To solve the problem of long logistics delivery time in supply chain, a Mixed Integer Non-linear Program (MINLP) model is built by using Mixed Integer nonlinear programming theory. Firstly, the General algebraic modeling system (GAMS) is used to build the model to fully integrate each parameter of logistics transportation, the total distribution time of the supply chain network, the coverage radius of the logistics base, the number of users, the total capacity of the logistics base, the mode of railway and road transportation, the nonlinear programming model is built and solved by DICOPT solver in GAMS. The cost of logistics can be decreased, transportation time can be reduced, and the logistics system's operating efficiency can be increased in the long term with the help of this algorithm. The proper operation of the logistics system is critical in encouraging the supply chain circulation of various industries and has a direct impact on the society's economic development. The optimal logistics distribution plan with 5 logistics bases covered users of 18 and railway capacity of 2. With the same railway capacity and the same total budget, the larger the number of covered users, the greater the total distribution time increases, but the larger the total budget, the growth of the total distribution time slows down significantly. Experiments show that MINLP model can solve the problem of logistics-based layout optimization in nonlinear logistics management.

To solve the problems of large mechanical powertrain such as complex structure, serious accident, strong nonlinear characteristics of running state, bad operating environment, non-Gaussian noise, and various uncertain factors, it is difficult to make an accurate fault diagnosis. This paper proposes a method for dealing with nonlinear characteristics using nuclear waves, as well as a system, deeply conducted nuclear base fault feature extraction, classification, and decision making, such as nuclear base state trend prediction technology research, focusing on exploring and improving the accuracy of fault diagnosis under nonlinear conditions, technical method, and way to state prediction accuracy. It offers effective technical assistance for the advancement and use of mechanical power train monitoring and diagnosis technology. A fault detection method based on kernel method is proposed. Based on the characteristics of this method in dealing with nonlinear problems, the research on kernel feature extraction, kernel fault classification and decision making, and kernel state trend prediction are carried out systematically. The experimental results show that the simulation analysis of typical chaotic time series prediction and the application of the operation state prediction of a certain ship main steam turbine unit have achieved good results, among which the average relative error of the single-step prediction of the unit state is 1.7881%, and the average relative error of the 30-step prediction is 3.3983%. Proved that the nuclear methods systematically applied to mechanical power transmission system fault diagnosis and state prediction, effectively enhancing some traditional methods and techniques dealing with nonlinear feature extraction, the nonlinear prediction capability for fault identification, and nonlinear state, to deal with nonlinear fault diagnosis problems of engineering practice, a large number of explored effective solution.

A novel secure energy aware game theory (SEGaT) method has proposed to have better coordination in wireless sensor actor networks. An actor has a cluster of sensor nodes which is required to perform different action based on the need that emerge in the network individually or sometime with coordination from other actors. The method has different stages for the fulfilment of these actions. Based on energy aware actor selection (EAAS), selection of number of actors and their approach is the initial step followed by the selection of best team of sensors with each actor to carry out the action and lastly the selection of reliable node within that team to finally nail the action into place in the network for its smooth working and minimum compromise in the energy The simulations are done in MATLAB and result of the energy and the packet delivery ratio are compared with game theory (GaT) and real time energy constraint (RTEC) method. The proposed protocol performs better in terms of energy consumption, packet delivery ratio as compared to its competitive protocols.

Agriculture and plants, which are a component of a nation's internal economy, play an important role in boosting the economy of that country. It becomes critical to preserve plants from infection at an early stage in order to be able to treat them. Previously, recognition and classification were carried out by hand, but this was a time-consuming operation. Nowadays, deep learning algorithms are frequently employed for recognition and classification tasks. As a result, this manuscript investigates the diseases of sunflower leaves, specifically Alternaria leaf blight, Phoma blight, downy mildew, and Verticillium wilt, and proposes a hybrid model for the recognition and classification of sunflower diseases using deep learning techniques. VGG-16 and MobileNet are two transfer learning models that are used for classification purposes, and the stacking ensemble learning approach is used to merge them or create a hybrid model from the two models. This work makes use of a data set that was built by the author with the assistance of Google Images and comprises 329 images of sunflowers divided into five categories. On the basis of accuracy, a comparison is made between several existing deep learning models and the proposed model using the same data set as the original comparison.

No abstract

Purpose Gaya, the holy city of Hindus, Buddhists and Jains, is facing an acute shortage of potable water. Although the city is blessed with some static and dynamic water bodies all around the region, they do not fulfill the requirement of millions of public either inhabitants of the area or tourists or pilgrims flocking every day. Countless crowds, congested roads, swarming pedestrians, innumerable vehicles moving throughout the day and night have made the city into a non-livable one. The present status of surface water is a mere nightmare to the requirements of the people. Due to which, massive ground water pumping mostly illegally has added a grid in addition to the other socio-economic issues. Design/methodology/approach To focus on such problem, the ground water of the region was studied thoroughly by calculating the depth of water level, discharge, pre-and post-monsoon water table and specifically the storativity in ten different locations. Some data were acquired, others were assessed, and few are calculated to provide an overall view of the ground water scenario. Findings After a long and tedious field study, it was finally established from that static water level ranges from 2.45 to 26.59 m, below ground level (bgl), discharge varies from 3.21 m3/day to 109.32 m3/day. Post pumping drawdown falls between 0.93 m and 16.59 m, whereas the specific capacity lies in between 0.96 and 7.78 m3/hr/m. Transmissivity, which is a key objective to assess ground water potential ranges from 109.8 to 168.86 m2/day. Originality/value This research work is original.

The addition of nanoclay in the polypropylene matrix has many applications in the field of automotive, packaging and aeronautical industry. Nanocomposites of polypropylene with nanoclay phr (part per hundred of resin) of 2.5, 5.0, 7.5 and 10 are prepared using melt mixing in twin-screw extruder and injection molding. The dispersion of nanoclay in the polypropylene matrix played a significant role in the preparation of nanocomposites. The freeze-fractured microstructures of the 5 phr of nanoclay composites shows better dispersion of clay particles in the polypropylene matrix. Tensile testing is performed to quantify the strength with respect to nanoclay phr in the nanocomposites. Stress strain behaviors during the tensile testing along with critical examining using field emission scanning electron microscope of the fracture surface have evolved that phr value around 5 provide maximum strength. In addition to this, surface roughness of these nanocomposites also indicate that the nanocomposites formed by 5 phr nanoclay give better surface finish. The wear behavior of nanocomposites is investigated using pin-on-disc tribo-tester at different loads (10, 20 and 30 N) and sliding speeds (0.5, 1.5 and 2.5 m/s). A response surface methodology based model is developed to explore the impact of nanoclay phr along with load and sliding speed on the wear behavior of these nanocomposites. Response surface methodology is a statistical technique in which the interaction among process variables is studies. It uses a sequence of design experiments to get an optimal response. It was found that 4.19 phr provides to be optimal value of nanoclay content exhibiting better wear resistance. Present study of composites with nanoclay reinforcement in polypropylene matrix concludes that phr value ranging around 4 to 5 gives best results.

This article describes the power train design specifics in Formula student race vehicles used in the famed SAE India championship. To facilitate the physical validation of the design of the power train system of a formula student race car category vehicle engine of 610 cc displacement bike engine (KTM 390 model), a detailed design has been proposed with an approach of easing manufacturing and assembly along with full-scale prototype manufacturing. Many procedures must be followed while selecting a power train, such as engine displacement, fuel type, cooling type, throttle actuation, and creating the gear system to obtain the needed power and torque under various loading situations. Keeping the rules in mind, a well-suited engine was selected for the race track and transmission train was selected which gives the maximum performance. Based on the requirement, a power train was designed with all considerations we need to follow. Aside from torque and power, we designed an air intake with fuel efficiency in mind. Wireless sensors and cloud computing were used to monitor transmission characteristics such as transmission temperature management and vibration. The current study describes the design of an air intake manifold with a maximum restrictor diameter of 20 mm.