Node Creation Research Articles

Dynamic multilayer growth: Parallel vs. sequential approaches

The decision of when to add a new hidden unit or layer is a fundamental challenge for constructive algorithms. It becomes even more complex in the context of multiple hidden layers. Growing both network width and depth offers a robust framework for leveraging the ability to capture more information from the data and model more complex representations. In the context of multiple hidden layers, should growing units occur sequentially with hidden units only being grown in one layer at a time or in parallel with hidden units growing across multiple layers simultaneously? The effects of growing sequentially or in parallel are investigated using a population dynamics-inspired growing algorithm in a multilayer context. A modified version of the constructive growing algorithm capable of growing in parallel is presented. Sequential and parallel growth methodologies are compared in a three-hidden layer multilayer perceptron on several benchmark classification tasks. Several variants of these approaches are developed for a more in-depth comparison based on the type of hidden layer initialization and the weight update methods employed. Comparisons are then made to another sequential growing approach, Dynamic Node Creation. Growing hidden layers in parallel resulted in comparable or higher performances than sequential approaches. Growing hidden layers in parallel promotes growing narrower deep architectures tailored to the task. Dynamic growth inspired by population dynamics offers the potential to grow the width and depth of deeper neural networks in either a sequential or parallel fashion.

GAO-RRT*: A path planning algorithm for mobile robot with low path cost and fast convergence

<abstract><p>Path planning is an essential research topic in the navigation of mobile robots. Currently, rapidly-exploring random tree star (RRT*) and its variants are known for their probabilistic completeness and asymptotic optimality, making them effective in finding solutions for many path planning problems. However, slow convergence rate of the RRT* limits its practical efficiency. To address this problem, this paper proposed an enhanced RRT* algorithm by refining the extension process of the exploring tree. This enhancement aims to guide the tree approaching to obstacles (GAO) while exploring toward the target point. First, GAO-RRT* employed a dual-weighted sample strategy instead of random sample to guide search direction of the exploring tree. Second, a variable step size extension strategy was adopted to increase the efficiency of node generation, balancing searching time and path safety in regions with different obstacles densities. Third, growth status of new nodes was monitored in real-time, and a reverse growth strategy was proposed to guide the exploring tree to escape local optima. In addition, parent node creation procedure for new nodes was used to produce a better initial path. Finally, the proposed GAO-RRT* was compared with three state of the art algorithms on 16 different instances of four representative environments. Compared to RRT*, Quick-RRT* (Q-RRT*), and Fast-RRT* (F-RRT*), the results showed that (1) the average path cost of initial solutions obtained by GAO-RRT* decreased by 38.32%, 29.69%, and 20.44%, respectively; and (2) the average convergence time of solution obtained by GAO-RRT* to suboptimal (1.05*$ C_{best} $) was reduced by 71.22%, 69.69%, and 58.37%, respectively. Simulation results indicated that GAO-RRT* outperforms the compared algorithms in terms of path cost and convergence speed.</p></abstract>

A novel secure aware privacy preserved data sharing framework in an E-government system based on a consortium blockchain

Electronic government (E-government) utilises information and communication techniques for delivering services to individuals. It is termed a complicated model that requires to be distributed, privacy-preserved and secured. The failure of these can lead to economic and social loss. The blockchain method facilitates the execution of a secured and privacy-preserved model wherein transactions are done securely. This paper presents a privacy-protected model for sharing of data in an e-governance system considering consortium blockchain. The proposed privacy-protected model involves eight different phases, namely initialisation, new node creation, delegates and witnesses voting, user registration, authentication, data protection, validation and data sharing. This method helps to facilitate the security of information and privacy and concurrently increases trust in the public sector. The proposed privacy-protected model provided enhanced performance with a small computational time of 40.422s and memory usage of 38.800MB.

Intensive Analysis of Routing Algorithm Detection over Mobile Ad hoc Network Using Machine Learning

As we are in the Digital Era, in our daily life activities we use different types of communication devices like Mobile Phone, Laptops, Smart watches, etc. and In Common these Mobile Devices allows users to access Information and Services through wireless mode. Basically, there are two types of wireless Networks they are Infrastructure and Infrastructure less Networks. This Infrastructure Network is known as Cellular Networks, they are stationary components, and they used to connect the Mobile Nodes within the Network. But this Infrastructure less Network is also known as Mobile Ad hoc Network (MANET). MANET consist of no fixed Routers and unlimited Nodes. They are Dynamic in Nature. They can move at any direction and at any Movement. It forms a temporary Network for Data Transmission Purpose from Source and Destination. There can be any number of Nodes in Between Source to Destination. Here this Transmission of data is taken place with an Optimal Path in the MANET. This MANET is preferred to be used during Natural Calamities and for Military Operations. Here the node will be created first for communication in this proposed research work. Then the Machine Learning Algorithm will be applied after the node creation. There will be n numbers of nodes, one is master and the n-1 are treated as slaves. The Master node will be concluded by using Highest Network range. The charge will be checked and maintained by Machine Learning Algorithm. Again, Master will update the information. Here ML Algorithm will be act as data centers. The Master node will be changed as per their Capacities based on ML algorithm. In this research work we will discuss about the process of Routing, which will be carried by DSR Algorithm which is more responsive when compared with AODV and DSDV.

A Topology Map Generation Algorithm for Optimal Path Finding for Image-Based Maps

Algorithms that automatically search for routes have various applications, such as games, navigation, and robots, and are used to create optimal paths in the space of real and virtual worlds. This paper introduces an indoor navigation algorithm allowing rescuers to create a topology map of floor plans, given that the amount of data provided by conventional mapping constructs is limited. Traditional pathfinding algorithms include the A* algorithm, which has demonstrated excellent performance; however, its applicability is limited in the case of high-resolution images, as the number of nodes increases significantly. Here, we use the corner node algorithm (CNA) to improve pathfinding performance by preprocessing the data to create a topology map for the pathfinding algorithm. The algorithm can reduce the number of nodes required for the pathfinding process by generating topology maps in advance through two preprocessing processes: node creation and node connection. This effectively reduces the number of nodes to be processed, as well as the error rate when creating more accurate routes. Furthermore, a generated topology map can be reused by the algorithm unless its structure changes, which enhances efficiency. For the user, this means that the sought-after mapping information of the floor plan is quickly made available for navigation. With this algorithm, we created an augmented reality navigation solution to display virtual objects for rescuers, to demonstrate the enhanced performance of our approach.

Investigation of an energy dependent node creation in graphene quantum states

A quantum state in monolayer graphene can acquire an extra node when its eigenenergy varies relative to the energy range of an applied potential well. In contrast to a non relativistic quantum state, this node creation is not followed by a change in the eigenenergy index. Here, we consider two-component confined states in a cylindrically symmetric graphene system and investigate an energy dependent node creation in a uniform magnetic field. We show that an extra node can be created in one of the two components by increasing the strength of the potential well and the same node can be destroyed by tuning the magnetic field. We demonstrate the importance of the sign of the angular momentum and examine the appropriate conditions which enhance the effect of the node on the quantum states.

‘Wonder’ Nouns and the Development of a Mirative Constructional Network: An Exercise in Semiotic Diachronic Construction Grammar

AbstractThis paper discusses the emergence and development of a mirative constructional network involving the shell nounswonder,marvelandchance, called ‘wonder’ nouns here. In combination with negative quantifiers (e.g.no wonder), they can be used either lexically or as part of grammatical, mirative markers, qualifying a proposition as unsurprising in view of another situation. The network emerges in Old English aroundwonder, with three meso-constructions which differ in surface structure but all inherit the anti-concessive discourse schema from the macro-construction, consisting of a proposition, mirative qualifier and justification. Two additional meso-constructions emerge in Middle English, which is also the time when the Romance loanmarveljoins the network, making it gain in schematicity, abstractness and productivity. In Present-day English, another Romance loan,chance, expands the mirative network even more. Throughout time, we observe node loss, node creation, constructional substitution and changes in frequencies of constructions. Theoretically, we propose a semiotic approach to diachronic construction grammar, arguing that multi-sign constructions invariably involve syntagmatic relations, which are themselves form-meaning pairings. This approach allows us to capture generalizations which would otherwise be missed.

Piping auto-routing using key-node generation method in ships

ABSTRACT Previous studies on automatic pipe routing algorithms in ships have typically used pathfinding and optimisation algorithms to satisfy relevant constraints in the field and improve the results of pipe auto-routing. However, the existing path-search algorithm takes a long time to search for nodes that do not need to be searched. Therefore, this study was conducted to identify the key nodes worth searching for when pipes are routed in a ship and accelerate pipe routing by reducing the search nodes. Key nodes in piping routing serve to connect points that require changes in the location of the piping; after node creation, the path search is performed using the A* algorithm the algorithm in the key-node environment proposed in this study and the existing algorithm were compared and verified. Finally, the effectiveness of the proposed algorithm was verified by analyzing the performance of each parameter.

A real time health care cyber attack detection using ensemble classifier

Healthcare has been a significant issue for many individuals in recent years. The Internet of things (IoT) and wireless communications may support many medical applications, including early diagnosis and real-time monitoring. Healthcare expenditures may be reduced by using secure and practical strategies to detect life-threatening emergencies in real-time quickly. The aim of the proposed tool is the detection of attacks targeting the Healthcare cyber-physical system. In this method, the wise greedy routing technique is initially used for sensor node placement and creation. The transmitted data is normalized and grouped using an agglomerative mean shift maximization clustering method. The abnormal health features are extracted using a multi-heuristic cyber ant optimization-based feature extraction process. Then the attack is detected by using the Ensemble crossover XG boost classifier. An optimized gradient tree boosting system creates decision trees in a sequential form. From the results, the concluded proposed system effectively monitors patient health conditions, detects data breaches, and improves cloud security. Simulated results show that our proposed strategy improves detection accuracy, increases the proportion of true positives, and reduces false positives by a significant margin.

Regularization Method for Discrete Mesh Points

A regularization method for discrete mesh points based on binary tree structure is presented to solve the link chaos between mesh points in the structured sorting of the interface mesh. Firstly, the idea of the present regularization method is introduced in detail. The present method is based on the one-to-one mapping relationship between the binary tree structure and the structured mesh data and reconstructs the row and column information as well as obtains the structured sorting of mesh points by creating the binary tree model of the mesh data. Then, the detailed procedure of regularizing the binary tree model is described, including mesh point classification, root node creation, child nodes addition and so on. Finally, the binary tree model is traversed layer by layer to obtain the sorted structured mesh points. The numerical experimental results on mesh data with different configurations, sizes and ranks show that the present regularization method has good adaptability and high robustness. Moreover, the method also indicates excellent efficiency in the structured sorting of interface mesh used in industrial cases.

Creation of a rat lymphedema model using extensive lymph node dissection and circumferential soft tissue resection: Is this a reliable model?

The medical demand for lymphedema treatment is huge since the disease mechanism remains unclear, and management are difficult. Our purpose was to develop a reliable lymphedema model mimicking the clinical scenario and allows a microsurgical approach. Male Lewis rats weighing 400 to 450 g were used to create lymphedema with groin and popliteal lymph node dissection and creation of 5 mm circumferential skin defect (n=6). A skin incision was made and closed primarily for control group (n=5). Evaluation included indocyanine green (ICG) lymphangiography 1 and 2months postoperatively, volume difference between bilateral hindlimbs measured using micro-CT, and the skin was harvested for histological evaluation 2months postoperatively. Larger volume differences present in the lymphedema group (17.50 ± 7.76 vs. 3.73 ± 2.66%, p < .05). ICG lymphangiography indicated dermal backflow only in the lymphedema group. Increased thickness of the epidermis was noted in lymphedema group (28.50 ± 12.61 μm vs. 15.10 ± 5.41 μm, p < .0001). More CD45+ (35.6 ± 26.68 vs. 2.8 ± 4.23 cells/high power field [HPF], p < .0001), CD3+ (38.39 ± 20.17 vs. 9.73 ± 8.62 cells/HPF, p < .0001), and CD4+ cell infiltration (11.7 ± 7.71 vs. 2.0 ± 2.67 cells/HPF, p < .0001) were observed in the lymphedema group. Collagen type I deposition was more in the lymphedema group (0.15 ± 0.06 vs. 0.07 ± 0.03, p < .0005). A rat lymphedema model was successfully established. The model can be applied in lymphedema related research.

An Adaptable Secure Scheme in Mobile Ad hoc Network to Protect the Communication Channel From Malicious Behaviours

Mobile ad-hoc network (MANET) is a trending field in the smart digital world; it is effectively utilized for communication sharing purposes. Besides this communication, it has numerous advances like a personal computer. However, the packet drop and low throughput ratio became serious issues. Several algorithms are implemented to increase the throughput ratio by developing multipath routing. But in some cases, the multipath routing ends in routing overhead and takes more time to transfer the data because of data load in the same path. To end this problem, this research aimed to develop a novel temporary ordered route energy migration (TOREM). Here, the migration approach balanced the data load equally and enhanced the communication channel; also, the reference node creation strategy reduced the routing overhead and packet drop ratio. Finally, the outcome of the proposed model is validated with recent existing works and earned better results by minimizing packet drop and maximizing throughput ratio.

Prolapse repair after anterior exenteration.

This report presents our experience in performing prolapse repair after anterior exenteration. The patient had a history of invasive bladder cancer and underwent a robotically assisted laparoscopic anterior exenteration with extended bilateral pelvic lymph node dissection and creation of an Indiana pouch continent diversion. Her pelvic organ prolapse progressed over time despite multiple pessary fittings. She eventually decided to proceed with pelvic reconstructive surgery 6 years after her cancer surgery. She underwent a successful vaginal native tissue reconstruction with uterosacral ligament suspension, posterior repair and reconstruction of the anterior compartment. The patient has been followed for 16months without recurrent prolapse. Vaginal native tissue pelvic reconstruction is feasible in a patient with a history of pelvic exenteration.

Dynamics of essential interaction between firms on financial reports.

Companies tend to publish financial reports in order to articulate strategies, disclose key performance measurements as well as summarise the complex relationships with external stakeholders as a result of their business activities. Therefore, any major changes to business models or key relationships will be naturally reflected within these documents, albeit in an unstructured manner. In this research, we automatically scan through a large and rich database, containing over 400,000 reports of companies in Japan, in order to generate structured sets of data that capture the essential features, interactions and resulting relationships among these firms. In doing so, we generate a citation type network where we empirically observe that node creation, annihilation and link rewiring to be the dominant processes driving its structure and formation. These processes prompt the network to rapidly evolve, with over a quarter of the interactions between firms being altered within every single calendar year. In order to confirm our empirical observations and to highlight and replicate the essential dynamics of each of the three processes separately, we borrow inspiration from ecosystems and evolutionary theory. Specifically, we construct a network evolutionary model where we adapt and incorporate the concept of fitness within our numerical analysis to be a proxy real measure of a company’s importance. By making use of parameters estimated from the real data, we find that our model reliably replicates degree distributions and motif formations of the citation network, and therefore reproducing both macro as well as micro, local level, structural features. This is done with the exception of the real frequency of bidirectional links, which are primarily formed as a result of an entirely separate and distinct process, namely the equity investments from one company into another.

Josephson signatures of Weyl node creation and annihilation in irradiated Dirac semimetals

Weyl node creation and annihilation are unique topological phenomena associated with Weyl fermions. Besides the magnetic field, high-frequency illumination can also break the time-reversal symmetry and induce the creation and annihilation of Weyl nodes from a Dirac semimetal. Experimentally, the Weyl node creation and annihilation induced by a magnetic field have been verified by the signature of negative magnetoresistance. In this work, instead of magnetoresistance signatures by application of a magnetic field, we theoretically study the Josephson signatures of Weyl node creation and annihilation in irradiated Dirac semimetals. It is found that Weyl node creation is accompanied by a two-mode oscillation and 0-$\ensuremath{\pi}$ transitions in the Josephson current. We further illustrate that two oscillation modes stem from two Andreev reflection processes: opposite-chirality and equal-chirality Andreev reflections, respectively. With Weyl node annihilation, the Josephson current is first shut down and then recovered by the activation of spin-flipping at interfaces by two ferromagnets. The recovered anomalous Josephson current has an arbitrary and tunable ground-state phase difference, other than 0 and $\ensuremath{\pi}$. These predictions are helpful for experimental observation of illumination-induced Weyl node creation and annihilation.

Improved Security of Data in Cloud Network to Prevent Detect Key Recovery Attacks Using Node Creation for Authentication

The use of internet in the past decade has increased rapidly people using it for transmission of data saving their works, storing all the private information in a system and transmitting through internet. Due to high usage of internet there is also possibility of losing data by unauthorized access and getting hacked and misuse of data. Previously there was a method used known as kids, but the problem with this method was the method used for generation of key and keeping it secrecy, the attackers could easily get access to the key after black box attack. In this paper the proposed system helps to provide more security and prevents it from attacks and also protect the data stored in the system. The proposed schema can be implemented in hospitals for health care domain, for saving the data of Patience by using cloud storage by using it in the detection system. Many developers and researched have introduced schemes in Machines learning and one of this scheme was key based detection system, But this system required more security to prevent from the attackers, in the proposed module am using cryptographic algorithm for creating secret key and for saving the data and Bowl Fish algorithm to hide the data from the attackers and recover the key from the AES algorithm which is saved in encrypted format which has steps of verification to recover the key and give prevention against unauthorized usage and it provides security from the attackers by saving all the data of patience in a hospital using different domains kept in cloud platform.

A 3D Finite Difference Thermal Model Tailored for Additive Manufacturing

Physics-based modeling of metal additive manufacturing (AM) processes is computationally challenging due to the very fine meshing required in both time and space. State-of-the-art numerical models that offer great insight into the process have been developed, but they require powerful computational resources and weeks of processing time. Thus, it is often more time-effective to fabricate multiple builds within the time it takes to complete one simulation prediction, further reinforcing the current trial-and-error approach to optimizing the build parameters. This study presents a simplified approach to the transient thermal modeling of the AM process. The numerical model is designed to run on a moderate laptop or desktop computer, without use of parallel processing. The method described in this study uses a unique approach to node creation which leverages the simplicity of the finite difference method to provide predictions in less time than it takes to build the part. Coarse meshing in both time and space along with simplifying assumptions about the solidification process are used in this numerical approach. Model predictions track well with experimental measurements. This approach is being developed for use in an industrial setting to inform deposition parameters based on a desired thermal profile.

Курс компьютерной графики для студентов строительных специальностей

The article considers the state and trends in the development&#x0D; of content and methodology of teaching of engineering&#x0D; graphics at universities, in particular at South Ural State University&#x0D; (SUSU). It is noted that the development goes in the direction of&#x0D; computerization of the course and of the expansion of the scope&#x0D; of application of 3D modeling and drawing.&#x0D; The author overviews the content and methodology of teaching&#x0D; construction engineering students of SUSU computer graphics.&#x0D; The course is designed for the AutoCAD package. The article introduces&#x0D; three graphical tasks that reveal features of construction&#x0D; drawing. The topics of the abovementioned tasks are the perspective&#x0D; and shadows, drawing of civil buildings, and drawing of truss&#x0D; nodes. The course focuses on modern design technologies in construction.&#x0D; To perform the aforementioned tasks the author implements&#x0D; both traditional 2D (computer) methods of drawing and&#x0D; modern 3D design methods which are actively developing. Work&#x0D; goals and objectives for each task are given, as well as the examples&#x0D; of drawings, 3D models and the sequence of their construction.&#x0D; The author shows methods of studying properties of geometrical&#x0D; projections and of shadowing difficult elements of building on&#x0D; the example of 3D modeling. The article gives the examples of&#x0D; photorealistic rendering done by the students for building visual&#x0D; images.&#x0D; The article also exposes shadowing in the orthographic projections&#x0D; on the example of smaller architectural projects and civil&#x0D; constructions. Shadows are built both in the automatic 3D modelling&#x0D; and visualization mode and in traditional 2D methods.&#x0D; The author dwells on modern means of automation of geometric&#x0D; construction as well as shows the example of parameterization&#x0D; in the process of determining optimal parameters of perspective&#x0D; projections. The article reveals the construction of the dynamic&#x0D; block as a means of storing graphical information of modern CAD&#x0D; systems. The example of block construction in the process of truss&#x0D; node creation is also given.&#x0D; The author provides the requirements for the contents of the&#x0D; semester report, the list of additional competencies acquired by the&#x0D; student after the development of the course.

Chirality effect on superconductivity

We consider electron systems characterized by chirality, such as Dirac fermion systems and iron-based superconductors. We investigate the chirality effect on superconducting states in such a system. We show that chirality effect leads to a nodal structure in the superconducting gap function. The node creation mechanism depends on the wave vector q of the pairing interaction and vorticity that characterizes chirality of electrons. The node creation effect due to chirality is significant for the case of Dirac fermions with q = (π, 0) and for the case of iron-based superconductors with q = (π,π).

An empirical comparison of cascade and flat variants of incremental node creation algorithm

We propose incremental node creation algorithm (INCA). INCA emphasizes on architectural adaptation and functional adaptation in a unified frame work. INCA starts from a single hidden node and then trains node one by one incrementally. Two variants of INCA are developed, namely cascade and flat. In the cascade variant, every hidden node is added in a new hidden layer that is connected to the network inputs and all pre-existing hidden nodes. In contrast, the flat variant adds node one by one to a single hidden layer. Sixteen regression problems are used to investigate which network growing strategy provides the better generalization performance. Simulation results reveal that both architectures perform well on all the investigated regression problems of varying complexities. In general, cascade is better than flat architecture except some real world problems. The trigonometric sine activation function provides better approximation capability than log-sigmoid function except some regression problems.