Hasil untuk "Labor systems"

S. Lee, H. Kim

Haoyan Ma, Peiguang Xin, Juncheng Ma et al.

Cough and snore are the most representative vocalizations for chicken respiratory diseases, which severely restrict poultry health due to highly contagious and lethal characteristics. Nighttime inspection by veterinarians is the foremost solution to identify bird respiratory symptoms during production. However, it is subjective, time-consuming, and labor-intensive. This study proposed a novel end-to-end model (ResNet18-TF) based on ResNet18 and a Time-Frequency Attention Mechanism (TFBlock) to automatically recognize chicken cough and snore using data collected in a commercial layer breeder house. In addition, a comparative analysis was conducted to evaluate the performance of different input features. The results revealed that LogFbank features exhibited superiority over MFCC features in the task of chicken sound recognition. By incorporating first-order and second-order delta features into LogFbank, the combination of ‘LogFbank+ΔLogFbank+ΔΔLogFbank’ further improved model recognition accuracy by 2.34 %. Additionally, the TFBlock structure enhanced the model's performance for recognizing coughs and snores. Specifically, the F1-score of MobileViTv3-TF, EfficientNetV2-TF, and ResNet18-TF models were increased by 1.30 %, 0.88 %, and 1.84 %, respectively, compared to their respective counterparts without TFBlock. ResNet18-TF achieved the highest accuracy, precision, recall, and F1-score, with 94.37 %, 94.59 %, 94.56 %, and 94.57 %, respectively. The generalization of ResNet18-TF in real production systems was validated, with precision and recall for detecting abnormal sounds (coughs and snores) reaching 92.97 % and 87.53 %, respectively. The proposed end-to-end model does not require denoising or endpoint detection processes, constructing an efficient and user-friendly pipeline of abnormal sound detection, which is highly suitable for practical deployment in poultry production systems.

Ziyi Wang, Congrong Zhang, Jingying Deng et al.

Homework tutoring work is a demanding and often conflict-prone practice in family life, and parents often lack targeted support for managing its cognitive and emotional burdens. Through interviews with 18 parents of children in grades 1-3, we examine how homework-related labor is divided and coordinated between parents, and where AI might meaningfully intervene. We found three key insights: (1) Homework labor encompasses distinct dimensions: physical, cognitive, and emotional, with the latter two often remaining invisible. (2) We identified father-mother-child triadic dynamics in labor division, with children's feedback as the primary factor shaping parental labor adjustments. (3) Building on prior HCI research, we propose an AI design that prioritizes relationship maintenance over task automation or broad labor mitigation. By employing labor as a lens that integrates care work, we explore the complexities of labor within family contexts, contributing to feminist and care-oriented HCI and to the development of context-sensitive coparenting practices.

Yigang Qin, EunJeong Cheon

The HCI community has called for renewed attention to labor issues and the political economy of computing. Yet much work remains in engaging with labor theory to better understand modern work and workers. This article traces the development of Labor Process Theory (LPT) -- from Karl Marx and Harry Braverman to Michael Burawoy and beyond -- and introduces it as an essential yet underutilized resource for structural analysis of work under capitalism and the design of computing systems. We examine HCI literature on labor, investigating focal themes and conceptual, empirical, and design approaches. Drawing from LPT, we offer directions for HCI research and practice: distinguish labor from work, link work practice to value production, study up the management, analyze consent and legitimacy, move beyond the point of production, design alternative institutions, and unnaturalize bourgeois designs. These directions can deepen analyses of tech-mediated workplace regimes, inform critical and normative designs, and strengthen the field's connection to broader political economic critique.

N. Koleva, N. Vasilev, V. Zheleva

This article AIMS to analyze the regional demographic disbalances in Bulgaria for the period 2003-2023. It examines the main demographic processes –birth rate, mortality, natural increase and migration -and assesses their impact on the socio-economic development of the country, including the labor market, health, education and pension systems. The study is based on a quantitative analysis of statistical data from the National Statistical Institute (NSI) and INFOSTAT for the period 2003-2023. Standard demographic METHODS are applied to calculate and analyse birth rate and mortality. Data on internal and external migration, as well as on the population structure by place of residence (urban/rural) and by region are analysed. The analysis of the obtained results reveals critical demographic trends: a significant decrease in the population of Bulgaria by 1 355 792 people over the last 20 years, determined by a persistently low birth rate, a high death rate and a negative natural increase, which in 2023 will reach -6.8‰. Regional imbalances are deepening, with intensive depopulation of rural and northern areas of thecountry. Demographic ageing is accelerating, with the average age of the population reaching 45.2 years. These processes are putting severe pressure on social systems, leading to labour shortages and contributing to economic instability.

WANG Rui, QUAN Jianing, TIAN Yunchen

With the continuous expansion of the aquaculture industry and the advancement of technology, the production model of the industry has gradually shifted toward greater modernization, mechanization, and automation. This transformation has become the primary trend in industry development, signaling the movement from traditional farming methods to intelligent and automated approaches. Fish fry, as a crucial link in the aquaculture supply chain, play an important role in the entire industry. Accurate fish fry counting is essential for managing the industry effectively, conducting scientific feeding practices, controlling stocking density, and ensuring fair pricing and transparent transactions in the sale of fry. In traditional aquaculture practices, fish fry counting mainly relies on manual methods, which are not only time consuming and labor intensive, but also prone to significant errors. Many farms still use the pushing method and bowl method for fry counting. The pushing method involves estimating the number of fry in a pile manually, whereas the bowl method estimates this number based on a sample. Both methods are subject to human error and often lead to inaccurate counts. Moreover, these manual methods are not only inefficient but can also harm the fry. During counting, the fry are often handled repeatedly, which can negatively impact their growth and survival, causing stress and affecting fry quality. With the advancement of technology and the development of computer systems, automated devices have been gradually introduced into the aquaculture industry. The advent of automatic fish fry counters has effectively addressed the inefficiencies of manual counting while ensuring accurate and transparent counting. These automated devices use sensors, image recognition, and machine learning technologies to automatically detect and track fry, efficiently completing counting with real-time data collection, high accuracy, and reliability. These tools provide aquaculture operators with a more scientific and convenient way of management, allowing for more precise feeding practices and reducing overfeeding or underfeeding, thus improving farm efficiency. However, despite the widespread use of automated counting technology in aquaculture, several challenges remain. In particular, when dealing with large volumes of fry, existing counting technologies face limitations in efficiency, accuracy, and handling fry overlap. As the number of fry increases, counting accuracy tends to decrease, especially when dealing with smaller fry, where detection systems can make errors. Additionally, the complex environment of aquaculture farms, such as light conditions, bubbles, and debris in the water, can interfere with counting accuracy, making the process complicated for automatic counting systems. Therefore, enhancing the accuracy of automated counting, especially in large volumes of fry or in complex environments, is still a technical issue that needs to be addressed. To tackle these issues, researchers have made significant improvements and innovations in automatic counting technology. The accuracy and efficiency of automatic counting systems have been significantly enhanced by incorporating advanced image recognition algorithms, deep learning techniques, and multisensor fusion technologies. These improved algorithms are effective at separating and tracking targets, achieving precise counting. Furthermore, with the development of simulation technology, virtual testing and simulations have played a crucial role in optimizing and designing automatic counting devices. Simulation allows device performance to be predicted under different working conditions, reducing the need for testing with live fry and minimizing potential losses. It also improves design efficiency and ensures that the stability, safety, and durability of the devices are thoroughly validated before practical application, providing reliable technical support for their implementation. Nevertheless, when handling large volumes of fry counting, challenges related to efficiency and dealing with overlapping fry remain. For instance, when designing automatic fry counting devices, design parameters are often difficult to calculate accurately because of the limitations of the fry and the aquaculture environment. Therefore, machine operating parameters must be adjusted to test counting effectiveness. However, this method wastes both human and material resources, and repeated testing can cause stress and harm to the fry. Simulation allows for testing the operational performance of prototype designs, reducing the need for physical testing and saving costs. This study introduces an improved YOLOV8-ByteTrack algorithm to achieve high-precision detection and tracking of fry. This algorithm focuses on real-time performance and efficiency by combining the lightweight YOLOV8 model for object detection with the precise multi-target tracking capabilities of ByteTrack. YOLOV8, being a lightweight model, reduces computational load while maintaining high detection accuracy, offering fast and stable performance in resource-limited environments. Once the fry are detected, ByteTrack uses an efficient data association strategy to track multiple targets and maintain identity consistency, significantly reducing issues such as ID switching and target loss caused by rapid movement, overlap, or environmental changes. Unlike traditional algorithms that rely solely on high-confidence detections, ByteTrack incorporates low-confidence results by utilizing motion consistency and appearance features, thus improving counting accuracy and continuity. To verify the performance and stability of the proposed fish fry automatic counting device in practical applications, a series of accuracy testing experiments was conducted on fish fry of different sizes. The experiments tested 3–5, 6–8, and 9–12 cm-sized grouper fry, with 200, 250, and 300 fry per group, respectively. The test results showed that the counting accuracy of the device was 99.1% and 99.6% for the 6–8 and 9–12 cm fry, respectively, with a slightly lower accuracy of 98.5% for the 3–5 cm fry. The algorithm achieved an average frame rate of 155 FPS, with a single-frame processing time of approximately 6.5 ms. Moreover, the processing speed at different frame rates demonstrated high real-time stability, with a minimum processing speed of 6.3 ms (158 FPS) and a maximum of 6.6 ms (152 FPS). The lower accuracy for the 3–5 cm fry can be attributed to their smaller size, which makes them more susceptible to background complexity and rapid movement, leading to a slight decrease in detection precision. As fry size increases, their features become more distinct, and their movements become more stable, resulting in higher detection accuracy. These results validate the excellent real-time and efficient performance of the algorithm even with limited hardware resources, meeting the practical needs of speed and accuracy in fish fry counting scenarios. The fish fry automatic counting device proposed in this study offers an innovative solution to improve fry counting precision and efficiency, providing valuable insights for theoretical research and practical applications in aquaculture.

Arkadiusz Ciach

Research objectives and hypothesis/research questions The aim is to critically analyze the challenges and inequalities in the management of the financing of the tasks of local government units (LGUs) in Poland, with particular emphasis on the impact of legislative, political, and financial factors on the effectiveness of their tasks. Research questions: 1. Does the presence of councilors employed in units subordinate to local government units lead to a conflict of interest, which negatively impacts the transparency and independence of financial decisions made? 2. Does the amount of subsidies and subsidies awarded depend solely on the economic situation of municipalities, or is it also influenced by political links between local authorities and the ruling party at the central level? 3. As a result of underestimating the educational subsidy, are local government units forced to redirect their funds to finance educational tasks at the expense of other public activity areas? 4. Do the currently used algorithms for the distribution of subsidies reflect the real needs of local government units, and, as a result, there is an optimal allocation of public funds? 5. Is there equal access for local government units to European and national funds? Research methods 1. Analysis of empirical data: Examination of data from local government units (LGUs) between 2019 and 2023. 2. Comparative analysis: Evaluation of financial indicators for LGUs based on their size, own revenues, and political affiliations. 3. Statistical analysis: Investigation of differences in the allocation of financial resources to identify disparities. 4. Analysis of source documents: Review legal documents, Supreme Audit Office (NIK) reports, and local budget data from LGUs. 5. Case study: Analysis of municipalities in the Radomsko focusing on underestimating educational subsidies and conflicts of interest. 6. Critical literature review: Examination of domestic and international literature to provide context and identify relevant issues. Main results 1. The amount of subsidies and grants awarded often depends on the political affiliations of local authorities with the ruling party. 2. Educational subsidies fall short of covering actual educational costs, straining resources for other public responsibilities. 3. Councilors employed by subordinate LGU units cause conflicts of interest, harming transparency and financial independence. 4. Under governmental support programs, grant allocation processes lacked transparency and clear criteria, enabling abuses and discretionary fund distribution. 5. Financial support was unevenly distributed, worsening inequalities between wealthier and poorer regions. Implications for theory and practice For theory: the research brought a new perspective to the analysis of decentralization and self-government, showing the impact of political, legislative, and financial factors on the functioning of local governments. In particular, the results confirm the importance of political distribution theory, pointing to the practice of favoring individuals associated with the ruling party, reflecting the phenomenon of political allocation of resources. The problems of unequal allocation of resources and underestimation of education subsidies bring new elements to the theory of distributive justice, highlighting the imbalance in access to public resources between regions. For practice: research indicates an urgent need for legislative reforms aimed at simplifying and stabilizing the regulations governing the activities of local government units. Recommendation for the introduction of more transparent mechanisms for allocating public funds. Emphasize the importance of support for less developed local government units, which would reduce regional inequalities and make more efficient use of available funds.

I. A. Kibkalo, I. G. Loskutov, N. P. Voitsutskaya et al.

The range of methods for assessing the quality of grain and its technological properties in cereal crops, of oat in particular, is extremely limited. The available methods are labor-intensive and not always sufficiently informative. The variety of modern processing methods dictates the necessity in searching for more universal and informative assessment methods. Cereal crop breeding also requires high-speed and low-cost methods for assessing grain quality. The present work is a methodological study that uses a limited set oat accessions from the genetic collection of VIR, differing by geographical origin and contrasting technological properties, with an aim of developing a new grain quality assessment method and testing new methods for analyzing technological properties. The resulting criteria are compared with each other and with more traditional indicators. New systems for assessing the technological properties of grain of naked and covered oat have been proposed. A new method of sedimentation analysis for cereal crops is proposed. The diversity of the oat protein complex is exemplified in the results of sedimentation analysis, and of the carbohydrate complex – in the results of its testing by a micro-visco-amylograph. The variety of interactions between oat grain storage substances and wheat material during joint processing is shown by assessing the rheological properties of the dough mixture using a farinograph. The obtained results can be recommended for the assessment for breeding purposes, as well as for obtaining complete information about the quality of oat grain for the purpose of its further processing.

Amarachi Igwe, Ogonna E Egbuchulam, Jacinta Nnaji

Financial distress in the hospitality industry affects both businesses and their employees. This study explores the perspectives of employees on financial distress within the hospitality sector in Imo State, Nigeria. The study addressed three research questions. Survey research design was adopted for the study. The study was carried out in Imo State Nigeria. 361 financial officers in the hotels within the hospitality industry in Owerri Imo State were the target population and random sampling was used to select 181 hotels whose financial officers served as the study respondents. Structured questionnaire was specifically designed for this study. The data was analyzed using mean, and standard deviation to provide an overview of employee perspectives on financial distress. The results indicate that a wide range of variables, such as economic downturns, irregular revenue, high cost of living, and management concerns within businesses, are responsible for financial hardship among employees in the hotel industry in Imo State. Employees also mentioned that worry, anxiety, and job instability were direct effects of their financial hardship. Based on the results, a number of suggestions are made to lessen financial hardship. These include putting in place financial literacy initiatives for staff members, enhancing management-staff communication and transparency, supporting ethical labor practices, and encouraging social support systems within the workplace.

Chongyang Tao, Lili Mou, Dongyan Zhao et al.

Open-domain human-computer conversation has been attracting increasing attention over the past few years. However, there does not exist a standard automatic evaluation metric for open-domain dialog systems; researchers usually resort to human annotation for model evaluation, which is time- and labor-intensive. In this paper, we propose RUBER, a Referenced metric and Unreferenced metric Blended Evaluation Routine, which evaluates a reply by taking into consideration both a groundtruth reply and a query (previous user-issued utterance). Our metric is learnable, but its training does not require labels of human satisfaction. Hence, RUBER is flexible and extensible to different datasets and languages. Experiments on both retrieval and generative dialog systems show that RUBER has a high correlation with human annotation, and that RUBER has fair transferability over different datasets.

D. O’Rourke

Irfan Abbas, Jizhan Liu, Muhammad Faheem et al.

Abstract Chemical application of nutrients and pesticides is one of the most important processes in agricultural production, but also one of the most dangerous agricultural operations. To improve the chemical efficacy, reduce chemical and labor costs, minimize labor hazards, and reduce the harmful environmental damage. Variable-rate spray applications that use intelligent control systems can significantly reduce pesticide use and off-target environmental pollution. Real-time variable-rate spraying technology offers effective and efficient use of pesticides. The variable-rate spray allows the farmers to apply pesticides only on the target, using only the correct amount based on the canopy size, season, and growth phase of the plants. In the past few decades, target detection systems have been developed using advanced methods such as laser and vision scanning systems or, more simply, ultrasound, infrared, and spectrum systems. Real-time target detection spray Systems used for the detection of the geometric properties of tree plants are reviewed in detail. Among these methods, machine vision and laser scanners systems are possibly the most capable and complementary means of obtaining three-dimensional (3D) images and maps of plants and canopies. This paper discusses a review of various sensing technologies available for the determination of canopy structural parameters and discusses how they are used for precision spraying. Some of the challenges and considerations of the use of these sensors and technologies are also discussed.

Christian Fiedler, Michael Herty, Sebastian Trimpe

Mean field limits are an important tool in the context of large-scale dynamical systems, in particular, when studying multiagent and interacting particle systems. While the continuous-time theory is well-developed, few works have considered mean field limits for deterministic discrete-time systems, which are relevant for the analysis and control of large-scale discrete-time multiagent system. We prove existence results for the mean field limit of very general discrete-time control systems, for which we utilize kernel mean embeddings. These results are then applied in a typical optimal control setup, where we establish the mean field limit of the relaxed dynamic programming principle. Our results can serve as a rigorous foundation for many applications of mean field approaches for discrete-time dynamical systems.

G. Paudel, D. Kc, D. Rahut et al.

Highlights • Labor shortage due to out-migration adversely affected smallholder farmers in Nepal.• Adoption of scale-appropriate mechanization increased rice productivity by 1110 kg/ha.• Adoption of mechanization by non-adopters would increase rice productivity by 1250 kg/ha.• Very small rice cultivating farms (≤0.25 ha) benefited most from adoption of mechanization.• Rising on-farm rural wage due to labor shortage was the primary driver of mini-tiller adoption.

Marco Guerini

The essay proposes a reconstruction of the main quantitative and qualitative theories that have emerged in economics about the impacts on the labour market deriving from the progressive replacement of human labour by robots. In light of this, the Author acknowledges several interpretative lines observed in the industry for about a decade. Such an analysis is functional to investigate how the process of man-machine substitution (or its threat) responds not exclusively to deterministic logic linked to technological progress. Instead, it closely intertwines with strategic choices originating in processes that characterise labour law and industrial relations, particularly affecting the determination of the working conditions of underqualified and, thus, more easily replaceable workers. Indeed, if the regulation of the phenomenon were determined solely by mercantile interests, this would present a risk to the very stability of the welfare state. Therefore, it is urgent to activate the protection techniques offered by labour law to encourage the spread of robotics that, instead of aiming at replacing workers tout court, aspires to make their work less burdensome and, thus, more dignified.

Evan Arsenault, Yuheng Wang, Margaret P. Chapman

We aim to analyze the behaviour of a finite-time stochastic system, whose model is not available, in the context of more rare and harmful outcomes. Standard estimators are not effective in making predictions about such outcomes due to their rarity. Instead, we use Extreme Value Theory (EVT), the theory of the long-term behaviour of normalized maxima of random variables. We quantify risk using the upper-semideviation $ρ(Y) = E(\max\{Y - μ,0\})$ of an integrable random variable $Y$ with mean $μ= E(Y)$. $ρ(Y)$ is the risk-aware part of the common mean-upper-semideviation functional $μ+ λρ(Y)$ with $λ\in [0,1]$. To assess more rare and harmful outcomes, we propose an EVT-based estimator for $ρ(Y)$ in a given fraction of the worst cases. We show that our estimator enjoys a closed-form representation in terms of the popular conditional value-at-risk functional. In experiments, we illustrate the extrapolation power of our estimator using a small number of i.i.d. samples ($<$50). Our approach is useful for estimating the risk of finite-time systems when models are inaccessible and data collection is expensive. The numerical complexity does not grow with the size of the state space.

Dominic Loske, Matthias Klumpp, Maria Keil et al.

<i>Background:</i> A large proportion of logistics jobs still rely on manual labor and therefore place a physical strain on employees. This includes the handling of heavy goods and physiologically unfavorable postures. Such issues pose a risk for employee health and work capability. This article provides a detailed empirical analysis and a decision process structure for the allocation of ergonomic measures in warehousing and intralogistics processes. <i>Methods:</i> The methodological basis is a load assessment of the musculoskeletal system in retail intralogistics. Based on the established measurements systems CUELA and OWAS, the specific loads on employees are assessed for four typical logistics workplace settings. These are combined with standards for efficient decision rules regarding contracting and developing ergonomic improvements. <i>Results:</i> The results suggest an increased risk of long-term low back injury for the selected four standard work situations in warehousing and likely apply to similar work environments in logistics. Using measures, posture descriptions, and international standards, we show how already few threshold values serve as sufficient conditions to decide if ergonomic interventions are required. <i>Conclusions:</i> The specific contribution is characterized by the combination of literature review results, empirical results, and the identification and discussion of specific mitigation measures. These elements are focused on the highly relevant ergonomic situation of logistics workers and present a unique contribution towards the knowledge base in this field due to the multi-perspective approach.

Masaki Waga, Étienne André, Ichiro Hasuo

Monitoring of hybrid systems attracts both scientific and practical attention. However, monitoring algorithms suffer from the methodological difficulty of only observing sampled discrete-time signals, while real behaviors are continuous-time signals. To mitigate this problem of sampling uncertainties, we introduce a model-bounded monitoring scheme, where we use prior knowledge about the target system to prune interpolation candidates. Technically, we express such prior knowledge by linear hybrid automata (LHAs) -- the LHAs are called bounding models. We introduce a novel notion of monitored language of LHAs, and we reduce the monitoring problem to the membership problem of the monitored language. We present two partial algorithms -- one is via reduction to reachability in LHAs and the other is a direct one using polyhedra -- and show that these methods, and thus the proposed model-bounded monitoring scheme, are efficient and practically relevant.

Alexander Sakhnovich

We construct so called Darboux matrices and fundamental solutions in the important case of the generalised Hamiltonian (or canonical) systems depending rationally on the spectral parameter. A wide class of explicit solutions is obtained in this way. Interesting results for dynamical systems depending on several variables and their explicit solutions follow. For these purposes we use our version of Bäcklund-Darboux transformation and square roots of the corresponding generalised matrix eigenvalues. Some new auxiliary results on the roots of matrices are included as well. An appendix is added to make the paper self-sufficient.

A. Moor, S. Itzkovitz