The Essence Of Logistics And Its Barter Lbp-Provider

At the moment, the highest level of supply chain management is 5PL providers, but 6 or 7 PL providers will be needed for logistics barter, or they need to be called logistics barter providers because there must be a completely different, predominant view of the role of logistics and logistics barter in the new economy system. Logistic barter is a some kind of web (system), a spider (operator) is a LBP provider.The theory of the proposed economy scheme on the basis of logistic barter assumes a developed infrastructure, i.e. a supersystem for supply chain management based on LBP - providers. Yes, there is a question of the "maturity" of logistics functional areas (procurement, production, distribution, transportation and information), i.e. Their ability to adopt new rules of the game in the sphere of another operator of the economy. Logistic barter will be the central unifying link, and the main operators will be the LBP-provider (Gabdullinet al., 2017).E-commerce, e-auctions, e-sourcing, and e-markets are better integrated under the auspices of logistics barter into an e-integrator, which will be the serving element (one of the tools) of the LBP-provider. E-integrator is an integrator of information and communication technologies for supply chains of logistics barter in the form of electronic means taking into account the closing link - e-commerce and the reverse distribution of added value

On the stochasticity parameter of quadratic residues

Following V. I. Arnold, we define the stochasticity parameter $S(U)$ of a set $U\subseteq \mathbb{Z}_M$ to be the sum of squares of the consecutive distances between elements of $U$. We study the stochasticity parameter of the set $R_M$ of quadratic residues modulo $M$. Denote by $s(k)=s(k,\mathbb{Z}_M)$ the average value of $S(U)$ over all subsets $U\subseteq \mathbb{Z}_M$ of size $k$, which can be thought of as the stochasticity parameter of a random set of size $k$. We prove that a) $\varliminf_{M\to\infty}\frac{S(R_M)}{s(|R_M|)}<1<\varlimsup_{M\to\infty}\frac{S(R_M)}{s(|R_M|)}$; b) the set $\{ M\in \mathbb{N}: S(R_M)<s(|R_M|) \}$ has positive lower density

Prime avoiding numbers is a basis of order 22

For a positive integer $n$, we denote by $F(n)$ the distance from $n$ to the nearest prime number. We prove that every sufficiently large positive integer $N$ can be represented as the sum $N=n_1+n_2$, where $$F(n_i) \geqslant (\log N)(\log\log N)^{1/325565},$$ for $i=1,2$. This improves the corresponding "trivial" statement where only $F(n_i)\gg \log N$ is required

Study of Non-Homogeneity of Magnetic Field Distribution in Single-Crystal Ni-Mn-Ga Magnetic Shape Memory Element in Actuators due to its Anisotropic Twinned Microstructure

Magnetic shape memory (MSM) alloys are relatively new and very promising “smart” materials which respond to magnetic fields and exhibit the shape memory effect at room temperature. Maximum strain varies from 6 to 12% of the MSM element’s length depending on its microstructure. The shape memory effect and magnetic field-induced reorientation of MSM twin variants in low-temperature martensite phase are subject to an ongoing research for almost two decades. However, the magnetic field distribution in the MSM elements and effects of its varying magnetic permeability on bias magnetic field are not well studied. In this paper we present an extension to the existing modeling approach for MSM elements applicable to actuator design. The effects arising from single-crystal anisotropy and demagnetization effects due to non-homogeneous multi-variant MSM microstructure are studied and discussed. The proposed approach is validated by comparing computational results with previously reported measurement data

Simulation-based Design Methodology for Magnetic Shape Memory Actuators

MSM alloys, especially Ni-Mn-Ga alloys have been studied extensively for almost two decades. Their remarkable properties make them very promising for use in various electromagnetic (EM) devices, notably in actuators and sensors. However, at present there are no well-established design methodologies for MSM-based devises. This paper proposes a design methodology that uses commercially available EM modelling software and just a small amount of experimental data for its implementation. It allows reliable actuator modelling and performance evaluation without needing to calculate the magnetic field-induced stresses

Electromagnetic and thermal analyses of high performance magnetic shape memory actuators for valve applications

Magnetic shape memory (MSM) alloys are relatively new “smart” alloys which have enormous potential to be used in actuators, sensors and other electrical devices. Their large strain and considerable stress output can be controlled by magnetic fields or mechanical stresses. Maximum magnetic field-induced strain varies from 6 to 12% of the MSM element’s length depending on its microstructure. However, very low operational temperature limit is one of the main drawbacks of conventional MSM alloys. This makes their application in high performance actuators challenging due to considerable power losses. This paper discusses different MSM actuator designs optimized particularly for large force output for pneumatic electromagnetic (EM) valve applications. The thermal problem is addressed through analyzing the heat transfer conditions of each particular design and the effects of different cooling systems. An energy-efficient operating cycle for varying actuator load that takes advantage of the shape memory effect is also proposed. This allows minimization of energy losses resulting in acceptable increase in temperature ensuring stable continuous actuation

Google Coral-based edge computing person reidentification using human parsing combined with analytical method

Person reidentification (re-ID) is becoming one of the most significant application areas of computer vision due to its importance for science and social security. Due to enormous size and scale of camera systems it is beneficial to develop edge computing re-ID applications where at least part of the analysis could be performed by the cameras. However, conventional re-ID relies heavily on deep learning (DL) computationally demanding models which are not readily applicable for edge computing. In this paper we adapt a recently proposed re-ID method that combines DL human parsing with analytical feature extraction and ranking schemes to be more suitable for edge computing re-ID. First, we compare parsers that use ResNet101, ResNet18, MobileNetV2, and OSNet backbones and show that parsing can be performed using compact backbones with sufficient accuracy. Second, we transfer parsers to tensor processing unit (TPU) of Google Coral Dev Board and show that it can act as a portable edge computing re-ID station. We also implement the analytical part of re-ID method on Coral CPU to ensure that it can perform a complete re-ID cycle. For quantitative analysis we compare inference speed, parsing masks, and re-ID accuracy on GPU and Coral TPU depending on parser backbone. We also discuss possible application scenarios of edge computing in re-ID taking into account known limitations mainly related to memory and storage space of portable devices.Comment: 11 pages, 3 figures, 3 table