Andrés Holgado-Sánchez, Holger Billhardt, Alberto Fernández
et al.
Agreement Technologies refer to open computer systems in which autonomous software agents interact with one another, typically on behalf of humans, in order to come to mutually acceptable agreements. With the advance of AI systems in recent years, it has become apparent that such agreements, in order to be acceptable to the involved parties, must remain aligned with ethical principles and moral values. However, this is notoriously difficult to ensure, especially as different human users (and their software agents) may hold different value systems, i.e. they may differently weigh the importance of individual moral values. Furthermore, it is often hard to specify the precise meaning of a value in a particular context in a computational manner. Methods to estimate value systems based on human-engineered specifications, e.g. based on value surveys, are limited in scale due to the need for intense human moderation. In this article, we propose a novel method to automatically \emph{learn} value systems from observations and human demonstrations. In particular, we propose a formal model of the \emph{value system learning} problem, its instantiation to sequential decision-making domains based on multi-objective Markov decision processes, as well as tailored preference-based and inverse reinforcement learning algorithms to infer value grounding functions and value systems. The approach is illustrated and evaluated by two simulated use cases.
With the growth of the population, the development of industrial construction, and the acceleration of urbanization, the generation of wastewater increases annually. Accordingly, the amount of sewage sludge is also rising, including sewage sludge containing significant concentrations of heavy metals, pathogens, and bacteria. The high moisture content of municipal sewage sludge creates serious challenges for its safe disposal and further utilization. In the countries of the European Union, landfilling of sewage sludge is prohibited. Therefore, sewage sludge is no longer accumulated in sewage sludge drying beds, sewage sludge storage lagoons, or dumps, as is still practiced in our country. Consequently, there is a need to revise the existing sewage sludge management approach. Mathematical modeling of the kinetics of sewage sludge dewatering using the dimensional analysis method made it possible to obtain a functional relationship expressed in terms of dimensionless similarity numbers. These similarity numbers have a clear physical meaning as ratios of forces or as analogues of classical similarity criteria. The analogy with filtration theory was confirmed in the study of the compression–filtration properties of sewage sludge mixture from the Lviv municipal wastewater treatment plants.
Maarten van der Hulst, Rodrigo A. González, Koen Classens
et al.
Physically interpretable models are essential for next-generation industrial systems, as these representations enable effective control, support design validation, and provide a foundation for monitoring strategies. The aim of this paper is to develop a system identification framework for estimating modal models of complex multivariable mechanical systems from frequency response data. To achieve this, a two-step structured identification algorithm is presented, where an additive model is first estimated using a refined instrumental variable method and subsequently projected onto a modal form. The developed identification method provides accurate, physically-relevant, minimal-order models, for both generally-damped and proportionally damped modal systems. The effectiveness of the proposed method is demonstrated through experimental validation on a prototype wafer-stage system, which features a large number of spatially distributed actuators and sensors and exhibits complex flexible dynamics.
Harsh Abhinandan, Aditya Dhanraj, Aryan Katoch
et al.
Unmanned Aerial Vehicles (UAVs) or drones have witnessed a spectacular surge in applications for military, commercial, and civilian purposes. However, their potential for flight is always limited by the finite power budget of their onboard power supplies. The limited flight time problem has led to intensive research into new sources of power and innovative charging strategies to enable protracted, autonomous flight. This paper gives a comparative summary of the current state-of-the-art in UAV power and refuelling technology. The paper begins with an analysis of the variety of energy sources, from classical batteries to fuel cells and hybrid systems, based on their relative advantages and disadvantages in energy density, weight, and safety. Subsequently, the review explores a spectrum of replenishment options, from simple manual battery swapping to sophisticated high-tech automatic docking stations and smart contact-based charging pads. Most of the review is dedicated to the newer technology of wireless power transfer, which involves near-field (inductive, capacitive) and far-field (laser, microwave) technology. The article also delves into the most important power electronic converter topologies, battery management systems, and control approaches that form the core of these charging systems. Finally, it recapitulates the most significant challenges in technical, economic, and social aspects for promising avenues of future research. The comprehensive review is a valuable guide for researchers, engineers, and policymakers striving to enhance UAV operational performance.
This paper addresses the challenge of amplitude-unbounded false data injection (FDI) attacks targeting the sensor-to-controller (S-C) channel in cyber-physical systems (CPSs). We introduce a resilient tube-based model predictive control (MPC) scheme. This scheme incorporates a threshold-based attack detector and a control sequence buffer to enhance system security. We mathematically model the common FDI attacks and derive the maximum duration of such attacks based on the hypothesis testing principle. Following this, the minimum feasible sequence length of the control sequence buffer is obtained. The system is proven to remain input-to-state stable (ISS) under bounded external disturbances and amplitude-unbounded FDI attacks. Moreover, the feasible region under this scenario is provided in this paper. Finally, the proposed algorithm is validated by numerical simulations and shows superior control performance compared to the existing methods.
Dynamic simulation plays a crucial role in power system transient stability analysis, but traditional numerical integration-based methods are time-consuming due to the small time step sizes. Other semi-analytical solution methods, such as the Differential Transformation method, often struggle to select proper orders and steps, leading to slow performance and numerical instability. To address these challenges, this paper proposes a novel adaptive dynamic simulation approach for power system transient stability analysis. The approach adds feedback control and optimization to selecting the step and order, utilizing the Differential Transformation method and a proportional-integral control strategy to control truncation errors. Order selection is formulated as an optimization problem resulting in a variable-step-optimal-order method that achieves significantly larger time step sizes without violating numerical stability. It is applied to three systems: the IEEE 9-bus, 3-generator system, IEEE 39-bus, 10-generator system, and a Polish 2383-bus, 327-generator system, promising computational efficiency and numerical robustness for large-scale power system is demonstrated in comprehensive case studies.
Benyapa Silamat, Ole Mark, Slobodan Djordjević
et al.
Hydrogen sulfide (H2S) is one of the sewer gases commonly found in wastewater collection systems. This anaerobic degradation product causes issues, ranging from odor nuisances and health hazards to pipe corrosion. Several studies have provided an understanding of H2S formation mechanism, including simulations of H2S emissions in sewers, especially in pressurized systems. However, the present models necessitate a large amount of data due to the complexity of the H2S processes and common routine-monitoring water quality parameters may not fit the requirements. This study aims to simulate the fate and transport of H2S in both air and water phases in combined sewers, with a realization of practicableness of the application. The study case is centered around a fresh market in Bangkok, where the sewers are commonly plagued with garbage-related issues. These challenges pose difficulties for site monitoring across various aspects, necessitating the application of unconventional methods. On-site hydrodynamics, wastewater quality, and H2S gas concentration data were monitored on hourly and daily bases. It was found that the sulfides in the combined sewerage were correlated with sewage quality, e.g., COD, sulfate (SO42-), and pH concentrations in particular. The model results were in an acceptable range of accuracy (R2 = 0.63; NSE = 0.52; RMSE = 1.18) after being calibrated with the measured hydrogen sulfide gas concentration. The results lead to the conclusion that the simplified model is practical and remains effective even in sewers with untraditional conditions. This could hold promise as a fundamental tool in shaping effective H2S mitigation strategies.
Today, customer satisfaction is one of the main issues that water and wastewater companies must consider. In this regard, it is crucial to identify effective strategies to increase customer satisfaction. Therefore, the aim of this research was to evaluate the satisfaction of the subscribers of Shiraz Water and Wastewater Company. For this purpose, the combined Delphi and Kano model was used. The method used in the current research was descriptive-analytical and qualitative-quantitative in terms of the type of the data. With this objective in mind, according to the Delphi method, 37 satisfaction factors of the subscribers of Shiraz Water and Wastewater Company were selected according to the opinion of the company's and other experts, and were investigated as the main variables of the research. In the following, using a research questionnaire based on the Kano model, information was collected from the statistical population; then, using an evaluation table, the subscriber's needs were identified, and the coefficient of satisfaction and dissatisfaction was calculated and analyzed. Based on Kano's model, customer satisfaction factors are mainly classified into three categories: must-be one-dimensional and attractive requirements. In this research, 10 factors were identified as must-be requirements, 9 factors as one-dimensional requirements, and 18 factors as attractive requirements, which were ranked based on the level of satisfaction and dissatisfaction of subscribers. Based on the results, Shiraz Water and Sewerage Company should focus more on the characteristics of attractive requirements instead of must-be or one-dimensional requirements in order to gain a competitive advantage and focus on customer satisfaction.
Technology, Water supply for domestic and industrial purposes
The increasing popularity of deep learning models has created new opportunities for developing AI-based recommender systems. Designing recommender systems using deep neural networks requires careful architecture design, and further optimization demands extensive co-design efforts on jointly optimizing model architecture and hardware. Design automation, such as Automated Machine Learning (AutoML), is necessary to fully exploit the potential of recommender model design, including model choices and model-hardware co-design strategies. We introduce a novel paradigm that utilizes weight sharing to explore abundant solution spaces. Our paradigm creates a large supernet to search for optimal architectures and co-design strategies to address the challenges of data multi-modality and heterogeneity in the recommendation domain. From a model perspective, the supernet includes a variety of operators, dense connectivity, and dimension search options. From a co-design perspective, it encompasses versatile Processing-In-Memory (PIM) configurations to produce hardware-efficient models. Our solution space's scale, heterogeneity, and complexity pose several challenges, which we address by proposing various techniques for training and evaluating the supernet. Our crafted models show promising results on three Click-Through Rates (CTR) prediction benchmarks, outperforming both manually designed and AutoML-crafted models with state-of-the-art performance when focusing solely on architecture search. From a co-design perspective, we achieve 2x FLOPs efficiency, 1.8x energy efficiency, and 1.5x performance improvements in recommender models.
The calibration of future wide field adaptive optics (WFAO) systems requires knowledge of the geometry of the system, in particular the alignment parameters between the sub-apertures of the wavefront sensors (WFS), pupil and deformable mirror (DM) actuator grid. Without this knowledge, closed-loop operation is not possible and the registration must be identified with an error significantly smaller than the sub-aperture size to achieve the nominal performance of the adaptive optics system. Furthermore, poor accuracy in this estimation will not only affect performance, but could also prevent the closed loop from being stable. Identification is not trivial because in a WFAO system several elements can move with respect to each other, more than in a SCAO system. For example, the pairing of the sub-aperture and the actuator grating on a DM conjugated to an altitude different from 0 can depend on the size of the pupil on the WFS, the exact conjugation of the DM, the position of the guide star and the field rotation. This is the same for each WFS/DM pair. SPRINT, System Parameters Recurrent INvasive Tracking, is a strategy for monitoring and compensating for DM/WFS mis-registrations and has been developed in the context of single conjugate adaptive optics (SCAO) systems for the ESO Extremely Large Telescope (ELT). In this work, we apply SPRINT in the context of WFAO systems with multiple WFSs and DMs, investigating the best approach for such systems, considering a simultaneous identification of all parameters or subsequent steps working on one DM at a time.
Orest Verbovskiy, Vadym Orel, Oksana Matsiyevska
et al.
The sewage sludge formed at wastewater treatment plants constitutes a small percentage of the volume of treated wastewater. However, the costs associated with sludge treatment and disposal account for the lion's share of the operational expenses of wastewater treatment plants. The sludge contains harmful and toxic substances. On the other hand, sludge is a source of carbon, nutrients, and trace elements, meaning it can be effectively utilized. An important stage in sludge disposal is its dewatering, particularly with the use of electric current. The study investigated the electro-dewatering of activated sludge with a moisture content of 98% from secondary clarifiers at the Ternopil wastewater treatment plant using direct electric current. Experiments were conducted on a laboratory setup with a U-shaped glass tube and carbon rod anode and cathode. The effect of the electric field was observed during the fading period, when, after a significant amount of water had been separated from the sludge, the electro-dewatering process slowed down. The obtained results were compared with those from the electro-dewatering of activated sludge with a moisture content of 98% from secondary clarifiers at the Ternopil wastewater treatment plant on a setup with a graphite rod anode and a flat cathode, as reported by other researchers. Electro-dewatering of activated sludge on both setups produced practically the same effect. It was confirmed that sludge dewatering using direct electric current can be applied on sludge drying beds at wastewater treatment plants.
Bacterial infections that are due to consumption of poor quality water are still an important threat to human health and life. The aim of the article was to investigate the bacteriological threat of water from home wells. The results of water testing from individual wells constituted research material. On their basis, the health risk of fecal streptococci, coliforms and Escherichia coli was assessed and an attempt was made to assess the impact of pollution on the health of residents. The results of water testing in private wells showed unacceptable values for bacteriological pollution. A signifi cant health risk was found for fecal streptococci, coliforms and Escherichia coli. The authors pointed out the need to take extensive actions aimed at raising environmental and health awareness of the inhabitants in terms of water quality used for living purposes, in particular for consumption. 22 E. Wysowska, K. Kudlik, A. Kicińska regulations. Especially dangerous items are devices used for periodic collection or disposal of domestic and household sewage, the so-called septic tanks. Taking into account the facts quoted in the area of the municipal water and sewage enterprise, free check-ups were proposed as part of which residents had the opportunity to test the quality of water taken from their private home wells. On their basis, the potential risk resulting from the consumption of water contaminated with microbial pathogens, such as: (a) fecal streptococci (Enterococcus faecalis), (b) coli group bacteria and c) Escherichia coli (hereinafter E. coli). The study of the indicated groups of microorganisms is required in the monitoring of intakes used for the collective supply of drinking water (Regulation of the Minister of Health 2017). Materials and methods The collected research material included the results of testing water samples from individual wells with a total amount of n = 435 from a selected area of south-eastern Lesser Poland. For the purposes of this article, the communes where the research material was collected were marked with symbols A–J (Tab. 1), and the waters in which fecal streptococci, coliforms and Escherichia coli were analyzed were collected in 2015–2018. The analyzed water samples were taken from home wells, mostly dug wells. These wells use the shallowest, Quaternary water layer, characterized by low resistance to pollution originating from the land surface. Raw water samples came from wells that: i. are a reserve source of drinking water for households using the collective water supply system, ii. can be a basic source of drinking water for households using the collective water supply system, iii. are a source of drinking water for households within the range of the collective water supply system, but not using it, iv. are a basic source of drinking water for households outside the range of the collective water supply system. The voluntary nature of testing water from individual home wells and the related anonymity of the research results made it impossible to assign specifi c wells to the groups described above. However, this does not diminish the advisability of the pilot research on the water supply company and the appropriateness of further analysis. Of the 435 samples tested, 6 came from households located outside the area of activity of the collective water supply company and 14 samples were repeated, i.e. a repeat check-up was made after the well user’s report. The number of samples taken in individual communes together with the breakdown by years is presented in Table 1. Due to the fact that the samples were not collected cyclically from each of the communes over the analyzed period, and the sampling was previously a verifi cation test, a research sample consisting of 425 samples from the communes was selected for further analysis: A, B, C and D, in which the greatest number of water samples was taken. Other sampling sites were rejected due to the negligible number of well water samples taken in 2015–2018 (n ≤ 2). It is mentioned that the total number of rejected samples (n = 10) represents only about 2% of the total test sample (n = 435). In Table 1, the rejected samples were marked grey. Further analyses were made based on a selected research material consisting of 425 samples. Microbiological tests of water were made in the Accredited Water and Sewage Testing Laboratory, belonging to the water supply company making verifi cation tests, based on the PN-EN ISO 7889-2:2004, PN-EN ISO 9308-1:2014 Ap1:2017 standards. Characteristics of the study area From the total number of tested water samples (n = 425), 127 samples (areas B, C, D) came from agricultural areas, while agricultural or post-agricultural areas located on the outskirts of cities were home to:298 samples (areas A and D) (Fig. 1). The research areas (A–D) are geographically located in the part of the Carpathian Foothills of the Outer Western Carpathians, constituting mountainous, upland and river valleys with a diversifi ed terrain. They are located at altitudes from 270 up to 450 m above sea level (Kubal 2001). The geological structure of the area consists of tertiary formations: sandstones, shales and marls that were uplifted and folded. The area is located within the main structural unit of the Carpathians. Table 1. Quantities of well water samples taken in 2015–2018 Commune Number of samples taken (n) 2015 2016 2017 2018 Total
Biomedical waste management is an important part of traditional and modern health care systems. This paper focuses on the identification and classification of biomedical waste in Ayurvedic hospitals. The terms ‘biomedical waste management’, ‘health care waste management’ alone and combined with ‘Ayurveda’ or ‘Ayurvedic’ current practices and recent advances in the treatment of these used conditions. We have made a concerted effort to classify biomedical waste in Ayurvedic hospitals as the available data on its collection is extremely rare. Proper waste management is fundamental to hospital hygiene, hospital hygiene and care services. Current methods of disposal using Ayurveda waste sewage /ditches, burning and landfilling. But these methods have their advantages and disadvantages. Our review identified many interesting areas for future research such as the rational use of bioremediation techniques in biomedical waste management and the use of active microbes and solar energy in waste disposal.
A modern city is a complex, dynamically changing natural and anthropogenic system that must provide its residents with a comfortable and safe living environment. Along with the traditional elements of the city's infrastructure: the transport system, sewerage, water supply, heat and electricity supply, and elements of the social infrastructure (schools, hospitals, etc.), the role of the city's ecological infrastructure is growing. The latter includes both artificial and natural objects that provide environmental services and reduce the negative anthropogenic impact of the urban environment on nature and living organisms. Such components are the city's green space and communal systems that neutralize the most pronounced manifestations of anthropogenic influence, such as ensuring waste disposal. The state of the urban ecosystem depends on a complex combination of structure, activity, risks, and intentions of its inhabitants, the state of the economic and financial and economic system, the stability of the natural base expressed in the landscape, and the city's visibility, the intensity of industrial activity and the level of environmental education. The prerequisite for developing the city as a dynamic system is ensuring its sustainability. According to the modern vision, a sustainable city is based on three pillars: economic, ecological, and social, which must develop harmoniously. Therefore, the ecological infrastructure of the city should be based on the appropriate level of technology and economic development. Lviv is a large city in Ukraine and the largest city in the territory of the western regions, a logistical and cultural center. At the same time, the ecological infrastructure of the city is mainly at the formation stage. A meaningful sign of its puberty is the lack of an effective waste management system and an imperfect air quality monitoring system. Municipal sewage treatment facilities and the city's transport system need improvement. The city's green infrastructure as a subsystem of the ecological infrastructure causes relatively few comments. However, it should be noted that its main structure has been updated for decades, and new microdistricts with active construction may need more green space. In order to improve the environment of Lviv, it is necessary to improve the elements of its ecological infrastructure with the involvement of best practices of well-known cities of the world.
Mathematical models are just models. The desire to describe battery energy storage system (BESS) operation using computationally tractable model formulations has motivated a long-standing discussion in both the scientific and industrial communities. Linear BESS models are the most widely used so far. However, finding suitable linear BESS models has been controversial. This paper focuses on the description of linear BESS models. Four linear BESS formulations are presented, among the most popularly used. A new formulation is also proposed. The 5 BESS models are tested in 100 random BESS and 1.450 random samples of daily profiles of renewable generation. Two classical problems of power systems, namely, the set-point tracking problem and the transmission expansion planning problem, are selected for numerical analysis. Five thousand simulations are used to draw a better interpretation of each linear formulation presented and showcase specific challenges of BESS models. Practical recommendations are provided based on the findings.