Specific Objectives Research Articles

RESMatch: Referring expression segmentation in a semi-supervised manner

Referring Expression segmentation (RES), a task that involves localizing specific instance-level objects on the basis of free-form linguistic descriptions, has emerged as a crucial frontier in human–AI interactions. It demands an intricate understanding of both the visual and textual contexts, and often requires extensive training data. This paper introduces RESMatch, the first semi-supervised learning (SSL) approach for RES aimed at reducing reliance on exhaustive data annotation. Moreover, our proposed RESMatch can leverage the abundance of image–text paired data available in the current era of training large models, resulting in an improved RES task performance without the need for costly semantic annotation, as evidenced by our experimental results. Moreover, although existing SSL techniques are effective in image segmentation, we find that they fall short in RES. Facing challenges such as the comprehension of free-form linguistic descriptions and the variability in object attributes, RESMatch introduces a trifecta of adaptations: revised strong perturbation, text augmentation, and adjustments for pseudolabel quality and strong–weak supervision. RESMatch has demonstrated its effectiveness by achieving state-of-the-art (SOTA) results in various experimental settings. This pioneering work lays the groundwork for future research in semi-supervised learning for referring expression segmentation.

Real-Time Environmental Contour Construction Using 3D LiDAR and Image Recognition with Object Removal

In recent years, due to the significant advancements in hardware sensors and software technologies, 3D environmental point cloud modeling has gradually been applied in the automation industry, autonomous vehicles, and construction engineering. With the high-precision measurements of 3D LiDAR, its point clouds can clearly reflect the geometric structure and features of the environment, thus enabling the creation of high-density 3D environmental point cloud models. However, due to the enormous quantity of high-density 3D point clouds, storing and processing these 3D data requires a considerable amount of memory and computing time. In light of this, this paper proposes a real-time 3D point cloud environmental contour modeling technique. The study uses the point cloud distribution from the 3D LiDAR body frame point cloud to establish structured edge features, thereby creating a 3D environmental contour point cloud map. Additionally, unstable objects such as vehicles will appear during the mapping process; these specific objects will be regarded as not part of the stable environmental model in this study. To address this issue, the study will further remove these objects from the 3D point cloud through image recognition and LiDAR heterogeneous matching, resulting in a higher quality 3D environmental contour point cloud map. This 3D environmental contour point cloud not only retains the recognizability of the environmental structure but also solves the problems of massive data storage and processing. Moreover, the method proposed in this study can achieve real-time realization without requiring the 3D point cloud to be organized in a structured order, making it applicable to unorganized 3D point cloud LiDAR sensors. Finally, the feasibility of the proposed method in practical applications is also verified through actual experimental data.

Image quality safety model for the safety of the intended functionality in highly automated agricultural machines

Achieving safe and reliable environmental perception is crucial for the success of highly automated or even autonomous agricultural machinery. However, developing such a system is challenging due to the inherent limitations of perception sensors. In certain conditions, these sensors may fail to capture accurate data, leading to erroneous perceptions of the environment and potentially compromising safety. Monitoring the functional insufficiencies of the measurement data is crucial for ensuring the safety and reliability of perception systems.This article introduces ISO standards, which provide guidelines for ensuring functional safety in highly automated mobile machines and vehicles. It also proposes an Image Quality Safety Model (IQSM) for monitoring the safety of the intended functionality in perception systems. The IQSM estimates the confidence level with which a camera can safely perform a specific object detection task. If the confidence level falls below a predefined threshold, the IQSM can trigger actions, alert operators, and prevent potential safety hazards. The IQSM exhibits remarkable performance, achieving a validation accuracy of about 90%, demonstrating its ability to effectively distinguish the safety of the intended functionality under a variety of image quality conditions.

Critical Elements and Theoretical Logic of Horizontal Transfer Payment System for Eco-Compensation: A Study Based on Grounded Theory

In recent years, how to coordinate the sustainable production and life of human society with the protection of ecological environment has become particularly important. This paper reviewed and analyzed the existing Chinese and English literature on Horizontal transfer payment system for eco-compensation (or hereinafter referred to as ECITPS), based on which this paper applied Grounded Theory to study the critical elements and theoretical logic of the System, exploring its formation process and logical procedure, and constructing a theoretical model of this System. It was found that the theoretical model of eco-compensation Horizontal transfer payment system is mainly divided into three stages, namely, the early, middle and late stages. Moreover, the logic of the ECITPS as a whole was the validation of PDCA Deming Cycle Theory, while the previous research on Horizontal transfer payment for eco-compensation was more focused on the specific object, with a lack of the overall macro understand of the theoretical framework for the system. Therefore, this paper assisted to promote the improvement of the ECITPS from the macro theoretical framework, and provided a reference idea for the development of the transfer payment field in the future period.

Enhancing DF-GAN for Text-to-Image Synthesis: Improved Text-Encoding and Network Structure

Enhancing DF-GAN for Text-to-Image Synthesis: Improved Text-Encoding and Network Structure

Medico-Legal Applications of the Human Microbiome and Critical Issues Due to Environmental Transfer: A Review

Microbiome has recently seen an increase in its forensic applications. It could be employed to identify a suspect when DNA is not available; it can be used to establish postmortem interval (PMI). Furthermore, it could prove to be fundamental in cases of sexual assault. One of the most interesting aspects to study is how microbiomes are transferred. The aim of this review is to analyze the existing literature focusing on the potential transfer of microbiome from humans to environment. Searches on PubMed, Scopus, and Web of Science identified a total of 348 articles. Furthermore, from the bibliographies of the included articles, an additional publication was selected, in accordance with the established inclusion and exclusion criteria. This study has shown the potential of utilizing microbiomes as trace evidence, particularly in connecting individuals to specific environments or objects. However, the variability and dynamics of microbial transfer and persistence need to be carefully addressed.

Spatial/Temporal Locality-Based Load-sharing in Speculative Discrete Event Simulation on Multi-core Machines

Shared-memory multi-processor/multi-core machines have become a reference for many application contexts. In particular, the recent literature on speculative parallel discrete event simulation has reshuffled the architectural organization of simulation systems in order to deeply exploit the main features of this type of machine. A core aspect dealt with has been the full sharing of the workload at the level of individual simulation events, which enables keeping the rollback incidence minimal. However, making each worker thread continuously switch its execution between events destined to different simulation objects does not favor locality. This problem appears even more evident in the case of Non-Uniform-Memory-Access (NUMA) machines, in which memory accesses generating a cache miss to be served by a far NUMA node give rise to both higher latency and higher traffic at the level of the NUMA interconnection. In this article, we propose a workload-sharing algorithm in which the worker threads can have short-term binding with specific simulation objects to favor spatial locality. The new bindings—carried out when a thread decides to switch its execution to other simulation objects—are based on both (a) the timeline according to which the object states have passed through the caching hierarchy and (b) the (dynamic) placement of objects within the NUMA architecture. At the same time, our solution still enables the worker threads to focus their activities on the events to be processed whose timestamps are closer to the simulation commit horizon—hence, we exploit temporal locality along virtual time and keep the rollback incidence minimal. In our design, we exploit lock-free constructs to support scalable thread synchronization while accessing the shared event pool. Furthermore, we exploit a multi-view approach of the event pool content, which additionally favors local accesses to the parts of the event pool that are currently relevant for the thread activity. Our solution has been released as an integration within the USE (Ultimate-Share-Everything) open-source speculative simulation platform available to the community. Furthermore, in this article we report the results of an experimental study that shows the effectiveness of our proposal.

A salient feature establishment tactic for cassava disease recognition

Accurate classification of cassava disease, particularly in field scenarios, relies on object semantic localization to identify and precisely locate specific objects within an image based on their semantic meaning, thereby enabling targeted classification while suppressing irrelevant noise and focusing on key semantic features. The advancement of deep convolutional neural networks (CNNs) paved the way for identifying cassava diseases by leveraging salient semantic features and promising high returns. This study proposes an approach that incorporates three innovative elements to refine feature representation for cassava disease classification. First, a mutualattention method is introduced to highlight semantic features and suppress irrelevant background features in the feature maps. Second, instance batch normalization (IBN) was employed after the residual unit to construct salient semantic features using the mutualattention method, representing high-quality semantic features in the foreground. Finally, the RSigELUD activation method replaced the conventional ReLU activation, enhancing the nonlinear mapping capacity of the proposed neural network and further improving fine-grained leaf disease classification performance. This approach significantly aided in distinguishing subtle disease manifestations in cassava leaves. The proposed neural network, MAIRNet-101 (Mutualattention IBN RSigELUD Neural Network), achieved an accuracy of 95.30 % and an F1-score of 0.9531, outperforming EfficientNet-B5 and RepVGG-B3g4. To evaluate the generalization capability of MAIRNet, the FGVC-Aircraft dataset was used to train MAIRNet-50, which achieved an accuracy of 83.64 %. These results suggest that the proposed algorithm is well suited for cassava leaf disease classification applications and offers a robust solution for advancing agricultural technology.

On some features of diurnal dynamics of solonchak emissivity in summer

ABSTRACT Widely represented in many arid regions of the world, dry marshes pose a potential threat to the adjacent areas because of soil salinization caused by wind transfer (for long distances) of toxic mineral salts from the dried surface. For environmental monitoring of such soils, remote microwave sensing methods are used. In this work, we study at a 2.3 cm wavelength the summer diurnal dynamics of microwave radiation of sodic solonchak formed on the dried bottom of a hypersaline lake. It has been established that the study indicator (in the centimetre range) depends on the cumulative changes in temperature, moisture and salinity of soils. With rise in soil temperature, intensive evaporation and topsoil drying, a salt crust and the underlying layer with less moisture (accompanied by microwave radiation interference on the layered structure of solonchak) can be formed. In the experiment, a daily variation in the brightness temperature of the study object (a specific object) by 25 K occurred with change in thermodynamic temperature of the skin layer by 10 K.

FuzzAGG: A Fuzzing-Driven Attack Graph Generation Framework for Industrial Robot Systems

As industrial robot systems (IRS) are increasingly utilized in smart factories, their information security issues have become particularly critical. Attack graphs, an essential system-level risk modeling technique, traditionally rely on predefined risk attributes and exploitation rules for their generation. However, this approach fails to meet the needs for attack graph generation and analysis in environments with missing risk data. To address this issue, this paper proposes a fuzzing-driven attack graph generation framework, FuzzAGG. This framework aims to provide an efficient and accurate method for generating attack graphs under conditions of incomplete risk data, thereby supporting information security analysis and risk assessment of IRS. In this paper, a risk data model (RDM) is constructed using the Meta Attack Language to achieve a structured description of the risk data of IRS. A fuzzing test case generation algorithm based on the MU-SeqGAN model is proposed, which can generate test cases suitable for the state machines of IRS and map them to specific Risk Data Model Objects (RDMOs). Additionally, a conversion unit is designed to integrate all RDMOs into a risk description file, which is then used by the generation unit to construct a graphical attack graph. In performance tests, FuzzAGG is able to achieve automated construction of IRS attack graphs containing 1000 state nodes in 42min and maintain 88% risk coverage. Taking the IRS of a PCB automated production line the effectiveness of the FuzzAGG framework is validated. The results demonstrate that FuzzAGG can automatically generate and validate an attack graph containing 184 attribute nodes and atomic attack nodes in 8min with high operational efficiency, proving the practicality and reliability of this method in automated attack graph generation.

Persistent Luminescence for Night‐Time Individual Identification Based on Quantum Tunneling

AbstractNight‐time individual identification requires recognizing a specific object from a bunch of homogeneous entities through night‐vision devices. It will facilitate more effective coordinated actions in night‐time disaster rescue or enforcement actions. In this work, the near infrared (NIR) persistent luminescent materials are proposed as the technology solution, which can emit the non‐visible photons continuously for hours without the external excitation. In a magnetoplumbite‐type structure, Cr3+ ions are incorporated to realize NIR emissions. By co‐doping lanthanide ions and constitutional modulation, the afterglow signal can be clearly traced under the night‐vision device over 144 h. A series of spectral measurements are utilized to reveal the mechanism behind this prolonged afterglow duration, and quantum tunneling accounts for the carrier pumping from the deep traps. It avoids the quick exhaust of carriers stored in the shallow traps, and extends the afterglow duration. In a proof‐of‐concept demonstration, the synthesized powders are used to make a quick response pattern, which can be clearly visualized in a dark room by the night‐vision devices. This work is expected to promote the research and development of persistent luminescent materials within NIR region, and to accelerate the applications in night‐time monitoring and recognition.

Application of big roll and heavy reduction in continuous casting of thick slabs

ABSTRACT Porosity and segregation are common internal defects in thick slabs, which negatively affect the flaw detection qualification rate and mechanical properties of heavy plate materials. This study presents a novel big roll and heavy reduction (BRHR) technology to mitigate these internal defects. The Q345 slab with a thickness of 400 mm and a width of 2400 mm was selected as the specific research object. The cooling strategy was investigated to optimise the solidification front during the BRHR process. Achieving uniform solidification within the slab width significantly reduced porosity during the BRHR process. As the BRHR amount increased from 0 to 20 mm, porosity spots in the center of the thick slab significantly decreased. Additionally, carbon segregation decreased in slabs with BRHR amounts of 10 and 20 mm compared with 0 mm BRHR slabs. Statistical measurements revealed that as the BRHR amount increased from 0 to 20 mm, the ratio of porosity spot area decreased from 0.244% to 0.014%, while the maximum carbon segregation degree decreased from 1.17 to 1.09. Optimal control of uniform solidification across width direction and the total BRHR amount contributed to improve solidification porosity and segregation.

The Construction of a Mathematical Modeling Curriculum System Oriented by New Engineering Talents

This article provides an overview of the research progress on mathematical modeling courses both domestically and internationally, and points out the main problems that currently exist. Propose to no longer include competition results in the evaluation criteria, and establish its own training model based on the actual situation of the school. With the assistance of teachers, establish cross disciplinary projects. Teach students to apply knowledge to new problems, allowing more students to achieve more lasting results. The role and significance of research projects in promoting teaching work and improving teaching quality, and the specific research objects and contents. The main research subjects are students from most majors in science and engineering at our university. The main value lies in the exploration and practical work done in the field of new engineering education to cultivate students' mathematical literacy and numerical calculation ability.

Study of isotropic stellar models via durgapal-lake solutions in rastall system

Abstract This manuscript is dealt with the influences of Rastall factor on the physical aspects of isotropic celestial models. In this scenario, both the ideal fluid distribution and static spherically symmetry are taken into consideration. In specifically, the Durgapal-Lake solutions are taken into consideration to analyze the different characteristics of several specific compact star models like Her X-1, Vela X-1, LMC X-4 and RXJ 1856-37. Due to its innovative combination of two methodologies, this solution is a significant advancement on Durgapal-Fuloria and Lake's previous ansatz in enormous crucial eras. Using observed estimates of radii and masses of certain specific star objects, the undefined parameters in Durgapal-Lake ansatz are derived by matching conditions. The consistency of the adopted solutions is examined through the visual interpretation of matter constituents, equation of state factor, energy conditions, mass function and stability criteria corresponding to distinct choices of Rastall factor. The radially symmetric graphs of matter variables as well as the mass function are also displayed. Moreover, We present the graphical analysis for vanishing Rastall factor. It is concluded that in the context of Rastall theory, the stars under examination exhibit stable compositions with Durgapal-Lake solution, while in the context of general relativity, they exhibit instability.

Interpretation of the Norms of Criminal Jurisdiction Objects under the Hong Kong National Security Law

The Hong Kong National Security Law specifies the specific targets of sanctions, and the legislative content of the law on criminal jurisdiction objects clarifies the scope of behaviors protected and prohibited by law. Chapter 3 of the Hong Kong National Security Law specifies four types of crimes that endanger national security, including the crimes of secession, subversion of state power, terrorist activities, and collusion with foreign or overseas forces to endanger national security. From the perspective of legal interpretation, by grasping the dual elements of criminal intent and criminal behavior, the specific composition of the criminal jurisdiction objects stipulated in the law is clarified, revealing the particularity and strictness of the Hong Kong National Security Law in safeguarding national security. The normative interpretation of the specific criminal jurisdiction objects of this law can clearly stipulate the constituent elements of specific criminal acts, provide strong guidance for the effective jurisdiction of crimes that endanger national security in the Hong Kong Special Administrative Region, strengthen the prevention and crackdown on acts that endanger national security, and effectively safeguard national sovereignty, security, and development interests.

Problems of Legality and Permissibility of Using Cryptocurrencies in Making Payments in the Russian Federation

The publication touches on one of the aspects of the integration of cryptocurrencies, as a special object of civil rights, into the national legal and financial systems. Based on the specifics of the “cryptocurrency” category itself, the author distinguishes the legal turnover of cryptocurrency and foreign currency at the present stage, identifies problems that prevent the full integration of digital assets into the financial structure of the state, with the prospect of free circulation, analyzes the state of modern legislative regulation, as well as the possibility of implementing its own cryptocurrency settlement system in the country. The prospects for the development and possible improvement of the legislative framework in this dynamic and relevant area are assessed. Based on the conducted research, the article substantiates that Russian law in the field of regulating settlements using cryptocurrency follows the model of domestic legislation on currency regulation.

The Sustainable Development Goals of the Commodity Economy Deeply Influence the Diversity of Sexual Life

Human sexuality is different from other species in nature in that it is creative, accessible, and responsible; however, it is this creativity that makes sexual life differentiated, and sexual orientations become rich and diverse. Discrimination against people is not only about occupation, income, sexuality, or gender becomes discrimination against people. To achieve the goal of sustainable development, there is no discrimination against people, so this content is approached from the methodology of human philosophy and social philosophy, at the same time combining qualitative methods to analyze, synthesize, compare, contrast, and reverse to clarify the transformation of sexual life in the commodity economy. The result of this content is to explain that human sexual life is creative; it depends on the object of satisfaction. Sex does not depend on space, time, or specific objects, but occupation, goods, and money also govern the market economy. The conclusion of the article affirms that life is human satisfaction. Sexual satisfaction is not only human instinct but also human creativity. Human satisfaction differs from satisfaction with things without humans, which is satisfaction with loneliness, isolation, and unhappiness. Humans become different types of goods serving the life of money, posing a challenge to the goal of sustainable development in the commodity economy. However, there must be practical solutions to survive and maintain the race, bringing humans back to a creative sexual life and responsible reproduction to achieve the goal of sustainable development in the commodity economy.

A Quantified Methodology for Evaluating Engineering Sustainability: Ecological Footprint Measurement Modeling

With the gradual increase in public awareness of ecological environmental protection, how to manage the increasingly tight supply of natural ecological energy and resources and the more evident greenhouse effect, how to properly treat and deal with the relationship between people, engineering and the ecological environment during the construction phase of engineering projects as well as how to evaluate the degree of environmental friendliness and sustainable development ability of engineering projects will become an urgent issue. Stakeholders in engineering projects must seriously consider these vital issues. Existing studies on the evaluation of engineering–ecology sustainable development capacity mainly focus on the regional and industry levels, with less research focusing on the sustainability of individual engineering projects; furthermore, they are primarily concentrated on the qualitative evaluation perspective. In order to refine these shortcomings, based on the viewpoint of the ecosystem of construction projects, this paper integrates the concept of whole life cycle with the ecological footprint measurement model and defines the notion of the ecological footprint of the whole life cycle of construction projects. Subsequently taking the above concept as the foundation and making the ecological footprint of various activities throughout the life cycle of a construction project a specific study object, the research establishes the ecological footprint measurement model of the whole life cycle of the project, and comprehensively evaluates the impacts on the surrounding environment, which include the consumption of energy resources, CO2 and the absorption of solid wastes across the whole life cycle of the project. We then measure the sustainable development ability of engineering projects by comparing the ecological footprint with the ecological carrying capacity of a certain surrounding region. Finally, the practicability and reliability of the model is verified through the example’s application. Thus, the results of the study have significant theoretical and practical implications: (1) the introduction of the ecological footprint addresses the gap about the quantitative evaluation of the sustainability of individual engineering projects from a micro perspective; (2) it compensates for the shortcomings of other evaluation methods that only evaluate a single element, such as only CO2, resources, energy or solid waste and so on; and (3) stakeholders can use the measured model to quantitatively assess the sustainability of new projects or urban renewal projects, providing strong support for project feasibility studies and project-establishment.

Analysis of the impact of environmental enrichment on the behaviors of bioterium rats

Rats are often used in experimental research due to their intelligence and ease of handling. However, traditional housing conditions can limit their natural behaviors, potentially leading to discomfort. Environmental enrichment aims to increase behavioral diversity, promote healthy behaviors, encourage positive use of the environment, enhance the animal's ability to cope with stressors, and reduce stereotypic behaviors. This study primarily aimed to assess the impact of environmental enrichment on laboratory rat behaviors. A group of 18 rats was selected and divided into three groups (n=6): control, physical enrichment, and feeding enrichment. The enrichment groups were provided with specific objects (a plastic tube for physical enrichment and a seed-filled cardboard roll for feeding enrichment) over a 10-day period, with open field tests conducted on days 1, 5, and 10 to evaluate time spent in central and peripheral zones. Statistical analyses were conducted in RStudio using t-test (p<0.05) to compare open field activity, water intake, and food consumption across groups. Results showed that animals exposed to environmental enrichment displayed fewer stereotypic behaviors and increased feeding frequency. Thus, assessing the impact of physical and feeding enrichment in rats of laboratory demonstrates that enrichment strategies provide positive impacts on animal welfare.

Deleuze and Foucault's Virtual Ontology of the Event

Deleuze's monograph on Foucault is often construed as a ‘metaphysical fiction’ (Frédéric Gros), which would attribute to Foucault a metaphysics of Deleuze's own issue. Notably, Paul Patton has argued that Deleuze thereby deeply mischaracterises Foucault's concepts of actuality, history, power and philosophy itself. Against this view, I argue that Deleuze's interpretation in Foucault clarifies the virtual force ontology that the two thinkers effectively developed in common. This ontological framework not only resolves Patton's specific objections; it also outlines a philosophy of the event demonstrating the conceptual consistency between Foucault and Deleuze on fundamental questions of philosophical critique and political agency.