A significant challenge arises in the characterization of urban systems, especially regarding the intricate structures of Central Business Districts (CBDs). Conventional models seem insufficient, failing to comprehend the non-linear, network-oriented structure of the city's economic and social dynamics. This creates a disparity between the city's physical, geographical structure and the unseen processes occurring within it. The fundamental inquiry is thus configurational: how can we systematically examine the inherent spatial logic of the CBD to develop a more efficient and predictive planning model? This paper presents a theoretical and methodological model to explore this inquiry, which focuses on Lower Manhattan as the primary su

     A new mathematical model describing the motion of manned maneuvering targets is presented. This model is simple to be implemented and closely represents the motion of maneuvering targets. The target maneuver or acceleration is correlated in time. Optimal Kalman filter is used as a tracking filter which results in effective tracker that prevents the loss of track or filter divergency that often occurs with conventional tracking filter when the target performs a moderate or heavy maneuver. Computer simulation studies show that the proposed tracker provides sufficient accuracy.

The increasing demand for continual learning in sequential data processing has led to progressively complex training methodologies and larger recurrent network architectures. Consequently, this has widened the knowledge gap between continual learning with recurrent neural networks (RNNs) and their ability to operate on devices with limited memory and compute. To address this challenge, we investigate the effectiveness of simplifying RNN architectures, particularly gated recurrent unit (GRU), and its impact on both single-task and multitask sequential learning. We propose a new variant of GRU, namely the minion recurrent unit (MiRU). MiRU replaces conventional gating mechanisms with scaling coefficients to regulate dynamic updates of hidden

With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

   With increasing population and development, the resources of fossil fuels decreased, leading to the need to find alternative sources of energy. Furthermore, the use of fossil fuels is accompanied by several downsides including environmental fatality associated with toxic gas emissions from diesel engines and continuous increase of the price of diesel fuel. Biodiesel is one of the most important types of renewable energy that replaces the fossil fuel requirement (mineral diesel) and maintains eco-friendly sustainability. Calcium is an essential plant nutrient as it plays an important role in the formation of plant cell walls and membranes. Therefore, the fallen leaves of mango tree can be utilized to produce nano calcium oxide a

Five new ceftazidime derivatives were designed and synthesized in an attempt to improve the acid stability and may increase the spectrum of ceftazidime. The synthesized compounds included;  Schiff base of ceftazidime (compound 1), ceftazidime lysine amide Schiff base (compound 2), ceftazidime lysine amide (compound 3), ceftazidime-di-lysine amide Schiff base (compound 4) and ceftazidime-di-lysine amide (compound 5). New ceftazidime derivatives were successfully prepared characterized and identified using spectral and elemental microanalysis (CHNS) analyses and the results comply with the calculated measurements.

Compounds 1 and 2 were subjected to a stability study in phosphate buffer (0.2M, pH 7.4) and in KCl/HCl buffer (0.

        Knowledge represents the foundation stone for the work of all organizations, are working who leads the thinking of individuals is the ability that leads to behavior based on rationality, it is the work that creates value to the organization and thus gain access to performance winning where that knowledge is a new type of capital based on the thought and experience and is the so-called intellectual capital, which is renewable and is constantly evolving. The study sought to explain the role of the climax  knowledge in achieving the highest levels of performance Organizational and then access to the performance winning in educational organizations the study sample, was found to be a co