Bowensharma5692

Frequent inspections are essential for false ceilings to maintain the service infrastructures, such as mechanical, electrical, and plumbing, and the structure of false ceilings. Human-labor-based conventional inspection procedures for false ceilings suffer many shortcomings, including safety concerns. Thus, robot-aided solutions are demanded for false ceiling inspections similar to other building maintenance services. However, less work has been conducted on developing robot-aided solutions for false ceiling inspections. This paper proposes a novel design for a robot intended for false ceiling inspections named Falcon. The compact size and the tracked wheel design of the robot allow it to traverse obstacles such as runners and lighting fixtures. The robot's ability to autonomously follow the perimeter of a false ceiling can improve the productivity of the inspection process since the heading of the robot often changes due to the nature of the terrain, and continuous heading correction is an overhead for a teleoperator. Therefore, a Perimeter-Following Controller (PFC) based on fuzzy logic was integrated into the robot. Experimental results obtained by deploying a prototype of the robot design to a false ceiling testbed confirmed the effectiveness of the proposed PFC in perimeter following and the robot's features, such as the ability to traverse on runners and fixtures in a false ceiling.The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed.Haptic technology allows us to experience tactile and force sensations without the need to expose ourselves to specific environments. It also allows a more immersive experience with virtual reality devices. This paper presents the development of a soft haptic glove for kinesthetic perception. It is lightweight and soft to allow for a more natural hand movement. This prototype actuates two fingers with two shape memory alloy (SMA) springs. Finite element (FE) simulations of the spring have been carried out to set the dimensions of the actuators. Flexible stretch sensors provide feedback to the system to calculate the tension of the cables attached to the fingers. The control can generate several recognizable levels of force for any hand position since the objects to be picked up can vary in weight and dimension. The glove can generate three levels of force (100, 200 and 300 g) to evaluate more easily the proper functioning. We realized tests on 15 volunteers simulating forces in various order after a quick training. We also asked volunteers about the experience for comfort, global experience and simplicity). Results were satisfactory in both aspects the glove fulfilled its function, and the users were comfortable with it.A reflectarray antenna with an optimized sectorial beam is designed for the surveillance channel of a DVB-S-based passive radar (PR). The employment of satellite illuminators requires a high gain antenna to counteract the losses due to the great distance from the transmitter, but without forgetting a beamwidth wide enough to provide angular coverage. A method based on optimizing the position of several contiguous beams is proposed to achieve the required sectorial pattern. Different reflectarray elements are designed to achieve S-curves with smooth slopes and covering all the required phases (the S-curve represents the reflection phase of a single element, as a function of size, rotation and incidence angle). The real phase and modulus of the reflection coefficient of each element are considered in the optimization process to achieve the best real prototype. Geometry has been studied and adapted to employ commercial elements for the feed, feed-arm and the structure that holds the aperture. The designed prototype has been characterized in an anechoic chamber achieving a stable gain greater than 19 dBi in almost the complete DVB-S band, from 10.5 GHz to 12 GHz with a sectorial beam of 8.7∘×5.2∘. The prototype has also been validated in PR trials in terrestrial scenarios allowing the detection of cars at distances up to 600 m away from the PR, improving the performance achieved with commercial parabolic dish antennas.Narrow band-gap semiconductors, namely ternary InAsSb alloys, find substantial technological importance for mid-infrared application as photodetectors in medical diagnostics or environmental monitoring. Thus, it is crucial to develop electrical contacts for these materials because they are the fundamental blocks of all semiconductor devices. This study demonstrates that electroplated gold contacts can be considered as a simple and reliable metallization technology for the electrical-response examination of a test structure. Unalloyed electroplated Au contacts to InAsSb exhibit specific contact resistivity even lower than vacuum-deposited standard Ti-Au. Moreover, temperature-dependent transport properties, such as Hall carrier concentration and mobility, show similar trends, with a minor shift in the transition temperature. It can be associated with a difference in metallization technology, mainly the presence of a Ti interlayer in vacuum-deposited contacts. Such a transition may give insight into not only the gentle balance changes between conductivity channels but also an impression of changing the dominance of carrier type from p- to n-type. The magnetotransport experiments assisted with mobility spectrum analysis clearly show that such an interpretation is incorrect. InAsSb layers are strongly p-type dominant, with a clear contribution from valence band carriers observed at the whole analyzed temperature range. Furthermore, the presence of thermally activated band electrons is detected at temperatures higher than 220 K.In this work, new highly sensitive graphene-based flexible strain sensors are produced. In particular, polyvinylidene fluoride (PVDF) nanocomposite films filled with different amounts of graphene nanoplatelets (GNPs) are produced and their application as wearable sensors for strain and movement detection is assessed. The produced nanocomposite films are morphologically characterized and their waterproofness, electrical and mechanical properties are measured. Furthermore, their electromechanical features are investigated, under both stationary and dynamic conditions. click here In particular, the strain sensors show a consistent and reproducible response to the applied deformation and a Gauge factor around 30 is measured for the 1% wt loaded PVDF/GNP nanocomposite film when a deformation of 1.5% is applied. The produced specimens are then integrated in commercial gloves, in order to realize sensorized gloves able to detect even small proximal interphalangeal joint movements of the index finger.Yearly population growth will lead to a significant increase in agricultural production in the coming years. Twenty-first century agricultural producers will be facing the challenge of achieving food security and efficiency. This must be achieved while ensuring sustainable agricultural systems and overcoming the problems posed by climate change, depletion of water resources, and the potential for increased erosion and loss of productivity due to extreme weather conditions. Those environmental consequences will directly affect the price setting process. In view of the price oscillations and the lack of transparent information for buyers, a multi-agent system (MAS) is presented in this article. It supports the making of decisions in the purchase of sustainable agricultural products. The proposed MAS consists of a system that supports decision-making when choosing a supplier on the basis of certain preference-based parameters aimed at measuring the sustainability of a supplier and a deep Q-learning agent for agricultural future market price forecast. Therefore, different agri-environmental indicators (AEIs) have been considered, as well as the use of edge computing technologies to reduce costs of data transfer to the cloud. The presented MAS combines price setting optimizations and user preferences in regards to accessing, filtering, and integrating information. The agents filter and fuse information relevant to a user according to supplier attributes and a dynamic environment. The results presented in this paper allow a user to choose the supplier that best suits their preferences as well as to gain insight on agricultural future markets price oscillations through a deep Q-learning agent.A recommendation system is often used to recommend items that may be of interest to users. One of the main challenges is that the scarcity of actual interaction data between users and items restricts the performance of recommendation systems. To solve this problem, multi-modal technologies have been used for expanding available information. However, the existing multi-modal recommendation algorithms all extract the feature of single modality and simply splice the features of different modalities to predict the recommendation results. This fusion method can not completely mine the relevance of multi-modal features and lose the relationship between different modalities, which affects the prediction results. In this paper, we propose a Cross-Modal-Based Fusion Recommendation Algorithm (CMBF) that can capture both the single-modal features and the cross-modal features. Our algorithm uses a novel cross-modal fusion method to fuse the multi-modal features completely and learn the cross information between different modalities. We evaluate our algorithm on two datasets, MovieLens and Amazon. Experiments show that our method has achieved the best performance compared to other recommendation algorithms. We also design ablation study to prove that our cross-modal fusion method improves the prediction results.