In this paper, we tackle the problem of multiple-input multiple-output (MIMO) mmWave channel estimation in a hybrid analog digital architecture by exploiting the structure of the mmWave channel and the physical constr...
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A task-board task is a task in which robots perform a set of fundamental assembly operations related to the assembly of a specific product such as inserting a part into another part, tightening bolts and nuts, attachi...
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In recent years, Creating Shared Value (CSV), a management strategy based on the concept of creating both economic and social value for a company, has been attracting attention, and companies are trying to put it into...
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Due to the strong turbulence that exists in the business environment, the view is sometimes articulated that the time horizon of decisions is no longer a hallmark of strategic management. Opposing views argue that a t...
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ISBN:
(纸本)9781917204101
Due to the strong turbulence that exists in the business environment, the view is sometimes articulated that the time horizon of decisions is no longer a hallmark of strategic management. Opposing views argue that a turbulent environment changes the trajectory of reaching future objectives determined by strategic decisions. Such trajectories require the company to be agile, which is manifested by seizing opportunities. Opportunities arise because the environment is volatile. An example of market opportunity is the unsatisfied demand for products. Buyers are driven by different motives when choosing between products that are alternative to them. From the producer's point of view, the purchase is therefore random. As a consequence, the alignment of the offered product portfolio with the actual purchasing decisions of customers is undetermined. In this article, we address the problem of determining the product portfolio structure expected by customers, i.e. one that is consistent with their future purchasing decisions. We hypothesise that this problem can be represented by a model of flows between alternative resources. Problems of this type are solved using Markov Chain Monte Carlo (MCMC) methods. In order to discover the expected demand (opportunity), we simulated the flow model we developed using the Metropolis-Hastings algorithm, which is a special case of the MCMC method used in AI. Due to operating on numerical data, such simulations fall under quantitative research. In the article, we present a model of customer flows between alternative products and then the simulation result, which is the expected value of these flows (stationary point). We convert this value into the structure of the product portfolio using a model of customer purchasing decisions that we have developed. The obtained results confirm the effectiveness of our method and have significant practical value, especially for SMEs. It also enables the assessment of the company's product strategy based
Silicone rubber(SR) composites are most widely used as thermal interface materials(TIMs) for electronics heat dissipation. Thermal impedance as the main bottleneck limiting the performance of TIMs is usually neglected...
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Silicone rubber(SR) composites are most widely used as thermal interface materials(TIMs) for electronics heat dissipation. Thermal impedance as the main bottleneck limiting the performance of TIMs is usually neglected. Herein, the thermal impedance of SR composites loaded with different levels of hexagonal boron nitride(h-BN) as TIMs was elaborated for the first time by the ASTM D 5470 standard test and finite element analysis. It was found that elastic modulus and surface roughness of SR composites increased with the increase of h-BN content, indicating that the conformity was reduced. When the assembly pressure was 0.69 MPa, there existed an optimal h-BN content at which the contact resistance was minimum(0.39 K·cm^(2)·W^(-1)). Although the decreased bond line thickness(BLT) by increasing the assembly pressure was beneficial to reduce the thermal impedance, the proper assembly pressure should be selected to prevent the warpage of the contact surfaces and the increase in contact resistance, according to the compression properties of the SR composites. This study provides valuable insights into fabrication of high-performance TIMs for modern electronic device applications.
Nowadays, social media applications and websites have become a crucial part of people’s lives;for sharing their moments, contacting their families and friends, or even for their jobs. However, the fact that these val...
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We have been using sparse modeling AI to identify factors and predict in power demand. In this research, we applied ensemble learning to further improve the accuracy by integrating the results of multiple models. Expe...
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Face authentication is an important biometric authentication method commonly used in security *** is vulnerable to different types of attacks that use authorized users’facial images and videos captured from social me...
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Face authentication is an important biometric authentication method commonly used in security *** is vulnerable to different types of attacks that use authorized users’facial images and videos captured from social media to perform spoofing attacks and dynamic movements for penetrating secur-ity *** paper presents an innovative challenge-response emotions authentication model based on the horizontal ensemble *** proposed model provides high accurate face authentication process by challenging the authorized user using a random sequence of emotions to provide a specific response for every authentication trial with a different sequence of *** proposed model is applied to the KDEF dataset using 10-fold *** improvements are made to the proposed ***,the VGG16 model is applied to the seven common ***,the system usability is enhanced by analyzing and selecting only the four common and easy-to-use ***,the horizontal ensemble technique is applied to enhance the emotion recognition accuracy and minimize the error during authen-tication ***,the Horizontal Ensemble Best N-Losses(HEBNL)is applied using challenge-response emotion to improve the authentication effi-ciency and minimize the computational *** successive improvements implemented on the proposed model led to an improvement in the accuracy from 92.1%to 99.27%.
The Internet of Things (IoT) detects context through sensors capturing data from dynamic physical environments, in order to inform automation decisions within cyber physical systems (CPS). Diverse types of uncertainty...
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With the rapid development of computer vision and deep learning technologies, object detection plays a crucial role in various fields. Due to the complexity and diversity of underwater environments, underwater vision ...
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