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Automatic assembly equipment is the key to improving the efficiency and quality of workpiece assembly. The precision of assembly directly influences the overall quality of the assembled product. To optimise the position control accuracy in the automatic assembly equipment, a variable universe fuzzy proportional integral (VUFPI) controller optimised by the sparrow search algorithm (SSA) is developed in this paper. The developed controller adopts the SSA to adjust in real time the universe of the fuzzy controller according to the deviation of the servo system. The servo system model is established to evaluate the performance of the proposed SSAVUFPI controller; furthermore, the SSA-VUFPI controller is implemented in the automatic assembly equipment for experimental evaluation. The analysis results demonstrate that the proposed SSA-VUFPI controller is capable of improving the anti-interference ability and position accuracy of the servo system compared to traditional PI, VUFPI, and currently used back propagation neural network proportional-integralderivative (BP-PID), fractional-order PID (FOPID), and SSAPID controllers. Moreover, it effectively improves the position accuracy of the workpiece and ultimately improves the quality of the assembly. [ABSTRACT FROM AUTHOR]

Aiming at energy saving and consumption reduction, this project applies the technology of combined heating and cooling heat pump to ecological building design. The combined hot and cold system is an integrated control system, which utilizes the solar system and heat pump technology (air source heat pump, water source heat pump) to complement each other based on changes in the outdoor environment, thus providing users with hot water heating and cold water cooling in winter. After installing a new heating and cooling system, coupled with well-equipped automatic control equipment, the heating coal consumption has been significantly reduced, and the emissions of CO2, SO2 dust, and other pollutants have also been correspondingly reduced. Compared with the cold and hot split supply system using electric refrigeration and thermal heating, the winter and summer sharing of the cold and hot combined supply device not only improves energy utilization efficiency, but also saves investment in heat source construction, thereby reducing costs and environmental pollution. [ABSTRACT FROM AUTHOR]

Litchi, a succulent and perishable fruit, presents a narrow annual harvest window of under two weeks. The advent of smart agriculture has driven the adoption of visually-guided, automated litchi harvesting techniques. However, conventional approaches typically rely on laboratory-based, high-performance computing equipment, which presents challenges in terms of size, energy consumption, and practical application within litchi orchards. To address these limitations,we propose a real-time litchi detectionmethodology for complex environments, utilizing portable, low-energy edge computing devices. Initially, the litchi orchard imagery is collected to enhance data generalization. Subsequently, a convolutional neural network (CNN)-based single-stage detector, YOLOx, is constructed to accurately pinpoint litchi fruit locationswithin the images. To facilitate deployment on portable, low-energy edge devices, we employed channel pruning and layer pruning algorithms to compress the trained model, reducing its size and parameters. Additionally, the knowledge distillation technique is harnessed to fine-tune the network. Experimental findings demonstrated that our proposed method achieved a 97.1% compression rate, yielding a compact litchi detection model of a mere 6.9 MB, while maintaining 94.9% average precision and 97.2% average recall. Processing 99 frames per second (FPS), the method exhibited a 1.8-fold increase in speed compared to the unprocessed model. Consequently, our approach can be readily integrated into portable, low-computational automatic harvesting equipment, ensuring real-time, precise litchi detection within orchard settings. [ABSTRACT FROM AUTHOR]

Control systems in industry today are increasingly sophisticated. Many modern factories use automatic equipment control systems, such as the water factory industry, which uses a programmable logic controller (PLC) based control system because its use will be more efficient and more practical. A programmable logic controller device can be used to control mineral water bottle-filling devices by utilizing the input-output (I/O) facilities contained in the device. The input devices on the PLC can be push buttons and infrared sensors, while the PLC output can be actuator components such as DC motors that function as conveyor drivers, solenoid valves and linear solenoids. The system for filling water into bottles is very important in the production of drinking water because it can optimize the final production process. So that when filling bottles, the volume of water corresponds to what is released and does not exceed the capacity of the bottle, automatic filling is needed. Filling water into bottles is done by storing the water in a water tank before the water is put into bottles. This water-filling system is very useful, both in terms of production effectiveness and saving production costs. By using this system, the production process is more effective, more efficient and easier to carry out because filling times are accurate and do not require much human labour, which ultimately results in savings in production costs. [ABSTRACT FROM AUTHOR]

In most industrial processes, it is required to know the dynamics of the process to achieve better adjustment and precision of the controllers; often, obtaining models by solving equations is complex to perform. With the development of technology, data can be obtained in real-time from the process. Identification methods are of great help in obtaining mathematical models experimentally, which is why engineering students must carry out practices in this countryside. A fluid heating-cooling plant is designed and built to have equipment for automatic control and instrumentation practices. The model was obtained from input-output data using parametric identification techniques; tests were carried out with ARX, ARMAX, OE, and BJ models, and the model was selected using similarity percentage, step response, and residual analysis. The best results were obtained with the BJ 22321 model, reaching a similarity percentage of 81.71%, for the model selection, parsimony was also considered, i.e., the one with the lowest number of poles and zeros. For the adjustment of the controller, the IMC-PID tuning was used. The response was tested with different controllers, and the PID-Fuzzy with 25 rules was selected; with this controller, a 10% surplus level percentage and a stabilization time of 200 seconds are obtained. [ABSTRACT FROM AUTHOR]

A high portion of electric consumption is air conditioning in householders or offices, reaching 42%. Therefore, it is necessary to automatically regulate air conditioning operations for energy saving using a control system, usually involving its hardware. As another option, the control system also involves electronic devices and software. This research developed an automatic control system using an ESP32 microcontroller integrated into the Blynk-based internet of things (IoT) for energy-saving air conditioning. The ESP32 was programmed using Arduino IDE and combined with a motion sensor to maximize energy saving. The motion sensor was a trigger to turn on the system. The recorded data were current, voltage, power, temperature, and motion detection. Based on the recorded power, the consumed energy was computed using trapezoidal and Simpson's composite rules of numerical integrations and ordinary methods. The testing was conducted in conventional, manual, and automatic operations. The yielded automatic control system operated adequately. The testing results revealed that the automatic operation saved 1.15 kWh (15.00%),0.99 kWh (13.66%), and 1.14 kWh (14.87%) average daily energy compared to the conventional operation, respectively, by using the ordinary, Simpson's composite rule, and trapezoidal composite rule computations. While the automatic compared to the manualmethodssaved1.68 kWh (20.44%), 1.78 kWh (22.14%), and 1.66 kWh (20.24%), respectively, for the same computations. Thus, the automatic system considerably saved energy compared to conventional and manual operations. Moreover, these energy savings were also higher than some previous research on air conditioning energy savings. [ABSTRACT FROM AUTHOR]

According to the "World Population Prospects 2022" released by the United Nations in August 2022, the world will officially enter an "aging society". In order to provide the elderly with an improved quality of daily life, "health promotion" and "prevention of disease" will be important. With respect to care of the elderly, the concepts of "therapeutic environment" and "green care" have been explored and developed. Therefore, in this study, we combine the currently popular Internet of Things (IoT) into an aquaponics system and proposes a smart green care system (SGCS). The proposed system uses face recognition technology to record the labor and rehabilitation history of the elderly, in combination with environmental data analysis, to enable automatic control decisions for equipment in conjunction with a voice control system to reduce the obstacles faced by the elderly in operating the information system. It also uses image recognition technology to monitor and notify about plant diseases and insect pests to achieve automatic management and enhance the interaction between the elderly and the SGCS through human–computer interaction. The SGCS allows the elderly to guide it to participate in appropriate activities through direct contact with the natural environment, thereby enhancing the quality of green healing life. In this study, taking long-term care institutions as an example, we verified proof of concept (PoC), proof of service (PoS), and proof of business (PoB), confirming the feasibility of the SGCS. The SGCS proposed in this study can be successfully used in long-term care institutions and various other environments, such as medical units and home care contexts. It can take full advantage of the functions associated with the concept of "healing environment" and "green care" widely recognized by users. Therefore, it can be widely used in the field of long-term care in the future. [ABSTRACT FROM AUTHOR]

Aiming at the problems of the low efficiency of manual pesticide application in the greenhouse, the narrow operating space of plant protection machinery, and the possibility of poisoning the pesticide applicators due to the closed space, a high-pressure atomization spraying equipment for the greenhouse was designed. The spraying equipment adopts two-way communication between PLC and HMI to realize the adjustment of atomization pressure and atomization flow, and the control equipment completes automatic spraying. To determine the best working parameters of the spraying equipment, orthogonal tests were conducted with atomization pressure and atomization nozzle aperture as the test factors and the coefficient of variation of the fog volume distribution as the evaluation index. The optimum combination after parameter optimization was determined to be as follows: atomization pressure of 4 MPa, atomization nozzle aperture of 0.4 mm. The test results under the optimal parameters showed that the spray distribution coefficient of variation was 10.5%, and the uniformity of fog volume distribution was good to meet the requirements of spraying in greenhouses. [ABSTRACT FROM AUTHOR]

Copyright of Revista de la Universidad del Valle de Guatemala is the property of Universidad del Valle de Guatemala and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In these days there are rapid changes in the environment which causes the major effects in the world. The farms are having the certain requirement to maintain the environment. Manually this process cost a huge Manuel work. In large poultry's it is hard to check and maintain the required environment in the suitable level for the animals in the farm. we proposed a solution for the problem by designing the automatic environmental monitoring system in the Animal forms. Here we are detecting the hazard situations and working on them to retain the environmental conditions in that farm to normal. The controller or maintenance officer of that farm can check these values either in the control room in pc or in the mobile screen. We are using the latest Zigbee technology to transfer the data from the control board to the computer. In case of the temperature fluctuations and humidity fluctuations it is hard for the animals to survive in that hard temperature. So when there is low labor available or in night times then this board plays key role to control the situations. When the situations are critical then this automatic environmental monitoring system works effectively to bring the situations under control. We designed this controlling process in a low cost manner so when compared to the labor wages here it is very low cost. When there are more number of farms in a particular area then we can access the data of all the farms at a time in the monitoring system. Here we are using the short range communication device for high speed. [ABSTRACT FROM AUTHOR]

User comfort in higher-level Automated Vehicles (AVs, SAE Level 4+) is crucial for public acceptance. AV driving styles, characterised by vehicle kinematic and proxemic factors, affect user comfort, with "human-like" driving styles expected to provide natural feelings. We investigated a) how the kinematic and proxemic factors of an AV's driving style affect users' evaluation of comfort and naturalness, and b) how the similarities between automated and users' manual driving styles affect user evaluation. Using a motion-based driving simulator, participants experienced three Level 4 automated driving styles: two human-like (defensive, aggressive) and one machine-like. They also manually drove the same route. Participants rated their comfort and naturalness of each automated controller, across twenty-four varied UK road sections. We calculated maximum absolute values of the kinematic and proxemic factors affecting the AV's driving styles in longitudinal, lateral, and vertical directions, for each road section, to characterise the automated driving styles. The Euclidean distance between AV and manual driving styles, in terms of kinematic and proxemic factors, was calculated to characterise the human-like driving style of the AV. We used mixed-effects models to examine a) the effect of AV's kinematic and proxemic factors on the evaluation of comfort and naturalness, and b) how similarities between manual and automated driving styles affected the evaluation. Results showed significant effects of lateral and rotational kinematic factors on comfort and naturalness, with longitudinal kinematic factors having a less prominent effect. Similarities in vehicle metrics, such as speed, longitudinal jerk, lateral offset, and yaw, between manual and automated driving styles, enhanced user comfort and naturalness. This research facilitates an understanding of how control features of AVs affect user experience, contributing to the design of user-centred controllers and better acceptance of higher-level AVs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Sciences & Information Technology is the property of Arab Journal of Sciences & Research Publishing (AJSRP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Automatically controlled machine tools have been used extensively in the industrial field, and fault analysis methods have garnered increasing attention. This paper first describes the software and hardware design of a machine tool and then presents a fault analysis of the machine tool. The fault types of machine tools are analyzed. A signal is obtained from a vibration sensor, the characteristic value is extracted, and the fault is analyzed using a back-propagation neural network (BPNN). The experimental results show that the BPNN yields the best performance when the structure is 8-9-8, and its recognition rate is 97.22% for different types of faults. Meanwhile, the recognition rate of naive Bayes is only 76.73%, and that of a support vector machine is only 85.55%, which is significantly lower than that of the BPNN. The results show that the BPNN is effective in fault analysis and can be promoted and applied more extensively. [ABSTRACT FROM AUTHOR]

Cycle identification via the rainflow‐algorithm is implemented online in a model predictive controller (MPC) for Li‐ion batteries. This is achieved by externalization of the cycle identification from the optimization problem. The limitation for cyclic aging estimation due to short prediction horizons is overcome by updating and utilizing a State of Charge memory. Furthermore, a comprehensive plant model for Li‐ion batteries is presented with novel submodels for calendric and cyclic aging. The novel MPC is implemented in the ACADO Toolkit and tested with the aforementioned plant model. Simulation results indicate that—even without tuning—the novel MPC clearly outperforms a rule‐based controller and an extensively tuned MPC from literature. [ABSTRACT FROM AUTHOR]

Performance limit evaluation of automatic driving system before putting into the market is critical for driving safety. The evolution test by genetic algorithm (GA) is a method by iteratively generating new test scenarios according to the last test results. To avoid its blind search for better efficiency, a scenario complexity index is proposed to measure the test effectiveness indirectly and guide the evolution process under the assumption that a complex scenario is more challenging to realise automatic driving. The traditional crossover and mutation operators are modified to generate more complex scenarios to improve the test efficiency. The advantage of the improved crossover/mutation operators in increasing the offspring's scenario complexity index is analysed in theory. Moreover, the influence of the design parameters on the evolution test process and the global convergence are also discussed. The new evolution test by this improved GA has been applied to find the collision condition of a parallel automatic parking system to validate its effectiveness. [ABSTRACT FROM AUTHOR]

The increasing popularity and maturity of plasma actuators for many flow control applications requires a common standard for plasma actuator performance evaluation. In the present work, a comprehensive comparative study of existing and new evaluation measures is presented, based on results from identical plasma-actuator configurations. A power-flow diagram is introduced that covers the entire range of power stages from the energy source to the flow-control success. All individual power stages are explained, existing controversial definitions are clarified, and an evaluation guideline is applied to previously obtained data. Finally, the defined systematic analysis is applied to the results of a recently conducted plasma-actuator in-flight experiment. [ABSTRACT FROM AUTHOR]

In recent years, people are committed to developing new technologies and technologies for energy storage and conversion, environmental detection, high-performance sensors and energy security, and other aspects of the increasingly prominent problems in the field of environmental and biosafety. The purpose of this paper is to explore the manufacturing system and automatic synthesis equipment of carbon nanomaterials, understand the control device and control method, and analyze the structure and morphology characteristics of three kinds of carbon nanomaterials produced by carbon nanomaterial manufacturing system by X-ray diffraction and infrared spectroscopy. The results show that the carbon nanomaterial manufacturing system and automatic synthesis system in this paper solve the problems of high cost, low efficiency, and small scale of the existing carbon nanomaterials manufacturing and achieve the precision control of automatic production, so that the productivity is increased by 20%–35%, and the cost is reduced by 15%–30%. Therefore, they are widely used in the fields of science and technology, environmental protection, and intelligent manufacturing broad prospects. Carbon nanotube manufacturing equipment and automatic synthesis equipment have great production advantages, which can greatly improve the quality and efficiency of carbon nanomaterials. UPY, GO, and UGO carbon nanomaterials produced by carbon nanotube manufacturing equipment are not easy to fall off from the materials. When the wavelength is 500 nm, the absorption frequency of the three materials is the largest. With the extension of the spectral wavelength, the absorption frequency of the three materials is reduced by 52%, 33%, and 34.7%, respectively. [ABSTRACT FROM AUTHOR]

In 2018, a German-Dutch project consortium under the scientific direction of the Emden/Leer University of Applied Sciences retrofitted and commissioned the latest rotor development of the Eco-Flettner type on the test ship Fehn Pollux of the Leer-based shipping company Fehn Ship Management. Main design features are both upper and lower endplates with large diameter for improved aerodynamic performance and modular manufacturing. The retrofitting concept is groundbreaking in terms of easy transferability to other ships. Upscaling to a significant share of the world merchant fleet could make a substantial and realizable contribution to climate protection in the short term and potentially reduced transport costs in the long term. The most frequently asked question in connection with modern sail drives is about the performance potential and the associated fuel savings. Transparent performance data is required to enable an economic prognosis for the use of Flettner rotors on ships. The Faculty of Maritime Sciences at Emden/Leer University of Applied Sciences has developed an automatic control and monitoring system for Flettner rotors that also records extensive operating and environmental data. The data shows that all previous assumptions and model calculations are basically correct. With regard to the performance potential, the first series of measurements show even higher rotor forces compared with model calculations. This is a further benefit for Flettner rotor efficiency and could help the technology achieve a breakthrough as a building block for low-emission shipping. [ABSTRACT FROM AUTHOR]

The article analyzes the application of product liability concepts to automated products and digitized distribution channels. It points out that automated objects including robots and self-driving automobiles as well as their separate parts are considered as products under the European Union (EU) directive. It describes the categories of defect covering automated products. Also cited is the issue of the ability of third parties to hold a digital platform liable under the directive.

The article describes the fabrication of Twisted Coiled Polymer Actuators (TCPA) and the different elements that compose it. Topics discussed include the initial TCPA manufacturing process, the use of an Arduino Mega with a stepper motor shield for the control system, and the major parts of the device including end plates and motors, carriage and rails, and sensor board.

Temperature in the creep area for piglets will decrease from birth to weaning. To reduce the consumption of electricity and meet the temperature requirement of piglets from birth to weaning, an experiment of variable power heating system of heat lamp compared with constant power heating system of heat lamp was conducted in a scaled pig farm in Northern China. Two units of farrowing room (one unit with 23 farrowing sows and 25 heat lamps of 250 W) in the pig farm were chosen for this study, except for heat lamps, hot water floor heating was provided for piglets. An automatic control system which was composed of ATS (air temperature sensor) and SCM (single chip microcomputer with PID (proportional, integral and derivative) control) and SCR (silicon controlled rectifiers) was used in the test unit and constant power heating system was used in the control unit. The temperature automatic control system can bear 10 000 W. In the test unit, temperature of 30.0 ℃ was set from piglets birth to the age of 7 days, and then reduce temperature by 2.0 ℃ every week till 21 days after birth. In the control unit, heat lamp was with constant power to heat piglets creep areas. Electricity consumption used in the test unit and control unit was recorded by two ammeters, respectively. Behaviors and temperatures in creep area of piglets were recorded and analyzed. Piglets performance was also recorded and analyzed. It was shown that during the first week after birth, both of the heat lamps in the test unit and in the control unit maintain full power operation, the average temperature right below the heat lamp (0.3 m high from the floor) was 27.4 ℃; during the second week, the average temperature right below the heat lamp for the test unit and the control unit were 27.2 and 27.5 ℃, respectively; during the third week, the average temperature right below the heat lamp for the test unit and control unit were 26.8 and 27.4 ℃, respectively. Floor temperature right below the test unit and control unit were 29.5-31.0 and 31.0-30.6 ℃, respectively. In brief, from birth to 21 days, floor temperature right below the heat lamp, side below the lamp and the slatted floor were 29.5-31.0, 28.9-29.5 and 22.9-23.0 ℃, respectively. Lying rates in different areas of right below the heat lamp, side below the lamp and the slatted floor were 40.7%-66.5%, 14.4%-33.4% and 0.9%-8.7%, respectively. Rates of survival of piglets (28 days weaning) in the test unit and control unit were 95.8% and 93.8%, respectively. Average daily gain of piglets (28 days weaning) in the test unit and control unit were 0.198 and 0.193 kg/(head·d), respectively. Using this kind of variable power heating system, the farrowing room can save 1.8 kW·h per lamp per day from 8 days to 14 days after piglets birth, and 2.7 kW·h per lamp per day from 15 days to 21 days after piglets birth. The energy consumption can be saved by 25.4% each batch of production based on 21 days weaning. On condition of electricity price of 0.5215 yuan/(kW·h), 25 heat lamps with 250 W in one farrowing unit and investment of one set of equipment of temperature automatic control with 2 980 yuan, payback period will be 2 a. The temperature automatic control system of heat lamp can not only save energy but also can improve piglets performance. [ABSTRACT FROM AUTHOR]

• Attributes of the trustworthiness of automated subways are grouped into automation- and service-related factors: 'automation trustworthiness' and 'service trustworthiness'. • Automation trustworthiness includes reliability and consistency of automation and operation. Service trustworthiness, on the other hand, includes reliability and reputation of problem detection, resolution and communication, and benevolence and integrity. • Both automation trustworthiness and service trustworthiness appear to significantly contribute to passengers' trust in automated subway services. • Both trustworthiness factors appear to negatively affect passengers' anxiety and fear, mediated by the passengers' sense of certainty and coping potential. Commuters worldwide can now travel to work using unmanned subway services while tourists may travel to holiday destinations on planes that employ automatic flight control equipment. More recently, autonomous buses have made their debut in several cities. Technological advances in transport services, however, are accompanied by challenges to passengers' perceived safety and the acceptability of the technology. While passengers' anxiety and fear appear to reduce their acceptance of new technologies, trust has been shown to positively affect their acceptance of automation and autonomous vehicles. In this vein, the present study investigates the trustworthiness of automated subway services in Korea with regard to passenger anxiety and fear. First, automated subway-specific trustworthiness factors are identified through exploratory factor analysis. Subsequently, the effects of the identified factors on passenger anxiety and fear are examined using structural equation modeling. The results indicate that attributes that contribute to the trustworthiness of automated subways are grouped into automation- and service-related factors: 'automation trustworthiness' and 'service trustworthiness', both of which appear to negatively affect passengers' anxiety and fear, mediated by the passengers' sense of certainty and coping potential. The negative effects of trustworthiness on anxiety and fear indicate that strengthening of the trustworthiness factors must be accompanied with technological advances in transportation. The implications for strengthening the trustworthiness of unmanned automated subways and other transport services employing autonomous features are presented, correspondingly, in this study. [ABSTRACT FROM AUTHOR]

Highlights • A novel adaptive tracking control method is proposed for a tower crane system. • The proposed control method can obtain better tracking performance for tower crane systems in complex working environment. • The payload swing can be effectively suppressed during the tracking process. Abstract As an efficient transportation tool, a tower crane is widely used in construction sites. To improve the working efficiency, some automatic control methods have been proposed for tower crane systems, including some open loop methods, such as input shaping methods, trajectory planning methods, and so on. However, generally, tower cranes usually work in outdoor environment, which are sensitive to unavoidable external disturbances. Additionally, accurate system parameters are hard to obtain, which increases the control difficulty of the tower crane system. Considering these factors, in this paper, we propose an adaptive tracking control method, which achieves satisfactory tracking performance w.r.t. parameter uncertainties and external disturbances. Specifically, utilizing the passivity property, a shaped energy-like function is designed as a Lyapunov candidate, based on which, an adaptive tracking controller is proposed to deal with parameter uncertainties. Using Lyapunov stability analysis, together with LaSalle's invariance principle, the closed-loop system is proven to be asymptotically stable. At last, a series of experimental tests are implemented to illustrate the satisfactory performance of the proposed method. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate milk yield and frequency of visits to the milking station of primiparous versus multiparous cows at different stages of lactation on farms with automatic milking systems (AMS) in the Upper Midwest United States. Forty farms were included in the study, and daily AMS software data were collected for 18 mo. For the investigation of milk yield and milking visits, stage of lactation was categorized into 14 periods, 7 d in length for the first 28 d in milk (DIM) and 30 d in length thereafter until 328 DIM. Cow traffic flow to the AMS (free or guided) was included in the model. For the evaluation of failures and refusals, stage of lactation was categorized into 6 periods, 7 d in length each for the first 28 DIM, and 2 periods of 150 d in length each thereafter until 328 DIM. Failures are milking station visits where a cow fails to be milked due to lack of machine attachment although it is time for the cow to be milked. Refusals are milking station visits before adequate time has passed since previous milking, thus the cow leaves the milking station without being milked. Data from lactation days beyond 328 DIM were excluded from the study. Primiparous cows in free-flow systems produced less milk than multiparous cows until the 11th stage of lactation and produced more milk from the 12th stage until the end of the study period. Primiparous cows in guided-flow systems produced less milk than multiparous cows all 14 stages of lactation, but were approaching the milk yield of multiparous cows at the end of the study period. This was a biologically normal lactation curve for primiparous cows. However, estimated peak ratio (primiparous vs. multiparous cows' peak milk yield) was lower than industry standards. Both traffic flow systems had fewer milking visits for primiparous cows compared with multiparous cows in early lactation. This lower milking frequency persisted until the 11th stage of lactation in free-flow systems. In guided-flow systems, primiparous cows were milked less frequently until the 5th stage of lactation, had similar milking frequency in the 6th stage of lactation, and were milked more frequently thereafter. Failures were greater for primiparous cows during all stages of lactation. However, the greatest differences were detected in the early stages of lactation. Primiparous cows had 0.067 more failures/cow per d on average than multiparous cows during the 1st wk of lactation. For the remaining lactation stages, differences in failures ranged from 0.003 to 0.039. Refusals were less frequent (0.4 to 0.6/d) for primiparous cows during the first 2 wk of lactation, similar for the 3rd wk of lactation, and more frequent for the remaining lactation stages (0.10 to 0.14/d). Failures and refusals were only evaluated in free-flow systems. These findings appear to indicate a potential lagging performance for primiparous cows in early lactation as compared with multiparous cows. Additional investigation into improving the adaptation of primiparous cows to AMS in early lactation may be warranted [ABSTRACT FROM AUTHOR]

The purpose of this work is to improve the understanding of the role of venetian blinds as a part of a building energy system. This is valuable for both designing automatic control of blinds and advising occupants towards energy-efficient use of manual blinds. A new strategy to control venetian blinds developed in the work aims at minimizing energy consumption by controlling blinds in a way that takes into account not only the effect of blinds on both solar transmission but also the effect on heat loss through windows. Annual computer simulations were performed to calculate the effect of blind use patterns on heating, cooling and lighting demand in four European climates in three single-family houses. The results show that the use patterns of blinds have a significant effect on energy consumption and that the new control strategy leads to lowest total energy consumption in all of the simulated buildings in all four climates. In contrast, a completely passive strategy—although very common in reality—consumes the most; depending on the climate and window size, total consumption is highest either when the blinds remain continually lowered and closed or continually raised. Occupants should be advised about the potential to save energy by changing blind use behaviours, also in the heating season. [ABSTRACT FROM AUTHOR]

Abstract Recognizing that two elements within a sequence of variable length depend on each other is a key ability in understanding the structure of language and music. Perception of such interdependencies has previously been documented in chimpanzees in the visual domain and in human infants and common squirrel monkeys with auditory playback experiments, but it remains unclear whether it typifies primates in general. Here, we investigated the ability of common marmosets (Callithrix jacchus) to recognize and respond to such dependencies. We tested subjects in a familiarization-discrimination playback experiment using stimuli composed of pure tones that either conformed or did not conform to a grammatical rule. After familiarization to sequences with dependencies, marmosets spontaneously discriminated between sequences containing and lacking dependencies ('consistent' and 'inconsistent', respectively), independent of stimulus length. Marmosets looked more often to the sound source when hearing sequences consistent with the familiarization stimuli, as previously found in human infants. Crucially, looks were coded automatically by computer software, avoiding human bias. Our results support the hypothesis that the ability to perceive dependencies at variable distances was already present in the common ancestor of all anthropoid primates (Simiiformes). [ABSTRACT FROM AUTHOR]

Maize inspection is an important and time-consuming task in the domain of food engineering. The human-based inspection strategy needs to be brought up to date with the rapid developments in the maize industry. In this paper, an automatic maize-inspection machine is proposed. Our proposed machine integrates several new designs in terms of both hardware and software components. First, a gravity-based dual-side camera design expands the machine's field-of-view to evaluate maize kernels more thoroughly. Second, touching kernels are pre-processed using a new k-means clustering guided-curvature method, which can improve the robustness of our machine. Next, a deep convolutional neural network, which has shown promise for application in image processing, is embedded into the system to evaluate maize kernels. In this work, the ResNet, which is a deep convolutional neural network architecture, was trained by fine-tuning with 1632 images. It achieved a 98.2% prediction accuracy for 408 test images, which outperforms existing approaches. Highlights • Design a dual-camera based synchronised maize inspection machine. • Applied an improved background removal method. • Propose a K-means-guided curvature method to segment the touching kernels. • Integrate deep convolutional neural network in the maize inspection machine. [ABSTRACT FROM AUTHOR]

Highlights • This paper proposes a general control logic framework based on human cognitive model (IDA). • In order to describe the control process in reliability analysis, the traditional GO-FLOW modeling theory is extended. It clearly describes the information interaction process between the control system and the controlled system. • In this paper, a hierarchical modeling and analysis method is used to achieve hierarchical GO-FLOW modeling. • The implementation of the above method is verified through a case study of chemical and volume control system (CVCS) in NPP. Abstract Reliability of system, structures and components plays a crucial role in ensuring the safe and stable operation of nuclear power plants. With the widespread application of automation in nuclear power plants, the role of the operator in main control room has been changing from actual implementation of control to supervision of the control process. Reliability monitoring of automatic control components and systems provides an insight of the ability of plant systems in realizing their expected goals over time. This paper presents an extension of GO-FLOW methodology in modeling automatic control component and systems from the perspective of cognitive process. Through the concept of hierarchical modeling, this paper designs an improved GO-FLOW model hierarchical modeling and analysis framework, which further increases the feasibility of modular modeling and model readability. Taking CVCS of nuclear power plant as an example, considering the control of ACP, the analysis and calculation of several scenarios are carried out in this study. In the course of the analysis, it was verified that the model is able to update automatically and realize the real-time system reliability monitoring function. The approach proposed in this paper is a general technique which could be extended further to describe more complex control logic. [ABSTRACT FROM AUTHOR]

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Developing Computer Integrated Manufacturing controllers is a complicated design activity. It requires mastery of the formidable complexity of manufacturing environments as well as of the hardware and software components required to build the controllers. We discuss system engineering techniques that can be applied to structure this complexity into manageable design phases. The starting point is a conceptual design of a factory wide CIM system, which describes, in manufacturing terminology, the tasks, information requirements, and performance requirements of a suite of CIM controllers. Formal, structured techniques are then available for translating the conceptual description of controllers to their detailed requirement specifications, design and computer based implementation. We demonstrate the translation techniques by reviewing the development of a particular CIM component, a workstation controller, currently in industrial use. [ABSTRACT FROM AUTHOR]

One of the biggest challenges in the process of establishing modern e-learning systems is figuring out ways to leverage legacy course materials and integrating them in the new information systems. Existing exam query repositories in particular are a very valuable data source, but one which usually lacks enough metadata to help establish relationships between exam questions and corresponding learning concepts whose adoption is being evaluated. In this paper we present the continuation of our research regarding the usage of educational data mining methods able to automatically annotate pre-existing exam queries with information about learning concepts they relate to. In our novel approach we leverage both textual and visual information contained in the queries. By combining the power of natural language processing which focuses on the text of the question, and annotated data extracted from figures accompanying the questions, we are able to further refine our classification methods and achieve noticeably improved results. By identifying learning concepts more accurately we further facilitate automatic creation of exams as well as even better insight into learning concept adoption. Our approach is again applied on data gathered from a large scale university course, and the results were validated in consultation with educational domain experts. [ABSTRACT FROM AUTHOR]

In this paper, a novel switching event-triggered synchronization scheme is established for chaotic networked control systems with different dimensions. First, a reduced-dimension observer is constructed to help the response system estimate all the states of the drive system. Next, a switching event-triggered networked control method which depends both on relative error and absolute error of the sampled-data is designed to reduce the burden of network bandwidth effectively while ensuring the desirable synchronization performance. On the basis of the above, some sufficient synchronization criterions are derived in the form of linear matrix inequalities. Finally, the numerical simulation is carried out to demonstrate the effectiveness and superiority of the synchronization method. [ABSTRACT FROM AUTHOR]

The optimal control of the heating, ventilation, and air-conditioning (HVAC) system in buildings has a significant energy saving potential and therefore is of a great practical interest. An event-based HVAC control adjusts control actions when certain events occur, which may be faster and more scalable than state-based or time-driven control methods. However, events may capture either local or global changes in the rooms. The choice of events is a tradeoff between the computational efficiency and the control performance. This challenging problem remains open. We consider this as an important problem in this paper and make three major contributions. First, we define local and global events for the HVAC control problem. The complexity of these event-based control policies is defined. Second, based on hypothesis testing, we develop a method to select events that capture a sufficient state information and with a relatively small event space. Third, we demonstrate the performance of this method on two groups of examples, including one group of small-scale problems for the proof of concept and the other group of large-scale problems in the HVAC control. It is shown that our method outperforms the Levin search, which is a traditional complexity-based search method and finds event-based HVAC control policies with a good performance. Note to Practitioners—When there are multiple rooms in a building, the HVAC control may achieve a significant energy saving and an indoor comfort satisfaction in the same time through exploring the coupling among the rooms. By appropriately defining the events, the size of the event space is usually much smaller than the state space. Therefore, an event-based control is more scalable and preferred in practice. Local events capture the state changes of rooms in a small neighborhood, which leads to a small event space but limited information. Global events capture the state changes of rooms in a large neighborhood, which leads to more information but a large event space. It remains open how to select events in large-scale HVAC control problems, especially when the computing budget is limited. In this paper, we define the complexity of an event-based control policy by the number of neighboring rooms considered. We develop a method based on hypothesis testing to select events with a proper complexity in order to achieve a good system performance. The performance of this method is demonstrated on an HVAC control problem. [ABSTRACT FROM AUTHOR]

In accordance with the occupational health and safety standards currently in force, the safety parameters that define the underground atmosphere (mainly temperature and gases) will be monitored during the closing of mines, both during the proper closing and the preservation stage, as well during the temporary or permanent closing of the mine areas damaged during the mining period. The solution intends to warn against the hazards of undergrounds fires and gas and powders explosions; it consists in the automatic sampling and processing of information on the evolution of temperature and gases inside goofs and closed underground areas. [ABSTRACT FROM AUTHOR]

Developing mechanical devices to restore natural locomotion for transfemoral amputees still raises many challenges. One of them is the development of an efficient control strategy for the prosthesis active joints, with the objective of making it flexible and intuitive to use. This paper focuses on the transfemoral CYBERLEGs Beta-Prosthesis, an actuated elastic ankle–knee prosthesis embedding bio-inspired mechanisms targeting the minimization of its total power consumption. We provide the development of a bio-inspired, torque-based, controller for this device, requiring no torque sensing. Torque control is achieved by means of static modelling of the prosthesis geometrical and elastic relationships. Bench testing of the prosthesis was performed to show that this static model is able to accurately predict the actual behaviour of the device. The model was then used to build the low-level controller of the prosthesis, converting desired torques into reference positions for the joint actuators. Next, a walking experiment with a transfemoral amputee was conducted to assess the feasibility of a torque-based control approach for the prosthesis, with a simple high-level controller combining reference torque trajectories and bio-inspired joint impedances. Results validated the use of our static model for implementing the low-level controller of such an elastic and redundant prosthesis. [ABSTRACT FROM AUTHOR]

Low-level control of autonomous underwater vehicles (AUVs) has been extensively addressed by classical control techniques. However, the variable operating conditions and hostile environments faced by AUVs have driven researchers towards the formulation of adaptive control approaches. The reinforcement learning (RL) paradigm is a powerful framework which has been applied in different formulations of adaptive control strategies for AUVs. However, the limitations of RL approaches have lead towards the emergence of deep reinforcement learning which has become an attractive and promising framework for developing real adaptive control strategies to solve complex control problems for autonomous systems. However, most of the existing applications of deep RL use video images to train the decision making artificial agent but obtaining camera images only for an AUV control purpose could be costly in terms of energy consumption. Moreover, the rewards are not easily obtained directly from the video frames. In this work we develop a deep RL framework for adaptive control applications of AUVs based on an actor-critic goal-oriented deep RL architecture, which takes the available raw sensory information as input and as output the continuous control actions which are the low-level commands for the AUV’s thrusters. Experiments on a real AUV demonstrate the applicability of the stated deep RL approach for an autonomous robot control problem. [ABSTRACT FROM AUTHOR]