Remote monitoring of objects or technological processes is used in many industries and service-oriented companies to obtain up-to-date information about the state of things or technical processes. The article is devot...
详细信息
In response to the growing imperative of addressing environmental concerns and aligning with governmental regulations in supply chain management, this study navigates the optimization landscape of closed-loop supply c...
详细信息
The research results of the Love wave propagation in the semi-space contact area and in a thin layer are presented. The dependences, which allow analyzing the effect of various conditions on the Love wave dispersion, ...
详细信息
In the present work, we developed a mathematical model for dengue-Chikungunya co-infection to analyze the disease transmission dynamics and interrelationship. We considered the essence of time dependent optimal contro...
详细信息
The number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. This increases the complexity of the search for relevant articles. Modern searc...
详细信息
ISBN:
(纸本)9781665476249
The number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. This increases the complexity of the search for relevant articles. Modern search engines leverage keyphrases to improve the performance of search results. Keyphrases (or keywords) are a set of single or multi-word expressions which provide a very compact summary of contents and describe the overall topic of a document. Implementation of keyphrase extraction can be varied for specific-domain databases. This motivated us to evaluate these methods on a database of influenza scientific literature. In this work, we considered 9 well known methods for extracting keyphrases. Our preliminary results show txhat graph-based methods which employ topics outperform others using our database. We also determined that influenza-related papers can be grouped into three general topics: public health & medical care; molecular biology & immunology; and phylogenetic & epidemiological studies.
Machine learning technique is full-fledged as a boosting sector to develop modeling and forecasting of complex time series observations in the present environment. This study made an attempt to inspect the future perf...
Machine learning technique is full-fledged as a boosting sector to develop modeling and forecasting of complex time series observations in the present environment. This study made an attempt to inspect the future performance of rainfall data and vapor in Chelyabinsk by using a machine learning technique. The data series is divided into a training set (60%) and a test set (40%) for model developing a validation purpose. We further developed deep learning models such as, LSTM, BILSTM, GRU and compared on the basis of ME, RMSE, MAE, MPE, MAPE, ACF1 on the training data set. For testing data set, we compared these deep learning models based on RMSE. LSTM model acts as a superior machine learning model over BILSTM and GRU in this data series. Forecasting performance of these three models significantly at par. This finding may be significant to build a strong literature of the Chelyabinsk weather's forecast, which can be helpful for policy makers and researchers. Also, we strongly believe that, this work could be used as a literature adaptation of machine learning technique for complex time series over statistical models.
For several years, traffic congestion has been a major problem in big cities where the number of cars and different means of transportation has been increasing significantly. The problem of congestion is becoming more...
For several years, traffic congestion has been a major problem in big cities where the number of cars and different means of transportation has been increasing significantly. The problem of congestion is becoming more and more critical, and if not treated smartly this issue will negatively affect drivers by wasting time and fuel gas while waiting for hours in lanes. This paper presents a new and smart way to mitigate this issue in an affordable cost, minimum processing power, and low power consumption. This concept takes into consideration the majority of the cases that may cause congestion and presents a smart and accurate outputs to ease traffic flow leading to the prediction of the peak hours of traffic congestion for smarter control. A model is designed to study the case of a four lanes crossroad with two traffic lights and two LCD monitors. The strategy in reading data is divided into two parts: real data from sensors and pre collected data from google maps to create a kind of a predicted pattern over a certain time interval. The responsiveness of the system is analyzed thoroughly, and the accuracy of all possible cases is carefully considered and evaluated. Each part of the system was tested alone, and the overall system is still in an ongoing testing phase. The results have shown minimum faulty errors and accepted outputs that can lead to safe traffic control decisions. Finally, integrating more IoT devices and sensors between V2V, V2P, V2I with the help of artificial intelligence will definitely optimize this system with higher accuracy.
Since the last few decades, the prey-predator system delivers attractive mathematical models to analyse the dynamics of prey-predator interaction. Due to the lack of precise information about the natural parameters, a...
详细信息
In recent decades, global climate change has become one of the most critical environmental issues, leading to increased environmental and social concerns about the sustainability of logistics networks. This study prop...
详细信息
The problem of the rational use of energy resources remains constantly relevant and requires the search for new approaches. One of them is power control. In AC circuits, the authors see the most promising method of ph...
The problem of the rational use of energy resources remains constantly relevant and requires the search for new approaches. One of them is power control. In AC circuits, the authors see the most promising method of phase AC power control. Based on it, a power control module was developed. The structural and circuit diagrams of the developed device are presented to implement the proposed solution. The authors produced its experimental prototype and conducted experimental testing at various levels of regulated power. Savings when using the proposed power control module were calculated using the example of energy consumption in various sectors of energy-intensive systems. According to the data obtained, the module allows saving energy consumption without significant discomfort to the energy user. The calculated results allow concluding that the proposed AC power control module is fully operational, and its widespread use will significantly reduce the need for electricity.
暂无评论