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Facing the dual pressure of eutrophication control and global phosphorus scarcity, the efficient removal and recovery of phosphate from wastewater has attracted growing attention in recent years. Herein, an efficient nanocomposite (nCaO2-BFS) was successfully synthesized through a facile coprecipitation method by loading nano-calcium peroxide (nCaO2) onto blast furnace slags (BFS) and used for phosphate removal and recovery from wastewater. Based on the preliminary screening of as-prepared nCaO2-BFS sorbents regarding phosphate removal efficiency, the nCaO2-BFS nanocomposite prepared with a CaCl2-to-BFS mass ratio of 0.6:1, NH3·H2O amount of 20 mL, and H2O2 amount of 12 mL was selected for further characterization and phosphate elimination. Results showed that the developed nCaO2-BFS sorbent exhibits a superior adsorption capacity of 67.48 mg·g-1, a broadly applicable pH range from 4 to 10, and strong selectivity for phosphate in the presence of competing anions including Cl-, NO3-, SO42-, HCO3-, and CO32-. Mechanistically, surface precipitation and inner-sphere complexation via ligand exchange were identified as the primary sorption mechanism for nCaO2-BFS in capturing phosphate. The plant growth test confirmed that the phosphate-laden nCaO2-BFS sorbent could be used as a slow-release fertilizer to promote the growth of Brassica rapa L. Therefore, applying nCaO2-BFS appears to be a promising method for remediating excessive phosphate and recovering the non-renewable phosphorus resource.

Diagnosing bearing defects (BFs) in squirrel cage induction machines (SCIMs) is essential to ensure their proper functioning and avoid costly breakdowns. This paper presents an innovative approach that combines intelligent direct torque control (DTC) with the use of Hilbert transform (HT) to detect and classify these BFs. The intelligent DTC allows precise control of the electromagnetic torque of the asynchronous machine, thus providing a quick response to BFs. Using HT, stator current is analyzed to extract important features related to BFs. The HT provides the analytical signal of the current, thus facilitating the detection of anomalies associated with BFs. The approach presented incorporates an intelligent DTC that adapts to stator current variations and characteristics extracted via the HT. This intelligent control uses advanced algorithms such as neural networks (ANN-DTCs) and fuzzy logic (FL-DTCs). In this paper, a comparison between these two algorithms was performed in the MATLAB/Simulink environment for a three-phase asynchronous machine to evaluate their effectiveness under the proposed approach. The results obtained demonstrated a high ability to detect and classify BFs, confirming the effectiveness of each algorithm. In addition, this comparison highlighted the specific advantages and disadvantages of each approach. This information is valuable in choosing the most suitable algorithm according to the constraints and specific needs of the application. [ABSTRACT FROM AUTHOR]

A comparative study was conducted using Python and Pmaze to evaluate the performance of DFS, BFS, and A* search algorithms in path planning for a maze. The main objective of the project was to compare the efficiency of these algorithms in terms of path cost and algorithmic complexity. No physical robot was used in this study as it focused solely on the analysis of search algorithms. This study contributes to the advancement of knowledge in the field of path planning by exploring different approaches for mazes using Python and Pmaze. [ABSTRACT FROM AUTHOR]

An optimized robot path-planning algorithm is required for various aspects of robot movements in applications. The efficacy of the robot path-planning model is vulnerable to the number of search nodes, path cost, and time complexity. The conventional A-star (A*) algorithm outperforms other grid-based algorithms because of its heuristic approach. However, the performance of the conventional A* algorithm is suboptimal for the time, space, and number of search nodes, depending on the robot motion block (RMB). To address these challenges, this paper proposes an optimal RMB with an adaptive cost function to improve performance. The proposed adaptive cost function keeps track of the goal node and adaptively calculates the movement costs for quickly arriving at the goal node. Incorporating the adaptive cost function with a selected optimal RMB significantly reduces the searches of less impactful and redundant nodes, which improves the performance of the A* algorithm in terms of the number of search nodes and time complexity. To validate the performance and robustness of the proposed model, an extensive experiment was conducted. In the experiment, an open-source dataset featuring various types of grid maps was customized to incorporate the multiple map sizes and sets of source-to-destination nodes. According to the experiments, the proposed method demonstrated a remarkable improvement of 93.98% in the number of search nodes and 98.94% in time complexity compared to the conventional A* algorithm. The proposed model outperforms other state-of-the-art algorithms by keeping the path cost largely comparable. Additionally, an ROS experiment using a robot and lidar sensor data shows the improvement of the proposed method in a simulated laboratory environment. [ABSTRACT FROM AUTHOR]

We propose a comprehensive Electric Vehicle (EV) routing algorithm to find the optimal set of intermediate charging stations (CSs) present between a given source and destination. Each intermediate charging station is selected to maximize efficiency by considering three crucial parameters: distance to reach the destination from the selected CS, waiting time at the CS, and energy consumed to reach the selected CS along the route. Unlike existing algorithms, that focus solely on energy or distance, this algorithm integrates all three factors to generate an efficient path. Machine Learning (ML) is employed to predict vehicle range using data provided by the user, ensuring that the selected route avoids the risk of battery depletion midway. This predicted range is then used to determine CSs that can be reached from current location. Furthermore, the algorithm utilizes Breadth-First Search (BFS) to identify CS nodes with the least cost, enhancing routing accuracy. The cost of reaching each CS node is calculated using Neuro-Fuzzy Logic, which effectively handles uncertain inputs, which is common in EV routing scenarios. Comparative analysis against a recently proposed route planning algorithm (EV-RPA) reveals superior performance of the proposed approach, particularly as the number of CSs increases. It excels in all three aspects: distance covered, waiting time, and energy consumed, highlighting its effectiveness in optimizing EV routing.

The possibility of utilizing calumite (BSF) in the glass-ceramic industry was analyzed in this study. The properties of melaphyre glasses modified with 25 % and 50 % of calumite were determined after the post-melting and directional crystallization process. The produced glasses were subjected to microstructural analysis using light LM and scanning electron microscopy SEM. Their chemical composition was determined using XRF spectroscopy. After melting and directional crystallization, the glasses' structural tests were performed using FTIR spectroscopy and XRD phase analysis. The characteristic temperatures and the thermal stability of the glasses were determined with thermal analysis (DTA/TG) and dilatometric tests, which analysis was also valuable to determine the parameters of the directional crystallization process of melaphyre glasses. The results showed that unmodified melaphyre glasses demonstrate a low crystallization ability and do not crystallize even at 900 °C, while incorporating calumite into their composition increases their crystallization ability. The study showed that calumite significantly influences the chemical and structural characteristics of melaphyre glasses, which gives it the chance to be successfully used as a raw material for producing glass crystalline materials or mineral fibres. Notably, the findings underscore the potential utility of calumite as a proficient raw material for fabricating glass crystalline fibrous or insulating materials. [ABSTRACT FROM AUTHOR]

The potential toxicity of Cd to soil and rice plant severely threaten human health. This study was conducted to investigate the remediation effects of blast furnace slag (BFS) on the bioavailability of Cd in a contaminated paddy soil from a perspective of soil solution chemistry. Batch experiments, pot culture experiments, and principal analysis (PCA) were used to study the effects and mechanisms of BFS addition changing Cd chemical behavior and Cd toxicity. Results indicated that BFS facilitated Cd adsorption in soils, increased pH, Eh, and EC values in soil solution, whereas reduced dissolved Cd content. BFS amendment was efficient in decreasing root Cd intake and Cd upward transport in rice plant, with the Cd translocation factor in brown rice decreased by ∼ 75% (BFS treatment, 6‰ wt) relative to Cd treatment, which in turn increased rice biomass and grain yield. PCA indicated that the dissolved Cd concentration had a close relationship with soil pH and metal concentration in soil solution. Results from this study indicated that BFS had potential ability for either immobilization or remobilization of Cd in soils, and the findings have important implications for Cd-polluted soil remediation or other resource utilization with slag-based materials.

An optimized robot path-planning algorithm is required for various aspects of robot movements in applications. The efficacy of the robot path-planning model is vulnerable to the number of search nodes, path cost, and time complexity. The conventional A-star (A*) algorithm outperforms other grid-based algorithms because of its heuristic approach. However, the performance of the conventional A* algorithm is suboptimal for the time, space, and number of search nodes, depending on the robot motion block (RMB). To address these challenges, this paper proposes an optimal RMB with an adaptive cost function to improve performance. The proposed adaptive cost function keeps track of the goal node and adaptively calculates the movement costs for quickly arriving at the goal node. Incorporating the adaptive cost function with a selected optimal RMB significantly reduces the searches of less impactful and redundant nodes, which improves the performance of the A* algorithm in terms of the number of search nodes and time complexity. To validate the performance and robustness of the proposed model, an extensive experiment was conducted. In the experiment, an open-source dataset featuring various types of grid maps was customized to incorporate the multiple map sizes and sets of source-to-destination nodes. According to the experiments, the proposed method demonstrated a remarkable improvement of 93.98% in the number of search nodes and 98.94% in time complexity compared to the conventional A* algorithm. The proposed model outperforms other state-of-the-art algorithms by keeping the path cost largely comparable. Additionally, an ROS experiment using a robot and lidar sensor data shows the improvement of the proposed method in a simulated laboratory environment.

Recirculating aquaculture systems (RAS) and biofloc systems (BFS) have been considered eco-friendly aquaculture technologies in the last few decades. However, which system performs better has become a common question for fish farmers. Thus, this study aimed to compare the performances of the two aquaculture systems in culturing Nile tilapia, Oreochromis niloticus, larvae.

It might be quite difficult to search for words or phrases in the many file formats that are based on various operating systems. To deal with this level of heterogeneity in different file systems, several academics have put up a number of alternative strategies. Given that data is stored in various formats and is controlled by several operating systems, such solutions, however, proved to be extremely time-consuming. The suggested techniques work best when the data is kept in a single source. The idea of bottlenecking and the resulting heterogeneity in file systems are two main issues with looking for a certain collection of data objects (folder, file, or directory) across many platforms (Windows, Linux, and so forth). We made an effort to suggest fundamental searching methods that may deal with the issue of heterogeneity while increasing efficiency and maintaining dependability. Our method makes use of a concept known as tree-based breadth first search (BFS) and depth first search techniques (DFS) to limit to an absolute minimum the amount of I/O operations that might be required in the heterogeneous environment. The experiment was run on Windows and Linux computers, and it was discovered that by using these strategies, the heterogeneity issues may be greatly decreased, leading to some encouraging outcomes. [ABSTRACT FROM AUTHOR]

Estimating the frequency of subgraphs is of importance for many tasks, including subgraph isomorphism, kernel-based anomaly detection and network structure analysis. While multiple algorithms were proposed for full enumeration or sampling-based estimates, these methods fail in very large graphs. Recent advances in parallelization allow for estimates of total subgraph counts in very large graphs. The task of counting the frequency of each subgraph associated with each vertex also received excellent solutions for undirected graphs. However, there is currently no good solution for very large directed graphs. We here propose VDMC (Vertex specific Distributed Motif Counting)—a fully distributed algorithm to optimally count all the three and four vertices connected directed graphs (network motifs) associated with each vertex of a graph. VDMC counts each motif only once and its efficiency is linear in the number of counted motifs. It is fully parallelized to be efficient in GPU-based computation. VDMC is based on three main elements: (1) Ordering the vertices and only counting motifs containing increasing order vertices; (2) sub-ordering motifs based on the average depth of the tree spanning them via a BFS traversal; and (3) removing isomorphisms only once for the entire graph. We here compare VDMC to analytical estimates of the expected number of motifs in Erdős–Rényi graphs and show its accuracy. VDMC is available as a highly efficient CPU and GPU code with a novel data structure for efficient graph manipulation. We show the efficacy of VDMC on real-world graphs. VDMC allows for the precise analysis of subgraph frequency around each vertex in large graphs and opens the way for the extension of methods until now limited to graphs of thousands of edges to graphs with millions of edges and above. GIT: https://github.com/louzounlab/graph-measures/ PyPI: https://pypi.org/project/graph-measures/ [ABSTRACT FROM AUTHOR]

On a GPU cluster, the ratio of high computing power to communication bandwidth makes scaling breadth-first search (BFS) on a scale-free graph extremely challenging. By separating high and low out-degree vertices, we present an implementation with scalable computation and a model for scalable communication for BFS and direction-optimized BFS. Our communication model uses global reduction for high-degree vertices, and point-to-point transmission for low-degree vertices. Leveraging the characteristics of degree separation, we reduce the graph size to one third of the conventional edge list representation. With several other optimizations, we observe linear weak scaling as we increase the number of GPUs, and achieve 259.8 GTEPS on a scale-33 Graph500 RMAT graph with 124 GPUs on the latest CORAL early access system.

The spanning trees of a graph constructed by the graph searches BFS and DFS are some of the most elementary structures in algorithmic graph theory. BFS-trees are first-in trees, i.e., every vertex is connected to its first visited neighbor. DFS-trees are last-in trees, i.e., every vertex is connected to its most recently visited neighbor. It is known since the 1980s that the problem of deciding whether a given spanning tree of a graph is a BFS-tree or a DFS-tree can be solved in linear time. Here, we will show that swapping the search-tree paradigms between these searches makes the problem hard, i.e., it is NP -complete to decide whether a spanning tree of a graph is a first-in-tree of a DFS or a last-in-tree of a BFS. To the best of our knowledge the latter result is the first hardness result for the recognition of last-in-trees for some graph search. Additionally, we study the complexity of both problems on split graphs. • Hardness of the recognition of last-in trees of BFS. • Hardness of the recognition of first-in trees of DFS. • Linear-time algorithm for the recognition of first-in trees of DFS on split graphs. • Better understanding of the last-in trees of generic search. [ABSTRACT FROM AUTHOR]

Scheduling in computing environments such as homogeneous and heterogonous is very challenging and faces various difficulties computationally. This computing needs an optimal method that decides how to allocate and execute the tasks on a computing platform, so, it generates an efficient result. Here, the tasks are connected to each other and depicted using DAG which is extensively used in Cloud Scheduling modeling. Generally, cloud work on principal pay per resources uses basis. This paper presents a new scheme for scheduling of the tasks in a cloud platform. The proposed algorithm uses heuristic-guided Breadth-First Search (BFS) which works on two steps process as first it the priority computation of the tasks and second is to assign these tasks to the available virtual machines with an entry task as duplicate to all virtual machines. This leads to reducing the scheduling length of the task scheduling and it is the prime with workflow scheduling algorithm. This paper also discussed performance analysis of the new method with the heuristic algorithms using various well known metrics. The proposed method gives better results than the state of the art. [ABSTRACT FROM AUTHOR]

Considering the recent eco-friendly and efficient utilization of three kinds of solid waste, including calcium silicate slag (CSS), fly ash (FA), and blast-furnace slag (BFS), alkali-activated cementitious composite materials using these three waste products were prepared with varying content of sodium silicate solution. The hydration mechanisms of the cementitious materials were analyzed by X-ray diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy, and energy dispersive spectroscopy. The results show that the composite is a binary cementitious system composed of C(N)-A-S-H and C-S-H. Si and Al minerals in FA and BFS are depolymerized to form the Q0 structure of SiO4 and AlO4. Meanwhile, β-dicalcium silicate in CSS hydrates to form C-S-H and Ca(OH)2. Part of Ca(OH)2 reacts with the Q0 structure of AlO4 and SiO4 to produce lawsonite and wairakite with a low polymerization degree of the Si-O and Al-O bonds. With the participation of Na+, part of Ca(OH)2 reacts with the Q0 structure of AlO4 and the Q3 structure of SiO4, which comes from the sodium silicate solution. When the sodium silicate content is 9.2%, the macro properties of the composites effectively reach saturation. The compressive strength for composites with 9.2% sodium silicate was 23.7 and 35.9 MPa after curing for 7 and 28 days, respectively. [ABSTRACT FROM AUTHOR]

Keywords: BFS; cyclic voltammetry; heavy metal; modified electrode EN BFS cyclic voltammetry heavy metal modified electrode 583 589 7 06/01/22 20220501 NES 220501 1 Introduction Environmental pollution such as water, air, soil, and noise, has been a great challenge to the research community that affects ecosystems, biodiversity, and human health. 3 Results and discussion 3.1 Cyclic voltammetry The comparative current response of the GCE, CeO SB 2 sb -GCE, BFS-CeO SB 2 sb modified electrodes were shown in Figure 1, tested by the conventional cyclic voltammetry analysis. Cyclic voltammetry, heavy metal, BFS, modified electrode. [Extracted from the article]

As the era of exascale supercomputing is coming, it is vital for next-generation supercomputers to find appropriate applications with high social and economic benefit. In recent years, it has been widely accepted that extremely-large graph computation is a promising killer application for supercomputing. Although Tianhe series supercomputers are leading in the world-wide competition of supercomputing (ranked No. 1 in the Top500 list for six times), previously they had been inefficient in graph computation according to the Graph500 list. This is mainly because the previous graph processing system cannot leverage the advanced hardware features of Tianhe supercomputers. To address the problem, in this paper we present our integrated optimizations for improving the graph computation performance on our next-generation Tianhe supercomputing system, mainly including sorting with buffering for heavy vertices, vectorized searching with SVE (Scalable Vector Extension) on matrix2000+ CPUs, and group communication on the proprietary interconnection network. Performance evaluation on a subset of the Tianhe supercomputer (with 512 nodes and 196,608 cores) shows that our customized graph processing system effectively improves the graph search performance and achieves the BFS performance of 2131.98 GTEPS. [ABSTRACT FROM AUTHOR]

Relationship networks such as an interpersonal relationship network or navigation route search can be expressed in graph form. However, as the amount of data increase, there is a problem that it is difficult to search for the desired data when it is displayed on one screen. In this paper, we propose a visualization method for searching for people, searching for the shortest path between people, and using graphs to express an interpersonal relationship network with many nodes. Unlike the search for the shortest path in the routing table, the shortest path in the interpersonal relationship network should be changeable according to the intension or importance of the researcher or user who is analyzing it. To this end, the BFS algorithm was modified to apply the characteristics of the interpersonal relationship network. For the verification of the results, the data in the character relationship information of the Korean Classics DB in the Korean Classics Translation Institute was used. [ABSTRACT FROM AUTHOR]

Read-only memory (ROM) model is a classical model of computation to study time-space tradeoffs of algorithms. More recently, several graph algorithms have been studied under ROM model. In this paper, we study graph algorithms under two different relaxations of ROM model, referred to as the implicit and rotate models, and show that these simple relaxations allow us to implement fundamental graph search methods like BFS and DFS more space efficiently than in ROM model. All our algorithms are simple but quite subtle, and we believe that these models are practical enough to spur interest for other graph problems in these models. [ABSTRACT FROM AUTHOR]

The paper presents the results of the efforts concerned with expanding the verification database and estimating the calculation uncertainty of the power density in the steel reflector of lead cooled fast reactor designs based on experiments performed in different years at the BFS critical assemblies by analyzing and revising earlier calculation and experimental studies on the transmission of neutrons through the steel reflector layers. The discussion includes experiments at the BFS-66 critical assembly to model neutron and photon fluxes in the reactor core shielding compositions, as well as experiments at the BFS-64 and BFS-80-2 critical assemblies to model the transmission of neutrons and gamma quanta through the reflector layers of various materials. The information provided in earlier materials with the descriptions of the above experiments has been analyzed and expanded through respective data required to prepare precision calculation models for Monte-Carlo neutronic codes. Precision neutronic models have been developed based on actualized and updated data with a detailed description of the BFS heterogeneous structure and experimental devices, and test calculations have been carried out to confirm their efficiency. The calculations of key neutronic characteristics measured at the BFS-66, -64 and -80-2 assemblies were performed using codes based on the Monte Carlo method (MCU-BR, MCNP, MMK-RF, MMK-ROKOKO) with BNAB-RF and MDBBR50 neutron data and the ROSFOND evaluated neutron data library. The developed precision calculation neutronic models of the experiments discussed can be used to justify lead cooled fast reactor designs, to verify neutronic codes and neutron data, and to evaluate the associated uncertainties.

İnşaat sektörünün önemli malzemelerinden biri olan çimento üretimi için yüksek miktarlarda enerji harcanmaktadır. Çimento üretiminin zararlı etkilerini azaltmaya yönelik araştırmalar yapılmaktadır. İnşaat sektöründe çok fazla kullanım alanı olan çimentolu kompozitler için alternatif olabilecek çevreci çözümler tercih edilebilir. Çimento kullanılmadan üretilecek yapı malzemeleri çimento üretim miktarını azaltarak küresel ısınmanın zararlı etkilerini azaltacaktır. Üretilecek çevreci ürünlerin dayanım ve durabilite özellikleri açısından hâlihazırda kullanılan yapı malzemelerinin yerine geçebilecek nitelikte olması beklenmektedir. Bu çalışmada demir çelik fabrikalarının bir atığı olan Öğütülmüş Yüksek Fırın Cürufu (ÖYFC), Sodyum Hidroksit (NaOH), Sodyum Silikat (Na2SiO3), agrega, hiperakışkanlaştırıcı ve su kullanılarak yüksek dayanımlı (65-85 MPa) jeopolimer betonlar üretilmiştir. Sertleşmiş jeopolimer numuneler, asit saldırılarına karşı dayanıklılık özelliklerini belirlemek amacıyla 0,5M, 1M ve 1,5 M’lık Sülfürik Asit (SA) çözeltisi içerisinde 1, 7, 14, 21 ve 28 gün süresince asit etkisine maruz bırakılmıştır. Jeopolimer numunelerin ağırlık kayıpları, su emme ve porozite değerleri belirlenmiştir. Sonuç olarak numunelerin asitte kalma süreleri arttıkça su emme, porozite ve ağırlık kayıp oranlarında artış gözlemlenmiştir. Su emme -ağırlık kaybı arasındaki ilişkiye benzer şekilde su emme –porozite arasında da istatiksel olarak doğrusal bir ilişki olduğu görülmüştür.

Replacing natural aggregates (NA) for blast furnace slag (BFS) is seen as a technique that is beneficial for the environment. Additionally, in high temperature climates, rigidizing the asphalt by employing gilsonites (G) could be an alternative in order to increase rutting resistance. This study substituted in volume, part of the coarse fraction of NA for BFS in a hot mix asphalt (HMA) that employed asphalt modified with G in wet process. Physical properties of BFS are presented, as well as its chemical and mineral compositions. Additionally, physical properties of asphalt modifi ed are shown. In regards to HMAs, their resistance under monotonic load (Marshall test and indirect tensile strength test), cyclic (resilient modulus, permanent deformation and fatigue) and moisture damage (tensile strength ratio – TSR) was evaluated. All HMAs were manufactured employing the same asphalt content from the control mix. An ANOVA variance analysis was conducted. Based on ANOVA, when the NA volume is substituted with BFS, Marshall stability/ /flow relation significantly drops. However, when such substitution is carried out using G-modified asphalt, resistance under monotonic load, stiffness under cyclic load, resistance to permanent deformation and moisture damage notably increase. Fatigue resistance also increases but such increase is not statistically significant.

For protection against high velocity projectile such as 7.62 mm or 5.56 mm, multilayered armor system (MAS) is suitably the best option. In the present work, the experimental study on MAS with a front Al2O3 ceramic tile followed by a composite of jute and kevlar reinforced with epoxy matrix has been studied. The analytical result has found to meet the performance requirement as specified by NIJ0101.06 when tested against 7.62 mm hard steel core (HSC) and mild steel core (MSC) projectile. It was found that all MAS with double ceramic tile has successfully defeated HSC and MSC projectile with maximum observed back face signature (BFS) as 26.71 mm and 28.70 mm, respectively. In case of single monolithic ceramic, 25.80 mm and 35.12 mm were the maximum observed BFS against HSC and MSC projectile. The extent of projectile damage has been more in HSC when compared to the MSC. Blunt erosion and core breakage were peculiar observations in HSC core, whereas a mushrooming and bulging were observed in MSC core. Macro- and SEM analysis of MAS has been studied to understand the energy dissipation and failure mechanism. [ABSTRACT FROM AUTHOR]

During its service life, concrete may encounter harsh environmental conditions. Ultra high performance Concrete (UHPC) offers a potential solution due to its exceptional strength and durability. This study evaluates the impact of different content of slag 2.5, 5 and 10% and as well nano-particles of 0.5, 1 and 2% as replacement by weight of cement materials (without addition) and two different curing conditions—standard and accelerated—on the compressive strength, ultrasonic pulse velocity (UPV), electrical resistivity, and drying shrinkage of UHPC. The UHPC used in the study contained varying amounts of slag, nano magnesium oxide (MgO) , nano copper oxide (CuO), and a combination of slag and nanoparticles for different ages. Additionally, to examine the microstructure, SEM (Scanning Electron Microscopy) was performed on the specimens. The findings indicate that the optimal presence of slag does not significantly compromise the physical and mechanical properties of UHPC. Whereas after 90 days, for each of the specimens containing 1% nano-MgO and Nano-CuO, approximately 37% increase in compressive strength was achieved compared to the 7-day specimen. Furthermore, after 72 hours, the growth rate of the compressive strength in the accelerated curing conditions for the mentioned specimens was 16.8% and 18.8%, respectively, more than the standard curing. Based on the results, the optimal accelerated curing time to achieve the desired compressive and electrical resistivity is determined to be 48 hours. Furthermore, the utilization of the thermal curing method results in a 75.8% reduction in drying shrinkage of the plain specimen compared to standard curing. In fact, by modifying the microstructure in the presence of optimal amounts of slag and nanoparticles while maintaining the required compressive strength, permeability control and corrosion conditions within the limits determined for UHPC by the existing standards in both curing conditions, it is possible to provide the method accelerated curing reduced the curing time to reach the desired condition. • The effect of nano -MgO and nano –CuO on compressive strength, electrical resistivity and drying shrinkage of UHPC under two different curing was evaluated. • The optimal amount of nanoparticles to achieve the maximum compressive strength and electrical resistivity of UHPC was reported to be 1%. • The optimal time to reach the desired compressive strength and electrical resistivity in the accelerated curing was estimated to be 48 hours. • The accelerated curing reduces drying shrinkage UHPC up to 75.8% compared to the standard method. [ABSTRACT FROM AUTHOR]

In recent years, communication networks on modern power substations have grown both in size and complexity, demanding the highest levels of reliability. However, there is no unique criterion to define the structure of the topology in such networks, since in every substation the end user implements their own topology or the topology suggested by a vendor, according to IEC 61850 standard guidelines. This paper proposes a methodology, using integer linear programming, to solve the problem of generating a reliable network topology in a software-defined power substations context. The trustworthiness of the reached solution is evaluated using terminal reliability techniques, graph metrics, and end-to-end time delay performance. The obtained results confirm that the proposed network topology is highly reliable to be implemented in power substations, according to the network redundancy considerations proposed by the IEC 62439 standard, and the operation time requirements suggested by the on IEC 61850 standard. In addition, we present software defined networking-based solutions for loop-based topologies in the proposed network topology, which would be technically unfeasible using traditional network protocols. These solutions include algorithms to solve problems related to the broadcast traffic containment and the diffusion and reliability of the multicast traffic.

Graph-structured data arise ubiquitously in many application domains. A fundamental problem is to quantify their similarities. Graph kernels are often used for this purpose, which decompose graphs into substructures and compare these substructures. However, most of the existing graph kernels do not have the property of scale-adaptivity, i.e., they cannot compare graphs at multiple levels of granularities. Many real-world graphs such as molecules exhibit structure at varying levels of granularities. To tackle this problem, we propose a new graph kernel called Tree++ in this paper. At the heart of Tree++ is a graph kernel called the path-pattern graph kernel. The path-pattern graph kernel first builds a truncated BFS tree rooted at each vertex and then uses paths from the root to every vertex in the truncated BFS tree as features to represent graphs. The path-pattern graph kernel can only capture graph similarity at fine granularities. In order to capture graph similarity at coarse granularities, we incorporate a new concept called super path into it. The super path contains truncated BFS trees rooted at the vertices in a path. Our evaluation on a variety of real-world graphs demonstrates that Tree++ achieves the best classification accuracy compared with previous graph kernels. [ABSTRACT FROM AUTHOR]

Considering the recent eco-friendly and efficient utilization of three kinds of solid waste, including calcium silicate slag (CSS), fly ash (FA), and blast-furnace slag (BFS), alkali-activated cementitious composite materials using these three waste products were prepared with varying content of sodium silicate solution. The hydration mechanisms of the cementitious materials were analyzed by X-ray diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy, and energy dispersive spectroscopy. The results show that the composite is a binary cementitious system composed of C(N)-A-S-H and C-S-H. Si and Al minerals in FA and BFS are depolymerized to form the Q0 structure of SiO4 and AlO4. Meanwhile, β-dicalcium silicate in CSS hydrates to form C-S-H and Ca(OH)2. Part of Ca(OH)2 reacts with the Q0 structure of AlO4 and SiO4 to produce lawsonite and wairakite with a low polymerization degree of the Si-O and Al-O bonds. With the participation of Na+, part of Ca(OH)2 reacts with the Q0 structure of AlO4 and the Q3 structure of SiO4, which comes from the sodium silicate solution. When the sodium silicate content is 9.2%, the macro properties of the composites effectively reach saturation. The compressive strength for composites with 9.2% sodium silicate was 23.7 and 35.9 MPa after curing for 7 and 28 days, respectively.

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The purpose of this study is to introduce an innovative multi-attribute group decision making (MAGDM) based on bipolar fuzzy set (BFS) by unifying" VIseKriterijumska Optimizacija I Kompromisno Rasenje (VIKOR)" method. The VIKOR method is considered to be a useful MAGDM method, specifically in conditions where an expert is unable to determine his choice correctly at the initiation of designing a system. The method of VIKOR is suitable for problems containing conflicting attributes, with an assumption that compromising is admissible for conflict decision, the expert wishes a solution very near to the best, and the different alternatives or choices are processed according to all developed attributes. The theory of set pair analysis is a state-of-the-art uncertainty theory which consists of three factors, including "identity degree", "discrepancy degree", and "contrary degree" of connection numbers (CNs) and coincidence with many existing theories dealing with vagueness in the given information. Consequently, inspired by this, in the present study, we make an effort to improve the theory of data measurement by introducing some metric spaces using CNs of BFSs. In this research paper, we extend VIKOR method in the context of CNs based metrics, which are obtained form bipolar fuzzy numbers (BFNs). Firstly, we develop CNs of BFNs as well as metric spaces based on CNs. We also discuss some interesting properties of proposed metric spaces. Secondly, we develop VIKOR method using CNs based metrics to handle an MAGDM problem under bipolar fuzzy type information. The predominance of proposed metric spaces is also studied by the means of examples. Furthermore, we demonstrate the efficiency of the extended VIKOR method by solving a numerical example, sensitivity analysis and a detailed comparison with some existing approaches. [ABSTRACT FROM AUTHOR]

Aiming at the problem of interference resource allocation in communication, an interference resource allocation algorithm based on Breadth First Search (BFS) is proposed in this paper. In the jamming problem, the jammer can interfere with the target on a number of frequencies. Affected by some factors, the jamming frequency of a single jammer needs to be concentrated as much as possible. The frequency point set is divided into multiple frequency bands. The signals in the same frequency band are considered to be close to each other. The optimization problem is transformed into allocating the least jamming frequency band of jammer. The optimal interference resource allocation method of the model can be obtained by BFS. Simulation results show that the algorithm has significant index advantages over the manual selection of methods.

We introduce the problem of hub-laminar decomposition which generalizes that of computing a shortest path with minimum eccentricity (MESP). Intuitively, it consists in decomposing a graph into several paths that collectively have small eccentricity and meet only at their extremities. We show that a graph having such a decomposition with long enough paths can be decomposed in polynomial time with bounds on the parameters of the decomposition. Moreover, such a decomposition with few paths allows to compute a compact representation of distances with additive distortion. The problem is related to computing an isometric cycle with minimum eccentricity (MEIC). We also show that having an isometric cycle with small eccentricity is related to the possibility of embedding the graph into a cycle with low distortion. [ABSTRACT FROM AUTHOR]

Carpoolng is a sysytem which the passenger can share the vehicale nad by this means the traffic also duces due to red ucing the no of vehicle on the the roa the government government organization has started the implementatio of carpooling system. To implement this system various Approaches has beendeveloped but becomes essentials that the Selection of optimal distance for pickingthe ger for improvi passenger for improving the recital of the system so in the research work, we use graph traversal technique to find the effective path and it is testedto find the opiimal solution The experimentl results of the proposed metdodology our approac showng approa more efficient than the existing approach. [ABSTRACT FROM AUTHOR]

This research analyzes the influences of radiation heat transfer and Brownian movement on the thermal characteristics of nanofluid flow over an inclined step in the presence of an axial magnetic field. The Rosseland approximation is applied to simulate the divergence of radiative heat flux in the energy equation. The Al2O3–H2O and CuO–H2O nanofluids are considered as the working fluid. The KKL correlation is used for modeling the Brownian movement influence on the effective viscosity and thermal conductivity. The impacts of radiation parameter 0 ≤ R d ≤ 1 , nanoparticles concentration 0 ≤ ϕ ≤ 0.04 and Lorentz force 0 ≤ H a ≤ 60 on temperature fields, mean bulk temperature and convective, radiative and total Nusselt numbers are examined with full details. The results show that the impact of CuO nanoparticles on the average of total heat transfer rates is greater that the influence of Al2O3 nanoparticles on them. Besides, the highest values of total heat transfer rates occur in the absence of magnetic field and for the highest values of Rd and ϕ parameters. [ABSTRACT FROM AUTHOR]