Tree-shaped Structure Research Articles

Multi-objective optimization of heat charging performance of phase change materials in tree-shaped perforated fin heat exchangers

To enhance the convective heat transfer and overall thermal performance of horizontal latent heat storage (LHS) units, an innovative tree-shaped fin structure with perforations was introduced. A numerical simulation study examined the impact of perforation layers on the unit's overall performance. For a comprehensive analysis of the perforations' cumulative effect on the LHS unit, the Response Surface Methodology (RSM) was utilized to assess the influence of variations in perforation diameter and number on material consumption and heat exchange targets, deriving predictive correlations. The results indicated that compared to a non-perforated structure, the maximum improvement was observed with three layers of perforations, reducing material usage by 0.93%, while increasing the Nusselt number (Nu) and heat exchange by 10.19% and 36.51%, respectively. Moreover, the average temperature of the phase change material (PCM) in one and three perforated layers was higher than in the non-perforated tree-shaped fins, with complete melting times reduced by 5.37% and 2.51%, respectively. RSM results showed a negative linear correlation between increased perforation diameter and number with reduced material consumption, with the number of perforations having a more significant impact on heat exchange than their diameter. The Pareto optimal points obtained using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) demonstrated lower material usage and higher heat exchange. Compared to the non-perforated tree-shaped fins, the Pareto-optimized solutions reduced material consumption by 2%–2.68% and increased heat exchange by 79.42%–94.45%. Analysis of the flow field, temperature field, and phase change process revealed that perforations significantly enhanced the mixing of PCM in different areas of the tree-like fins and secondary flow, with temperatures near the perforations increasing by 5–7K and flow velocity by 3–4 times, significantly promoting convective heat transfer.

COMPACT TWO-PORT ANTENNA WITH PARASITIC NOTCH AND DEFECTive GROUND FOR WIRELESS COMMUNICATION

This paper presents a compact multiple input multiple output antenna (MIMO) with a wireless local area network (WLAN) notch characteristic for ultra-wideband (UWB) applications. The two modified rectangular radiators share a common ground that provides UWB response. The design is modeled over FR4 material and has an overall compact size of 0.34 λ0 × 0.24 λ0 × 0.015 λ0 mm3 at the frequency of 2.9 GHz. A tree-shaped decoupling structure with multiple slots in the ground is introduced between the ports to establish good isolation. The open-ended slots in the ground perturb diminish the surface current between two ports and ensure the isolation larger than 20 dB in the entire UWB from 2.9 GHz to 10.2 GHz. An S-shaped parasitic stub is utilized at the backside of the radiating element to implement a band notch characteristic from 5.03 GHz to 5.90 GHz. The proposed antenna is also investigated for wearable applications with a human tissue model showing a small SAR value (less than 1.6 W/kg). The simulated and measured result shows that the designed antenna suits MIMO performance and wearable devices.

A low-profile flower-shaped MIMO antenna for wireless applications

ABSTRACT A low-profile, compact and efficient antenna is especially desirable for wireless applications, as it can reduce the size and weight of the system and improve its performance. In recent years, flower-shaped antennas have gained popularity due to their low profile, broad bandwidth and good radiation characteristics. In this work, a high-isolated dual-element UWB-MIMO antenna is experimentally verified having size of 32 × 39 × 0.8 mm3. The main radiating element of MIMO setup comprises a Half-Cut Flower-Shaped (HCFS) resonator. A tree-shaped decoupling structure is use to enhance the isolation. The simulated operating band of the proposed 2-port UWB-MIMO antenna ranges from 2.3 to 2.68 GHz and 3.15 to 12.87 GHz which covers Bluetooth, Wi-Fi/WLAN, Wi-MAX and UWB) with inter-element isolation of more than 15 dB and 20 dB, respectively. The measured results are found in close agreement with simulated ones. Furthermore, the diversity parameters such as Envelope Correlation Coefficient (ECC), Channel Capacity Loss (CCL), Mean Effective Gain (MEG), Effective Diversity Gain (EDG) and Total Active Reflection Coefficient (TARC) have also been analysed to ensure its legitimacy for wireless applications. Moreover, the simulation S-parameters characteristic of the proposed 8-element antenna for wireless access point applications has also been showcased.

An Improved Rank Order Centroid Method (IROC) for Criteria Weight Estimation: An Application in the Engine/Vehicle Selection Problem

The focus of this paper is on the criteria weight approximation in Multiple Criteria Decision Making (MCDM). An approximate weighting method produces the weights that are surrogates for the exact values that cannot be elicited directly from the DM. In this field, a very famous model is Rank Order Centroid (ROC). The paper shows that there is a drawback to the ROC method that could be resolved. The paper gives an idea to develop a revised version of the ROC method called Improved ROC (IROC). The behaviour of the IROC method is investigated using a set of simulation experiments. The IROC method could be employed in situations of time pressure, imprecise information, etc. The paper also proposes a methodology including the application of the IROC method in a group decision making mode, to estimate the weights of the criteria in a tree-shaped structure. The proposed methodology is useful for academics/managers/decision makers who want to deal with MCDM problem. A study case is examined to show applicability of the proposed methodology in a real-world situation. This case is engine/vehicle selection problem, that is one of the fundamental challenges of road transport sector of any country.

Identification of Tree-Shaped Structure using 3D Reconstruction and Density-Based Clustering

Identification of Tree-Shaped Structure using 3D Reconstruction and Density-Based Clustering

Super Ultra-Wideband Planar Antenna with Parasitic Notch and Frequency Selective Surface for Gain Enhancement

A compact Super ultra-wideband (SUW) antenna is discussed in this work. A rectangular radiator is modified into a tree-shaped structure with the defected partial ground to enhance the operating bandwidth. The novel rectangular parasitic with the circular slot is used as a notch in the ground plane which prevents the WLAN frequency. The proposed SUW antenna is achieving the 10 dB impedance bandwidth (IBW) from 3.5 GHz to 66.5 GHz frequency with a notched band varying from 5.0 GHz to 5.4 GHz. The bandwidth ratio (BDR) of the proposed SUW antenna is 1773.4 whereas the obtained bandwidth percentage (BW %) is 180. A modified SRR frequency selective surface (FSS) is designed for UWB application to improve the gain of the antenna. The compact unit cell of FSS is having electrical dimensions of 0.16λ0x 0.16λ0 The antenna achieves the maximum realized gain 9.46 dB when FSS is loaded as a superstrate and up to 5.2 dB gain enhancement is observed in the UWB frequency.

Mechanism study on the synergistic coupling of the double-dish solar latent heat storage system to enhance heat transfer

With the rapid advance of the global economy, latent heat storage (LHS) is critical to solar thermal utilization. In this study, a double-dish solar Stirling LHS power generation system was designed. The heat transfer performance of the thermal storage system was improved by using the gradient tree-shaped fins and adding graphene nanoparticles to paraffin. Two-dimensional numerical models of three thermal storage systems were developed to study the effects of natural convection and graphene nanoparticle concentration on the melting characteristics of paraffin. From the perspective of field synergy, the coupling effect of fin structure and graphene nanoparticle concentration on the heat transfer process was analyzed. The results show that natural convection exerts an important role in the heat transfer characteristics of paraffin melting. Compared with the six-longitudinal and snowflake fin structures, the gradient tree-shaped fin structure shows a 52.13% and 27.73% reduction in the complete melting time and a 52.16% and 9.53% increase in thermal storage efficiency. Little variation is observed in the liquid phase rate and the average temperature of the composite phase change materials (PCMs) with different concentrations of graphene nanoparticles. The total thermal storage capacity of composite PCMs is higher than that of pure paraffin. The synergistic coupling of gradient tree-shaped fin arrangement and graphene nanoparticles added in paraffin can enhance heat transfer.

Methanol steam reforming reactor with fractal tree-shaped structures for photovoltaic–thermochemical hybrid power generation

The photovoltaic–thermochemical (PVTC) hybrid system converts thermal energy dissipated by concentrating photovoltaic cells to gain in power generation via the endothermic methanol steam reforming (MSR) reaction. Conventional MSR reactors are challenged by undesirable performances in heat transfer and methanol conversion, impacting the performances of power generation and energy storage of PVTC systems. In this work, an innovative fractal tree-shaped structure is introduced into the flow channels configuration of an MSR reactor to enhance heat transfer performance and methanol conversion. The methanol conversion of the novel reactor is experimentally assessed, which is 12.1 percentage points (relative improvement of 26.5%) higher than that of conventional reactors with serpentine flow channels design. A 3-D multiphysics model of the MSR reactors coupling heat transfer, gas flow, and chemical reaction is developed to reveal the mechanism of methanol conversion improvement. The fractal tree-shaped structure can improve the net solar-electric efficiency of the photovoltaic–thermochemical hybrid system by 5.6–7.5% (up to 36.6%). The efficient solar energy power generation of the PVTC system with energy storage ratio ensures considerable dispatchability for hybrid solar power generation.

Hierarchical Semantic Risk Minimization for Large-Scale Classification

Hierarchical structures of labels usually exist in large-scale classification tasks, where labels can be organized into a tree-shaped structure. The nodes near the root stand for coarser labels, while the nodes close to leaves mean the finer labels. We label unseen samples from the root node to a leaf node, and obtain multigranularity predictions in the hierarchical classification. Sometimes, we cannot obtain a leaf decision due to uncertainty or incomplete information. In this case, we should stop at an internal node, rather than going ahead rashly. However, most existing hierarchical classification models aim at maximizing the percentage of correct predictions, and do not take the risk of misclassifications into account. Such risk is critically important in some real-world applications, and can be measured by the distance between the ground truth and the predicted classes in the class hierarchy. In this work, we utilize the semantic hierarchy to define the classification risk and design an optimization technique to reduce such risk. By defining the conservative risk and the precipitant risk as two competing risk factors, we construct the balanced conservative/precipitant semantic (BCPS) risk matrix across all nodes in the semantic hierarchy with user-defined weights to adjust the tradeoff between two kinds of risks. We then model the classification process on the semantic hierarchy as a sequential decision-making task. We design an algorithm to derive the risk-minimized predictions. There are two modules in this model: 1) multitask hierarchical learning and 2) deep reinforce multigranularity learning. The first one learns classification confidence scores of multiple levels. These scores are then fed into deep reinforced multigranularity learning for obtaining a global risk-minimized prediction with flexible granularity. Experimental results show that the proposed model outperforms state-of-the-art methods on seven large-scale classification datasets with the semantic tree.

Taṭbīq Al-Manhaj Al-Takamuly Fī Mu’assasāt Al-Ta’līm Al-‘Āly

This study aims to (1) describe the idea of an integrated curriculum in higher education, (2) depict its implementation at the university level, and (3) find out the impact of the curriculum on university development. This research used a qualitative approach. It employed a literature study. The researchers gathered the data from book reviews and related journals. Data analysis involved collecting the data, sorting, presenting, and drawing conclusions. The findings showed that (1) the idea of an integrated curriculum was depicted in a tree-shaped scientific structure; (2) the integrated curriculum was done by requiring all students to learn Arabic and English, as well as providing opportunities for all students to memorize the Quran and practice Islamic life; (3) integrated curriculum contributed to accelerating the development and internationalization of institutions. Moreover, it improved human resources competencies.

A Compact Planar Multi-Resonant Multi-Broadband Fractal Monopole Antenna for Wi-Fi, WLAN, Wi-MAX, Bluetooth, LTE, S, C, and X Band Wireless Communication Systems

In this paper, a highly efficient tree-shaped fractal antenna with multi-broadband resonance characteristics is proposed. The proposed antenna exhibits broad operating bandwidth, high gain, and high efficiency characteristics due to the suggested modifications in the antenna geometry. The suggested circular patch is modified by introducing slots in the form of a tree-shaped fractal structure, and the partial ground plane is modified by incorporating a narrow rectangular slot. The proposed antenna is designed on an FR4 substrate of [Formula: see text][Formula: see text]mm3. The prototype of the proposed antenna has been fabricated and tested to justify the simulation results. The measurement results are in good agreement with the simulation that validates the multi-broadband design approach of the proposed fractal antenna. As per the measurement results, the proposed antenna operates at four distinct bands with [Formula: see text]10[Formula: see text]dB impedance bandwidths of 600[Formula: see text]MHz (2.2–2.8) GHz, 1070[Formula: see text]MHz (3.3–4.37) GHz, 2550[Formula: see text]MHz (4.75–7.3) GHz, and 2200[Formula: see text]MHz (9.7–11.9) GHz. Furthermore, a high peak gain of 10.23[Formula: see text]dB and a peak radiation efficiency of 96.65% are recorded for the suggested fractal antenna. The suggested compact bandwidth enhanced multi-band antenna can be useful for several wireless communication systems such as wireless fidelity (Wi-Fi), wireless local area network (WLAN), Bluetooth, long-term evolution (LTE), C, S and X bands.

Implementation Of Backtracking Algorithm In Elena Puzzle Game Setup

Elena Puzzle is a puzzle game that appears on an anime called Phi Brain in episode 10, Elena puzzle game is a puzzle game where players have to put the 18 pieces of pawns on the game board size 6x6. Pawns are placed consists of the three different colors red, blue and yellow. Pawns put on in the game area must be in accordance with the instructions on the edge of the arena. The instructions are on the sidelines of arena explain that the first color that was encountered in the edge of the arena is a color that corresponds to these instructions. In each row and column in the game of arena can not have two same colors and in each row and column must have three different colors. The purpose of this research is to build an artificial intelligence agent that can solve the puzzle. The methodology used is the backtrack algorithm, that is an algorithm based on Depth-First Search, so the search for solutions is done by tracing the rooted tree-shaped structure in preorder. This process is characterized by the expansion of the deepest node until no longer found the successor of a node. The results will be obtained from existing applications is backtracking algorithm implementation in building artificial intelligence agencies in order to complete the puzzle in accordance with the instructions provided.

FEM analysis for the behaviour of two-dimensional CHS joints with asymmetrical Full-Overlapped top-connection

Circular hollow section steel profiles are often used for industrial purposes, like offshore structures or for aesthetical reasons. By welding two or more steel members with different inclination angles columns with a tree-shaped structure will be formed. Designers are using this column to get a natural optic for example in representative halls. Like in nature the connected members often have asymmetrical angles. To calculate the nodes of these structures is a complex part. Due to the geometrical and material heterogeneity, different stresses arise in the microstructure. Current standards have got limitations. These limitations are there for material, geometrical options or process in welding. The vertical column is defined as chord, the connected members as braces. The inclination angle is the horizontal imperfection between braces and chord. Standards have got limitations regrading this inclination angle. There is no definition for an angle smaller than 30°. Because of aesthetical reasons, there are steel joints with two or more braces, where the inclination angles are not equal. An example is the natural optic as the ideal of a tree. Columns with an on-top connection, together with a steel plate node is not included in the current standards. However, designing engineers often have to build their own models for complex structures or design it with the help of laboratory tests. In literature, it was figured out, that the inclination angle has got a large influence on the resistance of a steel joint. Due to the geometrical heterogeneity, internal bending moments can arise, which degrades the carrying capacity of the joint. This paper is about numerical case studies of tree-shaped columns with an asymmetrical shape. The full-overlapped node is made of circular hollow section profiles (CHS), which are welded in a three-dimensional way. The aim is to figure out the influence of the inclination angles on the stability of asymmetrical shaped columns in the ultimate limit state, when the angles are not equal.

A hybrid of genetic algorithm and particle swarm optimization for reducing material waste in extrusion-basedadditive manufacturing

PurposeThe purpose of this paper is to report the design of a lightweight tree-shaped support structure for fused deposition modeling (FDM) three-dimensional (3D) printed models when the printing path is considered as a constraint. Design/methodology/approachA hybrid of genetic algorithm (GA) and particle swarm optimization (PSO) is proposed to address the topology optimization of the tree-shaped support structures, where GA optimizes the topologies of the trees and PSO optimizes the geometry of a fixed tree-topology. Creatively, this study transforms each tree into an approximate binary tree such that GA can be applied to evolve its topology efficiently. Unlike FEM-based methods, the growth of tree branches is based on a large set of FDM 3D printing experiments. FindingsThe hybrid of GA and PSO is effective in reducing the volume of the tree supports. It is shown that the results of the proposed method lead to up to 46.71% material savings in comparison with the state-of-the-art approaches. Research limitations/implicationsThe proposed approach requires a large number of printing experiments to determine the function of the yield length of a branch in terms of a set of critical parameters. For brevity, one can print a small set of tree branches (e.g. 30) on a single platform and evaluate the function, which can be used all the time after that. The steps of GA for topology optimization and those of PSO for geometry optimization are presented in detail. Originality/valueThe proposed approach is useful for the designers and manufacturers to save materials and printing time in fabricating complex models using the FDM technique. It can be adapted to the design of support structures for other additive manufacturing techniques such as Stereolithography and selective laser melting.

Empirical and Theoretical Evaluation of a Tree-Shaped DNA Nanostructure with a Looped Arm (L-DNA)

Several nanostructures have been created with the advent of nanotechnology. DNA has been recognized as a new building block material in addition to its genetic coding role because of its unique features (e.g., intrinsic biocompatibility, precise tenability, specific selectivity). DNA can be organized into a variety of self-assembled nanomaterials including a sphere, a ball, and even an emoticon. In particular, a tree-shaped DNA structure possessing characteristic fractural patterns is easily controlled by size and functionality and can be exploited in various fields. Here, we report an empirical and theoretical evaluation of a Y-shaped tree DNA nanostructure with a looped arm (L-DNA). The synthesized L-DNAs were analyzed for thermal and structural stability. The melting temperature (Tm) of a Y-shaped DNA (Y-DNA) as a core unit and a model DNA nanostructure comprising of central Y-DNA and looped arm were measured individually. According to the complexity (e.g., increased length of the single stranded DNA (ssDNA) used), its yield suddenly decreased with the generation of ssDNAs with distinctive secondary structures. A complicated DNA product is predicted by considering the Tm of expected secondary structures, with increased Tm with respect to variation in salt concentrations. Therefore, the new DNA nanostructure may be utilized as a platform for various practical applications.

A Novel Decomposition Model for Visual Rail Surface Inspection

Rail surface inspection plays a pivotal role in large-scale railway construction and development. However, accurately identifying possible defects involving a large variety of visual appearances and their dynamic illuminations remains challenging. In this paper, we fully explore and use the essential attributes of our defect structure data and the inherent temporal and spatial characteristics of the track to establish a general theoretical framework for practical applications. As such, our framework can overcome the bottleneck associated with machine vision inspection technology in complex rail environments. In particular, we consider a differential regular term for background rather than a traditional low-rank constraint to ensure that the model can tolerate dynamic background changes without losing sensitivity when detecting defects. To better capture the compactness and completeness of a defect, we introduce a tree-shaped hierarchical structure of sparse induction norms to encode the spatial structure of the defect area. The proposed model is evaluated with respect to two newly released Type-I/II rail surfaces discrete defects (RSDD) data sets and a practical rail line. Qualitative and quantitative evaluations show that the decomposition model can handle the dynamics of the track surface well and that the model can be used for structural detection of the defect area.

Energy Balanced Source Location Privacy Scheme Using Multibranch Path in WSNs for IoT

Source location privacy, one of the core contents of Wireless Sensor Network (WSN) security, has a significant impact on extensive application of WSNs. In this paper, a novel location privacy protection routing scheme called Energy Balanced Branch Tree (EBBT) is proposed by using multibranch and fake sources. This scheme has three phases. In the first place, the data of the source are randomly sent to a certain intermediate node. Then, a minimum hop routing (MHR) from the intermediate node to the base station is formed. Then, branch paths with fake sources are generated dynamically from some nodes on the MHR path. Finally, a tree‐shaped structure from real source nodes and fake source nodes to the base station is achieved. In difference to the previous schemes, the location of the real source in the EBBT scheme does not affect the location and the number of fake sources. During the formation of the tree‐shaped multibranch paths, the residual energy of nodes is considered sufficiently, and the control of the direction of each branch path is also involved. The influence of the number and length of branches on the network lifetime and network security is also investigated. Experimental results show that the proposed algorithm has the advantages of long network security period and lifetime, as well as high path diversity. Our simulation further illustrates that the EBBT scheme has favorable privacy of the source location without changing the network lifetime.

Detecting factors associated with polypharmacy in general practitioners’ prescriptions: A data mining approach

Prescribing and consuming drugs more than necessary is considered as polypharmacy, which is both wasteful and harmful. The purpose of this paper is to establish an innovative data mining framework for analyzing physicians’ prescriptions regarding polypharmacy. The approach consists of three main steps: pre-modeling, modeling, and post-modeling. In the first step, after collecting and cleaning the raw data, several novel physicians’ features are extracted. In the modeling step, two popular decision trees, i.e., C4.5 and Classification and Regression Tree (CART), are applied to generate a set of If-Then rules in a tree-shaped structure to detect and describe physicians’ features associated with polypharmacy. In a novel approach, the response surface method (RSM) as a tool for hyper-parameter tuning is simultaneously applied along with correlation-based feature selection (CFS) to enhance the performance of the algorithms. In the post-modeling step, the discovered knowledge is visualized to make the results more perceptible, then is presented to domain experts to evaluate whether they make sense or not. The framework has been applied to a real-world dataset of prescriptions. The results have been confirmed by the experts, which demonstrates the capabilities of the data mining framework in the detection and analysis of polypharmacy.

An Improved Two-Level Support Structure for Extrusion-Based Additive Manufacturing

• Two-level support is an effective support for Extrusion Based Additive Manufacturing • An improved strategy for generating a two-level support is proposed • Experiments validate that the improved strategy saves more support volume Extrusion-Based Additive Manufacturing is one of the most commonly used Additive Manufacturing techniques. However, the technique requires that the overhang features in a model should be provided with supports from below. The added supports contribute to a major source of material waste during the manufacturing process. In order to save support materials, considering 3D printing directions as a constraint of adding supports, we propose a two-level support structure where Level 1 consists of a truncated beam-structure and Level 2 consists of a slim tree-shaped structure. The main contribution of this paper is the modification of the shape of Level 1 support and optimization of the topologies of the tree-supports in Level 2. The approach developed in this paper leads to material savings up to 31.01% and printing time savings up to 13.10% in comparison to the existing literature. Several comparison experiments were conducted on benchmark models to validate the developed approach and have been reported in this paper.

Evolution and Influencing Factors of Township Spatial Form: A Two-Dimensional Perspective

The countryside is the habitat of food, ecology, and culture, and the indispensable basis for human survival and development. Assessing the spatial and temporal evolution of rural settlements contributes to the promotion of rural scientific developments. This study used the fractal theory, center-of-gravity model, and spatial syntax to analyze the spatial and temporal evolution of Shenyang Ciyutuo Subdistrict and its influencing factors based on geospatial data from 2009‒2019, from the perspectives of internal characteristics and external morphological changes. In terms of the external characteristics, from 2009‒2019, the compactness index increased from 0.414 to 0.454, the expansion rate increased from 1.17% to 3.11%, and the expansion intensity increased from 0.05% to 0.15%. From 2014‒2019, the western part of the subdistrict experienced the maximum expansion rate and expansion intensity. The center-of-gravity of the construction land shifted to the west and southwest. The internal characteristics of land use depended on geographical conditions. Clusters of rural settlements were formed in a north-south direction due to the topography and along the riverside in a band-like manner. From 2009‒2019, the integration level of the subdistrict improved and the scale and number of integration axis increased, forming a multicore tree-shaped structure. Pearson’s correlation analysis showed that urbanization is the main factor affecting the spatial and temporal land-use evolution, with transportation convenience, industrial park, and proximity to the river having little effects. This study provides a theoretical basis for the development of Ciyutuo Subdistrict and provides a reference for the development of similar commercial towns.