Scan matching by cross-correlation and differential evolution

Scan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others. Methods that are accurate and adaptive and at the same time computationally efficient are required to enable location-based services in autonomous mobile devices. Such devices usually have a wide range of high-resolution sensors but only a limited processing power and constrained energy supply. This work introduces a novel high-level scan matching strategy that uses a combination of two advanced algorithms recently used in this field: cross-correlation and differential evolution. The cross-correlation between two laser range scans is used as an efficient measure of scan alignment and the differential evolution algorithm is used to search for the parameters of a transformation that aligns the scans. The proposed method was experimentally validated and showed good ability to match laser range scans taken shortly after each other and an excellent ability to match laser range scans taken with longer time intervals between them.Web of Science88art. no. 85

Harvesting-aware energy management for environmental monitoring WSN

Wireless sensor networks can be used to collect data in remote locations, especially when energy harvesting is used to extend the lifetime of individual nodes. However, in order to use the collected energy most effectively, its consumption must be managed. In this work, forecasts of diurnal solar energies were made based on measurements of atmospheric pressure. These forecasts were used as part of an adaptive duty cycling scheme for node level energy management. This management was realized with a fuzzy logic controller that has been tuned using differential evolution. Controllers were created using one and two days of energy forecasts, then simulated in software. These controllers outperformed a human-created reference controller by taking more measurements while using less reserve energy during the simulated period. The energy forecasts were comparable to other available methods, while the method of tuning the fuzzy controller improved overall node performance. The combination of the two is a promising method of energy management.Web of Science105art. no. 60

Economic optimization of component sizing for residential battery storage systems

Battery energy storage systems (BESS) coupled with rooftop-mounted residential photovoltaic (PV) generation, designated as PV-BESS, draw increasing attention and market penetration as more and more such systems become available. The manifold BESS deployed to date rely on a variety of different battery technologies, show a great variation of battery size, and power electronics dimensioning. However, given today's high investment costs of BESS, a well-matched design and adequate sizing of the storage systems are prerequisites to allow profitability for the end-user. The economic viability of a PV-BESS depends also on the battery operation, storage technology, and aging of the system. In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-art PV-BESS to determine its optimal parameters. Using a linear optimization method, a cost-optimal sizing of the battery and power electronics is derived based on solar energy availability and local demand. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, feed-in remuneration, and battery aging. Using up to date technology-specific aging information and the investment cost of battery and inverter systems, three mature battery chemistries are compared; a lead-acid (PbA) system and two lithium-ion systems, one with lithium-iron-phosphate (LFP) and another with lithium-nickel-manganese-cobalt (NMC) cathode. The results show that different storage technology and component sizing provide the best economic performances, depending on the scenario of load demand and PV generation.Web of Science107art. no. 83

Novel point-to-point scan matching algorithm based on cross-correlation

The localization of mobile robots in outdoor and indoor environments is a complex issue. Many sophisticated approaches, based on various types of sensory inputs and different computational concepts, are used to accomplish this task. However, many of the most efficient methods for mobile robot localization suffer from high computational costs and/or the need for high resolution sensory inputs. Scan cross-correlation is a traditional approach that can be, in special cases, used to match temporally aligned scans of robot environment. This work proposes a set of novel modifications to the cross-correlation method that extend its capability beyond these special cases to general scan matching and mitigate its computational costs so that it is usable in practical settings. The properties and validity of the proposed approach are in this study illustrated on a number of computational experiments.Web of Scienceart. ID 646394

Comparison of IMU Measurements of Curling Stone Dynamics with a Numerical Model

Abstract Despite almost a century of research, the question of what causes a curling stone to curl (move perpendicular to its initial direction of motion) has no complete answer. Many hypotheses have been formulated, but none has been able to account quantitatively for the full magnitude of the observed curl. The objective of this research was to equip a curling stone with an inertial measurement unit (IMU) and measure its motion, in order to verify a previously published, numerical model of curling stone dynamics. Low cost, small size, accuracy, ease of programming and operation, wireless data communication, and a data-sampling rate near 1 kHz, were selection criteria and constraints for the instrument package. We used the MicroStrain 3DM-GX4-25 system. This is a MEMS-based IMU with a tri-axial gyroscope and a tri-axial linear accelerometer. It was mounted and interfaced with a Bluetooth transmitter, on a curling stone handle. The data were streamed to a host laptop and displayed graphically in real time. Post-processing of the data included filtering and time-integration in order to obtain linear and angular velocities, and displacements. We have compared our experimental results with trajectory data calculated using a previously published numerical model, based on a thermodynamic approach to ice friction. While the observed longitudinal and angular motions are captured reasonably well by the model (errors of about 5% or less), no curl is predicted by the model

Acetylcholinesterase Inhibition of Diversely Functionalized Quinolinones for Alzheimer's Disease Therapy

In this communication, wereport the synthesis and cholinesterase (ChE)/monoamine oxidase (MAO) inhibition of 19 quinolinones (QN1-19) and 13 dihydroquinolinones (DQN1-13) designed as potential multitarget small molecules (MSM) for Alzheimer¿s disease therapy. Contrary to our expectations, none of them showed significant human recombinant MAO inhibition, but compounds QN8, QN9, and DQN7 displayed promising human recombinant acetylcholinesterase (hrAChE) and butyrylcholinesterase (hrBuChE) inhibition. In particular, molecule QN8 was found to be a potent and quite selective non-competitive inhibitor of hrAChE (IC50 = 0.29 M), with Ki value in nanomolar range (79 nM). Pertinent docking analysis confirmed this result, suggesting that this ligand is an interesting hit for further investigation.R.A., M.S., P.B., and K.M. were supported by European Regional Development Fund/European Social Fund (ERDF/ESF, project PharmaBrain, no. CZ.02.1.01/0.0/0.0/16_025/0007444), University of Hradec Kralove (no. SV2113-2019, VT2019-2021), and EU COST action CA15135 MuTaLig. J.M.C. thanks Ministerio de Economía (MINECO, SAF2015-65586-R) and Universidad Camilo José Cela (UCJC, grants UCJC 2020-03, and UCJC 2020-33) for support

THE DIFFERENCE IN THE MUSHROOMS YIELD (Agaricus bisporus Imbach) GROWN USING TWO DIFFERENT CACing METHODS

Cilj pokusa bio je ustanoviti postoji li razlika u prinosu šampinjona, ako se u proizvodnji koriste dvije CACing metode. U pokusu su korištene metoda sa „spawnom“ i metoda s proraslim kompostom. Rezultati pokusa pokazali su da nije bilo statistički značajne razlike između navedenih metoda. Stoga se može zaključiti da su obadvije metode dobre. Problem bi se mogao javiti kod umiješanja proraslog komposta u pokrivku zbog moguće zaraze patogenima, dok s druge strane „spawn“ materijal je skuplja opcija. Stoga bi možda ipak bolja bila opcija umiješanja „spawna“ s obzirom na sigurnost po pitanju patogena.The aim of the experiment was to determine the mushrooms yield difference using two CACing methods. In the experiment“spawn” and overgrowing compost methods were used. The test results showed that there were no statistically significant differences between these methods. It can be concluded that both methods are good. The problem could occur in blending overgrowing compost because of possible contamination with pathogens, while on the other hand "spawn" material is a more expensive option. Therefore, it might still be a better option blending "spawn" to protect from pathogens

Impact of Digital Transformation on the Energy Sector: A Review

Digital transformation is a phenomenon introduced by the transformative power of digital technologies, and it has become a key driver for the energy sector, with advancements in technology leading to significant changes in the way energy is produced, transmitted, and consumed. The impact of digital transformation on the energy sector is profound, with benefits such as improved efficiency, cost reduction, and enhanced customer experience. This article provides a review of the impact of digital transformation on the energy sector, highlighting key trends and emerging technologies that are transforming the sector. The article begins by defining the concept of digital transformation, describing its scope, and explaining two conceptual frameworks to provide a deep understanding of the concept. This article then explores the benefits of digital transformation, examines its impact, and identifies its enablers and barriers. Each source examined was analyzed to extract qualitative results and assess its contribution to the researched topic. This paper also acknowledges the challenges posed by digital transformation, including concerns about cybersecurity, data privacy, and workforce displacement. Finally, we discuss the potential developments that are expected in the future of digital transformation in the power sector and conclude that digital transformation has the potential to significantly improve the energy sector’s efficiency, sustainability, and resiliency

Energy management of buildings with energy storage and solar photovoltaic: A diversity in experience approach for deep reinforcement learning agents

Deep reinforcement learning (DRL) is a suitable approach to handle uncertainty in managing the energy consumption of buildings with energy storage systems. Conventionally, DRL agents are trained by randomly selecting samples from a data set, which can result in overexposure to some data categories and under/no exposure to other data categories. Thus, the trained model may be biased towards some data groups and underperform (provide suboptimal results) for data groups to which it was less exposed. To address this issue, diversity in experience-based DRL agent training framework is proposed in this study. This approach ensures the exposure of agents to all types of data. The proposed framework is implemented in two steps. In the first step, raw data are grouped into different clusters using the K-means clustering method. The clustered data is then arranged by stacking the data of one cluster on top of another. In the second step, a selection algorithm is proposed to select data from each cluster to train the DRL agent. The frequency of selection from each cluster is in proportion to the number of data points in that cluster and therefore named the proportional selection method. To analyze the performance of the proposed approach and compare the results with the conventional random selection method, two indices are proposed in this study: the flatness index and the divergence index. The model is trained using different data sets (1-year, 3-year, and 5-year) and also with the inclusion of solar photovoltaics. The simulation results confirmed the superior performance of the proposed approach to flatten the building’s load curve by optimally operating the energy storage system

State of Charge and Capacity Tracking in Vanadium Redox Flow Battery Systems

The vanadium redox flow battery electrolyte is prone to several capacity loss mechanisms, which must be mitigated to preserve electrolyte health and battery performance. This study investigates a simple and effective technique for the recovery of capacity loss arising from symmetrical mechanisms via automatic electrolyte rebalancing. However, chemical or electrochemical techniques must be used to mitigate capacity loss from asymmetrical mechanisms (e.g., air oxidation of V2+), which requires knowledge of the oxidation states present in the electrolytes. As such, this study assesses the suitability of SOC tracking via electrolyte absorption for independent monitoring of the anolyte and catholyte within an existing VRFB system. Testing is performed over cycling of a 40 cell, 2.5 kW with 40 L of electrolyte. Optical monitoring is performed using a custom-made flow cell with optical paths (interior cavity thicknesses) ranging from 1/4″ to 1/16″. Light transmitted through the cell by a 550 lumen white light source is monitored by a simple photodiode. The electrolyte rebalancing mechanism displayed success in recovering symmetrical capacity losses, while optical monitoring was unsuccessful due to the high absorbance of the electrolyte. Potential improvements to the monitoring system are presented to mitigate this issue