions.

An Experimental Evaluation of the APR1000 Core Flow Distribution Using a 1/5 Scale Model

The experimental data of core flow distribution are indispensable for obtaining licensing and facilitating the design of fluid systems of nuclear reactors. In this study, an Advanced power reactor Core flow and Pressure (ACOP) test facility was established to experimentally simulate the internal flow of the Advanced Power Reactor 1000 (APR1000) on a reduced length scale of 1/5. The core region was simulated by using 177 core simulators representing the fuel assemblies of the APR1000. The APR1000 flow distributions were synthetically identified by accurately measured parameters: the core inlet flow rate and outlet pressure under the four-pump balanced and unbalanced flow conditions. The overall inlet flow rates ranged from 87.7% to 112.0% relative to the averaged flow rate. Here, we scrutinize the flow distributions considering the flow conditions and internal structures and briefly describe the applied scaling method and design concept of the test facility.

An image encryption scheme without additional key transmission based on an N-dimensional closed-loop coupled triangular wave model

Currently, many image encryption schemes either require additional secure channels for key transmission or employ a key that exhibits a lack of correlation with the plaintext, thereby reducing the security of the algorithm. This study proposes a novel image encryption scheme to address this issue. A new N-dimensional closed-loop coupled triangular wave model is developed to overcome the limitations of the sine function in chaotic systems while reducing the difficulty of the chaotic system design. Experimental analysis demonstrates that the generated chaotic systems exhibit complex chaotic behaviors and outperform other chaotic systems designed using the sine function. Specifically, we utilize difference extension technology to embed key information into the plaintext image and design a scrambling and diffusion algorithm based on Latin rectangles to encrypt the remaining pixel matrix without key information. Finally, the pixel matrix containing the key information is concealed to obtain the final ciphertext image. Simulation analysis and security evaluation demonstrate that the proposed algorithm outperforms the encryption performance and security of several advanced image encryption algorithms.

CHATTER MITIGATION IN REAMING: EXPLORING EFFECTIVE TOOL HOLDER DESIGN

Reaming is a crucial technology in finishing operations, demanding high stability in the machining process for optimal results. The clamping system significantly influences the dynamic properties of the system tool – clamping - machine and is key in mitigating chatter. The introduction of new designs in clamping exchangeable reaming heads presents several challenges, particularly in terms of vibration suppression. This study explores various constructions of clamping bars, examining their dynamic properties in both static conditions and during machining. Through these evaluations, the research aims to understand how different designs impact the stability and effectiveness of reaming operations. The measured data from these experiments reveal how the construction of the holder influences machining process stability, providing insights into optimizing clamping system designs for improved reaming performance. the outcomes of this study contribute to the development of more effective and efficient clamping systems for finishing operations.

Empirical models for calculating soil wetting patterns under surface drip irrigation systems: A comprehensive analysis

AbstractAccurate estimation of the surface wetted radius (R) and vertical wetted depth (Z) of wetting patterns in drip irrigation systems is crucial for ensuring that the designs of such systems are effective. This study compared 14 empirical models for estimating drip irrigation wetting patterns by assessing their accuracy using published measurement data and HYDRUS‐2D/3D simulations. The technique for order of preference by similarity to the ideal solution (TOPSIS) was employed to comprehensively rank the models. The results indicate that the empirical model proposed by Fan et al. (2023) (FY) exhibited the highest accuracy when the estimations of R and measured and simulated values were compared, with mean absolute error (MAE), root mean square error (RMSE), Nash–Sutcliffe modelling efficiency (NSE), and percent bias (PB) values of 2.2 cm, 3.4 cm, 0.79, and −7.1% and 5.2 cm, 7.0 cm, 0.50, and −14.1%, respectively. The empirical model proposed by Amin and Ekhmaj (2006) (AE) demonstrated the highest accuracy when the estimations of Z were compared with measured and simulated values, with MAE, RMSE, NSE and PB values of 1.7 cm, 2.0 cm, 0.95 and 4.15% and 4.4 cm, 5.9 cm, 0.82 and 4.7%, respectively. The comprehensive rankings of available models in the present study indicate that the FY model is the most universally applicable, followed by the Li et al. (2022) (LY) model, with comprehensive indices of 0.960 and 0.936, respectively. This research can aid in the selection of universally applicable, reliable and straightforward empirical models for estimating wetting patterns in drip irrigation systems.