Cluster System Research Articles

A Case Study of Implementation Strategy for Performance Optimization in Distributed Cluster System

Nowadays, many people spend their time on the Internet, and the number of people subscribed to mobile phones is 69.4% of the 5.61 billion population in the world. To handle this situation, we need to implement a high-performance Distributed Cluster System (DCS) in the correct architecture as well. We separated the cluster for each purpose and gave it a unique VLAN. This study uses a mix of methodologies between case study and system development with evaluation after implementation. We observe all aspects of built-in technologies. In this research, monolith spikes us for performance issues, and also, the infrastructure is messy implemented. Event Based System (EBS) helps DCS to absorb high processing tasks in peak situations. EBS can easily lose a couple as needed. Labeling the incoming data assists us in managing inconsistent distributed data in the environment. Our research was evaluated for two weeks. The result is very pleasant, and the requirements in this research were satisfied.

Determination of “just-in-time” service and optimal order size in the logistics system of the regional agro cluster

Determination of “just-in-time” service and optimal order size in the logistics system of the regional agro cluster

CD4 Count and Central Nervous System Infection among HIV/AIDS Patients in an Indonesian Presidential Hospital from 2020 to 2022

Highlights:1. There were insufficient data on the correlation between CD4 count and central nervous system infection as well as the risk magnitude of the infection for HIV/AIDS patients in Indonesia.2. This study revealed a significant correlation between CD4 count and the incidence of central nervous system infection in HIV/AIDS patients, showing an increased risk with a low CD4 count.3. The findings suggest that CD4 count is a vital parameter in determining therapy and evaluating the presence of opportunistic infections in HIV/AIDS patients. Abstract People living with human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), referred to as PLWHA, have a high rate of mortality and morbidity due to opportunistic central nervous system infections. The infections are attributed to the immune deficiency caused by HIV exposure to the immune system's cluster of differentiation 4 (CD4) cells. This allows the central nervous system, the most vital body system, to acquire an opportunistic infection. The purpose of this study was to determine the existence and magnitude of a risk by examining the correlation between CD4 count and the incidence of central nervous system infection among HIV/AIDS patients. This analytical cross-sectional study utilized a simple random sampling technique on the population of HIV/AIDS patients, which consisted of 80 medical records from January 2020 to December 2022. This study was conducted at Gatot Soebroto Presidential Hospital, also known as Gatot Soebroto Central Army Hospital, in Jakarta, Indonesia. The data analysis was performed using Fisher's exact test (p<0.05) and the prevalence odds ratio (POR). The results showed that 16.3% of the patients suffered a central nervous system infection, which consisted of cerebral toxoplasmosis (76.9%) and brain abscess (23.1%). The bivariate analysis suggested a significant correlation between CD4 count and the incidence of central nervous system infection, with an 11.5-fold increased risk for HIV/AIDS patients who had a CD4 count of <200 cells/mm3 (p=0.000; OR=11.5; 95% CI=2.9–43.8). This study concludes that CD4 count is correlated with the incidence of central nervous system infection, indicating a higher risk for HIV/AIDS patients with a low CD4 count.

A Survey on AutoML Methods and Systems for Clustering

Automated Machine Learning (AutoML) aims to identify the best-performing machine learning algorithm along with its input parameters for a given dataset and a specific machine learning task. This is a challenging problem, as the process of finding the best model and tuning it for a particular problem at hand is both time-consuming for a data scientist and computationally expensive. In this survey, we focus on unsupervised learning, and we turn our attention on AutoML methods for clustering. We present a systematic review that includes many recent research works for automated clustering. Furthermore, we provide a taxonomy for the classification of existing works, and we perform a qualitative comparison. As a result, this survey provides a comprehensive overview of the field of AutoML for clustering. Moreover, we identify open challenges for future research in this field.

Effect of transmutation rhenium on tensile properties of tungsten by molecular dynamics simulation

The tensile properties of W-Re alloys are studied using molecular dynamics method. Two forms of transmutation Re uniform distribution and cluster distribution in W-Re alloys are systematically explored, W-xRe alloys and W-nRe clusters, respectively. The effects of Re concentration, Re cluster number density, and temperature on the tensile properties are discussed. Findings suggest that Young’s modulus of W-xRe alloys decreases with increasing Re concentration, reaching only 323 GPa when the Re concentration is 50 at.%. The ultimate stress of W-xRe alloys is lower than that of pure tungsten, indicating that the presence of Re would accelerates the fracture of W-xRe alloys. Additionally, Re clusters of different sizes and number density are constructed in tungsten, forming the W-nRe cluster system. Interestingly Re clusters can reduce tensile strength, and the strain hardening modulus (E sh) is independent of the single Re cluster size. With an increase in Re cluster number density, Young’s modulus, ultimate stress, and ultimate strain decrease gradually, leading to fracture in the Re cluster position. Non-coherent and semi-coherent interfaces between Re cluster (χ- and σ-phases) and W lattice cause Re cluster to undergo imbalance stress. For example, in W-12.5 at.% Re alloys, stress–strain curves are studied at different temperatures, revealing that Young’s modulus decreases with increasing temperature, reaching 292 GPa at 1300 K. A linear formula is obtained by fitting Young’s modulus-temperature curve. These results provide important theoretical references for the design of W-Re alloys as the PFMs in the ITER.

Anisotropic Metal-Metal Pauli Repulsion in Polynuclear d10 Metal Clusters.

Metallophilicity has been widely considered to be the driving force for self-assembly of closed-shell d10 metal complexes, but this view has been challenged by recent studies showing that metallophilicity in linear d10-d10 dimers is repulsive. This is due to strong metal-metal (M-M') Pauli repulsion (Wan, Q., Proc. Natl. Acad. Sci. U. S. A. 2021, 118, e2019265118). Here, we study M-M' Pauli repulsion in d10 metal clusters. Our results show that M-M' Pauli repulsion in d10 polynuclear clusters is 6-52% weaker than in similar linear d10 complexes due to the anisotropic shape of (n+1)s-nd hybridized orbitals. The overall M-M' interactions in closed-shell d10 polynuclear metal clusters remain repulsive. The effects of coordination geometry, relativistic effects, and the ligand's electronegativity on M-M' Pauli repulsion in polynuclear d10 clusters have been explored. These findings provide valuable guidance for the design and development of ligands and coordination geometries that alleviate M-M' Pauli repulsion in d10 metal cluster systems.

The Pivotal Radical Intermediate [Au21(SR)15]+ in the Ligand-Exchange-Induced Size-Reduction of [Au23(SR)16]- to Au16(SR)12.

The atomic precision of sub-nanometer-sized metal nanoclusters makes it possible to elucidate the kinetics of metal nanomaterials from the molecular level. Herein, the size reduction of an atomically precise [Au23(CHT)16]- (HCHT = cyclohexanethiol) cluster upon ligand exchange with HSAdm (1-adamantanethiol) has been reported. During the 16 h conversion of [Au23(CHT)16]- to Au16(SR)12, the neutral 6e Au21(SR)15, and its 1e-reduction state, i.e. the 5e, cationic radical, [Au21(SR)15]+, are active intermediates to account for the formation of thermodynamically stable Au16 products. The combination of spectroscopic monitoring (with UV-vis and ESI-MS) and DFT calculations indicates the preferential size-reduction on the corner Au atoms on the core surface and the terminal Au atoms on longer AunSn+1 staples. This study provides a reassessment on the electronic state of the Au21 structure and highlights the single electron transfer processes in cluster systems and thus the importance of the EPR analysis on the mechanistic issues.

The galactic acceleration scale is imprinted on globular cluster systems of early-type galaxies of most masses and on red and blue globular cluster subpopulations

Context. Globular clusters (GCs) carry information about the formation histories and gravitational fields of their host galaxies. It was found before that the radial profiles of the volume number density of GCs in GC systems (GCSs) follow broken power laws, while the breaks occur approximately at the a0 radii. These are the radii at which the gravitational fields of the galaxies equal the galactic acceleration scale a0 = 1.2 × 10−10 m s−2 known from the radial acceleration relation or the MOND theory of modified dynamics. Aims. Our main goals here are to explore whether the above results hold true for galaxies of a wider mass range and for the red and blue GC subpopulations. Methods. We exploited catalogs of photometric GC candidates in the Fornax galaxy cluster based on ground and space observations and a new catalog of spectroscopic GCs of NGC 1399, the central galaxy of the cluster. For every galaxy, we obtained the parameters of the broken power-law density by fitting the on-sky distribution of the GC candidates, while allowing for a constant density of contaminants. The logarithmic stellar masses of our galaxy sample span 8.0 − 11.4 M⊙. Results. All investigated GCSs with a sufficient number of members show broken power-law density profiles. This holds true for the total GC population and the blue and red subpopulations. The inner and outer slopes and the break radii agree well for the different GC populations. The break radii agree with the a0 radii typically within a factor of two for all GC color subpopulations. The outer slopes correlate better with the a0 radii than with the galactic stellar masses. The break radii of NGC 1399 vary in azimuth, such that they are greater toward and against the direction to NGC 1404, which tidally interacts with NGC 1399.

Mechanism of fruit and vegetable canning production development based on formation of cluster structures

The article is devoted to the formation of the structure of the organizational-economic mechanism for the development of fruit and vegetable canning production in Ukraine. It is determined that the main components of the organizational-economic regulation of activity and development of fruit and vegetable canning production are: regulation of the integrity of the development of enterprises; regulation of innovation and investment activities based on equity; regulation of financial activities; creation of conditions for the implementation of operational activities; conducting practical commercial activities; providing motivating and motivational social conditions; providing information and analytical assessment of the search and control of the use of enterprise resources. The conceptual foundations for creating a new organizational structure for developing fruit and vegetable canning production in Ukraine have been formed. A definition of a new type of cluster structure in the fruit and vegetable canning production system is given. This structure is an organic unity of production, investment, innovation, financial, sales, and other activities of enterprises, united by the chain-network (technological-functional) principle into an interconnected system of functional "fields": production of raw materials, procurement, and storage processing, and marketing. The creation of integrated fruit and vegetable canning structures of the cluster type will solve the problems of industry development through the operation of the organizational and economic mechanism for the development of the industry in the cluster system. The capabilities of the cluster allow to solve the following tasks: meeting the existing and future needs of consumers in quality food products; providing canning enterprises with high-quality raw materials of domestic origin; overcoming price disparity and optimizing the distribution of profits between the links of the technological chain; combining the financial capabilities of enterprises to solve development problems; ensuring guaranteed sales of products at an adequate price for agricultural producers; updating the technical and technological base of production; increasing the economic efficiency of the cluster's production, reducing costs, more precise identification and use of reserves of economic development; dissemination of corporate culture, new methods of work organization, raising collective consciousness, motivation of creative activity; increase in labor productivity; implementation of modern quality management systems; more complete and rational use of resources; solving the problem of staffing. Keywords: agrarian sector, fruit and vegetable canning production, organizational and economic mechanism, integrated structure, clustering, cluster formations.

Variable Stars in the 50BiN Open Cluster Survey. III. NGC 884

Open clusters are the basic building blocks that serve as a laboratory for the study of young stellar populations in the Milky Way. Variable stars in open clusters provide a unique way to accurately probe the internal structure, temporal and dynamical evolutionary stages of individual stars and the host cluster. The most powerful tool for such studies is time-domain photometric observations. This paper follows the route of our previous work, concentrating on a photometric search for variable stars in NGC 884. The target cluster is the companion of NGC 869, forming the well-known double cluster system that is gravitationally bound. From the observation run in 2016 November, a total of 9247 B-band CCD images and 8218 V-band CCD images were obtained. We detected a total of 15 stars with variability in visual brightness, including five Be stars, three eclipsing binaries, and seven of unknown types. Two new variable stars were discovered in this work. We also compared the variable star content of NGC 884 with its companion NGC 869.

Pengembangan Kawasan Berkarakter Urban Crack melalui Desain Pasar Tematik Berbasis Material Daur Ulang Kain di Ciakar, Tangerang

Ciakar Village, located in Panongan sub-district, Tangerang Regency, Banten, experienced significant physical spatial development, namely land use change from agriculture to settlements. The phenomenon of urban crack emerged as a result of this development. Urban crack refers to a narrow area hidden behind a prosperous and once thriving area that no longer has energy and is intrinsically characterized by emptiness. Urban crack in Ciakar village is triggered by the gated community system in the housing clusters that flank the site, resulting in street space that tends to be unmanaged and neglected which is then utilized wildly for plantations, kiosks, garbage disposal areas because there is no control and supervision.
 The Ciakar village government plans to activate and revitalize this area by injecting a thematic market function that is expected to improve the quality of urban space as well as become an economic space for informal communities in improving their standard of living. The concept of a thematic market that combines culinary areas, shopping tours, educational tours, community activities by promoting local wisdom in the form of a park that can be built at an affordable cost. PKM UPH team contributed to propose the design of this thematic market. In the design process, there are two scales of design. Micro-scale design produces affordable building materials by utilizing fabric-based recycled materials with experimental methods to produce prototypes. The macro-scale design produces architectural design ideas for the thematic market by considering the existing context. In this study, the team used qualitative research methods. Data were collected from activities: field observations and Forum Group Discussions (FGDs) involving Ciakar Village government officials and community members. The design method used was a participatory design approach.

Hot Jupiter formation in dense star clusters

ABSTRACT Hot Jupiters (HJ) are defined as Jupiter-mass exoplanets orbiting around their host star with an orbital period < 10 d. It is assumed that HJ do not form in-situ but ex-situ. Recent discoveries show that star clusters contribute to the formation of HJ. We present direct N-body simulations of planetary systems in star clusters and analyse the formation of HJ in them. We combine two direct N-body codes: nbody6++gpu for the dynamics of dense star clusters with 32 000 and 64 000 stellar members and lonelyplanets used to follow 200 identical planetary systems around solar mass stars in those star clusters. We use different sets with three, four, or five planets and with the innermost planet at a semimajor axis of 5 or 1 au and follow them for 100 Myr in our simulations. The results indicate that HJs are generated with high efficiency in dense star clusters if the innermost planet is already close to the host star at a semimajor axis of 1 au. If the innermost planet is initially beyond a semimajor axis of 5 au, the probability of a potential HJ ranges between 1.5 and 4.5 per cent. Very dense stellar neighbourhoods tend to eject planets rather than forming HJs. A correlation between HJ formation and angular momentum deficit is not witnessed. Young HJs (tage < 100 Myr) have only been found, in our simulations, in planetary systems with the innermost planet at a semimajor axis of 1 au.

Implementasi Algoritme K-Means++ Untuk Clustering Penjualan Bahan Bangunan

Utilization of the K-Means++ Clustering algorithm in the sales of building materials clustering system at UD Sumber Bangunan. Currently, the store does not use computers to run its system, resulting in transaction data being used merely as archives without being optimally utilized for marketing strategies and business decision-making. This research aims to examine whether the use of the K-Means++ Clustering algorithm can provide advantages in forming better and more efficient clusters for building material sales data. Evaluation is conducted by comparing K-Means++ with K-Means using the evaluation metrics DBI (Davies-Bouldin Index) and Silhouette Coefficient. The evaluation results show that K-Means++ outperforms using K-Means alone. The DBI values are lower for K-Means++, and the Silhouette Coefficient is higher for K-Means++, indicating that K-Means++ produces better-defined clustering. The utilization of the K-Means++ Clustering algorithm provides benefits in business decision-making at UD Sumber Bangunan, assisting in reducing stockpiles and enhancing customer satisfaction. Additionally, the clustering system built using the Waterfall method also contributes positively to achieving the set objectives..

The Role, Significance and Need For Clustering of Fruits and Vegetables In Ensuring Food Security

The article highlights the role, importance of fruit and vegetable production and the need for clustering in ensuring food security. Definitions and approaches of economists and industry experts to the concept of food insecurity are studied. In order to improve the provision of food safety, proposals and recommendations have been developed for the development of fruit and vegetable growing and the organization of a cluster system.

Optimized operational approach for multi-type reactive power compensation to enhance the grid integration strength of new energy clusters

The insufficient system strength in the high-proportion new energy access area has gradually emerged as a crucial factor contributing to the transient overvoltage issue. Therefore, it is imperative to propose a reactive power optimization operation mode that takes into consideration both the power grid strength and system operating voltage of the new energy cluster system. Firstly, the relationship between the evaluation index of power grid strength and the performance of system voltage response is elucidated, while analyzing the influence mechanism of various reactive power compensation devices on the power grid strength of new energy cluster systems. Then, a reactive power operation optimization model is proposed to maximize the strength of the system grid and minimize the voltage deviation. To solve this problem, a hybrid approach combining genetic algorithm and CPLEX solver is employed. Finally, the effectiveness of the proposed method is validated through a typical simulation example.

German - Algerian Cooperation: Emergence of the Agro-Logistics Beverage Cluster

Globalization and the opening up of the Algerian market have led to the emergence of numerous partnerships with the European Union countries, particularly with Germany. A country that has been able to differentiate itself by relying on its networks of players and which has seen the emergence of numerous internationally renowned clusters, this experience is discussed in detail in this study. The success of this experience has enabled Algeria to play the role of a pivotal country, participating in the emergence of cooperation aimed at strengthening cross-sectoral coordination and local and national economic development through the establishment of cluster systems in Algeria. This contribution aims to provide an overview of the impact of German-Algerian cooperation under the DEVED-GIZ program, which is based on the establishment of clusters in Algeria as a tool for strengthening competitiveness and innovation within the country. To this end, we illustrate the case of the agro-logistics beverage cluster located in the wilaya of Bejaia, which represents a major axis of Algerian industrial policy.

An effective hotspot mitigation system for Wireless Sensor Networks using hybridized prairie dog with Genetic Algorithm.

Wireless Sensor Networks (WSNs) consist of small, multifunctional nodes distributed across various locations to monitor and record parameters. These nodes store data and transmit signals for further processing, forming a crucial topic of study. Monitoring the network's status in WSN applications using clustering systems is essential. Collaboration among sensors from various domains enhances the precision of localised information reporting. However, nodes closer to the data sink consume more energy, leading to hotspot challenges. To address these challenges, this research employs clustering and optimised routing techniques. The aggregation of information involves creating clusters, further divided into sub-clusters. Each cluster includes a Cluster Head (CH) or Sensor Nodes (SN) without a CH. Clustering inherently optimises CHs' capabilities, enhances network activity, and establishes a systematic network topology. This model accommodates both multi-hop and single-hop systems. This research focuses on selecting CHs using a Genetic Algorithm (GA), considering various factors. While GA possesses strong exploration capabilities, it requires effective management. This research uses Prairie Dog Optimization (PDO) to overcome this challenge. The proposed Hotspot Mitigated Prairie with Genetic Algorithm (HM-PGA) significantly improves WSN performance, particularly in hotspot avoidance. With HM-PGA, it achieves a network lifetime of 20913 milliseconds and 310 joules of remaining energy. Comparative analysis with existing techniques demonstrates the superiority of the proposed approach.

Cu site differentiation in tetracopper(i) sulfide clusters enables biomimetic N2O reduction.

Copper clusters feature prominently in both metalloenzymes and synthetic nanoclusters that mediate catalytic redox transformations of gaseous small molecules. Such reactions are critical to biological energy conversion and are expected to be crucial parts of renewable energy economies. However, the precise roles of individual metal atoms within clusters are difficult to elucidate, particularly for cluster systems that are dynamic under operating conditions. Here, we present a metal site-specific analysis of synthetic Cu4(μ4-S) clusters that mimic the Cu Z active site of the nitrous oxide reductase enzyme. Leveraging the ability to obtain structural snapshots of both inactive and active forms of the synthetic model system, we analyzed both states using resonant X-ray diffraction anomalous fine structure (DAFS), a technique that enables X-ray absorption profiles of individual metal sites within a cluster to be extracted independently. Using DAFS, we found that a change in cluster geometry between the inactive and active states is correlated to Cu site differentiation that is presumably required for efficient activation of N2O gas. More precisely, we hypothesize that the Cu δ+⋯Cu δ- pairs produced upon site differentiation are poised for N2O activation, as supported by computational modeling. These results provide an unprecedented level of detail on the roles of individual metal sites within the synthetic cluster system and how those roles interplay with cluster geometry to impact the reactivity function. We expect this fundamental knowledge to inform understanding of metal clusters in settings ranging from (bio)molecular to nanocluster to extended solid systems involved in energy conversion.

A many-body energy decomposition analysis (MB-EDA) scheme based on a target state optimization self-consistent field (TSO-SCF) method.

In this paper, we combine an energy decomposition analysis (EDA) scheme with many-body expansion (MBE) to develop a MB-EDA method to study the cooperative and anti-cooperative effects in molecular cluster systems. Based on the target state optimization self-consistent field (TSO-SCF) method, the intermolecular interaction energy can be decomposed into five chemically meaningful terms, i.e., electrostatic, exchange, polarization, charge transfer and dispersion interaction energies. MB-EDA can decompose each of these terms in MBE. This MB-EDA has been applied to 3 different cluster systems: water clusters, ionic liquid clusters, and acetonitrile-methane clusters. This reveals that electrostatic, exchange, and dispersion interactions are highly pairwise additive in all systems. In water and ionic liquid clusters, the many-body effects are significant in both polarization and charge transfer interactions, but are cooperative and anti-cooperative, respectively. For acetonitrile-methane clusters, which do not involve hydrogen bonds or charge-charge Coulombic interactions, the many-body effects are quite small. The chemical origins of different many-body effects are deeply analyzed. The MB-EDA method has been implemented in Qbics (https://qbics.info) and can be a useful tool for understanding the many-body behavior in molecular aggregates at the quantum chemical level of theory.

Design of a neuro-fuzzy model for agricultural employment in Colombia using fuzzy clustering

<p>High levels of poverty in rural areas constitute one of the main challenges for developing countries. Since agricultural employment is the main source of income in these areas, the design of tools that simulate and help public policymakers will be remarkably useful. This work proposes the development of a model for agricultural employment in Colombia, considering input variables such as education, contract, and income, and the output is the amount of agricultural employment. Real data measured in Colombia are used for the design and adjustment of the model. To design the fuzzy system for an agricultural employment model, the methods employed are fuzzy C-means clustering and neuro-fuzzy systems. The systems were tested with different cluster configurations, and a fuzzy system was obtained with an adequate distribution of the fuzzy sets and the respective rules that relate the sets. It was observed that as the clusters increase, the adjustment function decreases. The implementation of neuro-fuzzy systems to model agricultural employment will allow public policymakers to generate guidelines that adjust to their political agendas with a lower degree of uncertainty.</p>