Analysis of acupoint selection and combinations in acupuncture treatment of asthma based on data mining

Objective: Using data mining, the present study aimed to discover the most effective acupoints and combinations in the acupuncture treatment of asthma. Methods: The main acupoints prescribed in these clinical trials was collected and quantified. A network analysis was performed to uncover the interconnections. Additionally, hierarchical clustering analysis and association rule mining were conducted to discover the potential acupoint combinations. Results: Feishu (BL13), Dingchuan (EX-B1), Dazhui (GV14), Shengshu (BL23), Pishu (BL20), and Fengmen (BL12) appeared to be the most frequently used acupoints for asthma. While the Bladder Meridian of Foot Taiyang, the Governor Vessel, and the Conception Vessel, compared to other meridians, were found to be the more commonly selected meridians. In the acupoint interconnection network, Feishu (BL13), Fengmen (BL12), Dingchuan (EX-B1), and Dazhui (GV14) were defined as key node acupoints. Association rule mining analysis demonstrated that the combination of Pishu, Shenshu, Feishu, and Dingchuan, as well as that of Feishu, Dazhui, and Fengmen were potential acupoint combinations that should be selected with priority in asthma treatment. Conclusion: This study provides valuable information regarding the selection of the most effective acupoints and combinations for clinical acupuncture practice and experimental study aimed at the prevention and treatment of asthma.

Impact of micro hydro power plants on transient stability for the micro grid 20 kV system

Transient stability analysis is conducted to determine the ability of the electric power system in maintaining the operating stability after a major disturbance. The disturbance can be trigger an impact on the stability of the rotor angle, voltage, and system frequency which can cause loss of synchronization. In this paper, the impact of the interconnection of the Tombolo-Pao mini hydro power plant (MHPP) on the stability of the system was analyzed by several scenarios to determine the behavior of system parameters in a 20 kV system interconnection network. This research is an implementation of regulatory provisions relating to the study of the connection to the PLN distribution network through by regulator. Based on the result of simulation study, transient stability of generators at TomboloPao power plant about 0.1 second, will not occur with network configuration according to modeling activation of anti-islanding protection of Tombolo Pao Power Plant which is set by 2 second. The simulation results show that the location of the disturbance in the electric power system has been influenced by the behavior of the power plant (synchronous generator) which can lead to the instability of the micro-hydro connected to the micro-grid system 20 kV.

Analisis Pengaruh Pengaturan Sudut Penyalaan Thyristor Pada Tegangan Eksitasi Terhadap Keluaran Daya Reaktif Generator di PT.PJB PLTU Gresik Unit 3

The process of changing mechanical energy into electrical energy is carried out by a synchronous generator using an excitation system that functions to supply a DC source to the generator field winding. In this study, the excitation system used is a static excitation system that uses a transformer and several thyristors connected in a bridge configuration. The excitation system is then implemented on a generator with a capacity of 200 MVA / 15 kV using the MATLAB Simulink R2017b simulation. By using the above circuit, the thyristor ignition angle setting can be adjusted so that it can adjust the excitation voltage and obtain the appropriate excitation current to maintain the stability of the generator output voltage. The simulation was carried out with variations in generator load and using 2 different types of excitation settings. The first setting is to set the thyristor ignition angle to 30° with t=10 ms, at this setting the generator can maintain a stable V out value with a voltage regulation limit of ±5% and the reactive power that can be generated by the generator is +50 MVAr and - 40 MVAr. When given a constant excitation at an angle of 35° with t=1 ms, the value of Vout exceeds the expected regulatory limit and the resulting reactive power limit is between +60 MVAr and -100 MVAR where the reactive power does not match the load requirements. This can have an impact on the interconnection system, namely when the reactive power of the generator is greater than the load requirement, the generator with a smaller reactive power will absorb reactive power in the interconnection system and can disrupt the stability of the interconnection network.

A Novel Tradeoff Analysis between Traffic Congestion and Packing Density of Interconnection Networks for Massively Parallel Computers

From disaster prevention to mitigation, drug analysis to drug design, agriculture to food security, IoT to AI, and big data analysis to knowledge or sentiment mining, a high computation power is a prime necessity at present. As such, massively parallel computer (MPC) systems comprising a large number of nodes are gaining popularity. To interconnect these huge numbers of nodes efficiently, hierarchical interconnection networks are an attractive and feasible option. A Tori-connected flattened butterfly network (TFBN) has been proposed by the authors in a prior work for future generation MPC systems. In the previous study, the static network performance and static cost-effectiveness were evaluated. In this research, a novel trade-off factor named message traffic congestion vs. packing density trade-off factor has been proposed, which characterizes the message congestion in the network and its packing density. The factor is used to statically assess the suitability of the implementation of an interconnection network. The message traffic density, packing density, and new factor have been evaluated for the proposed network and similar competitive networks such as TTN, TESH, 2D-Mesh, 3D-Mesh, 2D-Torus, and 3D-Torus. It has been found that the performance of the TFBN is superior to the other networks.

Petersen-star networks modeled by optical transpose interconnection system

One method to create a high-performance computer is to use parallel processing to connect multiple computers. The structure of the parallel processing system is represented as an interconnection network. Traditionally, the communication links that connect the nodes in the interconnection network use electricity. With the advent of optical communication, however, optical transpose interconnection system networks have emerged, which combine the advantages of electronic communication and optical communication. Optical transpose interconnection system networks use electronic communication for relatively short distances and optical communication for long distances. Regardless of whether the interconnection network uses electronic communication or optical communication, network cost is an important factor among the various measures used for the evaluation of networks. In this article, we first propose a novel optical transpose interconnection system–Petersen-star network with a small network cost and analyze its basic topological properties. Optical transpose interconnection system–Petersen-star network is an undirected graph where the factor graph is Petersen-star network. OTIS–PSN n has the number of nodes 102n, degree n+3, and diameter 6 n − 1. Second, we compare the network cost between optical transpose interconnection system–Petersen-star network and other optical transpose interconnection system networks. Finally, we propose a routing algorithm with a time complexity of 6 n − 1 and a one-to-all broadcasting algorithm with a time complexity of 2 n − 1.

An Efficient Interconnection System for Neural NOC Using Fault Tolerant Routing Method

Large scale Neural Network (NN) accelerators typically have multiple processing nodes that can be implemented as a multi-core chip, and can be organized on a network of chips (noise) corresponding to neurons with heavy traffic. Portions of several NoC-based NN chip-to-chip interconnect networks are linked to further enhance overall nerve amplification capacity. Large volumes of multicast on-chip or cross-chip can further complicate the construction of a cross-link network and create a NN barrier of device capacity and resources. In this paper, this refer to inter-chip and inter-chip communication strategies known as neuron connection for NN accelerators. Interconnect for powerful fault-tolerant routing system neural NoC is implemented in this paper. This recommends crossbar arbitration placement, virtual interrupts, and path-based parallelization strategies in terms of intra-chip communications for the virtual channel routing resulting in higher NoC output at lower hardware costs. A lightweight NoC compatible chip-to-chip interconnection scheme is proposed regarding to inter-chip communication for multicast-based data traffic to enable efficient interconnection for NoC-based NN chips. Moreover, the proposed methods will be tested with four Field Programmable Gate Arrays (FPGAs) on four hard-wired deep neural network (DNN) chips. From the experimental results it can be illustrate that a high throguput can obtained effectively by the proposed interconnection network in handling thedata traffic and low DNN through advanced links.

Study of θϕ Networks via Zagreb Connection Indices

Graph theory can be used to optimize interconnection network systems. The compatibility of such networks mainly depends on their topology. Topological indices may characterize the topology of such networks. In this work, we studied a symmetric network θϕ formed by ϕ time repetition of the process of joining θ copies of a selected graph Ω in such a way that corresponding vertices of Ω in all the copies are joined with each other by a new edge. The symmetry of θϕ is ensured by the involvement of complete graph Kθ in the construction process. The free hand to choose an initial graph Ω and formation of chemical graphs using θϕΩ enhance its importance as a family of graphs which covers all the pre-defined graphs, along with space for new graphs, possibly formed in this way. We used Zagreb connection indices for the characterization of θϕΩ. These indices have gained worth in the field of chemical graph theory in very small duration due to their predictive power for enthalpy, entropy, and acentric factor. These computations are mathematically novel and assist in topological characterization of θϕΩ to enable its emerging use.