Power loss investigation in HVDC for cascaded H-bridge multilevel inverters (CHB-MLI)

In the last decade, the use of voltage-source multilevel inverters in industrial and utility power applications has been increased significantly mainly due to the many advantages of multilevel inverters, compared to conventional two level inverters. These advantages include: 1) higher output voltage at low switching frequency, 2) low voltage stress (dv/dt), 3) lower total harmonic distortion (THD), 4) less electro-magnetic interference (EMI), 5) smaller output filter, and 6) higher fundamental output. However, the computation of multilevel inverter power losses is much more complicated compared to conventional two level inverters. This paper presents a detailed investigation of CHB-MLI losses for HVDC. Different levels, and IGBT switching devices have been considered in the study. The inverter has been controlled using selective harmonic elimination in which the switching angles were determined using the Genetic Algorithm (GA). MATLAB-SIMULINK is used for the modelling and simulation. This investigation should result in a deeper knowledge and understanding of the performance of CHB-MLI using different IGBT switching devices

Optimum SHE for cascaded H-bridge multilevel inverters using: NR-GA-PSO, comparative study

Selective Harmonic Elimination (SHE) is very widely applied technique in the control of multilevel inverters that can be used to eliminate the low order dominant harmonics. This is considered a low frequency technique, in which the switching angles are predetermined based on solving a system of transcendental equations. Iterative techniques such as NR and Heuristic techniques such as GA and PSO have been used widely in literatures for the problem of SHE. This paper presents a detailed comparative study of these three techniques when applied for a 7-level CHB-MLI

Artificial Intelligence in Pursuit-evasion Games, Specifically in the Scotland Yard Game

This research provides a heuristic algorithm for the detectives, who try to collectively capture a criminal known as Mr. X, in the Scotland Yard pursuer-evasion game. In Scotland Yard, a team of detectives attempts to converge on and capture a criminal known as Mr. X. The heuristic algorithm developed in this thesis is designed to emulate human strategies when playing the game. The algorithm uses the current state of the board at each time step, including the current positions of the detectives as well as the last known position of Mr. X. The heuristic algorithm then analyses all of the possible options. The heuristic algorithm then uses a process of elimination to detemine the best possible detective moves by running an appropriately constructed minimum cost flow maximum flow instance. The heuristic algorithm was tested in a series of experiments, in which the algorithm achieved a 57 win rate. This win rate was achieved using a random starting position for each of the pursuer detectives as well as for the evader, Mr. X. When Mr. X started at an easily accessible location, namely position 146, the pursuing detectives were able to capture him 62% of the time. These results show promise for this heuristic in pursuer-evader games like Scotland Yard

Hubungan Antara Mutu Pelayanan Perawat Dan Tingkat Pendidikan Dengan Kepuasan Pasien Peserta Badan Penyelenggara Jaminan Sosial (Bpjs) Kesehatan Di Ruang Rawat Inap Rumah Sakit Islam (Rsi) Sitti Maryam Kota Manado

HUBUNGAN ANTARA MUTU PELAYANAN PERAWAT DAN TINGKAT PENDIDIKAN DENGAN KEPUASAN PASIEN PESERTA BADAN PENYELENGGARA JAMINAN SOSIAL (BPJS) KESEHATAN DI RUANG RAWAT INAP RUMAH SAKIT ISLAM (RSI) SITTI MARYAM KOTA MANADO Azlika M. Alamri1), Adisti A. Rumayar1), Febi K. Kolibu1) 1)Fakultas Kesehatan Masyarakat Universitas Sam Ratulangi ABSTRACT Public as health services users expect the optimal health care organized by the hospital about the performance of health workers in order to fulfill the needs of patients which is measured by patient satisfaction. The increasing of public education demand for quality health services, especially nurses service which can be seen from the erviqual dimension (responsiveness, reliability, assurance, empathy, physical evidence). Nurse service has many parts that interact with patients directly, so the quality of services performed by nurses is an indicator of good or poor quality of care in hospitals. This study aims to determine the correlation between nurses service quality and education level with BPJS patients in the inpatient unit RSI Sitti Maryam Manado. This study is an analytic survey with cross sectional study design. There are 89 samples in total based on inclusion criteria. The collection of data obtained through questionnaires. The statistical tests used to analyze the relationship between variables is chi square test, with α = 0.05 and C1 = 95%. The result of bivariate analyzation show there is a corrrelation between the quality of nursing care with patient satisfaction because p value = 0,000 α (0,05) Through this study, researcher gives suggestions to the hospital in order to draw up a program of patient satisfaction surveys on a regular basis. Keywords: Quality of Care Nurse, Level of Education, Health BPJS Participants Patient Satisfaction ABSTRAK Masyarakat sebagai pengguna jasa layanan kesehatan mengharapkan pelayanan kesehatan yang optimal yang diselenggarakan oleh rumah sakit tentang kinerja tenaga-tenaga kesehatan dalam memenuhi kebutuhan pasien yang diukur dari kepuasan pasien. Meningkatnya pendidikan masyarakat menuntut adanya mutu pelayanan kesehatan terutama pelayanan perawat yang dapat dilihat dari dimensi serviqual (ketanggapan, kehandalan, jaminan, empati, bukti fisik). Pelayanan perawat mempunyai bagian yang banyak berinteraksi dengan pasien secara langsung sehingga mutu pelayanan yang dilaksanakan oleh perawat merupakan indikator baik atau buruknya mutu pelayanan di rumah sakit. Tujuan penelitian ini untuk mengetahui hubungan antara mutu pelayanan perawat dan tingkat pendidikan dengan kepuasan pasien pesertat Badan Penyelenggara Jaminan Sosial (BPJS Kesehatan) di ruang rawat inap RSI Sitti Maryam Kota Manado

Iteratively Decoded Irregular Variable Length Coding and Sphere-Packing Modulation-Aided Differential Space-Time Spreading

In this paper we consider serially concatenated and iteratively decoded Irregular Variable Length Coding (IrVLC) combined with precoded Differential Space-Time Spreading (DSTS) aided multidimensional Sphere Packing (SP) modulation designed for near-capacity joint source and channel coding. The IrVLC scheme comprises a number of component Variable Length Coding (VLC) codebooks having different coding rates for the sake of encoding particular fractions of the input source symbol stream. The relative length of these source-stream fractions can be chosen with the aid of EXtrinsic Information Transfer (EXIT) charts in order to shape the EXIT curve of the IrVLC codec, so that an open EXIT chart tunnel may be created even at low Eb/N0 values that are close to the capacity bound of the channel. These schemes are shown to be capable of operating within 0.9 dB of the DSTS-SP channel’s capacity bound using an average interleaver length of 113, 100 bits and an effective bandwidth efficiency of 1 bit/s/Hz, assuming ideal Nyquist filtering. By contrast, the equivalent-rate regular VLC-based benchmarker scheme was found to be capable of operating at 1.4 dB from the capacity bound, which is about 1.56 times the corresponding discrepancy of the proposed IrVLC-aided scheme

Multi-directional gated recurrent unit and convolutional neural network for load and energy forecasting: A novel hybridization

Energy operations and schedules are significantly impacted by load and energy forecasting systems. An effective system is a requirement for a sustainable and equitable environment. Additionally, a trustworthy forecasting management system enhances the resilience of power systems by cutting power and load-forecast flaws. However, due to the numerous inherent nonlinear properties of huge and diverse data, the classical statistical methodology cannot appropriately learn this non-linearity in data. Energy systems can appropriately evaluate data and regulate energy consumption because of advanced techniques. In comparison to machine learning, deep learning techniques have lately been used to predict energy consumption as well as to learn long-term dependencies. In this work, a fusion of novel multi-directional gated recurrent unit (MD-GRU) with convolutional neural network (CNN) using global average pooling (GAP) as hybridization is being proposed for load and energy forecasting. The spatial and temporal aspects, along with the high dimensionality of the data, are addressed by employing the capabilities of MD-GRU and CNN integration. The obtained results are compared to baseline algorithms including CNN, Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (Bi-LSTM), Gated Recurrent Unit (GRU), and Bidirectional Gated Recurrent Unit (Bi-GRU). The experimental findings indicate that the proposed approach surpasses conventional approaches in terms of accuracy, Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RSME).</p> </abstract&gt

Ultrabroadband nonreciprocal transverse energy flow of light in linear passive photonic circuits

Using a technique, analogous to coherent population trapping in an atomic system, we propose schemes to create transverse light propagation violating left-right symmetry in a photonic circuit consisting of three coupled waveguides. The frequency windows for the symmetry breaking of the left-right energy flow span over 80 nm. Our proposed system only uses linear passive optical materials and is easy to integrate on a chip.Comment: 13 pages, 22 figure

Effect of cultivar, packaging treatments and temperature on post-harvest quality of okra

ABSTRACT    Okra is one of the most popular vegetable crops in Sudan. The introduced cultivars such as Pusa Swani and Clemson Spineless have smooth pods and more adapted to the winter conditions of central Sudan. However, the local cultivar, Khartoumia, has hairy pods and not acceptable in international markets. Okra pods are highly perishable and subject to shriveling especially under the hot arid conditions of central Sudan. Therefore, the objective of this study was to determine the effect of packaging and temperature on the shelf life of okra pods of three introduced cultivars. Treatments consisted of three okra cultivars, namely, Clemson Spineless, Pusa Swani and Mahyco (hybrid); packaging treatments consisted of packing okra pods in cartons lined with intact polyethylene film, perforated polyethylene film or in cartons only and storage temperatures were 140C and 320C. Results showed that pods of the  cultivar Mahyco had the lowest weight loss, retained good colour and had the least decay and rot. Packaging of okra pods in intact or perforated polyethylene film and storing at 140C reduced weight loss and resulted in the best pod colour compared to the control. Packaging in perforated polyethylene film and storing at 140C resulted in the lowest incidence of decay and rot and best overall quality of pods. It is recommended to package okra pods in perforated polyethylene film and ship them to markets at 140C

Drought Vulnerability Assessment Using Geospatial Techniques in Southern Queensland, Australia.

In Australia, droughts are recurring events that tremendously affect environmental, agricultural and socio-economic activities. Southern Queensland is one of the most drought-prone regions in Australia. Consequently, a comprehensive drought vulnerability mapping is essential to generate a drought vulnerability map that can help develop and implement drought mitigation strategies. The study aimed to prepare a comprehensive drought vulnerability map that combines drought categories using geospatial techniques and to assess the spatial extent of the vulnerability of droughts in southern Queensland. A total of 14 drought-influencing criteria were selected for three drought categories, specifically, meteorological, hydrological and agricultural. The specific criteria spatial layers were prepared and weighted using the fuzzy analytical hierarchy process. Individual categories of drought vulnerability maps were prepared from their specific indices. Finally, the overall drought vulnerability map was generated by combining the indices using spatial analysis. Results revealed that approximately 79.60% of the southern Queensland region is moderately to extremely vulnerable to drought. The findings of this study were validated successfully through the receiver operating characteristics curve (ROC) and the area under the curve (AUC) approach using previous historical drought records. Results can be helpful for decision makers to develop and apply proactive drought mitigation strategies

Target Detection in a Known Number of Intervals Based on Cooperative Search Technique

Finding hidden/lost targets in a broad region costs strenuous effort and takes a long time. From a practical view, it is convenient to analyze the available data to exclude some parts of the search region. This paper discusses the coordinated search technique of a one-dimensional problem with a search region consisting of several mutual intervals. In other words, if the lost target has a probability of existing in a bounded interval, then the successive bounded interval has a far-fetched probability. Moreover, the search domain is swept by two searchers moving in opposite directions, leading to three categories of target distribution truncations: commensurate, uneven, and symmetric. The truncated probability distributions are defined and applied based on the proposed classification to calculate the expected value of the elapsed time to find the hidden object. Furthermore, the optimization of the associated expected time values of various cases is investigated based on Newton's method. Several examples are presented to discuss the behavior of various distributions under each case of truncation. Also, the associated expected time values are calculated as their minimum values.Comment: 32 pages, 11 figure