A modular IoT platform for next-generation smart homes: Architecture, real-time control, and edge AI readiness

Physiological performance in aquaculture: Using physiology to help define optimal conditions for growth and environmental tolerance

<span>Despite their complexity and uncertainty, air conditioning systems should provide the optimal thermal conditions in a building. These controller systems should be adaptable to changes in environmental parameters. In most air conditioning systems, today, there are On/Off controllers or PID in more advanced types, which, due to different environmental conditions, are not optimal and cannot provide the optimal environmental conditions. Controlling thermal comfort of an air conditioning system requires estimation of thermal comfort index. In this study, fuzzy controller was used to provide thermal comfort in an air conditioning system, and neural network was used to estimate thermal comfort in the feedback path of the controller. Fuzzy controller has a good response given the non-linear features of air conditioning systems. In addition, the neural network makes it possible to use thermal comfort feedback in a real-time control.</span>

Wire-mesh capped deposition sensors: Novel passive tool for coarse fraction flux estimation of radon thoron progeny in indoor environments

Academic buildings are the main gathering places in universities and colleges. The crowd flow could cause a change in environmental parameters of buildings. In other words, the change in environmental parameters in buildings can be somewhat reflective of the crowd flow. Therefore, field measurements of the crowd flow and environmental parameters in an academic building at a university were conducted in this study. During the periods of 7:30–8:00 and 13:20–13:50, the average speed of the crowd was the highest, which was about 1.2 m/s; the CO2 concentration was low, which was about 750 ppm. In the periods of 9:20–9:50 and 15:10–15:40, the average speed of people walking in the opposite directions was the lowest, which is 0.42 m/s; however, the CO2 concentration could reach 1800 ppm. Test results showed that the variations of CO2 concentrations were inversely related to the average speed of the crowd in the evacuation passage, except for the periods of 7:30–8:00 and 13:20–13:50. Spatial separation and physical separation could be used in the management of personnel flow in the academic building. The results may provide reference for the management of the crowd flow in similar academic buildings of other universities.

Wireless sensor networks have become widely used in industrial automation systems due to their ease of deployment, flexibility, and cost-effectiveness. They provide real-time monitoring, diagnostics, and control of technological processes without the need for complex cabling infrastructure. However, the operation of wireless sensor networks in production environments is accompanied by risks associated with limited energy resources of nodes, the impact of electromagnetic interference, data transmission delays, the inability to guarantee communication stability, and vulnerability to cyberattacks. These threats are exacerbated in complex environments where equipment is located in hard-to-reach places, and the network has limited bandwidth and variable topology. Such conditions require the construction of multi-level structures for network health analysis, risk assessment, and adaptive management. The aim of the research is to develop two functional modules of a multi-level ontology:a risk assessment module and a network description module,that allow for an integrated analysis of threats, vulnerabilities, and wireless sensor network parameters, taking into account their changing state. The research methodology is based on the construction of formalized mathematical models: the network description is implemented through a graph representation with the parameters of nodes, connections, and their dynamics, while the risk assessment is performed using a multifactor model that takes into account theprobability of threats, the level of their impact, the criticality of network components, and external risks. The article presents examples of the application of modules based on typical production scenarios that demonstrate the relationship between the structural description of the network and the dynamic assessment of threats. Information from the network description module is used to calculate risks in real time, while the results of the risk analysis affect the dynamic adjustment of network operation parameters. The scientific novelty of the research lies in the integration of two formalized models within a single ontological system of risk-oriented wireless sensor network management. The practical significance lies in the possibility of implementing the proposed approaches in real industrial conditions to increase the reliability, flexibility, adaptability and information security of sensor networks. The proposed system is the basis for building self-adjusting smart networks capable of independently responding to changes in technical condition, threats and environmental parameters.

The Study investigated the mites fauna obtained from dust of poultry and houses located at osmanabad district (Maharashtra state). The impact of changes in environmental parameters like humidity, temperature and rainfall in three different seasons on the population of mites was studied. This study revealed 6 different species of mites are found which are Dermatophagoides farinae Leiodinychus krameri, Prodinychus sp.(deutonymph,) Dermanyssus gallinae, and Urodiaspis tecta Dermatophagoides pteronyssinus. The impact of changes in environmental parameters on these mites population in three different seasons of monsoon, summer and winter were recorded in the course of this study. It was observed that weather significantly impacts the prevalence of mites the dust of poultry and houses. Maximum numbers of mites were found during monsoon as compared to both winter and summer.

Background Oil and oil product spills cause significant economic losses and damage to the environment. The increase in the number of accidents in the production, transportation, storage and use of fuel for its intended purpose necessitates the development and implementation of leakage detection systems. The efficiency of such systems is due to the performance of sensors that detect specific changes in the environment parameters during fuel leakages. Aims and Objectives Development of the sensor light oil products leakage detector (gasoline, kerosene) in closed rooms and closed volumes (warehouses, fuel pumping stations), different from the existing ones in efficiency and ease of maintenance and characterized by high reliability, speed, selectivity, long «life». Methods The operation of the proposed fuel leak sensor is based on the principle of piezo-quartz microweighing, based on the transformation of the analytical signal resulting from the interaction of volatile fuel components with the sorption coating of quartz electrodes of the AT-srez, into a physical signal - the change in the oscillation frequency. As a sorption coating of piezoelectric quartz electrodes, multilayer carbon nanotubes (MCNTs) showing resistance to aggressive vapors of hydrocarbon fuel, high sorption capacity and the ability to regenerate were used. To improve the reliability of the fuel leakage detector and prevent false positives, two identical detection cells with modified multilayer carbon nanotubes (piezo sensors) were included in its design in parallel. The detection cells are located in the place of probable fuel leakage (joints of pipelines, joints of hoses) at a height not more than 15 cm from the floor so that the fuel vapors diffuse freely from the spill site into the near-sensor space. The signaling device of the sensor is triggered by the simultaneous and identical change of the analytical signals of two piezosensors. Results The piezosorption sensor is characterized by high reliability (the probability of false positives is not more than 1,5 %); speed (the time from the beginning of leakage to the decision by the operator does not exceed 20 seconds); independence of operation from changes in environmental parameters in a wide temperature range (from minus 5 °C to 35 °C). The «lifetime» of the piezosensor based on multilayer carbon nanotubes is not less than 2500 cycles of «sorption - desorption» of fuel vapor, after which it is easily replaced by a similar one. The sensor was tested in the laboratory of FSBIHC «The Center of Hygiene and Epidemiology» and applied for the monitoring of kerosene in the air station, pumping fuel at the airport to Primorsko-Akhtarsk.

The national standard of length in Japan changed to a femtosecond optical frequency comb (FOFC) in July 2009. The center frequency of the FOFC standard is 1560 nm, which is in the transmission band (C-band) of the communication optical fiber. Thanks to this fact, through the communication fiber networks, an FOFC can be delivered to everywhere at anytime. That means everyone at everywhere may access the high-accuracy length standard via communication fiber networks at anytime. An FOFC is a stabilized pulse laser. In other words, an FOFC is a phase-coherent combination of several hundreds of thousands of wavelengths. Therefore, this fact means that there are several hundreds of thousands of different wavelengths and their combination, adjacent pulse repetition interval length (APRIL), which can be used as a length scale. Based on this idea, we proposed the APRIL-based method. APRIL-based length measurement method uses an APRIL (the physical length associated with the pulse repetition period) as a ruler for measuring distance. In this work, we show how the uncertainty in length conversion is affected by the change in environmental parameters via the sensitivity coefficients of refractive index under an actual experimental environment.

Neogene coastal sediments of the Mediterranean provide an excellent laboratory for a quantitative study of palaeoenvironmental parameters and their response to climate change. In order to examine change in environmental parameters during deposition of Tortonian limestone of southern central Crete, we use integrated field and biofacies analysis together with a detailed study of foraminfera and non-geniculate red algae. Patterns in the relative abundance of non-geniculate coralline red algae are interpreted by comparison with data from modern non-geniculate coralline red algae and with additional information from the studied sediments. Based on these integrated datasets, four red algal associations are identified: a Lithophyllum-dominated association restricted to the upper photic zone in warm-temperate environments, a Lithothamnion-dominated association found in the lower photic zone in warm-temperate environments, a Spongites-dominated association typical for shallow warm-temperate to tropical environments and an association with dominant Mesophyllum which is characteristic for the lower photic zone in warm-temperate to tropical environments. We introduce coralline red algal indices in order to quantify changes in environmental parameters. We recognise four warm intervals within a succession of the Tortonian limestones in southern central Crete. During the most extensive interval, widespread coral carpets formed under prevalent oligotrophic conditions. Analysis of the stratigraphic architecture shows that warm intervals are related to sea-level highstands and therefore may reflect global climatic processes.

This study examines the effect of a peptide complex extracted from chicken egg yolk on the action of the immune system of kuruma shrimp, Marsupenaeus japonicus, on pathogens as well as changes in environmental parameters. In the design of three independent experiments, we defined the treated shrimp or the control shrimp as shrimp receiving diet with or without peptide complex administration, respectively. In the first experiment, the shrimp were challenged by Vibrio sp. after 1 week of feeding; the results showed that the survival rates of the treated shrimp were 69%. In the other experiments, the shrimp were exposed to low salinity or high temperature to analyze the changes in various immunological parameters. In a low‐salinity test, results showed that the total hemocyte count (THC) of the treated group was significantly higher than that of the control group within 24 hr. In a high‐temperature test, THC and phenoloxidase activity of the shrimp in the treated group displayed significantly higher values than that in the control group during 48 hr. In short, the administration of the peptide complex was significantly effective in the prevention of disease and enhancement of the tolerance of kuruma shrimp to environmental changes.

The system of medical balance bed is the research project of combining of the dynamics theory and the automatic control theory and technology. The control system of the balance bed is a complex, unstable, nonlinear system. To achieve balance of the bed, well-designed control system is particularly important. Presently, there are many different types of control methods, but the system of medical balance bed needs to control balance automatically and law regulating the parameters of the system in real-time, and to adapt to the impact of environmental changes, parameters change of the system itself and external interference, etc, so that the whole system can run in the best condition. Based on comparison and analysis of several typical control algorithms, this paper puts forward a neural network adaptive PID control algorithm. It can not only suppress the external disturbance, and adapt to the impact of environmental changes and parameter changes of the system itself, to some extent, but also can effectively eliminate the modeling error and other factors. This paper discusses the neural network adaptive PID control algorithm, and simulates using MATLAB to prove that the neural network adaptive PID control algorithm is better than PID control algorithm.

To meet the energy demand, solar photovoltaic has already emerged as a convincing renewable energy technology. Solar Photovoltaic (PV) modules are one of the most effective, sustainable, and eco-friendly systems in recent world. Different types of PV solar technologies like Mono crystalline silicon, poly crystalline silicon, amorphous silicon, thin film are the most popular technologies to produce electricity. Their module performance and efficiency depend on the electrical and environment parameters of the PV materials. This paper presents some theoretical evaluations for variation in the efficiency of energy for different types of photovoltaic (PV) module under changes of environmental parameters. A proper comparison is developed among the mono-crystalline, polycrystalline and amorphous material using the model parameters. This work also illustrates the variation of fill factor and efficiency of a specific photovoltaic module under real operating conditions. MATLAB is used to investigate the P-V characteristics to evaluate the maximum power point of solar photovoltaic cell considering the effect of temperature and solar radiation.

BackgroundRegulatory networks often employ the model that attributes changes in gene expression levels, as observed across different cellular conditions, to changes in the activity of transcription factors (TFs). Although the actual conditions that trigger a change in TF activity should form an integral part of the generated regulatory network, they are usually lacking. This is due to the fact that the large heterogeneity in the employed conditions and the continuous changes in environmental parameters in the often used shake-flask cultures, prevent the unambiguous modeling of the cultivation conditions within the computational framework.ResultsWe designed an experimental setup that allows us to explicitly model the cultivation conditions and use these to infer the activity of TFs. The yeast Saccharomyces cerevisiae was cultivated under four different nutrient limitations in both aerobic and anaerobic chemostat cultures. In the chemostats, environmental and growth parameters are accurately controlled. Consequently, the measured transcriptional response can be directly correlated with changes in the limited nutrient or oxygen concentration. We devised a tailor-made computational approach that exploits the systematic setup of the cultivation conditions in order to identify the individual and combined effects of nutrient limitations and oxygen availability on expression behavior and TF activity.ConclusionIncorporating the actual growth conditions when inferring regulatory relationships provides detailed insight in the functionality of the TFs that are triggered by changes in the employed cultivation conditions. For example, our results confirm the established role of TF Hap4 in both aerobic regulation and glucose derepression. Among the numerous inferred condition-specific regulatory associations between gene sets and TFs, also many novel putative regulatory mechanisms, such as the possible role of Tye7 in sulfur metabolism, were identified.

The paper encompasses the study of the evolution of the functional parameters (suction air mass flow rate, plant efficiency, etc.) of naval gas turbines propulsion systems at changes in environmental parameters. The operational parameters of a gas turbine propulsion system and their evolution in relation to the modification of the environmental status parameters have been highlighted by calculation. Another sensitive area in the operation of gas turbine installations is the transient operating modes (stopping, starting, accelerating and decelerating sequences of the installation), which were highlighted by determinating of operating parameters on board the ship.

This paper presents the influence of selected natural environment parameters, i.e. temperature, relative humidity, electromagnetic interference and pressure on the operation of detectors used in fire signalling systems (FSS). Continuous diagnostics of environmental parameters, in particular their changes over time, may contributed to the lower numbers of false alarms in FSSs. Thus, development of an operating procedure for such elements in the continuously changing environment is an important functional issue related to operation of selected FSS detectors. Fire detector sensors detect various characteristic parameters of fire (CPF), such as smoke, temperature or electromagnetic radiation. The values of CPF depend on the changing environmental parameters - rooms, traffic routes, warehouses, etc. where detectors reacting to various test fires TF1 to TF9 are present.